Parent-Reported Symptoms of Sleep-Disordered Breathing Are Associated With Increased Behavioral Problems at 2 Years of Age: The Canadian Healthy Infant Longitudinal Development Birth Cohort Study

Group-based sleep trajectories in children and adolescents: A systematic review

Sleep is crucial for health and development. Evidence indicates that sleep changes over time and distinct subgroups may experience different longitudinal patterns. This study systematically reviewed the studies that used latent trajectory modeling to investigate sleep trajectories of children and adolescents aged 0-18 years, and summarized the associated determinants and health-related outcomes. We searched PubMed, Embase, CENTRAL, PsycINFO, and Web of Science, identifying 46 articles that met our criteria. To ensure the reliability of the review, only studies rated as good or fair in terms of methodological quality were included, resulting in a total of 36 articles. Group-based trajectories were identified on several sleep dimensions (i.e., sleep duration, general and specific sleep problems, and bed-sharing behavior) and three or four trajectories were reported in most studies. There was a convergence trend across sleep duration trajectories during the first six years of life. Studies on specific sleep problem (i.e., insomnia, night-waking, and sleep-onset difficulties) typically identified two trajectories: consistent, minimal symptoms or chronic yet fluctuating symptoms. Lower socioeconomic status, maternal depression, and night feeding behaviors were the most frequently reported determinants of sleep trajectories. Membership in a group with certain adverse patterns (e.g., persistent short sleep duration) was associated with increased risks of multiple negative health-related conditions, such as obesity, compromised immunity, neurological problems, substance use, or internalizing/externalizing symptoms. Generally, there is potential to improve the quality of studies in this field. Causality is hard to be inferred within the current body of literature. Future studies could emphasize early life sleep, incorporate more assessment timepoints, use objective measures, and employ experimental design to better understand changes of and mechanisms behind the various sleep trajectories and guide targeted interventions for at-risk subpopulations.

Sleep disordered breathing and neurobehavioral deficits in children and adolescents: a systematic review and meta-analysis

BACKGROUND

Sleep disordered breathing (SDB) is broadly recognized to be associated with neurobehavioral deficits, which have significant impacts on developing-aged children and adolescents. Therefore, our study aimed to quantify the proportion of neurobehavioral impairments attributed to SDB in general children and adolescents by population attributable fraction (PAF).

METHODS

The study was registered at PROSPERO (ID: CRD42023388143). We collected two types of literature on the prevalence of SDB and the risk of SDB-related neurobehavioral deficits from ten electronic databases and registers, respectively. The pooled effect sizes (Pe, Pc, RR) by random-effects meta-analysis were separately substituted into Levin's formula and Miettinen's formula to calculate PAFs.

RESULTS

Three prevalence literature and 2 risk literature, all with moderate/high quality, were included in the quantitative analysis individually. The prevalence of SDB was 11% (95%CI 2%-20%) in children and adolescents (Pe), while the SDB prevalence was 25% (95%CI 7%-42%) in neurobehavioral patients (Pc). SDB diagnosis at baseline was probably associated with about threefold subsequent incidence of neurobehavioral deficits (pooled RR 3.24, 95%CI 1.25-8.41), after multi-adjustment for key confounders. Up to 19.8% or 17.3% of neurobehavioral consequences may be attributed to SDB from Levin's formula and Miettinen's formula, respectively.

CONCLUSIONS

A certain number of neurobehavioral consequences may be attributable to SDB. It is essential for clinicians to identify and treat SDB timely, as well as screen for SDB in patients with neurobehavioral impairments. More longitudinal studies of SDB and neurobehavioral deficits are needed in the future to further certify the association between them.

Development of a predictive algorithm to identify pre-school children at risk for behavior changes associated with sleep-related breathing disorders

STUDY OBJECTIVES

Children with late-onset (2-5 years) or persistent (3 months-5 years) sleep-related breathing disorder (SRBD) have an increased risk of behavior problems compared to children with no or early-onset SRBD. We sought to determine whether a combination of urine metabolites and sleep questionnaires could identify children at risk for SRBD-associated behavior problems.

METHODS

Urine and data were analyzed from the Edmonton site of the CHILD birth cohort study. We measured urine metabolites (random, mid-stream) at age three-years among a sub-cohort of participants (n = 165). Random Forest with a Boruta wrapper was used to identify important metabolites (creatinine-corrected, z-scores) for late/persistent SRBD versus no/early SRBD (reference). An algorithm was subsequently generated to predict late/persistent SRBD in children with a history of snoring using a metabolite composite score (z-scores < or ≥ 0) plus the SDBeasy score defined as [age (yrs.) of most recent positive SRBD]² - [age (yrs.) first reported ever snoring]².

RESULTS

Of the 165 children with SRBD data, 40 participants had late/persistent SRBD. Seven urinary metabolites in addition to the SDBeasy score were confirmed as important for late/persistent SRBD (AUC = 0.87). Among children with an ever-snoring history and a metabolite composite score ≥0, those with SDBeasy score ≥3 were over 13-fold more likely to have late/persistent SRBD (OR 13.7; 95%CI: 3.0, 62.1; p = 0.001). This algorithm has a Sensitivity of 69.6%, Specificity of 85.7% and a positive likelihood ratio (+LR) of 4.9.

CONCLUSIONS

We developed a predictive algorithm using a combination of questionnaires and urine metabolites at age three-years to identify children with late/persistent SRBD by five-years of age.

Sleep disordered breathing symptoms are associated with depressive symptoms: A longitudinal study of Chinese adolescents

BACKGROUND

Little is known about the prospective association between sleep disordered breathing (SDB) and depressive symptoms in Chinese adolescents. This study examined the independent predictive role of SDB symptoms in depressive symptoms in a large sample of adolescents.

METHODS

A total of 11831 adolescents who participated in the baseline survey of Shandong Adolescent Behavior and Health Cohort and 7072 adolescents who were resurveyed 1 year later were included for the analyses. Adolescents completed a self-administered questionnaire about demographics, mental health, sleep problems, and family environment. SDB symptoms were assessed by 3 items about loud snoring, breathing pauses, and snorting/gasping. The Chinese Youth Self-Report anxious/depressed subscale was used to assess depressive symptoms.

RESULTS

In the cross-sectional analyses, 11.8% adolescents had depressive symptoms, and elevated frequency of SDB symptoms were significantly associated with depressive symptoms. In the longitudinal study, 4.5% of adolescents had persistent depressive symptoms, the incidence rate of depressive symptoms at 1-year follow-up was 6.5%, and elevated frequency of any SDB symptoms (often: OR=2.23, 95%CI:1.50-3.32) at baseline was significantly associated with incident depressive symptoms after adjusting for potential confounders. The associations between SDB symptoms and depressive symptoms were similar for boys and girls.

LIMITATION

SDB symptoms and depressive symptoms were measured by self-report.

CONCLUSION

SDB symptoms are an independent and significant predictor of depressive symptoms in adolescents. Further research is needed to understand the biological mechanisms between SDB and mood dysregulation in adolescents.

Conceptual models for implementing solution-oriented team science in large research consortia

Large translational research initiatives can strengthen efficiencies and support science with enhanced impact when practical conceptual models guide their design, implementation, and evaluation. The National Institutes of Health (NIH) Environmental influences on Child Health Outcomes (ECHO) program brings together data from 72 ongoing maternal–child cohort studies – involving more than 50,000 children and over 1200 investigators – to conduct transdisciplinary solution-oriented research that addresses how early environmental exposures influence child health. ECHO uses a multi-team system approach to consortium-wide data collection and analysis to generate original research that informs programs, policies, and practices to enhance children’s health. Here, we share two conceptual models informed by ECHO’s experiences and the Science of Team Science. The first conceptual model illuminates a system of teams and associated tasks that support collaboration toward shared scientific goals. The second conceptual model provides a framework for designing evaluations for continuous quality improvement of manuscript writing teams. Together, the two conceptual models offer guidance for the design, implementation, and evaluation of translational and transdisciplinary multi-team research initiatives.

Development and Validation of SDBeasy Score as a Predictor of Behavioral Outcomes in Childhood

Rationale: There are limited tools to identify which children are at greatest risk for developing sleep-disordered breathing (SDB)-associated behavioral morbidity.Objectives: To examine associations between age of onset and duration of parent-reported symptoms of SDB and behavioral problems at the age of 5 years.Methods: Data were collected and analyses were completed for participants in the CHILD (Canadian Healthy Infant Longitudinal Development) cohort at the Edmonton and Toronto sites. We generated an SDBeasy score on the basis of the age of onset and duration of SDB symptoms as reported by parents completing the Pediatric Sleep Questionnaire. Using CHILD-Edmonton data, we completed multivariate linear regression to determine whether the SDBeasy score was associated with behavioral problems at the age 5 years of age as assessed by using the Child Behavior Checklist (CBCL). We then validated the SDBeasy score using CHILD-Toronto data.Measurements and Main Results: At the 5-year visit, 581 of 716 (81%) CHILD-Edmonton participants still enrolled had CBCL data. Of the 581 children with data, 77% (446 of 581) had an SDBeasy score of 0 (never had SDB symptoms), whereas 20 of 581 children (3.4%) had persistent SDB symptoms from infancy through 5 years of age (SDBeasy score of 24). Children had a 0.35-point-higher CBCL total behavioral score at 5 years for each 1-point increase in their SDBeasy score (95% confidence interval, 0.24-0. 5; P < 0.01). We found consistent results among CHILD-Toronto participants; children had a 0.26-point-higher CBCL total behavioral score at 5 years for each 1-point increase in their SDBeasy score (95% confidence interval, 0.08-0.44; P = 0.005).Conclusions: The SDBeasy score, based on the Pediatric Sleep Questionnaire, enables identification of children with higher behavioral-problem scores.

Influence of Neighborhood Characteristics and Weather on Movement Behaviors at Age 3 and 5 Years in a Longitudinal Birth Cohort

BACKGROUND

Movement behaviors (physical activity, sedentary time, and sleep) established in early childhood track into adulthood and interact to influence health outcomes. This study examined the associations between neighborhood characteristics and weather with movement behaviors in preschoolers.

METHODS

A subset of Canadian Healthy Infant Longitudinal Development birth cohort (n = 385, 50.6% boys) with valid movement behaviors data were enrolled at age 3 years and followed through to age 5 years. Objective measures of neighborhood characteristics were derived by ArcGIS software, and weather variables were derived from the Government of Canada weather website. Random forest and linear mixed models were used to examine predictors of movement behaviors. Cross-sectional analyses were stratified by age and season (winter and nonwinter).

RESULTS

Neighborhood safety, temperature, green space, and roads were important neighborhood characteristics for movement behaviors in 3- and 5-year-olds. An increase in temperature was associated with greater light physical activity longitudinally from age 3 to 5 years and also in the winter at age 5 years in stratified analysis. A higher percentage of expressways was associated with less nonwinter moderate to vigorous physical activity at age 3 years.

CONCLUSIONS

Future initiatives to promote healthy movement behaviors in the early years should consider age differences, neighborhood characteristics, and season.

The relationship between machine-learning-derived sleep parameters and behavior problems in 3- and 5-year-old children: results from the CHILD Cohort study

STUDY OBJECTIVES

Machine learning (ML) may provide insights into the underlying sleep stages of accelerometer-assessed sleep duration. We examined associations between ML-sleep patterns and behavior problems among preschool children.

METHODS

Children from the CHILD Cohort Edmonton site with actigraphy and behavior data at 3-years (n = 330) and 5-years (n = 304) were included. Parent-reported behavior problems were assessed by the Child Behavior Checklist. The Hidden Markov Model (HMM) classification method was used for ML analysis of the accelerometer sleep period. The average time each participant spent in each HMM-derived sleep state was expressed in hours per day. We analyzed associations between sleep and behavior problems stratified by children with and without sleep-disordered breathing (SDB).

RESULTS

Four hidden sleep states were identified at 3 years and six hidden sleep states at 5 years using HMM. The first sleep state identified for both ages (HMM-0) had zero counts (no movement). The remaining hidden states were merged together (HMM-mov). Children spent an average of 8.2 ± 1.2 h/day in HMM-0 and 2.6 ± 0.8 h/day in HMM-mov at 3 years. At age 5, children spent an average of 8.2 ± 0.9 h/day in HMM-0 and 1.9 ± 0.7 h/day in HMM-mov. Among SDB children, each hour in HMM-0 was associated with 0.79-point reduced externalizing behavior problems (95% CI -1.4, -0.12; p < 0.05), and a 1.27-point lower internalizing behavior problems (95% CI -2.02, -0.53; p < 0.01).

CONCLUSIONS

ML-sleep states were not associated with behavior problems in the general population of children. Children with SDB who had greater sleep duration without movement had lower behavioral problems. The ML-sleep states require validation with polysomnography.

Sleep characteristics and problems of 2-year-olds with Williams syndrome: relations with language and behavior

Background

Sleep problems have been shown to have a negative impact on language development and behavior for both typically developing children and children with a range of neurodevelopmental disorders. The relation of sleep characteristics and problems to language and behavior for children with Williams syndrome (WS) is unclear. The goal of this study was to address these relations for 2-year-olds with WS. Associations of nonverbal reasoning ability, nighttime sleep duration, and excessive daytime sleepiness with language ability and behavior problems were considered.

Method

Ninety-six 2-year-olds with genetically confirmed classic-length WS deletions participated. Parents completed the Pediatric Sleep Questionnaire, which includes a Sleep-Related Breathing Disorder (SRBD) scale with a subscale measuring excessive daytime sleepiness, to assess sleep characteristics and problems. Parents also completed the Child Behavior Checklist (CBCL) and the MacArthur-Bates Communicative Development Inventory: Words and Sentences to assess behavior problems and expressive vocabulary, respectively. Children completed the Mullen Scales of Early Learning to measure nonverbal reasoning and language abilities.

Results

Parents indicated that children slept an average of 10.36 h per night (SD = 1.09, range 7.3–13.3), not differing significantly from the mean reported by Bell and Zimmerman (2010) for typically developing toddlers (p = .787). Sixteen percent of participants screened positive for SRBD and 30% for excessive daytime sleepiness. Children who screened positive for SRBD had significantly more behavior problems on all CBCL scales than children who screened negative. Children with excessive daytime sleepiness had significantly more attention/hyperactivity, stress, and externalizing problems than those who did not have daytime sleepiness. Individual differences in parent-reported nighttime sleep duration and directly measured nonverbal reasoning abilities accounted for unique variance in expressive language, receptive language, and internalizing problems. Individual differences in parent-reported daytime sleepiness accounted for unique variance in externalizing problems.

Conclusions

The relations of nighttime sleep duration, positive screens for SRBD, and excessive daytime sleepiness to language and behavior in toddlers with WS parallel prior findings for typically developing toddlers. These results highlight the importance of screening young children with WS for sleep problems. Studies investigating the efficacy of behavioral strategies for improving sleep in children with WS are warranted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-020-09336-z.

Using Parental Report to Identify Children at Risk for Poor Sleep and Daytime Problems

OBJECTIVE

To examine objective sleep patterns and the daytime behavioral, emotional and academic functioning of school-age children above and below the clinical cutoff score for the Child Sleep Habits Questionnaire (CSHQ), which is a parental-report-based measure of sleep disturbances.

PARTICIPANTS

48 boys and 74 girls aged 7-11 years.

METHODS

Participants' sleep was assessed in their home environment using a miniature actigraph (AW-64 series; Mini-Mitter, Sunriver, OR, USA) for five consecutive weeknights. The parents provided their child's report card and completed a battery of questionnaires that included the CSHQ, the Child Behavior Checklist, a demographic questionnaire and a health questionnaire.

RESULTS

Children that were above the cutoff score of the CSHQ had later objectively measured sleep schedule, were less likely to obtain the recommended amount of sleep for their age, had higher levels of internalizing and externalizing symptoms and a higher prevalence of clinical levels of externalizing and internalizing problems, had lower grades in English and French as a Second Language, and were more likely to fail these subjects. Discriminant analysis revealed that information from the objective sleep and emotional/behavioral and academic measures could significantly discriminate between those with or without parent-reported sleep disturbance.

CONCLUSION

Parental reports of sleep disturbances can be used to identify children at increased risk for sleep, emotional, behavioral and academic problems. Such questionnaires should be incorporated into clinical practice and school-based evaluations with the goal of identifying undiagnosed children who might be at risk for poor adjustment related to night- and daytime difficulties.

Application of latent class analysis in assessing the awareness, attitude, practice and satisfaction of paediatricians on sleep disorder management in children in Italy

AIM

To identify subgroups regarding paediatricians' awareness, attitude, practice and satisfaction about management of Sleep-Disordered Breathing (SDB) in Italy using Latent Class Analysis (LCA).

METHODS

A cross-sectional study was conducted on a large sample of Italian paediatricians. Using a self-administered questionnaire, the study collected information on 420 Paediatric Hospital Paediatricians (PHPs) and 594 Family Care Paediatricians (FCPs). LCA was used to discover underlying response patterns, thus allowing identification of respondent groups with similar awareness, attitude, practice and satisfaction. A logistic regression model was used to investigate which independent variables influenced latent class membership. Analyses were performed using R 3.5.2 software. A p-value<0.05 was considered statistically significant.

RESULTS

Two classes were identified: Class 1 (n = 368, 36.29%) "Untrained and poorly satisfied" and Class 2 (n = 646, 63.71%) "Trained and satisfied." Involving paediatric pneumologists or otorhinolaryngologists in clinical practice was associated with an increased probability of Class 2 membership (OR = 5.88, 95%CI [2.94-13.19]; OR = 15.95, 95% CI [10.92-23.81] respectively). Examining more than 20 children with SDB during the last month decreased the probability of Class 2 membership (OR = 0.29, 95% CI [0.14-0.61]). FCPs showed a higher probability of Class 2 membership than PHPs (OR = 4.64, 95% CI [3.31-6.55]).

CONCLUSIONS

These findings suggest that the LCA approach can provide important information on how education and training could be tailored for different subgroups of paediatricians. In Italy standardized educational interventions improving paediatricians' screening of SDB are needed in order to guarantee efficient management of children with SDB and reduce the burden of disease.

Pediatric pulmonology year in review 2018: Sleep medicine

Pediatric Pulmonology publishes original research, case reports, and review articles on topics related to a wide range of children's respiratory disorders. In this article (Part 4 of a five-part series), we summarize the past year's publications in sleep medicine, in the context of selected literature in this area from other journals. Articles are highlighted on topics including infant sleep, diagnosis, and treatment of obstructive sleep apnea, and sleep disorders in chronic disease.

Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study

BACKGROUND

Pre-school children spend an average of two-hours daily using screens. We examined associations between screen-time on pre-school behavior using data from the Canadian Healthy Infant Longitudinal Development (CHILD) study.

METHODS

CHILD participant parents completed the Child Behavior Checklist (CBCL) at five-years of age. Parents reported their child's total screen-time including gaming and mobile devices. Screen-time was categorized using the recommended threshold of two-hours/day for five-years or one-hour/day for three-years. Multiple linear regression examined associations between screen-time and externalizing behavior (e.g. inattention and aggression). Multiple logistic regression identified characteristics of children at risk for clinically significant externalizing problems (CBCL T-score≥65).

RESULTS

Screen-time was available for over 95% of children (2,322/2,427) with CBCL data. Mean screen-time was 1·4 hours/day (95%CI 1·4, 1·5) at five-years and 1·5 hours/day (95%CI: 1·5, 1·6) at three-years. Compared to children with less than 30-minutes/day screen-time, those watching more than two-hours/day (13·7%) had a 2·2-point increase in externalizing T-score (95%CI: 0·9, 3·5, p≤0·001); a five-fold increased odd for reporting clinically significant externalizing problems (95%CI: 1·0, 25·0, p = 0·05); and were 5·9 times more likely to report clinically significant inattention problems (95%CI: 1·6, 21·5, p = 0·01). Children with a DSM-5 ADHD T-score above the 65 clinical cut-off were considered to have significant ADHD type symptoms (n = 24). Children with more than 2-hours of screen-time/day had a 7·7-fold increased risk of meeting criteria for ADHD (95%CI: 1·6, 38·1, p = 0·01). There was no significant association between screen-time and aggressive behaviors (p>0.05).

CONCLUSION

Increased screen-time in pre-school is associated with worse inattention problems.