Occupation, hours worked, and leisure-time physical activity.
BACKGROUND
International research indicates that blue-collar employees typically exhibit lower rates of leisure-time physical activity. While "lack of time" and "work demands" are commonly reported barriers to activity, the extent to which time-at-work mediates the relationship between occupation and leisure-time physical activity is unclear. This study investigated the association between occupation, time spent in paid employment, and participation in leisure-time physical activity.


METHODS
This was a secondary analysis of cross-sectional data from the 1995 Australian Health Survey, focusing on employed persons ages 18-64 years (n = 24, 454). Occupation was coded as per the Australian Standard Classification of Occupations and collapsed into three categories (professional, white-collar, blue-collar). Hours worked was categorized into eight levels, ranging from 1-14 to more than 50 h per week. Participation in leisure-time physical activity was categorized as either insufficient or sufficient for health, consistent with recommended levels of energy expenditure (1600 METS-min/fortnight). The relationship between occupation, hours worked, and leisure-time physical activity was examined using logistic regression. Analyses were conducted separately for male and female, and the results are presented as a series of models that successively adjust for a range of potential covariates: age, living arrangement, smoking status, body mass index, and self-reported health.


RESULTS
Individuals in blue-collar occupations were approximately 50% more likely to be classified as insufficiently active. This occupational variability in leisure-time physical activity was not explained by hours worked. There was a suggested relationship between hours worked and leisure-time physical activity; however, this differed between men and women, and was difficult to interpret.


CONCLUSIONS
Occupational variability in leisure-time physical activity cannot be explained by hours worked. Therefore, reports that work constitutes a barrier to participation should be explored further. Identification of the factors contributing to occupational variability in leisure-time physical activity will add to our understanding of why population subgroups differ in their health risk profiles, and assist in the development of health promotion strategies to reduce rates of sedentariness and health inequalities.
Burton
N W
NW
School of Public Health, Queensland University of Technology, Victoria Park Road, Kelvin Grove, Queensland, 4059, Australia. n.burton@qut.edu.au
Turrell
G
G
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D001294:Attitude to Health; D003430:Cross-Sectional Studies; D003625:Data Collection; D015444:Exercise; D005260:Female; D006801:Humans; D007899:Leisure Activities; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009790:Occupations / Q000706:statistics & numerical data*; D011793:Queensland / Q000453:epidemiology; D018570:Risk Assessment; D012494:Sampling Studies; D017678:Sex Distribution; D014937:Work / Q000706:statistics & numerical data*; D016526:Workload / Q000706:statistics & numerical data*