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影响安全带使用的社区因素。

Neighborhood-level factors affecting seat belt use.

机构信息

Civil and Environmental Engineering, University of Tennessee, Knoxville, TN, United States.

Civil and Environmental Engineering, University of Tennessee, Knoxville, TN, United States.

出版信息

Accid Anal Prev. 2019 Jan;122:153-161. doi: 10.1016/j.aap.2018.10.005. Epub 2018 Oct 27.

Abstract

Despite the well-known safety benefits of seat belt use, some vehicle occupants still do not use them. This is a challenge in Tennessee, which has a lower seat belt use rate compared to the United States national average. Roadside observations and interviews are the two main sources for estimating seat belt use rate and have several limitations (e.g., small sample size, social desirability bias). To address these limitations, we attributed seat belt use of individuals who were involved in traffic crashes (N = 542,776) to their corresponding home-addresses. Home-addresses were retrieved from police crash reports and were geocoded, and assigned to their corresponding census tract revealing added information about the spatial distribution of seat belt use and socioeconomics of the areas surrounding the crash victim's home. The average seat belt use rate in the metropolitan area was 88% and for the non-metropolitan area was 87%. A Tobit model was used to evaluate the relationship between the seat belt use rate for both drivers and passengers over 16 years old, with neighborhood sociodemographic variables. Population, age cohorts, race, household vehicles' ownership, household size, and education were among the predictors of the seat belt use rate. Results of this analysis could be used in safety campaign design to reach specific geographic areas and groups with a lower seat belt use rate.

摘要

尽管系安全带的好处众所周知,但仍有一些车辆乘员不使用安全带。这是田纳西州面临的一个挑战,与美国全国平均水平相比,田纳西州的安全带使用率较低。路边观察和访谈是估计安全带使用率的两个主要来源,但它们存在一些局限性(例如,样本量小、社会期望偏差)。为了解决这些局限性,我们将涉及交通事故的个人(N=542776)的安全带使用情况归因于他们相应的家庭住址。家庭住址取自警方的事故报告并进行地理编码,然后分配给相应的普查区,揭示了安全带使用的空间分布和事故受害者家庭周边地区的社会经济情况。大都市区的平均安全带使用率为 88%,非大都市区为 87%。我们使用 Tobit 模型评估了 16 岁以上司机和乘客的安全带使用率与邻里社会人口统计学变量之间的关系。人口、年龄组、种族、家庭汽车拥有情况、家庭规模和教育程度是安全带使用率的预测因素。该分析的结果可用于安全运动的设计,以针对安全带使用率较低的特定地理区域和群体。

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