Exposure to polybrominated diphenyl ethers (PBDEs) during childhood and adiposity measures at age 8 years
Bibliographic record
Abstract
BACKGROUND: Animal studies suggest polybrominated diphenyl ethers (PBDEs) may be obesogens. However, epidemiologic studies investigating childhood exposure to PBDEs and adiposity are limited, with several reporting an inverse association. OBJECTIVES: To investigate associations between repeated childhood PBDE concentrations and adiposity measures at age 8 years. METHODS: We examined 206 children from the Health Outcomes and Measures of the Environment Study, a birth cohort in Cincinnati, OH (2003-2006). Serum PBDEs were measured at ages 1, 2, 3, 5, and 8 years. We used multiple imputation to estimate missing PBDE concentrations. At 8 years, we measured weight, height, waist circumference, and body fat percentage. We used multiple informant models to estimate age-specific associations between PBDEs and adiposity measures. RESULTS: We observed significant inverse associations between BDE-153 with all adiposity measures that became increasingly stronger with later childhood measurements. A 10-fold increase in BDE-153 at ages 1 and 8 years was associated with 2% (95% CI -3.9, -0.1) and 7% (95% CI -9.1, -4.7) lower body fat, respectively. No statistically significant associations were found with BDE-28, -47, -99, or -100. Child sex modified some associations; inverse associations between BDE-153 and body fat were stronger among boys, while positive and null associations were noted among girls. CONCLUSIONS: Childhood BDE-153 concentrations were inversely associated with adiposity measures and these associations became stronger as BDE-153 measurements were more proximal to adiposity measures. Inverse associations could be attributed to reverse causality arising from greater storage of PBDEs in adipose tissue of children with higher adiposity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".