Clusters of Healthy and Unhealthy Eating Behaviors Are Associated With Body Mass Index Among Adults

Abstract

Objective: To identify eating styles from 6 eating behaviors and test their association with body mass index (BMI) among adults.

Design: Cross-sectional analysis of self-report survey data.

Setting: Twelve primary care and specialty clinics in 5 states.

Participants: Of 11,776 adult patients who consented to participate, 9,977 completed survey questions.

Variables measured: Frequency of eating healthy food, frequency of eating unhealthy food, breakfast frequency, frequency of snacking, overall diet quality, and problem eating behaviors. The primary dependent variable was BMI, calculated from self-reported height and weight data.

Analysis: k-Means cluster analysis of eating behaviors was used to determine eating styles. A categorical variable representing each eating style cluster was entered in a multivariate linear regression predicting BMI, controlling for covariates.

Results: Four eating styles were identified and defined by healthy vs unhealthy diet patterns and engagement in problem eating behaviors. Each group had significantly higher average BMI than the healthy eating style: healthy with problem eating behaviors (β = 1.9; P < .001), unhealthy (β = 2.5; P < .001), and unhealthy with problem eating behaviors (β = 5.1; P < .001).

Conclusions and implications: Future attempts to improve eating styles should address not only the consumption of healthy foods but also snacking behaviors and the emotional component of eating.

Keywords: behavioral science; body mass index; eating patterns; nutrition; obesity.