No abstract

Actimetry has been used to estimate the sleep-wake cycle instead of the rest-activity rhythm. Although algorithms for assessing sleep from actimetry data exist, it is useful to analyze the rest-activity rhythm using nonparametric methods. This would then allow rest-activity rhythm stability, fragmentation and amplitude to be quantified. In addition, sleep and wakefulness efficiency can be quantified separately. These variables have been used in studies analyzing the effect of age, diseases and their respective treatments on human circadian rhythmicity. In this study, we carried out a comprehensive analysis of the main results from published articles and devised a functional model of interaction among the several components involved in generating the sleep-wake cycle. The nonparametric variables render it possible to infer the main characteristics of circadian rhythms, such as synchronization with a zeitgeber, and its amplitude and robustness.

Adolescents present with sleep timing delay, irregular sleep-wake (SW) schedules and short sleep duration (<7 h) on school days, all resulting from biological and behavioral factors. To minimize this, we evaluated the effect of a school-based sleep hygiene program on the SW cycle, sleep quality and sleepiness in 58 Brazilian adolescent students. The sleep hygiene program lasted a week and consisted of a daily 50 min activity, such as a sleep physiology class, constructing a sleep ontogeny map, discussing the causes and consequences of adolescent short sleep duration and a quiz about sleep hygiene statements. After this, the students showed a reduction in their index of sleep irregularity (represented by standard deviation from bedtime), their sleep latency decreased and their nap-wake up schedule advanced. Their sleep quality and daytime sleepiness showed no difference. The program was effective in reducing sleep irregularity and latency and advancing nap awaking but could be improved and extended to a larger sample to achieve a better evaluation.

Circadian rhythmicity in humans has been well studied using actigraphy, a method of measuring gross motor movement. As actigraphic technology continues to evolve, it is important for data analysis to keep pace with new variables and features. Our objective is to study the behavior of two variables, interdaily stability and intradaily variability, to describe rest activity rhythm. Simulated data and actigraphy data of humans, rats, and marmosets were used in this study. We modified the method of calculation for IV and IS by modifying the time intervals of analysis. For each variable, we calculated the average value (IVm and ISm) results for each time interval. Simulated data showed that (1) synchronization analysis depends on sample size, and (2) fragmentation is independent of the amplitude of the generated noise. We were able to obtain a significant difference in the fragmentation patterns of stroke patients using an IVm variable, while the variable IV60 was not identified. Rhythmic synchronization of activity and rest was significantly higher in young than adults with Parkinson׳s when using the ISM variable; however, this difference was not seen using IS60. We propose an updated format to calculate rhythmic fragmentation, including two additional optional variables. These alternative methods of nonparametric analysis aim to more precisely detect sleep–wake cycle fragmentation and synchronization.

An intrinsic association between suicidal ideation and sleep disorders in patients with depressive disorder has been observed in recent studies. This study was conducted in order to examine the relationship between suicidal ideation and sleep disorders, such as insomnia and excessive sleepiness, in outpatients with major depressive disorder. Seventy patients with diagnoses of major depressive disorder were interviewed and assessed with the Sleep Habits Questionnaire and the Beck Scale for Suicidal Ideation (SSI). Data analyses were performed through descriptive analysis, Students t-test, Chi-square test and logistic regression model, with a statistical significance of 5%. In this study, depressed patients had high SSI scores (6.12 ± 2.67), particularly for active suicidal ideation (1.61 ± 0.39) and specific plans for suicide components (1.51 ± 0.40). Depressed patients with insomnia had significantly higher SSI scores (7.39 ± 2.84), in relation to patients with excessive sleepiness (3.68 ± 1.73). Furthermore it was observed that insomniac patients had significantly higher scores on the following components: active suicide ideation, specific plans for suicide and previous suicide attempts. The results of multivariate analysis showed that only insomnia had a significant association with suicidal ideation. Thus, sleep disturbances, particularly insomnia, should be considered in the assessment of suicidal risk in outpatients with depressive disorder.