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极端环境温度与摩托车事故:一项时间序列分析。

Extreme environmental temperatures and motorcycle crashes: a time-series analysis.

机构信息

Department of Occupational Health, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China.

出版信息

Environ Sci Pollut Res Int. 2022 Oct;29(50):76251-76262. doi: 10.1007/s11356-022-21151-8. Epub 2022 Jun 6.

Abstract

Extreme temperature could affect traffic crashes by influencing road safety, vehicle performance, and drivers' behavior and abilities. Studies evaluating the impacts of extreme temperatures on the risk of traffic crashes have mainly overlooked the potential role of vehicle air conditioners. The aim of this study, therefore, was to evaluate the effect of exposure to extreme cold and hot temperatures on seeking medical attention due to motorcycle crashes. The study was conducted in Iran by using medical attendance for motorcycle crashes from March 2011 to June 2017. Data on daily minimum, mean and maximum temperature (°C), relative humidity (%), wind velocity (km/h), and precipitation (mm/day) were collected. We developed semi-parametric generalized additive models following a quasi-Poisson distribution with the distributed nonlinear lag model to estimate the immediate and lagged associations (reported as relative risk [RR], and 95% confidence interval [CI]). Between March 2011 and June 2017, 36,079 medical attendances due to motorcycle road traffic crashes were recorded (15.8 ± 5.92 victims per day). In this time period, the recorded temperature ranged from -11.2 to 45.4 °C (average: 25.5 ± 11.0 °C). We found an increased risk of medical attendance for motorcycle crashes (based on maximum daily temperature) at both extremely cold (1st percentile) and hot (99th percentile) temperatures and also hot (75th percentile) temperatures, mainly during lags 0 to 3 days (e.g., RR: 1.12 [95% CI: 1.05: 1.20]; RR: 1.08 [95% CI: 1.01: 1.16]; RR: 1.20 [95% CI: 1.09: 1.32] at lag0 for extremely cold, hot, and extremely hot conditions, respectively). The risk estimates for extremely hot temperatures were larger than hot and extremely cold temperatures. We estimated that 11.01% (95% CI: 7.77:14.06) of the medical attendance for motorcycle crashes is estimated to be attributable to non-optimal temperature (using mean temperature as exposure variable). Our findings have important public health messaging, given the considerable burden associated with road traffic injury, particularly in low- and middle-income countries.

摘要

极端温度会通过影响道路安全、车辆性能以及驾驶员的行为和能力来影响交通事故。评估极端温度对交通事故风险影响的研究主要忽略了车辆空调的潜在作用。因此,本研究旨在评估暴露于极寒和炎热温度对因摩托车事故而寻求医疗的影响。该研究在伊朗进行,使用 2011 年 3 月至 2017 年 6 月期间因摩托车车祸而接受医疗的病例。收集了每日最低、平均和最高温度(°C)、相对湿度(%)、风速(km/h)和降水量(mm/天)的数据。我们使用准泊松分布的半参数广义加性模型和分布式非线性滞后模型来估计即时和滞后关联(以相对风险 [RR] 和 95%置信区间 [CI] 表示)。在 2011 年 3 月至 2017 年 6 月期间,记录了 36079 起因摩托车道路交通事故而接受医疗的病例(每天平均 15.8 ± 5.92 名受害者)。在此期间,记录的温度范围从-11.2°C 到 45.4°C(平均:25.5 ± 11.0°C)。我们发现,在极寒(1%分位数)和炎热(99%分位数)温度以及炎热(75%分位数)温度下,摩托车事故医疗就诊的风险均增加,主要发生在滞后 0 至 3 天内(例如,极寒温度下的 RR:1.12 [95%CI:1.05:1.20];RR:1.08 [95%CI:1.01:1.16];RR:1.20 [95%CI:1.09:1.32]在滞后 0 时)。极热条件下的风险估计值大于热和极寒温度。我们估计,11.01%(95%CI:7.77:14.06)的摩托车事故医疗就诊归因于非最佳温度(使用平均温度作为暴露变量)。考虑到道路交通伤害带来的巨大负担,特别是在低收入和中等收入国家,我们的研究结果具有重要的公共卫生信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9e1/9553821/a255b80ac5ac/11356_2022_21151_Fig1_HTML.jpg

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