1
|
Zheng L, Zhou J, Zhu L, Xu X, Luo S, Xie X, Li H, Lin S, Luo J, Wu S. Associations of air pollutants and related metabolites with preterm birth during pregnancy. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175542. [PMID: 39151621 DOI: 10.1016/j.scitotenv.2024.175542] [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: 05/08/2024] [Revised: 08/09/2024] [Accepted: 08/13/2024] [Indexed: 08/19/2024]
Abstract
OBJECTIVE This study aimed to investigate the influence of exposure to ambient fine particulate matter (PM2.5) and its components during pregnancy on the prevalence of preterm birth (PTB). Additionally, we sought to identify the susceptible exposure window. Furthermore, we explored the potential mediating role of blood analysis and a comprehensive metabolic panel in the association between pollutant exposure and PTB incidence. METHODS This birth cohort study recruited 139 participants with PTB outcomes and 1713 controls from Fujian Maternal and Child Health Hospital between January 2021 and June 2023. Sociodemographic characteristics and clinical treatment data during participants' first pregnancies were collected. The exposure levels to pollutants during pregnancy were estimated via a combined geographic-statistical model utilising satellite remote sensing data. The distributional lag nonlinear modelling was employed to assess associations between pollutant exposure during pregnancy and the prevalence of PTB. Weighted quantile regression was used to identify key components associated with PM2.5 and PTB during pregnancy. Additionally, a mediating effect analysis was conducted to evaluate the role of blood analysis. The metabolic profile was used to screen for differentially abundant metabolites associated with PTB and explore their relative expression in relation to air pollutants and PTB incidence. RESULTS Following the adjustment for potential confounding variables, the mean weekly susceptibility windows for PM2.5 were identified as 7-10, 16-19, and 22-28 weeks; 8-10, and 15-19 weeks for inorganic sulfate; 6-10, and 15-28 weeks for nitrate; 6-12, and 15-28 weeks for ammonium (NH4+); and 7-9, 18-20, and 22-36 weeks for organic matter. During mixed exposure to PM2.5 components, the key component is NH4+. In the mixed exposure to PM2.5 components, NH4+ emerged as a key contributor. The results of the mediation analysis revealed that haemoglobin played a mediating role, accounting for 21.53 % of the association between exposure to environmental pollutants and the prevalence of PTB. It is noteworthy that, no mediating effects were observed for the other variables. Furthermore, non-targeted metabolomics identified 17 metabolites associated with PTB. Among these factors, hydrogen phosphate may impact metabolic pathways such as oxidative phosphorylation, influencing the risk of PTB. The interplay between environmental pollutants and metabolites, particularly through oxidative phosphorylation pathways, may contribute to PTB incidence. CONCLUSIONS The evidence indicates that exposure to PM2.5 and its components during pregnancy were a significant risk factor for PTB. Notably, specific weekly exposure windows were identified for pollutants during pregnancy. Among the PM2.5 components, NH4+ exhibited the most substantial weight in the association analysis between exposure to the mixture of components and PTB. Furthermore, our mediation analysis revealed that haemoglobin serves as a partial mediator in the relationship between exposure to pollutants during pregnancy and the prevalence of PTB. Additionally, maternal serum metabolic profiles differed between the preterm and control groups. Notably, a combined effect involving hydrogen phosphate and mixed exposure to PM2.5 fractions further contributed to the development of PTB. Oxidative phosphorylation pathways may play pivotal roles in this intricate association.
Collapse
Affiliation(s)
- Liuyan Zheng
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China
| | - Jungu Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China
| | - Li Zhu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China
| | - Xingyan Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China
| | - Suping Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China
| | - Xiaoxu Xie
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China
| | - Huangyuan Li
- Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fujian 350000, China.
| | - Shaowei Lin
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China.
| | - Jinying Luo
- Department of Obstetrics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou 350001, China.
| | - Siying Wu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fujian 350000, China.
| |
Collapse
|
2
|
Mei Y, Li A, Zhao J, Li Y, Zhou Q, Yang M, Zhao M, Xu J, Li K, Yin G, Wu J, Xu Q. Disturbed glucose homeostasis and its increased allostatic load in response to individual, joint and fluctuating air pollutants exposure: Evidence from a longitudinal study in prediabetes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175498. [PMID: 39151627 DOI: 10.1016/j.scitotenv.2024.175498] [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: 06/04/2024] [Revised: 07/30/2024] [Accepted: 08/12/2024] [Indexed: 08/19/2024]
Abstract
We investigated the effect of individual, joint and fluctuating exposure to air pollution (PM2.5, BC, NO3-, NH4+, OM, SO42-, PM10, NO2, SO2, O3) on glucose metabolisms among prediabetes, and simultaneously explored the modifying effect of lifestyle. We conducted a longitudinal study among prediabetes during 2018-2022. Exposure windows within 60-days moving averages and their variabilities were calculated. FBG, insulin, HOMA-IR, HOMA-B, triglyceride glucose index (TyG), glucose insulin ratio (GI) and allostatic load of glucose homeostasis system (AL-GHS) was included. Linear mixed-effects model and BKMR were adopted to investigate the individual and overall effects, respectively. We also explored the preventive role of lifestyle. Individual air pollutant was associated with increased FBG, insulin, HOMA-IR, HOMA-B, TyG, and decreased GI. People with FBG ≥6.1 mmol/L were more susceptible. Air pollutants mixture were only associated with increased HOMA-B, and constituents have the highest group-PIP. Air pollutants variation also exert harmful effect. We observed similar diabetic effect on AL-GHS. Finally, the diabetic effect of air pollutants disappeared if participants adopt a favorable lifestyle. Our findings highlighted the importance of comprehensively assessing multiple air pollutants and their variations, focusing on metabolic health status in the early prevention of T2D, and adopting healthy lifestyle to mitigate such harmful effect.
Collapse
Affiliation(s)
- Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100046, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Yanbing Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Ming Yang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Kai Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Guohuan Yin
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jingtao Wu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China.
| |
Collapse
|
3
|
Zhang T, Ren AX, Tong M, Li Y, Mendola P, Chen X, Wang M. Gestational exposure to wildfire PM 2.5 and its specific components and the risk of gestational hypertension and eclampsia in the southwestern United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 951:175781. [PMID: 39187088 DOI: 10.1016/j.scitotenv.2024.175781] [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: 05/13/2024] [Revised: 08/13/2024] [Accepted: 08/23/2024] [Indexed: 08/28/2024]
Abstract
In the southwestern United States, the frequency of summer wildfires has elevated ambient PM2.5 concentrations and rates of adverse birth outcomes. Notably, hypertensive disorders in pregnancy (HDP) constitute a significant determinant associated with maternal mortality and adverse birth outcomes. Despite the accumulating body of evidence, scant research has delved into the correlation between chemical components of wildfire PM2.5 and the risk of HDP. Derived from data provided by the National Center for Health Statistics, singleton births from >2.68 million pregnant women were selected across 8 states (Arizona, AZ; California, CA, Idaho, ID, Montana, MT; Nevada, NV; Oregon, OR; Utah, UT, and Wyoming, WY) in the southwestern US from 2001 to 2004. A spatiotemporal model and a Goddard Earth Observing System chemical transport model were employed to forecast daily concentrations of total and wildfire PM2.5-derived exposure. Various modeling techniques including unadjusted analyses, covariate-adjusted models, propensity-score matching, and double robust typical logit models were applied to assess the relationship between wildfire PM2.5 exposure and gestational hypertension and eclampsia. Exposure to fire PM2.5, fire-sourced black carbon (BC) and organic carbon (OC) were associated with an augmented risk of gestational hypertension (ORPM2.5 = 1.125, 95 % CI: 1.109,1.141; ORBC = 1.247, 95 % CI: 1.214,1.281; OROC = 1.153, 95 % CI: 1.132, 1.174) and eclampsia (ORPM2.5 = 1.217, 95 % CI: 1.145,1.293; ORBC = 1.458, 95 % CI: 1.291,1.646; OROC = 1.309, 95 % CI: 1.208,1.418) during the pregnancy exposure window with the strongest effect. The associations were stronger that the observed effects of ambient PM2.5 in which the sources primarily came from urban emissions. Social vulnerability index (SVI), education years, pre-pregnancy diabetes, and hypertension acted as effect modifiers. Gestational exposure to wildfire PM2.5 and specific chemical components (BC and OC) increased gestational hypertension and eclampsia risk in the southwestern United States.
Collapse
Affiliation(s)
- Tong Zhang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China
| | - Amber X Ren
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA
| | - Mingkun Tong
- Institute of Reproductive and Child Health / Ministry of Health Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yang Li
- Department of Environmental Science, Baylor University, Waco, TX, USA
| | - Pauline Mendola
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA
| | - Xushen Chen
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, Zhejiang Province, China.
| | - Meng Wang
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY, USA; RENEW Institute, University at Buffalo, Buffalo, NY, USA; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, WA, USA.
| |
Collapse
|
4
|
Cui Z, Yi X, Huang Y, Li M, Zhang Z, Kuang L, Song R, Liu J, Pan R, Yi W, Jin X, Song J, Cheng J, Wang W, Su H. Effects of socioeconomic status and regional inequality on the association between PM 2.5 and its components and cardiometabolic multimorbidity: A multicenter population-based survey in eastern China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 946:174453. [PMID: 38964410 DOI: 10.1016/j.scitotenv.2024.174453] [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: 05/06/2024] [Revised: 06/25/2024] [Accepted: 07/01/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND Despite evidence linking fine particulate matter (PM2.5) to cardiometabolic multimorbidity (CMM), the impact of its components remains unclear. Socioeconomic status (SES) and regional disparities may confound their association. We aim to evaluate the associations between PM2.5 components and CMM and explore how socioeconomic status and regional disparities affect these relationships. METHODS We recruited 108,941 participants aged 35-76 years from ten cities in eastern China. Individual exposure was assessed using Tracking Air Pollution in China (TAP) data, including PM2.5 and five components: ammonium (NH4+), black carbon (BC), nitrates (NO3-), organic matter (OM), and sulfates (SO42-). Generalized linear models and quantile g-computation models were employed to quantify the effects of PM2.5 components on CMM and to identify key components. Stratified analyses were performed to investigate the modifying effect of SES and regional disparities. RESULTS For each increase in interquartile range (IQR), BC (odds ratio [OR] 1.37, 95 % CI 1.29-1.47), OM (1.38, 1.29-1.48), NH4+ (1.31, 1.21-1.40), NO3- (1.34, 1.25-1.44), and SO42- (1.28, 1.20-1.38) were positively associated with CMM. Joint exposure to five components was significantly positively associated with CMM (OR: 1.27, 95 % CI: 1.21-1.33), with SO42- having the highest estimated weight, followed by NO3- and BC. These associations were stronger for participants from low socio-economic status and poor regions. CONCLUSION In summary, we found a stronger hazard effect of PM2.5 and its components on CMM, compared to those suffering from CMDs, particularly among participants with low socioeconomic status and in poor regions. SO42- may be a primary contributor to the association between PM2.5 components and CMM. These findings underscore the importance of prioritizing CMM and targeting SO42-related pollution sources in health policies, particularly amid China's aging population, reducing environmental health inequalities is critical.
Collapse
Affiliation(s)
- Zhiqian Cui
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xinxu Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Yuxin Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Ming Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Zichen Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Lingmei Kuang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China
| | | | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui 230032, China.
| |
Collapse
|
5
|
Lu X, Zhang Y, Jiang R, Qin G, Ge Q, Zhou X, Zhou Z, Ni Z, Zhuang X. Interpregnancy interval, air pollution, and the risk of low birth weight: a retrospective study in China. BMC Public Health 2024; 24:2529. [PMID: 39289643 PMCID: PMC11409551 DOI: 10.1186/s12889-024-19711-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Accepted: 08/07/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND Both interpregnancy intervals (IPI) and environmental factors might contribute to low birth weight (LBW). However, the extent to which air pollution influences the effect of IPIs on LBW remains unclear. We aimed to investigate whether IPI and air pollution jointly affect LBW. METHODS A retrospective cohort study was designed in this study. The data of birth records was collected from the Jiangsu Maternal Child Information System, covering January 2020 to June 2021 in Nantong city, China. IPI was defined as the duration between the delivery date for last live birth and date of LMP for the subsequent birth. The maternal exposure to ambient air pollutants during pregnancy-including particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5), PM10, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)-was estimated using a hybrid kriging-LUR-RF model. A novel air pollution score was proposed, assessing combined exposure to five pollutants (excluding CO) by summing their concentrations, weighted by LBW regression coefficients. Multivariate logistic regression models were used to estimate the effects of IPI, air pollution and their interactions on LBW. Relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (S) were utilized to assess the additive interaction. RESULTS Among 10, 512 singleton live births, the LBW rate was 3.7%. The IPI-LBW risk curve exhibited an L-shaped pattern. The odds ratios (ORs) for LBW for each interquartile range increase in PM2.5, PM10, O3 and the air pollution score were 1.16 (95% CI: 1.01-1.32), 1.30 (1.06-1.59), 1.22 (1.06-1.41), and 1.32 (1.10-1.60) during the entire pregnancy, respectively. An additive interaction between IPI and PM2.5 was noted during the first trimester. Compared to records with normal IPI and low PM2.5 exposure, those with short IPI and high PM2.5 exposure had the highest risk of LBW (relative risk = 3.53, 95% CI: 1.85-6.49, first trimester). CONCLUSION The study demonstrates a synergistic effect of interpregnancy interval and air pollution on LBW, indicating that rational birth spacing and air pollution control can jointly improve LBW outcomes.
Collapse
Affiliation(s)
- Xinyu Lu
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, No.9 Seyuan Road, Chongchuan District, Nantong, Jiangsu, China
| | - Yuyu Zhang
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, No.9 Seyuan Road, Chongchuan District, Nantong, Jiangsu, China
| | - Run Jiang
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, No.9 Seyuan Road, Chongchuan District, Nantong, Jiangsu, China
| | - Gang Qin
- Department of Infectious Diseases, Affiliated Hospital of Nantong University, No.20 Xisi Road, Chongchuan District, Nantong, Jiangsu, China
| | - Qiwei Ge
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, No.9 Seyuan Road, Chongchuan District, Nantong, Jiangsu, China
| | - Xiaoyi Zhou
- Nantong Center for Disease Control and Prevention, 189 Gongnong South Road, Chongchuan District, Nantong, Jiangsu, China
| | - Zixiao Zhou
- Faculty of Medical and Health, the University of Sydney, Sydney, NSW, Australia
| | - Zijun Ni
- School of Science, Nantong University, No.9 Seyuan Road, Chongchuan District, Nantong, Jiangsu, China
| | - Xun Zhuang
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, No.9 Seyuan Road, Chongchuan District, Nantong, Jiangsu, China.
| |
Collapse
|
6
|
Chu Z, Zhang Y, Guo B, Zhang X, Cao Y, Ji H, Sun B, Schikowski T, Zhao Q, Wang J, Chen Y. Long-term PM 2.5 exposure associated with severity of angina pectoris and related health status in patients admitted with acute coronary syndrome: Modification effect of genetic susceptibility and disease history. ENVIRONMENTAL RESEARCH 2024; 257:119232. [PMID: 38810823 DOI: 10.1016/j.envres.2024.119232] [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: 03/11/2024] [Revised: 05/08/2024] [Accepted: 05/25/2024] [Indexed: 05/31/2024]
Abstract
Long-term particulate matter with aerodynamic diameters ≤2.5 μm (PM2.5) exposure has been associated with the occurrence of acute coronary syndrome (ACS). However, the impact of PM2.5 exposure and its components on the severity of angina pectoris and disease-related health status in patients hospitalized for ACS is understudied. To assess the association between long-term exposure to PM2.5 components and the angina pectoris severity in ACS patients, as well as the modification effects of genetic factors and disease history in north China. During 2017-2019, 6729 ACS patients were collected in Shandong Province and Beijing, with their angina pectoris severity evaluated using Seattle Angina Questionnaire (SAQ). The 0-3 years' average concentrations of PM2.5 and its five major components were assigned to each patient's residential address. Linear mixed-effects model, weighted quantile regression, and quantile g-computation were used to estimate the effects of both single and joint associations between PM2.5 components and SAQ scores. The interactive effect was estimated by polygenic risk scores and disease history. For each interquartile range increase in PM2.5, the overall SAQ score changed by -3.71% (95%CI: -4.54% to -2.88%), with score of angina stability more affected than angina frequency and other dimensions of angina pectoris severity. Sulfate and ammonium were major contributors to the effect of PM2.5 exposure. Significant modification effect was only observed for disease history, especially for the dimension of physical limitation. Among a series of pre-existing diseases, patients with a family history of coronary artery disease, previous percutaneous coronary intervention or coronary artery bypass grafting, and stroke were more susceptible to PM2.5 exposure than others. Greater exposure to PM2.5 is associated with more serious angina pectoris and worse disease-related health status in ACS patients. Public health and clinical priority should be given to cutting down key effective components and protecting highly vulnerable individuals.
Collapse
Affiliation(s)
- Zunyan Chu
- Department of Epidemiology, School of Public Health/Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yan Zhang
- Medical Integration and Practice Center, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Bangjie Guo
- Department of Epidemiology, School of Public Health/Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Xiao Zhang
- Department of Emergency and Chest Pain Center, Qilu Hospital of Shandong University, Jinan, China; Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China
| | - Yingying Cao
- Department of Epidemiology, School of Public Health/Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Hongmei Ji
- Department of Emergency and Chest Pain Center, Qilu Hospital of Shandong University, Jinan, China; Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China
| | - Bo Sun
- Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, 40225, Germany
| | - Tamara Schikowski
- Department of Epidemiology, IUF-Leibniz Research Institute for Environmental Medicine, Düsseldorf, 40225, Germany
| | - Qi Zhao
- Department of Epidemiology, School of Public Health/Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
| | - Jiali Wang
- Department of Emergency and Chest Pain Center, Qilu Hospital of Shandong University, Jinan, China; Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China.
| | - Yuguo Chen
- Department of Emergency and Chest Pain Center, Qilu Hospital of Shandong University, Jinan, China; Shandong Provincial Clinical Research Center for Emergency and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China.
| |
Collapse
|
7
|
Wang SN, Shi YC, Lin S, He HF. Particulate matter 2.5 accelerates aging: Exploring cellular senescence and age-related diseases. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:116920. [PMID: 39208581 DOI: 10.1016/j.ecoenv.2024.116920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2024] [Revised: 08/17/2024] [Accepted: 08/20/2024] [Indexed: 09/04/2024]
Abstract
Exposure to Particulate matter 2.5 (PM2.5) accelerates aging, causing declines in tissue and organ function, and leading to diseases such as cardiovascular, neurodegenerative, and musculoskeletal disorders. PM2.5 is a major environmental pollutant and an exogenous pathogen in air pollution that is now recognized as an accelerator of human aging and a predisposing factor for several age-related diseases. In this paper, we seek to elucidate the mechanisms by which PM2.5 induces cellular senescence, such as genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, and mitochondrial dysfunction, and age-related diseases. Our goal is to increase awareness among researchers within the field of the toxicity of environmental pollutants and to advocate for personal and public health initiatives to curb their production and enhance population protection. Through these endeavors, we aim to promote longevity and health in older adults.
Collapse
Affiliation(s)
- Sheng-Nan Wang
- Department of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China
| | - Yan-Chuan Shi
- Centre of Neurological and Metabolic Research, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China; Group of Neuroendocrinology, Garvan Institute of Medical Research, 384 Victoria St, Sydney, Australia; St Vincent's Clinical School, Faculty of Medicine, UNSW Sydney, Australia
| | - Shu Lin
- Centre of Neurological and Metabolic Research, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China; Group of Neuroendocrinology, Garvan Institute of Medical Research, 384 Victoria St, Sydney, Australia.
| | - He-Fan He
- Department of Anesthesiology, the Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian Province, China.
| |
Collapse
|
8
|
Liu W, Zou H, Liu W, Qin J. The impact of PM 2.5 and its constituents on gestational diabetes mellitus: a retrospective cohort study. BMC Public Health 2024; 24:2249. [PMID: 39160489 PMCID: PMC11334325 DOI: 10.1186/s12889-024-19767-1] [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: 06/01/2024] [Accepted: 08/12/2024] [Indexed: 08/21/2024] Open
Abstract
BACKGROUND There is increasing evidence that exposure to PM2.5 and its constituents is associated with an increased risk of gestational diabetes mellitus (GDM), but studies on the relationship between exposure to PM2.5 constituents and the risk of GDM are still limited. METHODS A total of 17,855 pregnant women in Guangzhou were recruited for this retrospective cohort study, and the time-varying average concentration method was used to estimate individual exposure to PM2.5 and its constituents during pregnancy. Logistic regression was used to assess the relationship between exposure to PM2.5 and its constituents and the risk of GDM, and the expected inflection point between exposure to PM2.5 and its constituents and the risk of GDM was estimated using logistic regression combined with restricted cubic spline curves. Stratified analyses and interaction tests were performed. RESULTS After adjustment for confounders, exposure to PM2.5 and its constituents (NO3-, NH4+, and OM) was positively associated with the risk of GDM during pregnancy, especially when exposure to NO3- and NH4+ occurred in the first to second trimester, with each interquartile range increase the risk of GDM by 20.2% (95% CI: 1.118-1.293) and 18.2% (95% CI. 1.107-1.263), respectively. The lowest inflection points between PM2.5, SO42-, NO3-, NH4+, OM, and BC concentrations and GDM risk throughout the gestation period were 18.96, 5.80, 3.22, 2.67, 4.77 and 0.97 µg/m3, respectively. In the first trimester, an age interaction effect between exposure to SO42-, OM, and BC and the risk of GDM was observed. CONCLUSIONS This study demonstrates a positive association between exposure to PM2.5 and its constituents and the risk of GDM. Specifically, exposure to NO3-, NH4+, and OM was particularly associated with an increased risk of GDM. The present study contributes to a better understanding of the effects of exposure to PM2.5 and its constituents on the risk of GDM.
Collapse
Affiliation(s)
- Weiqi Liu
- Department of Clinical Laboratory, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, 510800, Guangdong, People's Republic of China.
| | - Haidong Zou
- Department of Obstetrics, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, 510800, Guangdong, People's Republic of China
| | - Weiling Liu
- Department of Clinical Laboratory, Foshan Fosun Chancheng Hospital, Foshan, 528000, Guangdong, People's Republic of China
| | - Jiangxia Qin
- Department of Obstetrics, The Maternal and Children Health Care Hospital (Huzhong Hospital) of Huadu, Guangzhou, 510800, Guangdong, People's Republic of China
| |
Collapse
|
9
|
Zhang D, Liu X, Sun L, Li D, Du J, Yang H, Yu D, Li C. Fine particulate matter disrupts bile acid homeostasis in hepatocytes via binding to and activating farnesoid X receptor. Toxicology 2024; 506:153850. [PMID: 38821196 DOI: 10.1016/j.tox.2024.153850] [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: 04/01/2024] [Revised: 05/20/2024] [Accepted: 05/28/2024] [Indexed: 06/02/2024]
Abstract
Fine particulate matter (PM2.5)-induced metabolic disorders have attracted increasing attention, however, the underlying molecular mechanism of PM2.5-induced hepatic bile acid disorder remains unclear. In this study, we investigated the effects of PM2.5 components on the disruption of bile acid in hepatocytes through farnesoid X receptor (FXR) pathway. The receptor binding assays showed that PM2.5 extracts bound to FXR directly, with half inhibitory concentration (IC50) value of 21.7 μg/mL. PM2.5 extracts significantly promoted FXR-mediated transcriptional activity at 12.5 μg/mL. In mouse primary hepatocytes, we found PM2.5 extracts (100 μg/mL) significantly decreased the total bile acid levels, inhibited the expression of bile acid synthesis gene (Cholesterol 7 alpha-hydroxylase, Cyp7a1), and increased the expression of bile acid transport genes (Multidrug resistance associated protein 2, Abcc2; and Bile salt export pump, Abcb11). Moreover, these alterations were significantly attenuated by knocking down FXR in hepatocytes. We further divided the organic components and water-soluble components from PM2.5, and found that two components bound to and activated FXR, and decreased the bile acid levels in hepatocytes. In addition, benzo[a]pyrene (B[a]P) and cadmium (Cd) were identified as two bioactive components in PM2.5-induced bile acid disorders through FXR signaling pathway. Overall, we found PM2.5 components could bind to and activate FXR, thereby disrupting bile acid synthesis and transport in hepatocytes. These new findings also provide new insights into PM2.5-induced toxicity through nuclear receptor pathways.
Collapse
Affiliation(s)
- Donghui Zhang
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Xinya Liu
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Lanchao Sun
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Daochuan Li
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Jingyue Du
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Huizi Yang
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Dianke Yu
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China
| | - Chuanhai Li
- School of Public Health, Qingdao University, 308 Ningxia Road, Qingdao 266071, China.
| |
Collapse
|
10
|
Guo J, Lei L, Yang H, Zhou B, Fan D, Wu B, Wang G, Yu L, Zhang C, Zhang W, Han Q, Zhang XY, Zhao J. Effects of nasal allergens and environmental particulate matter on brainstem metabolites and the consequence of brain-spleen axis in allergic rhinitis. ENVIRONMENT INTERNATIONAL 2024; 190:108890. [PMID: 39033732 DOI: 10.1016/j.envint.2024.108890] [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: 04/16/2024] [Revised: 06/19/2024] [Accepted: 07/15/2024] [Indexed: 07/23/2024]
Abstract
BACKGROUND The growing consensus links exposure to fine particulate matter (PM2.5) with an increased risk of respiratory diseases. However, little is known about the additional effects of particulate matter on brainstem function in allergic rhinitis (AR). Furthermore, it is unknown to what extent the PM2.5-induced effects in the brainstem affect the inflammatory response in AR. This study aimed to determine the effects, mechanisms and consequences of brainstem neural activity altered by allergenic stimulation and PM2.5 exposure. METHODS Using an AR model of ovalbumin (OVA) elicitation and whole-body PM2.5 exposure, the metabolic profile of the brainstem post-allergen stimulation was characterized through in vivo proton magnetic resonance imaging (1H-MRS). Then, the transient receptor potential vanilloid-1 (TRPV1) neuronal expression and sensitivity in the trigeminal nerve in AR were investigated. The link between TRPV1 expression and brainstem differential metabolites was also determined. Finally, we evaluated the mediating effects of brainstem metabolites and the consequences in the brain-spleen axis in the inflammatory response of AR. RESULTS Exposure to allergens and PM2.5 led to changes in the metabolic profiles of the brainstem, particularly affecting levels of glutamine (Gln) and glutamate (Glu). This exposure also increased the expression and sensitivity of TRPV1+ neurons in the trigeminal nerve, with the levels of TRPV1 expression closely linked to the brainstem metabolism of Glu and Gln. Moreover, allergens increased the activity of p38, while PM2.5 led to the phosphorylation of p38 and ERK, resulting in the upregulation of TRPV1 expression. The brainstem metabolites Glu and Gln were found to partially mediate the impact of TRPV1 on AR inflammation, which was supported by the presence of pro-inflammatory changes in the brain-spleen axis. CONCLUSION Brainstem metabolites are altered under allergen stimulation and additional PM2.5 exposure in AR via sensitization of the trigeminal nerve, which exacerbates the inflammatory response via the brain-splenic axis.
Collapse
Affiliation(s)
- JianShu Guo
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Lei Lei
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China; The Changning District Center for Disease Control and Prevention, Shanghai, China
| | - Haibo Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Bin Zhou
- State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China
| | - DongXia Fan
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Biao Wu
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Ge Wang
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Lu Yu
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - ChiHang Zhang
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - Wenqing Zhang
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China
| | - QingJian Han
- State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, China.
| | - Xiao-Yong Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; College of Health Science and Technology & Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - JinZhuo Zhao
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Fudan University, Shanghai, China.
| |
Collapse
|
11
|
Abel ED, Gloyn AL, Evans-Molina C, Joseph JJ, Misra S, Pajvani UB, Simcox J, Susztak K, Drucker DJ. Diabetes mellitus-Progress and opportunities in the evolving epidemic. Cell 2024; 187:3789-3820. [PMID: 39059357 PMCID: PMC11299851 DOI: 10.1016/j.cell.2024.06.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 06/21/2024] [Accepted: 06/24/2024] [Indexed: 07/28/2024]
Abstract
Diabetes, a complex multisystem metabolic disorder characterized by hyperglycemia, leads to complications that reduce quality of life and increase mortality. Diabetes pathophysiology includes dysfunction of beta cells, adipose tissue, skeletal muscle, and liver. Type 1 diabetes (T1D) results from immune-mediated beta cell destruction. The more prevalent type 2 diabetes (T2D) is a heterogeneous disorder characterized by varying degrees of beta cell dysfunction in concert with insulin resistance. The strong association between obesity and T2D involves pathways regulated by the central nervous system governing food intake and energy expenditure, integrating inputs from peripheral organs and the environment. The risk of developing diabetes or its complications represents interactions between genetic susceptibility and environmental factors, including the availability of nutritious food and other social determinants of health. This perspective reviews recent advances in understanding the pathophysiology and treatment of diabetes and its complications, which could alter the course of this prevalent disorder.
Collapse
Affiliation(s)
- E Dale Abel
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
| | - Anna L Gloyn
- Department of Pediatrics, Division of Endocrinology & Diabetes, Department of Genetics, Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA
| | - Carmella Evans-Molina
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Joshua J Joseph
- Division of Endocrinology, Diabetes and Metabolism, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Shivani Misra
- Department of Metabolism, Digestion and Reproduction, Imperial College London, and Imperial College NHS Trust, London, UK
| | - Utpal B Pajvani
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Judith Simcox
- Howard Hughes Medical Institute, Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Katalin Susztak
- Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel J Drucker
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada; Department of Medicine, University of Toronto, Toronto, ON, Canada
| |
Collapse
|
12
|
Liu J, Wang P, Shang L, Ye F, Liu L, He Z. Adverse Associations of Long-Term Exposure to PM 2.5 and Its Components with Platelet Traits among Subway Shift-Workers without Air Purifier Use. TOXICS 2024; 12:529. [PMID: 39195631 PMCID: PMC11359941 DOI: 10.3390/toxics12080529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 07/09/2024] [Accepted: 07/11/2024] [Indexed: 08/29/2024]
Abstract
Air purifier use, shift work, and long-term exposure to fine particulate matter (PM2.5) are linked to platelet abnormality. However, the role of air purifier use and shift work in the individual or joint associations of PM2.5 and its components with platelet indices are largely unknown. A total of 8772 participants were recruited from a population of subway workers in China. PM2.5 and its component data were obtained from the Tracking Air Pollution in China dataset. The role of air purifier use and shift work in the association between PM2.5 and its components and platelet indices were analyzed. Among shift workers without air purifier use, positive associations of PM2.5 and each component in PM2.5 with the mean platelet volume (MPV) or platelet counts (PLT) were observed, whereas negative associations of PM2.5 and each component in PM2.5 with the platelet distribution width (PDW) were observed. Furthermore, estimated changes (95%CIs) in PLT, MPV, and PDW in response to each 10th percentile increment in the mixture of PM2.5 and its components were 0.8657 (0.2496, 1.4819), 0.0192 (0.0054, 0.0329), and -0.0648 (-0.0945, -0.0351), respectively, and sulfate in PM2.5 was the major contributor to those associations. Long-term exposure to PM2.5 and its components was related to increased platelet disorders among shift workers without air purifier use, and those associations were mainly attributed to sulfate in PM2.5.
Collapse
Affiliation(s)
- Junling Liu
- Wuhan Center for Disease Control and Prevention, Wuhan 430024, China; (J.L.); (P.W.); (L.S.)
| | - Pei Wang
- Wuhan Center for Disease Control and Prevention, Wuhan 430024, China; (J.L.); (P.W.); (L.S.)
| | - Lv Shang
- Wuhan Center for Disease Control and Prevention, Wuhan 430024, China; (J.L.); (P.W.); (L.S.)
| | - Fang Ye
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (F.Y.); (L.L.)
| | - Li Liu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; (F.Y.); (L.L.)
| | - Zhenyu He
- Wuhan Center for Disease Control and Prevention, Wuhan 430024, China; (J.L.); (P.W.); (L.S.)
| |
Collapse
|
13
|
Zhang N, Liu X, Wang L, Zhang Y, Xiang Y, Cai J, Xu H, Xiao X, Zhao X. Lifestyle factors and their relative contributions to longitudinal progression of cardio-renal-metabolic multimorbidity: a prospective cohort study. Cardiovasc Diabetol 2024; 23:265. [PMID: 39026309 PMCID: PMC11264843 DOI: 10.1186/s12933-024-02347-3] [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: 04/24/2024] [Accepted: 07/01/2024] [Indexed: 07/20/2024] Open
Abstract
BACKGROUND The role of lifestyle factors and their relative contributions to the development and mortality of cardio-renal-metabolic multimorbidity (CRMM) remains unclear. METHODS A study was conducted with 357,554 UK Biobank participants. CRMM was defined as the coexistence of two or three cardio-renal-metabolic diseases (CRMDs), including cardiovascular disease (CVD), type 2 diabetes (T2D) and chronic kidney disease (CKD). The prospective study examined the associations of individual and combined lifestyle scores (diet, alcohol consumption, smoking, physical activity, sedentary behavior, sleep duration and social connection) with longitudinal progression from healthy to first cardio-renal-metabolic disease (FCRMD), then to CRMM, and ultimately to death, using a multistate model. Subsequently, quantile G-computation was employed to assess the relative contribution of each lifestyle factor. RESULTS During a median follow-up of 13.62 years, lifestyle played crucial role in all transitions from healthy to FCRMD, then to CRMM, and ultimately to death. The hazard ratios (95% CIs) per score increase were 0.91 (0.90, 0.91) and 0.90 (0.89, 0.91) for healthy to FCRMD, and for FCRMD to CRMM, and 0.84 (0.83, 0.86), 0.87 (0.86, 0.89), and 0.90 (0.88, 0.93) for mortality risk from healthy, FCRMD, and CRMM, respectively. Among the seven factors, smoking status contributed to high proportions for the whole disease progression, accounting for 19.88-38.10%. High-risk diet contributed the largest proportion to the risk of transition from FCRMD to CRMM, with 22.53%. Less-frequent social connection contributed the largest proportion to the risk of transition from FCRMD to death, with 28.81%. When we further consider the disease-specific transitions, we find that lifestyle scores had slightly stronger associations with development to T2D than to CVD or CKD. CONCLUSIONS Our study indicates that a healthy lifestyle may have a protective effect throughout the longitudinal progression of CRMM, informing more effective management and treatment. Smoking status, diet, and social connection played pivotal roles in specific disease transitions.
Collapse
Affiliation(s)
- Ning Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Xiang Liu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Lele Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Yuan Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Yi Xiang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Jiajie Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| | - Hao Xu
- State Key Laboratory of Oral Diseases, National Clinical Research Center for Oral Diseases, Research Unit of Oral Carcinogenesis and Management, West China Hospital of Stomatology, Chinese Academy of Medical Sciences , Sichuan University, Chengdu, 610041, China
| | - Xiong Xiao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610041, China
| |
Collapse
|
14
|
Zhao J, Mei Y, Li A, Zhou Q, Zhao M, Xu J, Li Y, Li K, Yang M, Xu Q. Association between PM 2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation. CHEMOSPHERE 2024; 359:142251. [PMID: 38710413 DOI: 10.1016/j.chemosphere.2024.142251] [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: 01/22/2024] [Revised: 04/17/2024] [Accepted: 05/03/2024] [Indexed: 05/08/2024]
Abstract
BACKGROUND The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear. METHOD A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively. RESULT PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP. CONCLUSION Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.
Collapse
Affiliation(s)
- Jiaxin Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China; Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Quan Zhou
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Yanbing Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Kai Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Ming Yang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, 100005, China.
| |
Collapse
|
15
|
Hou J, Sun H, Lu B, Yue Y, Li X, Ban K, Fu M, Zhang B, Luo X. Accelerated biological aging mediated associations of ammonium, sulfate in fine particulate matter with liver cirrhosis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 929:172638. [PMID: 38643869 DOI: 10.1016/j.scitotenv.2024.172638] [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: 01/02/2024] [Revised: 04/02/2024] [Accepted: 04/18/2024] [Indexed: 04/23/2024]
Abstract
BACKGROUND Although both air pollution and aging are related to the development of liver cirrhosis, the role of biological aging in association of the mixture of fine particulate matter (PM2.5) and its constituents with liver cirrhosis was unknown. METHODS This case-control retrospective study included 100 liver cirrhosis patients and 100 control subjects matched by age and sex. The concentrations of PM2.5 and its constituents were estimated for patients using machine-learning methods. The clinical biomarkers were used to calculate biological age using the Klemera-Doubalmethod (KDM) algorithms. Individual associations of PM2.5 and its constituents or biological age with liver cirrhosis were analyzed by generalized linear models. WQS and BKMR were applied to analyze association of mixture of PM2.5 and its constituents with liver cirrhosis. The mediation effect of biological age on associations of PM2.5 and its constituents with liver cirrhosis was further explored. RESULTS we found that each 1-unit increment in NH4+, NO3-, SO42- and biological age were related to 3.618-fold (95%CI: 1.896, 6.904), 1.880-fold (95%CI: 1.319, 2.680), 2.955-fold (95%CI: 1.656, 5.272) and 1.244-fold (95%CI: 1.093, 1.414) increased liver cirrhosis. Both WQS and BKMR models showed that the mixture of PM2.5 and its constituents was related to increased liver cirrhosis. Furthermore, the mediated proportion of biological age on associations of NH4+ and SO42- with liver cirrhosis were 14.7 % and 14.6 %, respectively. CONCLUSIONS Biological aging may partly explain the exposure to PM2.5 and its constituents in association with increased risk for liver cirrhosis, implying that delaying the aging process may be a key step for preventing PM2.5-related liver cirrhosis risk.
Collapse
Affiliation(s)
- Jian Hou
- Department of Gastroenterology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, PR China; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Huizhen Sun
- Hubei Provincial Center for Disease Control and Prevention, Hubei, Wuhan, PR China
| | - Bingxin Lu
- Department of Gastroenterology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, PR China
| | - Yanqin Yue
- Department of Gastroenterology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, PR China
| | - Xianxi Li
- Department of Gastroenterology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, PR China
| | - Kangjia Ban
- School of Architecture, Zhengzhou University, Zhengzhou, Henan, PR China
| | - Mengze Fu
- School of Architecture, Zhengzhou University, Zhengzhou, Henan, PR China.
| | - Bingyong Zhang
- Department of Gastroenterology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, PR China.
| | - Xiaoying Luo
- Department of Gastroenterology, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, Henan, PR China.
| |
Collapse
|
16
|
Chen L, Yuan W, Geng M, Xu R, Xing Y, Wen B, Wu Y, Ren X, Shi Y, Zhang Y, Song X, Qin Y, Wang R, Jiang J, Dong Z, Liu J, Guo T, Song Z, Wang L, Ma Y, Dong Y, Song Y, Ma J. Differentiated impacts of short-term exposure to fine particulate constituents on infectious diseases in 507 cities of Chinese children and adolescents: A nationwide time-stratified case-crossover study from 2008 to 2021. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 928:172299. [PMID: 38614340 DOI: 10.1016/j.scitotenv.2024.172299] [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: 01/11/2024] [Revised: 03/11/2024] [Accepted: 04/05/2024] [Indexed: 04/15/2024]
Abstract
This study assesses the association of short-term exposure to PM2.5 (particles ≤2.5 μm) on infectious diseases among Chinese children and adolescents. Analyzing data from 507 cities (2008-2021) on 42 diseases, it focuses on PM2.5 components (black carbon (BC), ammonium (NH4+), inorganic nitrate (NO3-), organic matter (OM), and sulfate (SO42-)). PM2.5 constituents significantly associated with incidence. Sulfate showed the most substantial effect, increasing all-cause infectious disease risk by 2.72 % per interquartile range (IQR) increase. It was followed by BC (2.04 % increase), OM (1.70 %), NO3- (1.67 %), and NH4+ (0.79 %). Specifically, sulfate and BC had pronounced impacts on respiratory diseases, with sulfate linked to a 10.73 % increase in seasonal influenza risk and NO3- to a 16.39 % rise in tuberculosis. Exposure to PM2.5 also marginally increased risks for gastrointestinal, enterovirus, and vectorborne diseases like dengue (7.46 % increase with SO42-). Sexually transmitted and bloodborne diseases saw an approximate 6.26 % increase in incidence, with specific constituents linked to diseases like hepatitis C and syphilis. The study concludes that managing PM2.5 levels could substantially reduce infectious disease incidence, particularly in China's middle-northern regions. It highlights the necessity of stringent air quality standards and targeted disease prevention, aligning PM2.5 management with international guidelines for public health protection.
Collapse
Affiliation(s)
- Li Chen
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China
| | - Wen Yuan
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Mengjie Geng
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Rongbin Xu
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Yi Xing
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Bo Wen
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Yao Wu
- School of Public Health and Preventive Medicine, Monash University, Melbourne 3004, Australia
| | - Xiang Ren
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yue Shi
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yi Zhang
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Xinli Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Yang Qin
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - RuoLin Wang
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Jianuo Jiang
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Ziqi Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Jieyu Liu
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Tongjun Guo
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Zhiying Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China
| | - Liping Wang
- Division of Infectious Disease Control and Prevention, Key Laboratory of Surveillance and Early Warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Yinghua Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China
| | - Yanhui Dong
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China.
| | - Yi Song
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China.
| | - Jun Ma
- Institute of Child and Adolescent Health, School of Public Health, Peking University; National Health Commission Key Laboratory of Reproductive Health, Beijing 100191, China; UNESCO Chair on Global Health and Education of Peking University, Beijing 100191, China
| |
Collapse
|
17
|
Cai C, Zhu S, Qin M, Li X, Feng C, Yu B, Dai S, Qiu G, Li Y, Ye T, Zhong W, Shao Y, Zhang L, Jia P, Yang S. Long-term exposure to PM 2.5 chemical constituents and diabesity: evidence from a multi-center cohort study in China. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2024; 47:101100. [PMID: 38881803 PMCID: PMC11179652 DOI: 10.1016/j.lanwpc.2024.101100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 04/30/2024] [Accepted: 05/08/2024] [Indexed: 06/18/2024]
Abstract
Background Long-term exposure to PM2.5 is known to increase the risks for diabetes and obesity, but its effects on their coexistence, termed diabesity, remain uncertain. This study aimed to investigate the associations of long-term exposure to PM2.5 and its chemical constituents with the risks for diabesity, diabetes, and obesity. Methods This cross-sectional study used the baseline data of a multi-center cohort, consisting of three provincially representative cohorts comprising a total of 134,403 participants from the eastern (Fujian Province), central (Hubei Province), and western (Yunnan Province) regions of China. Obesity and diabetes, and diabesity were identified by a body mass index (BMI) ≥28 kg/m2 and fasting plasma glucose (FPG) ≥126 mg/dL. The average concentrations of PM2.5 and five chemical constituents (NO3 -, SO4 2-, NH4 +, organic matter, and black carbon) over participants' residence during the past three years were estimated using machine learning models. Logistic regression models with double robust estimators, Bayesian kernel machine regression, and weighted quantile sum regression were employed to estimate independent and joint effects of PM2.5 chemical constituents on the risks for diabesity, diabetes, and obesity, as well as the differences from the effects on obesity. Stratified analyses were performed to examine effect modification of sociodemographic and lifestyle factors. Findings There were 129,244 participants with a mean age of 54.1 ± 13.8 years included in the study. Each interquartile range increase in PM2.5 concentration (8.53 μg/m3) was associated with an increased risk for diabesity (OR = 1.23 [1.17, 1.30]), diabetes only (OR = 1.16 [1.13, 1.19]), and obesity only (OR = 1.03 [1.00, 1.05]). Long-term exposure to each PM2.5 chemical constituent was associated with an increased risk for diabesity, where organic matter exposure, with maximum weight (48%), was associated with a higher risk for diabesity (OR = 1.21 [1.16, 1.27]). Among those with obesity, black carbon contributed most (68%) to the joint effect of PM2.5 chemical constituents on diabesity (OR = 1.16 [1.11, 1.22]). Physical activity reduced adverse effects of PM2.5 on diabesity. Also, additive rather than multiplicative effects of obesity on the PM2.5-diabetes association were observed. Interpretation Long-term exposure to PM2.5 and its chemical constituents was associated with an increased risk for diabesity, stronger than associations for diabetes and obesity alone. The main constituents associated with diabesity and obesity were black carbon and organic matter. Funding National Natural Science Foundation of China (42271433, 723B2017), National Key R&D Program of China (2023YFC3604702), Fundamental Research Funds for the Central Universities (2042023kfyq04, 2042024kf1024), the Science and Technology Major Project of Tibetan Autonomous Region of China (XZ202201ZD0001G), Science and technology project of Tibet Autonomous Region(XZ202303ZY0007G), Key R&D Project of Sichuan Province (2023YFS0251), Renmin Hospital of Wuhan University (JCRCYG-2022-003), Jiangxi Provincial 03 Special Foundation and 5G Program (20224ABC03A05), Wuhan University Specific Fund for Major School-level Internationalization Initiatives (WHU-GJZDZX-PT07).
Collapse
Affiliation(s)
- Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Shuzhen Zhu
- Hubei Center for Disease Control and Prevention, Wuhan, China
| | - Mingfang Qin
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Xiaoqing Li
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Chuanteng Feng
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Shaoqing Dai
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, the Netherlands
| | - Ge Qiu
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
| | - Yuchen Li
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
- Department of Geography, The Ohio State University, Columbus, OH, USA
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Wenling Zhong
- Fujian Provincial Center for Disease Control and Prevention, Fuzhou, China
| | - Ying Shao
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Lan Zhang
- Hubei Center for Disease Control and Prevention, Wuhan, China
| | - Peng Jia
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
- Hubei Luojia Laboratory, Wuhan, China
- Renmin Hospital, Wuhan University, Wuhan, China
- School of Public Health, Wuhan University, Wuhan, China
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
- International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
- Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, China
- Respiratory Department, Chengdu Seventh People's Hospital, Chengdu, China
| |
Collapse
|
18
|
Wei Y, Chen Y, Hong Y, Chen J, Li HB, Li H, Yao X, Mehmood T, Feng X, Luo XS. Comparative in vitro toxicological effects of water-soluble and insoluble components of atmospheric PM 2.5 on human lung cells. Toxicol In Vitro 2024; 98:105828. [PMID: 38621549 DOI: 10.1016/j.tiv.2024.105828] [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: 01/04/2024] [Revised: 03/12/2024] [Accepted: 04/11/2024] [Indexed: 04/17/2024]
Abstract
Fine particulates in city air significantly impact human health, but the hazardous compositional mechanisms are still unclear. Besides the toxicity of environmental PM2.5 to in vitro human lung epithelial cells (A549), the independent cytotoxicity of PM2.5-bound water-soluble (WS-PM2.5) and water-insoluble (WIS-PM2.5) fractions were also compared by cell viability, oxidative stress (reactive oxygen species, ROS), and inflammatory injury (IL-6 and TNF-α). The cytotoxicity of PM2.5 varied significantly by sampling season and place, with degrees greater in winter and spring than in summer and autumn, related to corresponding trend of air PM2.5 level, and also higher in industrial than urban site, although their PM2.5 pollution levels were comparable. The PM2.5 bound metals (Ni, Cr, Fe, and Mn) may contribute to cellular injury. Both WS-PM2.5 and WIS-PM2.5 posed significant cytotoxicity, that WS-PM2.5 was more harmful than WIS-PM2.5 in terms of decreasing cell viability and increasing inflammatory cytokines production. In particular, industrial samples were usually more toxic than urban samples, and those from summer were generally less toxic than other seasons. Hence, in order to mitigate the health risks of PM2.5 pollution, the crucial targets might be components of heavy metals and soluble fractions, and sources in industrial areas, especially during the cold seasons.
Collapse
Affiliation(s)
- Yaqian Wei
- International Center for Ecology, Meteorology, and Environment, School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Yan Chen
- International Center for Ecology, Meteorology, and Environment, School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China; Jiangsu Environmental Engineering Technology Co., Ltd., Nanjing 210036, China
| | - Youwei Hong
- Center for Excellence in Regional Atmospheric Environment, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Jinsheng Chen
- Center for Excellence in Regional Atmospheric Environment, Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Hong-Bo Li
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China
| | - Hanhan Li
- International Center for Ecology, Meteorology, and Environment, School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xuewen Yao
- International Center for Ecology, Meteorology, and Environment, School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Tariq Mehmood
- Helmholtz Centre for Environmental Research - UFZ, Department of Environmental Engineering, Permoserstr. 15, Leipzig D-04318, Germany
| | - Xinyuan Feng
- International Center for Ecology, Meteorology, and Environment, School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xiao-San Luo
- International Center for Ecology, Meteorology, and Environment, School of Ecology and Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| |
Collapse
|
19
|
Hu K, Cao B, Lu H, Xu J, Zhang Y, Wang C. Changes in PM 2.5-related diabetes risk under the implementation of the clean air act in Shanghai. Diabetes Res Clin Pract 2024; 212:111716. [PMID: 38777130 DOI: 10.1016/j.diabres.2024.111716] [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: 04/18/2024] [Revised: 05/15/2024] [Accepted: 05/19/2024] [Indexed: 05/25/2024]
Abstract
OBJECTIVES We examined the associations between PM2.5 exposure and Type 2 diabetes mellitus risk under the implementation of the Clean Air Act (CAA) among high-risk population for diabetes in Shanghai. METHODS A total of 10,499 subjects from the Shanghai High-Risk Diabetic Screen (SHiDS) project between 2002 and 2018, linked with remotely sensed PM2.5 concentrations, were enrolled in this study. Ordinary least squares and logistic regression were applied to explore associations between PM2.5 and diabetes risk in various exposure periods. RESULTS In year 2002-2013 (before CAA), the diabetes risk increased 7.5 % (95 % CI: 1.018-1.137), 8.0 % (95 % CI: 1.022-1.142) and 7.9 % (95 % CI: 1.021-1.141) under each 10 μg/m3 increase of long-term (1, 2 and 3 years) PM2.5 exposure, respectively. Elevated PM2.5 exposure were also associated with a significant increase in glycemic parameters before CAA implementation. However, in the year 2014-2018 (after CAA), the associations between PM2.5 exposure and diabetes risk were not significant after controlling for potential confounders. CONCLUSION Our findings suggest that long-term and high-level exposure to PM2.5 was associated with increased prevalence of diabetes. Moreover, the implementation of CAA might ameliorate PM2.5-related diabetes risk.
Collapse
Affiliation(s)
- Kai Hu
- Department of Sociology, School of Social and Public Administration, East China University of Science and Technology, Meilong Road 130, Xuhui District, Shanghai 200237, China
| | - Baige Cao
- Department of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China
| | - Huijuan Lu
- Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, The Metabolic Disease Biobank, Shanghai, China
| | - Jinfang Xu
- Department of Health Statistics, Naval Medical University, Shanghai 200433, China
| | - Yinan Zhang
- Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, The Metabolic Disease Biobank, Shanghai, China.
| | - Congrong Wang
- Department of Endocrinology & Metabolism, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
| |
Collapse
|
20
|
Feng H, Yang Y, Ye H, Xu J, Zhao M, Jin Y, Zhang S. Associations between PM 2.5 Components and Mortality of Ischemic Stroke, Chronic Obstructive Pulmonary Disease and Diabetes in Beijing, China. TOXICS 2024; 12:381. [PMID: 38922061 PMCID: PMC11209520 DOI: 10.3390/toxics12060381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 05/06/2024] [Accepted: 05/16/2024] [Indexed: 06/27/2024]
Abstract
Ischemic stroke (IS), chronic obstructive pulmonary disease (COPD) and diabetes mellitus (DM) account for a large burden of premature deaths. However, few studies have investigated the associations between fine particular matter (PM2.5) components and mortality of IS, COPD and DM. We aimed to examine these associations in Beijing, China. Data on daily mortality, air pollutants and meteorological factors from 2008 to 2011 in Beijing were collected. Daily concentrations of five PM2.5 components, namely, sulfate ion (SO42-), ammonium ion (NH4+), nitrate ion (NO3-), organic matter (OM) and black carbon (BC), were obtained from the Tracking Air Pollution (TAP) database in China. The association between PM2.5 components and daily deaths was explored using a quasi-Poisson regression with the distributed lag nonlinear model (DLNM). The average daily concentrations of SO42-, NH4+, NO3-, OM and BC were 11.24, 8.37, 12.00, 17.34 and 3.32 μg/m3, respectively. After adjusting for temperature, relative humidity, pressure, particulate matter less than 10 μm in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2), an IQR increase in OM at lag day 2 and lag day 6 was associated with an increased DM mortality risk (RR 1.038; 95% CI: 1.005-1.071) and COPD mortality risk (RR 1.013; 95% CI: 1.001-1.026). An IQR increase in BC at lag day 0 and lag day 6 was associated with increased COPD mortality risk (RR 1.228; 95% CI: 1.017-1.48, RR 1.059; 95% CI: 1.001-1.121). Cumulative exposure to SO42- and NH4+ was associated with an increased mortality risk for IS, with the highest effect found for lag of 0-7 days (RR 1.085; 95% CI: 1.010-1.167, RR 1.083; 95% CI: 1.003-1.169). These effects varied by sex and age group. This study demonstrated associations of short-term exposure to PM2.5 components with increased risk of IS, COPD and DM mortality in the general population. Our study also highlighted susceptible subgroups.
Collapse
Affiliation(s)
- Hao Feng
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China;
| | - Yisen Yang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; (Y.Y.); (H.Y.); (J.X.); (M.Z.)
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
| | - Hong Ye
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; (Y.Y.); (H.Y.); (J.X.); (M.Z.)
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; (Y.Y.); (H.Y.); (J.X.); (M.Z.)
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
| | - Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; (Y.Y.); (H.Y.); (J.X.); (M.Z.)
- Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
| | - Ye Jin
- Center for Digital Medicine and Artificial Intelligence, Institute of Clinical Medicine, Peking Union Medical College Hospital, Beijing 100730, China
- Department of Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| | - Shuyang Zhang
- Department of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China;
- Department of Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
| |
Collapse
|
21
|
Zhou H, Liang X, Zhang X, Wu J, Jiang Y, Guo B, Wang J, Meng Q, Ding X, Baima Y, Li J, Wei J, Zhang J, Zhao X. Associations of Long-Term Exposure to Fine Particulate Constituents With Cardiovascular Diseases and Underlying Metabolic Mediations: A Prospective Population-Based Cohort in Southwest China. J Am Heart Assoc 2024; 13:e033455. [PMID: 38761074 PMCID: PMC11179805 DOI: 10.1161/jaha.123.033455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 04/01/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND The health effects of particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5) might differ depending on compositional variations. Little is known about the joint effect of PM2.5 constituents on metabolic syndrome and cardiovascular disease (CVD). This study aims to evaluate the combined associations of PM2.5 components with CVD, identify the most detrimental constituent, and further quantify the mediation effect of metabolic syndrome. METHODS AND RESULTS A total of 14 427 adults were included in a cohort study in Sichuan, China, and were followed to obtain the diagnosis of CVD until 2021. Metabolic syndrome was defined by the simultaneous occurrence of multiple metabolic disorders measured at baseline. The concentrations of PM2.5 chemical constituents within a 1-km2 grid were derived based on satellite- and ground-based detection methods. Cox proportional hazard models showed that black carbon, organic matter (OM), nitrate, ammonium, chloride, and sulfate were positively associated with CVD risks, with hazard ratios (HRs) ranging from 1.24 to 2.11 (all P<0.05). Quantile g-computation showed positive associations with 4 types of CVD risks (HRs ranging from 1.48 to 2.25, all P<0.05). OM and chloride had maximum weights for CVD risks. Causal mediation analysis showed that the positive association of OM with total CVD was mediated by metabolic syndrome, with a mediation proportion of 1.3% (all P<0.05). CONCLUSIONS Long-term exposure to PM2.5 chemical constituents is positively associated with CVD risks. OM and chloride appear to play the most responsible role in the positive associations between PM2.5 and CVD. OM is probably associated with CVD through metabolic-related pathways.
Collapse
Affiliation(s)
- Hanwen Zhou
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xian Liang
- Chengdu Center for Disease Control and Prevention Chengdu Sichuan China
| | - Xueli Zhang
- Health Information Center of Sichuan Province Chengdu Sichuan China
| | - Jialong Wu
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Ye Jiang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Junhua Wang
- School of Public Health, The key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education Guizhou Medical University Guiyang China
| | - Qiong Meng
- Department of Epidemiology and Health Statistics, School of Public Health Kunming Medical University Kunming Yunnan China
| | - Xianbin Ding
- Chongqing Municipal Center for Disease Control and Prevention Chongqing China
| | | | - Jingzhong Li
- Tibet Center for Disease Control and Prevention Lhasa Tibet China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center University of Maryland College Park MD USA
| | - Juying Zhang
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital Sichuan University Chengdu Sichuan China
| |
Collapse
|
22
|
Wang S, Ma Y, Wu G, Du Z, Li J, Zhang W, Hao Y. Relationships between long-term exposure to major PM 2.5 constituents and outpatient visits and hospitalizations in Guangdong, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 348:123866. [PMID: 38537800 DOI: 10.1016/j.envpol.2024.123866] [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: 10/30/2023] [Revised: 03/22/2024] [Accepted: 03/23/2024] [Indexed: 04/01/2024]
Abstract
Ambient fine particulate matter (PM2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM2.5 constituents (WQS index) and outpatient visits (IR%, percentage increases in risk per unit WQS index increase:1.73, 95%CI: 1.72, 1.74) as well as hospitalizations (IR%:5.15, 95%CI: 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR%: 7.54, 95%CI: 7.33, 7.74 and IR%: 9.55, 95%CI: 8.36, 10.75, respectively) or decreased winter air temperatures (IR%: 1.88, 95%CI: 1.68, 2.08 and IR%: 4.87, 95%CI: 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM2.5 pollution.
Collapse
Affiliation(s)
- Shenghao Wang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Yujie Ma
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Gonghua Wu
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Zhicheng Du
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Jinghua Li
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China
| | - Wangjian Zhang
- Department of Medical Statistics, School of Public Health & Center for Health Information Research & Sun Yat-sen Global Health Institute, Sun Yat-sen University, Guangzhou 510080, China.
| | - Yuantao Hao
- Peking University Center for Public Health and Epidemic Preparedness & Response Peking University, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
| |
Collapse
|
23
|
Qiu T, Fang Q, Zeng X, Zhang X, Fan X, Zang T, Cao Y, Tu Y, Li Y, Bai J, Huang J, Liu Y. Short-term exposures to PM 2.5, PM 2.5 chemical components, and antenatal depression: Exploring the mediating roles of gut microbiota and fecal short-chain fatty acids. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 277:116398. [PMID: 38677066 DOI: 10.1016/j.ecoenv.2024.116398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 04/20/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND PM2.5 and its chemical components increase health risks and are associated with depression and gut microbiota. However, there is still limited evidence on whether gut microbiota and short-chain fatty acids (SCFAs) mediate the association between PM2.5, PM2.5 chemical components, and antenatal depression. The purpose of this study was to investigate the mediating role of maternal gut microbiota in correlations between short-term exposure to PM2.5, short-term exposure to PM2.5 chemical components, and antenatal depression. METHODS Demographic information and stool samples were collected from 75 pregnant women in their third trimester. Their exposure to PM2.5 and PM2.5 chemical components was measured. Participants were divided into the non-antenatal depression group or the antenatal depression group according to the cut-off of 10 points on the Edinburgh Postnatal Depression Scale (EPDS). The gut microbiota were analyzed using the 16 S rRNA-V3/V4 gene sequence, and the concentration of PM2.5 and its chemical components was calculated using the Tracking Air Pollution in China (TAP) database. Gas chromatography-mass spectrometry was used to analyze SCFAs in stool samples. In order to assess the mediating effects of gut microbiota and SCFAs, mediation models were utilized. RESULTS There were significant differences between gut microbial composition and SCFAs concentrations between the non-antenatal depression group and the antenatal depression group. PM2.5 and its chemical components were positively associated with EPDS scores and negatively associated with genera Enterococcus and Enterobacter. Genera Candidatus_Soleaferrea (β = -7.21, 95%CI -11.00 to -3.43, q = 0.01) and Enterococcus (β = -2.37, 95%CI -3.87 to -0.87, q = 0.02) were negatively associated with EPDS scores, indicating their potential protective effects against antenatal depression. There was no significant association between SCFAs and EPDS scores. The mediating role of Enterococcus between different lagged periods of PM2.5, PM2.5 chemical component exposure, and antenatal depression was revealed. For instance, Enterococcus explained 29.23% (95%CI 2.16-87.13%, p = 0.04) of associations between PM2.5 exposure level at the day of sampling (lag 0) and EPDS scores. CONCLUSION Our study highlights that Enterococcus may mediate the associations between PM2.5, PM2.5 chemical components, and antenatal depression. The mediating mechanism through which the gut microbiota influences PM2.5-induced depression in pregnant women still needs to be further studied.
Collapse
Affiliation(s)
- Tianlai Qiu
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Qingbo Fang
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Xueer Zeng
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China; Zhongnan Hospital of Wuhan University, Wuhan 430062, China
| | - Xu Zhang
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Xiaoxiao Fan
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Tianzi Zang
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Yanan Cao
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Yiming Tu
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Yanting Li
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China
| | - Jinbing Bai
- Emory University Nell Hodgson Woodruff School of Nursing, 1520 Clifton Road, Atlanta, GA 30322, USA
| | - Jing Huang
- Department of Occupational and Environmental Health Sciences, Peking University School of Public Health, Beijing 100191, China.
| | - Yanqun Liu
- Center for Women's and Children's Health Research, Wuhan University School of Nursing, Wuhan University, 169 Donghu Road, Wuhan 430071, China.
| |
Collapse
|
24
|
Bonanni LJ, Wittkopp S, Long C, Aleman JO, Newman JD. A review of air pollution as a driver of cardiovascular disease risk across the diabetes spectrum. Front Endocrinol (Lausanne) 2024; 15:1321323. [PMID: 38665261 PMCID: PMC11043478 DOI: 10.3389/fendo.2024.1321323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
The prevalence of diabetes is estimated to reach almost 630 million cases worldwide by the year 2045; of current and projected cases, over 90% are type 2 diabetes. Air pollution exposure has been implicated in the onset and progression of diabetes. Increased exposure to fine particulate matter air pollution (PM2.5) is associated with increases in blood glucose and glycated hemoglobin (HbA1c) across the glycemic spectrum, including normoglycemia, prediabetes, and all forms of diabetes. Air pollution exposure is a driver of cardiovascular disease onset and exacerbation and can increase cardiovascular risk among those with diabetes. In this review, we summarize the literature describing the relationships between air pollution exposure, diabetes and cardiovascular disease, highlighting how airborne pollutants can disrupt glucose homeostasis. We discuss how air pollution and diabetes, via shared mechanisms leading to endothelial dysfunction, drive increased cardiovascular disease risk. We identify portable air cleaners as potentially useful tools to prevent adverse cardiovascular outcomes due to air pollution exposure across the diabetes spectrum, while emphasizing the need for further study in this particular population. Given the enormity of the health and financial impacts of air pollution exposure on patients with diabetes, a greater understanding of the interventions to reduce cardiovascular risk in this population is needed.
Collapse
Affiliation(s)
- Luke J. Bonanni
- Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, United States
| | - Sharine Wittkopp
- Division of Cardiovascular Disease, Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, United States
| | - Clarine Long
- Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, United States
| | - José O. Aleman
- Division of Endocrinology, Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, United States
| | - Jonathan D. Newman
- Division of Cardiovascular Disease, Grossman School of Medicine, New York University (NYU) Langone Health, New York, NY, United States
| |
Collapse
|
25
|
Dai Y, Yin J, Li S, Li J, Han X, Deji Q, Pengcuo C, Liu L, Yu Z, Chen L, Xie L, Guo B, Zhao X. Long-term exposure to fine particulate matter constituents in relation to chronic kidney disease: evidence from a large population-based study in China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:174. [PMID: 38592609 DOI: 10.1007/s10653-024-01949-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 03/07/2024] [Indexed: 04/10/2024]
Abstract
The effects of long-term exposure to fine particulate matter (PM2.5) constituents on chronic kidney disease (CKD) are not fully known. This study sought to examine the association between long-term exposure to major PM2.5 constituents and CKD and look for potential constituents contributing substantially to CKD. This study included 81,137 adults from the 2018 to 2019 baseline survey of China Multi-Ethnic Cohort. CKD was defined by the estimated glomerular filtration rate. Exposure concentration data of 7 major PM2.5 constituents were assessed by satellite remote sensing. Logistic regression models were used to estimate the effect of each PM2.5 constituent exposure on CKD. The weighted quantile sum regression was used to estimate the effect of mixed exposure to all constituents. PM2.5 constituents had positive correlations with CKD (per standard deviation increase), with ORs (95% CIs) of 1.20 (1.02-1.41) for black carbon, 1.27 (1.07-1.51) for ammonium, 1.29 (1.08-1.55) for nitrate, 1.20 (1.01-1.43) for organic matter, 1.25 (1.06-1.46) for sulfate, 1.30 (1.11-1.54) for soil particles, and 1.63 (1.39-1.91) for sea salt. Mixed exposure to all constituents was positively associated with CKD (1.68, 1.32-2.11). Sea salt was the constituent with the largest weight (0.36), which suggested its importance in the PM2.5-CKD association, followed by nitrate (0.32), organic matter (0.18), soil particles (0.10), ammonium (0.03), BC (0.01). Sulfate had the least weight (< 0.01). Long-term exposure to PM2.5 sea salt and nitrate may contribute more than other constituents in increasing CKD risk, providing new evidence and insights for PM2.5-CKD mechanism research and air pollution control strategy.
Collapse
Affiliation(s)
- Yucen Dai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Jianzhong Yin
- School of Public Health, Kunming Medical University, Kunming, China
- Baoshan College of Traditional Chinese Medicine, Baoshan, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Jiawei Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Xinyu Han
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | | | - Ciren Pengcuo
- Tibet Center for Disease Control and Prevention CN, Lhasa, China
| | - Leilei Liu
- School of Public Health the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Zhimiao Yu
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Liling Chen
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China.
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| |
Collapse
|
26
|
Cui Z, Pan R, Liu J, Yi W, Huang Y, Li M, Zhang Z, Kuang L, Liu L, Wei N, Song R, Yuan J, Li X, Yi X, Song J, Su H. Green space and its types can attenuate the associations of PM 2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China. ENVIRONMENTAL RESEARCH 2024; 245:117997. [PMID: 38157960 DOI: 10.1016/j.envres.2023.117997] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 12/12/2023] [Accepted: 12/19/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.
Collapse
Affiliation(s)
- Zhiqian Cui
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Yuxin Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Ming Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Zichen Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Lingmei Kuang
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Xingxu Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, 230032, China.
| |
Collapse
|
27
|
Li D, Xiong J, Cheng G. Long-term exposure to ambient PM 2.5 and its components on menarche timing among Chinese adolescents: evidence from a representative nationwide cohort. BMC Public Health 2024; 24:707. [PMID: 38443853 PMCID: PMC10916212 DOI: 10.1186/s12889-024-18209-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 02/25/2024] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Ambient air pollutants have been suggested to affect pubertal development. Nevertheless, current studies indicate inconsistent effects of these pollutants, causing precocious or delayed puberty onset. This study aimed to explore the associations between long-term exposure to particulate matter with aerodynamic diameters ≤ 2.5 μm (PM2.5) along with its components and menarche timing among Chinese girls. METHOD Self-reported age at menarche was collected among 855 girls from China Health and Nutrition Survey 2004 to 2015. The pre-menarche annual average concentrations of PM2.5 and its components were calculated on the basis of a long-term (2000-2014) high-resolution PM2.5 components dataset. Generalized linear models (GLM) and logistic regression models were used to analyze the associations of exposure to a single pollutant (PM2.5, sulfate, nitrate, ammonium, black carbon and organic matter) with age at menarche and early menarche (< 12 years), respectively. Weighted quantile sum methods were applied to examine the impacts of joint exposure on menarche timing. RESULTS In the adjusted GLM, per 1 µg/m3 increase of annual average concentrations of nitrate and ammonium decreased age at menarche by 0.098 years and 0.127 years, respectively (all P < 0.05). Every 1 µg/m3 increase of annual average concentrations of PM2.5 (OR: 1.04, 95% CI: 1.00-1.08), sulfate (OR: 1.23, 95% CI: 1.01-1.50), nitrate (OR: 1.23, 95% CI: 1.06-1.43) and ammonium (OR: 1.32, 95% CI: 1.06-1.66) were significantly positively associated with early menarche. Higher level of joint exposure to PM2.5 and its components was associated with 11% higher odds of early menarche (P = 0.04). Additionally, the estimated weight of sulfate was the largest among the mixed pollutants. CONCLUSIONS Long-term exposure to PM2.5 and its components could increase the risk of early menarche among Chinese girls. Moreover, sulfate might be the most critical components responsible for this relationship. Our study provides foundation for targeted prevention of PM2.5 components.
Collapse
Affiliation(s)
- Danting Li
- Department of Nutrition and Food Safety, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, Maternal & Child Nutrition Center, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China
| | - Jingyuan Xiong
- Healthy Food Evaluation Research Center, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Guo Cheng
- Laboratory of Molecular Translational Medicine, Center for Translational Medicine, Key Laboratory of Birth Defects and Related Diseases of Women and Children, Ministry of Education, Maternal & Child Nutrition Center, West China Second University Hospital, Sichuan University, 610041, Chengdu, Sichuan, China.
| |
Collapse
|
28
|
Song L, Gao Y, Tian J, Liu N, Nasier H, Wang C, Zhen H, Guan L, Niu Z, Shi D, Zhang H, Zhao L, Zhang Z. The mediation effect of asprosin on the association between ambient air pollution and diabetes mellitus in the elderly population in Taiyuan, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:19674-19686. [PMID: 38363509 DOI: 10.1007/s11356-024-32255-8] [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: 10/12/2023] [Accepted: 01/25/2024] [Indexed: 02/17/2024]
Abstract
Evidence around the relationship between air pollution and the development of diabetes mellitus (DM) remains limited and inconsistent. To investigate the potential mediation effect of asprosin on the association between fine particulate matter (PM2.5), tropospheric ozone (O3) and blood glucose homeostasis. A case-control study was conducted on a total of 320 individuals aged over 60 years, including both diabetic and non-diabetic individuals, from six communities in Taiyuan, China, from July to September 2021. Generalized linear models (GLMs) suggested that short-term exposure to PM2.5 was associated with elevated fasting blood glucose (FBG), insulin resistance index (HOMA-IR), as well as reduced pancreatic β-cell function index (HOMA-β), and short-term exposure to O3 was associated with increased FBG and decreased HOMA-β in the total population and elderly diabetic patients. Mediation analysis showed that asprosin played a mediating role in the relationship of PM2.5 and O3 with FBG, with mediating ratios of 10.2% and 18.4%, respectively. Our study provides emerging evidence supporting that asprosin mediates the short-term effects of exposure to PM2.5 and O3 on elevated FBG levels in an elderly population. Additionally, the elderly who are diabetic, over 70 years, and BMI over 24 kg/m2 are more vulnerable to air pollutants and need additional protection to reduce their exposure to air pollution.
Collapse
Affiliation(s)
- Lulu Song
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Yuhui Gao
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Jiayu Tian
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Nannan Liu
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Halimaimaiti Nasier
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Caihong Wang
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Huiqiu Zhen
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Linlin Guan
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Zeyu Niu
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Dongxing Shi
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Hongmei Zhang
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Lifang Zhao
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China
| | - Zhihong Zhang
- Department of Environmental Health, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China.
- Center for Ecological Public Health Security of Yellow River Basin, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, 030001, China.
- Key Laboratory of Coal Environmental Pathogenicity and Prevention Shanxi Medical University, Ministry of Education, Taiyuan, China.
| |
Collapse
|
29
|
Ni Y, Zhang Y, Ye J, Yang X. Commentary: Causal relationship between particulate matter 2.5 and diabetes: two sample Mendelian randomization. Front Public Health 2024; 12:1353982. [PMID: 38469275 PMCID: PMC10925619 DOI: 10.3389/fpubh.2024.1353982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/13/2024] [Indexed: 03/13/2024] Open
Affiliation(s)
- Yao Ni
- Department of Dermatovenereology, Chengdu Second People's Hospital, Chengdu, Sichuan, China
| | - Youqian Zhang
- Health Science Center, Yangtze University, Jingzhou, Hubei, China
| | - Jianzhou Ye
- Department of Dermatology, Yunnan Provincial Hospital of Traditional Chinese Medicine, The First Affiliated Hospital of Yunnan University of Chinese Medicine, Kunming, Yunnan, China
| | - Xuesong Yang
- Department of Dermatology, Yunnan Provincial Hospital of Traditional Chinese Medicine, The First Affiliated Hospital of Yunnan University of Chinese Medicine, Kunming, Yunnan, China
| |
Collapse
|
30
|
Liu CX, Liu YB, Peng Y, Peng J, Ma QL. Causal effect of air pollution on the risk of cardiovascular and metabolic diseases and potential mediation by gut microbiota. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 912:169418. [PMID: 38104813 DOI: 10.1016/j.scitotenv.2023.169418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/13/2023] [Accepted: 12/14/2023] [Indexed: 12/19/2023]
Abstract
BACKGROUND Epidemiological studies have explored the relationship between air pollution and cardiovascular and metabolic diseases (CVMDs). Accumulating evidence has indicated that gut microbiota deeply affects the risk of CVMDs. However, the findings are controversial and the causality remains uncertain. To evaluate whether there is the causal association of four air pollutants with 19 CVMDs and the potential effect of gut microbiota on these relationships. METHODS Genetic instruments for particulate matter (PM) with aerodynamic diameter < 2.5 μm (PM2.5), <10 μm (PM10), PM2.5 absorbance, nitrogen oxides (NOx) and 211 gut microbiomes were screened. Univariable Mendelian randomization (UVMR) was used to estimate the causal effect of air pollutants on CVMDs in multiple MR methods. Additionally, to account for the phenotypic correlation among pollutant, the adjusted model was constructed using multivariable Mendelian randomization (MVMR) analysis to strength the reliability of the predicted associations. Finally, gut microbiome was assessed for the mediated effect on the associations of identified pollutants with CVMDs. RESULTS Causal relationships between NOx and angina, heart failure and hypercholesterolemia were observed in UVMR. After adjustment for air pollutants in MVMR models, the genetic correlations between PM2.5 and hypertension, type 2 diabetes mellitus (T2DM) and obesity remained significant and robust. In addition, genus-ruminococcaceae-UCG003 mediated 7.8 % of PM2.5-effect on T2DM. CONCLUSIONS This study firstly provided the genetic evidence linking air pollution to CVMDs and gut microbiota may mediate the association of PM2.5 with T2DM. Our findings highlight the significance of air quality in CVMDs risks and suggest the potential of modulating intestinal microbiota as novel therapeutic targets between air pollution and CVMDs.
Collapse
Affiliation(s)
- Chen-Xi Liu
- Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, Hunan 410008, China
| | - Yu-Bo Liu
- Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, Hunan 410008, China
| | - Yi Peng
- Department of Rheumatology and Immunology (T.X.), Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, Hunan 410008, China
| | - Jia Peng
- Department of Cardiovascular Medicine, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, Hunan 410008, China.
| | - Qi-Lin Ma
- Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, Hunan 410008, China.
| |
Collapse
|
31
|
He H, Wan N, Li Z, Zhang Z, Gao Z, Liu Q, Ma X, Zhang Y, Li R, Fu X, Qiu W. Short-term effects of exposure to ambient PM 2.5 and its components on hospital admissions for threatened and spontaneous abortions: A multicity case-crossover study in China. CHEMOSPHERE 2024; 350:141057. [PMID: 38158083 DOI: 10.1016/j.chemosphere.2023.141057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/09/2023] [Accepted: 12/26/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND The adverse effects of short-term exposure to PM2.5 and its components on hospital admissions for threatened and spontaneous abortions (TSAB) are still controversial. METHODS Data on daily hospitalizations for TSAB and PM2.5 and its components, including sulfate (SO42-), nitrate (NO3-), ammonium salt (NH4+), organic matter (OM), and black carbon (BC), were collected from January 2015 to December 2021 (total 2,557 days) in five cities in China. Case-crossover analyses were conducted to investigate the short-term associations between PM2.5 and its components and TSAB. Additionally, the modification effects by age (<35 and ≥35 years), season (cold and warm seasons), and the "Three-Year Action Plan to Win the Blue Sky Defense War" (before and after implementation) on the above associations were further conducted. RESULTS For each 10 μg/m3 (1 μg/m3 for BC) increase, the strongest relative risks (95% confidence intervals) of hospitalization for TSAB were 1.011 (1.001-1.021) for PM2.5 in lag02, 1.060 (1.003-1.120) for SO42- in lag02, 1.035 (1.000-1.070) for NO3- in lag02, 1.065 (1.009-1.124) for NH4+ in lag02, 1.047 (1.008-1.088) for OM in lag01 and 1.029 (1.005-1.054) for BC in lag02 (all P <0.05). Furthermore, significant modifying effects of age and the Action Plan were found. The effects of NO3- (lag2), NH4+ (lag2), and BC (lag2) were more pronounced in mothers aged ≥35 years and the effects of PM2.5 (lag4), NO3- (lag4), NH4+ (lag4), OM (lag4), and BC (lag4) was more pronounced in the period before the Action Plan was implemented (all P modification <0.05). CONCLUSION Short-term exposure to ambient PM2.5 and its components (SO42-, NO3-, NH4+, OM, and BC) was related to increased risks of hospitalization for TSAB. The effects were more pronounced in mothers aged ≥35 years and the period before the Action Plan.
Collapse
Affiliation(s)
- Heng He
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China
| | - Na Wan
- Henan Key Laboratory of Fertility Protection and Aristogenesis, Luohe Central Hospital, Luohe, Henan 462000, China
| | - Zhenzhen Li
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China
| | - Zihan Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China
| | - Zesen Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China
| | - Qingdan Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China
| | - Xiaolei Ma
- Henan Key Laboratory of Fertility Protection and Aristogenesis, Luohe Central Hospital, Luohe, Henan 462000, China
| | - Yuqing Zhang
- Henan Key Laboratory of Fertility Protection and Aristogenesis, Luohe Central Hospital, Luohe, Henan 462000, China
| | - Rongxiang Li
- Henan Key Laboratory of Fertility Protection and Aristogenesis, Luohe Central Hospital, Luohe, Henan 462000, China
| | - Xiuhong Fu
- Henan Key Laboratory of Fertility Protection and Aristogenesis, Luohe Central Hospital, Luohe, Henan 462000, China
| | - Weihong Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, Fujian 350122, China.
| |
Collapse
|
32
|
Pan R, Song J, Yi W, Liu J, Song R, Li X, Liu L, Yuan J, Wei N, Cheng J, Huang Y, Zhang X, Su H. Heatwave characteristics complicate the association between PM 2.5 components and schizophrenia hospitalizations in a changing climate: Leveraging of the individual residential environment. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 271:115973. [PMID: 38219619 DOI: 10.1016/j.ecoenv.2024.115973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/07/2024] [Accepted: 01/08/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND In the era characterized by global environmental and climatic changes, understanding the effects of PM2.5 components and heatwaves on schizophrenia (SCZ) is essential for implementing environmental interventions at the population level. However, research in this area remains limited, which highlights the need for further research and effort. We aim to assess the association between exposure to PM2.5 components and hospitalizations for SCZ under different heatwave characteristics. METHODS We conducted a 16 municipalities-wide, individual exposure-based, time-stratified, case-crossover study from January 1, 2017, to December 31, 2020, encompassing 160736 hospitalizations in Anhui Province, China. Daily concentrations of PM2.5 components were obtained from the Tracking Air Pollution in China dataset. Conditional logistic regression models were used to investigate the association between PM2.5 components and hospitalizations. Additionally, restricted cubic spline models were used to identify protective thresholds of residential environment in response to environmental and climate change. RESULTS Our findings indicate a positive correlation between PM2.5 and its components and hospitalizations. Significantly, a 1 μg/m3 increase in black carbon (BC) was associated with the highest risk, at 1.58% (95%CI: 0.95-2.25). Exposure to heatwaves synergistically enhanced the impact of PM2.5 components on hospitalization risks, and the interaction varied with the intensity and duration of heatwaves. Under the 99th percentile heatwave events, the impact of PM2.5 and its components on hospitalizations was most pronounced, which were PM2.5 (2-4d: 4.59%, 5.09%, and 5.09%), sulfate (2-4d: 21.73%, 23.23%, and 25.25%), nitrate (2-4d: 17.51%, 16.93%, and 20.31%), ammonium (2-4d: 27.49%, 31.03%, and 32.41%), organic matter (2-4d: 32.07%, 25.42%, and 24.48%), and BC (2-4d: 259.36%, 288.21%, and 152.52%), respectively. Encouragingly, a protective effect was observed when green and blue spaces comprised more than 17.6% of the residential environment. DISCUSSION PM2.5 components and heatwave exposure were positively associated with an increased risk of hospitalizations, although green and blue spaces provided a mitigating effect.
Collapse
Affiliation(s)
- Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Xuanxuan Li
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Li Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jiajun Yuan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Ning Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China
| | - Yuee Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Wannan Medical College, 241002 Wuhu, Anhui, China
| | - Xulai Zhang
- Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China.
| |
Collapse
|
33
|
Wang M, He Y, Zhao Y, Zhang L, Liu J, Zheng S, Bai Y. Exposure to PM 2.5 and its five constituents is associated with the incidence of type 2 diabetes mellitus: a prospective cohort study in northwest China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:34. [PMID: 38227152 DOI: 10.1007/s10653-023-01794-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 10/31/2023] [Indexed: 01/17/2024]
Abstract
Studies have demonstrated that fine particulate matter (PM2.5) is an underlying risk factor for type 2 diabetes mellitus (T2DM), but evidence exploring the relationship between PM2.5 chemical components and T2DM was extremely limited, to investigate the effects of long-term exposure to PM2.5 and its five constituents (sulfate [SO42-], nitrate [NO3-], ammonium [NH4+]), organic matter [OM] and black carbon [BC]) on incidence of T2DM. Based on the "Jinchang Cohort" platform, a total of 19,884 participants were selected for analysis. Daily average concentrations of pollutants were gained from Tracking Air Pollution in China (TAP). Cox proportional hazards regression models were utilized to estimate the hazard ratios (HR) and 95% confidence interval (CI) in single-pollutant models, restricted cubic splines functions were used to examine the dose-response relationships, and quantile g-computation (QgC) was applied to evaluate the combined effect of PM2.5 compositions on T2DM. Stratification analysis was also considered. A total of 791 developed new cases of T2DM were observed during a follow-up period of 45254.16 person-years. The concentrations of PM2.5, NO3-, NH4+, OM and BC were significantly associated with incidence of T2DM (P-trend < 0.05), with the HRs in the highest quartiles of 2.16 (95% CI 1.79, 2.62), 1.43 (95% CI 1.16, 1.75), 1.75 (95% CI 1.45, 2.11), 1.31 (95% CI 1.08, 1.59) and 1.79 (95% CI 1.46, 2.21), respectively. Findings of QgC model showed a noticeably positive joint effect of one quartile increase in PM2.5 constituents on increased T2DM morbidity (HR 1.27, 95% CI 1.09, 1.49), and BC (32.7%) contributed the most to the overall effect. The drinkers, workers and subjects with hypertension, obesity, higher physical activity, and lower education and income were generally more susceptible to PM2.5 components hazards. Long-term exposure to PM2.5 and its components (i.e., NO3-, NH4+, OM, BC) was positively correlated with T2DM incidence. Moreover, BC may be the most responsible for the association between PM2.5 constituents and T2DM. In the future, more epidemiological and experimental studies are needed to identify the link and potential biological mechanisms.
Collapse
Affiliation(s)
- Minzhen Wang
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Yingqian He
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Yanan Zhao
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Lulu Zhang
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Jing Liu
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| | - Shan Zheng
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China.
| | - Yana Bai
- Department of Epidemiology and Statistics, School of Public Health, Lanzhou University, No. 199 Donggang West Road, Lanzhou, 730000, China
| |
Collapse
|
34
|
Fang H, Jiang D, He Y, Wu S, Li Y, Zhang Z, Chen H, Zheng Z, Sun Y, Wang W. Association of ambient air pollution and pregnancy rate among women undergoing assisted reproduction technology in Fujian, China: A retrospective cohort study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168287. [PMID: 37924883 DOI: 10.1016/j.scitotenv.2023.168287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/19/2023] [Accepted: 10/31/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Previous studies have reported the impact of ambient air pollutants on assisted reproduction. They concentrated on highly polluted environments and individual pollutants. It is unclear whether these effects continue at lower levels and as mixed effects. We aimed to study the influence of lower pollutant concentrations on pregnancy rates and identify vulnerable populations. METHODS We conducted a retrospective cohort study involving 9465 patients with infertility who received treatment from a local hospital between 2015 and 2021. Daily average levels of six pollutants (PM2.5, PM10, NO2, CO, SO2, and O3) were collected from air quality monitoring stations. We employed generalized linear regression models (logistic, linear, and lasso), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) to assess the impact of pollutants on pregnancy rates. Additionally, stratified analyses were performed to identify potentially vulnerable populations. RESULTS Findings from the generalized linear models revealed a significant negative correlation between interquartile range increment exposure to PM2.5 (OR = 1.17, 95 % CI = 1.09-1.26), PM10 (OR = 1.18, 95 % CI = 1.11-1.26), NO2 (OR = 1.21, 95 % CI = 1.13-1.30), CO (OR = 1.02, 95 % CI = 1.00-1.03), SO2 (OR = 1.11, 95 % CI = 1.05-1.17) and pregnancy rate when considering the effects of individual pollutants. The WQS index exhibited a negative correlation with pregnancy rates and the number of oocytes retrieved (aOR = 1.20, 95 % CI = 1.08-1.34). BKMR analyses indicated an overall significant trend of decreasing pregnancy rates as pollutant concentrations increased across percentiles. Stratified analysis unveiled heightened sensitivity to pollutants among individuals aged ≥35 years. CONCLUSIONS By comparing results obtained from diverse models, we observed that exposure to lower levels of air pollutants led to decreased pregnancy rates. Notably, PM10, NO2, SO2, and CO emerged as the four most prominent pollutants in this context. Moreover, stratified analyses highlighted that individuals aged ≥35 years exhibited heightened susceptibility to pollutants.
Collapse
Affiliation(s)
- Hua Fang
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Dongdong Jiang
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Ye He
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Siyi Wu
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Yuehong Li
- Center of Reproductive Medicine, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, China; Fujian Key Laboratory of Prenatal Diagnosis and Birth Defect, Fuzhou, Fujian, China
| | - Ziqi Zhang
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Haoting Chen
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Zixin Zheng
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China
| | - Yan Sun
- Center of Reproductive Medicine, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, China; Fujian Key Laboratory of Prenatal Diagnosis and Birth Defect, Fuzhou, Fujian, China
| | - Wenxiang Wang
- Fujian Province Key Laboratory of Environment and Health, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China; Department of Health Inspection and Quarantine, School of Public Health, Fujian Medical University, Fuzhou, Fujian, China.
| |
Collapse
|
35
|
Zhang F, Yang C, Wang F, Liu Y, Guo CG, Li P, Zhang L. Air pollution and the risk of incident chronic kidney disease in patients with diabetes: An exposure-response analysis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 270:115829. [PMID: 38103521 DOI: 10.1016/j.ecoenv.2023.115829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/10/2023] [Accepted: 12/11/2023] [Indexed: 12/19/2023]
Abstract
Impact of air pollution on incident chronic kidney disease (CKD) in diabetic patients is insufficiently studied. We aimed to examine exposure-response associations of PM2.5, PM10, PM2.5-10, NO2, and NOX with incident CKD in diabetic patients in the UK. We also widened exposure level of PM2.5 and examined PM2.5-CKD association in diabetic patients across the entire range of global concentration. Based on data from UK biobank cohort, we applied Cox proportional hazards models and the shape constrained health impact function to investigate the associations between air pollutants and incident CKD in diabetic patients. Global exposure mortality model was applied to combine the PM2.5-CKD association in diabetic patients in the UK with all other published associations. Multiple air pollutants were positively associated with incident CKD in diabetic patients in the UK, with hazard ratios (HRs) of 1.034 (95 %CI: 1.015-1.053) and 1.021 (95 %CI: 1.007-1.036) for every 1 μg/m3 increase in PM2.5 and PM10 concentration, and 1.113 (95 %CI: 1.053-1.177) and 1.058 (95 %CI: 1.027-1.091) for every 10 μg/m3 increase in NO2 and NOX concentration, respectively. For PM2.5-10, associations with CKD in diabetic patients did not reach the statistical significance. Exposure-response associations with CKD in diabetic patients showed a near-linear trend for PM2.5, PM10, NO2, and NOX in the UK, whereas PM2.5-DKD associations in the globe exhibited a non-linear increasing trend. This study supports that air pollution could significantly increase the risk of CKD onset in diabetic patients.
Collapse
Affiliation(s)
- Feifei Zhang
- National Institute of Health Data Science at Peking University, Peking University Health Science Center, Beijing 100191, China; Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China
| | - Chao Yang
- Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing 100034, China; Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China; Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China
| | - Fulin Wang
- National Institute of Health Data Science at Peking University, Peking University Health Science Center, Beijing 100191, China; Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China
| | - Yuhao Liu
- Peking University Health Science Center, Beijing 100191, China
| | - Chuan-Guo Guo
- Department of Gastroenterology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
| | - Pengfei Li
- Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China
| | - Luxia Zhang
- National Institute of Health Data Science at Peking University, Peking University Health Science Center, Beijing 100191, China; Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing 100191, China; Renal Division, Department of Medicine, Peking University First Hospital, Peking University Institute of Nephrology, Beijing 100034, China; Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing 100034, China; Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China.
| |
Collapse
|
36
|
Cai C, Chen Y, Feng C, Shao Y, Ye T, Yu B, Jia P, Yang S. Long-term effects of PM 2.5 constituents on metabolic syndrome and mediation effects of serum uric acid. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 341:122979. [PMID: 37989407 DOI: 10.1016/j.envpol.2023.122979] [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: 06/11/2023] [Revised: 11/14/2023] [Accepted: 11/15/2023] [Indexed: 11/23/2023]
Abstract
Exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) was associated with the risk for metabolic syndrome (MetS) in the general population, but the contributions of individual PM2.5 constituents to this association and the potential pathway between PM2.5 constituents and MetS risk are not well elaborated. This study aimed to investigate associations between PM2.5 constituents and MetS in general populations, relative importance of PM2.5 constituents to and mediation effects of serum uric acid (SUA) on those associations. The 48,148 participants from a provincially representative cohort established in southwest China were included. The 3-year average concentrations of PM2.5 and its constituents (nitrate [NO3-], sulfate [SO42-], ammonium [NH4+], organic matter [OM], and black carbon [BC]) were estimated using a series of machine-learning models. Multivariate logistic regression and weighted quantile sum regression were used to estimate effects of independent PM2.5 constituents on MetS and their contributions to the joint effect. Mediation analysis examined the potential mediation effects of SUA on the associations between PM2.5 constituents and MetS. Each interquartile range (IQR) increase in the concentration of PM2.5 constituents was all positively associated with the increased MetS odds, including SO42- (OR = 1.15 [1.11, 1.19]]), NO3- (OR = 1.12 [1.08, 1.16]), NH4+ (OR = 1.13 [1.09, 1.17]), OM (OR = 1.09 [1.06, 1.13]), and BC (OR = 1.09 [1.06, 1.13]). Their joint associations on MetS were mainly attributed to SO42- (weight=46.1%) and NH4+ (44.0%). The associations of PM2.5 constituents with abnormal MetS components were mainly attributed to NH4+ for elevated BP (51.6%) and reduced HDL-C (97.0%), SO42- for elevated FG (68.9%), NO3- for elevated TG (51.0%), and OM for elevated WC (63.0%). Percentages mediated by SUA for the associations of PM2.5, SO42-, NO3-, and BC with MetS were 13.6%, 13.1%, 10.6%, and 11.1%, respectively. Long-term exposure to PM2.5 constituents, mainly NH4+ and SO42-, was positively associated with MetS odds, partially mediated by SUA.
Collapse
Affiliation(s)
- Changwei Cai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yang Chen
- Yunnan Center for Disease Prevention and Control, Kunming, China; School of Public Health, Kunming Medical University, Kunming, China
| | - Chuanteng Feng
- Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Ying Shao
- Yunnan Center for Disease Prevention and Control, Kunming, China
| | - Tingting Ye
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Bin Yu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Institute for Disaster Management and Reconstruction, Sichuan University-The Hong Kong Polytechnic University, Chengdu, China
| | - Peng Jia
- School of Resource and Environmental Sciences, Wuhan University, Wuhan, China; Hubei Luojia Laboratory, Wuhan, China; School of Public Health, Wuhan University, Wuhan, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China
| | - Shujuan Yang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; International Institute of Spatial Lifecourse Health (ISLE), Wuhan University, Wuhan, China; Department of Health Management Center, Clinical Medical College & Affiliated Hospital, Chengdu University, Chengdu, China.
| |
Collapse
|
37
|
Lin J, Zhang Y, Wang K, Xia H, Hua M, Lu K, Zheng W, Chen R. Long-term impact of PM 2.5 exposure on frailty, chronic diseases, and multimorbidity among middle-aged and older adults: insights from a national population-based longitudinal study. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:4100-4110. [PMID: 38097844 DOI: 10.1007/s11356-023-31505-5] [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: 10/19/2023] [Accepted: 12/08/2023] [Indexed: 01/19/2024]
Abstract
Particulate Matter 2.5 (PM2.5) is a significant risk factor for frailty and chronic diseases. Studies on the associations between PM2.5 and frailty, chronic diseases, and multimorbidity are scarce, especially from large cohort studies. We aimed to explore the potential association between PM2.5 exposure and the risk of frailty, chronic diseases, and multimorbidity. We collected data from a national cohort (CHARLS) with a follow-up period of 11-18 years, totaling 13,366 participants. We obtained PM2.5 concentration data from the Atmospheric Composition Analysis Group at Dalhousie University. PM2.5 exposure is based on the average annual concentration in the prefecture-level city where residents live. We define frailty as the comprehensive manifestation of declining various body functions, characterized by a frailty index of 0.25 or greater, and multimorbidity as the presence of at least two or more chronic conditions. Cox proportional hazards regression was used to estimate the hazard ratio (HR) with its 95% confidence interval (95%CI). A 10-μg/m3 increase for PM2.5 was significantly associated with an increased risk of frailty (HR = 1.289, 95%CI = 1.257-1.322, P < 0.001). A 10-μg/m3 increase for PM2.5 was significantly associated with the elevated risk for most chronic diseases. Compared to those with no morbidity or only single morbidity, a 10-μg/m3 increase for PM2.5 was significantly associated with the elevated risk for multimorbidity (HR = 1.220, 95%CI = 1.181-1.260, P < 0.001). Ambient PM2.5 exposure is a significant risk factor for frailty, chronic diseases, and multimorbidity, and some measures need to be taken to reduce PM2.5 concentration and prevent frailty and chronic diseases.
Collapse
Affiliation(s)
- Junjie Lin
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yu Zhang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Kunyi Wang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Huilin Xia
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Minxia Hua
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Kexin Lu
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Weijun Zheng
- Department of Medical Statistics, School of Public Health, Zhejiang Chinese Medical University, 548 Binwen Road, Binjiang District, Hangzhou City, 310053, Zhejiang Province, China
| | - Rucheng Chen
- Department of Medical Statistics, School of Public Health, Zhejiang Chinese Medical University, 548 Binwen Road, Binjiang District, Hangzhou City, 310053, Zhejiang Province, China.
| |
Collapse
|
38
|
Zheng W, Chu J, Bambrick H, Wang N, Mengersen K, Guo X, Hu W. Impact of environmental factors on diabetes mortality: A comparison between inland and coastal areas. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166335. [PMID: 37591381 DOI: 10.1016/j.scitotenv.2023.166335] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/02/2023] [Accepted: 08/14/2023] [Indexed: 08/19/2023]
Abstract
BACKGROUND Diabetes mortality varies between coastal and inland areas in Shandong Province, China. However, evidence about the reasons for this disparity is limited. We assume that distinct environmental conditions may contribute to the disparities in diabetes mortality patterns between coastal and inland areas. METHOD Qingdao and Jinan were selected as typical coastal and inland cities in Shandong Province, respectively, with similar socioeconomic but different environmental characteristics. Data on diabetes deaths and environmental factors (i.e., temperature, relative humidity and air pollution particles with a diameter of 2.5 μm or less (PM2.5)) were collected from 2013 to 2020. Spatial kriging methods were used to estimate the aggregated diabetes mortality at the city level. A distributed lag non-linear model (DLNM) was used to quantify the possible cumulative and non-cumulative associations between environmental factors and diabetes mortality by age, sex and location. RESULTS In the coastal city (Qingdao), the maximum cumulative relative risks (RRs) of temperature and PM2.5 associated with diabetes deaths were 2.54 (95 % confidence interval (CI): 1.25-5.15), and 1.17 (95 % CI: 1.01-1.37) respectively, at lag 1 week. In the inland city (Jinan), only temperature exhibited significant cumulative associations with diabetes deaths (RR = 1.54, 95 % CI: 1.07-2.23 at 29 °C). Lower relative humidity (22 %-45 %) had a lag-specific association with diabetes deaths in inland areas at lag 3 weeks (RR = 1.33, 95 % CI: 1.03-1.70 at 22 %). CONCLUSION Despite the lower PM2.5 concentrations in the coastal location, diabetes mortality exhibited stronger links to environmental variables in the coastal city than in the inland city. These findings suggest that the control of air pollution could decrease the mortality burden of diabetes, even in the region with relatively good air quality. Additionally, the spatial estimation method is recommended to identify associations between environmental factors and diseases in studies with limited data.
Collapse
Affiliation(s)
- Wenxiu Zheng
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Jie Chu
- Shandong Center for Disease Control and Prevention, Academy of Preventive Medicine, Shandong University, Jinan, Shandong, China
| | - Hilary Bambrick
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia; National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
| | - Ning Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Kerrie Mengersen
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Xiaolei Guo
- Shandong Center for Disease Control and Prevention, Academy of Preventive Medicine, Shandong University, Jinan, Shandong, China.
| | - Wenbiao Hu
- Ecosystem Change and Population Health Research Group, School of Public Health and Social Work, Queensland University of Technology, Brisbane, Queensland, Australia.
| |
Collapse
|
39
|
Li X, Wu Y, Li G, Shen W, Xiao W, Liu J, Hu W, Lu H, Huang F. The combined effects of exposure to multiple PM 2.5 components on overweight and obesity in middle-aged and older adults: a nationwide cohort study from 125 cities in China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:8749-8760. [PMID: 37726540 DOI: 10.1007/s10653-023-01741-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 08/21/2023] [Indexed: 09/21/2023]
Abstract
The prevalence of overweight or obesity increased rapidly over the past decades in most countries, including China. However, little evidence exists about the effects of long-term exposure to PM2.5 components on overweight or obesity, particularly in developing countries. We measured different weight stages according to body mass index (BMI), and investigated the effects of exposure to PM2.5 components (ammonium [[Formula: see text]], sulfate [[Formula: see text]], nitrate [[Formula: see text]], black carbon and organic matter) on different BMI levels in middle-aged and elderly people of China. Our study explored the effects of single and multiple air pollution exposures on overweight and obesity by using the Generalized Linear Model and Quantile g-Computation model (QgC). This study found a significantly positive association between five PM2.5 components and overweight/obesity. In the QgC model, there was still a positive association between multiple exposure to PM2.5 components and overweight when all PM2.5 components were considered as a whole. In addition, males, the elderly, and urban residents were also more sensitive to five PM2.5 components.
Collapse
Affiliation(s)
- Xue Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Yueyang Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Guoao Li
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Wenbin Shen
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Wei Xiao
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Jianjun Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Wenlei Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Huanhuan Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China
| | - Fen Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, 230032, Anhui, China.
| |
Collapse
|
40
|
Ryu J, Lee SH, Kim S, Jeong JW, Kim KS, Nam S, Kim JE. Urban dust particles disrupt mitotic progression by dysregulating Aurora kinase B-related functions. JOURNAL OF HAZARDOUS MATERIALS 2023; 459:132238. [PMID: 37586242 DOI: 10.1016/j.jhazmat.2023.132238] [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: 05/16/2023] [Revised: 08/02/2023] [Accepted: 08/04/2023] [Indexed: 08/18/2023]
Abstract
Particulate matter (PM), a major component of outdoor air pollution, damages DNA and increases the risk of cancer. Although the harmful effects of PM at the genomic level are known, the detailed mechanism by which PM affects chromosomal stability remains unclear. In this study, we investigated the novel effects of PM on mitotic progression and identified the underlying mechanisms. Gene set enrichment analysis of lung cancer patients residing in countries with high PM concentrations revealed the downregulation of genes associated with mitosis and mitotic structures. We also showed that exposure of lung cancer cells in vitro to urban dust particles (UDPs) inhibits cell proliferation through a prolonged M phase. The mitotic spindles in UDP-treated cells were hyperstabilized, and the number of centrioles increased. The rate of ingression of the cleavage furrow and actin clearance from the polar cortex was reduced significantly. The defects in mitotic progression were attributed to inactivation of Aurora B at kinetochore during early mitosis, and spindle midzone and midbody during late mitosis. While previous studies demonstrated possible links between PM and mitosis, they did not specifically identify the dysregulation of spatiotemporal dynamics of mitotic proteins and structures (e.g., microtubules, centrosomes, cleavage furrow, and equatorial and polar cortex), which results in the accumulation of chromosomal instability, ultimately contributing to carcinogenicity. The data highlight the novel scientific problem of PM-induced mitotic disruption. Additionally, we introduce a practical visual method for assessing the genotoxic outcomes of airborne pollutants, which has implications for future environmental and public health research.
Collapse
Affiliation(s)
- Jaewook Ryu
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, the Republic of Korea; Department of Pharmacology, College of Medicine, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Seung Hyeun Lee
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Sungyeon Kim
- Department of Genome Medicine and Science, AI Convergence Center for Medical Science, Gachon Institute of Genome Medicine and Science, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon 21565, the Republic of Korea
| | - Joo-Won Jeong
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, the Republic of Korea; Department of Anatomy and Neurobiology, College of Medicine, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Kyung Sook Kim
- Department of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Seungyoon Nam
- Department of Genome Medicine and Science, AI Convergence Center for Medical Science, Gachon Institute of Genome Medicine and Science, Gachon University Gil Medical Center, Gachon University College of Medicine, Incheon 21565, the Republic of Korea; Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences and Technology (GAIHST), Gachon University, Incheon 21999, the Republic of Korea
| | - Ja-Eun Kim
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, the Republic of Korea; Department of Pharmacology, College of Medicine, Kyung Hee University, Seoul 02447, the Republic of Korea; Department of Precision Medicine, Graduate School, Kyung Hee University, Seoul 02447, the Republic of Korea.
| |
Collapse
|
41
|
Xiang W, Wang W, Du L, Zhao B, Liu X, Zhang X, Yao L, Ge M. Toxicological Effects of Secondary Air Pollutants. Chem Res Chin Univ 2023; 39:326-341. [PMID: 37303472 PMCID: PMC10147539 DOI: 10.1007/s40242-023-3050-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 04/13/2023] [Indexed: 06/13/2023]
Abstract
Secondary air pollutants, originating from gaseous pollutants and primary particulate matter emitted by natural sources and human activities, undergo complex atmospheric chemical reactions and multiphase processes. Secondary gaseous pollutants represented by ozone and secondary particulate matter, including sulfates, nitrates, ammonium salts, and secondary organic aerosols, are formed in the atmosphere, affecting air quality and human health. This paper summarizes the formation pathways and mechanisms of important atmospheric secondary pollutants. Meanwhile, different secondary pollutants' toxicological effects and corresponding health risks are evaluated. Studies have shown that secondary pollutants are generally more toxic than primary ones. However, due to their diverse source and complex generation mechanism, the study of the toxicological effects of secondary pollutants is still in its early stages. Therefore, this paper first introduces the formation mechanism of secondary gaseous pollutants and focuses mainly on ozone's toxicological effects. In terms of particulate matter, secondary inorganic and organic particulate matters are summarized separately, then the contribution and toxicological effects of secondary components formed from primary carbonaceous aerosols are discussed. Finally, secondary pollutants generated in the indoor environment are briefly introduced. Overall, a comprehensive review of secondary air pollutants may shed light on the future toxicological and health effects research of secondary air pollutants.
Collapse
Affiliation(s)
- Wang Xiang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| | - Libo Du
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| | - Bin Zhao
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- College of Chemistry and Material Science, Hebei Normal University, Shijiazhuang, 050024 P. R. China
| | - Xingyang Liu
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| | - Xiaojie Zhang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| | - Li Yao
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190 P. R. China
- University of Chinese Academy of Sciences, Beijing, 100049 P. R. China
| |
Collapse
|