Female sex and cardiovascular disease risk in rural Uganda: a cross-sectional, population-based study

Sex-based differences in cardiovascular disease (CVD) burden are widely acknowledged, with male sex considered a risk factor in high-income settings. However, these relationships have not been examined in sub-Saharan Africa (SSA). We aimed to apply the American Heart Association (AHA) ideal cardiovascular health (CVH) tool modified by the addition of C-reactive protein (CRP) to examine potential sex-based differences in the prevalence of CVD risk in rural Uganda.

In a cross-sectional study nested within a population-wide census, 857 community-living adults completed physical and laboratory-based assessments to calculate individual ideal CVH metrics including an eight category for CRP levels. We summarized sex-specific ideal CVH indices, fitting ordinal logistic regression models to identify correlates of improving CVH. As secondary outcomes, we assessed subscales of ideal CVH behaviours and factors. Models included inverse probability of sampling weights to determine population-level estimates.

The weighted-population mean age was 39.2 (1.2) years with 52.0 (3.7) % females. Women had ideal scores in smoking (80.4% vs. 68.0%; p < 0.001) and dietary intake (26.7% vs. 16.8%; p = 0.037) versus men, but the opposite in body mass index (47.3% vs. 84.4%; p < 0.001), glycated hemoglobin (87.4% vs. 95.2%; p = 0.001), total cholesterol (80.2% vs. 85.0%; p = 0.039) and CRP (30.8% vs. 49.7%; p = 0.009). Overall, significantly more men than women were classified as having optimal cardiovascular health (6-8 metrics attaining ideal level) (39.7% vs. 29.0%; p = 0.025). In adjusted models, female sex was correlated with lower CVH health factors sub-scales but higher ideal CVH behaviors.

Contrary to findings in much of the world, female sex in rural SSA is associated with worse ideal CVH profiles, despite women having better indices for ideal CVH behaviors. Future work should assess the potential role of socio-behavioural sex-specific risk factors for ideal CVH in SSA, and better define the downstream consequences of these differences.