Behavioral Cluster Analysis of Food Consumption: Associations with Comparatively Healthier Food Choices

Abstract

Objectives – To identify demographic, behavioral, and health factors associated with food choices among communitydwelling adults. Methods – A cross-sectional health assessment was used for the study. K-means cluster analysis identified natural groupings of individuals reporting similar food choices among four categories: fruits, vegetables, sugared beverages, and fast food. Multinomial logistic regression identified differences in comparatively healthier food choices between the clusters. Results – Six unique cluster profiles of eating habits and food consumption were identified. Demographic, behavioral, and health factors were associated with variations in healthy food consumption. Compared to those in the cluster representing the least healthiest food choices, members of the cluster exhibiting the most healthy food choices were less likely to report physical illness (OR = 0.97, p<0.001). These cluster members were also 2.34 times as likely to be female (OR = 2.34, p<0.001), 2.78 times as likely to have earned more than a high school education (OR = 2.78, p<0.001), and 1.13 times as likely to spend more days per week engaging in at least 10 minutes of moderate physical activity (OR = 1.13, p<0.001) when compared to their counterparts in the cluster representing the least healthiest food choices. Conclusion – Comparatively poorer food choices of community members remains an essential and modifiable indicator of existing health status. Interventions to achieve healthy food choices should utilize a multi-level approach that emphasizes the role of important covariates.