• S. Afr. Med. J. · Mar 2021

    Economic growth as an underlying probable systemic driver for childhood obesity in South Africa: A Joinpoint regression and ecological analysis over 10 years.

    • P T Pisa, N M Pisa, P Chikandiwa, and A Chikandiwa.
    • MRC/Wits Developmental Pathways for Health Research Unit, Department of Paediatrics and Child Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Department of Human Nutrition and Dietetics, Faculty of Health Sciences, University of Pretoria, South Africa; Right to Care, Centurion, South Africa. pppedropissa@gmail.com.
    • S. Afr. Med. J. 2021 Mar 2; 111 (3): 220-226.

    BackgroundChildhood obesity has become a global public health problem and is a known risk factor for type 2 diabetes, cardiovascular disease, hypertension, stroke, myocardial infarction and various cancers in later adulthood.Associations between adult obesity and economic growth, technological changes, socioeconomic status and economic inequities have been reported, but limited data are available for children and adolescents in countries that are undergoing an epidemiological health transition exhibiting both under- and overnutrition.ObjectivesTo demonstrate childhood obesity trends and explore their associations with economic growth in South Africa (SA).MethodsThis was a retrospective review and analysis of obesity and economic growth trends in SA. Data for obesity levels were obtained from national surveys conducted in SA youths in 2002, 2008 and 2012. Economic growth indicators (EGIs), namely gross domestic product (GDP) per capita, household final consumption expenditure and Gini coefficient, were obtained from the World Bank and IHS Global Insight databases. Obesity trends for 2002 - 2012 are presented by gender and ethnicity. Annual percentage changes (APCs) in obesity prevalence were computed to assess obesity trends using the linear Joinpoint regression.ResultsAn overall increase in obesity prevalence over time from 3.8% to 6.0% was observed. Females had higher levels across all time points. APCs in both males (7.8%; 95% confidence interval (CI) 0.3 - 15.9; p=0.01) and females (3.1%; 95% CI -14.7 - 24.7; p=0.30) were observed. Among black Africans, coloureds and whites, females had higher obesity levels than males for the three time points. For males, the prevalence of obesity was highest in whites and Asians/Indians, whereas coloureds and blacks had lower levels across all time points. However, the black male population had the highest APC increase (9.4%; 95% CI -23.0 - 55.3; p=0.20). The prevalence of obesity was positively and inversely associated with GDP per capita and the Gini coefficient, respectively.ConclusionsAn increase in childhood and adolescent obesity over time was observed, while trend associations between obesity and EGIs exist.

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