Malathion Exposure and the Incidence of Cancer in the Agricultural Health Study
Bibliographic record
Abstract
Malathion is the most common organophosphate insecticide applied in the United States, and while some studies suggest that it may be clastogenic, its carcinogenicity has not been demonstrated in rodents. However, malathion has been associated with non-Hodgkin's lymphoma in several epidemiologic studies. The authors investigated associations between malathion exposure and cancer among 19,717 pesticide applicators enrolled in the Agricultural Health Study between 1993 and 1997. Information on lifetime years and days per year of use and intensity of malathion exposure was obtained with self-administered questionnaires prior to the onset of any cancer. The average follow-up time was 7.5 years (1993-2002). Rate ratios and 95% confidence intervals were calculated using Poisson regression, adjusting for potential confounders. Overall, lifetime days of malathion use (top tertile of exposure, >39 days) was not associated with all cancers combined (rate ratio = 0.97, 95% confidence interval: 0.81, 1.15). The risk of non-Hodgkin's lymphoma was not associated with malathion use, although the number of cases was small. The risk of melanoma with more than 39 lifetime exposure-days was 0.39 (95% confidence interval: 0.14, 1.03). In summary, malathion exposure was not clearly associated with cancer at any of the sites examined. Although the rate ratios for melanoma were reduced, small numbers and lack of experimental evidence suggest that the observed reductions may have arisen by chance.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".