The association of drinking water quality and sewage disposal with Helicobacter pylori incidence in infants: the potential role of water-borne transmission
Bibliographic record
Abstract
The mode of transmission of Helicobacter pylori, a bacterium causing gastric cancer and peptic ulcer disease, is unknown although waterborne transmission is a likely pathway. This study investigated the hypothesis that access to treated water and a sanitary sewerage system reduces the H. pylori incidence rate, using data from 472 participants in a cohort study that followed children in Juarez, Mexico, and El Paso, Texas, from April 1998, with caretaker interviews and the urea breath test for detecting H. pylori infection at target intervals of six months from birth through 24 months of age. The unadjusted hazard ratio comparing bottled/vending machine water to a municipal water supply was 0.71 (95% confidence interval (CI): 0.50, 1.01) and comparing a municipal sewer connection to a septic tank or cesspool, 0.85 (95% CI: 0.60, 1.20). After adjustment for maternal education and country, the hazard ratios decreased slightly to 0.70 (95% confidence interval: 0.49, 1.00) and 0.77 (95% confidence interval: 0.50, 1.21), respectively. These results provide moderate support for potential waterborne transmission of H. pylori.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".