肥胖卡车司机的睡眠、饮食和运动行为集群：对干预措施的启示。
Sleep, Dietary, and Exercise Behavioral Clusters Among Truck Drivers With Obesity: Implications for Interventions.
作者信息
Olson Ryan, Thompson Sharon V, Wipfli Brad, Hanson Ginger, Elliot Diane L, Anger W Kent, Bodner Todd, Hammer Leslie B, Hohn Elliot, Perrin Nancy A
机构信息
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.
出版信息
J Occup Environ Med. 2016 Mar;58(3):314-21. doi: 10.1097/JOM.0000000000000650.
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.
目的
本研究的目的是描述一个卡车司机样本，识别在影响能量平衡的行为（睡眠、饮食和运动）方面具有相似模式的司机群体，并测试这些群体在健康安全和社会心理因素方面的差异。
方法
在进行分层聚类分析之前，将参与者（n = 452，体重指数M = 37.2，86.4%为男性）的自我报告行为进行二分法处理，从而识别出具有相似行为协变的群体。使用广义估计方程测试聚类差异。
结果
识别出五个行为集群，它们在年龄、吸烟状况、糖尿病患病率、误工天数、压力和社会支持方面存在显著差异，但在体重指数方面没有差异。以最佳睡眠质量为特征的集群2的误工天数和压力明显低于其他集群。
结论
针对司机的体重管理干预措施应明确解决睡眠问题，并且在建立能够减少压力暴露的社会支持性工作环境后可能会达到最大效果。
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