Associations in physical activity and sedentary behaviour among the immigrant and non-immigrant US population
Bibliographic record
Abstract
Background Immigrants are at a higher risk of poor mental and physical health. Regular participation in physical activity (PA) and low levels of sedentary time are beneficial for both these aspects of health. The aim was to investigate levels and trends in domain-specific PA and sedentary behaviour in the US. immigrant compared with non-immigrant populations. Methods From the 2007–2016 National Health and Nutrition Examination Survey (NHANES), a total of 25 142 adults (≥18 years) were included in this analysis. PA and sedentary behaviour time were assessed by a questionnaire. Results Transit-related PA showed downward linear trends in young immigrant adults (p trend=0.006) and middle-aged non-immigrant adults (p trend=0.009). We found significant upward linear trends in sedentary behaviour for both immigrants and non-immigrants across all age groups. For sitting watching TV or videos ≥2 hours/day, there was a downward linear trend in young immigrant adults (p trend=0.009). For computer use ≥1 hours/day, an upward linear trend in older non-immigrants was found (p trend=0.024). Young immigrants spent 37.5 (95% CI −55.4 to −19.6) min less than non-immigrants on recreational PA per week. Also, older immigrants spent 23.5 (95% CI 1.5 to 45.6) and 22.5 (95% CI 5.9 to 39.0) min/week more than non-immigrants on recreational PA and transit-related PA, respectively. Last, young and middle-aged immigrants spent 37.6 (95% CI −68.2 to −7.0) and 37.6 (95% CI −99.7 to −9.7) min/day less than non-immigrants on sedentary behaviour, respectively. Conclusion Overall, levels of recreational PA were stable, yet the transit-related PA declined coupled with an increase in sedentary behaviour. US. immigrants exhibit higher levels of transit-PA, lower levels of leisure-time PA and lower levels of sedentary behaviour, in some age groups.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".