Saudi Journal of Nursing and Health Care (SJNHC)
Volume-9 | Issue-02 | 25-33
Original Research Article
Relationship between Body Composition and Impact on Sleep Patterns among Adults
Willy Barinem Vidona, John Nwolim Paul, Esther Ibukun Olorunjuwon, Imolore Ezekiel Dare, Udo Orukwowu, Idawarifa Frank Cooky-Gam, Deborah Akinola Umogbai, Simeon Chijioke Amadi, Chioma Akunnaya Ohannye, Chukwuebuka Nnamdi Ohannye, Anelechi Kenneth Madume
Published : Feb. 10, 2026
Abstract
Introduction: Sleep is a fundamental biological process essential for cognitive performance, emotional regulation, and physical health. However, among university students, sleep disturbances and irregular sleep patterns have become increasingly prevalent due to academic stress, poor lifestyle choices, and environmental factors. Aim: This study investigated the relationship between anthropometric body composition and sleep quality among university students. The research aimed to assess how specific anthropometric indices such as Body Mass Index (BMI), waist circumference, neck circumference, and waist-to-hip ratio (WHR)—influence sleep quality and duration. Methods: A cross-sectional descriptive design was employed, involving 423 participants selected through stratified sampling across various faculties. Anthropometric data were collected using standard procedures, while sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), a widely validated tool. Results: Descriptive analysis showed that 33.6% of the participants were either overweight or obese, with a mean BMI of 23.8 ± 3.7 kg/m². Furthermore, 59.3% of the students reported poor sleep quality (PSQI score > 5), and the mean sleep duration was 6.6 ± 1.2 hours, which falls below the optimal range for young adults. Correlation analysis revealed significant positive associations between anthropometric indices and PSQI scores (p < 0.001), indicating that increased body fat is related to poorer sleep quality. Notably, neck circumference (r = 0.42), BMI (r = 0.39), and waist circumference (r = 0.33) were strongly associated with sleep disturbances. Multiple regression analysis confirmed that BMI (β = 0.26), neck circumference (β = 0.33), and waist circumference (β = 0.15) significantly predicted poor sleep quality, accounting for approximately 29% of the variance in sleep outcomes (R² = 0.29, p < 0.001). WHR, however, did not emerge as a significant predictor. Conclusion: The study concludes that poor anthropometric profiles are strongly associated with sleep disruption among university students.