Obesity is associated with the future risk of heavy truck crashes among newly recruited commercial drivers

Jon E Anderson,Manjari Govada,Tricia K Steffen,Chris P Thorne,Vasileia Varvarigou,Stefanos N Kales,Stephen V Burks

doi:10.1016/j.aap.2012.02.018

Abstract

This study estimates the dose–response relationship between body mass index (BMI) and crash risk in operators of heavy commercial motor vehicles. Intake data were collected during the first two weeks of instruction from 744 new truck drivers training for their commercial driver's licenses at a school operated by the cooperating trucking firm. Drivers were then followed prospectively on the job using the firm's operational data for two years, or until employment separation, whichever came first. Multivariate Poisson regression and Cox proportional hazards models were used to estimate the relationship between crash risk and BMI, controlling for demographic characteristics and for variations in the exposure to risks on the road. Results from the Poisson regression, which used cumulative miles driven as an exposure control, indicated that compared to normal BMI (18.5<BMI<25) the risk ratio (RR) for all crashes was significantly higher for drivers in the combined obesity Classes II and III: RR=1.55 (95% CI 1.24–1.94). Similarly, the multivariate Cox proportional hazard model (controlling for miles and job type on a week-by-week basis) showed that crash risk was significantly higher compared to normal BMI for the same combined obesity Classes II and III: RR=1.54 (95% CI 1.13–2.10). The results of this prospective study establish an association between obesity and crash risk and have important implications for driver health and public safety.

Highlights

It is well known that the prevalence of obesity among US adults has more than doubled in recent decades (Flegal et al 2010)
Given obesity’s significant associations with obstructive sleep apnea (OSA), excessive daytime sleepiness (EDS) and fatigue, in this prospective study, we examined the risk of truck crashes as a function of Body Mass Index (BMI) among newly recruited professional drivers, statistically controlling for relevant factors that affect on-the-job exposure to accident risk
The study population has an overall self-reported obesity rate (BMI ≥ 30) of 33.7%, which is typical of the US adult population's 33.8% (95% confidence interval: 31.6%-36.0%) during the period of 2007-08 (Flegal et al 2010), and our subjects have a Class II and III rate of 14.65%

Summary

Introduction

It is well known that the prevalence of obesity among US adults has more than doubled in recent decades (Flegal et al 2010). Because of robust associations with obstructive sleep apnea (OSA), excessive daytime sleepiness (EDS), and fatigue, (Vgontzas et al 1998, TeranSantos et al 1999, Philip 2005, Vgontzas 2008b) obesity could present significant risks during the performance of complex tasks such as driving trucks, piloting aircraft, operating public transit vehicles, and similar operational activities found in several transportation modes that require constant attention and vigilance (Dinges et al 1997, Dagan et al 2006, Cohen et al 2010) If this hypothesis were true, even a small increase in risk would have a major impact on the population-attributable risk, given the frequent role of fatigue in crashes and the high prevalence of obesity (Dixon et al 2007). Any additional risk due to obesity would have enormous policy consequences for the transportation industry and society at large

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