**Background:** Sub-Saharan Africa (SSA) is experiencing rapid urbanisation and increasing life expectancy, driving a rise in non-communicable diseases (NCDs). Multimorbidity—the co-occurrence of two or more chronic conditions—poses major challenges for individuals, healthcare systems, and policy-makers. There is a paucity of multimorbidity data from SSA, particularly comparing multiple countries and settings. This study aimed to determine the prevalence of multimorbidity, identify disease clusters, and examine sociodemographic and lifestyle correlates across six communities in four SSA countries.
**Methods:** Data were drawn from the AWI-Gen study, a population-based cross-sectional study of adults aged 40–60 years (n=10,700; 4,808 men, 5,892 women) from six sites: Soweto, Agincourt, and Dikgale (South Africa); Nairobi (Kenya); Navrongo (Ghana); and Nanoro (Burkina Faso). Multimorbidity was defined as the presence of two or more of seven conditions: HIV infection, cardiovascular disease (CVD), chronic kidney disease (CKD), asthma, diabetes, dyslipidaemia, and hypertension. Hypertension was defined as systolic BP ≥140 mm Hg and/or diastolic BP ≥90 mm Hg or use of antihypertensives. Diabetes was defined by fasting glucose ≥7 mmol/L, random glucose ≥11.1 mmol/L, or medication use. Dyslipidaemia was defined by total cholesterol ≥5.0 mmol/L, HDL-C <1.0 mmol/L (men) or <1.3 mmol/L (women), LDL-C ≥3.0 mmol/L, triglycerides ≥1.7 mmol/L, or lipid-lowering medication. CKD was defined as eGFR <60 mL/min/1.73 m² (CKD-EPI equation) or albuminuria (urine albumin:creatinine ratio >3 mg/mmol). CVD and asthma were self-reported. Sociodemographic data, smoking, alcohol consumption (categorised as never, current problematic, current non-problematic, former), physical activity (MVPA min/week via GPAQ), and BMI were collected. Multinomial logistic regression was used to identify factors associated with having one condition or multimorbidity (vs. zero conditions), stratified by sex.
**Key Results:** Multimorbidity prevalence was higher in women than men overall (47.2% vs. 35%), and highest in South Africa (women 64.9%, men 51.7%), followed by East Africa (women 48.4%, men 31.3%) and West Africa (women 24.1%, men 20.2%). The site with the highest prevalence was Agincourt (66.6%) and the lowest was Nanoro (21.2%). The most common two-disease combination at all sites was dyslipidaemia and hypertension (men 12%, women 18% of total sample). In South African women, this combination was more prevalent than any single disease (25% vs. 21.6%). Among those with three conditions, the most common cluster in men was dyslipidaemia, hypertension, and CKD (2% of total sample); in women it was dyslipidaemia, hypertension, and HIV (3.2%). In multinomial regression, age was associated with higher multimorbidity risk in both sexes (women: RRR 1.04, 95% CI 1.02–1.06, p<0.001; men: RRR 1.03, 95% CI 1.02–1.05, p<0.001). Each 1 kg/m² increase in BMI was associated with an 11% higher risk of multimorbidity in women (RRR 1.11, 95% CI 1.08–1.14, p<0.001) and 14% in men (RRR 1.14, 95% CI 1.11–1.18, p<0.001). In women, former alcohol consumption was associated with higher multimorbidity risk (RRR 1.97, 95% CI 1.37–2.84, p<0.001). In men, current non-problematic alcohol consumption was associated with lower multimorbidity risk (RRR 0.68, 95% CI 0.51–0.89, p=0.006), and higher MVPA was associated with lower risk (RRR 0.99 per 100 min/week, 95% CI 0.99–0.10, p=0.004). Being married or previously partnered was associated with higher multimorbidity risk in men (married/cohabiting: RRR 1.53, 95% CI 1.10–2.15, p=0.011; divorced/separated/widowed: RRR 2.43, 95% CI 1.62–3.65, p<0.001). Employment was associated with lower multimorbidity risk in men (RRR 0.77, 95% CI 0.61–0.98, p=0.033).
**Clinical Implications:** The high prevalence of multimorbidity—particularly the dominant dyslipidaemia-hypertension cluster—underscores the need for integrated, multi-disease management strategies rather than single-disease approaches in SSA. The strong association with BMI highlights obesity as a critical intervention target. Sex differences in lifestyle correlates (alcohol, physical activity) suggest that interventions may need to be sex-stratified. As the epidemiological transition progresses, multimorbidity prevalence is expected to rise in East and West Africa and in men, making early, context-specific policy and health system planning essential. Limitations include the cross-sectional design, single screening for CKD (potential overestimation), incomplete data for Soweto women (only 4 of 7 conditions), and reliance on self-report for some conditions.