DÄ internationalArchive40/2020Chronic Sleep Reduction in Childhood and Adolescence

Original article

Chronic Sleep Reduction in Childhood and Adolescence

Point prevalence, psychosocial characteristics and sleep indicators in a representative sample

Dtsch Arztebl Int 2020; 117: 661-7. DOI: 10.3238/arztebl.2020.0661

Paschke, K; Laurenz, L; Thomasius, R

Background: Habitually shortened nighttime sleep is a common phenomenon in childhood and adolescence, sometimes associated with chronic sleep reduction (CSR). CSR is associated with impairments of performance ability and emotional well-being. The extent to which children and adolescents in Germany suffer from CSR is unclear; it is also unclear what factors are predictive of CSR.

Methods: In the present study, we carried out a telephone survey in a representative sample of 998 children and adolescents aged 12 to 17, asking them about their sleep behavior, sleep disturbances, and mental well-being. A standardized method was used.

Results: The point prevalence of CSR was found to be 12.5% (95% confidence interval, [10.5; 14.6]). Children and adolescents affected by CSR reported a significantly higher frequency of insomnia, delayed sleep-phase syndrome, restless legs syndrome, and obstructive sleep apnea. Female sex, prolonged absence from school or vocational training, emotional and behavioral disturbances, age over 15 years, bedtimes after 10:38 pm on nights before school (or vocational training), getting up after 10:04 on days off, and reported insomnia were all associated with CSR, with odds ratios (OR) ranging from 2.2 to 21.1 (R2 = 0.32 in a logistic regression model).

Conclusion: One in eight persons aged 12 to 17 in Germany, particularly girls, meets the criteria for CSR. CSR is associated with sleep disturbances and significantly impaired mental health and should, therefore, always be kept in mind in routine clinical practice. We provide a set of indicators for possible CSR that patients can easily be asked about.

LNSLNS

Sleep has a major role in the development of children and adolescents (1). A longer duration of sleep is positively associated with learning achievement/performance (2, 3) and negatively associated with rates of accidents (4). Insufficient and disrupted sleep is associated with poorer mental health and a higher incidence of antisocial behavior (5, 6). Sleep affects physiological function such as immune defense, healing processes, perception of pain, but also treatment adherence among children and adolescents with somatic or psychiatric disorders (7).

Reduced and disrupted night sleep is common in young obese patients (8), bronchial asthma (9), atopic dermatitis (10), juvenile rheumatoid arthritis (11), chronic headache (12), attention deficit hyperactivity disorder (13), depression (14), and anxiety disorders (15). Differences between the sexes in terms of sleep behavior manifest from the onset of puberty (16). For girls, the hormonal changes in this phase are associated with 1.4 times the risk for sleep problems (17).

Chronic sleep reduction is a widespread phenomenon in children and adolescents, as confirmed by international data, which is characterized by reduced night sleep, daytime sleepiness, and a reduced ability to perform (18); with a persistence of up to 50% after one year it often takes a chronic course (5). Worldwide, sleep reduction has been observed in children and adolescents (see also example [19, 20]). In Germany, more than 90% of 12–18 year-olds sleep less than the recommended 9.2 hours per day (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33).

The causes of sleep reduction are multifarious and range from deficient sleep hygiene to clinically relevant sleep disorders, such as insomnia, delayed sleep phase disorder (DSPD), obstructive sleep apnea, and restless legs syndrome (RLS). In addition to biological factors, sociocultural and behavioral factors—such as the use of digital media, nocturnal light, caffeine and tobacco consumption, and a lack of parental control—have an important role in this setting (22, 24). Adolescents from households of a lower socioeconomic status often go to sleep later and sleep for shorter periods and in more irregular patterns (25).

In spite of the close association between sleep deprivation and health we know of no study that investigated the spread of chronic sleep reduction in childhood and adolescence in Germany and its associated characteristics systematically, by using validated methods. Capturing the duration of sleep only is not sufficient because this documents merely the aspect of nocturnal sleep reduction in the age comparison, without providing any insights into associated bed times, sleep indices, and personal consequences for everyday life. Associations between sleep times, psychosocial characteristics/attributes, and chronic lack of sleep have thus far not been described to a satisfactory degree. The present study is an attempt to close this knowledge gap by asking the following questions:

  • What is the point prevalence of chronic lack of sleep in children and adolescents in Germany?
  • How do adolescents with and without chronic sleep reduction differ with regard to psychosocial and behavioral characteristics?
  • Is it possible to identify indicators that could be put to use in clinical practice in a simple manner?

Methods

The following paragraphs provide an overview of the study methods. The eMethods section provides a more detailed description.

Data collection

The data collection was undertaken by the market and opinion research institute forsa, using computer-assisted telephone interviews. A total of 1000 children and adolescents aged between 12 and 17 years from representative households included in the German ADM telephone sample (ADM, Arbeitskreis Markt- und Sozialforschungsinstitute e.V., a business association that represents the interests of private-sector market and social research agencies in Germany) were included in the survey.

Study methods

The sociodemographic and personal baseline data collected were age, sex, classification of residence (rural, small town, urban/city), occupation (school student, apprentice, voluntary service, etc.), the desired or achieved school leaving certificate, as well as absences from school, from the place of the apprenticeship or from work within the preceding four weeks. Data on chronic sleep reduction including the associated consequences affecting everyday life were collected by administering the nine item, validated Sleep Reduction Screening Questionnaire (SRSQ) (26) (Table 1). Responses agreeing with the given statement were recorded on a three-step ordinal scale. Individual results with a point score greater than 17 were taken as obvious indications of chronic sleep reduction.

Sleep Reduction Screening Questionnaire (SRSQ)
Table 1
Sleep Reduction Screening Questionnaire (SRSQ)

We collected or calculated the following sleep indices separately by days spent at school/vocational training/work and days off: bed time and getting-up time, time to go to sleep (sleep latency) and time from waking up to getting up (early waking), time of going to sleep, waking up time, and total duration of sleep. Symptoms of sleep disorders were documented by using the Insomnia Severity Index (ISI) for insomnia and the subscales of the Auckland Sleep Questionnaire (ASQ) for restless legs syndrome and obstructive sleep apnea. As eTable 1 shows, the symptoms of delayed sleep phase syndrome were determined. The children and adolescents were asked when responding to the sleep-related questions to consider the preceding four weeks. Additionally, emotional and behavioral problems were recorded by using the four subscales (emotional symptoms, behavioral problems, hyperactivity and attention deficit, and relationships with peers) of the Strengths and Difficulties Questionnaire (SDQ-D).

Delayed sleep phase syndrome (DSPS)
eTable 1
Delayed sleep phase syndrome (DSPS)

Data evaluation

For the analysis of the SRSQ we were able to evaluate the complete data sets of N=998 adolescents; regarding the sleep indices it was N=969, for the SDQ it was N=983, and combined it was N=960. We calculated the point prevalence for chronic sleep reduction by using relative frequencies and 95% confidence intervals first for the total sample and then stratified by sex. Adolescents with and without chronic sleep reduction were statistically compared regarding the parameters named earlier by using the chi squared test and t-tests and by determining effect sizes (Cohen’s d for parametric tests and Cramer’s V for non-parametric tests).

We used receiver operating characteristic (ROC) analyses to calculate cut-off values for bed times on school days and days off as well as getting-up times on days off with regard to the occurrence of chronic sleep reduction. Values above this cut-off were—together with insomnia (ISI ≥ 10) and age (≥ 15 years)—integrated as covariates as well as the factors sex, absences, and an abnormal SDQ total score (≥ 17) in a multiple logistic regression model with reverse selection according to the Akaike Information Criterion (AIC) for the description of chronic sleep reduction. The AIC model was used to estimate the adjusted odds ratios and 95% confidence intervals. We used the software package R (The R Project for Statistical Computing, www.r-project.org, Version 3.6.1) for our statistical analyses (27).

Results

Table 2 gives an overview of sociodemographic characteristics and absences of the representative total sample out of the total number (N=998) of participating 12–17 year old children and adolescents. In all age groups, the average sleep duration was significantly lower on school days than on days off. The total sleep duration we determined did not differ from the results of the Robert Koch-Institute’s German Health Interview and Examination Survey for Children and Adolescents (KiGGS) (17). eTable 2 shows the detailed results including age dependent percentiles and comparisons of means.

Sociodemographic characteristics, absences, and point prevalence of chronic sleep reduction (CSR) in the total sample (N = 998)
Table 2
Sociodemographic characteristics, absences, and point prevalence of chronic sleep reduction (CSR) in the total sample (N = 998)
Mean sleep duration by age: comparison of school days and days off as well as total sleep duration, KiGGS data
eTable 2
Mean sleep duration by age: comparison of school days and days off as well as total sleep duration, KiGGS data

For 125 of the 998 children and adolescents findings were positive for prevailing chronic sleep reduction (sum value in SRSQ>17) (26). The point prevalence estimate for chronic sleep reduction for the age group of 12–17 year olds in Germany is therefore 12.5%. For girls the estimated prevalence was statistically significantly higher than for boys (18.0% versus 7.8%). Adolescents affected by chronic sleep reduction were a mean of 10 months older than those without chronic sleep reduction (15.3 years versus 14.5 years). The proportion of absences of more than 25% from school, apprenticeship, or workplace, was significantly higher for adolescents affected by chronic sleep reduction than for youngsters of the same age without chronic sleep reduction (12.0% versus 5%). Furthermore, those affected by chronic sleep reduction displayed higher rates of emotional and behavioral abnormalities on the SDQ overall score (18.7% versus 3.4%) and on the subscales peer problems, behavioral problems, and emotional problems. They met the criteria of manifest sleep disorders to a greater extent than participants without chronic sleep reduction: insomnia (26.4% versus 1.2%), DSPS (11.8% versus 1.4%), restless legs syndrome (9.6% versus 3.2%) and obstructive sleep apnea (8.8% versus 0.9%). The results of the prevalence estimates including 95% confidence intervals, means, and standard deviations, as well as comparisons of frequencies and means with effect sizes are shown in Table 3.

Prevalence rates and comparisons between adolescents with/without chronic sleep reduction (CSR)
Table 3
Prevalence rates and comparisons between adolescents with/without chronic sleep reduction (CSR)

With regard to the occurrence of chronic sleep reduction, we calculated the following cut-off values across all age groups: 22.38 hrs for bed time on school days, 23.38 hrs for bed time on days off, and 10.04 hrs for getting up time on days off. These times show a positive predictive value between 18% and 26% and a negative predictive value between 92% and 93%. The likelihood ratios are between 1.56 and 2.41 when the criterion was met and between 0.54 and 0.59 when the criterion was not met. Sensitivities, specificities, the area under the curve (AUC), positive predictive values, negative predictive values, and likelihood ratios for met/unmet criteria are shown in Table 4.

Parameters for screening for chronic sleep reduction (CSR) according to ROC analyses
Table 4
Parameters for screening for chronic sleep reduction (CSR) according to ROC analyses

We found statistically significant associations between chronic sleep reduction and sex, absences, and an abnormal total score on the SDQ. Of the covariates integrated into the logistic regression model—insomnia, bed times on school days and days off, and getting up times on days off according to the calculated cut-offs and age ≥ 15 years—all except bed times on days off were considered in the reverse selection process (AIC== 564.02). The interaction between absences and abnormal SDQ scores was significant. Overall, this model clarified 32% of the total variance (Nagelkerke’s R2 = 0.32, Brier value = 0.08). Table 5 shows the parameters of the model and adjusted odds ratios.

Predictors for chronic sleep reduction (SR) according to a multiple logistic regression with reverse selection and adjusted odds ratios. Criterion: Sleep Reduction Screening Questionnaire (SRSQ) – total score >17
Table 5
Predictors for chronic sleep reduction (SR) according to a multiple logistic regression with reverse selection and adjusted odds ratios. Criterion: Sleep Reduction Screening Questionnaire (SRSQ) – total score >17

Discussion

The present study is the first to determine in a representative sample the prevalence of chronic sleep reduction in 12–17 year old children and adolescents in Germany. One in eight children was affected, older adolescents notably more so than younger ones. This finding is consistent with the well known observation that bed times of children and adolescents undergo a shift by up to two hours later (17, 28, 29).

In addition to changing circadian rhythms and the adaptation of the individual chronotype, a decrease in the parental control function and the increase in the use of electronic media play a part (22, 30, 31). The duration of sleep on weeknights reduces, since in most German schools the starts of morning lessons is not adapted to suit the circadian characteristics of adolescent students. Many adolescents seem to attempt to balance this “social jetlag” by sleeping in late at weekends (29). The available data confirm significant differences between sleep duration on school days and on days off. At the same time, a proportion of adolescents report significant sleep deficits.

The success or lack thereof of possible compensatory measures should be further investigated in longitudinal studies, as should the effect of biological—for example, hormonal—parameters. Girls in the described sample complained more about chronic sleep reduction than boys. This is consistent with the findings in the literature of the common occurrence of manifest sleep disorders (for example, DSPS) in adolescents affected by chronic sleep reduction (17).

For the purposes of the diagnostic evaluation of sleep disorders the recommendation is to document clinical symptoms, administer questionnaires and sleep diaries, but also to carry out actigraphy measurements. It also seems sensible to determine biomarkers, such as, for example, the dim light melatonin onset (DLMO) by taking repeated saliva specimens from five to six hours before the usual bed time (32). Furthermore, sleep laboratory investigations using (cardiorespiratory) polysomnography can provide differential diagnostic information about sleep architecture, motor patterns, and ventilation. Furthermore, in case of chronic sleep reduction or where this is suspected, one might consider involving a child and adolescent psychiatrist for an assessment. In our study, emotional and behavioral problems were a meaningful predictor of the occurrence of chronic sleep reduction (odds ratio [OR]=5.0). This result adds to the findings of a study in 8–11 year old schoolchildren (33).

For routine clinical practice, a quick and efficient screening for a possible chronic sleep reduction is useful. On the basis of the ROC analyses and the logistic regression, we think the following approach might be helpful parameter values are rounded for practical use): if 12–17 year olds report that they go to bed after 22.30 hrs on school nights and get up at 10.00 hrs on days off, the rate of chronic sleep reduction is about a quarter, so that further investigations may be worthwhile. Particular attention should go to girls and adolescents from the age of 15. In terms of health policy, the topic should receive increasing attention in the setting of prevention and education—for example, relating to sleep hygiene measures, including rules about the use of digital media and the role of parental control.

Limitations

For economic reasons, the use of questionnaires is usual practice in epidemiological cross sectional studies and yields robust results (34), especially when the study objective is description and representativeness of the population. Causal hypotheses, especially relating to psychosocial determinants, should, however, be tested in (if required) randomized cross sectional studies. Subsequent studies should consider moderators, such as the socioeconomic status and educational attainment of the families; cultural backgrounds; rhythms of family and daily life (for example, the parents’ and siblings’ sleep behavior or whether they are in gainful employment), the physical sleep environment; health related, seasonal, and chronobiological aspects; as well as media and substance use. Including these factors in our study was not possible because telephone interviews with children and adolescents are subject to methodological and ethical restrictions. Bias effects (social desirability, memory effects) on the subject of sleep can be assumed to be of lesser relevance than variables such as substance consumption. An important limitation of the study is the exclusive collection of self reports. Reports from others and objective markers, especially relating to the documented sleep disorders, should be collected in subsequent studies.

Furthermore our analyses were based on a categorical approach using cut-off values and neglect the scatter around the cut-off points. This approach reflects routine clinical practice, which requires efficient action even in uncertainty and often necessitates a binary “yes-no” diagnosis. The suggested indicators for chronic sleep reduction are not satisfactory as a diagnostic criterion because of their test quality and cannot be recommended as the single instrument. However, they seem satisfactory for a screening instrument that is easily handled in clinical practice with two brief questions about bed times/sleep times.

The parameters were determined in the context of a model that predicts which adolescents may already be affected by chronic sleep reduction. This makes it possible to initiate measures before the condition becomes chronic or secondary consequences ensue. Screening in the setting of early detection is not possible in this way.

Conclusions

The present study is the first to provide robust epidemiological data on the point prevalence and indicators for screening for chronic sleep reduction in 12–17 year olds in Germany. It highlights the health political relevance because of the associated complex psychosocial impairments. Sensitizing clinicians who are in contact with children and adolescents to chronic sleep reduction in this age group is of the essence, so as to detect it at an early stage and consider preventive and therapeutic interventions. Further studies, especially longitudinal studies with complementary objective methods are desirable, which should include further potential moderators—for example, socioeconomic status and parental monitoring.

Funding

The study was supported by funds from DAK-Gesundheit.

Acknowledgeement

The authors’ special thanks go to Peter-Michael Sack, who critically revised this manuscript, provided valuable pointers, and was always at hand for advice and to step in.

Conflict of interest statement
The authors declare that no conflict of interest exists.

Manuscript received on 25 January 2020, revised version accepted on
22 June 2020.

Translated from the original German by Birte Twisselmann, PhD.

Corresponding author
Dr. med. Dipl.-Psych. Kerstin Paschke
Deutsches Zentrum für Suchtfragen des Kindes- und Jugendalters (DZSKJ)
Universitätsklinikum Hamburg-Eppendorf
Martinistraße 52, 20246 Hamburg
k.paschke@uke.de

Cite this as
Paschke K, Laurenz L, Thomasius R: Chronic sleep reduction in childhood and adolescence—point prevalence, psychosocial characteristics and sleep indicators in a representative sample. Dtsch Arztebl Int 2020; 117: 661–7. DOI: 10.3238/arztebl.2020.0661

Supplementary material

For eReferences please refer to:
www.aerzteblatt-international.de/ref4020

eMethods, eTables:
www.aerzteblatt-international.de/20m0661

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German Center for Addiction Research in Childhood and Adolescence (DZSKJ), University Clinic Hamburg-Eppendorf (UKE):
Dr. med. Dipl.-Psych. Kerstin Paschke, Dr. med. Léa Laurenz, M.Sc.,
Prof. Dr. med. Rainer Thomasius
Key messages
Sleep Reduction Screening Questionnaire (SRSQ)
Table 1
Sleep Reduction Screening Questionnaire (SRSQ)
Sociodemographic characteristics, absences, and point prevalence of chronic sleep reduction (CSR) in the total sample (N = 998)
Table 2
Sociodemographic characteristics, absences, and point prevalence of chronic sleep reduction (CSR) in the total sample (N = 998)
Prevalence rates and comparisons between adolescents with/without chronic sleep reduction (CSR)
Table 3
Prevalence rates and comparisons between adolescents with/without chronic sleep reduction (CSR)
Parameters for screening for chronic sleep reduction (CSR) according to ROC analyses
Table 4
Parameters for screening for chronic sleep reduction (CSR) according to ROC analyses
Predictors for chronic sleep reduction (SR) according to a multiple logistic regression with reverse selection and adjusted odds ratios. Criterion: Sleep Reduction Screening Questionnaire (SRSQ) – total score >17
Table 5
Predictors for chronic sleep reduction (SR) according to a multiple logistic regression with reverse selection and adjusted odds ratios. Criterion: Sleep Reduction Screening Questionnaire (SRSQ) – total score >17
Delayed sleep phase syndrome (DSPS)
eTable 1
Delayed sleep phase syndrome (DSPS)
Mean sleep duration by age: comparison of school days and days off as well as total sleep duration, KiGGS data
eTable 2
Mean sleep duration by age: comparison of school days and days off as well as total sleep duration, KiGGS data
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