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Articles

Racial and ethnic differences in patients involved in alcohol-impaired motor vehicle crashes and its related clinical outcomes among various age groups in the U.S.

, ORCID Icon, , &
Pages 115-121 | Received 20 May 2019, Accepted 29 Oct 2019, Published online: 05 Feb 2020
 

Abstract

Objective(s): 1) to determine whether the proportion of alcohol-impaired patients involved in motor vehicle crashes (MVCs) varies by race/ethnicity within different age groups; 2) to explore the relationship between alcohol impairment, race/ethnicity and clinical outcomes among patients involved in MVCs across age groups.

Methods: The 2012 National Trauma Data Bank (NTDB) queried for patients aged 16–55 involved in MVCs who received a blood ethanol test on admission.

Results: Of the 44,216 patients involved in MVC, 68% were White, 14% Black, and 13% were Hispanic. About 36% were 16–25years old, and 19% were 46–55years old. Alcohol-impaired patients constituted 34% of the patients. The multiple logistic regression analysis of HLOS ≥ 2days revealed that, when controlling for age, gender, race/ethnicity, insurance status, and the interaction between alcohol impairment and age as well as alcohol impairment and race/ethnicity, alcohol impairment positivity carried a 15% increase in probability of HLOS ≥ 2days (OR 1.15, p<0.0001). Additionally, using the 16–25 age group as reference, each of the older age groupings showed an increased probability of HLOS ≥ 2days with ORs of 1.15, 1.32, and 1.51 for ages 26–35, 36–45, and 46–55, respectively (p-values<0.0001). Blacks, Hispanics, and Asians/others were less likely than Whites to have HLOS ≥ 2days with OR of 0.88, 0.89, and 0.88, respectively (p<0.05). There was no statistically significant difference in the clinical outcome of mortality between races/ethnicities and alcohol-impaired driving.

Conclusions: This study demonstrates that the proportions of alcohol-impaired driving and the associated clinical outcomes vary among race/ethnic groups in different age groups. More research is needed to determine the reasons for the observed differences in these vulnerable sub-groups.

Acknowledgments

We thank Kaveh Dehghan, MBA in the College of Medicine at Charles R. Drew University of Science for his assistance and helpful comments with editing the Manuscript, and formatting the references, and Tables.

Additional information

Funding

Research for this article was supported in part by National Institute on Minority Health, and Health Disparities of the National Institutes of Health (NIH-NIMHD) Accelerated Excellence in Translational Sciences (AXIS) grant number 2U54MD007598-07; the University of California at Los Angeles (UCLA) Clinical and Translational Science Institute (CTSI), grant number UL1TR001881; and the Urban Health Institute grant number S21 MD000103.

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