Associations of sleep problems with lifestyle, health-related quality of life, body composition, physical fitness, and academic performance in schoolchildren

Sleep problems are increasingly recognized as relevant to school health, yet lifestyle, physical fitness, wellbeing, body composition, and academic functioning are not always assessed together. This study examined the associations of these indicators with sleep problems in schoolchildren. Methods: A cross-sectional study included 949 students aged 9–15 years from 60 schools in Tenerife and Gran Canaria, Spain. Sleep problems were assessed using the Sleep Self-Report questionnaire. Moderate-to-vigorous physical activity, sedentary time, health-related quality of life, BMI-for-age z-score, waist circumference, handgrip strength, standing long jump, cardiorespiratory fitness, academic grades, and perceived academic performance were assessed using questionnaires, anthropometric measures, and field-based tests. Differences across sleep-problem tertiles were examined using cluster-adjusted analyses. Separate generalized estimating equation models examined each indicator individually, adjusting for sex, continuous age, family affluence, and area of residence, with school as the clustering variable. The handgrip model was additionally adjusted for body weight and height. Results: Higher sleep-problem scores were inversely associated with moderate-to-vigorous physical activity, health-related quality of life, standing long jump, cardiorespiratory fitness, academic grades, and perceived academic performance, and positively associated with sedentary time, BMI-for-age z-score, and waist circumference. Handgrip strength was not significantly associated with sleep problems after adjustment for body weight and height. All significant associations remained so after false-discovery-rate correction. Conclusions: Sleep-problem scores were associated with several lifestyle, health-related quality-of-life, body-composition, physical-fitness, and academic indicators. However, these indicator-specific cross-sectional models do not establish independence, temporal ordering, or causality. Longitudinal studies are needed to clarify potentially reciprocal relationships.