Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/8371
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dc.contributor.authorDavids, Saarah Fatomaen_US
dc.contributor.authorMatsha, Tandi Edithen_US
dc.contributor.authorPeer, Nasheetaen_US
dc.contributor.authorErasmus, Rajiven_US
dc.contributor.authorKengne, Andre Pascalen_US
dc.date.accessioned2022-05-07T09:25:25Z-
dc.date.available2022-05-07T09:25:25Z-
dc.date.issued2019-
dc.identifier.citationDavids, S. F., Matsha, T. E., Peer, N. et al. 2019. Changes in Obesity phenotype distribution in mixed-ancestry South Africans in Cape Town between 2008/09 and 2014/16. Frontiers in Endocrinology, 10: 753. [http://doi.org/10.3389/fendo.2019.00753]en_US
dc.identifier.issn1664-2392-
dc.identifier.urihttp://hdl.handle.net/11189/8371-
dc.description.abstractBackground: 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.en_US
dc.language.isoenen_US
dc.publisherFrontiers Mediaen_US
dc.relation.ispartofFrontiers in Endocrinologyen_US
dc.subjectObesity phenotypeen_US
dc.subjectbody mass indexen_US
dc.subjectcardiometabolic risk factorsen_US
dc.subjecttrendsen_US
dc.subjectAfricaen_US
dc.titleChanges in Obesity phenotype distribution in mixed-ancestry South Africans in Cape Town between 2008/09 and 2014/16en_US
dc.identifier.doihttp://doi.org/10.3389/fendo.2019.00753-
dc.typeArticleen_US
Appears in Collections:HWSci - Journal Articles (DHET subsidised)
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