Experimental studies suggest that highly variable sleep-wake patterns may impair vascular function, suggesting a potential mechanism for the increased risk of cardiovascular (CV) diseases seen in shift workers and those with sleep disorders. However, it is unclear if naturalistic, day-to-day variability in sleep-wake patterns of generally healthy individuals poses a risk to vascular function. PURPOSE: To examine the association between sleep variability (SLV) and vascular function in undergraduate college students. METHODS: SLV metrics were estimated in 39 healthy undergraduate students (20 ±0.2 years) using wrist actigraphy for 14 days and nights. Sleep timing was defined by sleep midpoint (halfway point between sleep onset and wake onset). Sleep timing variability (STV) was then quantified as the standard deviation (SD) of sleep midpoint, and sleep duration variability (SDV) as the SD of sleep duration across 14 days. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Peripheral vascular function was indexed as the magnitude of hyperemia in response to passive leg movement (PLM) and was performed immediately following the end of sleep monitoring. Blood velocity and femoral artery diameter were measured via Doppler ultrasound. RESULTS: In a linear regression model adjusting for sex and body mass, SDV predicted peak leg blood flow (LBF) (β=-0.49, p<0.01), change in LBF from baseline to peak (β=-0.50, p<0.01), and LBF area under the curve (AUC) (β=-0.57, p<0.01) during PLM. Associations remained significant when the model included PSQI score (all p<0.01). Similarly, models adjusting for sex and mass found that STV predicted LBF AUC (β=-0.30, p=0.05). CONCLUSION: In adjusted models, greater SLV is associated with less optimal peripheral vascular function in healthy college students. These data support the growing body of literature suggesting that regular sleep schedules may be important for CV health, even in otherwise healthy young adults.
Supported, in part, by NIH P20GM113125.