Association between pesticide exposure and childhood leukaemia: a systematic literature review of epidemiological studies
Bibliographic record
Abstract
Introduction: Cancer is the leading cause of death for children and adolescents globally with 300,000 children aged 0-19 are diagnosed with cancer every year, mainly leukaemia, lymphomas and brain cancers. Like other causes of cancer, the difficulty arises because of multi-factorial aetiologies involving the interaction between genetic factors as well as environmental exposures. Aims: This study aimed to analyse published studies on the relationship between childhood leukaemia and exposures to pesticides. Methods: The search on the literature database Ovid-MEDLINE search strategy was conducted for the period from 1995 to 2014. The quality of non-randomised studies was assessed by using Newcastle Ottawa Scale (NOS). Results: Six studies investigated the relationship related to parental residential exposure and one study, showed an association between childhood leukaemia and maternal exposure. Two studies investigated the relationship to maternal residential exposure. Two studies reported an association between childhood leukaemia and parental occupational exposure. One study showed a positive association out of two studies that evaluated the association related to parental occupational and residential exposure. This review provides evidence of weak to modest association between childhood leukaemia and pesticides exposure in most of the studies. Conclusion: Most studies showed an association; however, the causation remains unexplained because of limitations such as potential bias, faulty study design and sample frame, lack of statistical power and also ascertainment of exposure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".