Exposure to Polybrominated Diphenyl Ethers and Phthalates in China: A Disease Burden and Cost Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing evidence indicates that endocrine-disrupting chemicals (EDCs) cause a variety of adverse health outcomes and contribute to substantial disease burden. This study summarized the exposure status of polybrominated diphenyl ethers (PBDEs) and phthalates (PAEs) in China and evaluated the disease burden attributable to PBDEs and PAEs in 2015. The results showed that PBDE and PAE concentrations were higher in coastal areas. The disease burden attributable to PBDEs was 0.77 million cases, and the economic costs were CNY 18.92 billion. Meanwhile, 3.02 million individuals suffered from diseases attributable to PAEs, and the economic costs were CNY 49.20 billion. The economic burden caused by PBDEs and PAEs accounted for 0.28% and 0.72% of China's Gross Domestic Product (GDP) in 2015, respectively. When comparing China's results from 2010, it was determined that the GDP ratio of economic costs caused by PAEs in 2015 (0.72%) was lower than in 2010 (1.42%). Finally, compared with the results of the European Union and North America, the GDP ratios of economic costs caused by PAEs in 2015 were 0.19% in Canada (lower than China), 0.29% in the United States (lower than China), and 1.44% in the European Union (higher than China). This study provides important reference values for China's health governance, and further research should be conducted in the future.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it