Drinking-water nitrate and cancer risk: A systematic review and meta-analysis
Bibliographic record
Abstract
Nitrate is an inorganic compound that occurs naturally in all surface and groundwater, although higher concentrations tend to occur only where fertilizers are used on the land. The regulatory limit for nitrate in public drinking water supplies was set to protect against infant methemoglobinemia, but other health effects were not considered. Risk of specific cancers and congenital disabilities may be increased when the nitrate is ingested, and nitrate is reduced to nitrite, which can react with amines and amides by nitrosation to form N-nitroso compounds which are known animal carcinogens. This study aims to evaluate the association between nitrate ingested through drinking water and the risk of developing cancers in humans. We performed a systematic review following PRISMA and MOOSE guidelines. A literature search was performed using PubMed, EMBASE, the Cochrane Library databases, Web of Science and Google Scholars in the time-frame from their inception to January 2020, for potentially eligible publications. STATA version 12.0 was used to conduct meta-regression and a two-stage meta-analysis. A total of 48 articles with 13 different cancer sites were used for analysis. The meta-regression analysis showed stomach cancer had an association with the median dosage of nitrate from drinking water (t = 3.98, p = 0.0001, and adjusted R-squared = 50.61%), other types of cancers didn’t show any association. The first stage of meta-analysis showed there was an association only between the risk of brain cancer & glioma (OR = 1.15, 95% CI: 1.06, 1.24) and colon cancer (OR = 1.11, 95% CI: 1.04, 1.17) and nitrate consumption in the analysis comparing the highest ORs versus the lowest. The 2nd stage showed there was an association only between the risk colon cancer (OR = 1.14, 95% CI: 1.04, 1.23) and nitrate consumption in the analysis comparing all combined higher ORs versus the lowest. This study showed that there is an association between the intake of nitrate from drinking water and a type of cancer in humans. The effective way of controlling nitrate concentrations in drinking water is the prevention of contamination (water pollution). Further research work on this topic is needed.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.037 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".