MétaCan
Menu
Retour à la cohorte
Enregistrement W2765522807 · doi:10.47339/ephj.2017.81

Follow-up study of private well users affected by groundwater arsenic in the Surrey-Langley area

2017· article· en· W2765522807 sur OpenAlexvenueaboutno aff
Douglas H. Gordon, Environmental Health BCIT School of Health Sciences, Marc Zubel, Blair Choquette, Helen Heacock

Notice bibliographique

RevueBCIT Environmental Public Health Journal · 2017
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueArsenic contamination and mitigation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésArsenicArsenic contamination of groundwaterGroundwaterToxicantEnvironmental healthContaminated groundwaterEnvironmental scienceWater wellArsenic toxicityToxicologyWater qualityArsenic poisoningContaminationMedicineEcologyEngineeringChemistryToxicityBiologyEnvironmental remediationInternal medicine

Résumé

récupéré en direct d'OpenAlex


 Background: Arsenic is a potent toxicant and Group 1 human carcinogen which occurs naturally in certain sediments and can contaminate groundwater. In the Surrey-Langley area of British Columbia, a 2007 study of private wells found that 43% of wells tested contained arsenic concentrations above the maximum acceptable concentration (MAC) prescribed in Health Canada’s Guidelines for Canadian Drinking Water Quality. The well owners who participated in the 2007 study were informed of the results and of effective treatment methods that would remove the arsenic contamination. This is a follow-up study that surveyed affected well users approximately 10 years later in order to identify whether the well users had subsequently made any water treatment or behavioral changes to improve the quality of their drinking water, and also to determine whether knowledge translation of the arsenic risk had been effective. Methodology: This study contacted and enrolled private well users who were living at properties which had previously been included in the 2007 study and, in 2007, were found to have arsenic levels above the MAC in the groundwater. Respondents who agreed to participate completed a questionnaire designed to identify what treatment methods or behavioral methods they use to mitigate the risk posed by arsenic contamination. Pre-treatment and post-treatment samples of their drinking water were collected and the arsenic concentrations were analyzed. The effectiveness of treatment devices for arsenic removal was evaluated. The groundwater arsenic concentrations from approximately 10 years apart were compared to identify if arsenic levels had changed. Results: Of the 42 properties that participated in the 2007 study and had groundwater arsenic levels above the MAC, 17 participated in this follow-up study. 14 of the participants also took part in the 2007 study 10 years ago. 79% of participants had not known prior to taking part in the 2007 study that their drinking water contained arsenic levels above the MAC. All 79% then either installed reverse osmosis treatment devices to remove arsenic from their drinking water, or switched to using bottled water for drinking. This indicates that knowledge translation of the health risk was effective. Of the 8 properties using treatment devices rather than bottled water, to mitigate the arsenic risk, 2/8 (25%) were ineffective at reducing arsenic. In addition, arsenic groundwater concentrations were not found to have changed significantly in 10 years (p = 0.11). Conclusion: Participation in the 2007 study was viewed as useful and informative by participants. Knowledge translation of the health risk and the need for risk mitigation was effective, but 25% of treatment devices were found to be ineffective at removing arsenic from drinking water. These results suggests that further knowledge translation of the need for routine testing for arsenic in post-treated drinking water may be beneficial to affected private well users.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,037
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,032
Tête enseignante GPT0,265
Écart entre enseignants0,233 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueBCIT Environmental Public Health JournalMême sujetArsenic contamination and mitigationTravaux en français237 207