Fruit and Vegetable Consumption and Body Mass Index: A Quantile Regression Approach

Background: Empirical evidence on the relationship between consumption of fruits and vegetables and body weight is inconclusive. Previous studies mostly use linear regression methods to study the correlates of the conditional mean of body mass index (BMI). This approach may be less informative if the association between fruit and vegetable consumption and BMI significantly varies across the BMI distribution. Objective: The association between fruit and vegetable consumption and the BMI is examined using quantile regression. Methods: A nationally representative sample of 11,818 individuals from the Canadian Community Health Survey (2004) is used. A quantile regression model is estimated to account for the potential heterogeneous association between fruit and vegetable intake and BMI at different points of the conditional BMI distribution. The analyses are stratified by gender. Results: The multivariate analyses reveal that the association between fruit and vegetable intake and BMI is negative and statistically significant for both males and females; however, this association varies across the conditional quantiles of the BMI distribution. In particular, the estimates are larger for individuals at the higher quantiles of the distribution. The ordinary least squares (OLS) model overstates (understates) the association between FV intake and BMI at the lower (higher) half of the conditional BMI distribution. Conclusion: Findings of the standard models that assume uniform response across different quantiles of BMI distribution may be misleading. The findings of this paper suggest that increasing the intake of fruits and vegetables may be an effective dietary strategy t