Abstract

This study focused on adult obesity prevalence in Goiânia, Goiás State, Brazil, and the association between socio-demographic variables, lifestyle, physical activity, eating habits, and food consumption frequency and body mass index (BMI). A cross-sectional study was conducted in 2001 with a sample of 1,252 individuals from 20 to 64 years of age. The association between socio-demographic variables, lifestyle, food consumption, and physical activity and BMI was evaluated by hierarchical multiple linear regression analysis. Obesity prevalence was 10.7% in men and 13.9% in women. In males, age, income, and meat consumption showed a positive association with BMI, while physical activity during leisure time and commuting and the habit of eating > 4 meals per day were inversely associated with BMI. In women, positively associated factors were age, no smoking, and no meat consumption; in contrast, consumption of grains was inversely associated with BMI. High obesity prevalence was observed; active lifestyle coupled with ingestion of more grains and less meat appeared to protect against increased BMI.

Highlights

  • This study focused on adult obesity prevalence in Goiânia, Goiás State, Brazil, and the association between socio-demographic variables, lifestyle, physical activity, eating habits, and food consumption frequency and body mass index (BMI)

  • Age, income, and meat consumption showed a positive association with BMI, while physical activity during leisure time and commuting and the habit of eating ≥ 4 meals per day were inversely associated with BMI

  • The objective of the current study were to measure the prevalence of excess weight and obesity in the adult population in the city of Goiânia, Goiás State, Brazil, associated with variables related to socio-demographic conditions, lifestyle, physical activity, eating frequency and habits, and BMI

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Summary

Introduction

This study focused on adult obesity prevalence in Goiânia, Goiás State, Brazil, and the association between socio-demographic variables, lifestyle, physical activity, eating habits, and food consumption frequency and body mass index (BMI). The association between sociodemographic variables, lifestyle, food consumption, and physical activity and BMI was evaluated by hierarchical multiple linear regression analysis. Age, income, and meat consumption showed a positive association with BMI, while physical activity during leisure time and commuting and the habit of eating ≥ 4 meals per day were inversely associated with BMI. Positively associated factors were age, no smoking, and no meat consumption; in contrast, consumption of grains was inversely associated with BMI. High obesity prevalence was observed; active lifestyle coupled with ingestion of more grains and less meat appeared to protect against increased BMI

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