Objective sleep and cardiometabolic biomarkers: results from the community of mine study

Sleep Adv. 2023 Nov 28;4(1):zpad052. doi: 10.1093/sleepadvances/zpad052. eCollection 2023.

Abstract

Study objectives: Examining multiple dimensions of sleep health may better capture associations between sleep and health risks, including cardiometabolic disease (CMD). Hispanics have elevated risk for inadequate sleep and CMD biomarkers. Few studies have explored whether associations between sleep and CMD differ by Hispanic ethnicity.

Methods: Leveraging data from the Community of Mine (CoM) study, a cross-sectional investigation of 602 ethnically diverse participants, we derived accelerometer-measured sleep duration and efficiency, and self-reported sleep quality. Accelerometer-measured sleep exposures were analyzed both as continuous and categorical variables. Multivariate and quantile regression models were used to assess associations between sleep and CMD biomarkers (insulin resistance, systolic blood pressure, and low-density-lipoprotein cholesterol), controlling for age, sex, ethnicity, education, smoking status, and body mass index. We examined the potential effect modification of Hispanic ethnicity.

Results: We observed mixed results based on CMD biomarkers and sleep exposure. Increased sleep duration was significantly related to low-density lipoprotein cholesterol in adjusted models (estimate = 0.06; 95% CI: 0.02, 0.11). Poor sleep efficiency was associated with greater insulin resistance in the adjusted quantile (estimate = 0.20; 95% CI: 0.04, 0.36) model at the 90th percentile. Self-reported sleep quality was not associated with CMD outcomes. There was no evidence of effect modification by Hispanic ethnicity.

Conclusions: In this cohort, sleep health measures were found to have mixed and at times opposing effects on CMD outcomes. These effects did not demonstrate an interaction with Hispanic ethnicity.

Keywords: Latino ethnicity; accelerometry; cardiovascular health; health disparities; metabolic health; quantile regression.