Shi Hanxu, Zhou Qiang, Zhang Hongjuan, Sun Shengzhi, Zhao Junfeng, Wang Yasha, Huang Jie, Jin Yinzi, Zheng Zhijie, Wu Rengyu, Zhang Zhenyu
Department of Global Health, School of Public Health, Peking University, Beijing 100191, China.
Shenzhen Center for Prehospital Care, Shenzhen 518025, China.
Toxics. 2023 Oct 31;11(11):895. doi: 10.3390/toxics11110895.
Ambulance emergency calls (AECs) are seen as a more suitable metric for syndromic surveillance due to their heightened sensitivity in reflecting the health impacts of air pollutants. Limited evidence has emphasized the combined effect of hourly air pollutants on AECs. This study aims to investigate the combined effects of multipollutants (i.e., PM, PM, Ozone, NO, and SO) on all-cause and cause-specific AECs by using the quantile g-computation method.
We used ambulance emergency dispatch data, air pollutant data, and meteorological data from between 1 January 2013 and 31 December 2019 in Shenzhen, China, to estimate the associations of hourly multipollutants with AECs. We followed a two-stage analytic protocol, including the distributed lag nonlinear model, to examine the predominant lag for each air pollutant, as well as the quantile g-computation model to determine the associations of air pollutant mixtures with all-cause and cause-specific AECs.
A total of 3,022,164 patients were identified during the study period in Shenzhen. We found that each interquartile range increment in the concentrations of PM, PM, Ozone, NO, and SO in 0-8 h, 0-8 h, 0-48 h, 0-28 h, and 0-24 h was associated with the highest risk of AECs. Each interquartile range increase in the mixture of air pollutants was significantly associated with a 1.67% (95% CI, 0.12-3.12%) increase in the risk of all-cause AECs, a 1.81% (95% CI, 0.25-3.39%) increase in the risk of vascular AECs, a 1.77% (95% CI, 0.44-3.11%) increase in reproductive AECs, and a 2.12% (95% CI, 0.56-3.71%) increase in AECs due to injuries.
We found combined effects of pollutant mixtures associated with an increased risk of AECs across various causes. These findings highlight the importance of targeted policies and interventions to reduce air pollution, particularly for PM, Ozone, and NO emissions.
救护车紧急呼叫（AECs）被视为症状监测的更合适指标，因为其在反映空气污染物对健康的影响方面具有更高的敏感性。有限的证据强调了每小时空气污染物对AECs的综合影响。本研究旨在通过使用分位数g计算方法，调查多种污染物（即颗粒物、细颗粒物、臭氧、一氧化氮和二氧化硫）对全因和特定病因AECs的综合影响。
我们使用了中国深圳2013年1月1日至2019年12月31日期间的救护车紧急调度数据、空气污染物数据和气象数据，以估计每小时多种污染物与AECs之间的关联。我们遵循两阶段分析方案，包括分布滞后非线性模型，以检查每种空气污染物的主要滞后，以及分位数g计算模型，以确定空气污染物混合物与全因和特定病因AECs之间的关联。
在深圳的研究期间共识别出3022164名患者。我们发现，在0 - 8小时、0 - 8小时、0 - 48小时、0 - 28小时和0 - 24小时内，颗粒物、细颗粒物、臭氧、一氧化氮和二氧化硫浓度每增加一个四分位数间距，与AECs的最高风险相关。空气污染物混合物每增加一个四分位数间距，全因AECs风险显著增加1.67%（95%置信区间，0.12 - 3.12%），血管AECs风险增加1.81%（95%置信区间，0.25 - 3.39%），生殖AECs风险增加1.77%（95%置信区间，0.44 - 3.11%），因伤AECs风险增加2.l2%（95%置信区间，0.56 - 3.71%）。
我们发现污染物混合物的综合影响与各种病因导致的AECs风险增加相关。这些发现凸显了针对性政策和干预措施对于减少空气污染的重要性，特别是对于颗粒物、臭氧和一氧化氮排放。
