Background: Public health research, practice and policy focus on many health behaviors (HBs). Therefore, five studies were conducted to create the Health Behavior Taxonomy (HBT), a classification representing meaningful clusters of HBs, based on lay-perceptions. Methods: A comprehensive list of HBs was elicited from lay people and professionals (N=100), and their perceived importance was rated (N=266). A card sorting task and cluster analysis were applied (N=374), and replicated (N=510). Results: 66 HBs were reduced to the 45 most important ones. Hierarchical cluster analysis using similarity data revealed a taxonomy consisting of 4 main clusters (General well-being, Avoiding risk, Nutrition, and Physical health routines), representing the cognitive schema by which people process and integrate information regarding HBs. Clusters differed by importance judgments, and minor yet interpretable variations in clustering were associated with gender and age. Compared to the HBT, engagement reports formed a divergent structure. Discussion: The HBT can advance health promotion programs and cost-effectiveness of interventions by targeting clusters of meaningfully linked health behaviors.
