Estimating the causal effect of sleep duration on mental health in young adults: A meta-learner approach from physiological and nutritional perspectives

Abstract

This study analyzes the causal effect of sleep duration on mental health among young adults using a meta-learner-based causal inference framework. Specifically, we applied a T-Learner model with Random Forest and XGBoost as the base learner to data from 1,405 individuals aged 19–34, drawn from the 2022–2023 Korea National Health and Nutrition Examination Survey. The result indicates that adequate sleep increases the probability of maintaining normal mental health. Subgroup analysis comparing individuals with adequate sleep and normal mental health to those with insufficient sleep and poor mental health also reveals a statistically significant causal effect of sleep on mental health improvement. In addition, AST (SGOT) levels and blood creatinine concentration are identified as key confounding factors. Findings suggest that sufficient sleep could enhance mental health among young adults, and policy implications for youth mental health are derived from the perspective of sleep duration. By providing empirically identified causal evidence based on nationally representative data, this study contributes to the growing literature on sleep and mental health and highlights sleep duration as a modifiable target for evidence-based mental health interventions in young adults.