Investigating the Convergence between Actigraphy, Maternal Sleep Diaries, and the Child Behavior Checklist as Measures of Sleep in Toddlers

Carer-reported sleep disturbance and carer- and teacher-rated executive functioning in children with prenatal alcohol exposure and Fetal Alcohol Spectrum Disorder

Children with prenatal alcohol exposure (PAE) and Fetal Alcohol Spectrum Disorder (FASD) have high rates of sleep disturbance and marked difficulties with executive functioning (EF). Sleep disturbance has been associated with poorer EF across development in typically developing children. The contribution of insomnia symptoms and nightmares to EF difficulties in children with PAE and FASD is unclear. The current study examined whether caregiver-reported insomnia symptoms and nightmares predicted difficulties with EF in children with PAE who were assessed at FASD diagnostic clinics. Archival data on 116 children with PAE assessed at FASD diagnostic clinics were extracted from databases. Children were assigned to a preschool-age group (3.1 to 5.9 years, n = 40) and a school-age group (5.9 to 10.9 years, n = 76). Insomnia symptoms and nightmares were measured using items extracted from the Child Behavior Checklist (CBCL) while EF was measured using the caregiver and teacher Behavior Rating Inventory of Executive Function (BRIEF) rating forms. Bootstrapped regression models were used examine the effects of insomnia symptoms and nightmares on domains of EF in each group while adjusting for potential confounds. For preschool children, insomnia symptoms were associated with greater daytime tiredness while nightmares were associated with greater difficulties with Emergent Metacognition according to their teachers. For school-age children, insomnia symptoms predicted greater EF difficulties across most domains according to their caregivers but not teachers. Sleep disturbance may compound EF impairments in children with PAE and should be screened for as part of FASD diagnostic assessment.

Psychometric Properties and Clinical Utility of CBCL and P-GBI Sleep Items in Children and Adolescents

OBJECTIVE

Sleep is crucial to overall health, playing a complex role in a wide range of mental health concerns in children and adults. Nevertheless, clinicians may not routinely assess sleep problems due to lack of awareness or limitations such as cost or time. Scoring sleep-related items embedded on broader scales may help clinicians get more out of tools they are already using. The current study explores evidence of reliability, validity, and clinical utility of sleep-related items embedded on two caregiver-report tools: the Child Behavior Checklist (CBCL) and Parent General Behavior Inventory (P-GBI).

METHOD

Youth aged 5-18 years and their parents were recruited from both an academic medical center (N = 759) and an urban community health center (N = 618). Caregivers completed the CBCL and P-GBI as part of a more comprehensive outpatient evaluation. Exploratory factor analyses, multi-group confirmatory factor analyses, and graded response models evaluated dimensionality, reliability, and invariance across samples. Correlations and receiver operating characteristic curve analyses probed associations with diagnostic and demographic variables.

RESULTS

Two subscales emerged for each itemset. Across both samples, P-GBI sleep subscales were more reliable and consistent than CBCL sleep subscales, showed greater coverage of sleepiness and insomnia constructs, were better at discriminating individuals within a wider range of sleep complaints, and showed significant correlation with mood disorder diagnoses.

CONCLUSIONS

The P-GBI sleep items provide a brief, reliable measure for assessing distinct dimensions of sleep complaints and detecting mood symptoms or diagnoses related to the youth's sleep functioning, making them a useful addition to clinical practice.

Habitual sleep and intraindividual variability of sleep in gifted children: an actigraphy study

STUDY OBJECTIVES

Giftedness is a multidimensional condition. It is increasingly put forward that gifted children (GC) could be a population at high risk for sleep problems. The current study investigated GC and typically developing children for their habitual sleep, night-to-night sleep variability, and parental reports of child sleep.

METHODS

The sample consisted of 62 GC (31 girls; mean age = 9.63 ± 1.71 years) and 62 typically developing children (31 girls; mean age = 9.68 ± 1.68 years). Groups were age and sex matched. Giftedness was identified using Renzulli's 3-factor definition of giftedness. Sleep duration, quality, and night-to-night variability were assessed using actigraphy. Parents were asked to complete the short-form version of the Children's Sleep Habits Questionnaire to report on their child's sleep. Groups were compared with independent sample t-tests and chi-square analyses.

RESULTS

GC displayed lower sleep efficiencies, more wake time after sleep onset, and more night-to-night sleep variability than typically developing children. GC were found to experience less social jetlag compared to typically developing children, and they also showed more clinically significant sleep problems as reported by parents.

CONCLUSIONS

Sleep maintenance and stability tend to be challenged in GC. While there is growing evidence that greater sleep variability is associated with poorer physical and emotional health, studies have yet to examine these associations in GC specifically to get a better understanding of giftedness. Overall, there is a need for research focused on both predictors and consequences of sleep patterns and sleep variability in GC.

CITATION

Bastien L, Théoret R, Bernier A, Godbout R. Habitual sleep and intraindividual variability of sleep in gifted children: an actigraphy study. J Clin Sleep Med. 2023;19(5):925-934.

Convergence Between the Child Behavior Checklist Sleep Items, Actigraphy and Other Sleep Measures Among Children of Parents with Alcoholic Disorders and Controls

Purpose

The Child Behavior Checklist (CBCL) is a widely used instrument of children psychosocial functioning. CBCL sleep items have been used in both clinical settings and research. To date, few empirical studies have examined the relationships between CBCL sleep items and other sleep measures such as actigraphy and validated sleep questionnaires. This study extends the literature by examining these relationships in a group of children of parents with an alcohol use disorder (COAs) and matched controls.

Participants and Methods

Two hundred and forty-eight children aged 8-12 (48% COAs; 50% girls; Mean age =10.37 (Standard deviation = 1.47)), participated in this study. Data presented here were taken from Time 1 of a larger prospective study designed to understand the relationship between sleep and alcohol use. All participants were naïve to alcohol and other illicit drugs. Parents completed the Achenbach CBCL and the Pediatric Sleep Questionnaire (PSQ). Participants wore an actigraph watch on their non-dominant wrists for one week and filled out the Youth Self-Report (YSR).

Results

Multiple regression analyses showed that CBCL sleep items (eg, "trouble sleeping") correlated with related actigraphy (eg, shorter total sleep time and longer sleep onset latency) and Pediatrics Sleep Questionnaire (PSQ) items (eg, sleep difficulties and daytime sleepiness). Logistic regression analyses indicated that CBCL items (eg, "trouble sleeping) predicted similar items in the Youth Self Report (YSR) (eg, trouble sleeping). Structural equation modeling analyses showed that the latent variable "CBCL sleep" correlated significantly with the latent variables of actigraphy (r = -0.54, p < 0.001), PSQ (r = 0.93, p < 0.001) and YSR (r = 0.38, p < 0.01). These associations were largely the same for COAs and controls.

Conclusion

CBCL items were significantly associated with actigraphy variables, a validated sleep measure (PSQ) and youth report of sleep for both COAs and non-COAs.

A systematic review of proxy-report questionnaires assessing physical activity, sedentary behavior and/or sleep in young children (aged 0-5 years)

BACKGROUND

Accurate proxy-report questionnaires, adapted to the child's developmental stage, are required to monitor 24-h movement behaviors in young children, especially for large samples and low-resource settings.

OBJECTIVES

This review aimed to summarize available studies evaluating measurement properties of proxy-report questionnaires assessing physical activity, sedentary behavior and/or sleep in children aged 0-5 years.

METHODS

Systematic literature searches were carried out in the PubMed, Embase and SPORTDiscus databases, up to January 2021. For physical activity and sedentary behavior questionnaires this is a review update, whereas for sleep questionnaires we included all relevant studies published up to now. Studies had to evaluate at least one of the measurement properties of a proxy-report questionnaire assessing at least duration and/or frequency of physical activity, sedentary behavior and/or sleep in 0- to 5-year-old children. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) guideline was used to evaluate the quality of evidence.

RESULTS

Thirty-three studies were included, examining a total of 37 questionnaires. Ten questionnaires were designed for infants, two for toddlers, 11 for preschoolers, and 14 for a broader age range targeting multiple of these age groups. Twenty questionnaires assessed constructs of sleep, four assessed constructs of physical activity, two assessed screen behavior, five assessed constructs of both physical activity and sedentary behavior, and six assessed constructs of all 24-h movement behaviors. Content validity was evaluated for six questionnaires, structural validity for two, internal consistency for three, test-retest reliability for 16, measurement error for one, criterion validity for one, and construct validity for 26 questionnaires. None of the questionnaires were considered sufficiently valid and/or reliable for assessing one or more movement behaviors in 0- to 5-year-old children, and the quality of evidence was mostly low or very low.

CONCLUSIONS

Valid and/or reliable questionnaires assessing 24-h movement behaviors in 0- to 5-year-olds are lacking. High-quality studies are therefore required, to develop proxy-report questionnaires and evaluate their measurement properties.

PROSPERO REGISTRATION NUMBER

CRD42020169268.

Actigraphy in sleep research with infants and young children: Current practices and future benefits of standardized reporting

Actigraphy is a cost-efficient method to estimate sleep-wake patterns over long periods in natural settings. However, the lack of methodological standards in actigraphy research complicates the generalization of outcomes. A rapidly growing methodological diversity is visible in the field, which increasingly necessitates the detailed reporting of methodology. We address this problem and evaluate the current state of the art and recent methodological developments in actigraphy reporting with a special focus on infants and young children. Through a systematic literature search on PubMed (keywords: sleep, actigraphy, child *, preschool, children, infant), we identified 126 recent articles (published since 2012), which were classified and evaluated for reporting of actigraphy. Results show that all studies report on the number of days/nights the actigraph was worn. Reporting was good with respect to device model, placement and sleep diary, whereas reporting was worse for epoch length, algorithm, artefact identification, data loss and definition of variables. In the studies with infants only (n = 58), the majority of articles (62.1%) reported a recording of actigraphy that was continuous across 24 hr. Of these, 23 articles (63.9%) analysed the continuous 24-hr data and merely a fifth used actigraphy to quantify daytime sleep. In comparison with an evaluation in 2012, we observed small improvements in reporting of actigraphy methodology. We propose stricter adherence to standards in reporting methodology in order to streamline actigraphy research with infants and young children, to improve comparability and to facilitate big data ventures in the sleep community.

Does the Psychopathology of the Parents Predict the Developmental-Emotional Problems of the Toddlers?

Introduction

Parental psychopathology has been defined in respect of psychopathological development in early childhood. This study aimed to investigate the effects of parental psychopathologies on social and emotional problems in the age range of 1-3 years and to determine children at risk.

Methods

The study data were obtained from the 2009 Early Childhood Mental Health Profile taking population distribution into consideration with the properties representing Turkey. The primary caregiver of the child completed the Psychiatric Evaluation Form for 1-3 years, the Brief Infant-Toddler Social Emotional Assessment (BITSEA), the Ages and Stages Questionnaire (ASQ), and the Brief Symptom Inventory (BSI) for themselves. Machine learning models used for prediction. The performance of prediction models was evaluated with the ten-fold cross-validation method. Area Under Curve (AUC) values were calculated with Receiver Operating Characteristic (ROC) curves to evaluate the performance of each model.

Results

The evaluation was made of the data of 2775 children, comprising 1507 (54.3%) males and 1268 (45.7%) females with a mean age of 26.19±9.11 months (range, 10-48 months). A total of 106 children were identified as at risk, as they were above the clinical cut-off point (1.5 standard deviations) of the BITSEA points and below the cut-off points of any one of the developmental areas of the ASQ. Modeling was applied to the data of these 106 children. The Support Vector Machines (SVM) model was selected for prediction with the automatically optimized highest AUC value. Weighting for the SVM algorithm showed mothers' BSI scores, fathers' education and health problems, duration of breastfeeding, unplanned pregnancy are significant for predicting BITSEA-problem scores in the model.

Conclusion

To be able to understand the complex relationship with parental psychopathology and behavioral problems, machine learning methods were used successfully in this study. Further studies with more massive data sets, more extended follow-up periods, and stronger algorithms will be able to identify risk groups earlier and allow early interventions to be implemented.

Longitudinal Associations Among Diet Quality, Physical Activity and Sleep Onset Consistency With Body Mass Index z-Score Among Toddlers in Low-income Families

BACKGROUND

Habits surrounding health behaviors (i.e., sleep, physical activity, diet) are developed in toddlerhood. Lack of consistent health habits may increase obesity risk among toddlers in low-income families.

PURPOSE

To compare the role of sleep onset consistency, physical activity and diet quality as mediators between household poverty and toddler weight.

METHODS

Two hundred and seven toddlers (mean age = 20.2 months, 46% female, 68.1% Black) participating in an obesity prevention trial were assessed at three time points over 12 months. Using Actical accelerometers, we assessed sleep and physical activity at each time point for up to 1 week. We defined sleep onset consistency as the standard deviation of sleep onset across all days. We calculated the Healthy Eating Index-2015 from a 24-hr dietary recall. We used WHO standards to calculate BMI-for-age z-scores from toddlers' weight/length, and calculated poverty ratio from parent-reported income and family size. Multilevel mediation models tested toddler sleep onset consistency, physical activity, and diet quality as mediators between household poverty and toddler BMI z-score.

RESULTS

Toddlers from households with higher poverty ratios had more inconsistent sleep onset times. Toddlers with more inconsistent sleep onset times had higher BMI z-scores across all timepoints, even when accounting for physical activity and diet quality. Sleep onset consistency indirectly explained the association between household poverty and BMI z-score.

CONCLUSIONS

Inconsistent sleep schedules could help explain the association between poverty and BMI. Future research should examine strategies to support low-income families to develop and maintain routines as a mechanism to prevent obesity and reduce disparities.

TRIAL REGISTRATION NUMBER

NCT02615158.

A novel machine learning unsupervised algorithm for sleep/wake identification using actigraphy

Actigraphy is widely used in sleep studies but lacks a universal unsupervised algorithm for sleep/wake identification. An unsupervised algorithm is useful in large-scale population studies and in cases where polysomnography (PSG) is unavailable, as it does not require sleep outcome labels to train the model but utilizes information solely contained in actigraphy to learn sleep and wake characteristics and separate the two states. In this study, we proposed a machine learning unsupervised algorithm based on the Hidden Markov Model (HMM) for sleep/wake identification. The proposed algorithm is also an individualized approach that takes into account individual variabilities and analyzes each individual actigraphy profile separately to infer sleep and wake states. We used Actiwatch and PSG data from 43 individuals in the Multi-Ethnic Study of Atherosclerosis study to evaluate the method performance. Epoch-by-epoch comparisons and sleep variable comparisons were made between our algorithm, the unsupervised algorithm embedded in the Actiwatch software (AS), and the pre-trained supervised UCSD algorithm. Using PSG as the reference, the accuracy was 85.7% for HMM, 84.7% for AS, and 85.0% for UCSD. The sensitivity was 99.3%, 99.7%, and 98.9% for HMM, AS, and UCSD, respectively, and the specificity was 36.4%, 30.0%, and 31.7%, respectively. The Kappa statistic was 0.446 for HMM, 0.399 for AS, and 0.311 for UCSD, suggesting fair to moderate agreement between PSG and actigraphy. The Bland-Altman plots further show that the total sleep time, sleep latency, and sleep efficiency estimates by HMM were closer to PSG with narrower 95% limits of agreement than AS and UCSD. All three methods tend to overestimate sleep and underestimate wake compared to PSG. Our HMM approach is also able to differentiate relatively active and sedentary individuals by quantifying variabilities in activity counts: individuals with higher estimated activity variabilities tend to show more frequent sedentary behaviors. Our unsupervised data-driven HMM algorithm achieved better performance than the commonly used Actiwatch software algorithm and the pre-trained UCSD algorithm. HMM can help expand the application of actigraphy in cases where PSG is hard to acquire and supervised methods cannot be trained. In addition, the estimated HMM parameters can characterize individual activity patterns and sedentary tendencies that can be further utilized in downstream analysis.

Comparison Between Actigraphy Records and Parental Reports of Child's Sleep

Given the impact of sleep in several domains of a child's development, the comparison between actigraphy and parental questionnaires is of great importance in preschool-aged children, an understudied group. While parental reports tend to overestimate sleep duration, actigraphy boosts the frequency of night-waking's. Our primary goal was to compare actigraphy data and parental reports (Children's Sleep Habits Questionnaire, CSHQ), regarding bedtime, wake-up time, sleep duration, and wake after sleep onset (WASO), using the Bland-Altman technique. Forty-six children, age 3-6 years, and their parents participated. Results suggest that, despite existing associations between sleep schedule variables measured by both methods (from r = 0.57 regarding bedtime at weekends to r = 0.86 regarding wake-up time during the week, ps), differences between them were significant and agreements were weak, with parents overestimating bedtimes and wake-up times in relation to actigraphy. Differences between actigraphy and CSHQ were ± 52 min for weekly bedtime, ± 38 min for weekly wake-up time, ±159 min for total sleep time, and ± 62 min for WASO, indicating unsatisfactory agreement between methods. Correlations between actigraphy data and CSHQ dimensions are also explored. Our study contributes to the knowledge of the characteristics of each instrument, along with their tendency to overestimate and underestimate certain sleep parameters. We conclude that a complementary use of both instruments would better inform clinical practice and research on a child's sleep.

Development of sleep patterns in children with obese and normal-weight parents

AIM

To study the sleep development and sleep characteristics in children at different obesity risks, based on parental weight, and also to explore their weekday-weekend sleep variations and associated family factors.

METHODS

A total of 145 children participating in a longitudinal obesity prevention project were included, of which 37 had normal-weight parents (low obesity risk), and 108 had overweight/obese parents (high obesity risk). Sleep diaries at ages 1 and 2 years were used to study sleep development in children at different obesity risks. Objectively assessed sleep using an accelerometer at 2 years of age was used to analyse weekday-weekend sleep variations.

RESULTS

There was no difference in sleep development from age 1 to age 2 among children at different obesity risks, but more children in the high-risk group had prolonged sleep onset latency and low sleep efficiency. At 2 years of age, children in the high-risk group had more weekday-weekend variation in sleep offset (mean difference 18 min, 95% confidence interval (CI) 4-33 min), midpoint of sleep (mean difference 14 min, 95% CI 3-25 min) and nap onset (mean difference 42 min, 95% CI 10-74 min) than children in the low-risk group, after adjusting for other family factors. However, no difference could be detected between groups in weekday-weekend variation in sleep duration.

CONCLUSIONS

Unfavourable sleep characteristics, as well as more variation in sleep schedules, have been observed in children at high obesity risk. While the differences were relatively small, they may reflect the unfavourable sleep hygiene in families at high obesity risk.

Measuring sleep in young children and their mothers: Identifying actigraphic sleep composites

The present study considered multiple aspects of sleep in a community sample of young children (at ages 30, 36, and 42 months) and their mothers, using both diaries and actigraphy. Through principal components analysis, 17 of 20 commonly used actigraphy variables were reduced to four main components whose variables formed composites of: Activity, night-to-night Variability, Timing, and Duration. Sleep latency and daytime sleep variables remained separate from the composites. The same components were identified at each age, and for both children and mothers. Furthermore, the sleep composites derived from the components showed greater cross-age stability than individual actigraphy variables. Finally, child and mother sleep composites were related concurrently and longitudinally. These findings demonstrate a systematic and efficient way of summarizing child and mother sleep with actigraphy variables.

The Validity of a New Consumer-Targeted Wrist Device in Sleep Measurement: An Overnight Comparison Against Polysomnography in Children and Adolescents

STUDY OBJECTIVES

The validity of consumer-targeted wrist-worn sleep measurement systems has been little studied in children and adolescents. We examined the validity of a new fitness tracker (PFT) manufactured by Polar Electro Oy and the previously validated Actiwatch 2 (AW2) from Philips Respironics against polysomnography (PSG) in children and adolescents.

METHODS

Seventeen children (age 11.0 ± 0.8 years) and 17 adolescents (age 17.8 ± 1.8 years) wore the PFT and AW2 concurrently with an ambulatory PSG in their own home for 1 night. We compared sleep onset, offset, sleep interval (time from sleep on to offset), actual sleep time (time scored as sleep between sleep on and offset), and wake after sleep onset (WASO) between accelerometers and PSG. Sensitivity, specificity, and accuracy were calculated from the epoch-by-epoch data.

RESULTS

Both devices performed adequately against PSG, with excellent sensitivity for both age groups (> 0.91). In terms of specificity, the PFT was adequate in both groups (> 0.77), and AW2 adequate in children (0.68) and poor in adolescents (0.58). In the younger group, the PFT underestimated actual sleep time by 29.9 minutes and AW2 underestimated actual sleep time by 43.6 minutes. Both overestimated WASO, PFT by 24.4 minutes and AW2 by 20.9 minutes. In the older group, both devices underestimated actual sleep time (PFT by 20.6 minutes and AW2 by 26.8 minutes) and overestimated WASO (PFT by 12.5 minutes and AW2 by 14.3 minutes). Both devices were accurate in defining sleep onset.

CONCLUSIONS

This study suggests that this consumer-targeted wrist-worn device performs as well as, or even better than, the previously validated AW2 against PSG in children and adolescents. Both devices underestimated sleep but to a lesser extent than seen in many previous validation studies on research-targeted accelerometers.

Shorter sleep duration is associated with higher energy intake and an increase in BMI z-score in young children predisposed to overweight

BACKGROUND

Inadequate sleep has been shown to be a contributor to obesity in both children and adults. Less evidence is available for toddlers and among those with higher obesity risk. The objective of this study was to examine the relationship between sleep patterns and body weight development in a group of young obesity-predisposed children, and to assess whether intakes of energy or macronutrients mediate this relationship.

METHODS

Participants included 368 Danish children aged 2-6 years from the Healthy Start Study, a 1.3 year randomised controlled intervention trial. Sleep habits were measured using a 7-day sleep diary. Multivariate linear regression with adjustment for confounders was used to assess the association of sleep duration and sleep variability with 1.3 year changes (Δ) in body mass index (BMI) z-score from baseline to follow-up.

RESULTS

The average nighttime sleep duration was 10.7 h (range 8.8-12.5 h). After controlling for potential confounders, a significant inverse association between nighttime sleep duration and ΔBMI z-score (β=-0.090, P=0.046) was observed. This relationship was mediated by energy intake, with all macronutrients contributing to this mediation effect. No associations were found for sleep variability and ΔBMI z-score but baseline intake of added sugars and sugary beverages were positively associated with sleep variability.

CONCLUSION

Shorter sleep duration, mediated by energy intake in early in life, seems a risk factor for weight gain among young obesity-predisposed children.

Daily Sleep Patterns, Sleep Quality, and Sleep Hygiene Among Parent-Child Dyads of Young Children Newly Diagnosed With Juvenile Idiopathic Arthritis and Typically Developing Children

OBJECTIVES

Describe daily sleep patterns, sleep quality, and sleep hygiene in 2-5-year-old children newly diagnosed with juvenile idiopathic arthritis (JIA) and their parents in comparison with typically developing (TD) children and parents.

METHODS

Participants (13 JIA, 16 TD parent-child dyads) wore actigraphs for 10 days. Parents completed sleep diaries and sleep hygiene survey.

RESULTS

Children with JIA had significantly less total sleep time, lower sleep efficiency (SE), and longer naps than TD children. Parents of children with JIA had significantly earlier bedtimes, more wake after sleep onset (WASO) and lower SE than TD parents. Parent-child SE and WASO were interrelated in JIA dyads. Sleep hygiene practices were inconsistent in both groups of children.

CONCLUSIONS

Inadequate amounts of sleep and poor sleep quality were common in parent-child dyads. Early interventions to improve sleep duration and promote sleep hygiene practices may alleviate future sleep problems and improve parent and child well-being.