Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies
Web of Science
AuthorKengne, AP; Bentham, J; Zhou, B; Peer, N; Matsha, TE; Bixby, H; Di Cesare, M; Hajitathalian, K; Lu, Y; Taddei, C; ...
Source TitleInternational Journal of Epidemiology
PublisherOXFORD UNIV PRESS
University of Melbourne Author/sMagliano, Dianna
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsKengne, A. P., Bentham, J., Zhou, B., Peer, N., Matsha, T. E., Bixby, H., Di Cesare, M., Hajitathalian, K., Lu, Y., Taddei, C., Bovet, P., Kyobutungi, C., Agyemang, C., Aounallah-Skhiri, H., Assah, F. K., Barkat, A., Ben Romdhane, H., Chan, Q., Chaturvcdi, N. ,... Mbanya, J. C. N. (2017). Trends in obesity and diabetes across Africa from 1980 to 2014: an analysis of pooled population-based studies. INTERNATIONAL JOURNAL OF EPIDEMIOLOGY, 46 (5), pp.1421-1432. https://doi.org/10.1093/ije/dyx078.
Access StatusOpen Access
Background: The 2016 Dar Es Salaam Call to Action on Diabetes and Other non-communicable diseases (NCDs) advocates national multi-sectoral NCD strategies and action plans based on available data and information from countries of sub-Saharan Africa and beyond. We estimated trends from 1980 to 2014 in age-standardized mean body mass index (BMI) and diabetes prevalence in these countries, in order to assess the co-progression and assist policy formulation. Methods: We pooled data from African and worldwide population-based studies which measured height, weight and biomarkers to assess diabetes status in adults aged ≥ 18 years. A Bayesian hierarchical model was used to estimate trends by sex for 200 countries and territories including 53 countries across five African regions (central, eastern, northern, southern and western), in mean BMI and diabetes prevalence (defined as either fasting plasma glucose of ≥ 7.0 mmol/l, history of diabetes diagnosis, or use of insulin or oral glucose control agents). Results: African data came from 245 population-based surveys (1.2 million participants) for BMI and 76 surveys (182 000 participants) for diabetes prevalence estimates. Countries with the highest number of data sources for BMI were South Africa (n = 17), Nigeria (n = 15) and Egypt (n = 13); and for diabetes estimates, Tanzania (n = 8), Tunisia (n = 7), and Cameroon, Egypt and South Africa (all n = 6). The age-standardized mean BMI increased from 21.0 kg/m2 (95% credible interval: 20.3-21.7) to 23.0 kg/m2 (22.7-23.3) in men, and from 21.9 kg/m2 (21.3-22.5) to 24.9 kg/m2 (24.6-25.1) in women. The age-standardized prevalence of diabetes increased from 3.4% (1.5-6.3) to 8.5% (6.5-10.8) in men, and from 4.1% (2.0-7.5) to 8.9% (6.9-11.2) in women. Estimates in northern and southern regions were mostly higher than the global average; those in central, eastern and western regions were lower than global averages. A positive association (correlation coefficient ≃ 0.9) was observed between mean BMI and diabetes prevalence in both sexes in 1980 and 2014. Conclusions: These estimates, based on limited data sources, confirm the rapidly increasing burden of diabetes in Africa. This rise is being driven, at least in part, by increasing adiposity, with regional variations in observed trends. African countries' efforts to prevent and control diabetes and obesity should integrate the setting up of reliable monitoring systems, consistent with the World Health Organization's Global Monitoring System Framework.
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