Factors Associated with Detection of Bromoxynil in a Sample of Rural Residents
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".