Open access

Systematic review of the relationships between sleep duration and health indicators in school-aged children and youth

Publication: Applied Physiology, Nutrition, and Metabolism
16 June 2016

Abstract

The objective of this systematic review was to examine the relationships between objectively and subjectively measured sleep duration and various health indicators in children and youth aged 5–17 years. Online databases were searched in January 2015 with no date or study design limits. Included studies were peer-reviewed and met the a priori-determined population (apparently healthy children and youth aged 5–17 years), intervention/exposure/comparator (various sleep durations), and outcome (adiposity, emotional regulation, cognition/academic achievement, quality of life/well-being, harms/injuries, and cardiometabolic biomarkers) criteria. Because of high levels of heterogeneity across studies, narrative syntheses were employed. A total of 141 articles (110 unique samples), including 592 215 unique participants from 40 different countries, met inclusion criteria. Overall, longer sleep duration was associated with lower adiposity indicators, better emotional regulation, better academic achievement, and better quality of life/well-being. The evidence was mixed and/or limited for the association between sleep duration and cognition, harms/injuries, and cardiometabolic biomarkers. The quality of evidence ranged from very low to high across study designs and health indicators. In conclusion, we confirmed previous investigations showing that shorter sleep duration is associated with adverse physical and mental health outcomes. However, the available evidence relies heavily on cross-sectional studies using self-reported sleep. To better inform contemporary sleep recommendations, there is a need for sleep restriction/extension interventions that examine the changes in different outcome measures against various amounts of objectively measured sleep to have a better sense of dose–response relationships.

Résumé

Cette analyse systématique a pour objectif d’examiner la relation entre la mesure objective et subjective de la durée du sommeil et d’autres indicateurs sanitaires chez des enfants et des jeunes âgés de 5 à 17 ans. En janvier 2015, une recherche est faite dans les bases de données en ligne sans contrainte de date et de devis utilisé. Les études retenues sont sanctionnées par des pairs et sont conformes aux critères a priori déterminés : la population (des jeunes apparemment en bonne santé âgés de 5 à 17 ans), l’intervention/exposition/comparaison (durées variées du sommeil) et le résultat (adiposité, contrôle des émotions, cognition/rendement scolaire, qualité de vie/bien-être, préjudices/blessures et biomarqueurs cardiométaboliques). À cause du haut niveau d’hétérogénéité des études, on utilise des synthèses narratives. Au total, 141 articles (110 échantillons originaux) incluant 592 215 participants distincts de 40 pays différents sont conformes aux critères d’inclusion. Globalement, une plus longue durée de sommeil est associée aux indicateurs de plus faible adiposité, meilleur contrôle des émotions, meilleur rendement scolaire et meilleure qualité de vie/bien-être. Les données probantes sont mitigées et/ou limitées concernant l’association entre la durée du sommeil et la cognition, les préjudices/blessures et les biomarqueurs cardiométaboliques. La qualité des données probantes varie de très basse à élevée dépendamment des devis et des indicateurs de santé. En conclusion, nous confirmons les études antérieures indiquant une association entre une durée de sommeil plus courte et des effets négatifs sur la santé physique et mentale. Toutefois, les données probantes disponibles sont issues surtout d’études transversales utilisant un témoignage des sujets sur leur sommeil. Pour mieux appuyer les recommandations contemporaines en matière de sommeil, il faut réaliser des études sur la restriction/prolongation du sommeil qui examinent les variables dépendantes en relation avec diverses durées de sommeil objectivement mesurées afin d’établir une meilleure relation dose–réponse. [Traduit par la Rédaction]

Introduction

Sleep is an essential component of healthy development and is required for physical and mental health. However, sleep deprivation has become common in contemporary societies with 24/7 availability of commodities (Akerstedt and Nilsson 2003; Ohayon 2012). School-aged children and youth generally sleep less now compared with decades ago (Keyes et al. 2015; Matricciani et al. 2012a), and factors responsible for this secular decline in sleep duration are generally ascribed to the modern way of living (e.g., artificial light, late-night screen time, caffeine use, and no bedtime rules in the household) (Gruber et al. 2014). Chronic sleep loss and associated sleepiness and daytime impairments pose serious threats to the academic success, health, and safety of children and youth and are important public health issues (Owens 2014). Understanding the implications of insufficient sleep during childhood is critical in setting public policies and developing promising strategies aimed at mitigating the adverse effects of sleep deprivation.
A large number of studies have confirmed the importance of healthy sleep for various outcomes; however, a systematic review of studies that examined the influence of sleep duration on key health indicators in children and youth, a critical period for growth and development, is lacking. A comprehensive assessment of the relationships between sleep duration and various health indicators in children and youth is important to determine if the current sleep duration recommendations are evidence-informed. The National Sleep Foundation recommends sleeping between 9–11 h/night for school-aged children (ages 6–13 years) and 8–10 h/night for adolescents (ages 14–17 years) to maximize overall health and well-being (Hirshkowitz et al. 2015). Although the ideal amount of sleep per night varies from one person to another, sleep duration recommendations play an important role in informing public policies, guidelines, interventions, and parents and children/youth of healthy sleep behaviours (Matricciani et al. 2012b, 2013).
The objective of this systematic review was to examine the relationships between objectively and subjectively measured sleep duration and a broad range of health indicators in children and youth aged 5–17 years. Findings from this review will help inform and possibly confirm current sleep duration recommendations for children and youth.

Materials and methods

Protocol and registration

This review was registered a priori with the International Prospective Register of Ongoing Systematic Reviews (PROSPERO; registration no. CRD42015015492; available from www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42015015492), and was conducted following the PRISMA statement for reporting systematic reviews and meta-analyses (Moher et al. 2009).

Eligibility criteria

The participants, interventions, comparisons, outcomes, and study design (PICOS) framework (Schardt et al. 2007) was followed to identify key study concepts in the research question a priori, and to facilitate the search process.

Population

Apparently healthy (including children with overweight and obesity) school-aged children and youth, aged 5–17 years (mean age 5–17.99 years) for at least 1 exposure measurement point. Clinical populations (e.g., patients with sleep apnea) were excluded.

Intervention (exposure)

Various sleep durations. Studies were included if they used objective (polysomnography, actigraphy, accelerometry) or subjective (self-report, proxy-report) measures.

Comparison

Various sleep durations. However, a comparator or control group was not required for inclusion.

Outcome

Six health indicators were chosen based on the literature, expert input and consensus, and recognition of the importance of including a broad range of health indicators. Five health indicators were identified as critical (primary) by expert agreement: (i) adiposity markers; (ii) emotional regulation (e.g., stress, anxiety, depressive symptoms, mental health); (iii) cognition/academic achievement; (iv) quality of life/well-being; and (v) harms/injuries. One health indicator was identified as important (secondary) by expert agreement: cardiometabolic biomarkers (i.e., metabolic syndrome and cardiovascular disease risk factors).

Study design

All study designs were considered. For longitudinal studies, any follow-up length was allowed as long as the exposure was measured before follow-up at least once during the identified age range. Randomized controlled trials and other randomized interventions were required to have at least 30 participants in the intervention group. Observational studies were required to have a minimum sample size of 300 participants. For feasibility reasons related to the large number of studies examining adiposity, cross-sectional studies that examined adiposity and that used a self-report assessment of sleep were required to have a minimum sample size of 1000 participants.

Information sources and search strategy

The electronic search strategy was created by a research librarian with expertise in systematic review searching and peer-reviewed by a second research librarian. See Supplement S12 for complete search strategies. The following databases were searched using the Ovid interface: MEDLINE (1946 to January 19, 2015), EMBASE (1980 to 2015 week 3), PsychINFO (1906 to 2015 week 3), and CINAHL (1961 to 2015 week 3).

Study selection

Bibliographic records were extracted as text files from the OVID and EBSCO interfaces and imported into Reference Manager Software (Thompson Reuters, San Francisco, Calif., USA) for removal of duplicate references. Titles and abstracts of potentially relevant articles were imported to DistillerSR (a secure, internet-based software; Evidence Partners, Ottawa, Ont., Canada) where they were screened independently by 2 reviewers. Exclusion by both reviewers was required for a study to be excluded at level 1; all other papers passed to level 2, where 2 independent reviewers examined all full-text articles. Consensus was required for articles to be included; discrepancies between reviewers were resolved by discussion between them or with a third reviewer, if needed. Reference lists of included articles and relevant reviews were also checked for additional relevant studies. Published peer-reviewed original manuscripts and in-press manuscripts were eligible for inclusion. Studies were included if they were published in English or could be translated using Google Translate.

Data collection process

Data extraction forms were created by the study coordinators, reviewed by study collaborators, and piloted by all reviewers. Extraction was completed in DistillerSR by 1 reviewer and exported to Excel (Microsoft) to be checked for accuracy by a second reviewer. Reviewers were not blinded to the authors or journals when extracting data. Results were extracted from the most fully adjusted models for studies that reported findings from multiple models.

Data items

Important study features (e.g., publication year, study design, country, sample size, age, and sex of participants, measure of sleep and health outcomes, results, and confounders) were extracted.

Quality assessment

The risk of bias in primary research studies contributing to each health indicator was systematically evaluated using the methods described in the Cochrane Handbook (Higgins and Green 2011). The quality of evidence (i.e., the level of confidence that the estimates of effect are correct) for each health indicator by each type of study design was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework (Guyatt et al. 2011). According to the GRADE framework, which categorizes evidence quality into 4 groups (“high”, “moderate”, “low”, or “very low”), evidence quality ratings start at high for randomized studies and low for all other experimental and observational studies. The quality of evidence is downgraded if there are limitations across studies because of serious risk of bias, inconsistency of relative treatment effects, indirectness, imprecision, or other factors. If there is no cause to downgrade, the quality of evidence can be upgraded if there is a large effect size, there is a dose–response gradient, or if all plausible confounders would decrease an apparent treatment effect. Overall quality of evidence for each study design within each health outcome was assessed by 1 reviewer and verified by the larger review team, including 3 systematic review methodology experts.

Data synthesis

Meta-analyses were planned if results were found to be sufficiently homogenous in terms of statistical, clinical, and methodological characteristics. However, it was determined that a meta-analysis was not possible because of high levels of heterogeneity for the above characteristics across studies, and a narrative synthesis was performed for each health indicator.

Results

Description of studies

As shown in Fig. 1, a total of 5815 records were identified through database searches and an additional 10 unique records were identified through reference list searches and through the review team and collaborators. After de-duplication, a total of 4493 records remained. After titles and abstracts were screened, 318 full-text articles were obtained for further review and 141 articles met the inclusion criteria (110 unique samples). Reasons for excluding articles included ineligible age (n = 35), no measure of sleep duration (n = 39), no measure of a health indicator of interest (n = 35), clinical population (n = 5), not original research (e.g., review; n = 2), sample size too small (n = 51), non-English language article that could not be translated by Google Translate (n = 5), and unable to obtain the full text (n = 5). Some studies were excluded for multiple reasons.
Fig. 1.
Fig. 1. PRISMA flow diagram for the identification, screening, eligibility, and inclusion of studies.
Individual study characteristics are summarized in Supplementary Table S12 (n = 186, because some articles had more than 1 outcome measure). Data across studies involved 592 215 participants (from unique samples) and 40 different countries. Individual studies were randomized trials (n = 6), longitudinal studies (n = 33), cross-sectional studies (n = 145), or case-control studies (n = 2). Sleep duration was measured objectively (polysomnography or actigraphy/accelerometry) in 29 studies. In the remaining 157 studies, sleep duration was measured subjectively via self-report or parent-report questionnaires.

Data synthesis

Adiposity

A total of 71 studies examined the association between sleep duration and adiposity indicators (Table 1 and Supplementary Table S12). One study used a randomized cross-over design, 12 studies used a longitudinal design, and 58 studies used a cross-sectional design. The randomized trial (Hart et al. 2013) showed that increased sleep duration resulted in lower weight after a week compared with decreased sleep (mean difference in weight of 0.24 kg, p < 0.001, Cohen’s d = 0.93). There was a 2.4-h sleep duration difference between conditions (10.5 h vs. 8.1 h for the increased and decreased sleep, respectively, as reported with actigraphy). The quality of evidence was downgraded from high to moderate because only 1 randomized trial was published, so the risk of imprecision is high. Among the 12 longitudinal studies, 7 reported a significant association between short sleep duration and adiposity gain while 5 reported null findings. The quality of evidence was downgraded from low to very low because of a serious risk of bias. More specifically, only 2 studies (Hjorth et al. 2014a, 2014b) out of the 12 longitudinal studies used an objective measure of sleep duration. Finally, a total of 50 cross-sectional studies (out of 58) reported a significant association between short sleep duration and excess adiposity. The other 8 studies reported null findings. Despite a serious risk of bias (i.e., most studies used a subjective assessment of sleep with no psychometric properties reported), the quality of evidence remained at low (as opposed to very low) because of the large effect observed and the evidence of a dose–response gradient between sleep duration and adiposity (upgrade). Indeed, longer sleep was consistently associated with lower adiposity indicators and with large effect sizes overall.
Table 1.
Table 1. Association between sleep duration and adiposity in children and youth.

Note: Mean age ranged between 5 and 17.7 years. Intervention study was 1 week long and up to 6 years for longitudinal studies. Sleep duration was assessed by actigraphy, polysomnography, parent report, or self-report. Adiposity was assessed as body weight, body mass index (absolute, z score, or percentile), fat mass index, waist circumference, waist-to-height ratio, weight status (different definitions for underweight, normal weight, overweight, obese) or % body fat (bioelectrical impedance, dual-energy X-ray absorptiometry, skinfolds), either objectively or subjectively.

a
Randomized cross-over study (Hart et al. 2013).
b
Only 1 study was published so the risk of imprecision is high (the quality of evidence was downgraded from high to moderate).
d
Only 2 studies used an objective assessment of sleep duration (the quality of evidence was downgraded from low to very low).
e
f
Most studies used a subjective assessment of sleep with no psychometric properties reported (the quality of evidence was downgraded from low to very low). However, the quality of evidence for the cross-sectional studies was upgraded to low because of the large effect observed and the evidence of a dose–response gradient between sleep duration and adiposity (i.e., longer sleep is associated with lower adiposity indicators). Because of heterogeneity in the measurement of sleep and adiposity, a meta-analysis was not possible.

Emotional regulation

A total of 62 studies examined the association between sleep duration and emotional regulation, such as stress, anxiety, depressive symptoms, and mental health (Table 2 and Supplementary Table S12). Four studies were randomized experiments, 11 studies used a longitudinal design, and 47 studies used a cross-sectional design. All 4 randomized trials (Baum et al. 2014; Dagys et al. 2012; Tamura and Tanaka 2014; Vriend et al. 2013) were consistent in showing better emotional regulation in the healthy sleep group compared with the sleep-restricted one. The quality of evidence was rated as high for the randomized trials. Among the 11 longitudinal studies, 8 reported that longer sleep was associated with better emotional regulation at follow-up (Barlett et al. 2012; Fredriksen et al. 2004; Kalak et al. 2014; Lin and Yi 2015; Lumeng et al. 2007; Pasch et al. 2012; Roberts and Duong 2014; Roberts et al. 2009) while 3 reported no association (Asarnow et al. 2014; Chang and Gable 2013; Silva et al. 2011). Given that only 1 study used an objective assessment of sleep duration (Silva et al. 2011), the quality of evidence was downgraded from low to very low (serious risk of bias). Among the 47 cross-sectional studies, 37 reported that longer sleep was related to better emotional regulation, 8 reported null findings, and 2 reported opposite associations. The quality of evidence was downgraded from low to very low because of a serious risk of bias (i.e., most studies used a subjective assessment of sleep with no psychometric properties reported).
Table 2.
Table 2. Association between sleep duration and emotional regulation in children and youth.

Note: Mean age ranged between 7.6 and 17.3 years. Intervention studies were between 2 days and 2 weeks, and longitudinal studies were up to 8 years. Sleep duration was assessed by actigraphy, polysomnography, parent report or self-report. Emotional regulation was assessed through various self-reported instruments.

a
Includes 3 randomized cross-over studies (Vriend et al. 2013; Baum et al. 2014; Dagys et al. 2012) and 1 randomized controlled trial (Tamura and Tanaka 2014).
c
Only 1 study used an objective assessment of sleep (the quality of evidence was downgraded from low to very low).
d
e
Most studies used a subjective assessment of sleep with no psychometric properties reported (the quality of evidence was downgraded from low to very low). Because of heterogeneity in the measurement of sleep and emotional regulation, a meta-analysis was not possible.

Cognition/academic achievement

A total of 6 studies examined the association between sleep duration and cognition (e.g., concentration and memory) (Table 3 and Supplementary Table S12). Only 1 randomized trial examined this association (Vriend et al. 2013) and found that short-term memory, working memory, divided attention, and math fluency scores were lower in children in the short sleep condition (1 h later in bed for 4 nights with usual wake-up time) compared with long sleep (1 h earlier for 4 nights relative to their typical bedtime). However, no differences were found for reaction time on alerting, orienting, sustained, or executive attention tasks between long and short sleep conditions. Because of serious imprecision (small effect sizes and only 1 study), we downgraded the quality of evidence from high to moderate. The only longitudinal study (Silva et al. 2011) reported no increased odds of having learning problems across sleep duration categories. The quality of evidence for this study design was downgraded from low to very low because only 1 study was published (serious imprecision). Finally, the 4 cross-sectional studies reported either positive, negative, or null findings (Kim et al. 2011; McClure et al. 2014; Ortega et al. 2010; van der Heijden et al. 2013). The quality of evidence was downgraded from low to very low because of a serious risk of bias (all studies used a subjective assessment of sleep with no psychometric properties reported) and serious inconsistency (mixed findings observed).
Table 3.
Table 3. Association between sleep duration and cognition in children and youth.

Note: Mean age ranged between 8 and 17 years. Data were collected cross-sectionally and up to 5 years of follow-up. Sleep duration was assessed by actigraphy, polysomnography, parent report, or self-report. Cognition was measured by numerous computer testing modalities, and other tests/questionnaires: the CBCL, the TEA test, the CCTT (versions 1–2), the WISC-III, and the MFT. CBCL, Child Behaviour Checklist; CCTT, Children’s Colour Trails Test; MFT, Math Fluency Task; TEA, Test of Educational Ability; WISC III, Wechsler Intelligence Scale for Children-Third Edition.

a
Randomized cross-over study (Vriend et al. 2013).
b
Large standard deviations, small effect sizes, and only 1 study was published so the risk of imprecision is high (the quality of evidence was downgraded from high to moderate).
c
Includes 1 longitudinal study (Silva et al. 2011).
d
Only 1 study was published so the risk of imprecision is high (the quality of evidence was downgraded from low to very low).
f
All studies used a subjective assessment of sleep with no psychometric properties reported.
g
Studies reported either positive, negative, or null findings. Therefore, the quality of evidence was downgraded from low to very low. Because of heterogeneity in the measurement of sleep and cognition, a meta-analysis was not possible.
With regard to the association between sleep duration and academic achievement (Table 4 and Supplementary Table S12), 3 out of 4 longitudinal studies reported poorer grades with short sleep duration (Fredriksen et al. 2004; Lin and Yi 2015; Roberts et al. 2009). However, Asarnow et al. (2014) reported that short sleep duration did not predict cumulative Grade Point Average at follow-up. The quality of evidence was downgraded from low to very low because of a serious risk of bias (all studies used a subjective assessment of sleep with no psychometric properties reported). Among the 17 cross-sectional studies, 11 showed associations for longer sleep duration and better academic achievement, or shorter sleep duration and poorer academic achievement, while the other studies reported either null (n = 5) or opposite (n = 1) findings. The quality of evidence was downgraded from low to very low because of a serious risk of bias (most studies used a subjective assessment of sleep with no psychometric properties reported) and serious indirectness (only half of the studies assessed children’s actual grades or test results).
Table 4.
Table 4. Association between sleep duration and academic achievement in children and youth.

Note: Mean age ranged between 12 and 17.3 years. Data were collected cross-sectionally and up to 6 years of follow-up. Sleep duration was assessed by parent report or self-report. Academic achievement metrics were assessed by official school transcripts, GPA, self-report questionnaire, WJ-R, and NAPLAN. GPA, Grade Point Average; NAPLAN, National Assessment Program for Literacy and Numeracy; WJ-R, Woodcock-Johnson Psycho-Educational Battery-Revised test.

b
All studies used a subjective assessment of sleep with no psychometric properties reported (the quality of evidence was downgraded from low to very low).
d
Most studies used a subjective assessment of sleep with no psychometric properties reported.
e
Of the 17 studies, 8 examined student’s actual grades/test results while 9 studies used self-report metrics (not all asked for students to report their grades; some questions referred to if students felt they feel behind in school, how well to perform relative to your peers academically, etc.). It may be reasonable to assume that the “gold standard” would be to assess children/youth’s actual grades. Since only half of the studies did this, downgrading has been decided (from low to very low). Because of heterogeneity in the measurement of sleep and academic achievement, a meta-analysis was not possible.

Quality of life/well-being

Only 3 studies examined the relationship between sleep duration and quality of life/well-being (Table 5 and Supplementary Table S12). The longitudinal study by Roberts et al. (2009) showed that participants with short sleep duration (≤6 h) at baseline had increased odds of low life satisfaction at 1-year follow-up (odds ratio = 1.73, 95% confidence interval: 1.17–1.54). The quality of evidence was downgraded from low to very low for this study design because of a serious risk of bias (sleep duration was self-reported with no psychometric properties reported) and serious imprecision (only 1 study was published so the risk of imprecision is high). Both cross-sectional studies (Do et al. 2013; Perkinson-Gloor et al. 2013) reported better quality of life and well-being with longer sleep duration. The quality of evidence was downgraded from low to very low because of a serious risk of bias (both studies relied on self-reported sleep with no psychometric properties reported).
Table 5.
Table 5. Association between sleep duration and quality of life/well-being in children and youth.

Note: Mean age ranged between 11 and 18 years. Data were collected cross-sectionally and up to 1 year. Sleep duration was assessed by self-report. Quality of life/well-being was assessed by self-report as life satisfaction (Mental Health Diagnostic Interview Schedule for Children, Version IV), positive attitude towards life (Berne Questionnaire on Adolescent Subjective Well-Being), and self-rated health (single question). CI, confidence interval; OR, odds ratio.

a
Includes 1 longitudinal study (Roberts et al. 2009).
b
Sleep duration was self-reported with no psychometric properties reported.
c
Only 1 study was published so the risk of imprecision is high. Therefore, the quality of evidence was downgraded from low to very low.
d
Includes 2 cross-sectional studies (Perkinson-Gloor et al. 2013; Do et al. 2013).
e
Both studies used a subjective assessment of sleep with no psychometric properties reported (the quality of evidence was downgraded from low to very low). Because of heterogeneity in the measurement of sleep and quality of life/well-being, a meta-analysis was not possible.

Harms/injuries

A total of 4 studies looked at the association between sleep duration and harms/injuries (1 longitudinal, 1 cross-sectional, and 2 case-control studies) (Table 6 and Supplementary Table S12). The longitudinal study showed that children who slept <10 h/night at age 7 years had greater odds of migraine but not tension-type headache at age 11 years (Waldie et al. 2014). The quality of evidence was downgraded from low to very low because of serious imprecision (only 1 study). The cross-sectional study showed that adolescents who slept <7 h/night did not have greater odds of single injury compared with those who slept ≥7 h/night (Lam and Yang 2007). However, adolescents who slept <7 h/night were more likely to have experienced multiple episodes of injury during the 3 months prior to the survey compared with those who slept ≥7 h/night. The quality of evidence was downgraded from low to very low because of a serious risk of bias (sleep duration was self-reported with no psychometric properties reported) and serious imprecision (only 1 study). Finally, the 2 case-control studies reported different findings. Rafii et al. (2013) found that sleep duration was shorter in the injury group compared with the non-injury group, while Li et al. (2008) showed no difference in sleep duration in the case versus control groups. Here again, the quality of evidence was downgraded from low to very low because of a serious risk of bias (sleep duration was self-reported in both studies with no psychometric properties reported).
Table 6.
Table 6. Association between sleep duration and harms/injuries in children and youth.

Note: Mean age ranged between 8–14 years. Data were collected cross-sectionally and up to 4 years. Sleep duration was assessed by actigraphy, parent report or self-report. Harms/injuries were assessed by structured health interviews with parents, children and school nurses. CI, confidence interval; OR, odds ratio.

a
Includes 1 longitudinal study (Waldie et al. 2014).
b
Only 1 study was published so the risk of imprecision is high. Therefore, the quality of evidence was downgraded from low to very low.
c
Includes 1 cross-sectional study (Lam and Yang 2007).
d
Sleep duration was self-reported with no psychometric properties reported.
e
Only 1 study was published so the risk of imprecision is high. Therefore, the quality of evidence was downgraded from low to very low.
f
Includes 2 case-control studies (Li et al. 2008; Rafii et al. 2013).
g
Sleep duration was self-reported in both studies with no psychometric properties reported. Therefore, the quality of evidence was downgraded from low to very low. Because of heterogeneity in the measurement of sleep and harms/injuries, a meta-analysis was not possible.

Cardiometabolic biomarkers

A total of 19 studies investigated the association between sleep duration and various cardiometabolic biomarkers (Table 7 and Supplementary Table S12). The 3 longitudinal studies included in this review (Archbold et al. 2012; Hancox and Landhuis 2012; Hjorth et al. 2014a) reported mixed findings (either short sleep associated with adverse cardiometabolic biomarkers or null findings). The quality of evidence was rated as low. Finally, the 16 cross-sectional studies also reported mixed findings. The quality of evidence was downgraded from low to very low because of a serious risk of bias (most studies used a subjective assessment of sleep duration with no psychometric properties reported) and serious inconsistency (positive, negative, or null findings).
Table 7.
Table 7. Association between sleep duration and cardiometabolic biomarkers in children and youth.

Note: Mean age ranged between 7.9 and 16.7 years. Data were collected cross-sectionally and up to 5 years. Sleep duration was assessed by actigraphy, polysomnography, parent report, or self-report. Cardiometabolic biomarkers were measured objectively using fasting and non-fasting blood samples, blood pressure devices, various assays, Holter monitors, and elastic electrode belts; conventional lab methods were employed and all tests were performed by trained research staff or nurses. CI, confidence interval; CRP, C-reactive protein; CV, cardiovascular; DBP, diastolic blood pressure; HDL, high density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; HRV, heart rate variability; IL-4, interleukin-4LDL, low density lipoprotein; SBP, systolic blood pressure; SE, standard error; TC, total cholesterol; TGs, triglycerides; TNF, tumor necrosis factor.

c
Most studies used a subjective assessment of sleep with no psychometric properties reported.
d
Mixed findings observed. Therefore, the quality of evidence was downgraded from low to very low. Because of heterogeneity in the measurement of sleep and cardiometabolic biomarkers, a meta-analysis was not possible.
A high-level summary of findings by health outcome can also be found in Table 8.
Table 8.
Table 8. High-level summary of findings by health indicator.

Discussion

This systematic review synthesized peer-reviewed evidence from 141 articles examining the relationships between sleep duration and a broad range of health indicators in children and youth aged 5–17 years. A total of 1 241 056 participants from 40 different countries were represented in this review (n = 592 215 participants from unique samples). The overall quality of evidence ranged from very low to high across study designs and health indicators. Collectively, the preponderance of the evidence suggests that shorter sleep duration is associated with adverse physical and mental health in children and youth (i.e., excess adiposity, poorer emotional regulation and academic achievement, and lower quality of life/well-being). This comprehensive assessment of available evidence highlights the need for continued efforts promoting the importance of a good night’s sleep for overall health. It also highlights the need for higher quality studies with the hope of better informing sleep duration recommendations for children and youth.
An important observation of the available evidence in this field of research is the lack of use of objective measures for sleep duration. Among the 141 studies included in this systematic review, only 29 (20%) had an objective assessment of sleep duration. Although polysomnography is considered the gold standard technique in laboratory experiments, actigraphy is gaining popularity for the assessment of sleep in epidemiologic research (Meltzer et al. 2012). While actigraphy can have its own challenges, it generally provides a good objective estimate of sleep duration (Sadeh 2011). In contrast, sleep questions typically used in epidemiologic studies do not agree very well with objective measures of sleep as assessed using actigraphy (Girschik et al. 2012). This can certainly have implications for studies that are using self-reported sleep and it emphasizes the need for more accurate measures of sleep duration in future studies.
Another observation is the lack of studies examining the association between sleep duration and health indicators, such as quality of life/well-being and harms/injuries in children and youth. One explanation is that the majority of research looking at these relationships is done in the adult population. Additionally, the inclusion criteria used for the present systematic review (n ≥ 300 participants for observational studies and n ≥ 30 participants for intervention studies) may have resulted in the exclusion of a number of studies in this area with smaller samples. We also excluded clinical populations from the present review (e.g., patients with sleep disorders such as insomnia or obstructive sleep apnea). It is well-known that these individuals have a higher risk of accidents and reduced quality of life in general (Gruber et al. 2014), which suggests an association between sleep duration/quality and these health indicators, although whether these relationships can be extrapolated to apparently healthy populations is unclear. Inclusion/exclusion criteria were made a priori by a group of experts in the field with an objective to determine the optimal amount of sleep that is associated with improved health outcomes in apparently healthy children and youth. As a result, limiting the sample size of included studies allowed for inclusion of a broader range of health outcomes while keeping the review manageable.
As discussed earlier, an objective of this article was to examine if the current sleep duration recommendations issued by the National Sleep Foundation are consistent with the best available evidence. The National Sleep Foundation recommends between 9–11 h of sleep per night for school-aged children (ages 6–13 years) and 8–10 h of sleep per night for adolescents (ages 14–17 years) to maximize overall health and well-being (Hirshkowitz et al. 2015). The National Sleep Foundation convened a multidisciplinary expert panel to evaluate the latest scientific evidence, including a consensus and voting process. Then, the RAND/UCLA Appropriateness Method was used to formulate sleep duration recommendations. A clear observation is that the best available evidence that can inform the sleep duration recommendations is weak, suggesting that expert opinion is needed until we have more research. There is a clear need for sleep restriction/extension interventions in children and youth that try to determine upper and lower limits of healthy sleep duration (i.e., dose–response curve). Although current sleep recommendations tend to suggest that a generalized optimum exists for the population, it is possible that different optimal sleep durations exist for different health outcomes (Matricciani et al. 2013). There is also inter-individual variability in sleep needs (e.g., because of genetic differences or sociocultural contexts) and sleeping longer or shorter than the recommended times may not necessarily mean that it will adversely affect health. However, individuals with sleep durations far outside the normal range may be engaging in behavioural sleep restriction or may have other health problems. Intentionally restricting sleep duration over a prolonged period of time may compromise overall health (Hirshkowitz et al. 2015).
Sleep duration recommendations provide ranges and imply that there is a U-shaped relationship between sleep time and health outcomes. While this is more evident in adults, a majority of studies included in this systematic review (especially with adiposity as the outcome measure) showed that more sleep is better. However, not all studies used categories of sleep duration and were not able to examine this issue. Also, some studies had small variability in sleep durations so there was inadequate resolution to assess whether long sleep was associated with adverse health outcomes. It is increasingly recognized that the 2 peaks of the U-shaped association between sleep and health outcomes do not mean the same thing (Knutson and Turek 2006). While short sleep is consistently associated with adverse health outcomes, long sleep is generally associated with other health problems that may confound the association. This further highlights the need to rely on objective assessments of sleep because time in bed does not necessarily reflect actual sleep duration. There is also the possibility of displacing other behaviours if one spends too much time in bed (e.g., less time for physical activity). Thus, it appears logical to have a range of “healthy” or “optimal” sleep duration from a population health standpoint.
It is also important to remember that the present systematic review focused on sleep duration only. However, an assessment of optimal sleep reaches well beyond the notion of sleep quantity, and includes sleep quality (i.e., efficiency of staying asleep), timing (i.e., bedtime/wake up time), architecture (i.e., sleep stages), consistency (i.e., day-to-day variability), and continuity (i.e., variability in sleep duration within the same night). Furthermore, a constraint of such a large review is that it precludes a detailed analysis (e.g., trends related to age, sex differences, possibility of conflicting results depending on the sleep assessment used, etc.). It is also well-known that self-reported sleep duration overestimates actual sleep duration compared with objective measures. This can have important implications for sleep duration recommendations if future studies rely more heavily on objective assessments of sleep, because it will result in different sleep duration optima (i.e., lower for the objective measure and higher for the subjective measure). However, if parents and their children/youth are key targets for the sleep duration recommendations, it is more likely that they will use time in bed as their estimation of sleep duration.
In conclusion, the present article was the first to systematically examine the associations between sleep duration and such a large range of health indicators in children and youth. We confirmed previous investigations showing that shorter sleep duration is associated with adverse physical and mental health outcomes; however, the available evidence relies heavily on cross-sectional studies using self-reported sleep duration. To better inform contemporary sleep recommendations, there is an urgent need for sleep restriction/extension interventions in children and youth that examine the changes in different outcome measures against various amounts of sleep to have a better idea of dose–response relationships.

Conflict of interest statement

Michelle E. Kho received an honorarium for methodological input to guideline development. The other authors declare no conflicts of interest.

Acknowledgements

This study has been made possible through funding from the Canadian Society for Exercise Physiology, Healthy Active Living and Obesity Research Group from the Children’s Hospital of Eastern Ontario Research Institute, Conference Board of Canada, and the Public Health Agency of Canada.

Footnote

2
Supplementary data are available with the article through the journal Web site at Supplementary Material.

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Supplementary Material

Supplementary data (apnm-2015-0627suppla.doc)
Supplementary data (apnm-2015-0627supplb.doc)

Information & Authors

Information

Published In

cover image Applied Physiology, Nutrition, and Metabolism
Applied Physiology, Nutrition, and Metabolism
Volume 41Number 6 (Suppl. 3)June 2016
Pages: S266 - S282

History

Received: 13 November 2015
Accepted: 13 January 2016
Version of record online: 16 June 2016

Notes

This paper is part of a Special issue entitled Canadian 24-Hour Movement Guidelines for Children and Youth: An Integration of Physical Activity, Sedentary Behaviour, and Sleep.

Key Words

  1. sleep duration
  2. adiposity
  3. body weight
  4. emotional regulation
  5. mental health
  6. cognition
  7. academic achievement
  8. quality of life
  9. well-being
  10. injuries

Mots-clés

  1. durée du sommeil
  2. adiposité
  3. masse corporelle
  4. contrôle des émotions
  5. santé mentale
  6. cognition
  7. rendement scolaire
  8. qualité de vie
  9. bien-être
  10. blessures

Authors

Affiliations

Jean-Philippe Chaput [email protected]
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Casey E. Gray
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Veronica J. Poitras
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Valerie Carson
Faculty of Physical Education and Recreation, University of Alberta, Edmonton, AB, Canada.
Reut Gruber
Attention, Behavior, and Sleep Laboratory, Douglas Mental Health University Institute, Verdun, QC, Canada.
Timothy Olds
Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute of Health Research, University of South Australia, Adelaide, Australia.
Shelly K. Weiss
Division of Neurology, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
Sarah Connor Gorber*
Office of the Task Force on Preventive Health Care, Public Health Agency of Canada, Ottawa, ON, Canada.
Michelle E. Kho
School of Rehabilitation Science, McMaster University, Hamilton, ON, Canada.
Margaret Sampson
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Kevin Belanger
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Sheniz Eryuzlu
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Laura Callender
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.
Mark S. Tremblay
Healthy Active Living and Obesity Research Group, Children’s Hospital of Eastern Ontario Research Institute, 401 Smyth Road, Ottawa, ON K1H 8L1, Canada.

Notes

*
Present address: Canadian Institutes of Health Research, Ottawa, ON, Canada.
Copyright remains with the author(s) or their institution(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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