ArticleJournal of the American Heart Association2024
Prevalence of and Risk Factors for Peripheral Artery Disease in Rural South Africa: A Cross-Sectional Analysis of the HAALSI Cohort.
Article in Journal of the American Heart Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Pooled it
- Structural Cardiac Abnormalities, Ventricular Dysfunction Phenotypes, and Heart Failure Risk among Antiretroviral Therapy-treated People Living with HIV in South Africa.medRxiv : the preprint server for health sciences · 2026Article
- Systemic Inflammation and Malnutrition Define a High-Risk Phenotype in Chronic Limb-Threatening Ischemia.Journal of clinical medicine · 2026Article
- Human immunodeficiency virus in chronic limb-threatening ischaemia: Risk factors, management, and outcomes: A South African retrospective cohort study.Journal of the colleges of medicine of South Africa · 2026Article
- 2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.Circulation · 2025Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundThe burden of peripheral artery disease (PAD) is increasing in low- and middle-income countries. Existing literature from sub-Saharan Africa is limited and lacks population-representative estimates. We estimated the burden and risk factor profile of PAD for a rural South African population. METHODS AND
resultsWe used data from 1883 participants from a rural, low-income cohort of South African adults aged 40 to 69 years with available ankle-brachial index measurements. We defined clinical PAD as ankle-brachial index ≤0.90 or >1.40, and borderline PAD as ankle-brachial index >0.90 and ≤1.00. We compared the distribution of sociodemographic variables, biomarkers, and comorbidities across PAD classifications. To identify associated factors, we calculated unadjusted and age-sex-adjusted prevalence ratios (PRs) with log-binomial models. Overall, 6.6% (95% CI, 5.6-7.7) of the sample met the diagnostic criteria for clinical PAD, while 44.7% (95% CI, 42.4-47.0) met the diagnostic criteria for borderline PAD. Age (PR: 1.9 [95% CI, 1.2-3.1] for ages 50-59 years compared with 40-49 years; PR: 2.5 [95% CI, 1.5-4.0] for ages 60-69 years compared with 40-49 years); diagnosed hypertension (PR: 1.53 [95% CI, 1.08-2.17]); and C-reactive protein (PR: 1.08 [95% CI, 1.03-1.12]) were associated with increased prevalence of clinical PAD. All other examined factors were not significantly associated with clinical PAD.
conclusionsWe found high PAD prevalence for younger age groups compared with previous research and a lack of statistical evidence for the influence of traditional risk factors for this rural, low-income population. Future research should focus on identifying the underlying risk factors for PAD in this setting. South African policymakers and clinicians should consider expanded screening for early PAD detection in rural areas.
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