The Persistent Association Between Exposure to Intimate Partner Physical Violence and Current Cigarette Smoking Among Women in Papua New Guinea: A Modified Poisson Regression Analysis

The Persistent Association Between Exposure to Intimate Partner Physical Violence and Current Cigarette Smoking Among Women in Papua New Guinea: A Modified Poisson Regression Analysis | 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 The Persistent Association Between Exposure to Intimate Partner Physical Violence and Current Cigarette Smoking Among Women in Papua New Guinea: A Modified Poisson Regression Analysis Prince Peprah, Bernard Yeboah-Asiamah Asare, Williams Agyemang-Duah, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-779053/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Intimate partner physical violence (IPPV) is a preventable public health threat associated with health deteriorating lifestyles such as cigarette smoking. However, limited research has focused on the association between IPPV and cigarette smoking among women in unions in low-and middle-income countries like Papua New Guinea (PNG). The aim of this study was to examine the association between IPPV and current cigarette smoking using a nationally representative sample. Methods: We utilized 2016-2018 PNG Demographic and Health Survey data of 9,943 women aged 15-49 years who were in intimate unions. We estimated the direct risk of smoking cigarette using modified Poisson regression models with a robust variance relative risk and 95% confidence intervals (CI) of cigarette smoking. Results: Among the total participants, the prevalence of IPPV was 52.4% and smoking cigarette in the last 24 hours was 25.1%. The modified Poisson regression results indicated a robust and persistent association between IPPV and cigarette smoking among women in unions both in the absence and presence of covariates. The risk of smoking cigarette was significantly elevated among those who reported a history of IPPV relative to their counterparts with no physical violence history (IRR: 1.35, 95%CI: 1.20-1.52) in the absence of covariates. After controlling for demographic, social and economic variables, the association between IPPV and cigarette smoking persisted (IRR: 1.24, 95%CI: 1.08-1.41). Conclusions: The present study provides strong evidence to indicate a robust and persistent association between IPPV and current cigarette smoking among women in unions. Interventions aimed at addressing IPPV among women in unions in PNG to reduce the increased risk of cigarette smoking are needed. Health Policy Demographic and health survey intimate partner physical violence cigarette smoking Papua New Guinea Background Globally, gender-based violence is a serious public health issue with immediate and delayed consequences including physical injuries, poor psychological and behavioural outcomes, low birth weight, sexual disorders, pregnancy termination and complications and sexually transmitted diseases [ 1 , 2 , 3 ]. Gender-based violence is highly prevalent in Papua New Guinea (PNG) [ 4 , 5 , 6 , 7 ] and indicated to be among the highest in the world [ 8 , 9 , 10 , 11 ] and at epidemic levels [ 12 , 13 ]. Gender-based violence incidence in PNG is also often akin to that of a war zone or post-war situation (Hinton, 2008). The levels of violence perpetrated against women in PNG are higher compared with rates found in elsewhere in the world [ 4 , 5 , 6 , 7 ] than men in PNG [ 4 ]. Evidence indicates that about 53% of women in PNG experience more incidents of gender-based violence (average 9.4 incidents per year for women, compared with 6.1 for men) [ 4 ]. Violence perpetrated by intimate partners against women mostly includes physical assaults and threats [ 4 ], which are termed as intimate partner physical violence (IPPV). IPPV is indicated to be amongst the most common forms of gender-based violence in PNG [ 7 , 14 ]. It is estimated that between 58%-70% of women in PNG have suffered some form of physical violence from an intimate partner in their lifetime [ 7 , 14 , 15 ]. IPPV has been linked to many adverse economic, physical and mental health consequences [ 16 ]. For instance IPPV can affect health through negative health behaviours such as cigarette smoking [ 17 ], a notable preventable cause of morbidity and mortality among women word wide [ 18 ]. The association between gender-based violence, particularly intimate partner and smoking is theoretically grounded in stress and coping research [ 18 ]. All forms of intimate partner violence including IPPV can be conceptualized as a chronic psychological stressor [ 19 ]. Evidence suggests that cigarette smoking is common among women experiencing violence by partners [ 20 ]. Studies have shown that women exposed to partner violence are more likely to smoke compared to those who are not victim of partner violence [ 20 ]. This might be because of the stress that victims of intimate partner violence experience, and cigarette smoking serves to ease their stress. Additionally, the psychological feeling of hopeless and worthlessness experienced by women being violated could trigger the exposure to self-destructive behaviours such as cigarette smoking [ 21 ]. Other socio-economic and demographic factors that have been linked to risk of IPPV include women’s low education level, low income, unemployment, partner’s controlling behaviours, partner’s health lifestyles such as excessive drinking, limited decision making autonomy, and rural residency [22 _ 26]. Population-based studies demonstrated prevalence of IPPV [ 7 , 14 , 27 ], but they have scarcely considered the influence of IPPV on cigarette smoking among women in PNG. Studies linking IPPV and cigarette smoking among women in union are limited in PNG. This study extends the present literature by examining the association between IPPV and current cigarette smoking among women in PNG. This is an important public health issue for many reasons. While IPPV has been associated with an elevated risk for physical and mental health problems, cigarette smoking increase the risk of adverse health outcomes, status and mortality. The study has two main objectives: 1) describe the prevalence of IPPV and cigarette smoking and 2) examine the association between IPPV and current cigarette smoking among women in union in PNG. In this study, we focused on physical violence because it is the most prevalent form of gender-based violence in PNG [ 4 ]. Moreover, IPPV in this study excludes sexual violence. Though sexual abuse is a part of physical violence, associated factors could differ and as a result demands a separate analysis [ 22 ]. The findings from this study could contribute to the knowledge area and guide policy on reducing cigarette smoking in PNG. Methods Sample and data The study used data from the 2016-18 PNG Demography and Health Survey (PNGDHS) conducted from October 2016 to December 2018. The PNGDHS aimed to generate comprehensive data on demographic, maternal and reproductive issues such as fertility, family planning awareness and practices, breastfeeding practices, health behaviors, immunizations, domestic and intimate partner violence. Through the Demographic and Health Survey (DHS) programme, technical support for the execution of the survey was provided by Inner City Fund (ICF), with the financial support of the PNG Government, Australian Government Department of Foreign Affairs and Trade, the United Nations Population Fund (UNFPA) and UNICEF [28]. The 2016-18 PNG DHS sample was nationally representative and covered the entire population that lived in private dwelling units in the country. The survey used the list of census units (CUs) from the 2011 PNG National Population and Housing Census as the sampling frame and adopted a probability-based sampling approach. Specifically, a two-stage stratified cluster sampling procedure was followed. Details of the methodology and selection procedure have been reported in the PNGDHS final report [28]. In summary, each province in the country was stratified into urban and rural areas, yielding 43 sampling strata, except for the National Capital District, which has no rural areas. The division paid particular attention to urban-rural variations. Samples of census units were selected independently in each stratum in two stages. In the first stage, sorting the sampling frame within each sampling stratum to achieve implicit stratification and proportional allocation was done. In the second stage of sampling, a fixed number of 24 households per cluster was selected with an equal probability systematic selection from the newly created household listing, resulting in a total sample size of approximately 19,200 households. To prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementing stages. In cases where a census unit had fewer than 24 households, all households were included in the sample. A total of 17,505 households were selected for the sample, of which 16,754 were occupied. Of the occupied households, 16,021 were successfully interviewed, yielding a response rate of 96%. In the interviewed households, 18,175 women aged 15-49 years were identified for individual interviews, interviews were completed with 15,198 women, yielding a response rate of 84%. The present study has analyzed data only on women who were in union during the survey. Therefore, the comprised sample was 9,943 women aged 15-49 years who were in union (either married or cohabiting) during the survey. The dataset can be accessed at https://dhsprogram.com/data/ dataset/Papua-New-Guinea_Standard-DHS_2017.cfm?flag=0. Study Variables Outcome variable Current cigarette smoking was the outcome variable in this study and was measured as having smoked cigarette in the last 24 hours prior to the survey. Women in unions current smoking status were classified as “no” (0): no current smoking in the last 24 hours or “yes” (1): smoking in the last 24 hours. Key explanatory variable The key explanatory variable in this study was IPPV. In this study, IPPV was operationalized as any physical acts ensuing into abuse by a current or former partner within 12 months prior to the survey [29].This variable was derived from the optional domestic violence module, where questions are based on a modified version of the conflict tactics scale [30, 31]. Questions asked were concerning physical, sexual or emotional violence experiences. In this study, the focus was on the experience of IPPV. Six (6) standard items including whether respondent’s last partner ever: pushed, shook, or threw something at her, slapped her, punched her with his fist or something harmful, kicked or dragged her, strangled or burnt her, threatened her with a knife, gun or other weapons, and twisted her arm or pulled her hair were used to generate the experience of IPPV. For each of these questions, the responses were ‘never’, ‘often’, ‘sometimes’ and ‘yes, but not in the last 12 months. However, for our analysis purpose, we created a dichotomous variable to represent whether a respondent had experienced physical violence in the past 12 months by coding never, yes, but not in the last 12 months together as ‘No’ (0) and yes, often and sometimes, coded together as ‘Yes’ (1). Covariates Theoretically and empirically relevant demographic and socioeconomic variables were included as confounders. In all, we included twenty (20) socioeconomic and demographic variables to adjust for the modelling. These variables included age, region, religion, place of residence, highest educational level, literacy, marital status, residing with a partner, number of partner’s wives, partner’s age, partner’s education, health insurance cover, internet access, mobile phone ownership, watch television, listen to the radio, read newspaper/magazine, occupation and wealth index. The selection of these variables was informed by their statistically significant associations with physical violence in previous studies [32, 33]. (See Table 2 for the details on the coding of the covariates). Statistical analysis Both descriptive (frequencies, percentages, mean and standard deviation) and inferential (chi-square and modified Poisson regression) analytical frameworks embedded in SPSS software version 20.0 (IBM Armonk, NY) were used. The statistical analysis followed some essential steps. We performed descriptive statistics such as frequencies to describe and contextualize the sample. The Pearson Chi-square test was done to examine the differences in smoking cigarette by socio-demographic characteristics and IPPV. A modified Poisson regression, adjusting for demographic, social and economic variables, was also performed to model the association between IPPV and cigarette smoking, to estimate the relative risk of cigarette smoking directly [34, 35]. The study used the modified Poisson regression that incorporates the robust error variance procedure over logistic regression to optimize the accuracy of the estimates [34], as direct estimates of relative risk produce from modified Poisson regression modelling may be a preferred method for estimating population-level risk [35]. We fitted four regression models. Model 1 included only the dependent and independent variables, thus, was the base model. While adjusting for the theoretically relevant confounding variables, Models 2, 3 and 4 respectively introduced demographic and socioeconomic factors to investigate whether these variables play any role and might temper the effects of IPPV on cigarette smoking. Before the regression analysis, diagnostics checks for multicollinearity were conducted using the variance inflation factor (VIF). In this analysis, none of the VIF scores exceeded the value of 2.38, suggesting no multicollinearity. The results of the regression analyses were presented as crude relative risk (CRR) and adjusted relative risk (ARR) at 95% confidence intervals (CIs). All the estimates provided in this study are derived by applying appropriate sampling weights supplied by PNGDHS, 2016-18. A statistical significance threshold of p ≤ 0.05 was set. Results Background characteristics of the participants The mean age of the respondents was 32.68±0.08 years, with most of them (20.4%) aged between 25-29 years. The majority of the respondents (75.5%) lived in the rural areas, and mostly from the Highlands Region (28.6%). Further, most of the women were Christians (99%), married (83%), currently living together with their partner (86.6%), and had between 1-2 kids (33.8%). more of the respondent had attained primary school level education (49.7%), were unemployed (62.1%) and fell in richest wealth index (26.1%) (see Table 1). Prevalence of cigarette smoking among women exposed to IPPV Table 1 shows the distribution of cigarette smoking across IPPV. The results showed significant disparities in cigarette smoking and IPPV at p<0.001. Specifically, 52.4% of women were exposed to IPPV, while 25.1% of women who were exposed to IPPV smoked a cigarette. Association between exposure to IPPV and cigarette smoking among women in PNG The regression analysis showed a persistent association between IPPV and cigarette smoking. In Model I, the study revealed that women who had experienced IPPV have a significantly higher log count of smoking cigarette than their counterparts (IRR: 1.35, 95%CI: 1.20-1.52). In Model II, when demographic variables were added to the variable in Model I, the study found that participants who had experienced IPPV (IRR: 1.27, 95%CI: 1.11-1.45), those from the Momase region (IRR: 1.84, 95%CI: 1.52-2.23), those from urban area (IRR: 1.49, 95%CI: 1.27-1.75), those with no religion (IRR: 1.93, 95%CI: 1.16-3.20) and those whose partners have three or more wives (IRR: 1.67, 95%CI: 1.17-2.39) have a higher log count of smoking cigarette compared with their counterparts. Also, participants aged 45-49 years (IRR: 0.48, 95%CI: 0.29-0.80) and those who are able to read a whole sentence (IRR: 0.78, 95%CI: 0.61-0.99) significantly have a lower log count of smoking cigarette. One key issue that needs to be commented on at this stage is that, regardless of the introduction of demographic variables, IPPV still predicts cigarette smoking among women in union in PNG. In Model III, when social variables were added to all variables in Model II, the study revealed that participants who had experienced IPPV (IRR: 1.27, 95%CI: 1.11-1.45), those from the Momase region ( IRR: 1.85, 95%CI: 1.53-2.24), those residing in urban area ( IRR:1.41, 95%CI: 1.19-1.68), those with no religion ( IRR: 2.05, 95% CI: 1.26-3.34) and those whose partners have three or more wives (IRR: 1.76, 95%CI: 1.22-2.52) significantly have a higher log count of smoking cigarette compared with their counterparts. Also, participants aged 45-49 years (IRR: 0.50, 95%CI: 0.30-0.83) and those who are able to read and write (IRR: 0.75, 95%CI: 0.58-0.97) significantly have a lower log count of smoking cigarette compared with their counterparts. At this stage of the analysis, it is important to acknowledge that the inclusion of social and demographic variables could not render the association between IPPV and cigarette smoking insignificant. This finding suggests that IPPV is still a significant factor associated with cigarette smoking among women in union in PNG. In the full model (model IV), when economic variables were added to all variables in Model III, the study revealed that participants who had experienced IPPV (IRR: 1.24, 95%CI: 1.08-1.41), those from Momase region (IRR: 1.82, 95%CI: .50-2.21), those residing in urban area (IRR: 1.30, CI:1.08-1.57), those with no religion ( IRR:2, 95%CI:1.24-3.21), those whose partners have three or more wives (IRR:1.71, 95%CI: 1.19-2.44) and those who listen to radio (IRR: 1.20, CI: 1.01-1.43) significantly have a higher log count of smoking cigarette compared with their counterparts. Participants aged 45-49 years (IRR: 0.51, 95%CI: 0.30-0.86), those who are able to read a whole sentence (IRR: 0.74, 95% CI: 0.57-0.96), those who are clerical officers (IRR: 0.46, 95%CI: 0.24-0.92) and those who rated their wealth index as middle (IRR: 0.75, 95% CI: 0.59-0.95) significantly have a lower log count of smoking cigarette compared with their counterparts. The important finding as far as this study is concerned is that, throughout the stages of the model building that is from Model I through to Model IV (final Model), IPPV remains a strong predictor of cigarette smoking among women in union in PNG as the magnitude and direction of association persisted. Discussion The present study examined the association between IPPV and cigarette smoking among women in union in PNG. The study found the prevalence of IPPV and current cigarette smoking to be 52% and 25% respectively. The study further found evidence of statistically significant association between IPPV and cigarette smoking. The study also identified correlates of cigarette smoking among women aged 15-49 years, currently in a union, in PNG. Our findings suggest that prevalence of IPPV among women in union in PNG remains relatively high and comparable to rates reported in other studies conducted in PNG [4, 5, 7, 14]. However, the prevalence of IPPV reported in our study is higher than the rates found in studies from other developing countries such as Uganda [22, 36] and Rwanda [37]. The differences in the rates could be attributed to the variations in the study procedures, methodologies, samples, and study settings. Furthermore, the reported high prevalence of gender-based violence in PNG [4, 5, 14] suggests many more people may be exposed to IPPV at one point in time in their intimate relationships. The prevalence of cigarette smoking found in our study is comparable to that of the study conducted in Italy [38], but higher than a study conducted in Canada [39]. The relatively high prevalence of cigarette smoking among women in PNG confirms the report that smoking is high in PNG and recognized among the top 10 tobacco consuming countries globally [40]. Existing literature in the domain has highlighted consequences of IPV, which comprises a range of stress disorders, including anxiety and depression. Furthermore, it has been indicated that women experiencing IPV show a higher disposition towards detrimental health risks like consumption of alcohol [41, 42], and tobacco and smoking [43]. Thus, IPV is not just a human rights violation but also a potential public health concern among women [7, 44 _ 45]. Crane et al. [20] in a meta-analysis exploring the association between IPV and smoking in low-and-middle-income countries proposed a ‘victimization-smoking relationship’ among the women who have experienced IPV and study findings suggested that nicotine contained in cigarette, acts as a stress buster and lowers the adverse effects and anxiety related to IPV among victimized women [20]. In the absence of adequate social support and efficient law enforcement, women lack pro-social measures to cope with IPV-induced stress, thus, they choose maladaptive coping approaches like smoking [20, 42]. PNG is considered one of the worst places for gender-based violence, with little to no law enforcement [46] to protect the fundamental rights to equality, security, liberty, integrity and dignity of women [47]. Thus, in the absence of a conducive environment where women can grow to their highest social, economic and intellectual potentials, improving women’s status and thus, combating IPV-induced smoking remains a challenge. Also, women who belonged to the middle wealth quintile, were able to read whole sentences and had clerical jobs were less likely to smoke cigarette. All these can be considered positive indicators of women’s status, i.e., being at better economic disposition, being literate, and having a job, can improve the chances of being empowered and thus can reduce chances of being a victim of violence and hence have a lower inclination towards self-harming cigarette smoke. In addition, better status can impart them with the injurious health penalties related to smoking and can provide better ways to cope with IPV induced-stress [20]. The study revealed that women who lived in the Momase region had a higher risk of smoking cigarette in PNG, these findings are in concordance with other studies and report which also reports higher smoking rates in the Momase region [40, 48]. Cigarette smoking was also found to be higher for women who reside in urban areas. This could be attributed to the increased accessibility to cigarette, as PNG is majorly an island country, commutation and resource distribution remains a challenge, thus, women who are residing in urban areas have better access to cigarette than their rural counterparts. Furthermore, cigarette smoking was higher in women who had no religion. Although in the absence of comparable evidence from PNG, it is difficult for us to draw definite inferences. Religion always encourages the society to adopt habits that are beneficial for their health and well-being. Religion also provides strong social support, which might help in relieving the situational stress and anxiety associated with experiencing IPPV. Thus, in the absence of strong social support women who are victims of IPPV may find solace in cigarette smoking. In addition, women whose partners have three or more wives smoke more as they often have a higher likelihood of living in a complicated and stressful familial situation with low societal support [4, 5, 27]. This study is associated with some strengths and limitations that need be highlighted. The major strength of the study is the use of large-scale nationally representative data from PNG. In addition, being labelled as potentially the worst place for gender-based violence globally, these findings highlight the magnitude of the issue at the national level. More importantly, the present study uses a relatively new analytical approach by applying the modified Poisson regression that incorporates the robust error variance procedure to establish the association between IPPV and cigarette smoking. The modified Poisson regression approach can be regarded as very reliable in terms of both relative bias and percentage of confidence interval coverage (Zou, 2004). Also, extensive discussion in much of the literature has reached a consensus that the relative risk is preferred over the odds ratio for most prospective studies with binary outcomes as logistic regression modelling overestimates the odds ratios [34, 49 _ 52]. In that regard, the use of Poisson regression has been a promising alternative. However, despite these strengths, our study does not explore any causal relationship between IPPV and smoking, as PNGDHS data is cross-sectional. Implications for Practice and/or Policy This study offers a number of implications for policy and practice that need to be noted. Firstly, health institutions in collaboration with gender-based groups in PNG could organize regular education and sensitization programmes on IPPV and current cigarette smoking among women in unions. We argue that the health campaigns could focus on the social, economic and health risks of smoking among women in unions who experience IPPV in PNG and other developing countries which share similar demographic and socio-demographic characteristics with our participants. Secondly, since we found in this study that women in unions who have experienced IPPV have a higher log count of smoking cigarette, health institutions and gender-based institutions in PNG should make efforts to identify the causes of IPPV from the perspective of both the perpetuators (men) and victims (women) which in a way would concurrently help to reduce both IPPV and cigarette smoking. This is because, the identification of causes of the IPPV is important to serving as a framework to guide the health campaign to reduce cigarette smoking in PNG. Thirdly, the health campaign could be targeted at women in unions from Momase and highlands regions, those residing in urban area, those with no religion, those whose partners have three or more wives and those who listen to radio as these women groups were having a higher log count of smoking cigarettes. Apart from IPPV, other demographic, social and economic factors predict cigarette smoking among women in unions who experience intimate partner physical violence in PNG. Furthermore, we recommend that the formulation of health policy intended to scale down cigarette smoking among women in unions who experience IPPV in PNG should incorporate demographic, social and economic variables including region of residence, place of residence (rural/urban), religion, number of wives of partners, literacy, listening to radio, age, wealth index and employment type. Moreover, interventions could aim at positive and effective ways of managing stress associated with IPPV among victims, especially women. Conclusion This study presents a significant association between IPPV and cigarette smoking among women in union. The study findings are adequate to establish cigarette smoking among women experiencing IPPV as a potential health concern in PNG. Thus, there is an urgent need to combat the issue by installing policies aim at reducing the incidence of IPPV in PNG and to increase awareness levels concerning the adverse health implications of smoking among women. Furthermore, interventions could include a comprehensive framework that identifies and educates women; and establishing support groups to support women facing IPPV to cope with the associated stress. Research elaborating on the association and causation between IPPV and cigarette smoking employing prospective cohort studies is required. Declarations Ethics approval and consent to participate Ethical approval was not required for this study since the data used for this study are secondary data. Necessary permissions and survey data were obtained from the DHS programs. The DHS data upheld ethical standards in the research process. Consent for publication NA Availability of data and materials The data that support the findings of this study are available from the DHS. However, restrictions apply to the availability of the data, which were used under license for the current study, thus, the data are not publicly available. However, they can be made available from the authors upon reasonable request with the permission of DHS programs. Competing interests Authors declare that they have no competing interests. Funding The current research received no specific grant from any funding agency, commercial or not-for-profit source. No other entity besides the authors had a role in the design, analysis or writing of the current article. Authors' contributions PP performed the conception, the design of the work, the acquisition and the analysis. BY-AA, PP and WA-D performed the design of the work and the creation of tables. DOO, DV and GNA-A performed the design and drafted the work. All authors reviewed and edited the final version of the manuscript. The author(s) read and approved the final manuscript. Acknowledgements The authors gratefully acknowledge the women who participated in the Papua New Guinea 2016- 2018 Demographic and Health Survey. References Garcia-Moreno C, Watts C. 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Kampala, Uganda: UBOS and Calverton, Maryland: ICF International Inc, 2012. Ntaganira J, et al. Intimate partner violence among pregnant women in Rwanda. BMC women’s health. 2008,8(1):17. https://doi.org/10.1186/1472-6874-8-17 Lauria L, et al. Smoking behaviour before, during, and after pregnancy: The effect of breastfeeding. Sci World J. 2012,1–9. https://doi.org/10.1100/2012/154910 Bahadori B, et al. Hypothesis: Smoking decreases breast feeding duration by suppressing prolactin secretion. Med Hypotheses 2013,81(4):582–586. https://doi.org/10.1016/j.mehy.2013.07.007 Hou WL, et al. Recovery experiences of Taiwanese women after terminating abusive relationships: A phenomenology study. J Interpersonal Violence 2013,28(1):157-175. Leonard KE, Quigley BM. Thirty years of research show alcohol to be a cause of intimate partner violence: Future research needs to identify who to treat and how to treat them. Drug Alc Rev 2017,36(1):7-9. Klostermann KC, Fals-Stewart W. 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Tables Table 1: Demographics (n=9,943) Characteristics Total n (%) Smoking Pearson chi-square Yes n (%) No, n (%) P -value Age (mean) 15-49 (32.68±0.08) Age groups (years) <0.001 15-19 358(3.6) 71(19.8) 287(80.2) 20-24 1493(15.1) 357(23.9) 1136(76.1) 25-29 2008(20.4) 522(26.0) 1486(74.0) 30-34 1900(19.3) 457(24.0) 1443(76.0) 35-39 1755(17.8) 353(20.1) 1402(79.9) 40-44 1324(13.4) 271(20.5) 1053(79.5) 45-49 1030(10.4) 117(17.2) 853(82.8) Region <0.001 Southern 2810(28.5) 509(18.1) 2301(81.9) Highlands 2817(28.6) 647(23.0) 2170(77.0) Momase 2014(20.4) 579(28.8) 1435(71.3) Islands 2227(22.6) 473(21.2) 1754(78.8) Place of residence <0.001 Rural 7453(75.5) 1485(19.9) 5968(80.1) Urban 2415(24.5) 723(29.9) 1692(70.1) Highest education level 0.009 No education 2266(23.0) 530(23.4) 1736(76.6) Primary 4899(49.7) 1028(21.0) 3871(79.0) Secondary 2303(23.3) 559(24.3) 1744(75.7) Higher 400(4.0) 91(22.8) 309(77.2) Religion 0.003 Christian 9756(99.0) 2170(22.2) 7586(77.8) Non-Christian 53(0.6) 17(32.1) 36(67.9) No religion 47(0.4) 19(40.4) 28(59.6) Wealth index <0.001 Poorest 1485(15.0) 340(22.9) 1145(77.1) Poorer 1576(16.0) 340(21.6) 1236(78.4) Middle 1835(18.6) 334(18.2) 1501(81.8) Richer 2393(24.3) 518(21.7) 1875(78.4) Richest 2579(26.1) 676(26.2) 1903(73.8) Marital status 0.080 Married 8193(83.0) 1806(22.0) 6387(78.0) Co-habitation 1675(17.0) 402(24.0) 1273(76.0) Currently residing with partner 0.031 Living together 8503(86.6) 1867(22.0) 6636(78.0) Staying elsewhere 1316(13.4) 324(24.6) 992(75.4) Number of kids <0.001 None 945(9.6) 272(28.8) 673(71.2) 1-2 3335(33.8) 792(23.8) 2543(76.2) 3-4 3140(31.8) 688(21.9) 2452(78.1) 5-6 1734(17.6) 315(18.2) 1419(81.8) 7 and more 714(7.2) 141(19.8) 573(80.2) Occupational status <0.001 Not working 6044(62.1) 1348(22.3) 4696(77.7) Professional/technical/managerial 570(5.9) 112(19.7) 458(80.3) Clerical 210(2.2) 55(26.2) 155(73.8) Sales 486(5.0) 123(25.3) 363(74.7) Agricultural 1508(15.5) 261(17.3) 1247(82.7) Services 841(8.6) 254(30.2) 587(69.8) Manual job 77(0.8) 23(29.9) 54(70.1) Physical violence <0.001 No 1723(47.6) 322(18.7) 1401(81.3) Yes 1898(52.4) 477(25.1) 1421(74.9) Table 2: A modified Poisson regression of the relationship between IPPV with current smoking status Predictors Crude IRR (95% C.I.) Adjusted IRR (95% C.I.) Model I Model II Model III Model IV Experience physical violence ¥ No (Ref.) 1.00 1.00 1.00 1.00 Yes 1.35***(1.20-1.52) 1.29***(1.23-1.47) 1.27** (1.11-1.45) 1.24**(1.08-1.41) Age groups (years) 15-19 (Ref.) 1.00 1.00 1.00 20-24 0.85(0.58-1.25) 0.85(0.57-1.25) 0.86(0.58-1.27) 25-29 0.90(0.60-1.35) 0.91(0.60-1.37) 0.91(0.61-1.38) 30-34 0.85(0.56-1.29) 0.85(0.56-1.30) 0.87(0.57-1.32) 35-39 0.71(0.46-1.10) 0.72(0.46-1.11) 0.72(0.46-1.11) 40-44 0.60*(0.38-0.95) 0.59*(0.37-0.95) 0.60*(0.38-0.97) 45-49 0.48**(0.29-0.80) 0.50**(0.30-0.83) 0.51*(0.30-0.86) Region Southlands (Ref.) 1.00 1.00 1.00 Highlands 1.47***(1.20-1.79) 1.48***(1.21-1.81) 1.47***(1.20-1.80) Momase 1.84***(1.52-2.23) 1.85***(1.53-2.24) 1.82***(1.50-2.21) Islands 1.38**(1.12-1.69) 1.38**(1.12-1.70) 1.38**(1.12-1.70) Place of residence Rural (Ref.) 1.00 1.00 1.00 Urban 1.49***(1.27-1.75) 1.41***(1.19-1.68) 1.30**(1.08-1.57) Religion Christian (Ref.) 1.00 1.00 1.00 Non-Christian 0.68(0.19-2.39) 0.73(0.21-2.60) 0.69(0.19-2.45) No religion 1.93*(1.16-3.20) 2.05**(1.26-3.34) 2.00**(1.24-3.21) Highest education level No education (Ref.) 1.00 1.00 1.00 Primary 0.94(0.76-1.17) 0.93(0.75-1.17) 0.93(0.74-1.16) Secondary 1.10(0.81-1.48) 1.02(0.74-1.39) 1.02(0.75-1.40) Higher 1.05(0.67-1.64) 0.89(0.55-1.44) 1.01(0.61-1.66) Literacy level Cannot read at all (Ref.) 1.00 1.00 1.00 Able to read only parts of sentence 0.92(0.73-1.16) 0.90(0.71-1.14) 0.88(0.69-1.12) Able to read whole sentence 0.78*(0.61-0.99) 0.75*(0.58-0.97) 0.74*(0.57-0.96) No card with required language 0.62(0.24-1.64) 0.62(0.23-1.68) 0.64(0.24-1.71) Blind/visually impaired 1.93(0.30-12.50) 1.78(0.29-11.09) 1.70(0.25-11.56) Marital status Married (Ref.) 1.00 1.00 1.00 Co-habiting 0.99(0.84-1.17) 0.98(0.83-1.14) 1.03(0.87-1.22) Currently residing with partner Living together (Ref.) 1.00 1.00 1.00 Staying elsewhere 0.87(0.71-1.07) 0.87(0.71-1.07) 0.85(0.69-1.05) Number of partner’s wives No other wife (Ref.) 1.00 1.00 1.00 1 1.14(0.94-1.37) 1.14(0.95-1.37) 1.13(0.93-1.36) 2 0.95(0.64-1.41) 0.95(0.64-1.42) 1.01(0.68-1.50) 3 or more 1.67**(1.17-2.39) 1.76**(1.22-2.52) 1.71**(1.19-2.44) Don’t know 1.08(0.65-1.78) 1.07(0.65-1.75) 1.04(0.64-1.70) Partner’s age (in years) 15-24 (Ref.) 1.00 1.00 1.00 25-34 0.97(0.72-1.31) 0.99(0.73-1.04) 0.98(0.72-1.33) 35-44 1.12(0.80-1.56) 1.15(0.82-1.14) 1.16(0.83-1.62) 45+ 1.20(0.83-1.73) 1.21(0.84-1.19) 1.19(0.82-1.73) 55+ Partner’s educational level No education (Ref.) 1.00 1.00 1.00 Primary 0.85(0.71-1.03) 0.86(0.71-1.04) 0.91(0.75-1.11) Secondary 0.94(0.76-1.17) 0.91(0.73-1.14) 0.95(0.75-1.20) Higher 0.91(0.67-1.25) 0.86(0.63-1.19) 0.93(0.68-1.29) Don’t know Insurance cover No (Ref.) 1.00 1.00 Yes 0.90(0.63-1.30) 0.91(0.64-1.31) Internet access No (Ref.) 1.00 1.00 Yes 1.23(0.97-1.56) 1.27(1.00-1.63) Ownership of mobile phone No (Ref.) 1.00 1.00 Yes 0.99(0.85-1.17) 0.99(0.84-1.17) Watch television No (Ref.) 1.00 1.00 Yes 1.01(0.84-1.22) 1.04(0.85-1.26) Listen to radio No (Ref.) 1.00 1.00 Yes 1.18(1.00-1.41) 1.20*(1.01-1.43) Read newspapers/magazines No (Ref.) 1.00 1.00 Yes 1.05(0.86-1.29) 1.04(0.85-1.27) Occupation Not working (Ref.) 1.00 Professional/technical/managerial 0.67*(0.46-0.97) Clerical 0.46*(0.24-0.92) Sales 1.26(0.98-1.64) Agricultural 0.75**(0.61-0.93) Services 1.08(0.87-1.34) Manual job 0.48(0.17-1.33) Wealth index Poorest (Ref.) 1.00 Poorer 1.06(0.85-1.31) Middle 0.75*(0.59-0.95) Richer 0.99(0.78-1.26) Richest 0.94(0.70-1.25) Financial inclusion No (Ref.) 1.00 Yes 1.15(0.94-1.40) IRR=Incidence Risk Ratio , *p<0.05, **p<0.01, ***p<0.0001 Multicollinearity test Mean VIF =1.60 range 1.01-2.81 1/VIF range 0.355614-0.991019 Additional Declarations No competing interests reported. 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Gender-based violence is highly prevalent in Papua New Guinea (PNG) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and indicated to be among the highest in the world [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and at epidemic levels [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Gender-based violence incidence in PNG is also often akin to that of a war zone or post-war situation (Hinton, 2008). The levels of violence perpetrated against women in PNG are higher compared with rates found in elsewhere in the world [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] than men in PNG [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Evidence indicates that about 53% of women in PNG experience more incidents of gender-based violence (average 9.4 incidents per year for women, compared with 6.1 for men) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Violence perpetrated by intimate partners against women mostly includes physical assaults and threats [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], which are termed as intimate partner physical violence (IPPV). IPPV is indicated to be amongst the most common forms of gender-based violence in PNG [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. It is estimated that between 58%-70% of women in PNG have suffered some form of physical violence from an intimate partner in their lifetime [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIPPV has been linked to many adverse economic, physical and mental health consequences [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. For instance IPPV can affect health through negative health behaviours such as cigarette smoking [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], a notable preventable cause of morbidity and mortality among women word wide [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The association between gender-based violence, particularly intimate partner and smoking is theoretically grounded in stress and coping research [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. All forms of intimate partner violence including IPPV can be conceptualized as a chronic psychological stressor [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Evidence suggests that cigarette smoking is common among women experiencing violence by partners [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Studies have shown that women exposed to partner violence are more likely to smoke compared to those who are not victim of partner violence [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. This might be because of the stress that victims of intimate partner violence experience, and cigarette smoking serves to ease their stress. Additionally, the psychological feeling of hopeless and worthlessness experienced by women being violated could trigger the exposure to self-destructive behaviours such as cigarette smoking [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Other socio-economic and demographic factors that have been linked to risk of IPPV include women\u0026rsquo;s low education level, low income, unemployment, partner\u0026rsquo;s controlling behaviours, partner\u0026rsquo;s health lifestyles such as excessive drinking, limited decision making autonomy, and rural residency [22\u003csup\u003e_\u003c/sup\u003e26].\u003c/p\u003e \u003cp\u003ePopulation-based studies demonstrated prevalence of IPPV [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], but they have scarcely considered the influence of IPPV on cigarette smoking among women in PNG. Studies linking IPPV and cigarette smoking among women in union are limited in PNG. This study extends the present literature by examining the association between IPPV and current cigarette smoking among women in PNG. This is an important public health issue for many reasons. While IPPV has been associated with an elevated risk for physical and mental health problems, cigarette smoking increase the risk of adverse health outcomes, status and mortality. The study has two main objectives: 1) describe the prevalence of IPPV and cigarette smoking and 2) examine the association between IPPV and current cigarette smoking among women in union in PNG. In this study, we focused on physical violence because it is the most prevalent form of gender-based violence in PNG [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, IPPV in this study excludes sexual violence. Though sexual abuse is a part of physical violence, associated factors could differ and as a result demands a separate analysis [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The findings from this study could contribute to the knowledge area and guide policy on reducing cigarette smoking in PNG.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eSample and data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study used data from the 2016-18 PNG Demography and Health Survey (PNGDHS) conducted from October 2016 to December 2018. The PNGDHS aimed to generate comprehensive data on demographic, maternal and reproductive issues such as fertility, family planning awareness and practices, breastfeeding practices, health behaviors, immunizations, domestic and intimate partner violence. Through the Demographic and Health Survey (DHS) programme, technical support for the execution of the survey was provided by Inner City Fund (ICF), with the financial support of the PNG Government, Australian Government Department of Foreign Affairs and Trade, the United Nations Population Fund (UNFPA) and UNICEF [28]. The 2016-18 PNG DHS sample was nationally representative and covered the entire population that lived in private dwelling units in the country. The survey used the list of census units (CUs) from the 2011 PNG National Population and Housing Census as the sampling frame and adopted a probability-based sampling approach. Specifically, a two-stage stratified cluster sampling procedure was followed. Details of the methodology and selection procedure have been reported in the PNGDHS final report [28]. In summary, each province in the country was stratified into urban and rural areas, yielding 43 sampling strata, except for the National Capital District, which has no rural areas. The division paid particular attention to urban-rural variations. Samples of census units were selected independently in each stratum in two stages. In the first stage, sorting the sampling frame within each sampling stratum to achieve implicit stratification and proportional allocation was done. In the second stage of sampling, a fixed number of 24 households per cluster was selected with an equal probability systematic selection from the newly created household listing, resulting in a total sample size of approximately 19,200 households. To prevent bias, no replacements and no changes of the pre-selected households were allowed in the implementing stages. In cases where a census unit had fewer than 24 households, all households were included in the sample. A total of 17,505 households were selected for the sample, of which 16,754 were occupied. Of the occupied households, 16,021 were successfully interviewed, yielding a response rate of 96%. In the interviewed households, 18,175 women aged 15-49 years were identified for individual interviews, interviews were completed with 15,198 women, yielding a response rate of 84%. The present study has analyzed data only on women who were in union during the survey. Therefore, the comprised sample was 9,943 women aged 15-49 years who were in union (either married or cohabiting) during the survey. The dataset can be accessed at https://dhsprogram.com/data/ dataset/Papua-New-Guinea_Standard-DHS_2017.cfm?flag=0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Variables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eOutcome variable\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCurrent cigarette smoking was the outcome variable in this study and was measured as having smoked cigarette in the last 24 hours prior to the survey. \u0026nbsp; \u0026nbsp;Women in unions current smoking status were classified as \u0026ldquo;no\u0026rdquo; (0): no current smoking in the last 24 hours or \u0026ldquo;yes\u0026rdquo; (1): smoking in the last 24 hours.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKey explanatory variable\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe key explanatory variable in this study was IPPV. In this study, IPPV was operationalized as any physical acts ensuing into abuse by a current or former partner within 12 months prior to the survey [29].This variable was derived from the optional domestic violence module, where questions are based on a modified version of the conflict tactics scale [30, 31]. Questions asked were concerning physical, sexual or emotional violence experiences. In this study, the focus was on the experience of IPPV. Six (6) standard items including whether respondent\u0026rsquo;s last partner ever: pushed, shook, or threw something at her, slapped her, punched her with his fist or something harmful, kicked or dragged her, strangled or burnt her, threatened her with a knife, gun or other weapons, and twisted her arm or pulled her hair were used to generate the experience of IPPV. For each of these questions, the responses were \u0026lsquo;never\u0026rsquo;, \u0026lsquo;often\u0026rsquo;, \u0026lsquo;sometimes\u0026rsquo; and \u0026lsquo;yes, but not in the last 12 months. However, for our analysis purpose, we created a dichotomous variable to represent whether a respondent had experienced physical violence in the past 12 months by coding never, yes, but not in the last 12 months together as \u0026lsquo;No\u0026rsquo; (0) and yes, often and sometimes, coded together as \u0026lsquo;Yes\u0026rsquo; (1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCovariates\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTheoretically and empirically relevant demographic and socioeconomic variables were included as confounders. In all, we included twenty (20) socioeconomic and demographic variables to adjust for the modelling. These variables included age, region, religion, place of residence, highest educational level, literacy, marital status, residing with a partner, number of partner\u0026rsquo;s wives, partner\u0026rsquo;s age, partner\u0026rsquo;s education, health insurance cover, internet access, mobile phone ownership, watch television, listen to the radio, read newspaper/magazine, occupation and wealth index. The selection of these variables was informed by their statistically significant associations with physical violence in previous studies [32, 33]. (See Table 2 for the details on the coding of the covariates).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth descriptive (frequencies, percentages, mean and standard deviation) and inferential (chi-square and modified Poisson regression) analytical frameworks embedded in SPSS software version 20.0 (IBM Armonk, NY) were used. The statistical analysis followed some essential steps. We performed descriptive statistics such as frequencies to describe and contextualize the sample. The Pearson Chi-square test was done to examine the differences in smoking cigarette by socio-demographic characteristics and IPPV. A modified Poisson regression, adjusting for demographic, social and economic variables, was also performed to model the association between IPPV and cigarette smoking, to estimate the relative risk of cigarette smoking directly [34, 35]. The study used the modified Poisson regression that incorporates the robust error variance procedure over logistic regression to optimize the accuracy of the estimates [34], as direct estimates of relative risk produce from modified Poisson regression modelling may be a preferred method for estimating population-level risk [35]. We fitted four regression models. Model 1 included only the dependent and independent variables, thus, was the base model. While adjusting for the theoretically relevant confounding variables, Models 2, 3 and 4 respectively introduced demographic and socioeconomic factors to investigate whether these variables play any role and might temper the effects of IPPV on cigarette smoking. Before the regression analysis, diagnostics checks for multicollinearity were conducted using the variance inflation factor (VIF). In this analysis, none of the VIF scores exceeded the value of 2.38, suggesting no multicollinearity. The results of the regression analyses were presented as crude relative risk (CRR) and adjusted relative risk (ARR) at 95% confidence intervals (CIs). All the estimates provided in this study are derived by applying appropriate sampling weights supplied by PNGDHS, 2016-18. A statistical significance threshold of p \u0026le; 0.05 was set.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBackground characteristics of the participants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean age of the respondents was 32.68\u0026plusmn;0.08 years, with most of them (20.4%) aged between 25-29 years. The majority of the respondents (75.5%) lived in the rural areas, and mostly from the Highlands Region (28.6%). Further, most of the women \u0026nbsp;were Christians (99%), married (83%), currently living together with their partner (86.6%), and had between 1-2 kids (33.8%). more of the respondent had attained primary school level education (49.7%), were unemployed (62.1%) and fell in richest wealth index (26.1%) (see Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of cigarette smoking among women exposed to IPPV\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 shows the distribution of cigarette smoking across IPPV. The results showed significant disparities in cigarette smoking and IPPV at p\u0026lt;0.001. Specifically, 52.4% of women were exposed to IPPV, while 25.1% of women who were exposed to IPPV smoked a cigarette.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation between exposure to IPPV and cigarette smoking among women in PNG\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe regression analysis showed a persistent association between IPPV and cigarette smoking. In Model I, the study revealed that women who had experienced IPPV have a significantly higher log count of smoking cigarette than their counterparts (IRR: 1.35, 95%CI: 1.20-1.52). In Model II, when demographic variables were added to the variable in Model I, the study found that participants who had experienced IPPV (IRR: 1.27, 95%CI: 1.11-1.45), those from the Momase region (IRR: 1.84, 95%CI: 1.52-2.23), those from urban area (IRR: 1.49, 95%CI: 1.27-1.75), those with no religion (IRR: 1.93, 95%CI: 1.16-3.20) and those whose partners have three or more wives (IRR: 1.67, 95%CI: 1.17-2.39) have a higher log count of smoking cigarette compared with their counterparts. Also, participants aged 45-49 years (IRR: 0.48, 95%CI: 0.29-0.80) and those who are able to read a whole sentence (IRR: 0.78, 95%CI: 0.61-0.99) significantly have a lower log count of smoking cigarette. One key issue that needs to be commented on at this stage is that, regardless of the introduction of demographic variables, IPPV still predicts cigarette smoking among women in union in PNG. In Model III, when social variables were added to all variables in Model II, the study revealed that participants who had experienced IPPV (IRR: 1.27, 95%CI: 1.11-1.45), \u0026nbsp;those from the Momase region ( IRR: 1.85, 95%CI: 1.53-2.24), those residing in urban area ( IRR:1.41, 95%CI: 1.19-1.68), those with no religion ( IRR: 2.05, 95% CI: 1.26-3.34) and those whose partners have three or more wives (IRR: 1.76, 95%CI: 1.22-2.52) significantly have a higher log count of smoking cigarette compared with their counterparts. Also, participants aged 45-49 years (IRR: 0.50, 95%CI: 0.30-0.83) and those who are able to read and write (IRR: 0.75, 95%CI: 0.58-0.97) significantly have a lower log count of smoking cigarette compared with their counterparts. At this stage of the analysis, it is important to acknowledge that the inclusion of social and demographic variables could not render the association between IPPV and cigarette smoking insignificant. This finding suggests that IPPV is still a significant factor associated with cigarette smoking among women in union in PNG. In the full model (model IV), when economic variables were added to all variables in Model III, the study revealed that participants who had experienced IPPV (IRR: 1.24, 95%CI: 1.08-1.41), those from Momase region (IRR: 1.82, 95%CI: .50-2.21), those residing in urban area (IRR: 1.30, CI:1.08-1.57), those with no religion ( IRR:2, 95%CI:1.24-3.21), those whose partners have three or more wives (IRR:1.71, 95%CI: 1.19-2.44) and those who listen to radio (IRR: 1.20, CI: 1.01-1.43) significantly have a higher log count of smoking cigarette compared with their counterparts. Participants aged 45-49 years (IRR: 0.51, 95%CI: 0.30-0.86), those who are able to read a whole sentence (IRR: 0.74, 95% CI: 0.57-0.96), those who are clerical officers (IRR: 0.46, 95%CI: 0.24-0.92) and those who rated their wealth index as middle (IRR: 0.75, 95% CI: 0.59-0.95) significantly have a lower log count of smoking cigarette compared with their counterparts. The important finding as far as this study is concerned is that, throughout the stages of the model building that is from Model I through to Model IV (final Model), IPPV remains a strong predictor of cigarette smoking among women in union in PNG as the magnitude and direction of association persisted. \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study examined the association between IPPV and cigarette smoking among women in union in PNG. The study found the prevalence of IPPV and current cigarette smoking to be 52% and 25% respectively. The study further found evidence of statistically significant association between IPPV and cigarette smoking. The study also identified correlates of cigarette smoking among women aged 15-49 years, currently in a union, in PNG.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings suggest that prevalence of IPPV among women in union in PNG remains relatively high and comparable to rates reported in other studies conducted in PNG [4, 5, 7, 14]. However, the prevalence of IPPV reported in our study is higher than the rates found in studies from other developing countries such as Uganda [22, 36] and Rwanda [37]. The differences in the rates could be attributed to the variations in the study procedures, methodologies, samples, and study settings. Furthermore, the reported high prevalence of gender-based violence in PNG [4, 5, 14] suggests many more people may be exposed to IPPV at one point in time in their intimate relationships. The prevalence of cigarette smoking found in our study is comparable to that of the study conducted in Italy [38], but higher than a study conducted in Canada [39]. The relatively high prevalence of cigarette smoking among women in PNG confirms the report that smoking\u0026nbsp;is high in PNG and recognized among the top 10 tobacco consuming countries globally [40].\u003c/p\u003e\n\u003cp\u003eExisting literature in the domain has highlighted consequences of IPV, which comprises a range of stress disorders, including anxiety and depression. Furthermore, it has been indicated that women experiencing IPV show a higher disposition towards detrimental health risks like consumption of alcohol [41, 42], and tobacco and smoking [43]. Thus, IPV is not just a human rights violation but also a potential public health concern among women [7, 44\u003csup\u003e_\u003c/sup\u003e45]. Crane et al. [20] in a meta-analysis exploring the association between IPV and smoking in low-and-middle-income countries \u0026nbsp;proposed a \u0026lsquo;victimization-smoking relationship\u0026rsquo; \u0026nbsp;among the women who have experienced IPV and study findings suggested that nicotine contained in cigarette, acts as a stress buster and lowers the adverse effects and anxiety related to IPV among victimized women [20]. In the absence of adequate social support and efficient law enforcement, women lack pro-social measures to cope with IPV-induced stress, thus, they choose maladaptive coping approaches like smoking [20, 42]. PNG is considered one of the worst places for gender-based violence, with little to no law enforcement [46] to protect the fundamental rights to equality, security, liberty, integrity and dignity of women [47]. Thus, in the absence of a conducive environment where women can grow to their highest social, economic and intellectual potentials, improving women\u0026rsquo;s status and thus, combating IPV-induced smoking remains a challenge.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlso, women who belonged to the middle wealth quintile, were able to read whole sentences and had clerical jobs were less likely to smoke cigarette. All these can be considered positive indicators of women\u0026rsquo;s status, i.e., being at better economic disposition, being literate, and having a job, can improve the chances of being empowered and thus can reduce chances of being a victim of violence and hence have a lower inclination towards self-harming cigarette smoke. In addition, better status can impart them with the injurious health penalties related to smoking and can provide better ways to cope with IPV induced-stress [20].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study revealed that women who lived in the Momase region had a higher risk of smoking cigarette in PNG, these findings are in concordance with other studies and report which also reports higher smoking rates in the Momase region [40, 48]. Cigarette smoking was also found to be higher for women who reside in urban areas. This could be attributed to the increased accessibility to cigarette, as PNG is majorly an island country, commutation and resource distribution remains a challenge, thus, women who are residing in urban areas have better access to cigarette than their rural counterparts. Furthermore, cigarette smoking was higher in women who had no religion. Although in the absence of comparable evidence from PNG, it is difficult for us to draw definite inferences. Religion always encourages the society to adopt habits that are beneficial for their health and well-being. Religion also provides strong social support, which might help in relieving the situational stress and anxiety associated with experiencing IPPV. Thus, in the absence of strong social support women who are victims of IPPV may find solace in cigarette smoking. In addition, women whose partners have three or more wives smoke more as they often have a higher likelihood of living in a complicated and stressful familial situation with low societal support [4, 5, 27]. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is associated with some strengths and limitations that need be highlighted.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe major strength of the study is the use of large-scale nationally representative data from PNG. In addition, being labelled as potentially the\u0026nbsp;worst\u0026nbsp;place for gender-based violence globally, these findings highlight the magnitude of the issue at the national level. More importantly, the present study uses a relatively new analytical approach by applying the modified Poisson regression\u0026nbsp;that incorporates the robust error variance procedure to establish the association between IPPV and cigarette smoking.\u0026nbsp;The modified Poisson regression approach can be regarded as very reliable in terms of both relative bias and percentage of confidence interval coverage (Zou, 2004). Also, extensive discussion in much of the literature has reached a consensus that the relative risk is preferred over the odds ratio for most prospective studies with binary outcomes as\u0026nbsp;logistic regression modelling overestimates the odds ratios [34, 49\u003csup\u003e_\u003c/sup\u003e52]. In that regard, the use of Poisson regression has been a promising alternative. However, despite these strengths, our study does not explore any causal relationship between IPPV and smoking, as PNGDHS data is cross-sectional.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for Practice and/or Policy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study offers a number of implications for policy and practice that need to be noted. Firstly, health institutions in collaboration with gender-based groups in PNG could organize regular education and sensitization programmes on IPPV and current cigarette smoking among women in unions. We argue that the health campaigns could focus on the social, economic and health risks of smoking among women in unions who experience IPPV in PNG and other developing countries which share similar demographic and socio-demographic characteristics with our participants. Secondly, since we found in this study that women in unions who have experienced IPPV have a higher log count of smoking cigarette, health institutions and gender-based institutions in PNG should make efforts to identify the causes of IPPV from the perspective of both the perpetuators (men) and victims (women) which in a way would concurrently help to reduce both IPPV and cigarette smoking. This is because, the identification of causes of the IPPV is important to serving as a framework to guide the health campaign to reduce cigarette smoking in PNG. Thirdly, the health campaign could be targeted at women in unions from Momase and highlands regions, those residing in urban area, those with no religion, those whose partners have three or more wives and those who listen to radio as these women groups were having a higher log count of smoking cigarettes. Apart from IPPV, other demographic, social and economic factors predict cigarette smoking among women in unions who experience intimate partner physical violence in PNG. Furthermore, \u0026nbsp;we recommend that the formulation of health policy intended to scale down cigarette smoking among women in unions who experience IPPV in PNG should incorporate demographic, social and economic variables including region of residence, place of residence (rural/urban), religion, number of wives of partners, literacy, listening to radio, age, wealth index and employment type. Moreover, interventions could aim at positive and effective ways of managing stress associated with IPPV among victims, especially women.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents a significant association between IPPV and cigarette smoking among women in union. The study findings are adequate to establish cigarette smoking among women experiencing IPPV as a potential health concern in PNG. Thus, there is an urgent need to combat the issue by installing policies aim at reducing the incidence of IPPV in PNG and to increase awareness levels concerning the adverse health implications of smoking among women. Furthermore, interventions could include a comprehensive framework that identifies and educates women; and establishing support groups to support women facing IPPV to cope with the associated stress. Research elaborating on the association and causation between IPPV and cigarette smoking employing prospective cohort studies is required.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was not required for this study since the data used for this study are secondary data. Necessary permissions and survey data were obtained from the DHS programs. The DHS data upheld ethical standards in the research process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the DHS. However, restrictions apply to the availability of the data, which were used under license for the current study, thus, the data are not publicly available. However, they can be made available from the authors upon reasonable request with the permission of DHS programs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current research received no specific grant from any funding agency, commercial or not-for-profit source. No other entity besides the authors had a role in the design, analysis or writing of the current article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePP performed the conception, the design of the work, the acquisition and the analysis. BY-AA, PP and WA-D performed the design of the work and the creation of tables. DOO, DV and GNA-A performed the design and drafted the work. All authors reviewed and edited the final version of the manuscript. The author(s) read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the women who participated in the Papua New Guinea 2016- 2018 Demographic and Health Survey.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGarcia-Moreno C, Watts C. Violence against women: An urgent public health priority. Bull World Health Organ. 2011,89(1):2\u0026ndash;2. https://doi.org/10.2471/BLT.10.085217\u003c/li\u003e\n\u003cli\u003eKoenig MA, et al. Individual and contextual determinants of domestic violence in North India. Am J. Public Health. 2006,96(1):132\u0026ndash;138. https://doi.org/10.2105/AJPH.2004.050872\u003c/li\u003e\n\u003cli\u003eSilverman JG. Intimate partner violence and HIV infection among married Indian women. JAMA, 2008,300(6), 703. https://doi.org/10.1001/jama.300.6.703\u003c/li\u003e\n\u003cli\u003eDarko E, et al. Gender violence in Papua New Guinea: The cost to business. 2015.\u003c/li\u003e\n\u003cli\u003eLakhani S, Willman AM. Trends in crime and violence in Papua New Guinea. 2014.\u003c/li\u003e\n\u003cli\u003eNeuendorf NFM. \u003cem\u003eLuksave Em Bikpela Samting! Witnessing Violence In Papua New Guinea\u003c/em\u003e (Doctoral dissertation, James Cook University). 2019.\u003c/li\u003e\n\u003cli\u003eLewis I, et al. Violence against women in Papua New Guinea. J. Fam. Stud. 2008, 14(2\u0026ndash;3), 183\u0026ndash;197. https://doi.org/10.5172/jfs.327.14.2-3.183\u003c/li\u003e\n\u003cli\u003eUNDSS National Crime Summary Report, 1 Jan 2004‐31 Dec 2004, Port Moresby: UNDSS 2005.\u003c/li\u003e\n\u003cli\u003eHaley N, May R. (eds) Introduction: Roots of conflict in the Southern Highlands in Haley and May (eds) Conflict and Resource development in the Southern Highlands of Papua New Guinea in Conflict and Resource Development in the Southern Highlands of Papua New Guinea, State society and Governance in Melanesia Program, Studies in State and Society in the Pacific, No. 3, Canberra: ANU. 2007.\u003c/li\u003e\n\u003cli\u003eHaley N, Muggah R. Jumping the Gun: Armed Violence in Papua New Guinea, in Small Arms Survey 2006: Unfinished Business, Geneva: Small Arms Survey. 2006.\u003c/li\u003e\n\u003cli\u003eGoldman L. \u0026ldquo;Ho‐ha in Huli\u0026rsquo;: Considerations on commotion and community in the Southern Highlands, in Haley, N and R. May (eds) Conflict and Resource development in the Southern Highlands of Papua New Guinea in Conflict and Resource Development in the Southern Highlands of Papua New Guinea, State society and Governance in Melanesia Program, Studies in State and Society in the Pacific, No. 3, Canberra: ANU, 2007.\u003c/li\u003e\n\u003cli\u003eEves R. Masculinity Matters: men, gender‐based violence and the AIDS epidemic in Papua New Guinea, in Vicki Luker and Sinclair Dinnen (ed.), Civic Insecurity: Law, Order and HIV in Papua New Guinea, ANU ePress, Australia, 2010,pp. 47‐79\u003c/li\u003e\n\u003cli\u003eCochrane L. Papua New Guinea\u0026apos;s rate of violence at \u0026apos;pandemic\u0026apos; levels, Australian Federal Police Officer says. In. http://www.abc.net.au/news/2015-02-19/png-facing-a-domesticviolence-pandemic-afp-officer-says/6150064: Australian Broadcasting Corporation New, 2015.\u003c/li\u003e\n\u003cli\u003eJewkes R, et al. Prevalence of and factors associated with non-partner rape perpetration: findings from the UN Multi-country Cross-sectional Study on Men and Violence in Asia and the Pacific. Lancet Glob Health 2013,1(4):208-218.\u003c/li\u003e\n\u003cli\u003eMakail MA. Domestic Violence in Port Moresby, in Dinnen S and Ley A (Eds) Reflections on Violence in Melanesia, pp 181\u0026ndash;186, The Federation Press, Leichardt, Australia. 2000.\u003c/li\u003e\n\u003cli\u003eCoker AL. Physical health consequences of physical and psychological intimate partner violence. Arch. Fam. Med. 2000,9(5):451\u0026ndash;457. https://doi.org/10.1001/archfami.9.5.451\u003c/li\u003e\n\u003cli\u003eWyshak G. Violence, mental health, substance abuse\u0026mdash;Problems for women worldwide. Health Care Women Int. 2000,21(7):631\u0026ndash;639. https://doi.org/10.1080/07399330050151860\u003c/li\u003e\n\u003cli\u003eJun H, et al. Intimate partner violence and cigarette smoking: Association between smoking risk and psychological abuse with and without co-occurrence of physical and sexual abuse. Am J. Public Health 2008,98(3):527-535. doi:10.2105/AJPH.2003.037663\u003c/li\u003e\n\u003cli\u003eRomito P, et al. The impact of current and past interpersonal violence on women\u0026rsquo;s mental health. Soc Sci Med 2005,60(8):1717\u0026ndash;1727. https://doi.org/10.1016/j.socscimed.2004.08.026\u003c/li\u003e\n\u003cli\u003eCrane CA. Intimate partner violence victimization and cigarette smoking: A meta-analytic review. Trauma Violence Abuse. 2013,14(4):305\u0026ndash;315. https://doi.org/10.1177/1524838013495962\u003c/li\u003e\n\u003cli\u003eYoshihama M, Horrocks J. Risk of intimate partner violence: Role of childhood sexual abuse and sexual initiation in women in Japan. Child Youth Serv Rev. 2010,32(1):28-37.\u003c/li\u003e\n\u003cli\u003eKwagala B, et al. 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In the face of war: Examining sexual vulnerabilities of Acholi adolescent girls living in displacement camps in conflict-affected Northern Uganda. \u003cem\u003eBMC \u003c/em\u003eInt Health Hum Rights 2012,12(1):38. https://doi.org/10.1186/1472-698X-12-38\u003c/li\u003e\n\u003cli\u003eAbramsky T, et al. What factors are associated with recent intimate partner violence? Findings from the WHO multi-country study on women\u0026rsquo;s health and domestic violence. BMC public health. 2011,11(1):109. https://doi.org/10.1186/1471-2458-11-109\u003c/li\u003e\n\u003cli\u003eEves R. \u0026lsquo;Full price, full body\u0026rsquo;: norms, bride price and intimate partner violence in highlands Papua New Guinea. Cul Health Sex 2019,21(12):1367-1380, DOI: 10.1080/13691058.2018.1564937\u003c/li\u003e\n\u003cli\u003eNational Statistical Office (NSO) of Papua New Guinea, and ICF International. \u0026ldquo;Papua New Guinea Demographic and Health Survey 2016-18.\u0026rdquo;\u003c/li\u003e\n\u003cli\u003eAntai D. Controlling behavior, power relations within intimate relationships and intimate partner physical and sexual violence against women in Nigeria. BMC public health. 2011,11(1):511. https://doi.org/10.1186/1471-2458-11-511\u003c/li\u003e\n\u003cli\u003eKishor S. Domestic violence measurement in the demographic and health surveys: The history and the challenges (pp. 1\u0026ndash;10). Division for the Advancement of Women. 2005\u003c/li\u003e\n\u003cli\u003eStraus MA. Measuring intrafamily conflict and violence: The conflict tactics (Ct) scales. J Mar Fam. 1979,41(1):75. https://doi.org/10.2307/351733\u003c/li\u003e\n\u003cli\u003eAhinkorah BO, et al. Women decision-making capacity and intimate partner violence among women in sub-Saharan Africa. Arch Public Health 2018,76(1):5. https://doi.org/10.1186/s13690-018-0253-9\u003c/li\u003e\n\u003cli\u003eAhinkorah BO. Polygyny and intimate partner violence in sub-Saharan Africa: Evidence from 16 cross-sectional demographic and health surveys. SSM \u0026ndash; Pop Health, 2021,13:100729. https://doi.org/10.1016/j.ssmph.2021.100729\u003c/li\u003e\n\u003cli\u003eZou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004,159(7):702\u0026ndash;706. https://doi.org/10.1093/aje/kwh090\u003c/li\u003e\n\u003cli\u003eJean-Louis G, et al. Epidemiologic methods to estimate insufficient sleep in the US population. Int J Environ Res Public Health 2020,17(24), 9337. https://doi.org/10.3390/ijerph17249337\u003c/li\u003e\n\u003cli\u003eUBOS and ICF International: Uganda Demographic and Health Survey. Kampala, Uganda: UBOS and Calverton, Maryland: ICF International Inc, 2012.\u003c/li\u003e\n\u003cli\u003eNtaganira J, et al. Intimate partner violence among pregnant women in Rwanda. BMC women\u0026rsquo;s health. 2008,8(1):17. https://doi.org/10.1186/1472-6874-8-17\u003c/li\u003e\n\u003cli\u003eLauria L, et al. Smoking behaviour before, during, and after pregnancy: The effect of breastfeeding. Sci World J. 2012,1\u0026ndash;9. https://doi.org/10.1100/2012/154910\u003c/li\u003e\n\u003cli\u003eBahadori B, et al. Hypothesis: Smoking decreases breast feeding duration by suppressing prolactin secretion. Med Hypotheses 2013,81(4):582\u0026ndash;586. https://doi.org/10.1016/j.mehy.2013.07.007\u003c/li\u003e\n\u003cli\u003eHou WL, et al. Recovery experiences of Taiwanese women after terminating abusive relationships: A phenomenology study. J Interpersonal Violence 2013,28(1):157-175.\u003c/li\u003e\n\u003cli\u003eLeonard KE, Quigley BM. Thirty years of research show alcohol to be a cause of intimate partner violence: Future research needs to identify who to treat and how to treat them. Drug Alc Rev 2017,36(1):7-9.\u003c/li\u003e\n\u003cli\u003eKlostermann KC, Fals-Stewart W. Intimate partner violence and alcohol use: Exploring the role of drinking in partner violence and its implications for intervention. Agg Viol Behav. 2006,11(6):587\u0026ndash;597. https://doi.org/10.1016/j.avb.2005.08.008\u003c/li\u003e\n\u003cli\u003eCaleyachetty R, et al. Intimate partner violence and current tobacco smoking in low- to middle-income countries: Individual participant meta-analysis of 231,892 women of reproductive age. Glob Public Health 2014,9(5):570\u0026ndash;578. https://doi.org/10.1080/17441692.2014.905616\u003c/li\u003e\n\u003cli\u003eWorld Health Organisation. Violence against Women 2021. https://www.who.int/news-room/fact-sheets/detail/violence-against-women.\u003c/li\u003e\n\u003cli\u003eDuvvury N, et al. Intimate partner violence: Economic costs and implications for growth and development. 2013.\u003c/li\u003e\n\u003cli\u003eWorld Report. \u0026ldquo;Papua New Guinea: Events of 2020.\u0026rdquo; 2021. https://www.hrw.org/world-report/2021/country-chapters/papua-new-guinea.\u003c/li\u003e\n\u003cli\u003eUnited Nations Human Rights \u0026ldquo;Declaration on the Elimination of Violence against Women.\u0026rdquo; World Health Organization. 1993. https://www.ohchr.org/en/professionalinterest/pages/violenceagainstwomen.aspx.\u003c/li\u003e\n\u003cli\u003eWorld Bank \u0026ldquo;Crimes and Disputes :Missed Opportunities and Insights from a National Data Collection Effort in Papua New Guinea.\u0026rdquo; 2014.\u003c/li\u003e\n\u003cli\u003eMcnutt L-A, et al. Cumulative abuse experiences, physical health and health behaviors. Ann Epidemiol. 2002,12(2):123\u0026ndash;130. https://doi.org/10.1016/S1047-2797(01)00243-5\u003c/li\u003e\n\u003cli\u003eGreenland S. Interpretation and choice of effect measures in epidemiologic analyses. Am J Epidemiol. 1987,125(5):761-768.\u003c/li\u003e\n\u003cli\u003eSinclair JC, Bracken MB. Clinically useful measures of effect in binary analyses of randomized trials. J Clin Epidemiol. 1994,47(8):881-889.\u003c/li\u003e\n\u003cli\u003eNurminen M. To use or not to use the odds ratio in epidemiologic analyses? Eur J Epidemiol. 1995,11(4):365-371.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Demographics (n=9,943)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.94704992435703%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.49016641452345%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" width=\"31.316187594553707%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.24659606656581%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePearson chi-square\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (mean)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e15-49 (32.68\u0026plusmn;0.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e15-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e358(3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e71(19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e287(80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e20-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1493(15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e357(23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1136(76.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e25-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2008(20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e522(26.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1486(74.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e30-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1900(19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e457(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1443(76.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e35-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1755(17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e353(20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1402(79.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e40-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1324(13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e271(20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1053(79.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e45-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1030(10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e117(17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e853(82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eSouthern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2810(28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e509(18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e2301(81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eHighlands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2817(28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e647(23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e2170(77.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eMomase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2014(20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e579(28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1435(71.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eIslands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2227(22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e473(21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1754(78.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e7453(75.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e1485(19.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e5968(80.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2415(24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e723(29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1692(70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighest education level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2266(23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e530(23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1736(76.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e4899(49.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e1028(21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e3871(79.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2303(23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e559(24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1744(75.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e400(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e91(22.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e309(77.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e9756(99.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e2170(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e7586(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eNon-Christian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e53(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e17(32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e36(67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eNo religion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e47(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e19(40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e28(59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth index\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1485(15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e340(22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1145(77.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1576(16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e340(21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1236(78.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1835(18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e334(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1501(81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2393(24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e518(21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1875(78.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e2579(26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e676(26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1903(73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e8193(83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e1806(22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e6387(78.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eCo-habitation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1675(17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e402(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1273(76.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently residing with partner\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eLiving together\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e8503(86.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e1867(22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e6636(78.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eStaying elsewhere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1316(13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e324(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e992(75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of kids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e945(9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e272(28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e673(71.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e1-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e3335(33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e792(23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e2543(76.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e3-4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e3140(31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e688(21.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e2452(78.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e5-6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1734(17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e315(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1419(81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e7 and more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e714(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e141(19.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e573(80.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupational status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eNot working\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e6044(62.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e1348(22.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e4696(77.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eProfessional/technical/managerial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e570(5.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e112(19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e458(80.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eClerical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e210(2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e55(26.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e155(73.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eSales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e486(5.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e123(25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e363(74.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eAgricultural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1508(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e261(17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1247(82.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eServices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e841(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e254(30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e587(69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eManual job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e77(0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e23(29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e54(70.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical violence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1723(47.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e322(18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1401(81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"34.894259818731115%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.46525679758308%\"\u003e\n \u003cp\u003e1898(52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.558912386706949%\"\u003e\n \u003cp\u003e477(25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.861027190332326%\"\u003e\n \u003cp\u003e1421(74.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.220543806646525%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: A modified Poisson regression of the relationship between IPPV with current smoking status\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrude IRR (95% C.I.)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"53.116531165311656%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted IRR (95% C.I.)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.470134874759154%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel I\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.470134874759154%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel II\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.01156069364162%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel III\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.048169556840076%\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel IV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eExperience physical violence\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e\u0026yen;\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.35***(1.20-1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.29***(1.23-1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.27** (1.11-1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.24**(1.08-1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge groups (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e15-19 (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e20-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.85(0.58-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.85(0.57-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.86(0.58-1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e25-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.90(0.60-1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.91(0.60-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.91(0.61-1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e30-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.85(0.56-1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.85(0.56-1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.87(0.57-1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e35-39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.71(0.46-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.72(0.46-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.72(0.46-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e40-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.60*(0.38-0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.59*(0.37-0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.60*(0.38-0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e45-49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.48**(0.29-0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.50**(0.30-0.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.51*(0.30-0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eSouthlands (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eHighlands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.47***(1.20-1.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.48***(1.21-1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.47***(1.20-1.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eMomase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.84***(1.52-2.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.85***(1.53-2.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.82***(1.50-2.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eIslands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.38**(1.12-1.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.38**(1.12-1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.38**(1.12-1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePlace of residence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eRural (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.49***(1.27-1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.41***(1.19-1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.30**(1.08-1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eChristian (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNon-Christian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.68(0.19-2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.73(0.21-2.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.69(0.19-2.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo religion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.93*(1.16-3.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e2.05**(1.26-3.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e2.00**(1.24-3.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighest education level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo education (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.94(0.76-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.93(0.75-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.93(0.74-1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.10(0.81-1.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.02(0.74-1.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.02(0.75-1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.05(0.67-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.89(0.55-1.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.01(0.61-1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiteracy level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eCannot read at all (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eAble to read only parts of sentence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.92(0.73-1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.90(0.71-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.88(0.69-1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eAble to read whole sentence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.78*(0.61-0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.75*(0.58-0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.74*(0.57-0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo card with required language\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.62(0.24-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.62(0.23-1.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.64(0.24-1.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eBlind/visually impaired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.93(0.30-12.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.78(0.29-11.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.70(0.25-11.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eMarried (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eCo-habiting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.99(0.84-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.98(0.83-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.03(0.87-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrently residing with partner\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eLiving together (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eStaying elsewhere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.87(0.71-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.87(0.71-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.85(0.69-1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of partner\u0026rsquo;s wives\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo other wife (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.14(0.94-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.14(0.95-1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.13(0.93-1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.95(0.64-1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.95(0.64-1.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.01(0.68-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e3 or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.67**(1.17-2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.76**(1.22-2.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.71**(1.19-2.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.08(0.65-1.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.07(0.65-1.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.04(0.64-1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePartner\u0026rsquo;s age (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e15-24 (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.97(0.72-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.99(0.73-1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.98(0.72-1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.12(0.80-1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.15(0.82-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.16(0.83-1.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e45+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.20(0.83-1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.21(0.84-1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.19(0.82-1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003e55+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePartner\u0026rsquo;s educational level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo education (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.85(0.71-1.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.86(0.71-1.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.91(0.75-1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.94(0.76-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.91(0.73-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.95(0.75-1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e0.91(0.67-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.86(0.63-1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.93(0.68-1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eDon\u0026rsquo;t know\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInsurance cover\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.90(0.63-1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.91(0.64-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternet access\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.23(0.97-1.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.27(1.00-1.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOwnership of mobile phone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e0.99(0.85-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.99(0.84-1.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWatch television\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.01(0.84-1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.04(0.85-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eListen to radio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.18(1.00-1.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.20*(1.01-1.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRead newspapers/magazines\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e1.05(0.86-1.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.04(0.85-1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNot working (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eProfessional/technical/managerial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.67*(0.46-0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eClerical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.46*(0.24-0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eSales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.26(0.98-1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eAgricultural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.75**(0.61-0.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eServices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.08(0.87-1.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eManual job\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.48(0.17-1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWealth index\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003ePoorest (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.06(0.85-1.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.75*(0.59-0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.99(0.78-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e0.94(0.70-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"29.67479674796748%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinancial inclusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eNo (Ref.)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.67479674796748%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.208672086720867%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.615176151761517%\"\u003e\n \u003cp\u003e1.15(0.94-1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"64.09214092140921%\"\u003e\n \u003cp\u003eIRR=Incidence Risk Ratio , *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"64.09214092140921%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMulticollinearity test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"64.09214092140921%\"\u003e\n \u003cp\u003eMean VIF =1.60 range 1.01-2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" width=\"64.09214092140921%\"\u003e\n \u003cp\u003e1/VIF range 0.355614-0.991019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.29268292682927%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.615176151761517%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Demographic and health survey, intimate partner physical violence, cigarette smoking, Papua New Guinea","lastPublishedDoi":"10.21203/rs.3.rs-779053/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-779053/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Intimate partner physical violence (IPPV) is a preventable public health threat associated with health deteriorating lifestyles such as cigarette smoking. However, limited research has focused on the association between IPPV and cigarette smoking among women in unions in low-and middle-income countries like Papua New Guinea (PNG). The aim of this study was to examine the association between IPPV and current cigarette smoking using a nationally representative sample. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We utilized 2016-2018 PNG Demographic and Health Survey data of 9,943 women aged 15-49 years who were in intimate unions. We estimated the direct risk of smoking cigarette using modified Poisson regression models with a robust variance relative risk and 95% confidence intervals (CI) of cigarette smoking. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among the total participants, the prevalence of IPPV was 52.4% and smoking cigarette in the last 24 hours was 25.1%. The modified Poisson regression results indicated a robust and persistent association between IPPV and cigarette smoking among women in unions both in the absence and presence of covariates. The risk of smoking cigarette was significantly elevated among those who reported a history of IPPV relative to their counterparts with no physical violence history (IRR: 1.35, 95%CI: 1.20-1.52) in the absence of covariates. After controlling for demographic, social and economic variables, the association between IPPV and cigarette smoking persisted (IRR: 1.24, 95%CI: 1.08-1.41). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e The present study provides strong evidence to indicate a robust and persistent association between IPPV and current cigarette smoking among women in unions. Interventions aimed at addressing IPPV among women in unions in PNG to reduce the increased risk of cigarette smoking are needed.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"The Persistent Association Between Exposure to Intimate Partner Physical Violence and Current Cigarette Smoking Among Women in Papua New Guinea: A Modified Poisson Regression Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-24 21:10:04","doi":"10.21203/rs.3.rs-779053/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"608e41c5-aa0d-4c8e-8150-89ac6c51c943","owner":[],"postedDate":"August 24th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":6670061,"name":"Health Policy"}],"tags":[],"updatedAt":"2022-05-20T10:59:09+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-24 21:10:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-779053","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-779053","identity":"rs-779053","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}