Time trend analysis of environmental contaminants in human Arctic populations
Bibliographic record
Abstract
Background:\nArctic Monitoring and Assessment Programme (AMAP) monitors persistent organic pollutant (POP) levels in the Arctic and assesses health effects related to them. Many of the POPs are regulated internationally, but still found in humans and biota. There are also new emerging contaminants, of which many are unregulated. Arctic populations present high contaminant concentrations compared to non-Arctic populations, with traditional food being the main source of exposure. Time trend analyses give information of effectiveness of international regulations, but also of warning of new emerging contaminants.\nObjectives: \nThe objective of this study is to analyze time trends of 24 contaminants or their combination in Arctic populations including USA, Canada, Iceland, Faroe Islands, Greenland, Sweden, Norway, and Finland. Legacy POPs analyzed in this study include organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs), whereas per- and polyfluoroalkyl substances (PFAS) and polybrominated biphenyl ethers (PBDEs) are new emerging contaminants included in this study.\nMethods:\nData included in this study is aggregated data presented in the AMAP Human Health in the Arctic 2021 assessment. AMAP assessments provide contaminant concentrations measured in maternal, adult and child blood and breast milk samples from different epidemiological studies conducted in the Arctic since 1980s. For some populations, where no new data was presented or it was presented as figures in AMAP 2021, AMAP 2009 and AMAP 2015 were used to collect data. Linear regression was used to assess time trends of the different POPs within different Arctic populations.\nResults: \nOverall decreasing time trends were observed for PCBs and OCPs in Arctic populations. Regulated PFAS showed declining trends, but increasing trends were observed for unregulated PFAS in certain populations. PBDEs showed decreasing or inconsistent trends.\nConclusions: \nDeclining trends are observed for legacy POPs, but the trends for new emerging contaminant are inconsistent. More focus is needed on biomonitoring the new emerging contaminants in the Arctic and their health effects.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".