Prevalence of Alcohol Impairment and Odds of a Driver Injury or Fatality in On-road Farm Equipment Crashes

Overview

Journal Traffic Inj Prev

Specialties Emergency Medicine
Public Health

Date 2017 Dec 7

PMID 29211499

Citations 2

Authors

Karisa K Harland

Ronald Bedford

Hongqian Wu

Marizen Ramirez

Affiliations

Soon will be listed here.

Abstract

Objective: The objective of this article was to estimate the prevalence of alcohol impairment in crashes involving farm equipment on public roadways and the effect of alcohol impairment on the odds of crash injury or fatality.

Methods: On-road farm equipment crashes were collected from 4 Great Plains state departments of transportation during 2005-2010. Alcohol impairment was defined as an involved driver having blood alcohol content of ≥0.08 g/100 ml or a finding of alcohol impairment as a driver contributing circumstance recorded on the police crash report. Injury or fatality was categorized as (a) no injury (no and possible injury combined), (b) injury (nonincapacitating or incapacitating injury), and (c) fatality. Hierarchical multivariable logistic regression modeling, clustered on crash, was used to estimate the odds of an injury/fatality in crashes involving an alcohol-impaired driver.

Results: During the 5 years under study, 3.1% (61 of 1971) of on-road farm equipment crashes involved an alcohol-impaired driver. One in 20 (5.6%) injury crashes and 1 in 6 (17.8%) fatality crashes involved an alcohol-impaired driver. The non-farm equipment driver was significantly more likely to be alcohol impaired than the farm equipment driver (2.4% versus 1.1% respectively, P = .0012). After controlling for covariates, crashes involving an alcohol-impaired driver had 4.10 (95% confidence interval [CI], 2.30-7.28) times the odds of an injury or fatality. In addition, the non-farm vehicle driver was at 2.28 (95% CI, 1.92-2.71) times higher odds of an injury or fatality than the farm vehicle driver. No differences in rurality of the crash site were found in the multivariable model.

Conclusion: On-road farm equipment crashes involving alcohol result in greater odds of an injury or fatality. The risk of injury or fatality is higher among the non-farm equipment vehicle drivers who are also more likely to be alcohol impaired. Further studies are needed to measure the impact of alcohol impairment in on-road farm equipment crashes.

Citing Articles

Examination of Realism in a High-fidelity Tractor Driving Simulator.

Faust K, Casteel C, McGehee D, Peek-Asa C, Rohlman D, Ramirez M J Agric Saf Health. 2021; 26(4):123-137.

PMID: 33981134 PMC: 8112449. DOI: 10.13031/jash.14043.

Interpol review of toxicology 2016-2019.

Chan W, Wong G, Hung C, Wong Y, Fung K, Lee W Forensic Sci Int Synerg. 2021; 2:563-607.

PMID: 33385147 PMC: 7770452. DOI: 10.1016/j.fsisyn.2020.01.018.

References

Toussaint M, Faust K, Peek-Asa C, Ramirez M . Characteristics of Farm Equipment-Related Crashes Associated With Injury in Children and Adolescents on Farm Equipment. J Rural Health. 2015; 33(2):127-134. PMC: 8367094. DOI: 10.1111/jrh.12162. View

Borders T, Booth B . Rural, suburban, and urban variations in alcohol consumption in the United States: findings from the National Epidemiologic Survey on Alcohol and Related Conditions. J Rural Health. 2007; 23(4):314-21. DOI: 10.1111/j.1748-0361.2007.00109.x. View

Ranapurwala S, Mello E, Ramirez M . A GIS-based Matched Case-control Study of Road Characteristics in Farm Vehicle Crashes. Epidemiology. 2016; 27(6):827-34. DOI: 10.1097/EDE.0000000000000542. View

Ogden E, Moskowitz H . Effects of alcohol and other drugs on driver performance. Traffic Inj Prev. 2004; 5(3):185-98. DOI: 10.1080/15389580490465201. View

Peek-Asa C, Sprince N, Whitten P, Falb S, Madsen M, Zwerling C . Characteristics of crashes with farm equipment that increase potential for injury. J Rural Health. 2007; 23(4):339-47. DOI: 10.1111/j.1748-0361.2007.00112.x. View

Janstrup K, Kaplan S, Hels T, Lauritsen J, Prato C . Understanding traffic crash under-reporting: Linking police and medical records to individual and crash characteristics. Traffic Inj Prev. 2016; 17(6):580-4. DOI: 10.1080/15389588.2015.1128533. View

Paleti R, Eluru N, Bhat C . Examining the influence of aggressive driving behavior on driver injury severity in traffic crashes. Accid Anal Prev. 2010; 42(6):1839-54. DOI: 10.1016/j.aap.2010.05.005. View

Gkritza K, Kinzenbaw C, Hallmark S, Hawkins N . An empirical analysis of farm vehicle crash injury severities on Iowa's public road system. Accid Anal Prev. 2010; 42(4):1392-7. DOI: 10.1016/j.aap.2010.03.003. View

Gerberich S, ROBERTSON L, Gibson R, Renier C . An epidemiological study of roadway fatalities related to farm vehicles: United States, 1988 to 1993. J Occup Environ Med. 1996; 38(11):1135-40. DOI: 10.1097/00043764-199611000-00013. View

10.

Heron M . Deaths: Leading Causes for 2014. Natl Vital Stat Rep. 2016; 65(5):1-96. View

11.

Harland K, Greenan M, Ramirez M . Not just a rural occurrence: differences in agricultural equipment crash characteristics by rural-urban crash site and proximity to town. Accid Anal Prev. 2014; 70:8-13. DOI: 10.1016/j.aap.2014.02.013. View

12.

Shyhalla K . Alcohol involvement and other risky driver behaviors: effects on crash initiation and crash severity. Traffic Inj Prev. 2014; 15(4):325-34. DOI: 10.1080/15389588.2013.822491. View

13.

Loo B, Tsui K . Factors affecting the likelihood of reporting road crashes resulting in medical treatment to the police. Inj Prev. 2007; 13(3):186-9. PMC: 2598382. DOI: 10.1136/ip.2006.013458. View

14.

Ramirez M, Bedford R, Wu H, Harland K, Cavanaugh J, Peek-Asa C . Lighting and marking policies are associated with reduced farm equipment-related crash rates: a policy analysis of nine Midwestern US states. Occup Environ Med. 2016; 73(9):621-6. PMC: 5013097. DOI: 10.1136/oemed-2016-103672. View