A Comparative Analysis of Health Status of International Migrants and Local Population in Chile: a Population-based, Cross-sectional Analysis From a Social Determinants of Health Perspective

A Comparative Analysis of Health Status of International Migrants and Local Population in Chile: a Population-based, Cross-sectional Analysis From a Social Determinants of Health Perspective | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Comparative Analysis of Health Status of International Migrants and Local Population in Chile: a Population-based, Cross-sectional Analysis From a Social Determinants of Health Perspective Isabel Rada, Marcela Oyarte, Baltica Cabieses This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1239906/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Background: During recent decades intraregional migration has increased in Latin America. Chile became one of the main receiving countries and hosted diverse international migrant groups. Evidence have suggested a healthy migrant effect (HME) on health status but remains scarce, controversial and needs to be updated. This study performed a comprehensive analysis verifying the existence of HME and its association with social determinants of health (SDH). Methods: We analyzed data from the Chilean National Socioeconomic Characterization Survey (CASEN, version 2017). Crude prevalence of health status indicators such as negative self-perceived health, chronic morbidity, disability and activity limitations were described in both international migrants and local population. The association between these outcomes and demographic, socioeconomic, access to health care, psychosocial and migratory related factors were tested using multivariate logistic regression in each population. The HME was also tested using multivariate logistic regression, sequentially adjusted for each set of SDH to obtain the odds ratio of presenting each health outcome if being an international migrant (ref=Chilean). Results : International migrants had lower crude prevalence of all health indicators than Chileans. Age, unemployment and health care system affiliation were associated with health outcomes in both populations. Psychosocial determinants were both risk and protective factors. Crude analysis revealed an apparent HME in all health outcomes. After adjustment for each set of SDH, the immigrant health advantage was only significant for chronic morbidity. Being migrant was associated with 39% lower odds of having chronic diseases compared to locals (OR: 0,61; 95% CI: 0,44-0,84; P = 0,0003). For all other conditions, HME disappeared after adjusting by SDH, particularly unemployment, type of health system and psychosocial factors. Conclusions: Testing the HME in Chile reveals an advantage for chronic morbidities that remained significant after adjustment for SDH. This analysis shed light on health disparities between international migrants and local population in the Latin American region, with special relevance of unemployment, type of health system and psychosocial factors. As well as differential exposures faced during migration process that could dissolve the HME over time. Evidence from this integrative approach is useful for informed health planning and intersectoral local and regional solutions. International migration healthy migrant effect social determinants of health health disparities Background International migration is a complex process of voluntary or involuntary human mobility (1). Globally, in 2020 it was estimated that approximately 3.6% of world’s population were international migrants (2). In Latin America, one of the main migratory flows throughout the last decades has been intraregional migration, often know as south-south migration (3). Among the countries in the region, Chile has experienced a steady increase of international migration, current estimations from the National Institute of Statistics reported 1.462.103 international migrants at the end of 2020, reaching 8% of the total population. Estimations of sex distribution described a slightly higher proportion of migrant men (50.9%), almost half of migrants were aged 25-35 years old and the majority came from countries within the region such as Venezuela, Perú, Haiti, Colombia and Bolivia (4). Previous evidence has highlighted the heterogeneity of this population, whose demographic and socioeconomic characteristics not only differ from Chilean population, but also within migrant groups (5). This variability is particularly important, since diverse exposures during migration process might have effects on health and wellbeing (6, 7). Furthermore, migration itself has been recognized as a social determinant of health, given the potential influence of certain migration circumstances on health risks (8), which makes the relationship between migration and health a public health priority (6). The health of international migrants residing in Chile has been previously explored. Some evidence has suggested a health advantage over native population called “healthy migrant effect” (HME). This phenomenon postulates that migrants have better health outcomes (morbidity, mortality) when compared to the host population (9). Explanatory models have proposed a positive selection where migrants are self-selected when they feel capable to face the migratory process (10). For example, selection applies on those who are younger and those with labor market skills (11). Other explanation is based on healthy behaviors preserved during migration process, which could be enhanced with favorable life conditions at the destination country (12). Moreover, psychosocial resources like social support and social cohesion may be protective for positive reinforcement of healthy behaviors (13, 14), stress management and disease risk prevention (15). In Chile, evidence from population-based studies have reported the probable existence of the HME on crude health indicators, such as disability (16, 17), illness, accidents and chronic health conditions (17). As well as hospital discharges rates, particularly, migrants had lower proportion of infectious diseases, metabolic disorders, mental health conditions and cardiorespiratory diseases, among others (18). Recent studies have also observed this advantage on emergency consultations of migrants residing in the northern area of the capital of Chile. For instance, migrants had lower hospitalization rates and were not affected by severe clinical conditions (19). Meanwhile, Peruvian mothers living in Santiago have also shown an advantage on perinatal outcomes over native Chilean mothers (20). Interestingly, migrants living in diverse cities of Chile showed a healthier behavior, since migrants reported regular physical activity, which in turn promotes their integration and increases their psychosocial resources (21). Among the above-mentioned evidence, some authors have tested the apparent healthy migrant effect from the perspective of social determinants of health (SDH), which referrers to “ the conditions in which people are born, grow, work, live and age, and the wider set of forces and systems shaping the conditions of daily life ” (22). For example, after the adjustment for socioeconomic determinants, the crude advantage seen on disability, any health problem, any chronic condition or cancer disappeared. Similarly, determinants of migration process also had an influence over time, it seems that longer residence duration in Chile dissolves the healthy migrant effect (17). Likewise, it has been proposed that lower discharges rates could be explained by demographic factors (e.g. age) and reduced access to health care (18). Therefore, positive selection might not apply to all cases and diverse exposures during migration could challenge the health of international migrants, considering that some migrant groups face structural vulnerability (23). Literature describes SDH that influence the health of international migrants, including: i) economic disadvantage and poor living conditions; ii) the effect of educational level on health literacy and behavioral decisions; iii) public policies and migratory laws acting either acting as facilitator or limiter (24); iv) psychosocial determinants that could also promote risk according to migration circumstances and interaction with host society. The lack or imbalance of psychosocial resources such as social support and limited social network have negative impact on health outcomes (15); v) access to health care often mediated by migratory status and sociocultural barriers (24). Noteworthy, migrant population in Chile are more likely to be uninsured and have less use of healthcare system than local population (25). International literature has suggested that lower access to healthcare might lead to the under-report of medical conditions in migrants, raising questions around its influence on HME analysis (26). Overall, the social determinants of health approach go beyond merely crude comparisons and comprehensively explores its modulation on HME. Currently there is a paucity of evidence testing the healthy migrant effect on health status of international migrants residing in Chile and the Latin American region more generally. Local literature remains inconclusive but recognizes the potential impact of diverse exposures during migration process. The migrant population in Chile has changed over time while became increasingly heterogeneous, which points out the need of an update analysis of HME under the social determinants of health approach. This would help to develop a broad understanding of the complexity of migration and health, and its implications on Chilean public health. The present study aims to analyze the existence of the healthy migrant effect on self-perceived health, chronic morbidity, disability and activity limitations and its association with social determinants of health. This analysis was performed by comparing the health status of international migrants and Chilean population from population-based data. In order to contribute to the comprehensive analysis of HME we investigate the influence of demographic, socioeconomic, access to health care, psychosocial and migratory related factors. This update bring attention to the multidimensional nature of migration in the South American region and the detection of particular needs of international migrants for health planning process. Methods The present investigation was a cross-sectional observational study in which a secondary analysis of the National Socioeconomic Characterization Survey (CASEN version 2017) was performed. The CASEN survey is regularly applied by the Ministry of Social Development to Chilean households and their residents; aiming to know their socioeconomic situation, multidimensional poverty and income distribution. As well as update the evidence of priority groups and detect their particular needs. This voluntary survey follows a structured interview answered by an adult who provides data of the other household members. This survey was designed with a probabilistic, stratified and multistage sampling; that is representative at each national, regional (16 regions), and urban/rural level, but excluding geographic areas with difficult access. The total sample was comprised by 70.947 households with 216.439 residents, which represented 16.843.471 Chilean population and 777.407 international migrants. The data base of CASEN survey has public access (27). This study is part of the Fondecyt Regular project 1201461 approved by the Ethics Committee of the Faculty of Medicine of The Universidad del Desarrollo and Ethics Committee of the Servicio de Salud Metropolitano Sur-Oriente. The study complied with ethical guidelines and regulations according to the principles of the Declaration of Helsinki. Health status Health status was examined using the framework of the small module on health from the European Statistics of Income and Living Condition (EU-SILC) as a reference. The instrument contains 3 different variables with its corresponding concepts (28). These concepts were used to create new variables from the questions available in the CASEN survey. Negative Self-perceived health (NSPH) new variable was created based on the question “from 1 to 7 how would you rate your current health status”. According to previous literature the seven-grade scale could be interpreted as 1 very poor health to 7 excellent health that cannot be improved (29). Like previous studies (30), the variable was dichotomized as positive health for scores ranging 4-7 and negative health for scores ranging 1-3. This study focused on negative self-perceived health as indicator in order to maintain consistency with the other negative health indicators included in the analysis. Chronic morbidity (CM) based on question “have you been receiving medical treatment for the past 12 months?”. Dichotomized as yes or no according to the presence of hypertension/dental Emergency, diabetes, depression, acute myocardial infarction, cataracts, chronic obstructive pulmonary disease, leukemia, bronchial asthma, cancer (gastric, cervical uterine, breast, testicular, prostate, colorectal), preventive cholecystectomy, chronic kidney failure, ischemic brain accident, bipolar disorder, lupus or other chronic condition. Disability (DIS) Although the EU-SILC framework does not separate disability from the activity limitation variable. The CASEN survey includes a question focused on disability (31), from whom the new variable was created “¿Do you have any of the following permanent conditions? Dichotomized as yes or no according to the presence of one or more physical/speaking/psychiatric/mental/hearing/visual conditions. Activity limitations (AL) The variable was created using all types of daily living activities limitations asked by CASEN. “How much difficulty do you have for...”. This question was restricted to population over 6 years. Dichotomized as yes or no according to the presence of mild, moderate, severe, or extreme difficulty for one or more activities (eating, showering, displacing, bathroom use, lie down or get out of bed/ get dressed). Social determinants of health Demographic factors age as continuous variable and categorical (64 years). Sex (male, female). Ethnicity for those belonging or being descendant of minority groups in Chile (yes, no), marital status (single, married/cohabitant, separated/divorced/annulled, widow), area (urban, rural). Socioeconomic factors educational level according to the highest level achieved or current level of the household informant (categorized as university, technical, high school, primary, kinder, special education, none). Household income categorized in five quintiles of equal size sorted in ascending order according to the autonomous per capita household income (I, II, III, IV, V). Occupation defined by the occupational activity of the household informant. The variable was created from questions related to current job/occasional job/ work license/search for a job/ attending to educational center (categorized as unemployed, does not study, study, employed, and study and work). Access to health care The variable affiliation to the health care system was used as a proxy of access and created from the question “Which health insurance system do you use?”. Further categorized as none, public health system affiliation, private health system affiliation, other. Psychosocial factors the variable social support was created from available questions that were mainly related to instrumental social support network; dichotomized yes or no according to the presence of one or more supportive behaviors from someone at home and outside. Social capital variable was created from a question of belonging and participation in diverse organizations or organized groups over the last 12 months. Dichotomized as yes or no according to the participation in one or more of these groups. Migratory related factors Country of origin was created as a categorical variable based on the question “When you were born, ¿what country did your mother live in?”. The categories were selected according to the intraregional pattern reported in migratory statistics (4) (Venezuela, Perú, Haiti, Colombia, Bolivia, Argentina, Ecuador, other countries in South America and other). Time of residence was created based on the year period in which the migrant arrived and categorized (2015 or later, 2010-2014, 2005-2009, 2000-2004, 1999 or before). Statistical analysis Health status outcomes were analyzed descriptively for international migrants and Chilean born population. The crude and stratified prevalence by demographic, socioeconomic, access to health care and migratory related factors were presented as proportion. The Pearson’s chi-square test was used to test independence between migration and health status outcomes. Multivariate logistic regression was used to estimate the probability (odds ratio, OR) of reporting these health outcomes and adjusted by each set of SDH in international migrants and local population, separately. The association between migratory related factors and health outcomes was explored with multivariate logistic regression adjusted by sex and age. Then, the healthy migrant effect was examined using multivariate logistic regression sequentially adjusted for SDH, where NSPH, CM, DIS and AL were dependent variables and migrant status was the independent variable (reference Chilean born). In order to estimate the crude and adjusted probability of presenting these health outcomes if being international migrant. The Hosmer-Lemeshow goodness of fit test was used as post-estimation after logistic regression. Data analysis were performed with STATA 14 software (Stata Corp) and weighted according to the survey’s sampling design. Significance was set at 0.05 with 95% confidence interval (95% CI). Results Crude prevalence of health outcomes International migrants had lower crude prevalence of NSPH (3,97% vs 5,91%), CM (9,55% vs. 25,97%), DIS (14,63% vs. 23,89%) and AL (5,56 vs. 11,52%). Regarding stratified analysis, both groups showed higher prevalence of health status outcomes among female, people over 64 years, widow, unemployed and those with public health system affiliation. The outcomes differed by geographical area, for example prevalence of CM and DIS were higher in local and migrant population living in rural areas. Whereas negative self-perceived health and AL were higher in Chileans living in rural areas but lower in migrants. Stratified analysis of socioeconomic factors showed diverse results for these health outcomes, particularly there was a gradient in self-perceived health across income quintiles of both groups. Among migrants, higher prevalence of NSPH was observed in those who were uninsured and those with primary level education. However, CM was higher in migrants with the highest education level and those with private health system affiliation. Conversely, DIS and AL, was higher in those who were affiliated in the public health system (Table 1 - 3 ). Furthermore, migrants from Peru showed the highest prevalence of NSPH (6,43%), disability (7,69%) and AL (4,15%) whereas those from Ecuador had the higher percentage of CM (23,37%). Meanwhile, migrants who had arrived in 2015 or later showed higher rates of negative health perception (4,5%), but those who expended more than 20 years had higher rates of CM (31,08%), DIS (16,58%) and activity AL (7,34%) (Table 4 ). Table 1 Crude and stratified prevalence of health outcomes by SDH factors in immigrant population. Social determinant of health Negative self-perceived health Chronic morbidity Disability % 95% CI % 95% CI % 95% CI 3,97% [2,8% - 5,7%] 9,55% [8,3% - 10,9%] 14,63% [13,1% - 16,3%] Sex Female bc 4,67% [2,7% - 8,0%] 10,34% [8,9% - 12,0%] 7,07% [5,0% - 10,0%] Male abc 3,22% [2,4% - 4,4%] 8,92% [6,6% - 12,0%] 4,01% [3,1% - 5,2%] Age categories <6 1,66% [0,5% - 5,0%] 5,00% [2,6% - 9,5%] 6,02% [3,8% - 9,4%] 6-14 years b 3,78% [2,1% - 6,6%] 3,21% [1,6% - 6,4%] 6,45% [3,4% - 12,0%] 15-64 years bc 3,74% [2,4% - 5,8%] 9,09% [7,7% - 10,8%] 4,60% [3,2% - 6,5%] >64 years b 13,33% [8,8% - 19,7%] 49,88% [41,8% - 58,0%] 29,41% [22,3% - 37,7%] Ethnicity Yes bc 5,67% [3,6% - 8,8%] 10,44% [7,5% - 14,5%] 7,40% [5,2% - 10,4%] No abc 3,92% [2,7% - 5,7%] 9,63% [8,4% - 11,1%] 5,53% [4,2% - 7,3%] Marital Status Single b 4,21% [2,1% - 8,4%] 7,71% [5,4% - 11,0%] 6,05% [3,7% - 9,6%] Married/cohabitant abc 3,02% [2,2% - 4,1%] 9,35% [7,9% - 11,1%] 4,39% [3,6% - 5,4%] Separated/divorced/annulled bc 7,55% [3,8% - 14,6%] 22,55% [15,8% - 31,1%] 6,16% [3,4% - 10,9%] Widow b 19,81% [12,1% - 30,8%] 46,18% [35,3% - 57,4%] 32,13% [22,4% - 43,7%] Area Urban bc 4,02% [2,8% - 5,8%] 9,51% [8,2% - 11,0%] 5,56% [4,2% - 7,3%] Rural abc 2,40% [1,2% - 4,9%] 13,76% [9,7% - 19,1%] 6,27% [4,2% - 9,3%] Educational level None bc 3,65% [1,8% - 7,3%] 5,60% [3,2% - 9,6%] 8,42% [5,2% - 13,3%] University bc 2,90% [1,7% - 4,9%] 13,96% [9,9% - 19,4%] 3,80% [2,7% - 5,4%] Technical abc 1,68% [1,0% - 3,0%] 7,52% [5,2% - 10,8%] 3,56% [2,0% - 6,1%] High School bc 4,73% [2,4% - 9,3%] 7,77% [6,5% - 9,3%] 5,91% [3,5% - 9,9%] Primary abc 5,67% [4,2% - 7,7%] 9,95% [7,7% - 12,8%] 8,25% [6,3% - 10,7%] Income quintile I abc 4,71% [3,0% - 7,4%] 8,73% [6,5% - 11,7%] 5,63% [3,7% - 8,4%] II bc 6,01% [4,3% - 8,4%] 8,68% [6,9% - 10,9%] 7,68% [5,2% - 11,2%] III b 5,80% [1,9% - 16,8%] 8,29% [6,3% - 10,8%] 9,40% [4,7% - 18,0%] IV abc 1,91% [1,3% - 3,0%] 7,73% [6,2% - 9,6%] 3,93% [2,8% - 5,5%] V bc 3,30% [2,0% - 5,3%] 14,10% [10,1% - 19,3%] 3,13% [2,1% - 4,7%] Occupation Does not study 0,91% [0,2% - 3,6%] 2,73% [1,0% - 7,6%] 4,12% [1,5% - 11,0%] Unemployed bc 9,41% [4,8% - 17,8%] 17,46% [14,1% - 21,4%] 13,05% [8,1% - 20,3%] Study 3,85% [1,1% - 12,2%] 8,53% [5,2% - 13,8%] 4,33% [2,5% - 7,4%] Employed abc 2,59% [1,9% - 3,5%] 7,37% [6,0% - 9,0%] 3,38% [2,7% - 4,3%] Study or/and employed ab 0,54% [0,1% - 2,9%] 45,35% [13,9% - 81,0%] 1,92% [0,5% - 6,6%] Access to healthcare None abc 2,48% [1,5% - 4,2%] 3,78% [2,5% - 5,6%] 4,70% [2,8% - 7,8%] Public health system affiliation bc 4,36% [2,7% - 7,0%] 9,15% [7,8% - 10,8%] 6,48% [4,7% - 8,9%] Private health system affiliation c 4,10% [2,1% - 7,9%] 18,78% [11,1% - 29,9%] 2,95% [1,9% - 4,5%] Others c 2,55% [1,0% - 6,2%] 13,67% [7,6% - 23,3%] 3,93% [1,7% - 8,7%] Social Support Yes abc 4,33% [3,2% - 5,9%] 13,54% [10,7% - 17,1%] 4,30% [3,3% - 5,6%] No b 30,13% [6,6% - 72,5%] 3,54% [1,4% - 8,7%] 30,54% [6,8% - 72,7%] Social capital Yes abc 3,93% [2,7% - 5,7%] 15,42% [12,5% - 18,9%] 6,03% [4,6% - 7,9%] No abc 4,05% [2,6% - 6,3%] 9,05% [7,4% - 11,0%] 5,44% [3,9% - 7,6%] a Negative self-perceived health , b chronic morbidity , c disability p value < 0.05 when comparing the same category between the Chilean-born and the immigrant populations (Chi-square test). CI: confidence interval. Table 2 Crude and stratified prevalence of health outcomes by SDH factors in Chilean born population. Negative self-perceived health Chronic morbidity Disability Social determinant % 95% CI % 95% CI % 95% CI of health 5,91% [5,7% - 6,1%] 25,97% [25,6% - 26,4%] 23,89% [23,6% - 24,2%] Sex Female bc 6,61% [6,4% - 6,9%] 30,55% [30,0% - 31,1%] 12,59% [12,2% - 13,0%] Male abc 5,14% [4,9% - 5,4%] 21,47% [21,1% - 21,9%] 10,43% [10,1% - 10,7%] Age categories <6 2,81% [2,5% - 3,2%] 7,95% [7,2% - 8,7%] 5,87% [5,4% - 6,4%] 6-14 years b 2,61% [2,3% - 2,9%] 8,56% [8,1% - 9,1%] 5,10% [4,6% - 5,6%] 15-64 years bc 5,07% [4,9% - 5,3%] 22,58% [22,2% - 23,0%] 8,93% [8,6% - 9,2%] >64 years b 14,23% [13,7% - 14,8%] 67,80% [67,0% - 68,6%] 32,04% [31,1% - 32,9%] Ethnicity Yes bc 5,69% [5,2% - 6,2%] 21,36% [20,5% - 22,2%] 11,24% [10,6% - 11,9%] No abc 5,93% [5,7% - 6,1%] 26,78% [26,4% - 27,2%] 11,61% [11,3% - 11,9%] Marital Status Single b 3,77% [3,6% - 4,0%] 13,57% [13,1% - 14,0%] 8,17% [7,9% - 8,5%] Married/cohabitant abc 7,15% [6,9% - 7,4%] 35,04% [34,4% - 35,7%] 12,43% [12,0% - 12,9%] Separated/divorced/annuled bc 8,54% [7,9% - 9,2%] 40,18% [39,0% - 41,3%] 15,12% [14,3% - 16,0%] Widow b 14,54% [13,7% - 15,4%] 67,53% [66,4% - 68,7%] 35,48% [34,2% - 36,8%] Area Urban bc 5,80% [5,6% - 6,0%] 25,93% [25,5% - 26,4%] 11,45% [11,1% - 11,8%] Rural abc 6,67% [6,3% - 7,1%] 28,31% [27,4% - 29,2%] 12,34% [11,7% - 13,0%] Educational level None bc 6,32% [5,9% - 6,8%] 18,08% [17,2% - 19,0%] 13,89% [13,2% - 14,6%] University bc 2,92% [2,7% - 3,2%] 19,89% [19,2% - 20,6%] 6,78% [6,3% - 7,3%] Technical abc 3,71% [3,3% - 4,2%] 21,58% [20,5% - 22,7%] 7,57% [6,9% - 8,3%] High School bc 5,71% [5,5% - 6,0%] 26,68% [26,1% - 27,2%] 10,60% [10,3% - 11,0%] Primary abc 8,30% [8,0% - 8,6%] 33,48% [32,8% - 34,1%] 15,74% [15,2% - 16,3%] Income quintile I abc 7,89% [7,5% - 8,3%] 27,31% [26,6% - 28,0%] 14,24% [13,7% - 14,8%] II bc 6,60% [6,3% - 7,0%] 26,08% [25,4% - 26,7%] 12,34% [11,8% - 12,9%] III b 6,08% [5,7% - 6,5%] 26,58% [25,8% - 27,4%] 11,92% [11,4% - 12,5%] IV abc 5,02% [4,7% - 5,4%] 26,45% [25,7% - 27,2%] 10,20% [9,7% - 10,7%] V bc 2,99% [2,7% - 3,3%] 24,33% [23,4% - 25,3%] 7,90% [7,3% - 8,5%] Occupation Does not study 2,91% [2,4% - 3,5%] 6,59% [5,8% - 7,5%] 5,03% [4,4% - 5,8%] Unemployed bc 11,88% [11,5% - 12,3%] 48,73% [48,1% - 49,4%] 23,46% [22,9% - 24,1%] Study 2,10% [1,9% - 2,4%] 9,49% [8,9% - 10,2%] 5,51% [5,1% - 6,0%] Employed abc 4,20% [4,0% - 4,4%] 23,54% [23,1% - 24,0%] 7,61% [7,3% - 7,9%] Study or/and employed ab 2,94% [2,2% - 3,9%] 10,76% [9,5% - 12,2%] 5,71% [4,6% - 7,1%] Access to healthcare None abc 4,98% [4,1% - 6,1%] 13,63% [12,3% - 15,1%] 8,01% [6,9% - 9,2%] Public health system affiliation bc 6,54% [6,3% - 6,7%] 27,77% [27,3% - 28,2%] 12,68% [12,4% - 13,0%] Private health system affiliation c 2,86% [2,5% - 3,2%] 20,68% [19,7% - 21,7%] 6,34% [5,8% - 6,9%] Others c 5,66% [4,9% - 6,6%] 28,49% [26,4% - 30,7%] 11,22% [9,9% - 12,6%] Social Support Yes abc 7,54% [7,3% - 7,8%] 40,40% [39,8% - 41,0%] 15,00% [14,5% - 15,5%] No b 14,06% [11,8% - 16,6%] 40,92% [36,7% - 45,3%] 20,26% [17,4% - 23,5%] Social capital Yes abc 6,36% [6,1% - 6,7%] 36,23% [35,6% - 36,9%] 13,71% [13,2% - 14,2%] No abc 6,41% [6,2% - 6,6%] 26,18% [25,7% - 26,6%] 12,05% [11,7% - 12,4%] a Negative self-perceived health , b chronic morbidity , c disability p value < 0.05 when comparing the same category between the Chilean-born and the immigrant populations (Chi-square test). CI: confidence interval. Table 3 Crude and stratified prevalence of activity limitations by SDH in immigrant and Chilean born population. Activity limitations Social determinants of health Chilean born population Migrant population % 95% CI % 95% CI 11,52% [11,2 – 11,8%] 5,56% [4,3% - 7,2%] Sex Female* 6,18% [6,0% - 6,4%] 3,39% [1,6% - 7,1%] Male* 4,16% [4,0% - 4,4%] 1,33% [0,9% - 2,1%] Age categories 64 years 19,01% [18,4% - 19,7%] 21,14% [15,1% - 28,9%] Ethnicity Yes 4,68% [4,3% - 5,1%] 4,79% [3,1% - 7,4%] No* 5,29% [5,1% - 5,5%] 2,32% [1,3% - 4,2%] Marital Status Single 3,50% [3,3% - 3,7%] 3,16% [1,2% - 8,2%] Married/cohabitant* 4,65% [4,4% - 4,9%] 1,12% [0,7% - 1,7%] Separated/divorced/annulled* 6,34% [5,8% - 7,0%] 1,17% [0,5% - 2,9%] widow 23,99% [22,9% - 25,1%] 29,22% [19,9% - 40,7%] Area Urban 5,15% [5,0% - 5,3%] 2,40% [1,3% - 4,3%] Rural 5,75% [5,4% - 6,1%] 2,21% [1,2% - 4,0%] Educational level None* 24,5 [23,0% - 26,1%] 9,33% [3,0% - 25,3%] University* 1,73% [1,5% - 2,0%] 0,95% [0,6% - 1,6%] Technical* 1,66% [1,4% - 2,0%] 0,49% [0,2% - 1,2%] High School 3,78% [3,6% - 4,0%] 2,85% [0,9% - 8,3%] Primary* 8,19% [7,9% - 8,5%] 4,15% [2,6% - 6,6%] Income quintile I* 7,38% [7,0% - 7,8%] 2,86% [1,8% - 4,6%] II* 5,76% [5,5% - 6,1%] 1,71% [1,1% - 2,6%] III 5,15% [4,8% - 5,5%] 5,17% [1,4% - 17,7%] IV* 4,16% [3,9% - 4,5%] 1,75% [0,9% - 3,6%] V* 2,99% [2,7% - 3,3%] 1,38% [0,9% - 2,2%] Occupation Does not study 33,81% [21,8% - 48,3%] 1,77% [0,2% - 14,0%] Unemployed 12,33% [11,9% - 12,7%] 7,69% [3,4% - 16,5%] Study 0,62% [0,5% - 0,8%] 0,95% [0,4% - 2,5%] Employed 1,61% [1,5% - 1,8%] 0,61% [0,4% - 1,1%] Study and work 0,29% [0,1% - 0,6%] 0,93% [0,2% - 5,6%] Access to healthcare None 2,51% [1,9% - 3,2%] 1,58% [0,7% - 3,7%] Public health system affiliation* 5,92% [5,7% - 6,1%] 2,75% [1,3% - 5,8%] Private health system affiliation 1,93% [1,7% - 2,2%] 1,47% [0,8% - 2,7%] Others 5,84% [4,9% - 6,9%] 2,71% [1,0% - 7,0%] Social support Yes* 6,48% [6,2% - 6,8%] 1,62% [1,0% - 2,5%] No 8,18% [6,6% - 10,1%] 29,01% [5,8% - 73,0%] Social capital Yes* 5,42% [5,2% - 5,7%] 2,06% [1,3% - 3,2%] No* 5,19% [5,0% - 5,4%] 2,30% [1,1% - 4,8%] *p value < 0.05 when comparing the same category between the Chilean-born and the immigrant populations (Chi-square test). CI: confidence interval. Table 4 Crude and stratified prevalence of health outcomes by migratory related factors in immigrant population. Negative self-perceived health Chronic morbidity Disability Activity limitations % 95% IC % 95% IC % 95% IC % 95% IC Country of Origin Venezuela 1,93% [0,94% - 3,90%] 7,90% [3,97% - 15,11%] 4,36% [2,57% - 7,33%] 0,96% [0,44% - 2,07%] Peru 6,43% [2,71% - 14,50%] 8,65% [6,94% - 10,74%] 7,69% [3,76% - 15,08%] 4,15% [1,04% - 15,21%] Haiti 4,67% [2,60% - 8,25%] 1,79% [0,79% - 3,99%] 2,94% [1,65% - 5,17%] 0,58% [0,20% - 1,70%] Colombia 2,75% [1,37% - 5,47%] 6,22% [4,14% - 9,25%] 4,23% [2,50% - 7,06%] 1,91% [0,69% - 5,18%] Bolivia 2,95% [1,89% - 4,59%] 7,11% [5,22% - 9,63%] 5,85% [4,28% - 7,93%] 3,15% [2,12% - 4,67%] Argentina 2,36% [1,22% - 4,52%] 20,49% [16,24% - 25,50%] 7,21% [5,04% - 10,22%] 2,27% [1,28% - 3,99%] Ecuador 4,48% [2,41% - 8,17%] 23,37% [14,00% - 36,37%] 4,47% [2,55% - 7,71%] 1,37% [0,43% - 4,24%] Other countries in South America 4,61% [1,95% - 10,49%] 14,46% [9,40% - 21,59%] 4,06% [1,59% - 10,01%] 1,53% [0,46% - 4,93%] Others 5,79% [3,81% - 8,71%] 18,52% [14,63% - 23,17%] 7,89% [5,80% - 10,65%] 4,32% [2,96% - 6,27%] Time of residence 2015 o later 4,56% [2,71% - 7,58%] 8,04% [3,47% - 17,54%] 3,00% [2,11% - 4,23%] 0,23% [0,03% - 1,62%] 2010-2014 3,71% [1,14% - 11,37%] 6,84% [3,40% - 13,27%] 3,12% [1,29% - 7,34%] 2,48% [1,69% - 3,63%] 2005-2009 1,11% [0,33% - 3,67%] 4,46% [1,16% - 15,67%] 8,07% [3,23% - 18,76%] 0,29% [0,04% - 2,13%] 2000-2004 0,73% [0,16% - 3,28%] 7,99% [2,57% - 22,18%] 3,65% [0,58% - 19,76%] 0,23% [0,03% - 1,72%] 1999 or before 2,68% [0,86% - 7,99%] 31,08% [21,69% - 42,34%] 16,58% [10,02% - 26,19%] 7,34% [3,38% - 15,23%] doesn’t know 4,00% [2,11% - 6,70%] 13,73% [10,84% - 17,23%] 6,12% [4,51% - 8,24%] 3,47% [2,39% - 5,03%] CI: confidence interval. SDH associated with health outcomes Logistic regression models for NSPH, CM and DIS adjusted by different set of SDH in migrant population are presented in Table 5 . Models for Activity limitations in both populations are presented in Table 6 . Age was associated with all health outcomes in both populations. Among international migrants, after adjusting for demographic variables the odds of having NSPH was 7,44 times higher in those unemployed (OR: 7,44; 95% CI: 1,05–52,61). CM was associated with affiliation to the health system, particularly affiliation to private health system (OR 4,99; 95% CI: 2,70-9,25). Whereas the risk of CM was also associated with having social support (OR: 3,29; 95% CI: 1,29-8,40) and social capital (OR: 1,84; 95% CI:1,23-2,75). Conversely, social support was associated with reduced odds of DIS (OR: 0,23; 95% CI: 0,09-0,60). Moreover, other variables were associated with both reduced and higher odds, for example having social support reduced by 77% the odds of NSPH (OR: 0,23; 95% CI: 0,10-0,55) and AL (OR: 0,13; 95% CI: 0,05-0,35), but increased the odds for CM (OR: 3,29; 95% CI: 1,29-8,40). Likewise, being married/cohabitant was associated with less chances of DIS (OR: 0,50; 95% CI: 0,29-0,87) and AL (OR: 0,24; 95% CI: 0,09-0,62). Regarding migratory related factors (Table 7 .), those from Haiti had higher odds of NSPH (OR: 4,67; 95% CI: 1,31-16,66) and DIS (OR: 2,88; 95% CI: 0,15-7,19), while those from Argentina showed higher risk of CM (OR: 1,42; 95% CI: 0,59-3,42). Staying over 20 years in Chile was associated with 11,04 times more chances of DIS (OR: 11,04; 95% CI: 3,65-33,4) Table 5 Logistic regression models of health outcomes by SDH in immigrant population. Self-perceived bad health Chronic morbidity Disability OR 95% IC P value OR 95% IC P value OR 95% IC P value Demographic Age 1,02* [ 1,01 - 1,03] 0,000 1,06* [ 1,05 - 1,07] 0,000 1,03* [ 1,02 - 1,04] 0,000 Sex (ref = male) 1,33 [ 0,67 - 2,66] 0,410 1,01 [ 0,61 - 1,65] 0,983 1,65* [ 1,05 - 2,60] 0,029 ethnicity: (ref= no ethnicity) 1,62 [ 0,89 - 2,95] 0,114 0,85 [ 0,52 - 1,41] 0,532 1,29 [ 0,82 - 2,04] 0,267 Marital status (ref = single) Married/Cohabitant 0,54 [ 0,23 - 1,29] 0,167 0,65 [ 0,41 - 1,05] 0,076 0,50* [ 0,29 - 0,87] 0,014 Separated/divorced/annuled 1,07 [ 0,32 - 3,57] 0,917 1,01 [ 0,57 - 1,80] 0,965 0,49 [ 0,22 - 1,10] 0,081 widow 1,66 [ 0,42 - 6,57] 0,473 0,67 [ 0,37 - 1,19] 0,169 1,50 [ 0,60 - 3,77] 0,387 Zone (ref=urban) 0,48* [ 0,27 - 0,83] 0,009 1,13 [ 0,67 - 1,93] 0,628 0,96 [ 0,66 - 1,40] 0,848 GOF test 0,000 0,033 0,129 Socioeconomic Educational level (ref = none) University 0,72 [ 0,22 - 2,39] 0,596 1,56 [ 0,58 - 4,18] 0,380 0,33* [0,14 - 0,82] 0,017 Technical 0,39 [ 0,12 - 1,31] 0,128 1,04 [ 0,41 - 2,63] 0,933 0,29* [0,12 - 0,75] 0,011 High School 0,92 [ 0,29 - 2,97] 0,891 1,14 [ 0,46 - 2,79] 0,777 0,42* [0,19 - 0,97] 0,042 Primary 1,12 [ 0,38 - 3,30] 0,836 1,37 [ 0,57 - 3,29] 0,484 0,48 [0,22 - 1,03] 0,061 Income quintile (ref=I lower income level) II 1,43 [ 0,75 - 2,73] 0,273 1,09 [ 0,66 - 1,78] 0,742 1,49 [0,76 - 2,92] 0,245 III 1,43 [ 0,36 - 5,67] 0,609 0,92 [ 0,56 - 1,52] 0,758 2,44 [0,85 - 7,00] 0,097 IV 0,54 [ 0,27 - 1,10] 0,090 0,82 [ 0,50 - 1,36] 0,446 0,99 [0,47 - 2,05] 0,969 V 0,86 [ 0,35 - 2,14] 0,753 1,16 [ 0,68 - 1,97] 0,588 0,81 [0,36 - 1,80] 0,602 Occupation (ref= does not study) Unemployed 7,44* [1,05 - 52,61] 0,044 0,54 [ 0,13 - 2,24] 0,400 2.61 [0,52 - 13,17] 0,242 Study 4,01 [0,52 - 31,04] 0,183 1,28 [ 0,32 - 5,15] 0,614 1,66 [0,38 - 7,29] 0,503 Employed 2,98 [0,51 - 17,22] 0,223 0,35 [ 0,10- 1,30] 0,118 1,03 [0,26 - 4,08] 0,966 Study and work 0,73 [0,07- 7,47] 0,793 5,30 [ 0,57 - 49,68] 0,144 0,91 [0,15 - 5,44] 0,919 GOF test 0,084 0,536 0,220 Access to healthcare (ref= none) Public health system affiliation 2,02 [0,93 - 4,42] 0,076 2,94* [1,82 - 4,73] 0,000 1,41 [0,68 - 2,96] 0,357 Private health system affiliation 3,40* [1,30 - 8,86] 0,012 4,99* [ 2,70 - 9,25] 0,000 0,77 [0,34 - 1,72] 0,521 Other 1,11 [0,39- 3,10] 0,849 2,99* [ 1,29 - 6,91] 0,011 0,74 [0,26 - 2,17] 0,593 Doesn't know 1,28 [0,50- 3,26] 0,602 0,98 [ 0,38 - 2,57] 0,973 0,73 [0,26 - 2,11] 0,567 GOF test 0,574 0,000 0,445 Psychosocial Social support (ref=no) 0,23* [0,10 - 0,55] 0,001 3,29* [ 1,29 - 8,40] 0,013 0,23* [0,09 - 0,60] 0,003 Social capital (ref=no) 0,88 [0,51 - 1,53] 0,651 1,84* [ 1,23 - 2,75] 0,030 1,09 [0,59 - 2,01] 0,774 GOF test 0,014 0,000 0,747 CI: confidence interval; *p value < 0,05 Table 6 Logistic regression models of activity limitations by SDH in immigrant and Chilean born populations. Activity limitations Immigrant Chilean born OR 95% IC P value OR 95% IC P value Demographic Age 1,04* [ 1,02 - 1,07] 0,001 1,06* [1,05 - 1,06] 0,000 Sex (ref = male) 2,13 [0,77 - 5,90] 0,146 1,18* [ 1 , 12 - 1 , 24 ] 0,000 ethnicity: (ref= no ethnicity) 2,25* [ 1,13 - 4,50] 0,021 1,17* [1,07 - 1,28] 0,001 Marital status (ref = single) Married/Cohabitant 0,24* [ 0,09 - 0,62] 0,003 0,42* [0,39 - 0,45] 0,000 Separated/divorced/annuled 0,15* [0,04 - 0,55] 0,004 0,54* [0,48 - 0,60] 0,000 widow 1,67 [0,46 - 6,01] 0,434 0,89* [0,81 - 0,98] 0,014 Zone (ref=urban) 0,69 [0,37 - 1,28] 0,239 1,04 [0,96 - 1,12] 0,384 GOF test 0,000 0,000 Socioeconomic Educational level (ref = none) University 0,36 [0,10 - 1,27] 0,112 0,22* [0,18 - 0,27] 0,000 Technical 0,20* [0,43 - 0,90] 0,037 0,22 [0,18 - 0,27] 0,057 High School 1,03 [0,31 - 3,43] 0,958 0,29 [0,26 - 0,34] 0,235 Primary 0,67 [0,20 - 2,30] 0,527 0,38 [0,33 - 0,43] 0,604 Income quintile (ref=I lower income level) II 0,71 [0,31 - 1,65] 0,434 0,93 [0,86 - 1,01] 0,083 III 4,23 [0,89 - 19,98] 0,069 0,85* [0,77 - 0,93] 0,000 IV 0,98 [0,31 - 3,08] 0,975 0,79* [0,71 - 0,88] 0,000 V 1,12 [0,38 - 3,33] 0,840 0,73* [0,63 - 0,84] 0,000 Occupation (ref= none) Study or/and employed 1,66 [0,38 - 7,29] 0,503 0,01* [0,00 - 0,02] 0,000 GOF test 0,220 0,000 Access to healthcare (ref= none) Public health system affiliation 1,32 [0,34 - 5,18] 0,690 1,33 [0,99- 1,79] 0,058 Private health system affiliation 1,21 [0,32 - 4,67] 0,777 0,95 [0,68 - 1,31] 0,740 Other 0,55 [0,08 - 3,55] 0,527 1,21 [0,85 - 1,74] 0,292 Doesn't know 1,45 [0,38 - 5,54] 0,584 1,15 [0,80 - 1,68] 0,450 GOF test 0,445 0,000 Psychosocial Social support (ref=no) 0,13* [ 0,05 - 0,35] 0,000 1,06 [0,83 - 1,35] 0,648 Social capital (ref=no) 0,72 [0,29 - 1,81] 0,484 0,83* [0,76 - 0,90] 0,000 GOF test 0,747 0,000 Table 7 Logistic regression models of health outcomes by migratory related factors in immigrant population. Negative Self-perceived health Chronic morbidity Disability OR 95% IC P value OR 95% IC P value OR 95% IC P value sex + age + Country of Origin (ref = Perú) Venezuela 2,57 [ 0,29 – 22,78] 0,395 1,91 [ 0,43 – 8,89] 0,395 - Haiti 4,67* [ 1,31 – 16,66] 0,018 - 2,88* [ 0,15 – 7,19] 0,024 Colombia 0,57 [ 0,05 – 6,25] 0,645 1,08 [ 0,34 – 3,45] 0,891 0,67 [ 0,11 – 3,99] 0,658 Argentina 0,29 [ 0,02 – 4,64] 0,380 1,42 [ 0,59 – 3,42] 0,420 0,13* [ 0,03 – 0,58] 0,008 Other countries in South America 1,26 [ 0,20 – 7,85] 0,802 2,09 [ 0,68 – 6,01] 0,200 0,44 [ 0,13 – 1,49] 0,186 Others 3,86 [ 0,45 – 32,77] 0,214 1,90 [ 0,66 – 5,47] 0,232 0,79 [ 0,31 – 2,04] 0,625 Time of residencia (ref = 2010 or later) 2009 - 2000 0,25* [ 0,06 - 0,99] 0,048 0,63 [ 0,22 – 1,77] 0,375 2,89* [ 1,04 – 8,04] 0,042 1999 or before 0,45 [ 0,05 – 4,22] 0,481 1,66 [ 0,43 – 4,60] 0,324 11,04* [ 3,65 – 33,4] 0,000 GOF test 0,000 0,000 0,000 CI: confidence Interval; *p value < 0.05. CI: confidence Interval *p value < 0.05 Diverse variables were associated with health status of Chilean population, including all demographic factors (Table 8 ). After adjustment for demographics, the lack of educational attainment was associated with higher risk of NSPH, CM and DIS. In addition, being unemployed was associated with having NSPH (OR: 2,23; 95% CI: 1,72-2,89) and DIS (OR: 3,04; 95% CI: 2,49-3,70). The public health system affiliation was associated with higher odds of CM (OR: 1,83; 95% CI: 1,60-2,10) and DIS (OR: 1,24; 95% CI: 1,05-1,47). Meanwhile, those married/cohabitant were 58% less likely to have AL (OR: 0,42; 95% CI: 0,39-0,45), and 45% of having DIS (OR: 0,55; 95% CI: 0,52-0,58), while also reduced the odds of NSPH and CM. The highest level of income quintile was associated with 48% less chance of having NSPH (OR: 0,52; 95% CI: 0,46-0,59). As well as reduced odds of DIS (OR: 0,76; 95% CI: 0,69-0,85) and AL (OR: 0,73; 95% CI: 0,63-0,84). Among psychosocial factors, having social support was associated with 38% less odds of NSPH (OR: 0,62; 95% CI: 0,50-0,76). Whereas social capital increased the odds of having CM (OR: 1,21; 95% CI: 1,15-1,27). Table 8 Logistic regression models of health status outcomes by SDH in the Chilean born population. Self-perceived bad health Chronic morbidity Disability Activity limitations OR 95% IC P value OR 95% IC P value OR 95% IC P value OR 95% IC P value Demographic Age 1,03* [1,03 - 1,04] 0,000 1,06* [1,05 - 1,06] 0,000 1,04* [1,04 - 1,04] 0,000 1,06* [1,05 - 1,06] 0,000 Sex (ref = male) 1,18* [ 1 , 13 - 1 , 24 ] 0,000 1,54* [1,48 - 1,59] 0,000 1,05* [1,02 - 1,10] 0,002 1,18* [ 1 , 12 - 1 , 24 ] 0,000 ethnicity: (ref= no ethnicity) 1,16* [1,05 - 1,28] 0,003 0,99 [0,93 - 1,05] 0,696 1,22* [ 1 , 13 - 1 , 31 ] 0,000 1,17* [1,07 - 1,28] 0,001 Marital status (ref = single) Married/Cohabitant 0,84* [0,78 - 0,89] 0,000 0,94* [0,91 - 0,98] 0,007 0,55* [0,52 - 0,58] 0,000 0,42* [0,39 - 0,45] 0,000 Separated/divorced/annuled 0,93 [0,84 - 1,03] 0,161 0,98 [0,93 - 1,04] 0,526 0,64* [0,60 - 0,69] 0,000 0,54* [0,48 - 0,60] 0,000 widow 0,85* [0,77 - 0,94] 0,001 1,06 [0,99 - 1,13] 0,107 0,90* [0,84 - 0,98] 0,009 0,89* [0,81 - 0,98] 0,014 Zone (ref=urban) 1,08* [1,00 - 1,17] 0,004 1,04 [0,98 - 1,09] 0,172 1,00 [0,93 - 1,08] 0,971 1,04 [0,96 - 1,12] 0,384 GOF test 0,000 0,000 0,000 0,000 Socioeconomic Educational level (ref = none) University 0,34* [0,29 - 0,39] 0,000 0,55* [0,49 - 0,62] 0,000 0,24* [0,21 - 0,27] 0,000 0,22* [0,18 - 0,27] 0,000 Technical 0,38* [0,33 - 0,45] 0,000 0,60* [0,53 - 0,69] 0,000 0,27* [0,23 - 0,31] 0,000 0,22 [0,18 - 0,27] 0,057 High School 0,46* [0,41 - 0,52] 0,000 0,60* [0,54 - 0,68] 0,000 0,29* [0,26 - 0,32] 0,000 0,29 [0,26 - 0,34] 0,235 Primary 0,61* [0,54 - 0,69] 0,000 0,74* [0,66 - 0,83] 0,000 0,39* [0,36 - 0,44] 0,000 0,38 [0,33 - 0,43] 0,604 Income quintile (ref=I lower income level) II 0,89* [0,82 - 0,97] 0,005 1,00 [0,95 - 1,05] 0,913 1,00 [0,91 - 1,03] 0,310 0,93 [0,86 - 1,01] 0,083 III 0,84* [0,78 - 0,92] 0,000 0,99 [0,94 - 1,05] 0,742 0,94 [0,88 - 1,00] 0,074 0,85* [0,77 - 0,93] 0,000 IV 0,73* [0,66 - 0,81] 0,000 0,97 [0,91 - 1,03] 0,270 0,83* [0,78 - 0,89] 0,000 0,79* [0,71 - 0,88] 0,000 V 0,52* [0,46 - 0,59] 0,000 0,97 [0,90 - 1,05] 0,498 0,76* [0,69 - 0,85] 0,000 0,73* [0,63 - 0,84] 0,000 Occupation (ref= does not study) Unemployed 2,23* [1,72 - 2,89] 0,000 0,80* [0,67 - 0,97] 0,000 3,04* [2,49 - 3,70] 0,000 0,04* [0,02 - 0,07] 0,000 Study 1,13 [0,87 - 1,46] 0,350 0,87 [0,72 - 1,05] 0,151 2,15* [1,74 - 2,67] 0,000 0,19* [0,01 - 0,04] 0,000 Employed 1,21 [0,93 - 1,57] 0,152 0,51* [0,43 - 0,62] 0,000 1,44 [1,18 - 1,74] 0,000 0,01* [0,01 - 0,02] 0,000 Study and work 1,61* [ 1 , 10 - 2 , 37 ] 0,015 0,63* [0,50 - 0,79] 0,000 2,11* [1,56 - 2,85] 0,000 0,01* [0,00 - 0,02] 0,000 GOF test 0,011 0,000 0,000 0,000 Access to healthcare (ref= none) Public health system affiliation 1,01 [0,82 - 1,24] 0,944 1,83* [1,60 - 2,10] 0,000 1,24* [1,05 - 1,47] 0,010 1,33 [0,99- 1,79] 0,058 Private health system affiliation 0,85 [0,66 - 1,09] 0,195 1,91* [1,62 - 2,24] 0,000 1,03 [0,85 - 1,24] 0,757 0,95 [0,68 - 1,31] 0,740 Other 0,91 [0,70 - 1,19] 0,470 1,65* [1,40 - 1,95] 0,000 1,02 [0,83 - 1,25] 0,876 1,21 [0,85 - 1,74] 0,292 Doesn't know 0,89 [0,67 - 1,19] 0,437 1,21 [1,00 - 1,47] 0,045 1,13 [0,90 - 1,42] 0,302 1,15 [0,80 - 1,68] 0,450 GOF test 0,002 0,000 0,000 0,000 Psychosocial Social support (ref=no) 0,62* [0,50 - 0,76] 0,000 1,16 [0,98 - 1,37] 0,079 0,87 [0,72 - 1,05] 0,137 1,06 [0,83 - 1,35] 0,648 Social capital (ref=no) 0,80* [0,74- 0,87] 0,000 1,21* [ 1 , 15 - 1 , 27 ] 0,000 0,97 [0,90 - 1,03] 0,319 0,83* [0,76 - 0,90] 0,000 GOF test 0,384 0,000 0,001 0,000 CI: confidence Interval *p value < 0.05. Findings on Healthy Migrant effect The odds of having each health outcomes if being an international migrant were calculated and progressively adjusted by each set of SDH (Table 9 .). The crude analysis revealed a healthy migrant effect, since being an immigrant was significantly associated with lower odds of presenting all health outcomes. After adjustment for demographics, being immigrant was no longer protective for NSPH and AL. However, after adjustment for socioeconomic covariates, only the association with CM remained significant. The subsequent models showed a healthy migrant effect for CM after adjustment for access to health care and psychosocial factors. Being migrant was associated with 39% lower odds of chronic morbidity compared to Chilean population (OR: 0,61; 95% CI: 0,44-0,84; P = 0,0003). Table 9 Logistic regression models of health outcomes if being an international immigrant sequentially adjusted by SDH. Model 1 Crude OR of being migrant Model 2 Adjusted OR by demographics Model 3 Adjusted OR by demographics + SES Model 4 Adjusted OR by demographics +SES +access to health care Model 5 Adjusted OR by demographics +SES +access to health care +psychosocial Health outcome OR [IC95%] p OR [IC95%] p OR [IC95%] p OR [IC95%] p OR [IC95%] p Negative Self-perceived health 0,66* [0,45 - 0, 96] 0,031 0,90 [0,62 - 1,33] 0,638 1,10 [0,71 - 1,60] 0,752 1,1 [0,71 - 1,64] 0,716 1,36 [0,81 - 2,28] 0,252 Chronic morbidity 0,30* [0,26 - 0, 35] 0,000 0,43* [0,36 - 0,51] 0,000 0,50* [0,42 - 0,61] 0,000 0,54* [0,45 - 0,67] 0,000 0,61* [0,44 - 0,84] 0,003 Disability 0,45* [0,34 - 0, 60] 0,000 0,66* [0,50 - 0,87] 0,004 0,80 [0,57 - 1,05] 0,103 0,80 [0,58 - 1,08] 0,138 0,94 [0,55 - 1,62] 0,835 Activity limitations 0,44* [0,25 - 0, 80] 0,007 0,80 [0,46 - 1,53] 0,560 1,10 [0,49 - 2,50] 0,812 1,2 [0,51 - 2,70] 0,719 2,17 [0,82 - 5,76] 0,121 CI: confidence Interval *p value < 0.05. Discussion This study analyzed the prevalence of health outcomes of international migrants and local population, and its associated SDH. As well as the presence of the HME by comparing both populations. Results showed that migrants had lower crude prevalence across all health outcomes. In both groups age, unemployment, affiliation to the health system and psychosocial factors were associated with these outcomes. Among migrants, a time of residence over 20 years was associated with higher odds of disability. Crude models showed an apparent migrant’s health advantage on NSPH, CM, DIS and AL. However, after adjustment for demographics, socioeconomics, health care affiliation and psychosocial factors, being immigrant only confers protection for chronic morbidity. Previous evidence from CASEN survey-2006 revealed a crude and adjusted by demographics advantage for any disability, health problem/accident and any chronic condition. In contrast to our findings, this advantage was no longer significant after controlling for socioeconomic and material covariates. Thus, the healthy migrant effect did not persist for any health outcome, highlighting the influence of a poor socioeconomic status on health decline (17). Other crude comparisons between international migrants and local population in South America, have suggested a probable existence of healthy migrant effect on chronic conditions. In Colombia, migrants from Venezuela had a lower self-reported prevalence of diverse chronic diseases such as hypertension, cardiovascular diseases, diabetes mellitus and cancer than local population (32). Similar to the smaller percentage of chronic conditions reported by Venezuelans in Peru (33). Data from other sources such as hospital discharges, have revealed crude lower rates of CM in migrants residing in Chile (18). Moreover, adjusted analysis on cancer hospital discharges also showed a potential advantage on this indicator (34). The migrant’s advantage on CM could be explained by a positive selection, where those who decide to migrate are healthier, than those who decided to stay. This better baseline health could be derived from the access to a healthy diet, lower environmental risks, among other exposures at the country of origin. Besides, their attitude towards long-term health by adopting healthier behaviors that might reduce risks factors for chronic diseases, while those who have medical conditions are more prone to return (35). This explanation might be complementary to the “cultural buffering” of the migrant’s group, whose norms reduce risky behaviors and promotes a healthy decision making (36). Although, CASEN survey does not provide information related to behavioral factors, data from the Chilean national health survey (ENS 2016-2017) revealed elevated levels of alcohol consumption, smoking, sedentary lifestyle and low fruit and vegetable consumption in the general population. As well as, type II diabetes mellitus, hypertension, dyslipidemia and obesity (37). Chile has experienced an epidemiological transition, where overall non-communicable disease burden has increased, reaching more than four comorbidities in the general population (38). Among countries in the Americas Region, Chile has a high rate of deaths caused by chronic diseases, which contrast with lower rates reported by the main migrant’s countries of origin (39). Therefore, the advanced epidemiological transition in Chile could yield a health gap between migrants and locals, that needs to be analyzed throughout the migrant life trajectories. Literature have suggested that HME disappears with time of residence and migrant health converge to native population, mainly in elderly (40). This deterioration results from cumulative exposures such as adoption of unhealthy behaviors from host society (e.g. smoking, alcohol consumption, greater calories intake), acculturative stress, discrimination and precarious living conditions (40, 41). Our findings show a higher crude prevalence of CM for those migrants living over 20 years in Chile. However, time of residence was not associated with CM in the partially adjusted model. Thus, the exposure to diverse factors during migration process does not seem to dissolve the advantage for chronic diseases seen in international migrants residing in Chile. As mentioned, this protection does not apply for a long-term condition such as disability that could be derived from exposure to diverse SDH. Evidence have suggested that even if migrants experienced advantages in other health outcomes, they face disability in a great extent. A cumulative disadvantage resulted from social vulnerability could lead to occupational risks like high physical job demands, abuse and unsafe conditions that might play a role in the development of functional impairment (42). Moreover, migrants at older ages tend to display higher disability rates than recent migrants and local population (42, 43). In the same line, it has been documented that time of residence has an inverse association with self-perceived health. While there’s also evidence reporting poor health perception in recent migrants, suggesting the absence of HME in this indicator (44). Nevertheless, when examining the health perception trajectories, it could be either stable or decline over time at similar rate as locals, which contrast to the negative relationship described in cross-sectional data (45). Regarding the psychosocial resources, previous evidence have highlighted its protective role in migrants health (13, 15). Our results showed both risk and protective associations between psychosocial factors and health outcomes. Particularly, these factors were associated with increased odds of DI and CM but were protective for the remaining health outcomes. This dual effect has been previously suggested for migration networks (46). Depending on networks composition, migrants might be differentially exposed to healthy or risky behaviors (e.g., alcohol consumption determined by social situations, religious norms and ethnic identity) (47). Whereas, social support differs by migrant’s characteristics, including migratory related factors as well as social context and types of supportive ties. Literature have described an “isolation paradox” in which migrants with poor social support were healthier than natives with similar isolation levels. The expected gradient between social support and good health is not always seen in migrant population, those with greater social support could also display poor health outcomes (48). Moreover, CASEN survey asks if the participant was under treatment in the past 12 months for CM. Thus, the association might result from the positive influence of social networks on health care utilization and health seeking behavior. Similarly, having health insurance could lead to increased access to diagnosis and treatment (49), which could explain the association between CM and healthcare affiliation. Since these priority conditions are covered by the explicit health guarantees of Chilean health care system. The present study contributes to the understanding of the healthy migrant effect by comparing international migrants and local population from population-based data. Our findings provide an insight of the influence of health access and psychosocial factors on migrant’s health status, beyond the influence of socioeconomic factors already described in previous research in Chile. This new evidence shed light on health disparities between these populations and brings attention to its importance for health planning. However, the study has important limitations including the cross-sectional analysis that does not allow us to detect changes across time of residence. Estimations were based on self-reported data without medical confirmation. In addition, the CASEN survey does not provide data of behavioral and occupational risk factors to better understand prevalence of long-term conditions. Similarly, due to database limitations it was not possible to analyze other migratory variables and those analyzed were adjusted by sex and age. Furthermore, it is possible that some migrants did not report that they were born abroad or those with irregular administrative status have chosen not to participate. Therefore, migrants who experience greater social vulnerability might not be fully represented in this survey and the social determinants of health to which they were exposed, and their respective health needs could be overlooked. Future research should analyze migration trajectories, examining risks factors and health outcomes over time with longitudinal studies. The HME needs to be comprehensively tested by specific causes of morbidity from the SDH approach. Given the heterogeneity of migrant population and diverse exposures they face during migration process. The findings of this study have practical implication towards inclusive public health responses. Since unemployment, affiliation to health system and psychosocial factors could be potentially modified by migrant-sensitive intersectoral actions. These initiatives must be based on equity and human rights perspectives to promote migrant integration. Besides the articulation of joint efforts at community and national level. For instance, foster social protection strategies regardless of immigration status to counteract socioeconomic vulnerability and poor living conditions that might result from unemployment. Furthermore, addressing barriers for healthcare affiliation, effective access and use of health care. Overall, it should be integrated with psychosocial support-based activities. These measures might involve community based-interventions, intercultural competence in health care and evidence-based migration policies. In order to protect health and wellbeing of migrants and prevent a potential health decline. These practical implications may be useful for the current migratory context in Latin America and the need of encourage collaborative alliances and policy making at regional level. Conclusions The present study revealed a crude advantage on health status of International migrants residing in Chile. However, when an integrative approach was applied by adjusting for social determinants of health the healthy migrant effect disappeared for almost all outcomes. Being migrant remained protective for chronic morbidities which might reflect the health gap resulted from the advanced epidemiological transition in Chile where non-communicable diseases are main public health problems. These findings bring attention to the importance of studying health disparities between international migrants and locals, while considering the diverse exposures during migration process that could dissolve this health advantage over time. Our findings highlight the need to deepen study the HME by cause-specific morbidity, particularly, chronic conditions and its risks factors and could be useful to health care practitioners and policy makers in a more comprehensive understanding of how variables like unemployment, affiliation to the health system and psychosocial factors may shape migrants’ health over time. This could be relevant to both policy and practice for health systems in Chile and more broadly in the Latin American region, especially in the purpose of “leaving no one behind in health protection”. Abbreviations HME: Healthy migrant effect SDH: Social Determinants of health NSPH: Negative Self-perceived health CM: Chronic morbidity DIS: Disability AL: Activity limitations OR: Odds ratio CI: Confidence interval Declarations Ethics approval and consent to participate The investigation was conducted in accordance with ethical guidelines and regulations in compliance with the Declaration of Helsinki and local data protection law. This study is part of the Fondecyt Regular project 1201461 which was approved by the Ethics Committee of The Faculty of Medicine of The Universidad del Desarrollo, as well as the Ethics Committee of the Servicio de Salud Metropolitano Sur-Oriente. Specifically, this study performed a secondary analysis of The CASEN survey. The data base of the survey has public and free access provided for academic research by the Ministry of Social Development upon request on the website ( http://observatorio.ministeriodesarrollosocial.gob.cl/ ). All analyses were performed with anonymized data following ethical standards in research. Consent for publication Not Applicable. Availability of data and materials The dataset analyzed during the current study is available in the Social Observatory website of the Ministry of Social Development http://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-casen-2017 All data generated during this study are included in this published article. Competing interest The authors report no competing interest Funding Fondecyt Regular 1201461, ANID, Chile. Authors’ contributions All authors contributed to the design, interpretation of results and drafted the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors thank The Ministry of Social Development of Chile for providing the CASEN dataset. This paper was written as part of the research project: Fondecyt Regular 1201461, ANID, Chile. 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The isolation paradox: A comparative study of social support and health across migrant generations in the US. Soc Sci Med. 2021;283:114204. Yang PQ, Hwang SH. Explaining Immigrant Health Service Utilization: A Theoretical Framework. SAGE Open. 2016;6(2):2158244016648137. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 12 Apr, 2022 Reviews received at journal 01 Apr, 2022 Reviewers agreed at journal 24 Mar, 2022 Reviewers agreed at journal 23 Mar, 2022 Reviewers invited by journal 23 Mar, 2022 Editor assigned by journal 23 Mar, 2022 Editor invited by journal 29 Jan, 2022 Submission checks completed at journal 29 Jan, 2022 First submitted to journal 07 Jan, 2022 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1239906","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":80122424,"identity":"da4aa2f5-b1a9-4994-bf1c-8eef0fcf2227","order_by":0,"name":"Isabel Rada","email":"","orcid":"","institution":"Universidad del Desarrollo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Isabel","middleName":"","lastName":"Rada","suffix":""},{"id":80122425,"identity":"40286ab8-fd44-482d-802e-75b7df8ab175","order_by":1,"name":"Marcela Oyarte","email":"","orcid":"","institution":"Instituto de Salud Pública de Chile","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marcela","middleName":"","lastName":"Oyarte","suffix":""},{"id":80122426,"identity":"be4d27ef-1aca-4b98-825e-066eb4fa43de","order_by":2,"name":"Baltica Cabieses","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuUlEQVRIiWNgGAWjYBACAwYGNoYEEIu9gUGCh4FBhgQtPAfAWniI0wIGEglEajFnP/zswYOKOjn5mW8Mb7xhsCOsxbInzdwg4cxhY4PbOcaWcxiSiXDYDQYzicS2A4kbpHPMpHkYDhCjhf2bROK/uvr5M88QrYUHaEsDcwIDkEGcFsuenHKDhGOHDTecSSu2nGNAhF/M2Y9ve/ijpk5evv3wxhtvKuzkCGpBdyepGkbBKBgFo2AUYAUAMoY2b9ukqzYAAAAASUVORK5CYII=","orcid":"","institution":"Universidad del Desarrollo","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Baltica","middleName":"","lastName":"Cabieses","suffix":""}],"badges":[],"createdAt":"2022-01-07 22:44:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1239906/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1239906/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":17848595,"identity":"afa554f8-9504-4d0d-8a4b-3168d48e087b","added_by":"auto","created_at":"2022-02-01 16:20:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1227803,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1239906/v1/78ad5f33-5ea7-4fc1-a263-99c384bbde8f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Comparative Analysis of Health Status of International Migrants and Local Population in Chile: a Population-based, Cross-sectional Analysis From a Social Determinants of Health Perspective\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eInternational migration is a complex process of voluntary or involuntary human mobility (1). Globally, in 2020 it was estimated that approximately 3.6% of world\u0026rsquo;s population were international migrants (2). In Latin America, one of the main migratory flows throughout the last decades has been intraregional migration, often know as south-south migration (3). Among the countries in the region, Chile has experienced a steady increase of international migration, current estimations from the National Institute of Statistics reported 1.462.103 international migrants at the end of 2020, reaching 8% of the total population. Estimations of sex distribution described a slightly higher proportion of migrant men (50.9%), almost half of migrants were aged 25-35 years old and the majority came from countries within the region such as Venezuela, Per\u0026uacute;, Haiti, Colombia and Bolivia (4). Previous evidence has highlighted the heterogeneity of this population, whose demographic and socioeconomic characteristics not only differ from Chilean population, but also within migrant groups (5). This variability is particularly important, since diverse exposures during migration process might have effects on health and wellbeing (6, 7). Furthermore, migration itself has been recognized as a social determinant of health, given the potential influence of certain migration circumstances on health risks (8), which makes the relationship between migration and health a public health priority (6).\u003c/p\u003e \u003cp\u003eThe health of international migrants residing in Chile has been previously explored. Some evidence has suggested a health advantage over native population called \u0026ldquo;healthy migrant effect\u0026rdquo; (HME). This phenomenon postulates that migrants have better health outcomes (morbidity, mortality) when compared to the host population (9). Explanatory models have proposed a positive selection where migrants are self-selected when they feel capable to face the migratory process (10). For example, selection applies on those who are younger and those with labor market skills (11). Other explanation is based on healthy behaviors preserved during migration process, which could be enhanced with favorable life conditions at the destination country (12). Moreover, psychosocial resources like social support and social cohesion may be protective for positive reinforcement of healthy behaviors (13, 14), stress management and disease risk prevention (15).\u003c/p\u003e \u003cp\u003eIn Chile, evidence from population-based studies have reported the probable existence of the HME on crude health indicators, such as disability (16, 17), illness, accidents and chronic health conditions (17). As well as hospital discharges rates, particularly, migrants had lower proportion of infectious diseases, metabolic disorders, mental health conditions and cardiorespiratory diseases, among others (18). Recent studies have also observed this advantage on emergency consultations of migrants residing in the northern area of the capital of Chile. For instance, migrants had lower hospitalization rates and were not affected by severe clinical conditions (19). Meanwhile, Peruvian mothers living in Santiago have also shown an advantage on perinatal outcomes over native Chilean mothers (20). Interestingly, migrants living in diverse cities of Chile showed a healthier behavior, since migrants reported regular physical activity, which in turn promotes their integration and increases their psychosocial resources (21).\u003c/p\u003e \u003cp\u003eAmong the above-mentioned evidence, some authors have tested the apparent healthy migrant effect from the perspective of social determinants of health (SDH), which referrers to \u0026ldquo;\u003cem\u003ethe conditions in which people are born, grow, work, live and age, and the wider set of forces and systems shaping the conditions of daily life\u003c/em\u003e\u0026rdquo; (22). For example, after the adjustment for socioeconomic determinants, the crude advantage seen on disability, any health problem, any chronic condition or cancer disappeared. Similarly, determinants of migration process also had an influence over time, it seems that longer residence duration in Chile dissolves the healthy migrant effect (17). Likewise, it has been proposed that lower discharges rates could be explained by demographic factors (e.g. age) and reduced access to health care (18). Therefore, positive selection might not apply to all cases and diverse exposures during migration could challenge the health of international migrants, considering that some migrant groups face structural vulnerability (23). Literature describes SDH that influence the health of international migrants, including: i) economic disadvantage and poor living conditions; ii) the effect of educational level on health literacy and behavioral decisions; iii) public policies and migratory laws acting either acting as facilitator or limiter (24); iv) psychosocial determinants that could also promote risk according to migration circumstances and interaction with host society. The lack or imbalance of psychosocial resources such as social support and limited social network have negative impact on health outcomes (15); v) access to health care often mediated by migratory status and sociocultural barriers (24). Noteworthy, migrant population in Chile are more likely to be uninsured and have less use of healthcare system than local population (25). International literature has suggested that lower access to healthcare might lead to the under-report of medical conditions in migrants, raising questions around its influence on HME analysis (26). Overall, the social determinants of health approach go beyond merely crude comparisons and comprehensively explores its modulation on HME.\u003c/p\u003e \u003cp\u003eCurrently there is a paucity of evidence testing the healthy migrant effect on health status of international migrants residing in Chile and the Latin American region more generally. Local literature remains inconclusive but recognizes the potential impact of diverse exposures during migration process. The migrant population in Chile has changed over time while became increasingly heterogeneous, which points out the need of an update analysis of HME under the social determinants of health approach. This would help to develop a broad understanding of the complexity of migration and health, and its implications on Chilean public health. The present study aims to analyze the existence of the healthy migrant effect on self-perceived health, chronic morbidity, disability and activity limitations and its association with social determinants of health. This analysis was performed by comparing the health status of international migrants and Chilean population from population-based data. In order to contribute to the comprehensive analysis of HME we investigate the influence of demographic, socioeconomic, access to health care, psychosocial and migratory related factors. This update bring attention to the multidimensional nature of migration in the South American region and the detection of particular needs of international migrants for health planning process.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe present investigation was a cross-sectional observational study in which a secondary analysis of the National Socioeconomic Characterization Survey (CASEN version 2017) was performed. The CASEN survey is regularly applied by the Ministry of Social Development to Chilean households and their residents; aiming to know their socioeconomic situation, multidimensional poverty and income distribution. As well as update the evidence of priority groups and detect their particular needs. This voluntary survey follows a structured interview answered by an adult who provides data of the other household members. This survey was designed with a probabilistic, stratified and multistage sampling; that is representative at each national, regional (16 regions), and urban/rural level, but excluding geographic areas with difficult access. The total sample was comprised by 70.947 households with 216.439 residents, which represented 16.843.471 Chilean population and 777.407 international migrants. The data base of CASEN survey has public access (27). This study is part of the Fondecyt Regular project 1201461 approved by the Ethics Committee of the Faculty of Medicine of The Universidad del Desarrollo and Ethics Committee of the Servicio de Salud Metropolitano Sur-Oriente. The study complied with ethical guidelines and regulations according to the principles of the Declaration of Helsinki.\u003c/p\u003e \u003cp\u003eHealth status\u003c/p\u003e \u003cp\u003eHealth status was examined using the framework of the small module on health from the European Statistics of Income and Living Condition (EU-SILC) as a reference. The instrument contains 3 different variables with its corresponding concepts (28). These concepts were used to create new variables from the questions available in the CASEN survey.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNegative Self-perceived health (NSPH)\u003c/strong\u003e \u003cp\u003enew variable was created based on the question \u0026ldquo;from 1 to 7 how would you rate your current health status\u0026rdquo;. According to previous literature the seven-grade scale could be interpreted as 1 very poor health to 7 excellent health that cannot be improved (29). Like previous studies (30), the variable was dichotomized as positive health for scores ranging 4-7 and negative health for scores ranging 1-3. This study focused on negative self-perceived health as indicator in order to maintain consistency with the other negative health indicators included in the analysis.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eChronic morbidity (CM)\u003c/strong\u003e \u003cp\u003ebased on question \u0026ldquo;have you been receiving medical treatment for the past 12 months?\u0026rdquo;. Dichotomized as yes or no according to the presence of hypertension/dental Emergency, diabetes, depression, acute myocardial infarction, cataracts, chronic obstructive pulmonary disease, leukemia, bronchial asthma, cancer (gastric, cervical uterine, breast, testicular, prostate, colorectal), preventive cholecystectomy, chronic kidney failure, ischemic brain accident, bipolar disorder, lupus or other chronic condition.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDisability (DIS)\u003c/strong\u003e \u003cp\u003eAlthough the EU-SILC framework does not separate disability from the activity limitation variable. The CASEN survey includes a question focused on disability (31), from whom the new variable was created \u0026ldquo;\u0026iquest;Do you have any of the following permanent conditions? Dichotomized as yes or no according to the presence of one or more physical/speaking/psychiatric/mental/hearing/visual conditions.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eActivity limitations (AL)\u003c/strong\u003e \u003cp\u003eThe variable was created using all types of daily living activities limitations asked by CASEN. \u0026ldquo;How much difficulty do you have for...\u0026rdquo;. This question was restricted to population over 6 years. Dichotomized as yes or no according to the presence of mild, moderate, severe, or extreme difficulty for one or more activities (eating, showering, displacing, bathroom use, lie down or get out of bed/ get dressed).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eSocial determinants of health\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDemographic factors\u003c/strong\u003e \u003cp\u003eage as continuous variable and categorical (\u0026lt;6 years, 6-14, 15-64 and \u0026gt;64 years). Sex (male, female). Ethnicity for those belonging or being descendant of minority groups in Chile (yes, no), marital status (single, married/cohabitant, separated/divorced/annulled, widow), area (urban, rural).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSocioeconomic factors\u003c/strong\u003e \u003cp\u003eeducational level according to the highest level achieved or current level of the household informant (categorized as university, technical, high school, primary, kinder, special education, none). Household income categorized in five quintiles of equal size sorted in ascending order according to the autonomous per capita household income (I, II, III, IV, V). Occupation defined by the occupational activity of the household informant. The variable was created from questions related to current job/occasional job/ work license/search for a job/ attending to educational center (categorized as unemployed, does not study, study, employed, and study and work).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAccess to health care\u003c/strong\u003e \u003cp\u003eThe variable affiliation to the health care system was used as a proxy of access and created from the question \u0026ldquo;Which health insurance system do you use?\u0026rdquo;. Further categorized as none, public health system affiliation, private health system affiliation, other.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePsychosocial factors\u003c/strong\u003e \u003cp\u003ethe variable social support was created from available questions that were mainly related to instrumental social support network; dichotomized yes or no according to the presence of one or more supportive behaviors from someone at home and outside. Social capital variable was created from a question of belonging and participation in diverse organizations or organized groups over the last 12 months. Dichotomized as yes or no according to the participation in one or more of these groups.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMigratory related factors\u003c/strong\u003e \u003cp\u003eCountry of origin was created as a categorical variable based on the question \u0026ldquo;When you were born, \u0026iquest;what country did your mother live in?\u0026rdquo;. The categories were selected according to the intraregional pattern reported in migratory statistics (4) (Venezuela, Per\u0026uacute;, Haiti, Colombia, Bolivia, Argentina, Ecuador, other countries in South America and other). Time of residence was created based on the year period in which the migrant arrived and categorized (2015 or later, 2010-2014, 2005-2009, 2000-2004, 1999 or before).\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eHealth status outcomes were analyzed descriptively for international migrants and Chilean born population. The crude and stratified prevalence by demographic, socioeconomic, access to health care and migratory related factors were presented as proportion. The Pearson\u0026rsquo;s chi-square test was used to test independence between migration and health status outcomes. Multivariate logistic regression was used to estimate the probability (odds ratio, OR) of reporting these health outcomes and adjusted by each set of SDH in international migrants and local population, separately. The association between migratory related factors and health outcomes was explored with multivariate logistic regression adjusted by sex and age. Then, the healthy migrant effect was examined using multivariate logistic regression sequentially adjusted for SDH, where NSPH, CM, DIS and AL were dependent variables and migrant status was the independent variable (reference Chilean born). In order to estimate the crude and adjusted probability of presenting these health outcomes if being international migrant. The Hosmer-Lemeshow goodness of fit test was used as post-estimation after logistic regression. Data analysis were performed with STATA 14 software (Stata Corp) and weighted according to the survey\u0026rsquo;s sampling design. Significance was set at 0.05 with 95% confidence interval (95% CI).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eCrude prevalence of health outcomes\u003c/h2\u003e\n \u003cp\u003eInternational migrants had lower crude prevalence of NSPH (3,97% vs 5,91%), CM (9,55% vs. 25,97%), DIS (14,63% vs. 23,89%) and AL (5,56 vs. 11,52%). Regarding stratified analysis, both groups showed higher prevalence of health status outcomes among female, people over 64 years, widow, unemployed and those with public health system affiliation. The outcomes differed by geographical area, for example prevalence of CM and DIS were higher in local and migrant population living in rural areas. Whereas negative self-perceived health and AL were higher in Chileans living in rural areas but lower in migrants. Stratified analysis of socioeconomic factors showed diverse results for these health outcomes, particularly there was a gradient in self-perceived health across income quintiles of both groups. Among migrants, higher prevalence of NSPH was observed in those who were uninsured and those with primary level education. However, CM was higher in migrants with the highest education level and those with private health system affiliation. Conversely, DIS and AL, was higher in those who were affiliated in the public health system (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e-\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Furthermore, migrants from Peru showed the highest prevalence of NSPH (6,43%), disability (7,69%) and AL (4,15%) whereas those from Ecuador had the higher percentage of CM (23,37%). Meanwhile, migrants who had arrived in 2015 or later showed higher rates of negative health perception (4,5%), but those who expended more than 20 years had higher rates of CM (31,08%), DIS (16,58%) and activity AL (7,34%) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCrude and stratified prevalence of health outcomes by SDH factors in immigrant population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eSocial determinant\u003c/p\u003e\n \u003cp\u003eof health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003eself-perceived health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eChronic\u003c/p\u003e\n \u003cp\u003emorbidity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e3,97%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e[2,8% - 5,7%]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e9,55%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e[8,3% - 10,9%]\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e14,63%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e[13,1% - 16,3%]\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,7% - 8,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[8,9% - 12,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,0% - 10,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,4% - 4,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,6% - 12,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,1% - 5,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge categories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[0,5% - 5,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,6% - 9,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,8% - 9,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6-14 years\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,1% - 6,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,6% - 6,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,4% - 12,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15-64 years\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,4% - 5,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,09%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,7% - 10,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,2% - 6,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;64 years\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[8,8% - 19,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49,88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[41,8% - 58,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29,41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[22,3% - 37,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,6% - 8,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,5% - 14,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,2% - 10,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,7% - 5,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[8,4% - 11,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,2% - 7,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,1% - 8,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,4% - 11,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,7% - 9,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/cohabitant\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,2% - 4,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,9% - 11,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,39%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,6% - 5,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeparated/divorced/annulled\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,8% - 14,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22,55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[15,8% - 31,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,4% - 10,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidow\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[12,1% - 30,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46,18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[35,3% - 57,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32,13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[22,4% - 43,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eArea\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,8% - 5,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,51%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[8,2% - 11,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,2% - 7,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,2% - 4,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[9,7% - 19,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,27%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,2% - 9,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,8% - 7,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,2% - 9,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,2% - 13,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,7% - 4,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[9,9% - 19,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,7% - 5,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnical\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,0% - 3,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,2% - 10,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,0% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh School\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,4% - 9,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,5% - 9,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,5% - 9,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,2% - 7,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,7% - 12,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,3% - 10,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome quintile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,0% - 7,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,5% - 11,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,7% - 8,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,3% - 8,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,9% - 10,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,2% - 11,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,9% - 16,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,3% - 10,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,7% - 18,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,3% - 3,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,2% - 9,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,8% - 5,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,0% - 5,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[10,1% - 19,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,1% - 4,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoes not study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[0,2% - 3,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,0% - 7,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,5% - 11,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,8% - 17,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17,46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[14,1% - 21,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[8,1% - 20,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,1% - 12,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[5,2% - 13,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,5% - 7,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,9% - 3,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,0% - 9,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,7% - 4,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy or/and employed\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[0,1% - 2,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45,35%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[13,9% - 81,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[0,5% - 6,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccess to healthcare\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,5% - 4,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,5% - 5,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,8% - 7,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic health system affiliation\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,7% - 7,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,8% - 10,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,7% - 8,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate health system affiliation\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,1% - 7,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[11,1% - 29,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,9% - 4,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,0% - 6,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,6% - 23,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,7% - 8,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial Support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,2% - 5,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[10,7% - 17,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,3% - 5,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30,13%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,6% - 72,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[1,4% - 8,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[6,8% - 72,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial capital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,7% - 5,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15,42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[12,5% - 18,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,03%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[4,6% - 7,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[2,6% - 6,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[7,4% - 11,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,44%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e[3,9% - 7,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eNegative self-perceived health\u003c/em\u003e, \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003cem\u003echronic morbidity\u003c/em\u003e, \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003cem\u003edisability p value \u0026lt; 0.05 when comparing the same category between the Chilean-born and the immigrant populations (Chi-square test). CI: confidence interval.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCrude and stratified prevalence of health outcomes by SDH factors in Chilean born population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003eself-perceived health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eChronic\u003c/p\u003e\n \u003cp\u003emorbidity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial determinant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eof health\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,7% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25,97%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[25,6% - 26,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[23,6% - 24,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,4% - 6,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30,55%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[30,0% - 31,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[12,2% - 13,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,9% - 5,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21,47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[21,1% - 21,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,43%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[10,1% - 10,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge categories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,5% - 3,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,2% - 8,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,87%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,4% - 6,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6-14 years\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,3% - 2,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[8,1% - 9,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,6% - 5,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15-64 years\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,9% - 5,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22,58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[22,2% - 23,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[8,6% - 9,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;64 years\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[13,7% - 14,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[67,0% - 68,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32,04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[31,1% - 32,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,2% - 6,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21,36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[20,5% - 22,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[10,6% - 11,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,7% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26,78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[26,4% - 27,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,3% - 11,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,6% - 4,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[13,1% - 14,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,9% - 8,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/cohabitant\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,9% - 7,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35,04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[34,4% - 35,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,43%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[12,0% - 12,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeparated/divorced/annuled\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,9% - 9,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40,18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[39,0% - 41,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15,12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[14,3% - 16,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidow\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[13,7% - 15,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67,53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[66,4% - 68,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[34,2% - 36,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,6% - 6,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[25,5% - 26,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,1% - 11,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,3% - 7,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28,31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[27,4% - 29,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,7% - 13,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducational level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,9% - 6,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[17,2% - 19,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[13,2% - 14,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,7% - 3,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[19,2% - 20,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,3% - 7,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnical\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,3% - 4,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21,58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[20,5% - 22,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,9% - 8,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh School\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,5% - 6,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[26,1% - 27,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[10,3% - 11,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[8,0% - 8,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[32,8% - 34,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15,74%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[15,2% - 16,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncome quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,5% - 8,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27,31%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[26,6% - 28,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,24%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[13,7% - 14,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,3% - 7,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26,08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[25,4% - 26,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,8% - 12,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,7% - 6,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26,58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[25,8% - 27,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,4% - 12,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,02%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,7% - 5,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26,45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[25,7% - 27,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[9,7% - 10,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,7% - 3,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[23,4% - 25,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,3% - 8,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoes not study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,4% - 3,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,59%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,8% - 7,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,03%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,4% - 5,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,88%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,5% - 12,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[48,1% - 49,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[22,9% - 24,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,9% - 2,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,49%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[8,9% - 10,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,51%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,1% - 6,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,0% - 4,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[23,1% - 24,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,3% - 7,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy or/and employed\u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,94%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,2% - 3,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10,76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[9,5% - 12,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,6% - 7,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAccess to healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,98%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,1% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,63%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[12,3% - 15,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,9% - 9,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic health system affiliation\u003csup\u003ebc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,3% - 6,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27,77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[27,3% - 28,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[12,4% - 13,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate health system affiliation\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,86%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,5% - 3,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[19,7% - 21,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,8% - 6,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,9% - 6,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28,49%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[26,4% - 30,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[9,9% - 12,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,54%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,3% - 7,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[39,8% - 41,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[14,5% - 15,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,8% - 16,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[36,7% - 45,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20,26%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[17,4% - 23,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial capital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,1% - 6,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36,23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[35,6% - 36,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[13,2% - 14,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003csup\u003eabc\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,41%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,2% - 6,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26,18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[25,7% - 26,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,05%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,7% - 12,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\"\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003eNegative self-perceived health\u003c/em\u003e, \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003cem\u003echronic morbidity\u003c/em\u003e, \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003cem\u003edisability p value \u0026lt; 0.05 when comparing the same category between the Chilean-born and the immigrant populations (Chi-square test). CI: confidence interval.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCrude and stratified prevalence of activity limitations by SDH in immigrant and Chilean born population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eActivity limitations\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial determinants\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eof health\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eChilean born population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMigrant population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11,52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,2 \u0026ndash; 11,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,3% - 7,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,0% - 6,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,39%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,6% - 7,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,0% - 4,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,9% - 2,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAge categories\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6-14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,57%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,2% - 5,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,9% - 10,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15-64 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,3% - 2,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,5% - 4,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;64 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[18,4% - 19,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21,14%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[15,1% - 28,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,3% - 5,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,1% - 7,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,1% - 5,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,3% - 4,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarital Status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,3% - 3,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,2% - 8,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/cohabitant*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,4% - 4,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,7% - 1,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeparated/divorced/annulled*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,8% - 7,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,5% - 2,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewidow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[22,9% - 25,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29,22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[19,9% - 40,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,0% - 5,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,3% - 4,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,4% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,2% - 4,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEducational level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[23,0% - 26,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,0% - 25,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,5% - 2,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,6% - 1,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnical*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,66%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,4% - 2,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,49%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,2% - 1,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,78%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,6% - 4,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,9% - 8,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,9% - 8,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,6% - 6,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eIncome quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eI*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[7,0% - 7,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,86%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,8% - 4,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,76%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,5% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,1% - 2,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,8% - 5,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,17%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,4% - 17,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,9% - 4,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,9% - 3,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,7% - 3,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,38%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,9% - 2,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoes not study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33,81%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[21,8% - 48,3%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,77%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,2% - 14,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12,33%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[11,9% - 12,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,4% - 16,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,5% - 0,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,4% - 2,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,5% - 1,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,4% - 1,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy and work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,1% - 0,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,2% - 5,6%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAccess to healthcare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,51%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,9% - 3,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,7% - 3,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic health system affiliation*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,7% - 6,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,3% - 5,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,7% - 2,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,8% - 2,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,9% - 6,9%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,0% - 7,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,2% - 6,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,62%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,0% - 2,5%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,18%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,6% - 10,1%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29,01%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,8% - 73,0%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial capital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,42%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,2% - 5,7%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,3% - 3,2%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,19%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,0% - 5,4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,1% - 4,8%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cem\u003e*p value \u0026lt; 0.05 when comparing the same category between the Chilean-born and the immigrant populations (Chi-square test). CI: confidence interval.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003ctable border=\"1\" id=\"Tab4\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCrude and stratified prevalence of health outcomes by migratory related factors in immigrant population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eNegative self-perceived health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eChronic morbidity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eActivity limitations\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry of Origin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVenezuela\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,93%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,94% - 3,90%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,97% - 15,11%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,57% - 7,33%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,96%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,44% - 2,07%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePeru\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,43%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,71% - 14,50%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[6,94% - 10,74%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,69%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,76% - 15,08%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,04% - 15,21%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHaiti\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,60% - 8,25%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,79% - 3,99%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,94%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,65% - 5,17%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,20% - 1,70%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eColombia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,75%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,37% - 5,47%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,22%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,14% - 9,25%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,50% - 7,06%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,69% - 5,18%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBolivia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,95%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,89% - 4,59%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,22% - 9,63%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,85%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,28% - 7,93%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,15%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,12% - 4,67%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArgentina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,22% - 4,52%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20,49%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[16,24% - 25,50%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,21%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,04% - 10,22%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,27%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,28% - 3,99%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEcuador\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,41% - 8,17%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23,37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[14,00% - 36,37%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,55% - 7,71%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,37%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,43% - 4,24%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther countries in South America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,61%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,95% - 10,49%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14,46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[9,40% - 21,59%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,06%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,59% - 10,01%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,53%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,46% - 4,93%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,79%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,81% - 8,71%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,52%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[14,63% - 23,17%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,89%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[5,80% - 10,65%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,32%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,96% - 6,27%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015 o later\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,56%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,71% - 7,58%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,04%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,47% - 17,54%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,11% - 4,23%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,03% - 1,62%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2010-2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,14% - 11,37%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,84%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,40% - 13,27%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,29% - 7,34%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,48%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,69% - 3,63%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2005-2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,11%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,33% - 3,67%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,16% - 15,67%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,07%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,23% - 18,76%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,04% - 2,13%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2000-2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,16% - 3,28%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,99%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,57% - 22,18%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,65%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,58% - 19,76%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,23%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,03% - 1,72%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1999 or before\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,68%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,86% - 7,99%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31,08%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[21,69% - 42,34%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16,58%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[10,02% - 26,19%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,34%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[3,38% - 15,23%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003edoesn\u0026rsquo;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,11% - 6,70%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13,73%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[10,84% - 17,23%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6,12%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[4,51% - 8,24%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,47%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[2,39% - 5,03%]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"9\"\u003e\u003cem\u003eCI: confidence interval.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eSDH associated with health outcomes\u003c/h2\u003e\n \u003cp\u003eLogistic regression models for NSPH, CM and DIS adjusted by different set of SDH in migrant population are presented in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. Models for Activity limitations in both populations are presented in Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. Age was associated with all health outcomes in both populations. Among international migrants, after adjusting for demographic variables the odds of having NSPH was 7,44 times higher in those unemployed (OR: 7,44; 95% CI: 1,05\u0026ndash;52,61). CM was associated with affiliation to the health system, particularly affiliation to private health system (OR 4,99; 95% CI: 2,70-9,25). Whereas the risk of CM was also associated with having social support (OR: 3,29; 95% CI: 1,29-8,40) and social capital (OR: 1,84; 95% CI:1,23-2,75). Conversely, social support was associated with reduced odds of DIS (OR: 0,23; 95% CI: 0,09-0,60). Moreover, other variables were associated with both reduced and higher odds, for example having social support reduced by 77% the odds of NSPH (OR: 0,23; 95% CI: 0,10-0,55) and AL (OR: 0,13; 95% CI: 0,05-0,35), but increased the odds for CM (OR: 3,29; 95% CI: 1,29-8,40). Likewise, being married/cohabitant was associated with less chances of DIS (OR: 0,50; 95% CI: 0,29-0,87) and AL (OR: 0,24; 95% CI: 0,09-0,62). Regarding migratory related factors (Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.), those from Haiti had higher odds of NSPH (OR: 4,67; 95% CI: 1,31-16,66) and DIS (OR: 2,88; 95% CI: 0,15-7,19), while those from Argentina showed higher risk of CM (OR: 1,42; 95% CI: 0,59-3,42). Staying over 20 years in Chile was associated with 11,04 times more chances of DIS (OR: 11,04; 95% CI: 3,65-33,4)\u003c/p\u003e\n \u003ctable border=\"1\" id=\"Tab5\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression models of health outcomes by SDH in immigrant population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSelf-perceived bad health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eChronic morbidity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,02*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,01 - 1,03]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,06*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,05 - 1,07]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,02 - 1,04]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (ref = male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,67 - 2,66]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,410\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,61 - 1,65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,983\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,65*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,05 - 2,60]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,029\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eethnicity: (ref= no ethnicity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,89 - 2,95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,52 - 1,41]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,82 - 2,04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMarital status (ref = single)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/Cohabitant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,23 - 1,29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,41 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,50*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,29 - 0,87]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeparated/divorced/annuled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,32 - 3,57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,57 - 1,80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,965\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,22 - 1,10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewidow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,42 - 6,57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,37 - 1,19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,60 - 3,77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,387\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZone (ref=urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,48*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,27 - 0,83]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,67 - 1,93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,66 - 1,40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,129\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocioeconomic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEducational level (ref = none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,22 - 2,39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,58 - 4,18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,33*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,14 - 0,82]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,12 - 1,31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,41 - 2,63]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,29*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,12 - 0,75]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,29 - 2,97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,46 - 2,79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,42*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,19 - 0,97]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,042\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,38 - 3,30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,836\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,57 - 3,29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,22 - 1,03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eIncome quintile (ref=I lower income level)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,75 - 2,73]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,66 - 1,78]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,76 - 2,92]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,36 - 5,67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,56 - 1,52]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,85 - 7,00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,097\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,27 - 1,10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,50 - 1,36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,446\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,47 - 2,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,969\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,35 - 2,14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,753\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,68 - 1,97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,36 - 1,80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eOccupation (ref= does not study)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7,44*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,05 - 52,61]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,044\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,13 - 2,24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,52 - 13,17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,52 - 31,04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,32 - 5,15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,38 - 7,29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,503\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,51 - 17,22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,10- 1,30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,26 - 4,08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,966\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy and work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,07- 7,47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,57 - 49,68]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,15 - 5,44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,919\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccess to healthcare (ref= none)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,93 - 4,42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,94*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,82 - 4,73]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,68 - 2,96]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3,40*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,30 - 8,86]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4,99*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 2,70 - 9,25]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,34 - 1,72]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,39- 3,10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,99*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,29 - 6,91]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,26 - 2,17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoesn\u0026apos;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,50- 3,26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,602\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,38 - 2,57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,973\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,26 - 2,11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,567\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,445\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePsychosocial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial support (ref=no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,23*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,10 - 0,55]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3,29*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,29 - 8,40]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,23*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,09 - 0,60]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial capital (ref=no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,51 - 1,53]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,84*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,23 - 2,75]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,030\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,59 - 2,01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,774\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,747\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003cem\u003eCI: confidence interval; *p value \u0026lt; 0,05\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\u003cbr\u003e\n\u003c/div\u003e\n\u003ctable border=\"1\" style=\"border: none; border-collapse: collapse; empty-cells: show; max-width: 100%;\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eLogistic regression models of activity limitations by SDH in immigrant and Chilean born populations.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003cth align=\"left\" colspan=\"7\" style=\"border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eActivity limitations\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003eImmigrant\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003eChilean born\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003eDemographic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e1,04*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[ 1,02 - 1,07]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e1,06*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[1,05 - 1,06]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eSex (ref = male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e2,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,77 - 5,90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e1,18*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e - \u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eethnicity: (ref= no ethnicity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e2,25*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[ 1,13 - 4,50]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e1,17*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[1,07 - 1,28]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eMarital status (ref = single)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eMarried/Cohabitant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,24*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[ 0,09 - 0,62]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,42*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,39 - 0,45]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eSeparated/divorced/annuled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,15*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,04 - 0,55]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,54*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,48 - 0,60]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ewidow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,46 - 6,01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,89*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,81 - 0,98]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eZone (ref=urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,37 - 1,28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,96 - 1,12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003eSocioeconomic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eEducational level (ref = none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,10 - 1,27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,112\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,22*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,18 - 0,27]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eTechnical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,20*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,43 - 0,90]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,037\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,18 - 0,27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,31 - 3,43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,26 - 0,34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,20 - 2,30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,33 - 0,43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" colspan=\"3\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eIncome quintile (ref=I lower income level)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,31 - 1,65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,86 - 1,01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e4,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,89 - 19,98]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,85*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,77 - 0,93]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,31 - 3,08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,79*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,71 - 0,88]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,38 - 3,33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,73*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,63 - 0,84]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eOccupation (ref= none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eStudy or/and employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,38 - 7,29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,00 - 0,02]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" colspan=\"2\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003eAccess to healthcare (ref= none)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ePublic health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,34 - 5,18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,99- 1,79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003ePrivate health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,32 - 4,67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,68 - 1,31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,08 - 3,55]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,527\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,85 - 1,74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,292\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eDoesn\u0026apos;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,38 - 5,54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,584\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,80 - 1,68]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003ePsychosocial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eSocial support (ref=no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,13*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[ 0,05 - 0,35]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e1,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,83 - 1,35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,648\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eSocial capital (ref=no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e[0,29 - 1,81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,83*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e[0,76 - 0,90]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cstrong style=\"font-weight: 700;\"\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr style=\"user-select: none;\"\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" style=\"min-width: 5px; border: 1px solid rgb(221, 221, 221); user-select: text;\"\u003e\n \u003cp style=\"margin-bottom: 10px !important;\"\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp style=\"margin-bottom: 10px !important;\"\u003e\u003cbr style=\"color: rgb(0, 0, 0); font-family: \u0026quot;Times New Roman\u0026quot;; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\"\u003e\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab6\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression models of health outcomes by migratory related factors in immigrant population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003eSelf-perceived health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eChronic morbidity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003esex + age +\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry of Origin (ref = Per\u0026uacute;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVenezuela\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,29 \u0026ndash; 22,78]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,43 \u0026ndash; 8,89]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHaiti\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4,67*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,31 \u0026ndash; 16,66]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,88*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,15 \u0026ndash; 7,19]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eColombia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,05 \u0026ndash; 6,25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,34 \u0026ndash; 3,45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,11 \u0026ndash; 3,99]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,658\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArgentina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,02 \u0026ndash; 4,64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,42\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,59 \u0026ndash; 3,42]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,420\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,13*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,03 \u0026ndash; 0,58]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther countries in South America\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,20 \u0026ndash; 7,85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,09\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,68 \u0026ndash; 6,01]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,200\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,13 \u0026ndash; 1,49]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,186\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,45 \u0026ndash; 32,77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,66 \u0026ndash; 5,47]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,232\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,31 \u0026ndash; 2,04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,625\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime of residencia (ref = 2010 or later)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2009 - 2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,25*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 0,06 - 0,99]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,22 \u0026ndash; 1,77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,89*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 1,04 \u0026ndash; 8,04]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,042\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1999 or before\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,05 \u0026ndash; 4,22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[ 0,43 \u0026ndash; 4,60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e11,04*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ 3,65 \u0026ndash; 33,4]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e\u003cem\u003eCI: confidence Interval; *p value \u0026lt; 0.05.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch2\u003eCI: confidence Interval *p value \u0026lt; 0.05\u003c/h2\u003e\n\u003cp\u003eDiverse variables were associated with health status of Chilean population, including all demographic factors (Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). After adjustment for demographics, the lack of educational attainment was associated with higher risk of NSPH, CM and DIS. In addition, being unemployed was associated with having NSPH (OR: 2,23; 95% CI: 1,72-2,89) and DIS (OR: 3,04; 95% CI: 2,49-3,70). The public health system affiliation was associated with higher odds of CM (OR: 1,83; 95% CI: 1,60-2,10) and DIS (OR: 1,24; 95% CI: 1,05-1,47). Meanwhile, those married/cohabitant were 58% less likely to have AL (OR: 0,42; 95% CI: 0,39-0,45), and 45% of having DIS (OR: 0,55; 95% CI: 0,52-0,58), while also reduced the odds of NSPH and CM. The highest level of income quintile was associated with 48% less chance of having NSPH (OR: 0,52; 95% CI: 0,46-0,59). As well as reduced odds of DIS (OR: 0,76; 95% CI: 0,69-0,85) and AL (OR: 0,73; 95% CI: 0,63-0,84). Among psychosocial factors, having social support was associated with 38% less odds of NSPH (OR: 0,62; 95% CI: 0,50-0,76). Whereas social capital increased the odds of having CM (OR: 1,21; 95% CI: 1,15-1,27).\u003c/p\u003e\n\u003ctable border=\"1\" id=\"Tab8\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression models of health status outcomes by SDH in the Chilean born population.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eSelf-perceived bad health\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eChronic morbidity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eActivity limitations\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95% IC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,03 - 1,04]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,06*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,05 - 1,06]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,04*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,04 - 1,04]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,06*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,05 - 1,06]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex (ref = male)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,18*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e - \u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,54*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,48 - 1,59]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,05*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,02 - 1,10]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,18*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e - \u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eethnicity: (ref= no ethnicity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,16*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,05 - 1,28]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,93 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,22*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e - \u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,17*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,07 - 1,28]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMarital status (ref = single)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried/Cohabitant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,84*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,78 - 0,89]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,94*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,91 - 0,98]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,55*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,52 - 0,58]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,42*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,39 - 0,45]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSeparated/divorced/annuled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,84 - 1,03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,93 - 1,04]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,64*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,60 - 0,69]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,54*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,48 - 0,60]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ewidow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,85*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,77 - 0,94]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,99 - 1,13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,90*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,84 - 0,98]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,89*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,81 - 0,98]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZone (ref=urban)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,08*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,00 - 1,17]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,98 - 1,09]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,93 - 1,08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,971\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,96 - 1,12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,384\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocioeconomic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eEducational level (ref = none)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUniversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,34*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,29 - 0,39]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,55*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,49 - 0,62]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,24*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,21 - 0,27]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,22*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,18 - 0,27]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,38*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,33 - 0,45]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,60*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,53 - 0,69]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,27*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,23 - 0,31]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,18 - 0,27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,46*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,41 - 0,52]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,60*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,54 - 0,68]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,29*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,26 - 0,32]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,26 - 0,34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,235\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,61*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,54 - 0,69]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,74*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,66 - 0,83]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,39*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,36 - 0,44]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,33 - 0,43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eIncome quintile (ref=I lower income level)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,89*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,82 - 0,97]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,95 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,913\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,91 - 1,03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,86 - 1,01]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,84*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,78 - 0,92]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,94 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,88 - 1,00]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,85*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,77 - 0,93]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,73*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,66 - 0,81]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,91 - 1,03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,83*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,78 - 0,89]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,79*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,71 - 0,88]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,52*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,46 - 0,59]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,90 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,498\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,76*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,69 - 0,85]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,73*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,63 - 0,84]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eOccupation (ref= does not study)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,23*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,72 - 2,89]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,80*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,67 - 0,97]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3,04*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[2,49 - 3,70]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,04*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,02 - 0,07]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,87 - 1,46]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,350\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,72 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,15*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,74 - 2,67]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,19*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,01 - 0,04]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,93 - 1,57]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,51*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,43 - 0,62]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,18 - 1,74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,01 - 0,02]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudy and work\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,61*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e - \u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,63*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,50 - 0,79]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2,11*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,56 - 2,85]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,01*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,00 - 0,02]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccess to healthcare (ref= none)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,82 - 1,24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,83*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,60 - 2,10]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,24*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,05 - 1,47]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,99- 1,79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate health system affiliation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,66 - 1,09]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,91*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,62 - 2,24]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,85 - 1,24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,757\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,68 - 1,31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,70 - 1,19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,65*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[1,40 - 1,95]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,83 - 1,25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,85 - 1,74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,292\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDoesn\u0026apos;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,67 - 1,19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[1,00 - 1,47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,90 - 1,42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,80 - 1,68]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePsychosocial\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial support (ref=no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,62*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,50 - 0,76]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,98 - 1,37]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,72 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,83 - 1,35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,648\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial capital (ref=no)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,80*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,74- 0,87]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1,21*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e - \u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,90 - 1,03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,83*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,76 - 0,90]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGOF test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\"\u003e\u003cem\u003eCI: confidence Interval *p value \u0026lt; 0.05.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eFindings on Healthy Migrant effect\u003c/h2\u003e\n \u003cp\u003eThe odds of having each health outcomes if being an international migrant were calculated and progressively adjusted by each set of SDH (Table \u003cspan class=\"InternalRef\"\u003e9\u003c/span\u003e.). The crude analysis revealed a healthy migrant effect, since being an immigrant was significantly associated with lower odds of presenting all health outcomes. After adjustment for demographics, being immigrant was no longer protective for NSPH and AL. However, after adjustment for socioeconomic covariates, only the association with CM remained significant. The subsequent models showed a healthy migrant effect for CM after adjustment for access to health care and psychosocial factors. Being migrant was associated with 39% lower odds of chronic morbidity compared to Chilean population (OR: 0,61; 95% CI: 0,44-0,84; P = 0,0003).\u003c/p\u003e\n \u003ctable border=\"1\" id=\"Tab9\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression models of health outcomes if being an international immigrant sequentially adjusted by SDH.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003cp\u003eCrude OR of being migrant\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003cp\u003eAdjusted OR by demographics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eModel 3\u003c/p\u003e\n \u003cp\u003eAdjusted OR by\u003c/p\u003e\n \u003cp\u003edemographics + SES\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eModel 4\u003c/p\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003cp\u003eby demographics +SES\u003c/p\u003e\n \u003cp\u003e+access to health care\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eModel 5\u003c/p\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003cp\u003eby demographics +SES\u003c/p\u003e\n \u003cp\u003e+access to health care\u003c/p\u003e\n \u003cp\u003e+psychosocial\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[IC95%]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003ep\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[IC95%]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003ep\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[IC95%]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003ep\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[IC95%]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003ep\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[IC95%]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"BoldItalic\" name=\"Emphasis\" type=\"BoldItalic\"\u003ep\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNegative\u003c/p\u003e\n \u003cp\u003eSelf-perceived health\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,66*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,45 - 0, 96]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,62 - 1,33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,71 - 1,60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,71 - 1,64]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,81 - 2,28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,252\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic morbidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,30*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,26 - 0, 35]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,43*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,36 - 0,51]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,50*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,42 - 0,61]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,54*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,45 - 0,67]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,61*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,44 - 0,84]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDisability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,45*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,34 - 0, 60]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,000\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,66*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,50 - 0,87]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,57 - 1,05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,58 - 1,08]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,55 - 1,62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,835\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActivity limitations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,44*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0,25 - 0, 80]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0,007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,46 - 1,53]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,560\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,49 - 2,50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,812\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,51 - 2,70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,719\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[0,82 - 5,76]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"16\"\u003e\u003cem\u003eCI: confidence Interval *p value \u0026lt; 0.05.\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study analyzed the prevalence of health outcomes of international migrants and local population, and its associated SDH. As well as the presence of the HME by comparing both populations. Results showed that migrants had lower crude prevalence across all health outcomes. In both groups age, unemployment, affiliation to the health system and psychosocial factors were associated with these outcomes. Among migrants, a time of residence over 20 years was associated with higher odds of disability. Crude models showed an apparent migrant\u0026rsquo;s health advantage on NSPH, CM, DIS and AL. However, after adjustment for demographics, socioeconomics, health care affiliation and psychosocial factors, being immigrant only confers protection for chronic morbidity. Previous evidence from CASEN survey-2006 revealed a crude and adjusted by demographics advantage for any disability, health problem/accident and any chronic condition. In contrast to our findings, this advantage was no longer significant after controlling for socioeconomic and material covariates. Thus, the healthy migrant effect did not persist for any health outcome, highlighting the influence of a poor socioeconomic status on health decline (17). Other crude comparisons between international migrants and local population in South America, have suggested a probable existence of healthy migrant effect on chronic conditions. In Colombia, migrants from Venezuela had a lower self-reported prevalence of diverse chronic diseases such as hypertension, cardiovascular diseases, diabetes mellitus and cancer than local population (32). Similar to the smaller percentage of chronic conditions reported by Venezuelans in Peru (33). Data from other sources such as hospital discharges, have revealed crude lower rates of CM in migrants residing in Chile (18). Moreover, adjusted analysis on cancer hospital discharges also showed a potential advantage on this indicator (34).\u003c/p\u003e \u003cp\u003eThe migrant\u0026rsquo;s advantage on CM could be explained by a positive selection, where those who decide to migrate are healthier, than those who decided to stay. This better baseline health could be derived from the access to a healthy diet, lower environmental risks, among other exposures at the country of origin. Besides, their attitude towards long-term health by adopting healthier behaviors that might reduce risks factors for chronic diseases, while those who have medical conditions are more prone to return (35). This explanation might be complementary to the \u0026ldquo;cultural buffering\u0026rdquo; of the migrant\u0026rsquo;s group, whose norms reduce risky behaviors and promotes a healthy decision making (36). Although, CASEN survey does not provide information related to behavioral factors, data from the Chilean national health survey (ENS 2016-2017) revealed elevated levels of alcohol consumption, smoking, sedentary lifestyle and low fruit and vegetable consumption in the general population. As well as, type II diabetes mellitus, hypertension, dyslipidemia and obesity (37). Chile has experienced an epidemiological transition, where overall non-communicable disease burden has increased, reaching more than four comorbidities in the general population (38). Among countries in the Americas Region, Chile has a high rate of deaths caused by chronic diseases, which contrast with lower rates reported by the main migrant\u0026rsquo;s countries of origin (39). Therefore, the advanced epidemiological transition in Chile could yield a health gap between migrants and locals, that needs to be analyzed throughout the migrant life trajectories.\u003c/p\u003e \u003cp\u003eLiterature have suggested that HME disappears with time of residence and migrant health converge to native population, mainly in elderly (40). This deterioration results from cumulative exposures such as adoption of unhealthy behaviors from host society (e.g. smoking, alcohol consumption, greater calories intake), acculturative stress, discrimination and precarious living conditions (40, 41). Our findings show a higher crude prevalence of CM for those migrants living over 20 years in Chile. However, time of residence was not associated with CM in the partially adjusted model. Thus, the exposure to diverse factors during migration process does not seem to dissolve the advantage for chronic diseases seen in international migrants residing in Chile. As mentioned, this protection does not apply for a long-term condition such as disability that could be derived from exposure to diverse SDH. Evidence have suggested that even if migrants experienced advantages in other health outcomes, they face disability in a great extent. A cumulative disadvantage resulted from social vulnerability could lead to occupational risks like high physical job demands, abuse and unsafe conditions that might play a role in the development of functional impairment (42). Moreover, migrants at older ages tend to display higher disability rates than recent migrants and local population (42, 43). In the same line, it has been documented that time of residence has an inverse association with self-perceived health. While there\u0026rsquo;s also evidence reporting poor health perception in recent migrants, suggesting the absence of HME in this indicator (44). Nevertheless, when examining the health perception trajectories, it could be either stable or decline over time at similar rate as locals, which contrast to the negative relationship described in cross-sectional data (45).\u003c/p\u003e \u003cp\u003eRegarding the psychosocial resources, previous evidence have highlighted its protective role in migrants health (13, 15). Our results showed both risk and protective associations between psychosocial factors and health outcomes. Particularly, these factors were associated with increased odds of DI and CM but were protective for the remaining health outcomes. This dual effect has been previously suggested for migration networks (46). Depending on networks composition, migrants might be differentially exposed to healthy or risky behaviors (e.g., alcohol consumption determined by social situations, religious norms and ethnic identity) (47). Whereas, social support differs by migrant\u0026rsquo;s characteristics, including migratory related factors as well as social context and types of supportive ties. Literature have described an \u0026ldquo;isolation paradox\u0026rdquo; in which migrants with poor social support were healthier than natives with similar isolation levels. The expected gradient between social support and good health is not always seen in migrant population, those with greater social support could also display poor health outcomes (48). Moreover, CASEN survey asks if the participant was under treatment in the past 12 months for CM. Thus, the association might result from the positive influence of social networks on health care utilization and health seeking behavior. Similarly, having health insurance could lead to increased access to diagnosis and treatment (49), which could explain the association between CM and healthcare affiliation. Since these priority conditions are covered by the explicit health guarantees of Chilean health care system.\u003c/p\u003e \u003cp\u003eThe present study contributes to the understanding of the healthy migrant effect by comparing international migrants and local population from population-based data. Our findings provide an insight of the influence of health access and psychosocial factors on migrant\u0026rsquo;s health status, beyond the influence of socioeconomic factors already described in previous research in Chile. This new evidence shed light on health disparities between these populations and brings attention to its importance for health planning. However, the study has important limitations including the cross-sectional analysis that does not allow us to detect changes across time of residence. Estimations were based on self-reported data without medical confirmation. In addition, the CASEN survey does not provide data of behavioral and occupational risk factors to better understand prevalence of long-term conditions. Similarly, due to database limitations it was not possible to analyze other migratory variables and those analyzed were adjusted by sex and age. Furthermore, it is possible that some migrants did not report that they were born abroad or those with irregular administrative status have chosen not to participate. Therefore, migrants who experience greater social vulnerability might not be fully represented in this survey and the social determinants of health to which they were exposed, and their respective health needs could be overlooked. Future research should analyze migration trajectories, examining risks factors and health outcomes over time with longitudinal studies. The HME needs to be comprehensively tested by specific causes of morbidity from the SDH approach. Given the heterogeneity of migrant population and diverse exposures they face during migration process.\u003c/p\u003e \u003cp\u003eThe findings of this study have practical implication towards inclusive public health responses. Since unemployment, affiliation to health system and psychosocial factors could be potentially modified by migrant-sensitive intersectoral actions. These initiatives must be based on equity and human rights perspectives to promote migrant integration. Besides the articulation of joint efforts at community and national level. For instance, foster social protection strategies regardless of immigration status to counteract socioeconomic vulnerability and poor living conditions that might result from unemployment. Furthermore, addressing barriers for healthcare affiliation, effective access and use of health care. Overall, it should be integrated with psychosocial support-based activities. These measures might involve community based-interventions, intercultural competence in health care and evidence-based migration policies. In order to protect health and wellbeing of migrants and prevent a potential health decline. These practical implications may be useful for the current migratory context in Latin America and the need of encourage collaborative alliances and policy making at regional level.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe present study revealed a crude advantage on health status of International migrants residing in Chile. However, when an integrative approach was applied by adjusting for social determinants of health the healthy migrant effect disappeared for almost all outcomes. Being migrant remained protective for chronic morbidities which might reflect the health gap resulted from the advanced epidemiological transition in Chile where non-communicable diseases are main public health problems. These findings bring attention to the importance of studying health disparities between international migrants and locals, while considering the diverse exposures during migration process that could dissolve this health advantage over time. Our findings highlight the need to deepen study the HME by cause-specific morbidity, particularly, chronic conditions and its risks factors and could be useful to health care practitioners and policy makers in a more comprehensive understanding of how variables like unemployment, affiliation to the health system and psychosocial factors may shape migrants\u0026rsquo; health over time. This could be relevant to both policy and practice for health systems in Chile and more broadly in the Latin American region, especially in the purpose of \u0026ldquo;leaving no one behind in health protection\u0026rdquo;.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eHME: Healthy migrant effect\u003c/p\u003e\n\u003cp\u003eSDH: Social Determinants of health\u003c/p\u003e\n\u003cp\u003eNSPH:\u0026nbsp;Negative Self-perceived health\u003c/p\u003e\n\u003cp\u003eCM: Chronic morbidity\u003c/p\u003e\n\u003cp\u003eDIS: Disability\u003c/p\u003e\n\u003cp\u003eAL: Activity limitations\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOR: Odds ratio\u003c/p\u003e\n\u003cp\u003eCI: Confidence interval\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe investigation was conducted in accordance with ethical guidelines and regulations in compliance with the Declaration of Helsinki and local data protection law. \u0026nbsp;This study is part of the Fondecyt Regular project 1201461 which was approved by the Ethics Committee of The Faculty of Medicine of The Universidad del Desarrollo, as well as the Ethics Committee of the Servicio de Salud Metropolitano Sur-Oriente. Specifically, this study performed a secondary analysis of The CASEN survey. The data base of the survey has public and free access provided for academic research by the Ministry of Social Development upon request on the website (\u003ca href=\"http://observatorio.ministeriodesarrollosocial.gob.cl/\"\u003ehttp://observatorio.ministeriodesarrollosocial.gob.cl/\u003c/a\u003e). All analyses were performed with anonymized data following ethical standards in research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset analyzed during the current study is available in the Social Observatory website of the\u0026nbsp;Ministry of Social Development\u0026nbsp;http://observatorio.ministeriodesarrollosocial.gob.cl/encuesta-casen-2017\u003c/p\u003e\n\u003cp\u003eAll data generated during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no competing interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFondecyt Regular 1201461, ANID, Chile.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the design, interpretation of results and drafted the manuscript. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank The Ministry of Social Development of Chile for providing the CASEN dataset. This paper was written as part of the research project: Fondecyt Regular 1201461, ANID, Chile.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAffiliations\u003c/p\u003e\n\u003cp\u003eIR, BC:\u0026nbsp;Instituto de Ciencias e Innovaci\u0026oacute;n en Medicina, Facultad de Medicina,\u003c/p\u003e\n\u003cp\u003eCl\u0026iacute;nica Alemana, Universidad del Desarrollo, Av. las Condes 12461, Las Condes, Regi\u0026oacute;n\u003c/p\u003e\n\u003cp\u003eMetropolitana, Chile.\u003c/p\u003e\n\u003cp\u003eMO: Instituto de Salud P\u0026uacute;blica de Chile, Departamento de Asuntos Cient\u0026iacute;ficos, Subdepartamento de estudios y evaluaci\u0026oacute;n de proyectos. Santiago, Regi\u0026oacute;n Metropolitana, Chile\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSegal U. Globalization, migration, and ethnicity. 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Gerontologist. 2019;59(2):205\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLoi S, Hale JM. Migrant health convergence and the role of material deprivation. Demogr Res. 2019;40:933\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevchenko Y. Aging into disadvantage: Disability crossover among Mexican immigrants in America. Soc Sci Med 2021;285:114290.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou Q. Changing Disability Status of Immigrants in Australia-Three Cases. RDS. 2017;13(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLubbers M, Gijsberts M. Changes in self-rated health right after immigration: A panel study of economic, social, cultural, and emotional explanations of self-rated health among immigrants in the Netherlands. Front Sociol. 2019;4:45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu Y, Denier N, Wang JS-H, Kaushal N. Unhealthy assimilation or persistent health advantage? A longitudinal analysis of immigrant health in the United States. Soc Sci Med. 2017;195:105\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbra\u0026iacute;do-Lanza AF, Mendoza-Grey S, Fl\u0026oacute;rez KR. A Commentary on the Latin American Paradox. JAMA Netw Open. 2020;3(2):e1921165-e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuthra R, Nandi A, Benzeval M. Unravelling the \u0026lsquo;immigrant health paradox\u0026rsquo;: ethnic maintenance, discrimination, and health behaviours of the foreign born and their children in England. J Ethn Migr Stud. 2020;46(5):980\u0026ndash;1001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBilecen B, Vacca R. The isolation paradox: A comparative study of social support and health across migrant generations in the US. Soc Sci Med. 2021;283:114204.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang PQ, Hwang SH. Explaining Immigrant Health Service Utilization: A Theoretical Framework. SAGE Open. 2016;6(2):2158244016648137.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"International migration, healthy migrant effect, social determinants of health, health disparities","lastPublishedDoi":"10.21203/rs.3.rs-1239906/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1239906/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eDuring recent decades intraregional migration has increased in Latin America. Chile became one of the main receiving countries and hosted diverse international migrant groups. Evidence have suggested a healthy migrant effect (HME) on health status but remains scarce, controversial and needs to be updated. This study performed a comprehensive analysis verifying the existence of HME and its association with social determinants of health (SDH).\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe analyzed data from the Chilean National Socioeconomic Characterization Survey (CASEN, version 2017). Crude prevalence of health status indicators such as negative self-perceived health, chronic morbidity, disability and activity limitations were described in both international migrants and local population. The association between these outcomes and demographic, socioeconomic, access to health care, psychosocial and migratory related factors were tested using multivariate logistic regression in each population. The HME was also tested using multivariate logistic regression, sequentially adjusted for each set of SDH to obtain the odds ratio of presenting each health outcome if being an international migrant (ref=Chilean). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: International migrants had lower crude prevalence of all health indicators than Chileans. Age, unemployment and health care system affiliation were associated with health outcomes in both populations. Psychosocial determinants were both risk and protective factors. Crude analysis revealed an apparent HME in all health outcomes. After adjustment for each set of SDH, the immigrant health advantage was only significant for chronic morbidity. Being migrant was associated with 39% lower odds of having chronic diseases compared to locals (OR: 0,61; 95% CI: 0,44-0,84; P = 0,0003). For all other conditions, HME disappeared after adjusting by SDH, particularly unemployment, type of health system and psychosocial factors. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eTesting the HME in Chile reveals an advantage for chronic morbidities that remained significant after adjustment for SDH. This analysis shed light on health disparities between international migrants and local population in the Latin American region, with special relevance of unemployment, type of health system and psychosocial factors. As well as differential exposures faced during migration process that could dissolve the HME over time. Evidence from this integrative approach is useful for informed health planning and intersectoral local and regional solutions.\u003c/p\u003e","manuscriptTitle":"A Comparative Analysis of Health Status of International Migrants and Local Population in Chile: a Population-based, Cross-sectional Analysis From a Social Determinants of Health Perspective","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-02-01 16:20:14","doi":"10.21203/rs.3.rs-1239906/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-04-12T10:04:10+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-04-01T08:11:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1e85c1e4-7460-4bb0-bed0-439e8ae3f135","date":"2022-03-25T00:23:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276d069d-1918-426f-9f4c-a424fd44d13c","date":"2022-03-23T12:29:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-03-23T07:46:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-03-23T07:45:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-01-29T16:41:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-01-29T16:40:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2022-01-07T22:38:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b26b4985-588c-4d2a-8ab7-c96d274f6b1d","owner":[],"postedDate":"February 1st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-06-07T19:29:09+00:00","versionOfRecord":[],"versionCreatedAt":"2022-02-01 16:20:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1239906","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1239906","identity":"rs-1239906","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}