Evaluation of daily eating patterns on overall diet quality using decision tree analyses.

BACKGROUND

Preliminary evidence suggests that meal timing is associated with higher quality diets. Less is known about whether types of food consumed during specific eating episodes (i.e., day-level eating patterns) predict diet quality.

OBJECTIVES

We investigated the association between day-level eating patterns and diet quality.

METHODS

Decision tree models were built using 24-h dietary recall data from the National Health and Nutrition Examination Survey 2015 and 2017 cycles in a cross-sectional study. Sixteen food groups and 12 eating episodes (e.g., breakfast, lunch) were included as input parameters. Diet quality was scored using the Healthy Eating Index-2020 and categorized as higher or lower quality diets based on the median score. Mean decrease in impurity (MDI) ± standard deviation determined the relative contribution that day-level eating patterns had on diet quality; higher values represented greater contributions.

RESULTS

We analyzed 12,597 dietary recalls from 9347 United States adults who were aged 18 y and older with ≥1 complete recall. Meals (breakfast, lunch, dinner) and respective snacking episodes had the greatest variety of dietary groups that contributed to the Healthy Eating Index-2020 score. Any whole-grain intake at breakfast predicted a higher quality diet (MDI = 0.08 ± 0.00), followed by lower solid fat intake (<8.94 g; MDI = 0.07 ± 0.00) and any plant protein intake at dinner (MDI = 0.05 ± 0.00).

CONCLUSIONS

Day-level eating patterns were associated with diet quality, emphasizing the relevance of both food type and timing in relation to a high-quality diet. Future interventions should investigate the potential impact of targeting food type and timing to improve diet quality.