OBJECTIVE: Our aim was to examine the contribution of past and current physical workload to occupational class differences in leisure-time physical inactivity. METHODS: Data were taken from the Finnish population-based Health 2000 Survey of employees aged >or=30 years (N=3355). We assessed physical activity during leisure time using a questionnaire and dichotomized responses to inactive versus active. Occupational class was classified into white- and blue-collar worker. Adjustments were made for current work-related factors, other measures of socioeconomic position, clinically diagnosed chronic diseases, other health behaviors, and history of physical workload. We applied sequential logistic regression to the analyses. RESULTS: Inactivity during leisure time was more common in blue-collar employees than in their white-collar counterparts [women odds ratio (OR) 1.50, 95% confidence interval (95% CI) 1.12-2.00; men OR 1.66, 95% CI 1.30-2.12]. These occupational differences were not due to working hours, work schedule, or chronic diseases. Among women, current job strain decreased the occupational differences in leisure-time physical inactivity slightly (OR 1.37, 95% CI 0.99-1.04). Education and household income contributed to occupational differences for men (OR 1.45, 95% CI 1.02-2.07), but had no additional effect among women. The occupation differences in leisure-time physical inactivity disappeared after adjusting for smoking and body mass index in women (OR 1.33, 95% CI 0.97-1.83) and men (OR 1.27, 95% CI 0.88-1.82) and were further attenuated after adjusting for history of physical workload among men (OR 1.07, 95% CI 0.67-1.72). CONCLUSIONS: Having a long history of exposure to physical work (among men) and a high current job strain (among women) contributed to occupational class differences in leisure-time physical inactivity.
OBJECTIVE: Our aim was to examine the contribution of past and current physical workload to occupational class differences in leisure-time physical inactivity. METHODS: Data were taken from the Finnish population-based Health 2000 Survey of employees aged >or=30 years (N=3355). We assessed physical activity during leisure time using a questionnaire and dichotomized responses to inactive versus active. Occupational class was classified into white- and blue-collar worker. Adjustments were made for current work-related factors, other measures of socioeconomic position, clinically diagnosed chronic diseases, other health behaviors, and history of physical workload. We applied sequential logistic regression to the analyses. RESULTS: Inactivity during leisure time was more common in blue-collar employees than in their white-collar counterparts [women odds ratio (OR) 1.50, 95% confidence interval (95% CI) 1.12-2.00; men OR 1.66, 95% CI 1.30-2.12]. These occupational differences were not due to working hours, work schedule, or chronic diseases. Among women, current job strain decreased the occupational differences in leisure-time physical inactivity slightly (OR 1.37, 95% CI 0.99-1.04). Education and household income contributed to occupational differences for men (OR 1.45, 95% CI 1.02-2.07), but had no additional effect among women. The occupation differences in leisure-time physical inactivity disappeared after adjusting for smoking and body mass index in women (OR 1.33, 95% CI 0.97-1.83) and men (OR 1.27, 95% CI 0.88-1.82) and were further attenuated after adjusting for history of physical workload among men (OR 1.07, 95% CI 0.67-1.72). CONCLUSIONS: Having a long history of exposure to physical work (among men) and a high current job strain (among women) contributed to occupational class differences in leisure-time physical inactivity.
Authors: Nina Nevanperä; Jorma Seitsamo; Leena Ala-Mursula; Jouko Remes; Leila Hopsu; Juha Auvinen; Tuija Tammelin; Marjo-Riitta Järvelin; Jaana Laitinen Journal: Int J Behav Med Date: 2016-04
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Authors: Kaisa R Pulkkinen; Tomi Mäkinen; Heli Valkeinen; Ritva Prättälä; Katja Borodulin Journal: BMC Public Health Date: 2013-02-22 Impact factor: 3.295
Authors: Fehmidah Munir; Jonathan Houdmont; Stacy Clemes; Kelly Wilson; Robert Kerr; Ken Addley Journal: BMC Public Health Date: 2015-01-29 Impact factor: 3.295