PURPOSE: To describe differences in physical activity in the context of clustering patterns of health-promoting behaviors. DESIGN: A cross-sectional study with 1724 participants (response rate, 91.1%). SETTING: Tadami Town, in a rural area of Fukushima Prefecture, Japan. SUBJECTS: Part of the general population who participated in annual health checkups (age range, 30-93 years). MEASURES: The Health-Promoting Lifestyle Profile II was used to assess frequency of health-promoting behaviors (physical activity, health responsibility, spiritual growth, interpersonal relationships, nutrition, and stress management). Smoking status, alcohol consumption, and disease status were self-reported. Public health nurses measured the weight and height of participants. ANALYSIS: Cluster analysis was conducted to identify clustering patterns of health-promoting behaviors other than physical activity. Differences in physical activity between identified clusters were examined by multiple logistic regression analysis. RESULTS: Four clusters were identified and labeled as "Most challenged" (20.4%), "Adherence to norms" (30.3%), "Well in mentality" (20.9%), and "Health-promoting" (28.4%). "Health-promoting" was the most physically active cluster, followed by "Adherence to norms" and "Well in mentality." CONCLUSIONS: Although the survey methodology was subject to selection, self-report, and recall biases, we have described physical activity in the context of clustering patterns of health-promoting behaviors. Laying the groundwork for physical activity in the lifestyle is important for establishing health-promotion strategies to increase physical activity.
PURPOSE: To describe differences in physical activity in the context of clustering patterns of health-promoting behaviors. DESIGN: A cross-sectional study with 1724 participants (response rate, 91.1%). SETTING: Tadami Town, in a rural area of Fukushima Prefecture, Japan. SUBJECTS: Part of the general population who participated in annual health checkups (age range, 30-93 years). MEASURES: The Health-Promoting Lifestyle Profile II was used to assess frequency of health-promoting behaviors (physical activity, health responsibility, spiritual growth, interpersonal relationships, nutrition, and stress management). Smoking status, alcohol consumption, and disease status were self-reported. Public health nurses measured the weight and height of participants. ANALYSIS: Cluster analysis was conducted to identify clustering patterns of health-promoting behaviors other than physical activity. Differences in physical activity between identified clusters were examined by multiple logistic regression analysis. RESULTS: Four clusters were identified and labeled as "Most challenged" (20.4%), "Adherence to norms" (30.3%), "Well in mentality" (20.9%), and "Health-promoting" (28.4%). "Health-promoting" was the most physically active cluster, followed by "Adherence to norms" and "Well in mentality." CONCLUSIONS: Although the survey methodology was subject to selection, self-report, and recall biases, we have described physical activity in the context of clustering patterns of health-promoting behaviors. Laying the groundwork for physical activity in the lifestyle is important for establishing health-promotion strategies to increase physical activity.