Abstract 11579: Physical Activity versus Body Mass Index and Prevalence of Peripheral Arterial Disease
Bibliographic record
Abstract
Introduction: Physical activity and body mass index (BMI) are independently associated with peripheral arterial disease (PAD). However, their relative significance and combined association with PAD remain unclear. Hypothesis: We hypothesize that physical activity is associated with a lower odds of PAD across the BMI spectrum and that physical activity attenuates the prevalence of PAD in obese patients. Methods: We studied 3,250,350 U.S. adults who self-referred for PAD screening from 2003-2008 (Life Line Screening Inc., Independence, Ohio). Subjects completed a medical/lifestyle questionnaire. They were categorized into physically active or physically inactive based on their response in the questionnaire to whether they engaged in any type of vigorous leisure time exercise on a regular basis. All subjects were evaluated for PAD by ankle brachial index, with <0.9 considered abnormal. We divided participants into standardized BMI categories: underweight (< 18.5), normal weight (18.5-24.9), overweight (25-29.9), obese class I (30-34.9), class II (35-39.9), and class III (> 40). Multivariable logistic regression was used to estimate the odds of PAD among the BMI categories, based on physical activity. Results: Overall, mean age was 63.1 ± 10.5 years, 65.5% were female, and mean BMI was 27.7 ± 5.8 kg/m 2 . 41.5% were physically inactive. Average BMI was higher in the physically inactive versus physically active group (28.9 ± 6.3 vs. 27.0 ± 5.3, P<0.0001). Prevalence of PAD initially decreased and then increased with BMI and was attenuated with physical activity. Following multivariable adjustment, physical activity was independently associated with lower odds of PAD across the BMI spectrum (Table). Conclusion: Physical activity is associated with lower odds of PAD in underweight, normal weight, overweight and obese individuals. The higher prevalence of PAD with increasing BMI is attenuated with physical activity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".