Levels of persistent organic pollutants (POPs) in a coastal northern Norwegian population with high fish-liver intake
Bibliographic record
Abstract
Recent research has again raised the issue regarding the potential health effects of long term exposure to persistent organic pollutants (POPs) in the context of a risk-benefit analysis. There remains clear evidence of the beneficial effects of fish consumption on public health and in particular fatty fish with its essential fatty acids. In addition to providing fatty acids, fish fat constitutes an essential source to vitamin D for the northern Norwegian population. Norwegian Food Control Authorities have recommended that children and women of childbearing age should not consume fish liver due to the risk associated with high intake of POPs. The aim of this study was to assess the influence of fish liver intake on the levels of PCBs and chlorinated pesticides in a rural coastal community (n = 31) in northern Norway, applying a cross-sectional design. The geometric mean plasma levels of sum of PCBs (14 congeners) and p,p'-DDE was found to be 558 microg kg(-1) lipids and 179 microg kg(-1) lipids, respectively. These levels were not significantly affected by the reported intake of fish liver, when age and gender were considered. Age in particular, but also gender were significant predictors for most compounds. When merging the dataset with an urban population with considerable lower intake of fish liver, the intake of cod liver still did not significantly affect the levels of PCBs and p,p'-DDE when adjusted for age and gender. Age and gender remain the strongest predictors of plasma levels of POPs in this study whereas fish liver intake was not significantly associated with the POPs.
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.
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 | 0.001 |
| Science and technology studies | 0.001 | 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".