Dietary quality and associated factors among adults living in the state of São Paulo, Brazil

J Am Diet Assoc. 2006 Dec;106(12):2067-72. doi: 10.1016/j.jada.2006.09.010.

Abstract

This study sought to analyze dietary quality and associated factors among adults living in regions of the State of São Paulo, Brazil. It was a cross-sectional population-based study of a sample of 3,454 adults ages 20 years and over who were included in the Household Health Survey. Dietary intake was measured by means of the 24-hour recall method, and dietary quality was assessed by means of the Healthy Eating Index (HEI), adapted to local realities. Probabilistic samples were obtained via multistage cluster samples from four regions in the State of São Paulo. Linear regression analyses were performed to evaluate the relationships between the HEI and the demographic, socioeconomic, and lifestyle variables. Among the individuals assessed, 5% had a good diet, 74% a diet that needed some degree of improvement, and 21% a poor diet. The means for HEI components were lowest for vegetables, fruits, and dairy products. The highest HEI scores were obtained by individuals who were nonsmokers, practiced physical activity, were retired, lived in houses or apartments, and had adequate living conditions surrounding them. In the multiple regression analysis, the variables of numbers of consumer durable goods, schooling of the head of the family, energy intake, and age had a positive association with the HEI. However, the association was inverse for the variables of smoking and body mass index. Higher dietary quality is associated with higher income, higher schooling level, better nutritional status, and being a nonsmoker. Knowledge of these factors is important for implementing programs for preventive nutrition or intervention.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brazil
  • Cluster Analysis
  • Cross-Sectional Studies
  • Dairy Products
  • Diet / standards*
  • Diet Surveys*
  • Educational Status
  • Exercise / physiology*
  • Female
  • Fruit
  • Health Status Indicators*
  • Humans
  • Life Style
  • Linear Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Nutritional Status
  • Obesity / epidemiology*
  • Smoking
  • Socioeconomic Factors
  • Vegetables