DOI: 10.1542/peds.2013-3998; originally published online April 14, 2014; 2014;133;e1163Pediatrics

Rifas-Shiman, Susan Redline and Elsie M. TaverasElizabeth M. Cespedes, Matthew W. Gillman, Ken Kleinman, Sheryl L.

Mid-ChildhoodTelevision Viewing, Bedroom Television, and Sleep Duration From Infancy to

  

  http://pediatrics.aappublications.org/content/133/5/e1163.full.html

located on the World Wide Web at: The online version of this article, along with updated information and services, is

 

of Pediatrics. All rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.Boulevard, Elk Grove Village, Illinois, 60007. Copyright © 2014 by the American Academy published, and trademarked by the American Academy of Pediatrics, 141 Northwest Pointpublication, it has been published continuously since 1948. PEDIATRICS is owned, PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly

at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

Television Viewing, Bedroom Television, and SleepDuration From Infancy to Mid-Childhood

WHAT’S KNOWN ON THIS SUBJECT: Inadequate sleep in childhoodis associated with poor mental and physical health. Numerouscross-sectional studies reveal associations between televisionviewing and the presence of a bedroom TV and inadequate sleepin older children and adolescents, but longitudinal research islimited.

WHAT THIS STUDY ADDS: More TV viewing, and, among racial/ethnic minority children, bedroom TV, were associated withshorter sleep from infancy to midchildhood. These results raisethe possibility that interventions to reduce TV could improvechildren’s sleep.

abstractBACKGROUND: Television and insufficient sleep are associated withpoor mental and physical health. This study assessed associationsof TV viewing and bedroom TV with sleep duration from infancy to mid-childhood.

METHOD: We studied 1864 children in Project Viva. Parents reportedchildren’s average daily TV viewing and sleep (at 6 months and an-nually from 1–7 years) and the presence of a bedroom TV (annually4–7 years). We used mixed effects models to assess associations of TVexposures with contemporaneous sleep, adjusting for child age, gen-der, race/ethnicity, maternal education, and income.

RESULTS: Six hundred forty-three children (35%) were racial/ethnicminorities; 37% of households had incomes #$70 000. From 6months to 7 years, mean (SD) sleep duration decreased from 12.2(2.0) hours to 9.8 (0.9) hours per day; TV viewing increased from 0.9(1.2) hours to 1.6 (1.0) hours per day. At 4 years, 17% had a bedroomTV, rising to 23% at 7 years. Each 1 hour per day increase in lifetimeTV viewing was associated with 7 minutes per day (95% confidenceinterval [CI]: 4 to 10) shorter sleep. The association of bedroom TVvaried by race/ethnicity; bedroom TV was associated with 31 minutesper day shorter sleep (95% CI: 16 to 45) among racial/ethnic minoritychildren, but not among white, non-Hispanic children (8 fewerminutes per day [95% CI: 219 to 2]).

CONCLUSIONS: More TV viewing, and, among racial/ethnic minoritychildren, the presence of a bedroom TV, were associated withshorter sleep from infancy to midchildhood. Pediatrics 2014;133:e1163–e1171

AUTHORS: Elizabeth M. Cespedes, SM,a,b Matthew W.Gillman, MD, SM,a,b Ken Kleinman, ScD,a Sheryl L. Rifas-Shiman, MPH,a Susan Redline, MD, MPH,c and Elsie M.Taveras, MD, MPHb,d

aObesity Prevention Program, Department of PopulationMedicine, Harvard Medical School and Harvard Pilgrim HealthCare Institute, Boston, Massachusetts; bDepartment of Nutrition,Harvard School of Public Health, Boston, Massachusetts;cBrigham and Women’s Hospital and Beth Israel DeaconessMedical Center, Harvard Medical School, Boston, Massachusetts;and dDivision of General Pediatrics, Department of Pediatrics,Massachusetts General Hospital for Children, Boston,Massachusetts

KEY WORDStelevision, sleep duration, sleep hygiene, childhood

ABBREVIATIONSCI—confidence intervalLRT—likelihood ratio testTV—television

Ms Cespedes conceptualized and designed the present analysis,conducted all data analysis, drafted the initial manuscript, andcompleted all subsequent revisions until submission; DrGillman, Dr Kleinman, and Ms Rifas-Shiman were involved in thedesign and implementation of the parent study, Project Viva,advised in the design and presentation of the present analysis,and revised drafts critically for important intellectual content;Dr Redline advised in the design of the present analysis, andrevised drafts critically for important intellectual content; DrTaveras conceptualized the present analysis, was involved in thedesign and implementation of the Project Viva study, advised inpresentation of analysis results, and revised drafts critically forimportant intellectual content; and all authors approved thefinal manuscript as submitted.

www.pediatrics.org/cgi/doi/10.1542/peds.2013-3998

doi:10.1542/peds.2013-3998

Accepted for publication Feb 11, 2014

Address correspondence to Elizabeth M. Cespedes, SM,Department of Nutrition, Harvard School of Public Health, 665Huntington Ave, Building II, 3rd Floor, Boston, MA 02115. E-mail:emc611@mail.harvard.edu

PEDIATRICS (ISSN Numbers: Print, 0031-4005; Online, 1098-4275).

Copyright © 2014 by the American Academy of Pediatrics

(Continued on last page)

PEDIATRICS Volume 133, Number 5, May 2014 e1163

ARTICLE

at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

Inadequate sleep in childhood is asso-ciated with poor mental and physicalhealth, including impaired academicperformance, depression, injury, andincreased obesity risk.1–8 Among manyfactors that influence children’s sleep,television 1RCMB_20130063OC_wc_f4.tif (TV) viewing and the presence of aTV in the bedroom (bedroom TV) are in-creasingly prevalent in young children’slives.9,10 TV behaviors may directly dis-place sleep time or increase mental/emotional arousal and light expo-sure, which can be detrimental to sleeponset, duration, and quality.11–15 Nu-merous cross-sectional studies iden-tify associations of TV behavior withinadequate sleep or sleep disturbancein older children and adolescents,11,16–19

but longitudinal research is limited.20 Forexample, evening media use has beenassociated with increased sleep prob-lems in preschool-aged children,14 andNational Sleep Foundation data re-veal associations of bedroom TVwith shorter sleep duration in 6- to 10-year-olds.21 A recent study in Finnishschoolchildren, the first to examineTV and sleep duration longitudinally,revealed that TV viewing predictedshorter weekday sleep 18 monthslater.20

Our study examines longitudinal asso-ciations of TV viewing and bedroom TVwith sleep duration from infancy tomidchildhood and explores differencesby gender and race/ethnicity. Sleep inearly childhood is particularly impor-tant to child health.8,22 We hypothesizedthat greater TV viewing and bedroomTV would predict shorter sleep duration.

METHODS

Population and Study Design

We studied participants in Project Viva,a longitudinal cohort of 2128 children(born 1999–2003) and their mothersfounded to examine effects of diet andother factors during pregnancy andafter birth. This analysis included 1864

mothers and children (86%) whoreported average sleep and TV viewingat $1 assessment from infancy (6months) to midchildhood (7 years);Table 1. We recruited women at pre-natal visits to 8 Harvard VanguardMedical Associates practices in Mas-sachusetts. Details of recruitment/retention procedures are availableelsewhere.23 After obtaining writteninformed consent, we performed in-person study visits with mothersand children in infancy (mean age, 6months) and early (mean age, 3.2years) and midchildhood (mean age,7.9 years). Mothers completed ques-tionnaires at 1, 2, 4, 5, and 6 yearspostpartum. Institutional review boardsof participating institutions approvedthe study.

Main Exposures: TV Viewing andBedroom TV

At 6 months and 1 year, mothers re-ported average hours and minutes inthe past week children were in a place

where a TV thatwas on could be seen. Ateach assessment from 2 to 7 years,mothers selected children’s averagehours per day of TV and video viewingin the past month from response cat-egories (None, ,1, 1–3, 4–6, 7–9, and$10 hours per day), separating week-days and weekends. We assigned nu-meric values to categories (0, 0.5, 2, 5,8, and 10, respectively) and computedweighted averages to construct anapproximately continuous measure ofTV in hours per day. This TV viewingmeasure, adapted from the NationalLongitudinal Survey of Youth,24 is linkedin a dose-response manner with child-hood overweight.25 At each assessmentfrom 4 to 7 years, parents reported thepresence of a TV in the room wherechildren slept (bedroom TV [yes or no]).

Main Outcome: Sleep Duration

At 6 months, mothers reported chil-dren’s average 24-hour sleep durationover the past month in hours andminutes in response to 3 separate

TABLE 1 Selected Characteristics of 1864 Project Viva Participants

Overall Lifetime Average TVViewing ,2 h per

Daya (N = 1507; 81%)

Lifetime Average TVViewing $2 h perDay (N = 357; 19%)

Maternal characteristicsAge at enrollment, mean (SD), y 32.1 (5.1) 32.4 (4.9) 30.7 (5.8)Prepregnancy BMI, mean (SD) 24.9 (5.5) 24.6 (5.2) 26.0 (6.2)Educational attainment, N (%)College graduate or higher 1254 (68) 1083 (71) 171 (51)

Nulliparous, N (%)Yes 896 (48) 734 (48) 162 (49)

Household income, N (%).$70 000 1064 (63) 931 (67) 133 (47)

Married or cohabitating, N (%)Yes 1710 (92) 1434 (94) 276 (83)

Child characteristics, N (%)GenderBoy 958 (51) 786 (51) 172 (52)

Race/ethnicityWhite 1215 (65) 1041 (68) 174 (52)Black 288 (16) 199 (13) 89 (27)Latino 102 (5) 76 (5) 26 (8Asian 76 (4) 66 (4) 10 (3)Other 177 (10) 142 (9) 35 (10)

Bedroom TV any time between4- and 7-y assessments

397 (28) 245 (21) 152 (54)

a Lifetime average TV viewing is calculated as the subject-specific mean TV viewing averaged over all measurement occasionsfrom infancy to midchildhood.

e1164 CESPEDES et al at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

questions about morning naps, after-noon naps, and nighttime sleep. At 1year, respondents reported averagetotal 24-hour sleep duration over thepast month in hours and minutes in-cluding morning naps, afternoon naps,and nighttime sleep in response toa single question. From 2 to 4 and at 7years, mothers selected children’s av-erage 24-hour sleep duration over thepast month (separating weekdays andweekends) from categories (,9, 9, 10,11, 12, 13, and $14 hours per day),which we combined in a weighted av-erage sleep by assigning each a valuein hours per day (8, 9, 10, 11, 12, 13, and14, respectively). At 5 and 6 years,mothers reported average nightly sleepin hours per day without separatingweekdays from weekends. We com-bined all sleep questions to form anapproximately continuous measure ofsleep duration in hours per day.

Study Covariates

Using self-administered questionnairesand interviews, we collected infor-mation about prespecified potentialconfounders including maternal age,education, prepregnancy BMI, parity,household income, the child’s race/ethnicity, and active play.

Statistical Analysis

We examined longitudinal and cross-sectional associations of TV exposureswith sleep duration. Cross-sectionalanalyses of sleep as predicted by TVviewingused separate linear regressionmodels for each visit or questionnaireadjusted, first, for age in days; a secondmodel additionally adjusted for race/ethnicity, gender, maternal education,and household income. For 4 years orlater, we additionally adjusted for bed-roomTV.Wefit separatemodels forsleeppredicted by bedroom TV, adjusting forthe covariates above and for TV viewing.Other potential confounders did notmeet inclusion criteria.

Longitudinal analyses used linearmixed effects models with randomintercepts and random linear andquadratic slopes for age (includinga quadratic term improved model fit)to account for correlations betweenrepeated measures within subjectsand allow participants with partialmissing data to contribute information.We adjusted for age and age2 (thesquare of age), then additionally forrace/ethnicity, gender, education, andincome.

For all longitudinal analyses, we sepa-rated time-varyingexposureeffects into2 distinct sources of variation. Onesource is thewithin-subject variation insleep, TV viewing, and bedroom TV,which reflects that these factors maychange over time within subjects. Thewithin-subject effect addresses thequestion: if a given child increased/decreased TV viewing, was his/her sleepduration over that period affected? Theother source is the between-subjectvariation, which reflects that, at anygiven measurement occasion, differ-ent individuals have different valuesfor sleep duration and for TV viewingand/or bedroom TV. The between-subject effect addresses the ques-tion: do children who watch more/lessTV on average from infancy to mid-childhood sleep more/less than otherchildren?

To separatewithin- andbetween-subjectsources of variation, we included

mean-centered (subtracting the subject-specific average across time) andsubject-specificmean (averagedwithin-subject over time) variables for bothTV viewing and bedroom TV as covar-iates in models.26 For bedroom TV,we subtracted the average presenceof a TV (a proportion) from thepresence or not (1 or 0) at each as-sessment point. The standard linearmixed effects model estimates ef-fects of time-varying covariates onthe basis of optimal combinationsof within-subject and between-subject variation; if within-subjectand between-subject effects are con-flicting, they should not be combinedin a standard model. For this reason,we separated within-subject effects(centered on the subject-specificmean) from between-subject (aver-aged from infancy to midchildhood)effects.

To assess potential effect modifica-tion, we included interaction terms ofgender, race/ethnicity, and age withmean-centered and subject-specificmean TV exposures. We used likeli-hood ratio tests (LRTs) to determine iffull models including interactionterms fit better than simpler modelswith fewer interactions. Where ap-propriate (LRT P , .05), we reportstratified results and interactionP values.

All analyses used SAS version 9.3 (SASInstitute, Cary, NC).

TABLE 2 Average Daily Sleep Duration, TV Viewing, and Bedroom TV by Assessment Year

Assessment Average Daily Sleep, Hours per Day Average Daily TV Viewing, Hours per Day Bedroom TV

N Mean (SD) N Mean (SD) N (%)

6 mo 1673 12.2 (2.0) 1673 0.9 (1.2) —

1 y 1227 12.8 (1.6) 1224 1.2 (1.5) —

2 y 1360 12.0 (1.3) 1266 1.4 (1.2) —

3 y 1242 11.2 (1.1) 1263 1.7 (1.1) —

4 y 1202 10.8 (1.1) 1235 1.7 (1.0) 207 (17)5 y 863 10.6 (1.0) 859 1.6 (1.0) 128 (15)6 y 955 10.3 (0.9) 941 1.5 (0.9) 143 (15)7 y 1170 9.8 (0.9) 1162 1.6 (1.0) 269 (23)

Data from 1864 participants in the Project Viva cohort.

ARTICLE

PEDIATRICS Volume 133, Number 5, May 2014 e1165 at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

RESULTS

The sample consisted of equal pro-portions of girls and boys and wasmultiethnic (35% racial/ethnic minor-ity). At enrollment, most mothers (68%)had college education and householdincomes . $70 000 (63%). Mean (SD)sleep duration increased from 6monthsto 1 year from 12.2 (2.0) to 12.8 (1.6)hours per day, remaining relativelyconstant from 2 to 5 years, then de-creasing to 9.8 (0.9) hours per day by7 years. TV viewing increased 6 monthsto 4 years from 0.9 (1.2) to 1.7 (1.0)hours per day, then declined slightly to1.6 (1.0) hours per day at 7 years. At 4, 5,and 6 years, ∼15% of children hada bedroom TV, rising to 23% at 7 years(Table 2). Ever having a bedroom TVwasmore common among racial/ethnicminority children (53%) than non-Hispanicwhite children (14%).

Cross-Sectional and LongitudinalAssociations

In cross-sectional models, greater TVviewing was associated with shortersleep duration. After multivariate ad-justment, each additional hour of TVviewing was associated with 3 fewerminutes per day (95% confidence in-terval [CI]: 22 to 8) of sleep at 6months; 2 fewer minutes per day (95%CI: 22 to 6) at 3 years; and 6 fewer

minutes/day (95% CI: 3 to 9) at 7 years(Table 3). Bedroom TV was also asso-ciated with less sleep after multivari-ate adjustment, independent of TVviewing, at 5, 6, and 7 years.

In longitudinal models, between-subject analyses revealed that eachadditional hour per day of lifetime av-erage TV viewing was associated with7 fewer minutes per day of sleep (95%CI: 4 to 10; Table 4). The effect of lifetimeTV viewing did not vary by age, gen-der, or race/ethnicity, but between-subject associations of bedroom TVwith sleep did vary by race/ethnicity

(P interaction .002). For racial/ethnicminority children, bedroom TV from4 to 7 years was associated with 32fewer minutes per day of sleep (95%CI: 18 to 46; Table 5) over the sameperiod. Additional adjustment for TVviewing did not substantially changethis between-subject effect. For non-Hispanic white children, bedroomTV was associated with 12 fewerminutes per day of sleep (95% CI: 1to 22), which attenuated after ad-justment for TV viewing (Table 5).Between-subject effects of bedroomTV did not vary by age or gender.

TABLE 3 Cross-Sectional Associations of TV Viewing (Hours per Day) and Bedroom TV With SleepDuration (Minutes per Day)

Mean Difference in Sleep Duration, Minutes per Day (95% CI)

n Age-Adjusteda n Multivariate-Adjustedb n Bedroom TV-Adjustedc

TV Viewing6 mo 1666 23 (28 to 1) 1512 23 (28 to 2) — —

1 y 1200 27 (211 to 24) 1119 26 (29 to 22) — —

2 y 1224 28 (211 to 25) 1145 26 (210 to 22) — —

3 y 1233 25 (29 to 22) 1153 22 (26 to 22) — —

4 y 1197 25 (28 to 21) 1109 24 (28 to 0) 1108 24 (28 to 0)5 y 850 27 (212 to 23) 807 27 (211 to 22) 802 26 (210 to 21)6 y 935 212 (216 to 28) 879 212 (216 to 27) 876 211 (215 to 26)7 y 1158 213 (216 to 210) 1058 26 (29 to 23) 1054 25 (29 to 22)

Bedroom TV4 y 1201 216 (225 to 26) 1113 27 (219 to 5) 1108 216 (218 to 6)5 y 858 223 (235 to 211) 815 219 (232 to 26) 802 218 (231 to 25)6 y 952 231 (241 to 221) 896 221 (232 to 210) 876 214 (226 to 23)7 y 1162 236 (244 to 229) 1062 215 (224 to 27) 1054 214 (223 to 25)

a Linear regression models fit in PROC GLM adjusted for child age in years at time of assessment.b Additional adjustments for race/ethnicity, gender, maternal education, and household income.c Additional adjustment for TV viewing or bedroom TV.

TABLE 4 Longitudinal Associations of TV Viewing (Hours per Day) With Mean Difference in Sleep Duration (Minutes per Day) by Gender

TV Viewing Mean Difference in Sleep Duration, Minutes per Day (95% CI)a

All Children Male Children Female Children P for Interaction

Age-Adjusted1864 Subjects;

9463 Observations

Multivariate-Adjusted1672 Subjects; 8782

Observations

Age-Adjusted958 Subjects;

4821 Observations

Multivariate-Adjusted847 Subjects; 4406

Observations

Age-Adjusted 906Subjects; 4642Observations

Multivariate-Adjusted 825Subjects; 4376Observations

Multivariate-Adjusted 1672Subjects; 8782Observations

Between-subject(averagedover lifetime)

211 (214 to 28) 27 (210 to 24) 212 (216 to 28) 28 (212 to 24) 211 (215 to 27) 26 (210 to 22) .72

Within-subject(centeredon subject-specific mean)

22 (24 to 0) 22 (23 to 0) 25 (27 to 22) 24 (27 to 22) 1 (22 to 3) 1 (22 to 3) .005

aModels fit combined with no interactions, as well as separately for boys and girls. Age-adjusted estimates are from linear mixed effects models with random intercepts and slopes for age andage2 fit in PROC MIXED adjusted for age and age2. To decompose within-subject and between-subject effects, we include between-subject (averaged over time) and within-subject (centered onthe subject-specific mean) covariates for TV viewing. Multivariate models include additional adjustments for race/ethnicity, maternal education, and household income.

e1166 CESPEDES et al at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

Within-subject analyses revealed thatassociationsof individual-level changesin TV viewingwith sleep duration variedby gender (P interaction .005). If anindividual boy increased TV viewing by1 hour per day over any period, thischange was accompanied by a 4-minuteper day decrease in his average sleepduration (95% CI: 2 to 7) over the sameperiod (Table 4). By contrast, individual-level changes in TV viewing among girlsdid not influence sleep (1 minute perday, 95% CI:22 to 3; Table 4). In within-subject analyses of bedroom TV, sleepwas not associated with individual-level changes in the presence of abedroom TV (1 minute per day, 95% CI:27 to 10; Table 5).

Racial/ethnic minority (versus non-Hispanic white) children had lowerpredicted sleep duration regardless oflifetime TV viewing or bedroom TV (Figs1 and 2). Overall, between-subject dif-ferences (Figs 1 and 2) had strongerassociations with sleep duration thanwithin-subject changes in TV viewing(Fig 3). For example, comparing hypo-thetical white boys with college-educated mothers from householdsearning . $70 000 year with differentdurations of TV viewing, our modelpredicted that a boy who neverwatched TV and never had a bedroomTV would sleep 19 minutes per daylonger in midchildhood than a boy whoincreased average daily TV viewingfrom 0 hours per day in infancy to 3hours per day by midchildhood; 26minutes per day longer than a boy whowatched 3 hours per day of TV everyyear; and 34 minutes per day longerthan a boy who watched 3 hours perday of TV every year and ever hada bedroom TV.

DISCUSSION

In this prospective study of 1864 chil-dren, greater TV viewing and bedroomTV were associated with decreasedsleep duration. Overall, each additionalTA

BLE5

LongitudinalAssociations

ofBedroom

TVWith

MeanDifferencein

SleepDuration(M

inutes

perDay)

byRace/Ethnicity

BedroomTV

MeanDifferenceinSleepDuration,Minutes

perDay(95%

CI)a

AllChildren

Non-HispanicWhiteChildren

Racial/EthnicMinority

Children

Pfor

Interaction

Age-Adjusted

1438

Subjects;

4173

Observations

Multivariate-

Adjusted

1312

Subjects;3886

Observations

TVView

ing

Adjusted

1310

Subjects;3840

Observations

Age-Adjusted

947

Subjects;2925

Observations

Multivariate-

Adjusted

911

Subjects;2827

Observations

TVView

ing

Adjusted

909

Subjects;2790

Observations

Age-Adjusted

489

Subjects;1244

Observations

Multivariate-

Adjusted

401

Subjects;1059

Observations

TVView

ing

Adjusted

401

Subjects;1050

Observations

Multivariate-

Adjusted

1312

Subjects;3886

Observations

Between-

subject

(averaged

4–7y)

238

(244

to231)

222

(231

to214)

220

(228

to211)

222

(232

to212)

212

(222

to21)

28(2

19to2)

237

(248

to225)

232

(246

to218)

231

(245

to216)

.002

Within-

subject

(centered

onsubject-

specific

average)

0(2

8to9)

1(2

7to10)

1(2

7to

10)

23(2

13to8)

0(2

11to

11)

0(2

11to

11)

1(2

13to16)

0(2

15to

15)

21(2

16to14)

.87

aModelsfitcom

binedwith

nointeractions,aswellasseparatelyfornon-Hispanicwhiteandracial/ethnicminority

children.Age-adjusted

estim

ates

arefrom

linearmixed

effectsmodelswith

random

interceptsandslopes

forage

andage2fitinPROC

MIXED

adjusted

forageandage2.Todecompose

within-subjectandbetween-subjecteffects,weincludebetween-subject(averaged

over

time)andwithin-subject(centeredon

thesubject-specificmean)

covariates

forbedroomTV.Bedroom

TVwas

firstasked

aboutatthe

4-year

assessment;modelsincludingbedroomTV

werere-centeredforthistim

eperiod.M

ultivariatemodelsincludeadditionaladjustm

entsforgender,m

aternaleducation,andhouseholdincome,andTV-viewingadjusted

modelsinclude

additionaladjustm

entforwithinandbetween-subjecteffectsofTV

view

ing.

ARTICLE

PEDIATRICS Volume 133, Number 5, May 2014 e1167 at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

hour per day of average lifetime TVviewing from infancy through mid-childhood was associated with 7 fewerminutes per day of sleep over the sameperiod. By contrast, individual-level

changes in TV viewing decreasedsleep only among boys. For racial/ethnic minority children, bedroom TVwas associated with 31 fewer minutesper day of sleep from 4 to 7 years in-

dependent of TV viewing, whereas fornon-Hispanic white children associa-tions disappeared after adjustment forTV viewing.

Between-subject (average lifetime TV)and within-subject (individual-levelfluctuations) analyses yielded differ-ent effect estimates for TV viewing. Forall groups, between-subject associa-tions were of greater magnitude thanwithin-subject associations. Within-subject effects are not susceptibleto confounding by factors that do notvary within a subject (eg, race/ethnicityand, arguably, home environment orsystematic reporting biases). However,between-subject effects could arisefrom differences in unmeasured fac-tors (eg, parenting skills). Our datasuggest that research on the basisof cross-sectional analyses alone mayoverestimate TV’s influence on chil-dren’s sleep. It is also possible thatwithin-subject effects could be under-estimated due to random error inreporting.

Of interest, we observed strongerwithin-subject effects of TV viewingin boys versus girls, and strongerbetween-subject effects of bedroom TVfor racial/ethnic minority versuswhite children. Differences in effectsmay be due to differences in un-derlying susceptibility to externalstimuli across population groups:other studies also indicate boys areparticularly vulnerable to electronicmedia’s influence on sleep,20 as well asto the obesogenic effects of inadequateor disturbed sleep.27 Subgroup differ-ences may also relate to differences inpatterns of TV viewing or content. Forexample, TV close to bedtime may bealerting, resulting in a phase delay insleep onset. Exposure to violent contentmay lead to later sleep onset or inter-rupted sleep.14 It is also possible thatparents differentially report behaviorssuch as sleep and TV for boys versus

FIGURE 1Non-Hispanic white boys: predicted sleep by TV and bedroom TV. Predicted sleep: longitudinal mixedeffects model (random intercepts, random slopes for age and age2) adjusted for age, age2, race/ethnicity, gender, education, income, and gender-interactions with mean-centered and subject-specificmean TV. Fixed values: boys (white or racial/ethnic minority), household income .$70 000, maternaleducation $ college. Bedroom TV (never/ever).

FIGURE 2Racial/ethnic minority boys: predicted sleep by TV and bedroom TV. Predicted sleep: longitudinal mixedeffects model (random intercepts, random slopes for age and age2) adjusted for age, age2, race/ethnicity, gender, education, income, and gender-interactions with mean-centered and subject-specificmean TV. Fixed values: boys (white or racial/ethnic minority), household income .$70 000, maternaleducation $ college. Bedroom TV (never/ever).

e1168 CESPEDES et al at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

girls, or that parents’ race/ethnicityinfluences reporting biases.

Previous studies have been mostlycross-sectional or measured sleepproblemsrather thanduration.18,19,28–33

The magnitude of association in ourstudy is similar to that observed inthe only other longitudinal study of TVviewing and child sleep duration:among 353 Finnish schoolchildren 10to 11 years old, TV viewing predictedshorter weekday sleep duration 18months later (5 fewer minutes per day,95% CI: 1 to 10; adjusted for gender,grade level, and family structure).However, in the Finnish study, thepresence of a bedroom TV was notassociated with shorter sleep though itpredicted later bedtimes in boys.20 Ourstudy extends a sparse literature bydescribing longitudinal associations of

TV viewing and bedroom TV with sleepduration over a longer follow-up periodin a larger and more diverse sample.Further, ours is the first study to ex-amine this important period from in-fancy to midchildhood when habits arebeing formed that are likely to persistinto later childhood.34

Consistent with our finding that bed-room TV is associated with shortersleepduration, cross-sectionalNationalSleep Foundation data reveal thatchildren with a bedroom TV (versuswithout) slept 9 fewer minutes perday (95% CI: 1 to 19).21 In our study,between-subject associations withbedroom TV were particularly strongamong racial/ethnic minorities. Thisbetween-subject difference may par-tially reflect unmeasured confounders,differential reporting by race/ethnicity

or unmeasured TV viewing (the pres-ence of a bedroom TV may make itmore difficult for parents to accuratelyreport children’s viewing and/or sleep,particularly if children fall asleepwatching). However, the strength ofthe observed association (31 minutesless sleep for bedroom TV) may in-dicate an adverse influence of bedroomTV on children’s sleep independentof increased TV viewing; bedroom TVmay increase screen illumination andmental/emotional arousal near bed-time, negatively influencing sleep dura-tion.13,35 Racial/ethnic minority childrenin our study watched more TV andslept less than white non-Hispanicchildren; others have noted similardisparities by race/ethnicity in TVviewing, bedroom TV,10,36 and sleepduration.37,38

Our study makes a unique contributionto the literature: to our knowledge, noprevious study of TV and sleep durationincludes a cohort of children followedfrom infancy to midchildhood. Further,no previous study has separated time-varying TV exposures into within- andbetween-subject sources of variationto address the different impacts onsleep duration of lifetime average TVand individual-level changes in TV. Thisstudy also had several limitations.Measures of TV and sleep were fromparent-report, which may result inmisclassification. Because childrensleep less as they age,39 reverse cau-sation (less sleep leading to greaterTV) is a possibility. However, we con-trolled for age-related declines in sleepby adjusting for age and includingrandom slopes for age and age2 inlongitudinal models. Finally, althoughthere are many forms of screen media(eg, mobile phones), TV is still thelargest single contributor to children’stotal screen time.10 In this study, wefirst measured total screen exposureat 7 years and found that cross-sectional associations were similar to

FIGURE 3Predicted sleep by within-subject change in TV viewing among non-Hispanic white boys. Predicted sleepresults from longitudinal mixed effects model with random intercepts and random slopes for age andage2, adjusted for age, age2, race/ethnicity, gender, education, household income, and interactions ofgender with both mean-centered and subject-specific mean TV viewing. Bedroom TV is not included inthe model.

ARTICLE

PEDIATRICS Volume 133, Number 5, May 2014 e1169 at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

those observed with TV viewing alone,suggesting that longitudinal associa-tions with total screen time would alsobe similar.

Finally, bias due tononrandomdropout ispossible: motherswhose children’s sleepand TV relationship was different mightbe less likely to return questionnaires.This bias would attenuate our estimatesover time: racial/ethnic minority (vswhite) participants had a higher proba-bility of missing data at later assessmentpoints, and racial/ethnic minority chil-dren watched more TV and slept less.

CONCLUSIONS

Our study supports a negative influenceof TV viewing and bedroom TV onchildren’s sleep. Although a compari-son of within- and between-subjectanalyses suggests that associationspreviously reported by using cross-sectional data alone may have beeninflated, we demonstrated that sub-groups of young children, in particular,boys and racial/ethnic minorities, maybe more vulnerable to TV’s effects onsleep. TV viewing and the presence ofa bedroom TV track over time40,41; thus,

modest decreases in sleep durationcould form lasting habits leading tosubstantial sleep deficits as childrenage. Given the associations betweengreater TV viewing and shorter sleepsuggested by this study and the strongevidence that greater TV viewing andshorter sleep are associated with pooroutcomes, screen time interventionshave the potential to improve sleep.

ACKNOWLEDGMENTWe thank the Project Viva participantsand staff.

REFERENCES

1. Curcio G, Ferrara M, De Gennaro L. Sleeploss, learning capacity and academic per-formance. Sleep Med Rev. 2006;10(5):323–337

2. Drescher AA, Goodwin JL, Silva GE, Quan SF.Caffeine and screen time in adolescence:associations with short sleep and obesity.J Clin Sleep Med. 2011;7(4):337–342

3. Koulouglioti C, Cole R, Kitzman H. In-adequate sleep and unintentional injuriesin young children. Public Health Nurs. 2008;25(2):106–114

4. Landhuis CE, Poulton R, Welch D, Hancox RJ.Childhood sleep time and long-term riskfor obesity: a 32-year prospective birthcohort study. Pediatrics. 2008;122(5):955–960

5. Lin JD, Tung HJ, Hsieh YH, Lin FG. Interactiveeffects of delayed bedtime and family-associated factors on depression in ele-mentary school children. Res Dev Disabil.2011;32(6):2036–2044

6. Patel SR, Hu FB. Short sleep duration andweight gain: a systematic review. Obesity(Silver Spring). 2008;16(3):643–653

7. Rutters F, Gerver WJ, Nieuwenhuizen AG,Verhoef SP, Westerterp-Plantenga MS.Sleep duration and body-weight de-velopment during puberty in a Dutch chil-dren cohort. Int J Obes (Lond). 2010;34(10):1508–1514

8. Taveras EM, Rifas-Shiman SL, Oken E,Gunderson EP, Gillman MW. Short sleepduration in infancy and risk of childhoodoverweight. Arch Pediatr Adolesc Med.2008;162(4):305–311

9. National Sleep Foundation. Sleep in Amer-ica poll. Available at: www.sleepfoundation.org/sites/default/files/FINAL%20SOF%202004.

pdf Published 2004. Accessed February 28,2014

10. Roberts D, Foehr U, Rideout V. GenerationM: Media in the Lives of 8–18 Year-olds.Report #7251. Menlo Park, CA: Kaiser Fam-ily Foundation; 2005

11. Adam EK, Snell EK, Pendry P. Sleep timingand quantity in ecological and family con-text: a nationally representative time-diarystudy. J Fam Psychol. 2007;21(1):4–19

12. Alexandru G, Michikazu S, Shimako H, et al.Epidemiological aspects of self-reportedsleep onset latency in Japanese juniorhigh school children. J Sleep Res. 2006;15(3):266–275

13. Cain N, Gradisar M. Electronic media useand sleep in school-aged children andadolescents: A review. Sleep Med. 2010;11(8):735–742

14. Garrison MM, Liekweg K, Christakis DA.Media use and child sleep: the impact ofcontent, timing, and environment. Pediat-rics. 2011;128(1):29–35

15. Van den Bulck J. The effects of media onsleep. Adolesc Med State Art Rev. 2010;21(3):418–429, vii [vii.]

16. Garmy P, Nyberg P, Jakobsson U. Sleep andtelevision and computer habits of Swedishschool-Age children. J Sch Nurs. 2012;28(6):469–476

17. Hense S, Barba G, Pohlabeln H, et al. Fac-tors that influence weekday sleep durationin European children. Sleep. 2011;34(5):633–639

18. Li S, Jin X, Wu S, Jiang F, Yan C, Shen X. Theimpact of media use on sleep patterns andsleep disorders among school-aged chil-dren in China. Sleep. 2007;30(3):361–367

19. Owens J, Maxim R, McGuinn M, Nobile C,Msall M, Alario A. Television-viewing habitsand sleep disturbance in school children.Pediatrics. 1999;104(3). Available at: www.pediatrics.org/cgi/content/full/104/3/e27

20. Nuutinen T, Ray C, Roos E. Do computeruse, TV viewing, and the presence of themedia in the bedroom predict school-aged children’s sleep habits in a longi-tudinal study? BMC Public Health. 2013;13:684

21. Calamaro CJ, Yang K, Ratcliffe S, ChasensER. Wired at a young age: the effect ofcaffeine and technology on sleep durationand body mass index in school-aged chil-dren. J Pediatr Health Care. 2012;26(4):276–282

22. Bernier A, Beauchamp MH, Bouvette-TurcotAA, Carlson SM, Carrier J. Sleep and cog-nition in preschool years: specific links toexecutive functioning. Child Dev. 2013;84(5):1542–1553

23. Gillman MW, Rich-Edwards JW, Rifas-ShimanSL, Lieberman ES, Kleinman KP, Lipshultz SE.Maternal age and other predictors of new-born blood pressure. J Pediatr. 2004;144(2):240–245

24. Baker P, Keck C, Mott F, Quinlan S. NLYSChild Handbook, Revised Edition: A Guide tothe 1986–1990 National Longitudinal Sur-vey of Youth Child Data. Columbus, OH:Center for Human Resource Research OhioState University; 1993

25. Gortmaker SL, Must A, Sobol AM, PetersonK, Colditz GA, Dietz WH. Television viewingas a cause of increasing obesity amongchildren in the United States, 1986-1990.Arch Pediatr Adolesc Med. 1996;150(4):356–362

e1170 CESPEDES et al at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

26. Fitzmaurice GM, Laird NM, Ware JH. AppliedLongitudinal Analysis. Hoboken, NJ: Wiley;2011

27. Tatone-Tokuda F, Dubois L, Ramsay T, et al.Sex differences in the association betweensleep duration, diet and body mass index:a birth cohort study. J Sleep Res. 2012;21(4):448–460

28. Paavonen EJ, Pennonen M, Roine M, ValkonenS, Lahikainen AR. TV exposure associated withsleep disturbances in 5- to 6-year-old chil-dren. J Sleep Res. 2006;15(2):154–161

29. Thompson DA, Christakis DA. The associa-tion between television viewing and irreg-ular sleep schedules among children lessthan 3 years of age. Pediatrics. 2005;116(4):851–856

30. Van den Bulck J. Television viewing, com-puter game playing, and Internet use andself-reported time to bed and time out ofbed in secondary-school children. Sleep.2004;27(1):101–104

31. Wells JC, Hallal PC, Reichert FF, MenezesAM, Araújo CL, Victora CG. Sleep patternsand television viewing in relation to obesityand blood pressure: evidence from an

adolescent Brazilian birth cohort. Int JObes (Lond). 2008;32(7):1042–1049

32. Garaulet M, Ortega FB, Ruiz JR, et al. Shortsleep duration is associated with increasedobesity markers in European adolescents:effect of physical activity and dietary hab-its. The HELENA study. Int J Obes (Lond).2011;35(10):1308–1317

33. Johnson JG, Cohen P, Kasen S, First MB,Brook JS. Association between televisionviewing and sleep problems during ado-lescence and early adulthood. Arch PediatrAdolesc Med. 2004;158(6):562–568

34. Certain LK, Kahn RS. Prevalence, correlates,and trajectory of television viewing amonginfants and toddlers. Pediatrics. 2002;109(4):634–642

35. Rüger M, St Hilaire MA, Brainard GC, et al.Human phase response curve to a single6.5 h pulse of short-wavelength light. J Physiol.2013;591(pt 1):353–363

36. Dennison BA, Erb TA, Jenkins PL. Televisionviewing and television in bedroom associ-ated with overweight risk among low-income preschool children. Pediatrics.2002;109(6):1028–1035

37. Taveras EM, Gillman MW, Kleinman K, Rich-Edwards JW, Rifas-Shiman SL. Racial/ethnicdifferences in early-life risk factors forchildhood obesity. Pediatrics. 2010;125(4):686–695

38. Spilsbury JC, Storfer-Isser A, Drotar D, et al.Sleep behavior in an urban US sample ofschool-aged children. Arch Pediatr AdolescMed. 2004;158(10):988–994

39. Olds T, Blunden S, Petkov J, Forchino F.The relationships between sex, age,geography and time in bed in adoles-cents: a meta-analysis of data from 23countries. Sleep Med Rev. 2010;14(6):371–378

40. Hesketh K, Wake M, Graham M, Waters E.Stability of television viewing and elec-tronic game/computer use in a prospectivecohort study of Australian children: re-lationship with body mass index. Int JBehav Nutr Phys Act. 2007;4:60

41. Saelens BE, Sallis JF, Nader PR, Broyles SL,Berry CC, Taras HL. Home environmentalinfluences on children’s television watchingfrom early to middle childhood. J DevBehav Pediatr. 2002;23(3):127–132

(Continued from first page)

FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

FUNDING: This study was funded by National Institutes of Health (NIH) grants NCI 1U54CA15562601 and R37 HD 034568. Funded by the National Institutes of Health(NIH).

POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

ARTICLE

PEDIATRICS Volume 133, Number 5, May 2014 e1171 at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from

DOI: 10.1542/peds.2013-3998; originally published online April 14, 2014; 2014;133;e1163Pediatrics

Rifas-Shiman, Susan Redline and Elsie M. TaverasElizabeth M. Cespedes, Matthew W. Gillman, Ken Kleinman, Sheryl L.

Mid-ChildhoodTelevision Viewing, Bedroom Television, and Sleep Duration From Infancy to

  

ServicesUpdated Information &

htmlhttp://pediatrics.aappublications.org/content/133/5/e1163.full.including high resolution figures, can be found at:

References

html#ref-list-1http://pediatrics.aappublications.org/content/133/5/e1163.full.at:This article cites 37 articles, 9 of which can be accessed free

Subspecialty Collections

icine_subhttp://pediatrics.aappublications.org/cgi/collection/sleep_medSleep Medicine

e_subhttp://pediatrics.aappublications.org/cgi/collection/screen_timScreen Time

http://pediatrics.aappublications.org/cgi/collection/media_subMediathe following collection(s):This article, along with others on similar topics, appears in

Permissions & Licensing

tmlhttp://pediatrics.aappublications.org/site/misc/Permissions.xhtables) or in its entirety can be found online at: Information about reproducing this article in parts (figures,

Reprints http://pediatrics.aappublications.org/site/misc/reprints.xhtml

Information about ordering reprints can be found online:

rights reserved. Print ISSN: 0031-4005. Online ISSN: 1098-4275.Grove Village, Illinois, 60007. Copyright © 2014 by the American Academy of Pediatrics. All and trademarked by the American Academy of Pediatrics, 141 Northwest Point Boulevard, Elkpublication, it has been published continuously since 1948. PEDIATRICS is owned, published, PEDIATRICS is the official journal of the American Academy of Pediatrics. A monthly

at Tufts Univ on September 25, 2014pediatrics.aappublications.orgDownloaded from