Patterns of health risk behaviors among job-seekers: a latent class analysis

Int J Public Health. 2015 Jan;60(1):111-9. doi: 10.1007/s00038-014-0623-1. Epub 2014 Dec 23.

Abstract

Objectives: To examine the patterning of four behavior-related health risk factors (tobacco smoking, risky alcohol drinking, overweight, and physical inactivity) among job-seekers and to investigate socio-demographic and health-related predictors of patterning.

Methods: The sample of 3,684 female and 4,221 male job-seekers was proactively recruited at three job agencies in northeastern Germany in 2008/09. Participants provided data on socio-demographics, substance use, body mass index, physical activity and self-rated health. Latent class analyses (LCA) and multinomial logistic regression analyses were applied to identify health risk patterns and possible predictors of patterning, respectively.

Results: Forty-three percent of the female and 58% of the male participants had two or more health risk factors. LCA revealed three similar patterns for women and men: Substance use (tobacco smoking, risky drinking), Non-exercising overweight (physical inactivity, overweight/obesity) and Health-conscious (non-smoking, low-risk drinking, under-/normal weight, physical activity). Age, education, marital status, life-time unemployment and self-rated health were significantly associated with patterning in both genders.

Conclusions: Our results may help to define target populations for improving health behaviors among job-seekers.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Age Factors
  • Alcohol Drinking / epidemiology*
  • Educational Status
  • Female
  • Germany / epidemiology
  • Health Behavior*
  • Humans
  • Job Application
  • Male
  • Middle Aged
  • Overweight / epidemiology*
  • Regression Analysis
  • Risk Factors
  • Risk-Taking*
  • Sedentary Behavior
  • Sex Factors
  • Smoking / epidemiology*
  • Social Class
  • Socioeconomic Factors
  • Unemployment / statistics & numerical data*
  • Young Adult