Predictors of sleep quality among Operating Engineers

Background and Objective: The negative impact of sleep disturbances, including increases in absenteeism, fatal work accidents, the use of sick leave, work disability, medical comorbidities, as well as subsequent mortality, have been well-documented in the literature. However, sleep quality of blue collar workers has not been studied extensively, and no studies have focused Operating Engineers (heavy equipment operators) among whom daytime fatigue would place them at high risk for accidents. Therefore, the purpose of this study was to determine predictors of sleep quality among Operating Engineers.

Methods: This was a cross-sectional correlational design with a dependent variable of sleep quality and independent variables of personal and related health behavior factors. A convenience sample of 498 Operating Engineers was recruited from entire State of Michigan in 2008. Linear regression was used to determine personal and related health behavior factors associated with sleep quality.

Results: While sleep scores were similar to population norms, approximately 34% (n=143) showed interest in health services for sleep problems. Multivariate analyses showed that younger age, female sex, higher pain, more medical comorbidities, depressive symptoms, and nicotine dependence predicted poor sleep quality.

Conclusions: While many personal factors associated with poor sleep quality are not changeable, interventions to improve sleep hygiene as well as interventions to treat pain, depression and smoking may improve sleep quality resulting in less absenteeism, fatal work accidents, use of sick leave, work disability, medical comorbidities, as well as subsequent mortality.