1
|
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.
Collapse
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
| |
Collapse
|
2
|
Cheng Y, Meng Y, Li X, Yin J. Effects of ambient air pollution on the hospitalization risk and economic burden of mental disorders in Qingdao, China. Int Arch Occup Environ Health 2024; 97:109-120. [PMID: 38062177 DOI: 10.1007/s00420-023-02030-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 11/16/2023] [Indexed: 02/21/2024]
Abstract
OBJECTIVE The aim of this study was to examine the impacts of short-term exposure to air pollutants on hospitalizations for mental disorders (MDs) in Qingdao, a Chinese coastal city, and to assess the corresponding hospitalization risk and economic cost. METHODS Daily data on MD hospitalizations and environmental variables were collected from January 1, 2015, to December 31, 2019. An overdispersed generalized additive model was used to estimate the association between air pollution and MD hospitalizations. The cost of illness method was applied to calculate the corresponding economic burden. RESULTS With each 10 μg/m3 increase in the concentration of fine particulate matter (PM2.5) at lag05, inhalable particulate matter (PM10) at lag0, sulfur dioxide (SO2) at lag06 and ozone (O3) at lag0, the corresponding relative risks (RRs) and 95% confidence intervals (CIs) were 1.0182 (1.0035-1.0332), 1.0063 (1.0001-1.0126), 1.0997 (1.0200-1.1885) and 1.0099 (1.0005-1.0194), respectively. However, no significant effects of nitrogen dioxide (NO2) or carbon monoxide (CO) were found. Stratified analysis showed that males were susceptible to SO2 and O3, while females were susceptible to PM2.5. Older individuals (≥ 45 years) were more vulnerable to air pollutants (PM2.5, PM10, SO2 and O3) than younger individuals (< 45 years). Taking the Global Air Quality Guidelines 2021 as a reference, 8.71% (2,168 cases) of MD hospitalizations were attributable to air pollutant exposure, with a total economic burden of 154.36 million RMB. CONCLUSION Short-term exposure to air pollution was associated with an increased risk of hospitalization for MDs. The economic advantages of further reducing air pollution are enormous.
Collapse
Affiliation(s)
- Yuanyuan Cheng
- Qingdao Mental Health Center, 299 Nanjing Road, Qingdao, Shandong, China
| | - Yujie Meng
- Qingdao Mental Health Center, 299 Nanjing Road, Qingdao, Shandong, China
| | - Xiao Li
- Qingdao Mental Health Center, 299 Nanjing Road, Qingdao, Shandong, China
| | - Junbo Yin
- Qingdao Mental Health Center, 299 Nanjing Road, Qingdao, Shandong, China.
| |
Collapse
|
3
|
Zhang Y, Hu M, Xiang B, Yu H, Wang Q. Urban-rural disparities in the association of nitrogen dioxide exposure with cardiovascular disease risk in China: effect size and economic burden. Int J Equity Health 2024; 23:22. [PMID: 38321458 PMCID: PMC10845777 DOI: 10.1186/s12939-024-02117-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 01/23/2024] [Indexed: 02/08/2024] Open
Abstract
BACKGROUND Together with rapid urbanization, ambient nitrogen dioxide (NO2) exposure has become a growing health threat. However, little is known about the urban-rural disparities in the health implications of short-term NO2 exposure. This study aimed to compare the association between short-term NO2 exposure and hospitalization for cardiovascular disease (CVD) among urban and rural residents in Shandong Province, China. Then, this study further explored the urban-rural disparities in the economic burden attributed to NO2 and the explanation for the disparities. METHODS Daily hospitalization data were obtained from an electronic medical records dataset covering a population of 5 million. In total, 303,217 hospital admissions for CVD were analyzed. A three-stage time-series analytic approach was used to estimate the county-level association and the attributed economic burden. RESULTS For every 10-μg/m3 increase in NO2 concentrations, this study observed a significant percentage increase in hospital admissions on the day of exposure of 1.42% (95% CI 0.92 to 1.92%) for CVD. The effect size was slightly higher in urban areas, while the urban-rural difference was not significant. However, a more pronounced displacement phenomenon was found in rural areas, and the economic burden attributed to NO2 was significantly higher in urban areas. At an annual average NO2 concentration of 10 μg/m3, total hospital days and expenses in urban areas were reduced by 81,801 (44,831 to 118,191) days and 60,121 (33,002 to 86,729) thousand CNY, respectively, almost twice as much as in rural areas. Due to disadvantages in socioeconomic status and medical resources, despite similar air pollution levels in the urban and rural areas of our sample sites, the rural population tended to spend less on hospitalization services. CONCLUSIONS Short-term exposure to ambient NO2 could lead to considerable health impacts in either urban or rural areas of Shandong Province, China. Moreover, urban-rural differences in socioeconomic status and medical resources contributed to the urban-rural disparities in the economic burden attributed to NO2 exposure. The health implications of NO2 exposure are a social problem in addition to an environmental problem. Thus, this study suggests a coordinated intervention system that targets environmental and social inequality factors simultaneously.
Collapse
Affiliation(s)
- Yike Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Mengxiao Hu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Bowen Xiang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Haiyang Yu
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, China
| | - Qing Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- National Institute of Health Data Science of China, Shandong University, Jinan, China.
| |
Collapse
|
4
|
Pan R, Song J, Yi W, Liu J, Song R, Li X, Liu L, Yuan J, Wei N, Cheng J, Huang Y, Zhang X, Su H. Heatwave characteristics complicate the association between PM 2.5 components and schizophrenia hospitalizations in a changing climate: Leveraging of the individual residential environment. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 271:115973. [PMID: 38219619 DOI: 10.1016/j.ecoenv.2024.115973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/07/2024] [Accepted: 01/08/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND In the era characterized by global environmental and climatic changes, understanding the effects of PM2.5 components and heatwaves on schizophrenia (SCZ) is essential for implementing environmental interventions at the population level. However, research in this area remains limited, which highlights the need for further research and effort. We aim to assess the association between exposure to PM2.5 components and hospitalizations for SCZ under different heatwave characteristics. METHODS We conducted a 16 municipalities-wide, individual exposure-based, time-stratified, case-crossover study from January 1, 2017, to December 31, 2020, encompassing 160736 hospitalizations in Anhui Province, China. Daily concentrations of PM2.5 components were obtained from the Tracking Air Pollution in China dataset. Conditional logistic regression models were used to investigate the association between PM2.5 components and hospitalizations. Additionally, restricted cubic spline models were used to identify protective thresholds of residential environment in response to environmental and climate change. RESULTS Our findings indicate a positive correlation between PM2.5 and its components and hospitalizations. Significantly, a 1 μg/m3 increase in black carbon (BC) was associated with the highest risk, at 1.58% (95%CI: 0.95-2.25). Exposure to heatwaves synergistically enhanced the impact of PM2.5 components on hospitalization risks, and the interaction varied with the intensity and duration of heatwaves. Under the 99th percentile heatwave events, the impact of PM2.5 and its components on hospitalizations was most pronounced, which were PM2.5 (2-4d: 4.59%, 5.09%, and 5.09%), sulfate (2-4d: 21.73%, 23.23%, and 25.25%), nitrate (2-4d: 17.51%, 16.93%, and 20.31%), ammonium (2-4d: 27.49%, 31.03%, and 32.41%), organic matter (2-4d: 32.07%, 25.42%, and 24.48%), and BC (2-4d: 259.36%, 288.21%, and 152.52%), respectively. Encouragingly, a protective effect was observed when green and blue spaces comprised more than 17.6% of the residential environment. DISCUSSION PM2.5 components and heatwave exposure were positively associated with an increased risk of hospitalizations, although green and blue spaces provided a mitigating effect.
Collapse
Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Yuee Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, 241002 Wuhu, Anhui, China
| | - Xulai Zhang
- Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China.
| |
Collapse
|
5
|
Xu X, Zhang W, Shi X, Su Z, Cheng W, Wei Y, Ma H, Li T, Wang Z. China's air quality improvement strategy may already be having a positive effect: evidence based on health risk assessment. Front Public Health 2023; 11:1250572. [PMID: 37927881 PMCID: PMC10624126 DOI: 10.3389/fpubh.2023.1250572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 09/15/2023] [Indexed: 11/07/2023] Open
Abstract
Aiming to investigate the health risk impact of PM2.5 pollution on a heavily populated province of China. The exposure response function was used to assess the health risk of PM2.5 pollution. Results shows that the total number of premature deaths and diseases related to PM2.5 pollution in Shandong might reach 159.8 thousand people based on the new WHO (2021) standards. The health effects of PM2.5 pollution were more severe in men than in women. Five of the 16 cities in Shandong had higher health risks caused by PM2.5 pollution, including LinYi, HeZe, JiNing, JiNan, and WeiFang. PM2.5 pollution resulted in nearly 7.4 billions dollars in healthy economic cost, which accounted for 0.57% of GDP in Shandong in 2021. HeZe, LiaoCheng, ZaoZhuang, and LinYi were the cities where the health economic loss was more than 1% of the local GDP, accounted for 1.30, 1.26, 1.08, and 1.04%. Although the more rigorous assessment criteria, the baseline concentration was lowered by 30 μg/m3 compared to our previous study, there was no significant increase in health risks and economic losses. China's air quality improvement strategy may already be having a positive effect.
Collapse
Affiliation(s)
- Xianmang Xu
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
- Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Institute of Atmospheric Sciences, Fudan University, Shanghai, China
| | - Wen Zhang
- Department of Clinical Medicine, Heze Medical College, Heze, China
| | - Xiaofeng Shi
- Department of Clinical Medicine, Heze Medical College, Heze, China
| | - Zhi Su
- Heze Ecological Environment Monitoring Center of Shandong Province, Heze, China
| | - Wei Cheng
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - Yinuo Wei
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - He Ma
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - Tinglong Li
- Heze Branch, Biological Engineering Technology Innovation Center of Shandong Province, Qilu University of Technology (Shandong Academy of Sciences), Heze, China
| | - Zhenhua Wang
- Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| |
Collapse
|
6
|
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.
Collapse
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
| |
Collapse
|
7
|
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: 2.0] [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.
Collapse
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.
| |
Collapse
|