Prenatal exposure to insecticides and child cardiometabolic risk factors in the VHEMBE birth cohort
Bibliographic record
Abstract
Background: As part of malaria control programs, many countries spray dichlorodiphenyltrichloroethane (DDT) or pyrethroid insecticides inside dwellings in a practice called indoor residual spraying that results in high levels of exposure to local populations. Gestational exposure to these endocrine- and metabolism-disrupting chemicals may influence child cardiometabolic health. Methods: We measured the serum concentration of DDT and dichlorodiphenyldichloroethylene (DDE) and urinary concentration of pyrethroid metabolites (cis-DBCA, cis-DCCA, trans-DCCA, 3-PBA) in peripartum samples collected between August 2012 and December 2013 from 637 women participating in the Venda Health Examination of Mothers, Babies and their Environment (VHEMBE), a birth cohort study based in Limpopo, South Africa. We applied marginal structural models to estimate the relationship between biomarker concentrations and child-size (height and weight), adiposity (body mass index [BMI], body fat percentage, waist circumference) and blood pressure at 5 years of age. Results: Maternal concentrations of all four pyrethroid metabolites were associated with lower adiposity including reduced BMI z-scores, smaller waist circumferences, and decreased body fat percentages. Reductions in BMI z-score were observed only among children of mothers with sufficient energy intake during pregnancy (βcis-DCCA, trans -DCCA=−0.4, 95% confidence interval (CI) = −0.7,−0.1; pinteraction=0.03 and 0.04, respectively) but there was no evidence of effect modification for the other measures of adiposity. Maternal p,p’-DDT concentrations were associated with a reduction in body fat percentage (β = −0.4%, 95% CI = −0.8,−0.0). Conclusions: Gestational exposure to pyrethroids may reduce adiposity in children at 5 years of age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".