Clusters of health behaviours in Queensland adults are associated with different socio-demographic characteristics

J Public Health (Oxf). 2019 Jun 1;41(2):268-277. doi: 10.1093/pubmed/fdy043.

Abstract

Background: The co-occurrence of unhealthy lifestyles, calls for interventions that target multiple health behaviours. This study investigates the clustering of health behaviours and examines demographic differences between each cluster.

Methods: In total, 934 adults from Queensland, Australia completed a cross-sectional survey assessing multiple health behaviours. A two-step hierarchical cluster analysis using multiple iterations identified the optimal number of clusters and the subset of distinguishing health behaviour variables. Univariate analyses of variance and chi-squared tests assessed difference in health behaviours by socio-demographic factors and clusters.

Results: Three clusters were identified: the 'lower risk' cluster (n = 436) reported the healthiest profile and met all public health guidelines. The 'elevated risk' cluster (n = 105) reported a range of unhealthy behaviours such as excessive alcohol consumption, sitting time, fast-food consumption, smoking, inactivity and a lack of fruit and vegetables. The 'moderate risk behaviour' cluster (n = 393) demonstrated some unhealthy behaviours with low physical activity levels and poor dietary outcomes. The 'elevated risk' cluster were significantly younger and more socio-economically disadvantaged than both the 'lower and moderate risk' clusters.

Discussion: Younger people who live in more deprived areas were largely within the 'elevated risk' cluster and represent an important population for MHBC interventions given their wide range of unhealthy behaviours.

Keywords: clustering; health behaviours; multiple health behaviour change; public health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Alcoholism / epidemiology
  • Cluster Analysis
  • Cross-Sectional Studies
  • Diet / statistics & numerical data
  • Fast Foods / statistics & numerical data
  • Female
  • Fruit
  • Health Behavior*
  • Humans
  • Male
  • Middle Aged
  • Queensland / epidemiology
  • Sedentary Behavior
  • Smoking / epidemiology
  • Surveys and Questionnaires
  • Vegetables
  • Young Adult