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Hours-of-service compliance and safety outcomes among long-haul truck drivers.

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Title: Hours-of-service compliance and safety outcomes among long-haul truck drivers.
Authors: Lemke, Michael K.1,2 (AUTHOR) lemkem@uhd.edu, Hege, Adam3 (AUTHOR) hegeba@appstate.edu, Apostolopoulos, Yorghos2,4 (AUTHOR) yaposto@tamu.edu, Sönmez, Sevil5 (AUTHOR) sevil@ucf.edu
Source: Transportation Research: Part F. Jan2021, Vol. 76, p297-308. 12p.
Subjects: Truck drivers, Logistic regression analysis, Safety standards, Sleep, Bivariate analysis, Working hours, Safety regulations, Sleep spindles
Abstract: • Daily work hours predicted both HOS compliance and safety risk. • Sleep duration, fast pace of work, and miles per week predicted HOS compliance. • Supervisor support, self-reporting fatigue, and work hours predicted safety risk. • Greater HOS compliance was a nonsignificant predictor of safety risk. • Compensation type was a nonsignificant predictor of HOS compliance and safety risk. U.S. long-haul truck drivers (LHTD) experience the most work-related fatalities of any occupation. Hours-of-service (HOS) regulations constitute key public policies aimed at improving safety outcomes; however, little is known about the factors that are associated with HOS compliance, and questions remain about the efficacy of HOS laws in improving safety. This study seeks to identify factors associated with HOS compliance and to determine the significance of HOS compliance in sleep-related safety risk. Using cross-sectional survey data from 260 U.S. LHTD that measured demographic, work organization, sleep health, hours-of-service compliance, and sleep-related safety performance characteristics, we: 1) compiled descriptive statistics to summarize the variables included in this study; 2) performed bivariate correlation analyses between an HOS composite variable called "Hours-of-Service Violations" and the demographic, work organization, and sleep health variables; 3) conducted an ordinal logistic regression analysis, using the HOS composite variable as the outcome variable; and 4) conducted a multinomial logistic regression analysis, using a sleep-related safety performance composite variable called "Sleep-Related Safety Risk" as the outcome variable. Higher scores on the HOS composite variable were significantly associated with more miles driven per week, longer daily work hours, a higher frequency of a fast pace of work, shorter sleep duration, and poorer sleep quality. Statistically significant predictor variables in the Hours-of-Service Violations composite variable model were driving less than 2,500 miles per week (OR = 0.53), working less than 11 h daily (OR = 0.19) or between 11 and 13 h daily (OR = 0.43); a lower frequency of fast pace of work (OR = 0.42); and worknight sleep duration (OR = 0.80). Fewer than 11 h of work daily (OR = 0.37), a higher perception of supervisor support (OR = 0.17), and ever having told supervisor about being too tired to drive (OR = 0.42) were significant predictors in the Sleep-Related Safety Risk composite variable model, while the hours-of-service compliance variables were not. Reducing daily work hours and pace of work, strengthening driver-supervisor relationships and improving supervisor leadership and risk management techniques, making driver compensation fairer, and revisiting HOS policies may represent high-leverage targets for improving regulatory compliance and safety outcomes. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:• Daily work hours predicted both HOS compliance and safety risk. • Sleep duration, fast pace of work, and miles per week predicted HOS compliance. • Supervisor support, self-reporting fatigue, and work hours predicted safety risk. • Greater HOS compliance was a nonsignificant predictor of safety risk. • Compensation type was a nonsignificant predictor of HOS compliance and safety risk. U.S. long-haul truck drivers (LHTD) experience the most work-related fatalities of any occupation. Hours-of-service (HOS) regulations constitute key public policies aimed at improving safety outcomes; however, little is known about the factors that are associated with HOS compliance, and questions remain about the efficacy of HOS laws in improving safety. This study seeks to identify factors associated with HOS compliance and to determine the significance of HOS compliance in sleep-related safety risk. Using cross-sectional survey data from 260 U.S. LHTD that measured demographic, work organization, sleep health, hours-of-service compliance, and sleep-related safety performance characteristics, we: 1) compiled descriptive statistics to summarize the variables included in this study; 2) performed bivariate correlation analyses between an HOS composite variable called "Hours-of-Service Violations" and the demographic, work organization, and sleep health variables; 3) conducted an ordinal logistic regression analysis, using the HOS composite variable as the outcome variable; and 4) conducted a multinomial logistic regression analysis, using a sleep-related safety performance composite variable called "Sleep-Related Safety Risk" as the outcome variable. Higher scores on the HOS composite variable were significantly associated with more miles driven per week, longer daily work hours, a higher frequency of a fast pace of work, shorter sleep duration, and poorer sleep quality. Statistically significant predictor variables in the Hours-of-Service Violations composite variable model were driving less than 2,500 miles per week (OR = 0.53), working less than 11 h daily (OR = 0.19) or between 11 and 13 h daily (OR = 0.43); a lower frequency of fast pace of work (OR = 0.42); and worknight sleep duration (OR = 0.80). Fewer than 11 h of work daily (OR = 0.37), a higher perception of supervisor support (OR = 0.17), and ever having told supervisor about being too tired to drive (OR = 0.42) were significant predictors in the Sleep-Related Safety Risk composite variable model, while the hours-of-service compliance variables were not. Reducing daily work hours and pace of work, strengthening driver-supervisor relationships and improving supervisor leadership and risk management techniques, making driver compensation fairer, and revisiting HOS policies may represent high-leverage targets for improving regulatory compliance and safety outcomes. [ABSTRACT FROM AUTHOR]
ISSN:13698478
DOI:10.1016/j.trf.2020.11.017