State Ranks of Incident Cancer Burden due to Overweight and Obesity in the United States, 2003
Bibliographic record
Abstract
OBJECTIVE: Given links between obesity and cancer, we estimated incident cancer burden due to overweight and obesity at the state level in the United States. METHODS AND PROCEDURES: Using state rankings by per capita burden of incident cancer cases diagnosed in 2003 that were related to overweight and obesity, we examined the frequency with which states ranked in the highest and lowest quintiles of weight-related burden for cancers of the postmenopausal breast, endometrium, kidney, colon, and prostate. In this study, data from the Behavioral Risk Factor Surveillance System (BRFSS), US Census, US Mortality Public Use Data Tapes, and National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) Program were used. RESULTS: Western states had the lowest weight-related cancer burden for both sexes. Iowa, South Dakota, and West Virginia had the highest burden for all three types of male cancers. West Virginia is the only state that ranked in the quintile of highest weight-related burden for all four cancers considered in women. DISCUSSION: For certain cancers, including endometrial, postmenopausal breast, and colon cancers, states with high burdens clustered in geographic regions, warranting further inquiry. Although state ranks for the total cancer burden and the prevalence of overweight and obesity correlated with state ranks for weight-related incident cancer burden, they often served poorly as its proxy. Such a finding cautions against simply targeting states with high overweight and obesity or high total burdens of cancers for which overweight and obesity are risk factors, as this approach may not reach areas of unrecognized burden.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".