Health Lifestyles: Audience Segmentation Analysis for Public Health Interventions

Abstract

This article is concerned with the application of market segmentation techniques in order to improve the planning and implementation of public health education programs. Seven distinctive patterns of health attitudes, social influences, and behaviors are identified using cluster analytic techniques in a sample drawn from four central California cities, and are subjected to construct and predictive validation: The lifestyle clusters predict behaviors including seatbelt use, vitamin C use, and attention to health information. The clusters also predict self-reported improvements in health behavior as measured in a two-year follow-up survey, e.g., eating less salt and losing weight, and self-reported new moderate and new vigorous exercise. Implications of these lifestyle clusters for public health education and intervention planning, and the larger potential of lifestyle clustering techniques in public health efforts, are discussed.