The Relationship Between Economic Status, Poverty, and Health among Arabs in Israel

The Relationship Between Economic Status, Poverty, and Health among Arabs in Israel | 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 Relationship Between Economic Status, Poverty, and Health among Arabs in Israel Mohammad Khatib This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8369758/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 Arabs in Israel, comprising about 21% of the population, are recognized as an indigenous minority with full citizenship rights, yet they face persistent structural disadvantages compared to Jewish citizens. These disparities are evident across socioeconomic, educational, employment, and health domains. High poverty rates, particularly among women, children, and the elderly, are aggravated by limited governmental investment in infrastructure, education, and health services. Arab women’s labor force participation remains notably low due to systemic barriers. Extensive evidence links socioeconomic status with health outcomes and behaviors. This study examines how sociodemographic factors and health knowledge influence the relationship between economic status, self-rated health, and health behaviors among Arabs in Israel Methods This cross-sectional study utilized data from the 2015–2016 Health and Environment Survey among Arabs in Israel (HESPI). Employing a three-stage stratified cluster sampling of 2,018 households, face-to-face interviews gathered socio-demographic, economic, and health-related data. The final sample included 2,041 adults representing diverse socioeconomic and geographic groups within Arab communities. Results Approximately half of participants lived below the poverty line. Those with lower economic status exhibited poorer self-rated health, higher prevalence of chronic illness, and lower engagement in physical activity, while smoking and BMI did not significantly differ by economic status. Family size moderated the relationships between economic status and both chronic illness and SRH, indicating that smaller families serve as a resilience factor. Educational attainment moderated the link between economic status and physical activity. Regression analyses revealed that gender, age, education, and health knowledge significantly predicted health outcomes and behaviors, with health knowledge mediating several associations. Conclusions The findings indicate that poverty is strongly associated with poorer health outcomes and behaviors among Arabs in Israel. Smaller family size and higher education act as resilience factors, mitigating these effects. Health knowledge plays a key mediating role, emphasizing the importance of socioeconomic empowerment and education in promoting health equity. Arabs in Israel Health disparities Health knowledge Physical activity Self-rated health Socioeconomic status Poverty Figures Figure 1 Background Arabs in Israel, constituting 21% of the country’s citizens, are recognized as an indigenous population with individual civil rights, yet they encounter systemic disadvantages relative to Jewish citizens [ 1 ]. These disparities are evident in multiple spheres, including socioeconomic status, employment, education, and political and social inclusion [ 2 ]. In 2021, 38.8% of Arabs in Israel lived below the poverty line, 49% among Arab children and 38.9% among elderly Arabs compared to 11.9% among non-Orthodox Jews overall, 13.2% for children, and 15.3% for the elderly [ 3 ]. The persistent poverty among Arab communities is further intensified by limited government investment and underdevelopment in infrastructure, health services, and educational systems within Arab municipalities [ 4 ]. As a result, Arabs in Israel consistently report poorer health outcomes and lower self-rated health (SRH) in comparison to the Jewish majority [ 5 ]. Employment rates among Arab women in Israel are markedly lower than those of women in the general population, standing at 37% compared to 77%, respectively [ 4 ]. This employment gap is largely shaped by structural and systemic barriers, including residential segregation, institutional discrimination, limited access to public transportation, and insufficient childcare options. For instance, in 2020, only 8% of daycare subsidies were allocated to the Arab population, even though Arab toddlers represented 24% of all toddlers in Israel [ 6 ]. The relationship between economic status, particularly poverty, and health outcomes has been a central theme in public health research. Extensive evidence across different populations highlights that economic disparities profoundly shape health through multiple pathways, influencing both physical and mental health indicators, health behaviors, and overall well-being. Individuals and families with low income consistently face poorer health outcomes and limited access to medical services, preventive care, and health-promoting resources compared to those with higher socioeconomic status. Multiple studies have documented persistent health disparities associated with economic status. A comprehensive analysis by Cutler and Lleras-Muney (2010), based on data from diverse populations, demonstrated that individuals with lower socioeconomic status exhibit poorer health outcomes compared to those with higher economic standing [ 7 ]. These disparities are reflected across multiple health indicators, including higher rates of chronic diseases, reduced life expectancy, and increased prevalence of mental health disorders. Access to healthcare is a key determinant underpinning these outcomes. Adler and Rehkopf (2008), in their examination of health disparities in the United States, emphasized the constraining role of economic factors in healthcare accessibility [ 8 ]. Individuals from low-income backgrounds often encounter multiple barriers to medical services, such as financial limitations, inadequate healthcare infrastructure in disadvantaged areas, and lack of health insurance coverage. These barriers contribute to delayed diagnoses and treatment, thereby exacerbating health conditions and diminishing overall well-being. The link between poverty and health behaviors has also been extensively documented. Phelan, Link, and Tehranifar (2010) found that individuals from lower socioeconomic backgrounds are more likely to smoke than those with higher incomes [ 9 ]. Economic hardship and chronic stressors associated with poverty may contribute to elevated smoking rates, as smoking often functions as a coping mechanism. Economic status similarly influences physical activity. Giskes et al. (2010) reported that individuals from lower socioeconomic strata tend to have limited access to recreational facilities, safe public spaces, and affordable sports programs, resulting in lower physical activity levels and increased prevalence of obesity and related health conditions [ 10 ]. Nutritional behaviors are likewise shaped by economic constraints. Rehm et al. (2016), in their investigation of dietary intake among U.S. adults, found that individuals from low-income households often have limited access to nutritious foods due to financial barriers [ 11 ]. Consequently, they tend to consume more inexpensive, processed, and less nutritious products, which heightens their risk of obesity, diabetes, and cardiovascular disease. This study explores whether and how sociodemographic factors influence the relationship between economic status and health outcomes, SRH, and health behaviors among Arabs in Israel. It also examines whether general or specific health knowledge mediates or moderates this relationship. Methods Study design and population This cross-sectional study is based on data collected from the Health and Environment Survey among Arabs in Israel (HESPI), conducted by Rikaz – the Applied Social Research Center of the Galilee Society – between November 2015 and February 2016. The study population consisted of all Arabs households residing in Israel during the year 2015. The sample A three-stage stratified cluster sampling design utilizing systematic random sampling was implemented. The sampling frame encompassed segregated Arab municipalities and mixed Arab–Jewish cities, and enumeration areas were classified according to the Israeli Central Bureau of Statistics (CBS) 2008 Population Census. These enumeration areas functioned as the primary sampling units (PSUs) [12]. In the first sampling stage, 75 enumeration areas were selected through systematic random sampling. In the second stage, 30 households were randomly drawn from each selected area. In the third stage, a single individual aged 18 years or older was selected from each household using Kish selection tables [13,14] to participate in in-depth interviews. Stratification by gender and age was applied to the study population. The sample size was determined to provide sufficient statistical power for comparing participants with and without one or more chronic conditions. Based on an earlier reported prevalence of 14.5% for the presence of one or more chronic conditions, the sample size was estimated at 2,250 households [15]. Data collection Systematic sampling was used to recruit households within each enumeration area until 30 households were reached. A household member aged 18 years or older was selected for interview. If the selected individual was unavailable, interviewers made one or two additional visits to complete the questionnaire. Quality control procedures included review of completed questionnaires, field reports, and interviewer comments by the field coordinator. Of 2,246 sampled households, 2,018 participated in the study (response rate: 89.8%). Data was collected about total of 9,063 individuals (all families members), and 2,018 selected adults aged 18 or older (971 men and 1,047 women) completing in-depth follow-up interviews. The questionnaire A socio-demographic questionnaire was developed ad hoc for the present study. It included variables such as gender, age, educational attainment, geographical district, and household income. Income data was used to determine whether the participant classified as below or above the national poverty line[1]. The participant was considered below the poverty line if his\her total net monthly income was less than 2,526 NIS, according to the official poverty threshold for 2015 [16]. A health-related questionnaire was also constructed ad hoc and included items assessing selected health behaviors (e.g., cigarette and waterpipe (Nargila) smoking, physical activity), self-assessed health knowledge, presence of chronic diseases, as well as anthropometric measures (weight and height). In addition, participants were asked to provide a Self-Rated Health (SRH) score. Participants The study included 2,041 Arab adults in Israel, comprising 990 men (48.5%) and 1,051 women (51.5%). Participants ranged in age from 18 to 94 years (M = 41.0 years, SD = 16.10). The majority were Muslim (81.7%), resided in the northern district (72%), and lived in Arab municipalities (87%). Settlement size distribution was as follows: large settlements (53%), medium-sized settlements (27%), and small settlements (20%). Most participants were married (77%), with an average household size of 4.0 people (SD = 2.06). Educational attainment varied: less than secondary education (38%), secondary education (26%), high school matriculation certificate (23%), and academic education (12%). Detailed demographic characteristics are presented in Table 1. Participants living below the poverty line differed significantly from those above the poverty line across multiple demographic characteristics. Those below the poverty line were older, had larger households, and a higher proportion were widowed. They also had lower educational attainment and lower employment rates. Additionally, a higher proportion of participants below the poverty line were Muslim and resided in southern Israel compared to those above the poverty line. Table 1. Demographic characteristics of the participants* ( N = 2041) Characteristic Total sample Below poverty line (n = 908) Above poverty line (n = 847) Difference Age (years) M (SD) (range: 18-94) 40.90 (16.10) 41.64 (16.70) 38.59 (14.22) t(1738.88) = 4.12, p<.001 Family size M (SD) (range: 1-14) 4.32 (2.06) 4.68 (2.23) 4.22 (1.76) t(1706.66) = 4.74, p<.001 Gender n (%) Female 1051 (51.5) 477 (52.5) 416 (49.1) Z = 1.43 p = .152 Male 990 (48.5) 431 (47.5) 431 (50.9) Age categories n (%) 18-24 314 (15.4) 137 (15.1) 144 (17.0) χ 2 (4)=26.45 p < .001 25-34 527 (25.8) 208 (22.9) 252 (29.8) 35-44 480 (23.5) 245 (27.0) 181 (21.4) 45-59 415 (20.4) 176 (19.4) 185 (21.8) 60+ 305 (14.9) 142 (15.6) 85 (10.0) Marital status n (%) Single 303 (15.0) 142 (15.7) 133 (15.9) χ 2 (3)=37.80 p < .001 Married, engaged 1552 (76.7) 665 (73.7) 679 (81.0) Separated, divorced 40 (1.9) 23 (2.5) 8 (1.0) Widowed 129 (6.4) 72 (8.0) 18 (2.1) Education level n (%) Less than secondary 776 (38.4) 405 (45.3) 234 (27.7) χ 2 (3)=146.93 p < .001 Secondary certification 521 (25.8) 261 (29.2) 191 (22.6) High school, matriculation certificate 472 (23.4) 182 (20.4) 233 (27.6) Academic 250 (12.4) 46 (5.1) 187 (22.1) In labor force n (%) 1066 (52.9) 418 (46.6) 555 (66.3) Z = 8.26 p < .001 Employed from labor force n (%) (from n= 1066) 975 (91.5) 359 (85.9) 541 (97.5) Z = 6.80 p < .001 Total employment n (%) (from n = 2041) 975 (48.4) 359 (40.0) 541 (64.6) Z = 10.25 p < .001 Religion n (%) Muslim 1663 (81.7) 792 (87.4) 624 (73.9) χ 2 (2)=55.62 p < .001 Druze 241 (11.8) 82 (9.1) 132 (15.6) Christian 131 (6.5) 32 (3.5) 88 (10.4) District in Israel n (%) North 1477 (72.4) 634 (68.7) 664 (78.4) χ 2 (2)=27.15 p < .001 Center 290 (14.2) 118 (13.0) 98 (11.6) South 274 (13.4) 166 (18.3) 85 (10.0) Type of residence n (%) Arab 1778 (87.1) 798 (87.9) 734 (86.7) Z = 0.77 p = .441 Mixed Jewish-Arab 263 (12.9) 110 (12.1) 113 (13.3) Size of residence n (%) Large, over 15000 1086 (53.2) 472 (52.0) 447 (52.8) χ 2 (2)=5.61 p = .061 Medium, 5000 to 15000 544 (26.7) 222 (24.4) 236 (27.9) Small, less than 5000 411 (20.1) 214 (23.6) 9.4) *Percentages were calculated excluding missing data. Variables and measures Health Status Indicators : Body Mass Index (BMI) was calculated from self-reported height and weight. Chronic illness was measured as a dichotomous variable (yes/no). Medication use was assessed as a categorical variable with three levels: daily, occasionally, and none. Health Perception : Overall health perception was assessed using two items measured on a 5-point scale: (1) SRH (1 = very bad to 5 = very good) and (2) satisfaction with health status (1 = very low to 5 = very high). The items were strongly correlated (r = .85, p < .001), and mean scores were calculated to create a composite measure. Health Behaviors : Physical activity was measured as a dichotomous variable (yes/no). Smoking status was assessed using dichotomous variables for cigarette smoking and/or nargileh use (yes/no). Health Knowledge: General health knowledge: Eight items were measured on a 5-point scale (α = .95). Mean scores were calculated, with higher scores indicating greater health knowledge. Perceived nutrition knowledge was assessed by the question "do you have information about healthy nutrition?" and using dichotomous variable (yes/no) Economic Status: Dichotomous variable indicating individual income below or above the 2015 Israeli poverty line threshold. Sociodemographic variables included gender, age, household size, marital status, educational level, employment status, religion, geographic district, type of locality (Arab municipality/mixed Arab-Jewish city), and locality size. Data analysis Data was analyzed with SPSS software ver 28. First, 286 participants did not provide information about their economic status. An examination of their health perception, health behaviors, and knowledge, revealed that they had a lower health related status than those who provided information about their economic status. A higher percentage of them reported a chronic illness (p < .001), and their general perception of health was lower (p < .001). Further, a lower percent of them reported having knowledge about nutrition (p < .001). Descriptive statistics were used to characterize the demographic profile of participants and the study's dependent variables. Group comparisons (below/above the poverty line) were calculated using t-tests, chi-square tests, and Z-ratios for the significance of differences between two independent proportions. Next, the moderating role of demographic variables in the relationships between economic status and the study's dependent variables was examined using (a) multiple linear regressions with interactions for continuous dependent variables, (b) multiple logistic regressions with interactions for dichotomous dependent variables and continuous demographic variables, and (c) analyses of variance for dichotomous dependent variables and categorical demographic variables. Significant interactions were interpreted using simple slopes and estimated marginal means. The study model was first examined using a series of multiple linear and logistic regressions for SRH and related behaviors, including demographic variables, economic status, and health-related knowledge. Mediation was examined using a series of PROCESS models (Hayes, 2022), specifically Model 4, with 5,000 bootstrap samples and 95% confidence intervals [17]. The significance level was set at p < .01 due to sample size. [1] The poverty line in Israel in 2015 was 3,158 New Israeli Shekels, while the poverty line per standard person was 2,526 NIS (half of the median income), since according to the equivalence scale, one person is counted as 1.25 standard persons. Results Differences by economic status Approximately half of the participants were classified as living below the poverty line (n = of 1755; 51.7%), while the remainder were above the poverty line (n = 847; 48.3%). Table 2 shows the distribution of study variables for the total sample and stratified by economic status. The mean BMI for the sample was 26.5, with no significant differences observed between economic groups. Approximately 40% of participants had a BMI in the normal range, another 40% were overweight, and around 17% were classified as obese. A higher proportion of participants below the poverty line reported having a chronic illness compared to those above the poverty line (34% vs. 28%, respectively). Most of the participants in both groups adhered to daily medication for their chronic condition. SRH was lower among participants below the poverty line (M = 3.78) compared to those above the poverty line (M = 4.01). Similarly, a lower percentage of participants below the poverty line engaged in physical activity (20% vs. 33%). No significant group differences were detected for smoking status. Both general health knowledge (M = 2.65 vs. M = 2.87) and perceived nutrition knowledge (49% vs. 64%) were lower among participants living below the poverty line. Table 2 Health perception, related behavior, and knowledge, for the whole sample (N = 2041), and by economic status (N = 1755) Total sample Below poverty line (n = 908) Above poverty line (n = 847) Difference Chronic illness, overweight BMI M (SD), range 26.55 (4.57) (16–63) 26.64 (4.68) 26.40 (4.54) t(1687) = 1.05 p = .294 BMI categories, n (%) Underweight (< 18) 17 (0.9) 8 (0.9) 8 (1.0) χ 2 (4) = 1.91 p = .752 Normal (18-24.9) 758 (38.5) 330 (37.8) 326 (40.0) Overweight (25-29.9) 851 (43.2) 386 (44.2) 340 (41.7) Obese (30-34.9) 258 (13.1) 109 (12.5) 110 (13.5) Morbid obesity (35+) 84 (4.3) 40 (4.6) 32 (3.9) Chronic illness Yes, n (%) 668 (32.7) 309 (34.0) 239 (28.2) Z = 2.63 p = .009 Daily medication for chronic illness, n (%) (of n = 485) Yes 442 (91.1) 217 (91.9) 140 (88.1) Z = 1.29 p = .197 Irregularly, no 43 (8.9) 19 (8.1) 19 (11.9) Health perception : Total SRH, n (%) M (SD), range 3.85 (1.06) (1–5) 3.78 (1.09) 4.01 (0.98) t(1750.60) = -4.69 p < .001 Health related behavior : Physical activity Yes, n (%) 524 (25.8) 183 (20.3) 278 (32.9) Z = 5.98 p < .001 Smoking (cigarettes or Nargila) Yes, n (%) 672 (33.3) 294 (32.7) 303 (36.1) Z = 1.48 p = .139 Health related knowledge : General health knowledge M (SD), range 2.74 (0.99) (1–5) 2.65 (0.95) 2.87 (1.01) t(1709.53) = -4.73 p < .001 Perceived nutrition knowledge Yes, n (%) 1106 (54.5) 442 (49.1) 536 (63.6) Z = 6.11 p < .001 Differences by economic status and the demographic variables Exploratory attempts were calculated to assess whether the relationships between economic status and health were moderated by the demographic variables. Two significant results were found: for family size and level of education. Family size was found to moderate the relationship between economic status and having a chronic illness (B = 0.54, SE = 0.13, p < .001, OR = 1.71, 95%CI = 1.33, 2.19). Interpretation of the significant interaction with simple slopes has revealed that for smaller families, being an individual above the poverty line was related with lower odds for having a chronic illness (effect = -0.82, t = -5.57, p < .001), while the relationship was not significant for larger families (effect = 0.25, t = 1.36, p = .175). Further, family size was found to moderate the relationship between individual economic status and perception of health (B = -0.23, SE = 0.05, β = − .13, p < .001, 95%CI = -0.33, -0.13). Interpretation of the significant interaction with simple slopes has revealed that for smaller families, being above the poverty line was related with better SRH (effect = 0.51, t = 7.47, p < .001), while the relationship was not significant for larger families (effect = 0.05, t = 0.70, p = .487). Level of education was found to moderate the relationship between economic status and physical activity (F(1, 1727) = 5.86, p = .016, η 2 = .003). Interpretation of the significant interaction with estimated marginal means has revealed that for more educated participants (with a full high school education or a college degree), being above the poverty line was related with higher odds for doing physical activity (F(1, 1727) = 17.55, p < .001, η 2 = .010), while the relationship was not significant for less educated participants (with less than a full high school education) (F(1, 1727) = 2.35, p = .125, η 2 = .001). That is, a smaller family size was found to be a resilience factor for chronic illness and the perception of health. Level of education was found to be a resilience factor for proper physical activity. The study model Multiple linear and logistic regression analyses were performed to examine associations SRH and related behaviors. Independent variables included economic status and health-related knowledge, while gender (coded as 1 = male, 0 = female), age, family size, and educational attainment (coded as 1 = completion of full high school education or a college degree, 0 = less than full high school education) were included as covariates. General health knowledge was hypothesized to be associated with all outcome variables; perceived nutrition knowledge was hypothesized to be associated with BMI and chronic illness and was entered accordingly into the relevant regression models. Due to insufficient variance, daily medication adherence for chronic illness was excluded from the analyses. Results in Table 3 show that all five models are significant. About 10% of the variance in BMI were explained by the study variables, such that for females, younger participants, and with greater health related knowledge, BMI was lower. BMI was unrelated with perceived nutrition knowledge. About 43% of the variance in the likelihood of chronic illness were explained by the study variables, such that the odds for a chronic illness were higher for older participants, living in small family, and for participants with less than a full high school education. Health related knowledge and perceived nutrition knowledge were unrelated with the odds for a chronic illness. About 33% of the variance in health perception were explained by the study variables, such that for younger participants, participants with a full high school education or a college degree, and with greater health related knowledge, SRH was better. Further, about 17% of the variance in the likelihood of physical activity were explained by the study variables, such that the odds for physical activity were higher for males, younger participants, participants with a full high school education or a college degree, participants whose economic status was above the poverty line, and with greater health related knowledge. Finally, about 37% of the variance in the likelihood of smoking were explained by the study variables, such that the odds for smoking were higher for males, younger participants, and with lower health related knowledge. Table 3 Multiple linear and logistic regression models for SRH and related behavior, with economic status and health related knowledge (N = 1755) BMI Chronic illness SRH Physical activity Smoking β (p) OR (p) (95%CI) β (p) OR (p) (95%CI) OR (p) (95%CI) Gender .07 (.003) 0.92 (.545) (0.72, 1.19) .04 (.070) 1.67 (< .001) (1.32, 2.11) 13.39 (< .001) (10.25, 17.50) Age .22 (< .001) 1.09 (< .001) (1.08, 1.11) − .48 (< .001) 0.97 (< .001) (0.96, 0.98) 0.99 (.008) (0.98, 0.997) Family size − .06 (.024) 0.91 (.006) (0.85, 0.97) .04 (.073) 1.03 (.337) (0.97, 1.10) 1.04 (.275) (0.97, 1.10) Education level − .04 (.096) 0.66 (.006) (0.49, 0.89) .09 (< .001) 1.96 (< .001) (1.53, 2.52) 0.85 (.257) (0.65, 1.12) Poverty line .01 (.679) 0.96 (.759) (0.74, 1.25) .03 (.109) 1.54 (< .001) (1.21, 1.97) 1.25 (.077) (0.98, 1.61) General health knowledge − .13 (< .001) 0.89 (.101) (0.77, 1.02) .15 (< .001) 1.38 (< .001) (1.22, 1.56) 0.63 (< .001) (0.55, 0.72) Perceived nutrition knowledge .01 (.829) 0.98 (.914) (0.75, 1.30) -- -- -- Adj.R 2 = .10 R 2 = .43 Adj.R 2 = .33 R 2 = .17 R 2 = .37 F(7, 1642) = 26.37 p < .001 χ 2 (7) = 621.51 p < .001 F(6, 1718) = 144.94 p < .001 χ 2 (6) = 217.72 p < .001 χ 2 (6) = 536.20 p < .001 Note. For logistic regressions- Nagelkerke’s R 2 . In light of these results (Table 3 ), and the results shown in Table 2 , mediation was likely for BMI, total SRH, physical activity, and smoking - with general health knowledge as the mediator. It was examined with the Process procedure, model no.4, for continuous and dichotomous outcomes, controlling for gender, age, family size, and level of education. All four mediation models were found significant, with the indirect effects shown in Table 4 . Table 4 The indirect mediation effects for BMI, SRH, physical activity, and smoking, with general health knowledge (N = 1755) Indirect effect SE 95%CI BMI -0.07 0.03 -0.15, -0.01 SRH 0.02 0.01 0.01, 0.04 Physical activity 0.04 0.02 0.01, 0.08 Smoking -0.06 0.02 -0.11, -0.02 Figure 1 presents the mediated relationships. As may be observed, being above the poverty line was related to higher health related knowledge, which in turn was related to lower BMI, with a better SRH, with higher odds for physical activity, and with lower odds for smoking. Discussion This study examined the relationship between economic status, health status, and health behaviors among the Arab population in Israel, with a particular focus on mediating and moderating mechanisms. The findings reveal a complex picture of health inequities shaped by multiple sociodemographic factors. The fact that more than half of the participants live below the poverty line reflects the harsh socioeconomic reality of the Arab population in Israel, as documented in official state reports by national institutions. The findings indicate a clear association between the individual economic status and key health indicators. The higher prevalence of chronic conditions and lower SRH among participants living below the poverty line is consistent with the international literature on the social determinants of health. Numerous studies have shown that poverty constitutes a major risk factor for chronic morbidity through multiple mechanisms, including exposure to chronic stress, neglect of health needs, limited access to high-quality health services, and risk behaviors [18-20]. In the context of minority groups, the literature points to heightened severity of health inequities resulting from the accumulation of multiple structural barriers. Studies of ethnic minorities in the United States, the United Kingdom, and Australia report similar patterns, in which low socioeconomic status is combined with linguistic, cultural, and access barriers, generating a substantial burden of health distress [21]. Among the Arab population in Israel, this situation is further exacerbated by geographic concentration in the periphery, the low socioeconomic ranking of most Arab localities, and cultural–linguistic barriers within the health system [22,23]. Previous studies on the health of the Arab population in Israel have documented substantial gaps in key health indicators compared to the Jewish population, including shorter life expectancy, higher infant mortality, and increased prevalence of chronic diseases [24,25]. The present findings deepen this understanding by pointing to specific mechanisms through which economic status affects health in this population. Contrary to expectations and to some of the existing literature, no significant differences in body mass index (BMI) were found between participants living above and below the poverty line. This result deviates from the common pattern observed in many high‑income countries, where poverty is typically associated with obesity, particularly among women and children. Several possible explanations may account for this finding. First, it may reflect poverty and nutrition paradox characteristic of societies undergoing nutritional transition, in which inexpensive, energy‑dense foods are widely available even to low‑income groups, resulting in high obesity rates across socioeconomic strata. Second, the official definition of the poverty line may not adequately capture the economic reality of Arab society, in which families classified as above the poverty line may still experience substantial economic hardship relative to the cost of living. Third, cultural factors and social norms regarding diet and body weight may outweigh the direct impact of economic status. At the same time, the findings indicate a high prevalence of overweight and obesity in the sample as a whole. This pattern is alarming in view of the well-known links between excess body weight and chronic diseases such as diabetes, hypertension, and cardiovascular disease. Poor nutritional status was found to be associated with low health knowledge irrespective of economic status, underscoring the importance of health education as a potential strategy to improve this situation. The finding that only one fifth of participants living below the poverty line engaged in physical activity, compared with one third of those above the poverty line, provides evidence of a substantial gap in one of important preventive health behaviors. Physical activity is widely recognized as a protective factor against a range of chronic diseases and as a contributor to both physical and mental health. The observed gap is consistent with international findings indicating that populations experiencing economic hardship are less likely to engage in structured physical activity [26]. This disparity may be explained by multiple barriers, including lack of leisure time due to long working hours or multiple roles in large families, limited availability of appropriate facilities and public spaces in many Arab localities, the financial costs associated with gym memberships or equipment, and cultural barriers, particularly for women. Previous studies on the Arab population in Israel have shown that social norms and restrictions on women’s free movement in public spaces constitute a major barrier to physical activity, especially in more conservative communities [27,28]. One of the noteworthy findings of this study is the absence of significant differences in smoking prevalence between groups defined by economic status, a pattern that diverges from that observed in many high‑income countries, where smoking is more prevalent among low socioeconomic groups. This result may reflect the widespread normalization of smoking across economic strata in Arab society, a phenomenon documented in previous research. The particularly high smoking prevalence among Arab men in Israel has been repeatedly reported and is recognized as a key risk factor for cardiovascular disease and cancer [29]. The fact that smoking was associated with low health knowledge rather than with economic status suggests that it represents a culturally embedded behavior that is not directly determined by material resources. This finding highlights the need for culturally tailored smoking‑cessation interventions that focus on changing social norms and increasing awareness of health risks. The mediation analyses showed that health knowledge acts as a significant mediator in the association between economic status and nutritional status, SRH, physical activity, and smoking. This means that a substantial portion of the impact of poverty on health is explained by differences in health knowledge: individuals experiencing economic hardship tend to have lower levels of health knowledge, which in turn adversely affect their health status and health behaviors. This finding is consistent with theoretical models of health literacy, which emphasize the importance of the ability to obtain, process, and understand basic health information for making informed health decisions [30,31]. Populations in economic distress tend to have lower health literacy due in part to lower educational attainment, limited access to high‑quality information sources, and language and cultural barriers [32]. In the Israeli context, these barriers are exacerbated by the relative scarcity of health‑education materials in Arabic, the limited number of Arabic‑speaking health professionals, and digital gaps that constrain access to online information [23,24]. The practical implications of this finding are substantial: improving health knowledge may serve as an effective intervention strategy for reducing health disparities. Culturally adapted health education programs delivered through community institutions such as clinics, schools, and religious and cultural centers may contribute to improving health behaviors and health status even among populations facing economic hardship. At the same time, the findings point to two important resilience factors: small family size and higher educational attainment. These results enhance understanding of the conditions under which economic status affects health and indicate complex mechanisms of interaction between sociodemographic variables. The study shows that the association between economic status, chronic morbidity, and health perception is significant only among small families and not among large families. This finding points to a complex role of family structure. In small families, living above the poverty line confers a clear health advantage, likely due to more favorable distribution of economic resources among fewer family members. In large families, by contrast, households classified as above the poverty line may still experience substantial financial strain, which can offset the potential health benefits of better economic status. This pattern is particularly relevant to the Arab population in Israel, which is characterized by relatively large family size, especially in Bedouin and rural communities. In such households, income that formally places the family above the poverty line may nonetheless be insufficient to meet basic needs for all members, particularly health‑related expenditures such as supplemental insurance, medications, and services not fully covered by the national health basket. The finding that an association between economic status and physical activity was observed only among participants with a completed secondary education or an academic degree underscores the role of education as a cultural resource that enables the translation of economic advantage into health‑promoting behavior. Higher education provides not only knowledge about the importance of physical activity but also organizational skills, the ability to access information and resources, and a stronger orientation toward health and quality of life. Among individuals with low educational attainment, economic advantage alone does not appear to translate into increased participation in physical activity, likely due to persistent perceptual, cultural, and structural barriers. This result is consistent with international evidence showing that education is a powerful determinant of health behaviors, sometimes even stronger than income [7,20]. In the Israeli context, educational levels in the Arab population have increased substantially in recent decades, yet large gaps remain compared to the Jewish population, particularly in rural areas and among women in more conservative communities [22]. Taken together, the findings of this study call for careful attention to the structural and systemic barriers faced by the Arab population in accessing high quality health services. Although Israel is characterized by universal health insurance under the National Health Insurance Law, substantial gaps exist in the realization of formal entitlements. First, co‑payments for medications, tests, and treatments constitute a major financial barrier for low-income families. For a family with several members suffering from chronic conditions, monthly co‑payments amounting to significant sums may be unaffordable, leading to treatment avoidance or non‑adherence to prescribed medications [33]. The high reported adherence to daily medication use, without differences between economic groups, may reflect the great importance participants attribute to pharmacological treatment, but does not necessarily indicate equal access to all required interventions. Second, supplemental health insurance, which covers services and tests beyond the basic national basket, is less prevalent among the Arab population due to its cost. Documented gaps in the uptake of supplemental insurance between the Arab and Jewish populations constitute an important source of inequality in access to advanced treatments, diagnostic technologies, and complementary health services [34]. Third, the physical availability of health services is limited in many Arab localities, particularly in peripheral regions. Shortages of specialty clinics, diagnostic centers, and mental‑health services within these localities necessitate travel to urban centers, imposing financial and time costs that many low‑income families cannot afford. In addition, the limited number of Arabic‑speaking professionals across health disciplines and the scarcity of culturally adapted informational materials impede effective communication and understanding of medical instructions. Fourth, preventive and health‑promotion services, such as healthy‑nutrition workshops, smoking‑cessation programs, and community based physical activity initiatives are often less available or less culturally tailored in Arab communities. The finding of lower health knowledge and lower perceived nutritional knowledge among participants living below the poverty line points to the need for intensified investment in community-based health education programs. Conclusion and recommendations This study provides comprehensive empirical evidence for the complex relationship between economic status, health status, and health behaviors in the Arab population in Israel. The findings indicate substantial health inequities shaped by multiple mechanisms, including health knowledge, family size, and educational attainment. Identifying health knowledge as a key mediating factor underscores the potential of educational interventions to reduce health gaps. Considering the findings, several practical recommendations emerge. First, culturally adapted health education programs should be developed and implemented through community institutions such as schools, cultural centers, and community‑based health services. Second, the availability of health services in Arab localities should be expanded, and the number of Arabic‑speaking professionals in various health disciplines should be increased. Third, the financial burden of co‑payments should be reduced, and access to supplemental health insurance should be improved. Fourth, health‑promoting infrastructures and environments should be developed in Arab communities, including culturally appropriate facilities for physical activity, particularly for women, walking paths, green spaces, and parks. Fifth, culturally tailored smoking‑cessation interventions should be designed and implemented. Sixth, policies aimed at reducing socioeconomic ranking gaps between Arab and Jewish localities and at improving physical and social infrastructures should be advanced. Future research should examine the effectiveness of existing interventions, deepen understanding of the cultural and structural determinants of health behaviors, and assess the extent to which improving health knowledge and health literacy through targeted interventions leads to sustained improvements in health indicators and health behaviors over time. Study limitations Several limitations of the present study should be acknowledged. First, the cross‑sectional design does not allow for definitive causal inferences, and bidirectional or reverse relationships may exist; for example, poor health may lead to economic distress through reduced work capacity and increased treatment costs. Second, reliance on self‑reported measures (such as chronic disease and SRH) may introduce recall bias or social desirability bias, although such indicators are widely accepted and validated in health research. Third, the study did not include detailed information on specific types of chronic diseases, which could have provided deeper insights into the associations under investigation. Fourth, additional variables that may contribute to explaining the observed variance were not measured, such as social support, stress levels, and access to specific services. Abbreviations SRH : Self-rated health - SRH HESPI : Health and environment survey of Palestinian citizens of Israel CBS : Central bureau of statistics PSU: Preliminary sampling units BMI: Body mass index Declarations All participants were informed about the study and provided informed consent, and their participation was voluntary and confidential. Ethics approval and consent to participate This study was approved by The Ethical Committee of the Zefat Academic College (petition No. 48/61/15). The study complies with the requirements for conducting research involving human subjects, as defined in the Ethics Regulations of the Zefat Academic College (January 2013) and in accordance with the guidelines the College. The participants were asked if they accept to participate in the survey. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The author declares that he has no competing interests Funding This work was supported by a grant from the Galilee Society – The Arab National Society for Research and Health Services, PO. Box 330, Shefa-Amr 20200, Israel. Tel. + 972 4 986117. Email- [email protected] ; http://www.gal-soc.org/ . Authors' contributions MK conceived and designed the study, analyzed the data, and drafted the manuscript. MK formulated he research main questions, interpreted the data, and wrote the manuscript. MK reviewed the final version and approved the final manuscript. Acknowledgements Not applicable References Central Bureau of Statistics. Statistical Abstract of Israel 2022. No. 73. Jerusalem (IL): Central Bureau of Statistics; 2022. Hadad Haj-Yahya N, Saif I, Fargeon B. Arab society and the coronavirus crisis: Entry data, effects, and recommendations for a stronger recovery [Hebrew]. Jerusalem (IL): The Israel Institute for Democracy; 2020. Endbal M, Karadi L, Pines R, Kasir N. Poverty and social gaps: Annual report: Annex table 2 [Hebrew]. Jerusalem (IL): National Insurance Institute; 2022. Sheikh-Muhammad A, Abu-Mukh-Zoabi L, Shehadeh M, Miaari S, Moadi F, Fahoum L. The reality of Arab women in Israel [Arabic]. Shefa-Amer (IL): The Galilee Society; 2012. Khatib M, Mansbach-Kleinfeld I, Abu-Kaf S, Ifrah A, Sheikh-Muhammad A. Correlates of psychological distress and self-rated health among Palestinian citizens of Israel: Findings from the Health and Environment Survey (HESPI). Israel J Health Policy Res. 2021;10(3). https://doi.org/10.1186/s13584-021-00439-z State Comptroller. Report of the State Comptroller. Jerusalem (IL): State Comptroller and Ombudsman; 2022. Cutler DM, Lleras-Muney A. Understanding differences in health behaviors by education. J Health Econ. 2010;29(1):1–28. https://doi.org/10.1016/j.jhealeco.2009.10.003 Adler NE, Rehkopf DH. US disparities in health: Descriptions, causes, and mechanisms. Annu Rev Public Health. 2008;29:235–52. https://doi.org/10.1146/annurev.publhealth.29.020907.090852 Phelan JC, Link BG, Tehranifar P. Social conditions as fundamental causes of health inequalities: Theory, evidence, and policy implications. J Health Soc Behav. 2010;51(Suppl):S28–40. https://doi.org/10.1177/0022146510383498 Giskes K, van Lenthe F, Avendano-Pabon M, Brug J, Mackenbach J. A systematic review of environmental factors and obesogenic dietary intakes among adults: Are we getting closer to understanding obesogenic environments? Obes Rev. 2011;12(5):e95–106. https://doi.org/10.1111/j.1467-789X.2010.00769.x Rehm CD, Peñalvo JL, Afshin A, Mozaffarian D. Dietary intake among US adults, 1999–2012. JAMA. 2016;315(23):2542–53. doi:10.1001/jama.2016.7491 Central Bureau of Statistics. Statistical Abstract of Israel 2012. No. 63, chap. 6, Health. Jerusalem (IL): Central Bureau of Statistics; 2012. Kish L. A procedure for objective respondent selection within a household. J Am Sociol Assoc. 1949;44:380–7. https://doi.org/10.1080/01621459.1949.10483314 Benson D, Catania JA. Random selection in a national telephone survey: A comparison of the Kish, next-birthday, and last-birthday methods. J Off Stat. 2000;16(1):53–71. Sheikh Muhammad A, Khatib M, Rezek-Marjieh S. The Palestinians in Israel: 5th socio-economic survey. Shefa-Amr (IL): The Galilee Society, Rikaz Data Bank; 2017. National Insurance Institute. Research administration and planning: Poverty and social gaps: Annual report. Jerusalem (IL): National Insurance Institute; 2015. Hayes AF. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. 3rd ed. New York (NY): Guilford Press; 2022. Braveman P, Gottlieb L. The social determinants of health: It is time to consider the causes of the causes. Public Health Rep. 2014;129(Suppl 2):19–31. https://doi.org/10.1177/00333549141291S206 Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social determinants of health and diabetes: A scientific review. Diabetes Care. 2021;44(1):258–79. doi: 10.2337/dci20-0053 Braveman P, Egerter S, Williams DR. The social determinants of health: Coming of age. Annu Rev Public Health. 2011;32:381–98. https://doi.org/10.1146/annurev-publhealth-031210-101218 Williams DR, Mohammed SA. Discrimination and racial disparities in health: Evidence and needed research. J Behav Med. 2009;32(1):20–47. https://doi.org/10.1007/s10865-008-9185-0 Daoud N, Soskolne V, Mindell JS, Roth MA, Manor O. Ethnic inequalities in health between Arabs and Jews in Israel: The relative contribution of individual-level factors and the living environment. Int J Public Health. 2018;63(3):313–23. https://doi.org/10.1007/s00038-017-1065-3 Baron-Epel O, Weinstein R, Haviv-Messika A, Garty-Sandalon N, Green MS. Individual-level analysis of social capital and health: A comparison of Arab and Jewish Israelis. Soc Sci Med. 2008;66(4):900–10. https://doi.org/10.1016/j.socscimed.2007.10.025 Saabneh AM. Arab–Jewish gap in life expectancy in Israel. Eur J Public Health. 2016;26(3):433–8. https://doi.org/10.1093/eurpub/ckv211 Muhsen K, Green MS, Soskolne V, Neumark Y. Inequalities in non-communicable diseases between the major population groups in Israel: Achievements and challenges. Lancet. 2017;389(10088):2531–41. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)30574-3/abstract?rss=yes= Chastin SFM, Van Cauwenberg J, Maenhout L, et al. Inequality in physical activity: Global trends by income inequality and gender in adults. Int J Behav Nutr Phys Act. 2020;17:142. https://doi.org/10.1186/s12966-020-01039-x Merom D, Sinnreich R, Aboudi V, Kark JD, Nassar H. Lifestyle physical activity among urban Palestinians and Israelis: A cross-sectional comparison in the Palestinian–Israeli Jerusalem risk factor study. BMC Public Health. 2012;12:90. https://doi.org/10.1186/1471-2458-12-90 Daoud N, Alfayumi-Zeadna S, Jabareen YT. Barriers to health care services among Palestinian women denied family unification in Israel. Int J Health Serv. 2018;48(4):776–97. https://www.jstor.org/stable/48513035 Ministry of Health. The health minister report on smoking in Israel 2024 [Hebrew]. Jerusalem (IL): Ministry of Health; 2025 [cited 2025 Dec 12]. Available from: https://www.gov.il/he/pages/03062025-01 Stormacq C, Van den Broucke S, Wosinski J. Does health literacy mediate the relationship between socioeconomic status and health disparities? Integrative review. Health Promot Int. 2019;34(5):e1–17. https://doi.org/10.1093/heapro/day062 Berkman ND, Sheridan SL, Donahue KE, Halpern DJ, Crotty K. Low health literacy and health outcomes: An updated systematic review. Ann Intern Med. 2011;155(2):97–107. DOI: 10.1059/0003-4819-155-2-201107190-00005 Schillinger D, Grumbach K, Piette J, Wang F, Osmond D, Daher C, et al. Association of health literacy with diabetes outcomes. JAMA. 2002;288(4):475–82. doi:10.1001/jama.288.4.475 Simon-Tuval T, Triki N, Chodick G, Greenberg D. Determinants of cost-related nonadherence to medications among chronically ill patients in Maccabi Healthcare Services, Israel. Value Health Reg Issues. 2014;4:41–6. https://doi.org/10.1016/j.vhri.2014.06.010 Fialco S, Laron M, Maoz Breuer R. Health service use, attitudes and perceptions towards the health system: A comparison of residents of Israel’s periphery and its center [Hebrew]. Jerusalem (IL): Myers-JDC-Brookdale Institute; 2024. Report No.: S-226-24. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8369758","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":563600870,"identity":"70340689-5a10-4aba-8554-7a546396e887","order_by":0,"name":"Mohammad Khatib","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACCQkgkdjAkMDAwNzAzFAB5DEzNxDSwtgA0cLY2MxwBqSFkQgtjDAtjG0gMQJaJGc3P3/wcAdDHj/7wfbHhfNqo/nbgVp+VGzDqUVa5phhQ+IZhmLJnsTG5pnbjufOOAy0tufMbZxa5CQSgFraGBI3HABq4d12LLcBqIWZsQ2flvSPYC37zz8EaplzLHc+IS3SEjlQWyRAtjTU5G4gpEVyRk7hjMQzEokzbjxsnM1z7EDuRqCWg/j8InEjfcPHnztsEvv7kw985qmpy513/vDBBz8qcGuB6YQxDoPJA4TUI4M6UhSPglEwCkbBCAEAqsljeDZInyoAAAAASUVORK5CYII=","orcid":"","institution":"The Galilee Society","correspondingAuthor":true,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Khatib","suffix":""}],"badges":[],"createdAt":"2025-12-15 20:23:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8369758/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8369758/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":99191348,"identity":"10e4b44f-af15-4961-b1e3-86dcf6511b80","added_by":"auto","created_at":"2025-12-30 00:55:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":98466,"visible":true,"origin":"","legend":"\u003cp\u003eThe mediating role of general health knowledge in the relationship between economic status and BMI, SRH, physical activity, and smoking Note: Values on arrows: B(SE), values within rectangles: R\u003csup\u003e2\u003c/sup\u003e / Negelkerke’s R\u003csup\u003e2\u003c/sup\u003e, C = total effect for continuous outcomes, C’ = direct effect. *p\u0026lt;.05, **p\u0026lt;.01, ***p\u0026lt;.001\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8369758/v1/878b76f678de64edf0035dd5.png"},{"id":99318392,"identity":"8230c4d6-ad0f-4757-97a2-a2fbc482c65d","added_by":"auto","created_at":"2025-12-31 16:33:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1267283,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8369758/v1/98953741-f520-47fc-a492-f70ebca8d444.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Relationship Between Economic Status, Poverty, and Health among Arabs in Israel","fulltext":[{"header":"Background","content":"\u003cp\u003eArabs in Israel, constituting 21% of the country\u0026rsquo;s citizens, are recognized as an indigenous population with individual civil rights, yet they encounter systemic disadvantages relative to Jewish citizens [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These disparities are evident in multiple spheres, including socioeconomic status, employment, education, and political and social inclusion [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In 2021, 38.8% of Arabs in Israel lived below the poverty line, 49% among Arab children and 38.9% among elderly Arabs compared to 11.9% among non-Orthodox Jews overall, 13.2% for children, and 15.3% for the elderly [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The persistent poverty among Arab communities is further intensified by limited government investment and underdevelopment in infrastructure, health services, and educational systems within Arab municipalities [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As a result, Arabs in Israel consistently report poorer health outcomes and lower self-rated health (SRH) in comparison to the Jewish majority [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEmployment rates among Arab women in Israel are markedly lower than those of women in the general population, standing at 37% compared to 77%, respectively [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This employment gap is largely shaped by structural and systemic barriers, including residential segregation, institutional discrimination, limited access to public transportation, and insufficient childcare options. For instance, in 2020, only 8% of daycare subsidies were allocated to the Arab population, even though Arab toddlers represented 24% of all toddlers in Israel [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe relationship between economic status, particularly poverty, and health outcomes has been a central theme in public health research. Extensive evidence across different populations highlights that economic disparities profoundly shape health through multiple pathways, influencing both physical and mental health indicators, health behaviors, and overall well-being. Individuals and families with low income consistently face poorer health outcomes and limited access to medical services, preventive care, and health-promoting resources compared to those with higher socioeconomic status.\u003c/p\u003e \u003cp\u003eMultiple studies have documented persistent health disparities associated with economic status. A comprehensive analysis by Cutler and Lleras-Muney (2010), based on data from diverse populations, demonstrated that individuals with lower socioeconomic status exhibit poorer health outcomes compared to those with higher economic standing [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These disparities are reflected across multiple health indicators, including higher rates of chronic diseases, reduced life expectancy, and increased prevalence of mental health disorders. Access to healthcare is a key determinant underpinning these outcomes. Adler and Rehkopf (2008), in their examination of health disparities in the United States, emphasized the constraining role of economic factors in healthcare accessibility [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Individuals from low-income backgrounds often encounter multiple barriers to medical services, such as financial limitations, inadequate healthcare infrastructure in disadvantaged areas, and lack of health insurance coverage. These barriers contribute to delayed diagnoses and treatment, thereby exacerbating health conditions and diminishing overall well-being.\u003c/p\u003e \u003cp\u003eThe link between poverty and health behaviors has also been extensively documented. Phelan, Link, and Tehranifar (2010) found that individuals from lower socioeconomic backgrounds are more likely to smoke than those with higher incomes [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Economic hardship and chronic stressors associated with poverty may contribute to elevated smoking rates, as smoking often functions as a coping mechanism. Economic status similarly influences physical activity. Giskes et al. (2010) reported that individuals from lower socioeconomic strata tend to have limited access to recreational facilities, safe public spaces, and affordable sports programs, resulting in lower physical activity levels and increased prevalence of obesity and related health conditions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNutritional behaviors are likewise shaped by economic constraints. Rehm et al. (2016), in their investigation of dietary intake among U.S. adults, found that individuals from low-income households often have limited access to nutritious foods due to financial barriers [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consequently, they tend to consume more inexpensive, processed, and less nutritious products, which heightens their risk of obesity, diabetes, and cardiovascular disease.\u003c/p\u003e \u003cp\u003eThis study explores whether and how sociodemographic factors influence the relationship between economic status and health outcomes, SRH, and health behaviors among Arabs in Israel. It also examines whether general or specific health knowledge mediates or moderates this relationship.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design and population\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study is based on data collected from the Health and Environment Survey among Arabs in Israel (HESPI), conducted by Rikaz \u0026ndash; the Applied Social Research Center of the Galilee Society \u0026ndash; between November 2015 and February 2016. The study population consisted of all Arabs households residing in Israel during the year 2015.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThe sample\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA three-stage stratified cluster sampling design utilizing systematic random sampling was implemented. The sampling frame encompassed segregated Arab municipalities and mixed Arab\u0026ndash;Jewish cities, and enumeration areas were classified according to the Israeli Central Bureau of Statistics (CBS) 2008 Population Census. These enumeration areas functioned as the primary sampling units (PSUs) [12].\u003c/p\u003e\n\u003cp\u003eIn the first sampling stage, 75 enumeration areas were selected through systematic random sampling. In the second stage, 30 households were randomly drawn from each selected area. In the third stage, a single individual aged 18 years or older was selected from each household using Kish selection tables [13,14] to participate in in-depth interviews. Stratification by gender and age was applied to the study population.\u003c/p\u003e\n\u003cp\u003eThe sample size was determined to provide sufficient statistical power for comparing participants with and without one or more chronic conditions. Based on an earlier reported prevalence of 14.5% for the presence of one or more chronic conditions, the sample size was estimated at 2,250 households [15].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collection\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSystematic sampling was used to recruit households within each enumeration area until 30 households were reached. A household member aged 18 years or older was selected for interview. If the selected individual was unavailable, interviewers made one or two additional visits to complete the questionnaire. Quality control procedures included review of completed questionnaires, field reports, and interviewer comments by the field coordinator.\u003c/p\u003e\n\u003cp\u003eOf 2,246 sampled households, 2,018 participated in the study (response rate: 89.8%). Data was collected about total of 9,063 individuals (all families members), and 2,018 selected adults aged 18 or older (971 men and 1,047 women) completing in-depth follow-up interviews.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThe questionnaire\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA socio-demographic questionnaire was developed ad hoc for the present study. It included variables such as gender, age, educational attainment, geographical district, and household income. Income data was used to determine whether the participant classified as below or above the national poverty line[1]. The participant was considered below the poverty line if his\\her total net monthly income was less than 2,526 NIS, according to the official poverty threshold for 2015 [16].\u003c/p\u003e\n\u003cp\u003eA health-related questionnaire was also constructed ad hoc and included items assessing selected health behaviors (e.g., cigarette and waterpipe (Nargila) smoking, physical activity), self-assessed health knowledge, presence of chronic diseases, as well as anthropometric measures (weight and height). In addition, participants were asked to provide a Self-Rated Health (SRH) score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study included 2,041 Arab adults in Israel, comprising 990 men (48.5%) and 1,051 women (51.5%). Participants ranged in age from 18 to 94 years (M = 41.0 years, SD = 16.10). The majority were Muslim (81.7%), resided in the northern district (72%), and lived in Arab municipalities (87%). Settlement size distribution was as follows: large settlements (53%), medium-sized settlements (27%), and small settlements (20%). Most participants were married (77%), with an average household size of 4.0 people (SD = 2.06). Educational attainment varied: less than secondary education (38%), secondary education (26%), high school matriculation certificate (23%), and academic education (12%). Detailed demographic characteristics are presented in Table 1.\u003c/p\u003e\n\u003cp\u003eParticipants living below the poverty line differed significantly from those above the poverty line across multiple demographic characteristics. Those below the poverty line were older, had larger households, and a higher proportion were widowed. They also had lower educational attainment and lower employment rates. Additionally, a higher proportion of participants below the poverty line were Muslim and resided in southern Israel compared to those above the poverty line.\u003cbr\u003eTable 1. Demographic characteristics of the participants* (\u003cem\u003eN\u003c/em\u003e = 2041)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eTotal sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eBelow poverty line\u003c/p\u003e\n \u003cp\u003e(n = 908)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eAbove poverty line\u003c/p\u003e\n \u003cp\u003e(n = 847)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eDifference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eAge (years) M (SD) (range: 18-94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e40.90 (16.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e41.64 (16.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e38.59 (14.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et(1738.88) = 4.12, p\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eFamily size M (SD) (range: 1-14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e4.32 (2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e4.68 (2.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e4.22 (1.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et(1706.66) = 4.74, p\u0026lt;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eGender n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1051 (51.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e477 (52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e416 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eZ = 1.43\u003c/p\u003e\n \u003cp\u003ep = .152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e990 (48.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e431 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e431 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eAge categories n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e18-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e314 (15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e137 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e144 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(4)=26.45\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e25-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e527 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e208 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e252 (29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e35-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e480 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e245 (27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e181 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e45-59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e415 (20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e176 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e185 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003e60+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e305 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e142 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e85 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eMarital status n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e303 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e142 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e133 (15.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(3)=37.80\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eMarried, engaged\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1552 (76.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e665 (73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e679 (81.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSeparated, divorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e40 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e23 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e8 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e129 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e72 (8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e18 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eEducation level n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eLess than secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e776 (38.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e405 (45.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e234 (27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(3)=146.93\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSecondary certification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e521 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e261 (29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e191 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eHigh school, matriculation certificate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e472 (23.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e182 (20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e233 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eAcademic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e250 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e46 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e187 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eIn labor force n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1066 (52.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e418 (46.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e555 (66.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ = 8.26\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eEmployed from labor force n (%) (from n= 1066)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e975 (91.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e359 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e541 (97.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ = 6.80\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eTotal employment n (%) (from n = 2041)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e975 (48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e359 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e541 (64.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ = 10.25\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eReligion n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1663 (81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e792 (87.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e624 (73.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=55.62\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eDruze\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e241 (11.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e82 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e132 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eChristian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e131 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e32 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e88 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eDistrict in Israel n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eNorth\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1477 (72.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e634 (68.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e664 (78.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=27.15\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep \u0026lt; .001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eCenter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e290 (14.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e118 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e98 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e274 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e166 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e85 (10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eType of residence n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eArab\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1778 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e798 (87.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e734 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eZ = 0.77\u003c/p\u003e\n \u003cp\u003ep = .441\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eMixed Jewish-Arab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e263 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e110 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e113 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSize of residence n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eLarge, over 15000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1086 (53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e472 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e447 (52.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(2)=5.61\u003c/p\u003e\n \u003cp\u003ep = .061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eMedium, 5000 to 15000\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e544 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e222 (24.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e236 (27.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 33px;\"\u003e\n \u003cp\u003eSmall, less than 5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e411 (20.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e214 (23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003col start=\"164\"\u003e\n \u003cli\u003e9.4)\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e*Percentages were calculated excluding missing data.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables and measures\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth Status Indicators\u003c/em\u003e: Body Mass Index (BMI) was calculated from self-reported height and weight. Chronic illness was measured as a dichotomous variable (yes/no). Medication use was assessed as a categorical variable with three levels: daily, occasionally, and none.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth Perception\u003c/em\u003e: Overall health perception was assessed using two items measured on a 5-point scale: (1) SRH (1 = very bad to 5 = very good) and (2) satisfaction with health status (1 = very low to 5 = very high). The items were strongly correlated (r = .85, p \u0026lt; .001), and mean scores were calculated to create a composite measure.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth Behaviors\u003c/em\u003e: Physical activity was measured as a dichotomous variable (yes/no). Smoking status was assessed using dichotomous variables for cigarette smoking and/or nargileh use (yes/no).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth Knowledge:\u0026nbsp;\u003c/em\u003eGeneral health knowledge: Eight items were measured on a 5-point scale (\u0026alpha; = .95). Mean scores were calculated, with higher scores indicating greater health knowledge. Perceived nutrition knowledge was assessed by the question \u0026quot;do you have information about healthy nutrition?\u0026quot; and using dichotomous variable (yes/no)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEconomic Status:\u003c/em\u003e Dichotomous variable indicating individual income below or above the 2015 Israeli poverty line threshold.\u003c/p\u003e\n\u003cp\u003eSociodemographic variables included gender, age, household size, marital status, educational level, employment status, religion, geographic district, type of locality (Arab municipality/mixed Arab-Jewish city), and locality size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData was analyzed with SPSS software ver 28. First, 286 participants did not provide information about their economic status. An examination of their health perception, health behaviors, and knowledge, revealed that they had a lower health related status than those who provided information about their economic status. A higher percentage of them reported a chronic illness (p \u0026lt; .001), and their general perception of health was lower (p \u0026lt; .001). Further, a lower percent of them reported having knowledge about nutrition (p \u0026lt; .001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were used to characterize the demographic profile of participants and the study\u0026apos;s dependent variables. Group comparisons (below/above the poverty line) were calculated using t-tests, chi-square tests, and Z-ratios for the significance of differences between two independent proportions. Next, the moderating role of demographic variables in the relationships between economic status and the study\u0026apos;s dependent variables was examined using (a) multiple linear regressions with interactions for continuous dependent variables, (b) multiple logistic regressions with interactions for dichotomous dependent variables and continuous demographic variables, and (c) analyses of variance for dichotomous dependent variables and categorical demographic variables. Significant interactions were interpreted using simple slopes and estimated marginal means. The study model was first examined using a series of multiple linear and logistic regressions for SRH and related behaviors, including demographic variables, economic status, and health-related knowledge. Mediation was examined using a series of PROCESS models (Hayes, 2022), specifically Model 4, with 5,000 bootstrap samples and 95% confidence intervals [17]. The significance level was set at p \u0026lt; .01 due to sample size.\u003c/p\u003e\n\u003cp\u003e[1] The poverty line in Israel in 2015 was 3,158 New Israeli Shekels, while the poverty line per standard person was 2,526 NIS (half of the median income), since according to the equivalence scale, one person is counted as 1.25 standard persons.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eDifferences by economic status\u003c/h2\u003e\n \u003cp\u003eApproximately half of the participants were classified as living below the poverty line (n\u0026thinsp;=\u0026thinsp;of 1755; 51.7%), while the remainder were above the poverty line (n\u0026thinsp;=\u0026thinsp;847; 48.3%). Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the distribution of study variables for the total sample and stratified by economic status. The mean BMI for the sample was 26.5, with no significant differences observed between economic groups. Approximately 40% of participants had a BMI in the normal range, another 40% were overweight, and around 17% were classified as obese.\u003c/p\u003e\n \u003cp\u003eA higher proportion of participants below the poverty line reported having a chronic illness compared to those above the poverty line (34% vs. 28%, respectively). Most of the participants in both groups adhered to daily medication for their chronic condition. SRH was lower among participants below the poverty line (M\u0026thinsp;=\u0026thinsp;3.78) compared to those above the poverty line (M\u0026thinsp;=\u0026thinsp;4.01). Similarly, a lower percentage of participants below the poverty line engaged in physical activity (20% vs. 33%). No significant group differences were detected for smoking status. Both general health knowledge (M\u0026thinsp;=\u0026thinsp;2.65 vs. M\u0026thinsp;=\u0026thinsp;2.87) and perceived nutrition knowledge (49% vs. 64%) were lower among participants living below the poverty line.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eHealth perception, related behavior, and knowledge, for the whole sample (N\u0026thinsp;=\u0026thinsp;2041), and by economic status (N\u0026thinsp;=\u0026thinsp;1755)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal sample\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBelow poverty line\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;908)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAbove poverty line\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;847)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDifference\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eChronic illness, overweight\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM (SD), range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.55 (4.57)\u003c/p\u003e\n \u003cp\u003e(16\u0026ndash;63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.64 (4.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.40 (4.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003et(1687)\u0026thinsp;=\u0026thinsp;1.05\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.294\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eBMI categories, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnderweight\u003c/p\u003e\n \u003cp\u003e(\u0026lt;\u0026thinsp;18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(4)\u0026thinsp;=\u0026thinsp;1.91\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal\u003c/p\u003e\n \u003cp\u003e(18-24.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e758 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e330 (37.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e326 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOverweight\u003c/p\u003e\n \u003cp\u003e(25-29.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e851 (43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e386 (44.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e340 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObese\u003c/p\u003e\n \u003cp\u003e(30-34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e258 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMorbid obesity\u003c/p\u003e\n \u003cp\u003e(35+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84 (4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChronic illness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e668 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e309 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e239 (28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u0026thinsp;=\u0026thinsp;2.63\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026thinsp;=\u0026thinsp;.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDaily medication for chronic illness, n (%)\u003c/p\u003e\n \u003cp\u003e(of n\u0026thinsp;=\u0026thinsp;485)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e442 (91.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e217 (91.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e140 (88.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eZ\u0026thinsp;=\u0026thinsp;1.29\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIrregularly, no\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth perception\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal SRH, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM (SD), range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.85 (1.06)\u003c/p\u003e\n \u003cp\u003e(1\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.78 (1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.01 (0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003et(1750.60) = -4.69\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth related behavior\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e524 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e183 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e278 (32.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u0026thinsp;=\u0026thinsp;5.98\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking (cigarettes or Nargila)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e672 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e294 (32.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e303 (36.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZ\u0026thinsp;=\u0026thinsp;1.48\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;=\u0026thinsp;.139\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth related knowledge\u003c/strong\u003e:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeneral health knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM (SD), range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.74 (0.99)\u003c/p\u003e\n \u003cp\u003e(1\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.65 (0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.87 (1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003et(1709.53) = -4.73\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived nutrition knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1106 (54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e442 (49.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e536 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u0026thinsp;=\u0026thinsp;6.11\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eDifferences by economic status and the demographic variables\u003c/h2\u003e\n \u003cp\u003eExploratory attempts were calculated to assess whether the relationships between economic status and health were moderated by the demographic variables. Two significant results were found: for family size and level of education.\u003c/p\u003e\n \u003cp\u003eFamily size was found to moderate the relationship between economic status and having a chronic illness (B\u0026thinsp;=\u0026thinsp;0.54, SE\u0026thinsp;=\u0026thinsp;0.13, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, OR\u0026thinsp;=\u0026thinsp;1.71, 95%CI\u0026thinsp;=\u0026thinsp;1.33, 2.19). Interpretation of the significant interaction with simple slopes has revealed that for smaller families, being an individual above the poverty line was related with lower odds for having a chronic illness (effect = -0.82, t = -5.57, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), while the relationship was not significant for larger families (effect\u0026thinsp;=\u0026thinsp;0.25, t\u0026thinsp;=\u0026thinsp;1.36, p\u0026thinsp;=\u0026thinsp;.175).\u003c/p\u003e\n \u003cp\u003eFurther, family size was found to moderate the relationship between individual economic status and perception of health (B = -0.23, SE\u0026thinsp;=\u0026thinsp;0.05, \u0026beta; = \u0026minus;\u0026thinsp;.13, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, 95%CI = -0.33, -0.13). Interpretation of the significant interaction with simple slopes has revealed that for smaller families, being above the poverty line was related with better SRH (effect\u0026thinsp;=\u0026thinsp;0.51, t\u0026thinsp;=\u0026thinsp;7.47, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), while the relationship was not significant for larger families (effect\u0026thinsp;=\u0026thinsp;0.05, t\u0026thinsp;=\u0026thinsp;0.70, p\u0026thinsp;=\u0026thinsp;.487).\u003c/p\u003e\n \u003cp\u003eLevel of education was found to moderate the relationship between economic status and physical activity (F(1, 1727)\u0026thinsp;=\u0026thinsp;5.86, p\u0026thinsp;=\u0026thinsp;.016, \u0026eta;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.003). Interpretation of the significant interaction with estimated marginal means has revealed that for more educated participants (with a full high school education or a college degree), being above the poverty line was related with higher odds for doing physical activity (F(1, 1727)\u0026thinsp;=\u0026thinsp;17.55, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u0026eta;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.010), while the relationship was not significant for less educated participants (with less than a full high school education) (F(1, 1727)\u0026thinsp;=\u0026thinsp;2.35, p\u0026thinsp;=\u0026thinsp;.125, \u0026eta;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.001).\u003c/p\u003e\n \u003cp\u003eThat is, a smaller family size was found to be a resilience factor for chronic illness and the perception of health. Level of education was found to be a resilience factor for proper physical activity.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eThe study model\u003c/h2\u003e\n \u003cp\u003eMultiple linear and logistic regression analyses were performed to examine associations SRH and related behaviors. Independent variables included economic status and health-related knowledge, while gender (coded as 1\u0026thinsp;=\u0026thinsp;male, 0\u0026thinsp;=\u0026thinsp;female), age, family size, and educational attainment (coded as 1\u0026thinsp;=\u0026thinsp;completion of full high school education or a college degree, 0\u0026thinsp;=\u0026thinsp;less than full high school education) were included as covariates. General health knowledge was hypothesized to be associated with all outcome variables; perceived nutrition knowledge was hypothesized to be associated with BMI and chronic illness and was entered accordingly into the relevant regression models. Due to insufficient variance, daily medication adherence for chronic illness was excluded from the analyses.\u003c/p\u003e\n \u003cp\u003eResults in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e show that all five models are significant. About 10% of the variance in BMI were explained by the study variables, such that for females, younger participants, and with greater health related knowledge, BMI was lower. BMI was unrelated with perceived nutrition knowledge. About 43% of the variance in the likelihood of chronic illness were explained by the study variables, such that the odds for a chronic illness were higher for older participants, living in small family, and for participants with less than a full high school education. Health related knowledge and perceived nutrition knowledge were unrelated with the odds for a chronic illness. About 33% of the variance in health perception were explained by the study variables, such that for younger participants, participants with a full high school education or a college degree, and with greater health related knowledge, SRH was better. Further, about 17% of the variance in the likelihood of physical activity were explained by the study variables, such that the odds for physical activity were higher for males, younger participants, participants with a full high school education or a college degree, participants whose economic status was above the poverty line, and with greater health related knowledge. Finally, about 37% of the variance in the likelihood of smoking were explained by the study variables, such that the odds for smoking were higher for males, younger participants, and with lower health related knowledge.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultiple linear and logistic regression models for SRH and related behavior, with economic status and health related knowledge (N\u0026thinsp;=\u0026thinsp;1755)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChronic illness\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSRH\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; (p)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (p)\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026beta; (p)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (p)\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (p)\u003c/p\u003e\n \u003cp\u003e(95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e.07 (.003)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92 (.545)\u003c/p\u003e\n \u003cp\u003e(0.72, 1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.04 (.070)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.67 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.32, 2.11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e13.39 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(10.25, 17.50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e.22 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.09 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.08, 1.11)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.48 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.96, 0.98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.99 (.008)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.98, 0.997)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFamily size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.06 (.024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.91 (.006)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.85, 0.97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.04 (.073)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.03 (.337)\u003c/p\u003e\n \u003cp\u003e(0.97, 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04 (.275)\u003c/p\u003e\n \u003cp\u003e(0.97, 1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.04 (.096)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.66 (.006)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.49, 0.89)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e.09 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.96 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.53, 2.52)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85 (.257)\u003c/p\u003e\n \u003cp\u003e(0.65, 1.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePoverty line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.01 (.679)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96 (.759)\u003c/p\u003e\n \u003cp\u003e(0.74, 1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.03 (.109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.54 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.21, 1.97)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.25 (.077)\u003c/p\u003e\n \u003cp\u003e(0.98, 1.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGeneral health knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026minus;\u0026thinsp;.13 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.89 (.101)\u003c/p\u003e\n \u003cp\u003e(0.77, 1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e.15 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.38 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(1.22, 1.56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.63 (\u0026lt;\u0026thinsp;.001)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(0.55, 0.72)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived nutrition knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e.01 (.829)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98 (.914)\u003c/p\u003e\n \u003cp\u003e(0.75, 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdj.R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdj.R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF(7, 1642)\u0026thinsp;=\u0026thinsp;26.37\u003c/p\u003e\n \u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(7)\u0026thinsp;=\u0026thinsp;621.51 p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eF(6, 1718)\u0026thinsp;=\u0026thinsp;144.94 p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;217.72 p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e(6)\u0026thinsp;=\u0026thinsp;536.20 p\u0026thinsp;\u0026lt;\u0026thinsp;.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote. For logistic regressions- Nagelkerke\u0026rsquo;s R\u003csup\u003e2\u003c/sup\u003e.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eIn light of these results (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), and the results shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, mediation was likely for BMI, total SRH, physical activity, and smoking - with general health knowledge as the mediator. It was examined with the Process procedure, model no.4, for continuous and dichotomous outcomes, controlling for gender, age, family size, and level of education. All four mediation models were found significant, with the indirect effects shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe indirect mediation effects for BMI, SRH, physical activity, and smoking, with general health knowledge (N\u0026thinsp;=\u0026thinsp;1755)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eIndirect effect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.15, -0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSRH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01, 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical activity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01, 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.11, -0.02\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\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents the mediated relationships. As may be observed, being above the poverty line was related to higher health related knowledge, which in turn was related to lower BMI, with a better SRH, with higher odds for physical activity, and with lower odds for smoking.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the relationship between economic status, health status, and health behaviors among the Arab population in Israel, with a particular focus on mediating and moderating mechanisms. The findings reveal a complex picture of health inequities shaped by multiple sociodemographic factors. The fact that more than half of the participants live below the poverty line reflects the harsh socioeconomic reality of the Arab population in Israel, as documented in official state reports by national institutions.\u003c/p\u003e\n\u003cp\u003eThe findings indicate a clear association between the individual economic status and key health indicators. The higher prevalence of chronic conditions and lower SRH among participants living below the poverty line is consistent with the international literature on the social determinants of health. Numerous studies have shown that poverty constitutes a major risk factor for chronic morbidity through multiple mechanisms, including exposure to chronic stress, neglect of health needs, limited access to high-quality health services, and risk behaviors [18-20].\u003c/p\u003e\n\u003cp\u003eIn the context of minority groups, the literature points to heightened severity of health inequities resulting from the accumulation of multiple structural barriers. Studies of ethnic minorities in the United States, the United Kingdom, and Australia report similar patterns, in which low socioeconomic status is combined with linguistic, cultural, and access barriers, generating a substantial burden of health distress [21]. Among the Arab population in Israel, this situation is further exacerbated by geographic concentration in the periphery, the low socioeconomic ranking of most Arab localities, and cultural–linguistic barriers within the health system [22,23]. Previous studies on the health of the Arab population in Israel have documented substantial gaps in key health indicators compared to the Jewish population, including shorter life expectancy, higher infant mortality, and increased prevalence of chronic diseases [24,25]. The present findings deepen this understanding by pointing to specific mechanisms through which economic status affects health in this population.\u003c/p\u003e\n\u003cp\u003eContrary to expectations and to some of the existing literature, no significant differences in body mass index (BMI) were found between participants living above and below the poverty line. This result deviates from the common pattern observed in many high‑income countries, where poverty is typically associated with obesity, particularly among women and children. Several possible explanations may account for this finding. First, it may reflect poverty\u0026nbsp;and nutrition paradox characteristic of societies undergoing nutritional transition, in which inexpensive, energy‑dense foods are widely available even to low‑income groups, resulting in high obesity rates across socioeconomic strata. Second, the official definition of the poverty line may not adequately capture the economic reality of Arab society, in which families classified as above the poverty line may still experience substantial economic hardship relative to the cost of living. Third, cultural factors and social norms regarding diet and body weight may outweigh the direct impact of economic status.\u003c/p\u003e\n\u003cp\u003eAt the same time, the findings indicate a high prevalence of overweight and obesity in the sample as a whole. This pattern is alarming in view of the well-known links between excess body weight and chronic diseases such as diabetes, hypertension, and cardiovascular disease. Poor nutritional status was found to be associated with low health knowledge irrespective of economic status, underscoring the importance of health education as a potential strategy to improve this situation.\u003c/p\u003e\n\u003cp\u003eThe finding that only one fifth of participants living below the poverty line engaged in physical activity, compared with one third of those above the poverty line, provides evidence of a substantial gap in one of important preventive health behaviors. Physical activity is widely recognized as a protective factor against a range of chronic diseases and as a contributor to both physical and mental health. The observed gap is consistent with international findings indicating that populations experiencing economic hardship are less likely to engage in structured physical activity [26]. This disparity may be explained by multiple barriers, including lack of leisure time due to long working hours or multiple roles in large families, limited availability of appropriate facilities and public spaces in many Arab localities, the financial costs associated with gym memberships or equipment, and cultural barriers, particularly for women. Previous studies on the Arab population in Israel have shown that social norms and restrictions on women’s free movement in public spaces constitute a major barrier to physical activity, especially in more conservative communities [27,28].\u003c/p\u003e\n\u003cp\u003eOne of the noteworthy findings of this study is the absence of significant differences in smoking prevalence between groups defined by economic status, a pattern that diverges from that observed in many high‑income countries, where smoking is more prevalent among low socioeconomic groups. This result may reflect the widespread normalization of smoking across economic strata in Arab society, a phenomenon documented in previous research. The particularly high smoking prevalence among Arab men in Israel has been repeatedly reported and is recognized as a key risk factor for cardiovascular disease and cancer [29]. The fact that smoking was associated with low health knowledge rather than with economic status suggests that it represents a culturally embedded behavior that is not directly determined by material resources. This finding highlights the need for culturally tailored smoking‑cessation interventions that focus on changing social norms and increasing awareness of health risks.\u003c/p\u003e\n\u003cp\u003eThe mediation analyses showed that health knowledge acts as a significant mediator in the association between economic status and nutritional status, SRH, physical activity, and smoking. This means that a substantial portion of the impact of poverty on health is explained by differences in health knowledge: individuals experiencing economic hardship tend to have lower levels of health knowledge, which in turn adversely affect their health status and health behaviors. This finding is consistent with theoretical models of health literacy, which emphasize the importance of the ability to obtain, process, and understand basic health information for making informed health decisions [30,31]. Populations in economic distress tend to have lower health literacy due in part to lower educational attainment, limited access to high‑quality information sources, and language and cultural barriers [32]. In the Israeli context, these barriers are exacerbated by the relative scarcity of health‑education materials in Arabic, the limited number of Arabic‑speaking health professionals, and digital gaps that constrain access to online information [23,24]. The practical implications of this finding are substantial: improving health knowledge may serve as an effective intervention strategy for reducing health disparities. Culturally adapted health education programs delivered through community institutions such as clinics, schools, and religious and cultural centers may contribute to improving health behaviors and health status even among populations facing economic hardship.\u003c/p\u003e\n\u003cp\u003eAt the same time, the findings point to two important resilience factors: small family size and higher educational attainment. These results enhance understanding of the conditions under which economic status affects health and indicate complex mechanisms of interaction between sociodemographic variables. The study shows that the association between economic status, chronic morbidity, and health perception is significant only among small families and not among large families. This finding points to a complex role of family structure. In small families, living above the poverty line confers a clear health advantage, likely due to more favorable distribution of economic resources among fewer family members. In large families, by contrast, households classified as above the poverty line may still experience substantial financial strain, which can offset the potential health benefits of better economic status. This pattern is particularly relevant to the Arab population in Israel, which is characterized by relatively large family size, especially in Bedouin and rural communities. In such households, income that formally places the family above the poverty line may nonetheless be insufficient to meet basic needs for all members, particularly health‑related expenditures such as supplemental insurance, medications, and services not fully covered by the national health basket.\u003c/p\u003e\n\u003cp\u003eThe finding that an association between economic status and physical activity was observed only among participants with a completed secondary education or an academic degree underscores the role of education as a cultural resource that enables the translation of economic advantage into health‑promoting behavior. Higher education provides not only knowledge about the importance of physical activity but also organizational skills, the ability to access information and resources, and a stronger orientation toward health and quality of life. Among individuals with low educational attainment, economic advantage alone does not appear to translate into increased participation in physical activity, likely due to persistent perceptual, cultural, and structural barriers. This result is consistent with international evidence showing that education is a powerful determinant of health behaviors, sometimes even stronger than income [7,20]. In the Israeli context, educational levels in the Arab population have increased substantially in recent decades, yet large gaps remain compared to the Jewish population, particularly in rural areas and among women in more conservative communities [22].\u003c/p\u003e\n\u003cp\u003eTaken together, the findings of this study call for careful attention to the structural and systemic barriers faced by the Arab population in accessing high quality health services. Although Israel is characterized by universal health insurance under the National Health Insurance Law, substantial gaps exist in the realization of formal entitlements. First, co‑payments for medications, tests, and treatments constitute a major financial barrier for low-income families. For a family with several members suffering from chronic conditions, monthly co‑payments amounting to significant sums may be unaffordable, leading to treatment avoidance or non‑adherence to prescribed medications [33]. The high reported adherence to daily medication use, without differences between economic groups, may reflect the great importance participants attribute to pharmacological treatment, but does not necessarily indicate equal access to all required interventions.\u003c/p\u003e\n\u003cp\u003eSecond, supplemental health insurance, which covers services and tests beyond the basic national basket, is less prevalent among the Arab population due to its cost. Documented gaps in the uptake of supplemental insurance between the Arab and Jewish populations constitute an important source of inequality in access to advanced treatments, diagnostic technologies, and complementary health services [34]. Third, the physical availability of health services is limited in many Arab localities, particularly in peripheral regions. Shortages of specialty clinics, diagnostic centers, and mental‑health services within these localities necessitate travel to urban centers, imposing financial and time costs that many low‑income families cannot afford. In addition, the limited number of Arabic‑speaking professionals across health disciplines and the scarcity of culturally adapted informational materials impede effective communication and understanding of medical instructions.\u003c/p\u003e\n\u003cp\u003eFourth, preventive and health‑promotion services, such as healthy‑nutrition workshops, smoking‑cessation programs, and community based physical activity initiatives are often less available or less culturally tailored in Arab communities. The finding of lower health knowledge and lower perceived nutritional knowledge among participants living below the poverty line points to the need for intensified investment in community-based health education programs.\u003c/p\u003e"},{"header":"Conclusion and recommendations","content":"\u003cp\u003eThis study provides comprehensive empirical evidence for the complex relationship between economic status, health status, and health behaviors in the Arab population in Israel. The findings indicate substantial health inequities shaped by multiple mechanisms, including health knowledge, family size, and educational attainment. Identifying health knowledge as a key mediating factor underscores the potential of educational interventions to reduce health gaps.\u003c/p\u003e\n\u003cp\u003eConsidering the findings, several practical recommendations emerge. First, culturally adapted health education programs should be developed and implemented through community institutions such as schools, cultural centers, and community‑based health services. Second, the availability of health services in Arab localities should be expanded, and the number of Arabic‑speaking professionals in various health disciplines should be increased. Third, the financial burden of co‑payments should be reduced, and access to supplemental health insurance should be improved. Fourth, health‑promoting infrastructures and environments should be developed in Arab communities, including culturally appropriate facilities for physical activity, particularly for women, walking paths, green spaces, and parks. Fifth, culturally tailored smoking‑cessation interventions should be designed and implemented. Sixth, policies aimed at reducing socioeconomic ranking gaps between Arab and Jewish localities and at improving physical and social infrastructures should be advanced. Future research should examine the effectiveness of existing interventions, deepen understanding of the cultural and structural determinants of health behaviors, and assess the extent to which improving health knowledge and health literacy through targeted interventions leads to sustained improvements in health indicators and health behaviors over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations of the present study should be acknowledged. First, the cross‑sectional design does not allow for definitive causal inferences, and bidirectional or reverse relationships may exist; for example, poor health may lead to economic distress through reduced work capacity and increased treatment costs. Second, reliance on self‑reported measures (such as chronic disease and SRH) may introduce recall bias or social desirability bias, although such indicators are widely accepted and validated in health research. Third, the study did not include detailed information on specific types of chronic diseases, which could have provided deeper insights into the associations under investigation. Fourth, additional variables that may contribute to explaining the observed variance were not measured, such as social support, stress levels, and access to specific services.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSRH\u003c/em\u003e\u003c/strong\u003e: Self-rated health - SRH\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHESPI\u003c/em\u003e\u003c/strong\u003e: Health and environment survey of Palestinian citizens of Israel\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCBS\u003c/em\u003e\u003c/strong\u003e: Central bureau of statistics\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePSU:\u003c/em\u003e\u003c/strong\u003ePreliminary sampling units\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBMI:\u003c/em\u003e\u003c/strong\u003eBody mass index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll participants were informed about the study and provided informed consent, and their participation was voluntary and confidential.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by The Ethical Committee of the Zefat Academic College (petition No. 48/61/15). The study complies with the requirements for conducting research involving human subjects, as defined in the Ethics Regulations of the Zefat Academic College (January 2013) and in accordance with the guidelines the College.\u003c/p\u003e\n\u003cp\u003eThe participants were asked if they accept to participate in the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares that he has no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by a grant from the Galilee Society \u0026ndash; The Arab National Society for Research and Health Services, PO. Box 330, Shefa-Amr 20200, Israel. Tel. +\u0026thinsp;972 4 986117. Email- [email protected] ; http://www.gal-soc.org/ .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMK conceived and designed the study, analyzed the data, and drafted the manuscript. MK formulated he research main questions, interpreted the data, and wrote the manuscript. MK reviewed the final version and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eCentral Bureau of Statistics. Statistical Abstract of Israel 2022. No. 73. Jerusalem (IL): Central Bureau of Statistics; 2022.\u003c/li\u003e\n \u003cli\u003eHadad Haj-Yahya N, Saif I, Fargeon B. 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Int J Public Health. 2018;63(3):313\u0026ndash;23. https://doi.org/10.1007/s00038-017-1065-3\u003c/li\u003e\n \u003cli\u003eBaron-Epel O, Weinstein R, Haviv-Messika A, Garty-Sandalon N, Green MS. Individual-level analysis of social capital and health: A comparison of Arab and Jewish Israelis. Soc Sci Med. 2008;66(4):900\u0026ndash;10. https://doi.org/10.1016/j.socscimed.2007.10.025\u003c/li\u003e\n \u003cli\u003eSaabneh AM. Arab\u0026ndash;Jewish gap in life expectancy in Israel. Eur J Public Health. 2016;26(3):433\u0026ndash;8. https://doi.org/10.1093/eurpub/ckv211\u003c/li\u003e\n \u003cli\u003eMuhsen K, Green MS, Soskolne V, Neumark Y. Inequalities in non-communicable diseases between the major population groups in Israel: Achievements and challenges. Lancet. 2017;389(10088):2531\u0026ndash;41. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(17)30574-3/abstract?rss=yes=\u003c/li\u003e\n \u003cli\u003eChastin SFM, Van Cauwenberg J, Maenhout L, et al. 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Report No.: S-226-24.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Arabs in Israel, Health disparities, Health knowledge, Physical activity, Self-rated health, Socioeconomic status, Poverty","lastPublishedDoi":"10.21203/rs.3.rs-8369758/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8369758/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eArabs in Israel, comprising about 21% of the population, are recognized as an indigenous minority with full citizenship rights, yet they face persistent structural disadvantages compared to Jewish citizens. These disparities are evident across socioeconomic, educational, employment, and health domains. High poverty rates, particularly among women, children, and the elderly, are aggravated by limited governmental investment in infrastructure, education, and health services. Arab women\u0026rsquo;s labor force participation remains notably low due to systemic barriers. Extensive evidence links socioeconomic status with health outcomes and behaviors. This study examines how sociodemographic factors and health knowledge influence the relationship between economic status, self-rated health, and health behaviors among Arabs in Israel\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study utilized data from the 2015\u0026ndash;2016 Health and Environment Survey among Arabs in Israel (HESPI). Employing a three-stage stratified cluster sampling of 2,018 households, face-to-face interviews gathered socio-demographic, economic, and health-related data. The final sample included 2,041 adults representing diverse socioeconomic and geographic groups within Arab communities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eApproximately half of participants lived below the poverty line. Those with lower economic status exhibited poorer self-rated health, higher prevalence of chronic illness, and lower engagement in physical activity, while smoking and BMI did not significantly differ by economic status. Family size moderated the relationships between economic status and both chronic illness and SRH, indicating that smaller families serve as a resilience factor. Educational attainment moderated the link between economic status and physical activity. Regression analyses revealed that gender, age, education, and health knowledge significantly predicted health outcomes and behaviors, with health knowledge mediating several associations.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe findings indicate that poverty is strongly associated with poorer health outcomes and behaviors among Arabs in Israel. Smaller family size and higher education act as resilience factors, mitigating these effects. Health knowledge plays a key mediating role, emphasizing the importance of socioeconomic empowerment and education in promoting health equity.\u003c/p\u003e","manuscriptTitle":"The Relationship Between Economic Status, Poverty, and Health among Arabs in Israel","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-30 00:55:05","doi":"10.21203/rs.3.rs-8369758/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":"d7282632-a861-4069-863e-e9f462d408c6","owner":[],"postedDate":"December 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-05T13:38:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-30 00:55:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8369758","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8369758","identity":"rs-8369758","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}