Physical activity in the context of clustering patterns of health-promoting behaviors

Am J Health Promot. 2011 Jul-Aug;25(6):410-6. doi: 10.4278/ajhp.090720-QUAN-232.

Abstract

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.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Body Mass Index
  • Cluster Analysis
  • Counseling
  • Cross-Sectional Studies
  • Exercise*
  • Female
  • Health Behavior*
  • Health Promotion / methods*
  • Health Status
  • Humans
  • Interpersonal Relations
  • Japan
  • Life Style*
  • Logistic Models
  • Male
  • Middle Aged
  • Population Surveillance
  • Rural Population / statistics & numerical data