空气污染与黄石市院前急救需求的时间序列分析

A time-series analysis of the association between ambient air pollution and emergency medical services demand in Huangshi city

摘要

目的：探索黄石市城区短期大气污染物暴露对急救车出诊次数的影响，并识别易受特定污染物影响的疾病类别。方法：收集2023年5月1日至2024年4月30日期间黄石市城区的急救车出诊次数、大气污染物浓度（PM_2.5、PM₁₀、SO₂、NO₂、CO、O₃）以及气象因素数据。采用时间序列研究设计，利用广义相加模型评估了空气污染与急救车出诊次数之间的关联，并分析了单日滞后及累积滞后效应，并根据急救出诊原因进行亚组分析以识别敏感疾病类型。结果：在暴露当日，PM_2.5、PM₁₀和SO₂的浓度每增加10 μg∙m^-3与黄石市城区急救车出诊次数的增加有显著关联，分别为0.89%（95%CI：0.03~1.76）、0.83%（95%CI：0.14~1.53）和16.18%（95%CI：6.11~27.21）。CO的浓度每增加1 mg∙m^-3，急救车出诊次数增加了13.96%（95%CI：0.60~29.10）。SO₂与因内科急症类疾病而出诊的急救车次数之间存在显著的关联。结论：PM_2.5、PM₁₀、SO₂和CO的短期暴露显著增加黄石市急救车出诊次数，其中SO₂对内科急症的影响尤为突出。建议建立空气污染-急救需求预警联动机制，优化重污染日医疗资源调度策略。

Abstract

Objective: To explore the impact of short-term exposure to air pollution on emergency ambulance dispatches in the main urban area of Huangshi (a city in central Hubei, China), and to identify disease categories particularly susceptible to specific pollutants. Methods: Data on the number of emergency ambulance dispatches, concentrations of air pollutants (PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃), and meteorological factors in the urban area of Huangshi City from May 1, 2023 to April 30, 2024 were collected. We constructed a time-series study and evaluated the correlation between air pollution and the number of emergency ambulance visits using a generalized additive model, and analyzed the single-day lag and cumulative lag effects. Subgroup analyses were conducted based on dispatch reasons to identify sensitive disease categories. Results: At lag 0 day, we observed a significant association between an increase of 10 μg∙m^-3 in the concentrations of PM_2.5, PM₁₀, and SO₂ and emergency ambulance dispatches in the urban area of Huangshi City, with percent changes of 0.89% (95%CI: 0.03-1.76), 0.83% (95%CI: 0.14-1.53), and 16.18% (95%CI: 6.11-27.21), respectively. For every 1 mg∙m^-3 increase in CO concentration, there was a 13.96% (95%CI: 0.60-29.10) increase in the number of emergency ambulance dispatches. We found a significant correlation between SO₂ and the number of emergency ambulance dispatches due to internal medicine emergency diseases. Conclusion: Short-term exposure to PM_2.5, PM₁₀, SO₂, and CO has a significant impact on the frequency of emergency ambulance dispatches, with SO₂ showing prominent effects on internal medicine emergencies. These findings highlight the need to establish an early warning system linking air pollution monitoring with emergency medical resource allocation, particularly during heavy pollution episodes.

关键词

空气污染 / 急救车出诊 / 急症医学 / 时间序列研究

Key words

Air Pollution / Emergency Ambulance Dispatch / Emergency Medicine / Time-Series Study

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