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Zhang B, Liu J, Zhang Z, Zhu Y. Research on ecological management zoning in Jilin Province based on a human well-being framework. Sci Rep 2025; 15:16730. [PMID: 40369109 PMCID: PMC12078575 DOI: 10.1038/s41598-025-99942-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2025] [Accepted: 04/23/2025] [Indexed: 05/16/2025] Open
Abstract
Taking Jilin Province in 2020 as the study area, this research categorizes ecosystem service supply and demand by integrating ecosystem service functions with a human well-being framework. The study evaluates the supply and demand of ecosystem services and examines their spatial distribution characteristics. To further delineate ecological management zones, the SC K-means clustering algorithm and the coupling coordination degree model are employed. The results reveal significant regional disparities in the availability and necessity of six ecosystem services. Food production services exhibit a spatial pattern characterized by an increase in the central region while declining in the eastern and western areas. In contrast, the supply of the other five ecosystem services generally follows a "low in the west, high in the east" trend. Additionally, except for soil conservation, the demand for ecosystem services demonstrates a distribution pattern of being high in the central region and lower in the surrounding areas. The overall supply of ecosystem services gradually increases from west to east, reaching its peak in the eastern region, whereas the comprehensive demand is highest in the central region and lower in both the eastern and western areas, with central cities and their surrounding counties exhibiting the most pronounced demand. Based on the dynamics of supply and demand, Jilin Province is divided into five ecological management zones. The ecological potential zone, where supply-demand coordination transitions from low to high, is suited for developing green agricultural economies and optimizing industrial structures. The ecological restoration zone, experiencing a shift from high to low supply-demand balance, faces imbalances that necessitate efforts to alleviate human-land conflicts and enhance the equilibrium between social development and ecological conservation. The ecological consolidation zone, which maintains a high-to-low supply-demand trend with relative stability, requires continued efforts in preserving its natural environment. The ecological adjustment zone, characterized by an imbalanced high-to-low supply-demand transition, should focus on industrial restructuring and eco-tourism development. Lastly, the ecological coordination zone, which maintains a well-balanced supply-demand relationship, should leverage its economic foundation to advance environmental protection technologies and strengthen conservation efforts. This study provides a systematic evaluation of the spatial patterns of ecosystem service supply and demand in Jilin Province and offers targeted ecological management strategies to promote sustainable environmental development.
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Affiliation(s)
- Baihao Zhang
- College of Geographic Sciences and Tourism, Jilin Normal University, Haifeng Street, Siping, 136000, Jilin, China
| | - Jiafu Liu
- College of Geographic Sciences and Tourism, Jilin Normal University, Haifeng Street, Siping, 136000, Jilin, China.
| | - Zhenyu Zhang
- College of Geographic Sciences and Tourism, Jilin Normal University, Haifeng Street, Siping, 136000, Jilin, China
| | - Yu Zhu
- College of Geographic Sciences and Tourism, Jilin Normal University, Haifeng Street, Siping, 136000, Jilin, China
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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 PMCID: PMC11318452 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] [Grants] [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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Chen X, Li P, Huang Y, Lv Y, Xu X, Nong H, Zhang L, Wu H, Yu C, Chen L, Liu D, Wei L, Zhang H. Joint associations among non-essential heavy metal mixtures and nutritional factors on glucose metabolism indexes in US adults: evidence from the NHANES 2011-2016. Food Funct 2024; 15:2706-2718. [PMID: 38376466 DOI: 10.1039/d3fo05439j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Dietary intake can modify the impact of metals on human health, and is also closely related to glucose metabolism in human bodies. However, research on their interaction is limited. We used data based on 1738 adults aged ≥20 years from the National Health and Nutrition Examination Survey 2011-2016. We combined linear regression and restricted cubic splines with Bayesian kernel machine regression (BKMR) to identify metals associated with each glucose metabolism index (P < 0.05 and the posterior inclusion probabilities of BKMR >0.5) in eight non-essential heavy metals (barium, cadmium, antimony, tungsten, uranium, arsenic, lead, and thallium) and glucose metabolism indexes [fasting plasma glucose (FPG), blood hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)]. We identified two pairs of metals associated with glucose metabolism indexes: cadmium and tungsten to HbA1c and barium and thallium to HOMA-IR. Then, the cross-validated kernel ensemble (CVEK) approach was applied to identify the specific nutrient group (nutrients) that interacted with the association. By using the CVEK model, we identified significant interactions between the energy-adjusted diet inflammatory index (E-DII) and cadmium, tungsten and barium (all P < 0.05); macro-nutrients and cadmium, tungsten and barium (all P < 0.05); minerals and cadmium, tungsten, barium and thallium (all P < 0.05); and A vitamins and thallium (P = 0.043). Furthermore, a lower E-DII, a lower intake of carbohydrates and phosphorus, and a higher consumption of magnesium seem to attenuate the positive association between metals and glucose metabolism indexes. Our finding identifying the nutrients that interact with non-essential heavy metals could provide a feasible nutritional guideline for the general population to protect against the adverse effects of non-essential heavy metals on glucose metabolism.
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Affiliation(s)
- Xiaolang Chen
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Peipei Li
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Yuanhao Huang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Yingnan Lv
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, Guangxi, China
| | - Xia Xu
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Huiyun Nong
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Lulu Zhang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, Guangxi, China
| | - Huabei Wu
- School of General Practice, Guangxi Medical University, Nanning 530021, China
| | - Chao Yu
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Lina Chen
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Di Liu
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Lancheng Wei
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
| | - Haiying Zhang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning 530021, China
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning 530021, Guangxi, China
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Issah I, Duah MS, Arko-Mensah J, Bawua SA, Agyekum TP, Fobil JN. Exposure to metal mixtures and adverse pregnancy and birth outcomes: A systematic review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168380. [PMID: 37963536 DOI: 10.1016/j.scitotenv.2023.168380] [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: 08/30/2023] [Revised: 11/04/2023] [Accepted: 11/04/2023] [Indexed: 11/16/2023]
Abstract
BACKGROUND Prenatal exposure to metal mixtures is associated with adverse pregnancy and birth outcomes like low birth weight, preterm birth, and small for gestational age. However, prior studies have used individual metal analysis, lacking real-life exposure scenarios. OBJECTIVES This systematic review aims to evaluate the strength and consistency of the association between metal mixtures and pregnancy and birth outcomes, identify research gaps, and inform future studies and policies in this area. METHODS The review adhered to the updated Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) checklist, along with the guidelines for conducting systematic reviews and meta-analyses of observational studies of etiology (COSMOS-E). Our data collection involved searching the PubMed, MEDLINE, and SCOPUS databases. We utilized inclusion criteria to identify relevant studies. These chosen studies underwent thorough screening and data extraction procedures. Methodological quality evaluations were conducted using the NOS framework for cohort and case-control studies, and the AXIS tool for cross-sectional studies. RESULTS The review included 34 epidemiological studies, half of which focused on birth weight, and the others investigated neonate size, preterm birth, small for gestational age, miscarriage, and placental characteristics. The findings revealed significant associations between metal mixtures (including mercury (Hg), nickel (Ni), arsenic (As), cadmium (Cd), manganese (Mn), cobalt (Co), lead (Pb), zinc (Zn), barium (Ba), cesium (Cs), copper (Cu), selenium (Se), and chromium (Cr)) and adverse pregnancy and birth outcomes, demonstrating diverse effects and potential interactions. CONCLUSION In conclusion, this review consistently establishes connections between metal exposure during pregnancy and adverse consequences for birth weight, gestational age, and other vital birth-related metrics. This review further demonstrates the need to apply mixture methods with caution but also shows that they can be superior to traditional approaches. Further research is warranted to deeper understand the underlying mechanisms and to develop effective strategies for mitigating the potential risks associated with metal mixture exposure during pregnancy.
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Affiliation(s)
- Ibrahim Issah
- West Africa Center for Global Environmental & Occupational Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana; Department of Surgery, Tamale Teaching Hospital, Tamale, Ghana.
| | - Mabel S Duah
- West Africa Center for Global Environmental & Occupational Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana; Department of Biological, Environmental and Occupational Health, School of Public Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana; West African Center for Cell Biology of Infectious Pathogens, College of Basic and Applied Sciences, University of Ghana, Legon, Accra, Ghana
| | - John Arko-Mensah
- West Africa Center for Global Environmental & Occupational Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana; Department of Biological, Environmental and Occupational Health, School of Public Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana
| | - Serwaa A Bawua
- West Africa Center for Global Environmental & Occupational Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana; Department of Biological, Environmental and Occupational Health, School of Public Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana
| | - Thomas P Agyekum
- Department of Occupational and Environmental Health and Safety, School of Public Health, College of Health Sciences, Kwame Nkrumah University of Science and Technology, Kumasi 00233, Ghana
| | - Julius N Fobil
- West Africa Center for Global Environmental & Occupational Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana; Department of Biological, Environmental and Occupational Health, School of Public Health, College of Health Sciences, University of Ghana, Legon, Accra, Ghana
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5
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Bragg MG, Westlake M, Alshawabkeh AN, Bekelman TA, Camargo CA, Catellier DJ, Comstock SS, Dabelea D, Dunlop AL, Hedderson MM, Hockett CW, Karagas MR, Keenan K, Kelly NR, Kerver JM, MacKenzie D, Mahabir S, Maldonado LE, McCormack LA, Melough MM, Mueller NT, Nelson ME, O’Connor TG, Oken E, O’Shea TM, Switkowski KM, Sauder KA, Wright RJ, Wright RO, Zhang X, Zhu Y, Lyall K, on behalf of program collaborators for Environmental influences on Child Health Outcomes. Opportunities for Examining Child Health Impacts of Early-Life Nutrition in the ECHO Program: Maternal and Child Dietary Intake Data from Pregnancy to Adolescence. Curr Dev Nutr 2023; 7:102019. [PMID: 38035205 PMCID: PMC10681943 DOI: 10.1016/j.cdnut.2023.102019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/10/2023] [Accepted: 10/11/2023] [Indexed: 12/02/2023] Open
Abstract
Background Longitudinal measures of diet spanning pregnancy through adolescence are needed from a large, diverse sample to advance research on the effect of early-life nutrition on child health. The Environmental influences on Child Health Outcomes (ECHO) Program, which includes 69 cohorts, >33,000 pregnancies, and >31,000 children in its first 7-y cycle, provides such data, now publicly available. Objectives This study aimed to describe dietary intake data available in the ECHO Program as of 31 August, 2022 (end of year 6 of Cycle 1) from pregnancy through adolescence, including estimated sample sizes, and to highlight the potential for future analyses of nutrition and child health. Methods We identified and categorized ECHO Program dietary intake data, by assessment method, participant (pregnant person or child), and life stage of data collection. We calculated the number of maternal-child dyads with dietary data and the number of participants with repeated measures. We identified diet-related variables derived from raw dietary intake data and nutrient biomarkers measured from biospecimens. Results Overall, 66 cohorts (26,941 pregnancies, 27,103 children, including 22,712 dyads) across 34 US states/territories provided dietary intake data. Dietary intake assessments included 24-h recalls (1548 pregnancies and 1457 children), food frequency questionnaires (4902 and 4117), dietary screeners (8816 and 23,626), and dietary supplement use questionnaires (24,798 and 26,513). Repeated measures were available for ∼70%, ∼30%, and ∼15% of participants with 24-h recalls, food frequency questionnaires, and dietary screeners, respectively. The available diet-related variables describe nutrient and food intake, diet patterns, and breastfeeding practices. Overall, 17% of participants with dietary intake data had measured nutrient biomarkers. Conclusions ECHO cohorts have collected longitudinal dietary intake data spanning pregnancy through adolescence from a geographically, socioeconomically, and ethnically diverse US sample. As data collection continues in Cycle 2, these data present an opportunity to advance the field of nutrition and child health.
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Affiliation(s)
- Megan G. Bragg
- AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, United States
| | - Matt Westlake
- RTI International, Research Triangle Park, NC, United States
| | | | - Traci A. Bekelman
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Carlos A. Camargo
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | | | - Sarah S. Comstock
- Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI, United States
| | - Dana Dabelea
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Anne L. Dunlop
- Department of Gynecology & Obstetrics, Emory University School of Medicine, Atlanta, GA, United States
| | - Monique M. Hedderson
- Kaiser Permanente Northern California Division of Research, Oakland, CA, United States
| | - Christine W. Hockett
- Avera Research Institute, Sioux Falls, SD, United States
- Department of Pediatrics, University of South Dakota School of Medicine, Sioux Falls, SD, United States
| | - Margaret R. Karagas
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Kate Keenan
- Department of Psychiatry & Behavioral Neuroscience, University of Chicago, Chicago, IL, United States
| | - Nichole R. Kelly
- Department of Counseling Psychology and Human Services, College of Education, University of Oregon, Eugene, OR, United States
| | - Jean M. Kerver
- Departments of Epidemiology & Biostatistics and Pediatrics & Human Development, College of Human Medicine, Michigan State University, East Lansing, MI, United States
| | - Debra MacKenzie
- Community Environmental Health Program, College of Pharmacy, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Somdat Mahabir
- National Cancer Institute, National Institutes of Health, Bethesda, MD, United States
| | - Luis E. Maldonado
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Lacey A. McCormack
- Avera Research Institute, Sioux Falls, SD, United States
- Department of Pediatrics, University of South Dakota School of Medicine, Sioux Falls, SD, United States
| | - Melissa M. Melough
- Department of Health Behavior and Nutrition Sciences, University of Delaware, Newark, DE, United States
- Department of Child Health, Behavior and Development, Seattle Children’s Research Institute, Seattle, WA, United States
| | - Noel T. Mueller
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | | | - Thomas G. O’Connor
- Departments of Psychiatry, Neuroscience, Obstetrics and Gynecology, University of Rochester, Rochester, NY, United States
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - T Michael O’Shea
- Department of Pediatrics, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC, United States
| | - Karen M. Switkowski
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Katherine A. Sauder
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - Rosalind J. Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Robert O. Wright
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Xueying Zhang
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Yeyi Zhu
- Kaiser Permanente Northern California Division of Research, Oakland, CA, United States
| | - Kristen Lyall
- AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, United States
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Cano-Sancho G, Warembourg C, Güil N, Stratakis N, Lertxundi A, Irizar A, Llop S, Lopez-Espinosa MJ, Basagaña X, González JR, Coumoul X, Fernández-Barrés S, Antignac JP, Vrijheid M, Casas M. Nutritional Modulation of Associations between Prenatal Exposure to Persistent Organic Pollutants and Childhood Obesity: A Prospective Cohort Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:37011. [PMID: 36927187 PMCID: PMC10019508 DOI: 10.1289/ehp11258] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 02/10/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Prenatal exposure to persistent organic pollutants (POPs) may contribute to the development of childhood obesity and metabolic disorders. However, little is known about whether the maternal nutritional status during pregnancy can modulate these associations. OBJECTIVES The main objective was to characterize the joint associations and interactions between prenatal levels of POPs and nutrients on childhood obesity. METHODS We used data from to the Spanish INfancia y Medio Ambiente-Environment and Childhood (INMA) birth cohort, on POPs and nutritional biomarkers measured in maternal blood collected at the first trimester of pregnancy and child anthropometric measurements at 7 years of age. Six organochlorine compounds (OCs) [dichlorodiphenyldichloroethylene, hexachlorobenzene (HCB), β-hexachlorocyclohexane (β-HCH) and polychlorinated biphenyls 138, 153, 180] and four per- and polyfluoroalkyl substances (PFAS) were measured. Nutrients included vitamins (D, B12, and folate), polyunsaturated fatty acids (PUFAs), and dietary carotenoids. Two POPs-nutrients mixtures data sets were established: a) OCs, PFAS, vitamins, and carotenoids (n=660), and b) OCs, PUFAs, and vitamins (n=558). Joint associations of mixtures on obesity were characterized using Bayesian kernel machine regression (BKMR). Relative importance of biomarkers and two-way interactions were identified using gradient boosting machine, hierarchical group lasso regularization, and BKMR. Interactions were further characterized using multivariate regression models in the multiplicative and additive scale. RESULTS Forty percent of children had overweight or obesity. We observed a positive overall joint association of both POPs-nutrients mixtures on overweight/obesity risk, with HCB and vitamin B12 the biomarkers contributing the most. Recurrent interactions were found between HCB and vitamin B12 across screening models. Relative risk for a natural log increase of HCB was 1.31 (95% CI: 1.11, 1.54, pInteraction=0.02) in the tertile 2 of vitamin B12 and in the additive scale a relative excess risk due to interaction of 0.11 (95% CI: 0.02, 0.20) was found. Interaction between perfluorooctane sulfonate and β-cryptoxanthin suggested a protective effect of the antioxidant on overweight/obesity risk. CONCLUSION These results support that maternal nutritional status may modulate the effect of prenatal exposure to POPs on childhood overweight/obesity. These findings may help to develop a biological hypothesis for future toxicological studies and to better interpret inconsistent findings in epidemiological studies. https://doi.org/10.1289/EHP11258.
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Affiliation(s)
- German Cano-Sancho
- Laboratory for the Study of Residues and Contaminants in Foods (LABERCA), Oniris, Institut national de la recherche agronomique (INRAE), Nantes, France
| | - Charline Warembourg
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Institut de recherche en santé, environnement et travail (IRSET), Ecole des hautes études en santé publique (EHESP), Unité Mixte de Recherche (UMR) 1085 Institut national de la santé et de la recherche médicale (INSERM), Université de Rennes, Rennes, France
| | - Nuria Güil
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Nikos Stratakis
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
| | - Aitana Lertxundi
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Biodonostia, Unidad de Epidemiologia Ambiental y Desarrollo Infantil, San Sebastian, Gipuzkoa, Spain
- Facultad de Medicina, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Leioa, Bizkaia, Spain
| | - Amaia Irizar
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Biodonostia, Unidad de Epidemiologia Ambiental y Desarrollo Infantil, San Sebastian, Gipuzkoa, Spain
- Facultad de Medicina, Universidad del País Vasco/Euskal Herriko Unibertsitatea, Leioa, Bizkaia, Spain
| | - Sabrina Llop
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO)–Public Health, FISABIO–Universitat Jaume I–Universitat de València, Valencia, Valencia, Spain
| | - Maria-Jose Lopez-Espinosa
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Epidemiology and Environmental Health Joint Research Unit, Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, Foundation for the Promotion of Health and Biomedical Research in the Valencian Community (FISABIO)–Public Health, FISABIO–Universitat Jaume I–Universitat de València, Valencia, Valencia, Spain
- Faculty of Nursing and Chiropody, University of Valencia, Valencia, Valencia, Spain
| | - Xavier Basagaña
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Juan Ramon González
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Xavier Coumoul
- Institut national de la santé et de la recherche médicale (INSERM) UMR-S1124, Université de Paris, Paris, France
| | - Sílvia Fernández-Barrés
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Jean-Philippe Antignac
- Laboratory for the Study of Residues and Contaminants in Foods (LABERCA), Oniris, Institut national de la recherche agronomique (INRAE), Nantes, France
| | - Martine Vrijheid
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Maribel Casas
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
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7
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Dou Y, Yin Y, Li Z, Du J, Jiang Y, Jiang T, Guo W, Qin R, Li M, Lv H, Lu Q, Qiu Y, Lin Y, Jin G, Lu C, Ma H, Hu Z. Maternal exposure to metal mixtures during early pregnancy and fetal growth in the Jiangsu Birth Cohort, China. ENVIRONMENTAL RESEARCH 2022; 215:114305. [PMID: 36096164 DOI: 10.1016/j.envres.2022.114305] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 08/26/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
Previous epidemiological studies have reported that prenatal exposure to metals might have influence on fetal growth. Most studies assessed the effect of individual metals, while the investigation on the relationship between multiple metal exposure and fetal growth is sparse. The objective of the present study is to assess the joint impact of metal mixtures on fetal growth during pregnancy. A total of 1275 maternal-infant pairs from the Jiangsu Birth Cohort (JBC) Study were included to investigate the effect of maternal metal exposure on fetal biometry measures at 22-24, 30-32, and 34-36 weeks of gestation. Lead (Pb), arsenic (As), cadmium (Cd), mercury (Hg), chromium (Cr), vanadium(V), thallium (Tl) and barium (Ba) were measured by inductively coupled plasma mass spectrometry (ICP-MS) in maternal urine samples collected in the first trimester. We used general linear models and restricted cubic splines to test dose-response relationships between single metals and fetal growth. The weighted quantile sum (WQS) models were then applied to evaluate the overall effect of all these metals. We observed inverse associations of exposure to Pb, V and Cr with estimated fetal weight (EFW) at 34-36 weeks of gestation. Notably, maternal exposure to metal mixtures was significantly associated with reduced EFW at 34-36 weeks of gestation after adjusting for some covariates and confounders (aβ -0.05 [95% CI: 0.09, -0.01], P = 0.023), and this association was mainly driven by Cr (30.41%), Pb (23.92%), and Tl (15.60%). These findings indicated that prenatal exposure to metal mixtures might impose adverse effects on fetal growth.
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Affiliation(s)
- Yuanyan Dou
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Yin Yin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Obstetrics, The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Zhi Li
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Jiangbo Du
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Yangqian Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Tao Jiang
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Wenhui Guo
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Rui Qin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Mei Li
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Hong Lv
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Qun Lu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Yun Qiu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Yuan Lin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China; Department of Maternal, Child and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China
| | - Chuncheng Lu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China.
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China.
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, Jiangsu, China; State Key Laboratory of Reproductive Medicine (Suzhou Centre), The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Suzhou, 215002, Jiangsu, China.
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8
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Pacyga DC, Talge NM, Gardiner JC, Calafat AM, Schantz SL, Strakovsky RS. Maternal diet quality moderates associations between parabens and birth outcomes. ENVIRONMENTAL RESEARCH 2022; 214:114078. [PMID: 35964672 PMCID: PMC10052883 DOI: 10.1016/j.envres.2022.114078] [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: 04/26/2022] [Revised: 08/01/2022] [Accepted: 08/05/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND/OBJECTIVE Maternal paraben exposure and diet quality are both independently associated with birth outcomes, but whether these interact is unknown. We assessed sex-specific associations of parabens with birth outcomes and differences by maternal diet quality. METHODS Illinois pregnant women (n = 458) provided five first-morning urines collected at 8-40 weeks gestation, which we pooled for quantification of ethylparaben, methylparaben, and propylparaben concentrations. We collected/measured gestational age at delivery, birth weight, body length, and head circumference within 24 h of birth, and calculated sex-specific birth weight-for-gestational-age z-scores and weight/length ratio. Women completed three-month food frequency questionnaires in early and mid-to-late pregnancy, which we used to calculate the Alternative Healthy Eating Index (AHEI)-2010. Linear regression models evaluated sex-specific associations of parabens with birth outcomes, and differences in associations by average pregnancy AHEI-2010. RESULTS In this predominately non-Hispanic white, college-educated sample, maternal urinary paraben concentrations were only modestly inversely associated with head circumference and gestational length. However, methylparaben and propylparaben were inversely associated with birth weight, birth weight z-scores, body length, and weight/length ratio in female, but not male newborns. For example, each 2-fold increase in methylparaben concentrations was associated with -46.61 g (95% CI: -74.70, -18.51) lower birth weight, -0.09 (95% CI: -0.15, -0.03) lower birth weight z-scores, -0.21 cm (95% CI: -0.34, -0.07) shorter body length, and -0.64 g/cm (95% CI: -1.10, -0.19) smaller weight/length ratio in females. These inverse associations were more prominent in females of mothers with poorer diets (AHEI-2010 < median), but attenuated in those with healthier diets (AHEI-2010 ≥ median). In newborn males of mothers with healthier diets, moderate inverse associations emerged for propylparaben with gestational length and head circumference. CONCLUSIONS Maternal diet may moderate associations of parabens with birth size in a sex-specific manner. Additional studies may consider understanding the inflammatory and metabolic mechanisms underlying these findings.
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Affiliation(s)
- Diana C Pacyga
- Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI, 48824, USA; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI, 48824, USA
| | - Nicole M Talge
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, 48824, USA
| | - Joseph C Gardiner
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, 48824, USA
| | - Antonia M Calafat
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, 30341, USA
| | - Susan L Schantz
- The Department of Comparative Biosciences, University of Illinois, Urbana-Champaign, IL, 61802, USA; The Beckman Institute, University of Illinois, Urbana-Champaign, IL, 61801, USA
| | - Rita S Strakovsky
- Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI, 48824, USA; Institute for Integrative Toxicology, Michigan State University, East Lansing, MI, 48824, USA.
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