Prenatal exposure to endocrine disrupting chemical mixtures and infant birth weight: A Bayesian analysis using kernel machine regression

Hu, Janice M.Y.; Arbuckle, Tye E.; Janssen, Patricia A.; Lanphear, Bruce P.; Zhuang, Liheng Harry; Braun, Joseph M.; Chen, Aimin; McCandless, Lawrence C.

doi:10.1016/j.envres.2021.110749

Cited by 57 publications

(10 citation statements)

References 73 publications

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“…A monitoring study by Zheng et al showed that PFAS are routinely detected in breast milk in the United States, demonstrating the scope of this potential concern [ 83 ]. Beyond lactation, numerous recent studies have shown that PFAS are frequently detected in cord blood samples, indicating that there is ubiquitous fetal exposure to PFAS globally [ 84 , 85 , 86 , 87 , 88 , 89 ]. Though the majority of the studies included in this scoping review focused upon adults, more studies are needed to elucidate whether these fetal and infant exposures may increase risk for diabetes in children.…”

Section: Discussionmentioning

confidence: 99%

Associations between Exposures to Perfluoroalkyl Substances and Diabetes, Hyperglycemia, or Insulin Resistance: A Scoping Review

Margolis

Sant

2021

JoX

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Per- and polyfluoroalkyl substances (PFASs) are persistent environmental pollutants that are commonly found in the human body due to exposures via drinking water, surfactants used in consumer materials, and aqueous film-forming foams (AFFFs). PFAS exposure has been linked to adverse health effects such as low infant birth weights, cancer, and endocrine disruption, though increasingly studies have demonstrated that they may perturb metabolic processes and contribute to dysfunction. This scoping review summarizes the chemistry of PFAS exposure and the epidemiologic evidence for associations between exposure to per- and polyfluoroalkyl substances and the development of diabetes, hyperglycemia, and/or insulin resistance. We identified 11 studies on gestational diabetes mellitus, 3 studies on type 1 diabetes, 7 studies on type 2 diabetes, 6 studies on prediabetes or unspecified diabetes, and 15 studies on insulin resistance or glucose tolerance using the SCOPUS and PubMed databases. Approximately 24 reported positive associations, 9 negative associations, 2 non-linear associations, and 2 inverse associations, and 8 reported no associations found between PFAS and all diabetes search terms. Cumulatively, these data indicate the need for further studies to better assess these associations between PFAS exposure and diabetes.

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Section: Discussionmentioning

confidence: 99%

Associations between Exposures to Perfluoroalkyl Substances and Diabetes, Hyperglycemia, or Insulin Resistance: A Scoping Review

Margolis

Sant

2021

JoX

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“…First, we repeated previous analyses restricted to live births, as is typical in the birth cohort studies. [20][21][22] We used linear regression or logistic regression analysis to examine the effect of the intervention on three health outcomes: (1) PTB, (2) birth weight measured in grams, and (3) FSIQ. The analyses of PTB and birth weight included 465 participants after excluding three live births (two with a chromosomal abnormality and one with unknown gestational age at birth and birth weight), while the analysis of FSIQ included 383 participants who completed the WPPSI-IV.…”

Section: Methodsmentioning

confidence: 99%

Sensitivity analysis for live birth bias in the Ulaanbaatar Gestation and Air Pollution Research study

McCandless

Gombojav

Allen

2022

Environmental Epidemiology

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Background: The Ulaanbaatar Gestation and Air Pollution Research (UGAAR) study is a randomized controlled trial of the effects of portable high efficiency particulate air (HEPA) filter air cleaner use during pregnancy on fetal growth and child health outcomes. A challenge with the study is that the outcome variables cannot be measured in the absence of a live birth. Thus pregnancy loss is a competing event for the outcome variables that can obscure the intervention-outcome relationship. This phenomenon is called “live birth bias” in the epidemiological literature, and it is an example of selection bias due to adjustment for variables affected by previous exposure. Methods: In this investigation, we reanalyzed data from the UGAAR study and examined the impacts of the intervention on three health outcomes: preterm birth (PTB), birth weight, and full-scale IQ (FSIQ) measured with the Wechsler Preschool and Primary Scale of Intelligence III when children were four years old, while accounting for live birth bias. Specifically, we used a novel multiple imputation approach to simulate scenarios in which pregnancy losses had instead been born alive and experienced a range of health outcomes. Results: After accounting for live birth bias, the association between the intervention and PTB diminished. Additionally, the magnitude of intervention effect on birth weight and FSIQ increased. FSIQ was less sensitive to live birth bias than birth weight. Conclusion: We introduced a novel analysis approach to examine the role of live birth bias, and the findings will be useful in environmental epidemiology studies of birth cohorts.

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“…However, the GLM has some limitations, including its ine ciency in investing in the overall effect, interaction effects, potential multicollinearity problems, and non-linear exposure-response relationship. Bayesian kernel machine regression (BKMR) model has been investigated in the environmental co-exposure factors to health effects (Bobb et al 2018;Hu et al 2021;Li et al 2021). It not only has a good identi cation effect on the major environmental factors that harm health but also can use the kernel function to estimate the relationship between the overall effect generated by joint exposure and the nonlinear exposure-response relationship and nd meaningful conclusions that are di cult to nd by GLM (Bellavia et al 2019;Bobb et al 2018;Bobb et al 2015).…”

Section: Introductionmentioning

confidence: 99%

The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing

Liu

et al. 2022

Environ Sci Pollut Res

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Epidemiological studies have demonstrated that various kinds of urinary element concentrations were different between healthy, prediabetes, and diabetes patients. Meanwhile, many studies have explored the relationship between element concentration and fasting blood glucose (FBG), but the association between joint exposure to co-existing elements and FBG level has not been well understood. The study explored the associations of joint exposure to co-existing urinary elements with FBG level in a crosssectional design. 275 retired elderly people were recruited from Beijing, China. The questionnaire survey was conducted, and biological samples were collected. The generalized linear model (GLM) and twophase Bayesian kernel machine regression (BKMR) model were used to perform in-depth association analysis between urinary elements and FBG. The GLM analysis showed that Zn, Sr, and Cd were signi cantly correlated with the FBG level, under control potential confounding factors. The BKMR analysis demonstrated 8 elements (Zn, Se, Fe, Cr, Ni, Cd, Mn, and Al) had a higher in uence on FBG (Posterior inclusion probabilities >0.1). Further intensive analyses result of the BKMR model indicated that the overall estimated exposure of 8 elements was positively correlated with the FBG level and was statistically signi cant when all element concentrations were at their 65th percentile. Meanwhile, the BKMR analysis showed that Cd and Zn had a statistically signi cant association with FBG levels when other co-existing elements were controlled at different levels (25th, 50th or 75th percentile), respectively.The results of the GLM and BKMR model were inconsistent. The BKMR model could exibly calculate the joint exposure to co-existing elements, evaluate the possible interaction effects and nonlinear correlations. The meaningful conclusions were found that it was di cult to get by traditional methods. This study will provide methodological reference and experimental evidence for the association between joint exposure to co-existing elements and FBG in elderly people. Materials And Methods Research Design and Study PopulationA cross-sectional study design was implemented. The retired elderly people (aged above age 60 or more) recruited from the community-based in Beijing, in 2016. This study was approved by the Ethics Committee of the Institute of Basic Medical Sciences, Peking Union Medical College (Beijing, China), and all participants had signed informed consent before the interviews.Personal information was collected using a structured questionnaire through face-to-face communication by the investigator, including gender, age, smoking status, alcohol drinking status, and body mass index (BMI). Medical records were used to gather information on whether the subjects had diabetes and medication use related to blood sugar control.The vein blood (4 mL) was collected from each subject after overnight fasting and used to measure FBG. Blood samples were collected in vacuum tubes containing a thixotropic gel barrier (BD Vacutainer SST II, REF 367...

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Prenatal exposure to endocrine disrupting chemical mixtures and infant birth weight: A Bayesian analysis using kernel machine regression

Cited by 57 publications

References 73 publications

Associations between Exposures to Perfluoroalkyl Substances and Diabetes, Hyperglycemia, or Insulin Resistance: A Scoping Review

Associations between Exposures to Perfluoroalkyl Substances and Diabetes, Hyperglycemia, or Insulin Resistance: A Scoping Review

Sensitivity analysis for live birth bias in the Ulaanbaatar Gestation and Air Pollution Research study

The association between urine elements and fasting glucose levels in a community-based elderly people in Beijing

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