Predicting Sleep Quality Based on Metabolic, Body Composition, and Physical Fitness Variables in Aged People:...

Area of Science:

• Gerontology
• Sleep Science
• Exercise Physiology

Background:

• Sleep quality is vital for older adults' health, influenced by physiological and functional factors.
• The interplay between sleep quality, physical fitness, body composition, and metabolic health in seniors is not well understood.

Purpose of the Study:

• To explore associations between sleep quality and physical, metabolic, and body composition variables in older adults.
• To assess a logistic regression model's ability to classify sleep quality using non-sleep-related predictors.

Main Methods:

• Evaluated 32 older adults (mean age 69) on sleep quality (Pittsburgh Sleep Quality Index), physical fitness (Functional Fitness Test), body composition (bioimpedance), and clinical markers.
• Employed group comparisons, associative analysis, and 5-fold cross-validated logistic regression for sleep quality classification.

Main Results:

• Good sleep quality correlated with superior back stretch, lower limb strength (5TSTS), and longer sleep duration.
• Poor sleep quality showed moderate associations with reduced lower limb strength and mobility.
• A logistic regression model using 5TSTS and Timed Up and Go (TUG) test achieved 76% accuracy in classifying sleep quality.

Conclusions:

• Physical fitness and clinical factors significantly impact sleep quality in older adults.
• Interventions targeting lower limb strength may improve sleep outcomes in this demographic.