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Record W2516568009 · doi:10.1289/ehp.1308005

Prenatal and Postnatal Exposure to Persistent Organic Pollutants and Infant Growth: A Pooled Analysis of Seven European Birth Cohorts

2015· article· en· W2516568009 on OpenAlexaff
Nina Iszatt, Hein Stigum, Marc-André Verner, Richard White, Eva Govarts, Ľubica Palkovičová, Greet Schoeters, T. Trnovec, Juliette Legler, Fabienne Pelé, Jérémie Botton, Cécile Chevrier, Jürgen Wittsiepe, Ulrich Ranft, Stéphanie Vandentorren, Monika Kasper-Sonnenberg, Claudia Klümper, Nynke Weisglas‐Kuperus, Anuschka Polder, Merete Eggesbø

Bibliographic record

VenueEnvironmental Health Perspectives · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversité de Montréal
FundersNational Cancer Institute
KeywordsPrenatal exposureMedicineEnvironmental healthPregnancyPollutantCohort studyObstetricsPediatricsPhysiologyGestationBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Abstract Background Infant exposure to persistent organic pollutants (POPs) may contribute to obesity. However, many studies so far have been small, focused on transplacental exposure, used an inappropriate measure to assess postnatal exposure through breastfeeding if any, or did not discern between prenatal and postnatal effects. Objectives We investigated prenatal and postnatal exposure to POPs and infant growth (a predictor of obesity). Methods We pooled data from seven European birth cohorts with biomarker concentrations of polychlorinated biphenyl 153 (PCB-153) (n = 2,487), and p,p´-dichlorodiphenyldichloroethylene (p,p´-DDE) (n = 1,864), estimating prenatal and postnatal POPs exposure using a validated pharmacokinetic model. Growth was change in weight-for-age z-score between birth and 24 months. Per compound, multilevel models were fitted with either POPs total exposure from conception to 24 months or prenatal or postnatal exposure. Results We found a significant increase in growth associated with p,p´-DDE, seemingly due to prenatal exposure (per interquartile increase in exposure, adjusted β = 0.12; 95% CI: 0.03, 0.22). Due to heterogeneity across cohorts, this estimate cannot be considered precise, but does indicate that an association with infant growth is present on average. In contrast, a significant decrease in growth was associated with postnatal PCB-153 exposure (β = –0.10; 95% CI: –0.19, –0.01). Conclusion To our knowledge, this is the largest study to date of POPs exposure and infant growth, and it contains state-of-the-art exposure modeling. Prenatal p,p´-DDE was associated with increased infant growth, and postnatal PCB-153 with decreased growth at European exposure levels. Citation Iszatt N, Stigum H, Verner MA, White RA, Govarts E, Palkovicova Murinova L, Schoeters G, Trnovec T, Legler J, Pelé F, Botton J, Chevrier C, Wittsiepe J, Ranft U, Vandentorren S, Kasper-Sonnenberg M, Klümper C, Weisglas-Kuperus N, Polder A, Eggesbø M, OBELIX. 2015. Prenatal and postnatal exposure to persistent organic pollutants and infant growth: a pooled analysis of seven European birth cohorts. Environ Health Perspect 123:730–736; http://dx.doi.org/10.1289/ehp.1308005

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)0.011
metaresearch head score (Gemma)0.010
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 score0.015
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.009
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.000
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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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

Citations127
Published2015
Admission routes1
Has abstractyes

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