Associations Between Salivary Cortisol, DHEA-S, and Alpha-Amylase and Longitudinal Sleep Disruption in Shift-Working...

Shift work is a well-established disruptor of sleep, yet the biological mechanisms driving sleep disturbances remain poorly understood. Salivary cortisol (HPA axis), α-amylase (sympathetic-adrenomedullary output), and DHEA-S (adrenal androgen with anti-glucocorticoid/resilience properties) are candidate indicators of stress-related sleep disruption. We therefore examined whether changes in these biomarkers were associated with 6-month sleep trajectories in health professionals.

In a prospective 6-month repeated-measures design, 52 healthcare professionals (daytime vs rotating shifts; mean age 31.4 ± 9.4 years; 57% female) completed validated sleep assessments, PROMIS Sleep Disturbance, PROMIS Sleep Impairment, the Sleep-Wake Disorder Index (SWDI), and the NIH 7-day Sleep Diary, at baseline and six-month follow-up. Salivary cortisol, Dehydroepiandrosterone Sulfate (DHEA-S), and alpha-amylase were collected on the morning of Day 7 of each diary period. Change scores (Δ = follow-up - baseline) were computed. Repeated-measures ANOVA, Pearson correlations, and multivariable regressions assessed group differences and biomarker-sleep associations.

Compared with daytime workers, rotating shift workers reported significantly greater increases in sleep disturbance, impairment, and reduced sleep efficiency over time (all p < 0.05). Reductions in cortisol and alpha-amylase were significantly associated with worsening PROMIS Sleep Disturbance and SWDI scores (r = -0.65 and -0.53, respectively; p < 0.05). Multivariable regression showed that decreased cortisol (β = -41.845, p = 0.0064) and increased DHEA-S (β = 0.001, p = 0.0405) associated with worsening PROMIS Sleep Impairment. A combined model including reduced cortisol, and increased DHEA-S associated with greater PROMIS Sleep Disturbance (adjusted R² = 0.698).

In this pilot, changes in salivary cortisol and DHEA-S were associated with longitudinal changes in sleep. These results suggest potential utility for biomarker-informed risk stratification, warranting confirmation in larger, controlled studies.