Visceral obesity and incident cancer and cardiovascular disease: An integrative review of the epidemiological evidence
Bibliographic record
Abstract
Evidence shows a strong relationship between obesity, cancer and cardiovascular disease (CVD) risk. However, there is not enough evidence of the role of visceral obesity on both CVD and cancer. Visceral obesity may be more pro-oncogenic than total body fat. Therefore, it is important to know whether abdominal obesity can lead to both CVD and cancer. The present integrative review aimed at evaluating epidemiological evidence on the potential connection of visceral obesity in the occurrence of cancer and CVD. The following databases were searched: SCOPUS, PubMed, Science Direct, Lilacs, SciELO, Google Scholar, Web of Science, Scopus and ProQuest. The presence of visceral obesity can increase the risk of some specific cancer types, but there is controversial evidence about CVD risk based on sex-specific and ageing analyses. There is enough evidence that visceral obesity increases the risk of colorectal, pancreatic and gastro-oesophageal cancer. However, for some types of cancer such as breast, endometrial and renal, visceral obesity is a risk only in post-menopausal women. Regarding prostate cancer, the evidence is controversial. Despite the risk of visceral obesity being consistently associated with CVD in adults, this association disappears in sex-specific and older adults analyses. Moreover, in older adults, the results are controversial due to the use of different measures such as waist circumference and visceral adipose tissue. However, the evidence showing visceral obesity as a risk factor to CVD remains controversial. Sex differences, ageing and body mass index (BMI) category can potentially modify this association. Therefore, further epidemiological studies with analyses stratified by sex and samples including older adults aged 65 and older are 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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".