Guo · Psychoneuroendocrinology 2024 · repeated-measures observational cohort study · n=79

Relationship of sleep with diurnal cortisol rhythm considering sleep measurement and cortisol sampling schemes.

Level 3 - non-randomized controlled study

Prospective repeated-measures observational cohort study

PubMed 38232528 · doi:10.1016/j.psyneuen.2023.106952 · record verified 2026-08-26

What was done

Researchers evaluated 79 college students over 3 days using wrist actigraphy (objective sleep) and daily sleep diaries (subjective sleep). Participants provided six salivary cortisol samples per day. Multilevel models assessed how trait (average) and state (previous night) sleep parameters related to next-day diurnal cortisol metrics, evaluating six different cortisol sampling protocols and two diurnal cortisol slope (DCS) calculation methods.

What was found

The abstract reports directional associations without numerical effect sizes, confidence intervals, or p-values. Higher objective state sleep efficiency and longer objective state total sleep time were associated with a higher cortisol awakening response (CAR). Higher objective trait sleep efficiency and longer objective trait total sleep time were associated with higher waking cortisol levels and steeper DCS. A minimum of four daily saliva samples (waking, +30 min, +1 h, and bedtime) was identified as necessary to capture these relationships. Peak-to-bed slope calculation was optimal for sleep efficiency, whereas wake-to-bed slope worked best for total sleep time.

Why it matters

It provides methodological guidance on minimum salivary sampling points (four per day) and slope calculation methods needed to reliably detect associations between objective sleep dimensions and diurnal cortisol rhythms.

Limits

The sample was small (n = 79) and restricted to college students, limiting generalizability to older or clinical populations. The monitoring period was brief (3 days), the design was observational (precluding causal conclusions), and the abstract omitted quantitative point estimates and statistical precision metrics.

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