Background Unlike developed countries, higher socioeconomic status (SES-education, and wealth) is associated with hypertension in low and middle-income countries (LMICs) with limited evidence. We examined the associations between SES and hypertension in Nepal and the extent to which these associations vary by sex and urbanity. The body mass index (BMI) was examined as a secondary outcome and assessed as a potential mediator. Materials and methods We analyzed the latest Nepal Demographic and Health Survey data (N = 13,436) collected between June 2016 and January 2017, using a multistage stratified sampling technique. Participants aged 15 years or older from selected households were interviewed with an overall response rate of 97%. Primary outcomes were hypertension and normal blood pressure defined by the widely used Seventh Report of the Joint National Committee (JNC7) and the American College of Cardiology/American Heart Association (ACC/AHA) 2017. Results The prevalence of hypertension was higher in Nepalese men than women. The likelihood of being hypertensive was significantly higher in the higher education group compared with the lowest or no education group for men (OR 1.89 95% CI: 1.36, 2.61) and for women (OR 1.20 95% CI: 0.79, 1.83). People in the richest group were more likely to be hypertensive compared with people in the poorest group for men (OR 1.66 95% CI: 1.26, 2.19) and for women (OR 1.60 95% CI: 1.20, 2.12). The associations between SES (education) and

Introduction:Nonfinancial barriers are frequent causes of unmet need in health-care services. The significance of transportation barriers can weigh more than the issues of access to care. The purpose of this cross-sectional study was to examine transportation and other nonfinancial barriers among low-income uninsured patients of a safety net health-care facility (free clinic).Methods:The survey data were collected from patients aged 18 years and older who spoke English or Spanish at a free clinic, which served uninsured individuals in poverty in the United States.Results:Levels of transportation barriers were associated with levels of other nonfinancial barriers. Higher levels of nonfinancial barriers were associated with elevation in levels of stress and poorer self-rated general health. Higher educational attainment and employment were associated with an increase in other nonfinancial barriers.Conclusion:Focusing only on medical interventions might not be sufficient for the well-being of the underserved populations. Future studies should examine integrative care programs that include medical treatment and social services together and evaluate such programs to improve care for underserved populations.

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ObjectivesSmoking is a significant public health issue in Bangladesh. The purpose of this study was to examine peer smoking and smoking-related beliefs among college students in Bangladesh.MethodsCollege students at two universities in Dhaka, Bangladesh participated in a self-administered survey in May and June 2017.ResultsFirst, being a current or former smoker is associated with lower levels of beliefs among respondents that they would not smoke even with smoker friends or nervousness, and lower levels of intentions that they would not smoke, while current smokers and former smokers have different smoking-related beliefs. Second, having smoker friends is associated with lower levels of intentions that they would not smoke. Third, higher levels of normative beliefs that it is important not to smoke are associated with higher levels of beliefs that they would not smoke even with smoker friends or nervousness, higher levels of intentions that they would not smoke, and higher levels of avoidance of smoking.ConclusionsSmoking-related beliefs and perceived norms in individuals’ social networks are important components in promoting tobacco cessation in Bangladesh. But it is challenging to prevent or intervene in smoking because of the high rates of smoking in this country and the high prevalence of smokers in individuals’ social networks. Future studies should examine the most effective interventions to combat smoking in high-smoking social networks, such as using mobile apps or social media, and evaluate the effectiveness of such interventions.

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