Cumulative Health Risk from Exposure Load (CHREL): Looking at multi-chemical exposures through the lens of biomonitoring guidance values
Bibliographic record
Abstract
Exposure load (EL) is an indicator of multiple chemical exposures based on human biomonitoring data. We used EL methodology and human biomonitoring health-based guidance values (HB2GVs) as exposure thresholds to create a new metric called Cumulative Health Risk from Exposure Load (CHREL). HB2GVs are derived by calculating the concentration of a biomarker consistent with a health protective exposure guidance value. CHREL analysis was conducted using Canadian Health Measures Survey (CHMS) cycle 3 and 4 biomonitoring data. Based on 18 chemicals, more than half of the Canadian population had an estimated CHREL TOTAL of 1 or more, indicative of chemical exposures potentially above selected exposure guidance values. Females had a significantly lower CHREL TOTAL compared to males, 12–19 year olds had a lower CHREL TOTAL compared to older age groups (significant compared to 40–59 year olds), and nonsmokers had a significantly lower CHREL TOTAL than smokers. Small segments of the population had a CHREL LIVER or a CHREL NERV of 1 or more, indicating exposures potentially above guideline levels for chemicals affecting the liver or nervous system. CHREL CANC was calculated based on 6 chemicals with HB2GVs derived for cancer endpoints. At the 10 −5 risk level, most people had an estimated CHREL CANC of 3, indicative of multiple chemicals that may exceed negligible cancer risk. The most important contributors to exposures above HB2GVs were inorganic arsenic, mercury, acrylamide, xylenes, benzene and triclosan. Keeping certain assumptions, uncertainties and limitations in mind, the CHREL indicator can be used to obtain a picture of potential cumulative health risks from combined chemical exposures in a population, and as a comparative measure between subpopulations, including vulnerable subgroups. • We created a metric called Cumulative Health Risk from Exposure Load (CHREL). • CHREL is an indicator of potential health risks from multiple chemical exposures. • CHREL uses human biomonitoring guidance values as exposure thresholds. • Females had lower CHREL than males; adolescents had lower CHREL than older adults. • Nonsmokers had lower CHREL than people who smoke.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".