ArticleBMJ open2019
Migration status and prevalence of diabetes and hypertension in Gauteng province, South Africa: effect modification by demographic and socioeconomic characteristics-a cross-sectional population-based study.
Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Empirical evidence of predictive adaptive response in humans: systematic review and meta-analysis of migrant populations.Journal of developmental origins of health and disease · 2023Pooled it
- The Healthy Aging Adult South Africa report card: a systematic review of the evidence between 2013 and 2020 for middle-aged South African men and women.Cardiovascular journal of AfricaPooled it
- Migration-driven exposome reconfiguration: a predictive, preventive and personalized medicine perspective on cardiometabolic risk.The EPMA journal · 2026Review
- Risk factors of hypertension in South Africa: A systematic review and meta-analysis to inform the development of a clinical prediction model.Health SA = SA Gesondheid · 2026Article
- Black South Africans Who Migrate Away From Their Rural Homes and Their Chances of Having Abdominal Obesity.American journal of human biology : the official journal of the Human Biology Council · 2025Article
- Hypertension and the Well-Being of African Migrants in South Africa.International journal of environmental research and public health · 2025Article
- Epidemiology of chronic multimorbidity and temporary migration in a rural South African community in health transition: A cross-sectional population-based analysis.Frontiers in epidemiology · 2023Article
- Haemoplasma Prevalence and Diversity in Three InvasiveMicroorganisms · 2022Article
- Pre-morbid cardiometabolic risks among South Africans living in informal settlements.Cardiovascular journal of AfricaArticle
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Authors and funding
2 authors.
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Abstract
introductionEvidence from low-income and middle-income countries suggests that migration status has an impact on health. However, little is known about the effect that migration status has on morbidity in sub-Saharan Africa. The aim of this study is to investigate the association between migration status and hypertension and diabetes and to assess whether the association was modified by demographic and socioeconomic characteristics.
methodsA Quality ofLife survey conducted in 2015 collected data on migration status and morbidity from a sample of 28 007 adults in 508 administrative wards in Gauteng province (GP). Migration status was divided into three groups: non-migrant if born in Gauteng province, internal migrant if born in other South African provinces, and external migrant if born outside of South Africa. Diabetes and hypertension were defined based on self-reported clinical diagnosis. We applied a recently developed original, stepwise-multilevel logistic regression of discriminatory accuracy to investigate the association between migration status and hypertension and diabetes. Potential effect modification by age, sex, race, socioeconomic status (SES) and ward-level deprivation on the association between migration status and morbidities was tested.
resultsMigrants have lower prevalence of diabetes and hypertension. In multilevel models, migrants had lower odds of reporting hypertension than internal migrants (OR=0.86; 95% CI 0.78 to 0.95) and external migrant (OR=0.60; 95% CI 0.49 to 0.75). Being a migrant was also associated with lower diabetes prevalence than being an internal migrant (OR=0.84; 95% CI 0.75 to 0.94) and external migrant (OR=0.53; 95% CI 0.41 to 0.68). Age, race and SES were significant effect modifiers of the association between migration status and morbidities. There was also substantial residual between-ward variance in hypertension and diabetes with median OR of 1.61 and 1.24, respectively.
conclusionsMigration status is associated with prevalence of two non-communicable conditions. The association was modified by age, race and SES. Ward-level effects also explain differences in association.
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