Associations of physical fitness and physical activity with sleep among middle-aged women
Bibliographic record
Abstract
BACKGROUND: Sleep is an important component of health. Sleep disturbances increase in women as they enter menopause. Physical activity has been associated with improved sleep among older populations. The purpose of this study was to determine if physical activity and/or physical fitness are associated with sleep quantity and quality in middle-aged women. METHODS: This study recruited 114 healthy women, aged 30-55 (43±8 y) from Saskatoon, Saskatchewan, from 2015-2019. Sleep quantity and quality were evaluated. Participants were classified on their aerobic fitness, based on estimated peak aerobic capacity, as high or low grip strength and, as active or inactive. RESULTS: The high aerobic fitness group had a greater mean sleep duration of 7.04±1.02 h compared to the low fit group 6.61±1.00 h after adjusting for age, Body Mass Index, waist circumference and menstrual status (P=0.01). The percentage of high aerobic fitness women who felt rested was greater than low aerobic fitness women (67±6% vs. 45±7%, P=0.03), after adjusting for age, Body Mass Index, waist circumference and menstrual status. Our study found a significant difference between women with higher aerobic fitness levels getting more sleep each night and feeling more rested. CONCLUSIONS: The continued examination of physical fitness and its relationship to sleep holds importance for women's health.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".