Norton Jennifer M, Fung Lawrence, Stayton Catherine
Department of Population Health, NYU Langone Health, Grossman School of Medicine, New York, NY, USA.
New York City Department of Health and Mental Hygiene, New York, NY, USA.
J Community Health. 2021 Jun;46(3):626-634. doi: 10.1007/s10900-020-00924-7. Epub 2020 Sep 20.
Motor vehicle crashes are a leading cause of injury related deaths. Urban areas accommodate multiple road users and pedestrians account for a larger share of traffic fatalities. Speed reduction has been one component of New York City's multidisciplinary approach to reduce traffic fatalities-Vision Zero. Data from the New York City (NYC) Community Health Survey 2015-2016 were used to document population-based estimates of self-reported speeding (defined as driving ten miles per hour or more over the posted speed limit in the past 30 days) among NYC adult drivers collected soon after the adoption of Vision Zero in 2014. Self-reported speeding is common, with nearly two-thirds (63%) of adult drivers indicating they ever sped and 13% often speeding. In adjusted multivariable models, often speeding was more common among younger drivers vs. older drivers (adjusted prevalence ratio: 2.77; 95%CI 1.93-3.98), males vs. females (adjusted prevalence ratio: 1.59; 95%CI 1.35-1.87), wealthier drivers vs. poorer drivers (adjusted prevalence ratio: 1.37; 95%CI 1.10-1.70) and those reporting worse perceived social cohesion vs. better perceived social cohesion (adjusted prevalence ratio 1.51; 95%CI 1.09-2.10). Population-based health surveys facilitate exploration of a range of potential influences on health behaviors.
机动车撞车事故是与伤害相关死亡的主要原因。城市地区有多种道路使用者，行人在交通死亡事故中占比更大。降低车速一直是纽约市多学科方法“零愿景”中减少交通死亡事故的一个组成部分。2014年采用“零愿景”后不久收集的纽约市成年司机自我报告超速（定义为在过去30天内驾驶速度比张贴的限速每小时快10英里或更多）的基于人群的估计数据来自2015 - 2016年纽约市社区健康调查。自我报告超速很常见，近三分之二（63%）的成年司机表示他们曾超速，13%的人经常超速。在调整后的多变量模型中，年轻司机相较于年长司机、男性相较于女性、较富裕司机相较于较贫穷司机以及那些自我感觉社会凝聚力较差的人相较于自我感觉社会凝聚力较好的人，经常超速更为常见（调整后的患病率比值：分别为2.77；95%置信区间1.93 - 3.98、1.59；95%置信区间1.35 - 1.87、1.37；95%置信区间1.10 - 1.70、1.51；95%置信区间1.09 - 2.10）。基于人群的健康调查有助于探索对健康行为的一系列潜在影响。
