How to Estimate Food Prices and Diet Costs in Population-Based Studies?

Author:

de Mello Aline Veroneze,Sarti Flavia Mori,Fisberg Regina Mara

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 [Inquérito de Saúde de São Paulo (ISA-Capital)] conducted in 2003, 2008, and 2015. Data referring to the household characteristics and food prices acquired by the household members living in São Paulo municipality were selected from the HBS datasets for integration with the ISA-Capital dataset. Specific deflators referring to the food items surveyed in São Paulo were obtained from the datasets of the Brazilian Broad Consumer Price Index (BCPI). Therefore, the pairing criteria referring to time, location, and household characteristics were adopted to allow linking foods consumed by the individuals in the ISA-Capital with the prices from the foods acquired by household members interviewed in the HBS. Matching data on the key pairing criteria (location/year/household income per capita/number of residents/family profile) resulted in the linkage of 94.4% (2003), 92.6% (2008), and 81.2% of the cases (2015). Following the data linkage, it was possible to estimate diet costs per gram and per calorie including application of cooking and conversion factors. Data were presented in the International Monetary Unit under the purchasing power parity (PPP) to allow the comparison at the international level. The mean diet costs identified in the population of São Paulo municipality were $8.45 (dp = 0.38) per capita per day in 2003, $8.72 (dp = 0.24) per capita per day in 2008, and $9.62 (dp = 0.23) per capita per day in 2015. Thus, it was possible to estimate the diet costs based on the prices of food items through pairing linkage of information from the household surveys, such as the Brazilian HBS, with the health and nutrition surveys lacking information on the expenditures or prices such as the ISA-Capital. Similar procedures may be used in the diverse countries with availability of the datasets of the household expenditures and health and nutrition surveys, allowing the researchers worldwide to associate the diet quality with food demand.

Publisher

Frontiers Media SA

Subject

Nutrition and Dietetics,Endocrinology, Diabetes and Metabolism,Food Science

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