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A Time Series Analysis of Associations between Daily Temperature and Crime Events in Philadelphia Pennsylvania

机译:宾夕法尼亚州费城每日温度与犯罪事件之间的关联的时间序列分析

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摘要

Urban crime may be an important but overlooked public health impact of rising ambient temperatures. We conducted a time series analysis of associations between temperature and crimes in Philadelphia, PA, for years 2006–2015. We obtained daily crime data from the Philadelphia Police Department, and hourly temperature and dew point data from the National Centers for Environmental Information. We calculated the mean daily heat index and daily deviations from each year’s seasonal mean heat index value. We used generalized additive models with a quasi-Poisson distribution, adjusted for day of the week, public holiday, and long-term trends and seasonality, to estimate relative rates (RR) and 95% confidence intervals. We found that the strongest associations were with violent crime and disorderly conduct. For example, relative to the median of the distribution of mean daily heat index values, the rate of violent crimes was 9% (95% CI 6–12%) higher when the mean daily heat index was at the 99th percentile of the distribution. There was a positive, linear relationship between deviations of the daily mean heat index from the seasonal mean and rates of violent crime and disorderly conduct, especially in cold months. Overall, these analyses suggest that disorderly conduct and violent crimes are highest when temperatures are comfortable, especially during cold months. This work provides important information regarding the temporal patterns of crime activity.Electronic supplementary materialThe online version of this article (doi:10.1007/s11524-017-0181-y) contains supplementary material, which is available to authorized users.
机译:城市犯罪可能是环境温度升高对公众健康的重要但被忽视的影响。我们对宾夕法尼亚州费城的温度与犯罪之间的关联进行了时间序列分析(2006-2015年)。我们从费城警察局获得每日犯罪数据,并从国家环境信息中心获得每小时温度和露点数据。我们计算了平均每日热量指数以及与每年的季节性平均热量指数值的每日偏差。我们使用准Poisson分布的广义加性模型(针对一周中的某天,公共假日以及长期趋势和季节性进行了调整)来估计相对利率(RR)和95%置信区间。我们发现最紧密的联系是暴力犯罪和行为不检。例如,相对于平均每日热量指数值分布的中位数,当平均每日热量指数位于分布值的99%时,暴力犯罪的发生率要高9%(95%CI 6-12%)。每日平均热量指数与季节平均值的偏差与暴力犯罪和无序行为的发生率之间存在正线性关系,特别是在寒冷月份。总体而言,这些分析表明,温度适宜时,尤其是在寒冷月份,无序行为和暴力犯罪最高。这项工作提供了有关犯罪活动的时间模式的重要信息。电子补充材料本文的在线版本(doi:10.1007 / s11524-017-0181-y)包含补充材料,授权用户可以使用。

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