Associations between organochlorine pesticide mixtures and sex steroid hormones modified by age, gender and body mass index in the US 2011-2016: a quantile-based g-computation approach
Bibliographic record
Abstract
BACKGROUND AND AIM: Toxicological studies have shown adverse effects of organochlorine pesticides on reproductive function in animals; however, human studies are limited and mostly on a single pesticide. This study, therefore, examined the combined effects of lipid-adjusted serum concentrations of organochlorine pesticides and sex hormones in the US and to what extent these associations vary by age, gender, and body mass index (BMI). METHODS: We have used six years of repeated cross-sectional data that consist of three consecutive National Health and Nutrition Examination Survey (NHANES) cycles from 2011 to 2016. Serum concentrations of seven organochlorine pesticides (β-hexachlorocyclohexane, hexachlorobenzene, oxychlordane, p,p'-dichlorodiphenyltrichloroethene, p,p'-dichlorodiphenyltrichlorethane, trans-Nonachlor, and Mirex) were used as mixtures. The sex hormones considered were testosterone in nmol/L (n=798), estradiol in pmol/L (n=528 in), sex hormone-binding globulin -SHBG in nmol/L (n=497), and testosterone/estradiol in pg/mL (n=528). Quantile-based g-computation method was used for mixture effects, adjusting for potential confounders, and survey design. RESULTS: Results showed that lipid-adjusted pesticide mixtures had an inverse association with testosterone (β=-1.02, 95% CI: -1.81, -0.23; p= 0.012), estradiol (β= -663.16, 95% CI: -1232.09, -94.23, p= 0.022), SHBG (β= -14.62, 95% CI: -32.00, 2.77, p=0.100) and testosterone/estradiol (β= -3.06, 95% CI: -17.41, 11.29, p= 0.676). These associations were modified by gender with higher precisions for testosterone (Male: -1.90, 95% CI: -3.46, -0.35, pint= 0.003; Female: -0.79, 95% CI: -1.60, 0.02, p= 0.003). Moreover, age and BMI also significantly modified the effects of pesticide mixtures on sex hormones with higher precision in testosterone and estradiol. CONCLUSIONS: Our study suggests that pesticide mixture is inversely associated with sex hormones in the US population aged 12-80 years old, and these associations are modified by age, gender, and BMI. Intervention should be focused on reducing pesticide mixture exposures focusing on vulnerable communities. KEYWORDS: Pesticides; Mixture; Testosterone; Hormones; Quantile g-computation
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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) | 0.000 | 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".