Differences in prevalence and determinants of hypertension according to rural-urban place of residence among adults in Bangladesh.

Research paper by Gulam Muhammed Al GMA Kibria, Krystal K Swasey, Rajat R Das Gupta, Allysha A Choudhury, Jannatun J Nayeem, Atia A Sharmeen, Vanessa V Burrowes

Indexed on: 20 Dec '18Published on: 20 Dec '18Published in: Journal of biosocial science


This cross-sectional study analysed Bangladesh Demographic and Health Survey 2011 data with the aim of investigating the prevalence of, and risk factors for, hypertension in individuals aged over 35 by rural-urban place of residence. After estimation of the stratified prevalence of hypertension by background characteristics, multivariable logistic regression analysis was conducted to calculate the adjusted odds (AORs) and 95% confidence intervals (CIs) for selected factors. Of the 7839 participants, 1830 were from urban areas and 6009 from rural areas. The overall prevalence of hypertension was 32.6% (95% CI: 30.5-34.8) in urban areas and 23.6% (95% CI: 22.5-24.7) in rural areas. The prevalence and odds of hypertension increased with increasing age, female sex, concomitant diabetes and overweight/obesity and richer wealth status in both urban and rural regions. Although residence in Khulna and Rangpur divisions and higher education level were associated with increased odds of hypertension in urban regions, this was not the case in rural regions (p>0.05). Residence in Sylhet and Chittagong divisions had lower odds of hypertension in rural regions. Furthermore, the proportions of overweight/obese, diabetic and higher wealth status participants were higher in urban than in rural regions. The prevalence and odds of hypertension were found to be associated with several common factors after stratifying by place of residence. Some of these factors are more concentrated in urban regions, so urban residents with these risk factors need to be made more aware of these in order to control hypertension in Bangladesh. Public health programmes also need to be tailored differently for urban and rural regions, based on the different distribution of these significant factors in the two areas.