Morning sleep inertia and its associated factors: Findings from a nationwide study
Abstract
Objectives: Sleep inertia, a transitional state of grogginess and impaired alertness upon awakening, varies in duration and influencing factors. This study examined its characteristics and associations with sociodemographic factors, sleep patterns, and comorbidities in a Korean adult population.
Methods: Data from 2,355 participants (49.2% male, aged 19-92) in the Korean Sleep Headache Study (2018) was analyzed. Morning sleep inertia was assessed via self-reported duration in minutes using the question, "How long does it typically take for you to clear your grogginess in the morning after waking from overnight sleep?" While this single-item question was appropriate for a population-based study, it may not fully capture the multidimensional nature of sleep inertia. Multiple linear regression analyses were conducted using log-transformed sleep inertia as the dependent variable.
Results: The mean (SD) sleep inertia was 15.8 (12.9) minutes. Females reported 1.1 minutes longer sleep inertia than males, although no significant differences were observed across age groups. Participants with anxiety reported 14.3 minutes longer inertia than those without anxiety, showing the largest effect size (Cohen's d = 1.12). Sleep inertia was negatively associated with sleep duration (beta [95% CI]: -0.05 [-0.07, -0.02]), morning chronotype (-0.16 [-0.24, -0.08]), and habitual snoring (-0.10 [-0.17, -0.02]), but positively associated with evening chronotype (0.12 [0.04, 0.19]), insomnia (0.22…
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.