Jennifer Manne-Goehler1,2,3, Kathy Baisley4,5, Alain Vandormael6,7, Till Bärnighausen5,6,8, Frank Tanser5,9,10, Kobus Herbst5,11, Deenan Pillay5,12, Mark J Siedner1,2,3,5. 1. Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA. 2. Harvard Medical School, Boston, Massachusetts, USA. 3. Medical Practice Evaluation Center, Massachusetts General Hospital, Boston, Massachusetts, USA. 4. Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK. 5. Africa Health Research Institute, KwaZulu-Natal, South Africa. 6. Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany. 7. KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), University of KwaZulu-Natal, KwaZulu-Natal, South Africa. 8. Department of Global Health and Population and Harvard Center for Population and Development Studies, Harvard School of Public Health, Boston, Massachusetts, USA. 9. Lincoln International Institute for Rural Health, University of Lincoln, Lincoln, UK. 10. School of Nursing and Public Health, University of KwaZulu-Natal, KwaZulu-Natal, South Africa. 11. SAPRIN, South African Medical Research Council, Cape Town, South Africa. 12. Division of Infection and Immunity, University College, London, UK.
Abstract
OBJECTIVE: This study evaluates the association between BMI and all-cause and cause-specific mortality in South Africa. METHODS: Prospective, population-based observational cohort data from rural South Africa were analyzed. BMI was measured in 2010. Demographic characteristics were recorded and deaths were verified with verbal autopsy interview. The InterVA-5 tool was used to assign causes of death. HIV testing was conducted annually. Cox proportional hazards models were fit to estimate the effect of BMI on all-cause and cause-specific mortality, accounting for the competing risk of death from other causes. Models were adjusted for sociodemographic characteristics and HIV status, and inverse probability weighting for survey nonparticipation was used. RESULTS: The cohort consisted of 9,728 individuals. In adjusted models, those with BMI of 25.0 to 29.9 kg/m2 or 30.0 to 34.9 kg/m2 had a lower hazard of death (adjusted hazard ratio: 0.80; 95% CI: 0.69-0.92 and adjusted hazard ratio: 0.75; 95% CI: 0.60-0.93, respectively) compared with those with BMI of 18.5 to 24.9 kg/m2 . CONCLUSIONS: Individuals in South Africa who meet clinically defined criteria for overweight or obesity had a lower risk of all-cause mortality than those with a normal BMI. These findings were stronger for women and communicable conditions.
OBJECTIVE: This study evaluates the association between BMI and all-cause and cause-specific mortality in South Africa. METHODS: Prospective, population-based observational cohort data from rural South Africa were analyzed. BMI was measured in 2010. Demographic characteristics were recorded and deaths were verified with verbal autopsy interview. The InterVA-5 tool was used to assign causes of death. HIV testing was conducted annually. Cox proportional hazards models were fit to estimate the effect of BMI on all-cause and cause-specific mortality, accounting for the competing risk of death from other causes. Models were adjusted for sociodemographic characteristics and HIV status, and inverse probability weighting for survey nonparticipation was used. RESULTS: The cohort consisted of 9,728 individuals. In adjusted models, those with BMI of 25.0 to 29.9 kg/m2 or 30.0 to 34.9 kg/m2 had a lower hazard of death (adjusted hazard ratio: 0.80; 95% CI: 0.69-0.92 and adjusted hazard ratio: 0.75; 95% CI: 0.60-0.93, respectively) compared with those with BMI of 18.5 to 24.9 kg/m2 . CONCLUSIONS: Individuals in South Africa who meet clinically defined criteria for overweight or obesity had a lower risk of all-cause mortality than those with a normal BMI. These findings were stronger for women and communicable conditions.
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