{"paper_id":"07aefd14-53cb-49d2-af78-e41338277c09","body_text":"Socio-Demographic Factors Influencing Obesity Among Ever-Married Jordanian Women of Reproductive Age: Insights from the 2023 Jordan Demographic and Health Survey | 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 Socio-Demographic Factors Influencing Obesity Among Ever-Married Jordanian Women of Reproductive Age: Insights from the 2023 Jordan Demographic and Health Survey Amr Ahmed Aly Ibrahim, Sara Hosny El-Farargy, Shadi Isac, Mahmoud Shaaban Abdelgalil This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7590700/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Journal of Health, Population and Nutrition → Version 1 posted 10 You are reading this latest preprint version Abstract Background Obesity prevalence has been rising globally, including in Jordan. This study aims to identify the factors influencing obesity rates among married Jordanian women aged 20–49 years, using data from the Jordan Demographic and Health Survey (JDHS). Methods The study analyzed data from the 2023 JDHS, encompassing a representative sample of 12,595 Jordanian women aged 15–49. Socioeconomic variables examined included age, education level, wealth index, urban or rural residence, and media consumption habits (television, radio, magazines/newspapers, internet usage) along with smoking status. Multivariate logistic regression was employed to determine the associations between these factors and obesity risk. Results Of the 4,048 married women included in the analysis, 1,697 (41.9%) had a normal BMI, while 2,351 (59.7%) were classified as obese. Multivariate analysis revealed that increasing age, listening to the radio less than once a week, daily internet use, and residing in Karak or Ajloun were significantly associated with higher odds of obesity. Conversely, reading newspapers or magazines at least once a week and daily cigarette smoking were linked to a reduced risk of obesity. No significant associations were observed between obesity and place of residence, wealth index, educational level, television viewing habits, or residence in other governorates. Conclusion With obesity rates continuing to rise, targeted health programs for Jordanian women of reproductive age are essential. National health initiatives should focus on promoting healthy lifestyle habits, addressing regional disparities, and encouraging balanced media consumption to mitigate obesity risk. Region-specific prevention and awareness campaigns are also vital for effective intervention. 1. Introduction Obesity has emerged as a rapidly growing global health crisis, particularly in low- and middle-income countries undergoing socioeconomic transitions. It is characterized by excessive fat accumulation, which poses significant health risks ( 1 ). The World Health Organization (WHO) now classifies obesity as a pandemic, with over 2 billion adults worldwide being overweight, and 677.6 million of them classified as obese ( 2 , 3 ). Women, in particular, face high rates of obesity, comprising 393.5 million, which places them at increased risk for numerous health issues, including cardiovascular diseases, type 2 diabetes, and certain cancers ( 2 , 4 ). Additionally, obesity among women of reproductive age is linked to challenges with conception, an elevated risk of miscarriage, and various complications during pregnancy, labor, and postpartum, contributing to higher rates of maternal morbidity and mortality ( 5 – 7 ). The COVID-19 pandemic has further complicated the landscape, amplified sedentary lifestyles and increased the demand for weight-loss surgeries, such as gastric sleeve procedures, as individuals struggle to manage weight in the face of lifestyle changes and limited access to physical activity( 8 ). Jordan, like other countries in the Middle East, has witnessed a significant rise in obesity rates, especially among women( 9 ). With 43.1% of Jordanian females considered obese compared to 28.2% of males, the trend has been steadily increasing at an annual rate of 1.38% over the last two decades ( 10 ). According to the Global Obesity Observatory, the prevalence of obesity among females is projected to reach 77.54% by 2060. Additionally, the economic burden of obesity is expected to rise significantly, with associated costs increasing from USD 850.48 million in 2019 to USD 8.97 billion by 2026( 11 ). Key contributing factors to obesity include dietary shifts, urbanization, changing marital norms, and a higher intake of processed foods and sugary beverages, all of which have fueled the regional obesity crisis ( 9 ). A study based on data from the 2009 Jordan Population and Family Health Survey (JPFHS) identified several factors associated with obesity over time, including age, residence in southern regions of Jordan, early marriage, parity, wealth status, and smoking ( 12 ). Similarly, an analysis of data from the 2017/18 JPFHS, which included 4,226 Jordanian women of reproductive age, highlighted additional obesity-related factors( 13 ). The study found that increasing age and residing in Tafilah were significantly associated with higher odds of obesity, while belonging to the wealthiest category, living in Maan or Aqaba, and daily smoking were linked to reduced odds of obesity ( 13 ). Despite previous research ( 12 , 13 ), obesity remains a significant and growing public health concern in Jordan. The rapidly evolving socio-economic, cultural, and lifestyle patterns in the region highlight the need for updated studies to reflect current trends. This study seeks to examine the socio-demographic factors associated with obesity among adult ever-married women in Jordan, utilizing the most recent data from the 2023 JPFHS. 2. Methods 2.1 Data collection Our study utilized data from 2023 JPFHS. The survey initially recruited a representative sample of 12,595 eligible women aged 15–49 from all 12 governorates in Jordan. Key data collected included anthropometric measurements, particularly body mass index (BMI), alongside socioeconomic and behavioral factors. 2.2 Inclusion criteria We included data from ever-married women aged 20–49 years with a reported BMI (kg/m²) measured in accordance with the guidelines of the Centers for Disease Control and Prevention ( 14 ). 2.3 Exclusion criteria We excluded women younger than 20 years old, those with missing BMI data, underweight women with a BMI < 18.5, and overweight women with BMI between 25–29.9. 2.4 Included variables We studied some socioeconomic and behavioral variables including Age (divided into five-year groups); type of residence: rural or urban; governorate of residence categorized as Mafraq, Ajloun, Amman, Zarqa, Karak, Tafiela, Madaba, Aqaba, Irbid, Balqa, Jarash, and Ma’an; wealth index as classified by the DHS survey into richest, richer, middle, poorer and poorest; educational level categorized as higher education, secondary education, primary education and no education; and frequency of listening to the radio, watching television, reading magazines or newspapers or frequency of internet usage categorized as at least once a week, less than once a week and not at all. We also added the frequency of smoking categorized as everyday smoking, some days smoking, and does not smoke. 2.5 Statistical analysis Analysis of data was done using SPSS version 24, running a weighted count for all analyses based on DHS recommendations ( 15 ). Sample weight was noted to be an eight-digit variable with six implied decimal places and then adjusted by dividing by 1,000,000. The results were reported as frequencies and percentages. We then performed multivariable logistic regression, presenting the results in the form of an adjusted odds ratio (AOR), with 95% confidence interval (CI). A p-value of less than 0.05 was considered statistically significant. 3. Results Data was collected from 4,048 Jordanian women aged 20–49, with 41.9% of the sample having normal BMI and 58.1% being obese ( Table 1 ) . Table 1 Characteristics of the included women according to BMI BMI Normal Obese Count Column N % Count Column N % Age in 5-year groups 20–24 238 14.0% 75 3.2% 25–29 360 21.2% 203 8.6% 30–34 404 23.8% 370 15.7% 35–39 329 19.4% 481 20.4% 40–44 219 12.9% 513 21.8% 45–49 147 8.6% 709 30.1% Highest educational level No education 44 2.5% 58 2.4% Primary 100 5.7% 224 9.5% Secondary 876 50.1% 1456 61.5% Higher 729 41.7% 631 26.6% Wealth index combined Poorest 407 23.3% 539 22.8% Poorer 342 19.6% 545 23.0% Middle 393 22.5% 494 20.9% Richer 272 15.5% 480 20.3% Richest 335 19.2% 309 13.1% Type of place of residence Urban 1589 90.8% 2159 91.1% Rural 160 9.2% 210 8.9% Frequency of reading newspaper or magazine Not at all 1290 73.8% 1852 78.2% Less than once a week 200 11.4% 246 10.4% At least once a week 259 14.8% 270 11.4% Almost every day 0 0.0% 0 0.0% Frequency of listening to radio Not at all 1236 70.7% 1661 70.1% Less than once a week 227 13.0% 330 13.9% At least once a week 286 16.3% 378 15.9% Almost every day 0 0.0% 0 0.0% Frequency of watching television Not at all 278 15.9% 368 15.5% Less than once a week 346 19.8% 438 18.5% At least once a week 1126 64.3% 1563 66.0% Almost every day 0 0.0% 0 0.0% Frequency of using internet last month Not at all 430 24.6% 480 20.3% Less than once a week 25 1.4% 40 1.7% At least once a week 45 2.6% 86 3.6% Almost every day 1249 71.4% 1764 74.5% Frequency smokes cigarettes Does not smoke 1568 89.6% 2171 91.7% Every day 158 9.0% 137 5.8% Some days 24 1.3% 60 2.5% Governorate Central region Amman 891 50.9% 988 41.7% Balqa 99 5.7% 154 6.5% Zarqa 220 12.6% 376 15.9% Madaba 26 1.5% 51 2.2% Northern region Irbid 297 17.0% 458 19.3% Mafraq 71 4.1% 84 3.5% Jarash 35 2.0% 62 2.6% Ajloun 23 1.3% 46 2.0% Southern Region Karak 26 1.5% 65 2.8% Tafiela 13 0.7% 20 0.9% Ma'an 23 1.3% 25 1.1% Aqaba 25 1.4% 37 1.6% The result showed that the highest proportion of obese participants was from the 35 to 49 years age group representing 72.3% of total obese women with the highest proportion between 45–49 representing 30.1%. However, 45% of normal BMI females were 25–34 years old with the highest proportion between 30–34. Among women with normal BMI, approximately half (50.1%) had completed their secondary education, 5.7% had only primary education, 41.7% had a higher learning degree, and about 2.5% were non-educated. On the other hand, of the obese population, 61.5% of them reached the secondary educational level, 9.5% were only primarily educated, 26.6% had a higher learning degree whereas 2.4% were non-educated. Regarding residence, about 90.8% of the normal BMI and 91.1% of the obese group lived in urban while 9.2% of the normal BMI group and 8.9% of the obese group lived in rural areas. Most of the normal BMI group and the obese group lived in: Amman with 50.9% in the normal BMI group and 41.7% in the obese group, Irbid with 17% in the normal BMI group and 19.3% in the obese group, and Zarqa with 12.6% in the normal BMI group and 15.9% in the obese group. Obesity was more predominant in the poorer group 23% followed by the poorest, middle, richer, and richest (22.8%, 20.9%, 20.3%, and 13.1% respectively). On the other hand, the normal BMI was predominant in the poorest group 23.3% followed by middle, poorer, richest, and richer (22.5%, 19.6%, 19.2%, and 15.5%, respectively). Most of the participants in both groups did not read magazines or newspapers at all with 73.8% in the normal BMI group and 78.2% in the obese group. Additionally, 11.4% in the normal BMI group and 10.4% in the obese group did less than once a week, while 14.8% in the normal BMI group and 11.4% in the obese group did at least once a week. Most of the participants in both groups did not listen to the radio at all with 70.7% in the normal BMI group and 70.1% in the obese group. Additionally,13% in the normal BMI group and 13.9% in the obese group listened to the radio less than once a week while 16.3% in the normal BMI group and 15.9% in the obese group listened to the radio at least once a week. 64.3% of the normal BMI group and 66% of the obese group watched television at least once a week. In contrast,19.8% of the normal BMI group and 18.5% of the obese group did less than once a week, while 15.9% of the normal BMI group and 15.5% of the obese group didn’t watch at all. The majority of the normal BMI group (71.4%) and the obese group (74.5%) used the internet last month almost every day, while 24.6% of the normal BMI group and 20.3% of the obese group didn’t use the internet at all. Regarding smoking, 89.6% of the normal BMI group and 91.7% of the obese group didn't smoke. In multivariable analysis ( Table 2 ) , we found that the odds of obesity increased with increasing the women's age, 25–29 years (OR: 2.061; 95%CI: 1.342–3.164; p = 0.001), 30–34 years (OR: 3.963; 95%CI: 2.601–6.037; p < 0.001), 35–39 years (OR: 6.517; 95%CI: 4.274–9.938; p < 0.001), 40–44 years (OR: 9.872; 95%CI: 6.372–15.294; p < 0.001), 45–49 years (OR: 20.930; 95%CI: 13.396–32.702; p < 0.001). Table 2 Predictors of women obesity Parameters Estimate Variables B Standard Error AOR 95% Confidence Interval for AOR Lower Upper P Value Age at 5 years 20–24 Reference 25–29 0.723 0.218 2.061 1.342 3.164 0.001 30–34 1.377 0.215 3.963 2.601 6.037 < 0.001 35–39 1.874 0.215 6.517 4.274 9.938 < 0.001 40–44 2.290 0.223 9.872 6.372 15.294 < 0.001 45–49 3.041 0.227 20.930 13.396 32.702 < 0.001 Highest Educational level No Education Reference Primary 0.483 0.394 1.621 0.748 3.514 0.220 Secondary 0.082 0.341 1.086 0.555 2.122 0.810 Higher -0.512 0.350 0.599 0.302 1.190 0.143 Governorate Aqaba Reference Ma'an -0.131 0.228 0.877 0.561 1.372 0.565 Tafiela 0.245 0.236 1.277 0.804 2.030 0.300 Karak 0.755 0.236 2.128 1.340 3.378 0.001 Ajloun 0.558 0.225 1.747 1.124 2.715 0.013 Jarash 0.352 0.219 1.422 0.925 2.184 0.108 Mafraq 0.004 0.248 1.004 0.617 1.634 0.987 Irbid 0.129 0.203 1.138 0.764 1.694 0.524 Madaba 0.379 0.233 1.461 0.926 2.307 0.103 Zarqa 0.372 0.199 1.451 0.981 2.145 0.062 Balqa 0.236 0.200 1.266 0.855 1.876 0.239 Amman -0.235 0.194 0.791 0.540 1.158 0.228 Wealth index Poorest Reference Poorer 0.230 0.173 1.259 0.897 1.767 0.183 middle 0.045 0.169 1.046 0.751 1.456 0.791 Richer 0.233 0.198 1.262 0.856 1.861 0.240 Richest -0.314 0.253 0.731 0.445 1.200 0.215 Type of place residence Urban Reference Rural -0.215 0.129 0.807 0.626 1.040 0.098 Frequency of using Internet last month Not at all Reference Less than once a week 0.316 0.473 1.372 0.543 3.470 0.504 At least once a week 0.518 0.296 1.678 0.939 3.001 0.081 Almost everyday 0.285 0.137 1.330 1.016 1.741 0.038 Frequency of watching Television Not at all Reference Less than once a week -0.067 0.191 0.936 0.643 1.360 0.727 At least once a week 0.103 0.148 1.109 0.829 1.484 0.487 Frequency of listening to Radio Not at all Reference Less than once a week 0.335 0.158 1.398 1.026 1.906 0.034 At least once a week 0.185 0.162 1.204 0.876 1.655 0.253 Frequency of reading newspaper or magazine Not at all Reference Less than once a week -0.345 0.233 0.708 0.448 1.119 0.139 At least once a week -0.480 0.146 0.619 0.465 0.823 0.001 Frequency smokes cigarettes Does not smoke Reference Everyday -0.669 0.189 0.512 0.354 0.742 < 0.001 Somedays 0.350 0.506 1.420 0.526 3.833 0.489 AOR: adjusted odds ratio Regarding media consumption, women who listened to the radio less than once a week were more likely to be obese (OR: 1.398; 95% CI: 1.026–1.906; p = 0.034) than those who never listened to the radio. However, there was no significant association between obesity and women who listened to the radio at least once a week (OR: 1.204; 95% CI: 0.876–1.655; p = 0.253). Also, we found that women who used the internet almost every day in the last month were more likely to be obese (OR: 1.330; 95%CI: 1.016–1.741; p = 0.038) than those who didn’t use it. In contrast, women who used the internet less than once a week (OR: 1.372; 95%CI: 0.543–3.470; p = 0.504) and at least once a week (OR: 1.678; 95%CI: 0.939–3.001; p = 0.081) showed no significant association with obesity. Regarding the frequency of reading newspapers or magazines, women who read at least once a week (OR: 0.619; 95%CI: 0.465–0.823; p = 0.001) were associated with a lower risk of obesity than those who didn’t read. However, reading less than once a week showed no significant association with obesity (OR: 0.708; 95%CI 0.448–1.119; p = 0.139). In terms of Smoking, we found that everyday smoking was significantly associated with lower odds of obesity (OR: 0.512; 95%CI: 0.354–0.742; p < 0.001) while some days smoking was not significantly associated with obesity (OR: 1.420; 95%CI: 0.526–3.833; p = 0.489). Geographical location also played a role, as living in Karak and Ajloun was significantly associated with higher odds of obesity (OR: 2.128; 95%CI: 1.340–3.378; p = 0.001), (OR: 1.747; 95%CI: 1.124–2.715; p = .013) respectively. On the other hand, we found no significant association between obesity and the education level, wealth index, type of place of residence, and frequency of watching television (p > 0.05). 4. Discussion To the best of our knowledge, this study is the first to explore the socio-demographic factors influencing obesity among ever-married adult women in Jordan, using data from the 2023 JDHS. The prevalence of obesity in Jordan has risen sharply in recent years. In 2009, 38.8% of individuals were classified as obese( 12 ), increasing to 51.3% by 2017/18 ( 13 ), and reaching 58.1% in 2023, as observed in this study. This upward trend may be partly driven by significant lifestyle changes and unhealthy eating behaviors following the COVID-19 pandemic ( 16 ), as lockdowns, distance learning, and remote work led to more sedentary routines. Our analysis identified a significant association between age and obesity, revealing that older women had considerably higher obesity rates. Specifically, women aged 44–49 were 20.9 times more likely to be obese compared to those aged 20–24. These findings are consistent with previous studies conducted in Jordan, including Al Nsour et al. 2008 ( 12 ), Bustami et al. 2021 ( 17 ), and Shaaban Abdelgalil et al. 2024 ( 13 ) as well as studies by Pengpid et al. in Iraq 2015 ( 18 ), and Chamieh et al. in Lebanon 2015 ( 19 ), all of which reported a significantly higher prevalence of obesity among older women. This trend is largely due to hormonal and psychological changes associated with aging. As women approach menopause, declining estrogen and increased androgens lead to muscle loss, increased abdominal fat, and altered body composition. Coupled with a sedentary lifestyle, these changes reduce energy expenditure and basal metabolic rate, increasing obesity risk ( 20 , 21 ). Aging also brings physical declines, such as sarcopenia, which impairs mobility, balance, and bone density. Regular physical activity can mitigate these effects, enhancing longevity and reducing metabolic and chronic disease risk ( 22 ). Additionally, psychological changes like increased stress, mood fluctuations, and anxiety often trigger emotional or stress-induced eating, further contributing to obesity risk ( 23 ). The analysis of obesity odds across regions revealed significant variations. Women in Karak, located in the southern region, and Ajloun, in the northern region, had significantly higher odds of obesity compared to those in Aqaba in the southern region. These findings differ from those of Shaaban Abdelgalil et al. 2024 in Jordan ( 13 ), which reported no significant differences in obesity odds between the central and northern governorates. However, the study noted that in the southern governorates, living in Tafilah in southern region was associated with an increased likelihood of obesity, whereas residing in Maan or Aqaba in southern region was linked to a decreased likelihood ( 13 ). The regional variations in obesity odds among Jordanian women can be explained by a combination of factors. Socioeconomic inequalities may restrict access to nutritious food options and quality healthcare, while cultural and lifestyle practices, such as consuming traditional high-calorie diets and engaging in minimal physical activity, further elevate obesity risks in certain areas( 24 , 25 ). Additionally, regions with lower levels of urbanization often lack the necessary infrastructure, such as parks and recreational facilities, to encourage physical activity, leading to more sedentary lifestyles( 26 ). Differences in healthcare access and public awareness also contribute, as areas with limited healthcare resources may fall short in providing adequate education and interventions for obesity prevention and management( 24 , 27 ). Our study found that certain media habits were linked to obesity. Women who listened to the radio less than once a week had higher odds of obesity compared to those who never listened. This finding is consistent with El-Qushayri et al. 2023 in Egypt ( 28 ). It is possible that individuals who listen to the radio may engage in less physical activity, leading to a more sedentary lifestyle, which is associated with obesity( 29 ). Furthermore, regular internet use was associated with higher odds of obesity compared to individuals who did not use the internet at all. This suggests that frequent internet use may limit the time available for physical activity( 29 , 30 ). A meta-analysis by Aghasi et al. found a linear dose-response relationship, indicating that each additional hour of internet use per day was associated with an 8% increase in the odds of overweight and obesity( 31 ). Conversely, our study found no association between watching television and obesity, which contrasts with studies in countries such as Ghana, Bangladesh, and Myanmar, where higher television consumption has been linked to obesity due to prolonged sedentary behaviors and exposure to unhealthy food advertisements ( 32 – 34 ). Our study suggests that appropriate actions should be taken through both traditional and social media, targeting obese Jordanian women to raise awareness about the negative effects of reduced physical activity, excessive radio listening, and frequent internet use. Smoking was significantly associated with lower odds of obesity among daily smokers in our sample. This finding aligns with previous studies by Al Nsour et al. 2009 in Jordan ( 12 ), Shaaban Abdelgalil et al. 2024 in Jordan( 13 ), Watanabe et al. 2016 in Japan ( 35 ) and Dare et al. 2015 in the UK ( 36 ). Some studies suggest that nicotine may contribute to appetite suppression, which could explain the link between smoking and a reduced risk of obesity ( 37 ). However, while smoking may be associated with lower obesity risk, it also carries significant health risks, including higher rates of central adiposity, cardiovascular disease, and cancer ( 37 , 38 ). Unlike some studies conducted in other countries, our findings did not show a significant association between education level and obesity among women, aligning with the study by Shaaban Abdelgalil et al. 2024 in Jordan ( 13 ). However, some studies have suggested that women with secondary education experience higher obesity rates compared to those with higher education. Research has often linked higher education to improved health outcomes, largely due to greater health literacy and socioeconomic advantages ( 39 – 41 ). Nevertheless, variations in findings across countries, including Ghana, Bangladesh, and Ethiopia, highlight the diverse influence of social determinants of health and the differing effects of education on lifestyle and diet ( 42 – 45 ). Our study found no significant association between place of residence and obesity among Jordanian women, consistent with the findings of Shaaban Abdelgalil et al. 2024 in Jordan ( 13 ). This contrasts with findings from some low- and middle-income countries, where urban living is often associated with higher obesity rates( 39 , 46 – 48 ). In our sample, both urban and rural areas exhibited similar obesity prevalence, likely due to shared dietary patterns and lifestyle similarities within Jordan’s relatively compact urban-rural structure. Our analysis did not find a significant association between wealth index and obesity, which aligns with the study by Shaaban Abdelgalil et al. 2024 in Jordan ( 13 ). However, wealth index is still a relevant factor, as obesity rates were higher among women in the poorer wealth quintiles, contrasting with findings in other countries where obesity is often more prevalent among the affluent( 42 , 49 – 51 ). In Jordan, socioeconomic factors may influence dietary choices, with lower-income individuals more likely to choose cheaper, calorie-dense foods over more nutritious alternatives. Additionally, cultural perceptions that associate larger body sizes with well-being may also contribute to obesity patterns among wealthier women in some Middle Eastern countries ( 47 , 50 , 52 ). 4.1 Limitations and Recommendations Our study utilized data from the 2023 JPFHS, focusing on ever-married women aged 20–49 years, but several limitations must be acknowledged. First, as a cross-sectional study, it cannot establish causal relationships between obesity and associated factors. Second, our analysis excluded specific groups, such as women younger than 20 years, and single women, which may have introduced selection bias and limited the generalizability of our findings. Third, the exclusion of comorbidities from the dataset, despite their potential role in influencing obesity, further limits the scope of our analysis. Additionally, the reliance on self-reported media consumption habits and internet usage may be subject to recall bias, potentially affecting the accuracy of the associations observed. Despite these limitations, our findings offer actionable insights into obesity determinants among Jordanian women. We recommend future research to include broader age groups and examine the role of comorbidities to provide a more comprehensive understanding of obesity risk factors. Longitudinal studies are particularly needed to establish causality and capture temporal trends in obesity and its predictors. From a policy perspective, targeted interventions addressing age-related increases in obesity are essential. These interventions should focus on promoting healthy lifestyles, particularly among women with frequent internet use or irregular physical activity. Additionally, regional disparities, such as higher obesity odds in Karak and Ajloun, call for tailored, location-specific programs. National initiatives emphasizing nutrition education, lifestyle modifications, and community-based support could play a pivotal role in curbing obesity rates among Jordanian women. 5. Conclusion In conclusion, older women, frequent internet users, those who listen to the radio less than once a week, and residents of Karak and Ajloun are associated with higher obesity rates among Jordanian women. Conversely, everyday smoking is linked to lower odds of obesity. No significant associations were observed with education level, wealth index, or place of residence. Targeted interventions focusing on age-specific and region-specific factors, along with strategies to promote healthier lifestyles, could help address obesity and its related health risks in Jordanian women. Declarations Conflicts of interest: All the authors declare no conflict of interest. Funding: All author(s) received no financial support for the research, authorship, and/or publication of this article. Ethics approval and consent to participate: Not applicable as we obtained the data from a publicly accessible database (https://dhsprogram.com/data/available-datasets.cfm). Consent for publication: not applicable. Availability of data and material: Data is available upon request from ICF International's website (https://dhsprogram.com/data/available-datasets.cfm). Acknowledgment: I would like to thank Dr. Mohamed Abd-ElGawad for his invaluable mentorship and unwavering support throughout my research journey. Authors’ Contributions: Amr Ahmed Aly Ibrahim played a key role in the study by validating the research concept, performing the data analysis, and writing the results section. Sara Hosny El-Farargy handled the data request from the Demographic and Health Survey, carried out data cleaning, and wrote the introduction and discussion sections. Shadi Isac assisted in developing the methods section. 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Advances in nutrition [Internet]. 2020 Mar 1 [cited 2024 Dec 22];11(2):349–56. Available from: https://doi.org/10.1093/advances/nmz073 Gupta R, Das, Haider SS, Sutradhar I, Hashan MR, Sajal IH, Hasan M, Association of frequency of television watching with overweight and obesity among women of reproductive age in India: Evidence from a nationally representative study. PLoS One [Internet]. 2019 Aug 1 [cited 2024 Dec 22];14(8). Available from: https://pubmed.ncbi.nlm.nih.gov/31465465/ Ghose B Frequency of TV viewing and prevalence of overweight and obesity among adult women in Bangladesh: a cross-sectional study. BMJ Open [Internet]. 2017 Jan 1 [cited 2024 Dec 22];7(1):e014399. Available from: https://bmjopen.bmj.com/content/7/1/e014399 Tuoyire DA Television exposure and overweight/obesity among women in Ghana. BMC Obes [Internet]. 2018 Feb 14 [cited 2024 Dec 22];5(1). Available from: https://pubmed.ncbi.nlm.nih.gov/29468075/ Watanabe T, Tsujino I, Konno S, Ito YM, Takashina C, Sato T, Association between Smoking Status and Obesity in a Nationwide Survey of Japanese Adults. PLoS One [Internet]. 2016 Mar 1 [cited 2024 Oct 31];11(3). Available from: https://doi.org/10.1371/journal.pone.0148926 Dare S, Mackay DF, Pell JP Relationship between Smoking and Obesity: A Cross-Sectional Study of 499,504 Middle-Aged Adults in the UK General Population. PLoS One [Internet]. 2015 Apr 17 [cited 2024 Oct 31];10(4). Available from: https://doi.org/10.1371/journal.pone.0123579 Chiolero A, Faeh D, Paccaud F, Cornuz J Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr [Internet]. 2008 Apr 1 [cited 2024 Oct 31];87 4(4):801–9. Available from: https://doi.org/10.1093/AJCN/87.4.801 Khani Y, Khani Y, Pourgholam-Amiji N, Afshar M, Otroshi O, Sharifi-Esfahani M, Tobacco Smoking and Cancer Types: A Review. Biomedical Research and Therapy [Internet]. 2018 Apr 16 [cited 2024 Nov 1];5(4):2142–59. Available from: http://bmrat.org/index.php/BMRAT/article/view/428 Neupane S, Prakash KC, Doku DT Overweight and obesity among women: Analysis of demographic and health survey data from 32 Sub-Saharan African Countries. BMC Public Health [Internet]. 2016 Jan 13 [cited 2024 Dec 22];16(1):1–9. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-016-2698-5 Fletcher JM, Frisvold DE Higher Education and Health Investments: Does More Schooling Affect Preventive Health Care Use? J Hum Cap [Internet]. 2009 Jun [cited 2024 Dec 22];3(2):144–76. Available from: https://pubmed.ncbi.nlm.nih.gov/22368727/ Chandola T, Clarke P, Morris JN, Blane D Pathways between education and health: A causal modelling approach. J R Stat Soc Ser Stat Soc. 2006;169(2):337–59. Abrha S, Shiferaw S, Ahmed KY Overweight and obesity and its socio-demographic correlates among urban Ethiopian women: Evidence from the 2011 EDHS. BMC Public Health [Internet]. 2016 Jul 26 [cited 2024 Dec 22];16(1):1–7. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-016-3315-3 increasing overweight and obesity and stall underweight trends among Ghanaian women | BMC Public Health | Full Text [Internet]. [cited 2024 Dec 22]. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-015-2033-6 Doku DT, Neupane S Double burden of malnutrition: Increasing overweight and obesity and stall underweight trends among Ghanaian women. BMC Public Health [Internet]. 2015 Dec 12 [cited 2024 Dec 22];15(1):1–9. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-015-2033-6 Subramanian S V., Perkins JM, Özaltin E, Smith GD Weight of nations: a socioeconomic analysis of women in low- to middle-income countries. Am J Clin Nutr [Internet]. 2011 Feb 1 [cited 2024 Dec 22];93(2):413–21. Available from: https://pubmed.ncbi.nlm.nih.gov/21068343/ Hashan MR, Das Gupta R, Day B, Al Kibria GM Differences in prevalence and associated factors of underweight and overweight/obesity according to rural–urban residence strata among women of reproductive age in Bangladesh: evidence from a cross-sectional national survey. BMJ Open [Internet]. 2020 Feb 1 [cited 2024 Dec 22];10(2):e034321. Available from: https://bmjopen.bmj.com/content/10/2/e034321 Christensen DL, Eis J, Hansen AW, Larsson MW, Mwaniki DL, Kilonzo B, Obesity and regional fat distribution in Kenyan populations: impact of ethnicity and urbanization. Ann Hum Biol [Internet]. 2008 Mar [cited 2024 Dec 22];35(2):232–49. Available from: https://pubmed.ncbi.nlm.nih.gov/18428015/ Neuman M, Kawachi I, Gortmaker S, Subramanian S V Urban-rural differences in BMI in low- and middle-income countries: the role of socioeconomic status. Am J Clin Nutr [Internet]. 2013 Feb 1 [cited 2024 Dec 22];97(2):428–36. Available from: https://pubmed.ncbi.nlm.nih.gov/23283503/ Biswas T, Garnett SP, Pervin S, Rawal LB The prevalence of underweight, overweight and obesity in Bangladeshi adults: Data from a national survey. PLoS One [Internet]. 2017 May 1 [cited 2024 Dec 22];12(5):e0177395. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177395 Ettarh R, Van de Vijver S, Oti S, Kyobutungi C Overweight, Obesity, and Perception of Body Image Among Slum Residents in Nairobi, Kenya, 2008–2009. Prev Chronic Dis [Internet]. 2013 Dec [cited 2024 Dec 22];10(12):E212. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3869529/ Mukora-Mutseyekwa F, Zeeb H, Nengomasha L, Adjei NK Trends in Prevalence and Related Risk Factors of Overweight and Obesity among Women of Reproductive Age in Zimbabwe, 2005–2015. Int J Environ Res Public Health [Internet]. 2019 Aug 1 [cited 2024 Dec 22];16(15):2758. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6695964/ Griffiths P, Bentley M Women of higher socio-economic status are more likely to be overweight in Karnataka, India. Eur J Clin Nutr [Internet]. 2005 Oct [cited 2024 Dec 22];59(10):1217–20. Available from: https://pubmed.ncbi.nlm.nih.gov/16077746/ Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Mar, 2026 Read the published version in Journal of Health, Population and Nutrition → Version 1 posted Editorial decision: Revision requested 08 Dec, 2025 Reviews received at journal 06 Nov, 2025 Reviews received at journal 04 Nov, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers agreed at journal 14 Oct, 2025 Reviewers invited by journal 14 Oct, 2025 Editor assigned by journal 12 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 11 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Introduction\",\"content\":\"\\u003cp\\u003eObesity has emerged as a rapidly growing global health crisis, particularly in low- and middle-income countries undergoing socioeconomic transitions. It is characterized by excessive fat accumulation, which poses significant health risks (\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e). The World Health Organization (WHO) now classifies obesity as a pandemic, with over 2\\u0026nbsp;billion adults worldwide being overweight, and 677.6\\u0026nbsp;million of them classified as obese (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eWomen, in particular, face high rates of obesity, comprising 393.5\\u0026nbsp;million, which places them at increased risk for numerous health issues, including cardiovascular diseases, type 2 diabetes, and certain cancers (\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e). Additionally, obesity among women of reproductive age is linked to challenges with conception, an elevated risk of miscarriage, and various complications during pregnancy, labor, and postpartum, contributing to higher rates of maternal morbidity and mortality (\\u003cspan additionalcitationids=\\\"CR6\\\" citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e). The COVID-19 pandemic has further complicated the landscape, amplified sedentary lifestyles and increased the demand for weight-loss surgeries, such as gastric sleeve procedures, as individuals struggle to manage weight in the face of lifestyle changes and limited access to physical activity(\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eJordan, like other countries in the Middle East, has witnessed a significant rise in obesity rates, especially among women(\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e). With 43.1% of Jordanian females considered obese compared to 28.2% of males, the trend has been steadily increasing at an annual rate of 1.38% over the last two decades (\\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e). According to the Global Obesity Observatory, the prevalence of obesity among females is projected to reach 77.54% by 2060. Additionally, the economic burden of obesity is expected to rise significantly, with associated costs increasing from USD 850.48\\u0026nbsp;million in 2019 to USD 8.97\\u0026nbsp;billion by 2026(\\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e11\\u003c/span\\u003e). Key contributing factors to obesity include dietary shifts, urbanization, changing marital norms, and a higher intake of processed foods and sugary beverages, all of which have fueled the regional obesity crisis (\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eA study based on data from the 2009 Jordan Population and Family Health Survey (JPFHS) identified several factors associated with obesity over time, including age, residence in southern regions of Jordan, early marriage, parity, wealth status, and smoking (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e). Similarly, an analysis of data from the 2017/18 JPFHS, which included 4,226 Jordanian women of reproductive age, highlighted additional obesity-related factors(\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). The study found that increasing age and residing in Tafilah were significantly associated with higher odds of obesity, while belonging to the wealthiest category, living in Maan or Aqaba, and daily smoking were linked to reduced odds of obesity (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eDespite previous research (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e), obesity remains a significant and growing public health concern in Jordan. The rapidly evolving socio-economic, cultural, and lifestyle patterns in the region highlight the need for updated studies to reflect current trends. This study seeks to examine the socio-demographic factors associated with obesity among adult ever-married women in Jordan, utilizing the most recent data from the 2023 JPFHS.\\u003c/p\\u003e\"},{\"header\":\"2. Methods\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.1 Data collection\\u003c/h2\\u003e\\u003cp\\u003eOur study utilized data from 2023 JPFHS. The survey initially recruited a representative sample of 12,595 eligible women aged 15\\u0026ndash;49 from all 12 governorates in Jordan. Key data collected included anthropometric measurements, particularly body mass index (BMI), alongside socioeconomic and behavioral factors.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.2 Inclusion criteria\\u003c/h2\\u003e\\u003cp\\u003eWe included data from ever-married women aged 20\\u0026ndash;49 years with a reported BMI (kg/m\\u0026sup2;) measured in accordance with the guidelines of the Centers for Disease Control and Prevention (\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e).\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.3 Exclusion criteria\\u003c/h2\\u003e\\u003cp\\u003eWe excluded women younger than 20 years old, those with missing BMI data, underweight women with a BMI\\u0026thinsp;\\u0026lt;\\u0026thinsp;18.5, and overweight women with BMI between 25\\u0026ndash;29.9.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.4 Included variables\\u003c/h2\\u003e\\u003cp\\u003eWe studied some socioeconomic and behavioral variables including Age (divided into five-year groups); type of residence: rural or urban; governorate of residence categorized as Mafraq, Ajloun, Amman, Zarqa, Karak, Tafiela, Madaba, Aqaba, Irbid, Balqa, Jarash, and Ma\\u0026rsquo;an; wealth index as classified by the DHS survey into richest, richer, middle, poorer and poorest; educational level categorized as higher education, secondary education, primary education and no education; and frequency of listening to the radio, watching television, reading magazines or newspapers or frequency of internet usage categorized as at least once a week, less than once a week and not at all. We also added the frequency of smoking categorized as everyday smoking, some days smoking, and does not smoke.\\u003c/p\\u003e\\u003c/div\\u003e\\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e2.5 Statistical analysis\\u003c/h2\\u003e\\u003cp\\u003eAnalysis of data was done using SPSS version 24, running a weighted count for all analyses based on DHS recommendations (\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e). Sample weight was noted to be an eight-digit variable with six implied decimal places and then adjusted by dividing by 1,000,000. The results were reported as frequencies and percentages. We then performed multivariable logistic regression, presenting the results in the form of an adjusted odds ratio (AOR), with 95% confidence interval (CI). A p-value of less than 0.05 was considered statistically significant.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"3. Results\",\"content\":\"\\u003cp\\u003eData was collected from 4,048 Jordanian women aged 20\\u0026ndash;49, with 41.9% of the sample having normal BMI and 58.1% being obese \\u003cb\\u003e(\\u003c/b\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e\\u003cb\\u003e)\\u003c/b\\u003e.\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003eCharacteristics of the included women according to BMI\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"6\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" morerows=\\\"2\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\" rowspan=\\\"3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"4\\\" nameend=\\\"c6\\\" namest=\\\"c3\\\"\\u003e\\u003cp\\u003eBMI\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e\\u003cp\\u003eNormal\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e\\u003cp\\u003eObese\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003eCount\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003eColumn N %\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003eCount\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eColumn N %\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAge in 5-year groups\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e20\\u0026ndash;24\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e238\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e14.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e75\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e3.2%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e25\\u0026ndash;29\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e360\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e21.2%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e203\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e30\\u0026ndash;34\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e404\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e23.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e370\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e15.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e35\\u0026ndash;39\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e329\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e19.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e481\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e20.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e40\\u0026ndash;44\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e219\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e12.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e513\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e21.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e45\\u0026ndash;49\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e147\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e8.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e709\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e30.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eHighest educational level\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNo education\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e44\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e2.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e58\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePrimary\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e100\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e5.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e224\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e9.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSecondary\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e876\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e50.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1456\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e61.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eHigher\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e729\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e41.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e631\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e26.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"4\\\" rowspan=\\\"5\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eWealth index combined\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePoorest\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e407\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e23.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e539\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e22.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003ePoorer\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e342\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e19.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e545\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e23.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMiddle\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e393\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e22.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e494\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e20.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eRicher\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e272\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e15.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e480\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e20.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eRichest\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e335\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e19.2%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e309\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e13.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eType of place of residence\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eUrban\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1589\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e90.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e2159\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e91.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eRural\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e160\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e9.2%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e210\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e8.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of reading newspaper or magazine\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNot at all\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1290\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e73.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1852\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e78.2%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eLess than once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e200\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e11.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e246\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e10.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAt least once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e259\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e14.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e270\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e11.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAlmost every day\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of listening to radio\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNot at all\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1236\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e70.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1661\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e70.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eLess than once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e227\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e13.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e330\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e13.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAt least once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e286\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e16.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e378\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e15.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAlmost every day\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of watching television\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNot at all\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e278\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e15.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e368\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e15.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eLess than once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e346\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e19.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e438\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e18.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAt least once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1126\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e64.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1563\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e66.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAlmost every day\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of using internet last month\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNot at all\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e430\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e24.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e480\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e20.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eLess than once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e40\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAt least once a week\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e45\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e2.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e86\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e3.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAlmost every day\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1249\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e71.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1764\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e74.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency smokes cigarettes\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eDoes not smoke\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1568\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e89.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e2171\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e91.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eEvery day\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e158\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e9.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e137\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e5.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSome days\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e24\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e60\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"14\\\" rowspan=\\\"15\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eGovernorate\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eCentral region\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAmman\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e891\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e50.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e988\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e41.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eBalqa\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e99\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e5.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e154\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e6.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eZarqa\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e220\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e12.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e376\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e15.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMadaba\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e26\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e51\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.2%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eNorthern region\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eIrbid\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e297\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e17.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e458\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e19.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMafraq\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e71\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e4.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e84\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e3.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eJarash\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e35\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e2.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e62\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAjloun\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e23\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e46\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.0%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eSouthern Region\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eKarak\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e26\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.5%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e65\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.8%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eTafiela\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e13\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.7%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e20\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.9%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eMa'an\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e23\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.3%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1.1%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003eAqaba\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e25\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e1.4%\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e37\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1.6%\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eThe result showed that the highest proportion of obese participants was from the 35 to 49 years age group representing 72.3% of total obese women with the highest proportion between 45\\u0026ndash;49 representing 30.1%. However, 45% of normal BMI females were 25\\u0026ndash;34 years old with the highest proportion between 30\\u0026ndash;34.\\u003c/p\\u003e\\u003cp\\u003eAmong women with normal BMI, approximately half (50.1%) had completed their secondary education, 5.7% had only primary education, 41.7% had a higher learning degree, and about 2.5% were non-educated. On the other hand, of the obese population, 61.5% of them reached the secondary educational level, 9.5% were only primarily educated, 26.6% had a higher learning degree whereas 2.4% were non-educated.\\u003c/p\\u003e\\u003cp\\u003eRegarding residence, about 90.8% of the normal BMI and 91.1% of the obese group lived in urban while 9.2% of the normal BMI group and 8.9% of the obese group lived in rural areas. Most of the normal BMI group and the obese group lived in: Amman with 50.9% in the normal BMI group and 41.7% in the obese group, Irbid with 17% in the normal BMI group and 19.3% in the obese group, and Zarqa with 12.6% in the normal BMI group and 15.9% in the obese group.\\u003c/p\\u003e\\u003cp\\u003eObesity was more predominant in the poorer group 23% followed by the poorest, middle, richer, and richest (22.8%, 20.9%, 20.3%, and 13.1% respectively). On the other hand, the normal BMI was predominant in the poorest group 23.3% followed by middle, poorer, richest, and richer (22.5%, 19.6%, 19.2%, and 15.5%, respectively).\\u003c/p\\u003e\\u003cp\\u003eMost of the participants in both groups did not read magazines or newspapers at all with 73.8% in the normal BMI group and 78.2% in the obese group. Additionally, 11.4% in the normal BMI group and 10.4% in the obese group did less than once a week, while 14.8% in the normal BMI group and 11.4% in the obese group did at least once a week.\\u003c/p\\u003e\\u003cp\\u003eMost of the participants in both groups did not listen to the radio at all with 70.7% in the normal BMI group and 70.1% in the obese group. Additionally,13% in the normal BMI group and 13.9% in the obese group listened to the radio less than once a week while 16.3% in the normal BMI group and 15.9% in the obese group listened to the radio at least once a week.\\u003c/p\\u003e\\u003cp\\u003e64.3% of the normal BMI group and 66% of the obese group watched television at least once a week. In contrast,19.8% of the normal BMI group and 18.5% of the obese group did less than once a week, while 15.9% of the normal BMI group and 15.5% of the obese group didn\\u0026rsquo;t watch at all.\\u003c/p\\u003e\\u003cp\\u003eThe majority of the normal BMI group (71.4%) and the obese group (74.5%) used the internet last month almost every day, while 24.6% of the normal BMI group and 20.3% of the obese group didn\\u0026rsquo;t use the internet at all. Regarding smoking, 89.6% of the normal BMI group and 91.7% of the obese group didn't smoke.\\u003c/p\\u003e\\u003cp\\u003eIn multivariable analysis \\u003cb\\u003e(\\u003c/b\\u003eTable\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e\\u003cb\\u003e)\\u003c/b\\u003e, we found that the odds of obesity increased with increasing the women's age, 25\\u0026ndash;29 years (OR: 2.061; 95%CI: 1.342\\u0026ndash;3.164; p\\u0026thinsp;=\\u0026thinsp;0.001), 30\\u0026ndash;34 years (OR: 3.963; 95%CI: 2.601\\u0026ndash;6.037; p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), 35\\u0026ndash;39 years (OR: 6.517; 95%CI: 4.274\\u0026ndash;9.938; p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), 40\\u0026ndash;44 years (OR: 9.872; 95%CI: 6.372\\u0026ndash;15.294; p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001), 45\\u0026ndash;49 years (OR: 20.930; 95%CI: 13.396\\u0026ndash;32.702; p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001).\\u003c/p\\u003e\\u003cp\\u003e\\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab2\\\" border=\\\"1\\\"\\u003e\\u003ccaption language=\\\"En\\\"\\u003e\\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 2\\u003c/div\\u003e\\u003cdiv class=\\\"CaptionContent\\\"\\u003e\\u003cp\\u003ePredictors of women obesity\\u003c/p\\u003e\\u003c/div\\u003e\\u003c/caption\\u003e\\u003ccolgroup cols=\\\"8\\\"\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e\\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e\\u003cthead\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"3\\\" nameend=\\\"c5\\\" namest=\\\"c3\\\"\\u003e\\u003cp\\u003eParameters Estimate\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"2\\\" morerows=\\\"1\\\" nameend=\\\"c2\\\" namest=\\\"c1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eVariables\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c3\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eB\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eStandard Error\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e\\u003cp\\u003eAOR\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c7\\\" namest=\\\"c6\\\"\\u003e\\u003cp\\u003e95% Confidence Interval for AOR\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/th\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003eLower\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003eUpper\\u003c/p\\u003e\\u003c/th\\u003e\\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003eP Value\\u003c/p\\u003e\\u003c/th\\u003e\\u003c/tr\\u003e\\u003c/thead\\u003e\\u003ctbody\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"5\\\" rowspan=\\\"6\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAge at 5 years\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e20\\u0026ndash;24\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e25\\u0026ndash;29\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.723\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.218\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e2.061\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1.342\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e3.164\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e30\\u0026ndash;34\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.377\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.215\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e3.963\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e2.601\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e6.037\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e35\\u0026ndash;39\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e1.874\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.215\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e6.517\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e4.274\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e9.938\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e40\\u0026ndash;44\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e2.290\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.223\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e9.872\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e6.372\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e15.294\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e45\\u0026ndash;49\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e3.041\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.227\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e20.930\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e13.396\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e32.702\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eHighest Educational level\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eNo Education\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003ePrimary\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.483\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.394\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.621\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.748\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e3.514\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.220\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eSecondary\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.082\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.341\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.086\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.555\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e2.122\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.810\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eHigher\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.512\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.350\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.599\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.302\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.190\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.143\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"11\\\" rowspan=\\\"12\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eGovernorate\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAqaba\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eMa'an\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.131\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.228\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.877\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.561\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.372\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.565\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eTafiela\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.245\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.236\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.277\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.804\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e2.030\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.300\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" 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align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.262\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.856\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.861\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.240\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eRichest\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.314\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.253\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" 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colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.626\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.040\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.098\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"3\\\" rowspan=\\\"4\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of using Internet last month\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eNot at all\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eLess than once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.316\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.473\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.372\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.543\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e3.470\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.504\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAt least once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.518\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.296\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.678\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.939\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e3.001\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.081\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAlmost everyday\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.285\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.137\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.330\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1.016\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.741\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e0.038\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of watching Television\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eNot at all\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eLess than once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.067\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.191\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.936\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.643\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.360\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.727\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAt least once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.103\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.148\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.109\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.829\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.484\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.487\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of listening to Radio\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eNot at all\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eLess than once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.335\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.158\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.398\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e1.026\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.906\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e0.034\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAt least once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.185\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.162\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.204\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.876\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.655\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.253\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency of reading newspaper or magazine\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eNot at all\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eLess than once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.345\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.233\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.708\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.448\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e1.119\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.139\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eAt least once a week\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.480\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.146\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.619\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.465\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.823\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eFrequency smokes cigarettes\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eDoes not smoke\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eReference\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e\\u0026nbsp;\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eEveryday\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e-0.669\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.189\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e0.512\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.354\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e0.742\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003e\\u0026lt;\\u0026thinsp;0.001\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003ctr\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e\\u003cp\\u003e\\u003cb\\u003eSomedays\\u003c/b\\u003e\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e\\u003cp\\u003e0.350\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e\\u003cp\\u003e0.506\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e\\u003cp\\u003e1.420\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c6\\\"\\u003e\\u003cp\\u003e0.526\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e\\u003cp\\u003e3.833\\u003c/p\\u003e\\u003c/td\\u003e\\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e\\u003cp\\u003e0.489\\u003c/p\\u003e\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tbody\\u003e\\u003c/colgroup\\u003e\\u003ctfoot\\u003e\\u003ctr\\u003e\\u003ctd colspan=\\\"8\\\"\\u003eAOR: adjusted odds ratio\\u003c/td\\u003e\\u003c/tr\\u003e\\u003c/tfoot\\u003e\\u003c/table\\u003e\\u003c/div\\u003e\\u003c/p\\u003e\\u003cp\\u003eRegarding media consumption, women who listened to the radio less than once a week were more likely to be obese (OR: 1.398; 95% CI: 1.026\\u0026ndash;1.906; p\\u0026thinsp;=\\u0026thinsp;0.034) than those who never listened to the radio. However, there was no significant association between obesity and women who listened to the radio at least once a week (OR: 1.204; 95% CI: 0.876\\u0026ndash;1.655; p\\u0026thinsp;=\\u0026thinsp;0.253).\\u003c/p\\u003e\\u003cp\\u003eAlso, we found that women who used the internet almost every day in the last month were more likely to be obese (OR: 1.330; 95%CI: 1.016\\u0026ndash;1.741; p\\u0026thinsp;=\\u0026thinsp;0.038) than those who didn\\u0026rsquo;t use it. In contrast, women who used the internet less than once a week (OR: 1.372; 95%CI: 0.543\\u0026ndash;3.470; p\\u0026thinsp;=\\u0026thinsp;0.504) and at least once a week (OR: 1.678; 95%CI: 0.939\\u0026ndash;3.001; p\\u0026thinsp;=\\u0026thinsp;0.081) showed no significant association with obesity.\\u003c/p\\u003e\\u003cp\\u003eRegarding the frequency of reading newspapers or magazines, women who read at least once a week (OR: 0.619; 95%CI: 0.465\\u0026ndash;0.823; p\\u0026thinsp;=\\u0026thinsp;0.001) were associated with a lower risk of obesity than those who didn\\u0026rsquo;t read. However, reading less than once a week showed no significant association with obesity (OR: 0.708; 95%CI 0.448\\u0026ndash;1.119; p\\u0026thinsp;=\\u0026thinsp;0.139).\\u003c/p\\u003e\\u003cp\\u003eIn terms of Smoking, we found that everyday smoking was significantly associated with lower odds of obesity (OR: 0.512; 95%CI: 0.354\\u0026ndash;0.742; p\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.001) while some days smoking was not significantly associated with obesity (OR: 1.420; 95%CI: 0.526\\u0026ndash;3.833; p\\u0026thinsp;=\\u0026thinsp;0.489).\\u003c/p\\u003e\\u003cp\\u003eGeographical location also played a role, as living in Karak and Ajloun was significantly associated with higher odds of obesity (OR: 2.128; 95%CI: 1.340\\u0026ndash;3.378; p\\u0026thinsp;=\\u0026thinsp;0.001), (OR: 1.747; 95%CI: 1.124\\u0026ndash;2.715; p\\u0026thinsp;=\\u0026thinsp;.013) respectively.\\u003c/p\\u003e\\u003cp\\u003eOn the other hand, we found no significant association between obesity and the education level, wealth index, type of place of residence, and frequency of watching television (p\\u0026thinsp;\\u0026gt;\\u0026thinsp;0.05).\\u003c/p\\u003e\"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eTo the best of our knowledge, this study is the first to explore the socio-demographic factors influencing obesity among ever-married adult women in Jordan, using data from the 2023 JDHS.\\u003c/p\\u003e\\u003cp\\u003eThe prevalence of obesity in Jordan has risen sharply in recent years. In 2009, 38.8% of individuals were classified as obese(\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e), increasing to 51.3% by 2017/18 (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e), and reaching 58.1% in 2023, as observed in this study. This upward trend may be partly driven by significant lifestyle changes and unhealthy eating behaviors following the COVID-19 pandemic (\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e), as lockdowns, distance learning, and remote work led to more sedentary routines.\\u003c/p\\u003e\\u003cp\\u003eOur analysis identified a significant association between age and obesity, revealing that older women had considerably higher obesity rates. Specifically, women aged 44\\u0026ndash;49 were 20.9 times more likely to be obese compared to those aged 20\\u0026ndash;24. These findings are consistent with previous studies conducted in Jordan, including Al Nsour et al. 2008 (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e), Bustami et al. 2021 (\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e), and Shaaban Abdelgalil et al. 2024 (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e) as well as studies by Pengpid et al. in Iraq 2015 (\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e), and Chamieh et al. in Lebanon 2015 (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e), all of which reported a significantly higher prevalence of obesity among older women.\\u003c/p\\u003e\\u003cp\\u003eThis trend is largely due to hormonal and psychological changes associated with aging. As women approach menopause, declining estrogen and increased androgens lead to muscle loss, increased abdominal fat, and altered body composition. Coupled with a sedentary lifestyle, these changes reduce energy expenditure and basal metabolic rate, increasing obesity risk (\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eAging also brings physical declines, such as sarcopenia, which impairs mobility, balance, and bone density. Regular physical activity can mitigate these effects, enhancing longevity and reducing metabolic and chronic disease risk (\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e). Additionally, psychological changes like increased stress, mood fluctuations, and anxiety often trigger emotional or stress-induced eating, further contributing to obesity risk (\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eThe analysis of obesity odds across regions revealed significant variations. Women in Karak, located in the southern region, and Ajloun, in the northern region, had significantly higher odds of obesity compared to those in Aqaba in the southern region. These findings differ from those of Shaaban Abdelgalil et al. 2024 in Jordan (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e), which reported no significant differences in obesity odds between the central and northern governorates. However, the study noted that in the southern governorates, living in Tafilah in southern region was associated with an increased likelihood of obesity, whereas residing in Maan or Aqaba in southern region was linked to a decreased likelihood (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eThe regional variations in obesity odds among Jordanian women can be explained by a combination of factors. Socioeconomic inequalities may restrict access to nutritious food options and quality healthcare, while cultural and lifestyle practices, such as consuming traditional high-calorie diets and engaging in minimal physical activity, further elevate obesity risks in certain areas(\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e). Additionally, regions with lower levels of urbanization often lack the necessary infrastructure, such as parks and recreational facilities, to encourage physical activity, leading to more sedentary lifestyles(\\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e). Differences in healthcare access and public awareness also contribute, as areas with limited healthcare resources may fall short in providing adequate education and interventions for obesity prevention and management(\\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eOur study found that certain media habits were linked to obesity. Women who listened to the radio less than once a week had higher odds of obesity compared to those who never listened. This finding is consistent with El-Qushayri et al. 2023 in Egypt (\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e). It is possible that individuals who listen to the radio may engage in less physical activity, leading to a more sedentary lifestyle, which is associated with obesity(\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eFurthermore, regular internet use was associated with higher odds of obesity compared to individuals who did not use the internet at all. This suggests that frequent internet use may limit the time available for physical activity(\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e). A meta-analysis by Aghasi et al. found a linear dose-response relationship, indicating that each additional hour of internet use per day was associated with an 8% increase in the odds of overweight and obesity(\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eConversely, our study found no association between watching television and obesity, which contrasts with studies in countries such as Ghana, Bangladesh, and Myanmar, where higher television consumption has been linked to obesity due to prolonged sedentary behaviors and exposure to unhealthy food advertisements (\\u003cspan additionalcitationids=\\\"CR33\\\" citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e34\\u003c/span\\u003e). Our study suggests that appropriate actions should be taken through both traditional and social media, targeting obese Jordanian women to raise awareness about the negative effects of reduced physical activity, excessive radio listening, and frequent internet use.\\u003c/p\\u003e\\u003cp\\u003eSmoking was significantly associated with lower odds of obesity among daily smokers in our sample. This finding aligns with previous studies by Al Nsour et al. 2009 in Jordan (\\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e12\\u003c/span\\u003e), Shaaban Abdelgalil et al. 2024 in Jordan(\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e), Watanabe et al. 2016 in Japan (\\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e35\\u003c/span\\u003e) and Dare et al. 2015 in the UK (\\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e36\\u003c/span\\u003e). Some studies suggest that nicotine may contribute to appetite suppression, which could explain the link between smoking and a reduced risk of obesity (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e). However, while smoking may be associated with lower obesity risk, it also carries significant health risks, including higher rates of central adiposity, cardiovascular disease, and cancer (\\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e37\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e38\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eUnlike some studies conducted in other countries, our findings did not show a significant association between education level and obesity among women, aligning with the study by Shaaban Abdelgalil et al. 2024 in Jordan (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). However, some studies have suggested that women with secondary education experience higher obesity rates compared to those with higher education. Research has often linked higher education to improved health outcomes, largely due to greater health literacy and socioeconomic advantages (\\u003cspan additionalcitationids=\\\"CR40\\\" citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e41\\u003c/span\\u003e). Nevertheless, variations in findings across countries, including Ghana, Bangladesh, and Ethiopia, highlight the diverse influence of social determinants of health and the differing effects of education on lifestyle and diet (\\u003cspan additionalcitationids=\\\"CR43 CR44\\\" citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e45\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cp\\u003eOur study found no significant association between place of residence and obesity among Jordanian women, consistent with the findings of Shaaban Abdelgalil et al. 2024 in Jordan (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). This contrasts with findings from some low- and middle-income countries, where urban living is often associated with higher obesity rates(\\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e39\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR47\\\" citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e46\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e48\\u003c/span\\u003e). In our sample, both urban and rural areas exhibited similar obesity prevalence, likely due to shared dietary patterns and lifestyle similarities within Jordan\\u0026rsquo;s relatively compact urban-rural structure.\\u003c/p\\u003e\\u003cp\\u003eOur analysis did not find a significant association between wealth index and obesity, which aligns with the study by Shaaban Abdelgalil et al. 2024 in Jordan (\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e). However, wealth index is still a relevant factor, as obesity rates were higher among women in the poorer wealth quintiles, contrasting with findings in other countries where obesity is often more prevalent among the affluent(\\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e42\\u003c/span\\u003e, \\u003cspan additionalcitationids=\\\"CR50\\\" citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e49\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR51\\\" class=\\\"CitationRef\\\"\\u003e51\\u003c/span\\u003e). In Jordan, socioeconomic factors may influence dietary choices, with lower-income individuals more likely to choose cheaper, calorie-dense foods over more nutritious alternatives. Additionally, cultural perceptions that associate larger body sizes with well-being may also contribute to obesity patterns among wealthier women in some Middle Eastern countries (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e47\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e50\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR52\\\" class=\\\"CitationRef\\\"\\u003e52\\u003c/span\\u003e).\\u003c/p\\u003e\\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e\\u003ch2\\u003e4.1 Limitations and Recommendations\\u003c/h2\\u003e\\u003cp\\u003eOur study utilized data from the 2023 JPFHS, focusing on ever-married women aged 20\\u0026ndash;49 years, but several limitations must be acknowledged. First, as a cross-sectional study, it cannot establish causal relationships between obesity and associated factors. Second, our analysis excluded specific groups, such as women younger than 20 years, and single women, which may have introduced selection bias and limited the generalizability of our findings. Third, the exclusion of comorbidities from the dataset, despite their potential role in influencing obesity, further limits the scope of our analysis. Additionally, the reliance on self-reported media consumption habits and internet usage may be subject to recall bias, potentially affecting the accuracy of the associations observed.\\u003c/p\\u003e\\u003cp\\u003eDespite these limitations, our findings offer actionable insights into obesity determinants among Jordanian women. We recommend future research to include broader age groups and examine the role of comorbidities to provide a more comprehensive understanding of obesity risk factors. Longitudinal studies are particularly needed to establish causality and capture temporal trends in obesity and its predictors. From a policy perspective, targeted interventions addressing age-related increases in obesity are essential. These interventions should focus on promoting healthy lifestyles, particularly among women with frequent internet use or irregular physical activity. Additionally, regional disparities, such as higher obesity odds in Karak and Ajloun, call for tailored, location-specific programs. National initiatives emphasizing nutrition education, lifestyle modifications, and community-based support could play a pivotal role in curbing obesity rates among Jordanian women.\\u003c/p\\u003e\\u003c/div\\u003e\"},{\"header\":\"5. Conclusion\",\"content\":\"\\u003cp\\u003eIn conclusion, older women, frequent internet users, those who listen to the radio less than once a week, and residents of Karak and Ajloun are associated with higher obesity rates among Jordanian women. Conversely, everyday smoking is linked to lower odds of obesity. No significant associations were observed with education level, wealth index, or place of residence. Targeted interventions focusing on age-specific and region-specific factors, along with strategies to promote healthier lifestyles, could help address obesity and its related health risks in Jordanian women.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eConflicts of interest:\\u003c/strong\\u003e All the authors declare no conflict of interest.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding:\\u003c/strong\\u003e All author(s) received no financial support for the research, authorship, and/or publication of this article.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics approval and consent to participate:\\u003c/strong\\u003e Not applicable as we obtained the data from a publicly accessible database (https://dhsprogram.com/data/available-datasets.cfm).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication:\\u003c/strong\\u003e not applicable.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and material:\\u003c/strong\\u003e Data is available upon request from ICF International's website (https://dhsprogram.com/data/available-datasets.cfm).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgment:\\u003c/strong\\u003e I would like to thank Dr. Mohamed Abd-ElGawad for his invaluable mentorship and unwavering support throughout my research journey.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors’ Contributions:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAmr Ahmed Aly Ibrahim played a key role in the study by validating the research concept, performing the data analysis, and writing the results section. Sara Hosny El-Farargy handled the data request from the Demographic and Health Survey, carried out data cleaning, and wrote the introduction and discussion sections. Shadi Isac assisted in developing the methods section. Mahmoud Shaaban Abdelgalil provided overall supervision of the project, offering guidance and oversight throughout the research process.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003ePopkin BM, Ng SW. The nutrition transition to a stage of high obesity and noncommunicable disease prevalence dominated by ultra-processed foods is not inevitable. Obes Rev [Internet]. 2022 Jan 1 [cited 2024 Dec 21];23(1). 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Available from: https://doi.org/10.1093/advances/nmz073\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGupta R, Das, Haider SS, Sutradhar I, Hashan MR, Sajal IH, Hasan M, Association of frequency of television watching with overweight and obesity among women of reproductive age in India: Evidence from a nationally representative study. PLoS One [Internet]. 2019 Aug 1 [cited 2024 Dec 22];14(8). Available from: https://pubmed.ncbi.nlm.nih.gov/31465465/\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGhose B Frequency of TV viewing and prevalence of overweight and obesity among adult women in Bangladesh: a cross-sectional study. BMJ Open [Internet]. 2017 Jan 1 [cited 2024 Dec 22];7(1):e014399. Available from: https://bmjopen.bmj.com/content/7/1/e014399\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eTuoyire DA Television exposure and overweight/obesity among women in Ghana. BMC Obes [Internet]. 2018 Feb 14 [cited 2024 Dec 22];5(1). Available from: https://pubmed.ncbi.nlm.nih.gov/29468075/\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eWatanabe T, Tsujino I, Konno S, Ito YM, Takashina C, Sato T, Association between Smoking Status and Obesity in a Nationwide Survey of Japanese Adults. PLoS One [Internet]. 2016 Mar 1 [cited 2024 Oct 31];11(3). Available from: https://doi.org/10.1371/journal.pone.0148926\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDare S, Mackay DF, Pell JP Relationship between Smoking and Obesity: A Cross-Sectional Study of 499,504 Middle-Aged Adults in the UK General Population. PLoS One [Internet]. 2015 Apr 17 [cited 2024 Oct 31];10(4). Available from: https://doi.org/10.1371/journal.pone.0123579\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eChiolero A, Faeh D, Paccaud F, Cornuz J Consequences of smoking for body weight, body fat distribution, and insulin resistance. Am J Clin Nutr [Internet]. 2008 Apr 1 [cited 2024 Oct 31];87 4(4):801\\u0026ndash;9. Available from: https://doi.org/10.1093/AJCN/87.4.801\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eKhani Y, Khani Y, Pourgholam-Amiji N, Afshar M, Otroshi O, Sharifi-Esfahani M, Tobacco Smoking and Cancer Types: A Review. Biomedical Research and Therapy [Internet]. 2018 Apr 16 [cited 2024 Nov 1];5(4):2142\\u0026ndash;59. Available from: http://bmrat.org/index.php/BMRAT/article/view/428\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eNeupane S, Prakash KC, Doku DT Overweight and obesity among women: Analysis of demographic and health survey data from 32 Sub-Saharan African Countries. BMC Public Health [Internet]. 2016 Jan 13 [cited 2024 Dec 22];16(1):1\\u0026ndash;9. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-016-2698-5\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eFletcher JM, Frisvold DE Higher Education and Health Investments: Does More Schooling Affect Preventive Health Care Use? J Hum Cap [Internet]. 2009 Jun [cited 2024 Dec 22];3(2):144\\u0026ndash;76. Available from: https://pubmed.ncbi.nlm.nih.gov/22368727/\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eChandola T, Clarke P, Morris JN, Blane D Pathways between education and health: A causal modelling approach. J R Stat Soc Ser Stat Soc. 2006;169(2):337\\u0026ndash;59.\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eAbrha S, Shiferaw S, Ahmed KY Overweight and obesity and its socio-demographic correlates among urban Ethiopian women: Evidence from the 2011 EDHS. BMC Public Health [Internet]. 2016 Jul 26 [cited 2024 Dec 22];16(1):1\\u0026ndash;7. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-016-3315-3\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eincreasing overweight and obesity and stall underweight trends among Ghanaian women | BMC Public Health | Full Text [Internet]. [cited 2024 Dec 22]. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-015-2033-6\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eDoku DT, Neupane S Double burden of malnutrition: Increasing overweight and obesity and stall underweight trends among Ghanaian women. BMC Public Health [Internet]. 2015 Dec 12 [cited 2024 Dec 22];15(1):1\\u0026ndash;9. 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Available from: https://pubmed.ncbi.nlm.nih.gov/23283503/\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eBiswas T, Garnett SP, Pervin S, Rawal LB The prevalence of underweight, overweight and obesity in Bangladeshi adults: Data from a national survey. PLoS One [Internet]. 2017 May 1 [cited 2024 Dec 22];12(5):e0177395. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177395\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eEttarh R, Van de Vijver S, Oti S, Kyobutungi C Overweight, Obesity, and Perception of Body Image Among Slum Residents in Nairobi, Kenya, 2008\\u0026ndash;2009. Prev Chronic Dis [Internet]. 2013 Dec [cited 2024 Dec 22];10(12):E212. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC3869529/\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eMukora-Mutseyekwa F, Zeeb H, Nengomasha L, Adjei NK Trends in Prevalence and Related Risk Factors of Overweight and Obesity among Women of Reproductive Age in Zimbabwe, 2005\\u0026ndash;2015. Int J Environ Res Public Health [Internet]. 2019 Aug 1 [cited 2024 Dec 22];16(15):2758. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6695964/\\u003c/span\\u003e\\u003c/li\\u003e\\u003cli\\u003e\\u003cspan\\u003eGriffiths P, Bentley M Women of higher socio-economic status are more likely to be overweight in Karnataka, India. Eur J Clin Nutr [Internet]. 2005 Oct [cited 2024 Dec 22];59(10):1217\\u0026ndash;20. Available from: https://pubmed.ncbi.nlm.nih.gov/16077746/\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"journal-of-health-population-and-nutrition\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"johp\",\"sideBox\":\"Learn more about [Journal of Health, Population and Nutrition](http://jhpn.biomedcentral.com/)\",\"snPcode\":\"41043\",\"submissionUrl\":\"https://submission.nature.com/new-submission/41043/3\",\"title\":\"Journal of Health, Population and Nutrition\",\"twitterHandle\":\"@BioMedCentral\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-7590700/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-7590700/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e\\u003cp\\u003eObesity prevalence has been rising globally, including in Jordan. This study aims to identify the factors influencing obesity rates among married Jordanian women aged 20\\u0026ndash;49 years, using data from the Jordan Demographic and Health Survey (JDHS).\\u003c/p\\u003e\\u003ch2\\u003eMethods\\u003c/h2\\u003e\\u003cp\\u003eThe study analyzed data from the 2023 JDHS, encompassing a representative sample of 12,595 Jordanian women aged 15\\u0026ndash;49. Socioeconomic variables examined included age, education level, wealth index, urban or rural residence, and media consumption habits (television, radio, magazines/newspapers, internet usage) along with smoking status. Multivariate logistic regression was employed to determine the associations between these factors and obesity risk.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e\\u003cp\\u003eOf the 4,048 married women included in the analysis, 1,697 (41.9%) had a normal BMI, while 2,351 (59.7%) were classified as obese. Multivariate analysis revealed that increasing age, listening to the radio less than once a week, daily internet use, and residing in Karak or Ajloun were significantly associated with higher odds of obesity. Conversely, reading newspapers or magazines at least once a week and daily cigarette smoking were linked to a reduced risk of obesity. No significant associations were observed between obesity and place of residence, wealth index, educational level, television viewing habits, or residence in other governorates.\\u003c/p\\u003e\\u003ch2\\u003eConclusion\\u003c/h2\\u003e\\u003cp\\u003eWith obesity rates continuing to rise, targeted health programs for Jordanian women of reproductive age are essential. National health initiatives should focus on promoting healthy lifestyle habits, addressing regional disparities, and encouraging balanced media consumption to mitigate obesity risk. Region-specific prevention and awareness campaigns are also vital for effective intervention.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Socio-Demographic Factors Influencing Obesity Among Ever-Married Jordanian Women of Reproductive Age: Insights from the 2023 Jordan Demographic and Health Survey\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-09-24 10:31:32\",\"doi\":\"10.21203/rs.3.rs-7590700/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-12-08T13:38:07+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-11-06T07:18:37+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-11-04T16:45:08+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"231651177379720366897927529077249886654\",\"date\":\"2025-10-27T11:48:31+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"184404355963990493125067364105433585441\",\"date\":\"2025-10-27T11:42:52+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"88875525904070987925055815113411648503\",\"date\":\"2025-10-14T16:53:17+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-10-14T16:45:39+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-09-12T08:43:31+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-09-12T08:42:18+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Journal of Health, Population and Nutrition\",\"date\":\"2025-09-11T10:16:16+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"journal-of-health-population-and-nutrition\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"johp\",\"sideBox\":\"Learn more about [Journal of Health, Population and Nutrition](http://jhpn.biomedcentral.com/)\",\"snPcode\":\"41043\",\"submissionUrl\":\"https://submission.nature.com/new-submission/41043/3\",\"title\":\"Journal of Health, Population and Nutrition\",\"twitterHandle\":\"@BioMedCentral\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC/SO AJ\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"0cb47376-8b98-4087-9f9c-e8afea8f9db9\",\"owner\":[],\"postedDate\":\"September 24th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-03-16T16:01:01+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-7590700\",\"link\":\"https://doi.org/10.1186/s41043-026-01273-2\",\"journal\":{\"identity\":\"journal-of-health-population-and-nutrition\",\"isVorOnly\":false,\"title\":\"Journal of Health, Population and Nutrition\"},\"publishedOn\":\"2026-03-10 15:57:55\",\"publishedOnDateReadable\":\"March 10th, 2026\"},\"versionCreatedAt\":\"2025-09-24 10:31:32\",\"video\":\"\",\"vorDoi\":\"10.1186/s41043-026-01273-2\",\"vorDoiUrl\":\"https://doi.org/10.1186/s41043-026-01273-2\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-7590700\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-7590700\",\"identity\":\"rs-7590700\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}