Polybrominated Diphenyl Ether Concentrations in Human Breast Milk Specimens Worldwide
Bibliographic record
Abstract
BACKGROUND: Polybrominated diphenyl ethers (PBDEs) are a class of flame retardants of ubiquitous presence in numerous consumer products. PBDEs may impair neurodevelopment in infants. There is a lack of meta-analysis on PBDE concentrations in human breast milk worldwide. We aimed to summarize global research data on PBDE concentrations in human breast milk specimens in recent years. METHODS: We conducted a systematic review through PubMed search of original studies on PBDE concentrations in human individual breast milk specimens collected in the general population over the recent 15-year period (2000-2015) worldwide. RESULTS: A total of 49 eligible studies (total number of study subjects = 7,502) were identified. The pooled means (95% CI) of total PBDE concentration in breast milk (ng/g lipid) were 66.8 (44.7, 88.9) in North America, 2.6 (2.2, 3.1) in Europe, and 2.8 (2.4, 3.3) in Asia, respectively. The pooled means (95% CI) of median total PBDEs concentration in breast milk (ng/g lipid) were 40.0 (30.8-49.1) in North America, 1.9 (1.4-2.4) in Europe, and 2.2 (1.3-3.2) in Asia. The high concentrations of total PBDEs in breast milk in North America were mainly due to high concentrations of brominated diphenyl ether-47 (BDE-47), BDE-99, BDE-100, and BDE-153. There were too few studies from other continents (Africa, South America, and Oceania) for meaningful meta-analysis. CONCLUSION: Total PBDE concentrations in breast milk in the recent 15-year period were over 20 times higher in North America versus Asia or Europe, and comparable in Europe versus Asia. There is a need for more research data from other continents.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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; both teacher heads agree on what is shown here.
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".