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Wu H, Liu J, Conway E, Zhan N, Zheng L, Sun S, Li J. Fine particulate matter components associated with exacerbated depressive symptoms among middle-aged and older adults in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174228. [PMID: 38914329 DOI: 10.1016/j.scitotenv.2024.174228] [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: 03/07/2024] [Revised: 05/22/2024] [Accepted: 06/21/2024] [Indexed: 06/26/2024]
Abstract
Growing awareness acknowledges ambient fine particulate matter (PM2.5) as an environmental risk factor for mental disorders, especially among older people. However, there remains limited evidence regarding which specific chemical components of PM2.5 may be more detrimental. This nationwide prospective cohort study included 22,126 middle-aged and older adult participants of the China Health and Retirement Longitudinal Study (CHARLS, 2011-2016), to explore the individual and joint associations between long-term exposure to various PM2.5 components (sulfate, nitrate, ammonium, organic matter, and black carbon) and depressive symptoms. The depressive symptoms were assessed using the 10-item Center for Epidemiological Studies-Depression Scale (CES-D-10). Using the novel quantile-based g-computation for multi-pollutant mixture analysis, we found that exposure to the mixture of major PM2.5 components was significantly associated with aggravating depressive symptoms, with the exposure-response curve exhibiting consistent linear or supra-linear shape without a lower threshold. The estimated weight index indicated that, among major PM2.5 components, only nitrate, sulfate, and black carbon significantly contributed to the exacerbation of depressive symptoms. Given the expanding aging population, stricter regulation on the emissions of particularly toxic PM2.5 components may mitigate the escalating disease burden of depression.
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Affiliation(s)
- Haisheng Wu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Jiaqi Liu
- Department of Mathematics, Faculty of Science, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Erica Conway
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | - Na Zhan
- Department of Psychiatry, School of Clinical Medicine, The University of Hong Kong, Hong Kong Special Administrative Region of China
| | | | - Shengzhi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing, China.
| | - Jinhui Li
- Department of Urology, Stanford University Medical Center, Stanford, CA, USA.
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Tao C, Liu Z, Fan Y, Yuan Y, Wang X, Qiao Z, Li Z, Xu Q, Lou Z, Wang H, Li X, Li R, Lu C. Estimating neighborhood-based mortality risk associated with air pollution: A prospective study. JOURNAL OF HAZARDOUS MATERIALS 2024; 475:134861. [PMID: 38870855 DOI: 10.1016/j.jhazmat.2024.134861] [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: 04/08/2024] [Revised: 06/06/2024] [Accepted: 06/07/2024] [Indexed: 06/15/2024]
Abstract
Effect modification of integrated neighborhood environment on associations of air pollution with mortality remained unclear. We analyzed data from UK biobank prospective study (n = 421,650, median 12.5 years follow-up) to examine disparities of mortality risk associated with air pollution among varied neighborhood settings. Fine particulate matter (PM2.5), PM10 and nitrogen dioxide (NO2) were measured and assigned to each participants' address. Diverse ecological and societal settings of neighborhoods were integrated with principal component analysis and categorized into disadvantaged, intermediate and advantaged levels. We estimated mortality risk associated with air pollution across diverse neighborhoods using Cox regression. We calculated community-level proportions of mortality attributable to air pollutants. There was evidence of higher all-cause and respiratory disease mortality risk associated with PM2.5 and NO2 among those in disadvantaged neighborhoods. In disadvantaged communities, air pollutants explained larger proportions of deaths and such disparities persisted over past decades. Across 2010-2021, reducing PM2.5 and NO2 to 10 μg/m3 (World Health Organization limits) would save 87,000 (52,000-120,000) and 91,000 (37,000-145,000) deaths of populations aged ≥ 40 years, with 150 000 deaths occurred in disadvantaged neighborhood settings. These findings suggested that disadvantaged neighborhoods can exacerbate mortality risk associated with air pollution.
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Affiliation(s)
- Chengzhe Tao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhaoyin Liu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yun Fan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yiting Yuan
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xinru Wang
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Ziyan Qiao
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhi Li
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Qiaoqiao Xu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Zhe Lou
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Haowei Wang
- School of Public Health, Imperial College London, UK; MRC Centre for Global Infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
| | - Xiang Li
- School of Public Health, Imperial College London, UK; MRC Centre for Global Infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, UK
| | - Ruiyun Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
| | - Chuncheng Lu
- State Key Laboratory of Reproductive Medicine and Offspring Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing 211166, China.
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3
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Yuan W, Yang T, Chen L, Zhang Y, Liu J, Song X, Jiang J, Qin Y, Wang R, Guo T, Song Z, Zhang X, Dong Y, Song Y, Ma J. Sufficient sleep and physical activity can relieve the effects of long-term exposure to particulate matter on depressive symptoms among 0.31 million children and adolescents from 103 counties in China. J Affect Disord 2024; 364:116-124. [PMID: 39142569 DOI: 10.1016/j.jad.2024.08.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 07/04/2024] [Accepted: 08/09/2024] [Indexed: 08/16/2024]
Abstract
BACKGROUND Although long-term exposures to air pollutants have been linked to mental disorders, existing studies remain limited and inconsistent. We investigated the relationship between exposure to particulate matter (PM) and depressive symptoms, as well as the potential role of sleep duration and physical activity. METHOD Using the surveillance data (2019 to 2022) of common diseases and risk factors among 312,390 students aged 10-25 years, logistic regression, generalized liner model (GLM) and restricted cubic spline (RCS) were employed to investigate the relationship between long-term exposure to PM and depressive symptoms. RESULT Significant associations were found between PM1 (OR = 1.21, 95 % CI: 1.12-1.32), PM2.5 (OR = 1.24, 95 % CI: 1.19-1.38), and PM10 (OR = 1.87, 95 % CI: 1.69-2.07) and increased risks of depressive symptoms. Sleep duration and physical activity relieved these associations. The odds ratios (ORs) of PM1, PM2.5, and PM10 on depressive symptoms were lower in group with sufficient sleep (1.02 vs. 1.49, 1.20 vs. 1.80, 2.15 vs. 2.23), lower in group with high level MVPA (1.13 vs. 1.48, 1.14 vs. 1.58, 1.85 vs. 2.38), and lower in group with high level outdoor activity (1.19 vs. 1.55, 1.23 vs. 1.63, 1.83 vs. 2.72). LIMITATIONS Conclusions about causality remain speculative because of the cross-sectional design. CONCLUSION Sufficient sleep duration and outdoor activity may mitigate the decline in mental health among adults in developing countries caused by long-term exposure to PM. This contribution enhanced our understanding of the mechanisms linking air pollution to mental health.
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Affiliation(s)
- Wen Yuan
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Tian Yang
- Inner Mongolia Autonomous Region Center for Comprehensive Disease Control and Prevention, Huhhot 010030, China
| | - Li Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Yi Zhang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Jieyu Liu
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Xinli Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Jianuo Jiang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Yang Qin
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Ruolin Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Tongjun Guo
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Zhiying Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
| | - Xiuhong Zhang
- Inner Mongolia Autonomous Region Center for Comprehensive Disease Control and Prevention, Huhhot 010030, China.
| | - Yanhui Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China.
| | - Yi Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China.
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University, Beijing 100191, China
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He G, Jiang M, Tian S, He L, Bai X, Chen S, Li G, Wang C, Zhang Z, Wu Y, Su M, Li X, Guo X, Yang Y, Zhang X, Cui J, Xu W, Song L, Yang H, He W, Zhang Y, Li X, Gao X, Chen L. Clean air policy reduces the atherogenic lipid profile levels: Results from China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) Study. JOURNAL OF HAZARDOUS MATERIALS 2024; 478:135394. [PMID: 39128148 DOI: 10.1016/j.jhazmat.2024.135394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/16/2024] [Accepted: 07/30/2024] [Indexed: 08/13/2024]
Abstract
Evidence of the associations between long-term exposure to PM2.5 and O3 and human blood lipid concentrations is abundant yet inconclusive. Whether clean air policies could improve lipid profiles remains unclear. In total, 2979312 participants from a Chinese nationwide prospective study were included. For cross-sectional analyses, linear mixed-effects models were utilized to assess the associations of pollutants with lipid profiles (TC, LDL-C, TG, HDL-C). For longitudinal analyses, a quasi-experimental design and difference-in-differences models were employed to investigate the impact of China's Clean Air Act. In the cross-sectional analyses, each IQR increase in PM2.5 was associated with 2.49 % (95 % CI: 2.36 %, 2.62 %), 2.51 % (95 % CI: 2.26 %, 2.75 %), 3.94 % (95 % CI: 3.65 %, 4.23 %), and 1.54 % (95 % CI: 1.38 %, 1.70 %) increases in TC, LDL-C, TG, and HDL-C, respectively. For each IQR increase in O3, TC, LDL-C, TG, and HDL-C changed by 1.06 % (95 % CI: 0.95 %, 1.17 %), 1.21 % (95 % CI: 1.01 %, 1.42 %), 1.78 % (95 % CI: 1.54 %, 2.02 %), and -0.63 % (95 % CI: -0.76 %, -0.49 %), respectively. Longitudinal analyses showed that the intervention group experienced greater TC, LDL-C, and HDL-C reductions (1.77 %, 4.26 %, and 7.70 %, respectively). Our findings suggest that clean air policies could improve lipid metabolism and should be implemented in countries with heavy air pollution burdens.
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Affiliation(s)
- Guangda He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Meijie Jiang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Sifan Tian
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China
| | - Linkang He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xueke Bai
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Shi Chen
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Guangyu Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; 4+4 Medical Doctor Program, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Chunqi Wang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zenglei Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yi Wu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Mingming Su
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiangjie Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xinxin Guo
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yang Yang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaoyan Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianlan Cui
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wei Xu
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lijuan Song
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hao Yang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wenyan He
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yan Zhang
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xi Li
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China.
| | - Liang Chen
- National Clinical Research Center for Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Ha YW, Kim TH, Kang DR, Park KS, Shin DC, Cho J, Kim C. Estimation of Attributable Risk and Direct Medical and Non-Medical Costs of Major Mental Disorders Associated With Air Pollution Exposures Among Children and Adolescents in the Republic of Korea, 2011-2019. J Korean Med Sci 2024; 39:e218. [PMID: 39106887 PMCID: PMC11301008 DOI: 10.3346/jkms.2024.39.e218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Accepted: 06/21/2024] [Indexed: 08/09/2024] Open
Abstract
BACKGROUND Recent studies have reported the burden of attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and depressive disorder. Also, there is mounting evidence on the effects of environmental factors, such as ambient air pollution, on these disorders among children and adolescents. However, few studies have evaluated the burden of mental disorders attributable to air pollution exposure in children and adolescents. METHODS We estimated the risk ratios of major mental disorders (ADHD, ASD, and depressive disorder) associated with air pollutants among children and adolescents using time-series data (2011-2019) obtained from a nationwide air pollution monitoring network and healthcare utilization claims data in the Republic of Korea. Based on the estimated risk ratios, we determined the population attributable fraction (PAF) and calculated the medical costs of major mental disorders attributable to air pollution. RESULTS A total of 33,598 patients were diagnosed with major mental disorders during 9 years. The PAFs for all the major mental disorders were estimated at 6.9% (particulate matter < 10 μm [PM10]), 3.7% (PM2.5), and 2.2% (sulfur dioxide [SO2]). The PAF of PM10 was highest for depressive disorder (9.2%), followed by ASD (8.4%) and ADHD (5.2%). The direct medical costs of all major mental disorders attributable to PM10 and SO2 decreased during the study period. CONCLUSION This study assessed the burden of major mental disorders attributable to air pollution exposure in children and adolescents. We found that PM10, PM2.5, and SO2 attributed 7%, 4%, and 2% respectively, to the risk of major mental disorders among children and adolescents.
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Affiliation(s)
- Yae Won Ha
- Department of Public Health, Yonsei University College of Medicine, Seoul, Korea
| | - Tae Hyun Kim
- Department of Healthcare Management, Graduate School of Public Health, Yonsei University, Seoul, Korea
| | - Dae Ryong Kang
- Department of Precision Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
| | - Ki-Soo Park
- Department of Preventive Medicine and Institute of Medical Sciences, College of Medicine, Gyeongsang National University, Jinju, Korea
| | - Dong Chun Shin
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Korea
| | - Jaelim Cho
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.
| | - Changsoo Kim
- Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
- Institute for Environmental Research, Yonsei University College of Medicine, Seoul, Korea.
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Zhou Y, Li X, Fouxi Zhao, Yao C, Wang Y, Tang E, Wang K, Li D, Yu L, Zhou Z, Wei J, Li D, Liu T, Cai T. Rural-urban difference in the association between particulate matters and stroke incidence: the evidence from a multi-city perspective cohort study. ENVIRONMENTAL RESEARCH 2024:119695. [PMID: 39102936 DOI: 10.1016/j.envres.2024.119695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 07/15/2024] [Accepted: 07/26/2024] [Indexed: 08/07/2024]
Abstract
Available evidence suggests that air pollutants can cause stroke, but little research has investigated the confounding effects of urban-rural differences. Here, we investigated the urban-rural difference in the correlation between particulate matter (PM2.5 and PM10) exposure and stroke. This cohort study was based on a prospective multi-city community-based cohort (Guizhou Population Health Cohort Study (GPHCS)) in Guizhou Province, China. A total of 7,988 eligible individuals (≥18 years) were enrolled with baseline assessments from November 2010 to December 2012, and follow-up was completed by June 2020. Two major particulate matters (PMs, including PM2.5 and PM10) were assessed monthly from 2000 by using satellite-based spatiotemporal models. The risk of stroke was estimated using a Cox proportional hazard regression model. The association between particulate matters' exposure and stroke in different areas (total, urban, and rural) and the potential modification effect of comorbidities (hypertension, diabetes, and dyslipidemia) and age (≤65 / >65 years) were examined using stratified analyses. The risk of stroke increased for every 10 μg/m3 increase in mean PMs' concentrations during the previous one year at the residential address (HR: 1.26, 95%CI: 1.24, 1.29 (PM2.5); HR: 1.13, 95%CI: 1.11, 1.15 (PM10)). The presence of diabetes and dyslipidemia increased the risk of PM10-induced stroke in whole, urban, and rural areas. Specifically, people living in rural areas were more likely to experience the effects of PMs in causing a stroke. The risk of stroke due to PMs was statistically increased in the young and older populations living in rural areas. In conclusion, long-term exposure to PMs increased the risk of stroke and such association was more pronounced in people living in rural areas with lower income levels. Diabetes and dyslipidemia seemed to strengthen the association between PMs and stroke.
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Affiliation(s)
- Yumeng Zhou
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Xuejiao Li
- Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, China
| | - Fouxi Zhao
- Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, China
| | - Chunyan Yao
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Yiying Wang
- Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, China
| | - Enjie Tang
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Kexue Wang
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Dawei Li
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Lisha Yu
- Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, China
| | - Zhujuan Zhou
- Department of Neurology, Xinqiao Hospital, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland 20742, United States
| | - Dawei Li
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China
| | - Tao Liu
- Guizhou Center for Disease Control and Prevention, Guiyang, Guizhou, 550004, China.
| | - Tongjian Cai
- Department of Epidemiology, College of Preventive Medicine, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Chongqing, 400038, China.
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7
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Sun X, Ma S, Guo Y, Chen C, Pan L, Cui Y, Chen Z, Dijkhuizen RM, Zhou Y, Boltze J, Yu Z, Li P. The association between air pollutant exposure and cerebral small vessel disease imaging markers with modifying effects of PRS-defined genetic susceptibility. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 281:116638. [PMID: 38944013 DOI: 10.1016/j.ecoenv.2024.116638] [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: 04/09/2024] [Revised: 06/20/2024] [Accepted: 06/21/2024] [Indexed: 07/01/2024]
Abstract
Studies have highlighted a possible link between air pollution and cerebral small vessel disease (CSVD) imaging markers. However, the exact association and effects of polygenic risk score (PRS) defined genetic susceptibility remains unclear. This cross-sectional study used data from the UK Biobank. Participants aged 40-69 years were recruited between the year 2006 and 2010. The annual average concentrations of NOX, NO2, PM2.5, PM2.5-10, PM2.5 absorbance, and PM10, were estimated, and joint exposure to multiple air pollutants was reflected in the air pollution index (APEX). Air pollutant exposure was classified into the low (T1), intermediate (T2), and high (T3) tertiles. Three CSVD markers were used: white matter hyper-intensity (WMH), mean diffusivity (MD), and fractional anisotropy (FA). The first principal components of the MD and FA measures in the 48 white matter tracts were analysed. The sample consisted of 44,470 participants from the UK Biobank. The median (T1-T3) concentrations of pollutants were as follows: NO2, 25.5 (22.4-28.7) μg/m3; NOx, 41.3 (36.2-46.7) μg/m3; PM10, 15.9 (15.4-16.4) μg/m3; PM2.5, 9.9 (9.5-10.3) μg/m3; PM2.5 absorbance, 1.1 (1.0-1.2) per metre; and PM2.5-10, 6.1 (5.9-6.3) μg/m3. Compared with the low group, the high group's APEX, NOX, and PM2.5 levels were associated with increased WMH volumes, and the estimates (95 %CI) were 0.024 (0.003, 0.044), 0.030 (0.010, 0.050), and 0.032 (0.011, 0.053), respectively, after adjusting for potential confounders. APEX, PM10, PM2.5 absorbance, and PM2.5-10 exposure in the high group were associated with increased FA values compared to that in the low group. Sex-specific analyses revealed associations only in females. Regarding the combined associations of air pollutant exposure and PRS-defined genetic susceptibility with CSVD markers, the associations of NO2, NOX, PM2.5, and PM2.5-10 with WMH were more profound in females with low PRS-defined genetic susceptibility, and the associations of PM10, PM2.5, and PM2.5 absorbance with FA were more profound in females with higher PRS-defined genetic susceptibility. Our study demonstrated that air pollutant exposure may be associated with CSVD imaging markers, with females being more susceptible, and that PRS-defined genetic susceptibility may modify the associations of air pollutants.
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Affiliation(s)
- Xiaowei Sun
- Clinical Research Center, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Shiyang Ma
- Clinical Research Center, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yunlu Guo
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Caiyang Chen
- Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Lijun Pan
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Yidan Cui
- Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zengai Chen
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Rick M Dijkhuizen
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Yan Zhou
- Department of Radiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China
| | - Johannes Boltze
- School of Life Sciences, University of Warwick, Coventry, UK.
| | - Zhangsheng Yu
- Clinical Research Institute, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
| | - Peiying Li
- Clinical Research Center, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Department of Anesthesiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China; Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Outcomes Research Consortium, Cleveland, OH, United States.
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Chen HW, Huang RD, Li LH, Zhou R, Cao BF, Liu K, Wang SA, Zhong Q, Wei YF, Wu XB. Impact of healthy lifestyle on the incidence and progression trajectory of mental disorders: A prospective study in the UK Biobank. J Affect Disord 2024; 358:383-390. [PMID: 38735583 DOI: 10.1016/j.jad.2024.05.054] [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: 03/29/2024] [Revised: 05/08/2024] [Accepted: 05/09/2024] [Indexed: 05/14/2024]
Abstract
BACKGROUND Healthier lifestyle decreased the risk of mental disorders (MDs) such as depression and anxiety. However, research on the effects of a comprehensive healthy lifestyle on their progression is lacking. METHODS 385,704 individuals without baseline MDs from the UK Biobank cohort were included. A composite healthy lifestyle score was computed by assessing alcohol intake, smoking status, television viewing time, physical activity, sleep duration, fruit and vegetable intake, oily fish intake, red meat intake, and processed meat intake. Follow-up utilized hospital and death register records. Multistate model was used to examine the role of healthy lifestyle on the progression of specific MDs, while a piecewise Cox regression model was utilized to assess the influence of healthy lifestyle across various phases of disease progression. RESULTS Higher lifestyle score reduced risks of transitions from baseline to anxiety and depression, as well as from anxiety and depression to comorbidity, with corresponding hazard ratios (HR) and 95 % confidence intervals (CI) of 0.94 (0.93, 0.95), 0.90 (0.89, 0.91), 0.94 (0.91, 0.98), and 0.95 (0.92, 0.98), respectively. Healthier lifestyle decreased the risk of transitioning from anxiety to comorbidity within 2 years post-diagnosis, with HR 0.93 (0.88, 0.98). Higher lifestyle scores at 2-4 years and 4-6 years post-depression onset were associated with reduced risk of comorbidity, with HR 0.93 (0.87, 0.99) and 0.92 (0.86, 0.99), respectively. LIMITATION The generalizability to other ethnic groups is limited. CONCLUSION This study observed a protective role of holistic healthy lifestyle in the trajectory of MDs and contributed to identifying critical progression windows.
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Affiliation(s)
- Hao-Wen Chen
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Rui-Dian Huang
- Public Health Division, Hospital of Zhongluotan Town, Baiyun District, Guangzhou 510515, China
| | - Liang-Hua Li
- Public Health Division, Hospital of Zhongluotan Town, Baiyun District, Guangzhou 510515, China
| | - Rui Zhou
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Bi-Fei Cao
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Kuan Liu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Shi-Ao Wang
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Qi Zhong
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Yan-Fei Wei
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China
| | - Xian-Bo Wu
- Department of Epidemiology, School of Public Health, Southern Medical University (Guangdong Provincial Key Laboratory of Tropical Disease Research), Guangzhou 510515, China.
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Fu L, Cai M, Zhao Y, Zhang Z, Qian Q, Xue H, Chen Y, Sun Z, Zhao Q, Wang S, Wang C, Wang W, Jiang Y, Tian Y, Ma J, Guo W, Liu F. Twenty-five years of research on resting-state fMRI of major depressive disorder: A bibliometric analysis of hotspots, nodes, bursts, and trends. Heliyon 2024; 10:e33833. [PMID: 39050435 PMCID: PMC11266997 DOI: 10.1016/j.heliyon.2024.e33833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 06/15/2024] [Accepted: 06/27/2024] [Indexed: 07/27/2024] Open
Abstract
Major depressive disorder (MDD) is a debilitating mental health condition that poses significant risks and burdens. Resting-state functional magnetic resonance imaging (fMRI) has emerged as a promising tool in investigating the neural mechanisms underlying MDD. However, a comprehensive bibliometric analysis of resting-state fMRI in MDD is currently lacking. Here, we aimed to thoroughly explore the trends and frontiers of resting-state fMRI in MDD research. The relevant publications were retrieved from the Web of Science database for the period between 1998 and 2022, and the CiteSpace software was employed to identify the influence of authors, institutions, countries/regions, and the latest research trends. A total of 1501 publications met the search criteria, revealing a gradual increase in the number of annual publications over the years. China contributed the largest publication output, accounting for the highest percentage among all countries. Particularly, the University of Electronic Science and Technology of China, Capital Medical University, and Harvard Medical School were identified as key institutions that have made substantial contributions to this growth. Neuroimage, Biological Psychiatry, Journal of Affective Disorders, and Proceedings of the National Academy of Sciences of the United States of America are among the influential journals in the field of resting-state fMRI research in MDD. Burst keywords analysis suggest the emerging research frontiers in this field are characterized by prominent keywords such as dynamic functional connectivity, cognitive control network, transcranial brain stimulation, and childhood trauma. Overall, our study provides a systematic overview into the historical development, current status, and future trends of resting-state fMRI in MDD, thus offering a useful guide for researchers to plan their future research.
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Affiliation(s)
- Linhan Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300070, China
| | - Mengjing Cai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yao Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Qian Qian
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Qiyu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Chunyang Wang
- Department of Scientific Research, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wenqin Wang
- School of Mathematical Sciences, Tianjin Polytechnic University, Tianjin, 300387, China
| | - Yifan Jiang
- School of Nursing, Tianjin Medical University, Tianjin, 300070, China
| | - Yuxuan Tian
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300070, China
| | - Juanwei Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
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Zhang Q, Meng X, Luo H, Yu K, Li A, Zhou L, Chen R, Kan H. Air pollutants, genetic susceptibility, and incident schizophrenia in later life: A prospective study in the UK Biobank. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 934:173009. [PMID: 38734111 DOI: 10.1016/j.scitotenv.2024.173009] [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: 12/21/2023] [Revised: 04/10/2024] [Accepted: 05/03/2024] [Indexed: 05/13/2024]
Abstract
OBJECTIVE Air pollution has been linked to multiple psychiatric disorders, but little is known on its long-term association with schizophrenia. The interaction between air pollution and genetic susceptibility on incident schizophrenia has never been reported. We aimed to explore the associations between long-term air pollution exposure and late-onset schizophrenia and evaluate whether genetic susceptibility could modify the association. METHODS This population-based prospective cohort study included 437,802 middle-aged and elderly individuals free of schizophrenia at baseline in the UK Biobank. Land use regression models were applied in the estimation of the annual average concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), fine particulate matter (PM2.5), and inhalable particulate matter (PM10) at residence. The associations between air pollutants and schizophrenia were evaluated by using Cox proportional hazard models. A polygenic risk score of schizophrenia was constructed for exploring potential interaction of air pollutants with genetic susceptibility. RESULTS An interquartile range increase in PM2.5, PM10, NO2, and NOx was associated with the hazard ratios (HR) for incident schizophrenia at 1.19, 1.16, 1.22, and 1.09, respectively. The exposure-response curves for the association of air pollution with incident schizophrenia were approximately linear. There are additive interactions of air pollution score (APS), PM10, NO2, and NOx with genetic risk. Specifically, compared with participants with low genetic susceptibility and low APS, the HR was 3.23 for individuals with high genetic risk and high APS, among which 0.49 excess risk could be attributed to the additive interaction, accounting for 15 % of the schizophrenia risk. CONCLUSION This large-scale, prospective cohort study conveys the first-hand evidence that long-term air pollution exposure could elevate schizophrenia incidence in later life, especially for individuals with higher genetic risks. The findings highlight the importance of improving air quality for preventing the late-onset schizophrenia in an aging era, especially among those with high genetic risks.
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Affiliation(s)
- Qingli Zhang
- 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; Ministry of Education - Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xia Meng
- 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
| | - Huihuan Luo
- 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
| | - Kexin Yu
- 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
| | - Anni Li
- 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
| | - 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
| | - Renjie 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; School of Public Health, University of South China, Hengyang, Hunan, China; School of Public Health, Hengyang Medical School, University of South China, Hengyang, Hunan, China..
| | - Haidong Kan
- 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; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China.
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Min Y, Wei X, Yang C, Duan Z, Yang J, Ju K, Peng X. Associations and attributable burdens in late-life exposure to PM 2.5 and its major components and depressive symptoms in middle-aged and older adults: A nationwide cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 280:116531. [PMID: 38852465 DOI: 10.1016/j.ecoenv.2024.116531] [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: 12/06/2023] [Revised: 04/21/2024] [Accepted: 05/29/2024] [Indexed: 06/11/2024]
Abstract
BACKGROUND Depression in late life has been associated with reduced quality of life and increased mortality. Whether the chronic fine particular matter (PM2.5) and its components exposure are contributed to the older depression symptoms remains unclear. METHOD Middle-aged and older adults (>45 years) were selected from the China Health and Retirement Longitudinal Study during the four waves of interviews. The concentrations of PM2.5 and its major constituents were calculated using near real-time data at a spatial resolution of 10 km during the study period. The depressive symptom was evaluated by the Depression Center for Epidemiologic Studies Depression (CES-D)-10 score. The fix-effect model was applied to evaluate the association between PM2.5 and its major constituents with depressive symptoms. Three three-step methods were used to explore the modification role of sleep duration against the depressive symptoms caused by PM2.5 exposure. RESULTS In our study, a total of 52,683 observations of 16,681 middle-aged and older adults were assessed. Each interquartile range (IQR) level of PM2.5 concentration exposure was longitudinally associated with a 2.6 % (95 % confidence interval [CI]: 1.3 %, 4.0 %) increase in the depression CES-D-10 score. Regarding the major components of PM2.5, OM, NO3-, and NH4+ showed the leading toxicity effects, which could increase the depression CES-D-10 score by 2.2 % (95 %CI: 1.0 %, 3.4 %), 2.2 % (0.6 %, 3.9 %), and 2.0 % (95 %CI: 0.6 %, 3.4 %) correspondingly. Besides, males were more susceptible to the worse depressive symptoms caused by PM2.5 and its major components exposure than female subpopulations. Shortened sleep duration might be the mediator of PM2.5-associated depressive symptoms. CONCLUSION Our results suggest that long-term exposure to PM2.5 and its major components were associated with an increased risk for depressive symptoms in middle-aged and older adults. Reducing the leading components of PM2.5 may cost-effectively alleviate the disease burden of depression and promote healthy longevity in heavy pollutant countries.
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Affiliation(s)
- Yu Min
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoyuan Wei
- Department of Head and Neck Oncology, Department of Radiation Oncology, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Chenyu Yang
- Department of Big Data in Health Science, School of Public Health, and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Zhongxin Duan
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Jingguo Yang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Ke Ju
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
| | - Xingchen Peng
- Department of Biotherapy and National Clinical Research Center for Geriatrics, Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
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Zhu Y, Wu Y, Cheng J, Liang H, Chang Q, Lin F, Li D, Zhou X, Chen X, Pan P, Liu H, Guo Y, Zhang Y. Ambient air pollution, lifestyle, and genetic predisposition on all-cause and cause-specific mortality: A prospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 933:173120. [PMID: 38750765 DOI: 10.1016/j.scitotenv.2024.173120] [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: 01/20/2024] [Revised: 05/07/2024] [Accepted: 05/08/2024] [Indexed: 05/19/2024]
Abstract
BACKGROUND Although it is widely acknowledged that long-term exposure to ambient air pollution is closely related to the risk of mortality, there were inconsistencies in terms of cause-specific mortality and it is still unknown whether lifestyle and genetic susceptibility could modify the association. METHODS This population-based prospective cohort study involved 461,112 participants from the UK Biobank. The land-use regression model was used to estimate the concentrations of particulate matter (PM2.5, PMcoarse, PM10), and nitrogen oxides (NO2 and NOx). The association between air pollution and mortality was evaluated using Cox proportional hazard models. Furthermore, a lifestyle score incorporated with smoking status, physical activity, alcohol consumption, and diet behaviors, and polygenic risk score using 12 genetic variants, were developed to assess the modifying effect of air pollution on mortality outcomes. RESULTS During a median follow-up of 14.0 years, 33,903 deaths were recorded, including 17,083 (2835; 14,248), 6970, 2429, and 1287 deaths due to cancer (lung cancer, non-lung cancer), cardiovascular disease (CVD), respiratory and digestive disease, respectively. Each interquartile range (IQR) increase in PM2.5, NO2 and NOx was associated with 7 %, 6 % and 5 % higher risk of all-cause mortality, respectively. Specifically, for cause-specific mortality, each IQR increase in PM2.5, NO2 and NOx was also linked to mortality due to cancer (lung cancer and non-lung cancer), CVD, respiratory and digestive disease. Furthermore, additive and multiplicative interactions were identified between high ambient air pollution and unhealthy lifestyle on mortality. In addition, associations between air pollution and mortality were modified by lifestyle behaviors. CONCLUSION Long-term exposure to air pollutants increased the risk of all-cause and cause-specific mortality, which was modified by lifestyle behaviors. In addition, we also revealed a synergistically detrimental effect between air pollution and an unhealthy lifestyle, suggesting the significance of joint air pollution management and adherence to a healthy lifestyle on public health.
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Affiliation(s)
- Yiqun Zhu
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Jun Cheng
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Huaying Liang
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China
| | - Qinyu Chang
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China
| | - Fengyu Lin
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China
| | - Dianwu Li
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China
| | - Xin Zhou
- Department of Dermatology, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China
| | - Xiang Chen
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia; Department of Dermatology, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha 410008, Hunan, China
| | - Pinhua Pan
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha 410008, Hunan, China
| | - Hong Liu
- Department of Dermatology, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha 410008, Hunan, China
| | - Yuming Guo
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - Yan Zhang
- Department of Respiratory Medicine, National Key Clinical Specialty, Branch of National Clinical Research Center for Respiratory Disease, Xiangya Hospital, Central South University, Changsha 410008, Hunan, China; Center of Respiratory Medicine, Xiangya Hospital of Central South University, Changsha 410008, Hunan, China; Hunan Engineering Research Center for Intelligent Diagnosis and Treatment of Respiratory Disease, Changsha 410008, Hunan, China.
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Li S, Liu Y, Li R, Xiao W, Ou J, Tao F, Wan Y. Association between green space and multiple ambient air pollutants with depressive and anxiety symptoms among Chinese adolescents: The role of physical activity. ENVIRONMENT INTERNATIONAL 2024; 189:108796. [PMID: 38838489 DOI: 10.1016/j.envint.2024.108796] [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: 02/21/2024] [Revised: 05/31/2024] [Accepted: 05/31/2024] [Indexed: 06/07/2024]
Abstract
OBJECTIVE To explore the association between green space, multiple ambient air pollutants and depressive/anxiety symptoms and the mediating role of physical activity (PA) in Chinese adolescents. METHOD A school-based health survey was conducted in eight provinces in China in 2021. 22,868 students aged 14.64 (±1.77) years completed standard questionnaires to record details of depressive, anxiety symptoms and PA. We calculated the average normalized difference vegetation index (NDVI) in circular buffers of 200 m, 500 m and 1000 m and estimated the concentrations of PM10, PM2.5, CO, NO2, O3, SO2 around the adolescents' school addresses. RESULTS The exposure-response curves showed that the lower the NDVI value, the higher the risk of depressive and anxiety symptoms. CO, PM2.5 and SO2 and air pollution score were associated with increased risk of depressive and anxiety symptoms. NDVI in all circular buffers decreased the risk of depressive and anxiety symptoms at low levels of PA, but the associations were not significant at high levels of PA. In the subgroup analysis, PM10, PM2.5, CO, NO2, SO2, AQI and air pollution score increased the risk of depressive and anxiety symptoms at low PA levels, but the associations were not significant at high levels of PA. Mediation analysis indicated that the mediating effect of PA on the association between NDVI, NDVI-200 m NDVI-500 m, CO, PM10, PM2.5, SO2, AQI and depressive/anxiety symptoms was statistically significant(p < 0.05). CONCLUSION Middle-high level PA could reduce the strength of association between air pollution and depressive and anxiety symptoms. Meanwhile, the association between green space/air pollution and depressive/anxiety symptoms was partly mediated by PA.
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Affiliation(s)
- Shuqin Li
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Yu Liu
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Ruoyu Li
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Wan Xiao
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China
| | - Jinping Ou
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China.
| | - Fangbiao Tao
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China.
| | - Yuhui Wan
- School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei 230032, Anhui, China; Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China; NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, No 81 Meishan Road, Hefei 230032, Anhui, China.
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14
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Bai L, Wang K, Liu D, Wu S. Potential Early Effect Biomarkers for Ambient Air Pollution Related Mental Disorders. TOXICS 2024; 12:454. [PMID: 39058106 PMCID: PMC11280925 DOI: 10.3390/toxics12070454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 06/18/2024] [Accepted: 06/21/2024] [Indexed: 07/28/2024]
Abstract
Air pollution is one of the greatest environmental risks to health, with 99% of the world's population living where the World Health Organization's air quality guidelines were not met. In addition to the respiratory and cardiovascular systems, the brain is another potential target of air pollution. Population- and experiment-based studies have shown that air pollution may affect mental health through direct or indirect biological pathways. The evidence for mental hazards associated with air pollution has been well documented. However, previous reviews mainly focused on epidemiological associations of air pollution with some specific mental disorders or possible biological mechanisms. A systematic review is absent for early effect biomarkers for characterizing mental health hazards associated with ambient air pollution, which can be used for early warning of related mental disorders and identifying susceptible populations at high risk. This review summarizes possible biomarkers involved in oxidative stress, inflammation, and epigenetic changes linking air pollution and mental disorders, as well as genetic susceptibility biomarkers. These biomarkers may provide a better understanding of air pollution's adverse effects on mental disorders and provide future research direction in this arena.
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Affiliation(s)
- Lijun Bai
- Department of Occupational and Environmental Health, School of Public Health, Xi’an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases (Xi’an Jiaotong University), Ministry of Education, Xi’an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an 710061, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi’an 710061, China
| | - Kai Wang
- Department of Occupational and Environmental Health, School of Public Health, Xi’an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases (Xi’an Jiaotong University), Ministry of Education, Xi’an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an 710061, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi’an 710061, China
| | - Dandan Liu
- Department of Occupational and Environmental Health, School of Public Health, Xi’an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases (Xi’an Jiaotong University), Ministry of Education, Xi’an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an 710061, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi’an 710061, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi’an Jiaotong University Health Science Center, 76 Yanta West Road, Yanta District, Xi’an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases (Xi’an Jiaotong University), Ministry of Education, Xi’an 710061, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi’an 710061, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi’an 710061, China
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15
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Wang Y, Li H, Huang J, Jiang M, Tian S, Liu S, Zhang L, Wu S, Kan H, Gao X. Short-Term PM 2.5 Exposure and DNA Methylation Changes of Circadian Rhythm Genes: Evidence from Two Experimental Studies. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:9991-10000. [PMID: 38814053 DOI: 10.1021/acs.est.4c00108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
The circadian rhythm regulates many crucial physiological processes, impacting human aging and aging-related outcomes. Observational evidence links circadian rhythm disturbance to PM2.5 exposure, yet the underlying DNA methylation mechanisms remain unclear due to limited PM2.5-dominated experimental settings. Therefore, we investigated the associations between short-term PM2.5 exposure and DNA methylation changes of 1188 CpG candidates across circadian genes among 32 young adults in the FDU study, with the validation in 26 individuals from the PKU study. Further mediation analyses tested whether DNA methylation of circadian genes could mediate the influence of PM2.5 on aging measured by three epigenetic ages: DNAmGrimAge, DunedinPoAm, and the mortality risk score. We identified three CpG sites associated with personal PM2.5 exposure: cg01248361 (CSNK2A2), cg17728065 (RORA), and cg22513396 (PRKAG2). Acute effects of PM2.5 on the three loci could be mediated by several circulating biomarkers, including MDA and EGF, with up to ∼30% of mediated proportions. Three loci further showed varying potentials in mediating the aging acceleration effect of PM2.5. Locus cg17728065 is the key site exhibiting a robust mediating effect (7.54-12.52%) on PM2.5-induced aging acceleration. Our findings demonstrated that PM2.5, even short-term peaks, could leave imprints on human aging via inducing aberrant temporal fluctuation in circadian homeostasis captured by DNA methylation profiles.
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Affiliation(s)
- Yuting Wang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100871, China
| | - Huichu Li
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100871, China
| | - Meijie Jiang
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100871, China
| | - Sifan Tian
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100871, China
| | - Shuzhen Liu
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100871, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University and Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China
| | - Shaowei Wu
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
- Key Laboratory of Environment and Genes Related to Diseases, Ministry of Education, Xi'an, Shaanxi 710049, China
- Key Laboratory of Trace Elements and Endemic Diseases in Ministry of Health, Xi'an, Shaanxi 710049, China
- Key Laboratory for Disease Prevention and Control and Health Promotion of Shaanxi Province, Xi'an, Shaanxi 710049, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200032, China
- IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China
- National Center for Children's Health, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Xu Gao
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100871, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100871, China
- Peking University Institute of Environmental Medicine, Beijing 100191, China
- Center for Healthy Aging, Peking University Health Science Center, Beijing 100083, China
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16
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Hu Y, Chavez T, Eckel SP, Yang T, Chen X, Vigil M, Pavlovic N, Lurmann F, Lerner D, Lurvey N, Grubbs B, Al-Marayati L, Toledo-Corral C, Johnston J, Dunton GF, Farzan SF, Habre R, Breton C, Bastain TM. Joint effects of traffic-related air pollution and hypertensive disorders of pregnancy on maternal postpartum depressive and anxiety symptoms. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2024:10.1038/s41370-024-00692-9. [PMID: 38822090 DOI: 10.1038/s41370-024-00692-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 05/16/2024] [Accepted: 05/20/2024] [Indexed: 06/02/2024]
Abstract
BACKGROUND Ambient air pollution has been linked to postpartum depression. However, few studies have investigated the effects of traffic-related NOx on postpartum depression and whether any pregnancy-related factors might increase susceptibility. OBJECTIVES To evaluate the association between traffic-related NOx and postpartum depressive and anxiety symptoms, and effect modification by pregnancy-related hypertension. METHODS This study included 453 predominantly low-income Hispanic/Latina women in the MADRES cohort. Daily traffic-related NOx concentrations by road class were estimated using the California LINE-source dispersion model (CALINE4) at participants' residential locations and averaged across pregnancy. Postpartum depressive and anxiety symptoms were evaluated by a validated questionnaire (Postpartum Distress Measure, PDM) at 1, 3, 6 and 12 months postpartum. Multivariate linear regressions were performed to estimate the associations at each timepoint. Interaction terms were added to the linear models to assess effect modification by hypertensive disorders of pregnancy (HDPs). Repeated measurement analyses were conducted by using mixed effect models. RESULTS We found prenatal traffic-related NOx was associated with increased PDM scores. Specifically, mothers exposed to an IQR (0.22 ppb) increase in NOx from major roads had 3.78% (95% CI: 0.53-7.14%) and 5.27% (95% CI: 0.33-10.45%) significantly higher 3-month and 12-month PDM scores, respectively. Similarly, in repeated measurement analyses, higher NOx from major roads was associated with 3.06% (95% CI: 0.43-5.76%) significantly higher PDM scores across the first year postpartum. Effect modification by HDPs was observed: higher freeway/highway and total NOx among mothers with HDPs were associated with significantly higher PDM scores at 12 months postpartum compared to those without HDPs. IMPACT This study shows that prenatal traffic-related air pollution was associated with postpartum depressive and anxiety symptoms. The study also found novel evidence of greater susceptibility among women with HDPs, which advances the understanding of the relationships between air pollution, maternal cardiometabolic health during pregnancy and postpartum mental health. Our study has potential implications for clinical intervention to mitigate the effects of traffic-related pollution on postpartum mental health disorders. The findings can also offer valuable insights into urban planning strategies concerning the implementation of emission control measures and the creation of green spaces.
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Affiliation(s)
- Yuhong Hu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Thomas Chavez
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sandrah P Eckel
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Tingyu Yang
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xinci Chen
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Mario Vigil
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | | | | | - Brendan Grubbs
- Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Laila Al-Marayati
- Department of Obstetrics and Gynecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Claudia Toledo-Corral
- Department of Health Sciences, California State University, Northridge, Northridge, CA, USA
| | - Jill Johnston
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Genevieve F Dunton
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Shohreh F Farzan
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Rima Habre
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Carrie Breton
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Theresa M Bastain
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
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17
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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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18
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Gao X. Environmental aging: through the prism of DNA methylation. Epigenomics 2024:1-4. [PMID: 38869463 DOI: 10.1080/17501911.2024.2345042] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 04/15/2024] [Indexed: 06/14/2024] Open
Affiliation(s)
- Xu Gao
- Department of Occupational & Environmental Health Sciences, School of Public Health,Peking University, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
- Center for Healthy Aging, Peking University Health Science Center, Beijing, 100191, China
- Peking University Institute of Environmental Medicine, Beijing, 100191, China
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19
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Xie T, Huang Z, Tan Y, Tan T. Analysis of the situations and influencing factors of public anxiety in China: based on Baidu index data. Front Public Health 2024; 12:1360119. [PMID: 38721539 PMCID: PMC11077890 DOI: 10.3389/fpubh.2024.1360119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 04/08/2024] [Indexed: 05/15/2024] Open
Abstract
Background Anxiety disorders have emerged as one of the most prevalent mental health problems and health concerns. However, previous research has paid limited attention to measuring public anxiety from a broader perspective. Furthermore, while we know many factors that influence anxiety disorders, we still have an incomplete understanding of how these factors affect public anxiety. We aimed to quantify public anxiety from the perspective of Internet searches, and to analyze its spatiotemporal changing characteristics and influencing factors. Methods This study collected Baidu Index from 2014 to 2022 in 31 provinces in mainland China to measure the degree of public anxiety based on the Baidu Index from 2014 to 2022. The spatial autocorrelation analysis method was used to study the changing trends and spatial distribution characteristics of public anxiety. The influencing factors of public anxiety were studied using spatial statistical modeling methods. Results Empirical analysis shows that the level of public anxiety in my country has continued to rise in recent years, with significant spatial clustering characteristics, especially in the eastern and central-southern regions. In addition, we constructed ordinary least squares (OLS) and geographically weighted regression (GWR) spatial statistical models to examine the relationship between social, economic, and environmental factors and public anxiety levels. We found that the GWR model that considers spatial correlation and dependence is significantly better than the OLS model in terms of fitting accuracy. Factors such as the number of college graduates, Internet traffic, and urbanization rate are significantly positively correlated with the level of public anxiety. Conclusion Our research results draw attention to public anxiety among policymakers, highlighting the necessity for a more extensive examination of anxiety issues, especially among university graduates, by the public and relevant authorities.
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Affiliation(s)
- Tiantian Xie
- Institute of New Rural Development, South China Agricultural University, Guangzhou, China
- Centre de Recherche Sur Les Liens Sociaux (CERLIS), Université Paris Descartes, Paris, France
| | - Zetao Huang
- Institute of Biomass Engineering, South China Agricultural University, Guangzhou, China
| | - Yue Tan
- School of Marxism, Chongqing Three Gorges Medical College, Chongqing, China
| | - Tao Tan
- Institute of Biomass Engineering, South China Agricultural University, Guangzhou, China
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20
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Jiang Z, Zhang S, Gao T, Chen K, Liu Y, Liu Y, Wang T, Zeng P. Co-exposure to multiple air pollutants, genetic susceptibility, and the risk of myocardial infarction onset: a cohort analysis of the UK Biobank participants. Eur J Prev Cardiol 2024; 31:698-706. [PMID: 38085043 DOI: 10.1093/eurjpc/zwad384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 11/18/2023] [Accepted: 12/06/2023] [Indexed: 04/19/2024]
Abstract
AIMS The relationship between the long-term joint exposure to ambient air pollution and incidence of myocardial infarction (MI) and modification by genetic susceptibility remain inconclusive. METHODS AND RESULTS We analysed 329 189 UK Biobank participants without MI at baseline. Exposure concentrations to particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), and nitrogen oxides (NOx) were obtained. Air pollution score assessing the joint exposure was calculated, and its association with MI was evaluated via Cox model under the P value aggregation framework. Genetic susceptibility to MI was evaluated by incorporating polygenic risk score (PRS) into models. Risk prediction models were also established. During a median follow-up of 13.4 years, 9993 participants developed MI. Per interquartile range increase of PM2.5, PM10, NO2, and NOx resulted in 74% [95% confidence intervals (CIs) 69%-79%], 67% (63%-72%), 46% (42%-49%), and 38% (35%-41%) higher risk of MI. Compared with the lowest quartile (Q1) of air pollution score, the multivariable adjusted hazard ratio (HR) (95%CIs) of Q4 (the highest cumulative air pollution) was 3.50 (3.29-3.72) for MI. Participants with the highest PRS and air pollution score possessed the highest risk of incident MI (HR = 4.88, 95%CIs 4.35-5.47). Integrating PRS, air pollution exposure, and traditional factors substantially improved risk prediction of MI. CONCLUSION Long-term joint exposure to air pollutants including PM2.5, PM10, NO2, and NOx is substantially associated with increased risk of MI. Genetic susceptibility to MI strengthens such adverse joint association. Air pollutions together with genetic and traditional factors enhance the accuracy of MI risk prediction.
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Affiliation(s)
- Zhou Jiang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Tongyu Gao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Keying Chen
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Yuxin Liu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Ying Liu
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
- Xuzhou Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
- Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, 209 Tongshan Road, Yunlong District, Xuzhou, Jiangsu 221004, China
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Li C, Chen H, Gu Y, Chen W, Liu M, Lei Q, Li Y, Liang X, Wei B, Huang D, Liu S, Su L, Zeng X, Wang L. Causal effects of PM 2.5 exposure on neuropsychiatric disorders and the mediation via gut microbiota: A Mendelian randomization study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 275:116257. [PMID: 38564871 DOI: 10.1016/j.ecoenv.2024.116257] [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: 12/20/2023] [Revised: 03/03/2024] [Accepted: 03/21/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Growing evidence has revealed the impacts of exposure to fine particulate matter (PM2.5) and dysbiosis of gut microbiota on neuropsychiatric disorders, but the causal inference remains controversial due to residual confounders in observational studies. METHODS This study aimed to examine the causal effects of exposure to PM2.5 on 4 major neuropsychiatric disorders (number of cases = 18,381 for autism spectrum disorder [ASD], 38,691 for attention deficit hyperactivity disorder [ADHD], 67,390 for schizophrenia, and 21,982 cases for Alzheimer's disease [AD]), and the mediation pathway through gut microbiota. Two-sample Mendelian randomization (MR) analyses were performed, in which genetic instruments were identified from genome-wide association studies (GWASs). The included GWASs were available from (1) MRC Integrative Epidemiology Unit (MRC-IEU) for PM2.5, PMcoarse, PM10, and NOX; (2) the Psychiatric Genomics Consortium (PGC) for ASD, ADHD, and schizophrenia; (3) MRC-IEU for AD; and (4) MiBioGen for gut microbiota. Multivariable MR analyses were conducted to adjust for exposure to NOX, PMcoarse, and PM10. We also examined the mediation effects of gut microbiota in the associations between PM2.5 exposure levels and neuropsychiatric disorders, using two-step MR analyses. RESULTS Each 1 standard deviation (1.06 ug/m3) increment in PM2.5 concentrations was associated with elevated risk of ASD (odds ratio [OR] 1.42, 95% confidence interval [CI] 1.00-2.02), ADHD (1.51, 1.15-1.98), schizophrenia (1.47, 1.15-1.87), and AD (1.57, 1.16-2.12). For all the 4 neurodevelopmental disorders, the results were robust under various sensitivity analyses, while the MR-Egger method yielded non-significant outcomes. The associations remained significant for all the 4 neuropsychiatric disorders after adjusting for PMcoarse, while non-significant after adjusting for NOX and PM10. The effects of PM2.5 exposure on ADHD and schizophrenia were partially mediated by Lachnospiraceae and Barnesiella, with the proportions ranging from 8.31% to 15.77%. CONCLUSIONS This study suggested that exposure to PM2.5 would increase the risk of neuropsychiatric disorders, partially by influencing the profile of gut microbiota. Comprehensive regulations on air pollutants are needed to help prevent neuropsychiatric disorders.
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Affiliation(s)
- Chanhua Li
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Hao Chen
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Ye Gu
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Wanling Chen
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Meiliang Liu
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Qinggui Lei
- The Eighth People's Hospital of Nanning, Nanning, Guangxi 530001, China
| | - Yujun Li
- Nanning Children's Rehabilitation Center, Nanning, Guangxi 530005, China
| | - Xiaomei Liang
- Nanning Children's Rehabilitation Center, Nanning, Guangxi 530005, China
| | - Binyuan Wei
- Nanning Children's Rehabilitation Center, Nanning, Guangxi 530005, China
| | - Dongping Huang
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Shun Liu
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Li Su
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Xiaoyun Zeng
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China
| | - Lijun Wang
- School of Public Health, Guangxi Medical University, Nanning, Guangxi 530021, China; Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China.
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Cai L, Tan J, Chen X, Wang F, Zhang X, Chen J, Liu C, Sun Y. Ambient air pollution exposure and the risk of probable sarcopenia: A prospective cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 275:116273. [PMID: 38564861 DOI: 10.1016/j.ecoenv.2024.116273] [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: 12/10/2023] [Revised: 03/26/2024] [Accepted: 03/28/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Sarcopenia is characterized by decreased muscle mass and strength, posing threat to quality of life. Air pollutants are increasingly recognized as risk factors for diseases, while the relationship between the two remains to be elucidated. This study investigated whether exposure to ambient air pollution contributes to the development of sarcopenia. METHODS We employed the data from the UK Biobank with 303,031 eligible participants. Concentrations of PM2·5, NO2, and NOx were estimated. Cox proportional hazard regression models were applied to investigate the associations between pollutants and sarcopenia. RESULTS 30,766 probable sarcopenia cases was identified during the follow-up. We observed that exposure to PM2.5 (HR, 1.232; 95% CI, 1.053-1.440), NO2 (HR, 1.055; 95% CI, 1.032-1.078) and NOx (HR, 1.016; 95% CI, 1.007-1.026) were all significantly associated with increased risk for probable sarcopenia for each 10 μg/m3 increase in pollutant concentration. In comparison with individuals in the lowest quartiles of exposure, those in the upper quartiles had significantly increased risk of probable sarcopenia. Sarcopenia-related factors, e.g., reduced lean muscle mass, diminished walking pace, and elevated muscle fat infiltration ratio, also exhibited positive associations with exposure to ambient air pollution. On the contrary, high level physical activity significantly mitigated the influence of air pollutants on the development of probable sarcopenia. CONCLUSIONS Air pollution exposure elevated the risk of developing sarcopenia and related manifestations in a dose-dependent manner, while physical activity maintained protective under this circumstance. Efforts should be made to control air pollution and emphasize the importance of physical activity for skeletal muscle health under this circumstance.
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Affiliation(s)
- Lubing Cai
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
| | - Jiale Tan
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
| | - Xinyi Chen
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
| | - Fuchao Wang
- 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 200032, China
| | - Xingyu Zhang
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
| | - Jiwu Chen
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China
| | - Cong Liu
- 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 200032, China.
| | - Yaying Sun
- Department of Sports Medicine, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
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23
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Li P, Wang Y, Tian D, Liu M, Zhu X, Wang Y, Huang C, Bai Y, Wu Y, Wei W, Tian S, Li Y, Qiao Y, Yang J, Cao S, Cong C, Zhao L, Su J, Wang M. Joint Exposure to Ambient Air Pollutants, Genetic Risk, and Ischemic Stroke: A Prospective Analysis in UK Biobank. Stroke 2024; 55:660-669. [PMID: 38299341 DOI: 10.1161/strokeaha.123.044935] [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: 08/29/2023] [Accepted: 12/20/2023] [Indexed: 02/02/2024]
Abstract
BACKGROUND Our primary objective was to assess the association between joint exposure to various air pollutants and the risk of ischemic stroke (IS) and the modification of the genetic susceptibility. METHODS This observational cohort study included 307 304 British participants from the United Kingdom Biobank, who were stroke-free and possessed comprehensive baseline data on genetics, air pollutant exposure, alcohol consumption, and dietary habits. All participants were initially enrolled between 2006 and 2010 and were followed up until 2022. An air pollution score was calculated to assess joint exposure to 5 ambient air pollutants, namely particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, as well as nitrogen oxide and nitrogen dioxide. To evaluate individual genetic risk, a polygenic risk score for IS was calculated for each participant. We adjusted for demographic, social, economic, and health covariates. Cox regression models were utilized to estimate the associations between air pollution exposure, polygenic risk score, and the incidence of IS. RESULTS Over a median follow-up duration of 13.67 years, a total of 2476 initial IS events were detected. The hazard ratios (95% CI) of IS for per 10 µg/m3 increase in particulate matter with diameters equal to or <2.5 µm, ranging from 2.5 to 10 µm, equal to or <10 µm, nitrogen dioxide, and nitrogen oxide were 1.73 (1.33-2.14), 1.24 (0.88-1.70), 1.13 (0.89-1.33), 1.03 (0.98-1.08), and 1.04 (1.02-1.07), respectively. Furthermore, individuals in the highest quintile of the air pollution score exhibited a 29% to 66% higher risk of IS compared with those in the lowest quintile. Notably, participants with both high polygenic risk score and air pollution score had a 131% (95% CI, 85%-189%) greater risk of IS than participants with low polygenic risk score and air pollution score. CONCLUSIONS Our findings suggested that prolonged joint exposure to air pollutants may contribute to an increased risk of IS, particularly among individuals with elevated genetic susceptibility to IS.
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Affiliation(s)
- Panlong Li
- Department of Medical Imaging (P.L., Y.B., Y. Wu, W.W., M.W.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, China (P.L., X.Z., Yanfeng Wang, C.H.)
| | - Ying Wang
- Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou, China (Ying Wang)
- School of Public Health, Zhengzhou University (Ying Wang)
| | - Dandan Tian
- Department of Hypertension (D.T., M.L.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
| | - Min Liu
- Department of Hypertension (D.T., M.L.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
| | - Xirui Zhu
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, China (P.L., X.Z., Yanfeng Wang, C.H.)
| | - Yanfeng Wang
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, China (P.L., X.Z., Yanfeng Wang, C.H.)
| | - Chun Huang
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, China (P.L., X.Z., Yanfeng Wang, C.H.)
| | - Yan Bai
- Department of Medical Imaging (P.L., Y.B., Y. Wu, W.W., M.W.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
- Laboratory of Brain Science and Brain-Like Intelligence Technology, Biomedical Research Institute, Henan Academy of Science, China (Y.B.)
| | - Yaping Wu
- Department of Medical Imaging (P.L., Y.B., Y. Wu, W.W., M.W.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
| | - Wei Wei
- Department of Medical Imaging (P.L., Y.B., Y. Wu, W.W., M.W.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
| | - Shan Tian
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Yuna Li
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Yuan Qiao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Junting Yang
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Shanshan Cao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Chaohua Cong
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Lei Zhao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Jingjing Su
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China (S.T., Y.L., Y.Q., J.Y., S.C., C.C., L.Z., J.S.)
| | - Meiyun Wang
- Department of Medical Imaging (P.L., Y.B., Y. Wu, W.W., M.W.), Henan Provincial People's Hospital and Zhengzhou University People's Hospital, China
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Zhang S, Cao H, Chen K, Gao T, Zhao H, Zheng C, Wang T, Zeng P, Wang K. Joint Exposure to Multiple Air Pollutants, Genetic Susceptibility, and Incident Dementia: A Prospective Analysis in the UK Biobank Cohort. Int J Public Health 2024; 69:1606868. [PMID: 38426188 PMCID: PMC10901982 DOI: 10.3389/ijph.2024.1606868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Accepted: 02/05/2024] [Indexed: 03/02/2024] Open
Abstract
Objectives: This study aimed to evaluate the joint effects of multiple air pollutants including PM2.5, PM10, NO2, and NOx with dementia and examined the modifying effects of genetic susceptibility. Methods: This study included 220,963 UK Biobank participants without dementia at baseline. Weighted air pollution score reflecting the joint exposure to multiple air pollutants were constructed by cross-validation analyses, and inverse-variance weighted meta-analyses were performed to create a pooled effect. The modifying effect of genetic susceptibility on air pollution score was assessed by genetic risk score and APOE ε4 genotype. Results: The HR (95% CI) of dementia for per interquartile range increase of air pollution score was 1.13 (1.07∼1.18). Compared with the lowest quartile (Q1) of air pollution score, the HR (95% CI) of Q4 was 1.26 (1.13∼1.40) (P trend = 2.17 × 10-5). Participants with high air pollution score and high genetic susceptibility had higher risk of dementia compared to those with low air pollution score and low genetic susceptibility. Conclusion: Our study provides evidence that joint exposure to multiple air pollutants substantially increases the risk of dementia, especially among individuals with high genetic susceptibility.
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Affiliation(s)
- Shuo Zhang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Hongyan Cao
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Keying Chen
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Tongyu Gao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Huashuo Zhao
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Chu Zheng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Xuzhou Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Ting Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Ping Zeng
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Xuzhou Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, China
| | - Ke Wang
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Center for Medical Statistics and Data Analysis, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Human Genetics and Environmental Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Key Laboratory of Environment and Health, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Xuzhou Engineering Research Innovation Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, China
- Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, China
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25
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Jin J, Xu Z, Beevers SD, Huang J, Kelly F, Li G. Long-term ambient ozone, omega-3 fatty acid, genetic susceptibility, and risk of mental disorders among middle-aged and older adults in UK biobank. ENVIRONMENTAL RESEARCH 2024; 243:117825. [PMID: 38081346 DOI: 10.1016/j.envres.2023.117825] [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: 08/03/2023] [Revised: 11/14/2023] [Accepted: 11/29/2023] [Indexed: 12/17/2023]
Abstract
BACKGROUND Evidence linking ozone to depression and anxiety disorders remains sparse and results are heterogeneous. It remains unknown whether omega-3 fatty acid, or genetic susceptibility of mental disorders modify the impacts of ozone. The aim is to assess the associations of ambient ozone with depression and anxiety, and further explore the potential modification effects of omega-3 fatty acid and genetic susceptibility. METHODS In total of 257,534 participants were enrolled from 2006 to 2010 and followed up to 2016. Depression and anxiety were assessed using mental health questionnaires, primary care records and hospital admission records. The annual average concentrations of ozone were calculated and linked to individuals by home address. Dietary intake and plasma concentration were selected to reflect levels of omega-3 fatty acid. Polygenetic risk scores were selected to reflect genetic susceptibility. We examined the associations of ozone and incident mental disorders, and potential modification of omega-3 fatty acid and genetic susceptibility. RESULTS Incidences of depression (N = 6957) and anxiety (N = 6944) was associated with increase of ozone. Higher levels of omega-3 fatty acid might attenuate the ozone related depression risk. However, the modification effects of genetic susceptibility were not found. CONCLUSIONS Long-term exposure to ambient ozone increase the risk of mental disorders among the middle aged and older adults, and omega-3 fatty acid could reduce the adverse effects of ozone on mental health. Higher intake of omega-3 fatty acid is a potential strategy to prevent the risks caused by ozone on public mental health.
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Affiliation(s)
- Jianbo Jin
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China.
| | - Zhihu Xu
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China.
| | - Sean D Beevers
- Environmental Research Group, School of Public Health, Imperial College London, London, UK.
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China; Peking University Institute for Global Health and Development, Beijing, China.
| | - Frank Kelly
- Environmental Research Group, School of Public Health, Imperial College London, London, UK.
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China; Environmental Research Group, School of Public Health, Imperial College London, London, UK.
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26
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Zhuang Z, Li D, Zhang S, Hu Z, Deng W, Lin H. Short-Term Exposure to PM 2.5 Chemical Components and Depression Outpatient Visits: A Case-Crossover Analysis in Three Chinese Cities. TOXICS 2024; 12:136. [PMID: 38393231 PMCID: PMC10892610 DOI: 10.3390/toxics12020136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 12/26/2023] [Accepted: 12/28/2023] [Indexed: 02/25/2024]
Abstract
BACKGROUND The association between specific chemical components of PM2.5 and depression remains largely unknown. METHODS We conducted a time-stratified case-crossover analysis with a distributed lag nonlinear model (DLNM) to evaluate the relationship of PM2.5 and its chemical components, including black carbon (BC), organic matter (OM), sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+), with the depression incidence. Daily depression outpatients were enrolled from Huizhou, Shenzhen, and Zhaoqing. RESULTS Among 247,281 outpatients, we found the strongest cumulative effects of PM2.5 and its chemical components with the odd ratios (ORs) of 1.607 (95% CI: 1.321, 1.956) and 1.417 (95% CI: 1.245, 1.612) at the 50th percentile of PM2.5 and OM at lag 21, respectively. Furthermore, the ORs with SO42- and NH4+ at the 75th percentile on the same lag day were 1.418 (95% CI: 1.247, 1.613) and 1.025 (95% CI: 1.009, 1.140). Relatively stronger associations were observed among females and the elderly. CONCLUSIONS Our study suggests that PM2.5 and its chemical components might be important risk factors for depression. Reducing PM2.5 emissions, with a particular focus on the major sources of SO42- and OM, might potentially alleviate the burden of depression in South China.
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Affiliation(s)
- Zitong Zhuang
- School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Guangzhou 510080, China
| | - Dan Li
- School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Guangzhou 510080, China
| | - Shiyu Zhang
- School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Guangzhou 510080, China
| | - Zhaoyang Hu
- School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Guangzhou 510080, China
| | - Wenfeng Deng
- Huizhou Center for Disease Control and Prevention, No. 10 Jiangbei Fumin Road, Huizhou 516003, China;
| | - Hualiang Lin
- School of Public Health, Sun Yat-Sen University, No. 74 Zhongshan Road 2, Guangzhou 510080, China
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27
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Tang L, Liu M, Tian J. Volatile organic compounds exposure associated with depression among U.S. adults: Results from NHANES 2011-2020. CHEMOSPHERE 2024; 349:140690. [PMID: 37995973 DOI: 10.1016/j.chemosphere.2023.140690] [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: 06/18/2023] [Revised: 10/18/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023]
Abstract
Volatile organic compounds (VOCs) are important contributors to air pollution. VOCs exposure was associated with various human diseases. Depression is one of the most prevalent mental disorders and poses a serious mental health burden. Although VOCs are neurotoxic and can damage the central nervous system, the association between VOCs exposure and depression remains obscure. Based on data from the National Health and Nutrition Examination Survey, we included 5676 adult individuals and 15 major components of urinary volatile organic compound metabolites (mVOCs). We comprehensively evaluated the potential association between each single urinary mVOC exposure and depressive symptoms using binary logistic and restricted cubic spline regression, whereas the weighted quantile sum regression and least absolute shrinkage and selection operator regression model were used to explore the mixture co-exposure association. The results indicated significantly higher mean concentrations of the 11 urinary mVOC components in the depression group than that in the non-depression group. And 12 mVOC components had a significantly positive association with depression. The overall effect of all 15 mVOCs components was also significantly positive. The corresponding odds ratio was 1.56 (95%CI: 1.2-2.03) in the categorical variable model and the regression coefficient was 0.36 (95%CI: 0.12-0.6) in the numerical variable model. Five urinary mVOCs (URXCYM, URXPHG, URX34 M, URXMB3, and URXAMC) were identified as the most relevant components associated with depression, with 89.06% total weights in the categorical variable model and 89.39% in the numerical variable model. The mVOCs were the biomarkers of VOCs, their concentrations in urine could specifically represent the contents of their metabolic parents in the human body. Considering that the metabolic parents of the above five mVOCs were predominantly acrylonitrile, toluene, styrene, acrylamide, 1,3-Butadiene, and xylenes, our results further indicated that exposure to these VOCs was closely related to depression, and more attention should be paid to the mental health risks of VOCs exposure.
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Affiliation(s)
- Liwei Tang
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, Guangdong, 518055, China
| | - Min Liu
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, Guangdong, 518055, China; Brain Cognition and Brain Disease Institute, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, 518055, China
| | - Jing Tian
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, Guangdong, 518055, China.
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28
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Wang J, Hu X, Yang T, Jin J, Hao J, Kelly FJ, Huang J, Li G. Ambient air pollution and the dynamic transitions of stroke and dementia: a population-based cohort study. EClinicalMedicine 2024; 67:102368. [PMID: 38169700 PMCID: PMC10758736 DOI: 10.1016/j.eclinm.2023.102368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/25/2023] [Accepted: 11/28/2023] [Indexed: 01/05/2024] Open
Abstract
Background Stroke and dementia are the leading causes of neurological disease burden. Detrimental effects of air pollution on both conditions are increasingly recognised, while the impacts on the dynamic transitions have not yet been explored, and whether critical time intervals exist is unknown. Methods This prospective study was conducted based on the UK Biobank. Annual average air pollution concentrations at baseline year 2010 estimated by land-use regression models were used as a proxy for long-term air pollution exposure. Associations between multiple air pollutants (PM2.5, PM2.5-10, and NO2) indicated by air pollution score and the dynamic transitions of stroke and dementia were estimated, and the impacts during critical time intervals were explored. The date cutoff of this study was February 29, 2020. Findings During a median follow-up of 10.9 years in 413,372 participants, 6484, 3813, and 376 participants developed incident stroke, dementia, and comorbidity of stroke and dementia. For the overall transition from stroke to comorbid dementia, the hazard ratio (HR) for each interquartile range (IQR) increase in air pollution score was 1.38 (95% CI, 1.15, 1.65), and the risks were limited to two time intervals (within 1 year and over 5 years after stroke). As for the transition from dementia to comorbid stroke, increased risk was only observed during 2-3 years after dementia. Interpretation Our findings suggested that air pollution played an important role in the dynamic transition of stroke and dementia even at concentrations below the current criteria. The findings provided new evidence for alleviating the disease burden of neurological disorders related to air pollution during critical time intervals. Funding The State Scholarship Fund of China Scholarship Council.
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Affiliation(s)
- Jiawei Wang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Xin Hu
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Teng Yang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Jianbo Jin
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
| | - Junwei Hao
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Frank J. Kelly
- Environmental Research Group, Faculty of Medicine, School of Public Health, Imperial College London, London, UK
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
- Institute for Global Health and Development, Peking University, Beijing, China
| | - Guoxing Li
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing, China
- Environmental Research Group, Faculty of Medicine, School of Public Health, Imperial College London, London, UK
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29
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Nobile F, Forastiere A, Michelozzi P, Forastiere F, Stafoggia M. Long-term exposure to air pollution and incidence of mental disorders. A large longitudinal cohort study of adults within an urban area. ENVIRONMENT INTERNATIONAL 2023; 181:108302. [PMID: 37944432 DOI: 10.1016/j.envint.2023.108302] [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: 06/09/2023] [Revised: 10/02/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023]
Abstract
BACKGROUND Recent epidemiological evidence suggests associations between air pollution exposure and major depressive disorders, but the literature is inconsistent for other mental illnesses. We investigated the associations of several air pollutants and road traffic noise with the incidence of different categories of mental disorders in a large population-based cohort. METHODS We enrolled 1,739,277 individuals 30 + years from the 2011 census in Rome, Italy, and followed them up until 2019. In detail, we analyzed 1,733,331 participants (mean age 56.43 +/- 15.85 years; 54.96 % female) with complete information on covariates of interest. We excluded subjects with prevalent mental disorders at baseline to evaluate the incidence (first hospitalization or co-pay exemption) of schizophrenia spectrum disorders, bipolar, anxiety, personality, or substance use disorders. In addition, we studied subjects with first prescriptions of antipsychotics, antidepressants, and mood stabilizers. Annual average concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO₂), Black Carbon (BC), ultrafine particles (UFP), and road traffic noise were assigned to baseline residential addresses. We applied Cox regression models adjusted for individual and area-level covariates. RESULTS Each interquartile range (1.13 µg/m3) increase in PM2.5 was associated with a hazard ratio (HR) of 1.070 (95 % confidence interval [CI]: 1.017, 1.127) for schizophrenia spectrum disorder, 1.135 (CI: 1.086, 1.186) for depression, 1.097 (CI: 1.030, 1.168) for anxiety disorders. Positive associations were also detected for BC and UFP, and with the three categories of drug prescriptions. Bipolar, personality, and substance use disorders did not show clear associations. The effects were highest in the age group 30-64 years, except for depression. CONCLUSIONS Long-term exposure to ambient air pollution, especially fine and ultrafine particles, was associated with increased risks of schizophrenia spectrum disorder, depression, and anxiety disorders. The association of the pollutants with the prescriptions of specific drugs increases the credibility of the results.
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Affiliation(s)
- Federica Nobile
- Department of Epidemiology, Lazio Region Health Service/ASL Rome 1, Rome, Italy.
| | | | - Paola Michelozzi
- Department of Epidemiology, Lazio Region Health Service/ASL Rome 1, Rome, Italy
| | - Francesco Forastiere
- Environmental Research Group, Imperial College, London, UK; National Research Council, IFT, Palermo, Italy
| | - Massimo Stafoggia
- Department of Epidemiology, Lazio Region Health Service/ASL Rome 1, Rome, Italy
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Li D, Ma Y, Cui F, Yang Y, Liu R, Tang L, Wang J, Tian Y. Long-term exposure to ambient air pollution, genetic susceptibility, and the incidence of bipolar disorder: A prospective cohort study. Psychiatry Res 2023; 327:115396. [PMID: 37549511 DOI: 10.1016/j.psychres.2023.115396] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/27/2023] [Accepted: 07/29/2023] [Indexed: 08/09/2023]
Abstract
There is mounting recent evidence showing that air pollution exposure may be related to the risk of mental health, yet the association between long-term exposure to air pollution and the risk of incident bipolar disorder (BD) remains unclear. Thus we aim to identify associations between air pollution and the incidence of BD in a prospective population-based cohort. In total, 482,726 participants who were free of BD from the UK Biobank were included in this prospective study. We applied time-varying Cox proportional hazards models, accounting for relevant confounders, and used annual-year moving averages of air pollution as time-varying exposures. The genetic risk for BD was categorized into three categories (low, intermediate, and high) according to the tertiles of polygenic risk score. During a median of 10.79-year follow-up, 923 incident BD events were recorded. Long-term exposures to PM2.5, PM10, NO2, and NOx were associated with increased BD risk. Estimated HRs (95% CIs) for each interquartile range increase in PM2.5, PM10, NO2, and NOx concentrations were 1.31 (1.18-1.45), 1.19 (1.09-1.31), 1.19 (1.08-1.30), and 1.16 (1.07-1.26), respectively. Associations were still observed and even stronger at pollutant concentrations lower than WHO air quality guideline. In subgroup analysis stratified by genetic risk, we observed consistent associations between all pollutants and BD risk in intermediate and high genetic risk groups, but not in low genetic risk group. For example, the HRs (95% CIs) for PM2.5 were 1.00 (0.94-1.53), 1.30 (1.06-1.59), and 1.34 (1.16-1.54) in low, intermediate, and high genetic groups, respectively. In conclusion, long-term exposure to air pollution was significantly associated with an elevated risk of BD. Associations of air pollution with BD occurred only within intermediate and high genetic risk categories and were even stronger at the pollutants levels below WHO air quality guidelines. These findings could help inform policy makers regarding ambient air quality standards and BD management.
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Affiliation(s)
- Dankang Li
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Yudiyang Ma
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Feipeng Cui
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Yingping Yang
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Run Liu
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Linxi Tang
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Jianing Wang
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China
| | - Yaohua Tian
- Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China; Department of Maternal and Child Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No.13 Hangkong Road, Wuhan, 430030, China.
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