TY - JOUR
T1 - Sleep, dietary, and exercise behavioral clusters among truck drivers with obesity
AU - Olson, Ryan
AU - Thompson, Sharon V.
AU - Wipfli, Brad
AU - Hanson, Ginger
AU - Elliot, Diane L.
AU - Anger, W. Kent
AU - Bodner, Todd
AU - Hammer, Leslie B.
AU - Hohn, Elliot
AU - Perrin, Nancy A.
N1 - Publisher Copyright:
© 2016 American College of Occupational and Environmental Medicine.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - 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.
AB - 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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U2 - 10.1097/JOM.0000000000000650
DO - 10.1097/JOM.0000000000000650
M3 - Article
C2 - 26949883
AN - SCOPUS:84963665117
SN - 1076-2752
VL - 58
SP - 314
EP - 321
JO - Journal of occupational and environmental medicine
JF - Journal of occupational and environmental medicine
IS - 3
ER -