A new strategy to analyze possible association structures between dynamic nocturnal hormone activities and sleep alterations in humans.

The human sleep process shows dynamic alterations during the night. Methods are needed to examine whether and to what extent such alterations are affected by internal, possibly time-dependent, factors, such as endocrine activity. In an observational study, we examined simultaneously sleep EEG and nocturnal levels of renin, growth hormone (GH), and cortisol (between 2300 and 0700) in 47 healthy volunteers comprising 24 women (41.67 +/- 2.93 yr of age) and 23 men (37.26 +/- 2.85 yr of age). Hormone concentrations were measured every 20 min. Conventional sleep stage scoring at 30-s intervals was applied. Semiparametric multinomial logit models are used to study and quantify possible time-dependent hormone effects on sleep stage transition courses. Results show that increased cortisol levels decrease the probability of transition from rapid-eye-movement (REM) sleep to wakefulness (WAKE) and increase the probability of transition from REM to non-REM (NREM) sleep, irrespective of the time in the night. Via the model selection criterion Akaike's information criterion, it was found that all considered hormone effects on transition probabilities with the initial state WAKE change with time. Similarly, transition from slow-wave sleep (SWS) to light sleep (LS) is affected by a "hormone-time" interaction for cortisol and renin, but not GH. For example, there is a considerable increase in the probability of SWS-LS transition toward the end of the night, when cortisol concentrations are very high. In summary, alterations in human sleep possess dynamic forms and are partially influenced by the endocrine activity of certain hormones. Statistical methods, such as semiparametric multinomial and time-dependent logit regression, can offer ambitious ways to investigate and estimate the association intensities between the nonstationary sleep changes and the time-dependent endocrine activities.