Ryan Olson1, Sharon V Thompson, Brad Wipfli, Ginger Hanson, Diane L Elliot, W Kent Anger, Todd Bodner, Leslie B Hammer, Elliot Hohn, Nancy A Perrin. 1. Oregon Institute of Occupational Health Sciences (Dr Olson, Ms Thompson, Dr Wipfli, Dr Kent Anger, Mr Hohn), Oregon Health & Science University; School of Public Health (Dr Olson), Oregon Health & Science University and Portland State University; Department of Psychology (Dr Olson, Dr Bodner, Dr Hammer), Portland State University; Center for Health Research (Dr Hanson, Dr Perrin), Kaiser Permanente Northwest; and Division of Health Promotion & Sports Medicine (Dr Elliot), Oregon Health & Science University, Portland.
Abstract
OBJECTIVE: The objectives of the study were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health safety, and psychosocial factors. METHODS: Participants' (n = 452, body mass index M = 37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior covariation. Cluster differences were tested with generalized estimating equations. RESULTS: Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in body mass index. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. CONCLUSIONS: Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures.
OBJECTIVE: The objectives of the study were to describe a sample of truck drivers, identify clusters of drivers with similar patterns in behaviors affecting energy balance (sleep, diet, and exercise), and test for cluster differences in health safety, and psychosocial factors. METHODS:Participants' (n = 452, body mass index M = 37.2, 86.4% male) self-reported behaviors were dichotomized prior to hierarchical cluster analysis, which identified groups with similar behavior covariation. Cluster differences were tested with generalized estimating equations. RESULTS: Five behavioral clusters were identified that differed significantly in age, smoking status, diabetes prevalence, lost work days, stress, and social support, but not in body mass index. Cluster 2, characterized by the best sleep quality, had significantly lower lost workdays and stress than other clusters. CONCLUSIONS: Weight management interventions for drivers should explicitly address sleep, and may be maximally effective after establishing socially supportive work environments that reduce stress exposures.
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