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Urban–rural and geographic differences in overweight and obesity in four sub-Saharan African adult populations: a multi-country cross-sectional study

BACKGROUND: Overweight and obesity are on the rise in developing countries including sub-Saharan Africa. We undertook a four-country survey to show the collective burden of these health conditions as they occur currently in sub-Saharan Africa and to determine the differences between urban and rural...

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Detalles Bibliográficos
Autores principales: Ajayi, IkeOluwapo O., Adebamowo, Clement, Adami, Hans-Olov, Dalal, Shona, Diamond, Megan B., Bajunirwe, Francis, Guwatudde, David, Njelekela, Marina, Nankya-Mutyoba, Joan, Chiwanga, Faraja S., Volmink, Jimmy, Kalyesubula, Robert, Laurence, Carien, Reid, Todd G., Dockery, Douglas, Hemenway, David, Spiegelman, Donna, Holmes, Michelle D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5084330/
https://www.ncbi.nlm.nih.gov/pubmed/27793143
http://dx.doi.org/10.1186/s12889-016-3789-z
Descripción
Sumario:BACKGROUND: Overweight and obesity are on the rise in developing countries including sub-Saharan Africa. We undertook a four-country survey to show the collective burden of these health conditions as they occur currently in sub-Saharan Africa and to determine the differences between urban and rural populations and other socio-economic factors. METHODS: Participants were nurses in two hospitals in Nigeria (200), school teachers in South Africa (489) and Tanzania (229), and village residents in one peri-urban (297) and one rural location in Uganda (200) who completed a standardised questionnaire. Their height and weight were measured and body mass index calculated. Factor analysis procedure (Principal component) was used to generate a wealth index. Univariate and multivariate analyses with binary logistic regression models were conducted to examine the associations between potential correlates and the prevalence of overweight and obesity with 95 % confidence intervals. RESULTS: The prevalence of overweight and obese (combined) was 46 %, 48 %, 68 %, 75 % and 85 % in rural Uganda, peri-urban Uganda, Nigeria, Tanzania and South Africa (SA), respectively. Rural Uganda, Peri- urban Uganda, Nigeria, Tanzania and SA had obesity prevalence of 10 %, 14 %, 31 %, 40 % and 54 %, respectively (p < 0.001). Overall, prevalence of overweight was 374 (31 %) and obesity, 414 (34 %). Female sex was a predictor of overweight and obesity (combined) in peri-urban Uganda [AOR = 8.01; 95 % CI: 4.02, 15.96) and obesity in rural Uganda [AOR = 11.22; 95%CI: 2.27, 55.40), peri-urban Uganda [AOR = 27.80; 95 % CI: 7.13, 108.41) and SA [AOR = 2.17; 95 % CI: 1.19, 4.00). Increasing age was a predictor of BMI > =25 kg/m(2) in Nigeria [Age > =45 - AOR = 9.11; 95 % CI: 1.72, 48.16] and SA [AOR = 6.22; 95 % CI: 2.75, 14.07], while marital status was predictor of BMI > =25 kg/m(2) only in peri-urban Uganda. [Married - AOR = 4.49; 95 % CI: 1.74, 11.57]. Those in Nigeria [AOR = 2.56; 95 % CI: 1.45, 4.53], SA [AOR = 4.97; 95 % CI: 3.18, 7.78], and Tanzania [AOR = 2.68; 95 % CI: 1.60, 4.49] were more likely to have BMI > =25 kg/m(2) compared with the rural and peri-urban sites. CONCLUSION: The high prevalence of overweight and obesity in these sub-Saharan African countries and the differentials in prevalence and risk factors further highlights the need for urgent focused intervention to stem this trend, especially among women, professionals and urban dwellers.