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Nazarpour S, Shokati Poursani A, Mousavi M, Ramezani Tehrani F, Behboudi-Gandevani S. Investigation of the relationship between air pollution and gestational diabetes. J OBSTET GYNAECOL 2024; 44:2362962. [PMID: 38853776 DOI: 10.1080/01443615.2024.2362962] [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: 01/30/2024] [Accepted: 05/27/2024] [Indexed: 06/11/2024]
Abstract
BACKGROUND Gestational diabetes mellitus (GDM) can have negative effects on both the pregnancy and perinatal outcomes, as well as the long-term health of the mother and the child. It has been suggested that exposure to air pollution may increase the risk of developing GDM. This study investigated the relationship between exposure to air pollutants with gestational diabetes. METHODS The present study is a retrospective cohort study. We used data from a randomised community trial conducted between September 2016 and January 2019 in Iran. During this period, data on air pollutant levels of five cities investigated in the original study, including 6090 pregnant women, were available. Concentrations of ozone (O3), nitric oxide (NO), nitrogen dioxide (NO2), nitrogen oxides (NOx), sulphur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 (PM2.5) or <10 μm (PM10) were obtained from air pollution monitoring stations. Exposure to air pollutants during the three months preceding pregnancy and the first, second and third trimesters of pregnancy for each participant was estimated. The odds ratio was calculated based on logistic regression in three adjusted models considering different confounders. Only results that had a p < .05 were considered statistically significant. RESULTS None of the logistic regression models showed any statistically significant relationship between the exposure to any of the pollutants and GDM at different time points (before pregnancy, in the first, second and third trimesters of pregnancy and 12 months in total) (p > .05). Also, none of the adjusted logistic regression models showed any significant association between PM10 exposure and GDM risk at all different time points after adjusting for various confounders (p > .05). CONCLUSIONS This study found no association between GDM risk and exposure to various air pollutants before and during the different trimesters of pregnancy. This result should be interpreted cautiously due to the lack of considering all of the potential confounders.
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Affiliation(s)
- Sima Nazarpour
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Department of Midwifery, Varamin-Pishva Branch, Islamic Azad University, Tehran, Iran
| | - Afshin Shokati Poursani
- Department of Chemical Engineering - Health, Safety & Environment, Najafabad Branch, Islamic Azad University, Najafabad, Iran
| | - Maryam Mousavi
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fahimeh Ramezani Tehrani
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Lv X, Lin G, Zhang Y, Yuan K, Liang T, Liu R, Du Y, Yu H, Sun S. Weekly-specific ambient PM 1 before and during pregnancy and the risk of gestational diabetes mellitus. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:117006. [PMID: 39244877 DOI: 10.1016/j.ecoenv.2024.117006] [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: 07/06/2024] [Revised: 09/01/2024] [Accepted: 09/02/2024] [Indexed: 09/10/2024]
Abstract
BACKGROUND Exposure to fine or respirable particulate matter has been linked to an elevated risk of gestational diabetes mellitus (GDM). However, the association between exposure to particulate matter with an aerodynamic diameter ≤ 1 μm (PM1) and GDM has not been explored. METHODS We conducted a cohort study involving 60,173 pregnant women from nine hospitals in Beijing, China, from February 2015 to April 2021. Daily concentrations of PM1 and ozone were obtained from a validated spatiotemporal artificial intelligence model. We used a modified Poisson regression combined with distributed lag models to estimate the association between weekly-specific PM1 exposure and the risk of GDM after adjusting for individual-level covariates. RESULTS Among the 51,299 pregnant women included in the final analysis, 4008 were diagnosed with GDM. Maternal exposure to PM1 during preconception and gestational periods was generally associated with an increased risk of GDM. The most pronounced associations were identified during the 12th week before pregnancy, the 5th-8th weeks of the first trimester, and the 23rd-24th weeks of the second trimester. Each 10 μg/m3 increase in PM1 was associated with a relative risk of GDM of 1.65 (95 % CI: 1.59, 1.72) during the preconception period, 1.67 (95 % CI: 1.61, 1.73) in the first trimester, 1.52 (95 % CI: 1.47, 1.58) in the second trimester, and 2.54 (95 % CI: 2.45, 2.63) when considering the first and second trimester combined. CONCLUSIONS Exposure to PM1 before and during pregnancy was associated with an increased risk of GDM, particularly during the 12 weeks before pregnancy and gestational weeks 5-8 and 23-24.
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Affiliation(s)
- Xin Lv
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Guiyin Lin
- Beijing Tongzhou District Maternal and Child Health Hospital, 124 Yuqiao Middle Road, Beijing, Tongzhou District 101100, China
| | - Yangchang Zhang
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Kun Yuan
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Tian Liang
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Ruiyi Liu
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Ying Du
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Huanling Yu
- School of Public Health, Capital Medical University, Beijing 100069, China
| | - Shengzhi Sun
- School of Public Health, Capital Medical University, Beijing 100069, China.
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Chen Z, Zhu M, Ni W, Wu B, Liu T, Lin B, Lai L, Jing Y, Jiang L, Ouyang Z, Hu J, Zheng H, Peng W, Yu X, Fan J. Association of PM 2.5 exposure in early pregnancy and maternal liver function: A retrospective cohort study in Shenzhen, China. ENVIRONMENTAL RESEARCH 2024; 263:119934. [PMID: 39276834 DOI: 10.1016/j.envres.2024.119934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Revised: 09/02/2024] [Accepted: 09/03/2024] [Indexed: 09/17/2024]
Abstract
OBJECTIVE Studies have shown that fine particulate matter (PM2.5) has adverse effects on the liver function, but epidemiological evidence is limited, especially regarding pregnant women. This study aims to investigate the association between PM2.5 exposure in early pregnancy and maternal liver function during pregnancy. METHODS This retrospective cohort study included 13,342 pregnant participants. PM2.5 and Ozone (O3) exposure level, mean temperature, and relative humidity for each participant were assessed according to their residential address. The levels of serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and total bilirubin (TBIL) were measured during the second and third trimesters. Data on PM2.5 and O3 exposure level were sourced from Tracking Air Pollution in China (TAP), while the mean temperature and relative humidity were obtained from the ERA5 dataset. The Generalized Additive Model (GAM) was used to analyze the associations between PM2.5 exposure and maternal liver function during pregnancy, adjusting for potential confounding factors. RESULTS According to the results, each 10 μg/m3 increase in PM2.5 was associated with an increase of 3.57% (95% CI: 0.29%, 6.96%) in ALT and 4.25% (95% CI: 2.33%, 6.21%) in TBIL during the second trimester and 4.51% (95% CI: 2.59%, 6.47%) in TBIL during the third trimester, respectively. After adjusting for O3, these associations remained significant, and the effect of PM2.5 on ALT during the second trimester was further strengthened. No significant association observed between PM2.5 and AST. CONCLUSIONS PM2.5 exposure in early pregnancy is associated with increasement of maternal ALT and TBIL, suggesting that PM2.5 exposure may have an adverse effect on maternal liver function. Although this finding indicates an association between PM2.5 exposure and maternal liver function, more research is needed to confirm our findings and explore the underlying biological mechanisms.
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Affiliation(s)
- Zhijian Chen
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China; Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Minting Zhu
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Weigui Ni
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Bo Wu
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Tao Liu
- China Greater Bay Area Research Center of Environmental Health, School of Medicine, Jinan University, Guangzhou 510632, China; Key Laboratory of Viral Pathogenesis & Infection Prevention and Control, Jinan University, Ministry of Education, Guangzhou 510632, China
| | - Bingyi Lin
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Lijuan Lai
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Yi Jing
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Long Jiang
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China
| | - Zhongai Ouyang
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China; School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Jianxiong Hu
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Haoqu Zheng
- Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China
| | - Wan Peng
- Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China
| | - Xi Yu
- Faculty of Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China.
| | - Jingjie Fan
- Department of Preventive Healthcare, Shenzhen Maternity and Child Healthcare Hospital, Shenzhen 518028, China.
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Zhang S, Li X, Zhang L, Zhang Z, Li X, Xing Y, Wenger JC, Long X, Bao Z, Qi X, Han Y, Prévôt ASH, Cao J, Chen Y. Disease types and pathogenic mechanisms induced by PM 2.5 in five human systems: An analysis using omics and human disease databases. ENVIRONMENT INTERNATIONAL 2024; 190:108863. [PMID: 38959566 DOI: 10.1016/j.envint.2024.108863] [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: 05/15/2024] [Revised: 06/21/2024] [Accepted: 06/28/2024] [Indexed: 07/05/2024]
Abstract
Atmospheric fine particulate matter (PM2.5) can harm various systems in the human body. Due to limitations in the current understanding of epidemiology and toxicology, the disease types and pathogenic mechanisms induced by PM2.5 in various human systems remain unclear. In this study, the disease types induced by PM2.5 in the respiratory, circulatory, endocrine, and female and male urogenital systems have been investigated and the pathogenic mechanisms identified at molecular level. The results reveal that PM2.5 is highly likely to induce pulmonary emphysema, reperfusion injury, malignant thyroid neoplasm, ovarian endometriosis, and nephritis in each of the above systems respectively. The most important co-existing gene, cellular component, biological process, molecular function, and pathway in the five systems targeted by PM2.5 are Fos proto-oncogene (FOS), extracellular matrix, urogenital system development, extracellular matrix structural constituent conferring tensile strength, and ferroptosis respectively. Differentially expressed genes that are significantly and uniquely targeted by PM2.5 in each system are BTG2 (respiratory), BIRC5 (circulatory), NFE2L2 (endocrine), TBK1 (female urogenital) and STAT1 (male urogenital). Important disease-related cellular components, biological processes, and molecular functions are specifically induced by PM2.5. For example, response to wounding, blood vessel morphogenesis, body morphogenesis, negative regulation of response to endoplasmic reticulum stress, and response to type I interferon are the top uniquely existing biological processes in each system respectively. PM2.5 mainly acts on key disease-related pathways such as the PD-L1 expression and PD-1 checkpoint pathway in cancer (respiratory), cell cycle (circulatory), apoptosis (endocrine), antigen processing and presentation (female urogenital), and neuroactive ligand-receptor interaction (male urogenital). This study provides a novel analysis strategy for elucidating PM2.5-related disease types and is an important supplement to epidemiological investigation. It clarifies the risks of PM2.5 exposure, elucidates the pathogenic mechanisms, and provides scientific support for promoting the precise prevention and treatment of PM2.5-related diseases.
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Affiliation(s)
- Shumin Zhang
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China
| | - Xiaomeng Li
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China; Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; Department of Laboratory Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China
| | - Liru Zhang
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China
| | - Zhengliang Zhang
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China; School of Public Health, North Sichuan Medical College, Nanchong 637000, Sichuan, China
| | - Xuan Li
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China; School of Public Health, North Sichuan Medical College, Nanchong 637000, Sichuan, China
| | - Yan Xing
- Department of Laboratory Medicine, North Sichuan Medical College, Nanchong 637000, Sichuan, China
| | - John C Wenger
- School of Chemistry and Environmental Research Institute, University College Cork, Cork, Ireland
| | - Xin Long
- Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
| | - Zhier Bao
- Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
| | - Xin Qi
- Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
| | - Yan Han
- Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
| | - André S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institut, Villigen, PSI 5232, Switzerland
| | - Junji Cao
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yang Chen
- Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.
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Huang X, Liang W, Yang R, Jin L, Zhao K, Chen J, Shang X, Zhou Y, Wang X, Yu H. Variations in the LINGO2 and GLIS3 Genes and Gene-Environment Interactions Increase Gestational Diabetes Mellitus Risk in Chinese Women. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:11596-11605. [PMID: 38888423 DOI: 10.1021/acs.est.4c03221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2024]
Abstract
Gestational diabetes mellitus (GDM) has been found to be a common complication in pregnant women, known to escalate the risk of negative obstetric outcomes. In our study, we genotyped 1,566 Chinese pregnant women for two single nucleotide polymorphisms (SNPs) in the LINGO2 gene and one SNP in the GLIS3 gene, utilizing targeted next-generation sequencing. The impact of two interacting genes, and the interaction of genes with the environment─including exposure to particulate matter (PM2.5), ozone (O3), and variations in prepregnancy body mass index (BMI)─on the incidence of GDM were analyzed using logistic regression. Our findings identify the variants LINGO2 rs10968576 (P = 0.022, OR = 1.224) and rs1412239 (P = 0.018, OR = 1.231), as well as GLIS3 rs10814916 (P = 0.028, OR = 1.172), as risk mutations significantly linked to increased susceptibility to GDM. Further analysis underscores the crucial role of gene-gene and gene-environment interactions in the development of GDM among Chinese women (P < 0.05). Particularly, the individuals carrying the rs10968576 G-rs1412239 G-rs10814916 C haplotype exhibit increased susceptibility to GDM during the prepregnancy period when interacting with PM2.5, O3, and BMI (P = 8.004 × 10-7, OR = 1.206; P = 6.3264 × 10-11, OR = 1.280; P = 9.928 × 10-7, OR = 1.334, respectively). In conclusion, our research emphasizes the importance of the interaction between specific gene variations─LINGO2 and GLIS3─and environmental factors in influencing GDM risk. Notably, we found significant associations between these gene variations and GDM risk across various environmental exposure periods.
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Affiliation(s)
- Xiao Huang
- Department of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi 563000, China
| | - Weiwei Liang
- Department of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi 563000, China
| | - Runqiu Yang
- Department of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi 563000, China
| | - Lei Jin
- Institute of Reproductive and Child Health, National Health Commission Key Laboratory of Reproductive Health, Peking University, Beijing 100091, China
| | - Kai Zhao
- Institute of Reproductive Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Juan Chen
- Department of Occupational and Environmental Health, School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an 710061, China
| | - Xuejun Shang
- Department of Urology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210023, China
| | - Yuanzhong Zhou
- School of Public Health, Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi Medical University, Zunyi 563000, China
| | - Xin Wang
- Department of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi 563000, China
| | - Hongsong Yu
- Department of Immunology, Special Key Laboratory of Gene Detection and Therapy of Guizhou Province, Zunyi Medical University, Zunyi 563000, China
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Okui T, Nakashima N. Effects of ambient air pollution on the risk of small- and large-for-gestational-age births: an analysis using national birth data in Japan. Int Arch Occup Environ Health 2024; 97:545-555. [PMID: 38602525 DOI: 10.1007/s00420-024-02063-1] [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: 12/27/2023] [Accepted: 03/28/2024] [Indexed: 04/12/2024]
Abstract
OBJECTIVES Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births are major adverse birth outcomes related to newborn health. In contrast, the association between ambient air pollution levels and SGA or LGA births has not been investigated in Japan; hence, the purpose of our study is to investigate this association. METHODS We used birth data from Vital Statistics in Japan from 2017 to 2021 and municipality-level data on air pollutants, including nitrogen dioxide (NO2), sulfur dioxide (SO2), photochemical oxidants, and particulate matter 2.5 (PM2.5). Ambient air pollution levels throughout the first, second, and third trimesters, as well as the whole pregnancy, were calculated for each birth. The association between SGA/LGA and ambient levels of the air pollutants was investigated using crude and adjusted log-binomial regression models. In addition, a regression model with spline functions was also used to detect the non-linear association. RESULTS We analyzed data from 2,434,217 births. Adjusted regression analyses revealed statistically significant and positive associations between SGA birth and SO2 level, regardless of the exposure period. Specifically, the risk ratio for average SO2 values throughout the whole pregnancy was 1.014 (95% confidence interval [CI] 1.009, 1.019) per 1 ppb increase. In addition, regression analysis with spline functions indicated that an increase in risk ratio for SGA birth depending on SO2 level was linear. Furthermore, statistically significant and negative associations were observed between LGA birth and SO2 except for the third trimester. CONCLUSIONS It was suggested that ambient level of SO2 during the pregnancy term is a risk factor for SGA birth in Japan.
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Affiliation(s)
- Tasuku Okui
- Medical Information Center, Kyushu University Hospital, Maidashi 3-1-1 Higashi-ku, Fukuoka City , Fukuoka prefecture, 812-8582, Japan.
| | - Naoki Nakashima
- Medical Information Center, Kyushu University Hospital, Maidashi 3-1-1 Higashi-ku, Fukuoka City , Fukuoka prefecture, 812-8582, Japan
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Mazumder H, Rimu FH, Shimul MH, Das J, Gain EP, Liaw W, Hossain MM. Maternal health outcomes associated with ambient air pollution: An umbrella review of systematic reviews and meta-analyses. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:169792. [PMID: 38199356 DOI: 10.1016/j.scitotenv.2023.169792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/20/2023] [Accepted: 12/28/2023] [Indexed: 01/12/2024]
Abstract
A growing body of literature demonstrated an association between exposure to ambient air pollution and maternal health outcomes with mixed findings. The objective of this umbrella review was to systematically summarize the global evidence on the effects of air pollutants on maternal health outcomes. We adopted the Joanna Briggs Institute (JBI) methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting standards for this umbrella review. We conducted a comprehensive search across six major electronic databases and other sources to identify relevant systematic reviews and meta-analyses (SRMAs) published from the inception of these databases up to June 30, 2023. Out of 2399 records, 20 citations matched all pre-determined eligibility criteria that include SRMAs focusing on exposure to air pollution and its impact on maternal health, reported quantitative measures or summary effects, and published in peer-reviewed journals in the English language. The risk of bias of included SRMAs was evaluated based on the JBI critical appraisal checklist. All SRMAs reported significant positive associations between ambient air pollution and several maternal health outcomes. Specifically, particulate matter (PM), SO2, and NO demonstrated positive associations with gestational diabetes mellitus (GDM). Moreover, PM and NO2 showed a consistent positive relationship with hypertensive disorder of pregnancy (HDP) and preeclampsia (PE). Although limited, available evidence highlighted a positive correlation between PM and gestational hypertension (GH) and spontaneous abortion (SAB). Only one meta-analysis reported the effects of air pollution on maternal postpartum depression (PPD) where only PM10 showed a significant positive relationship. Limited studies were identified from low- and middle-income countries (LMICs), suggesting evidence gap from the global south. This review necessitates further research on underrepresented regions and communities to strengthen evidence on this critical issue. Lastly, interdisciplinary policymaking and multilevel interventions are needed to alleviate ambient air pollution and associated maternal health disparities.
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Affiliation(s)
- Hoimonty Mazumder
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, The University of Memphis, Memphis, TN 38152, United States.
| | - Fariha Hoque Rimu
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, United States
| | - Monir Hossain Shimul
- Department of Public Health, Daffodil International University, Dhaka, Bangladesh
| | - Jyoti Das
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO 80523, United States
| | - Easter Protiva Gain
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, The University of Memphis, Memphis, TN 38152, United States
| | - Winston Liaw
- Department of Health Systems and Population Health Sciences, Tilman J. Fertitta Family College of Medicine, University of Houston, TX 77204, United States
| | - M Mahbub Hossain
- Department of Health Systems and Population Health Sciences, Tilman J. Fertitta Family College of Medicine, University of Houston, TX 77204, United States; Department of Decision and Information Sciences, C.T. Bauer College of Business, University of Houston, TX 77204, United States
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