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O98 ASSOCIATION BETWEEN FOOD PRICES AND BODY WEIGHT IN BRAZILIAN ADULTS, 2007 TO 2018

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  1. Ufmg, Belo Horizonte, Brazil
  2. UFV, Viçosa, Brasil
  3. UESC, Ilhéus, Brasil.

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Abstract

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O98 ASSOCIATION BETWEEN FOOD PRICES AND BODY WEIGHT IN BRAZILIAN ADULTS, 2007 TO 2018

Objective: To estimate the association between food prices and BMI, prevalence of overweight and prevalence of obesity among Brazilian adults (≥ 18 years), from 2007 to 2018. Methods: Panel study involving ecological data from 10 Brazilian capitals and Federal District (FD) for the period between 2007 and 2018. Data on food price from national Household Budget Survey (HBS 2008/9) were used to calculate real price of four food groups over time using the monthly variation in prices from National System of Consumer Price Indexes (NSCPI). Based on this, relative price of healthy foods (healthy groups) was established for each city and year of study (defined as the ratio between the price of non-ultra-processed foods and the price of ultra-processed foods). Data on body weight of individuals from Surveillance System of Risk and Protective Factors for Chronic Diseases by Telephone Survey (VIGITEL) were used to estimate mean BMI, prevalence of overweight and obesity of each capital per year. Fixed effect regression models for panel data were estimated. Results: The relative price of healthy foods was positively associated the population’s BMI and the prevalence of overweight and obesity. We observed that a 10.0% increase in the relative price of healthy foods, would lead to 0.3% increase in mean BMI, 1.6% in prevalence of overweight and 2.1% in prevalence of obesity. Conclusions: The present study revealed the positive association between relative price of healthy foods and body weight among adults in Brazil. Policy Implications: Fiscal policies capable to increase the price of ultra-processed foods or reduce the price of all other groups should be encouraged to combat obesity in the country.

Keywords: food prices, ultra-processed foods, obesity, panel data, public health.


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