Gariazzo Claudio, Bruzzone Silvia, Finardi Sandro, Scortichini Matteo, Veronico Liana, Marinaccio Alessandro
Occupational and Environmental Medicine, Epidemiology and Hygiene Department, Italian Workers' Compensation Authority (INAIL), Monte Porzio Catone, RM, Italy.
Italian National Institute of Statistics, Rome, Italy.
Accid Anal Prev. 2021 Jun;155:106110. doi: 10.1016/j.aap.2021.106110. Epub 2021 Apr 6.
Despite the relevance of road crashes and their impact on social and health care costs, the effects of extreme temperatures on road crashes risk have been scarcely investigated, particularly for those occurring in occupational activities. A nationwide epidemiological study was carried out to estimate the risk of general indistinct and work-related road crashes related with extreme temperatures and to identify crash and occupation parameters mostly involved. Data about road crashes, resulting in death or injury, occurring during years 2013-2015 in Italy, were collected from the National Institute of Statistics, for general indistinct road crashes, and from the compensation claim applications registered by the national workers' compensation authority, for work-related ones. Time series of hourly temperature were derived from the results provided by the meteorological model WRF applied at a national domain with 5 km resolution. To consider the different spatial-temporal characteristics of the two road crashes archives, the association with extreme temperatures was estimated by means of a case-crossover time-stratified approach using conditional logistic regression analysis, and a time-series analysis, using over-dispersed Poisson generalized linear regression model, for general indistinct and work-related datasets respectively. The analyses were controlled for other covariates and confounding variables (including precipitation). Non-linearity and lag effects were considered by using a distributed lag non-linear model. Relative risks were calculated for increment from 75th to 99th percentiles (hot) and from 25 to first percentile (cold) of temperature. Results for general indistinct crashes show a positive association with hot temperature (RR = 1.12, 95 % CI: 1.09-1.16) and a negative one for cold (RR = 0.93, 95 % CI: 0.91-0.96), while for work-related crashes a positive association was found for both hot and cold (RR = 1.06 (95 % CI: 1.01-1.11) and RR = 1.10 (95 % CI: 1.05-1.16). The use of motorcycles, the location of accident (urban vs out of town), presence of crossroads, as well as occupational factors like the use of a vehicle on duty were all found to produce higher risks of road crashes during extreme temperatures. Mitigation and prevention measures are needed to limit social and health care costs.
尽管道路交通事故具有相关性及其对社会和医疗成本产生影响,但极端温度对道路交通事故风险的影响却鲜有研究,尤其是在职业活动中发生的事故。开展了一项全国性的流行病学研究,以估计与极端温度相关的一般不明事故及与工作相关的道路交通事故的风险,并确定主要涉及的事故及职业参数。关于2013 - 2015年期间在意大利发生的导致人员伤亡的道路交通事故数据,一般不明事故的数据来自国家统计局,与工作相关事故的数据来自国家工人赔偿机构登记的赔偿申请。每小时温度的时间序列来自于应用于全国范围、分辨率为5公里的气象模型WRF的结果。为考虑两类道路交通事故档案不同的时空特征,分别采用条件逻辑回归分析的病例交叉时间分层方法以及使用过分散泊松广义线性回归模型的时间序列分析,来估计与极端温度的关联,分别针对一般不明事故数据集和与工作相关的数据集。分析中对其他协变量和混杂变量(包括降水量)进行了控制。通过使用分布滞后非线性模型来考虑非线性和滞后效应。计算了温度从第75百分位数到第99百分位数(高温)以及从第25百分位数到第1百分位数(低温)增量的相对风险。一般不明事故的结果显示与高温呈正相关(RR = 1.12,95% CI:1.09 - 1.16),与低温呈负相关(RR = 0.93,95% CI:0.91 - 0.96),而与工作相关的事故中,高温和低温均呈正相关(RR = 1.06(95% CI:1.01 - 1.11)和RR = 1.10(95% CI:1.05 - 1.16)。研究发现,骑摩托车、事故发生地点(城市与城外)、是否有十字路口以及诸如工作时使用车辆等职业因素,都会在极端温度期间产生更高的道路交通事故风险。需要采取缓解和预防措施以限制社会和医疗成本。