Cardiometabolic risk and scalable diagnostics in the Ghanaian population Advancing prevention, early detection and equitable cardiovascular care

Cardiometabolic diseases are an increasing cause of morbidity, premature mortality, and healthcare expenditure in Ghana, yet evidence spanning disease burden, upstream risk, and scalable diagnostic solutions remains limited. This thesis integrates six studies across a prevention–diagnostics continuum to characterize cardiometabolic risk and identify context-appropriate strategies for earlier detection and care in Ghanaian populations.
Cardiovascular admissions at a major tertiary hospital increased substantially over time, with heart failure—predominantly hypertension-related—accounting for most admissions, while ischaemic heart disease emerged rapidly. Acute cardiovascular hospitalizations were associated with high case fatality and substantial costs. A systematic review demonstrated a high burden of elevated lipoprotein(a) in African populations, particularly in West Africa. Among adults living with HIV in Ghana, peripheral artery disease was common and largely asymptomatic, highlighting opportunities for targeted vascular screening. In the prospective RODAM cohort, greater adherence to an animal-products dietary pattern was associated with increased incident type 2 diabetes among migrant and nonmigrant Ghanaians. Finally, the DAMSUN-HF study showed that artificial intelligence-enabled digital auscultation achieved high sensitivity for detecting heart failure with reduced ejection fraction and was feasible across multiple Ghanaian sites.
Collectively, these findings demonstrate an accelerating and largely preventable cardiometabolic disease burden alongside important gaps in early detection. They support a strategic shift from predominantly reactive hospital-based care toward integrated prevention, targeted risk detection, and scalable AI-enabled diagnostics embedded within strengthened referral pathways, with the potential to advance equitable cardiovascular care in Ghana and similar resource-limited settings.