title: Body mass index: accounting for full time sedentary occupation and 24-hr self-reported time use.
abstract: OBJECTIVE
  We used linked existing data from the 2006-2008 American Time Use Survey (ATUS), the Current Population Survey (CPS, a federal survey that provides on-going U.S. vital statistics, including employment rates) and self-reported body mass index (BMI) to answer: How does BMI vary across full time occupations dichotomized as sedentary/non-sedentary, accounting for time spent in sleep, other sedentary behaviors, and light, moderate, and vigorous intensity activities?
  
  
  METHODS
  We classified time spent engaged at a primary job (sedentary or non-sedentary), sleep, and other non-work, non-sleep intensity-defined behaviors, specifically, sedentary behavior, light, moderate, and vigorous intensity activities. Age groups were defined by 20-29, 30-39, 40-49, and 50-64 years. BMI groups were defined by 18.5-24.9, 25.0-27.4, 27.5-29.9, 30.0-34.9, and ≥35.0 kg/m2. Logistic and linear regression were used to examine the association between BMI and employment in a sedentary occupation, considering time spent in sleep, other non-work time spent in sedentary behaviors, and light, moderate, and vigorous intensity activities, sex, age race/ethnicity, and household income.
  
  
  RESULTS
  The analysis data set comprised 4,092 non-pregnant, non-underweight individuals 20-64 years of age who also reported working more than 7 hours at their primary jobs on their designated time use reporting day. Logistic and linear regression analyses failed to reveal any associations between BMI and the sedentary/non-sedentary occupation dichotomy considering time spent in sleep, other non-work time spent in sedentary behaviors, and light, moderate, and vigorous intensity activities, sex, age, race/ethnicity, and household income.
  
  
  CONCLUSIONS
  We found no evidence of a relationship between self-reported full time sedentary occupation classification and BMI after accounting for sex, age, race/ethnicity, and household income and 24-hours of time use including non-work related physical activity and sedentary behaviors. The various sources of error associated with self-report methods and assignment of generalized activity and occupational intensity categories could compound to obscure any real relationships.
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America.
authors.forename: Catrine
authors.initials: C
authors.lastname: Tudor-Locke
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America.
authors.forename: John M
authors.initials: JM
authors.lastname: Schuna
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America.
authors.forename: Peter T
authors.initials: PT
authors.lastname: Katzmarzyk
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America.
authors.forename: Wei
authors.initials: W
authors.lastname: Liu
authors.affiliation: U.S. Department of Agriculture Economic Research Service, Washington, DC, United States of America.
authors.forename: Karen S
authors.initials: KS
authors.lastname: Hamrick
authors.affiliation: Pennington Biomedical Research Center, Baton Rouge, Louisiana, United States of America.
authors.forename: William D
authors.initials: WD
authors.lastname: Johnson
mesh_terms: D000328:Adult; D017677:Age Distribution; D015992:Body Mass Index; D015444:Exercise; D005260:Female; D015438:Health Behavior; D006801:Humans; D008297:Male; D008875:Middle Aged; D009790:Occupations / Q000706:statistics & numerical data*; D057185:Sedentary Behavior; D057566:Self Report; D055815:Young Adult