Geographic variation of hypertension in sub-saharan Africa: a case study of South Africa

Am J Hypertens. 2013 Mar;26(3):382-91. doi: 10.1093/ajh/hps063. Epub 2013 Jan 8.


Background: Hypertension is of public health importance in sub-Saharan Africa, with considerable underdiagnosis, poor management, and lack of community-wide preventive strategies. We examined the geographic variation of hypertension at the province level in South Africa, while accounting for individual-level risk factors such as sociodemographics, lifestyle, and cardiovascular comorbidities.

Methods: Our analysis was based on the South African Demographic and Health Survey, including 13,596 men and women aged 15 years and over. Individual data were collected on lifestyle habits and cardiovascular comorbidities, but were aggregated to the nine country's provinces. We used a Bayesian geo-additive mixed model to map the geographic distribution of hypertension at the province level, accounting for individual risk factors.

Results: The overall prevalence of hypertension (blood pressure ≥140/90 mmHg or self-reported diagnosis or on medication) was 30.4%. In multivariate Bayesian geo-additive models, current smokers (odds ratio [OR] and 95% credible region [CR]: 1.14 [1.03, 1.26]), current drinkers (1.17 [1.05, 1.29]), people reporting sleep problems (1.16 [1.02, 1.31]), and participants with prevalent cardiovascular comorbidities, such as type 2 diabetes (2.49 [1.92, 3.13]), were significantly associated with a higher prevalence of hypertension. There was a striking variation in hypertension prevalence across provinces, the highest being in North West (1.33 [1.14, 1.61]), Free State (1.32 [1.08, 1.68]) and Northern Cape (1.30 [1.02, 1.55]), the lowest in Limpopo (0.68 [0.56, 0.84]).

Conclusions: This study showed distinct geographic patterns in hypertension prevalence in South Africa, suggesting the potential role of socioeconomic, nutritional, and environmental factors at the province level, beyond individual-level risk factors in this setting.

MeSH terms

  • Adolescent
  • Adult
  • Africa South of the Sahara / epidemiology
  • Bayes Theorem
  • Black People / statistics & numerical data*
  • Comorbidity
  • Cross-Sectional Studies
  • Female
  • Health Surveys
  • Humans
  • Hypertension / epidemiology*
  • Life Style
  • Male
  • Prevalence
  • Risk Factors
  • Rural Health
  • Socioeconomic Factors
  • South Africa / epidemiology
  • Urban Health