Cultural and economic macro-environmental determinants of obesity: an analysis of 70 countries.

Background: Obesity is essentially caused by an energy imbalance whereby energy intake exceeds the amount of energy expenditure. Due to multifactorial nature of obesity, its determinants span from cell to society. Much of the research on obesity determinants has focused on individual level risk factors including genetic endowment, behavioural factors, socio-demographic and socio-economic status. Recent research has acknowledged the role of environmental factors that create obesity-promoting spaces for residents. The ANGELO (Analysis Grid for Environments Linked to Obesity) Framework is an appropriate tool for understanding the role of environment in obesity development. It divides environmental factors into multiple types (e.g., economic, physical, policy, socio and cultural) and scales (micro and macro) of environments. Among these, macro-level culture and economic environment are the most neglected factors in obesity research and most researches on culture and economics are focused on the micro-environment level. The aim of this study was to explore the effect of country level cultural and economic macro-environments on individual level BMI after controlling for individual and country level factors. Methods: Seventy-two different datasets were used in this thesis including 70 datasets from World Health Survey (WHS) for 70 countries, World Bank Datasets and the Hofstede cultural dimensions dataset. The outcome variable (BMI) and all individual level explanatory variables (Age, gender, marital status, education level, household wealth, occupation, living in urban or rural area) were derived from the WHS datasets. Data on national income (GNI-PPP) and income inequality (Gini index) were collected from World Bank Datasets. Data on country level cultural dimensions, uncertainty avoidance, individualism power distance and masculinity were collected from Hofstede cultural dimensions data. The design based descriptive analysis (analysis with sampling design features) was performed for BMI and all individual-level variables for 70 countries. Bivariate and multivariate associations were examined between the BMI and country level national income, income inequality and cultural dimensions after controlling for individual level variables. R-statistical software with survey and lme4 packages was used for analysis. Results: A sample of 2,062,66 people from 70 countries was included. The weighted mean BMI(SE) in these 70 countries was 23.9(4.84). In high-income countries, male, married, had lower education level, lower household wealth, manual occupations and living in rural areas had higher BMI. In low-income countries female, married, had higher education level, higher household wealth, professional occupations and living in urban areas had higher BMI. Multilevel analysis shows that national income (β=0.48,p<0.001) was significantly associated with BMI after controlling for individual level factors. To determine the association of country level cultural dimensions and BMI, a sample of 156,192 people from 53 countries was included. The weighted mean BMI(SE) in these 53 countries was 23.95(0.08). Uncertainty avoidance (β=0.03,p<0.001) and individualism (β=0.03,p<0.001) had a significant positive association with BMI. Income inequality (β=0.06,p<0.05) was significantly associated with BMI after controlling for cultural dimensions. Conclusion: Higher uncertainty avoidance and individualism cultures of the countries were associated with a higher individual level BMI. However, power distance and masculinity cultures were not associated with individual level BMI. Countries higher national income and income inequality were associated higher BMI. These results indicate that culture should be a consideration in the development of public health policies to address obesity. For instance, a public health policy or programme in a country with higher uncertainty avoidance scores may focus on more familiar approaches, which may be more readily embraced. If new approaches are to be used then enough time needs to be allowed for people to develop an understanding of the initiative to help foster confidence in it. Involving the community in projects and project development may allow them a sense of understanding, and then decrease the element of the unknown.