ArticleCurrent developments in nutrition2024
Decomposing Socioeconomic Effects on the Consumption of Calories and Macronutrients in Pakistan Between 2006 and 2016.
Article in Current developments in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Not yet cited in PubMed.
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Abstract
Background: This study examines the impact of socioeconomic factors on calorie intake and macronutrient composition at the household level in Pakistan from 2006 to 2016, using data from the Household Integrated Income and Consumption Survey (HIICS). By applying a copula-based decomposition method, it identifies key drivers such as urbanization, household size, paternal education, income, and cultivation, highlighting their roles in dietary changes and implications for public health. The findings are crucial for understanding nutritional shifts and addressing non-communicable diseases. Objectives: This study was conducted to assess the socioeconomic changes in total calorie intake per capita and calories obtained from macronutrients (fat, protein, and carbohydrates) at the household level in Pakistan. Methods: : Cross-sectional data were taken from 2 national-level surveys published by the Pakistan Bureau of Statistics: the Household Integrated Economic Survey 2006 (14,948 households) and the Household Integrated Income and Consumption Survey 2016 (7842 households). Participants were from all 4 provinces of Pakistan. A copula-based decomposition method was applied to decompose the 10-y change in the distribution (mean, median, and quartiles) of the total calorie intake per capita and calories obtained from macronutrients. Results: The estimated results of decomposition revealed that total calorie intake per capita has increased on average and in the considered quartiles. The calories obtained from fat and carbohydrates have increased, whereas calories from protein have decreased, according to the distribution of the mean and quartile. The composition effect was negative for all outcome variables, and the main drivers of the composition effect were urbanization, household size, paternal education, income, and cultivation for all outcome variables. Conclusions: Household size and income are the most important covariates in an increase of total calories per capita and consumption of macronutrients, but urbanization, paternal education, and cultivation contribute negatively to the composition effect. Such findings are very important to inform researchers about nutritional change at the national level because the correlation between dietary change and risk factors for noncommunicable diseases such as heart disease and obesity is very strong.
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