From the Departments of Anesthesiology and Epidemiology, Columbia University, New York, NY.
Epidemiology. 2015 Mar;26(2):247-54. doi: 10.1097/EDE.0000000000000222.
This study quantifies the spatiotemporal risk of pedestrian and bicyclist injury in New York City at the census tract level over a recent 10-year period, identifies areas of increased risk, and evaluates the role of socioeconomic and traffic-related variables in injury risk.
Crash data on 140,835 pedestrian and bicyclist injuries in 1908 census tracts from 2001 to 2010 were obtained from the New York City Department of Transportation. We analyzed injury counts within census tracts with Bayesian hierarchical spatial models using integrated nested Laplace approximations. The model included variables for social fragmentation, median household income, and average vehicle speed and traffic density, as well as a spatially unstructured random effect term, a spatially structured conditional autoregression term, a first-order random walk-correlated time variable, and an interaction term for time and place. Incidence density ratios, credible intervals, and probability exceedances were calculated and mapped.
The yearly rate of crashes involving injuries to "pedestrians" (including bicyclists) decreased 16.2% over the study period, from 23.7 per 10,000 population to 16.2 per 10,000. The temporal term in the spatiotemporal model indicated that much of the decrease over the study period occurred during the first 4 years of the study period. Despite an overall decrease, the model identified census tracts that were at persistently high risk of pedestrian injury throughout the study period, as well as areas that experienced sporadic annual increases in risk. Aggregate social, economic, and traffic-related measures were associated with pedestrian injury risk at the ecologic level. Every 1-unit increase in a standardized social fragmentation index was associated with a 19% increase in pedestrian injury risk (incidence density ratio = 1.19 [95% credible interval = 1.16 - 1.23]), and every 1 standardized unit increase in traffic density was associated with a 20% increase in pedestrian injury risk (1.20 [1.15 - 1.26]). Each 10-mile-per-hour increase in average traffic speed in a census tract was associated with a 24% decrease in pedestrian injury risk (0.76 [0.69 - 0.83]).
The risk of a pedestrian or bicyclist being struck by a motor vehicle in New York City decreased from 2001 to 2004 and held fairly steady thereafter. Some census tracts in the city did not benefit from overall reductions or experienced sporadic years of increased risk compared with the city as a whole. Injury risk at the census tract level was associated with social, economic, and traffic-related factors.
本研究在最近的 10 年时间内，以普查区为单位，量化了纽约市行人与自行车骑行者受伤的时空风险，确定了风险增加的区域，并评估了社会经济和交通相关变量在受伤风险中的作用。
从纽约市交通局获取了 2001 年至 2010 年期间 1908 个普查区 140835 名行人与自行车骑行者受伤的碰撞数据。我们使用整合嵌套拉普拉斯近似法，通过贝叶斯分层空间模型分析普查区内的受伤次数。模型纳入了社会碎片化、家庭中位数收入、平均车速和交通密度变量，以及空间非结构化随机效应项、空间结构化条件自回归项、一阶随机游走相关时间变量以及时间和地点的交互项。计算并绘制了发病率密度比、可信区间和概率超标。
研究期间，涉及“行人”（包括骑自行车者）受伤的事故发生率每年下降 16.2%，从每 10000 人 23.7 例降至每 10000 人 16.2 例。时空模型中的时间项表明，研究期间的大部分下降发生在研究的前 4 年。尽管总体呈下降趋势，但该模型确定了在整个研究期间行人受伤风险持续居高不下的普查区，以及每年风险间歇性增加的区域。综合社会、经济和交通相关措施与生态水平的行人受伤风险相关。社会碎片化标准化指数每增加 1 个单位，行人受伤风险增加 19%（发病率密度比=1.19[95%可信区间=1.16-1.23]），每增加 1 个标准化交通密度单位，行人受伤风险增加 20%（1.20[1.15-1.26]）。普查区的平均交通速度每增加 10 英里/小时，行人受伤风险降低 24%（0.76[0.69-0.83]）。
纽约市行人或骑自行车者被机动车撞击的风险从 2001 年至 2004 年下降，此后基本保持稳定。与整个城市相比，该市的一些普查区并未受益于整体减少或经历了零星的风险增加年份。在普查区层面，受伤风险与社会、经济和交通相关因素有关。
