ArticleBMJ global health2021
Estimating the burden of cardiovascular risk in community dwellers over 40 years old in South Africa, Kenya, Burkina Faso and Ghana.
Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Discrimination and calibration performances of non-laboratory-based and laboratory-based cardiovascular risk predictions: a systematic review.Open heart · 2025Pooled it
- Comparing Non-Laboratory-Based and Laboratory-Based Cardiovascular Risk Predictions: Systematic Review and Meta-Analysis.Health science reports · 2026Review
- Non-laboratory-based cardiovascular risk assessment: 10-year absolute risk, predicted heart age and intervention requirements in a Nigerian population.BMC cardiovascular disorders · 2026Article
- Systematic review and meta-analysis of cardiovascular disease risk among hypertensive patients in Africa.International journal of cardiology. Cardiovascular risk and prevention · 2026Review
- Diversity and Representation in Cardiovascular Research: Evidence Gaps, Emerging Models, and Policy Implications.International journal of environmental research and public health · 2026Review
- Population and health system factors affecting the transferability of health kiosks in markets in Kenya.International health · 2026Article
- Article
- Cardiovascular Risk among People Living with HIV in Ghana.Infection & chemotherapy · 2025Article
- Cardiovascular disease risk factors and the ten-year Cardiovascular disease risk among employees of a public university in Blantyre, Malawi.Malawi medical journal : the journal of Medical Association of Malawi · 2025Article
- Article
- Agreement between Framingham, Pooled Cohort Equations, and Globorisk-LAC in the Estimation of Cardiovascular Risk in Brazil, 2013.Arquivos brasileiros de cardiologia · 2025Article
- Cohort Profile: Africa Wits-INDEPTH partnership for Genomic studies (AWI-Gen) in four sub-Saharan African countries.International journal of epidemiology · 2024Article
- Ancestry-aligned polygenic scores combined with conventional risk factors improve prediction of cardiometabolic outcomes in African populations.Genome medicine · 2024Article
- Article
- Risk factor contributions to socioeconomic inequality in cardiovascular risk in the Philippines: a cross-sectional study of nationally representative survey data.BMC public health · 2023Article
- Cardiovascular Risk Estimation Based on Country-of-Birth- and Country-of-Residence-Specific Scores among Migrants in the Netherlands: The HELIUS Study.International journal of environmental research and public health · 2023Article
- Clinicians' Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa.Journal of personalized medicine · 2022Article
- Older persons experiences of healthcare in rural Burkina Faso: Results of a cross sectional household survey.PLOS global public health · 2022Article
- Cardiovascular disease risk profile and management among people 40 years of age and above in Bo, Sierra Leone: A cross-sectional study.PloS one · 2022Article
- Prevalence and socio-demographic associations of diet and physical activity risk-factors for cardiovascular disease in Bo, Sierra Leone.BMC public health · 2021Article
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11 authors.
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Abstract
introductionCardiovascular disease (CVD) risk factors are increasing in sub-Saharan Africa. The impact of these risk factors on future CVD outcomes and burden is poorly understood. We examined the magnitude of modifiable risk factors, estimated future CVD risk and compared results between three commonly used 10-year CVD risk factor algorithms and their variants in four African countries.
methodsIn the Africa-Wits-INDEPTH partnership for Genomic studies (the AWI-Gen Study), 10 349 randomly sampled individuals aged 40-60 years from six sites participated in a survey, with blood pressure, blood glucose and lipid levels measured. Using these data, 10-year CVD risk estimates using Framingham, Globorisk and WHO-CVD and their office-based variants were generated. Differences in future CVD risk and results by algorithm are described using kappa and coefficients to examine agreement and correlations, respectively.
resultsThe 10-year CVD risk across all participants in all sites varied from 2.6% (95% CI: 1.6% to 4.1%) using the WHO-CVD lab algorithm to 6.5% (95% CI: 3.7% to 11.4%) using the Framingham office algorithm, with substantial differences in risk between sites. The highest risk was in South African settings (in urban Soweto: 8.9% (IQR: 5.3-15.3)). Agreement between algorithms was low to moderate (kappa from 0.03 to 0.55) and correlations ranged between 0.28 and 0.70. Depending on the algorithm used, those at high risk (defined as risk of 10-year CVD event >20%) who were under treatment for a modifiable risk factor ranged from 19.2% to 33.9%, with substantial variation by both sex and site.
conclusionThe African sites in this study are at different stages of an ongoing epidemiological transition as evidenced by both risk factor levels and estimated 10-year CVD risk. There is low correlation and disparate levels of population risk, predicted by different risk algorithms, within sites. Validating existing risk algorithms or designing context-specific 10-year CVD risk algorithms is essential for accurately defining population risk and targeting national policies and individual CVD treatment on the African continent.
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