Global obesity epidemic and rising incidence of early-onset cancers
Bibliographic record
Abstract
Background: Incidence of early-onset cancers at multiple organ sites has increased worldwide in recent decades. We investigated whether such increasing trends could be explained by trends in obesity. Methods: We obtained incidence data for 21 common cancers among 25-49-year-olds during 2000-2012 in 42 countries from the Cancer Incidence in Five Continents database. Nine cancers we examined have been classified as obesity-related by the International Agency for Research on Cancer. Estimates of overweight and obesity prevalence came from the Non-communicable Disease Risk Factor Collaboration. Using country-level data, we examined whether changes in the prevalence of overweight and obesity combined were correlated with changes in cancer incidence, after accounting for various time lags (0-15 years) between exposure and cancer diagnosis. To test the validity of our approach, we conducted negative control analyses (using non-obesity-related cancers as the outcome variable, and per-capita gross national income as the exposure variable), and sensitivity and supplemental analyses using alternative data streams or processing. Results: We found increased incidence for six of nine obesity-related and seven of twelve non-obesity-related cancers in 25-49-year-olds. These increases were more predominant in Western countries (particularly Australia, the USA, Canada, Norway, the Netherlands, and Lithuania). For four obesity-related cancers displaying increased incidence (colon, rectum, pancreas, kidney), changes in cancer incidence were positively correlated with changes in overweight and obesity prevalence. When accounting for a 15-year lag, the estimated correlation was 0.27 (95% confidence interval (CI) = -0.04, 0.53; P = 0.090) for colon cancer, 0.33 (95% CI = 0.02, 0.58; P = 0.036) for rectal cancer, 0.39 (95% CI = 0.08, 0.64; P = 0.018) for pancreatic cancer, and 0.22 (95% CI = -0.10, 0.50; P = 0.173) for kidney cancer. Similar correlations were found in the sensitivity and supplemental analyses. We did not find similar correlations with excess body weight for the non-obesity-related early-onset cancers, nor correlations with per-capita gross national income for any cancer types, in the negative control analyses. Conclusions: Worldwide increases in early-onset colon, rectal, pancreatic, and kidney cancers may have been partly driven by increases in excess body weight. The increases in other early-onset cancers, however, were likely driven by other factors deserving of further investigation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".