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Prevalence of Hypertension and Its Associated Risk Factors in a Rural Black Population of Mthatha Town, South Africa

Author

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  • Jyoti Rajan Sharma

    (Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa)

  • Sihle E. Mabhida

    (Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa
    Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, Cape Town 7535, South Africa)

  • Bronwyn Myers

    (Division of Alcohol Tobacco and Other Drug Research Unit, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa
    Division of Addiction Psychiatry, Department of Psychiatry and Mental Health, Groote Schuur Hospital, University of Cape Town, Observatory, Cape Town 7925, South Africa)

  • Teke Apalata

    (Division of Medical Microbiology, Department of Pathology and Laboratory-Medicine, Faculty of Health Sciences, Walter Sisulu University, Mthatha 5117, South Africa)

  • Edward Nicol

    (Burden of Disease Research Unit, South African Medical Research Council, Cape Town 7505, South Africa
    Division of Health Systems and Public Health, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town 7505, South Africa)

  • Mongi Benjeddou

    (Department of Biotechnology, Faculty of Natural Sciences, University of the Western Cape, Bellville, Cape Town 7535, South Africa)

  • Christo Muller

    (Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa
    Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town 7505, South Africa)

  • Rabia Johnson

    (Biomedical Research and Innovation Platform, South African Medical Research Council, Tygerberg, Cape Town 7505, South Africa
    Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, Cape Town 7505, South Africa)

Abstract

Background : The occurrence of hypertension has been increasing alarmingly in both low and middle-income countries. Despite acknowledging hypertension as the most common life-threatening risk factor for cardiovascular disease (CVD), a dearth of data is available on the prevalence, awareness, and determinants of hypertension in rural parts of South Africa. The principal aim of the current study is to determine the prevalence and associated risk factors of hypertension among a black rural African population from the Mtatha town of Eastern Cape Province. Methods : This was a cross-sectional study, and individuals over 18 years of age were randomly screened using a World Health Organization stepwise questionnaire. Sociodemographic information, anthropometric measurements, fasting blood glucose levels, and three independent blood pressure (BP) readings were measured. Blood pressure measurements were classified according to the American Heart Association guidelines. Univariate and multivariate analyses were performed to determine the significant predictors of hypertension. Results : Of the total participants (n = 556), 71% of individuals had BP scores in the hypertensive range. In univariate analysis, age, westernized diet, education, income, and diabetic status, as well as overweight/obese status were positively associated with the prevalence of hypertension. However, in a multivariate logistic regression analysis only, age, body mass index (BMI), diabetic status, and westernized diet were significantly associated with a higher risk of developing hypertension. Gender, age, and BMI were potential factors having a significant association with the treatment of hypertension. Individuals who did not consider the importance of medicine had higher chances of having their hypertension being untreated. Conclusions : Prevalence of hypertension was high among the black rural African population of Mthatha town. Gender, age, westernized diet, education level, income status, diabetic as well as overweight/obese status were the most significant predictors of hypertension.

Suggested Citation

  • Jyoti Rajan Sharma & Sihle E. Mabhida & Bronwyn Myers & Teke Apalata & Edward Nicol & Mongi Benjeddou & Christo Muller & Rabia Johnson, 2021. "Prevalence of Hypertension and Its Associated Risk Factors in a Rural Black Population of Mthatha Town, South Africa," IJERPH, MDPI, vol. 18(3), pages 1-17, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:1215-:d:489478
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    1. Ana-Lucia Mayén & Pascal Bovet & Helena Marti-Soler & Bharathi Viswanathan & Jude Gedeon & Fred Paccaud & Pedro Marques-Vidal & Silvia Stringhini, 2016. "Socioeconomic Differences in Dietary Patterns in an East African Country: Evidence from the Republic of Seychelles," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-13, May.
    2. David Cutler & Angus Deaton & Adriana Lleras-Muney, 2006. "The Determinants of Mortality," Journal of Economic Perspectives, American Economic Association, vol. 20(3), pages 97-120, Summer.
    3. Stuckler, D. & Basu, S. & McKee, M., 2011. "Health care capacity and allocations among South Africa's provinces: Infrastructure-inequality traps after the end of apartheid," American Journal of Public Health, American Public Health Association, vol. 101(1), pages 165-172.
    4. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    5. Colin Bell, A. & Adair, Linda S. & Popkin, Barry M., 2004. "Understanding the role of mediating risk factors and proxy effects in the association between socio-economic status and untreated hypertension," Social Science & Medicine, Elsevier, vol. 59(2), pages 275-283, July.
    6. Cooper, R. & Rotimi, C. & Ataman, S. & McGee, D. & Osotimehin, B. & Kadiri, S. & Muna, W. & Kingue, S. & Fraser, H. & Forrester, T. & Bennett, F. & Wilks, R., 1997. "The prevalence of hypertension in seven populations of West African origin," American Journal of Public Health, American Public Health Association, vol. 87(2), pages 160-168.
    7. Olufunke Alaba & Lumbwe Chola, 2014. "Socioeconomic Inequalities in Adult Obesity Prevalence in South Africa: A Decomposition Analysis," IJERPH, MDPI, vol. 11(3), pages 1-20, March.
    8. Weimann, Amy & Dai, Dajun & Oni, Tolu, 2016. "A cross-sectional and spatial analysis of the prevalence of multimorbidity and its association with socioeconomic disadvantage in South Africa: A comparison between 2008 and 2012," Social Science & Medicine, Elsevier, vol. 163(C), pages 144-156.
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