Physical Activity and Acculturation Among Adult Hispanics in the United States
Bibliographic record
Abstract
Understanding the prevalence and demographic correlates of physical activity is important for public health and epidemiological research. This analysis examines the association between acculturation and physical activity in a large (approximately 5,000) sample of Hispanic adults from the 2000 National Health Interview Survey. Scores for eight questions concerning language use were summed to produce an acculturation index. Factor analysis indicated that these questions assessed a single underlying construct. Self-reported adherence to recommendations concerning leisure time physical activity increased from 22. 6% in the least acculturated tertile to 47% in the most acculturated tertile. In contrast, prevalence of walking or bicycling for errands decreased from 25.2 to 18.2%, and prevalence of standing or walking during most of the day decreased from 82.8 to 65.6% as acculturation increased. Thus, patterns of physical activity associated with leisure versus nonleisure time differed among Hispanics with varying acculturation levels. Alternatively, cultural factors may have differential effects on responses to questions concerning leisure and nonleisure time physical activity. In either case, assessing both types of activity is important for monitoring and understanding Hispanic health behaviors and interpreting epidemiological studies that involve physical activity in Hispanics.
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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) | 0.001 | 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".