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Record W4316924483 · doi:10.1289/isee.2022.o-op-078

Latent profiles of early life perfluoroalkyl substances exposure and body composition at age 12 years: The Health Outcomes and Measures of the Environment (HOME) Study

2022· article· en· W4316924483 on OpenAlexaff
Jordan R. Kuiper, Joseph M. Braun, Shelley Liu, Bruce P. Lanphear, Kim M. Cecil, Yingying Xu, Kimberly Yolton, Heidi J. Kalkwarf, Aimin Chen, Jessie P. Buckley

Bibliographic record

VenueISEE Conference Abstracts · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBody mass indexConfidence intervalPerfluorooctanoic acidMedicineBreastfeedingLean body massDemographyCotininePregnancyPediatricsChemistryInternal medicineBody weightNicotineBiologyEnvironmental chemistry

Abstract

fetched live from OpenAlex

Background and aim: We used latent profile analysis (LPA) to identify subpopulations with distinct perfluoroalkyl substances (PFAS) exposure trajectories during early life, and assess their associations with body composition at age 12 years. Methods: Among 390 mother-child dyads enrolled in the HOME Study, we quantified serum concentrations of perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorohexane sulfonate (PFHxS), and perfluorooctanesulfonic acid (PFOS) at least once during pregnancy (mothers) or at ages 3, 8, and 12 years (children). We measured child’s weight and height to calculate body mass index (BMI) and performed dual energy x-ray absorptiometry to measure fat mass index (FMI) and lean body mass index (LBMI) at age 12 years, and calculated age- and sex-standardized Z-scores for all measures. We performed an LPA of all log2-transformed PFAS measures, across all timepoints, using full information maximum likelihood to account for missing exposure data, and used likelihood ratio tests to assess model fit. We estimated adjusted associations (95% confidence intervals) for profile membership with body composition measures among 239 singletons with at least one outcome measure, and adjusted for parity, duration of breastfeeding (weeks), household income, and average maternal serum cotinine and blood lead concentrations during pregnancy. Results: A two-profile model fit best, with ~50% of the analytic sample in each profile. Relative to profile 1, geometric means of PFAS concentrations in profile 2 were higher at all timepoints, particularly at the 3-year visit. In adjusted analyses, membership in profile 2 was associated with a -0.49 (-0.94, -0.03) lower height Z-score, -0.46 (-0.89, -0.02) lower BMI Z-score, -0.22 (-0.58, 0.08) lower FMI Z-score, and -0.74 (-1.23, -0.24) lower LBMI Z-score. Conclusions: Using LPA to model longitudinal PFAS biomarkers, we found evidence that higher PFAS exposure during early life affects adolescent stature and body composition. Keywords: BMD, child, LPA, PFAS

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.269
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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