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Multicenter Study
. 2017 Nov;10(11):e004094.
doi: 10.1161/CIRCOUTCOMES.117.004094.

Disparities in Management of Cardiovascular Disease in Rural South Africa: Data From the HAALSI Study (Health and Aging in Africa: Longitudinal Studies of International Network for the Demographic Evaluation of Populations and Their Health Communities)

Thiago Veiga Jardim  1 , Sheridan Reiger  1 , Shafika Abrahams-Gessel  1 , Nigel J Crowther  1 , Alisha Wade  1 , F Xavier Gómez-Olivé  1 , Joshua Salomon  1 , Stephen Tollman  1 , Thomas A Gaziano  2
Affiliations
Multicenter Study

Disparities in Management of Cardiovascular Disease in Rural South Africa: Data From the HAALSI Study (Health and Aging in Africa: Longitudinal Studies of International Network for the Demographic Evaluation of Populations and Their Health Communities)

Thiago Veiga Jardim et al. Circ Cardiovasc Qual Outcomes. 2017 Nov.

Abstract

Background: Optimal secondary prevention is critical for the reduction of repeated cardiovascular events, and the control of cardiovascular risk factors in this context is essential. Data on secondary prevention of cardiovascular disease (CVD) in sub-Saharan Africa are needed to inform intervention strategies with a particular focus on local disparities. The aim of this study was to assess CVD management in a rural community in northeast South Africa.

Methods and results: We recruited adults aged ≥40 years residing in the Agincourt subdistrict of Mpumalanga province. Data collection included socioeconomic and clinical data, anthropometric measures, blood pressure, human immunodeficiency virus status, and point-of-care glucose and lipid levels. CVD was defined as self-report of myocardial infarction and stroke or angina diagnosed by Rose Criteria. A linear regression model was built to identify variables independently associated with the number of cardiovascular risk factors controlled. Of 5059 subjects, 592 (11.7%) met CVD diagnostic criteria. Angina was reported in 77.0% of these subjects, stroke in 25.2%, and myocardial infarction in 3.7%. Percent controlled of the 5 individual risk factors assessed were as follows: tobacco 92.9%; blood pressure 51.2%; body mass index 33.8%; low-density lipoprotein 31.4%; and waist-to-hip ratio 29.7%. Only 4.4% had all 5 risk factors controlled and 42.4% had ≥3 risk factors controlled. Male sex (β coefficient=0.44; 95% confidence interval, 0.25-0.63; P<0.001), absence of physical disability (β coefficient=0.40; 95% confidence interval, 0.16-0.65; P=0.001), and socioeconomic status (β coefficient=0.10; 95% confidence interval, 0.01-0.19; P=0.035) were directly associated with the number of risk factors controlled.

Conclusions: Currently, CVD is not being optimally managed in this rural area of South Africa. There are significant disparities in control of CVD risk factors by sex, socioeconomic status, and level of disability. Efforts to improve secondary prevention in this population should be focused on females, subjects from lower socioeconomic status, and those with physical disabilities.

Keywords: South Africa; aging; body mass index; cardiovascular diseases; secondary prevention.

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Figures

Figure 1
Figure 1. Number of risk factors* controlled among subjects with CVD† stratified by sex, Agincourt sub-district, South Africa 2015 (n=592)
*LDL cholesterol < 1.8mmol/L; blood pressure < 140 × 90 mmHg; not smoking; waist-hip ratio: ≤ 0.90 (men) or ≤ 0.85 (women); body mass index < 25 kg/m2. †CVD – cardiovascular disease (self-report of Stroke/Myocardial Infarction or Angina by Rose criteria).
Figure 2
Figure 2. Cardiovascular risk factors controlled* stratified by angina, myocardial infarction and stroke, Agincourt sub-district, South Africa 2015
*LDL cholesterol < 1.8mmol/L; blood pressure < 140 × 90 mmHg; not smoking; waist-hip ratio: ≤ 0.90 (men) or ≤ 0.85 (women); body mass index < 25 kg/m2. †MI – myocardial infarction.
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