OBM Neurobiology

(ISSN 2573-4407)

OBM Neurobiology is an international peer-reviewed Open Access journal published quarterly online by LIDSEN Publishing Inc. By design, the scope of OBM Neurobiology is broad, so as to reflect the multidisciplinary nature of the field of Neurobiology that interfaces biology with the fundamental and clinical neurosciences. As such, OBM Neurobiology embraces rigorous multidisciplinary investigations into the form and function of neurons and glia that make up the nervous system, either individually or in ensemble, in health or disease. OBM Neurobiology welcomes original contributions that employ a combination of molecular, cellular, systems and behavioral approaches to report novel neuroanatomical, neuropharmacological, neurophysiological and neurobehavioral findings related to the following aspects of the nervous system: Signal Transduction and Neurotransmission; Neural Circuits and Systems Neurobiology; Nervous System Development and Aging; Neurobiology of Nervous System Diseases (e.g., Developmental Brain Disorders; Neurodegenerative Disorders).

OBM Neurobiology publishes a variety of article types (Original Research, Review, Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, etc.). Although the OBM Neurobiology Editorial Board encourages authors to be succinct, there is no restriction on the length of the papers. Authors should present their results in as much detail as possible, as reviewers are encouraged to emphasize scientific rigor and reproducibility.

Publication Speed (median values for papers published in 2023): Submission to First Decision: 7.5 weeks; Submission to Acceptance: 15.9 weeks; Acceptance to Publication: 7 days (1-2 days of FREE language polishing included)

Current Issue: 2024  Archive: 2023 2022 2021 2020 2019 2018 2017
Open Access Review

Short Sleep in Pupils in Japan: Current Status and Associated Factors

Jun Kohyama *

Department of Sleep Medicine, Tokyo Bay Urayasu Ichikawa Medical Center, Toudaijuma 3-4-32, Urayasu 279-0001, Chiba, Japan

Correspondence: Jun Kohyama

Academic Editor: Bart Ellenbroek

Received: February 21, 2019 | Accepted: July 15, 2019 | Published: July 22, 2019

OBM Neurobiology 2019, Volume 3, Issue 3, doi:10.21926/obm.neurobiol.1903034

Recommended citation: Kohyama J. Short Sleep in Pupils in Japan: Current Status and Associated Factors. OBM Neurobiology 2019; 3(3): 034; doi:10.21926/obm.neurobiol.1903034.

© 2019 by the authors. This is an open access article distributed under the conditions of the Creative Commons by Attribution License, which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is correctly cited.

Abstract

Background: Several recommendations on optimum sleep duration have been published for adolescents to secure a healthy life. This study aimed to compare the sleep duration of middle and high school pupils in Japan with the recommended values and determined the factors associated with the duration of sleep among them.

Methods: A total of 1766 completed questionnaires were obtained from grades 7 to 12 pupils in Japan. The questionnaire addressed the following points: sleeping, eating, defecation, physical activity, screen time, after-school activity, body mass index, and self-reported academic performance. On self-reported academic performance, they were asked to select their overall academic performance from the following four choices: very good, good, average, poor.

Results: The mean sleep duration of school nights did not reach the lowest recommended level in case of all grades. By means of multiple linear regression analysis, the regression equation for sleep duration of both school nights (adjusted R2 = 0.2046, F = 38.84, p < 0.001) and non-school nights (adjusted R2 = 0.093, F = 16.15, p < 0.001) were obtained. For both school and non-school nights, grade (standardized partial regression coefficient (β), -0.321 for school days and -0.176 for non-school days), after-school activity (β, -0.100 for school days and -0.142 for non-school days) and school day screen time (β, -0.097 for school days and -0.092 for non-school days) showed significant associations with sleep duration. Self-reported academic performance was not associated with the sleep duration of both school and non-school nights.

Conclusions: The mean sleep duration of school nights of grade 7 to 12 pupils in Japan was lower than the recommendations. Pupils may compensate for their sleep shortage during school nights by increasing sleep duration of non-school nights. Shortening after-school activity and school day screen time would be expected to increase their sleep duration.

Keywords

Sleep duration; after-school activity; screen time; insufficient sleep syndrome

1. Introduction

According to the recent data of the Organization for Economic Co-operation and Development [1], Japan is the most sleep-deprived nation in the world. In such a sleep-deprived society, the attitude toward sleep is a serious issue, especially among adolescents, who represent the next generation, because the consequences of sleep problems are presumed to affect various aspects of the life [2]. Insufficient sleep is associated with a wide range of negative outcomes such as obesity, cardiovascular disease, malignant neoplasms, cerebrovascular disease, diabetes, hypertension, accidents and injuries, and poor academic performance [3]. Indeed, a considerable number of pupils in Japan purportedly suffer from insufficient sleep syndrome defined by the international classification of sleep disorders version 3 [4].

The U.S. Centers for Disease Control and Prevention assessed the prevalence of short sleep duration according to the American Academy of Sleep Medicine recommendations (6-12 years old, 9-12 h and 13-18 years old, 8-10 h) on school nights [5] in American middle and high school students. They reported that the overall prevalence of short-sleeping pupils was 57.8% and 72.7% for middle and high school students, respectively [6]. According to the National sleep foundation [7], the lower recommendation of sleep duration is 9 h for 6-13 years, 8 h for 14-17 years, and 7 h for 18-25 years. The National Heart, Lung, and Blood Institute recommended that at least 10 h sleep is essential for school-aged children and adolescents to perform adequately [8]. It should be noted that there are large differences among recommendations on sleep duration. Indeed, there was a recent article objecting the set recommendations for sleep duration in children and teens [9]. The article claimed that the sleep ranges and age groupings are too wide and the indicators for determining sleep need and guidelines on the timing of day and night sleep periods should be provided. Despite these recommendations, the problem of insufficient sleep among adolescents remains unaddressed. Since grade 7 pupils includes 12-13-year-old children, grade 8 includes 13-14-year-old, grade 9 includes 14-15-year-old, grade 10 includes 15-16-year-old, grade 11 includes 16-17-year-old, and grade 12 includes 17-18-year-old pupils, in general, the above-cited recommendations can be simplified as the lowest recommended sleep duration is 8 h for grade 7-11 and 7 h for grade 12, respectively. The current study aimed to compare the sleep duration of middle and high school pupils in Japan with the lowest recommended values [5,7,8] and revealed the factors associated with their sleep duration.

Some part of the present analyzed data has been used in other publications [10,11]. According to the former analysis [11], early non-school day wake time in addition to less sleepiness, lower body mass index (BMI), less breakfast skipping, less constipation, and short non-school day screen time were found to be associated with good self-reported academic performance. However, the previous study [10] did not investigate these factors in association with sleep duration.

This study was approved by the Committee for Medical Research Ethics of Tokyo Bay Urayasu Ichikawa Medical Centre (no. 199).

2. Methods

A questionnaire was delivered to each student by their school teachers between October 2016 and November 2018. A letter was also delivered assuring them that their responses would be treated anonymously and confidentially and that it is voluntary to participate. Written consent (signed by any of the parents) and completed questionnaires were collected by school teachers on any of the subsequent days and were subsequently delivered to the author. Of the 3117 questionnaires collected from 13 public schools (eight junior high schools and five high schools), 1766 students agreed to participate in the study and answered all the required questions.

The queries in the questionnaire are shown in Table 1. The responses on sleepiness, breakfast, and defecation were expressed as sleepiness score, breakfast score, and defecation score, respectively. On dinner regularity, the choice of 1 to 7 was categorised into regular dinner (dinner regularity score 1) and the last choice of 8 into irregular dinner (dinner regularity score 2). The hours of after-school activity per week were taken as the product of the frequency and duration of activities. The responses on physical activity, screen time, and self-reported academic performance (1, very good; 2, good; 3, average; 4, poor) were termed as physical activity score, screen time score, and self-reported academic performance score, respectively. This categorization on self-reported academic performance was carried out following by Wolfson and Carskadon [12].

Table 1 Questionnaire.

In order to calculate sleep duration, we needed representative time for each category of bed and wake times. Representative times for each bedtime category (1. < 8PM, 2. 8PM–9PM, 3. 9PM–10PM, 4. 10PM–11PM, 5. 11PM–12AM, 6. 12AM–1AM, 7. 1AM–2AM, 8. 2AM–3AM, 9. > 3AM) were determined as follows: 7:30PM, 8:30PM, 9:30PM, 10:30PM, 11:30PM, 12:30AM, 1:30AM, 2:30AM, and 3:30AM. As for the wake time category (1. < 5AM, 2. 5AM–6AM, 3. 6AM–7AM, 4. 7AM–8AM, 5. 8AM–9AM, 6. 9AM–10AM, 7. 10AM–11AM, 8. 11AM–12PM, 9. > 12PM), representative times were as follows: 4:30AM, 5:30AM, 6:30AM, 7:30AM, 8:30AM, 9:30AM, 10:30AM, 11:30AM, and 12:30PM. The sleep duration on school nights was calculated as the difference between the bedtime before school days and wake time on school days of these representative times. The sleep duration of non-school nights was calculated as the difference between bedtime before non-school days and wake time on non-school days of these representative times. In order to calculate screen time from the screen time scores, representative times for each screen time category (1. less than 2 h, 2. 2-4 h, 3. 4-6 h, 4. 6-8 h, and 5. 8 h or more) were determined as follows: 1 h, 3 h, 5 h, 7 h, and 9 h.

Since BMI has been reported to be altered markedly during school-aged children and adolescents in Japan [13], an analysis of variance (ANOVA) was conducted to determine the differences among BMI of twelve categories divided by gender and grade (male and female categories of grade 7 to 12). Student’s t-test was used to assess the gender difference among the factors investigated. The factors associated with sleep duration on school nights and non-school nights were assessed by multiple regression analysis using grade, gender, BMI, breakfast score, dinner regularity score, physical activity score, defecation score, sleepiness score, screen time scores on both school days and non-school days, after-school activity hours per week, and self-reported academic performance score as explanatory variables.

A p-value of < 0.05 was considered statistically significant. These analyses were conducted by a Bell Curve in Excel.

3. Results

The pupils in each of the twelve categories, segregated by gender and grade of the current subjects, are shown in Table 2 with the factors that had no relation with school days (nights) and non-school days (nights). The ANOVA of the BMI among these twelve categories revealed a significant difference (F = 9.67 (df = 1754)). Then, BMI values were standardized by gender and grade in the subsequent analysis.

The sleep parameters including mean sleep duration and screen time of both school nights (not “nights” but “days” for screen time) and non-school nights (not “nights” but “days” for screen time) in each grade are shown in Table 3 with the standard deviation. The mean sleep duration of school nights of grade 7 to 12 pupils of both genders did not reach the lowest recommended values (8 h for grade 7 to 11, and 7 h for grade 12) [5,7,8]. Even in the non-school nights, the mean sleep duration of grade 10 and 11 male pupils did not reach these figures [5,7,8]. In contrast with the school nights, the mean sleep duration of non-school nights was increased in all twelve categories (from 50.4 min (grade 7 male) to 112.2 min (grade 12 female)).

The distribution of sleep duration categories (less than 6 h, 6-7 h, 7-8 h, 8-9 h, 9-10 h, 10 h or more) of school nights and non-school nights in each grade is shown in Figure 1 with the data for both genders together. Among the sleep duration categories of school nights, the highest rate was 8-9 h in grade 7 and 8 pupils, 7-8 h in grade 9, 6-7, and 7-8 h in grade 10, 7-8 h in grade 11, and 6-7 h in grade 12 pupils. On the other hand, for the non-school nights, the highest rate was 9-10 h in grade 7, 8, and 9 pupils, 8-9 h in grade 10 and 11, and 9-10 h in grade 12 pupils, respectively. Except for the non-school nights of grade 12 pupils, the highest sleep duration category moved toward the shorter categories with the grade progression. The percentage of pupils with school night sleep duration of fewer than 6 h was 1.8% in grade 7, 2.3% in grade 7, 9.3% in grade 9, 13.5% in grade 10, 12.4% in grade 11, and 13.2% in grade 12. These values were decreased to 0.9%, 1.9%, 2.5%, 5.7%, 2.0%, and 3.8% in non-school nights, respectively. The actual number of these short sleep pupils was 136 for school nights while 14 for non-school nights. The average rate of pupils with sleep duration of 10 h or more for school nights was 0.7%, and the same became 19.0% for non-school nights. The actual number of these long-sleep pupils was 48 in school nights and 350 in non-school nights, respectively.

Figure 1 Distribution of sleep duration categories (less than 6 h, 6-7 h, 7-8 h, 8-9 h, 9-10 h, 10 h or more) of school nights (left) and non-school nights (right) by the grade group. Except for non-school nights of grade 12 pupils, the highest sleep duration category (the percentage is underlined) moved toward shorter category with the grade progression. Please see further explanations in the text.

On the basis of the multiple linear regression analysis, significantly predictable regression equation were developed for sleep duration of both school nights (adjusted R2 = 0.2046, F = 38.84 (df = 1753), p < 0.001) and non-school nights (adjusted R2 = 0.093, F = 16.15 (df = 1753), p < 0.001). The regression coefficients for school nights and non-school nights are shown in Table 4. The common factors associated with short sleep duration in both school nights and non-school nights were a higher grade and the increase of both after-school activity and school day screen time. Self-reported academic performance was not a significant factor associated with sleep duration.

Table 2 The mean values with standard deviation of the scores of the factors investigated.

Table 3 The mean values with standard deviation of sleep-related parameters and screen time of both school nights and non-school nights.

Table 4 The regression coefficients for sleep duration for school nights and non-school nights.

4. Discussion

The current study revealed that the mean sleep duration of school nights in grade 7 to 12 pupils did not reach any of the lowest recommended levels [5,7,8]. Even in non-school nights, the mean sleep duration of grade 10 and 11 male pupils was below the recommended level [5,7,8]. The number of pupils with a short-sleep duration of fewer than six hours decreased remarkably from 136 in school nights to 14 in non-school nights, while the number of pupils with a long-sleep duration of 10 h or more increased markedly from 48 in school nights to 350 in the non-school night. According to the multiple linear regression analysis, grade progression was associated with short-sleep duration for both school nights and non-school nights. In addition, the increase in after-school activity and school day screen time was associated with the short-sleep duration of both school nights and non-school nights.

This study confirmed the serious status of insufficient sleep among middle and high school pupils in Japan. Since the mean sleep duration was increased more than 50 min from school nights to non-school nights, it can be assumed that pupils try to compensate for their sleep shortage by increasing sleep duration during non-school nights. The issues of sleep shortage have been acknowledged for more than 20 years [12]; however, the problem could not be sufficiently addressed. Although several trials have been conducted [14,15], it could be said that no fundamental change has occurred in the sleep situation of middle and high school pupils for these 20 years.

In order to help these sleep-deprived pupils for insufficient sleep, we should know the factors associated with short sleep duration. As far as the present study is concerned, in addition to grade progression, increases in after-school activity and school day screen time were found to be significant factors associated with short sleep duration of both school nights and non-school nights. Shortening after-school activity and school day screen time would be expected to increase their sleep duration; however, these questions remain to be solved.

In Japan, to improve their academic performance, 41.3% of middle-high school pupils and 27.2% of high school pupils engage in private cram schools [16]. Some pupils also attend piano lessons, swimming club, etc. In addition, 11.3% of high school students get engaged in some kind of part-time jobs [17]. It should be noted that after-school activity in the current study did not consider these activities specifically and might include all these extracurricular activities.

An association between screen media use and decreased sleep duration has been widely acknowledged [18,19,20]. Carter et al. [18] reported a strong and consistent association between bedtime media device use and inadequate sleep quantity. The association between media use and adolescents’ poor sleep efficiency has also been well documented [20]. However, few studies considered the screen time of school days and non-school days separately. In the present study, a long school day screen time was associated with a short-sleep duration during school nights. However, the present study also demonstrated a significant association between long school day screen time and short-sleep duration of non-school nights. Furthermore, sleep duration of non-school nights and non-school day screen time revealed a positive significant association. The reason for these latter two associations remains to be elucidated.

The association between academic performance and a short-sleep duration is widely acknowledged [12,21,22,23,24,25,26]; however, in the current study, we could not find such association. It should be noted that the necessary sleep duration varies from person to person and from night to night [27], and individual variabilities in the need for sleep are influenced by genetic, behavioral, medical, and environmental factors [5]. The present result may be affected by these individual variabilities in sleep duration. In addition, contrary to the widely accepted notion [12,21,22,23,24,25,26], sleep duration was recently reported to be a weaker predictor of academic performance in contrast to sleepiness [28]. Further studies are required to clarify the association between sleep duration and academic performance.

This study depended on the responses given for the questionnaire answers, thus the lack of objective data is the major limitation. Additionally, this study lacked age information. This was because some pupils in Japan tend to be sleep-deprived during entrance examinations, and examinations are essentially grade-related issues rather than age-related ones. Then, the current study focused on the grade and ignored the age data from a social viewpoint. However, it should not be forgotten that age is one of the important biological factors. Moreover, this study did not assess the socioeconomic status. Low socioeconomic status might be closely associated with biological sleep problems during development, probably due to nutritional, hygienic, and educational problems. Indeed, children from a low socioeconomic status [29,30,31] show higher rates of sleep problems, such as short sleep duration, although the opposite results have also been reported [32]. An association between socioeconomic status and sleep habits remains to be elucidated.

In summary, we can say that (i) The mean sleep duration of school nights of grade 7 to 12 pupils did not reach the lower level of recommendations. (ii) Pupils are assumed to compensate for their sleep shortage during school nights by increasing sleep duration during non-school nights. (iii) Shortening after-school activity and school day screen time would be expected to increase their sleep duration. (iv) The association between sleep duration and academic performance remains to be delineated.

Author Contributions

The author did all the research work of this study.

Competing Interests

The author has declared that no competing interests exist.

References

  1. OECD. Gender data portal, 2018, time use across the world [Internet]. Paris. [June 22, 2019]. Available from: https://www.oecd.org/gender/data/OECD_1564_TUSupdatePortal.xlsx.
  2. Kohyama J. Good daily habits during the early stages of life determine success throughout life. Sleep Sci. 2016; 9: 153-157. [CrossRef]
  3. Chattu VK, Manzar MD, Kumary S, Burman D, Spence DW, Pandi-Perumal SR. The global problem of insufficient sleep and its serious public health implications. Healthcare. 2018; 7: doi: 10.3390/healthcare7010001. [CrossRef]
  4. Kohyama J, Anzai Y, Ono M, Kishino A, Tamanuki K, Takada K, et al. Insufficient sleep syndrome: An unrecognized but important clinical entity. Pediatr Int. 2018; 60: 372-375. [CrossRef]
  5. Paruthi S, Brooks LJ, D'Ambrosio C, Hall WA, Kotagal S, Lloyd RM, et al. Recommended amount of sleep for pediatric populations: A consensus statement of the American Academy of Sleep Medicine. J Clin Sleep Med. 2016; 12: 785-786. [CrossRef]
  6. Wheaton AG, Jones SE, Cooper AC, Croft JB. Short sleep duration among middle school and high school students - United States, 2015. MMWR Morb Mortal Wkly Rep. 2018; 67: 85-90. [CrossRef]
  7. National Sleep Foundation. Children and sleep [Internet]. Arlington: National Sleep Foundation; 2019 [June 22, 2019]. Available from: https://www.sleepfoundation.org/press-release/national-sleep-foundation-recommends-new-sleep-times/page/0/1.
  8. National Heart, Lung, And Blood Institute. Your guide to healthy sleep [Internet]. Bethesda: US Department of Health and Human Services; 2011 [June 22, 2019] Available from: https://www.nhlbi.nih.gov/files/docs/public/sleep/healthy_sleep.pdf.
  9. Lewin D, Wolfson AR, Bixler EO, Carskadon MA. Duration isn't everything. Healthy sleep in children and teens: Duration, individual need and timing. J Clin Sleep Med. 2016; 12: 1439-1441. [CrossRef]
  10. Kohyama J. Self-reported academic performance and lifestyle habits of school children in Japan. Int J Child Health Nutr. 2017; 6: 90-97. [CrossRef]
  11. Kohyama J, Ono M, Anzai Y, Kishino A, Tamanuki K, Moriyama K, et al. Factors associated with sleep duration among pupils in Japan. Ped Int. (in preparation).
  12. Wolfson AR, Carskadon MA. Sleep schedules and daytime functioning in adolescents. Child Dev. 1998; 69: 875-887. [CrossRef]
  13. Japan Society of School Health. Annual reports on health of children attending elementary schools, junior high schools, and high schools in 2014. Tokyo: Japan Society of School Health; 2016.
  14. Wahlstrom KL, Owens JA. School start time effects on adolescent learning and academic performance, emotional health and behaviour. Curr Opin Psychiatry. 2017; 30: 485-490. [CrossRef]
  15. Uchimura N. Sleep and academic performance in high school students; effects of nap. Progress in Medicine. 2015; 35: 39-41 (in Japanese).
  16. Ohta M. The fifth report on basic study on learning. Opportunities of learning except for school [Internet]. Okayama: Benesse Corporation; 2015 [June 22, 2019]. Available from: https://berd.benesse.jp/up_images/research/3_chp3.pdf.
  17. Benesse Educational Research and Development Institute. The report on the second survey on the basic child life-style, 2009. [June 22, 2019]. Available from: https://berd.benesse.jp/berd/center/open/report/kodomoseikatu_data/2009/hon2_1_05c.html.
  18. Carter B, Rees P, Hale L, Bhattacharjee D, Paradkar MS. Association between portable screen-based media device access or use and sleep outcomes: A systematic review and meta-analysis. JAMA Pediatr. 2016; 170: 1202-1208. [CrossRef]
  19. Hale L, Kirschen GW, LeBourgeois MK, Gradisar M, Garrison MM, Montgomery-Downs H, et al. Youth screen media habits and sleep: Sleep-friendly screen-behavior recommendations for clinicians, educators, and parents. Child Adolesc Psychiatr Clin N Am. 2018; 27: 229-245. [CrossRef]
  20. Fobian AD, Avis K, Schwebel DC. The impact of media use on adolescent sleep efficiency. J Dev Behav Pediatr. 2016; 37: 9-14. [CrossRef]
  21. Curcio, G, Ferrara, M, De Gennaro, L. Sleep loss, learning capacity and academic performance. Sleep Med Rev. 2006; 10: 323-337. [CrossRef]
  22. Owens JA, Weiss MR. Insufficient sleep in adolescents: Causes and consequences. Minerva Pediatr. 2017; 69: 326-336.
  23. Chaput JP, Gray CE, Poitras VJ, Carson V, Gruber R, Olds T, et al. Systematic review of the relationships between sleep duration and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016; 41: S266-S282. [CrossRef]
  24. Dumuid D, Olds T, Martín-Fernández JA, Lewis LK, Cassidy L, Maher C. Academic performance and lifestyle behaviors in Australian school children: A cluster analysis. Health Educ Behav. 2017; 44: 918-927. [CrossRef]
  25. Beebe DW, Field J, Miller MM, Miller LE, Le Blond E. Impact of multi-night experimentally induced short sleep on adolescent performance in a simulated classroom. Sleep. 2017; 40: doi: 10.1093/sleep/zsw035. [CrossRef]
  26. Hysing M, Harvey AG, Linton SJ, Askeland KG, Sivertsen B. Sleep and academic performance in later adolescence: Results from a large population-based study. J Sleep Res. 2016; 25: 318-324. [CrossRef]
  27. Carskadon MA, Dement WC. Normal human sleep: an overview. In: Kryger MH, Roth T, Dement WC, editors. Principles and practice of sleep medicine, 6th edn. Philadelphia: Elsevier Saunders. 2017: 15-24. [CrossRef]
  28. Cohen-Zion M, Shiloh E. Evening chronotype and sleepiness predict impairment in executive abilities and academic performance of adolescents. Chronobiol Int. 2018; 35: 137-145. [CrossRef]
  29. Hale L, Berger LM, LeBourgeois MK, Brooks-Gunn J. Social and demographic predictors of preschoolers’ bedtime routines. J Dev Behav Pediatr. 2009; 30: 394-402. [CrossRef]
  30. Biggs SN, Lushington K, James Martin A, van den Heuvel C, Declan Kennedy J. Gender, socioeconomic, and ethnic differences in sleep patterns in school-aged children. Sleep Med. 2013; 14: 1304-1309. [CrossRef]
  31. Felden ÉP, Leite CR, Rebelatto CF, Andrade RD, Beltrame TS. Sleep in adolescents of different socioeconomic status: A systematic review. Rev Paul Pediatr. 2015; 33: 467-473. [CrossRef]
  32. Zhang J, Li AM, Fok TF, Wing YK. Roles of parental sleep/wake patterns, socioeconomic status, and daytime activities in the sleep/wake patterns, socioeconomic status, and daytime activities in the sleep/wake patterns of children. J Pediatr. 2010; 156: 606-612. [CrossRef]
Newsletter
Download PDF Download Full-Text XML Download Citation
0 0

TOP