Factors Associated with Detection of Bromoxynil in a Sample of Rural Residents
Notice bibliographique
Résumé
In regions of intensive crop production residents may be exposed to herbicides through direct contact or environmental sources. The environmental herbicide exposures of rural populations and resultant potential health effects are not well understood. Epidemiologic studies or herbicides have focused on occupational exposures using, primarily, self-reported data (e.g., information on occupational and non-occupational herbicide use, agricultural practices and exposures, farm residence). Herbicide exposure characterization in epidemiologic research would be strengthened by the use of self-reported data and biological monitoring (e.g. measuring the herbicide parent compound or its metabolites in blood or urine specimens) to classify individual exposures, identify factors associated with exposure, and obtain integrated estimates of exposure. As both exposure metrics are susceptible to measurement error and some self-reported and biological monitoring data might not be correlated, a worthwhile first step is to identify self-reported data that are statistically associated with biological measures or exposure. This study use gas chromatography/mass spectrometry analysis to measure blood plasma concentrations of target herbicides in a sample of rural residents (men, women, and youths) of Saskatchewan, Canada, and identified factors, based on self-reported data, associated with detection. The questionnaire data and blood specimens were collected in February/March 1996 during winter (frozen soil and water and snow cover) conditions. Sixty-four of the 332 study participants (19.3%) had detectable levels of the herbicide bromoxynil although herbicide application in the region had not occurred for approximately 5 mo and bromoxynil has a relatively short environmental half-life. The prevalence of detection of other target herbicides (2,4-D, triallate, trifluralin, dicamba, fenoxaprop, MCPA, and ethalfluralin) varied from 0.3% to 2.7%. Self reported factors identified in the multiple-variable analysis as statistically significant predictors of bromoxynil detection included recent exposure to grain production as the main farming operation (statistically significant for producers and for non-farming family members of producers), a history of bromoxynil use, a history of having felt ill with a pesticide exposure and a history of pesticide spill on skin or clothing, with apparent gender differences in the relative importance of these factors. Detection of bromoxynil in this rural sample, 3-4 mo after freeze-up and winter snow cover, suggests either that bromoxynil is very slowly metabolized/excreted from the body or study participants were environmentally or occupationally exposed tothe herbicide during this period. Further research is needed to elucidate the pathways of exposure, biological half-life, and potentialhuman health effects of bromoxynil.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».