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Tota M, Karska J, Kowalski S, Piątek N, Pszczołowska M, Mazur K, Piotrowski P. Environmental pollution and extreme weather conditions: insights into the effect on mental health. Front Psychiatry 2024; 15:1389051. [PMID: 38863619 PMCID: PMC11165707 DOI: 10.3389/fpsyt.2024.1389051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/13/2024] [Indexed: 06/13/2024] Open
Abstract
Environmental pollution exposures, including air, soil, water, light, and noise pollution, are critical issues that may implicate adverse mental health outcomes. Extreme weather conditions, such as hurricanes, floods, wildfires, and droughts, may also cause long-term severe concerns. However, the knowledge about possible psychiatric disorders associated with these exposures is currently not well disseminated. In this review, we aim to summarize the current knowledge on the impact of environmental pollution and extreme weather conditions on mental health, focusing on anxiety spectrum disorders, autism spectrum disorders, schizophrenia, and depression. In air pollution studies, increased concentrations of PM2.5, NO2, and SO2 were the most strongly associated with the exacerbation of anxiety, schizophrenia, and depression symptoms. We provide an overview of the suggested underlying pathomechanisms involved. We highlight that the pathogenesis of environmental pollution-related diseases is multifactorial, including increased oxidative stress, systematic inflammation, disruption of the blood-brain barrier, and epigenetic dysregulation. Light pollution and noise pollution were correlated with an increased risk of neurodegenerative disorders, particularly Alzheimer's disease. Moreover, the impact of soil and water pollution is discussed. Such compounds as crude oil, heavy metals, natural gas, agro-chemicals (pesticides, herbicides, and fertilizers), polycyclic or polynuclear aromatic hydrocarbons (PAH), solvents, lead (Pb), and asbestos were associated with detrimental impact on mental health. Extreme weather conditions were linked to depression and anxiety spectrum disorders, namely PTSD. Several policy recommendations and awareness campaigns should be implemented, advocating for the advancement of high-quality urbanization, the mitigation of environmental pollution, and, consequently, the enhancement of residents' mental health.
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Affiliation(s)
- Maciej Tota
- Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Julia Karska
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
| | - Szymon Kowalski
- Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Natalia Piątek
- Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| | | | - Katarzyna Mazur
- Faculty of Medicine, Wroclaw Medical University, Wroclaw, Poland
| | - Patryk Piotrowski
- Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland
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Cheng C, Liu Y, Han C, Fang Q, Cui F, Li X. Effects of extreme temperature events on deaths and its interaction with air pollution. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 915:170212. [PMID: 38246371 DOI: 10.1016/j.scitotenv.2024.170212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 12/17/2023] [Accepted: 01/14/2024] [Indexed: 01/23/2024]
Abstract
BACKGROUND Both extreme temperature events (ETEs) and air pollution affected human health, and their effects were often not independent. Previous studies have provided limited information on the interactions between ETEs and air pollution. METHODS We collected data on deaths (non-accidental, cardiovascular, and respiratory) in Zibo City along with daily air pollution and meteorological data from January 2015 to December 2019. Distributed lag non-linear model was used to explore the health effects of ETEs on deaths. Non-parametric binary response model, hierarchical model and joint effect model were used to further explore the interaction between ETEs and air pollution in different seasons. Meanwhile, subgroup analysis by gender and age (≥ 65 years old and < 65 years old) was conducted to identify the vulnerable population. RESULTS ETEs increased death risk, especially for cardiovascular and respiratory deaths. Heat waves had a stronger impact than cold spells. Cold spells had a longer lag and fluctuating trend. Heat waves had a short-term impact, followed by a decrease. Females and those aged ≥ 65 were more affected, but subgroup differences were not significant. During ETEs and non-ETEs, there were different effects on deaths with per IQR increase in air pollutant concentrations. Joint effect models revealed that there was a significant interaction between ETEs and air pollution on non-accidental deaths. The interaction between PM2.5 and cold spells was antagonistic in the cold season. In the warm season, the health effects of heat waves and high O3 concentration were enhanced. The relative excess risk due to interaction (RERI) of cold spells and PM2.5 in total population was -0.09 (95 % CI: -0.17, -0.01), and 9 % (95 % CI: 1 %, 17 %) of the total effect was attributable to interaction. Subgroup analysis confirmed the interactions in females and those aged ≥ 65. CONCLUSIONS Significant association observed between ETEs and deaths. Females and ≥ 65 age groups were vulnerable. There were interactions between ETEs and air pollution. The effect of PM2.5 on deaths decreased during cold spells, while the effect of O3 increased during heat waves. In addition to improving air quality, it is necessary to further strengthen the prevention and control of ETEs.
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Affiliation(s)
- Chuanlong Cheng
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Ying Liu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Ma'anshan Center for Disease Control and Prevention, Ma'anshan 243000, Anhui, China
| | - Chuang Han
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Qidi Fang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Feng Cui
- Zibo Center for Disease Control and Prevention, Zibo, Shandong, China
| | - Xiujun Li
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
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Li Z, Wan J, Peng S, Wang R, Dai Z, Liu C, Feng Y, Xiang H. Associations between cold spells of different time types and coronary heart disease severity. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 343:123100. [PMID: 38070638 DOI: 10.1016/j.envpol.2023.123100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/15/2023] [Accepted: 12/03/2023] [Indexed: 12/24/2023]
Abstract
Limited evidence showed the association between cold spells and the severity of coronary heart disease (CHD). This study was to investigate the association between cold spells with their different time types and CHD severity. We collected data on CHD patients admitted to the Zhongnan Hospital, Wuhan, China from 2016 to 2021. CHD severity was quantified using the SYNTAX score and transformed into a binomial variable. Daily mean, maximum and minimum temperature were collected during the study period. We first used daily mean temperature to find the optimum definition among multiple thresholds and durations. The daily maximum and minimum temperatures were used to define different types of cold spells (daytime, nighttime and compound) based on the optimum definition. Annual cold spell days were included to assess individual exposure to cold spells. Logistic regression models were performed to fit the association between cold spell days and CHD severity stratified by different tertiles of PM2.5 and NDVI. In this study, 1937 CHD patients were included. The cold spell defined as at least four consecutive days with daily mean temperature below the 5th percentile exhibited the optimum model. We found that a 4-day increase in cold spell days was associated with more severe CHD (OR = 1.170, 95% CI: 1.074, 1.282). Such an association was more pronounced under higher levels of PM2.5 by OR = 1.270 (1.086, 1.494) and lower levels of greenness by OR = 1.240 (1.044, 1.476). Compared with daytime and compound cold spells, nighttime cold spells showed the strongest association with CHD severity by OR = 1.141 (1.026, 1.269). This study showed that exposure to cold spells was positively associated with CHD severity, especially the nighttime cold spells. The association between cold spells and CHD severity was more significant in high levels of PM2.5 and low levels of greenness.
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Affiliation(s)
- Zhaoyuan Li
- School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Jing Wan
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, China
| | - Shouxin Peng
- School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Ruonan Wang
- School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Zhongli Dai
- School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China
| | - Cuiyi Liu
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, China
| | - Yujia Feng
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, 430071, China
| | - Hao Xiang
- School of Public Health, Wuhan University, 115# Donghu Road, Wuhan, 430071, China; Global Health Institute, Wuhan University, 115# Donghu Road, Wuhan, 430071, China.
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Mastellari T, Rogers JP, Cortina-Borja M, David AS, Zandi MS, Amad A, Lewis G. Seasonality of presentation and birth in catatonia. Schizophr Res 2024; 263:214-222. [PMID: 36933976 DOI: 10.1016/j.schres.2023.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2022] [Revised: 03/06/2023] [Accepted: 03/07/2023] [Indexed: 03/20/2023]
Abstract
BACKGROUND Catatonia is a neuropsychiatric syndrome associated with both psychiatric disorders and medical conditions. Understanding of the pathophysiology of catatonia remains limited, and the role of the environment is unclear. Although seasonal variations have been shown for many of the disorders underlying catatonia, the seasonality of this syndrome has not yet been adequately explored. METHODS Clinical records were screened to identify a cohort of patients suffering from catatonia and a control group of psychiatric inpatients, from 2007 to 2016 in South London. In a cohort study, the seasonality of presentation was explored fitting regression models with harmonic terms, while the effect of season of birth on subsequent development of catatonia was analyzed using regression models for count data. In a case-control study, the association between month of birth and catatonia was studied fitting logistic regression models. RESULTS In total, 955 patients suffering from catatonia and 23,409 controls were included. The number of catatonic episodes increased during winter, with a peak in February. Similarly, an increasing number of cases was observed during summer, with a second peak in August. However, no evidence for an association between month of birth and catatonia was found. CONCLUSIONS The presentation of catatonia showed seasonal variation in accordance with patterns described for many of the disorders underlying catatonia, such as mood disorders and infections. We found no evidence for an association between season of birth and risk of developing catatonia. This may imply that recent triggers may underpin catatonia, rather than distal events.
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Affiliation(s)
- Tomas Mastellari
- University of Lille, Inserm U1172, CHU de Lille, Lille Neuroscience & Cognition (LilNCog), Lille, France; Division of Psychiatry, University College London, London, UK.
| | - Jonathan P Rogers
- Division of Psychiatry, University College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK
| | - Mario Cortina-Borja
- Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Anthony S David
- Institute of Mental Health, University College London, London, UK
| | - Michael S Zandi
- Queen Square Institute of Neurology, University College London, London, UK; National Hospital for Neurology and Neurosurgery, London, UK
| | - Ali Amad
- University of Lille, Inserm U1172, CHU de Lille, Lille Neuroscience & Cognition (LilNCog), Lille, France; Department of Neuroimaging, King's College London, London, UK
| | - Glyn Lewis
- Division of Psychiatry, University College London, London, UK
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Zhou L, Wang Y, Wang Q, Ding Z, Jin H, Zhang T, Zhu B. The interactive effects of extreme temperatures and PM 2.5 pollution on mortalities in Jiangsu Province, China. Sci Rep 2023; 13:9479. [PMID: 37301905 PMCID: PMC10257702 DOI: 10.1038/s41598-023-36635-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 06/07/2023] [Indexed: 06/12/2023] Open
Abstract
Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM2.5 pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM2.5 pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.
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Affiliation(s)
- Lian Zhou
- Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, China
| | - Yuning Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 Dingjia Bridge, Gulou District, Nanjing, 210009, China.
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China.
| | - Qingqing Wang
- Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, China
| | - Zhen Ding
- Center for Disease Control and Prevention of Jiangsu Province, Nanjing, 210009, China
| | - Hui Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 Dingjia Bridge, Gulou District, Nanjing, 210009, China
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, 210009, China
| | - Ting Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China.
- Department of Civil, Environmental, and Infrastructure Engineering, George Mason University, Fairfax, VA, 22030, USA.
| | - Baoli Zhu
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
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Yuan J, Chang W, Yao Z, Wen L, Liu J, Pan R, Yi W, Song J, Yan S, Li X, Liu L, Wei N, Song R, Jin X, Wu Y, Li Y, Liang Y, Sun X, Mei L, Cheng J, Su H. The impact of hazes on schizophrenia admissions and the synergistic effect with the combined atmospheric oxidation capacity in Hefei, China. ENVIRONMENTAL RESEARCH 2023; 220:115203. [PMID: 36592807 DOI: 10.1016/j.envres.2022.115203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/15/2022] [Accepted: 12/30/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVES Currently, most epidemiological studies on haze focus on respiratory diseases, cardiovascular diseases, etc. However, the relationship between haze and mental health has not been adequately explored. The purpose of this study was to investigate the influence of hazes on schizophrenia admissions and to further explore the potential interaction effect with the combined atmospheric oxidative indices (Ox and Oxwt). METHODS We collected 5328 cases during the cold season from 2013 to 2015 in Hefei, China. By integrating the Poisson Generalized Linear Models with the Distributed Lag Non-linear Models, the association between haze and schizophrenia admissions was evaluated. The interaction between hazes and two combined oxidation indexes was tested by stratifying hazes and Ox, and Oxwt. RESULTS Haze was found to be significantly linked to an increased risk of hospitalization for schizophrenia, and a 9-day lag effect on schizophrenia (lag 3-lag 11), with the largest effect on lag 6 (RR = 1.080, 95% confidence interval (CI): 1.046-1.116). Males, females, and <40 y (people under 40 years old) were sensitive to hazes. Furthermore, in the stratified analysis, we found synergies between two combined oxidation indexes and hazes. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) between Ox and hazes were 1.170 (95% CI: 1.071-1.277) and 0.149 (95% CI: 0.045-0.253), respectively. For Oxwt, the IRR and RERI were 1.179 (95% CI: 1.087-1.281) and 0.159 (95% CI: 0.056-0.263), respectively. It is noteworthy that this synergistic effect was significant in males and <40 y when examining the various subgroups in the interaction analysis. CONCLUSIONS Our findings suggest that exposure to haze significantly increases the risk of hospitalization for schizophrenia. More significant public health benefits can be obtained by prioritizing haze periods with high combined atmospheric oxidation capacity.
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Affiliation(s)
- Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Weiwei Chang
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, 241002, Wuhu, Anhui, China
| | - Zhenhai Yao
- Anhui Public Meteorological Service Center, Hefei, Anhui, China
| | - Liying Wen
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, 241002, Wuhu, Anhui, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Diseases, Hefei, Anhui, 230032, China.
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Huang Y, Wang Y, Zhang T, Wang P, Huang L, Guo Y. Exploring Health Effects under Specific Causes of Mortality Based on 90 Definitions of PM 2.5 and Cold Spell Combined Exposure in Shanghai, China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:2423-2434. [PMID: 36724352 DOI: 10.1021/acs.est.2c06461] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In this study, a total of 90 definitions were set up based on six air pollution definitions, five cold spell definitions, and three combined exposure scenarios. The relative risks (RRs) on all-cause, circulatory, and respiratory mortality were explored by a model combining a distributed linear lag model with quasi-Poisson regression. The definition in which daily PM2.5 increases more than 75 μg/m3 for at least 2 days and the average temperature falls below the 10th percentile for at least 2 days produced the best model fit performance in all-cause mortality. The high peaks of the health effect were generally observed around the lag days 6-9. The cumulative relative risks (CRRs) were more significant in the simultaneous-exposure scenario and higher in respiratory mortality, where the highest CRR (12.15, 3.69-40.03) was observed in definition P1T5, in which daily PM2.5 increases more than 75 μg/m3, and the average temperature falls below the 2.5th percentile for at least two days. For relative risk due to interaction (RERI), we found positive additive interactions (RERI > 0) between PM2.5 pollution and cold spell, especially in respiratory mortality. Clarifying the definition of combined events can help policymakers to capture health risks and construct more effective risk warning systems.
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Affiliation(s)
- Yujia Huang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Yiyi Wang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Ting Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Peng Wang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
- Faculty of Civil Engineering and Mechanics, Jiangsu University, Zhenjiang 212013, China
| | - Lei Huang
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Yuming Guo
- Department of Epidemiology and Preventive Medicine, School of Public and Preventive Medicine, Monash University, Melbourne 3004, VIC, Australia
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