An emerging double burden of disease: the prevalence of individuals with cardiovascular disease and cancer
Bibliographic record
Abstract
OBJECTIVE: Cardiovascular disease (CVD) and cancer are the two leading causes of death in the United States; at the same time, the number of survivors is increasing as therapies continue to improve. The primary objective of this study is to determine the prevalence and characteristics of individuals affected by both CVD and cancer. DESIGN AND SETTING: We conducted a prevalence study using the 2009 and 2010 national Behavioural Risk Factor Surveillance System population survey. Data from a random sample of individuals (aged 25-99 years) from all states were collected. All participants provided information regarding their CVD and cancer status. Multivariable regression identified associations between participants' characteristics and the prevalence of double disease burden. RESULTS: Amongst 442,964 study participants, the overall prevalence rates were 11% for CVD and 15% for cancer; 3% of participants reported being survivors of both CVD and cancer. The prevalence of CVD+cancer increased twofold by 65 years of age (odds ratio [OR] 2.4, 95% confidence interval [CI] 2.3-2.5) and doubled again at ≥75 years (OR 4.9, 95% CI 4.6-5.1) and was higher amongst men (OR 1.6, 95% CI 1.6-1.7), multiracial individuals (OR 1.8, 95% CI 1.5-2.0) and those without a high school diploma (OR 1.3, 95% CI 1.2-1.4). Amongst individuals with CVD, 25% also reported having cancer, whilst 19% of all cancer survivors reported having CVD. CONCLUSIONS: The prevalence of the double burden of disease increased with age; this is particularly important as the 'baby boomers' reach this high-risk age group. Future studies should explore potential common upstream or downstream mechanisms of CVD and cancer as well as public health strategies to cope with the double burden of disease.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".