Causal effects of socioeconomic status on central adiposity risks: Evidence using panel data from urban Mexico

Abstract

Associated with overweight, obesity and chronic diseases, the nutrition transition process reveals important socioeconomic issues in Mexico. Using panel data from the Mexican Family Life Survey, the purpose of the study is to estimate the causal effect of household socioeconomic status (SES) on nutritional outcomes among urban adults. We divide the analysis into two steps. First, using a mixed clustering procedure, we distinguish four socioeconomic classes based on income, educational and occupational dimensions: (i) a poor class; (ii) a lower-middle class; (iii) an upper-middle class; (iv) a rich class. Second, using an econometric framework adapted to our study (the Hausman-Taylor estimator), we measure the impact of belonging to these socioeconomic groups on individual anthropometric indicators, based on the body-mass index (BMI) and the waist-to-height ratio (WHtR). Our results make several contributions: (i) we show that a new middle class, rising out of poverty, is the most exposed to the risks of adiposity; (ii) as individuals from the upper class seem to be fatter than individuals from the upper-middle class, we can reject the assumption of an inverted U-shaped relationship between socioeconomic and anthropometric status as commonly suggested in emerging economies; (iii) the influence of SES on central adiposity appears to be particularly strong for men.

Gene and environment interaction: Is the differential susceptibility hypothesis relevant for obesity?

“…A recent Mexican study showed that a new middle class, rising out of poverty, is the most exposed to adiposity risk; individuals from the upper class seem to be fatter than individuals from the upper middle class; and the influence of SES on central adiposity appears to be particularly strong for men. The results reveal that education and work status (positions with high levels of responsibility vs. precarious and informal activities) have important and independent effects on anthropometric health indicators (Levasseur, 2015). Educational disparities can impact dietary knowledge and, consequently, how people classify foods as healthy or unhealthy as well as food purchasing behavior (Bhurosy and Jeewon, 2014).…”

Risk of developing pre-diabetes or diabetes over time in a cohort of Mexican health workers

“…The surge in weight gain is attributed to changes in lifestyle commonly observed in lowand middle-income countries that have experienced recent advances in per capita socioeconomic resources. [29,30] This increased income has resulted in a higher consumption of calorie-dense, nutrient-poor, low-fiber foods and a corresponding decrease in the consumption of fresh fruits and vegetables, and minimally processed grains and legumes [31]. Globalization, urbanization and increased marketing by multinational food companies have provided low-income populations in Mexico with increased exposure to ultra-processed foods that are high in calories, saturated fat and sugar, and low in dietary fiber and nutritional value [32].…”

The nutrition transition in Mexico 1988–2016: the role of wealth in the social patterning of obesity by education

“…As countries develop and economies become largely based on service industries, most 10 can afford high-calorie foods and avoid physical labour. As living conditions improve and food 11 availability, accessibility and diversity increases, disadvantaged populations become at risk of 12 obesity (5) . At the same time, more advantaged groups may become more health conscious and 13 western ideas of attractiveness associated with thinness may set in which protects them from 14 obesity.…”

“…Therefore, we hypothesise that within countries, 26 household wealth will be an effect modifier in the association between education and obesity. 27 Education will be protective of obesity over a certain level of household wealth and will not be 28 protective within very poor households (5) . We use five waves of Mexican nationally 29 representative data covering a period of 28 years over which there was sustained economic 30 development and important changes in the food environment in the country (10) .…”