Food Away From Home and Body Mass Index: Insights From a Quantile Regression Analysis of NHANES 2011-2020

Food away from home (FAFH) has several health implications and is believed to be a contributing factor to the rise in obesity. However, studies focusing on the impact of FAFH along the distribution of body mass index (BMI) remain scarce. This cross-sectional study is aimed at using nationally representative survey data over multiple years to examine whether FAFH affects individuals differently based on their BMI.

Data from the four recent cycles of the US National Health and Nutrition Examination Survey (NHANES) were pooled for analysis. Quantile regression (QR) method was utilized to model the outcome of interest "BMI" and the exposure "FAFH," adjusted for potential confounders. The use of QR allowed differential effects of FAFH on BMI to be evident that would otherwise be masked using a linear or logistic regression model. Survey weights were applied in all analyses to address the complex sampling procedure of the NHANES.

QR method showed differential effects of FAFH on conditional BMI distribution. For individuals in the lower tail of the BMI distribution (0.05 quantile), three or more FAFH a week was associated with BMI increase of 0.29 kg/m² (95% CI: 0.00, 0.58) compared with less than three FAFH. The effect became stronger at the middle quantiles with the strongest effect observed at the 0.60 quantile, where individuals consuming three or more FAFH a week had a BMI of 0.41 kg/m² (95% CI: 0.12, 0.71) higher than those consuming FAFH less frequently. Although higher consumption of FAFH was associated with increased BMI for individuals in lower to middle quantiles, the effect at the upper tail (0.90 quantile), representing individuals in the highest BMI range, was not statistically significant. Additional investigation at the upper quantiles revealed that the association remained statistically significant at 0.70 quantile, whereas estimates at the 0.80 and 0.95 quantiles remained positive but were not statistically significant.

QR revealed a broadly positive FAFH-BMI association across the BMI distribution, with statistically significant associations through the 70th percentile and less precise estimates in the upper tail. Although further research is needed to better understand these associations, our findings highlight the importance of considering distributional patterns and statistical uncertainty when evaluating the impact of FAFH consumption on BMI and designing public health interventions.