Abstract PR008: Incidence of early onset colorectal, kidney, uterine and pancreatic cancer by county-level obesity prevalence in the U.S., 2010-2022
Bibliographic record
Abstract
Abstract Background: Obesity has been implicated as a potential driving factor in rising rates of several cancers in early onset age groups, including cancers of the colorectum, kidney, uterus and pancreas. We assessed whether obesity prevalence in U.S. counties was associated with rates and trends in rates of these cancers over time in 20-49-year-olds. Methods: We used cancer incidence data from 21 cancer registries in the Surveillance, Epidemiology, and End Results (SEER) program during 2010-2022. SEER-21 data were merged with data on the 2015 county-level prevalence of obesity from the CDC Diabetes Interactive Atlas, categorized into quintiles. Average annual percentage changes (AAPCs) in age-standardized rates (ASRs) during 2010-2022 were estimated with Joinpoint regression and tested for equality across quintiles of county-level obesity among 20-49-year-olds. In addition, rate ratios of recent ASRs of cancers of the colorectum, kidney, uterus, and pancreas were compared across quintiles of county-level obesity during 2018-2022. Results: During 2010-2022, ASRs of each obesity-related cancer increased significantly among 20-49-year-olds: colorectum (AAPC=2.47%; 95% confidence interval CI 2.12, 2.89), kidney (1.69%; 95%CI 1.02, 2.77), uterus (1.94%; 95%CI 1.50, 2.63), and pancreas (2.02%; 95%CI 1.74, 2.43). There were significant increases in AAPCs during 2010-2022 for each of these cancers in each quintile of county-level obesity, with the exception of kidney cancer rates in counties with the lowest obesity prevalence. There were no significant differences in the magnitudes of the AAPCs across county-level quintiles obesity for colorectal cancer (p=0.30). While AAPCs differed significantly across quintiles for kidney (p=0.05), uterine (p=0.03) and pancreatic cancers (p=0.01), AAPCs were greatest in the highest quintile of county-level obesity only for kidney cancer. However, during 2018-2022, ASRs in the highest quintile of county-level obesity were significantly higher than in the lowest quintile of county-level obesity for colorectal cancer (rate ratio [RR]=1.21; 95%CI 1.17-.25), pancreatic cancer (RR=1.25; 95%CI 1.15-1.35), uterine cancer (RR=1.08; 95%CI 1.03-1.13) and kidney cancer (RR=1.73; 95%CI 1.65-1.80). Conclusions: Higher county-level obesity prevalence in the U.S. was associated with higher ASRs of colorectal, kidney, uterine and pancreatic cancers in early onset age groups. Age-standardized incidence rates of these cancers increased during 2010-2022, regardless of county-level obesity. Future work should examine histologic subtypes and assess whether increases over time in county-level obesity prevalence is associated with a more rapid increase in colorectal, kidney, uterine and pancreatic cancer rates. Citation Format: Meredith Shiels, Anika Haque, Ruth Pfeiffer, Constanza Camargo, Megan Clarke, Brittny Davis Lynn, Eric Engels, Neal Freedman, Gretchen Gierach, Jonathan Hofmann, Rena Jones, Erikka Loftfield, Rashmi Sinha, Lindsay Morton, Stephen Chanock. Incidence of early onset colorectal, kidney, uterine and pancreatic cancer by county-level obesity prevalence in the U.S., 2010-2022 [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr PR008.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".