Effect of Prenatal Phthalate Exposure on Childhood Atopic Dermatitis: a Systematic Review and a Meta-analysis of Birth Cohort Studies
Bibliographic record
Abstract
Abstract Background: The association between prenatal exposure to phthalate and childhood atopic dermatitis (AD) has been previously investigated; however, the results are inconsistent. We aimed to perform a systematic review and meta-analysis of birth cohort studies to investigate whether prenatal exposure to phthalate increases the risk of developing AD in children.Methods: We performed an electronic search of the MEDLINE, Embase, and Cochrane library databases. Studies were critically appraised, and meta-analyses were performed.Results: Among 129 articles identified, 11 studies met the eligibility criteria. Included studies originated from Europe (n = 5), USA (n = 4), and Asia (n = 2). The study sample size ranged from 147 to 1024 mother-child pairs. Quality assessment using the Newcastle–Ottawa scale of all studies had scores of six or greater. A meta-analysis of data from eight selected studies suggested that monobenzyl phthalate (MBzP) exposure was significantly associated with the risk of AD development (odds ratio 1.16, 95% confidence interval 1.04-1.31, I2 = 17.36%). However, AD development was not associated with other phthalate metabolites such as mono-(2-ethylhexyl) phthalate, monoethyl phthalate, mono-isobutyl phthalate, mono-n-butyl phthalate, and the sum of di-[2-ethylhexyl] phthalate on the development of AD (all P-values > 0.05).Conclusions: Our study suggests a positive association between prenatal exposure to MBzP and the development of childhood AD.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.042 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".