Epidemiology of multimorbidity in low-income countries of sub-Saharan Africa: Findings from four population cohorts

Abstract

We investigated prevalence and demographic characteristics of adults living with multimorbidity (≥2 long-term conditions) in three low-income countries of sub-Saharan Africa, using secondary population-level data from four cohorts; Malawi (urban & rural), The Gambia (rural) and Uganda (rural). Information on; measured hypertension, diabetes and obesity was available in all cohorts; measured hypercholesterolaemia and HIV and self-reported asthma was available in two cohorts and clinically diagnosed epilepsy in one cohort. Analyses included calculation of age standardised multimorbidity prevalence and the cross-sectional associations of multimorbidity and demographic/lifestyle factors using regression modelling. Median participant age was 29 (Inter quartile range-IQR 22–38), 34 (IQR25-48), 32 (IQR 22–53) and 37 (IQR 26–51) in urban Malawi, rural Malawi, The Gambia, and Uganda, respectively. Age standardised multimorbidity prevalence was higher in urban and rural Malawi (22.5%;95% Confidence intervals-CI 21.6–23.4%) and 11.7%; 95%CI 11.1–12.3, respectively) than in The Gambia (2.9%; 95%CI 2.5–3.4%) and Uganda (8.2%; 95%CI 7.5–9%) cohorts. In multivariate models, females were at greater risk of multimorbidity than males in Malawi (Incidence rate ratio-IRR 1.97, 95% CI 1.79–2.16 urban and IRR 2.10; 95% CI 1.86–2.37 rural) and Uganda (IRR- 1.60, 95% CI 1.32–1.95), with no evidence of difference between the sexes in The Gambia (IRR 1.16, 95% CI 0.86–1.55). There was strong evidence of greater multimorbidity risk with increasing age in all populations (p-value <0.001). Higher educational attainment was associated with increased multimorbidity risk in Malawi (IRR 1.78; 95% CI 1.60–1.98 urban and IRR 2.37; 95% CI 1.74–3.23 rural) and Uganda (IRR 2.40, 95% CI 1.76–3.26), but not in The Gambia (IRR 1.48; 95% CI 0.56–3.87). Further research is needed to study multimorbidity epidemiology in sub-Saharan Africa with an emphasis on robust population-level data collection for a wide variety of long-term conditions and ensuring proportionate representation from men and women, and urban and rural areas.