University of Florida Transportation Institute, University of Florida, Gainesville, FL 32611, USA.
Department of Civil Engineering, University of Kentucky, Lexington, KY 40506, USA.
Int J Environ Res Public Health. 2022 Jul 26;19(15):9087. doi: 10.3390/ijerph19159087.
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.
机动车事故是美国可预防伤害死亡的第三大主要原因。先前的研究发现驾驶员居住邮政编码的社会经济特征与事故频率之间存在联系。本研究的目的是通过调查驾驶员居住邮政编码的社会经济特征是否影响他们在事故后寻求医疗服务的可能性，来扩展早期的工作。数据来自肯塔基州、犹他州和俄亥俄州的警察事故报告与医院记录相关的通用使用模型（GUM）数据，以及美国社区调查的邮政编码级社会经济数据也被纳入分析。为每个州开发了逻辑回归模型，结果表明，在针对寻求事故后医疗服务的几率进行测试时，教育程度、中位数住房价值、性别和年龄等社会经济变量的 p 值均<0.001。肯塔基州和犹他州的模型还包括就业与人口的比例。结果表明，除了年龄和性别外，教育程度、中位数住房价值和邮政编码级别的农村比例与驾驶员在事故后寻求后续医疗服务的可能性相关。结论是，收入较低和教育程度较低地区的驾驶员更有可能在事故后寻求医疗服务，主要是在急诊室。女性驾驶员也更有可能寻求事故后医疗服务。
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