Your browser doesn't support javascript.
loading
The Combined Effects of Hourly Multi-Pollutant on the Risk of Ambulance Emergency Calls: A Seven-Year Time Series Study.
Shi, Hanxu; Zhou, Qiang; Zhang, Hongjuan; Sun, Shengzhi; Zhao, Junfeng; Wang, Yasha; Huang, Jie; Jin, Yinzi; Zheng, Zhijie; Wu, Rengyu; Zhang, Zhenyu.
Afiliação
  • Shi H; Department of Global Health, School of Public Health, Peking University, Beijing 100191, China.
  • Zhou Q; Shenzhen Center for Prehospital Care, Shenzhen 518025, China.
  • Zhang H; Shenzhen Center for Prehospital Care, Shenzhen 518025, China.
  • Sun S; School of Public Health, Capital Medical University, Beijing 100054, China.
  • Zhao J; School of Computer Science, Peking University, Beijing 100871, China.
  • Wang Y; National Engineering Research Center of Software Engineering, Peking University, Beijing 100871, China.
  • Huang J; School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen 518055, China.
  • Jin Y; Department of Global Health, School of Public Health, Peking University, Beijing 100191, China.
  • Zheng Z; Institute for Global Health and Development, Peking University, Beijing 100871, China.
  • Wu R; Department of Global Health, School of Public Health, Peking University, Beijing 100191, China.
  • Zhang Z; Shenzhen Center for Prehospital Care, Shenzhen 518025, China.
Toxics ; 11(11)2023 Oct 31.
Article em En | MEDLINE | ID: mdl-37999547
ABSTRACT

BACKGROUND:

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., PM2.5, PM10, Ozone, NO2, and SO2) on all-cause and cause-specific AECs by using the quantile g-computation method.

METHODS:

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.

RESULTS:

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 PM2.5, PM10, Ozone, NO2, and SO2 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.

CONCLUSIONS:

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 NO2 emissions.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Toxics Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Toxics Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China
...