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Wang Y, Chang J, Hu P, Deng C, Luo Z, Zhao J, Zhang Z, Yi W, Zhu G, Zheng G, Wang S, He K, Liu J, Liu H. Key factors in epidemiological exposure and insights for environmental management: Evidence from meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 362:124991. [PMID: 39303936 PMCID: PMC7616677 DOI: 10.1016/j.envpol.2024.124991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 08/14/2024] [Accepted: 09/17/2024] [Indexed: 09/22/2024]
Abstract
In recent years, the precision of exposure assessment methods has been rapidly improved and more widely adopted in epidemiological studies. However, such methodological advancement has introduced additional heterogeneity among studies. The precision of exposure assessment has become a potential confounding factors in meta-analyses, whose impacts on effect calculation remain unclear. To explore, we conducted a meta-analysis to integrate the long- and short-term exposure effects of PM2.5, NO2, and O3 on all-cause, cardiovascular, and respiratory mortality in the Chinese population. Literature was identified through Web of Science, PubMed, Scopus, and China National Knowledge Infrastructure before August 28, 2023. Sub-group analyses were performed to quantify the impact of exposure assessment precisions and pollution levels on the estimated risk. Studies achieving merely city-level resolution and population exposure are classified as using traditional assessment methods, while those achieving sub-kilometer simulations and individual exposure are considered finer assessment methods. Using finer assessment methods, the RR (under 10 μg/m3 increment, with 95% confidence intervals) for long-term NO2 exposure to all-cause mortality was 1.13 (1.05-1.23), significantly higher (p-value = 0.01) than the traditional assessment result of 1.02 (1.00-1.03). Similar trends were observed for long-term PM2.5 and short-term NO2 exposure. A decrease in short-term PM2.5 levels led to an increase in the RR for all-cause and cardiovascular mortality, from 1.0035 (1.0016-1.0053) and 1.0051 (1.0021-1.0081) to 1.0055 (1.0035-1.0075) and 1.0086 (1.0061-1.0111), with weak between-group significance (p-value = 0.13 and 0.09), respectively. Based on the quantitative analysis and literature information, we summarized four key factors influencing exposure assessment precision under a conceptualized framework: pollution simulation resolution, subject granularity, micro-environment classification, and pollution levels. Our meta-analysis highlighted the urgency to improve pollution simulation resolution, and we provide insights for researchers, policy-makers and the public. By integrating the most up-to-date epidemiological research, our study has the potential to provide systematic evidence and motivation for environmental management.
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Affiliation(s)
- Yongyue Wang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jie Chang
- National Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, Beijing, 100084, China; Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Piaopiao Hu
- Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Chun Deng
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhenyu Luo
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Junchao Zhao
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Zhining Zhang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Wen Yi
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Guanlin Zhu
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Guangjie Zheng
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Shuxiao Wang
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Kebin He
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Jing Liu
- Centre for Clinical and Epidemiologic Research, Beijing an Zhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, 100029, China
| | - Huan Liu
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China.
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Feng Q, Chen Y, Su S, Zhang X, Lin X. Acute effect of fine particulate matter and respiratory mortality in Changsha, China: a time-series analysis. BMC Pulm Med 2022; 22:416. [PMID: 36368963 PMCID: PMC9652800 DOI: 10.1186/s12890-022-02216-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 11/02/2022] [Indexed: 11/13/2022] Open
Abstract
Background Previous studies have confirmed that exposure to fine particulate matter (PM2.5) is associated with respiratory disease mortality. However, due to the differences in PM2.5 concentration, composition and population susceptibility within different regions, the estimates of the association between PM2.5 concentration and mortality are different. Moreover, few studies have examined the potential hazard of excessive PM2.5 exposure in terms of respiratory disease mortality. Methods Daily recorded data on meteorological indices, environmental pollutants, and causes of death data in Changsha from January 2015 to December 2018 were obtained. The potential relationship between PM2.5 concentrations and respiratory disease mortality was determined using distributed lag nonlinear model (DLNM), which includes the relative risk (RR) and cumulative relative risk (CRR) of the lagged effect. The synergistic effects of other air pollutants were also considered. Results A total of 8,825 cases of respiratory disease mortality occurred in Changsha between 2015 and 2018. The acute effect of PM2.5 concentration was associated with an increased risk of respiratory disease mortality. Regarding the lag specific effect, a 10 μg/m3 increase in PM2.5 concentration on respiratory disease mortality was statistically significant at lag day 0 and lag day 7 with a relative risk of 1.019 (95% CI 1.007- 1.031) and 1.013(95%CI: 1.002-1.024). As for the cumulative lag effect, a 4-day moving average of PM2.5 concentrations was significantly associated with a cumulative relative risk of 1.027 (95%CI: 1.011-1.031). The single-day lag effect and cumulative 4-day lag effect for male individuals were more significant than those observed in females. The effect of PM2.5 concentrations and respiratory disease mortality remained statistically significant in the multi-pollutant models (SO2, NO2, and O3). A higher risk was observed in the cold season than in the warm season. Conclusions Our findings show a potential association between exposure to PM2.5 concentration and respiratory disease mortality in Changsha, with male individuals observed to have particularly higher risk.
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Wang M, Li H, Huang S, Qian Y, Steenland K, Xie Y, Papatheodorou S, Shi L. Short-term exposure to nitrogen dioxide and mortality: A systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2021; 202:111766. [PMID: 34331919 PMCID: PMC8578359 DOI: 10.1016/j.envres.2021.111766] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/18/2021] [Accepted: 07/23/2021] [Indexed: 05/05/2023]
Abstract
BACKGROUND Ambient air pollution has been characterized as a leading cause of mortality worldwide and has been associated with cardiovascular and respiratory diseases. There is increasing evidence that short-term exposure to nitrogen dioxide (NO2), is related to adverse health effects and mortality. METHODS We conducted a systematic review of short-term NO2 and daily mortality, which were indexed in PubMed and Embase up to June 2021. We calculated random-effects estimates by different continents and globally, and tested for heterogeneity and publication bias. RESULTS We included 87 articles in our quantitative analysis. NO2 and all-cause as well as cause-specific mortality were positively associated in the main analysis. For all-cause mortality, a 10 ppb increase in NO2 was associated with a 1.58% (95%CI 1.28%-1.88%, I2 = 96.3%, Eggers' test p < 0.01, N = 57) increase in the risk of death. For cause-specific mortality, a 10 ppb increase in NO2 was associated with a 1.72% (95%CI 1.41%-2.04%, I2 = 87.4%, Eggers' test p < 0.01, N = 42) increase in cardiovascular mortality and a 2.05% (95%CI 1.52%-2.59%, I2 = 78.5%, Eggers' test p < 0.01, N = 38) increase in respiratory mortality. In the sensitivity analysis, the meta-estimates for all-cause mortality, cardiovascular and respiratory mortality were nearly identical. The heterogeneity would decline to varying degrees through regional and study-design stratification. CONCLUSIONS This study provides evidence of an association between short-term exposure to NO2, a proxy for traffic-sourced air pollutants, and all-cause, cardiovascular and respiratory mortality.
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Affiliation(s)
- Mingrui Wang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Haomin Li
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Shiwen Huang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yaoyao Qian
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Kyle Steenland
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Yang Xie
- School of Economics and Management, Beihang University, Beijing, China
| | | | - Liuhua Shi
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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