Body mass index of North American participants at the World Masters Games
Bibliographic record
Abstract
WMG (World Masters Games) athletes have either pursued a physically active lifestyle for an extended period of time or have initiated exercise/sport in later life. This unique cohort of middle-aged to older-aged adults remains relatively uninvestigated with regards to various measures of health. With a need for multifaceted solutions to the obesity epidemic, investigating special populations such as those competing in sport at older ages may further the understanding of the nexus between aging, physical activity and obesity. This study aims to investigate the BMI (body mass index) of North American WMG competitors with respect to national health guidelines and demographics. An online survey was utilized to collect demographic information from athletes competing at the Sydney WMG. BMI was derived using the participant’s height and body mass. A total of 928 (46.7% male, 53.3% female) participants from Canada and the United States (age: 52.6 ±9.8 years) completed the survey. The top 5 sports in which participants competed were football (25.6%), track/field (15.4%), swimming (8.4%), volleyball (8.2%), and softball (7.8%). Female and male BMI (kg/m2 ) across all sports were: > 30 (obese: 13.9%), 25-29.9 (overweight: 34.1%), 18.5-24.9 (normal: 50.3%), and <18.5 (underweight: 1.7%). Data indicated that BMI was a health risk factor for 13.9% of the participants and a developing risk factor for 34.1% of the participants. Analysis demonstrated a significantly reduced (P < 0.05) classification of obesity of the North American WMG competitors when compared to Canadian and United States national populations. It is believed that adherence to exercise improves indices of general health. A key index of health (obesity) is significantly lower in incidence for North American WMG competitors when compared to Canadian and US populations.
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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 | 0.001 |
| 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".