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Geographic distribution of cardiovascular comorbidities in South Africa: a national cross-sectional analysis

  • Ngianga Bakwin Kandala
  • , Samuel O.M. Manda
  • , William W. Tigbe
  • , Henry Mwambi
  • , Saverio Stranges
  • University of Warwick
  • Wellcome Trust Research Laboratories Nairobi
  • University of the Witwatersrand
  • South African Medical Research Council
  • University of KwaZulu-Natal

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Objectives: We sought to estimate the spatial coexistence of hypertension, coronary heart disease (CHD), stroke and hypercholesterolaemia in South Africa. Design: Cross-sectional. Setting: Sub-Saharan Africa and South Africa. Participants: Data were from 13,827 adults (mean±SD age 39±18 years, 58.4% women) interviewed in the 1998 South African Health and Demographic Survey. Interventions: N/A. Primary and secondary outcome measures: We used multivariate spatial disease models to estimate district-level shared and disease-specific spatial risk components, controlling for known individual risk factors. Results: In univariate analysis, observed prevalence of hypertension and CHD is was high in the south-western parts, and low in the north east. Stroke and high blood cholesterol prevalence appeared to be evenly distributed across the country. In multivariate analysis (adjusting for age, gender, ethnicity, education, urban-dwelling, smoking, alcohol consumption and obesity), hypertension and stroke prevalence were highly concentrated in the south-western parts, whilst CHD and hypercholesterolaemia were highly prevalent in central and top north-eastern corridor, respectively. The shared component, which we took to represent nutrition and other lifestyle factors not accounted for in the model, had a larger effect on cardiovascular disease prevalence in the south-western areas of the country. It appeared to have greater effect on hypertension and CHD. Conclusion: This study suggests a clear geographic distribution of cardiovascular disease in South Africa, driven possibly by shared lifestyle behaviours. These findings might be useful for public health resource allocation in low-income settings.

Original languageEnglish
Pages (from-to)1203-1216
Number of pages14
JournalJournal of Applied Statistics
Volume41
Issue number6
DOIs
StatePublished - Jun 2014

Keywords

  • dietary patterns
  • joint spatial models
  • lifestyle
  • non-communicable diseases

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