Shults Ruth A, Banerjee Tanima, Perry Timothy
a Division of Unintentional Injury Prevention , National Center for Injury Prevention and Control , Atlanta , Georgia.
b Office of Research and Global Affairs , University of Michigan School of Nursing , Ann Arbor , Michigan.
Traffic Inj Prev. 2016 Nov 16;17(8):803-9. doi: 10.1080/15389588.2016.1161761. Epub 2016 Apr 11.
We examined associations among race/ethnicity, socioeconomic factors, and driving status in a nationally representative sample of >26,000 U.S. high school seniors.
Weighted data from the 2012 and 2013 Monitoring the Future surveys were combined and analyzed. We imputed missing values using fully conditional specification multiple imputation methods. Multivariate logistic regression modeling was conducted to explore associations among race/ethnicity, socioeconomic factors, and driving status, while accounting for selected student behaviors and location. Lastly, odds ratios were converted to prevalence ratios.
23% of high school seniors did not drive during an average week; 14% of white students were nondrivers compared to 40% of black students. Multivariate analysis revealed that minority students were 1.8 to 2.5 times more likely to be nondrivers than their white counterparts, and students who had no earned income were 2.8 times more likely to be nondrivers than those earning an average of ≥$36 a week. Driving status also varied considerably by student academic performance, number of parents in the household, parental education, census region, and urbanicity.
Our findings suggest that resources-both financial and time-influence when or whether a teen will learn to drive. Many young people from minority or lower socioeconomic families who learn to drive may be doing so after their 18th birthday and therefore would not take advantage of the safety benefits provided by graduated driver licensing. Innovative approaches may be needed to improve safety for these young novice drivers.
在一个超过26000名美国高中高年级学生的全国代表性样本中,我们研究了种族/族裔、社会经济因素和驾驶状况之间的关联。
对2012年和2013年“未来监测”调查的加权数据进行合并和分析。我们使用完全条件指定多重插补方法对缺失值进行插补。进行多变量逻辑回归建模,以探索种族/族裔、社会经济因素和驾驶状况之间的关联,同时考虑选定的学生行为和地点。最后,将优势比转换为患病率比。
23%的高中高年级学生在平均一周内不开车;14%的白人学生不开车,而黑人学生中这一比例为40%。多变量分析显示,少数族裔学生不开车的可能性是白人学生的1.8至2.5倍,没有收入的学生不开车的可能性是那些平均每周收入≥36美元的学生的2.8倍。驾驶状况在学生学业成绩、家庭中父母数量、父母教育程度、人口普查区域和城市化程度方面也有很大差异。
我们的研究结果表明,资源——无论是经济资源还是时间资源——都会影响青少年何时或是否会学习开车。许多来自少数族裔或社会经济地位较低家庭的年轻人可能在18岁生日后才开始学开车,因此无法受益于分级驾照制度带来的安全保障。可能需要创新方法来提高这些年轻新手司机的安全性。