Trajectories of Objectively Measured Physical Activity in Free-Living Older Men
Bibliographic record
Abstract
BACKGROUND: The steep decline in physical activity (PA) among the oldest old is not well understood; there is little information about the patterns of change in PA and sedentary behaviour (SB) in older people. Longitudinal data on objectively measured PA data can give insights about how PA and SB change with age. METHODS: Men age 70-90 yr, from a United Kingdom population-based cohort wore a GT3X accelerometer over the hip annually on up to three occasions (56%, 50%, and 51% response rates) spanning 2 yr. Multilevel models were used to estimate change in activity. Men were grouped according to achieving ≥150 min·wk of MVPA in bouts of ≥10 min (current guidelines) at two or three time points. RESULTS: A total of 1419 ambulatory men had ≥600 min wear time on ≥3 d at ≥2 time points. At baseline, men took 4806 steps per day and spent 72.5% of their day in SB, 23.1% in light PA, and 4.1% in moderate-to-vigorous PA (MVPA). Mean change per year was -341 steps, +1.1% SB, -0.7% light PA, and -0.4% MVPA each day (all P < 0.001). A total of 76.3% (n = 1083) never met guidelines ("stable low"), 7.9% (n = 112) consistently met guidelines ("stable high"), 8.2% (n = 116) stopped meeting guidelines by the last occasion ("decreasers"), and 4.9% (n = 69) started meeting guidelines by the last occasion ("increasers"). "Decreasers" spent 69.3% of each day in SB at baseline, which increased by 2% per year (P < 0.005), light activity remained at 23.3% (change, -0.2% per year; P = 0.4), and total MVPA decreased from 7.1% by -1.7% per year, (P < 0.001). The number of sedentary bouts >30 min increased from 5.1 by 0.1 per year (P = 0.02). CONCLUSIONS: Among older adults, the steep decline in total PA occurred because of reductions in MVPA, while light PA is relatively spared and sedentary time and long sedentary bouts increase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".