title: Mid-aged adults' sitting time in three contexts.
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.
  
  
  OBJECTIVE
  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.
authors.affiliation: School of Human Movement Studies, University of Queensland, St. Lucia, Brisbane, Australia. nburton@hms.uq.edu.au
authors.forename: Nicola W
authors.initials: NW
authors.lastname: Burton
authors.forename: Michele
authors.initials: M
authors.lastname: Haynes
authors.forename: Jannique G Z
authors.initials: JG
authors.lastname: van Uffelen
authors.forename: Wendy J
authors.initials: WJ
authors.lastname: Brown
authors.forename: Gavin
authors.initials: G
authors.lastname: Turrell
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D003625:Data Collection; D004522:Educational Status; D004651:Employment / Q000706:statistics & numerical data; D019317:Evidence-Based Medicine; D005260:Female; D006304:Health Status; D006801:Humans; D007899:Leisure Activities; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D057185:Sedentary Behavior; D012737:Sex Factors; D012907:Smoking / Q000453:epidemiology; D012959:Socioeconomic Factors; D013997:Time Factors