ArticleFrontiers in nutrition2021
How to Estimate Food Prices and Diet Costs in Population-Based Studies?
Article in Frontiers in nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Association of monetary diet cost of foods and diet quality in Spanish older adults.Frontiers in public health · 2023Trial
- Environmental and economic impact of a vegan versus traditional mediterranean diet: OMNIVEG study.European journal of nutrition · 2026Article
- Differences in Cost-Effectiveness of Adherence to Nutritional Recommendations: Why, Where, and What?International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Health and nutrition surveys usually comprise detailed information on health characteristics and food consumption of certain population groups; however, the lack of data collection on the food prices may pose challenges for the estimation of the diet costs for the comprehensive analysis of food demand. The Household Budget Survey (HBS) represents an opportunity to obtain the data on the food prices for the nutrition surveys in the diverse countries worldwide. Although the HBS and the health and nutrition surveys may correspond to different periods, the application of the appropriate Consumer Price Index (CPI) allows to address the changes in the relative prices to perform the linkage between the data of food consumption with information on the food prices. Therefore, the aim of this study was to present the methods for the extraction and linkage of the food prices data from the Brazilian HBS (2002-2003 and 2008-2009) by using the pairing features related to the household characteristics to match the Health Survey of São Paulo [
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