Objectively Measured Physical Activity Reduces the Risk of Mortality among Brazilian Older Adults
Bibliographic record
Abstract
OBJECTIVES: Use of objectively measured physical activity (PA) in older adults to assess relationship between PA and risk of all-causes mortality is scarce. This study evaluated the associations of PA based on accelerometry and a questionnaire with the risk of mortality among older adults from a city in Southern Brazil. DESIGN: A cohort study. SETTING: Urban area of Pelotas, Southern Brazil. PARTICIPANTS: A representative sample of older adults (≥60 y) from Pelotas, enrolled in 2014. MEASUREMENTS: Overall physical activity (mg), light physical activity (LPA), and moderate to vigorous physical activity (MVPA) were estimated by raw accelerometer data. The International Physical Activity Questionnaire estimated leisure time and commuting PA. Hazard ratios (excluding deaths in the first 6 mo) stratified by sex were estimated by Cox regression analysis considering adjustment for confounders. RESULTS: From the 1451 older adults interviewed in 2014, 145 died (10%) after a follow-up of an average 2.6 years. Men and women in the highest tertile of overall PA had on average a 77% and 92% lower risk of mortality than their less active counterparts (95% confidence interval [CI] = .06-.84 and 95% CI = .01-.65, respectively). The highest tertile of LPA was also related to a lower risk of mortality in individuals of both sexes (74% and 91% lower risk among men and women, respectively). MVPA statistically reduced the risk of mortality only among women (hazard ratio [HR] = .30 and HR = .07 in the second and third tertiles). Self-reported leisure-time PA was statistically associated with a lower risk of mortality only among men. Women in the highest tertiles of commuting PA showed a lower risk of mortality than those in the reference group. CONCLUSION: Accelerometry-based PA was associated with a lower risk of mortality among Brazilian older adults. Older individuals should practice any type of PA. J Am Geriatr Soc 68:137-146, 2019.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".