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Record W2973037307 · doi:10.1016/j.ijheh.2019.07.009

Evaluation of human biomonitoring data in a health risk based context: An updated analysis of population level data from the Canadian Health Measures Survey

2019· article· en· W2973037307 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Hygiene and Environmental Health · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsHealth CanadaUniversité de Montréal
FundersGovernment of CanadaPublic Health Agency of Canada
KeywordsBiomonitoringPerfluorooctanoic acidPerfluorooctaneContext (archaeology)PopulationEnvironmental healthRisk assessmentCotinineEnvironmental scienceEnvironmental chemistryChemistryMedicineBiologyNicotine

Abstract

fetched live from OpenAlex

In order to characterize exposure of the Canadian population to environmental chemicals, a human biomonitoring component has been included in the Canadian Health Measures Survey (CHMS). This nationally-representative survey, launched in 2007 by the Government of Canada, has measured over 250 chemicals in approximately 30,000 Canadians during the last decade. The capacity to interpret these data at the population level in a health risk context is gradually improving with the development of biomonitoring screening values, such as biomonitoring equivalents (BE) and human biomonitoring (HBM) values. This study evaluates recent population level biomonitoring data from the CHMS in a health risk context using biomonitoring screening values. Nationally representative biomonitoring data for fluoride, selenium, molybdenum, arsenic, silver, thallium, cyfluthrin, 2,4-dichlorophenoxyacetic acid (2,4-D), 3-phenoxybenzoic acid (3-PBA), chlorpyrifos, deltamethrin, bisphenol A, triclosan, acrylamide, cadmium, perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), bromoform, chloroform, benzene, toluene, xylene, ethylbenzene, styrene and tetrachloroethylene were screened as part as this study. For non-cancer endpoints, hazard quotients (HQs) were calculated as the ratio of population level concentrations of a specific chemical at the geometric mean and 95th percentile to the corresponding biomonitoring screening value. Cancer risks were calculated at the 5th, 25th, 50th, 75th and 95th percentiles of the population concentration using BEs based on a risk specific dose. Most of the chemicals analyzed had HQs below 1 suggesting that levels of exposure to these chemicals are not a concern at the population level. However, HQs exceeded 1 in smokers for cadmium, acrylamide and benzene, as well as in the general population for inorganic arsenic, PFOS and PFOA, 3-PBA and fluoride. Furthermore, cancer risks for inorganic arsenic, acrylamide, and benzene at most population percentiles of exposure were elevated (>10−5). Specifically, for inorganic arsenic in the general population, the HQ was 3.13 at the 95th percentile concentration and the cancer risk was 3.4 × 10−4 at the 50th percentile of population concentrations. These results suggest that the levels of exposure in the Canadian population to some of the environmental chemicals assessed might be of concern. The results of this screening exercise support the findings of previous risk assessments and ongoing efforts to reduce risks from exposure to chemicals evaluated as part of this study. Although paucity of biomonitoring screening values for several environmental contaminants may be a limitation to this approach, our assessment contributes to the prioritization of a number of chemicals measured as part of CHMS for follow-up activities such as more detailed characterization of exposure sources.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.130
GPT teacher head0.443
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it