Exposure Load: Using biomonitoring data to quantify multi-chemical exposure burden in a population
Notice bibliographique
Résumé
People are often concurrently exposed to numerous chemicals. Here we sought to leverage existing large biomonitoring datasets to improve our understanding of multi-chemical exposures in a population. Using nationally-representative data from the 2012-2015 Canadian Health Measures Survey (CHMS), we developed Exposure Load, a metric that counts the number of chemicals measured in people above a defined concentration threshold. We calculated Exposure Loads based on five concentration thresholds: the analytical limit of detection (LOD) and the 50th, 75th, 90th and 95th percentiles. Our analysis considered 44 analyte biomarkers representing 26 chemicals from the 2012-2015 CHMS; complete biomarker data were available for 1858 participants aged 12-79 years following multiple imputation of results that were missing due to sample loss. Chemicals may have one or more biomarkers, and for the purposes of Exposure Load calculation, participants were considered to be exposed to a chemical if at least one biomarker was above the threshold. Distributions of Exposure Loads are reported for the total population, as well as by age group, sex and smoking status. Canadians had an Exposure Load between 9 and 21 (out of 26) when considering LOD as the threshold, with the majority between 13 and 18. At higher thresholds, such as the 95th percentile, the majority of Canadians had an Exposure Load between 0 and 3, although some people had an Exposure Load of up to 15, indicating high exposures to multiple chemicals. Adolescents aged 12-19 years had significantly lower Exposure Loads than adults aged 40-79 years at all thresholds and adults aged 20-39 years at the 50th and 75th percentiles. Smokers had significantly higher Exposure Loads than nonsmokers at all thresholds except the LOD, which was expected given that tobacco smoke is a known source of certain chemicals included in our analysis. No differences in Exposure Loads were observed between males and females at any threshold. These findings broadly suggest that Canadians are concurrently exposed to many chemicals at lower concentrations and to fewer chemicals at high concentrations. They should assist in identifying vulnerable subpopulations disproportionately exposed to numerous chemicals at high concentrations. Future work will use Exposure Loads to identify prevalent chemical combinations and their link with adverse health outcomes in the Canadian population. The Exposure Load concept can be applied to other large datasets, through collaborative efforts in human biomonitoring networks, in order to further improve our understanding of multiple chemical exposures in different populations.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,027 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».