ArticleGlobal heart2020
Determinants of Mortality from Cardiovascular Disease in the Slums of Nairobi, Kenya.
Article in Global heart, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Decomposing wealth-based inequalities in ideal cardiovascular health in Kenya.Communications medicine · 2025Article
- Tobacco use patterns and associated factors among youth in Kampala's informal settlements: a cross-sectional study in Bwaise.BMC public health · 2025Article
- Bridging the gaps in the unmet needs of hypertension care in Nigeria: post-intervention evaluation of the community action against non-communicable diseases (COMAAND) project.BMC public health · 2025Article
- Cardiovascular disease risk estimation among slums residents of Lucknow using QRISK3 calculator.Journal of education and health promotion · 2025Article
- No Evidence for an Association of HIV and Antiviral Treatment With Changes in Framingham Cardiovascular Risk Score in the Ndlovu Cohort Study.Journal of the American Heart Association · 2024Article
- Article
- Trends and risk factors for non-communicable diseases mortality in Nairobi slums (2008-2017).Global epidemiology · 2021Article
- Comparative performance of pooled cohort equations and Framingham risk scores in cardiovascular disease risk classification in a slum setting in Nairobi Kenya.International journal of cardiology. Heart & vasculature · 2020Article
- Article
- Effect of a Nurse-Led Intervention on Knowledge of the Modifiable Risk Behaviors of Cardiovascular Disease: A Randomized Controlled Trial.SAGE open nursingArticle
- PASCAR and WHF Cardiovascular Diseases Scorecard project.Cardiovascular journal of AfricaArticle
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6 authors.
Funding
Abstract
Background: Cardiovascular diseases (CVD) comprise eighty percent of non-communicable disease (NCD) burden in low- and middle-income countries and are increasingly impacting the poor inequitably. Traditional and socioeconomic factors were analyzed for their association with CVD mortality over 10 years of baseline assessment in an urban slum of Nairobi, Kenya. Methods and results: A 2008 survey on CVD risk factors was linked to cause of death data collected between 2008 and 2018. Cox proportional hazards on relative risk of dying from CVD over a 10-year period following the assessment of cardiovascular disease risk factors were computed. Population attributable fraction (PAF) of incident CVD death was estimated for key risk factors. In total, 4,290 individuals, 44.0% female, mean age 48.4 years in 2008 were included in the analysis. Diabetes and hypertension were 7.8% and 24.9% respectively in 2008. Of 385 deaths recorded between 2008 and 2018, 101 (26%) were caused by CVD. Age (hazard ratio (HR) 1.11; 95% confidence interval (CI) 1.03-1.20, p = 0.005) and hypertension (HR 2.19, 95% CI 1.44-3.33, p <0.001) were positively associated with CVD mortality. Primary school education and higher (HR 0.57, 95% CI 0.33-0.99, p = 0.044) and formal employment (HR 0.22, 95% CI 0.06-0.75, p = 0.015) were negatively associated with CVD mortality. Controlling hypertension would avert 27% (95% CI 9%-42%, p = 0.004) CVD deaths, while if every member of the community attained primary school education and unemployment was eradicated, 39% (95% CI 5% - 60%, p = 0.026), and 17% (95% CI 5%-27%, p = 0.030) of CVD deaths, would be averted respectively. Conclusions: A holistic approach in addressing socioeconomic factors in the broader context of social determinants of health at the policy, population and individual level will enhance prevention and treatment-adherence for CVD in underserved settings.
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