Predicting Sleep Quality Based on Metabolic, Body Composition, and Physical Fitness Variables in Aged People: Exploratory Analysis with a Conventional Machine Learning Model
Abstract
1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Sample
2.3. Procedures
2.3.1. Anthropometrics, Body Composition, and Metabolic Variables
2.3.2. Arterial Blood Pressure, Resting Heart Rate and Sleep Quality
2.3.3. Handgrip Strength
2.3.4. Functional Fitness
2.3.5. Relative Lower Limb Muscle Power
2.4. Statistical Analysis
3. Results
3.1. Descriptives
3.2. Sleep Quality Comparisons
3.3. Associative Analysis and Machine Learning
4. Discussion
4.1. Sleep Quality Comparisons
4.2. Associative Analysis and Machine Learning
4.3. Psychophysiological Remarks
4.4. Strengths, Limitations and Future Studies
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variables | Good Sleep Quality (n = 15) | Poor Sleep Quality (n = 17) | Sleep Quality Comparison | ||
---|---|---|---|---|---|
Mean (±SD) | Mean (±SD) | t | p | η2 | |
Age (yo) | 69.47 (±5.99) | 73.24 (±7.34) | −1.724 | 0.095 | 0.456 |
Mass (kg) | 64.73 (±11.87) | 67.44 (±9.25) | −0.724 | 0.474 | 0.002 |
Stature (cm) | 157.49 (±4.30) | 159.16 (±5.58) | −0.938 | 0.356 | 0.013 |
Rest Heart rate (Bpm) | 71.82 (±6.26) | 72.38 (±8.91) | 1.742 | 0.197 | 0.411 |
Hand grip (kg) | 21.67 (±8.61) | 26.12 (±5.46) | 0.411 | 0.526 | 0.002 |
Arm curl (Repetition) | 21.29 (±4.75) | 23.30 (±4.00) | −0.204 | 0.840 | 0.408 |
Waist circumference (cm) | 88.00 (±10.23) | 89.05 (±9.34) | −1.766 | 0.088 | 0.178 |
Hip circumference (cm) | 101.53 (±9.68) | 99.62 (±4.86) | −1.302 | 0.203 | 0.634 |
5TSTS (seconds) | 7.69 (±1.00) | 6.75 (±1.08) | −0.303 | 0.764 | 0.164 |
CS30 (repetitions) | 21.14 (±4.05) | 22.84 (±3.30) | 0.691 | 0.497 | 0.138 |
TUG (seconds) | 5.96 (±1.04) | 5.36 (±0.67) | 2.564 | 0.016 * | 0.476 |
Seat and Reach (cm) | −2.14 (±7.39) | −0.15 (±9.92) | −1.309 | 0.200 | 0.733 |
Back Stretch (cm) | −5.21 (±8.40) | −14.49 (±11.40) | 1.957 | 0.060 | 0.188 |
2MST (Repetitions) | 180.52 (±22.38) | 186.69 (±35.45) | −0.637 | 0.529 | 0.453 |
Total Fat (kg) | 20.94 (±7.33) | 20.05 (±5.27) | 2.592 | 0.015 * | 0.239 |
Total Fat (%) | 32.13 (±6.79) | 29.93 (±5.78) | −0.580 | 0.566 | 0.148 |
Lean Mass (kg) | 41.23 (±5.60) | 44.54 (±6.37) | 0.990 | 0.330 | 0.337 |
Lean Mass (%) | 63.73 (±7.54) | 64.88 (±7.49) | −1.552 | 0.131 | 0.157 |
Body Water (%) | 47.95 (±4.70) | 49.33 (±3.83) | −0.430 | 0.670 | 0.431 |
Visceral Fat | 7.47 (±2.23) | 8.29 (±3.42) | −0.911 | 0.369 | 0.344 |
MET [KJ] | 5405.20 (±709.26) | 5648.75 (±599.06) | −0.792 | 0.435 | 0.000 |
MET [Kcal] | 1411.87 (±521.07) | 1477.87 (±463.82) | −0.379 | 0.707 | 0.438 |
Total Sleep | 6.13 (±1.46) | 3.35 (±0.61) | 6.882 | <0.001 * | 0.675 |
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Forte, P.; Encarnação, S.G.; Teixeira, J.E.; Branquinho, L.; Barbosa, T.M.; Monteiro, A.M.; Pecos-Martín, D. Predicting Sleep Quality Based on Metabolic, Body Composition, and Physical Fitness Variables in Aged People: Exploratory Analysis with a Conventional Machine Learning Model. J. Funct. Morphol. Kinesiol. 2025, 10, 337. https://doi.org/10.3390/jfmk10030337
Forte P, Encarnação SG, Teixeira JE, Branquinho L, Barbosa TM, Monteiro AM, Pecos-Martín D. Predicting Sleep Quality Based on Metabolic, Body Composition, and Physical Fitness Variables in Aged People: Exploratory Analysis with a Conventional Machine Learning Model. Journal of Functional Morphology and Kinesiology. 2025; 10(3):337. https://doi.org/10.3390/jfmk10030337
Chicago/Turabian StyleForte, Pedro, Samuel G. Encarnação, José E. Teixeira, Luís Branquinho, Tiago M. Barbosa, António M. Monteiro, and Daniel Pecos-Martín. 2025. "Predicting Sleep Quality Based on Metabolic, Body Composition, and Physical Fitness Variables in Aged People: Exploratory Analysis with a Conventional Machine Learning Model" Journal of Functional Morphology and Kinesiology 10, no. 3: 337. https://doi.org/10.3390/jfmk10030337
APA StyleForte, P., Encarnação, S. G., Teixeira, J. E., Branquinho, L., Barbosa, T. M., Monteiro, A. M., & Pecos-Martín, D. (2025). Predicting Sleep Quality Based on Metabolic, Body Composition, and Physical Fitness Variables in Aged People: Exploratory Analysis with a Conventional Machine Learning Model. Journal of Functional Morphology and Kinesiology, 10(3), 337. https://doi.org/10.3390/jfmk10030337