Decoding 10-Year Cardiovascular Risk in Ethiopia: The Impact of Individual and Community Factors

Highlight

This retrospective, population-based study quantified the 10-year primary cardiovascular disease (CVD) risk in Ethiopian adults aged 40-69 using the 2019 WHO CVD risk equation, revealing that 7.3% have a ≥10% risk of developing CVD. Individual factors such as urban residency, lower education, retirement status, and low physical activity, alongside community-level climatic factors like higher water vapour pressure and cooler temperatures, significantly influence risk.

Study Background and Disease Burden

Cardiovascular disease remains a leading cause of morbidity and mortality globally, with a growing impact in low- and middle-income countries, including Ethiopia. Despite improvements in infectious disease control, non-communicable diseases such as CVD are rising with demographic and epidemiologic transitions. Prior to this study, comprehensive quantification of primary CVD risk at the individual and community levels in Ethiopia was lacking, especially using updated WHO risk prediction models. Understanding these determinants is vital for targeted prevention and resource allocation to mitigate CVD burden in this population.

Study Design

This retrospective, population-based, cross-sectional observational study utilized data collected in 2015 from Ethiopia’s nationally representative WHO STEPwise Approach to Noncommunicable Disease Risk Factor Surveillance (STEPS) survey. The study included 2658 participants aged 40-69 years from 453 enumeration areas across Ethiopia. The primary outcome was the calculated 10-year risk of developing primary CVD, utilizing the validated 2019 WHO CVD risk equation. Risk factors integrated in the calculation included age, smoking status, systolic blood pressure, diabetes history, and total cholesterol levels. Exclusions were made for participants with missing data, pregnancy, or existing CVD history. Multilevel regression analyses assessed the association of individual-level variables (education, employment status, physical activity, residence) and community-level environmental factors (water vapour pressure, climate temperature) with CVD risk.

Key Findings

Among 2658 Ethiopian adults analyzed, 7.3% (95% CI 6.3-8.2) exhibited a 10-year primary CVD risk ≥10%. Analysis revealed key individual factors significantly associated with increased CVD risk:

• Urban residence: Urban dwellers had a higher CVD risk (β coefficient = 0.88%, 95% CI 0.60-1.15; p<0.0001) compared to rural residents. Odds of risk ≥10% were twice as high (adjusted OR 2.03; 95% CI 1.26-3.27; p=0.0031).
• Employment status: Individuals retired or unable to work demonstrated elevated risk (β 0.50%, p=0.028), with adjusted odds ratio 2.01 (95% CI 1.15-3.49; p=0.014) compared to employed or able unemployed persons.
• Physical activity: Low physical activity correlated with increased CVD risk (β 0.46%, p=0.0021). Participants with low activity had an adjusted odds ratio of 2.35 (95% CI 1.47-3.76; p<0.0001) versus those with high activity.
• Education level: Lower education independently predicted higher risk. Those with primary education or less had an adjusted OR of 4.14 (95% CI 1.25-13.68; p=0.021), and those with secondary education had OR 4.04 (95% CI 1.15-14.10; p=0.028), compared to college-educated participants.

Community-level factors also influenced CVD risk:

• Water vapour pressure: Higher atmospheric moisture correlated with increased CVD risk (β 1.56%, 95% CI 0.68-2.43; p<0.0001).
• Climate temperature: Hotter climates showed a modest protective effect relative to cooler climates (β -0.07%, 95% CI -0.14 to -0.01; p=0.023).

These findings emphasize the complex multifactorial nature of cardiovascular risk in Ethiopia, encompassing socioeconomic, lifestyle, and environmental determinants.

Expert Commentary

The use of the updated 2019 WHO CVD risk model, calibrated and validated globally, lends robust applicability to this Ethiopian cohort. The stratification by individual and community levels adds critical granularity, highlighting vulnerable subpopulations that may benefit from targeted interventions. Urbanization is linked with lifestyle changes favoring sedentary behavior and dietary risk factors, explaining the urban risk elevation. Elevated risk in retirees/unable to work may reflect accumulated comorbidities and socioeconomic disadvantage.

Notably, the environmental findings are novel, suggesting that humid conditions may exacerbate cardiovascular stress, possibly via mechanisms such as higher blood viscosity or inflammation, while warmer temperate zones confer some protective effect. These environmental interactions merit further mechanistic investigation to inform localized public health strategies.

Some limitations include the cross-sectional design precluding causal inference, reliance on a secondary dataset collected in 2015 which may not capture current trends, and potential unmeasured confounding from dietary or genetic factors not addressed by the data.

Conclusion

This pioneering population-based study quantifies the 10-year primary cardiovascular disease risk in Ethiopia and identifies distinct individual-level and community-level determinants. Findings underscore the need for proactive screening and intervention in urban populations, those with lower education, retirees or those unable to work, and persons with low physical activity. Additionally, environmental context – particularly water vapour pressure and climate temperature – should be considered in regional CVD prevention strategies. These insights can guide tailored public health policies and resource allocation aimed at reducing Ethiopia’s growing cardiovascular disease burden.

References

1. Alemu YM, Bagheri N, Wangdi K, Chateau D. Individual-level and community-level factors for 10-year cardiovascular disease risk in Ethiopia: a retrospective, population-based, cross-sectional, observational study. Lancet Glob Health. 2025 Sep;13(9):e1574-e1582. doi: 10.1016/S2214-109X(25)00226-8. PMID: 40845883.
2. World Health Organization. WHO cardiovascular disease risk charts: revised models to estimate risk in 21 global regions. Eur J Prev Cardiol. 2019;26(2):129-134.
3. Gaziano TA, et al. Cardiovascular disease screening and risk reduction in low-resource settings: feasibility and accuracy of a modified WHO risk score in Sub-Saharan Africa. Glob Heart. 2017;12(1):1-5.