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Impact of Socio-Economic Factors on Nutrition Efficiency: An Application of Data Envelopment Analysis

BACKGROUND: Paying particular attention to sustainable food consumption in low-income households is essential for increasing human health. Due to the growing population globally, this concept will likely become more serious soon. METHODS: Following the importance of optimizing food consumption for s...

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Detalles Bibliográficos
Autores principales: Pakravan-Charvadeh, Mohammad Reza, Flora, Cornelia Butler, Emrouznejad, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9085191/
https://www.ncbi.nlm.nih.gov/pubmed/35548565
http://dx.doi.org/10.3389/fnut.2022.859789
Descripción
Sumario:BACKGROUND: Paying particular attention to sustainable food consumption in low-income households is essential for increasing human health. Due to the growing population globally, this concept will likely become more serious soon. METHODS: Following the importance of optimizing food consumption for sustainability, in this study, a novel methodology is introduced for calculating nutrient intake efficiency and determining choices of food in different locations. The impact of socio-economic factors on nutrition efficiency is assessed. Data Envelopment Analysis (DEA) as a well-known linear programming (LP) and a Tobit model are used to achieve the goals. Household Consumption and Expenditure Surveys (HCESs) of 30,000 rural and urban Iranian households in all provinces in 2016 are analyzed. A Nutrient Efficiency Map (NEM) of Iran was depicted by GIS software. RESULTS: The results showed that many townships had nutrient efficiency scores of less than 70%. Northeast townships had the lowest scores, with an efficiency score of less than 50%. Overall, townships have lower efficiency in the North (seaside cities), East (desert cities), and North East (isolated cities) when compared with other areas. CONCLUSION: Therefore, it is suggestible that the government should modify the support policies and the protection packages based on social, geographical, and cultural status.