Occupational phthalate exposure and health outcomes among hairdressing apprentices
Bibliographic record
Abstract
We studied occupational exposure to phthalates from first-morning-void urine sample of hairdressing apprentices by HPLC-MS/MS analyses and association with health status. Metabolites of mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono ethyl phthalate (MEP), mono- n-butyl phthalate (MnBP) and mono-iso-butyl phthalate (MiBP) were detected in all urine samples, followed by metabolites mono(2-ethyl-5-oxohexyl) phthalate (MEOHP) and mono(2-etylhexyl) phthalate (MEHP) occurring in 97.06% and 86.76% of samples, respectively. Positive associations for females were observed between MnBP and fat-free mass index (FFMI) and age; negative associations were found between MEHP, MEOHP, MEHHP, sum of MEHP, MEHHP, MEOHP and vital capacity and also between MEHP and forced vital capacity (FVC of predicted value (PV)). Lengths of exposure were associated to MnBP, MEHHP, and MEP. We also documented positive associations between anthropometry (body mass index, waist-to-height ratio (WHtR), FFMI, fat mass index) and pulmonary function FVC% of PV for females and negative associations between WHtR, waist-to-hip ratio, FFMI and ratio of forced expiratory volume in 1 s (FEV 1 ) to FVC (FEV 1 /FVC). We assume that factors of occupational environment of hairdressing apprentices are affected by phthalates and resulted in negative outcomes in breathing mechanism and influence of body composition. Adipose tissue could play role as confounding factor in urine excretion of phthalates because of their lipid solubility and accumulation.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".