This study examined the links between sleep disorders and subtypes of attention deficit-hyperactivity disorder (ADHD-inattention, ADHD-combined, ADHD-hyperactive/impulsive) in childhood. We set up a hypothetical model linking different symptoms of both disorders to construct the underlying and shared pathways. By examining a sample of children with ADHD we firstly tested parts of the model.

The purpose of this study is to assess the sleep behaviors, sleep problems and frequency, and relationship with psychiatric comorbidities in ADHD Combined type and to evaluate the effect of sleep problems on quality of life. Forty-six boys, aged 7 to 13 years, with ADHD-combined type and 31 healthy boys were included. ADHD children were never treated for sleep or psychiatric disorders. Intelligence quotient (IQ) test scores were minimum 80, body mass index were normal and did not have medical disorders. Parents completed Children’s Sleep Habits Questionnaire, Conners’ Parent Rating Scale and The Pediatric Quality of Life Inventory (PedsQL) and participants were asked about sleep behaviors and were administered PedsQL and Schedule for Affective Disorders and Schizophrenia.

Oral health practitioners routinely perform oral health assessments for the dental patient to determine if oral disease is present. Systemic health is often a contributor to oral health concerns. One area in particular that has a direct effect on oral structures and oral health is poor sleep quality and open mouth breathing. Sleep is a fundamental process of the human body, which regulates core biological functions. Sleep quality reflects a person’s ability to fall asleep, stay asleep, and enter into the various rejuvenating sleep cycles for the full duration. A person who does not obtain quality sleep can exhibit a wide range of oral, systemic, and cognitive health problems. Obstructive sleep apnea, which historically has been considered an adult male disease, is being recognized more often in women children.

Sleep disturbances and insomnia are highly prevalent in children with Autism Spectrum Disorder (ASD). Sleep homeostasis, a fundamental mechanism of sleep regulation that generates pressure to sleep as a function of wakefulness, has not been studied in children with ASD so far, and its potential contribution to their sleep disturbances remains unknown. Here, we examined whether slow-wave activity (SWA), a measure that is indicative of sleep pressure, differs in children with ASD.

The aim of this study was to assess risk factors for excessive autonomic activation during sleep (EAAS) and its association with sleep problems, impaired behavior, and poor academic performance in primary school children.

Two sources of information (parent-reported sleep diaries and actigraph records) were used to investigate how toddler sleep characteristics (bed time/sleep onset, wake time/sleep offset, total nighttime sleep, and total sleep time) are related to sleep problems and temperament. There were 64 toddler participants in the study. Consistent with studies of older children, parent reports differed from actigraph-based records.

Ten scans from the airway prototype were obtained by using cone-beam computed tomography. The volume from each scan was measured with 8 values (25, 50, 70, 71, 72, 73, 74, and 75) of the threshold tool from the Dolphin software (Dolphin Imaging and Management Solutions, Chatsworth, Calif). The gold standard method used was the actual volume of the airway prototype, which was compared with the different threshold values. An intraclass correlation coefficient test was applied to evaluate the intraexaminer calibration and verify differences among the airway volumes measured in all cone-beam computed tomography scans. Analysis of variance with the Tukey post-hoc test was used to compare differences among the measurements with different threshold values with the gold standard.

Resting state functional magnetic resonance imaging (rs-fMRI) in infants enables important studies of functional brain organization early in human development. However, rs-fMRI in infants has universally been obtained during sleep to reduce participant motion artifact, raising the question of whether differences in functional organization between awake adults and sleeping infants that are commonly attributed to development may instead derive, at least in part, from sleep. This question is especially important as rs-fMRI differences in adult wake vs. sleep are well documented. To investigate this question, we compared functional connectivity and BOLD signal propagation patterns in 6, 12, and 24 month old sleeping infants with patterns in adult wakefulness and non-REM sleep.

This survey was conducted to examine the prevalence of sleep disorders in 2- to 12-year-old children in the Beijing area of China.

Recent evidence has been accumulating that the sleep of individuals with attention deficit hyperactivity disorder (ADHD) is not only disrupted in a nonspecific way but that ADHD has an increased association with simple sleep related movement disorders such as restless legs syndrome/periodic limb movements in sleep (RLS/PLMS), rhythmic movement disorder (body rocking and head banging), and parasomnias, such as disorders of partial arousal (sleep walking, sleep terrors, and confusional arousals). In addition increased associations have been reported between ADHD and hypersomnias such as narcolepsy and sleep apnea as well as circadian rhythm disorders, such as delayed sleep phase syndrome. These relationships are reviewed and the implications for such associations are explored. Patients with sleep disorders should be queried about the symptoms of ADHD and vice versa.

To determine whether individual differences in developmental patterns of general sleep problems are associated with 3 executive function abilities-inhibiting, updating working memory, and task shifting-in late adolescence.

A prospective blind evaluation was performed. Children between the ages of 2 to 14 years with clinical suspicion of OSAS who were referred to the Sleep Unit were included. An initial HRP followed by a later date, same night, in-laboratory overnight respiratory polygraphy and polysomnography (PSG) in the sleep laboratory were performed. The apnea-hypopnea index (AHI)-HRP was compared with AHI-PSG, and therapeutic decisions based on AHI-HRP and AHI-PSG were analyzed using intraclass correlation coefficients, Bland-Altman plots, and receiver operator curves (ROCs).