Association between social economic status and obesity in a rural South African community - Chisi, Songelwayo Lufu (My University, 2014)
Obesity is an emerging problem in South Africa, particularly in women for whom prevalence rates well above 40% have been reported. Parallel to this health problem, South Africa continues to experience relatively high poverty levels of 10.5% to 48.0%. The aim of this study was to estimate the prevalence of obesity and low social economic status (SES) levels at Agincourt Health and Socio-Demographic Surveillance System site (AHDSS). The study also sought to investigate the association between low SES and obesity at AHDSS. Materials and methods This was a secondary data analysis of the original Na Nakekela HIV/Non communicable disease (NCD) study conducted at AHDSS from August 2010 to May 2011. Included in the study presented in this report were residents of AHDSS aged 15 years or older during this time period. Data from 4 502 individuals (2 683 females and 1 819 males) were analysed. Age-specific prevalences of obesity (body mass index ≥ 30kg/m2), and central obesity (waist hip ratio ≥1.0 and ≥0.85 in men and women, respectively), stratified by sex and SES, were calculated. SES was assessed by ascertaining the household assets of AHDSS residents and assigning a weighted score to the household assets, using multiple correspondence analysis (MCA). The household score was then computed and used to classify the population into SES categories. The relative ranks of households, using this score, were then used as a measure of SES. The association between SES and obesity (BMI ≥ 30) was assessed by means of chi-square tests and logistic regression. Results The overall prevalence of obesity at the AHDSS in the study period was 20.4%. Overall, sex -specific prevalences of obesity were 29.3% and 7.4% in females and males, respectively. Females aged 50-59 years and males aged 45-49 years had the highest age-specific prevalence of obesity, at 40.1% and 18.3%, respectively. The overall prevalence of central obesity was 31.1%. Sex-specific prevalence of central obesity in females was 51.1%, while in males it was 4.9%. The highest age-specific prevalence of central obesity in both sexes was for those 70 years and older: 74.3% in females and 11.1% in males. Around 50% of individuals at the AHDSS were classified as belonging to lower SES categories, with females constituting 56.6% of these individuals. The highest prevalence of individuals in the high SES category was females aged 60-69 (14.5%) and males aged 70 (16.4%) years and older. After adjusting for other variables, being in a lower SES category was inversely associated with obesity as measured by BMI, as was being male and being HIV positive. The only positive predictor of high BMI was older age. No association between central obesity and lower SES was found after adjusting for confounders and other explanatory variables. However, older age was a predictor of central obesity. Being male, HIV positive and the male head of the household were factors that were inversely associated with central obesity. Discussion The high prevalence of individuals in the lower SES group (50.5%) reported in this study is similar to the Mpumalanga provincial poverty estimate of 51%.The ratio of obese females to males was at least 2.2 in every age group. The prevalence of central obesity in females of 51.1% in the AHDSS was higher than the national estimate of 47.1% for females, while the male estimate of 4.9% was lower than the 6.8% national estimate for males. In contrast to other studies, no associations between lower SES and obesity as measured by central obesity were observed. Conclusion and Recommendations Specific interventions to reduce obesity in females should be undertaken, including the provision of educational talks. This would empower them to make better informed decisions about food and lifestyle choices. These recommendations should be integrated into already existing HIV prevention programmes because HIV prevention is currently the main focus of policy makers in South Africa. Measures to reduce the number of individuals in the lower SES group, which this study reported to be very high (especially among women), e.g. through job creation, should be considered.
Research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science (MSc) in Epidemiology in the field of Epidemiology and Biostatistics
Keywords: Obesity; Socioeconomic Factors--South Africa