Participation by US Adults in Sports, Exercise, and Recreational Physical Activities
Bibliographic record
Abstract
BACKGROUND: Given the evidence that regular physical activity produces substantial health benefits, participation in sports, exercise, and recreation is widely encouraged. The objective of this study was to describe participation in sports, exercise, and recreational physical activities among US adults. METHODS: Data from 2 national surveys of respondents age 18 years and older were analyzed. Respondents to the American Time Use Survey (ATUS) from 2003 through 2005 (N=45,246) reported all activities on 1 randomly selected survey day. Respondents to the National Health and Nutrition Examination Survey (NHANES) from 1999 through 2004 (N=17,061) reported leisure-time physical activities in the 30 days before the interview. RESULTS: One-quarter of adults participated in any sport, exercise, or recreational activity on a random day, and 60.9% of adults participated in any leisure-time activity in the previous 30 days. The most common types of activities were walking, gardening and yard work, and other forms of exercise. The sports and recreational activities had typical durations of 1/2 to 3 hours per session, and the exercise activities typically lasted 1 hour or less. CONCLUSIONS: The prevalence of sports, exercise, and recreational physical activities is generally low among US adults; exercise is the most commonly reported type of 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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".