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Trees IR, Saha A, Putnick DL, Clayton PK, Mendola P, Bell EM, Sundaram R, Yeung EH. Prenatal exposure to air pollutant mixtures and birthweight in the upstate KIDS cohort. ENVIRONMENT INTERNATIONAL 2024; 187:108692. [PMID: 38677086 DOI: 10.1016/j.envint.2024.108692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 04/02/2024] [Accepted: 04/23/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND Single-pollutant models have linked prenatal PM2.5 exposure to lower birthweight. However, analyzing air pollutant mixtures better captures pollutant interactions and total effects. Unfortunately, strong correlations between pollutants restrict traditional methods. OBJECTIVES We explored the association between exposure to a mixture of air pollutants during different gestational age windows of pregnancy and birthweight. METHODS We included 4,635 mother-infant dyads from a New York State birth cohort born 2008-2010. Air pollution data were sourced from the EPA's Community Multiscale Air Quality model and matched to the census tract centroid of each maternal home address. Birthweight and gestational age were extracted from vital records. We applied linear regression to study the association between prenatal exposure to PM2.5, PM10, NOX, SO2, and CO and birthweight during six sensitive windows. We then utilized Bayesian kernel machine regression to examine the non-linear effects and interactions within this five-pollutant mixture. Final models adjusted for maternal socio-demographics, infant characteristics, and seasonality. RESULTS Single-pollutant linear regression models indicated that most pollutants were associated with a decrement in birthweight, specifically during the two-week window before birth. An interquartile range increase in PM2.5 exposure (IQR: 3.3 µg/m3) from the median during this window correlated with a 34 g decrement in birthweight (95 % CI: -54, -14), followed by SO2 (IQR: 2.0 ppb; β: -31), PM10 (IQR: 4.6 µg/m3; β: -29), CO (IQR: 60.8 ppb; β: -27), and NOX (IQR: 7.9 ppb; β: -26). Multi-pollutant BKMR models revealed that PM2.5, NOX, and CO exposure were negatively and non-linearly linked with birthweight. As the five-pollutant mixture increased, birthweight decreased until the median level of exposure. DISCUSSION Prenatal exposure to air pollutants, notably PM2.5, during the final two weeks of pregnancy may negatively impact birthweight. The non-linear relationships between air pollution and birthweight highlight the importance of studying pollutant mixtures and their interactions.
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Affiliation(s)
- Ian R Trees
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, United States
| | - Abhisek Saha
- Biostatistics and Bioinformatics Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, United States
| | - Diane L Putnick
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, United States
| | - Priscilla K Clayton
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, United States
| | - Pauline Mendola
- Department of Epidemiology and Environmental Health, University at Buffalo, United States
| | - Erin M Bell
- Department of Environmental Health Sciences, University at Albany School of Public Health, United States
| | - Rajeshwari Sundaram
- Biostatistics and Bioinformatics Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, United States.
| | - Edwina H Yeung
- Epidemiology Branch, Division of Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, United States.
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Pan W, Wang M, Hu Y, Lian Z, Cheng H, Qin JJ, Wan J. The association between outdoor air pollution and body mass index, central obesity, and visceral adiposity index among middle-aged and elderly adults: a nationwide study in China. Front Endocrinol (Lausanne) 2023; 14:1221325. [PMID: 37876545 PMCID: PMC10593432 DOI: 10.3389/fendo.2023.1221325] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 08/22/2023] [Indexed: 10/26/2023] Open
Abstract
Background Previous animal studies have suggested that air pollution (AP) exposure may be a potential risk factor for obesity; however, there is limited epidemiological evidence available to describe the association of obesity with AP exposure. Methods A retrospective cross-sectional study was conducted on 11,766 participants across mainland China in 2015. Obesity was assessed using body mass index (BMI), waist circumference (WC), and visceral adiposity index (VAI). The space-time extremely randomized tree (STET) model was used to estimate the concentration of air pollutants, including SO2, NO2, O3, PM1, PM2.5, and PM10, matched to participants' residential addresses. Logistic regression models were employed to estimate the associations of obesity with outdoor AP exposure. Further stratified analysis was conducted to evaluate whether sociodemographics or lifestyles modified the effects. Results Increased AP exposure was statistically associated with increased odds of obesity. The odds ratio (ORs) and 95% confidence interval (CI) of BMI-defined obesity were 1.21 (1.17, 1.26) for SO2, 1.33 (1.26, 1.40) for NO2, 1.15 (1.10, 1.21) for O3, 1.38 (1.29, 1.48) for PM1, 1.19 (1.15, 1.22) for PM2.5, and 1.11 (1.09, 1.13) for PM10 per 10 μg/m3 increase in concentration. Similar results were found for central obesity. Stratified analyses suggested that elderly participants experienced more adverse effects from all 6 air pollutants than middle-aged participants. Furthermore, notable multiplicative interactions were found between O3 exposure and females as well as second-hand smokers in BMI-defined obesity. Conclusions This study suggested that outdoor AP exposure had a significant association with the risk of obesity in the middle-aged and elderly Chinese population. Elderly individuals and women may be more vulnerable to AP exposure.
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Affiliation(s)
- Wei Pan
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Menglong Wang
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
| | - Yingying Hu
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Zhengqi Lian
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
| | - Haonan Cheng
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
| | - Juan-Juan Qin
- Department of Geriatrics, Zhongnan Hospital of Wuhan University, Wuhan, China
- Center for Healthy Aging, Wuhan University School of Nursing, Wuhan, China
| | - Jun Wan
- Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China
- Cardiovascular Research Institute, Wuhan University, Wuhan, China
- Hubei Key Laboratory of Cardiology, Wuhan, China
- Dong Fureng Institute of Economic and Social Development, Wuhan University, Wuhan, China
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Li P, Wu J, Tong M, Li J, Wang R, Ni X, Lu H, Deng J, Ai S, Xue T, Zhu T. The association of birthweight with fine particle exposure is modifiable by source sector: Findings from a cross-sectional study of 17 low- and middle-income countries. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 253:114696. [PMID: 36857918 DOI: 10.1016/j.ecoenv.2023.114696] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 02/24/2023] [Accepted: 02/25/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Low birthweight attributable to fine particulate matter (PM2.5) exposure is a global issue affecting infant health, especially in low- and middle-income countries (LMICs). However, large-population studies of multiple LMICs are lacking, and little is known about whether the source of PM2.5 is a determinant of the toxic effect on birthweight. OBJECTIVE We examined the effect on birthweight of long-term exposure to PM2.5 from different sources in LMICs. METHODS The birthweights of 53,449 infants born between September 16, 2017 and September 15, 2018 in 17 LMICs were collected from demographic and health surveys. Long-term exposure to PM2.5 in 2017 produced by 20 different sources was estimated by combining chemical transport model simulations with satellite-based concentrations of total mass. Generalized linear regression models were used to investigate the associations between birthweight and each source-specific PM2.5 exposure. A multiple-pollutant model with a ridge penalty on the coefficients of all 20-source-specific components was employed to develop a joint exposure-response function (JERF) of the PM2.5 mixtures. The estimated JERF was then used to quantify the global burden of birthweight reduction attributable to PM2.5 mixtures and to PM2.5 from specific sources. RESULTS The fully adjusted single-pollutant model indicated that exposure to a 10 μg/m3 increase in total PM2.5 was significantly associated with a -6.6 g (95% CI -11.0 to -2.3) reduction in birthweight. In single- and multiple-pollutant models, significant birthweight changes were associated with exposure to PM2.5 produced by international shipping (SHP), solvents (SLV), agricultural waste burning (GFEDagburn), road transportation (ROAD), waste handling and disposal (WST), and windblown dust (WDUST). Based on the global average exposure to PM2.5 mixtures, the JERF showed that the overall change in birthweight could mostly be attributed to PM2.5 produced by ROAD (-37.7 g [95% CI -49.2 to -24.4] for a global average exposure of 2.2 μg/m3), followed by WST (-27.5 g [95% CI -42.6 to -10.7] for a 1.6-μg/m3 exposure), WDUST (-19.5 g [95% CI -26.7 to -12.6] for a 8.6-μg/m3 exposure), and SHP (-19.0 g [95% CI -32.3 to -5.7] for a 0.2-μg/m3 exposure), which, with the exception of WDUST, are anthropogenic sources. The changes in birthweight varied geographically and were co-determined by the concentration as well as the source profile of the PM2.5 mixture. CONCLUSION PM2.5 exposure is associated with a reduction in birthweight, but our study shows that the magnitude of the association differs depending on the PM2.5 source. A source-targeted emission-control strategy that considers local features is therefore critical to maximize the health benefits of air quality improvement, especially with respect to promoting maternal and child health.
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Affiliation(s)
- Pengfei Li
- 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 Center, Beijing 100191, China; Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China; National Institute of Health Data Science, Peking University, Beijing 100191, China.
| | - Jingyi Wu
- Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China.
| | - Mingkun Tong
- 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 Center, Beijing 100191, China.
| | - Jiajianghui Li
- 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 Center, Beijing 100191, China.
| | - Ruohan Wang
- 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 Center, Beijing 100191, China.
| | - Xueqiu Ni
- 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 Center, Beijing 100191, China.
| | - Hong Lu
- 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 Center, Beijing 100191, China.
| | - Jianyu Deng
- 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 Center, Beijing 100191, China.
| | - Siqi Ai
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, 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 Center, Beijing 100191, China; Center for Environment and Health, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
| | - Tong Zhu
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China; Center for Environment and Health, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
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Predisposed obesity and long-term metabolic diseases from maternal exposure to fine particulate matter (PM2.5) — A review of its effect and potential mechanisms. Life Sci 2022; 310:121054. [DOI: 10.1016/j.lfs.2022.121054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/30/2022] [Accepted: 10/05/2022] [Indexed: 11/05/2022]
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Xu Y, Yi L, Cabison J, Rosales M, O'Sharkey K, Chavez TA, Johnson M, Lurmann F, Pavlovic N, Bastain TM, Breton CV, Wilson JP, Habre R. The impact of GPS-derived activity spaces on personal PM 2.5 exposures in the MADRES cohort. ENVIRONMENTAL RESEARCH 2022; 214:114029. [PMID: 35932832 DOI: 10.1016/j.envres.2022.114029] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/22/2022] [Accepted: 07/30/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND In-utero exposure to particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) is associated with low birth weight and health risks later in life. Pregnant women are mobile and locations they spend time in contribute to their personal PM2.5 exposures. Therefore, it is important to understand how mobility and exposures encountered within activity spaces contribute to personal PM2.5 exposures during pregnancy. METHODS We collected 48-h integrated personal PM2.5 samples and continuous geolocation (GPS) data for 213 predominantly Hispanic/Latina pregnant women in their 3rd trimester in Los Angeles, CA. We also collected questionnaires and modeled outdoor air pollution and meteorology in their residential neighborhood. We calculated three GPS-derived activity space measures of exposure to road networks, greenness (NDVI), parks, traffic volume, walkability, and outdoor PM2.5 and temperature. We used bivariate analyses to screen variables (GPS-extracted exposures in activity spaces, individual characteristics, and residential neighborhood exposures) based on their relationship with personal, 48-h integrated PM2.5 concentrations. We then built a generalized linear model to explain the variability in personal PM2.5 exposure and identify key contributing factors. RESULTS Indoor PM2.5 sources, parity, and home ventilation were significantly associated with personal exposure. Activity-space based exposure to roads was associated with significantly higher personal PM2.5 exposure, while greenness was associated with lower personal PM2.5 exposure (β = -3.09 μg/m3 per SD increase in NDVI, p-value = 0.018). The contribution of outdoor PM2.5 to personal exposure was positive but relatively lower (β = 2.05 μg/m3 per SD increase, p-value = 0.016) than exposures in activity spaces and the indoor environment. The final model explained 34% of the variability in personal PM2.5 concentrations. CONCLUSIONS Our findings highlight the importance of activity spaces and the indoor environment on personal PM2.5 exposures of pregnant women living in Los Angeles, CA. This work also showcases the multiple, complex factors that contribute to total personal PM2.5 exposure.
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Affiliation(s)
- Yan Xu
- Spatial Sciences Institute, University of Southern California, USA.
| | - Li Yi
- Spatial Sciences Institute, University of Southern California, USA.
| | - Jane Cabison
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | - Marisela Rosales
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | - Karl O'Sharkey
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | - Thomas A Chavez
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | - Mark Johnson
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | | | | | - Theresa M Bastain
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | - Carrie V Breton
- Department of Population and Public Health Sciences, University of Southern California, USA.
| | - John P Wilson
- Spatial Sciences Institute, University of Southern California, USA; Department of Population and Public Health Sciences, University of Southern California, USA; Department of Civil & Environmental Engineering, Computer Science, and Sociology, University of Southern California, USA.
| | - Rima Habre
- Spatial Sciences Institute, University of Southern California, USA; Department of Population and Public Health Sciences, University of Southern California, USA.
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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.
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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
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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.
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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.
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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.
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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
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Zou Z, Liu W, Huang C, Cai J, Fu Q, Sun C, Zhang J. Gestational exposures to outdoor air pollutants in relation to low birth weight: A retrospective observational study. ENVIRONMENTAL RESEARCH 2021; 193:110354. [PMID: 33098816 DOI: 10.1016/j.envres.2020.110354] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2019] [Revised: 10/08/2020] [Accepted: 10/12/2020] [Indexed: 06/11/2023]
Abstract
Findings for impacts of outdoor air pollutants on birth outcomes were controversial. We performed a retrospective observational study in 2527 preschoolers of Shanghai, China and investigated associations of duration-averaged concentrations of outdoor sulphur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter ≤ 10 μm (PM10) in different months and trimesters of gestation, with preterm birth (PB), low birth weight (LBW), term low birth weight (T-LBW), and small for gestational age (SGA). Daily concentrations of outdoor air pollutants were collected in each residence-located district. Parents reported health information. In the multivariate logistic regression analyses, exposures to outdoor NO2 were consistently associated with the higher odds of LBW and T-LBW. These associations were generally stronger for early months than for later months of the gestation. Adjusted odds ratios generally were larger in multi-pollutant model than in single-pollutant model. Exposure to NO2 in the first month of the gestation was significantly associated with T-LBW (adjusted OR, 95%CI: 1.91, 1.02-3.58 for increment of interquartile range (18.5 μg/m3); p-value = 0.044) in multi-pollutant model. This association was stronger in girls, renters, and children whose mothers ≥30 years-old, with household dampness-related exposures, and with parental smoking during pregnancy. Our results indicate that exposure to NO2 during gestation perhaps is a risk factor for LBW and T-LBW, and effects of NO2 exposures could be greater during early periods than during later periods of gestation.
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Affiliation(s)
- Zhijun Zou
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Wei Liu
- Institute for Health and Environment, Chongqing University of Science and Technology, Chongqing, China.
| | - Chen Huang
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Jiao Cai
- Joint International Research Laboratory of Green Buildings and Built Environments (Ministry of Education), Chongqing University, Chongqing, China
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai, China
| | - Chanjuan Sun
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
| | - Jialing Zhang
- Department of Building Environment and Energy Engineering, School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai, China
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