Abstract
This paper contributes to the analysis of the impact of socioeconomic factors, like food expenditure level and urbanization, on diet patterns in Vietnam, from 2004 to 2014. Contrary to the existing literature, we focus on the diet balance in terms of macronutrients consumption (protein, fat and carbohydrate) and we take into account the fact that the volumes of macronutrients are not independent. In other words, we are interested in the shares of each macronutrient in the total calorie intake. We use compositional data analysis (CODA), adapted to deal with the relative information contained in shares, to describe the evolution of diet patterns over time, and to model the impact of household characteristics on the macronutrient shares vector. We compute food expenditure elasticities of macronutrient shares, and we compare them to classical elasticities for macronutrient volumes and total calorie intake. The compositional model highlights the important role of many factors in the determination of diet choices and we will focus mainly on the role of food expenditure. Our results are consistent with the rest of the literature, but they have the advantage to highlight the substitution effects between macronutrients in the context of nutrition transition.
Keywords
Macronutrient shares; diet pattern; compositional regression models; expenditure elasticity; Vietnam;
JEL codes
- C02: Mathematical Methods
- C21: Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions
- C51: Model Construction and Estimation
- P46: Consumer Economics • Health • Education and Training • Welfare, Income, Wealth, and Poverty
Replaces
Joanna Morais, and Thi-Huong Trinh, “Impact of socioeconomic factors on nutritional diet in Vietnam from 2004 to 2014: new insights using compositional data analysis”, TSE Working Paper, n. 17-825, June 2017.
Reference
Michel Simioni, Christine Thomas-Agnan, and Thi-Huong Trinh, “Relations between socio-economic factors and nutritional diet in Vietnam from 2004 to 2014: New insights using compositional data analysis”, Statistical Methods in Medical Research Journal, vol. 28, n. 8, August 2019, pp. 2305–2325.
See also
Published in
Statistical Methods in Medical Research Journal, vol. 28, n. 8, August 2019, pp. 2305–2325