Citation

Sagar S, Stamatiadis N, Codden R, Benedetti M, Cook L, Zhu M. Int. J. Environ. Res. Public Health 2022; 19(15): e9087.

Copyright

(Copyright © 2022, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/ijerph19159087

PMID

35897457

Abstract

Motor vehicle crashes are the third leading cause of preventable-injury deaths in the United States. Previous research has found links between the socioeconomic characteristics of driver residence zip codes and crash frequencies. The objective of the study is to extend earlier work by investigating whether the socioeconomic characteristics of a driver's residence zip code influence their likelihood of resulting in post-crash medical services. Data were drawn from General Use Model (GUM) data for police crash reports linked to hospital records in Kentucky, Utah, and Ohio. Zip-code-level socioeconomic data from the American Community Survey were also incorporated into analyses. Logistic regression models were developed for each state and showed that the socioeconomic variables such as educational attainment, median housing value, gender, and age have p-values < 0.001 when tested against the odds of seeking post-crash medical services. Models for Kentucky and Utah also include the employment-to-population ratio. The results show that in addition to age and gender, educational attainment, median housing value and rurality percentage at the zip code level are associated with the likelihood of a driver seeking follow-up medical services after a crash. It is concluded that drivers from areas with lower household income and lower educational attainment are more likely to seek post-crash medical services, primarily in emergency departments. Female drivers are also more likely to seek post-crash medical services.

Language: en

Keywords

Humans; Female; Police; Socioeconomic Factors; United States; Logistic Models; Age Factors; Demography; logistic regression; *Accidents, Traffic; *Automobile Driving; general use model; highway safety; socioeconomic factors