write a summary for the article

15 Jun write a summary for the article

RESEARCH ARTICLE

Sleep Duration, Schedule and Quality among Urban Chinese Children and Adolescents: Associations with Routine After-School Activities Xiaoxiao Jiang1,2, Louise L. Hardy2, Louise A. Baur2, Ding Ding2, LingWang1, Huijing Shi1*

1 School of Public Health and Key Laboratory of Public Health Safety, Fudan University, Shanghai, China, 2 Prevention Research Collaboration, School of Public Health, University of Sydney, Sydney, Australia

* hjshi@fudan.edu.cn

Abstract

Background

With rapid urbanization accompanied by lifestyle changes, children and adolescents living

in metropolitan areas are faced with many time use choices that compete with sleep. This

study reports on the sleep hygiene of urban Chinese school students, and investigates the

relationship between habitual after-school activities and sleep duration, schedule and

quality on a regular school day.

Methods

Cross-sectional, school-based survey of school children (Grades 4–8) living in Shanghai,

China, conducted in 2011. Self-reported data were collected on students’ sleep duration

and timing, sleep quality, habitual after-school activities (i.e. homework, leisure-time physi-

cal activity, recreational screen time and school commuting time), and potential correlates.

Results

Mean sleep duration of this sample (mean age: 11.5-years; 48.6% girls) was 9 hours. Nearly

30% of students reported daytime tiredness. On school nights, girls slept less (p<0.001) and went to bed later (p<0.001), a sex difference that was more pronounced in older stu- dents. Age by sex interactions were observed for both sleep duration (p=0.005) and bed- time (p=0.002). Prolonged time spent on homework and mobile phone playing was related to shorter sleep duration and later bedtime. Adjusting for all other factors, with each addi- tional hour of mobile phone playing, the odds of daytime tiredness and having difficulty maintaining sleep increased by 30% and 27% among secondary students, respectively. PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 1 / 12 OPEN ACCESS Citation: Jiang X, Hardy LL, Baur LA, Ding D, Wang L, Shi H (2015) Sleep Duration, Schedule and Quality among Urban Chinese Children and Adolescents: Associations with Routine After-School Activities. PLoS ONE 10(1): e0115326. doi:10.1371/journal. pone.0115326 Academic Editor: Masako Taniike, Osaka University, JAPAN Received: July 9, 2014 Accepted: November 22, 2014 Published: January 22, 2015 Copyright: © 2015 Jiang et al. This is an open ac- cess article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: All relevant data are within the paper. Funding: The study is mainly funded by the Shang- hai Municipal Committee of Education and also spon- sored by Shanghai Municipal Health Bureau (Award Number: 12GWZX0301). The authors also thank the China Scholarship Council (CSC) for funding Xiaox- iao Jiang’s doctoral scholarship in joint-PhD program with University of Sydney and this analysis, which is part of the requirements for her PhD studies. The funders had no role in study design, data collection http://crossmark.crossref.org/dialog/?doi=10.1371/journal.pone.0115326&domain=pdf http://creativecommons.org/licenses/by/4.0/ Conclusion There are sex differences in sleep duration, schedule and quality. Habitual activities had small but significant associations with sleep hygiene outcomes especially among second- ary school students. Intervention strategies such as limiting children’s use of electronic screen devices after school are implicated. Introduction Adequate sleep plays a crucial role in the physical, mental and cognitive development of chil- dren and adolescents. [1–3] Insufficient sleep is linked to impaired mental health [4] and school performance, [5] obesity, [6] and health risk behaviors. [7] The sleep duration of chil- dren and adolescents has declined by nearly one hour per night during the past century, espe- cially in countries in Asia and North America. [8] Among the Chinese pediatric population, short sleep duration and sleep problems including sleep onset latency (i.e. difficulty initiating sleep), sleep disturbance (i.e. difficulty maintaining sleep), and daytime tiredness or sleepiness are prevalent, [9–10] with sleep duration being less than for American children [11]. Although there is no current international consensus on optimal sleep duration for each age group, [12] many factors, such as age, health status and the urban context, contribute to children’s sleep behavior and quality. [13–16] Sociocultural [17] and family environments [18] have been explored to explain Chinese chil- dren’s sleep behaviors, but few studies have focused on the relationship between children’s and adolescents’ routine activities outside school hours and sleep outcomes. It is possible that children today, consciously or not, trade their sleep time for other activities that are pressing or of greater interest. In Asian children, academic performance and pressure are strongly associated with sleep duration, especially among adolescents. [19–20] However, there has been little investigation of the actual time that children spend studying after school, which may have an independent associ- ation with sleep apart from academic pressure. Among nighttime activities, inverse associations between electronic screen entertainment (i.e. TV viewing, playing computers and videogames) and sleep have been observed in both developed and developing countries [21–23] though the ev- idence was inconsistent regarding mobile phone use. [24] Western studies [25–26] have empha- sized the benefits of delaying school start times, however, in China long distances travelled between home and school and traffic congestion may compromise such efforts. Furthermore, most Chinese studies have focused on younger children and there are no studies in adolescents. Rapid urbanization, accompanied by tremendous changes in lifestyle, is affecting young people in Shanghai and other developed areas of China. Children and adolescents are faced with a new range of time use choices and prolonged commuting times that compete with sleep time and possibly interfere with sleep, schedule and quality. Therefore, in this study of older children and adolescents living in the Shanghai inner city area, we aimed to: 1) report the sleep duration, schedule, and sleep quality and 2) examine the associations between time spent on routine activities outside school hours and a range of sleep hygiene outcomes. Materials and Methods Sampling and procedures A cross-sectional, school-based questionnaire survey was conducted among Shanghai inner city students from Grades 4 to 8 (both elementary and secondary grades) between October and Correlates of Sleep among Chinese Children and Adolescents PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 2 / 12 and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. November 2011, a period when there were no public holidays or exams. Trained field staff admin- istered a questionnaire to the students during a school visit. Parents or guardians filled out sepa- rate questionnaires which were submitted by the student within a week after the first submission. Informed consent was well-explained for all students and their parents, and signed by both stu- dents themselves and their parents or guardians voluntarily before participating in the study. The study was approved by the Ethics Review Board of Fudan University (IRB # 2011–12–0321)”. A multi-stage random cluster sampling design was used to select districts, schools and clas- ses. The first stage involved the random selection of four districts in inner city areas of Shang- hai. The second stage involved the random selection of schools (three elementary schools and three middle schools from each district) and the third stage involved the random selection of classes stratified by grade (213 classes from 24 schools). Private or international schools in Shanghai were not included in this study because of the difference in school curricula. Measures Students’ sex, date of birth, weight and height were extracted from the Shanghai annual physi- cal examination database. [27] Weight (kg) and height (m) were measured by authorized clini- cal staff in the spring of 2011 and body mass index (BMI) was calculated. BMI was classified based on the International Obesity Taskforce (IOTF) age-sex specific BMI cut-points for the Asian pediatric population. [28] A questionnaire was given to parents to provide their educa- tional level (whether or not they had a university degree) and the number of children at home. Sleep hygiene (timing, duration, and quality). Students were asked to report what time they usually go to bed and wake up on a regular school day (timing). Sleep duration was calcu- lated as the time lapse between bedtime and wake up time. Sleep quality was assessed using the Multidimensional Sub-health Questionnaire of Adoles- cents (MSQA), which shows good internal reliability and criterion validity among Chinese ad- olescents. [29] Students reported “For the past six months, how many weeks/months in total have you been: (1) having difficulty falling asleep?; (2) having difficulty staying asleep at night?; (3) feeling tired and lacking energy during the day?” to indicate three sleep problems as ‘Had difficulty initiating sleep’, ‘Had difficulty maintaining sleep’, and ‘Daytime tiredness’, respec- tively. For each question, response categories were none; less than one week; 1–2 weeks; more than 2 weeks; more than 1 month; more than 2 months; and, more than 3 months. Responses were dichotomized as not having sleep problems (none and less than one week) or having sleep problems (remaining responses). Recreational screen time and mobile phone playing. Students reported the duration of weekday after-school screen-time (i.e. watching TV, playing on a computer (desktop, laptop or tablet devices) and playing videogames), which were summed and categorized according to recommendations of<2 hours or�2 hours. [30] The duration of mobile phone playing was determined by the question ‘How many hours and minutes have you spent playing the mobile phone (i.e. texting, playing games, or surfing on internet) after school?’, and the 10-day test- retest reliability of the questions was satisfactory (intraclass correlation coefficient = 0.78 and 0.74 for screen-time and time spent mobile phone playing, respectively). Study load and academic pressure. For the study load, students reported time they spent on homework on an average school day, as measured by the question “How many hours and minutes do you usually spend on doing your homework with or without a computer on an av- erage school night?” (Test-retest reliability of intraclass correlation coefficient = 0.85 for total time spent on homework). For self-perceived academic pressure, students also responded to the question “How much are you stressed about your academic performance?” with a five- point Likert scale ranging from “very much” to “not at all”. Correlates of Sleep among Chinese Children and Adolescents PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 3 / 12 Commuting time. Students reported the time spent commuting to and from home to school by car, public transport, cycling or walking, separately. These items were summed to cal- culate total commuting time. Leisure-time physical activity. After-school leisure-time physical activity (LTPA) was mea- sured by asking students how long they spent in light (e.g. walking), moderate (e.g. jogging, badminton) and vigorous (e.g. tennis, swimming) physical activity and summed to determine total LTPA. Statistical analysis Main outcome variables were sleep duration, sleep schedule (represented by time going to bed, or bedtime), and sleep quality (represented by having or not having sleep problems). One-way ANOVA and the Chi-square test were used to describe the sleep duration, timing, and the prevalence of sleep problems across age groups respectively. Age and sex interactions for sleep duration and bedtime were tested by two-way ANOVA. Multiple linear regression analysis was used to examine the potential correlates of sleep du- ration and bedtime (transformed into decimals). Separate analyses were conducted for school levels (i.e. elementary and secondary), as different patterns of sleep are expected at different de- velopmental stages. Multivariate logistic regression was used for the three sleep quality out- comes. Multicollinearity diagnostic statistics were computed and the VIF values ranged from 1.01 to 1.12 (i.e., no evidence of multicollinearity). For multivariate analysis, the list-wise dele- tion method was used for handling missing data and the students were excluded from analyses if any single value was missing. The difference in demographic characteristics between the ex- cluded students and the remaining students was compared by t-test or Chi-square test. Com- pared with students with complete data, more boys than girls (41.8% vs 33.7%, p<0.001) were with missing information of any of the independent variable. Due to missing data, the propor- tions of participants excluded from the analysis for elementary and secondary students were 34.7% and 42.9%, respectively. Sensitivity analyses were conducted by re-analyzing data includ- ing missing values on covariates as a separate category. Furthermore, to examine potential effect modification by parental education, we tested the interaction terms between parental ed- ucation and each independent variable. Data were analyzed in 2013, using SPSS (version 21 for Windows, Chicago, IL). P values were two sided with a significance level of 0.05. Results A total of 6,247 (response rate: 94.8%) students with parental data completed the survey. Table 1 summarizes the characteristics of the sample. The mean age was 11.5 years (range: 8.08–16.71 years), 48.6% were girls and 41.7% were in elementary school. The numbers of par- ticipants in each age group and school grade were distributed evenly. Sleep duration, sleep timing and the prevalence of sleep problems by age group and sex are shown in Table 2. The mean sleep duration on a regular school night was 9 hours, with the av- erage bedtime approximately 9:30 pm and wake up time around 6:30 am. Older children woke up earlier, went to bed later and had a shorter sleep duration than younger ones (p for trend <0.001). Overall, 19% of the students reported having difficulty initiating sleep, 15.6% reported having difficulty maintaining sleep and almost one third (29.7%) reported daytime tiredness. There were significant differences among age groups for difficulty maintaining sleep (p=0.004) and daytime tiredness (p<0.001), but not for difficulty initiating sleep (p=0.371). Girls went to bed later, woke up earlier and slept less than boys (Table 2). Age by sex inter- actions were found for both sleep duration (p=0.005) and bedtime (p=0.002). Sex differences increased with age. For sleep problems, the only sex difference detected was among secondary Correlates of Sleep among Chinese Children and Adolescents PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 4 / 12 school students, with more secondary school girl students reporting difficulty in maintaining sleep (p<0.001) and daytime tiredness (p<0.001). Table 3 shows variables associated with sleep duration. For all students, sleep duration was inversely associated with time spent on homework, commuting and mobile phone playing, ad- justing for potential confounders. The largest effect size was for homework, especially for sec- ondary students. For secondary school boys,<2 hours daily screen-time was associated with Table 1. Sample characteristics. Total Sample (n = 6247) n (%) Sex (girls) 3034 (48.6) Age (years old) group <10 1291 (20.7) 10–11 1167 (18.7) 11–12 1351 (21.6) 12–13 1146 (18.3) >13 1292 (20.7)

School grade

4 1279 (20.5)

5 1326 (21.2)

6 1310 (21.0)

7 1169 (18.7)

8 1163 (18.6)

Father with university degree 1666 (27.4)

Mother with university degree 1339 (22.0)

Lives with a sibling 1513 (25.0)

Self-reported academic pressure

Not at all or seldom 958 (16.7)

A little 2738 (47.8)

Yes or very much 2036 (35.5)

Daily screen time � 2 hours 686 (12.4) Overweight/obese a 2382 (40.1)

a According to International Task Force on Obesity Asian reference, sex-age-specific BMI cut-offs that

correspond to overweight BMI of 23kg/m2 at age 18 years.

doi:10.1371/journal.pone.0115326.t001

Table 2. Sleep duration, sleep timing and sleep problems by age group and sex (N = 6274).

Age group Sex

<10 years 10–11 years 11–12 years 12–13 years �13 years p Boys Girls p Sleep duration (hours) 9.58(0.67) 9.43(0.70) 8.93(0.78) 8.67(0.71) 8.28(0.84) <0.001 9.03(0.89) 8.92(0.88) <0.001 Sleep schedule a Bedtime (pm) 9.07(0.63) 9.18(0.66) 9.47(0.66) 9.67(0.66) 10.00(0.76) <0.001 9.44(0.75) 9.52(0.76) <0.001 Wake up time (am) 6.67(0.43) 6.63(0.43) 6.40(0.39) 6.34(0.39) 6.29(0.43) <0.001 6.48(0.45) 6.45(0.43) 0.023 Sleep problems (%) Had difficulty initiating sleep 20.8 18.5 17.8 18.3 19.4 0.37 19.8 18.1 0.10 Had difficulty maintaining sleep 15.0 14.8 13.4 16.4 18.7 0.004 15.5 15.8 0.80 Daytime tiredness 25.2 25.7 28.4 31.3 37.8 <0.001 27.2 32.3 <0.001 a Minutes were divided by 60 and multiplied by 100 and added to number of hours to generate a metric variable doi:10.1371/journal.pone.0115326.t002 Correlates of Sleep among Chinese Children and Adolescents PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 5 / 12 longer sleep duration, while among secondary school girls, participating in less LTPA after school was associated with shorter sleep duration. For the variables associated with school night bedtime (Table 4), more time spent on home work was found to be associated with later bedtime in all students. With the exception of ele- mentary school boys, mobile phone playing was related to a later bedtime, especially in second- ary school students. Secondary school girls who participated in less LTPA after school and� 2 hours/day of screen-time had a later bedtime. School commuting time was not associated with bedtime in any of the models. Table 3. Associations (indicated by regression coefficients) of weekday habitual after-school activity factors and sleep duration by school level and sex. School level Elementary school (Grade 4 and 5) Secondary school (Grade 6,7 and 8) Beta P Beta P Boys Commuting time (hour) -0.097 0.004 -0.088 0.003 After-school LTPA (hour) 0.029 0.40 0.026 0.38 Homework time (hour) -0.124 <0.001 -0.184 <0.001 Screen time (0= < 2 hours/ day, 1 = � 2 hours/ day) -0.016 0.65 -0.075 0.013 Playing mobile phone (hour) -0.081 0.024 -0.119 <0.001 Girls Commuting time (hour) -0.081 0.017 -0.079 0.003 After-school LTPA (hour) -0.025 0.47 0.059 0.030 Homework time (hour) -0.095 0.005 -0.294 <0.001 Screen time (0= < 2 hours/ day, 1 = � 2 hours/ day) -0.034 0.34 0.018 0.53 Playing mobile phone (hour) -0.100 0.004 -0.092 0.001 All models were adjusted for age, BMI categories, parents’ education, whether or not lived with a sibling and academic pressure. doi:10.1371/journal.pone.0115326.t003 Table 4. Associations (indicated by regression coefficients) of weekday habitual after-school activity factors and bedtime by school level and sex. Age group Elementary school (Grade 4 and 5) Secondary school (Grade 6,7 and 8) Beta P Beta P Boys Commuting time (hour) 0.012 0.72 -0.019 0.51 After-school LTPA (hour) -0.043 0.20 -0.043 0.14 Homework time (hour) 0.109 0.001 0.219 <0.001 Academic pressure (0 = not at all, 4 = very much, 0–4) 0.082 0.015 0.137 <0.001 Screen time (0= < 2 hours/ day, 1 = � 2 hours/ day) 0.045 0.20 -0.016 0.58 Playing mobile phone (hour) -0.049 0.17 0.121 <0.001 Girls Commuting time (hour) 0.042 0.21 -0.002 0.94 After-school LTPA (hour) -0.012 0.72 -0.067 0.013 Homework time (hour) 0.078 0.022 0.303 <0.001 Screen time (0= < 2 hours/ day, 1 = � 2 hours/ day) 0.077 0.027 0.007 0.81 Playing mobile phone (hour) 0.070 0.046 0.079 0.005 All models were adjusted for age, BMI categories, parents’ education, whether or not lived with a sibling and academic pressure. doi:10.1371/journal.pone.0115326.t004 Correlates of Sleep among Chinese Children and Adolescents PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 6 / 12 Table 5 presents correlates of sleep problems. In elementary school, girls were less likely to have difficulty initiating (AOR[95%CI] = 0.73[0.57–0.94]) or maintaining sleep (AOR[95%CI] = 0.65[0.49–0.85]) than boys, while in secondary school, girls were more likely to report daytime tiredness (AOR[95%CI] = 1.35[1.11–1.64]), after adjusting for other fac- tors. Homework time was independently associated with difficulty maintaining sleep and daytime tiredness among only secondary school students. Similarly, the adjusted odds of diffi- culty maintaining sleep and daytime tiredness increased by 27% and 37%, respectively, among secondary school students for each additional hour of mobile phone playing. We didn’t not find evidence for interactions between parental education and other independent variables (all p>0.05). As a sensitivity analysis, we reran all models with missing values of co- variates coded as a category, which reduced case exclusion to 15.2% and 24.6% for elementary and secondary students. Results from sensitivity analysis were consistent with our original analysis, indicating robustness in our findings.

Discussion We investigated sleep duration, schedule and quality in a large sample of 4th to 8th grade school students living in metropolitan Shanghai. In our study, the average sleep duration was 9 hours and the time duration decreased with age. The result is similar to that reported in other Chi- nese studies of urban school-aged children [31–32] and Shanghai local government report. For example, in Shanghai, in the 2011 Green Standard Assessment of the Academic Perfor- mance (GSAAP) found that less than 50% of the Grade 4 students who slept more than 9 hours. [33] A recent meta-analysis has shown that Asian children have shorter weekday sleep duration compared with children in Australia, Europe and USA. [34] In contrast, we found that the sleep duration of the current sample was similar to counterparts in European countries [35–36] but longer than that of children from other Asian countries/regions such as Korea, [37] Malaysia [16] and Hong Kong. [38] Considering the different measures across studies, the comparisons among countries should be interpreted with caution. Within Shanghai, In 2011 GSAAP also found that there were less than 20% of the Grade 9 students who slept more than

Table 5. Associations (indicated by odd ratios) of weekday habitual after-school activity factors and sleep quality problems by school level.

Elementary school (Grade 4 and 5)

Difficulty initiating sleep Difficulty maintaining sleep Day time tiredness

OR (95% CI) AOR(95% CI)a OR (95% CI) AOR(95% CI)a OR (95% CI) AOR(95% CI)a

Being a girl 0.76(0.63–0.93) 0.73(0.57–0.94) 0.80(0.64–0.99) 0.65(0.49–0.85) 1.06(0.89–1.28) 1.06(0.84–1.33)

After-school LTPA (hour) 1.00 (1.00–1.00) 1.00 (1.00–1.00) 1.00 (1.00–1.00) 1.00(1.00–1.00) 1.00 (1.00–1.00) 1.00 (1.00–1.00)

Commuting time (hour) 1.00(1.00–1.00) 1.00(1.00–1.00) 1.00(0.99–1.00) 1.00(0.99–1.00) 0.99(0.99–1.00) 1.00(1.00–1.00)

Homework time (hour) 0.98(0.90–1.07) 0.98(0.88–1.08) 1.08(0.98–1.18) 0.98(0.87–1.09) 1.10(1.02–1.18) 1.07(0.97–1.17)

Screen time >= 2 hours 0.85(0.62–1.17) 0.78(0.51–1.20) 1.20(0.87–1.67) 1.34(0.88–2.05) 1.03(0.78–1.36) 0.98(0.67–1.43)

Playing mobile phone (hour) 1.32(1.01–1.72) 1.43(0.98–2.07) 1.32(1.00–1.76) 1.19(0.79–1.77) 1.29(0.99–1.67) 1.34(0.94–1.93)

Secondary school (Grade 6, 7 and 8)

Being a girl 1.01(0.85–1.20) 1.07(0.85–1.35) 1.19(1.00–1.43) 1.13(0.89–1.44) 1.40(1.22–1.62) 1.35(1.11–1.64)

After-school LTPA (hour) 1.00 (1.00–1.00) 1.00 (1.00–1.00) 1.00 (1.00–1.00) 1.00(1.00–1.00) 1.00 (1.00–1.00) 1.00 (1.00–1.00)

Commuting time (hour) 1.00 (1.00–1.00) 1.00 (1.00–1.00) 1.00(0.99–1.00) 0.99(0.99–1.00) 1.00 (1.00–1.00) 1.00 (1.00–1.00)

Homework time (hour)) 1.10(1.02–1.19) 1.05(0.95–1.17) 1.22(1.12–1.32) 1.18(1.07–1.31) 1.25(1.17–1.38) 1.16(1.07–1.27)

Screen time >= 2 hours 1.41(1.08–1.84) 1.15(0.80–1.67) 1.01(0.75–1.36) 0.79(0.52–1.21) 1.21(0.96–1.53) 1.06(0.77–1.46)

Playing mobile phone (hour) 1.25(1.04–1.51) 1.20(0.95–1.51) 1.39(1.15–1.67) 1.27(1.00–1.61) 1.58(1.33–1.88) 1.37(1.10–1.71)

a All models were adjusted for age, BMI categories, parents’ education and whether or not lived with a sibling.

doi:10.1371/journal.pone.0115326.t005

Correlates of Sleep among Chinese Children and Adolescents

PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 7 / 12

8 hours. [33] Our study did not include Grade 9 students who face much more study load and academic pressure because of junior to high school graduation exam. In such case, it is possible our results may overestimate the sleep duration of Shanghai school-aged children in general.

A major finding of our study is that girls slept less and went to bed later compared with boys, and these differences increased with age. Although a sex difference in school night bed- time among urban Chinese children (5–12 years old) has been previously reported, [31] the age-sex interaction on sleep among Chinese children has not been reported. Our finding is sim- ilar to one Spanish study [39] which showed the difference of sleep duration between boys and girls varied with age among older adolescents. However, in other studies, the sex differences in sleep behaviors were either not significant [31] or in the opposite direction. [40] In our study, the most frequently reported sleep problem was daytime tiredness, ranging from one quarter to almost 40%, with the prevalence increasing with age and being higher among girls. Boys in elementary school (Grade 4 and 5) were at higher risk of having difficulty initiating sleep and maintaining sleep compared to girls of the same grade. The sex difference observed in this study suggests that boys and girls at each developmental stage are susceptible to different types of sleep problems.

We found consistent associations between secondary students’ time spent on homework and sleep duration and bedtime, after adjusting for perceived academic pressure. Academic performance has always been highly valued within Asian families and societies. In our study, homework time in secondary students was also associated with poorer sleep quality. Such find- ings highlight the potentially adverse effect of academic burden placed on Asian children which is a cultural phenomenon that is distinct from many Western populations.

More time spent on LTPA was associated with longer sleep duration and earlier bedtime among older girls. There have been similar findings among Japanese adolescents [41] for sleep duration and American adolescents [42] for sleep quality in cross-sectional studies. A possible explanation for the observed association among girls, but not among boys, was the beneficial effect of LTPA on sleep could be more pronounced among people who had more sleep com- plaints or disturbance. [43–44] In our sample, older girls reported more problems with sleep and the moderate association may be more easily detected in this subgroup.

Interestingly, school commuting time was inversely associated with sleep duration but not bedtime, a finding which may reflect the inability of school students to adjust their schedule to compensate for sleep loss caused by daily commuting to/from school. In Chinese cities, while parents are encouraged to send their children to local schools, many parents send their children to academically prestigious schools which may well be out of area, with subsequent longer commuting times. Our finding suggests there is a need to inform parents of the health benefits of both providing children with bedtime rules and strategies to address time issues associated with school commuting.

We examined the unique relationship between mobile phone playing and sleep. Mobile phone playing was inversely associated with sleep duration and bedtime; it was also associated with difficulty in maintaining sleep and daytime tiredness among adolescents in secondary school. One Canadian study found that access to mobile phones but not the duration of the usage was associated with shorter sleep duration among elementary students [45], while find- ings from Taiwan showed that such relationships could not be confirmed in adolescents. [46] In our study, mobile phone playing (i.e. surfing the internet and playing games), instead of total usage, was measured. Thus, the inverse association found in our study may reflect the neg- ative influence of certain functions of mobile phone use on sleep. Future studies should mea- sure each type of mobile phone usage based on the nature of the behavior.

In our sample, surveyed in 2011, 56.4% of children and adolescents owned personal mobile phones (results not shown). Given the exponential growth of smart phones that mimic

Correlates of Sleep among Chinese Children and Adolescents

PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 8 / 12

functions that were once only available on desk-top computers, and recognizing that China has already become the leading consumer market for mobile phones, [47] we expect that short sleep duration and poor sleep quality attributed to mobile devices are likely to increase in the future. Information on types of phones (i.e., smart vs. traditional phones) and specific func- tions of mobile phone that children playing with could better inform the projection of mobile- phone related sleep loss of Chinese children.

It should be noted that spending�2 hours per day on screen-time for entertainment was not consistently associated with our measures of sleep quality. A separate study conducted among the Chinese pediatric population, six years prior to our study, found that more than 2 hours’ TV viewing time was linked to later bed time, but not sleep duration, among elementary students. [23] A possible explanation could be that, on school days, TV viewing and playing computers are more likely to be limited within the family, especially among primary school stu- dents, while secondary students tend to use mobile phones for communication in the evening, possibly resulting in interrupted sleep and daytime tiredness. [48] Thus, a practical solution would be to keep all electronic devices out of children’s bedrooms and to restrict night use of mobile phones, especially after children go to bed.

Strengths and limitations To our knowledge, this is the first study to investigate the association between after-school ac- tivities and sleep among a Chinese child and adolescent population. Study strengths include the large representative sample, the high response rate, and comprehensive measures of sleep outcomes. Although questions of sleep problems are indicators, not clinical measures, of sleep quality, the findings provide useful population information of sleep hygiene in Chinese school- aged children. The inclusion of mobile phone playing was a novel aspect of this study and shows that mobile screen technologies may play a critical role in children’s sleep hygiene, and hence there is a need to monitor children’s engagement with these technologies.

Limitations to take into account when interpreting our results include self-report data, which may be subject to recall bias; however, a separate study shown good agreement and cor- relation between self-report and objective measures of sleep especially on school nights. [49] Other factors, such as bed sharing and parents’ sleep habits, were not included in the study, nor did we have measures of sleep during non-school days. We are aware that sleep behaviors and outcomes and relevant risk factors could differ between school and non-school days.

Conclusion Girls slept less and reported more sleep problems. Mobile phone playing had a small but signif- icant association with sleep duration, schedule, and quality in secondary school students. The findings build evidence for formulating intervention strategies to change unhealthy practices associated with poor sleep hygiene, especially among adolescents. Simple measures such as set- ting a bed time and restricting children’s use of mobile phones after school are implicated. However, a remaining challenge is how to address the academic pressure felt by Chinese chil- dren, given the cultural emphasis the Chinese population places on education.

Acknowledgments We gratefully acknowledge all participating students and their parents for their collaboration. We also acknowledge the district education committees of Shanghai and 24 schools that helped facilitate the study. The study was mainly funded by the Shanghai Municipal Committee of Education and also sponsored by Shanghai Municipal Health Bureau (Award Number: 12GWZX0301). We also thank the China Scholarship Council (CSC) for funding Xiaoxiao

Correlates of Sleep among Chinese Children and Adolescents

PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 9 / 12

Jiang’s doctoral scholarship in joint-PhD program with University of Sydney and this analysis, which is part of the requirements for her PhD studies.

Author Contributions Conceived and designed the experiments: HS LH. Performed the experiments: XJ HS. Analyzed the data: XJ DD. Contributed reagents/materials/analysis tools: LB LWHS. Wrote the paper: XJ LH LB DD HS LW.

References 1. Chen M, Wang EK, Jeng Y (2006) Adequate sleep among adolescents is positively associated with

health status and health-related behaviors. BMC Public Health 6: 59. doi: 10.1186/1471-2458-6-59 PMID: 16524482

2. Smaldone A, Honig JC, Byrne MW (2007) Sleepless in America: inadequate sleep and relationships to health and well-being of our nation’s children. Pediatrics 119: S29–S37. doi: 10.1542/peds.2006- 2089F PMID: 17272582

3. Sadeh A (2007) Consequences of sleep loss or sleep disruption in children. Sleep Med Clin 2: 513–520. doi: 10.1016/j.jsmc.2007.05.012

4. Paavonen EJ, Almqvist F, Tamminen T, Moilanen I, Piha J, et al. (2002) Poor sleep and psychiatric symptoms at school: an epidemiological study. Eur Child Adolesc Psychiatry 11: 10–17. doi: 10.1007/ s007870200002 PMID: 11942422

5. Curcio G, Ferrara M, De Gennaro L (2006) Sleep loss, learning capacity and academic performance. Sleep Med Rev 10: 323–337. doi: 10.1016/j.smrv.2005.11.001 PMID: 16564189

6. Chen X, BeydounMA, Wang Y (2008) Is sleep duration associated with childhood obesity? A systemat- ic review and meta‐analysis. Obesity 16: 265–274. doi: 10.1038/oby.2007.63 PMID: 18239632

7. McKnight-Eily LR, Eaton DK, Lowry R, Croft JB, Presley-Cantrell L, et al. (2011) Relationships between hours of sleep and health-risk behaviors in US adolescent students. Prev Med 53: 271–273. doi: 10. 1016/j.ypmed.2011.06.020 PMID: 21843548

8. Matricciani L, Olds T, Petkov J (2012) In search of lost sleep: secular trends in the sleep time of school- aged children and adolescents. Sleep Med Rev 16: 203–211. doi: 10.1016/j.smrv.2011.03.005 PMID: 21612957

9. ChenWJ, Li F, Li SH, Yan CH, Jin XM, et al. (2011) Follow-up study of school-age children’s sleep qual- ity in Shanghai. Zhonghua Er Ke Za Zhi 49:333–7. In Chinese. doi: 10.1016/j.sleep.2010.03.018 PMID: 21624282

10. Guo X, Zheng L, Li Y, Yu S, Liu S, et al. (2011) Association between sleep duration and hypertension among Chinese children and adolescents. Clin Cardiol 34:774–81. doi: 10.1002/clc.20976 PMID: 21997181

11. Liu X, Liu L, Owens JA, Kaplan DL (2005) Sleep patterns and sleep problems among schoolchildren in the United States and China. Pediatrics 115: 241–249. doi: 10.1542/peds.2004-0815F PMID: 15866858

12. Matricciani LA, Olds TS, Blunden S, Rigney G, Williams MT (2012) Never enough sleep: a brief history of sleep recommendations for children. Pediatrics 129: 548–556. doi: 10.1542/peds.2011-2039 PMID: 22331340

13. Iglowstein I, Jenni OG, Molinari L, Largo RH (2003) Sleep duration from infancy to adolescence: refer- ence values and generational trends. Pediatrics 111: 302–307. doi: 10.1542/peds.111.2.302 PMID: 12563055

14. Cortese S, Brown TE, Corkum P, Gruber R, O’Brien LM, et al. (2013) Assessment and management of sleep problems in youths with attention-deficit/hyperactivity disorder. J Am Acad Child Adolesc Psychi- atry 52: 784–796. doi: 10.1016/j.jaac.2013.06.001 PMID: 23880489

15. Yang QZ, Bu YQ, Dong SY, Fan SS, Wang LX (2009) A comparison of sleeping problems in school‐ age children between rural and urban communities in China. J Paediatr Child Health 45: 414–418. doi: 10.1111/j.1440-1754.2009.01530.x PMID: 19712177

16. Firouzi S, Bee Koon P, Noor MI, Sadeghilar A (2013) Sleep pattern and sleep disorders among a sam- ple of Malaysian children. Sleep Biol Rhythms 11: 185–193. doi: 10.1111/sbr.12020

17. Tie L, Yu H, Huang S (2010) Cultural influences on the bedtime behaviour of Chinese children. Biol Rhythm Res 41: 183–202. doi: 10.1080/09291011003687957

Correlates of Sleep among Chinese Children and Adolescents

PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 10 / 12

http://dx.doi.org/10.1186/1471-2458-6-59
http://www.ncbi.nlm.nih.gov/pubmed/16524482
http://dx.doi.org/10.1542/peds.2006-2089F
http://dx.doi.org/10.1542/peds.2006-2089F
http://www.ncbi.nlm.nih.gov/pubmed/17272582
http://dx.doi.org/10.1016/j.jsmc.2007.05.012
http://dx.doi.org/10.1007/s007870200002
http://dx.doi.org/10.1007/s007870200002
http://www.ncbi.nlm.nih.gov/pubmed/11942422
http://dx.doi.org/10.1016/j.smrv.2005.11.001
http://www.ncbi.nlm.nih.gov/pubmed/16564189
http://dx.doi.org/10.1038/oby.2007.63
http://www.ncbi.nlm.nih.gov/pubmed/18239632
http://dx.doi.org/10.1016/j.ypmed.2011.06.020
http://dx.doi.org/10.1016/j.ypmed.2011.06.020
http://www.ncbi.nlm.nih.gov/pubmed/21843548
http://dx.doi.org/10.1016/j.smrv.2011.03.005
http://www.ncbi.nlm.nih.gov/pubmed/21612957
http://dx.doi.org/10.1016/j.sleep.2010.03.018
http://www.ncbi.nlm.nih.gov/pubmed/21624282
http://dx.doi.org/10.1002/clc.20976
http://www.ncbi.nlm.nih.gov/pubmed/21997181
http://dx.doi.org/10.1542/peds.2004-0815F
http://www.ncbi.nlm.nih.gov/pubmed/15866858
http://dx.doi.org/10.1542/peds.2011-2039
http://www.ncbi.nlm.nih.gov/pubmed/22331340
http://dx.doi.org/10.1542/peds.111.2.302
http://www.ncbi.nlm.nih.gov/pubmed/12563055
http://dx.doi.org/10.1016/j.jaac.2013.06.001
http://www.ncbi.nlm.nih.gov/pubmed/23880489
http://dx.doi.org/10.1111/j.1440-1754.2009.01530.x
http://www.ncbi.nlm.nih.gov/pubmed/19712177
http://dx.doi.org/10.1111/sbr.12020
http://dx.doi.org/10.1080/09291011003687957
18. Li S, Zhu S, Jin X, Yan C, Wu S, et al. (2010) Risk factors associated with short sleep duration among Chinese school-aged children. Sleep Med 11: 907–916. doi: 10.1016/j.sleep.2010.03.018 PMID: 20817554

19. Chung K, Cheung M (2008) Sleep-wake patterns and sleep disturbance among Hong Kong Chinese adolescents. Sleep 31: 185. PMID: 18274265

20. Yang C, Kim JK, Patel SR, Lee J (2005) Age-related changes in sleep/wake patterns among Korean teenagers. Pediatrics 115: 250–256. doi: 10.1542/peds.2004-0815G PMID: 15866859

21. Dworak M, Schierl T, Bruns T, Strüder HK (2007) Impact of singular excessive computer game and tele- vision exposure on sleep patterns and memory performance of school-aged children. Pediatrics 120: 978–985. doi: 10.1542/peds.2007-0476 PMID: 17974734

22. Nuutinen T, Ray C, Roos E (2013) Do computer use, TV viewing, and the presence of the media in the bedroom predict school-aged children’s sleep habits in a longitudinal study. BMC public health 13: 684. doi: 10.1186/1471-2458-13-684 PMID: 23886318

23. Li S, Jin X, Wu S, Jiang F, Yan C, et al. (2007) The impact of media use on sleep patterns and sleep dis- orders among school-aged children in China. Sleep 30: 361–367. PMID: 17425233

24. Cain N, Gradisar M (2010) Electronic media use and sleep in school-aged children and adolescents: A review. Sleep Med 11: 735–742. doi: 10.1016/j.sleep.2010.02.006 PMID: 20673649

25. Wolfson AR, Spaulding NL, Dandrow C, Baroni EM (2007) Middle school start times: the importance of a good night’s sleep for young adolescents. Behav Sleep Med 5: 194–209. doi: 10.1080/ 15402000701263809 PMID: 17680731

26. Owens JA, Belon K, Moss P (2010) Impact of delaying school start time on adolescent sleep, mood, and behavior. Arch Pediatr Adolesc Med 164: 608–614. doi: 10.1001/archpediatrics.2010.96 PMID: 20603459

27. Shanghai Students Health Monitoring Center (2014). Available: . Accessed 2011 December 12th.

28. Cole TJ, Lobstein T (2012) Extended international (IOTF) body mass index cut‐offs for thinness, over- weight and obesity. Pediatr Obes 7: 284–294. doi: 10.1111/j.2047-6310.2012.00064.x PMID: 22715120

29. Tao FB, Hu CL, Sun YH, Hao JH (2008) The development and application of multidimensional sub- health questionnaire of adolescents (MSQA). Chinese Journal of Disease Control and Prevention 12: 309–314.

30. American Academy of Pediatrics. (2001) Children, adolescents, and television. Pediatrics 107: 423–426. doi: 10.1542/peds.107.2.423 PMID: 11158483

31. Zhang Z, Chen T, Jin X, Yan C, Shen X, et al. (2013) Sleep Patterns, Sleep Problems and Associations with Reported Sleep Quality in Chinese School-Aged Children. Am J Public Health Res 1: 93–100. doi: 10.12691/ajphr-1-4-3

32. Wang G, Xu G, Liu Z, Lu N, Ma R, et al. (2013) Sleep patterns and sleep disturbances among Chinese school-aged children: Prevalence and associated factors. Sleep Med 14: 45–52. doi: 10.1016/j.sleep. 2012.09.022 PMID: 23218539

33. 2011Green Standard Assessment of the Academic Performance (GSAAP). Accessed 2014 October 12th.

34. Olds T, Blunden S, Petkov J, Forchino F (2010) The relationships between sex, age, geography and time in bed in adolescents: a meta-analysis of data from 23 countries. Sleep Med Rev 14: 371–378. doi: 10.1016/j.smrv.2009.12.002 PMID: 20207558

35. Russo PM, Bruni O, Lucidi F, Ferri R, Violani C (2007) Sleep habits and circadian preference in Italian children and adolescents. J Sleep Res 16: 163–169. doi: 10.1111/j.1365-2869.2007.00584.x PMID: 17542946

36. Loessl B, Valerius G, Kopasz M, Hornyak M, Riemann D, et al. (2008) Are adolescents chronically sleep‐deprived? An investigation of sleep habits of adolescents in the Southwest of Germany. Child Care Health Dev 34: 549–556. doi: 10.1111/j.1365-2214.2008.00845.x PMID: 18549435

37. Lee YJ, Cho S, Cho IH, Kim SJ (2012) Insufficient sleep and suicidality in adolescents. Sleep 35: 455. doi: 10.5665/sleep.1722 PMID: 22467982

38. Chung K, Kan KK, YeungW (2013) Sleep duration, sleep–wake schedule regularity, and body weight in Hong Kong Chinese adolescents. Biol Rhythm Res 44: 169–179. doi: 10.1080/09291016.2012. 656247

39. Ortega FB, Chillón P, Ruiz JR, Delgado M, Albers U, et al. (2010) Sleep patterns in Spanish adoles- cents: associations with TV watching and leisure-time physical activity. Eur J Appl Physiol 110: 563–573. doi: 10.1007/s00421-010-1536-1 PMID: 20556419

Correlates of Sleep among Chinese Children and Adolescents

PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 11 / 12

http://dx.doi.org/10.1016/j.sleep.2010.03.018
http://www.ncbi.nlm.nih.gov/pubmed/20817554
http://www.ncbi.nlm.nih.gov/pubmed/18274265
http://dx.doi.org/10.1542/peds.2004-0815G
http://www.ncbi.nlm.nih.gov/pubmed/15866859
http://dx.doi.org/10.1542/peds.2007-0476
http://www.ncbi.nlm.nih.gov/pubmed/17974734
http://dx.doi.org/10.1186/1471-2458-13-684
http://www.ncbi.nlm.nih.gov/pubmed/23886318
http://www.ncbi.nlm.nih.gov/pubmed/17425233
http://dx.doi.org/10.1016/j.sleep.2010.02.006
http://www.ncbi.nlm.nih.gov/pubmed/20673649
http://dx.doi.org/10.1080/15402000701263809
http://dx.doi.org/10.1080/15402000701263809
http://www.ncbi.nlm.nih.gov/pubmed/17680731
http://dx.doi.org/10.1001/archpediatrics.2010.96
http://www.ncbi.nlm.nih.gov/pubmed/20603459
http://www.tzjk.net/
http://dx.doi.org/10.1111/j.2047-6310.2012.00064.x
http://www.ncbi.nlm.nih.gov/pubmed/22715120
http://dx.doi.org/10.1542/peds.107.2.423
http://www.ncbi.nlm.nih.gov/pubmed/11158483
http://dx.doi.org/10.12691/ajphr-1-4-3
http://dx.doi.org/10.1016/j.sleep.2012.09.022
http://dx.doi.org/10.1016/j.sleep.2012.09.022
http://www.ncbi.nlm.nih.gov/pubmed/23218539
http://www.age06.com/Age06.Web/Detail.aspx?InfoGuid = 1a680950-bfc1–4f77–8b21–1a2edfc70648
http://dx.doi.org/10.1016/j.smrv.2009.12.002
http://www.ncbi.nlm.nih.gov/pubmed/20207558
http://dx.doi.org/10.1111/j.1365-2869.2007.00584.x
http://www.ncbi.nlm.nih.gov/pubmed/17542946
http://dx.doi.org/10.1111/j.1365-2214.2008.00845.x
http://www.ncbi.nlm.nih.gov/pubmed/18549435
http://dx.doi.org/10.5665/sleep.1722
http://www.ncbi.nlm.nih.gov/pubmed/22467982
http://dx.doi.org/10.1080/09291016.2012.656247
http://dx.doi.org/10.1080/09291016.2012.656247
http://dx.doi.org/10.1007/s00421-010-1536-1
http://www.ncbi.nlm.nih.gov/pubmed/20556419
40. Biggs SN, Lushington K, James Martin A, van den Heuvel C, Declan Kennedy J (2013) Gender, socio- economic, and ethnic differences in sleep patterns in school-aged children. Sleep Med 14: 1304–1309. doi: 10.1016/j.sleep.2013.06.014 PMID: 24074692

41. TAGAYA H, UchiyamaM, OHIDA T, KAMEI Y, SHIBUI K, et al. (2004) Sleep habits and factors associ- ated with short sleep duration among Japanese high‐school students: A community study. Sleep Biol Rhythms 2: 57–64. doi: 10.1111/j.1479-8425.2003.00079.x

42. Foti KE, Eaton DK, Lowry R, McKnight-Ely LR (2011) Sufficient sleep, physical activity, and sedentary behaviors. Am J Prev Med 41: 596–602. doi: 10.1016/j.amepre.2011.08.009 PMID: 22099236

43. Merrill RM, Aldana SG, Greenlaw RL, Diehl HA, Salberg A (2006) The effects of an intensive lifestyle modification program on sleep and stress disorders. J Nutr Health Aging 11: 242–248.

44. Passos GS, Poyares D, Santana MG, D Aurea CVR, Youngstedt SD, et al. (2011) Effects of moderate aerobic exercise training on chronic primary insomnia. Sleep Med 12: 1018–1027. doi: 10.1016/j. sleep.2011.02.007 PMID: 22019457

45. Chahal H, Fung C, Kuhle S, Veugelers PJ (2013) Availability and night‐time use of electronic entertain- ment and communication devices are associated with short sleep duration and obesity among Canadi- an children. Pediatr Obes 8: 42–51. doi: 10.1111/j.2047-6310.2012.00085.x PMID: 22962067

46. Yen C, Ko C, Yen J, Cheng C (2008) The multidimensional correlates associated with short nocturnal sleep duration and subjective insomnia among Taiwanese adolescents. Sleep 31: 1515. PMID: 19014071

47. Global Mobile Statistics (2013) Part A: Mobile subscribers; handset market share; mobile operators. Available: . Accessed 2013 June 8.

48. Van den Bulck J (2007) Adolescent use of mobile phones for calling and for sending text messages after lights out: results from a prospective cohort study with a one-year follow-up. Sleep 30: 1220. PMID: 17910394

49. Wolfson AR, Carskadon MA, Acebo C, Seifer R, Fallone G, et al. (2003) Evidence for the validity of a sleep habits survey for adolescents. Sleep 26: 213–217. PMID: 12683482

Correlates of Sleep among Chinese Children and Adolescents

PLOS ONE | DOI:10.1371/journal.pone.0115326 January 22, 2015 12 / 12

http://dx.doi.org/10.1016/j.sleep.2013.06.014
http://www.ncbi.nlm.nih.gov/pubmed/24074692
http://dx.doi.org/10.1111/j.1479-8425.2003.00079.x
http://dx.doi.org/10.1016/j.amepre.2011.08.009
http://www.ncbi.nlm.nih.gov/pubmed/22099236
http://dx.doi.org/10.1016/j.sleep.2011.02.007
http://dx.doi.org/10.1016/j.sleep.2011.02.007
http://www.ncbi.nlm.nih.gov/pubmed/22019457
http://dx.doi.org/10.1111/j.2047-6310.2012.00085.x
http://www.ncbi.nlm.nih.gov/pubmed/22962067
http://www.ncbi.nlm.nih.gov/pubmed/19014071
http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats/a#topmobilemarkets
http://www.ncbi.nlm.nih.gov/pubmed/17910394
http://www.ncbi.nlm.nih.gov/pubmed/12683482