Individual and environmental factors associated with overweight among children in primary schools in Ghana
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Background Overweight/obesity is a risk factor for non-communicable diseases such as cardiovascular diseases, diabetes, and some cancers. Obesity in childhood is known to predict later obesity in adolescence and adulthood. Understanding the factors associated with overweight/obesity among children may present an opportunity for timely and appropriate interventions in the African setting. Aims 1. To describe the prevalence of overweight and obesity and associated factors among school children aged 8 - 11 years in primary schools in Adentan Municipality, Ghana. 2. To review the available literature on childhood obesity in the African context to provide evidence to support the design and improvement of appropriate school-based interventions for the prevention and control of overweight/obesity among African learners. Methodology This was a cross-sectional study design which was conducted in two phases. In Phase I, the available literature on the prevalence of overweight and obesity among learners, school-based interventions to promote healthy nutrition and physical activity (PA), and weight status, and key policy interventions at the national levels to provide supportive environments in the African context was reviewed and synthesised. In Phase II, interviews were conducted to collect individual and family data from 543 learners in 14 schools to assess family socio-demographics characteristics, dietary, PA, and sedentary behaviours, and sleep duration. Body weight, height, and waist circumference were measured. Data on perceived school neighbourhood/ community, school food, and PA environments were collected from school heads/administrators. A sub-sample of 183 children participated in the assessment of body fat using the deuterium dilution method. Multivariable and logistic regressions, multilevel logistic regressions, and multilevel linear regression models were used to examine the associations among child, family, and school level explanatory variables, and overweight/obesity, abdominal obesity and body mass index (BMI). Results The reviews revealed the following: (i) The pooled overweight and obesity estimates across Africa were: (10.5% 95% CI: 7.1-14.3) and 6.1% (3.4-9.7) by World Health Organization; 9.5% (6.5-13.0) and 4.0% (2.5-5.9) by International Obesity Task Force; and 11.5% (9.6-13.4) and 6.9% (5.0-9.0) by Centers for Disease Control and Prevention, respectively and differed for overweight (p=0.0027) and obesity (p<0.0001) by the criteria. The estimates were mostly higher in urban, and private schools, but generally similar by gender, major geographic regions, publication year, and sample size; (ii) Although inconsistent, school-based interventions broadly improved weight status and some energy-balance related health behaviours of African learners; (iii) On applying the Analysis Grid for Environments Linked to Obesity (ANGELO) framework, key interventions on unhealthy diets and physical inactivity targeted the school, family and community settings, and macro environments, and broadly aligned with global recommendations. In the school-based study, 16.4% of Ghanaian learners were overweight (9.2%) or obese (7.2%), with the prevalence being significantly higher in children from middle- to high socio-economic status (SES) households, and private schools. In multivariable regression models, attending private school (AOR = 2.44, 1.39–4.29) and excessive television viewing (AOR = 1.72, 1.05–2.82) significantly increased the likelihood of overweight/obesity, whereas adequate sleep (AOR = 0.53, 0.31–0.88), and active transport to and from school (AOR = 0.51, 0.31 – 0.82) decreased the odds. Using deuterium-derived percent body fat as criterion method, the published BMI criteria was found to be highly specific but with moderate sensitivity for diagnosing obesity among Ghanaian children. Moreover, the BMI-for-age z-scores that optimise sensitivity, specificity, and predictive values for obesity were lower than the published cut-off points. Multilevel logistic and linear regression analyses revealed that the school contextual level contributed 30.0%, 20.6% and 19.7% of the total variance observed in overweight (including obesity), abdominal obesity, and BMI respectively. Availability of school cafeteria (β = 1.83, p = 0.017) and shops (β = 2.34, p = 0.001), healthy foods (β = 0.77, p = 0.046), less healthy foods (β = 0.38, p = 0.048), child age (β = 0.40, p = 0.008), school-level SES (β = 1.02, p < 0.0001), private school attendance (β = -1.80, p = 0.006), and after-school recreational facilities (β = 0.89, p < 0.0001) were all associated with BMI. In the mutually adjusted models for all significant predictors, school-level SES, healthy foods, after-school recreational facilities, and PA facility index remained significant predictors of overweight and or abdominal obesity. Conclusions The prevalence of overweight/obesity is significantly higher in urban children attending private or high SES schools, regardless of criteria used to define obesity. A number of individual, family, and school-level factors significantly predicted weight status of school children in Ghana. Given that many African governments have initiated policy interventions aiming to provide supportive environments for healthy choices, it is recommended that resources are made readily available for the implementation of these interventions across the home, school and community.