Mid-aged adults' sitting time in three contexts

Am J Prev Med. 2012 Apr;42(4):363-73. doi: 10.1016/j.amepre.2011.11.012.

Abstract

Background: To develop evidence-based approaches for reducing sedentary behavior, there is a need to identify the specific settings where prolonged sitting occurs, associated factors, and variations.

Purpose: To examine the sociodemographic and health factors associated with mid-aged adults' sitting time in three contexts and variations between weekdays and weekend days.

Methods: A mail survey was sent to 17,000 adults (aged 40-65 years) in 2007; 11,037 responses were received (68.5%); and 7719 were analyzed in 2010. Respondents indicated time spent sitting on a usual weekday and weekend day for watching TV, general leisure, and home computer use. Multivariate linear mixed models with area-level random intercepts were used to examine (1) associations between sociodemographic and health variables and sitting time, and (2) interaction effects of weekday/weekend day with each of gender, age, education, and employment status, on sitting time.

Results: For each context, longer sitting times were reported by those single and living alone, and those whose health restricted activity. For watching TV, longer sitting times were reported by men; smokers; and those with high school or lower education, not in paid employment, in poor health, and with BMI ≥25. For general leisure, longer sitting times were reported by women, smokers, and those not employed full-time. For home computer use, longer sitting times were reported by men; and those aged 40-44 years, with university qualifications; in the mid-income range; and with BMI ≥30. Sitting times tended to be longer on weekend days than weekdays, although the extent of this differed among sociodemographic groups.

Conclusions: Sociodemographic and health factors associated with sitting time differ by context and between weekdays and weekend days.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Age Factors
  • Aged
  • Data Collection
  • Educational Status
  • Employment / statistics & numerical data
  • Evidence-Based Medicine
  • Female
  • Health Status*
  • Humans
  • Leisure Activities*
  • Linear Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Sedentary Behavior*
  • Sex Factors
  • Smoking / epidemiology
  • Socioeconomic Factors
  • Time Factors