Mapping the burden of hypertension in South Africa: a comparative analysis of the national 2012 SANHANES and the 2016 Demographic and Health Survey

SOURCE: International Journal of Environmental Research and Public Health
OUTPUT TYPE: Journal Article
PUBLICATION YEAR: 2021
TITLE AUTHOR(S): N.B.Kandala, C.C.Nnanatu, N.Dukhi, R.Sewpaul, A.Davids, S.P.Reddy
KEYWORDS: DEMOGRAPHIC AND HEALTH SURVEY, HEALTH, HYPERTENSION, KWAZULU-NATAL PROVINCE, MPUMALANGA PROVINCE, SANHANES
DEPARTMENT: Public Health, Societies and Belonging (HSC)
Print: HSRC Library: shelf number 12030
HANDLE: 20.500.11910/16070
URI: http://hdl.handle.net/20.500.11910/16070

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Abstract

This study investigates the provincial variation in hypertension prevalence in South Africa in 2012 and 2016, adjusting for individual level demographic, behavioural and socio-economic variables, while allowing for spatial autocorrelation and adjusting simultaneously for the hierarchical data structure and risk factors. Data were analysed from participants aged 15 years from the South African National Health and Nutrition Examination Survey (SANHANES) 2012 and the South African Demographic and Health Survey (DHS) 2016. Hypertension was defined as blood pressure 140/90 mmHg or self-reported health professional diagnosis or on antihypertensive medication. Bayesian geo-additive regression modelling investigated the association of various socio-economic factors on the prevalence of hypertension across South Africas nine provinces while controlling for the latent effects of geographical location. Hypertension prevalence was 38.4% in the SANHANES in 2012 and 48.2% in the DHS in 2016. The risk of hypertension was significantly high in KwaZuluNatal and Mpumalanga in the 2016 DHS, despite being previously nonsignificant in the SANHANES 2012. In both survey years, hypertension was significantly higher among males, the coloured population group, urban participants and those with self-reported high blood cholesterol. The odds of hypertension increased non-linearly with age, body mass index (BMI), waist circumference. The findings can inform decision making regarding the allocation of public resources to the most affected areas of the population.