A Comparison of Mean-Based and Quantile Regression Methods for Analyzing Self-Report Dietary Intake Data

Abstract

In mean-based approaches to dietary data analysis, it is possible for potentially important associations at the tails of the intake distribution, where inadequacy or excess is greatest, to be obscured due to unobserved heterogeneity. Participants in the upper or lower tails of dietary intake data will potentially have the greatest change in their behavior when presented with a health behavior intervention; thus, alternative statistical methods to modeling these relationships are needed to fully describe the impact of the intervention. Using data from Tu Salud ¡Si Cuenta! (Your Health Matters!) at Home Intervention, we aimed to compare traditional mean-based regression to quantile regression for describing the impact of a health behavior intervention on healthy and unhealthy eating indices. The mean-based regression model identified no differences in dietary intake between intervention and standard care groups. In contrast, the quantile regression indicated a nonconstant relationship between the unhealthy eating index and study groups at the upper tail of the unhealthy eating index distribution. The traditional mean-based linear regression was unable to fully describe the intervention effect on healthy and unhealthy eating, resulting in a limited understanding of the association.

Protocol and statistical analysis plan for the phase 3 randomised controlled Treatment of Invasively Ventilated Adults with Early Activity and Mobilisation (TEAM III) trial

“…These results will be reported graphically and/or in tables that also show, for comparison, the mean TEAM intervention effect estimate across all quantiles returned from a similarly constructed linear mixed-effect model. 35 , 40 , 41 …”

“…These results will be reported graphically and/ or in tables that also show, for comparison, the mean TEAM intervention effect estimate across all quantiles returned from a similarly constructed linear mixed-effect model. 35,40,41 Results at each research site. The differential primary outcome according to randomised treatment group will be tabulated according to research site.…”