Macronutrients, vitamins and minerals intake and risk of esophageal squamous cell carcinoma: a case-control study in Iran
Bibliographic record
Abstract
BACKGROUND: Although Iran is a high-risk region for esophageal squamous cell carcinoma (ESCC), dietary factors that may contribute to this high incidence have not been thoroughly studied. The aim of this study was to evaluate the effect of macronutrients, vitamins and minerals on the risk of ESCC. METHODS: In this hospital-based case-control study, 47 cases with incident ESCC and 96 controls were interviewed and usual dietary intakes were collected using a validated food frequency questionnaire. Data were modeled through unconditional multiple logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI), controlling for age, sex, gastrointestinal reflux, body mass index, smoking history (status, intensity and duration), physical activity, and education. RESULTS: ESCC cases consumed significantly more hot foods and beverages and fried and barbecued meals, compared to the controls (p < 0.05). After adjusting for potential confounders, the risk of ESCC increased significantly in the highest tertiles of saturated fat [OR:2.88,95%CI:1.15-3.08], cholesterol [OR:1.53, 95%CI: 1.41-4.13], discretionary calorie [OR:1.51, 95%CI: 1.06-3.84], sodium [OR:1.49,95%CI:1.12-2.89] and total fat intakes [OR:1.48, 95%CI:1.09-3.04]. In contrast, being in the highest tertile of carbohydrate, dietary fiber and (n-3) fatty acid intake reduced the ESCC risk by 78%, 71% and 68%, respectively. The most cancer-protective effect was observed for the combination of high folate and vitamin E intakes (OR: 0.02, 95%CI: 0.00-0.87; p < 0.001). Controls consumed 623.5 times higher selenium, 5.48 times as much β-carotene and 1.98 times as much α-tocopherol as the amount ESCC cases consumed. CONCLUSION: This study suggests that high intake of nutrients primarily found in plant-based foods is associated with a reduced esophageal cancer risk. Some nutrients such as folate, vitamin E and selenium might play major roles in the etiology of ESCC and their status may eventually be used as an epidemiological marker for esophageal cancer in Iran, and perhaps other high-risk regions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".