How You Sleep May Impact How You Walk: A Pilot Cohort Study (Preprint)
Bibliographic record
Abstract
<sec> <title>BACKGROUND</title> Higher step width variability while walking is associated with poor physical function and falls. Sleep is an established modifiable risk factor for both gait and physical function impairments, but it has yet to be examined whether sleep is also related to step width variability. </sec> <sec> <title>OBJECTIVE</title> This study aimed to evaluate the cross-sectional associations between objectively measured sleep quality, using cardiopulmonary coupling (CPC) spectrograms, and step width variability during a preferred walking condition among middle aged and older adults. </sec> <sec> <title>METHODS</title> This study included 72 adults (mean age: 71 years, 51% female, 90% non-Hispanic White) who had ≥ 2 nights of objectively measured sleep (CPC via SleepImage ring) and completed a 10-meter walk while at preferred speed wearing inertial sensors (APDM Mobility Lab). Sleep measures included: sleep duration, efficiency, fragmentation, stability, apnea hypopnea index, time SpO2 levels < 90%, oxygen desaturation index, and respiratory disturbance index. Additional derived sleep variables were explored using LASSO models. Step width variability was defined by asymmetry of lateral step variability and categorized as medial (≤ -7.5 cm), minimal (within ± 7.5 cm; reference), or lateral displacement (≥ 7.5 cm). Multinomial logistic regression models adjusted for age, sex, race, education, and body mass index evaluated cross-sectional associations between sleep and step width variability categories. </sec> <sec> <title>RESULTS</title> We found that 1% higher sleep fragmentation was associated with 6% higher probability of step width variability ≥ 7.5 cm (95% CI: 1.01-1.11), while 1% higher sleep stability was associated with 5% lower probability of variability ≥ 7.5 cm (95% CI: 0.91-0.99), compared to minimal variability. From the LASSO models, we found that 1% higher sleep quality index, 1% higher REM sleep, 1-second shorter apnea duration, and 1-beat/minute slower mean heart rate were also associated with lower probability of lateral compared to minimal displacement. </sec> <sec> <title>CONCLUSIONS</title> Poor sleep quality was associated with higher step width variability among middle aged and older adults. This suggests that sleep may be a modifiable risk factor for maintaining postural stability while walking among middle aged and older adults. Future studies are needed to examine whether intervening on these sleep measures also lowers risk of falls. </sec>
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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 | 0.001 | 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".