PEDIATRICS Vol. 119 No. 1 January 2007, pp. 86-93 (doi:10.1542/peds.2006-1757)
ARTICLE |
Adverse Associations of Sleep Problems in Australian Preschoolers: National Population Study
a Centre for Community Child Health
d Clinical Epidemiology and Biostatistics Unit, Royal Children's Hospital, Melbourne, Australia
b Murdoch Childrens Research Institute, Melbourne, Australia
c Department of Paediatrics, University of Melbourne, Melbourne, Australia
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ABSTRACT |
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 TOP ABSTRACT METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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OBJECTIVE. In contrast to school-aged children, the impact of sleep problems in preschool-aged children is not well documented. We aimed to determine relationships between preschool-aged child sleep problems and child behavior; health-related quality of life; verbal, preliteracy, and early numeracy skills; diagnosis of attention-deficit/hyperactivity disorder; and injury.
PARTICIPANTS AND METHODS. Participants included families (n = 4983) participating in the first wave of the Longitudinal Study of Australian Children, a nationally representative study of Australian children aged 4 to 5 years surveyed from March to November 2004. Measures consisted of a primary caregiver's report of whether their child had a sleep problem (none versus mild versus moderate/severe); specific sleep patterns occurring 
4 nights per week; health-related quality of life (by using the Pediatric Quality of Life Inventory 4.0); behavior (by using the Strengths and Difficulties Questionnaire) and parent-reported diagnosis of attention-deficit/hyperactivity disorder; and injury requiring medical attention in the past 12 months. Tests of receptive vocabulary and preliteracy/numeracy skills (by using the Who Am I? developmental assessment and the adapted Peabody Picture Vocabulary Test, 3rd Edition) were directly administered to each child.
RESULTS. Sleep problems were common, and compared with children without sleep problems, children with sleep problems had poorer child health-related quality of life, more behavior problems, and higher rates of attention-deficit/hyperactivity disorder. Difficulty going to sleep and morning tiredness had greater adverse associations than snoring or night waking.
CONCLUSIONS. Given that sleep problems are very common, the adverse outcomes shown here could affect the transition to school for a very large number of preschoolers.
Key Words: sleep • preschool-aged children • behavior • health-related quality of life • injury • literacy • receptive language
Abbreviations: HRQoL—health-related quality of life • LSAC—Longitudinal Study of Australian Children • SDQ—Strengths and Difficulties Questionnaire • ADD—attention-deficit disorder • ADHD—attention-deficit/hyperactivity disorder • PedsQL—Pediatric Quality of Life Inventory 4.0 • PPVT-III—Peabody Picture Vocabulary Test, 3rd Edition • WAI—Who Am I? • CI—confidence interval
Sleep problems in preschool-aged children are common, with 14% to 27% of parents reporting a problem with their child's sleep between the ages of 4 and 6 years.1,2 Problematic sleep patterns include snoring or difficulty breathing (affecting 5%–12% of preschool-aged children2,3), waking during the night (16%–25%2,4), difficulty getting off to sleep at night (
9%2), and seeming tired in the morning (1%2).
In school-aged children, such sleep problems impact adversely on behavior,5,6 school functioning,7 and health-related quality of life (HRQoL).8,9 In particular, habitual snoring, a marker of sleep-disordered breathing, has been associated with aggression, inattention, and hyperactivity3,10,11 and significantly lower mean scores on validated measures of cognitive and executive function and phonological awareness, the latter a skill critical for learning to read.12 Difficulty settling to sleep at the start of the night has been associated with conduct problems.5 For some children with hyperactive behavior and sleep-disordered breathing, adenotonsillectomy has resulted in resolution of both the breathing and behavior problems,13 strongly suggesting that the sleep disturbance causes the behavior problems.
Surprisingly little attention has been paid to the impact of sleep problems in the vital preschool years. If the consequences for younger children are similar to those above, this might impact significantly on the transition to school (usually between 4 and 6 years of age for Australian children) and subsequent early formal learning. A few individual studies have linked preschool sleep problems with specific outcomes. In a study of 510 American children aged 2 to 5 years, children who slept less were more likely to experience externalizing behavior problems,1 whereas in a community sample of 68 3-year-olds the combination of persistent night waking and ongoing settling difficulties was associated with higher total scores on the Child Behavior Checklist.14 Injury is a leading cause of death and hospitalization in Australian children aged 1 to 9 years,15 and both sleep disturbance and shortened sleep duration (in boys only) have been associated with an increased risk of injury resulting in attendance at a hospital emergency department.16,17 However, the impact of sleep problems on the preschool-aged child's HRQoL, language, and cognitive abilities is unknown. Furthermore, no study has simultaneously examined the relative impacts of early sleep problems on a range of postulated outcomes or been able to extrapolate this to whole populations.
Finally, little is known about which problematic aspects of sleep patterns are associated with specific outcomes. For example, does seeming tired in the morning have a greater impact on a child's HRQoL than difficulty getting off to sleep? Such information may allow a clinician to target management strategies to specific sleep patterns to ensure the best outcome for the child.
Therefore, we sought to determine, in a large, nationally representative sample of Australian preschool children, (a) the prevalence of parent-reported sleep problems, (b) the prevalence of a range of specific sleep patterns occurring 4 nights per week, and (c) associations between sleep and child behavior, HRQoL, verbal and preliteracy skills, and injuries requiring medical attention. We also sought to determine whether specific sleep patterns were associated with each of the child outcomes listed previously. We hypothesized that sleep problems would be common in preschool-aged children and would impact adversely on each of these areas.
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METHODS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Study Design and Sample
Data for this study (collected March to November 2004) were drawn from the first wave of the nationally representative Longitudinal Study of Australian Children (LSAC). The sampling design and field methods have been described elsewhere.18 Briefly, LSAC used a 2-stage cluster sampling design with Australian postal codes (except the most remote) as the primary sampling units and children as the secondary sampling units. To ensure proportional geographic representation, sampling of postal codes was stratified by state of residence and urban versus rural status. The sampling frame for the second stage consisted of all children born in the selected primary sampling units between March 1999 and February 2000 who were enrolled on the Health Insurance Commission Medicare database, with which 98% of all 4-year-old Australian children are registered. Children born between March 1999 and February 2000 were selected randomly within each selected postal code to achieve a cohort aged between 4.3 and 5.2 years at interview with all birth months represented. Of the 10596 children who were selected, 8391 were still resident within that postal code and could be contacted, and of these, 4983 (59%) took part. The sample shown here comprised all participating 4- and 5-year-old children.
Procedure
After receiving a written invitation to participate, parents who did not opt out were approached for written informed consent. Trained professional interviewers conducted a 2 hour face-to-face interview in the child's home with the study child's primary caregiver (usually the biological mother) who also completed a separate written questionnaire. The study was approved by the Australian Institute of Family Studies Ethics Committee.
Measures: Child Sleep
The primary caregiver reported on whether they considered their child to have a sleep problem (no, mild, moderate, or severe problem). Responses were trichotomized into no, mild, and moderate/severe problem. The primary caregiver also indicated whether any of the following specific patterns were occurring 4 nights per week: snoring or difficulty breathing, difficulty getting off to sleep at night, waking during the night, and seeming tired in the morning.
Outcomes
Behavior was assessed by the parent-reported Strengths and Difficulties Questionnaire (SDQ),19 a 25-item validated measure of behavioral and emotional problems for children aged 4 to 16 years. It provides standard scores on 5 subscales (conduct problems, emotional symptoms, peer relationship problems, hyperactivity/inattention, and prosocial behavior); a total problems score is derived from the first 4 subscales. Normative data for Australian 4- to 6-year-olds include a clinical cut point for the total problems score.20 Attention-deficit disorder (ADD) or attention-deficit/hyperactivity disorder (ADHD) was measured by primary caregiver's report of whether their child had been diagnosed with ADD or ADHD.
HRQoL was measured by the parent-proxy Pediatric Quality of Life Inventory 4.0 (PedsQL 4.0),21 a 23-item validated questionnaire for children aged 2 to 18 years that provides total, physical, and psychosocial health summary scores.
Receptive vocabulary was assessed by using the adapted Peabody Picture Vocabulary Test, 3rd Edition (PPVT-III), a shortened 40-item version of the full PPVT-III22 that assesses receptive vocabulary as a screening test of verbal ability. In the LSAC pilot study of 215 children aged 41 to 66 months (mean: 54.7 months), the Pearson product-moment correlation between the full PPVT-III and the adapted PPVT-III was 0.93 for all children and 0.91 for 4-year-olds.23 The Who Am I? (WAI) developmental assessment assesses the cognitive processes that underlie the learning of early literacy and numeracy skills.24 Children are asked to write their names, copy shapes, and write words and numbers, with each response assessed on a 4-point scale relating to the skill required for the task. A total score is generated that has a moderate correlation with standardized measures of early literacy (r = 0.63) and numeracy (r = 0.48).
The number of injuries requiring medical attention from a doctor or hospital over the last 12 months was reported by the primary caregiver. The interviewer clarified the nature of the injury (eg, broken bone, accidental poisoning). Results were dichotomized into no injuries versus 1 injury.
Sociodemographic data included the child's age and gender, number of caregivers in the home, maternal and paternal age, country of birth (Australia/New Zealand versus other), language spoken at home (English versus other), educational status, and employment status. Annual gross household income was collected and equivalized to household size by taking the midpoint of the 15 income brackets reported in the LSAC data set and dividing by the square root of the number of people residing in the house.25
Statistical Analysis
We report both the prevalences (both unweighted sample prevalences and estimated national population prevalences weighted for the survey design) of mild and moderate/severe child sleep problems and each of the 4 specific sleep patterns. The outcomes of interest were compared between (a) children with no sleep problem and children with a mild problem and (b) children with no sleep problem and children with a moderate/severe sleep problem. To do this, we fitted regression models in both unadjusted analyses and analyses adjusted for the potential confounders of child age, gender and equivalized household income. These confounders were chosen a priori because each has been associated with sleep problems and the outcomes of interest in previous studies.1,4,8,17 Linear regression was used to estimate the mean difference between the mild- and no-sleep-problem groups and between the moderate/severe- and no-sleep-problem groups with respect to quantitative outcomes (PedsQL total and physical/psychosocial Summary scores; SDQ total and subscale scores; PPVT-III score; and WAI score). Effect size for the adjusted mean difference was calculated by dividing the adjusted mean difference by the unweighted standard deviation (for the whole sample) of the relevant outcome measure.26 Logistic regression was used to estimate the odds ratios for dichotomous outcomes (whether or not the child had been diagnosed with ADD or ADHD, whether or not the child had had any injuries) between the (a) mild- and no-sleep-problem groups and (b) the moderate/severe- and no-sleep-problem groups.
Finally, bivariate analyses were conducted to determine the relationship between specific sleep patterns and each outcome. Diagnostic checks did not reveal sizeable levels of multicollinearity between the specific sleep problems in any of these models.
All analyses were weighted for the multistage sampling design, allowing for unequal probabilities of selection into the sample and for nonresponse (to account for the known underrepresentation of female caregivers who did not speak English and/or had not completed high school in LSAC). To obtain national population estimates, the LSAC population weights derived from Health Insurance Commission population figures were applied. First-order Taylor linearization was used to obtain estimates of standard error taking account of the correlation of responses within postal codes. For skewed outcomes, bias-corrected accelerated bootstrap confidence intervals (CIs) were used to validate the model-based 95% CIs from the linear regression analyses. Because the bootstrap limits were essentially the same as the nonbootstrap intervals, the latter are presented.
All analyses were implemented by using Stata 9.0 (Stata Corp, College Station, TX).
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RESULTS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Both sleep and outcome data were available for all 4983 families. Sample characteristics are shown in Table 1. The children were aged 51 to 67 months, and 51% were male. The majority of children lived in a 2-parent household (86%), had an English-speaking mother (84%), and had a father who was employed (93%).
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The estimated national prevalence of mild sleep problems was 19.8% (95% CI: 18.6–21.0) and moderate/severe sleep problems was 13.8% (95% CI: 12.7–14.8). Waking during the night affected almost 1 in 5 children (18.1%, 95% CI: 16.8–19.3) and difficulty falling asleep affected 1 in 8 (12.8%, 95% CI: 11.7–14.0) (Table 2). As can be seen, the estimated (weighted) national population prevalences closely resembled the actual sample proportions.
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The presence of a sleep problem was adversely associated with a number of outcomes, especially HRQoL and child behavior problems (P < .001 for all PedsQL and SDQ scales and subscales; see Table 3). Even after adjusting for child age, gender, and equivalized household income, the effect sizes for these outcomes were generally substantial, especially for the PedsQL psychosocial summary and the SDQ conduct and hyperactivity/inattention scales. The proportions of girls and boys falling into the clinical range for total scores on the SDQ for no versus mild versus moderate/severe sleep problems were 12.8%, 19.6%, and 32.6% for girls and 12.3%, 21.5%, and 28.8% for boys, respectively.20 Parents reported that 1.08% (n = 54) of children had been diagnosed with ADHD, of whom 52% (n = 28) had a sleep problem. Children with a moderate/severe sleep problem were, therefore, 12.06 times more likely than children with no sleep problem to have been diagnosed with ADD/ADHD (95% CI: 5.59–26.01). Parents also reported that 17.2% (n = 883) of children had had an injury requiring medical attention in the preceding year, of whom 16% (n = 142) had a moderate/severe sleep problem. The odds of having sustained an injury requiring medical attention were, therefore, 37% (95% CI: 8%–75%) greater for the moderate/severe-sleep-problem group relative to the no-sleep-problem group.
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Of the specific sleep patterns, difficulty getting off to sleep and seeming tired in the morning had the greatest association with outcomes, particularly HRQoL (PedsQL total and psychosocial summary scores) and diagnosis of ADD/ADHD (see Table 4). Neither a moderate/severe sleep problem nor any specific sleep patterns seemed to have sizeable associations with children's receptive vocabulary or preliteracy skills.
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DISCUSSION |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Sleep problems in preschool-aged children were common and associated with sizeable decrements in children's HRQoL (particularly psychosocial), externalizing and internalizing behavior, and injury rates requiring medical attention. Children with moderate/severe sleep problems were also 12 times more likely than those with no sleep problems to receive a diagnosis of ADHD/ADD. Seeming tired in the morning was associated with the lowest HRQoL, whereas difficulty getting to sleep was most strongly associated with receiving a diagnosis of ADHD.
This is the first article, to our knowledge, to describe in a nationally representative sample the prevalence of sleep problems in preschool-aged children and their associations with a diverse range of adverse outcomes. The large sample size enabled precise estimates of parent-reported sleep parameters to be calculated. As an "omnibus" study, LSAC avoided the reporting bias that might result from being in a study specifically about children's sleep. Unlike previous studies in this age group, it was also able to study a range of potential outcomes and, therefore, provide information about the effect sizes of sleep on all these outcomes simultaneously.
This study has some limitations. First, only 59% of the eligible sample took part in LSAC. Although weighting was used for all analyses to account for differences in nonresponders, this may limit generalizability somewhat to those population groups underrepresented in LSAC (although congruence with previous studies2,27 is reassuring in this regard). Second, the data are cross-sectional and as such, causality cannot be assumed. Finally, although we used validated outcomes measures, the sleep measures were based on subjective parent report. More objective measures of sleep may have resulted in less impact of sleep on child outcomes. Nonetheless, parent report is an established marker of problematic child sleep patterns, and there are strong indications of the reliability of parent reporting. Parents who report a sleep problem in younger children also report more frequent and longer night wakings and greater delay in sleep onset than do parents who report that their child has no sleep problems.28 Parents who report a child sleep problem are also more accurate reporters of their child's sleep patterns than parents who do not report a child sleep problem when compared with over night infrared camera footage.29
The prevalence of mild and moderate/severe sleep problems was 33.6% similar to the 27% reported in a study of 378 5- to 6-year-old Swedish preschool-aged children in which the researchers defined children as having a sleep problem if night waking, difficulty initiating sleep, or snoring were reported to occur 3 times per week.2 The prevalence of habitual snoring (9.7%) is similar to the 12% reported in a community study of 784 English children aged 4 to 5 years27 but greater than the 5.3% reported in the Swedish study.2 Sleep-disordered breathing improves with age, and this may explain the difference.3 In the Swedish study, prevalence of night waking (15.8%) and difficulty getting off to sleep at the start of the night (9%) were similar to those in our study.
The association between sleep problems and the SDQ total score is similar to that reported in Swedish children aged 6 to 8 years.5 Likewise, the strong association between sleep problems and diagnosis of ADHD confirms findings from previous studies summarized in a recent review of sleep and ADHD.30 Difficulty getting to sleep was more strongly associated with a diagnosis of ADHD than snoring or difficulty breathing, echoing findings from a case-control study of 46 children with ADHD31 but contrasting with a more recent ADHD case-control study where sleep disordered breathing was more prevalent.32
It is unclear why sleep problems had little association with receptive vocabulary or early literacy and numeracy skills. These attributes are strongly determined by a child's intrinsic characteristics (eg, underlying cognitive capacity) and may, therefore, be less likely than behavior to be affected by external factors such as sleep. Alternatively, given that the Who Am I? developmental assessment has only a moderate correlation with standardized measures of early literacy and numeracy, the association between sleep problems and these outcomes may be weakened. In addition, sleep problems may exert greater impacts on learning after children enter the formal school setting when concentrated and sustained efforts are required by the child to make progress with literacy and numeracy.
Specifically, difficulty getting to sleep and seeming tired in the morning seemed to have the greatest association with outcomes. Difficulty getting to sleep responds well to behavior management strategies such as establishing good "sleep hygiene" routines and reducing parental presence at sleep time.33 Seeming tired in the morning is usually because of inadequate sleep duration and/or impaired sleep quality. Although there may be many causes of both, proven strategies exist to manage common causes of each, such as shifting the bedtime earlier in a child who has a delayed sleep phase. Asking about and managing sleep problems in the preschool-aged group may in turn improve a child's quality of life, behavior, and injury risk.
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CONCLUSIONS |
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TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
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Sleep problems in preschool-aged children are common. Their apparently strong negative associations with behavior and HRQoL could adversely affect the transition to school of very large numbers of children. Because it is likely that these problems would be amenable to simple treatment, we urge both additional research to confirm the causal nature of these findings and trials to determine whether systematic detection and intervention improves these areas of functioning and subsequent learning outcomes.
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ACKNOWLEDGMENTS |
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This article uses a confidentialized unit record file from the LSAC. The LSAC project was initiated and is funded by the Commonwealth Department of Families, Community Services and Indigenous Affairs, and is managed by the Australian Institute of Family Studies.
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FOOTNOTES |
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Accepted Aug 31, 2006.
Address correspondence to Harriet Hiscock, MD, Centre for Community Child Health, Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, Australia. E-mail: harriet.hiscock{at}rch.org.au
The authors have indicated they have no financial relationship relevant to this article to disclose.
The findings and views reported in this article are those of the authors and should not be attributed to either Families, Community Services and Indigenous Affairs or the Australian Institute of Family Studies.
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PEDIATRICS (ISSN 1098-4275). ©2007 by the American Academy of Pediatrics
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