El-Shahawi MS, Hamza A, Bashammakh AS, Al-Saggaf WT. An overview on the accumulation, distribution, transformations, toxicity and analytical methods for the monitoring of persistent organic pollutants. Talanta. 2010;80:1587–97.
Google Scholar
Ashraf MA. Persistent organic pollutants (POPs): a global issue, a global challenge. Environ Sci Pollut Res. 2017;24:4223–7.
Google Scholar
Guo W, Pan B, Sakkiah S, Yavas G, Ge W, Zou W, et al. Persistent Organic Pollutants in Food: Contamination Sources, Health Effects and Detection Methods. IJERPH. 2019;16:4361.
Google Scholar
Miniero R, Iamiceli AL, De Felip E. Persistent Organic Pollutants. In: Reference Module in Earth Systems and Environmental Sciences. Elsevier; 2015 https://doi.org/10.1016/B978-0-12-409548-9.09496-3.
Lallas PL. The Stockholm Convention on Persistent Organic Pollutants. Am J Int Law. 2001;95:692–708.
Google Scholar
Bedi JS, Singh V, Gupta A, Gill JPS, Aulakh RS. Persistent organic pollutants (POPs) in fresh water farm fish species from Punjab (India) and evaluation of their dietary intake for human risk assessment. Hum Ecol Risk Assess: Int J. 2018;24:1659–72.
Google Scholar
Fair PA, White ND, Wolf B, Arnott SA, Kannan K, Karthikraj R, et al. Persistent organic pollutants in fish from Charleston Harbor and tributaries, South Carolina, United States: A risk assessment. Environ Res. 2018;167:598–613.
Google Scholar
Harmouche-Karaki M, Mahfouz Y, Salameh P, Matta J, Helou K, Narbonne J-F. Patterns of PCBs and OCPs exposure in a sample of Lebanese adults: The role of diet and physical activity. Environ Res. 2019;179:108789.
Google Scholar
Chen JC, Baumert BO, Li Y, Li Y, Pan S, Robinson S, et al. Associations of per- and polyfluoroalkyl substances, polychlorinated biphenyls, organochlorine pesticides, and polybrominated diphenyl ethers with oxidative stress markers: A systematic review and meta-analysis. Environ Res. 2023;239:117308.
Google Scholar
Arrebola JP, Fernández MF, Martin-Olmedo P, Bonde JP, Martín-Rodriguez JL, Expósito J, et al. Historical exposure to persistent organic pollutants and risk of incident hypertension. Environ Res. 2015;138:217–23.
Google Scholar
Lee Y-M, Jacobs Jr. DR, Lee D-H. Persistent Organic Pollutants and Type 2 Diabetes: A Critical Review of Review Articles. Front Endocrinol. 2018;9 https://www.frontiersin.org/articles/10.3389/fendo.2018.00712.
Costello E, Rock S, Stratakis N, Eckel SP, Walker DI, Valvi D et al. Exposure to per-and Polyfluoroalkyl Substances and Markers of Liver Injury: A Systematic Review and Meta-Analysis. Environ Health Perspect 2022; 130. doi:10.1289/EHP10092.
Berghuis SA, Bos AF, Sauer PJJ, Roze E. Developmental neurotoxicity of persistent organic pollutants: an update on childhood outcome. Arch Toxicol 2015; 89: 687–709.
Kahn LG, Harley KG, Siegel EL, Zhu Y, Factor-Litvak P, Porucznik CA et al. Persistent organic pollutants and couple fecundability: a systematic review. Human Reproduction Update 2021; 27: 339–366.
Mustieles V, Pérez-Carrascosa FM, León J, Lange T, Bonde J-P, Gómez-Peña C, et al. Adipose Tissue Redox Microenvironment as a Potential Link between Persistent Organic Pollutants and the 16-Year Incidence of Non-hormone-Dependent Cancer. Environ Sci Technol. 2021;55:9926–37.
Google Scholar
Savitz DA, Hattersley AM. Evaluating Chemical Mixtures in Epidemiological Studies to Inform Regulatory Decisions. Environ Health Perspect. 2023;131:045001.
Google Scholar
NIEHS. RFA-ES-17-001: Powering Research through Innovative Methods for mixtures in Epidemiology (PRIME) (R01). Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) https://grants.nih.gov/grants/guide/rfa-files/RFA-ES-17-001.html.
Wild CP. Complementing the genome with an ‘exposome’: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomark Prev. 2005;14:1847–50.
Google Scholar
Huhn S, Escher BI, Krauss M, Scholz S, Hackermüller J, Altenburger R. Unravelling the chemical exposome in cohort studies: routes explored and steps to become comprehensive. Environ Sci Eur. 2021;33:17.
Google Scholar
Gibson EA, Nunez Y, Abuawad A, Zota AR, Renzetti S, Devick KL, et al. An overview of methods to address distinct research questions on environmental mixtures: an application to persistent organic pollutants and leukocyte telomere length. Environ Health. 2019;18:76.
Google Scholar
Joubert BR, Kioumourtzoglou M-A, Chamberlain T, Chen HY, Gennings C, Turyk ME, et al. Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods. Int J Environ Res Public Health. 2022;19:1378.
Google Scholar
Bobb JF, Valeri L, Claus Henn B, Christiani DC, Wright RO, Mazumdar M, et al. Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures. Biostatistics. 2015;16:493–508.
Google Scholar
Keil AP, Buckley JP, O’Brien KM, Ferguson KK, Zhao S, White AJ. A Quantile-Based g-Computation Approach to Addressing the Effects of Exposure Mixtures. Environ Health Perspect. 2020;128:047004.
Google Scholar
Czarnota J, Gennings C, Wheeler DC. Assessment of weighted quantile sum regression for modeling chemical mixtures and cancer risk. Cancer Inform. 2015;14:159–71.
Google Scholar
Braun JM, Gennings C, Hauser R, Webster TF. What Can Epidemiological Studies Tell Us about the Impact of Chemical Mixtures on Human Health? Environ Health Perspect. 2016;124:A6–9 https://doi.org/10.1289/ehp.1510569.
Google Scholar
Gibson EA, Goldsmith J, Kioumourtzoglou M-A. Complex Mixtures, Complex Analyses: an Emphasis on Interpretable Results. Curr Envir Health Rpt. 2019;6:53–61.
Google Scholar
Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med. 2018;169:467–73.
Google Scholar
Pan S. Applications of environmental mixture methods on associations with persistent organic pollutants exposures: A scoping review. 2022. Accessed 1 Feb 2024.
Listing of POPs in the Stockholm Convention. All POPs listed in the Stockholm Convention, 2019 https://www.pops.int/TheConvention/ThePOPs/AllPOPs/tabid/2509/Default.aspx.
Toxicological Profiles | ATSDR. 2023 Accessed 16 Nov 2023.
Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, et al. PubChem 2023 update. Nucleic Acids Res. 2023;51:D1373–D1380.
Google Scholar
Lazarevic N, Barnett AG, Sly PD, Knibbs LD. Statistical Methodology in Studies of Prenatal Exposure to Mixtures of Endocrine-Disrupting Chemicals: A Review of Existing Approaches and New Alternatives. Environ Health Perspect. 2019;127:026001.
Google Scholar
Suk WA, Olden K, Yang RSH. Chemical mixtures research: significance and future perspectives. Environ Health Perspect. 2002;110:891–2.
Google Scholar
van den Berg M, Birnbaum LS, Denison M, De Vito M, Farland W, Feeley M, et al. The 2005 World Health Organization Re-evaluation of Human and Mammalian Toxic Equivalency Factors for Dioxins and Dioxin-like Compounds. Toxicol Sci. 2006;93:223–41.
Google Scholar
Carlson LM, Christensen K, Sagiv SK, Rajan P, Klocke CR, Lein PJ, et al. A systematic evidence map for the evaluation of noncancer health effects and exposures to polychlorinated biphenyl mixtures. Environ Res. 2023;220:115148.
Google Scholar
Pelch KE, Reade A, Kwiatkowski CF, Merced-Nieves FM, Cavalier H, Schultz K, et al. The PFAS-Tox Database: A systematic evidence map of health studies on 29 per- and polyfluoroalkyl substances. Environ Int. 2022;167:107408.
Google Scholar
Goodrich JA, Walker DI, He J, Lin X, Baumert BO, Hu X et al. Metabolic Signatures of Youth Exposure to Mixtures of Per- and Polyfluoroalkyl Substances: A Multi-Cohort Study. Environ Health Perspect. 2023;131:027005.
Hwang BS, Chen Z, M Buck Louis G, Albert PS. A Bayesian multi-dimensional couple-based latent risk model with an application to infertility. Biometrics. 2019;75:315–25.
Google Scholar
Lazarevic N, Barnett AG, Sly PD, Callan AC, Stasinska A, Heyworth JS, et al. Prenatal exposure to mixtures of persistent environmental chemicals and fetal growth outcomes in Western Australia. Int J Hyg Environ Health. 2022;240:113899.
Google Scholar
Pearce JL, Neelon B, Bloom MS, Buckley JP, Ananth CV, Perera F, et al. Exploring associations between prenatal exposure to multiple endocrine disruptors and birth weight with exposure continuum mapping. Environ Res. 2021;200:111386 https://doi.org/10.1016/j.envres.2021.111386.
Google Scholar
Varona-Uribe ME, Torres-Rey CH, Díaz-Criollo S, Palma-Parra RM, Narváez DM, Carmona SP, et al. Exposure to pesticide mixtures and DNA damage among rice field workers. Arch Environ Occup Health. 2016;71:3–9.
Google Scholar
Roberts EK, Boss J, Mukherjee B, Salerno S, Zota A, Needham BL. Persistent organic pollutant exposure contributes to Black/White differences in leukocyte telomere length in the National Health and Nutrition Examination Survey. Sci Rep. 2022;12:19960.
Google Scholar
Zhang B, Chen Z, Albert PS. Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data. Biostatistics. 2012;13:74–88.
Google Scholar
Yonkman AM, Alampi JD, Kaida A, Allen RW, Chen A, Lanphear BP, et al. Using Latent Profile Analysis to Identify Associations Between Gestational Chemical Mixtures and Child Neurodevelopment. Epidemiology. 2023;34:45–55.
Google Scholar
Vuong AM, Xie C, Jandarov R, Dietrich KN, Zhang H, Sjödin A, et al. Prenatal Exposure to a Mixture of Persistent Organic Pollutants (POPs) and Child Reading Skills at School Age. Int J Hyg Environ Health. 2020;228:113527.
Google Scholar
Oulhote Y, Coull B, Bind M-A, Debes F, Nielsen F, Tamayo I, et al. Joint and independent neurotoxic effects of early life exposures to a chemical mixture: A multi-pollutant approach combining ensemble learning and G-computation. Environ Epidemiol. 2019;3:e063 https://doi.org/10.1097/EE9.0000000000000063.
Google Scholar
Maitre L, Jedynak P, Gallego M, Ciaran L, Audouze K, Casas M, et al. Integrating -omics approaches into population-based studies of endocrine disrupting chemicals: A scoping review. Environ Res. 2023;228:115788.
Google Scholar
Liu SH, Chen Y, Kuiper JR, Ho E, Buckley JP, Feuerstahler L. Applying Latent Variable Models to Estimate Cumulative Exposure Burden to Chemical Mixtures and Identify Latent Exposure Subgroups: A Critical Review and Future Directions. Stat Biosci. 2024;16:482–502.
Google Scholar
Ding N, Harlow SD, Randolph JF, Calafat AM, Mukherjee B, Batterman S, et al. Associations of Perfluoroalkyl Substances with Incident Natural Menopause: The Study of Women’s Health across the Nation. J Clin Endocrinol Metab. 2020;105:E3169–E3182.
Google Scholar
Kim S, Cho YH, Lee I, Kim W, Won S, Ku J-L, et al. Prenatal exposure to persistent organic pollutants and methylation of LINE-1 and imprinted genes in placenta: A CHECK cohort study. Environ Int. 2018;119:398–406.
Google Scholar
Kim S, Cho YH, Won S, Ku J-L, Moon H-B, Park J, et al. Maternal exposures to persistent organic pollutants are associated with DNA methylation of thyroid hormone-related genes in placenta differently by infant sex. Environ Int. 2019;130:104956 https://doi.org/10.1016/j.envint.2019.104956.
Google Scholar
Kalloo G, Wellenius GA, McCandless L, Calafat AM, Sjodin A, Romano ME, et al. Exposures to chemical mixtures during pregnancy and neonatal outcomes: The HOME study. Environ Int. 2020;134:105219 https://doi.org/10.1016/j.envint.2019.105219.
Google Scholar
Kalloo G, Wellenius GA, McCandless L, Calafat AM, Sjodin A, Sullivan AJ, et al. Chemical mixture exposures during pregnancy and cognitive abilities in school-aged children. Environ Res. 2021;197:111027 https://doi.org/10.1016/j.envres.2021.111027.
Google Scholar
Oppenheimer AV, Bellinger DC, Coull BA, Weisskopf MG, Korrick SA. Prenatal exposure to chemical mixtures and cognitive flexibility among adolescents. Toxics. 2021;9:329 https://doi.org/10.3390/toxics9120329.
Google Scholar
Oppenheimer AV, Bellinger DC, Coull BA, Weisskopf MG, Zemplenyi M, Korrick SA. Prenatal exposure to chemical mixtures and inhibition among adolescents. Toxics. 2021;9:329 https://doi.org/10.3390/toxics9110311.
Google Scholar
Oppenheimer AV, Bellinger DC, Coull BA, Weisskopf MG, Korrick SA. Prenatal exposure to chemical mixtures and working memory among adolescents. Environ Res. 2022;205:112436 https://doi.org/10.1016/j.envres.2021.112436.
Google Scholar
Rokoff LB, Coull BA, Bosquet Enlow M, Korrick SA. Associations of Prenatal Chemical and Nonchemical Stressors with Early-Adulthood Anxiety and Depressive Symptoms. Environ Health Perspect. 2023;131:027004.
Google Scholar
Govarts E, Remy S, Bruckers L, Den Hond E, Sioen I, Nelen V, et al. Combined effects of prenatal exposures to environmental chemicals on birth weight. Int J Environ Res Public Health. 2016;13:495 https://doi.org/10.3390/ijerph13050495.
Google Scholar
Kupsco A, Lee JJ, Prada D, Valvi D, Hu L, Petersen MS, et al. Marine pollutant exposures and human milk extracellular vesicle-microRNAs in a mother-infant cohort from the Faroe Islands. Environ Int. 2022;158:106986 https://doi.org/10.1016/j.envint.2021.106986.
Google Scholar
Tanner EM, Hallerbäck MU, Wikström S, Lindh C, Kiviranta H, Gennings C, et al. Early prenatal exposure to suspected endocrine disruptor mixtures is associated with lower IQ at age seven. Environ Int. 2020;134:105185 https://doi.org/10.1016/j.envint.2019.105185.
Google Scholar
Svensson K, Tanner E, Gennings C, Lindh C, Kiviranta H, Wikström S, et al. Prenatal exposures to mixtures of endocrine disrupting chemicals and children’s weight trajectory up to age 5.5 in the SELMA study. Sci Rep. 2021;11:11036.
Google Scholar
Berg V, Nøst TH, Pettersen RD, Hansen S, Veyhe A-S, Jorde R, et al. Persistent organic pollutants and the association with maternal and infant thyroid homeostasis: A multipollutant assessment. Environ Health Perspect. 2017;125:127–33.
Google Scholar
Pavuk M, Rosenbaum PF, Lewin MD, Serio TC, Rago P, Cave MC, et al. Polychlorinated biphenyls, polychlorinated dibenzo-p-dioxins, polychlorinated dibenzofurans, pesticides, and diabetes in the Anniston Community Health Survey follow-up (ACHS II): single exposure and mixture analysis approaches. Sci Total Environ. 2023;877:162920.
Google Scholar
Wang Z, Zhang C, Williams PL, Bellavia A, Wylie BJ, Hacker MR, et al. Polybrominated diphenyl ethers in early pregnancy and preterm birth: Findings from the NICHD Fetal Growth Studies. Int J Hyg Environ Health. 2022;243:113978.
Google Scholar
Wu B, Pan Y, Li Z, Wang J, Ji S, Zhao F, et al. Serum per- and polyfluoroalkyl substances and abnormal lipid metabolism: A nationally representative cross-sectional study. Environ Int. 2023;172:107779.
Google Scholar
Grandjean P, Budtz‐Jørgensen E. Total imprecision of exposure biomarkers: implications for calculating exposure limits. Am J Ind Med. 2007;50:712–9.
Google Scholar
Kwiatkowski CF, Andrews DQ, Birnbaum LS, Bruton TA, DeWitt JC, Knappe DRU, et al. Scientific Basis for Managing PFAS as a Chemical Class. Environ Sci Technol Lett. 2020;7:532–43.
Google Scholar
Eick SM, Barr DB, Brennan PA, Taibl KR, Tan Y, Robinson M, et al. Per- and polyfluoroalkyl substances and psychosocial stressors have a joint effect on adverse pregnancy outcomes in the Atlanta African American Maternal-Child cohort. Sci Total Environ. 2023;857:159450.
Google Scholar
Eick SM, Enright EA, Padula AM, Aung M, Geiger SD, Cushing L et al. Prenatal PFAS and psychosocial stress exposures in relation to fetal growth in two pregnancy cohorts: Applying environmental mixture methods to chemical and non-chemical stressors. Environ Int 2022;163. https://doi.org/10.1016/j.envint.2022.107238.
Maitre L, Guimbaud J-B, Warembourg C, Güil-Oumrait N, Petrone PM, Chadeau-Hyam M, et al. State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event. Environ Int. 2022;168:107422.
Google Scholar
Valeri L, Mazumdar MM, Bobb JF, Claus Henn B, Rodrigues E, Sharif OIA, et al. The Joint Effect of Prenatal Exposure to Metal Mixtures on Neurodevelopmental Outcomes at 20–40 Months of Age: Evidence from Rural Bangladesh. Environ Health Perspect. 2017;125:067015.
Google Scholar
Rosato I, Zare Jeddi M, Ledda C, Gallo E, Fletcher T, Pitter G, et al. How to investigate human health effects related to exposure to mixtures of per- and polyfluoroalkyl substances: A systematic review of statistical methods. Environ Res. 2022;205:112565.
Google Scholar
Wheeler DC, Rustom S, Carli M, Whitehead TP, Ward MH, Metayer C. Bayesian group index regression for modeling chemical mixtures and cancer risk. Int J Environ Res Public Health. 2021;18:3486 https://doi.org/10.3390/ijerph18073486.
Google Scholar
Wheeler DC, Rustom S, Carli M, Metayer C, Whitehead TP, Ward MH. Assessment of grouped weighted quantile sum regression for modeling chemical mixtures and cancer risk. Int J Environ Res Public Health. 2021;18:1–20.
Bellavia A 5.1 Bayesian Kernel Machine Regression | Statistical Methods for Environmental Mixtures, 2023 https://bookdown.org/andreabellavia/mixtures/bayesian-kernel-machine-regression.html.
Midya V, Alcala CS, Rechtman E, Gregory JK, Kannan K, Hertz-Picciotto I, et al. Machine Learning Assisted Discovery of Interactions between Pesticides, Phthalates, Phenols, and Trace Elements in Child Neurodevelopment. Environ Sci Technol. 2023;57:18139–50.
Google Scholar
Könemann WH, Pieters MN. Confusion of concepts in mixture toxicology. Food Chem Toxicol. 1996;34:1025–31.
Google Scholar
Gennings C, Carter WH, Campain JA, Bae D, Yang RSH. Statistical analysis of interactive cytotoxicity in human epidermal keratinocytes following exposure to a mixture of four metals. JABES. 2002;7:58–73.
Google Scholar
Bellavia A, James-Todd T, Williams PL. Approaches for incorporating environmental mixtures as mediators in mediation analysis. Environ Int. 2019;123:368–74.
Google Scholar
Yu L, Liu W, Wang X, Ye Z, Tan Q, Qiu W, et al. A review of practical statistical methods used in epidemiological studies to estimate the health effects of multi-pollutant mixture. Environ Pollut. 2022;306:119356.
Google Scholar
Bellavia A, Dickerson AS, Rotem RS, Hansen J, Gredal O, Weisskopf MG. Joint and interactive effects between health comorbidities and environmental exposures in predicting amyotrophic lateral sclerosis. Int J Hyg Environ Health. 2021;231:113655.
Google Scholar
Bellavia A. 5.2 Assessing interactions | Statistical Methods for Environmental Mixtures, 2023 https://bookdown.org/andreabellavia/mixtures/assessing-interactions.html.
Gao Y, Luo J, Zhang Y, Pan C, Ren Y, Zhang J et al. Prenatal Exposure to Per-and Polyfluoroalkyl Substances and Child Growth Trajectories in the First Two Years. Environ Health Perspect 2022;130. https://doi.org/10.1289/EHP9875.
Padula AM, Ning X, Bakre S, Barrett ES, Bastain T, Bennett DH et al. Birth Outcomes in Relation to Prenatal Exposure to Per- and Polyfluoroalkyl Substances and Stress in the Environmental Influences on Child Health Outcomes (ECHO) Program. Environ Health Perspect 2023; 131: 037006.
Wang H, Li W, Yang J, Wang Y, Du H, Han M, et al. Gestational exposure to perfluoroalkyl substances is associated with placental DNA methylation and birth size. Sci Total Environ. 2023;858:159747.
Google Scholar
Shen C, Ding J, Xu C, Zhang L, Liu S, Tian Y. Perfluoroalkyl Mixture Exposure in Relation to Fetal Growth: Potential Roles of Maternal Characteristics and Associations with Birth Outcomes. Toxics 2022;10:650.
Song X, Wu J, Ji H, Liang H, Chen Y, Yang L et al. Maternal per- and poly-fluoroalkyl substances exposure and child adiposity measures: A birth cohort study. Ecotoxicology and Environmental Safety 2023;253:114684.
Hu JMY, Arbuckle TE, Janssen P, Lanphear BP, Zhuang LH, Braun JM et al. Prenatal exposure to endocrine disrupting chemical mixtures and infant birth weight: A Bayesian analysis using kernel machine regression. Environmental Research 2021;195:110749.
Wang Z, Zhang J, Dai Y, Zhang L, Guo J, Xu S, et al. Mediating effect of endocrine hormones on association between per- and polyfluoroalkyl substances exposure and birth size: Findings from sheyang mini birth cohort study. Environ Res. 2023;226:1156580.
Google Scholar
Luo D, Wu W, Pan Y, Du B, Shen M, Zeng L. Associations of Prenatal Exposure to Per- and Polyfluoroalkyl Substances with the Neonatal Birth Size and Hormones in the Growth Hormone/Insulin-Like Growth Factor Axis. Environ Sci Technol 2021;55:11859–73.
Marks KJ, Howards PP, Smarr MM, Flanders WD, Northstone K, Daniel JH et al. Prenatal Exposure to Mixtures of Persistent Endocrine-disrupting Chemicals and Birth Size in a Population-based Cohort of British Girls. Epidemiology 2021;32:573–82.
Kalloo G, Wellenius GA, McCandless L, Calafat AM, Sjodin A, Romano ME et al. Exposures to chemical mixtures during pregnancy and neonatal outcomes: The HOME study. Environ Int 2020;134. https://doi.org/10.1016/j.envint.2019.105219.
Zhuang LH, Chen A, Braun JM, Lanphear BP, Hu JMY, Yolton K et al. Effects of gestational exposures to chemical mixtures on birth weight using Bayesian factor analysis in the Health Outcome and Measures of Environment (HOME) Study. Environ Epidemiology 2021. https://doi.org/10.1097/EE9.0000000000000159.
Eick SM, Tan Y, Taibl KR, Barry Ryan P, Barr DB, Hüls A et al. Prenatal exposure to persistent and non-persistent chemical mixtures and associations with adverse birth outcomes in the Atlanta African American Maternal-Child Cohort. J Expo Sci Environ Epidemiol. 2023
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