Sleep Quality and Daytime Functioning as Predictors of Metabolic Risk: A Structural Equation Modeling Analysis of NHANES Data
DOI:
https://doi.org/10.51137/wrp.ijdht.782Keywords:
Sleep Quality, Daytime Sleepiness, Metabolic Risk, Body Mass Index, Waist Circumference, Structural Equation Modeling, NHANES, Health InformaticsAbstract
Sleep is increasingly recognized as a multidimensional contributor to cardiometabolic health, yet many population studies focus primarily on sleep duration rather than restorative aspects such as sleep quality and daytime functioning. Structural equation modeling (SEM) enables the assessment of latent wellness constructs while accounting for measurement error. This study examined the association between a latent Sleep Wellness construct and a latent Metabolic Risk construct among adults participating in the National Health and Nutrition Examination Survey (NHANES) 2017–March 2020 prepandemic cycle. A cross-sectional secondary analysis was conducted using publicly available NHANES data. Sleep Wellness was modeled as a latent construct measured by perceived sleep quality and reverse-coded daytime sleepiness. Metabolic Risk was modeled as a latent construct measured by body mass index (BMI) and waist circumference. SEM was estimated in Stata 19 using maximum likelihood estimation. Model fit was evaluated using RMSEA, CFI, TLI, and SRMR. Standardized factor loadings and the structural association between Sleep Wellness and Metabolic Risk were interpreted. The population sample included 8420 adults after listwise exclusion of missing data. Model fit was strong (RMSEA=.046, CFI=.999, TLI=.993, SRMR=.005). Sleep quality and reverse-coded daytime sleepiness loaded on Sleep Wellness (.585 and .397, respectively), while BMI and waist circumference strongly loaded on Metabolic Risk (.919 and .987). Sleep Wellness was inversely associated with Metabolic Risk (standardized β=-.292, P<.001). Sleep quality and daytime functioning may be meaningful indicators of sleep wellness in relation to metabolic risk, supporting multidimensional modeling approaches beyond sleep duration alone.
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