Davids, S.FMatsha, T.EPeer, NErasmus, R.TKengne, A.P2024-09-012024-09-012019-11-06Davids SF, Matsha TE, Peer N, Erasmus RT and Kengne AP. (2019) Changes in Obesity Phenotype Distribution in Mixed-ancestry South Africans in Cape Town Between 2008/09 and 2014/16. Front. Endocrinol. 10:753. doi: 10.3389/fendo.2019.00753https://doi.org/10.3389/fendo.2019.00753https://www.frontiersin.org/articles/10.3389/fendo.2019.00753/fullhttps://hdl.handle.net/11288/597370Background: The concept of obesity phenotypes encompasses a different approach to evaluating the relationship between obesity and cardiometabolic diseases. Considering the minimal research on obesity phenotypes in Africa, we investigated these changes from 2008/09 to 2014/16 in the mixed ancestry population in Cape Town, South Africa. Methods: In all, 928 (2008/09) and 1969 (2014/16) ≥20 year old participants were included in two community-based cross-sectional studies. For obesity phenotype classification, a combination of body mass index (BMI) categories and prevalent cardiometabolic disease risk factors were used, with the presence of ≥2 cardiometabolic abnormalities defining abnormal metabolic status. Interaction tests were used to investigate changes in their distribution across the years of study. Results: Distribution of BMI categories differed significantly between the 2 years; normal weight, overweight and obese: 27.4, 27.4, and 45.3% in 2008/09 vs. 34.2, 23.6, and 42.2% in 2014/16 (p = 0.001). There was no differential effect in the distribution of obesity phenotypes pattern across the two time-points (interaction p = 0.126). Across BMI categories, levels of cardiometabolic risk factors linearly deteriorated in both metabolically healthy and abnormal participants (all p ≤ 0.018 for linear trends). Findings were not sensitive to the number of metabolic abnormalities included in the definition of obesity phenotypes. Conclusions: Our study showed negligible differences in obesity phenotypes over time, but a high burden of metabolic abnormalities among normal weight participants, and a significant proportion of metabolically health obese individuals. Further investigation is needed to improve risk stratification and cost-effective identification of individuals at high risk for cardiometabolic diseases.enAttribution 3.0 United Stateshttp://creativecommons.org/licenses/by/3.0/us/ObesityOverweightObesity phenotypesArticleFrontiers in Endocrinology