BMI modifies the association between dietary intake and serum levels of PCBs
Bibliographic record
Abstract
Polychlorinated biphenyls (PCBs) are a group of persistent organic pollutants that are carcinogenic, neurotoxic, and endocrine disrupting in humans. Although diet is the primary source of exposure, there is no consensus on the association between dietary intake and serum PCBs. Additionally, body mass index (BMI) - with its inverse association with serum PCBs - may play a role in the association, which has never been studied. Therefore, we aimed to examine the association between dietary intake and serum levels of PCBs, and whether the association was modified by BMI. We used data from the National Health and Nutrition Examination Survey (NHANES) 2003-2004, including 1531 participants. We estimated dietary intake of PCBs using the 24-hour diet recall, USDA Food Composition Intake Database, and PCB content in foods from the Canada Total Diet Study. Serum PCBs were measured by high-resolution gas chromatography-mass spectrometry (HRGC-HRMS). We used linear regression to examine the associations of dietary PCB intake with serum levels of seven PCB congeners and six PCB metrics. Further, we explored the role of BMI in the associations. We found that participants who were older and non-Hispanic tended to have a higher serum level of ∑37-PCB. In addition, we observed positive associations between dietary intake and serum PCBs for: PCB 105, 118, 126, 138 + 158, and 153 (P value ranges 0.005-0.03); seven PCB indicators (P value = 0.03) and the sum of 37 PCBs (P value = 0.04). Furthermore, we observed an effect modification by BMI (P for interaction = 0.01 for ∑37-PCBs), with stronger associations in underweight or normal-weight individuals, and no association in overweight and obese individuals. In conclusion, within a cross-sectional, nationally representative sample of the US population, dietary PCB intake was positively associated with serum PCBs and the association was modified by BMI. Additional studies are warranted to replicate and confirm this effect modification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.012 | 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 teacher head, 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".