The association between maternal urinary phthalate concentrations and blood pressure in pregnancy: The HOME Study
Bibliographic record
Abstract
BACKGROUND: Exposure to phthalates, a class of endocrine disrupting chemicals, is ubiquitous. We examined the association of urinary phthalate metabolite concentrations during pregnancy with maternal blood pressure and risk of pregnancy-induced hypertensive diseases. METHODS: We used data from the Health Outcomes and Measures of the Environment Study, a prospective birth cohort of low-risk pregnant women recruited between March 2003 and January 2006. We analyzed maternal urine samples collected at 16 and 26 weeks gestation for 9 phthalate monoester metabolites reflecting exposure to 6 phthalate diesters. Outcomes included maternal blood pressure at <20 and ≥ 20 weeks gestation and pregnancy induced hypertensive diseases (gestational hypertension, preeclampsia, eclampsia, and HELLP syndrome). RESULTS: Data were available for 369 women who gave birth to singleton, live-born infants without congenital anomalies. Of the phthalate metabolites evaluated, only mono-benzyl phthalate (MBzP) concentrations were significantly associated with maternal diastolic blood pressure at <20 weeks gestation. Women in the third MBzP tercile at 16 weeks gestation had diastolic blood pressure 2.2 (95% CI: 0.5-3.9) mm Hg higher at <20 weeks gestation and 2.8 (95% CI: 0.9-4.7) mm Hg higher at ≥ 20 weeks gestation compared to women in the first tercile. Compared to women in the first tercile, women in the top MBzP tercile at 16 weeks had an increased risk of developing pregnancy-induced hypertensive diseases (RR = 2.92, 95 % CI 1.15-7.41, p-value for trend = 0.01). MBzP concentrations at 26 weeks gestation were not as strongly associated with blood pressure at ≥ 20 weeks gestation or risk of pregnancy-induced hypertensive diseases. CONCLUSION: This study suggests that maternal urinary MBzP concentrations may be associated with increased diastolic blood pressure and risk of pregnancy-induced hypertensive diseases.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".