Sleep quality and neurohormonal and psychophysiological accompanying factors in adolescents with depressive disorders: study protocol

Sleep quality and the cortisol and alpha-amylase awakening responses in adolescents with depressive disorders

BACKGROUND

Depressive disorders in adolescents affect all aspects of life and impose a very large burden of disease. Sleep is frequently affected by depression and is crucial for facing challenges during development. One of the postulated reasons for depression-induced sleep disruption is dysregulation of the physiological stress system.

AIMS

To investigate the links of adolescent depressive disorders with subjective sleep quality, objective sleep quality, and the course of cortisol and alpha-amylase after awakening.

METHOD

We compared subjective sleep quality (via daily questionnaires) and objective sleep quality (via actigraphy measurement) of 35 adolescents with depressive disorders and 29 healthy controls over 7 consecutive days. In addition, saliva samples were collected on 3 days to examine cortisol and alpha-amylase patterns after awakening.

RESULTS

No significant differences in cortisol or alpha-amylase awakening responses were observed between participants with depressive disorders and healthy controls. We found severe reductions in subjective sleep quality in the depression group (Z = -5.19, P < 0.001, d = 1.80) and a prolonged actigraphy-measured sleep onset latency (Z = -2.42, P = 0.015, d = 0.64) compared with controls. Reductions in subjective sleep quality were partially correlated with objective sleep measures (sleep onset latency: r = -0.270, P = 0.004, sleep efficiency: r = 0.215, P = 0.017).

CONCLUSIONS

Sleep onset latency seems to aggravate depressive symptoms and to have an important role in perception of sleep quality. Adolescents with depressive disorders should be supported regarding the establishment of good sleep hygiene and avoiding activities that may impede falling asleep.

Covariate selection in causal learning under non-Gaussianity

Understanding causal mechanisms is a central goal in the behavioral, developmental, and social sciences. When estimating and probing causal effects using observational data, covariate adjustment is a crucial element to remove dependencies between focal predictors and the error term. Covariate selection, however, constitutes a challenging task because availability alone is not an adequate criterion to decide whether a covariate should be included in the statistical model. The present study introduces a non-Gaussian method for covariate selection and provides a forward selection algorithm for linear models (i.e., non-Gaussian forward selection; nGFS) to select appropriate covariates from a set of potential control variables to avoid inconsistent and biased estimators of the causal effect of interest. Further, we demonstrate that the forward selection algorithm has properties compatible with principles of direction of dependence, i.e., probing whether the causal target model is correctly specified with respect to the causal direction of effects. Results of a Monte Carlo simulation study suggest that the selection algorithm performs well, in particular when sample sizes are large (i.e., n ≥ 250) and data strongly deviate from Gaussianity (e.g., distributions with skewness beyond 1.5). An empirical example is given for illustrative purposes.

Sleep-associated insulin resistance promotes neurodegeneration

Lifestyle modification can lead to numerous health issues closely associated with sleep. Sleep deprivation and disturbances significantly affect inflammation, immunity, neurodegeneration, cognitive depletion, memory impairment, neuroplasticity, and insulin resistance. Sleep significantly impacts brain and memory formation, toxin excretion, hormonal function, metabolism, and motor and cognitive functions. Sleep restriction associated with insulin resistance affects these functions by interfering with the insulin signalling pathway, neurotransmission, inflammatory pathways, and plasticity of neurons. So, in this review, We discuss the evidence that suggests that neurodegeneration occurs via sleep and is associated with insulin resistance, along with the insulin signalling pathways involved in neurodegeneration and neuroplasticity, while exploring the role of hormones in these conditions.

Effects of Screen Viewing Time on Sleep Duration and Bedtime in Children Aged 1 and 3 Years: Japan Environment and Children's Study

This study aimed to clarify the effects of television/digital versatile disc (TV/DVD) viewing time and portable electronic device (PED) usage time on sleep duration and bedtime and the difference between the effects of TV/DVD and PED on sleep. The effect of TV/DVD viewing time or PED usage time on sleep duration and bedtime was analyzed using a multiple logistic regression analysis adjusted for covariates. A total of 74,525 participants were included in the analysis, using data from Japan Environment and Children’s Study. TV/DVD viewing was not associated with short sleep duration, but PED usage was associated with short sleep duration. In addition, the risk of short sleep duration increased as PED usage time increased. We also investigated the effects of sleep habits at age 1 year on sleep at age 3 years. This study showed that late bedtime at age 1 year posed a significant risk of late bedtime at age 3 years. In summary, particular caution should be paid to PED use from a child’s health perspective, and sleep habits should be focused on bedtime from the age of 1 year.