Maternal cured meat consumption during pregnancy and risk of paediatric brain tumour in offspring: potentially harmful levels of intake
Bibliographic record
Abstract
OBJECTIVE: To describe the relationship between specific levels of nitrite intake from cured meat consumption during pregnancy and the relative risk of paediatric brain tumours in the offspring. DESIGN: Exposure data were previously collected for a population-based case-control study of paediatric brain tumours; data on nitrite content were obtained by a comprehensive literature review of surveys of residual nitrite content in cured meats published in the USA and Canada. The level of nitrite intake for each mother was predicted by year of pregnancy based on survey results. Dose-response was evaluated both categorically and continuously using polynomial and quadratic spline regression. SETTING: The US west coast: Los Angeles County, the San Francisco-Oakland Bay Area and the Seattle-Puget Sound area. SUBJECTS: There were 540 cases diagnosed between 1984 and 1990 at ages varying from 0 to 19 years, and 801 controls frequency-matched by geographic area, age and birth year. RESULTS: In general, survey results suggest a trend of decreasing nitrite levels in cured meats over time. We observed a moderate increase in brain tumour risk in the offspring of mothers with relatively low levels of nitrite consumption from cured meats during pregnancy, and a two- to three-fold risk increase in offspring of mothers who consumed 3 mg day-1 nitrite from cured meats (about 125 g day-1 of cured meat consumption throughout the pregnancy). CONCLUSIONS: A substantial risk of paediatric brain tumour appears to be associated with relatively high levels of maternal cured meat consumption during pregnancy. A more scientifically valid approach than a literature review to estimate nitrite intake from cured meats and data from a large group of highly exposed subjects would be useful in determining potentially harmful levels.
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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".