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Huang X, Zhou C, Tang X, Wei Y, Li D, Shen B, Lei Q, Zhou Q, Lan J, Qin Y, Su L, Long J. Durational effect of ambient air pollution on hospital admissions of schizophrenia: a time series analysis. Soc Psychiatry Psychiatr Epidemiol 2025:10.1007/s00127-025-02831-5. [PMID: 40019522 DOI: 10.1007/s00127-025-02831-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Accepted: 02/05/2025] [Indexed: 03/01/2025]
Abstract
BACKGROUND Schizophrenia may be exacerbated by ambient air pollution. In this study, we aim to explore the association of air pollution with hospital admission for schizophrenia in Liuzhou, China. METHODS The daily concentration of air pollutants was gathered from an average of seven fixed monitoring sites in Liuzhou, while the daily admission data for schizophrenia was received from The Guangxi Zhuang Autonomous Region Brain Hospital. A Poisson generalized linear regression model in conjunction with a distributed lag nonlinear model was utilized to quantify the exposure-lag-response connection between ambient air pollution and schizophrenia hospitalization. The stratification analysis was then carried out by age, gender, and season. RESULTS PM2.5, PM10, and SO2 was significantly associated with elevated number of schizophrenia hospitalization. We observed the largest single-day effects of PM2.5 at lag 17 day, PM10 at lag 17 day, and SO2 at lag 28 day, with the corresponding RRs being 1.01611 (95% CI:1.00652-1.02579), 1.01648 (95% CI:1.00603-1.02704), and 1.02001 (95% CI: 1.00001-1.04041), respectively. Stratification analysis revealed that patients who were < 45 years old and female were more vulnerable to hospitalization due to exposure to PM2.5 and PM10. The effects of PM2.5 and PM10 were more noticeable during the cooler seasons than during the warmer one. CONCLUSIONS This study reveals that being exposed to PM2.5, PM10, and SO2 may increase the chance of schizophrenia hospitalization.
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Affiliation(s)
- Xiaolan Huang
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China
| | - Chun Zhou
- The Guangxi Zhuang Autonomous Region Brain Hospital, Liuzhou, Guangxi Zhuang Autonomous Region, 545005, China
| | - Xianyan Tang
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China
| | - Yuhua Wei
- The Guangxi Zhuang Autonomous Region Brain Hospital, Liuzhou, Guangxi Zhuang Autonomous Region, 545005, China
| | - Dongmei Li
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China
| | - Bing Shen
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China
| | - Qinggui Lei
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China
| | - Qian Zhou
- The Guangxi Zhuang Autonomous Region Brain Hospital, Liuzhou, Guangxi Zhuang Autonomous Region, 545005, China
| | - Jun Lan
- The Guangxi Zhuang Autonomous Region Brain Hospital, Liuzhou, Guangxi Zhuang Autonomous Region, 545005, China
| | - Yanli Qin
- The Guangxi Zhuang Autonomous Region Brain Hospital, Liuzhou, Guangxi Zhuang Autonomous Region, 545005, China
| | - Li Su
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China
| | - Jianxiong Long
- School of Public Health, Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
- China(Guangxi)-ASEAN Engineering Research Center of Big Data for Public Health, Beijing, China.
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Li H, Zhai F, Ma Y, Wang Y, Gu R, Cao C, Wang L, Ge B, Wu W, Zhai C, Wu W. Associations of short-term exposure to air pollution with outpatient visits and treatment costs for chronic obstructive pulmonary disease in Xinxiang, China (2016-2021). THE SCIENCE OF THE TOTAL ENVIRONMENT 2025; 963:178438. [PMID: 39826208 DOI: 10.1016/j.scitotenv.2025.178438] [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: 09/18/2024] [Revised: 12/31/2024] [Accepted: 01/07/2025] [Indexed: 01/22/2025]
Abstract
The acute health effects of air pollution on the risk of chronic obstructive pulmonary disease (COPD) have not been adequately studied and results remain inconsistent. Furthermore, fewer studies have explored the impact of air pollution on the cost of treating patients with COPD. Generalized additive models (GAM) based on Poisson distribution and gamma were applied to evaluate the association between short-term exposure to air pollution and daily COPD outpatient visits and daily COPD treatment costs. A total of 14,611 outpatient in Xinxiang from 2016 to 2021 were included for analysis. We found that short-term exposure to PM2.5, PM10, NO2 and CO were positively associated with COPD outpatient visits, and gaseous pollutants appeared to have greater effects on outpatient visits than particulate matter. For the largest effect, per 10 μg/m3 increment in (per 1 mg/m3 increment in CO concentration) CO (lag 01), NO2 (lag 01), PM2.5 (lag 02) and PM10 (lag 06) were significantly associated with 7.859 % (95 % CI:3.421,12.488), 4.894 % (95 % CI:3.422,6.386), 0.627 % (95 % CI:0.010, 1.248) and 0.531 % (95 % CI:0.050,1.014) increase in daily COPD outpatient visits, respectively. Short-term exposure to air pollutants (PM10, CO and NO2) was positively associated with COPD treatment costs. No significant sex or age differences were found in the stratified analysis of outpatient visits. The effect of gaseous pollutants (NO2) on COPD outpatient visits was greater in the cold season (October to March) (P < 0.05), whereas the effect of particulate matter (PM2.5 and PM10) was greater in the warm season (April to September) (P < 0.05). Greater health benefits could be obtained when pollutant concentrations meet WHO standards. In conclusion, short-term exposure to PM2.5, PM10, NO2 and CO was significantly associated with increased COPD outpatient visits, and gaseous pollutants appeared to have greater effects on outpatient visits than particulate matter. Further larger-scale studies are needed to validate our findings.
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Affiliation(s)
- Huijun Li
- Pulmonary and Critical Care Medicine, The Affiliated People's Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China; School of Public Health, Xinxiang Medical University, Xinxiang, Henan 453003, China.
| | - Fei Zhai
- Pulmonary and Critical Care Medicine, The Affiliated People's Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China
| | - You Ma
- School of Public Health, Xinxiang Medical University, Xinxiang, Henan 453003, China
| | - Yongbin Wang
- School of Public Health, Xinxiang Medical University, Xinxiang, Henan 453003, China
| | - Rongrong Gu
- Pulmonary and Critical Care Medicine, The Affiliated People's Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China
| | - Chenlong Cao
- Pulmonary and Critical Care Medicine, The Affiliated People's Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China
| | - Lei Wang
- Public Health Department, The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China
| | - Beilei Ge
- Pulmonary and Critical Care Medicine, The Affiliated People's Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China
| | - Wei Wu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Chengkai Zhai
- Pulmonary and Critical Care Medicine, The Affiliated People's Hospital of Xinxiang Medical University, Xinxiang, Henan 453000, China
| | - Weidong Wu
- School of Public Health, Xinxiang Medical University, Xinxiang, Henan 453003, China.
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Hao Y, Xu L, Peng M, Yang Z, Wang W, Meng F. Synergistic air pollution exposure elevates depression risk: A cohort study. ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY 2025; 23:100515. [PMID: 39687214 PMCID: PMC11647501 DOI: 10.1016/j.ese.2024.100515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2024] [Revised: 11/20/2024] [Accepted: 11/20/2024] [Indexed: 12/18/2024]
Abstract
Depression is a leading mental health disorder worldwide, contributing substantially to the global disease burden. While emerging evidence suggests links between specific air pollutants and depression, the potential interactions among multiple pollutants remain underexplored. Here we show the influence of six common air pollutants on depressive symptoms among middle-aged and older Chinese adults. In single-pollutant models, a 10 μg m-3 increase in SO2, CO, PM10, and PM2.5 is associated with increased risks of depressive symptoms, with odds ratios (95% confidence intervals) of 1.276 (1.238-1.315), 1.007 (1.006-1.008), 1.066 (1.055-1.078), and 1.130 (1.108-1.153), respectively. In two-pollutant models, SO2 remains significantly associated with depressive symptoms after adjusting for other pollutants. Multi-pollutant models uncover synergistic effects, with SO2, CO, NO2, PM10, and PM2.5 exhibiting significant interactions, identifying SO2 as the primary driver of these associations. Mediation analyses further indicate that cognitive and physical impairments partially mediate the relationship between air pollution and depressive symptoms. These findings underscore the critical mental health impacts of air pollution and highlight the need for integrated air quality management strategies. Targeted mitigation of specific pollutants, particularly SO2, is expected to significantly enhance public mental health outcomes.
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Affiliation(s)
- Yuqing Hao
- Department of Environmental Hygiene, School of Public Health, Harbin Medical University, Harbin, 150081, China
| | - Longzhu Xu
- Department of Environmental Hygiene, School of Public Health, Harbin Medical University, Harbin, 150081, China
| | - Meiyu Peng
- Department of Environmental Hygiene, School of Public Health, Harbin Medical University, Harbin, 150081, China
| | - Zhugen Yang
- Faculty of Engineering and Applied Science, Cranfield University, Cranfield, MK43 0AL, UK
| | - Weiqi Wang
- Department of Environmental Hygiene, School of Public Health, Harbin Medical University, Harbin, 150081, China
| | - Fanyu Meng
- Department of Environmental Hygiene, School of Public Health, Harbin Medical University, Harbin, 150081, China
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Fan H, Li J, Dou Y, Yan Y, Wang M, Yang X, Ma X. Linking ambient air pollution to mental health: evidence based on the two-sample Mendelian randomization and colocalization study. Transl Psychiatry 2024; 14:489. [PMID: 39695075 DOI: 10.1038/s41398-024-03196-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 11/29/2024] [Accepted: 12/06/2024] [Indexed: 12/20/2024] Open
Abstract
Growing evidence links air pollution, a ubiquitous environmental stressor, to a higher risk of developing mental disorders, raising significant public health concerns. Mental disorders represent a significant global public health challenge which can have a profound impact on individual lives. In this study, we used Mendelian randomization (MR) to investigate the causal relationship between ambient air pollution and four common mental disorders. Genome-wide association study (GWAS) data for ambient air pollution and summary-level GWAS data for four representative mental disorders were obtained from open-access database. Inverse variance weighted (IVW) method with multiplicative random-effects model was the main analysis. Sensitivity analyses were conducted to validate the results. Bayesian colocalization analysis was conducted to explore the potential shared genetic causal variants between specific air pollutants and mental disorders. A suggestive association was observed between political matter (PM) 2.5 and anxiety disorders (OR 2.96, 95%CI 1.29-6.81, p = 0.010). Exposure to nitrogen dioxide (NO2) was significantly linked to an elevated risk of schizophrenia (OR 1.95, 95% CI 1.45-2.63, p = 1.13E-05) and showed a nominal association with an increased risk of bipolar disorder (OR 1.43, 95% CI 1.09-1.86, p = 0.009). A suggestive causal association was detected between nitrogen oxides (NOx) and anxiety disorder (OR 2.90, 95%CI 1.21-6.97, p = 0.017). No significant association was detected between exposure to PM2.5-10, PM10 and mental disorders. No significant horizonal pleiotropy and heterogeneity was found. The colocalization analysis revealed robust evidence supporting the colocalization of NO2 with schizophrenia at SNP rs12203592. Our findings support causal associations between exposure to ambient air pollution, particularly PM2.5, NO2, and NOx, and an increased risk of specific mental disorders.
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Affiliation(s)
- Huanhuan Fan
- Mental health center and laboratory of psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Junhong Li
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan province, China
| | - Yikai Dou
- Mental health center and laboratory of psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Yushun Yan
- Mental health center and laboratory of psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Min Wang
- Mental health center and laboratory of psychiatry, West China Hospital, Sichuan University, Chengdu, China
| | - Xiao Yang
- Mental health center and laboratory of psychiatry, West China Hospital, Sichuan University, Chengdu, China.
| | - Xiaohong Ma
- Mental health center and laboratory of psychiatry, West China Hospital, Sichuan University, Chengdu, China.
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5
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Smolker HR, Reid CE, Friedman NP, Banich MT. The Association between Exposure to Fine Particulate Air Pollution and the Trajectory of Internalizing and Externalizing Behaviors during Late Childhood and Early Adolescence: Evidence from the Adolescent Brain Cognitive Development (ABCD) Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:87001. [PMID: 39106155 DOI: 10.1289/ehp13427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/09/2024]
Abstract
BACKGROUND Exposure to high levels of fine particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) via air pollution may be a risk factor for psychiatric disorders during adulthood. Yet few studies have examined associations between exposure and the trajectory of symptoms across late childhood and early adolescence. OBJECTIVE The current study evaluated whether PM 2.5 exposure at 9-11 y of age affects both concurrent symptoms as well as the longitudinal trajectory of internalizing and externalizing behaviors across the following 3 y. This issue was examined using multiple measures of exposure and separate measures of symptoms of internalizing disorders (e.g., depression, anxiety) and externalizing disorders (e.g., conduct disorder), respectively. METHODS In a sample of more than 10,000 youth from the Adolescent Brain Cognitive Development (ABCD) Study, we used a dataset of historical PM 2.5 levels and growth curve modeling to evaluate associations of PM 2.5 exposure with internalizing and externalizing symptom trajectories, as assessed by the Child Behavioral Check List. Three distinct measures of PM 2.5 exposure were investigated: annual average concentration during 2016, number of days in 2016 above the US Environmental Protection Agency (US EPA) 24-h PM 2.5 standards, and maximum 24-h concentration during 2016. RESULTS At baseline, higher number of days with PM 2.5 levels above US EPA standards was associated with higher parent-reported internalizing symptoms in the same year. This association remained significant up to a year following exposure and after controlling for PM 2.5 annual average, maximum 24-h level, and informant psychopathology. There was also evidence of an association between PM 2.5 annual average and externalizing symptom levels at baseline in females only. DISCUSSION Results suggested PM 2.5 exposure during childhood is associated with higher symptoms of internalizing and externalizing disorders at the time of exposure and 1 y later. In addition, effects of PM 2.5 exposure on youth internalizing symptoms may be most impacted by the number of days of exposure above US EPA standards in comparison with annual average and maximum daily exposure. https://doi.org/10.1289/EHP13427.
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Affiliation(s)
- Harry R Smolker
- Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado, USA
| | - Colleen E Reid
- Department of Geography, University of Colorado Boulder, Boulder, Colorado, USA
- Institute of Behavioral Science, University of Colorado Boulder, Boulder, Colorado, USA
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, USA
| | - Marie T Banich
- Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, Colorado, USA
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6
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Yoo EH, Roberts JE. Differential effects of air pollution exposure on mental health: Historical redlining in New York State. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 948:174516. [PMID: 39009165 DOI: 10.1016/j.scitotenv.2024.174516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 07/03/2024] [Accepted: 07/03/2024] [Indexed: 07/17/2024]
Abstract
Growing evidence suggests that ambient air pollution has adverse effects on mental health, yet our understanding of its unequal impact remains limited, especially in areas with historical redlining practices. This study investigates whether the impact of daily fluctuations in ambient air pollutant levels on emergency room (ER) visits for mental disorders (MDs) varies across neighborhoods affected by redlining. Furthermore, we explored how demographic characteristics and ambient temperature may modify the effects of air pollution. To assess the disproportional short-term effects of PM2.5, NO2, and O3 on ER visits across redlining neighborhoods, we used a symmetric bidirectional case-crossover design with a conditional logistic regression model. We analyzed data from 2 million ER visits for MDs between 2005 and 2016 across 17 cities in New York State, where redlining policies were historically implemented. A stratified analysis was performed to examine potential effect modification by individuals' demographic characteristics (sex, age, and race/ethnicity) and ambient temperature. We found that both PM2.5 and NO2 were significantly associated with MD-related ER visits primarily in redlined neighborhoods. Per 10μgm-3 increase in daily PM2.5 and per 10 ppb increase in NO2 concentration were associated with 1.04 % (95 % Confidence Interval (CI): 0.57 %, 1.50 %) and 0.44 % (95 % CI: 0.21 %, 0.67 %) increase in MD-related ER visits in redlined neighborhoods, respectively. We also found significantly greater susceptibility among younger persons (below 18 years old) and adults aged 35-64 among residents in grade C or D, but not in A or B. Furthermore, we found that positive and statistically significant associations between increases in air pollutants (PM2.5 and NO2) and MD-related ER visits exist during medium temperatures (4.90 °C to 21.11 °C), but not in low or high temperature. Exposures to both PM2.5 and NO2 were significantly associated with MD-related ER visits, but these adverse effects were disproportionately pronounced in redlined neighborhoods.
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Affiliation(s)
- Eun-Hye Yoo
- Department of Geography, State University of New York at Buffalo, Buffalo, NY, USA.
| | - John E Roberts
- Department of Psychology, State University of New York at Buffalo, Buffalo, NY, USA
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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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Jiang W, Chen H, Li H, Zhou Y, Xie M, Zhou C, Yang L. The Short-Term Effects and Burden of Ambient Air Pollution on Hospitalization for Type 2 Diabetes: Time-Stratified Case-Crossover Evidence From Sichuan, China. GEOHEALTH 2023; 7:e2023GH000846. [PMID: 38023385 PMCID: PMC10680437 DOI: 10.1029/2023gh000846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 10/22/2023] [Accepted: 11/02/2023] [Indexed: 12/01/2023]
Abstract
Type 2 diabetes mellitus (T2DM), a complicated metabolic disease, might be developed or exacerbated by air pollution, resulting in economic and health burden to patients. So far, limited studies have estimated associations between short-term exposure to air pollution and disease burden of T2DM in China. Hence, we aimed to estimate the associations and burden of ambient air pollutants (NO2, PM10, PM2.5, SO2, and CO) on hospital admissions (HAs) for T2DM using a time-stratified case-crossover design. Data on HAs for T2DM during 2017-2019 were collected from hospital electronic health records in nine cities in Sichuan Province using conditional poisson regression. Totally, 92,381 T2DM hospitalizations were recorded. There were significant short-term effects of NO2, PM10, PM2.5, SO2 and CO on HAs for T2DM. A 10 μg/m3 increment of NO2, PM10, PM2.5, SO2 and CO as linked with a 3.39% (95% CI: 2.26%, 4.54%), 0.33% (95% CI: 0.04%, 0.62%), 0.76% (95% CI: 0.35%, 1.16%), 12.68% (95% CI: 8.14%, 17.42%) and 79.00% (95% CI: 39.81%, 129.18%) increase in HAs for T2DM at lag 6. Stratified analyses modified by age, sex, and season showed old (≥65 years) and female patients linked with higher impacts. Using WHO's air quality guidelines of NO2, PM10, PM2.5, and CO as the reference, the attributable number of T2DM HAs exceeding these pollutants exposures were 786, 323, 793, and 2,127 during 2017-2019. Besides, the total medical costs of 25.83, 10.54, 30.74, and 67.78 million China Yuan were attributed to NO2, PM10, PM2.5, and CO. In conclusion, short-term exposures to air pollutants were associated with higher risks of HAs for T2DM.
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Affiliation(s)
- Wanyanhan Jiang
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Han Chen
- Sichuan Wanhao Consulting Co., LtdChengduSichuanChina
| | - Hongwei Li
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Yuelin Zhou
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Mengxue Xie
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
| | - Chengchao Zhou
- Centre for Health Management and Policy ResearchSchool of Public HealthCollege of MedicineShandong UniversityJinanChina
| | - Lian Yang
- School of Public HealthChengdu University of Traditional Chinese MedicineChengduSichuanChina
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Yan K, Wang M, Cheng Y, Zou J, Zhang Y, Hu S, Chen Y, Lv Q, Ying S. An update on the association between ambient short-term air pollution exposure and daily outpatient visits for conjunctivitis: a time-series study in Hangzhou, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:102790-102802. [PMID: 37672159 DOI: 10.1007/s11356-023-29647-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023]
Abstract
Air pollution is a major public health problem that can lead to conjunctivitis. This study aimed to explore the associations between air pollutants and outpatient visits for conjunctivitis in Hangzhou, China. This study collected data on 50,772 patients with conjunctivitis and the concentrations of six air pollutants from February 1, 2014, to August 31, 2018. A time series analysis using a generalized additive model (GAM) was conducted. We found that the risk of conjunctivitis was related to the air pollutants PM2.5, PM10, SO2, NO2, and O3, which had concentration hysteresis effects. The risk of conjunctivitis increased by 1.009 (95% confidence interval (CI): 1.003, 1.014), 1.011 (95% CI: 1.008, 1.015), 1.238 (95% CI: 1.186, 1.292), 1.028 (95% CI: 1.019, 1.038), and 1.013 (95% CI: 1.008, 1.017) for every 10 µg/m3 increase in PM2.5, PM10, SO2, NO2, and O3 concentrations, respectively. The lag effects of SO2 and NO2 were stronger than those of particulate matter. Females exposed to PM10, PM2.5, SO2, and O3 had a higher risk of conjunctivitis than males, while males exposed to NO2 had a nearly identical risk of conjunctivitis as females. People aged 19-59 were more likely to suffer from conjunctivitis. The risk of conjunctivitis caused by PM10, SO2, and O3 was highest in the transitional season, while the risk caused by NO2 was highest in the winter season. In conclusion, females and middle-aged adults were at higher risk of conjunctivitis. People were more susceptible to conjunctivitis during the transitional season. These findings highlight the importance of atmospheric pollution governance and reference for public health measures.
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Affiliation(s)
- Kaili Yan
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China
| | - Mingwei Wang
- Affiliated Hospital of Hangzhou Normal University, Zhejiang Province, Hangzhou, China
| | - Yongran Cheng
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China
| | - Jin Zou
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China
| | - Yu Zhang
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China
| | - Shuaiyue Hu
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China
| | - Yitong Chen
- Savaid Stomatology School, Hangzhou Medical College, Zhejiang Province, Hangzhou, China
| | - Qingqing Lv
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China
| | - Shibo Ying
- School of Public Health, Zhejiang Academy of Medical Sciences, Hangzhou Medical College, No.182, Tianmushan Road Zhejiang Province, Hangzhou, 310013, China.
- Institute of Occupational Diseases, Zhejiang Academy of Medical Sciences, Zhejiang Province, Hangzhou, China.
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10
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Xu J, Lan Z, Xu P, Zhang Z. The association between short-term exposure to nitrogen dioxide and hospital admission for schizophrenia: A systematic review and meta-analysis. Medicine (Baltimore) 2023; 102:e35024. [PMID: 37773873 PMCID: PMC10545286 DOI: 10.1097/md.0000000000035024] [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: 11/28/2022] [Accepted: 08/09/2023] [Indexed: 10/01/2023] Open
Abstract
BACKGROUND Ambient air pollution has been identified as a primary risk factor for mental disorders. In recent years, the relationship between exposure to ambient nitrogen dioxide (NO2) and the risk of hospital admissions (HAs) for schizophrenia has garnered increasing scientific interest, but evidence from epidemiological studies has been inconsistent. Therefore, a systematic review and meta-analysis were conducted to comprehensively identify potential correlations. METHODS A literature search in 3 international databases was conducted before December 31, 2022. Relative risk (RR) and corresponding 95% confidence intervals (CI) were calculated to evaluate the strength of the associations. Summary effect sizes were calculated using a random-effects model due to the expected heterogeneity (I2 over 50%). RESULTS A total of ten eligible studies were included in the meta-analysis, including 1,412,860 participants. The pooled analysis found that an increased risk of HAs for schizophrenia was associated with exposure to each increase of 10 μg/m3 in NO2 (RR = 1.029, 95% CI = 1.016-1.041, P < .001). However, the heterogeneity was high for the summary estimates, reducing the credibility of the evidence. In 2-pollutant models, results for NO2 increased by 0.3%, 0.2% and 2.3%, respectively, after adjusting for PM2.5, PM10 and SO2. CONCLUSIONS This study provides evidence that NO2 exposure significantly increases the risk of hospital admission for schizophrenia. Future studies are required to clarify the potential biological mechanism between schizophrenia and NO2 exposure to provide a more definitive result.
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Affiliation(s)
- Jiating Xu
- Department of General Psychiatry II, The Third Hospital of Quzhou, Quzhou City, China
| | - Zhiyong Lan
- Department of General Psychiatry II, The Third Hospital of Quzhou, Quzhou City, China
| | - Penghao Xu
- Department of Geriatric Psychiatry II, The Third Hospital of Quzhou, Quzhou City, China
| | - Zhihua Zhang
- Department of Geriatric Psychiatry II, The Third Hospital of Quzhou, Quzhou City, China
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11
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Hu Y, Zhou C, Tan C, Liu J, Huang X, Liu X, Yao C, Li D, Huang Q, Li N, Long J, Li X, Li Y, Zhou L, Cai T. The association between intermediate-term sulfur dioxide exposure and outpatient visits for Parkinson's disease: a time-series study in southwestern China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:99694-99703. [PMID: 37615914 DOI: 10.1007/s11356-023-29408-6] [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: 02/17/2023] [Accepted: 08/16/2023] [Indexed: 08/25/2023]
Abstract
Parkinson's disease (PD) is the second most common human neurodegenerative disorder, and the pathogenesis of it remains poorly understood. Limited studies have shown that both long- and short-term exposure to air pollutants may be associated with increased risk of PD while lacking evidence on the effects of intermediate-term exposure. In this study, over-dispersed Poisson generalized additive models (GAMs) were applied to explore the association between intermediate-term sulfur dioxide (SO2) exposure and outpatient visits for PD in Chongqing, China, and further stratified analyses were performed by age and gender. A total of 39,984 PD cases from January 1, 2014, to December 31, 2019 (2191 days) were included. The association of intermediate-term SO2 exposure with outpatient visits for PD was statistically significant: per 1 μg/m3 increase of SO2 corresponded to 2.34% (95% CI: 0.88%, 3.80%) elevation in monthly PD outpatient visits at lag 0 (the concurrent month). Stratified analyses showed that the associations between SO2 and PD outpatient visits were stronger in younger (≤ 60 years) and female patients. In conclusion, intermediate-term SO2 exposure can be associated with an increased risk of PD outpatient visits. Our results highlight the importance of recognizing the role of intermediate-term SO2 exposure in the development of PD. In addition to focusing on the effects of long-term or short-term air pollutants, it is necessary to pay more attention to the health effects of intermediate-term exposure time windows of air pollutants, which will facilitate policy formulation and public health interventions for health risks.
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Affiliation(s)
- Yuegu Hu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Chunbei Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
- Chongqing Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Chunlei Tan
- Department of Quality Management, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Jianghong Liu
- Department of Family and Community Health, University of Pennsylvania School of Nursing, Philadelphia, PA, 19104, USA
| | - Xiaolong Huang
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Xiaoling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Chunyan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Dawei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Qingsong Huang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Na Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Jinyun Long
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Xiukuan Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Yafei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China
| | - Laixin Zhou
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Tongjian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Chongqing, 400038, Shapingba, China.
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12
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Zhang T, Huang R, Yang M, Lin G, Ma X, Wang X, Huang Q. Perceptions of the health risk from hot days and the cooling effect of urban green spaces: a case study in Xi'an, China. Front Public Health 2023; 11:1211164. [PMID: 37674680 PMCID: PMC10477602 DOI: 10.3389/fpubh.2023.1211164] [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: 04/24/2023] [Accepted: 08/08/2023] [Indexed: 09/08/2023] Open
Abstract
Background Hot days are one of the typical threats to human health and sustainable cities. The exploration of residents' perceptions of thermal environment and its mitigation measures will support the health risk prevention. Methods A survey with a combination of closed-ended and open-ended questions was conducted in July 2021 among 13 urban parks in Xi'an City, China. With the help of ANOVA and ordinal logistic regression, this study investigated the influencing factors both on residents' health risk perception of hot days and their perception of the effect of urban ecological landscape on reducing the thermal risk. The relationship between health risk perception and residents' needs of urban ecological construction was also explored. Results According to 325 valid questionnaires, the male-female ratio of respondents was found to be 1:0.87, young people aged 18-29 (26.46%), the retirees (27.08%) and the ones with undergraduate education (33.23%) were, relatively, the largest groups. The results show that 92.31% of the respondents believed that their daily lives were under the influence of hot days. Housing types, occupation, cooling equipment at work, and outdoor working hours all had a significant impact on their high temperature perceptions. The proportion of respondents who were under a huge health risk and sought medical treatment due to hot days was 30.16% and 44.92%, respectively. Women were 18.52 and 2.33 times more likely to suffer health threats and experience discomforts than men. Furthermore, 73.23% of the respondents believed that the urban ecological landscapes in Xi'an had an enhanced cooling effect in recent years. Compared with the morphological characteristics, residents' recognition of the restriction of landscape's area on its cooling effect was higher, and the residence duration showed a significant influence. Conclusion The cooling effect of green spaces and water effectively resisted urban thermal threats, and residents' needs of the urban ecological landscapes was associated with their health risk perceptions of hot days. In the future, it is necessary to promote the early warning of hot days, meanwhile, the optimization of landscape patterns of green infrastructures should be implemented in urban planning for the purposes of residents' health risk prevention.
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Affiliation(s)
- Tian Zhang
- Northwest Land and Resource Research Center, Shaanxi Normal University, Xi’an, China
| | - Rong Huang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Mei Yang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Guohua Lin
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Xiaoyan Ma
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Xuan Wang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
| | - Qian Huang
- School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
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13
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Kumar P, Singh AB, Arora T, Singh S, Singh R. Critical review on emerging health effects associated with the indoor air quality and its sustainable management. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 872:162163. [PMID: 36781134 DOI: 10.1016/j.scitotenv.2023.162163] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Indoor air quality (IAQ) is one of the fundamental elements affecting people's health and well-being. Currently, there is a lack of awareness among people about the quantification, identification, and possible health effects of IAQ. Airborne pollutants such as volatile organic compounds (VOCs), particulate matter (PM), sulfur dioxide (SO2), carbon monoxide (CO), nitrous oxide (NO), polycyclic aromatic hydrocarbons (PAHs) microbial spores, pollen, allergens, etc. primarily contribute to IAQ deterioration. This review discusses the sources of major indoor air pollutants, molecular toxicity mechanisms, and their effects on cardiovascular, ocular, neurological, women, and foetal health. Additionally, contemporary strategies and sustainable methods for regulating and reducing pollutant concentrations are emphasized, and current initiatives to address and enhance IAQ are explored, along with their unique advantages and potentials. Due to their longer exposure times and particular physical characteristics, women and children are more at risk for poor indoor air quality. By triggering many toxicity mechanisms, including oxidative stress, DNA methylation, epigenetic modifications, and gene activation, indoor air pollution can cause a range of health issues. Low birth weight, acute lower respiratory tract infections, Sick building syndromes (SBS), and early death are more prevalent in exposed residents. On the other hand, the main causes of incapacity and early mortality are lung cancer, chronic obstructive pulmonary disease, and cardiovascular disorders. It's crucial to acknowledge anticipated research needs and implemented efficient interventions and policies to lower health hazards.
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Affiliation(s)
- Pradeep Kumar
- Department of Environmental Studies, Satyawati College, University of Delhi, Delhi 52, India
| | - A B Singh
- Institute of Genomics and Integrative Biology (IGIB), Mall Road Campus, Delhi 07, India
| | - Taruna Arora
- Division of Reproductive Biology, Maternal and Child Health, Indian Council of Medical Research, Ansari Nagar, New Delhi 110029, India
| | - Sevaram Singh
- Translational Health Science and Technology Institute, NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, India; Jawaharlal Nehru University, New Mehrauli Road, New Delhi 110067, India
| | - Rajeev Singh
- Department of Environmental Studies, Satyawati College, University of Delhi, Delhi 52, India; Department of Environmental Science, Jamia Millia Islamia (A Central University), New Delhi 110025, India.
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14
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Li YZ, Huang SH, Shi S, Chen WX, Wei YF, Zou BJ, Yao W, Zhou L, Liu FH, Gao S, Yan S, Qin X, Zhao YH, Chen RJ, Gong TT, Wu QJ. Association of long-term particulate matter exposure with all-cause mortality among patients with ovarian cancer: A prospective cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 884:163748. [PMID: 37120017 DOI: 10.1016/j.scitotenv.2023.163748] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/19/2023] [Accepted: 04/22/2023] [Indexed: 05/03/2023]
Abstract
BACKGROUND Evidence of the association between particles with a diameter of 2.5 μm or less (PM2.5) in long term and ovarian cancer (OC) mortality is limited. METHODS This prospective cohort study analyzed data collected between 2015 and 2020 from 610 newly diagnosed OC patients, aged 18-79 years. The residential average PM2.5 concentrations 10 years before the date of OC diagnosis were assessed by random forest models at a 1 km × 1 km resolution. Cox proportional hazard models fully adjusted for the covariates (including age at diagnosis, education, physical activity, kitchen ventilation, FIGO stage, and comorbidities) and distributed lag non-linear models were used to estimate the hazard ratios (HRs) and 95 % confidence intervals (CIs) of PM2.5 and all-cause mortality of OC. RESULTS During a median follow-up of 37.6 months (interquartile: 24.8-50.5 months), 118 (19.34 %) deaths were confirmed among 610 OC patients. One-year PM2.5 exposure levels before OC diagnosis was significantly associated with an increase in all-cause mortality among OC patients (single-pollutant model: HR = 1.22, 95 % CI: 1.02-1.46; multi-pollutant models: HR = 1.38, 95 % CI: 1.10-1.72). Furthermore, during 1 to 10 years prior to diagnosis, the lag-specific effect of long-term PM2.5 exposure on the all-cause mortality of OC had a risk increase for lag 1-6 years, and the exposure-response relationship was linear. Of note, significant interactions between several immunological indicators as well as solid fuel use for cooking and ambient PM2.5 concentrations were observed. CONCLUSION Higher ambient PM2.5 concentrations were associated with an increased risk of all-cause mortality among OC patients, and there was a lag effect in long-term PM2.5 exposure.
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Affiliation(s)
- Yi-Zi Li
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shu-Hong Huang
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Su Shi
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Wen-Xiao Chen
- Department of Sports Medicine and Joint Surgery, The People's Hospital of Liaoning Province, Shenyang, China
| | - Yi-Fan Wei
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Bing-Jie Zou
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Wei Yao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lu Zhou
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Fang-Hua Liu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Song Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Shi Yan
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Xue Qin
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Yu-Hong Zhao
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China
| | - Ren-Jie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Ting-Ting Gong
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
| | - Qi-Jun Wu
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China; Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Precision Medical Research on Major Chronic Disease, Shengjing Hospital of China Medical University, Shenyang, China; Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China; Key Laboratory of Reproductive and Genetic Medicine (China Medical University), National Health Commission, Shenyang, China.
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15
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Liu H, Zhao H, Huang J, He M. Air pollution associated with hospital visits for mental and behavioral disorders in Northeast China. FRONTIERS IN EPIDEMIOLOGY 2023; 3:1090313. [PMID: 38455902 PMCID: PMC10910900 DOI: 10.3389/fepid.2023.1090313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 03/10/2023] [Indexed: 03/09/2024]
Abstract
Background Related studies have found that air pollution is an important factor affecting mental and behavioral disorders. Thus, we performed this time-series study to evaluate the relationship between short-term exposure to ambient air pollutants and visits to hospital by patients with mental and behavioral disorders in northeastern China. Methods We used quasi-Poisson regression models and generalized additive models to probe the links between air pollution and mental and behavioral disorders. The possible influences were also explored stratified by season, age and gender. Results We found that sulfur dioxide (SO2) had a cumulative effect on mental and behavioral disorders at lag04-lag07 and had the greatest effect at lag07 [Relative risk (RR) = 1.068, 95%CI = 1.021-1.117]. Particulate matter of size 2.5 μm (PM2.5) and SO2 had a cumulative effect on depression and both had the largest effect at lag07 (RR = 1.021, 95%CI = 1.002-1.041; RR = 1.103, 95%CI = 1.032-1.178); SO2 also had a cumulative effect on anxiety disorders, with the largest effect at lag06 (RR = 1.058, 95%CI = 1.009-1.110). In the stratified analysis, people are more susceptible in the cold season compared to the warm season and females and the 18-60-year age group are more sensitive to air pollutants. It is suggested to strengthen management and preventive measures to decrease air pollution exposure. Conclusion This study found an association between increased concentrations of air pollutants and increased outpatient visits for mental and behavioral disorders. We recommend that preventive and protective measures should be strengthened in an effort to reduce exposure to air pollution in order to maintain physical and mental health.
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Affiliation(s)
- Huo Liu
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
| | - Hang Zhao
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
| | - Jinling Huang
- Department of Hospital Management Office, Shengjing Hospital of China Medical University, Shenyang, China
- Department of Cardiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Miao He
- Liaoning Key Laboratory of Environmental Health Damage Research and Assessment, Department of Environmental Health, School of Public Health, China Medical University, Shenyang, China
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16
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Wu X, Shen YS, Cui S. Global Trends in Green Space and Senior Mental Health Studies: Bibliometric Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:1316. [PMID: 36674070 PMCID: PMC9858913 DOI: 10.3390/ijerph20021316] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 01/08/2023] [Accepted: 01/10/2023] [Indexed: 06/17/2023]
Abstract
The Sustainable Development Goals and the World Health Organization have prioritized senior mental health as an important goal. Senior mental health is a critical issue within the global public health sphere. Notably, green spaces are a useful alternative for improving senior mental health. Many studies have focused on green space and senior mental health, especially on their connection and relationship. However, this research topic lacks a comprehensive and systematic review. Owing to the lack of critical reviews, this study clarified the trend, progress, status, and focus of studies on green spaces and senior mental health using bibliometric analysis of literature within the Web of Science database. The literature analysis within this study specifically focused on the following, including the country/region contribution analysis, institution contribution analysis, keyword analysis, and highly productive journal analysis. Furthermore, this study systematically recorded the content of green space and senior mental health, identified the gap that exists, and provided future frontier directions or issues for research. These contribute toward comprehending the progress and content of this research topic and further provide a guide, reference, and inspiration for possible future research.
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Affiliation(s)
- Xialu Wu
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Xiamen Key Lab of Urban Metabolism, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yu-Sheng Shen
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Xiamen Key Lab of Urban Metabolism, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shenghui Cui
- Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- Xiamen Key Lab of Urban Metabolism, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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17
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Wang C, Qi Y, Chen Z. Explainable Gated Recurrent Unit to explore the effect of co-exposure to multiple air pollutants and meteorological conditions on mental health outcomes. ENVIRONMENT INTERNATIONAL 2023; 171:107689. [PMID: 36508748 DOI: 10.1016/j.envint.2022.107689] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 11/03/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m3 of NO2, and 14.1 µg/m3 of SO2 at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM2.5, and O3 interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.
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Affiliation(s)
- Ce Wang
- School of Energy and Environment, Southeast University, Nanjing 210096, PR China; State Key Laboratory of Environmental Medicine Engineering, Ministry of Education, Southeast University, Nanjing 210096, PR China.
| | - Yi Qi
- School of Architecture and Urban Planning, Nanjing University, No. 22 Hankoulu Road, Nanjing 210093, PR China
| | - Zhenhua Chen
- Department of Information, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No. 264 Guangzhou Road, Nanjing 210029, RP China.
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18
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Song R, Liu L, Wei N, Li X, Liu J, Yuan J, Yan S, Sun X, Mei L, Liang Y, Li Y, Jin X, Wu Y, Pan R, Yi W, Song J, He Y, Tang C, Liu X, Cheng J, Su H. Short-term exposure to air pollution is an emerging but neglected risk factor for schizophrenia: A systematic review and meta-analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 854:158823. [PMID: 36116638 DOI: 10.1016/j.scitotenv.2022.158823] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/03/2022] [Accepted: 09/13/2022] [Indexed: 06/15/2023]
Abstract
OBJECTIVE This meta-analysis aimed to explore the association between short-term exposure to air pollution and schizophrenia (SCZ)1, and investigate the susceptible population and the lag characteristics of different pollutants. METHODS A systematic review and meta-analysis was conducted by searching PubMed, Cochrane, Web of Sciences, and CNKI for relevant literature published up to 28 Feb 2022. Meta-analysis was performed separately to investigate the association of ambient particulates (diameter ≤ 2.5 μm (PM2.5)2, 2.5 μm < diameter < 10 μm (PMC)3, ≤10μm (PM10)4) and gaseous pollutants (nitrogen dioxide (NO2)5, sulfur dioxide (SO2)6, carbon monoxide (CO)7) with SCZ. Relative risk (RR)8 per 10 μg/m3 increase in air pollutants concentration was used as the effect estimate. Subgroup analyses were conducted by age, gender, country, median pollutant concentration, and median temperature. RESULTS We identified 17 articles mainly conducted in Asia, of which 13 were included in the meta-analysis. Increased risk of SCZ was associated with short-term exposure to PM2.5 (RR: 1.0050, 95 % confidence interval (CI)9: 1.0017, 1.0083), PMC (1.0117, 1.0023, 1.0211), PM10 (1.0047, 1.0025, 1.0070), NO2 (1.0275, 1.0132, 1.0420), and SO2 (1.0288, 1.0146, 1.0432) exposure. Subgroup analyses showed that females may be more susceptible to SO2 and NO2, and the young seem to be more sensitive to PM2.5 and PM10. Gaseous pollutants presented the immediate risk, and particulates showed the delayed risk. CONCLUSIONS The present meta-analysis suggests that short-term exposure to PM2.5, PMC, PM10, SO2, and NO2 exposure may be associated with an elevated risk of SCZ.
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Affiliation(s)
- Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Shuangshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xiaoni Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Lu Mei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yunfeng Liang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yuxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yudong Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China.
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Fu Y, Zhang W, Li Y, Li H, Deng F, Ma Q. Association and interaction of O 3 and NO 2 with emergency room visits for respiratory diseases in Beijing, China: a time-series study. BMC Public Health 2022; 22:2265. [PMID: 36464692 PMCID: PMC9721066 DOI: 10.1186/s12889-022-14473-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Accepted: 10/26/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Ozone (O3) and nitrogen dioxide (NO2) are the two main gaseous pollutants in the atmosphere that act as oxidants. Their short-term effects and interaction on emergency room visits (ERVs) for respiratory diseases remain unclear. METHODS We conducted a time-series study based on 144,326 ERVs for respiratory diseases of Peking University Third Hospital from 2014 to 2019 in Beijing, China. Generalized additive models with quasi-Poisson regression were performed to analyze the association of O3, NO2 and their composite indicators (Ox and Oxwt) with ERVs for respiratory diseases. An interaction model was further performed to evaluate the interaction between O3 and NO2. RESULTS Exposure to O3, NO2, Ox and Oxwt was positively associated with ERVs for total respiratory diseases and acute upper respiratory infection (AURI). For instance, a 10 μg/m3 increase in O3 and NO2 were associated with 0.93% (95%CI: 0.05%, 1.81%) and 5.87% (95%CI: 3.92%, 7.85%) increase in AURI at lag0-5 days, respectively. Significant linear exposure-response relationships were observed in Ox and Oxwt over the entire concentration range. In stratification analysis, stronger associations were observed in the group aged < 18 years for both O3 and NO2, in the warm season for O3, but in the cold season for NO2. In interaction analysis, the effect of O3 on total respiratory emergency room visits and AURI visits was the strongest at high levels (> 75% quantile) of NO2 in the < 18 years group. CONCLUSIONS Short-term exposure to O3 and NO2 was positively associated with ERVs for respiratory diseases, particularly in younger people (< 18 years). This study for the first time demonstrated the synergistic effect of O3 and NO2 on respiratory ERVs, and Ox and Oxwt may be potential proxies.
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Affiliation(s)
- Yuanwei Fu
- grid.411642.40000 0004 0605 3760Emergency Department, Peking University Third Hospital, Beijing, 100191 China
| | - Wenlou Zhang
- grid.11135.370000 0001 2256 9319Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191 China
| | - Yan Li
- grid.411642.40000 0004 0605 3760Emergency Department, Peking University Third Hospital, Beijing, 100191 China
| | - Hongyu Li
- grid.11135.370000 0001 2256 9319Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191 China
| | - Furong Deng
- grid.11135.370000 0001 2256 9319Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, 100191 China
| | - Qingbian Ma
- grid.411642.40000 0004 0605 3760Emergency Department, Peking University Third Hospital, Beijing, 100191 China
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20
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Rantala MJ, Luoto S, Borráz-León JI, Krams I. Schizophrenia: the new etiological synthesis. Neurosci Biobehav Rev 2022; 142:104894. [PMID: 36181926 DOI: 10.1016/j.neubiorev.2022.104894] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 08/25/2022] [Accepted: 09/25/2022] [Indexed: 10/31/2022]
Abstract
Schizophrenia has been an evolutionary paradox: it has high heritability, but it is associated with decreased reproductive success. The causal genetic variants underlying schizophrenia are thought to be under weak negative selection. To unravel this paradox, many evolutionary explanations have been suggested for schizophrenia. We critically discuss the constellation of evolutionary hypotheses for schizophrenia, highlighting the lack of empirical support for most existing evolutionary hypotheses-with the exception of the relatively well supported evolutionary mismatch hypothesis. It posits that evolutionarily novel features of contemporary environments, such as chronic stress, low-grade systemic inflammation, and gut dysbiosis, increase susceptibility to schizophrenia. Environmental factors such as microbial infections (e.g., Toxoplasma gondii) can better predict the onset of schizophrenia than polygenic risk scores. However, researchers have not been able to explain why only a small minority of infected people develop schizophrenia. The new etiological synthesis of schizophrenia indicates that an interaction between host genotype, microbe infection, and chronic stress causes schizophrenia, with neuroinflammation and gut dysbiosis mediating this etiological pathway. Instead of just alleviating symptoms with drugs, the parasite x genotype x stress model emphasizes that schizophrenia treatment should focus on detecting and treating possible underlying microbial infection(s), neuroinflammation, gut dysbiosis, and chronic stress.
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Affiliation(s)
- Markus J Rantala
- Department of Biology, University of Turku, FIN-20014 Turku, Finland.
| | - Severi Luoto
- School of Population Health, University of Auckland, 1023 Auckland, New Zealand
| | | | - Indrikis Krams
- Institute of Ecology and Earth Sciences, University of Tartu, 51014 Tartu, Estonia; Department of Zoology and Animal Ecology, Faculty of Biology, University of Latvia, 1004, Rīga, Latvia
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21
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He Y, Zhang X, Gao J, Gao H, Cheng J, Xu Z, Pan R, Yi W, Song J, Liu X, Tang C, Song S, Su H. The impact of cold spells on schizophrenia admissions and the synergistic effect with the air quality index. ENVIRONMENTAL RESEARCH 2022; 212:113243. [PMID: 35398316 DOI: 10.1016/j.envres.2022.113243] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 03/20/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVES Under current global climate conditions, there are insufficient studies on the health influences of cold spells, especially on mental health. This study aimed to examine the effect of cold spells on schizophrenia admissions and to analyze the potential interaction effect with the air quality index (AQI). METHODS Daily data on schizophrenia admissions and climatic variables in Hefei were collected from 2013 to 2019. Based on 20 definitions, the impacts of cold spells were quantified separately to find the most appropriate definition for the region, and meta-regression was used to explore the different effect sizes of the different days in a cold spell event. In addition, the potential interaction effect was tested by introducing a categorical variable, CSH, reflecting the cold spell and AQI level. RESULTS The cold spell defined by temperature below the 6th centile while lasting for at least three days produced the optimum model fit performance. In general, the risk of schizophrenia admissions increased on cold spell days. The largest single-day effect occurred on the 12th day with RR = 1.081 (95% CI: 1.044, 1.118). In a single cold spell event, the effect of the 3rd and subsequent days of a cold spell (RR = 1.082, 95% CI: 1.036, 1.130) was higher than that on the 2nd day (RR = 1.054, 95% CI: 1.024, 1.085). Similarly, the effect of the 2nd day was also higher than that of the 1st day (RR = 1.027, 95% CI: 1.012, 1.042). We found a synergistic effect between cold spells and high AQI in the male group, and the relative excess risk due to interaction (RERI) was 0.018 (95% CI: 0.005-0.030). CONCLUSIONS This study suggested that the impacts of cold spells should be considered based on the definition of the most appropriate for the region when formulating targeted measures of schizophrenia. The discovery of the synergistic effect was referred to help the selection of the timing of precautions for susceptible people.
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Affiliation(s)
- Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xulai Zhang
- Anhui Mental Health Center, Hefei, Anhui, China
| | - Jiaojiao Gao
- Pudong New Area Center for Disease Control and Prevention, Shanghai, China
| | - Hua Gao
- Anhui Mental Health Center, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhiwei Xu
- School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Shasha Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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22
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Zhou YM, An SJ, Cao Y, Xu C, Liu XL, Yao CY, Li X, Wu N, Li CY, Wu L, Li YF, Ji AL, Cai TJ. Elder people can be more susceptible to the association between short-term ambient air pollution and sleep disorder outpatient visits: a time-series study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:64902-64913. [PMID: 35474431 DOI: 10.1007/s11356-022-20242-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 04/09/2022] [Indexed: 06/14/2023]
Abstract
Sleep disorders attract increasing concerns. However, the evidence of the association between ambient air pollution and sleep disorders is limited. Therefore, our aim was to determine the association between short-term air pollution exposure and outpatient visits for sleep disorders in Xi'an, the largest city in Northwest China. Baseline outpatient data of daily sleep disorders between 2011 and 2013 were collected. Quasi-Poisson distribution was applied by adjusting the day of the week and weather conditions. A total of 49,282 sleep disorder outpatient visits were recorded. The most significant association between air pollutants and outpatient visits was observed on concurrent day: per 10 μg/m3 increase of NO2, SO2, and PM10 at lag 0 corresponded to increased outpatient sleep disorder visits at 0.22% (95% CI: 0.03%, 0.42%), 1.53% (95% CI: 0.53, 2.53%), and 2.57% (95% CI: 1.33%, 3.82%), respectively. As for gender-specific analysis, there was no statistically significant difference between males and females. The result of season-specific analysis showed no statistically significant difference between warm seasons and cool seasons, either. As for age-specific analysis, obvious associations were observed in 20-40 age group (NO2) and > 40 age group (PM10 and SO2), while no evident association was found for the young age group (< 20 years old). Conclusively, short-term exposure to air pollutants, especially gaseous air pollutants, might increase the risk of sleep disorders, and such association appears to be more obvious in elder people. We provide novel data that there may be age differences in the relationship between short-term air pollution exposure and sleep disorders.
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Affiliation(s)
- Yu-Meng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Shu-Jie An
- Health Management Center, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710032, China
| | - Yi Cao
- Department of Health Economics Management, Xijing Hospital, Air Force Medical University, Xi'an, 710032, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710032, China
| | - Xiao-Ling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Chun-Yan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Xiang Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
- Department of Plastic & Cosmetic Surgery, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, 400042, People's Republic of China
| | - Na Wu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Cheng-Ying Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Long Wu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China
| | - Ai-Ling Ji
- Department of Preventive Medicine, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, 400038, China.
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23
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Li X, Zhou LX, Yang LL, Huang XL, Wang N, Hu YG, Tang EJ, Xiao H, Zhou YM, Li YF, Lu YG, Cai TJ. The relationship between short-term PM 2.5 exposure and outpatient visits for acne vulgaris in Chongqing, China: a time-series study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:61502-61511. [PMID: 35442002 DOI: 10.1007/s11356-022-20236-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 04/09/2022] [Indexed: 06/14/2023]
Abstract
Many researches have reported the air pollution impacts, either long term or short term, on inflammatory skin diseases, but there are few studies on the relation between PM2.5 and acne vulgaris. To determine the correlation between short-term PM2.5 exposure and acne outpatient visits, data for 120,842 acne vulgaris outpatient visits between December 2013 and December 2019 were obtained from three large hospitals in Chongqing, China. Both single-pollutant models and two-pollutant models were established to explore the relationship between PM2.5 exposure and acne outpatient visits. The stratified analyses were conducted through two-sample z-tests to investigate the possible gender (male or female) and age (< 25 years or ≥ 25 years) differences in PM2.5 effects. The results demonstrated positive correlations between PM2.5 concentrations and acne outpatient visits. A 10 μg/m3 increase in PM2.5 concentration was associated with a 1.71% (95% CI: 1.06-2.36%) increase in acne outpatient visits at lag 0-7 day. Stratified analyses showed that PM2.5 effects were greater in individuals aged ≥ 25 years than those aged < 25 years, but no gender difference was found. In conclusion, short-term PM2.5 exposure was positively associated with the risk of acne outpatient visits, especially for people ≥ 25 years old.
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Affiliation(s)
- Xiang Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
- Department of Plastic & Cosmetic Surgery, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, 400042, China
| | - Lai-Xin Zhou
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Li-Li Yang
- Department of Information, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, China
| | - Xiao-Long Huang
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Nan Wang
- Medical Department, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, 400037, China
| | - Yue-Gu Hu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - En-Jie Tang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Hua Xiao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yu-Meng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yuan-Gang Lu
- Department of Plastic & Cosmetic Surgery, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, 400042, China
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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Ji Y, Liu B, Song J, Pan R, Cheng J, Wang H, Su H. Short-term effects and economic burden assessment of ambient air pollution on hospitalizations for schizophrenia. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:45449-45460. [PMID: 35149942 DOI: 10.1007/s11356-022-19026-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 01/29/2022] [Indexed: 06/14/2023]
Abstract
The evidence on the health and economic impacts of air pollution with schizophrenia is scarce, especially in developing countries. In this study, we aimed to systemically examine the short-term effects of PM2.5 (particulate matter ≤ 2.5 μm in diameter), PM10 (≤ 10 μm in diameter), NO2 (nitrogen dioxide), SO2 (sulfur dioxide), CO (carbon monoxide), and O3 (ozone) on hospital admissions for schizophrenia in a Chinese coastal city (Qingdao) and to further assess the corresponding attributable risk and economic burden. A generalized additive model (GAM) was applied to model the impact of air pollution on schizophrenia, and the corresponding economic burden including the direct costs (medical expenses) and indirect costs (productivity loss). Stratified analyses were also performed by age, gender, and season (warm or cold). Our results showed that for a 10 μg/m3 increase in the concentrations of PM2.5, PM10, SO2, and CO at lag5, the corresponding relative risks (RRs) were 1.0160 (95% CI: 1.0038-1.0282), 1.0097 (1.0018-1.0177), 1.0738 (1.0222-1.01280), and 1.0013 (1.0001-1.0026), respectively. However, no significant effect of NO2 or O3 on schizophrenia admissions was found. The stratified analysis indicated that females and younger individuals (< 45 years old) appeared to be more vulnerable, but no significant difference was found between seasons. Furthermore, 12.41% of schizophrenia hospitalizations were attributable to exposure to air pollution exceeding the World Health Organization (WHO) air quality standard, with a total economic burden of 89.67 million RMB during the study period. At the individual level, excessive air pollution exposure resulted in an economic burden of 8232.08 RMB per hospitalization. Our study found that short-term exposure to air pollutants increased the risk of hospital admissions for schizophrenia and resulted in a substantial economic burden. Considerable health benefits can be achieved by further reducing air pollution.
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Affiliation(s)
- Yanhu Ji
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Bin Liu
- Qingdao Mental Health Center, 299 Nanjing Road, Qingdao, Shandong, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Heng Wang
- Department of Hospital Management, The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui, China.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China.
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Saxena A, Dodell-Feder D. Explaining the Association Between Urbanicity and Psychotic-Like Experiences in Pre-Adolescence: The Indirect Effect of Urban Exposures. Front Psychiatry 2022; 13:831089. [PMID: 35360125 PMCID: PMC8962621 DOI: 10.3389/fpsyt.2022.831089] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/27/2022] [Indexed: 11/30/2022] Open
Abstract
Urban living is a growing worldwide phenomenon with more than two-thirds of people expected to live in cities by 2050. Although there are many benefits to living in an urban environment, urbanicity has also been associated with deleterious health outcomes, including increased risk for psychotic outcomes particularly when the urban exposure occurs in pre-adolescence. However, the mechanisms underlying this association is unclear. Here, we utilize one-year follow-up data from a large (N=7,979), nationwide study of pre-adolescence in the United States to clarify why urbanicity (i.e., census-tract population density) might impact psychotic-like experiences (PLE) by looking at the indirect effect of eight candidate urbanicity-related physical (e.g., pollution) and social (e.g., poverty) exposures. Consistent with other work, we found that of the evaluated exposures related to urbanicity, several were also related to increased number of PLE: PM2.5, proximity to roads, census-level homes at-risk for exposure to lead paint, census-level poverty, and census-level income-disparity. These same urban-related exposures were also related to the persistence of PLE after 1 year, but not new onset of PLE. Mediation analysis revealed that a substantial proportion the urbanicity-PLE association (number and persistence) could be explained by PM2.5 (23-44%), families in poverty (68-93%), and income disparity (67-80%). Together, these findings suggest that specific urban-related exposures contribute to the existence and maintenance, but not onset of PLE, which might help to explain why those in urban environments are disproportionately at-risk for psychosis and point toward areas for public health intervention.
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Affiliation(s)
- Abhishek Saxena
- Department of Psychology, University of Rochester, Rochester, NY, United States
| | - David Dodell-Feder
- Department of Psychology, University of Rochester, Rochester, NY, United States
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
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Qiu H, Wang L, Luo L, Shen M. Gaseous air pollutants and hospitalizations for mental disorders in 17 Chinese cities: Association, morbidity burden and economic costs. ENVIRONMENTAL RESEARCH 2022; 204:111928. [PMID: 34437848 DOI: 10.1016/j.envres.2021.111928] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 08/06/2021] [Accepted: 08/19/2021] [Indexed: 06/13/2023]
Abstract
The short-term morbidity effects of gaseous air pollutants on mental disorders (MDs), and the corresponding morbidity and economic burdens have not been well studied. We aimed to explore the associations of ambient sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3) and carbon monoxide (CO) with MDs hospitalizations in 17 Chinese cities during 2015-2018, and estimate the attributable risk and economic costs of MDs hospitalizations associated with gaseous pollutants. City-specific relationships between gaseous pollutants and MDs hospitalizations were evaluated using over-dispersed generalized additive models, then combined to obtain the pooled effect. Concentration-response (C-R) curves of gaseous pollutants with MDs from each city were pooled to allow regional estimates to be derived. The morbidity and economic burdens of MDs hospitalizations attributable to gaseous pollutants were further assessed. A total of 171,939 MDs hospitalizations were included. We observed insignificant association of O3 with MDs. An interquartile range increase in SO2 at lag0 (9.1 μg/m³), NO2 at lag0 (16.7 μg/m³) and CO at lag2 (0.4 mg/m³) corresponded to a 3.02% (95%CI: 0.72%, 5.38%), 5.03% (95%CI: 1.84%, 8.32%) and 2.18% (95%CI: 0.40%, 4.00%) increase in daily MDs hospitalizations, respectively. These effects were modified by sex, season and cause-specific MDs. The C-R curves of SO2 and NO2 with MDs indicated nonlinearity and the slops were steeper at lower concentrations. Overall, using current standards as reference concentrations, 0.27% (95%CI: 0.07%, 0.48%) and 0.06% (95%CI: 0.02%, 0.10%) of MDs hospitalizations could be attributable to extra SO2 and NO2 exposures, and the corresponding economic costs accounted for 0.34% (95%CI: 0.08%, 0.60%) and 0.07% (95%CI: 0.03%, 0.11%) of hospitalization expenses, respectively. Moreover, using threshold values detected from C-R curves as reference concentrations, the above mentioned morbidity and economic burdens increased a lot. These findings suggest more strict emission control regulations are needed to protect mental health from gaseous pollutants.
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Affiliation(s)
- Hang Qiu
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China; Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China.
| | - Liya Wang
- Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Luo
- Business School, Sichuan University, Chengdu, China
| | - Minghui Shen
- Health Information Center of Sichuan Province, Chengdu, China
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27
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Li X, Cao Y, An SJ, Xiang Y, Huang HX, Xu B, Zhang Y, Li YF, Lu YG, Cai TJ. The association between short-term ambient air pollution and acne vulgaris outpatient visits: a hospital-based time-series analysis in Xi'an. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:14624-14633. [PMID: 34617215 DOI: 10.1007/s11356-021-16607-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 09/14/2021] [Indexed: 06/13/2023]
Abstract
Recent studies have suggested that exposure to ambient airborne pollutants is associated with inflammatory skin diseases, but the epidemiological evidence regarding the association between air pollution and acne vulgaris is limited. To address that, a hospital-based time-series analysis was conducted in Xi'an, a metropolitan in northwest China. A total of 71,625 outpatient visits for acne from 2010 to 2013 were identified. The mean daily concentrations of PM10, SO2, and NO2 were 142.6 μg/m3, 44.7 μg/m3, and 48.5 μg/m3, and all were higher than WHO air quality guidelines. A generalized additive model was used to analyze the relationship between short-term ambient air pollution exposure and outpatient visits for acne. The gender- and age-specific analyses were conducted as well. The results showed that the increase of SO2 and NO2 concentrations corresponded to a significant rise in the number of outpatient visits for acne at lag 0 in both single-lag and cumulative exposure models. Both SO2 and NO2 were positively associated with acne outpatient visits for both males and females. In age-specific analyses, the effect estimate of PM10 was only significant for adults over 30 years old; SO2 was significantly associated with acne visits in children and adolescents (<21 years) and young adults (21-30 years); and NO2 was significantly associated with acne visits in all age subgroups. In conclusion, short-term exposure to ambient air pollutants (PM10, SO2, or NO2) with the average levels above WHO limits was associated with increased risk of outpatient visits for both teenage acne and adult acne. Moreover, the effects of air pollutants may vary with age.
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Affiliation(s)
- Xiang Li
- Department of Plastic & Cosmetic Surgery, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, People's Republic of China
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, People's Republic of China, 400038
| | - Yi Cao
- Department of Health Economics Management, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, People's Republic of China
| | - Shu-Jie An
- Medical Department, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, People's Republic of China
| | - Ying Xiang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, People's Republic of China, 400038
| | - He-Xiang Huang
- Department of Social Medicine and Health Service Management, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, People's Republic of China
| | - Bin Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, People's Republic of China, 400038
| | - Yao Zhang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, People's Republic of China, 400038
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, People's Republic of China, 400038
| | - Yuan-Gang Lu
- Department of Plastic & Cosmetic Surgery, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, People's Republic of China.
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), 30 Gaotanyan Main Street, Shapingba, Chongqing, People's Republic of China, 400038.
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28
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Tang C, Ji Y, Li Q, Yao Z, Cheng J, He Y, Liu X, Pan R, Wei Q, Yi W, Su H. Effects of different heat exposure patterns (accumulated and transient) and schizophrenia hospitalizations: a time-series analysis on hourly temperature basis. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:69160-69170. [PMID: 34286435 DOI: 10.1007/s11356-021-15371-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 07/06/2021] [Indexed: 06/13/2023]
Abstract
Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.
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Affiliation(s)
- Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Yifu Ji
- Anhui Mental Health Center, Hefei, 230032, Anhui, China
| | - Qingru Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Zhenhai Yao
- Anhui Public Meteorological Service Center, Hefei, 230011, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Xiangguo Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Qiannan Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, 230032, Anhui, China.
- Anhui Provincial Laboratory of Inflammatory and Immune Diseases, Hefei, 230032, Anhui, China.
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29
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Wu C, Yan Y, Chen X, Gong J, Guo Y, Zhao Y, Yang N, Dai J, Zhang F, Xiang H. Short-term exposure to ambient air pollution and type 2 diabetes mortality: A population-based time series study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 289:117886. [PMID: 34371265 DOI: 10.1016/j.envpol.2021.117886] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/27/2021] [Accepted: 07/30/2021] [Indexed: 06/13/2023]
Abstract
Acute health effects of air pollution on diabetes risk have not been fully studied in developing countries and the results remain inconsistent. This study aimed to investigate the association between short-term exposure to ambient air pollution and Type 2 diabetes mellitus (T2DM) mortality in China. Data on T2DM mortality from 2013 to 2019 were obtained from the Cause of Death Reporting System (CDRS) of Wuhan Center for Disease Control and Prevention. Air pollution data for the same period were collected from 10 national air quality monitoring stations of Wuhan Ecology and Environment Institute, including daily average PM2.5, PM10, SO2, and NO2. Meteorological data including daily average temperature and relative humidity were collected from Wuhan Meteorological Bureau. Generalized additive models (GAM) based on quasi-Poisson distribution were applied to evaluate the association between short-term exposure to air pollution and daily T2DM deaths. A total of 9837 T2DM deaths were recorded during the study period in Wuhan. We found that short-term exposure to PM2.5, PM10, SO2, and NO2 were positively associated with T2DM mortality, and gaseous pollutants appeared to have greater effects than particulate matter (PM). For the largest effect, per 10 μg/m3 increment in PM2.5 (lag 02), PM10 (lag 02), SO2 (lag 03), and NO2 (lag 02) were significantly associated with 1.099% (95% CI: 0.451, 1.747), 1.016% (95% CI: 0.517, 1.514), 3.835% (95% CI: 1.480, 6.189), and 1.587% (95% CI: 0.646, 2.528) increase of daily T2DM deaths, respectively. Stratified analysis showed that females or elderly population aged 65 and above were more susceptible to air pollution exposure. In conclusion, short-term exposure to air pollution was significantly associated with a higher risk of T2DM mortality. Further research is required to verify our findings and elucidate the underlying mechanisms.
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Affiliation(s)
- Chuangxin Wu
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, China
| | - Yaqiong Yan
- Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Xi Chen
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, China; Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Jie Gong
- Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Yan Guo
- Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Yuanyuan Zhao
- Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Niannian Yang
- Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Juan Dai
- Wuhan Centers for Disease Control and Prevention, 288# Machang Road, Wuhan, China
| | - Faxue Zhang
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, China
| | - Hao Xiang
- Department of Global Health, School of Health Sciences, Wuhan University, Wuhan, China.
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30
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Ji Y, Liu B, Song J, Pan R, Cheng J, Su H, Wang H. Particulate matter pollution associated with schizophrenia hospital re-admissions: a time-series study in a coastal Chinese city. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:58355-58363. [PMID: 34115296 DOI: 10.1007/s11356-021-14816-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 06/07/2021] [Indexed: 06/12/2023]
Abstract
Schizophrenia (SCZ) hospital re-admissions constitute a serious disease burden worldwide. Some studies have reported an association between air pollutants and hospital admissions for SCZ. However, evidence is scarce regarding the effects of ambient particulate matter (PM) on SCZ hospital re-admissions, especially in coastal cities in China. The purpose of this study was to examine whether PM affects the risk of SCZ hospital re-admission in the coastal Chinese city of Qingdao. Daily SCZ hospital re-admissions, daily air pollutants, and meteorological factors from 2015 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was applied to model the exposure-lag-response relationship between PM and SCZ hospital re-admissions. The relative risks (RRs) were estimated for an inter-quartile range (IQR) increase in PM concentrations. Subgroup analyses by age and gender were conducted to identify the vulnerable subgroups. There were 6220 SCZ hospital re-admissions during 2015-2019. The results revealed that PM, including PM10 (particles with an aerodynamic diameter ≤10 μm), PMc (particles >2.5 μm but <10 μm), and PM2.5 (particles ≤2.5 μm), was positively correlated with SCZ hospital re-admissions. The strongest single-day effects all occurred on lag3 day, and the corresponding RRs were 1.07 (95% CI: 1.02-1.11) for PM10, 1.03 (95% CI: 1.00-1.07) for PMc, and 1.05 (95% CI: 1.01-1.09) for PM2.5 per IQR increase. Stronger associations were observed in males and younger individuals (<45 years). Our findings suggest that PM exposure is associated with increased risk of SCZ hospital re-admission. Active intervention measures against PM exposure should be taken to reduce the risk of SCZ hospital re-admission, especially for males and younger individuals.
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Affiliation(s)
- Yanhu Ji
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Bin Liu
- Qingdao Mental Health Center, Qingdao, Shandong, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China
| | - Heng Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, China.
- The First Affiliated Hospital of Anhui Medical University, 218 Jixi Road, Hefei, Anhui Province, China.
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31
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Bakolis I, Hammoud R, Stewart R, Beevers S, Dajnak D, MacCrimmon S, Broadbent M, Pritchard M, Shiode N, Fecht D, Gulliver J, Hotopf M, Hatch SL, Mudway IS. Mental health consequences of urban air pollution: prospective population-based longitudinal survey. Soc Psychiatry Psychiatr Epidemiol 2021; 56:1587-1599. [PMID: 33097984 PMCID: PMC7584487 DOI: 10.1007/s00127-020-01966-x] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 09/23/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE The World Health Organisation (WHO) recently ranked air pollution as the major environmental cause of premature death. However, the significant potential health and societal costs of poor mental health in relation to air quality are not represented in the WHO report due to limited evidence. We aimed to test the hypothesis that long-term exposure to air pollution is associated with poor mental health. METHODS A prospective longitudinal population-based mental health survey was conducted of 1698 adults living in 1075 households in South East London, from 2008 to 2013. High-resolution quarterly average air pollution concentrations of nitrogen dioxide (NO2) and oxides (NOx), ozone (O3), particulate matter with an aerodynamic diameter < 10 μm (PM10) and < 2.5 μm (PM2.5) were linked to the home addresses of the study participants. Associations with mental health were analysed with the use of multilevel generalised linear models, after adjusting for large number of confounders, including the individuals' socioeconomic position and exposure to road-traffic noise. RESULTS We found robust evidence for interquartile range increases in PM2.5, NOx and NO2 to be associated with 18-39% increased odds of common mental disorders, 19-30% increased odds of poor physical symptoms and 33% of psychotic experiences only for PM10. These longitudinal associations were more pronounced in the subset of non-movers for NO2 and NOx. CONCLUSIONS The findings suggest that traffic-related air pollution is adversely affecting mental health. Whilst causation cannot be proved, this work suggests substantial morbidity from mental disorders could be avoided with improved air quality.
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Affiliation(s)
- Ioannis Bakolis
- Health Services and Population Research Department, Centre for Implementation Science, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Ryan Hammoud
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience King's College London, King's College London, London, UK
| | - Robert Stewart
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, UK, London, UK
| | - Sean Beevers
- MRC Centre for Environment and Health, School of Public Health, Environmental Research Group, Imperial College London, London, UK
| | - David Dajnak
- MRC Centre for Environment and Health, School of Public Health, Environmental Research Group, Imperial College London, London, UK
| | - Shirlee MacCrimmon
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Matthew Broadbent
- NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, UK, London, UK
| | - Megan Pritchard
- NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, UK, London, UK
| | | | - Daniela Fecht
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - John Gulliver
- Centre for Environmental Health and Sustainability, School of Geography, Geology and the Environment, University of Leicester, Leicester, UK
| | - Matthew Hotopf
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, UK, London, UK
| | - Stephani L Hatch
- Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, UK, London, UK
| | - Ian S Mudway
- MRC Centre for Environment and Health, School of Public Health, Environmental Research Group, Imperial College London, London, UK
- National Institute for Health Research, Health Protection Research Unit on Environmental Exposures and Health, Imperial College London, London, UK
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32
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Liang Z, Xu C, Liang S, Cai TJ, Yang N, Li SD, Wang WT, Li YF, Wang D, Ji AL, Zhou LX, Liang ZQ. Short-term ambient nitrogen dioxide exposure is associated with increased risk of spontaneous abortion: A hospital-based study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2021; 224:112633. [PMID: 34411816 DOI: 10.1016/j.ecoenv.2021.112633] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 08/06/2021] [Accepted: 08/11/2021] [Indexed: 06/13/2023]
Abstract
There are increasing concerns with regard to spontaneous abortion (SAB), the loss of pregnancy without external intervention before 20 weeks of gestation, among reproductive-aged women. To date, limited evidence is available concerning the association between SAB and air pollutants, especially in developing countries. Daily baseline outpatient data for SAB from January 1, 2014, to December 31, 2018 (1826 days) were obtained in Chongqing, a metropolis of southwest China. The over-dispersed Poisson generalized additive model with control of meteorological conditions and day of week was used to estimate the short-term effects of ambient air pollution on the daily number of SAB outpatients. A total of 42,334 SAB outpatient visits for SAB were recorded. No statistically significant association was observed between SAB and CO, PM2.5, PM10, O3, and SO2. The positive association only appeared for NO2: positive associations between SAB and NO2 were observed in both single-day models (lag 0, lag 1, lag 3, and lag 4) and cumulative exposure models (lag 01, lag 03, and lag 05) and the most significant effects were observed at lag 05 (3.289%; 95% CI: 1.568%, 5.011%). Moreover, the women with higher ages (30-39 and > 39) were more sensitive than those with lower ages (18-29), and the effect estimates were more evident in cool seasons. Collectively, our results suggested that short-term NO2 exposure was associated with higher risk of SAB, especially in elder women and cool seasons, which may contribute to further understand the role of air pollution on SAB and other adverse obstetric outcomes.
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Affiliation(s)
- Zhen Liang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China; Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China; Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, China
| | - Shi Liang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China; Department of Chemistry, Brigham Young University-Idaho, Rexburg, ID, USA
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China.
| | - Neng Yang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Si-Di Li
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Wen-Ting Wang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Dan Wang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Ai-Ling Ji
- Department of Preventive Medicine, Chongqing Medical and Pharmaceutical College, Chongqing, China
| | - Lai-Xin Zhou
- Medical Department, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Zhi-Qing Liang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
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Robinson N, Bergen SE. Environmental Risk Factors for Schizophrenia and Bipolar Disorder and Their Relationship to Genetic Risk: Current Knowledge and Future Directions. Front Genet 2021; 12:686666. [PMID: 34262598 PMCID: PMC8273311 DOI: 10.3389/fgene.2021.686666] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 05/20/2021] [Indexed: 12/16/2022] Open
Abstract
Schizophrenia (SZ) and bipolar disorder (BD) are severe psychiatric disorders which result from complex interplay between genetic and environmental factors. It is well-established that they are highly heritable disorders, and considerable progress has been made identifying their shared and distinct genetic risk factors. However, the 15-40% of risk that is derived from environmental sources is less definitively known. Environmental factors that have been repeatedly investigated and often associated with SZ include: obstetric complications, infections, winter or spring birth, migration, urban living, childhood adversity, and cannabis use. There is evidence that childhood adversity and some types of infections are also associated with BD. Evidence for other risk factors in BD is weaker due to fewer studies and often smaller sample sizes. Relatively few environmental exposures have ever been examined for SZ or BD, and additional ones likely remain to be discovered. A complete picture of how genetic and environmental risk factors confer risk for these disorders requires an understanding of how they interact. Early gene-by-environment interaction studies for both SZ and BD often involved candidate genes and were underpowered. Larger samples with genome-wide data and polygenic risk scores now offer enhanced prospects to reveal genetic interactions with environmental exposures that contribute to risk for these disorders. Overall, although some environmental risk factors have been identified for SZ, few have been for BD, and the extent to which these account for the total risk from environmental sources remains unknown. For both disorders, interactions between genetic and environmental risk factors are also not well understood and merit further investigation. Questions remain regarding the mechanisms by which risk factors exert their effects, and the ways in which environmental factors differ by sex. Concurrent investigations of environmental and genetic risk factors in SZ and BD are needed as we work toward a more comprehensive understanding of the ways in which these disorders arise.
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Affiliation(s)
| | - Sarah E. Bergen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Zhou YM, Fan YN, Yao CY, Xu C, Liu XL, Li X, Xie WJ, Chen Z, Jia XY, Xia TT, Li YF, Ji AL, Cai TJ. Association between short-term ambient air pollution and outpatient visits of anxiety: A hospital-based study in northwestern China. ENVIRONMENTAL RESEARCH 2021; 197:111071. [PMID: 33798515 DOI: 10.1016/j.envres.2021.111071] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Revised: 03/21/2021] [Accepted: 03/21/2021] [Indexed: 06/12/2023]
Abstract
Anxiety, a common and devastating mental disorder, has raised widespread interests. The impacts of air pollution on physical health are well known, whereas few studies have explored the association of atmospheric pollution, especially short-term air pollution exposure, with the risk of anxiety disorders. In addition, there are increasing concerns in emerging evidence supporting a possible etiological link. Therefore, our aim was to evaluate the relationship between short-term exposure to atmospheric pollutants and anxiety outpatient visits in Xi'an, a city of northwestern China and a metropolis with relatively heavy air pollution. We collected the data of both daily outpatient visits and daily air pollution (SO2, NO2, and PM10) between January 1, 2010 and January 31, 2016 (2222 days). To clarify the association between short-term ambient atmospheric pollution exposure and anxiety outpatient visits, an over-dispersed Poisson generalized additive model was applied by adjusting the day of the week and weather conditions (including temperature, humidity, sunlight hours, and rainfalls). Positive association between gaseous air pollutants (SO2 and NO2) and anxiety daily outpatient visits was observed. Moreover, the largest estimated values of both SO2 and NO2 were evidence at lag 03 (4-day moving average lag), with 10 μg/m3 increase corresponded to the increase of outpatient anxiety visits at 4.11% (95% CI: 2.15%, 6.06%) for SO2 and 3.97% (95% CI: 1.90%, 6.06%) for NO2. However, there was no differences in susceptibility to air pollutants between different genders as well as different ages. Taken together, short-term exposure to ambient air pollutants, especially gaseous air pollutants (NO2 and SO2), can be related to higher risk of anxiety outpatient visits.
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Affiliation(s)
- Yu-Meng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Yan-Ni Fan
- Medical Record Room of Information Department, Second Affiliated Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, China.
| | - Chun-Yan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710032, China.
| | - Xiao-Ling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Xiang Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Department of Plastic & Cosmetic Surgery, Daping Hospital, Army Medical University (Third Military Medical University), Chongqing, 400042, China.
| | - Wei-Jia Xie
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Zheng Chen
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Xiao-Yue Jia
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Ting-Ting Xia
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
| | - Ai-Ling Ji
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China.
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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Zhou YM, An SJ, Tang EJ, Xu C, Cao Y, Liu XL, Yao CY, Xiao H, Zhang Q, Liu F, Li YF, Ji AL, Cai TJ. Association between short-term ambient air pollution exposure and depression outpatient visits in cold seasons: a time-series analysis in northwestern China. JOURNAL OF TOXICOLOGY AND ENVIRONMENTAL HEALTH. PART A 2021; 84:389-398. [PMID: 33622183 DOI: 10.1080/15287394.2021.1880507] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Depression is known to be one of the most common mental disorders raising global concerns. However, evidence regarding the association between short-term air pollution exposure and risk of development of depression is limited. The aim of this was to assess the relationship between short-term ambient air pollution exposure and depression in outpatient visits in Xi'an, a northwestern Chinese metropolis. Data for air pollutants including particulate matter (PM10), sulfur dioxide (SO2), and nitrogen dioxide (NO2) levels from October 1, 2010 to December 31, 2013 and number of daily depression outpatient visits (92,387 in total) were collected. A time-series quasi-Poisson regression model was adopted to determine the association between short-term air pollutant concentrations and frequency of outpatient visits for depression with different lag models. Consequently, 10 μg/m3 increase of SO2 and NO2 levels corresponded to significant elevation in number of outpatient-visits for depression on concurrent days (lag 0), and this relationship appeared stronger in cool seasons (October to March). However, the association of PM10 was only significant in males aged 30-50 at lag 0. Evidence indicated that short-term exposure to ambient air pollutants especially in cool seasons might be associated with increased risk of outpatient visits for depression.
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Affiliation(s)
- Yu-Meng Zhou
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Shu-Jie An
- Medical Department, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, China
| | - En-Jie Tang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
- Department of Hepatobiliary Surgery, Xijing Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, China
| | - Yi Cao
- Department of Health Economics Management, Xijing Hospital, Air Force Medical University, Xi'an, China
| | - Xiao-Ling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Chun-Yan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Hua Xiao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Qian Zhang
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, China
| | - Feng Liu
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Ai-Ling Ji
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Tong-Jian Cai
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, China
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The association between ozone and fine particles and mental health-related emergency department visits in California, 2005-2013. PLoS One 2021; 16:e0249675. [PMID: 33798241 PMCID: PMC8018671 DOI: 10.1371/journal.pone.0249675] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 03/22/2021] [Indexed: 11/20/2022] Open
Abstract
Recent studies suggest that air pollutant exposure may increase the incidence of mental health conditions, however research is limited. We examined the association between ozone (O3) and fine particles (PM2.5) and emergency department (ED) visits related to mental health outcomes, including psychosis, neurosis, neurotic/stress, substance use, mood/affective, depression, bipolar, schizotypal/delusional, schizophrenia, self-harm/suicide, and homicide/inflicted injury, from 2005 through 2013 in California. Air monitoring data were provided by the U.S. EPA's Air Quality System Data Mart and ED data were provided by the California Office of Statewide Health Planning and Development. We used the time-series method with a quasi-Poisson regression, controlling for apparent temperature, day of the week, holidays, and seasonal/long-term trends. Per 10 parts per billion increase, we observed significant cumulative 7-day associations between O3 and all mental health [0.64%, 95% confidence interval (CI): 0.21, 1.07], depression [1.87%, 95% CI: 0.62, 3.15], self-harm/suicide [1.43%, 95% CI: 0.35, 2.51], and bipolar [2.83%, 95% CI: 1.53, 4.15]. We observed 30-day lag associations between O3 and neurotic disorder [1.22%, 95% CI: 0.48, 1.97] and homicide/inflicted injury [2.01%, 95% CI: 1.00, 3.02]. Same-day mean PM2.5 was associated with a 0.42% [95% CI: 0.14, 0.70] increase in all mental health, 1.15% [95% CI: 0.62, 1.69] increase in homicide/inflicted injury, and a 0.57% [95% CI: 0.22, 0.92] increase in neurotic disorders per 10 μg/m3 increase. Other outcomes not listed here were not statistically significant for O3 or PM2.5. Risk varied by age group and was generally greater for females, Asians, and Hispanics. We also observed seasonal variation for outcomes including but not limited to depression, bipolar, schizophrenia, self-harm/suicide, and homicide/inflicted injury. Ambient O3 or PM2.5 may increase the risk of mental health illness, though underlying biological mechanisms remain poorly understood. Findings warrant further investigation to better understand the impacts of air pollutant exposure among vulnerable groups.
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Gao J, Wei Q, Pan R, Yi W, Xu Z, Duan J, Tang C, He Y, Liu X, Song S, Su H. Elevated environmental PM 2.5 increases risk of schizophrenia relapse: Mediation of inflammatory cytokines. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 753:142008. [PMID: 32892002 DOI: 10.1016/j.scitotenv.2020.142008] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Revised: 08/13/2020] [Accepted: 08/25/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Ecological epidemiology suggests that hospital admissions for schizophrenia are associated with an increased environmental PM2.5, but no prospective study has verified this result, and the physiological mechanism is not clear. METHODS We used a repeated-measures design to prospectively assess the association of environmental PM2.5 and the risk of relapse in schizophrenia, and used two linear mixed-effects models to explore possible mediating effects of immune cytokines on the premise of controlling confounders. RESULTS We import the data using EpiData software, and collate and analyze of the data using R software. The increase of PM2.5 at lag0 had the greatest impact on the relapse of schizophrenia (for each 10 μg/m3 increase in PM2.5, the relapse risk score increased by 1.504, that is to say, odds ratio (OR) = 4.500 (95% confidence interval (CI): 2.849-7.106,P < 0.001)), and cumulative effects lasted for four days with the maximum at the second day (for each 10 μg/m3 increase in PM2.5, the relapse risk score increased by 1.301, OR = 3.673 (95%CI: 1.962-6.876,P < 0.001)). PM2.5 exposure was statistically related to four symptom dimensions of early signs scale (ESS), and the symptoms most affected by the increased PM2.5 were depression/withdrawal (ESSN) (OR = 1.990, 95%CI: 1.701-2.328), anxiety/agitation (ESS-A) (OR = 1.537, 95%CI: 1.340-1.763), initial psychosis (ESS-IP) (OR = 1.398, 95%CI: 1.151-1.697), and disinhibition (ESS-D) (OR = 1.235, 95%CI: 1.133-1.347). Furthermore, there are three statistically significant pathways in intermediary analysis: of PM2.5 and relapse risk: "PM2.5 → IL-17 → ESS", "PM2.5 → IL-17 → ESS-A", and "PM2.5 → IL-17 → ESS-N", and the intermediary ratio of IL-17 was 11.66%, 16.37% and 22.55%, respectively. CONCLUSIONS Increased environmental PM2.5 is a risk factor for the relapse of schizophrenia. Early relapse identification and intervention based on clinical characteristics are of great significance for timely termination of relapse and slowing down of relapse.
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Affiliation(s)
- Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Qiannan 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 Disease, 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 Disease, 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 Disease, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Chao Tang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Yangyang He
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Xiangguo 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 Disease, China
| | - Shasha 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 Disease, 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 Disease, China.
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Kim H, Kim WH, Kim YY, Park HY. Air Pollution and Central Nervous System Disease: A Review of the Impact of Fine Particulate Matter on Neurological Disorders. Front Public Health 2020; 8:575330. [PMID: 33392129 PMCID: PMC7772244 DOI: 10.3389/fpubh.2020.575330] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 11/20/2020] [Indexed: 12/19/2022] Open
Abstract
Background: It is widely known that the harmful effects of fine dust can cause various diseases. Research on the correlation between fine dust and health has been mainly focused on lung and cardiovascular diseases. By contrast, the effects of air pollution on the central nervous system (CNS) are not broadly recognized. Findings: Air pollution can cause diverse neurological disorders as the result of inflammation of the nervous system, oxidative stress, activation of microglial cells, protein condensation, and cerebral vascular-barrier disorders, but uncertainty remains concerning the biological mechanisms by which air pollution produces neurological disease. Neuronal cell damage caused by fine dust, especially in fetuses and infants, can cause permanent brain damage or lead to neurological disease in adulthood. Conclusion: It is necessary to study the air pollution–CNS disease connection with particular care and commitment. Moreover, the epidemiological and experimental study of the association between exposure to air pollution and CNS damage is critical to public health and quality of life. Here, we summarize the correlations between fine dust exposure and neurological disorders reported so far and make suggestions on the direction future research should take.
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Affiliation(s)
- Hyunyoung Kim
- Division of Allergy and Respiratory Disease Research, Department of Chronic Disease Convergence Research, Korea National Institute of Health, Cheongju-si, South Korea
| | - Won-Ho Kim
- Division of Cardiovascular Disease Research, Department of Chronic Disease Convergence Research, Korea National Institute of Health, Cheongju-si, South Korea
| | - Young-Youl Kim
- Division of Allergy and Respiratory Disease Research, Department of Chronic Disease Convergence Research, Korea National Institute of Health, Cheongju-si, South Korea
| | - Hyun-Young Park
- Department of Precision Medicine, Korea National Institute of Health, Cheongju-si, South Korea
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Li H, Zhang S, Qian ZM, Xie XH, Luo Y, Han R, Hou J, Wang C, McMillin SE, Wu S, Tian F, Deng WF, Lin H. Short-term effects of air pollution on cause-specific mental disorders in three subtropical Chinese cities. ENVIRONMENTAL RESEARCH 2020; 191:110214. [PMID: 32946889 DOI: 10.1016/j.envres.2020.110214] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Revised: 08/25/2020] [Accepted: 09/09/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND The effects of ambient air pollution on specific mental disorders are rarely studied, and the reported results are inconsistent. OBJECTIVE To assess the short-term effect of ambient air pollution on the morbidity of mental disorders in three subtropical Chinese cities. METHODS Daily concentrations of air pollution were averaged from 19 fixed monitoring stations across each city, and data on patients were collected from three psychiatric specialty hospitals. A time-series study combined with a generalized additive Poisson model was conducted to investigate the association between air pollution and mental disorders. The exposure-response relationships were explored and stratified analyses by age and sex were conducted. RESULTS A total of 1,133,220 outpatient visits were recorded in three subtropical cities (Huizhou, Shenzhen, and Zhaoqing). The number of daily outpatient visits for mental disorders increased with higher air pollutant (PM2.5, PM10, SO2 and NO2) concentrations, and the effect of NO2 appeared to be consistently significant across the three cities, with excess risk (ER) of 4.45% (95% CI: 2.90%, 6.04%) in Huizhou, 7.94% (95% CI: 6.28%, 9.62%) in Shenzhen, and 2.19% (95% CI: 0.51%, 3.89%) in Zhaoqing, respectively, at lag03. We also observed significant effect of PM2.5 at lag0 (ER = 1.20%, 95% CI: 0.28%, 2.13%), PM10 at lag0 (ER = 0.99%, 95% CI: 0.36%, 1.62%), and SO2 at lag0 (ER = 10.74%, 95% CI: 3.20%, 18.84%) in Shenzhen. For specific mental disorders, significant associations were found in all the air pollutants except between SO2 and affective disorder and between PM2.5 and schizophrenia. In addition, we found that air pollution exhibited stronger effects for males and adults (≥18 years). CONCLUSION Acute exposure to air pollution, especially NO2, might be an important trigger of mental disorders.
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Affiliation(s)
- Huan Li
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Shiyu Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Zhengmin Min Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, USA
| | - Xin-Hui Xie
- Brain Function and Psychosomatic Medicine Institute, The Second People's Hospital of Huizhou, Huizhou, Guangdong, China
| | - Yang Luo
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Rong Han
- Department of Psychiatry, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen, Guangdong, China
| | - Jiesheng Hou
- The Third People's Hospital of Zhaoqing, Guangdong, China
| | - Chongjian Wang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Stephen Edward McMillin
- School of Social Work, College for Public Health & Social Justice, Saint Louis University, USA
| | - Shaowei Wu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, China
| | - Fei Tian
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China
| | - Wen-Feng Deng
- Brain Function and Psychosomatic Medicine Institute, The Second People's Hospital of Huizhou, Huizhou, Guangdong, China.
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 510080, China.
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Air Pollution-Related Brain Metal Dyshomeostasis as a Potential Risk Factor for Neurodevelopmental Disorders and Neurodegenerative Diseases. ATMOSPHERE 2020. [DOI: 10.3390/atmos11101098] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Increasing evidence links air pollution (AP) exposure to effects on the central nervous system structure and function. Particulate matter AP, especially the ultrafine (nanoparticle) components, can carry numerous metal and trace element contaminants that can reach the brain in utero and after birth. Excess brain exposure to either essential or non-essential elements can result in brain dyshomeostasis, which has been implicated in both neurodevelopmental disorders (NDDs; autism spectrum disorder, schizophrenia, and attention deficit hyperactivity disorder) and neurodegenerative diseases (NDGDs; Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, and amyotrophic lateral sclerosis). This review summarizes the current understanding of the extent to which the inhalational or intranasal instillation of metals reproduces in vivo the shared features of NDDs and NDGDs, including enlarged lateral ventricles, alterations in myelination, glutamatergic dysfunction, neuronal cell death, inflammation, microglial activation, oxidative stress, mitochondrial dysfunction, altered social behaviors, cognitive dysfunction, and impulsivity. Although evidence is limited to date, neuronal cell death, oxidative stress, and mitochondrial dysfunction are reproduced by numerous metals. Understanding the specific contribution of metals/trace elements to this neurotoxicity can guide the development of more realistic animal exposure models of human AP exposure and consequently lead to a more meaningful approach to mechanistic studies, potential intervention strategies, and regulatory requirements.
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Zhang P, Zhou X. Health and economic impacts of particulate matter pollution on hospital admissions for mental disorders in Chengdu, Southwestern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 733:139114. [PMID: 32447079 DOI: 10.1016/j.scitotenv.2020.139114] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 04/11/2020] [Accepted: 04/27/2020] [Indexed: 04/14/2023]
Abstract
The evidence for adverse effects of ambient particulate matter (PM) pollution on mental disorders (MDs) is limited, especially in developing countries. This study aimed to quantify both PM related health impacts and corresponding economic loses for overall and specific MDs in southwestern China. Data regarding 134,292 hospital admissions for MDs were collected from local Compulsory Medical Insurance Database in 2013-2017. A generalized additive model (GAM) was applied to estimate the exposure-response effects of PM pollution on hospital admissions for MDs. And the cost of illness method (COI) was adopted to further assess corresponding hospitalization costs and productivity loses. It was showed that PM pollution was significantly related to hospital admissions for overall and specific MDs. Each 10 μg/m3 increase in concentrations of PM10 (particles with an aerodynamic diameters ≤10 μm), PM2.5 (≤ 2.5 μm) and PMc (2.5 μm < c < 10 μm) at the cumulative lag03 day would be responsible for 3.25% (95%CI: 2.34-4.16%), 6.38% (95%CI: 4.79-7.97%), and 3.81% (95%CI: 2.13-5.50%) increments in daily hospital admissions for MDs, respectively. Stronger associations were observed in males, cool season and people over 45 years. During the study period, PM pollution brought 1453.18 million Yuan economic losses for overall MDs, accounting for 0.026% of local GDP. This study suggested that short-term exposure to PM pollution, especially to PM2.5, was associated with increased hospital admissions for MDs in southwestern China. In addition, potential benefits of lowering PM concentrations are considerable.
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Affiliation(s)
- Pei Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Xiaoyuan Zhou
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
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Bai L, Yang J, Zhang Y, Zhao D, Su H. Durational effect of particulate matter air pollution wave on hospital admissions for schizophrenia. ENVIRONMENTAL RESEARCH 2020; 187:109571. [PMID: 32416354 DOI: 10.1016/j.envres.2020.109571] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Revised: 04/01/2020] [Accepted: 04/20/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Short-term exposure to high level of ambient particulate matters (PM) concentrations has been linked with increased hospital admissions (HA) for schizophrenia. However, evidence is inconclusive about the added effect of multi-day exposure to high-level PM concentration on schizophrenia. This study aims to evaluate the durational effect of PM air pollution wave on schizophrenia. METHOD Data on daily HA for schizophrenia, PM (PM2.5 and PM10) and meteorological variables over the period of 2014-2017 was collected in Jining, Shandong, China. Air pollution wave of PM was defined as ≥2 or ≥3 or ≥4 consecutive days with PM concentration ≥90th or ≥92.5th or ≥95th or ≥97.5th percentiles, respectively. A time-series Poisson regression model with duration as the variable of interest was used to evaluate the associations of PM air pollution wave with HA for schizophrenia. RESULTS A total of 14650 hospital admissions for schizophrenia were identified. Under various air pollution wave definitions, both PM2.5 and PM10 had significant adverse effects on schizophrenia HA. PM2.5 wave defined as ≥2 consecutive days with concentration ≥90th, ≥92.5th, ≥95th and ≥97.5th percentile was associated with 4.8% (2.0%-7.6%), 4.9% (1.9%-7.9%), 5.5% (2.0%-9.2%), and 7.6% (2.9%-12.6%) increase of HA for schizophrenia at lag 6. PM2.5 waves defined as ≥3 consecutive days with concentration ≥90th, ≥92.5th, ≥95th and ≥97.5th percentile respectively corresponded to 5.0% (2.3%-7.8%), 5.1% (1.9%-8.4%), 6.9% (3.0%-10.8%) and 12.0% (5.3%-19.1%) increases in HA for schizophrenia at lag 6. The most significant associations were observed on the sixth day in different lag models. CONCLUSIONS PM air pollution wave was associated with increased risk of hospital admissions for schizophrenia, with stronger associations among married and female patients.
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Affiliation(s)
- Lijun Bai
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230036, China
| | - Jing Yang
- Research Institution of Behavioral Medicine Education, Jining Medical University, Jining, Shandong, 272067, China
| | - Yanwu Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230036, China
| | - Desheng Zhao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230036, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China.
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Liang Z, Xu C, Ji AL, Liang S, Kan HD, Chen RJ, Lei J, Li YF, Liang ZQ, Cai TJ. Effects of short-term ambient air pollution exposure on HPV infections: A five-year hospital-based study. CHEMOSPHERE 2020; 252:126615. [PMID: 32443276 DOI: 10.1016/j.chemosphere.2020.126615] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 03/21/2020] [Accepted: 03/23/2020] [Indexed: 06/11/2023]
Abstract
Human papillomavirus (HPV) infections are common sexually-transmitted diseases among reproductive-aged women with increasing concern. Until now, there are no prior study about the association between HPV infections and ambient air pollution. This study aimed to explore the relationship between short-term exposure to ambient pollutants and daily outpatient visits for HPV infections in China. Data of daily outpatient visits for HPV infections were obtained from January 1, 2014 to December 31, 2018 (1826 days). Over-dispersed Poisson generalized additive models were applied by adjusting weather conditions and day of the week. We identified a total of 39,746 cases for HPV infections. A 10 μg/m3 increase of PM10, PM2.5, SO2, and NO2 or a 0.1 mg/m3 rise of CO in concurrent day (lag 0) concentrations was related to an elevation of 0.822% (95% Cl: 0.282%, 1.36%), 1.05% (95% Cl: 0.280%, 1.81%), 5.72% (95% Cl: 1.79%, 9.65%), 5.02% (95% Cl: 3.45%, 6.60%), and 2.40% (95% Cl: 1.43%, 3.37%) in daily outpatient-visits for HPV infections, respectively. The association was more significant in those women aged 41 or over. As for 10 μg/m3 increase of O3, a -1.33% (95% Cl: -2.13%, -0.530%) change was observed on the lag 03 and such effects appeared to be more obvious in the aged 18-40 group. Our results provided the first evidence that short-term exposure to ambient pollutants was related to, which may be indirectly, the increased risk of HPV infections while O3 may act as a "protective" factor.
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Affiliation(s)
- Zhen Liang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Troop 94498 of PLA, Nanyang, 474350, China
| | - Ai-Ling Ji
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China
| | - Shi Liang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Brigham Young University Provo, UT 84602, 801-422-4636, USA
| | - Hai-Dong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Ren-Jie Chen
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Jie Lei
- Department of Internal Medicine, Hui Long-Ba Town Hospital, Chongqing, 401335, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Zhi-Qing Liang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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Wei F, Wu M, Qian S, Li D, Jin M, Wang J, Shui L, Lin H, Tang M, Chen K. Association between short-term exposure to ambient air pollution and hospital visits for depression in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 724:138207. [PMID: 32268289 DOI: 10.1016/j.scitotenv.2020.138207] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 03/06/2020] [Accepted: 03/23/2020] [Indexed: 06/11/2023]
Abstract
Depression is one of the leading causes of disability, but the etiology remains unclear. Recently, it has been suggested that air pollution is a potential risk factor for depression. However, the results remained inconsistent. So we conducted this study to assess the association between short-term exposure to ambient air pollution and hospital visits for depression in China. Daily hospital visits for depression from January 18, 2013 to June 10, 2018 were extracted from a regional health information system (HIS) covered 1.34 million population in Ningbo, China. We collected daily air pollutant concentrations and meteorological data from environmental air quality monitoring sites and meteorological stations in the study area. Quasi-Poisson regression models with generalized additive models (GAM) were applied to explore the associations between air pollution and hospital visits for depression. Stratified analyses were also conducted by gender, age, and season to examine the effects modification. The results disclosed that air pollutants including PM2.5, PM10, SO2, CO, and NO2 were positively correlated with hospital visits for depression. The strongest effects all occurred on lag0 (the same) day, and the corresponding excess risks (ERs) were 2.59 (95%CI: 0.72, 4.49) for PM2.5, 3.08 (95%CI: 1.05, 5.16) for PM10, 3.22 (95%CI: 1.16, 5.32) for SO2, 4.38 (95%CI: 1.83, 6.99) for CO, and 4.94 (95%CI: 2.03, 7.92) for NO2 per IQR increase, respectively. The associations were found to be stronger in the elderly (≥65 years) and cold season. Furthermore, the effects of CO and NO2 remained significant in most two-pollutant models, suggesting that traffic-related air pollutants might be more important triggers of depression.
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Affiliation(s)
- Fang Wei
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Mengyin Wu
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Sangni Qian
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Die Li
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Mingjuan Jin
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Jianbing Wang
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; National Clinical Research Center for Child Health of the Children's Hospital, Zhejiang University School of Medicine, Zhejiang, China
| | - Liming Shui
- Health Commission of Ningbo, Zhejiang, China
| | - Hongbo Lin
- The Center for Disease Control and Prevention of Yinzhou District, Ningbo, Zhejiang, China
| | - Mengling Tang
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
| | - Kun Chen
- Department of Epidemiology and Biostatistics, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; Cancer Institute of the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, China.
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Xu C, Fan YN, Liang Z, Xiao SH, Huang L, Kan HD, Chen RJ, Liu XL, Yao CY, Luo G, Zhang Y, Li YF, Ji AL, Cai TJ. Unexpected association between increased levels of ambient carbon monoxide and reduced daily outpatient visits for vaginitis: A hospital-based study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 723:137923. [PMID: 32220730 DOI: 10.1016/j.scitotenv.2020.137923] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 02/16/2020] [Accepted: 03/12/2020] [Indexed: 06/10/2023]
Abstract
Carbon monoxide (CO) is a well-known "toxic gas". It represents a toxic inhalation hazard at high concentration and is commonly found in polluted air. However, a series of recent studies have suggested that low concentration of CO can also produce protective functions. This study was performed to investigate the association between ambient CO exposure and vaginitis outpatient visits. Daily baseline outpatient data of vaginitis from January 1, 2013 to December 31, 2015 were obtained from Xi'an, a heavily-polluted metropolis in China. The over-dispersed Poisson generalized additive model was applied to discover the relations between short-term ambient CO exposure and the number of vaginitis outpatient visits by adjusting day of the week and weather conditions. A total of 16,825 outpatient hospital visits for vaginitis were recorded. The mean daily concentration of carbon monoxide (CO) was well below Chinese and WHO guidelines. During the study period, increased levels of ambient CO was associated with reduced outpatient-visits through concurrent to lag 5 days, and the most significant association was evidenced at lag 05. A 0.1 mg/m3 increase in daily average CO at lag 05 corresponded to -1.25% (95%CI: -1.85%, -0.65%) change in outpatient-visits for vaginitis. Moreover, the association was more significant in those women aged 20-29 years. After adjustment for PM10, PM2.5, SO2, and NO2, and O3, the negative associations of CO with vaginitis kept significant, suggesting relative stability of effect estimates. In summary, this is the first evidence that increased ambient CO exposure can be related to reduced daily outpatient visits for vaginitis. The results of our study may not only help to establish more comprehensive understanding of the health effects of ambient air on vaginitis and other gynecological diseases, but also provide a clue to new potential interventions.
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Affiliation(s)
- Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China; Troop 94498 of PLA, Nanyang, China
| | - Yan-Ni Fan
- Medical Record Room of Information Department, Tangdu Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, China
| | - Zhen Liang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China; Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | | | | | - Hai-Dong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Ren-Jie Chen
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, China
| | - Xiao-Ling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Chun-Yan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Gan Luo
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Yao Zhang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
| | - Ai-Ling Ji
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, China.
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China.
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Liang Z, Xu C, Fan YN, Liang ZQ, Kan HD, Chen RJ, Yao CY, Liu XL, Lang HB, Lei J, Zhao YS, Li YF, Ji AL, Cai TJ. Association between air pollution and menstrual disorder outpatient visits: A time-series analysis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2020; 192:110283. [PMID: 32061980 DOI: 10.1016/j.ecoenv.2020.110283] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 01/29/2020] [Accepted: 01/31/2020] [Indexed: 06/10/2023]
Abstract
Menstrual disorders are common diseases among reproductive-aged women with increasing concerns. Until now, there have been limited studies about the association between menstrual disorders and air pollution. This study aimed to investigate the association between short-term (concurrent day and within 1 week prior) ambient air pollution exposure and menstrual disorder outpatient visits in Xi'an, a metropolis in northwestern China. Daily baseline outpatient data of menstrual disorders from January 1, 2010 to February 18, 2016 (2239 days) were obtained. An over-dispersed Poisson generalized additive model was applied to discover the relationship between short-term air pollution exposure and the number of menstrual disorder outpatient visits by adjusting the day of the week and weather conditions. A total of 51,893 outpatient visits for menstrual disorders were recorded. A 10 μg/m3 increase of PM10 and NO2 concentrations corresponded to 0.236% (95% Cl: 0.075%, 0.397%) and 2.173% (95% Cl: 0.990%, 3.357%) elevations in outpatient-visits for menstrual disorders at lag 7 and lag 01 (concurrent day and previous 1 day), respectively. The association was more significant in young females (18-29 years) and there was no obvious association observed between SO2 and menstrual disorder outpatient visits. This is the first evidence that short-term exposure to ambient air pollution can be associated with an increased risk of menstrual disorder attacks. The results of our study may help to establish more comprehensive understanding of the health effects of ambient air pollution on menstrual disorders and other reproductive diseases.
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Affiliation(s)
- Zhen Liang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Chen Xu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China; Troop 94498 of PLA, Nanyang, 474350, China
| | - Yan-Ni Fan
- Medical Record Room of Information Department, Second Affiliated Hospital, Air Force Medical University (Fourth Military Medical University), Xi'an, 710038, China
| | - Zhi-Qing Liang
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Hai-Dong Kan
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Ren-Jie Chen
- Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China
| | - Chun-Yan Yao
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Xiao-Ling Liu
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Hai-Bin Lang
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Jie Lei
- Department of Internal Medicine, Hui Long-Ba Town Hospital, Chongqing, 401335, China
| | - Ying-Shu Zhao
- Department of Obstetrics and Gynecology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ya-Fei Li
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Ai-Ling Ji
- Department of Preventive Medicine & Chongqing Engineering Research Center of Pharmaceutical Sciences, Chongqing Medical and Pharmaceutical College, Chongqing, 401331, China.
| | - Tong-Jian Cai
- Department of Epidemiology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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Antonsen S, Mok PLH, Webb RT, Mortensen PB, McGrath JJ, Agerbo E, Brandt J, Geels C, Christensen JH, Pedersen CB. Exposure to air pollution during childhood and risk of developing schizophrenia: a national cohort study. Lancet Planet Health 2020; 4:e64-e73. [PMID: 32112749 DOI: 10.1016/s2542-5196(20)30004-8] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 01/06/2020] [Accepted: 01/07/2020] [Indexed: 06/10/2023]
Abstract
BACKGROUND Ambient air pollution affects neurological function, but its association with schizophrenia risk is unclear. We investigated exposure to nitrogen oxides (NOX) as a whole and nitrogen dioxide (NO2) specifically, as well as PM10, and PM2·5, during childhood and subsequent schizophrenia risk. METHODS People born in Denmark from 1980 to 1984 (N=230 844), who were residing in the country on their tenth birthday, and who had two Danish-born parents were followed-up from their tenth birthday until schizophrenia diagnosis or Dec 31, 2016. Mean daily exposure to each pollutant (NO2, NOX, PM10, and PM2·5) at all of an individual's residential addresses from birth to their tenth birthday was modelled. Incidence rate ratios, cumulative incidence, and population attributable risks were calculated using survival analysis techniques. FINDINGS We analysed data between Aug 1, 2018, and Nov 15, 2019. Of 230 844 individuals included, 2189 cohort members were diagnosed with schizophrenia during follow-up. Higher concentrations of residential NO2 and NOX exposure during childhood were associated with subsequent elevated schizophrenia risk. People exposed to daily mean concentrations of more than 26·5 μg/m3 NO2 had a 1·62 (95% CI 1·41-1·87) times increased risk compared with people exposed to a mean daily concentration of less than 14·5 μg/m3. The absolute risks of developing schizophrenia by the age of 37 years when exposed to daily mean concentrations of more than 26·5 μg/m3 NO2 between birth and 10 years were 1·45% (95% CI 1·30-1·62%) for men and 1·03% (0·90-1·17) for women, whereas when exposed to a mean daily concentration of less than 14·5 μg/m3, the risk was 0·80% (95% CI 0·69-0·92%) for men and 0·67% (0·57-0·79) for women. Associations between exposure to PM2·5 or PM10 and schizophrenia risk were less consistent. INTERPRETATION If the association between air pollution and schizophrenia is causal, reducing ambient air pollution including NO2 and NOX could have a potentially considerable effect on lowering schizophrenia incidence at the population level. Further investigations are necessary to establish a causal relationship. FUNDING Lundbeck Foundation, Stanley Medical Research Institute, European Research Council, NordForsk, Novo Nordisk Foundation, National Health and Medical Research Council, Danish National Research Foundation.
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Affiliation(s)
- Sussie Antonsen
- National Centre for Register-Based Research, Aarhus Business and Social Sciences, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark; Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
| | - Pearl L H Mok
- Centre for Mental Health and Safety, Division of Psychology and Mental Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK.
| | - Roger T Webb
- Centre for Mental Health and Safety, Division of Psychology and Mental Health, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK; NIHR Greater Manchester Patient Safety Translational Research Centre, Manchester, UK
| | - Preben B Mortensen
- National Centre for Register-Based Research, Aarhus Business and Social Sciences, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark; Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
| | - John J McGrath
- National Centre for Register-Based Research, Aarhus Business and Social Sciences, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark; Queensland Brain Institute, The University of Queensland, St Lucia, QLD, Australia; Queensland Centre for Mental Health Research, The Park Centre for Mental Health, Wacol, QLD, Australia
| | - Esben Agerbo
- National Centre for Register-Based Research, Aarhus Business and Social Sciences, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark; Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
| | - Jørgen Brandt
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Camilla Geels
- Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | | | - Carsten B Pedersen
- National Centre for Register-Based Research, Aarhus Business and Social Sciences, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark; Centre for Integrated Register-based Research, Aarhus University, Aarhus, Denmark; Big Data Centre for Environment and Health, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Denmark
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Wei Q, Zhang X, Yi W, Pan R, Gao J, Duan J, Xu Z, Cheng Q, Bai L, Zhang Y, Su H. Association between floods and hospital admissions for schizophrenia in Hefei, China: The lag effects of degrees of floods and time variation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 698:134179. [PMID: 31514040 DOI: 10.1016/j.scitotenv.2019.134179] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Revised: 08/03/2019] [Accepted: 08/27/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Schizophrenia is a serious mental disorder, endangering 7.5 million patients in China. Floods, as the adverse consequence of temperature-rise, have a negative influence on mental health. However, the relationship between floods and schizophrenia is still insufficient. This study aimed to quantitative the relationship between floods and the admissions for schizophrenia in Hefei, China. METHODS A Poisson generalized linear model (GLM) combining a distributed lag non-linear model (DLNM) was used to quantify the lag effects of floods on schizophrenia and subgroups (male, female; ≤40 y, >40 y; the married, the unmarried) from 2005 to 2014, Hefei, China. We further explored the effects of different degrees (moderate and severe) of floods and their temporal changes on schizophrenia. RESULTS There was a significant association between floods and admissions risk for schizophrenia. And the lag effects for schizophrenia lasted ten days (lag 5-lag 14), with the greatest effect on lag 9 (RR = 1.036, 95% confidence interval (CI): 1.014-1.058). The married, ≤40 y were sensitive to floods. The significant difference wasn't found for genders. The effects of the severe flood were higher than moderate floods, with the largest RR of 1.073 (95%CI: 1.029-1.119). The adverse effects were found in the middle and late period with a decreasing trend in the later period. CONCLUSIONS This study suggests a significant association between floods and schizophrenia with ten days of lag effects in Hefei, China. Male, female, <40 y and the married are vulnerable to both moderate and severe floods. The findings might be used to allocate medical resources of mental health after floods.
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Affiliation(s)
- Qiannan 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
| | - Xulai Zhang
- Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, 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
| | - 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
| | - Jiaojiao Gao
- 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
| | - Jun Duan
- 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
| | - Zihan Xu
- 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
| | - Qiang 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
| | - Lijun Bai
- 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
| | - Yanwu Zhang
- 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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Pan R, Zhang X, Gao J, Yi W, Wei Q, Xu Z, Duan J, Bai L, Cheng Q, Zhang Y, Su H. Impacts of heat and cold on hospitalizations for schizophrenia in Hefei, China: An assessment of disease burden. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 694:133582. [PMID: 31394323 DOI: 10.1016/j.scitotenv.2019.133582] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 07/23/2019] [Accepted: 07/23/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND Compared with risk data (e.g., RR or OR), attributable fraction (AF) provides more information on the formulation of policies and measures in the field of public health. However, to date, existing AF evidence is scarce for the relationship between temperature and the hospitalizations for SCZ. OBJECTIVES Our primary goal is to estimate the attributable burden of hospitalizations for SCZ related to cold and heat, respectively. Furthermore, to identify vulnerable populations due to heat and cold. METHODS Poisson generalized linear models combined with DLNMs were used to estimate the association between hospitalizations for SCZ and temperature from 2005 to 2014. The minimum risk temperature (MRT) was used as a reference, to calculate the burden of disease caused by cold and heat. RESULTS We found that the majority hospitalizations attributed to heat (70.9%). In different individual levels, men are more sensitive to heat exposure while women are more vulnerable to cold. Among different age groups, the results showed that the attributable risk was slightly higher in the over-40s than in the under-40s. Besides, under different marital conditions, it showed that the unmarried had a little higher attributional risk than the married. CONCLUSIONS We should pay attention to the impact of heat on hospitalizations for SCZ, especially in those over 40 years old, men and non-married. Our research will provide a basis for policymakers to develop intervention strategies to minimize the impact of adverse temperatures on hospitalizations for SCZ, thereby reducing the burden of disease.
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Affiliation(s)
- 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 Disease, China
| | - Xulai Zhang
- Fourth People's Hospital of Hefei, Anhui, China
| | - Jiaojiao Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 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 Disease, China
| | - Qiannan 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 Disease, China
| | - Zihan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Jun Duan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Lijun Bai
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, China
| | - Qiang 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 Disease, China
| | - Yanwu Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Anhui Province Key Laboratory of Major Autoimmune Disease, 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 Disease, China.
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