Daily step volume and intensity moderate the association of sedentary time and cardiometabolic disease risk in community-dwelling older adults: A cross-sectional study
Bibliographic record
Abstract
OBJECTIVE: To investigate the moderating effect of step count and peak cadence on the relationship of sedentary time and cardiometabolic disease risk in community-dwelling older adults. METHODS: This cross-sectional study included 248 older adults aged 60-80 years without cardiovascular disease (66.0 ± 4.6 years of age; 78 % females). Sedentary time, step count and peak cadence were measured by a hip-worn accelerometer for seven days. Peak cadence was defined as the average of 30 min of the day (but not necessarily consecutive) with the highest cadence (steps per minute) for all valid days. Cardiometabolic disease risk was defined using a sex-specific continuous metabolic syndrome score (cMetS). Sedentary time was used as an explanatory variable for cMetS and step count and peak cadence as moderators. The analyses were adjusted for known cardiometabolic disease risk factors and accelerometer wear time. The Johnson-Neyman technique was used to specify the value of moderator variables at which the significant relationship between sedentary time and cMetS disappears. RESULTS: Both step count (β = -0.186, P = 0.032) and peak cadence (β = -0.003, P = 0.007) showed a moderating effect on the relationship of sedentary time and cMetS. The association of sedentary time and cMetS was not statistically significant (p > 0.05) when step count or peak cadence exceed 5715 steps per day and 57 steps per minute, respectively. CONCLUSION: Steps per day and peak cadence moderate the association of sedentary time and cardiometabolic disease risk in older adults. Therefore, steps per day and peak cadence seem to offset the deleterious effects of sedentary time on cardiometabolic health in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".