PURPOSE: To examine how sleep and physical activity predict body mass index (BMI) in college students. DESIGN: Cross-sectional. SETTING: Medium-sized public university in the Southeastern United States. SUBJECTS: 386 undergraduate students (245 females; 18-25 years). MEASURES: Surveys included the Pittsburg Sleep Quality Index (PSQI) and Concise Physical Activity Questionnaire (CPAQ). PSQI provided 5 sleep scores: PSQI Global Score, Sleep Quality Factor Score, Sleep Efficiency Factor Score, Sleep Duration, and Habitual Sleep Efficiency. Height and weight measurements were taken to calculate Body Mass Index (BMI). ANALYSIS: Correlational analyses were completed first. Linear and moderation regression models using CPAQ as the moderator were used to predict BMI. The Johnson-Neyman technique determined regions of significance where sleep significantly predicted BMI dependent on CPAQ score. RESULTS: Sleep Duration significantly predicted BMI (β = -.385, p = .043) while significant interaction terms predicting BMI were found for Global PSQI Score × CPAQ (β = -.103, p = .015) and Sleep Quality Factor Score × CPAQ (β = -.233, p = .013). Johnson-Neyman analyses demonstrated that better sleep quality (measured by Global PSQI and Sleep Quality Factor Scores) predict lower BMI when exercise levels are low and higher BMI when exercise levels are high. CONCLUSION: At low levels of exercise, better sleep quality significantly predicts lower BMI, suggesting that interventions designed to increase sleep quality could promote healthy weight maintenance in college students.
PURPOSE: To examine how sleep and physical activity predict body mass index (BMI) in college students. DESIGN: Cross-sectional. SETTING: Medium-sized public university in the Southeastern United States. SUBJECTS: 386 undergraduate students (245 females; 18-25 years). MEASURES: Surveys included the Pittsburg Sleep Quality Index (PSQI) and Concise Physical Activity Questionnaire (CPAQ). PSQI provided 5 sleep scores: PSQI Global Score, Sleep Quality Factor Score, Sleep Efficiency Factor Score, Sleep Duration, and Habitual Sleep Efficiency. Height and weight measurements were taken to calculate Body Mass Index (BMI). ANALYSIS: Correlational analyses were completed first. Linear and moderation regression models using CPAQ as the moderator were used to predict BMI. The Johnson-Neyman technique determined regions of significance where sleep significantly predicted BMI dependent on CPAQ score. RESULTS: Sleep Duration significantly predicted BMI (β = -.385, p = .043) while significant interaction terms predicting BMI were found for Global PSQI Score × CPAQ (β = -.103, p = .015) and Sleep Quality Factor Score × CPAQ (β = -.233, p = .013). Johnson-Neyman analyses demonstrated that better sleep quality (measured by Global PSQI and Sleep Quality Factor Scores) predict lower BMI when exercise levels are low and higher BMI when exercise levels are high. CONCLUSION: At low levels of exercise, better sleep quality significantly predicts lower BMI, suggesting that interventions designed to increase sleep quality could promote healthy weight maintenance in college students.
Keywords:
education; exercise; sleep; students; weight control
Authors: Edlin Garcia Colato; Chen Chen; Sina Kianersi; Christina Ludema; Molly Rosenberg; Jonathan T Macy Journal: Front Public Health Date: 2022-08-18