Metabolic Syndrome and Prevalent Any-site, Prostate, Breast and Colon Cancers in the U.S. Adult Population: NHANES 1999-2010
Bibliographic record
Abstract
Background: Metabolic Syndrome (MetS) is associated with elevated risk of diabetes, cardiovascular disease, and premature mortality.To date, however, the association between MetS and obesity-related cancers has not been systematically assessed within a population-based sample.Methods: In order to quantify the association between MetS and its components on any-site, breast, prostate, and colon cancers, data from the U.S. NHANES 1999-2010 (n=15 141, 18-85 years) were used.Results: In general, the prevalence of MetS was higher amongst those with a self-reported history of cancer.Although MetS, its individual components, and total number of components were positively related to odds of any-site, breast, prostate, and colon cancers, this effect was almost entirely eliminated after adjustment for age.In age-adjusted models, elevated blood glucose was associated with higher odds of prostate (OR: 1.67, 95% CI: 1.08-2.56)and colon cancer (OR: 1.60, 95% CI: 1.02-2.53),and a protective effect of low HDL cholesterol on prostate cancer (OR: 0.64, 95% CI: 0.43-0.94).Further adjustment for sex, ethnicity, income, education, smoking, alcohol, and recreational/ leisure-time physical activity had only minimal influence on these associations.In multivariable analyses, no uniform linear trends were observed between the number of MetS components and site-specific cancers.Conclusion: After accounting for covariates, no consistent association between MetS and any-site, breast, prostate, or colon cancer was observed.Further prospective study is necessary to confirm and extend our understanding of the role of age and other risk factors on the inter-relationship between metabolic health and cancer.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".