The Association between Obesity and Cancer Risk: A Meta-Analysis of Observational Studies from 1985 to 2011
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background. Cancer and cardiovascular diseases are the leading causes of mortality and morbidity worldwide. The purpose of this meta-analysis is to synthesize the evidence evaluating the association between obesity and 13 cancers shown previously to be significantly associated with obesity. Methods. Relevant papers from a previously conducted review were included in this paper. In addition, database searches of Medline and Embase identified studies published from the date of the search conducted for the previous review (January, 2007) until May, 2011. The reference lists of relevant studies and systematic reviews were screened to identify additional studies. Relevance assessment, quality assessment, and data extraction for each study were conducted by two reviewers independently. Meta-analysis was performed for men and women separately using DerSimonian and Laird's random effects model. Results. A total of 98 studies conducted in 18 countries from 1985 to 2011 were included. Data extraction was completed on the 57 studies judged to be of strong and moderate methodological quality. Results illustrated that obese men were at higher risk for developing colon (Risk Ratio (RR), 1.57), renal (1.57), gallbladder (1.47), pancreatic (1.36), and malignant melanoma cancers (1.26). Obese women were at higher risk for esophageal adenocarcinoma (2.04), endometrial (1.85), gallbladder (1.82), renal (1.72), pancreatic (1.34), leukemia (1.32), postmenopausal breast (1.25), and colon cancers (1.19). Conclusions. The results of this meta-analysis illustrate a significant, positive, and, for some cancers, strong association between obesity and cancer incidence. Given that approximately 23% of Canadians are obese, a significant proportion of cancer in Canada could be avoided if obesity was eliminated or significantly reduced.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it