1
|
Abu Ahmad W, Nirel R, Barges S, Jolles M, Levine H. Meta-analysis of fine particulate matter exposure during pregnancy and birth weight: Exploring sources of heterogeneity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 934:173205. [PMID: 38754513 DOI: 10.1016/j.scitotenv.2024.173205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 03/31/2024] [Accepted: 05/11/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Several meta-analyses assessed the relationship between exposure to PM with aerodynamic diameter ≤ 2.5 μm (PM2.5) during pregnancy and birth weight (BW), but results were inconsistent and substantial unexplained heterogeneity was reported. We aimed to investigate the above association and to explore sources of heterogeneity across studies. METHODS We systematically reviewed the current worldwide evidence examining the association between PM2.5 and BW. The review protocol was registered on the PROSPERO website (CRD42020188996) and followed PRISMA guidelines. We extracted association measures for BW and low birth weight (LBW, BW < 2500 g) from each study to evaluate pooled summary measures and to explore sources of between-study heterogeneity. FINDINGS Of the 2677 articles identified, 84 met the inclusion criteria (~42 M births). Our random effects meta-analyses revealed substantial heterogeneity among included studies (I2 = 98.4 % and I2 = 77.7 %, for BW and LBW respectively). For LBW, the heterogeneity decreased (I2 = 59.7 %) after excluding four outlying studies, with a pooled odds ratio 1.07 (95 % confidence interval, CI: 1.05, 1.09) per a 10-μg/m3 increase in mean PM2.5 exposure over the entire pregnancy. Further subgroup analysis revealed geographic heterogeneity with higher association in Europe (1.34, (1.16, 1.55)) compared to Asia (1.06, (1.03, 1.10)) and US (1.07, (1.04, 1.10)). CONCLUSION The association between PM2.5 and birth weight varied depending on several factors. The sources of heterogeneity between studies included modifiers such as study region and period. Hence, it is advisable not to pool summary measures of PM2.5-BW associations and that policy would be informed by local evidence.
Collapse
Affiliation(s)
- Wiessam Abu Ahmad
- School of Public Health, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Ronit Nirel
- Department of Statistics and Data Science, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Saleh Barges
- Community Medical Services Division, Clalit Health Services, Tel-Aviv, Israel
| | - Maya Jolles
- School of Public Health, University of Haifa, Haifa, Israel
| | - Hagai Levine
- School of Public Health, Hadassah Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| |
Collapse
|
2
|
Ahn TG, Kim YJ, Lee G, You YA, Kim SM, Chae R, Hur YM, Park MH, Bae JG, Lee SJ, Kim YH, Na S. Association Between Individual Air Pollution (PM 10, PM 2.5) Exposure and Adverse Pregnancy Outcomes in Korea: A Multicenter Prospective Cohort, Air Pollution on Pregnancy Outcome (APPO) Study. J Korean Med Sci 2024; 39:e131. [PMID: 38599601 PMCID: PMC11004777 DOI: 10.3346/jkms.2024.39.e131] [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: 11/26/2023] [Accepted: 03/05/2024] [Indexed: 04/12/2024] Open
Abstract
BACKGROUND Prenatal exposure to ambient air pollution is linked to a higher risk of unfavorable pregnancy outcomes. However, the association between pregnancy complications and exposure to indoor air pollution remains unclear. The Air Pollution on Pregnancy Outcomes research is a hospital-based prospective cohort research created to look into the effects of aerodynamically exposed particulate matter (PM)10 and PM2.5 on pregnancy outcomes. METHODS This prospective multicenter observational cohort study was conducted from January 2021 to June 2023. A total of 662 women with singleton pregnancies enrolled in this study. An AirguardK® air sensor was installed inside the homes of the participants to measure the individual PM10 and PM2.5 levels in the living environment. The time-activity patterns and PM10 and PM2.5, determined as concentrations from the time-weighted average model, were applied to determine the anticipated exposure levels to air pollution of each pregnant woman. The relationship between air pollution exposure and pregnancy outcomes was assessed using logistic and linear regression analyses. RESULTS Exposure to elevated levels of PM10 throughout the first, second, and third trimesters as well as throughout pregnancy was strongly correlated with the risk of pregnancy problems according to multiple logistic regression models adjusted for variables. Except for in the third trimester of pregnancy, women exposed to high levels of PM2.5 had a high risk of pregnancy complications. During the second trimester and entire pregnancy, the risk of preterm birth (PTB) increased by 24% and 27%, respectively, for each 10 μg/m3 increase in PM10. Exposure to high PM10 levels during the second trimester increased the risk of gestational diabetes mellitus (GDM) by 30%. The risk of GDM increased by 15% for each 5 μg/m3 increase in PM2.5 during the second trimester and overall pregnancy, respectively. Exposure to high PM10 and PM2.5 during the first trimester of pregnancy increased the risk of delivering small for gestational age (SGA) infants by 96% and 26%, respectively. CONCLUSION Exposure to high concentrations of PM10 and PM2.5 is strongly correlated with the risk of adverse pregnancy outcomes. Exposure to high levels of PM10 and PM2.5 during the second trimester and entire pregnancy, respectively, significantly increased the risk of PTB and GDM. Exposure to high levels of PM10 and PM2.5 during the first trimester of pregnancy considerably increased the risk of having SGA infants. Our findings highlight the need to measure individual particulate levels during pregnancy and the importance of managing air quality in residential environment.
Collapse
Affiliation(s)
- Tae Gyu Ahn
- Department of Obstetrics and Gynecology, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Young Ju Kim
- Department of Obstetrics and Gynecology, Ewha Womans University Mokdong Hospital, Ewha Medical Research Institute College of Medicine, Seoul, Korea
| | - Gain Lee
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Korea
| | - Young-Ah You
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Soo Min Kim
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, Korea
| | - Rin Chae
- Division of Artificial Intelligence and Software/Artificial Intelligence Convergence, Ewha Womans University, Seoul, Korea
| | - Young Min Hur
- Department of Obstetrics and Gynecology, College of Medicine, Ewha Womans University, Seoul, Korea
| | - Mi Hye Park
- Department of Obstetrics and Gynecology, Ewha Womans University Seoul Hospital, Seoul, Korea
| | - Jin-Gon Bae
- Department of Obstetrics and Gynecology, School of Medicine, Keimyung University, Dongsan Medical Center, Daegu, Korea
| | - Soo-Jeong Lee
- Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Korea
| | - Young-Han Kim
- Department of Obstetrics and Gynecology, Severance Hospital, Institute of Women's Life Medical Science, Yonsei University College of Medicine, Seoul, Korea.
| | - Sunghun Na
- Department of Obstetrics and Gynecology, Kangwon National University School of Medicine, Chuncheon, Korea.
| |
Collapse
|
3
|
Zhang J, Cheng H, Zhu Y, Xie S, Shao X, Wang C, Chung SK, Zhang Z, Hao K. Exposure to Airborne PM 2.5 Water-Soluble Inorganic Ions Induces a Wide Array of Reproductive Toxicity. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:4092-4103. [PMID: 38373958 DOI: 10.1021/acs.est.3c07532] [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: 02/21/2024]
Abstract
Water-soluble inorganic ions (WSIIs, primarily NH4+, SO42-, and NO3-) are major components in ambient PM2.5, but their reproductive toxicity remains largely unknown. An animal study was conducted where parental mice were exposed to PM2.5 WSIIs or clean air during preconception and the gestational period. After delivery, all maternal and offspring mice lived in a clean air environment. We assessed reproductive organs, gestation outcome, birth weight, and growth trajectory of the offspring mice. In parallel, we collected birth weight and placenta transcriptome data from 150 mother-infant pairs from the Rhode Island Child Health Study. We found that PM2.5 WSIIs induced a broad range of adverse reproductive outcomes in mice. PM2.5 NH4+, SO42-, and NO3- exposure reduced ovary weight by 24.22% (p = 0.005), 14.45% (p = 0.048), and 16.64% (p = 0.022) relative to the clean air controls. PM2.5 SO42- exposure reduced the weight of testicle by 5.24% (p = 0.025); further, mice in the PM2.5 SO42- exposure group had 1.81 (p = 0.027) fewer offspring than the control group. PM2.5 NH4+, SO42-, and NO3- exposure all led to lower birth than controls. In mice, 557 placenta genes were perturbed by exposure. Integrative analysis of mouse and human data suggested hypoxia response in placenta as an etiological mechanism underlying PM2.5 WSII exposure's reproductive toxicity.
Collapse
Affiliation(s)
- Jushan Zhang
- State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, Shanghai, China 200092
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China 200072
- College of Environmental Science and Engineering, Tongji University, Shanghai, China 200092
| | - Haoxiang Cheng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Yujie Zhu
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China 200072
| | - Shuanshuan Xie
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China 200072
| | - Xiaowen Shao
- Department of Obstetrics and Gynecology, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China 200072
| | - Changhui Wang
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China 200072
| | - Sookja Kim Chung
- Faculty of Medicine, Macau University of Science and Technology, Taipa, Macau SAR 999078, China
- Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine; State Key Laboratory of Pharmaceutical Biotechnology, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, United States
| | - Ke Hao
- State Key Laboratory of Pollution Control and Resource Reuse, Tongji University, Shanghai, China 200092
- Department of Respiratory Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China 200072
- College of Environmental Science and Engineering, Tongji University, Shanghai, China 200092
| |
Collapse
|
4
|
Shi TS, Ma HP, Li DH, Pan L, Wang TR, Li R, Ren XW. Prenatal exposure to PM 2.5 components and the risk of different types of preterm birth and the mediating effect of pregnancy complications: a cohort study. Public Health 2024; 227:202-209. [PMID: 38241901 DOI: 10.1016/j.puhe.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2023] [Revised: 11/28/2023] [Accepted: 12/05/2023] [Indexed: 01/21/2024]
Abstract
OBJECTIVES This study aims to reveal the single and mixed associations of PM2.5 and its components with very, moderately, and late preterm births and to explore the potential mediating role of pregnancy complications in PM2.5-induced preterm birth. STUDY DESIGN This was a retrospective cohort study. METHODS We enrolled 168,852 mothers and matched the concentrations of PM2.5 and its five components (OM, SO42-, BC, NO3-, and NH4+) based on their geographical location. Next, we used generalized linear models, quantile g-computation, and mediation analysis to evaluate the associations of PM2.5 and its components with very, moderately, and late preterm births and the mediating role of pregnancy complications. RESULTS Prenatal exposure to PM2.5 and its components was associated with preterm birth, and the association was strongest in the third trimester. Preterm birth was associated with co-exposure to a mixture of PM2.5 components in the third trimester, and the contributions of NO3-, NH4+, and BC to the risk of preterm birth were positive. Meanwhile, pregnancy complications mediated PM2.5-induced preterm birth. Moreover, very and moderately preterm births were associated with PM2.5 and its components in the second and third trimesters, and very and late preterm births were associated with co-exposure to a mixture of PM2.5 components in the third trimester. CONCLUSIONS Later exposure to PM2.5 during pregnancy will cause earlier preterm birth. Targeted and positive interventions for anthropogenic sources of specific PM2.5 components and pregnancy complications are helpful for preterm birth prevention.
Collapse
Affiliation(s)
- T S Shi
- Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China
| | - H P Ma
- Lanzhou Maternal and Child Health Hospital, Lanzhou, Gansu, China
| | - D H Li
- Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China
| | - L Pan
- Lanzhou Maternal and Child Health Hospital, Lanzhou, Gansu, China
| | - T R Wang
- Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China
| | - R Li
- Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China
| | - X W Ren
- Institute of Epidemiology and Health Statistics, School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
| |
Collapse
|
5
|
Ji C, Lv J, Zhang J, Zhu M, Yu C, Ma H, Jin G, Guo Y, Pei P, Yang L, Chen Y, Du H, Chen Z, Hu Z, Li L, Shen H. Household air pollution and risk of incident lung cancer in urban China: A prospective cohort study. Int J Cancer 2023; 153:1592-1601. [PMID: 37403464 DOI: 10.1002/ijc.34646] [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: 02/01/2023] [Revised: 05/22/2023] [Accepted: 06/15/2023] [Indexed: 07/06/2023]
Abstract
Household air pollution (HAP) is associated with the development of lung cancer, yet few studies investigated the exposure patterns and joint associations with tobacco smoking. In our study, we included 224 189 urban participants from China Kadoorie Biobank (CKB), 3288 of which diagnosed with lung cancer during the follow-up. Exposure to four HAP sources (solid fuels for cooking/heating/stove and environmental tobacco smoke exposure) was assessed at baseline. Distinct HAP patterns and their associations with lung cancer were examined through latent class analysis (LCA) and multivariable Cox regression. A total of 76.1% of the participants reported regular cooking and 52.2% reported winter heating, of which 9% and 24.7% used solid fuels, respectively. Solid fuel heating increased lung cancer risk (Hazards ratio [HR]: 1.25, 95% confidence interval [CI]: 1.08-1.46). LCA identified three HAP patterns; the "clean fuel cooking and solid fuel heating" pattern significantly increased lung cancer risk (HR: 1.25, 95% CI: 1.10-1.41), compared to low HAP pattern. An additive interaction was observed between heavy smoking and "clean fuel cooking and solid fuel heating" (relative excess risk [RERI]: 1.32, 95% CI: 0.29-2.47, attributable proportion [AP]: 0.23, 95% CI: 0.06-0.36). Cases resulting from solid fuel account for ~4% of total cases (population attribute fraction [PAF]overall : 4.31%, 95% CI: 2.16%-6.47%, PAFever smokers : 4.38%, 95% CI: 1.54%-7.23%). Our results suggest that in urban China, solid fuel heating increased the risk of lung cancer, particularly among heavy smokers. The whole population could benefit from cleaner indoor air quality by reducing using solid fuels, especially smokers.
Collapse
Affiliation(s)
- Chen Ji
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Jing Zhang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Zhibin Hu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China
| |
Collapse
|
6
|
Wang X, Wang X, Gao C, Xu X, Li L, Liu Y, Li Z, Xia Y, Fang X. Relationship Between Outdoor Air Pollutant Exposure and Premature Delivery in China- Systematic Review and Meta-Analysis. Int J Public Health 2023; 68:1606226. [PMID: 37876739 PMCID: PMC10590883 DOI: 10.3389/ijph.2023.1606226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 09/28/2023] [Indexed: 10/26/2023] Open
Abstract
Objective: Preterm birth (PTB) is considered as a public health problem and one of the main risk factors related to the global disease burden. The purpose of this study aims to explore the influence of exposure to major air pollutants at different pregnancies on PTB. Methods: The relationship between air pollutants and PTB in China was collected from cohort studies and case-control studies published before 30 April 2022. Meta-analysis was carried out with STATA 15.0 software. Results: A total of 2,115 papers were retrieved, of which 18 papers met the inclusion criteria. The comprehensive effect of pollutant exposure and PTB were calculated. PM2.5 during entire pregnancy and O3 exposure during third trimester were positively associated with preterm birth. Every 10 μg/m3 increase in the average concentration of PM2.5 during the whole pregnancy will increase the risk of premature delivery by 4%, and every 10 μg/m3 increase in the average concentration of O3 in the third trimester will increase the risk of premature delivery by 1%. Conclusion: Exposure to PM2.5 entire prenatal pregnancy and O3 in third trimester is associated with an increased risk of preterm birth occurrence.
Collapse
Affiliation(s)
- Xue Wang
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Xin Wang
- Division of Molecular Signaling, Department of the Advanced Biomedical Research, Interdisciplinary Graduate School of Medicine, University of Yamanashi, Kofu, Japan
| | - Chenghua Gao
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Xiaoqian Xu
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Lehui Li
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Yan Liu
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Zichao Li
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Yuan Xia
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| | - Xin Fang
- School of Public Health of Inner Mongolia Medical University, Hohhot, China
| |
Collapse
|
7
|
Huang Y, Gong X, Liu L, Luo L, Leng S, Lin Y. Maternal exposure to metal components of PM 2.5 and low birth weight in New Mexico, USA. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:98526-98535. [PMID: 37608181 PMCID: PMC10829739 DOI: 10.1007/s11356-023-29291-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/08/2023] [Indexed: 08/24/2023]
Abstract
Infants with low birth weight (LBW) are more likely to have health problems than normal weight infants. In studies examining the associations between particulate matter (PM) exposures and LBW, there is a tendency to focus on PM2.5 as a whole. However, insufficient information is available regarding the effects of different components of PM2.5 on birth weight. This study identified the associations between maternal exposure to 10 metal components of PM2.5 and LBW in offspring based on small area (divided by population size) level data in New Mexico, USA, from 2012 to 2016. This study used a pruned feed-forward neural network (pruned-FNN) approach to estimate the annual average exposure index to each metal component in each small area. The linear regression model was employed to examine the association between maternal PM2.5 metal exposures and LBW rate in small areas, adjusting for the female percentage and race/ethnicity compositions, marriage status, and educational level in the population. An interquartile range increase in maternal exposure to mercury and chromium of PM2.5 increased LBW rate by 0.43% (95% confidence interval (CI): 0.18-0.68%) and 0.63% (95% CI: 0.15-1.12%), respectively. These findings suggest that maternal exposure to metal components of air pollutants may increase the risk of LBW in offspring. With no similar studies in New Mexico, this study also posed great importance because of a higher LBW rate in New Mexico than the national average. These findings provide critical information to inform further epidemiological, biological, and toxicological studies.
Collapse
Affiliation(s)
- Yanhong Huang
- Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM, 87131, USA
- UNM Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM, 87131, USA
| | - Xi Gong
- Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM, 87131, USA.
- UNM Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM, 87131, USA.
| | - Lin Liu
- UNM Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM, 87131, USA
- Department of Computer Science, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Li Luo
- Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, 87131, USA
- UNM Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, 87131, USA
| | - Shuguang Leng
- Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, University of New Mexico, Albuquerque, NM, 87131, USA
- UNM Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM, 87131, USA
- Lung Cancer Program, Lovelace Biomedical Research Institute, Albuquerque, NM, USA
| | - Yan Lin
- Department of Geography & Environmental Studies, University of New Mexico, Albuquerque, NM, 87131, USA
- UNM Center for the Advancement of Spatial Informatics Research and Education (ASPIRE), University of New Mexico, Albuquerque, NM, 87131, USA
| |
Collapse
|
8
|
Sun D, Liu C, Zhu Y, Yu C, Guo Y, Sun D, Pang Y, Pei P, Du H, Yang L, Chen Y, Meng X, Liu Y, Zhang J, Schmidt D, Avery D, Chen J, Chen Z, Lv J, Kan H, Li L. Long-Term Exposure to Fine Particulate Matter and Incidence of Esophageal Cancer: A Prospective Study of 0.5 Million Chinese Adults. Gastroenterology 2023; 165:61-70.e5. [PMID: 37059339 PMCID: PMC7615725 DOI: 10.1053/j.gastro.2023.03.233] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Revised: 02/22/2023] [Accepted: 03/02/2023] [Indexed: 04/16/2023]
Abstract
BACKGROUND & AIMS Evidence is sparse and inconclusive on the association between long-term fine (≤2.5 μm) particulate matter (PM2.5) exposure and esophageal cancer. We aimed to assess the association of PM2.5 with esophageal cancer risk and compared the esophageal cancer risk attributable to PM2.5 exposure and other established risk factors. METHODS This study included 510,125 participants without esophageal cancer at baseline from China Kadoorie Biobank. A high-resolution (1 × 1 km) satellite-based model was used to estimate PM2.5 exposure during the study period. Hazard ratios (HR) and 95% CIs of PM2.5 with esophageal cancer incidence were estimated using Cox proportional hazard model. Population attributable fractions for PM2.5 and other established risk factors were estimated. RESULTS There was a linear concentration-response relationship between long-term PM2.5 exposure and esophageal cancer. For each 10-μg/m3 increase in PM2.5, the HR was 1.16 (95% CI, 1.04-1.30) for esophageal cancer incidence. Compared with the first quarter of PM2.5 exposure, participants in the highest quarter had a 1.32-fold higher risk for esophageal cancer, with an HR of 1.32 (95% CI, 1.01-1.72). The population attributable risk because of annual average PM2.5 concentration ≥35 μg/m3 was 23.3% (95% CI, 6.6%-40.0%), higher than the risks attributable to lifestyle risk factors. CONCLUSIONS This large prospective cohort study of Chinese adults found that long-term exposure to PM2.5 was associated with an elevated risk of esophageal cancer. With stringent air pollution mitigation measures in China, a large reduction in the esophageal cancer disease burden can be expected.
Collapse
Affiliation(s)
- Dong Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Cong Liu
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, National Health Commission Key Laboratory of Health Technology Assessment, Integrated Research on Disaster Risk, International Centers of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yunqing Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, United Kingdom; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, National Health Commission Key Laboratory of Health Technology Assessment, Integrated Research on Disaster Risk, International Centers of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia
| | - Jun Zhang
- Suzhou Center for Disease Prevention and Control, Suzhou, China
| | - Dan Schmidt
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Daniel Avery
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
| | - Haidong Kan
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education, National Health Commission Key Laboratory of Health Technology Assessment, Integrated Research on Disaster Risk, International Centers of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
| |
Collapse
|
9
|
Li X, Wang P, Wang W, Zhang H, Shi S, Xue T, Lin J, Zhang Y, Liu M, Chen R, Kan H, Meng X. Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models. ENVIRONMENT INTERNATIONAL 2023; 176:107967. [PMID: 37244002 DOI: 10.1016/j.envint.2023.107967] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 04/07/2023] [Accepted: 05/07/2023] [Indexed: 05/29/2023]
Abstract
BACKGROUND A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 μg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 μg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 μg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.
Collapse
Affiliation(s)
- Xinyue Li
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Peng Wang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200438, China
| | - Weidong Wang
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Hongliang Zhang
- Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai 200438, China
| | - Su Shi
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Tao Xue
- Institute of Reproductive and Child Health/National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Jintai Lin
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Yuhang Zhang
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Mengyao Liu
- Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Renjie Chen
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Haidong Kan
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China
| | - Xia Meng
- School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and Key Laboratory of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai 200302, China; Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China.
| |
Collapse
|
10
|
Liang W, Zhu H, Xu J, Zhao Z, Zhou L, Zhu Q, Cai J, Ji L. Ambient air pollution and gestational diabetes mellitus: An updated systematic review and meta-analysis. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 255:114802. [PMID: 36934545 DOI: 10.1016/j.ecoenv.2023.114802] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/23/2023] [Accepted: 03/15/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVE We aimed to evaluate the relationship between the composition of particulate matter (PM) and gestational diabetes mellitus (GDM) by a comprehensively review of epidemiological studies. METHODS We systematically identified cohort studies related to air pollution and GDM risk before February 8, 2023 from six databases (PubMed, Embase, Web of Science Core Collection, China National Knowledge Infrastructure, Wanfang Data Knowledge Service Platform and Chongqing VIP Chinese Science and Technology Periodical databases). We calculated the relative risk (RR) and its 95% confidence intervals (CIs) to assess the overall effect by using a random effects model. RESULTS This meta-analysis of 31 eligible cohort studies showed that exposure to PM2.5, PM10, SO2, and NO2 was associated with a significantly increased risk of GDM, especially in preconception and first trimester. Analysis of the components of PM2.5 found that the risk of GDM was strongly linked to black carbon (BC) and nitrates (NO3-). Specifically, BC exposure in the second trimester and NO3- exposure in the first trimester elevated the risk of GDM, with the RR of 1.128 (1.032-1.231) and 1.128 (1.032-1.231), respectively. The stratified analysis showed stronger correlations of GDM risk with higher levels of pollutants in Asia, except for PM2.5 and BC, which suggested that the specific composition of particulate pollutants had a greater effect on the exposure-outcome association than the concentration. CONCLUSIONS Our study found that ambient air pollutant is a critical factor for GDM and further studies on specific particulate matter components should be considered in the future.
Collapse
Affiliation(s)
- Weiqi Liang
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China
| | - Hui Zhu
- Department of Internal Medicine, School of Medicine, Ningbo University, Ningbo, China
| | - Jin Xu
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China; Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, China
| | - Zhijia Zhao
- Department of Preventive Medicine, School of Medicine, Ningbo University, Ningbo, China
| | - Liming Zhou
- Center for Reproductive Medicine, Ningbo Women and Children's Hospital, Ningbo, China
| | - Qiong Zhu
- Department of Pediatrics, Affiliated People's Hospital of Ningbo University, Ningbo, China
| | - Jie Cai
- Center for Reproductive Medicine, Ningbo Women and Children's Hospital, Ningbo, China.
| | - Lindan Ji
- Zhejiang Key Laboratory of Pathophysiology, School of Medicine, Ningbo University, Ningbo, China; Department of Biochemistry, School of Medicine, Ningbo University, Ningbo, China.
| |
Collapse
|
11
|
Sun D, Liu C, Ding Y, Yu C, Guo Y, Sun D, Pang Y, Pei P, Du H, Yang L, Chen Y, Meng X, Liu Y, Liu J, Sohoni R, Sansome G, Chen J, Chen Z, Lv J, Kan H, Li L. Long-term exposure to ambient PM 2·5, active commuting, and farming activity and cardiovascular disease risk in adults in China: a prospective cohort study. Lancet Planet Health 2023; 7:e304-e312. [PMID: 37019571 PMCID: PMC10104773 DOI: 10.1016/s2542-5196(23)00047-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/12/2023] [Accepted: 02/15/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Increased physical activity is associated with a reduced risk of cardiovascular disease, but outdoor physical activity can be accompanied by increased inhalation of fine particulate matter (PM2·5). The extent to which long-term exposure to PM2·5 can offset the cardiovascular benefits of physical activity is unknown. We aimed to evaluate whether the associations between active commuting or farming activity and incident risks of cerebrovascular disease and ischaemic heart disease were consistent between populations with different ambient PM2·5 exposures. METHODS We did a prospective cohort study using data from people aged 30-79 years without cardiovascular disease at baseline from the China Kadoorie Biobank (CKB). Active commuting and farming activity were assessed at baseline using questionnaires. A high-resolution (1 × 1 km) satellite-based model was used to estimate annual average PM2·5 exposure during the study period. Participants were stratified according to PM2·5 exposure (54 μg/m3 or greater vs less than 54 μg/m3). Hazard ratios (HRs) and 95% CIs for incident cerebrovascular disease and ischaemic heart disease by active commuting and farming activity were estimated using Cox proportional hazard models. Effect modifications by PM2·5 exposure were tested by likelihood ratio tests. Analyses were restricted to the period from Jan 1, 2005, to Dec 31, 2017. FINDINGS Between June 25, 2004, and July 15, 2008, 512 725 people were enrolled in the CKB cohort. 322 399 eligible participants completed the baseline survey and were included in the analysis of active commuting (118 274 non-farmers and 204 125 farmers). Among 204 125 farmers, 2985 reported no farming time and 201 140 were included in the farming activity analysis. During a median follow-up of 11 years, 39 514 cerebrovascular disease cases and 22 313 ischaemic heart disease cases were newly identified. Among non-farmers with exposure to annual average PM2·5 concentrations of less than 54 μg/m3, increased active commuting was associated with lower risks of cerebrovascular disease (highest active commuting vs lowest active commuting HR 0·70, 95% CI 0·65-0·76) and ischaemic heart disease (0·60, 0·54-0·66). However, among non-farmers with exposure to annual average PM2·5 concentrations of 54 μg/m3 or greater, there was no association between active commuting and cerebrovascular disease or ischaemic heart disease. Among farmers with exposure to annual average PM2·5 concentrations of less than 54 μg/m3, increased active commuting (highest active commuting vs lowest active commuting HR 0·77, 95% CI 0·63-0·93) and increased farming activity (highest activity vs lowest activity HR 0·85, 95% CI 0·79-0·92) were both associated with a lower cerebrovascular disease risk. However, among farmers with exposure to annual average PM2·5 concentrations of 54 μg/m3 or greater, increases in active commuting (highest active commuting vs lowest active commuting HR 1·12, 95% CI 1·05-1·19) and farming activity (highest activity vs lowest activity HR 1·18, 95% CI 1·09-1·28) were associated with an elevated cerebrovascular disease risk. The above associations differed significantly between PM2·5 strata (all interaction p values <0·0001). INTERPRETATION For participants with long-term exposure to higher ambient PM2·5 concentrations, the cardiovascular benefits of active commuting and farming activity were significantly attenuated. Higher levels of active commuting and farming activity even increased the cerebrovascular disease risk among farmers with exposure to annual average PM2·5 concentrations of 54 μg/m3 or greater. FUNDING National Natural Science Foundation of China, National Key Research and Development Program of China, Kadoorie Charitable Foundation, UK Wellcome Trust.
Collapse
Affiliation(s)
- Dong Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC 12 Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and 13 Governance on Weather or Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yinqi Ding
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Yu Guo
- Fuwai Hospital Chinese Academy of Medical Sciences, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Pei Pei
- Chinese Academy of Medical Sciences, Beijing, China
| | - Huaidong Du
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ling Yang
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Medical Research Council Population Health Research Unit, University of Oxford, Oxford, UK; Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC 12 Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and 13 Governance on Weather or Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jiben Liu
- Prevention and Health Department, Yongqinglu Community Health Service, Qingdao, China
| | - Rajani Sohoni
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Gary Sansome
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, NHC 12 Key Lab of Health Technology Assessment, IRDR ICoE on Risk Interconnectivity and 13 Governance on Weather or Climate Extremes Impact and Public Health, Fudan University, Shanghai, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China; Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China.
| |
Collapse
|
12
|
Huang Y, Gong X, Liu L, Luo L, Leng S, Lin Y. Maternal exposure to metal components of PM2.5 and low birth weight in New Mexico, USA. RESEARCH SQUARE 2023:rs.3.rs-2666605. [PMID: 37034648 PMCID: PMC10081375 DOI: 10.21203/rs.3.rs-2666605/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2023]
Abstract
Infants with low birth weight (LBW) are more likely to have health problems than normal weight infants. In studies examining the associations between particulate matter (PM) exposures and LBW, there is a tendency to focus on PM 2.5 as a whole. However, insufficient information is available regarding the effects of different components of PM 2.5 on birth weight. This study identified the associations between maternal exposure to 10 metal components of PM 2.5 and LBW in offspring based on small area (divided by population size) level data in New Mexico, USA, from 2012 to 2016. This study used a pruned feed-forward neural network (pruned-FNN) approach to estimate the annual average exposure index to each metal component in each small area. The linear regression model was employed to examine the association between maternal PM 2.5 metal exposures and LBW rate in small areas, adjusting for the female percentage and race/ethnicity compositions, marriage status and educational level in the population. An interquartile range increase in maternal exposure to mercury and chromium of PM 2.5 increased LBW rate by 0.43% (95% confidence interval (CI): 0.18%-0.68%) and 0.63% (95% CI: 0.15%-1.12%), respectively. These findings suggest that maternal exposure to metal components of air pollutants may increase the risk of LBW in offspring. With no similar studies in New Mexico, this study also posed great importance because of a higher LBW rate in New Mexico than the national average. These findings provide critical information to inform further epidemiological, biological, and toxicological studies.
Collapse
Affiliation(s)
- Yanhong Huang
- The University of New Mexico - Albuquerque: The University of New Mexico
| | | | - Lin Liu
- University of New Mexico - Albuquerque: The University of New Mexico
| | - Li Luo
- University of New Mexico - Albuquerque: The University of New Mexico
| | - Shuguang Leng
- University of New Mexico - Albuquerque: The University of New Mexico
| | - Yan Lin
- University of New Mexico - Albuquerque: The University of New Mexico
| |
Collapse
|
13
|
Zhou W, Ming X, Yang Y, Hu Y, He Z, Chen H, Li Y, Cheng J, Zhou X. Associations between maternal exposure to ambient air pollution and very low birth weight: A birth cohort study in Chongqing, China. Front Public Health 2023; 11:1123594. [PMID: 36960371 PMCID: PMC10028238 DOI: 10.3389/fpubh.2023.1123594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/15/2023] [Indexed: 03/09/2023] Open
Abstract
Introduction There have been many researches done on the association between maternal exposure to ambient air pollution and adverse pregnancy outcomes, but few studies related to very low birth weight (VLBW). This study thus explores the association between maternal exposure to ambient air pollutants and the risk of VLBW, and estimates the sensitive exposure time window. Methods A retrospective cohort study analyzed in Chongqing, China, during 2015-2020. The Generalized Additive Model were applied to estimate exposures for each participant during each trimester and the entire pregnancy period. Results For each 10 μg/m3 increase in PM2.5 during pregnancy, the relative risk of VLBW increased on the first trimester, with RR = 1.100 (95% CI: 1.012, 1.195) in the single-pollutant model. Similarly, for each 10 μg/m3 increase in PM10, there was a 12.9% (RR = 1.129, 95% CI: 1.055, 1.209) increase for VLBW on the first trimester in the single-pollutant model, and an 11.5% (RR = 1.115, 95% CI: 1.024, 1.213) increase in the multi-pollutant model, respectively. The first and second trimester exposures of NO2 were found to have statistically significant RR values for VLBW. The RR values on the first trimester were 1.131 (95% CI: 1.037, 1.233) and 1.112 (95% CI: 1.015, 1.218) in the single-pollutant model and multi-pollutant model, respectively; The RR values on the second trimester were 1.129 (95% CI: 1.027, 1.241) and 1.146 (95% CI: 1.038, 1.265) in the single-pollutant model and multi-pollutant model, respectively. The RR of O3 exposure for VLBW on the entire trimester was 1.076 (95% CI: 1.010-1.146), and on the second trimester was 1.078 (95% CI: 1:016, 1.144) in the single-pollutant model. Conclusion This study indicates that maternal exposure to high levels of PM2.5, PM10, NO2, and O3 during pregnancy may increase the risk of very low birth weight, especially for exposure on the first and second trimester. Reducing the risk of early maternal exposure to ambient air pollution is thus necessary for pregnant women.
Collapse
Affiliation(s)
- Wenzheng Zhou
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Xin Ming
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Yunping Yang
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Yaqiong Hu
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Ziyi He
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Hongyan Chen
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Yannan Li
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
| | - Jin Cheng
- Institute of Toxicology, College of Preventive Medicine, Army Medical University (Third Military Medical University), Chongqing, China
- Jin Cheng
| | - Xiaojun Zhou
- Department of Quality Management Section, Women and Children's Hospital of Chongqing Medical University, Chongqing, China
- Department of Quality Management Section, Chongqing Health Center for Women and Children, Chongqing, China
- *Correspondence: Xiaojun Zhou
| |
Collapse
|
14
|
Association between prenatal PM2.5 exposure and the risk of large for gestational age. Pediatr Res 2022; 92:1773-1779. [PMID: 35277595 DOI: 10.1038/s41390-021-01889-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 07/11/2021] [Accepted: 07/21/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND The relationship between particulate matter <2.5 µm (PM2.5) and large for gestational age (LGA) is unclear, and studies conducted in highly polluted areas are lacking. We aimed to explore the association between PM2.5 and the risk of LGA in China. METHODS Maternal and neonatal characteristics were collected in the National Prepregnancy Examination Project. The definition of LGA was neonates with a weight over the 90th percentile for gestational age. Logistic regression was used to evaluate the relationship between PM2.5 exposure and the risk of LGA. The dose-response relationship was evaluated using a restricted cubic spline model. RESULTS There were 196,243 mother-neonate pairs included, among which the percentage of LGA was 15.3%. The average PM2.5 concentration was 75.29 µg/m3. A 10 µg/m3 increase in PM2.5 during the whole pregnancy was associated with an increased risk of LGA (odds ratio (OR) 1.097, 95% confidence interval (CI) 1.091-1.103). Pregnant women in the high-exposure group had a higher risk of giving birth to an LGA infant (OR 1.37, 95% CI 1.33-1.41). There was a nonlinear relationship between PM2.5 concentration and the risk of LGA, and the risk increased more rapidly at higher PM2.5 levels. CONCLUSIONS Prenatal exposure to PM2.5 was linked to an increased risk of LGA. IMPACT A nation-wide study in a highly polluted country suggested the association between prenatal PM2.5 exposure and LGA. A trimester-specific relationship between PM2.5 exposure and LGA was established. Call for attention on the pregnant women in highly polluted areas who were in high risk of giving birth to LGA.
Collapse
|
15
|
Liu C, Chan KH, Lv J, Lam H, Newell K, Meng X, Liu Y, Chen R, Kartsonaki C, Wright N, Du H, Yang L, Chen Y, Guo Y, Pei P, Yu C, Shen H, Wu T, Kan H, Chen Z, Li L. Long-Term Exposure to Ambient Fine Particulate Matter and Incidence of Major Cardiovascular Diseases: A Prospective Study of 0.5 Million Adults in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:13200-13211. [PMID: 36044001 PMCID: PMC9494741 DOI: 10.1021/acs.est.2c03084] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Few cohort studies explored the long-term effects of ambient fine particulate matter (PM2.5) on incidence of cardiovascular diseases (CVDs), especially in countries with higher levels of air pollution. We aimed to evaluate the association between long-term exposure to PM2.5 and incidence of CVD in China. We performed a prospective cohort study in ten regions that recruited 512,689 adults during 2004-2008, with follow-up until 2017. Annual PM2.5 concentrations were estimated using a satellite-based model with national coverage and 1 x 1 km spatial resolution. Time-varying Cox proportional hazard regression models were used to estimate hazard ratios (HRs) for all-cause and cause-specific CVDs associated with PM2.5, adjusting for conventional covariates. During 5.08 million person-years of follow-up, 148,030 incident cases of CVD were identified. Long-term exposure to PM2.5 showed positive and linear association with incidence of CVD, without a threshold below any concentration. The adjusted HRs per 10 μg/m3 increase in PM2.5 was 1.04 (95%CI: 1.02, 1.07) for total CVD. The risk estimates differed between certain population subgroups, with greater HRs in men, in household with higher income, and in people using unclean heating fuels. This prospective study of large Chinese population provided essential epidemiological evidence for CVD incident risk associated with PM2.5.
Collapse
Affiliation(s)
- Cong Liu
- School
of Public Health, Key Lab of Public Health Safety of the Ministry
of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE
on Risk Interconnectivity and Governance on Weather/Climate Extremes
Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Ka Hung Chan
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Oxford
British Heart Foundation Center of Research Excellence, University of Oxford, Oxford OX3 7LF, UK
| | - Jun Lv
- Department
of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking
University Center for Public Health and Epidemic Preparedness &
Response, Beijing 100191, China
- Key Laboratory
of Molecular Cardiovascular Sciences (Peking University), Ministry
of Education, Beijing 100191, China
| | - Hubert Lam
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Katherine Newell
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Xia Meng
- School
of Public Health, Key Lab of Public Health Safety of the Ministry
of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE
on Risk Interconnectivity and Governance on Weather/Climate Extremes
Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Yang Liu
- Gangarosa
Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, United States
| | - Renjie Chen
- School
of Public Health, Key Lab of Public Health Safety of the Ministry
of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE
on Risk Interconnectivity and Governance on Weather/Climate Extremes
Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Christiana Kartsonaki
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Neil Wright
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Huaidong Du
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Ling Yang
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Yiping Chen
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
| | - Yu Guo
- Fuwai
Hospital Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Pei Pei
- Fuwai
Hospital Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Canqing Yu
- Department
of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking
University Center for Public Health and Epidemic Preparedness &
Response, Beijing 100191, China
| | - Hongbing Shen
- Department
of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Tangchun Wu
- School
of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Haidong Kan
- School
of Public Health, Key Lab of Public Health Safety of the Ministry
of Education, NHC Key Lab of Health Technology Assessment, IRDR ICoE
on Risk Interconnectivity and Governance on Weather/Climate Extremes
Impact and Public Health, Fudan University, Shanghai 200032, China
| | - Zhengming Chen
- Clinical
Trial Service Unit & Epidemiological Studies Unit, Nuffield Department
of Population Health, University of Oxford, Oxford OX3 7LF, UK
- MRC
Population Health Research Unit, Nuffield Department of Population
Health, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - Liming Li
- Department
of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
- Peking
University Center for Public Health and Epidemic Preparedness &
Response, Beijing 100191, China
| | | |
Collapse
|
16
|
Yu Z, Zhang X, Zhang J, Feng Y, Zhang H, Wan Z, Xiao C, Zhang H, Wang Q, Huang C. Gestational exposure to ambient particulate matter and preterm birth: An updated systematic review and meta-analysis. ENVIRONMENTAL RESEARCH 2022; 212:113381. [PMID: 35523275 DOI: 10.1016/j.envres.2022.113381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/17/2022] [Accepted: 04/26/2022] [Indexed: 06/14/2023]
Abstract
Previous studies on gestational particulate matter (PM) exposure and preterm birth (PTB) showed inconsistent results, and no study systematically examined the short-term effect of PM exposure on PTB subtypes. To investigate both long- and short-term effects of the evidence to date in general population, we searched for epidemiological studies on PM exposure and PTB that published in PubMed, Web of Science, Embase and Cochrane Library up to March 31, 2022. The protocol for this review was registered with PROSPERO (CRD42021265202). Heterogeneity was assessed by Cochran's Q test and I2 statistic. Publication bias was evaluated using funnel plots and Egger's tests. Subgroup analysis, meta-regression and sensitivity analysis were performed. Of 16,801 records, 84 eligible studies were finally included. The meta-analysis of long-term effect showed that per 10 μg/m3 increase in PM2.5 and PM10 during entire pregnancy were associated with PTB, the pooled odds ratios (ORs) were 1.084 (95% CI: 1.055-1.113) and 1.034 (95% CI: 1.018-1.049). Positive associations were found between PM2.5 in second trimester and PTB subtypes. For the short-term exposure, we observed that PTB was positively associated with a 10 μg/m3 increment in PM2.5 on lag day 2 and 3, the pooled ORs and 95% CIs were 1.003 (1.001-1.004) and 1.003 (1.001-1.005), with I2 of 65.30% and 76.60%. PM10 exposure on ave day 1 increased the risk of PTB, the pooled OR was 1.001 (95% CI: 1.000, 1.001). We also found that PM10 exposure in 2 weeks prior to birth increased PTB risk. Our results support the hypothesis of both long- and short-term PM2.5 exposure increase the risk of PTB. Further well-designed longitudinal studies and investigations into potential biological mechanisms are warranted.
Collapse
Affiliation(s)
- Zengli Yu
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Junxi Zhang
- National Health Commission Key Laboratory of Birth Defects Prevention; Key Laboratory of Population Defects Prevention, Zhengzhou, China
| | - Yang Feng
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Han Zhang
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Zhongxiao Wan
- School of Public Health, Zhengzhou University, Zhengzhou, China
| | - Chenglong Xiao
- School of Earth Sciences, Chengdu University of Technology, Chengdu, China
| | - Huanhuan Zhang
- School of Public Health, Zhengzhou University, Zhengzhou, China; National Health Commission Key Laboratory of Birth Defects Prevention; Key Laboratory of Population Defects Prevention, Zhengzhou, China.
| | - Qiong Wang
- School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Cunrui Huang
- Vanke School of Public Health, Tsinghua University, Beijing, China
| |
Collapse
|
17
|
Rocha ADS, Falcão IR, Teixeira CSS, Alves FJO, Ferreira AJF, Silva NDJ, Almeida MFD, Ribeiro-Silva RDC. Determinants of preterm birth: proposal for a hierarchical theoretical model. CIENCIA & SAUDE COLETIVA 2022. [DOI: 10.1590/1413-81232022278.03232022en] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Abstract Preterm birth (PB) is a syndrome resulting from a complex relationship between multiple factors which do not have fully understood relationships and causality. This article discusses a hierarchical theoretical model of PB determinants, considering maternal characteristics such as sociodemographic, psychosocial, nutritional, behavioral and biological aspects, traditionally associated with increased risk of PB. The variables were distributed in six dimensions within three hierarchical levels (distal, intermediate and proximal). In this model, the socioeconomic determinants of the mother, family, household and neighborhood play indirect effects on PB through variables at the intermediate level, which in turn affect biological risk factors at the proximal level that have a direct effect on PB. The study presents a hierarchical theoretical model of the factors involved in the PB determination chain and their interrelationships. Understanding these interrelationships is an important step in trying to break the causal chain that makes some women vulnerable to preterm birth.
Collapse
Affiliation(s)
| | - Ila Rocha Falcão
- Universidade Federal da Bahia, Brazil; Fundação Oswaldo Cruz, Brazil
| | | | | | | | | | | | | |
Collapse
|
18
|
Rocha ADS, Falcão IR, Teixeira CSS, Alves FJO, Ferreira AJF, Silva NDJ, Almeida MFD, Ribeiro-Silva RDC. Determinants of preterm birth: proposal for a hierarchical theoretical model. CIENCIA & SAUDE COLETIVA 2022; 27:3139-3152. [PMID: 35894325 DOI: 10.1590/1413-81232022278.03232022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 05/05/2022] [Indexed: 11/22/2022] Open
Abstract
Preterm birth (PB) is a syndrome resulting from a complex relationship between multiple factors which do not have fully understood relationships and causality. This article discusses a hierarchical theoretical model of PB determinants, considering maternal characteristics such as sociodemographic, psychosocial, nutritional, behavioral and biological aspects, traditionally associated with increased risk of PB. The variables were distributed in six dimensions within three hierarchical levels (distal, intermediate and proximal). In this model, the socioeconomic determinants of the mother, family, household and neighborhood play indirect effects on PB through variables at the intermediate level, which in turn affect biological risk factors at the proximal level that have a direct effect on PB. The study presents a hierarchical theoretical model of the factors involved in the PB determination chain and their interrelationships. Understanding these interrelationships is an important step in trying to break the causal chain that makes some women vulnerable to preterm birth.
Collapse
Affiliation(s)
- Aline Dos Santos Rocha
- Escola de Nutrição, Universidade Federal da Bahia, Salvador. Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. R. Mundo 121, ed. Tecnocentro, sl. 315, Trobogy. 41745-715 Salvador BA Brasil.
| | - Ila Rocha Falcão
- Escola de Nutrição, Universidade Federal da Bahia, Salvador. Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. R. Mundo 121, ed. Tecnocentro, sl. 315, Trobogy. 41745-715 Salvador BA Brasil.
| | - Camila Silveira Silva Teixeira
- Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. Instituto de Saúde Coletiva, Universidade Federal da Bahia. Salvador BA Brasil
| | - Flávia Jôse Oliveira Alves
- Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. Instituto de Saúde Coletiva, Universidade Federal da Bahia. Salvador BA Brasil
| | - Andrêa Jacqueline Fortes Ferreira
- Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. Instituto de Saúde Coletiva, Universidade Federal da Bahia. Salvador BA Brasil
| | - Natanael de Jesus Silva
- Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. Instituto de Saúde Global de Barcelona, Hospital Clínic. Barcelona Espanha
| | | | - Rita de Cássia Ribeiro-Silva
- Escola de Nutrição, Universidade Federal da Bahia, Salvador. Centro de Integração de Dados e Conhecimentos para Saúde (Cidacs), Fundação Oswaldo Cruz. R. Mundo 121, ed. Tecnocentro, sl. 315, Trobogy. 41745-715 Salvador BA Brasil.
| |
Collapse
|
19
|
Ahmad WA, Nirel R, Golan R, Jolles M, Kloog I, Rotem R, Negev M, Koren G, Levine H. Mother-level random effect in the association between PM 2.5 and fetal growth: A population-based pregnancy cohort. ENVIRONMENTAL RESEARCH 2022; 210:112974. [PMID: 35192805 DOI: 10.1016/j.envres.2022.112974] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Revised: 02/02/2022] [Accepted: 02/16/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND A growing body of literature reports associations between exposure to particulate matter with diameter ≤2.5 μm (PM2.5) during pregnancy and birth outcomes. However, findings are inconsistent across studies. OBJECTIVES To assess the association between PM2.5 and birth outcomes of fetal growth in a cohort with high prevalence of siblings by multilevel models accounting for geographical- and mother-level correlations. METHODS In Israel, we used Maccabi Healthcare Services data to establish a population-based cohort of 381,265 singleton births reaching 24-42 weeks' gestation and birth weight of 500-5000 g (2004-2015). Daily PM2.5 predictions from a satellite-based spatiotemporal model were linked to the date of birth and maternal residence. We generated mean PM2.5 values for the entire pregnancy and for exposure periods during pregnancy. Associations between exposure and birth outcomes were modeled by using multilevel logistic regression with random effects for maternal locality of residence, administrative census area (ACA) and mother. RESULTS In fully adjusted models with a mother-level random intercept only, a 10-μg/m3 increase in PM2.5 over the entire pregnancy was positively associated with term low birth weight (TLBW) (Odds ratio, OR = 1.25, 95% confidence interval, CI: 1.09,1.43) and small for gestational age (SGA) (OR = 1.15, 95% CI: 1.06,1.26). Locality- and ACA-level effects accounted for <0.4% of the variance while mother-level effects explained ∼50% of the variability. Associations varied by exposure period, infants' sex, birth order, and maternal pre-pregnancy BMI. CONCLUSIONS Consideration of mother-level variability in a region with high fertility rates provides new insights on the strength of associations between PM2.5 and birth outcomes.
Collapse
Affiliation(s)
| | - Ronit Nirel
- Hebrew University of Jerusalem, Jerusalem, Israel
| | - Rachel Golan
- Ben-Gurion University of the Negev, Beer Sheva, Israel
| | | | - Itai Kloog
- Ben-Gurion University of the Negev, Beer Sheva, Israel
| | - Ran Rotem
- Harvard T.H. Chan School of Public Health, Boston, MA, USA; Institute of Research and Innovation, Maccabitech, Tel-Aviv, Israel
| | | | - Gideon Koren
- Institute of Research and Innovation, Maccabitech, Tel-Aviv, Israel; Tel Aviv University, Tel-Aviv, Israel
| | | |
Collapse
|
20
|
Xu J, Yang Z, Han B, Yang W, Duan Y, Fu Q, Bai Z. A unified empirical modeling approach for particulate matter and NO 2 in a coastal city in China. CHEMOSPHERE 2022; 299:134384. [PMID: 35337823 DOI: 10.1016/j.chemosphere.2022.134384] [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: 11/19/2021] [Revised: 02/27/2022] [Accepted: 03/18/2022] [Indexed: 06/14/2023]
Abstract
Modeling air pollutants on a fine spatiotemporal scale is necessary for health studies that focus on critical short-term exposure windows. A unified empirical modeling approach is useful for health studies; however, it is unclear whether this approach can be used in a coastal city for air pollutants driven by local emissions and regional meteorological factors. An advanced empirical modeling approach was used to develop exposure models from October 2012 to December 2019, for particulate matter with aerodynamic diameters less than or equal to 2.5 and 10 μm (PM2.5 and PM10) and nitrogen dioxide (NO2) in the coastal city of Shanghai, China. Air pollutant concentrations were obtained from daily measurements at 55 administrative monitoring sites that were integrated into three-day average concentrations. Data on a large array of geographic variables were collected, and their dimensions were reduced using the partial least squares regression method. A geostatistical model using the land-use regression approach in a universal kriging framework was developed to estimate short-term exposure concentrations. The prediction ability of the models were determined by leave-one (site)-out cross-validation (LOOCV) and external validation (EV). Compared to the LOOCV results, the EV results for PM2.5 and PM10 were consistently reliable, but the EV for NO2 had a larger root mean squared error. The temporal random effects involved in the model structure were interpreted using sensitivity analyses. This affected the short-term PM2.5 and PM10 model predictions. This unified empirical modeling approach was successfully used for particulate matter in Shanghai, where air pollution is affected by complex regional and meteorological conditions. These exposure models are going to be applied for making exposure predictions at residential locations for short-term exposure predictions in the "Growth trajectories and air pollution" (GAAP) study in Shanghai that focuses on maternal and early life exposure to air pollutants.
Collapse
Affiliation(s)
- Jia Xu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhenchun Yang
- Duke Global Health Institute, Duke University, Durham, NC, 27708, United States
| | - Bin Han
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Wen Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Yusen Duan
- Shanghai Environmental Monitoring Center, Shanghai, China.
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai, China
| | - Zhipeng Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| |
Collapse
|
21
|
Zeng Z, Xu X, Wang Q, Zhang Z, Meng P, Huo X. Maternal exposure to atmospheric PM 2.5 and fetal brain development: Associations with BAI1 methylation and thyroid hormones. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 308:119665. [PMID: 35738517 DOI: 10.1016/j.envpol.2022.119665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/13/2022] [Accepted: 06/18/2022] [Indexed: 02/05/2023]
Abstract
Maternal exposure to atmospheric fine particulate matter (PM2.5) during pregnancy is associated with adverse fetal development, including abnormal brain development. However, the underlying mechanisms and influencing factors remain uncertain. This study investigated the roles of DNA methylation in genes involving neurodevelopment and thyroid hormones (THs) in fetal brain development after maternal exposure to PM2.5 from e-waste. Among 939 healthy pregnant women recruited from June 2011 to September 2012, 101 e-waste-exposed and 103 reference mother-infant pairs (204 pairs totally) were included. Annual ground-level PM2.5 concentrations over e-waste-exposed area (116.38°E, 23.29°N) and reference area (116.67°E, 23.34°N) in 2011, 2012 were obtained by estimates and maternal exposure was evaluated by calculating individual chronic daily intakes (CDIs) of PM2.5. Methylation and THs including thyroid-stimulating hormone (TSH), free triiodothyronine (FT3) and free thyroxine (FT4) level were measured in umbilical cord blood collected shortly after delivery. We found higher ground-level PM2.5 concentrations led to greater individual CDI of PM2.5 in e-waste-exposed pregnant women. After adjustment for gender and birth BMI, significant mediation effects on the adverse associations of maternal PM2.5 exposure with birth head circumference were observed for methylations at positions +13 and + 32 (respectively mediated proportion of 9.8% and 5.3%, P < 0.05 and P < 0.01) in the brain-specific angiogenesis inhibitor 1 (BAI1) gene, but not for methylations in the catenin cadherin-associated protein, alpha 2 (CTNNA2) gene. BAI1 (position +13) methylation was also significantly correlated with FT3 levels (rs = -0.156, P = 0.032), although maternal CDI of PM2.5 was positively associated with higher odds of abnormal TSH levels (OR = 5.03, 95% CI: 1.00, 25.20, P = 0.05) rather than FT3 levels. Our findings suggest that methylation (likely linked to THs) in neonates may play mediation roles associated with abnormal brain development risk due to maternal exposure to atmospheric PM2.5 from e-waste.
Collapse
Affiliation(s)
- Zhijun Zeng
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, Guangdong, China
| | - Xijin Xu
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Provincial Key Laboratory of Infectious Diseases and Molecular Immunopathology, Shantou University Medical College, Shantou, 515041, Guangdong, China; Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, 515041, Guangdong, China
| | - Qihua Wang
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, Guangdong, China
| | - Zhuxia Zhang
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, Guangdong, China
| | - Peipei Meng
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, Guangdong, China
| | - Xia Huo
- Laboratory of Environmental Medicine and Developmental Toxicology, Guangdong Key Laboratory of Environmental Pollution and Health, School of Environment, Jinan University, Guangzhou, 511443, Guangdong, China.
| |
Collapse
|
22
|
Shukla K, Seppanen C, Naess B, Chang C, Cooley D, Maier A, Divita F, Pitiranggon M, Johnson S, Ito K, Arunachalam S. ZIP Code-Level Estimation of Air Quality and Health Risk Due to Particulate Matter Pollution in New York City. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:7119-7130. [PMID: 35475336 PMCID: PMC9178920 DOI: 10.1021/acs.est.1c07325] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 03/30/2022] [Accepted: 04/01/2022] [Indexed: 05/19/2023]
Abstract
Exposure to PM2.5 is associated with hundreds of premature mortalities every year in New York City (NYC). Current air quality and health impact assessment tools provide county-wide estimates but are inadequate for assessing health benefits at neighborhood scales, especially for evaluating policy options related to energy efficiency or climate goals. We developed a new ZIP Code-Level Air Pollution Policy Assessment (ZAPPA) tool for NYC by integrating two reduced form models─Community Air Quality Tools (C-TOOLS) and the Co-Benefits Risk Assessment Health Impacts Screening and Mapping Tool (COBRA)─that propagate emissions changes to estimate air pollution exposures and health benefits. ZAPPA leverages custom higher resolution inputs for emissions, health incidences, and population. It, then, enables rapid policy evaluation with localized ZIP code tabulation area (ZCTA)-level analysis of potential health and monetary benefits stemming from air quality management decisions. We evaluated the modeled 2016 PM2.5 values against observed values at EPA and NYCCAS monitors, finding good model performance (FAC2, 1; NMSE, 0.05). We, then, applied ZAPPA to assess PM2.5 reduction-related health benefits from five illustrative policy scenarios in NYC focused on (1) commercial cooking, (2) residential and commercial building fuel regulations, (3) fleet electrification, (4) congestion pricing in Manhattan, and (5) these four combined as a "citywide sustainable policy implementation" scenario. The citywide scenario estimates an average reduction in PM2.5 of 0.9 μg/m3. This change translates to avoiding 210-475 deaths, 340 asthma emergency department visits, and monetized health benefits worth $2B to $5B annually, with significant variation across NYC's 192 ZCTAs. ZCTA-level assessments can help prioritize interventions in neighborhoods that would see the most health benefits from air pollution reduction. ZAPPA can provide quantitative insights on health and monetary benefits for future sustainability policy development in NYC.
Collapse
Affiliation(s)
- Komal Shukla
- Institute
for the Environment, The University of North
Carolina at Chapel Hill, Chapel
Hill, North Carolina 27599, United States
| | - Catherine Seppanen
- Institute
for the Environment, The University of North
Carolina at Chapel Hill, Chapel
Hill, North Carolina 27599, United States
| | - Brian Naess
- Institute
for the Environment, The University of North
Carolina at Chapel Hill, Chapel
Hill, North Carolina 27599, United States
| | - Charles Chang
- Institute
for the Environment, The University of North
Carolina at Chapel Hill, Chapel
Hill, North Carolina 27599, United States
| | - David Cooley
- Abt
Associates, Durham, North Carolina 27703, United States
| | - Andreas Maier
- Abt
Associates, Durham, North Carolina 27703, United States
| | - Frank Divita
- Abt
Associates, Durham, North Carolina 27703, United States
| | - Masha Pitiranggon
- New
York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, New York 10013, United States
| | - Sarah Johnson
- New
York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, New York 10013, United States
| | - Kazuhiko Ito
- New
York City Department of Health and Mental Hygiene, Bureau of Environmental Surveillance and Policy, New York, New York 10013, United States
| | - Saravanan Arunachalam
- Institute
for the Environment, The University of North
Carolina at Chapel Hill, Chapel
Hill, North Carolina 27599, United States
| |
Collapse
|
23
|
Fang J, Yang Y, Zou X, Xu H, Wang S, Wu R, Jia J, Xie Y, Yang H, Yuan N, Hu M, Deng Y, Zhao Y, Wang T, Zhu Y, Ma X, Fan M, Wu J, Song X, Huang W. Maternal exposures to fine and ultrafine particles and the risk of preterm birth from a retrospective study in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 812:151488. [PMID: 34742962 DOI: 10.1016/j.scitotenv.2021.151488] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/02/2021] [Accepted: 11/02/2021] [Indexed: 06/13/2023]
Abstract
Maternal exposure to fine particulate matter (PM2.5) has been associated with increased risk of preterm birth (PTB), but evidence on particles in smaller sizes and PTB risk remains limited. In this retrospective analysis, we included birth records of 24,001 singleton live births from Haidian Maternal and Child Health Hospital in Beijing, China, 2014-2017. Concurrently, number concentrations of size-fractioned particles in size ranges of 5-560 nm (PNC5-560) and mass concentrations of PM2.5, black carbon (BC) and gaseous pollutants were measured from a fixed-location monitoring station in central Haidian District. Logistic regression models were used to estimate the odds ratio (OR) of air pollutants on PTB risk after controlling for temperature, relative humidity, and individual covariates (e.g., maternal age, ethnicity, gravidity, parity, gestational weight gain, fetal gender, the year and season of conception). Positive matrix factorization models were then used to apportion the sources of PNC5-560. Among the 1062 (4.4%) PTBs, increased PTB risk was observed during the third trimester of pregnancy per 10 μg/m3 increase in PM2.5 [OR = 1.92; 95% Confidence Interval (95% CI): 1.76, 2.09], per 1000 particles/cm3 increase in PNC25-100 (OR = 1.09; 95% CI: 1.03, 1.15) and PNC100-560 (OR = 1.22; 95% CI: 1.05, 1.42). Among the identified sources of PNC5-560, emissions from gasoline and diesel vehicles were significantly associated with increased PTB risk, with ORs of 1.14 (95% CI: 1.01, 1.29) and 1.11 (95% CI: 1.04, 1.18), respectively. Exposures to other traffic-related air pollutants, such as BC and nitrogen dioxide (NO2) were also significantly associated with increased PTB risk. Our findings highlight the importance of traffic emission reduction in urban areas.
Collapse
Affiliation(s)
- Jiakun Fang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Ying Yang
- National Research Institute for Family Planning, Beijing, China; Graduate School of Peking Union Medical College, Beijing, China; National Human Genetic Resources Center, Beijing, China.
| | - Xiaoxuan Zou
- Hadian Maternal and Child Health Hospital, Beijing, China
| | - Hongbing Xu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Shuo Wang
- Hadian Maternal and Child Health Hospital, Beijing, China
| | - Rongshan Wu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jiajing Jia
- Graduate School of Peking Union Medical College, Beijing, China
| | - Yunfei Xie
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Haishan Yang
- Graduate School of Peking Union Medical College, Beijing, China
| | - Ningman Yuan
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Meina Hu
- Graduate School of Peking Union Medical College, Beijing, China
| | - Yuzhi Deng
- Graduate School of Peking Union Medical College, Beijing, China
| | - Yinzhu Zhao
- Graduate School of Peking Union Medical College, Beijing, China
| | - Tong Wang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Yutong Zhu
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Xu Ma
- National Human Genetic Resources Center, Beijing, China; Hadian Maternal and Child Health Hospital, Beijing, China; State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effect and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Meng Fan
- Aerospace Information Research Institute, Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Beijing, China
| | - Jianbin Wu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Xiaoming Song
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China
| | - Wei Huang
- Department of Occupational and Environmental Health, Peking University School of Public Health, and Peking University Institute of Environmental Medicine, Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences of Ministry of Education, Peking University, Beijing, China.
| |
Collapse
|
24
|
Cao K, Jin H, Li H, Tang M, Ge J, Li Z, Wang X, Wei X. Associations of maternal exposure to fine particulate matter with preterm and early-term birth in high-risk pregnant women. Genes Environ 2022; 44:9. [PMID: 35292103 PMCID: PMC8922917 DOI: 10.1186/s41021-022-00239-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 02/23/2022] [Indexed: 11/10/2022] Open
Abstract
Background Environmental pollution is a risk factor for adverse birth outcomes, especially preterm birth (PTB) and early-term birth (ETB). It has been revealed that exposure to fine particulate matter (PM2.5) during pregnancy increase the prevalence of PTB. However, the relationship between PM2.5 exposure and ETB has not been elucidated. In high-risk pregnancies, whether PM2.5 exposure will bring higher risk of PTB and ETB than in normal pregnancies is still unclear, and the susceptible exposure window is obscure. Therefore, it is worthy of assessing the risk on PTB and ETB and identifying the susceptible exposure windows of PM2.5 exposure in high-risk pregnant women. Results This paper collected the clinical data of 7974 singletons, high-risk pregnant women in Peking University First Hospital from 2014 to 2018, and analyzed them using logistic regression and stratified analysis. We observed that exposure to high-level (≥ 75 µg/m3) of PM2.5 during the third trimester of pregnancy increases the risk of PTB and ETB (PTB: odds ratio[OR] = 1.43, 95% confidence interval [CI]:1.05–1.93. ETB: OR = 1.29, 95%CI: 1.09–1.54). Furthermore, the effects of each 10ug/m3 increase in PM2.5 on PTB and ETB were significant during the third trimester (PTB: OR = 1.35, 95%CI:1.16–1.58. ETB: OR = 1.12, 95%CI:1.02–1.22) and the entire pregnancy (PTB: OR = 6.12, 95%CI:4.27–8.89. ETB: OR = 1.96, 95%CI:1.59–2.43) in the high-level exposure group. Conclusions These results suggest that high-level PM2.5 exposure during pregnancy is associated with high risk of PTB and ETB in high-risk pregnancies. The third trimester of pregnancy is speculated to be the susceptible exposure window. Supplementary Information The online version contains supplementary material available at 10.1186/s41021-022-00239-0.
Collapse
Affiliation(s)
- Kaixin Cao
- School of Public Health, Peking University, 100191, Beijing, China.,Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, 100191, Beijing, China.,Peking University First Hospital, 100191, Beijing, China
| | - Hongyan Jin
- Peking University First Hospital, 100191, Beijing, China
| | - Haoxin Li
- School of Public Health, Peking University, 100191, Beijing, China
| | - Mengmeng Tang
- School of Public Health, Peking University, 100191, Beijing, China.,Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, 100191, Beijing, China
| | - Jianhong Ge
- School of Public Health, Peking University, 100191, Beijing, China.,Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, 100191, Beijing, China
| | - Zekang Li
- School of Public Health, Peking University, 100191, Beijing, China.,Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, 100191, Beijing, China
| | - Xiaoyun Wang
- School of Public Health, Peking University, 100191, Beijing, China.,Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, 100191, Beijing, China
| | - Xuetao Wei
- School of Public Health, Peking University, 100191, Beijing, China. .,Beijing Key Laboratory of Toxicological Research and Risk Assessment for Food Safety, Peking University, 100191, Beijing, China.
| |
Collapse
|
25
|
Cheng X, Ji X, Yang D, Zhang C, Chen L, Liu C, Meng X, Wang W, Li H, Kan H, Huang H. Associations of PM 2.5 exposure with blood glucose impairment in early pregnancy and gestational diabetes mellitus. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 232:113278. [PMID: 35131583 DOI: 10.1016/j.ecoenv.2022.113278] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/22/2022] [Accepted: 01/30/2022] [Indexed: 06/14/2023]
Abstract
Exposure to fine particulate matter (PM2.5) during pregnancy has been linked to the risk of gestational diabetes mellitus (GDM), while conclusions are inconsistent. In this study we aimed to estimate the effects of prenatal PM2.5 exposure with blood glucose in early pregnancy and the GDM risk. Participants were recruited from the SH-IPMCH-BTH cohort (n = 41,929), a study of air pollution and birth outcome. All participants provided serum samples for analyses of fasting blood glucose (FBG) and HbA1c during early pregnancy. GDM was diagnosed using an oral glucose tolerance test (OGTT) with the time interval of 1 h. Prenatal exposure to PM2.5 was estimated using gap-filled satellite exposure assessments in Shanghai, China. Both FBG and HbA1c levels were significantly and positively associated with PM2.5 exposure during early pregnancy. A 10 μg/m3 increase of PM2.5 exposure from early to middle pregnancy was associated with the risk of GDM (first trimester OR=1.09, 95% CI: 1.02, 1.16; second trimester OR=1.09, 95% CI: 1.03, 1.16; first two trimester OR=1.15, 95%CI: 1.04, 1.28). The combined effects were greater among elevated FBG and HbA1c women with higher PM2.5 exposure in middle trimester (P for interaction=0.037 and 0.001, respectively). This study found that exposure to PM2.5 exposure in the 1st and 2nd trimesters was related to GDM. FBG and HbA1c played roles in the relationship between PM2.5 exposure in the 2nd trimester and GDM.
Collapse
Affiliation(s)
- Xiaoyue Cheng
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
| | - Xinhua Ji
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
| | - Dongjian Yang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China
| | - Chen Zhang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Lei Chen
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Weidong Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Huichu Li
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Fudan University, Shanghai, China
| | - Hefeng Huang
- International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China.
| |
Collapse
|
26
|
Liang Z, Zhao L, Qiu J, Zhu X, Jiang M, Liu G, Zhao Q. PM 2.5 exposure increases the risk of preterm birth in pre-pregnancy impaired fasting glucose women: A cohort study in a Southern province of China. ENVIRONMENTAL RESEARCH 2022; 204:112403. [PMID: 34800533 DOI: 10.1016/j.envres.2021.112403] [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: 07/18/2021] [Revised: 11/14/2021] [Accepted: 11/15/2021] [Indexed: 06/13/2023]
Abstract
Previous studies have indicated maternal exposure to particles with aerodynamic diameter <2.5 μm (PM2.5) is associated with preterm birth (PTB). However, no study has investigated this effect in pre-pregnancy impaired fasting glucose (IFG) women. This study aimed to differentiate the effects of maternal PM2.5 exposure on PTB between pre-pregnancy IFG and normoglycemia women, and to further identify the susceptible window. This cohort study was conducted between January 2014 and December 2017 in 21 Chinese cities. All the recruited women received pre-pregnancy fasting serum glucose (FSG) tests and were followed up for their delivery outcomes. The PM2.5 exposures were estimated by the daily air pollution concentrations of the nearby monitors. Women with FSG below 7.0 mmol/L were included in the analysis. We employed the Cox proportional hazards models to examine whether PM2.5 exposure was associated with PTB. 237957 women were included and 7055 (3.0%) of them were pre-pregnancy IFG. During the entire pregnancy, we found 24.1% (HR = 1.241; 95% CI: 1.069, 1.439), 61.8% (HR = 1.618; 95% CI: 1.311, 1.997) and 18.6% (HR = 1.186; 95% CI: 1.004, 1.402) of increases in risk for all PTB, early PTB (20-33 gestational weeks) and late PTB (34-36 gestational weeks) among the pre-pregnancy IFG women, and 15.9% (HR = 1.159; 95% CI: 1.127, 1.192), 33.9% (HR = 1.339; 95% CI: 1.255, 1.430) and 13.2% (HR = 1.132; 95% CI: 1.098, 1.168) of increases in risk for all PTB, early PTB and late PTB among the normoglycemia women, with each 10 μg/m3 increment of PM2.5 exposure, respectively. Furthermore, PM2.5 exposure had the strongest effect on all PTB during trimester 1 (0-12 gestational weeks) among the pre-pregnancy IFG women, compared with the less strong effect during trimester 1 among the normoglycemia women. In conclusion, pre-pregnancy IFG increases the risk of PTB attributed to PM2.5, especially during trimester 1. Moreover, the effects of PM2.5 are greater on early PTB than late PTB for both pre-pregnancy IFG and normoglycemia women.
Collapse
Affiliation(s)
- Zhijiang Liang
- Department of Public Health, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China
| | - Lina Zhao
- Department of Obstetrics, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China
| | - Jialing Qiu
- Department of Public Health, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China
| | - Xinhong Zhu
- Department of Public Health, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China
| | - Min Jiang
- Guangdong Institute of Family Planning Science and Technology, 17th Meidong Road, Yuexiu District, Guangzhou, 510245, China; Guangdong Province Fertility Hospital, 17th Meidong Road, Yuexiu District, Guangzhou, 510245, China; National Health Committee of China (NHCC) Key Laboratory of Male Reproduction and Genetics, 17th Meidong Road, Yuexiu District, Guangzhou, 510245, China
| | - Guocheng Liu
- Department of Obstetrics, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China.
| | - Qingguo Zhao
- Guangdong Institute of Family Planning Science and Technology, 17th Meidong Road, Yuexiu District, Guangzhou, 510245, China; Guangdong Province Fertility Hospital, 17th Meidong Road, Yuexiu District, Guangzhou, 510245, China; National Health Committee of China (NHCC) Key Laboratory of Male Reproduction and Genetics, 17th Meidong Road, Yuexiu District, Guangzhou, 510245, China.
| |
Collapse
|
27
|
Zhou W, Ming X, Yang Y, Hu Y, He Z, Chen H, Li Y, Zhou X, Yin P. Association between Maternal Exposure to Ambient Air Pollution and the Risk of Preterm Birth: A Birth Cohort Study in Chongqing, China, 2015-2020. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19042211. [PMID: 35206398 PMCID: PMC8871940 DOI: 10.3390/ijerph19042211] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 02/07/2022] [Accepted: 02/09/2022] [Indexed: 12/16/2022]
Abstract
Recent study results on the association between maternal exposure to ambient air pollution with preterm birth have been inconsistent. The sensitive window of exposure and influence level of air pollutants varied greatly. We aimed to explore the association between maternal exposure to ambient air pollutants and the risk of preterm birth, and to estimate the sensitive exposure time window. A total of 572,116 mother–newborn pairs, daily concentrations of air pollutants from nearest monitoring stations were used to estimate exposures for each participant during 2015–2020 in Chongqing, China. We applied a generalized additive model and estimated RRs and 95% CIs for preterm birth in each trimester and the entire pregnancy period. In the single-pollutant model, we observed that each 10 μg/m3 increase in PM2.5 had a statistically significant effect on the third trimester and entire pregnancy, with RR = 1.036 (95% CI: 1.021, 1.051) and RR = 1.101 (95% CI: 1.075, 1.128), respectively. Similarly, for each 10 μg/m3 increase in PM10, there were 2.7% (RR = 1.027, 95% CI: 1.016, 1.038) increase for PTB on the third trimester, and 3.8% (RR = 1.038, 95% CI: 1.020, 1.057) increase during the whole pregnancy. We found that for each 10 mg/m3 CO increases, the relative risk of PTB increased on the first trimester (RR = 1.081, 95% CI: 1.007, 1.162), second trimester (RR = 1.116, 95% CI: 1.035, 1.204), third trimester (RR = 1.167, 95% CI: 1.090, 1.250) and whole pregnancy (RR = 1.098, 95% CI: 1.011, 1.192). No statistically significant RR was found for SO2 and NO2 on each trimester of pregnancy. Our study indicates that maternal exposure to high levels of PM2.5 and PM10 during pregnancy may increase the risk for preterm birth, especially for women at the late stage of pregnancy. Statistically increased risks of preterm birth were associated with CO exposure during each trimester and entire pregnancy. Reducing exposure to ambient air pollutants for pregnant women is clearly necessary to improve the health of infants.
Collapse
Affiliation(s)
- Wenzheng Zhou
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China;
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Xin Ming
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Yunping Yang
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Yaqiong Hu
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Ziyi He
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Hongyan Chen
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Yannan Li
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
| | - Xiaojun Zhou
- Chongqing Health Center for Women and Children, Chongqing 401147, China; (X.M.); (Y.Y.); (Y.H.); (Z.H.); (H.C.); (Y.L.)
- Correspondence: (X.Z.); (P.Y.)
| | - Ping Yin
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China;
- Correspondence: (X.Z.); (P.Y.)
| |
Collapse
|
28
|
Gong C, Wang J, Bai Z, Rich DQ, Zhang Y. Maternal exposure to ambient PM 2.5 and term birth weight: A systematic review and meta-analysis of effect estimates. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 807:150744. [PMID: 34619220 DOI: 10.1016/j.scitotenv.2021.150744] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/18/2021] [Accepted: 09/28/2021] [Indexed: 06/13/2023]
Abstract
Effect estimates of prenatal exposure to ambient PM2.5 on change in grams (β) of birth weight among term births (≥37 weeks of gestation; term birth weight, TBW) vary widely across studies. We present the first systematic review and meta-analysis of evidence regarding these associations. Sixty-two studies met the eligibility criteria for this review, and 31 studies were included in the meta-analysis. Random-effects meta-analysis was used to assess the quantitative relationships. Subgroup analyses were performed to gain insight into heterogeneity derived from exposure assessment methods (grouped by land use regression [LUR]-models, aerosol optical depth [AOD]-based models, interpolation/dispersion/Bayesian models, and data from monitoring stations), study regions, and concentrations of PM2.5 exposure. The overall pooled estimate involving 23,925,941 newborns showed that TBW was negatively associated with PM2.5 exposure (per 10 μg/m3 increment) during the entire pregnancy (β = -16.54 g), but with high heterogeneity (I2 = 95.6%). The effect estimate in the LUR-models subgroup (β = -16.77 g) was the closest to the overall estimate and with less heterogeneity (I2 = 18.3%) than in the other subgroups of AOD-based models (β = -41.58 g; I2 = 95.6%), interpolation/dispersion models (β = -10.78 g; I2 = 86.6%), and data from monitoring stations (β = -11.53 g; I2 = 97.3%). Even PM2.5 exposure levels of lower than 10 μg/m3 (the WHO air quality guideline value) had adverse effects on TBW. The LUR-models subgroup was the only subgroup that obtained similar significant of negative associations during the three trimesters as the overall trimester-specific analyses. In conclusion, TBW was negatively associated with maternal PM2.5 exposures during the entire pregnancy and each trimester. More studies based on relatively standardized exposure assessment methods need to be conducted to further understand the precise susceptible exposure time windows and potential mechanisms.
Collapse
Affiliation(s)
- Chen Gong
- Department of Family Planning, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Jianmei Wang
- Department of Family Planning, The Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zhipeng Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China; Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA
| | - David Q Rich
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, New York, USA
| | - Yujuan Zhang
- Department of Family Planning, The Second Hospital of Tianjin Medical University, Tianjin, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China.
| |
Collapse
|
29
|
He C, Liu C, Chen R, Meng X, Wang W, Ji J, Kang L, Liang J, Li X, Liu Y, Yu X, Zhu J, Wang Y, Kan H. Fine particulate matter air pollution and under-5 children mortality in China: A national time-stratified case-crossover study. ENVIRONMENT INTERNATIONAL 2022; 159:107022. [PMID: 34890897 DOI: 10.1016/j.envint.2021.107022] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Under-5 mortality rate is an important indicator in Millennium Development Goals and Sustainable Development Goals. To date, no nationally representative studies have examined the effects of fine particulate matter (PM2.5) air pollution on under-5 mortality. OBJECTIVE To investigate the association of short-term exposure to PM2.5 with under-5 mortality from total and specific causes in China. METHODS We used the national Maternal and Child Health Surveillance System to identify under-5 mortality cases during the study period of 2009 to 2019. We adopted a time-stratified case-crossover study design at the individual level to capture the effect of short-term exposure to daily PM2.5 on under-5 mortality, using conditional logistic regression models. RESULTS A total of 61,464 under-5 mortality cases were included. A 10 μg/m3 increase in concentrations of PM2.5 on lag 0-1 d was significantly associated with a 1.15% (95%confidence interval: 0.65%, 1.65%) increase in under-5 mortality. Mortality from diarrhea, pneumonia, digestive diseases, and preterm birth were significantly associated with exposure to PM2.5. The effect estimates were larger for neonatal mortality (<28 days), female children, and in warm seasons. We observed steeper slopes in lower ranges (<50 μg/m3) of the concentration-response curve between PM2.5 and under-5 mortality, and positive associations remained below the 24-h PM2.5 concentration limit recommended by WHO Air Quality Guidelines and China Air Quality Standards. CONCLUSIONS This nationwide case-crossover study in China demonstrated that acute exposure to PM2.5 may significantly increase the risk of under-5 mortality, with larger effects for neonates, female children, and during warm seasons. Relevant control strategies are needed to remove this roadblock to achieving under-5 mortality targets in developing countries.
Collapse
Affiliation(s)
- Chunhua He
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Xia Meng
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Weidong Wang
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - John Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Leni Kang
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Juan Liang
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Xiaohong Li
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Yuxi Liu
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Xue Yu
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China
| | - Jun Zhu
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, China.
| | - Yanping Wang
- National Office of Maternal and Child Health Surveillance of China, Department of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, China; Key Laboratory of Birth Defects and Related Diseases of Women and Children, Sichuan University, Ministry of Education, Chengdu, China.
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, China; Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China.
| |
Collapse
|
30
|
Zhou G, Wu J, Yang M, Sun P, Gong Y, Chai J, Zhang J, Afrim FK, Dong W, Sun R, Wang Y, Li Q, Zhou D, Yu F, Yan X, Zhang Y, Jiang L, Ba Y. Prenatal exposure to air pollution and the risk of preterm birth in rural population of Henan Province. CHEMOSPHERE 2022; 286:131833. [PMID: 34426128 DOI: 10.1016/j.chemosphere.2021.131833] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/29/2021] [Accepted: 08/05/2021] [Indexed: 06/13/2023]
Abstract
Due to the poor living and healthcare conditions, preterm birth (PTB) in rural population is a pressing health issue. However, PTB studies in rural population are rare. To explore the effects of air pollutants on PTB in rural population, we collected 697,316 medical records during 2014-2016 based on the National Free Preconception Health Examination Project. Logistic regression models were used to estimate the association between air pollutants and PTB and the modifying effects of demographic characteristics. Relative contribution and principal component analysis-generalized linear model (PCA-GLM) analysis were used to explore the most significant air pollutant and gestational period. Our results demonstrated that PTB risk is positively associated with exposure to air pollutants including PM10, PM2.5, SO2, NO2, and CO, while negatively associated with O3 exposure (P < 0.05). In addition, we found that NO2 was the largest contributor to the risk of PTB caused by air pollutants (26.5%). The third trimester of pregnancy was the most sensitive exposure window. PCA-GLM analysis showed that the first component (a combination of PM, SO2, NO2, and CO) increased the risk of PTB. Moreover, we found that rural women who are younger, had higher educated, multi-parity, or smoke appeared to be more sensitive to the association between air pollutants exposure and PTB (P-interaction<0.05). Our findings suggested that increased air pollutants except O3 were associated with elevated PTB risk, especially among vulnerable mothers. Therefore, the effects of air pollutants exposure on PTB should be mitigated by restricting emission sources of NO2 and SO2 in rural population, especially during the third trimester.
Collapse
Affiliation(s)
- Guoyu Zhou
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China; Yellow River Institute for Ecological Protection & Regional Coordinated Development, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Jingjing Wu
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Meng Yang
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Panpan Sun
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Yongxiang Gong
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Jian Chai
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Junxi Zhang
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Francis-Kojo Afrim
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Wei Dong
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Renjie Sun
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Yuhong Wang
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Qinyang Li
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Dezhuan Zhou
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Fangfang Yu
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China
| | - Xi Yan
- Department of Neurology, Henan Provincial People's Hospital; Zhengzhou University People's Hospital; Henan University People's Hospital, Zhengzhou, Henan, 450001, PR China
| | - Yawei Zhang
- Department of Environment Health Science, Yale University School of Public Health, New Haven, CT, USA
| | - Lifang Jiang
- National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Henan Institute of Reproduction Health Science and Technology, Zhengzhou, Henan, 450002, PR China
| | - Yue Ba
- Department of Environmental Health & Environment and Health Innovation Team, School of Public Health, Zhengzhou University, Zhengzhou, Henan, 450001, PR China; Yellow River Institute for Ecological Protection & Regional Coordinated Development, Zhengzhou University, Zhengzhou, Henan, 450001, PR China.
| |
Collapse
|
31
|
Xie G, Sun L, Yang W, Wang R, Shang L, Yang L, Qi C, Xin J, Yue J, Chung MC. Maternal exposure to PM 2.5 was linked to elevated risk of stillbirth. CHEMOSPHERE 2021; 283:131169. [PMID: 34146867 DOI: 10.1016/j.chemosphere.2021.131169] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/02/2021] [Accepted: 06/07/2021] [Indexed: 05/11/2023]
Abstract
BACKGROUND More and more studies began to explore the hazardous health effects of PM2.5, but few reported its impacts on stillbirth. The sparse results were inconsistent and remained to be integrated. Therefore, we aimed to reveal the association between maternal exposure to PM2.5 and stillbirth. METHODS In this meta-analysis, we searched PubMed, Web of Science, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases for related articles written in English and published before October 18, 2020. Study selection was conducted according to the predetermined criteria and data attraction was done with predesigned form. A new instrument was applied to conduct the risk of bias assessment. And random-effect models were used to pool the estimates. RESULTS A total of 3655 records were identified from the databases, but only 7 studies were ultimately included in this study. Positive association was found between the maternal exposure to PM2.5 (per 10 μg/m3 increased) in the entire pregnancy (OR: 1.15, 95% CI: 1.07-1.25) and third trimester (OR: 1.09, 95% CI: 1.01-1.18) and stillbirth, but the association between the maternal exposure to PM2.5 (per 10 μg/m3 increased) in the first trimester (OR: 1.01, 95% CI: 0.90-1.13) and second trimester (OR: 1.06, 95% CI: 0.98-1.14) and stillbirth was not statistically significant. Besides, there was no publication bias. CONCLUSIONS Maternal exposure to PM2.5 in the entire pregnancy and third trimester was associated with elevated risk of stillbirth. However, due to the high heterogeneity, further pathophysiological researches and high quality population studies were still warranted.
Collapse
Affiliation(s)
- Guilan Xie
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi Province, People's Republic of China
| | - Landi Sun
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi Province, People's Republic of China
| | - Wenfang Yang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China.
| | - Ruiqi Wang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi Province, People's Republic of China
| | - Li Shang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi Province, People's Republic of China
| | - Liren Yang
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi Province, People's Republic of China
| | - Cuifang Qi
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China
| | - Juan Xin
- Department of Obstetrics and Gynecology, Maternal & Child Health Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi Province, People's Republic of China
| | - Jie Yue
- Department of Pediatrics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi Province, People's Republic of China
| | - Mei Chun Chung
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Massachusetts, Boston, USA
| |
Collapse
|
32
|
Chu C, Zhu Y, Liu C, Chen R, Yan Y, Ren Y, Li X, Wang J, Ge W, Kan H, Gui Y. Ambient fine particulate matter air pollution and the risk of preterm birth: A multicenter birth cohort study in China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 287:117629. [PMID: 34182393 DOI: 10.1016/j.envpol.2021.117629] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 05/07/2021] [Accepted: 06/19/2021] [Indexed: 06/13/2023]
Abstract
Preterm birth (PTB), defined as live birth before the 37th week of gestation, is believed to have profound impacts on the infant's health in later life. Air pollution has been suggested to be a potential risk factor of PTB, but the evidence was inconsistent. In this multicenter birth cohort study, we aimed to examine the association between fine particulate matter (PM2.5) exposure during pregnancy and PTB in China. A total of 5976 live births were identified between Jan. 2009 and Feb. 2011 from 8 provinces in China. Residential exposures to PM2.5 were assigned based on satellite remote sensing estimates. Cox proportional hazards regressions were employed to explore the correlation for each trimester as well as the entire pregnancy. A total of 443 (7.4%) preterm births were observed. The average PM2.5 during pregnancy was 57.2 ± 8.8 μg/m3. We found exposure to PM2.5 during the whole pregnancy (hazard ratio, HR = 1.262; 95% CI: 1.087-1.465) and in the first trimester (HR = 1.114; 95% CI: 1.007-1.232) was associated with higher risk of PTB. The associations of PM2.5 were stronger for subjects with older maternal or paternal age, lower maternal pre-pregnancy BMI, and lower family income. This study adds supports to the cumulating evidence linking PM2.5 exposure and elevated PTB risk. Measures of air pollution reduction are needed during pregnancy, especially at early stage of pregnancy to prevent adverse birth outcomes.
Collapse
Affiliation(s)
- Chen Chu
- Heart Center, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China
| | - Yixiang Zhu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Cong Liu
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Yingliu Yan
- Ultrasound Department, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Yunyun Ren
- Ultrasound Department, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Xiaotian Li
- Department of Obstetrics, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Jimei Wang
- Neonatology Department, Obstetrics and Gynecology Hospital, Fudan University, Shanghai, China
| | - Wenzhen Ge
- Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Road, Tarrytown, NY, 10605, United States
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Lab of Health Technology Assessment, Fudan University, Shanghai, 200032, China
| | - Yonghao Gui
- Heart Center, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China.
| |
Collapse
|
33
|
Geng G, Xiao Q, Liu S, Liu X, Cheng J, Zheng Y, Xue T, Tong D, Zheng B, Peng Y, Huang X, He K, Zhang Q. Tracking Air Pollution in China: Near Real-Time PM 2.5 Retrievals from Multisource Data Fusion. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:12106-12115. [PMID: 34407614 DOI: 10.1021/acs.est.1c01863] [Citation(s) in RCA: 153] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Air pollution has altered the Earth's radiation balance, disturbed the ecosystem, and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant data set with timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://tapdata.org.cn/) that combines information from multiple data sources, including ground observations, satellite aerosol optical depth (AOD), operational chemical transport model simulations, and other ancillary data such as meteorological fields, land use data, population, and elevation. Daily full-coverage PM2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R2 of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM2.5 data allow us to track the day-to-day variations in PM2.5 concentrations over China in a timely manner. The long-term records of PM2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM2.5 data are publicly available through our website for sharing with the research and policy communities.
Collapse
Affiliation(s)
- Guannan Geng
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Qingyang Xiao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Shigan Liu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Xiaodong Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jing Cheng
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Yixuan Zheng
- Center of Air Quality Simulation and System Analysis, Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Tao Xue
- 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, Beijing 100191, China
| | - Dan Tong
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Bo Zheng
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Yiran Peng
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Xiaomeng Huang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| |
Collapse
|
34
|
Deyssenroth MA, Rosa MJ, Eliot MN, Kelsey KT, Kloog I, Schwartz JD, Wellenius GA, Peng S, Hao K, Marsit CJ, Chen J. Placental gene networks at the interface between maternal PM 2.5 exposure early in gestation and reduced infant birthweight. ENVIRONMENTAL RESEARCH 2021; 199:111342. [PMID: 34015297 PMCID: PMC8195860 DOI: 10.1016/j.envres.2021.111342] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 05/10/2021] [Accepted: 05/12/2021] [Indexed: 05/31/2023]
Abstract
BACKGROUND A growing body of evidence links maternal exposure to particulate matter <2.5 μM in diameter (PM2.5) and deviations in fetal growth. Several studies suggest that the placenta plays a critical role in conveying the effects of maternal PM2.5 exposure to the developing fetus. These include observed associations between air pollutants and candidate placental features, such as mitochondrial DNA content, DNA methylation and telomere length. However, gaps remain in delineating the pathways linking the placenta to air pollution-related health effects, including a comprehensive profiling of placental processes impacted by maternal PM2.5 exposure. In this study, we examined alterations in a placental transcriptome-wide network in relation to maternal PM2.5 exposure prior to and during pregnancy and infant birthweight. METHODS We evaluated PM2.5 exposure and placental RNA-sequencing data among study participants enrolled in the Rhode Island Child Health Study (RICHS). Daily residential PM2.5 levels were estimated using a hybrid model incorporating land-use regression and satellite remote sensing data. Distributed lag models were implemented to assess the impact on infant birthweight due to PM2.5 weekly averages ranging from 12 weeks prior to gestation until birth. Correlations were assessed between PM2.5 levels averaged across the identified window of susceptibility and a placental transcriptome-wide gene coexpression network previously generated using the WGCNA R package. RESULTS We identified a sensitive window spanning 12 weeks prior to and 13 weeks into gestation during which maternal PM2.5 exposure is significantly associated with reduced infant birthweight. Two placental coexpression modules enriched for genes involved in amino acid transport and cellular respiration were correlated with infant birthweight as well as maternal PM2.5 exposure levels averaged across the identified growth restriction window. CONCLUSION Our findings suggest that maternal PM2.5 exposure may alter placental programming of fetal growth, with potential implications for downstream health effects, including susceptibility to cardiometabolic health outcomes and viral infections.
Collapse
Affiliation(s)
- Maya A Deyssenroth
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, 10032, USA.
| | - Maria José Rosa
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Melissa N Eliot
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, 02903, USA
| | - Karl T Kelsey
- Department of Epidemiology, Brown University School of Public Health, Providence, RI, 02903, USA; Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, 02903, USA
| | - Itai Kloog
- Department of Geography and Environmental Development, Faculty of Humanities and Social Sciences, Ben Gurion University, Beersheba, 8410501, Israel
| | - Joel D Schwartz
- Department of Environmental Health, Harvard TH Chan School of Public Health, Boston, MA, 02215, USA; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, 02215, USA
| | - Gregory A Wellenius
- Boston University School of Public Health, Boston University, Boston, MA, 02215, USA
| | - Shouneng Peng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Carmen J Marsit
- Environmental Health, Rollins School of Public Health of Emory University, Atlanta, GA, 30322, USA
| | - Jia Chen
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| |
Collapse
|
35
|
Holloway T, Miller D, Anenberg S, Diao M, Duncan B, Fiore AM, Henze DK, Hess J, Kinney PL, Liu Y, Neu JL, O'Neill SM, Odman MT, Pierce RB, Russell AG, Tong D, West JJ, Zondlo MA. Satellite Monitoring for Air Quality and Health. Annu Rev Biomed Data Sci 2021; 4:417-447. [PMID: 34465183 DOI: 10.1146/annurev-biodatasci-110920-093120] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM2.5) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.
Collapse
Affiliation(s)
- Tracey Holloway
- Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, Wisconsin 53726, USA; .,Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53726, USA
| | - Daegan Miller
- Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, Wisconsin 53726, USA;
| | - Susan Anenberg
- Department of Environmental and Occupational Health, George Washington University, Washington, DC 20052, USA
| | - Minghui Diao
- Department of Meteorology and Climate Science, San José State University, San Jose, California 95192, USA
| | - Bryan Duncan
- Atmospheric Chemistry and Dynamics Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
| | - Arlene M Fiore
- Lamont-Doherty Earth Observatory and Department of Earth and Environmental Sciences, Columbia University, Palisades, New York 10964, USA
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA
| | - Jeremy Hess
- Department of Environmental and Occupational Health Sciences, Department of Global Health, and Department of Emergency Medicine, University of Washington, Seattle, Washington 98105, USA
| | - Patrick L Kinney
- School of Public Health, Boston University, Boston, Massachusetts 02215, USA
| | - Yang Liu
- Gangarosa Department of Environment Health, Rollins School of Public Health, Emory University, Atlanta, Georgia 30322, USA
| | - Jessica L Neu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, USA
| | - Susan M O'Neill
- Pacific Northwest Research Station, USDA Forest Service, Seattle, Washington 98103, USA
| | - M Talat Odman
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - R Bradley Pierce
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53726, USA.,Space Science and Engineering Center, University of Wisconsin-Madison, Madison, Wisconsin 53726, USA
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Daniel Tong
- Atmospheric, Oceanic and Earth Sciences Department, George Mason University, Fairfax, Virginia 22030, USA
| | - J Jason West
- Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Mark A Zondlo
- Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey 08544, USA
| |
Collapse
|
36
|
Mueller W, Tantrakarnapa K, Johnston HJ, Loh M, Steinle S, Vardoulakis S, Cherrie JW. Exposure to ambient particulate matter and biomass burning during pregnancy: associations with birth weight in Thailand. JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2021; 31:672-682. [PMID: 33603098 PMCID: PMC8263346 DOI: 10.1038/s41370-021-00295-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 12/12/2020] [Accepted: 01/18/2021] [Indexed: 05/25/2023]
Abstract
BACKGROUND There is a growing evidence that exposure to ambient particulate air pollution during pregnancy is associated with adverse birth outcomes, including reduced birth weight (BW). The objective of this study was to quantify associations between BW and exposure to particulate matter (PM) and biomass burning during pregnancy in Thailand. METHODS We collected hourly ambient air pollutant data from ground-based monitors (PM with diameter of <10 µm [PM10], Ozone [O3], and nitrogen dioxide [NO2]), biomass burning from satellite remote sensing data, and individual birth weight data during 2015-2018. We performed a semi-ecological analysis to evaluate the association between mean trimester exposure to air pollutants and biomass burning with BW and low-birth weight (LBW) (<2500 g), adjusting for gestation age, sex, previous pregnancies, mother's age, heat index, season, year, gaseous pollutant concentrations, and province. We examined potential effect modification of PM10 and biomass burning exposures by sex. RESULTS There were 83,931 eligible births with a mean pregnancy PM10 exposure of 39.7 µg/m3 (standard deviation [SD] = 7.7). The entire pregnancy exposure was associated with reduced BW both for PM10 (-6.81 g per 10 µg/m3 increase in PM10 [95% CI = -12.52 to -1.10]) and biomass burning (-6.34 g per 1 SD increase in fires/km2 [95% CI = -11.35 to -1.34]) only after adjustment for NO2. In contrast with these findings, a reduced odds ratio (OR) of LBW was associated with PM10 exposure only in trimesters one and two, with no relationship across the entire pregnancy period. Associations with biomass burning were limited to increased ORs of LBW with exposure in trimester three, but only for male births. CONCLUSION Based on our results, we encourage further investigation of air pollution, biomass burning and BW in Thailand and other low-income and middle-income countries.
Collapse
Affiliation(s)
| | - Kraichat Tantrakarnapa
- Department of Social and Environmental Medicine, Faculty of Tropical Medicine, Mahidol University, Bangkok, Thailand
| | - Helinor Jane Johnston
- School of Engineering and Physical Sciences, Institute of Biological Chemistry, Biophysics and Bioengineering, Heriot Watt University, Edinburgh, UK
| | - Miranda Loh
- Institute of Occupational Medicine, Edinburgh, UK
| | | | - Sotiris Vardoulakis
- Institute of Occupational Medicine, Edinburgh, UK
- National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, Australia
| | - John W Cherrie
- Institute of Occupational Medicine, Edinburgh, UK.
- School of Engineering and Physical Sciences, Institute of Biological Chemistry, Biophysics and Bioengineering, Heriot Watt University, Edinburgh, UK.
| |
Collapse
|
37
|
Liang Z, Yang Y, Yi J, Qian Z, Zhang Z, McMillin SE, Liu E, Lin H, Liu G. Maternal PM 2.5 exposure associated with stillbirth: A large birth cohort study in seven Chinese cities. Int J Hyg Environ Health 2021; 236:113795. [PMID: 34186502 DOI: 10.1016/j.ijheh.2021.113795] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 05/14/2021] [Accepted: 06/14/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Maternal exposure to fine particulate matter (PM2.5) has been associated with a few adverse birth outcomes. However, its effect on stillbirth remains unknown in China, especially the susceptible windows and potential modifiers. OBJECTIVE This study aimed to evaluate the associations between maternal PM2.5 exposure and stillbirth in seven Chinese cities. METHODS We used birth cohort data of 1,273,924 mother-and-birth pairs in seven cities in southern China between 2014 and 2017 to examine these associations. Pregnant women were recruited in the cohort at their first visit to a doctor for pregnancy, and stillbirths were recorded at the time of birth. Air pollution exposures were assessed through linking daily air pollutant concentrations from nearby monitoring stations to the mother's residential community. Cox regression models were applied to determine the associations between PM2.5 and stillbirth for different gestational periods. RESULTS Among the participants, 3150 (2.47‰) were identified as stillbirth cases. The hazard ratio (HR) of stillbirths was 1.52 (95% CI: 1.42, 1.62) for each 10 μg/m3 increase in PM2.5 during the entire pregnancy after controlling for some important covariates. Relatively stronger associations were observed during the second trimester [adjusted HR = 1.67 (95% CI: 1.57, 1.77)] than trimesters 1 [HR = 1.44 (95% CI: 1.37, 1.52)] and trimester 3 [HR = 1.23 (95% CI: 1.16, 1.30)]. Stratified analyses also showed a stronger association among pregnant women without previous pregnancy and previous delivery experiences. CONCLUSION The study indicates that maternal exposure to PM2.5, especially during the midpoint period of pregnancy, might increase the risk of stillbirths. Maternal previous pregnancy and delivery may modify this association.
Collapse
Affiliation(s)
- Zhijiang Liang
- Department of Public Health, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China
| | - Yin Yang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Jing Yi
- Department of Obstetrics, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China
| | - Zhengmin Qian
- Department of Epidemiology and Biostatistics, College for Public Health & Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA
| | - Zilong Zhang
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Stephen Edward McMillin
- School of Social Work, College for Public Health & Social Justice, Saint Louis University, St. Louis, MO, 63103, USA
| | - Echu Liu
- Department of Health Management and Policy, College for Public Health and Social Justice, Saint Louis University, Saint Louis, MO, 63104, USA
| | - Hualiang Lin
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
| | - Guocheng Liu
- Department of Obstetrics, Guangdong Women and Children Hospital, 521 Xingnan Road, Panyu District, Guangzhou, 511442, China.
| |
Collapse
|
38
|
Wei H, Baktash MB, Zhang R, Wang X, Zhang M, Jiang S, Xia Y, Zhao X, Hu W. Associations of maternal exposure to fine particulate matter constituents during pregnancy with Apgar score and duration of labor: A retrospective study in Guangzhou, China, 2012-2017. CHEMOSPHERE 2021; 273:128442. [PMID: 33082001 DOI: 10.1016/j.chemosphere.2020.128442] [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: 07/19/2020] [Revised: 09/16/2020] [Accepted: 09/24/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND Limited evidence is available for demonstrating effects of prenatal PM2.5 and its components exposure on Apgar score and duration of labor. OBJECTIVE We sought to investigate the associations between PM2.5 constituents, Apgar score and duration of labor, and evaluated the potential mediating role of duration of labor. METHODS This study included 5396 participants. The V4·CH.02 was applied to assessing exposure to PM2.5 constituents. The associations between PM2.5 constituents Apgar score and duration of labor were examined by multivariate linear regression. Mediation analysis was conducted to estimate the potential mediation effect of duration of labor. RESULTS Trimester-specific exposure to soil dust was significantly associated with 1-min Apgar score (1st trimester: OR: 1.03, 95% CI:0.97, 1.10; 2nd trimester: OR: 1.07, 95% CI: 1.01, 1.14; 3rd trimester: OR: 1.07, 95% CI: 1.01, 1.13), duration of first stage of labor (1st trimester: β: 0.32, 95% CI: 0.07, 0.58; 2nd trimester: β: 0.27, 95% CI: 0.04, 0.51; 3rd trimester: β: 0.37, 95% CI: 0.13, 0.61) and duration of second stage of labor (1st trimester: β: 0.04, 95% CI: -0.00, 0.09; 2nd trimester: β: 0.05, 95% CI: 0.01, 0.10; 3rd trimester: β: 0.05, 95% CI: 0.00, 0.09). The duration of labor mediated the relationship between soil dust and 1-min Apgar score. CONCLUSION This study demonstrated that prenatal exposure to soil dust was significantly associated with the risk of abnormal 1-min Apgar score and extended stage of labor.
Collapse
Affiliation(s)
- Hongcheng Wei
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Mohammad Basir Baktash
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Rui Zhang
- Department of Obstetrics and Gynecology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
| | - Xu Wang
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Mingzhi Zhang
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Suzhi Jiang
- Department of Obstetrics and Gynecology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
| | - Yankai Xia
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xiaomiao Zhao
- Department of Obstetrics and Gynecology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China.
| | - Weiyue Hu
- State Key Laboratory of Reproductive Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
| |
Collapse
|
39
|
Thomas N, Ebelt ST, Newman AJ, Scovronick N, D’Souza RR, Moss SE, Warren JL, Strickland MJ, Darrow LA, Chang HH. Time-series analysis of daily ambient temperature and emergency department visits in five US cities with a comparison of exposure metrics derived from 1-km meteorology products. Environ Health 2021; 20:55. [PMID: 33962633 PMCID: PMC8106140 DOI: 10.1186/s12940-021-00735-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 04/22/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND Ambient temperature observations from single monitoring stations (usually located at the major international airport serving a city) are routinely used to estimate heat exposures in epidemiologic studies. This method of exposure assessment does not account for potential spatial variability in ambient temperature. In environmental health research, there is increasing interest in utilizing spatially-resolved exposure estimates to minimize exposure measurement error. METHODS We conducted time-series analyses to investigate short-term associations between daily temperature metrics and emergency department (ED) visits for well-established heat-related morbidities in five US cities that represent different climatic regions: Atlanta, Los Angeles, Phoenix, Salt Lake City, and San Francisco. In addition to airport monitoring stations, we derived several exposure estimates for each city using a national meteorology data product (Daymet) available at 1 km spatial resolution. RESULTS Across cities, we found positive associations between same-day temperature (maximum or minimum) and ED visits for heat-sensitive outcomes, including acute renal injury and fluid and electrolyte imbalance. We also found that exposure assessment methods accounting for spatial variability in temperature and at-risk population size often resulted in stronger relative risk estimates compared to the use of observations at airports. This pattern was most apparent when examining daily minimum temperature and in cities where the major airport is located further away from the urban center. CONCLUSION Epidemiologic studies based on single monitoring stations may underestimate the effect of temperature on morbidity when the station is less representative of the exposure of the at-risk population.
Collapse
Affiliation(s)
- Nikita Thomas
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA
| | - Stefanie T. Ebelt
- Gangarosa Department of Environmental Health, Emory University, Atlanta, USA
| | - Andrew J. Newman
- Research Applications Laboratory, National Center for Atmospheric Research, Boulder, USA
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Emory University, Atlanta, USA
| | - Rohan R. D’Souza
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA
| | - Shannon E. Moss
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA
| | | | | | - Lyndsey A. Darrow
- School of Community Health Sciences, University of Nevada Reno, Reno, USA
| | - Howard H. Chang
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, USA
- Gangarosa Department of Environmental Health, Emory University, Atlanta, USA
| |
Collapse
|
40
|
Uwak I, Olson N, Fuentes A, Moriarty M, Pulczinski J, Lam J, Xu X, Taylor BD, Taiwo S, Koehler K, Foster M, Chiu WA, Johnson NM. Application of the navigation guide systematic review methodology to evaluate prenatal exposure to particulate matter air pollution and infant birth weight. ENVIRONMENT INTERNATIONAL 2021; 148:106378. [PMID: 33508708 PMCID: PMC7879710 DOI: 10.1016/j.envint.2021.106378] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/11/2020] [Accepted: 01/04/2021] [Indexed: 05/04/2023]
Abstract
Low birth weight is an important risk factor for many co-morbidities both in early life as well as in adulthood. Numerous studies report associations between prenatal exposure to particulate matter (PM) air pollution and low birth weight. Previous systematic reviews and meta-analyses report varying effect sizes and significant heterogeneity between studies, but did not systematically evaluate the quality of individual studies or the overall body of evidence. We conducted a new systematic review to determine how prenatal exposure to PM2.5, PM10, and coarse PM (PM2.5-10) by trimester and across pregnancy affects infant birth weight. Using the Navigation Guide methodology, we developed and applied a systematic review protocol [CRD42017058805] that included a comprehensive search of the epidemiological literature, risk of bias (ROB) determination, meta-analysis, and evidence evaluation, all using pre-established criteria. In total, 53 studies met our inclusion criteria, which included evaluation of birth weight as a continuous variable. For PM2.5 and PM10, we restricted meta-analyses to studies determined overall as "low" or "probably low" ROB; none of the studies evaluating coarse PM were rated as "low" or "probably low" risk of bias, so all studies were used. For PM2.5, we observed that for every 10 µg/m3 increase in exposure to PM2.5 in the 2nd or 3rd trimester, respectively, there was an associated 5.69 g decrease (I2: 68%, 95% CI: -10.58, -0.79) or 10.67 g decrease in birth weight (I2: 84%, 95% CI: -20.91, -0.43). Over the entire pregnancy, for every 10 µg/m3 increase in PM2.5 exposure, there was an associated 27.55 g decrease in birth weight (I2: 94%, 95% CI: -48.45, -6.65). However, the quality of evidence for PM2.5 was rated as "low" due to imprecision and/or unexplained heterogeneity among different studies. For PM10, we observed that for every 10 µg/m3 increase in exposure in the 3rd trimester or the entire pregnancy, there was a 6.57 g decrease (I2: 0%, 95% CI: -10.66, -2.48) or 8.65 g decrease in birth weight (I2: 84%, 95% CI: -16.83, -0.48), respectively. The quality of evidence for PM10 was rated as "moderate," as heterogeneity was either absent or could be explained. The quality of evidence for coarse PM was rated as very low/low (for risk of bias and imprecision). Overall, while evidence for PM2.5 and course PM was inadequate primarily due to heterogeneity and risk of bias, respectively, our results support the existence of an inverse association between prenatal PM10 exposure and low birth weight.
Collapse
Affiliation(s)
- Inyang Uwak
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA
| | - Natalie Olson
- Department of Veterinary Integrative Biosciences. Texas A&M University, College Station, TX, USA
| | - Angelica Fuentes
- Department of Veterinary Integrative Biosciences. Texas A&M University, College Station, TX, USA
| | - Megan Moriarty
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA
| | - Jairus Pulczinski
- Department of Environmental Health and Engineering. Johns Hopkins University, Baltimore, MD, USA
| | - Juleen Lam
- Department of Health Sciences, California State University, East Bay, Hayward, CA USA
| | - Xiaohui Xu
- Department of Epidemiology and Biostatistics. Texas A&M University, College Station, TX, USA
| | - Brandie D Taylor
- Department of Epidemiology and Biostatistics. Temple University, Philadelphia, PA, USA
| | - Samuel Taiwo
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA
| | - Kirsten Koehler
- Department of Environmental Health and Engineering. Johns Hopkins University, Baltimore, MD, USA
| | - Margaret Foster
- Medical Sciences Library. Texas A&M University, College Station, TX, USA
| | - Weihsueh A Chiu
- Department of Veterinary Integrative Biosciences. Texas A&M University, College Station, TX, USA
| | - Natalie M Johnson
- Department of Environmental and Occupational Health. Texas A&M University, College Station, TX, USA.
| |
Collapse
|
41
|
Jing S, Chen C, Gan Y, Vogel J, Zhang J. Incidence and trend of preterm birth in China, 1990-2016: a systematic review and meta-analysis. BMJ Open 2020; 10:e039303. [PMID: 33310797 PMCID: PMC7735132 DOI: 10.1136/bmjopen-2020-039303] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 10/19/2020] [Accepted: 11/24/2020] [Indexed: 01/02/2023] Open
Abstract
OBJECTIVES To update the WHO estimate of preterm birth rate in China in 1990-2016 and to further explore variations by geographic regions and years of occurrence. DESIGN Systematic review and meta-analysis. DATA SOURCES Pubmed, Embase, Cochrane Library and Sinomed databases were searched from 1990 to 2018. ELIGIBILITY CRITERIA Studies were included if they provided preterm birth data with at least 500 total births. Reviews, case-control studies, intervention studies and studies with insufficient information or published before 1990 were excluded. We estimated pooled incidence of preterm birth by a random effects model, and preterm birth rate in different year, region and by livebirths or all births in subgroup analyses. RESULTS Our search identified 3945 records. After the removal of duplicates and screening of titles and abstracts, we reviewed 254 studies in full text and excluded 182, leaving 72 new studies. They were combined with the 82 studies included in the WHO report (154 studies, 187 data sets in total for the meta-analysis), including 24 039 084 births from 1990 to 2016. The pooled incidence of preterm birth in China was 6.09% (95% CI 5.86% to 6.31%) but has been steadily increasing from 5.36% (95% CI 4.89% to 5.84%) in 1990-1994 to 7.04% (95% CI 6.09% to 7.99%) in 2015-2016. The annual rate of increase was about 1.05% (95% CI 0.85% to 1.21%). Northwest China appeared to have the highest preterm birth rate (7.3%, 95% CI 4.92% to 9.68% from 1990 to 2016). CONCLUSIONS The incidence of preterm birth in China has been rising gradually in the past three decades. It was 7% in 2016. Preterm birth rate varied by region with the West having the highest occurrence.
Collapse
Affiliation(s)
- Shiwen Jing
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chang Chen
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuexin Gan
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Joshua Vogel
- Maternal, Child and Adolescent Health Program, Burnet Institute, Melbourne, Victoria, Australia
| | - Jun Zhang
- School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
42
|
Cai J, Zhao Y, Kan J, Chen R, Martin R, van Donkelaar A, Ao J, Zhang J, Kan H, Hua J. Prenatal Exposure to Specific PM 2.5 Chemical Constituents and Preterm Birth in China: A Nationwide Cohort Study. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:14494-14501. [PMID: 33146526 DOI: 10.1021/acs.est.0c02373] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Exposure to fine particulate matter (PM2.5) during pregnancy has been associated with preterm birth (PTB). However, the existing evidence is inconsistent, and the roles of specific PM2.5 chemical constituents remain unclear. Based on the China Labor and Delivery Survey, we included birth data from 89 hospitals in 25 provinces in mainland China, and conducted a national multicenter cohort study to examine the associations of PM2.5 and its chemical constituents with PTB risk in China. We applied satellite-based models to predict prenatal PM2.5 mass and six main component exposure. Multilevel logistic regression analysis was used to examine the associations, controlling for sociodemographic characteristics, seasonality, and spatial variation. We observe an increased PTB risk with an increase in PM2.5 mass and the most significant association is found during the third trimester when the adjusted odds ratio (OR) per interquartile range increases in PM2.5 total mass is 1.12 (95% confidence Interval, CI: 1.05-1.20). Infants conceived by assisted reproductive technology (ART) show greater PTB risk associated with PM2.5 exposure (OR = 1.33, 95% CI: 1.05-1.69) than those conceived naturally (OR = 1.11, 95% CI: 1.03-1.19). We also find black carbon, sulfate, ammonium and nitrate, often linked to fossil combustion, have comparable or larger estimates of the effect (OR = 1.07-1.14) than PM2.5. Our findings provide evidence that components mainly from fossil fuel combustion may have a perceptible influence on increased PTB risk associated with PM2.5 exposure in China. Additionally, compared to natural conception, conception through ART may be more susceptible to PM2.5 exposure.
Collapse
Affiliation(s)
- Jing Cai
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
- Shanghai Key Laboratory of Meteorology and Health, Shanghai Typhoon Institute/CMA, Shanghai 200030, China
| | - Yan Zhao
- Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai 201204, China
| | - Julia Kan
- University of Bristol Medical School, Bristol BS8 1TH, U.K
| | - Renjie Chen
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
| | - Randall Martin
- Department of Physics and Atmospheric Science, Dalhousie University, 6300 Coburg Road, Halifax, Nova Scotia B3H 3J5, Canada
- Harvard-Smithsonian Center for Astrophysics, Cambridge, Massachusetts 02138, United States
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science, Dalhousie University, 6300 Coburg Road, Halifax, Nova Scotia B3H 3J5, Canada
| | - Junjie Ao
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200096, China
| | - Jun Zhang
- Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200096, China
| | - Haidong Kan
- School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai 200032, China
- National Center for Children's Health, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Jing Hua
- Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai 201204, China
| |
Collapse
|
43
|
Li C, Yang M, Zhu Z, Sun S, Zhang Q, Cao J, Ding R. Maternal exposure to air pollution and the risk of low birth weight: A meta-analysis of cohort studies. ENVIRONMENTAL RESEARCH 2020; 190:109970. [PMID: 32763280 DOI: 10.1016/j.envres.2020.109970] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 07/07/2020] [Accepted: 07/16/2020] [Indexed: 05/14/2023]
Abstract
Previous studies have evaluated the relationship between prenatal air pollution exposure and low birth weight, but the results are inconsistent. The purpose of this meta-analysis is to quantitatively analyze the relationship between maternal air pollutant exposure and low birth weight (LBW). PubMed and Web of Science databases were searched to obtain the studies on the relationship between the prenatal exposure of air pollutants and LBW that published as of June 2020. The pooled effects of air pollutant exposure and LBW were calculated using random-effect model (for studies with significant heterogeneity) or fixed-effect model (for studies without significant heterogeneity). Totally, 54 studies were included in this meta-analysis. The pooled effect of PM2.5, PM10, NO2, CO, SO2, and O3 exposure on LBW were 1.081 (95% CI: 1.043, 1.120), 1.053 (95% CI: 1.030, 1.076), 1.030 (95% CI: 1.008, 1.053), 1.007 (95% CI: 1.001, 1.014), 1.125 (95% CI: 1.017, 1.244), and 1.045 (95% CI: 1.005, 1.086), respectively. NO2 (per 10 ppb increase) and CO (per 100 ppb increase) exposure in the first trimester were positively correlated with LBW, of which the pooled effect was 1.022 (95% CI: 1.009, 1. 035) and 1.008 (95% CI: 1.004, 1.012), respectively. PM2.5 (per 10 μg/m3 increase) exposure in the third trimester significantly affected the LBW, of which the pooled effect was 1.053 (95% CI: 1.010, 1.097). In addition, PM10 (per 10 μg/m3 increase) exposure in the second trimester also significantly affected the LBW, with the pooled effect of 1.011 (95% CI: 1.005, 1.017). Prenatal exposure of the major air pollutants during the entire pregnancy could increase the risk of LBW, while the susceptible window of the pollutants varied.
Collapse
Affiliation(s)
- Changlian Li
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| | - Mei Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| | - Zijian Zhu
- Second School of Clinical Medicine, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| | - Shu Sun
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| | - Qi Zhang
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| | - Jiyu Cao
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China; Department of Teaching Center for Preventive Medicine, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| | - Rui Ding
- Department of Occupational Health and Environmental Health, School of Public Health, Anhui Medical University, 81 Meishan Road, Hefei, Anhui, 230032, China.
| |
Collapse
|
44
|
Zhang J, Zeng X, Du X, Pan K, Song L, Song W, Xie Y, Zhao J. Parental PM2.5 Exposure-Promoted Development of Metabolic Syndrome in Offspring Is Associated With the Changes of Immune Microenvironment. Toxicol Sci 2020; 170:415-426. [PMID: 31086988 DOI: 10.1093/toxsci/kfz109] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Parental exposure to ambient fine particulate matter (PM2.5) has been associated with some of adverse health outcomes in offspring. The association between parental PM2.5 exposure and the development of metabolic syndrome (MetS) in offspring, and the effects of parental PM2.5 exposure on the susceptibility of offspring mice to PM2.5, has not been evaluated. The C57BL/6 parental mice (male and female mice) were exposed to filtered air (FA) or concentrated PM2.5 (PM) using Shanghai-METAS for a total of 16 weeks. At week 12 during the exposure, we allowed the parental male and female mice to breed offspring mice. The male offspring mice were divided into 4 groups and exposed to PM and FA again. The results showed that whether the parental mice were exposed to PM2.5 or not, the offspring mice exposure to PM2.5 appeared the elevation of blood pressure, insulin resistance, impairment of glucose tolerance, and dyslipidemia when compared to the offspring mice exposure to FA. More importantly, no matter what the offspring mice were exposed to, parental PM exposure overwhelmingly impacted the fasting blood insulin, homeostasis model assessment-insulin resistance, serous low-density lipoprotein cholesterol, and total cholesterol, splenic T helper cell 17 (Th17) and Treg cells, serous interleukin (IL)-17A, IL-6, and IL-10 in offspring mice. The results suggested that the parental exposure to air pollution might induce the development of MetS in offspring and might enhance the susceptibility of offspring to environmental hazards. The effects of parental PM exposure on offspring might be related to the changes of immune microenvironment.
Collapse
Affiliation(s)
- Jia Zhang
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Xuejiao Zeng
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Xihao Du
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Kun Pan
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Liying Song
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Weimin Song
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yuquan Xie
- Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200092, China
| | - Jinzhuo Zhao
- Department of Environmental Health, School of Public Health and the Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai 200032, China.,Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China
| |
Collapse
|
45
|
Earth Observation Data Supporting Non-Communicable Disease Research: A Review. REMOTE SENSING 2020. [DOI: 10.3390/rs12162541] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
A disease is non-communicable when it is not transferred from one person to another. Typical examples include all types of cancer, diabetes, stroke, or allergies, as well as mental diseases. Non-communicable diseases have at least two things in common—environmental impact and chronicity. These diseases are often associated with reduced quality of life, a higher rate of premature deaths, and negative impacts on a countries’ economy due to healthcare costs and missing work force. Additionally, they affect the individual’s immune system, which increases susceptibility toward communicable diseases, such as the flu or other viral and bacterial infections. Thus, mitigating the effects of non-communicable diseases is one of the most pressing issues of modern medicine, healthcare, and governments in general. Apart from the predisposition toward such diseases (the genome), their occurrence is associated with environmental parameters that people are exposed to (the exposome). Exposure to stressors such as bad air or water quality, noise, extreme heat, or an overall unnatural surrounding all impact the susceptibility to non-communicable diseases. In the identification of such environmental parameters, geoinformation products derived from Earth Observation data acquired by satellites play an increasingly important role. In this paper, we present a review on the joint use of Earth Observation data and public health data for research on non-communicable diseases. We analyzed 146 articles from peer-reviewed journals (Impact Factor ≥ 2) from all over the world that included Earth Observation data and public health data for their assessments. Our results show that this field of synergistic geohealth analyses is still relatively young, with most studies published within the last five years and within national boundaries. While the contribution of Earth Observation, and especially remote sensing-derived geoinformation products on land surface dynamics is on the rise, there is still a huge potential for transdisciplinary integration into studies. We see the necessity for future research and advocate for the increased incorporation of thematically profound remote sensing products with high spatial and temporal resolution into the mapping of exposomes and thus the vulnerability and resilience assessment of a population regarding non-communicable diseases.
Collapse
|
46
|
Ren F, Ji C, Huang Y, Aniagu S, Jiang Y, Chen T. AHR-mediated ROS production contributes to the cardiac developmental toxicity of PM2.5 in zebrafish embryos. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 719:135097. [PMID: 31837856 DOI: 10.1016/j.scitotenv.2019.135097] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 10/03/2019] [Accepted: 10/19/2019] [Indexed: 06/10/2023]
Abstract
Recent studies have shown an association between maternal exposure to ambient fine particle matter (PM2.5) and congenital heart defects in the offspring, but the underlying molecular mechanisms are yet to be elucidated. Previously, we demonstrated that extractable organic matter (EOM) from PM2.5 induced heart defects in zebrafish embryos by activating the aromatic hydrocarbon receptor (AHR). Hence, we hypothesized that AHR mediates excessive reactive oxygen species (ROS) production, leading to the cardiac developmental toxicity of PM2.5. To test our hypothesis, we examined AHR activity and ROS levels in the heart of zebrafish embryos under a fluorescence microscope. mRNA expression levels were then quantified using qPCR whereas DNA damage and apoptosis were detected by immunofluorescence. Our results showed that the AHR inhibitor, CH223191 (CH) as well as the ROS scavenger, N-Acetyl-L-cysteine (NAC), significantly mitigated the PM2.5-induced cardiac malformations in zebrafish embryos. Furthermore, both CH and NAC diminished the EOM-elevated ROS generation, DNA damage and apoptosis in the test system. Incidentally, both CH and NAC attenuated the EOM-induced changes in the mRNA expression of genes involved in cardiac development (nkx2.5, sox9b), oxidative stress (nrf2a, nrf2b, gstp1, gstp2, sod2, ho1, cat) and apoptosis (p53, bax). We further confirmed that AHR activity is a necessary condition for EOM-induced ROS generation, DNA damage and apoptosis, through AHR knockdown. However, the ROS scavenger NAC did not counteract the EOM-induced AHR activity. In conclusion, our findings suggest that AHR mediates EOM-induced oxidative stress, resulting in DNA damage and apoptosis, thereby contributing to the cardiac developmental toxicity of PM2.5.
Collapse
Affiliation(s)
- Fei Ren
- Medical College of Soochow University, Suzhou, China; Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Cheng Ji
- Medical College of Soochow University, Suzhou, China
| | - Yujie Huang
- Medical College of Soochow University, Suzhou, China; Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China
| | - Stanley Aniagu
- Toxicology, Risk Assessment and Research Division, Texas Commission on Environmental Quality, 12015 Park 35 Cir, Austin, TX, USA
| | - Yan Jiang
- Medical College of Soochow University, Suzhou, China.
| | - Tao Chen
- Medical College of Soochow University, Suzhou, China; Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China.
| |
Collapse
|
47
|
Zhang X, Fan C, Ren Z, Feng H, Zuo S, Hao J, Liao J, Zou Y, Ma L. Maternal PM 2.5 exposure triggers preterm birth: a cross-sectional study in Wuhan, China. Glob Health Res Policy 2020; 5:17. [PMID: 32377568 PMCID: PMC7193342 DOI: 10.1186/s41256-020-00144-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 03/24/2020] [Indexed: 11/10/2022] Open
Abstract
Background Most of the studies regarding air pollution and preterm birth (PTB) in highly polluted areas have estimated the exposure level based on fixed-site monitoring. However, exposure assessment methods relying on monitors have the potential to cause exposure misclassification due to a lack of spatial variation. In this study, we utilized a land use regression (LUR) model to assess individual exposure, and explored the association between PM2.5 exposure during each time window and the risk of preterm birth in Wuhan city, China. Methods Information on 2101 singleton births, which were ≥ 20 weeks of gestation and born between November 1, 2013 and May 31, 2014; between January 1, 2015 and August 31, 2015, was obtained from the Obstetrics Department in one 3A hospital in Wuhan. Air quality index (AQI) data were accessed from the Wuhan Environmental Protection Bureau website. Individual exposure during pregnancy was assessed by LUR models and Kriging interpolation. Logistic regression analyses were conducted to determine the association between women exposure to PM2.5 and the risk of different subtypes of PTB. Results During the study period, the average individual exposure concentration of PM2.5 during the entire pregnancy was 84.54 μg/m3. A 10 μg/m3 increase of PM2.5 exposure in the first trimester (OR: 1.169; 95% CI: 1.077, 1.262), the second trimester (OR: 1.056; 95% CI: 1.015, 1.097), the third trimester (OR: 1.052; 95% CI: 1.002, 1.101), and the entire pregnancy (OR: 1.263; 95% CI: 1.158, 1.368) was significantly associated with an increased risk of PTB. For the PTB subgroup, the hazard of PM2.5 exposure during pregnancy was stronger for very preterm births (VPTB) than moderate preterm births (MPTB). The first trimester was the most susceptible exposure window. Moreover, women who had less than 9 years of education or who conceived during the cold season tended to be more susceptible to the PM2.5 exposure during pregnancy. Conclusions Maternal exposure to PM2.5 increased the risk of PTB, and this risk was stronger for VPTB than for MPTB, especially during the first trimester.
Collapse
Affiliation(s)
- Xiaotong Zhang
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China
| | - Cuifang Fan
- 2Department of Obstetrics, Renmin Hospital of Wuhan University, Wuhan, 430060 China
| | - Zhan Ren
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China
| | - Huan Feng
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China
| | - Shanshan Zuo
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China
| | - Jiayuan Hao
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China
| | - Jingling Liao
- 3Department of Public Health, Wuhan University of Science and Technology School of Medicine, Wuhan, 430081 China
| | - Yuliang Zou
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China.,4Global Health Institute, Wuhan University, Wuhan, 430071 China
| | - Lu Ma
- 1Department of Epidemiology and Health Statistics, School of Health Sciences, Wuhan University, Wuhan, 430071 China.,4Global Health Institute, Wuhan University, Wuhan, 430071 China
| |
Collapse
|
48
|
Riaz H, Syed BM, Laghari Z, Pirzada S. Analysis of inflammatory markers in apparently healthy automobile vehicle drivers in response to exposure to traffic pollution fumes. Pak J Med Sci 2020; 36:657-662. [PMID: 32494251 PMCID: PMC7260889 DOI: 10.12669/pjms.36.4.2025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
Objective: This study aimed to evaluate pattern of markers of inflammation in apparently healthy drivers who exposed to traffic fumes. Methods: This cross-sectional study was conducted from June 2016 to January 2017 at Liaquat University of Medical & Health Sciences (LUMHS), Jamshoro. It looked into the effects of traffic pollutants on markers of inflammation including CRP, Leukocytes count, IL-6, TNF-α, TNF-β of healthy human volunteers. Eighty-seven, apparently healthy, non-smoking automobile vehicle drivers, having daily contact of traffic exhaust for at least six hours, aged between 18-40 years recruited for this study. Levels of traffic-generated pollutants P.M2.5, P.M10, NOx were recorded in different areas of Hyderabad City. Results: P.M2.5 found to be positively correlated with markers of inflammation including IL-6 (rs = 0.99), TNF-α (rs = 0.41), CRP mg/dl (rs = 0.99) , neutrophils (rs = 0.29), lymphocytes (rs = 0.31), eosinophils (rs = 0.20), monocytes (rs = 0.42) and basophils (rs = 0.16). Positive correlation present among IL-6 (rs = 0.21), TNF-α (rs = 0.49) and CRP mg/dl (rs = 0.22) % (rs = -0.31), Leukocytes (rs = 0.14) neutrophils (rs = 0.31), lymphocytes (rs = 0.21), monocytes (rs = 0.50), basophils (rs = 0.17) with P.M10. NOx showed positive correlation with IL-6 (rs = 0.22), TNF-α (rs = 0.48), CRP (rs = 0.22), neutrophils (rs = 0.31), lymphocytes (rs = 0.13), basophils (rs = 0.17) and monocytes (rs = 0.48). Conclusion: Findings of our study suggest that almost all markers of inflammation are positively correlated with traffic pollutants and this condition might raise the risk of systemic diseases.
Collapse
Affiliation(s)
- Hina Riaz
- Dr. Hina Riaz, MBBS, Lecturer, Department of Physiology, Liaquat University of Medical & Health Sciences (LUMHS), Jamshoro, Pakistan
| | - Binafsha Manzoor Syed
- Dr. Binafsha Manzoor Syed, MBBS, PhD, Director Medical Research Centre, Director Clinical Research Division, Director ORIC, Liaquat University of Medical & Health Sciences (LUMHS), Jamshoro, Pakistan
| | - Zulfiqar Laghari
- Prof. Dr. Zulfiqar Laghari, PhD, Chairperson, Department of Physiology, University of Sindh, Jamshoro, Pakistan
| | - Suleman Pirzada
- Dr. Suleman Peerzada, MBBS, PhD, Assistant Professor, Department of Molecular Biology and Genetics, Liaquat University of Medical & Health Sciences (LUMHS), Jamshoro, Pakistan
| |
Collapse
|
49
|
Lin L, Li Q, Yang J, Han N, Jin C, Xu X, Liu Z, Liu J, Luo S, Raat H, Wang H. The associations of particulate matters with fetal growth in utero and birth weight: A birth cohort study in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 709:136246. [PMID: 31927434 DOI: 10.1016/j.scitotenv.2019.136246] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 11/28/2019] [Accepted: 12/18/2019] [Indexed: 05/07/2023]
Abstract
BACKGROUND Previous studies examined the associations of particulate matters (PM) with fetal growth in utero or birth weight with inconsistent results, and few studies investigated that whether the associations of PM with fetal growth in utero also present at birth. We aimed to investigate the associations of PM with both fetal growth in utero and birth weight. METHODS We established a birth cohort (2014-2017) with 18,863 singleton pregnancies in Tongzhou Maternal and Child Hospital of Beijing, China. Maternal exposure to PM with aerodynamic diameters ≤2.5 μm and ≤ 10 μm (PM2.5/PM10) during pregnancy was estimated using the inverse distance weighting method. Estimated birth weight (EFW) was assessed by ultrasound measurements and birth weight was measured at birth, which were both standardized as gestational-age- and gender-adjusted Z-score. EFW undergrowth, low birth weight (LBW) and small-for-gestational-age were defined as the categorized outcomes. Generalized estimating equations and generalized linear regression were used to examine the associations of PM with quantitative and categorized outcomes, controlling for temperature, greenspace and individual covariates. RESULTS A 10 μg/m3 increase in PM2.5 and PM10 were associated with lower EFW Z-score [-0.031, 95% confident interval (CI): -0.047, -0.016 and -0.030, 95% CI: -0.043, -0.017]. A 10 μg/m3 increase in PM2.5 was associated with lower birth weight Z-score (-0.035, 95% CI: -0.061, -0.010) and higher risk of LBW (OR = 1.240, 95% CI: 1.019, 1.508). These results remained robust in co-pollutant models and sensitivity analyses. We didn't find significant results in other analyses. CONCLUSIONS The study identified an inverse association between PM and fetal growth in utero. The association between PM2.5 and fetal growth persisted from pregnancy to birth. This study supported that further actions towards controlling air pollution are strongly recommended for promoting early-life health.
Collapse
Affiliation(s)
- Lizi Lin
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China; Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Qin Li
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China; Reproductive Medical Centre, Department of Obstetrics and Gynaecology, Peking University Third Hospital, Beijing, 100191, People's Republic of China
| | - Jie Yang
- Maternal and Child Health Care Hospital of Tongzhou District, Beijing 101101, People's Republic of China
| | - Na Han
- Maternal and Child Health Care Hospital of Tongzhou District, Beijing 101101, People's Republic of China
| | - Chuyao Jin
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China
| | - Xiangrong Xu
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China
| | - Zheng Liu
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China
| | - Jue Liu
- Department of Epidemiology and Biostatistics, School of Public Healths, Peking University, Beijing 100191, People's Republic of China
| | - Shusheng Luo
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China
| | - Hein Raat
- Department of Public Health, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Haijun Wang
- Department of Maternal and Child Health, School of Public Health, Peking University, Beijing 100191, People's Republic of China.
| |
Collapse
|
50
|
Long-Term Exposure to Fine Particulate Matter and Cardiovascular Disease in China. J Am Coll Cardiol 2020; 75:707-717. [DOI: 10.1016/j.jacc.2019.12.031] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 11/25/2019] [Accepted: 12/10/2019] [Indexed: 11/20/2022]
|