journal pediatrics 2002

DOI: 10.1542/peds.109.4.634 2002;109;634Pediatrics

Laura K. Certain and Robert S. KahnToddlers

Prevalence, Correlates, and Trajectory of Television Viewing Among Infants and

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Prevalence, Correlates, and Trajectory of Television ViewingAmong Infants and Toddlers

Laura K. Certain, BA, and Robert S. Kahn, MD, MPH

ABSTRACT. Objectives. Recognizing the negative ef-fects of television on children, the American Academy ofPediatrics (AAP) recommends that children 2 years andolder watch 2 hours per day at age2 were more likely to watch >2 hours per day at age 6(odds ratio: 2.7; 95% confidence interval: 1.83.9), control-ling for maternal education, race, marital status and em-ployment, household income, and birth order.

Conclusions. A substantial number of children beginwatching television at an earlier age and in greateramounts than the AAP recommends. Furthermore, theseearly viewing patterns persist into childhood. Preventiveintervention research on television viewing should con-sider targeting infants and toddlers and their families.Pediatrics 2002;109:634642; television, infant, children,longitudinal survey, socioeconomic factors.

ABBREVIATIONS. AAP, American Academy of Pediatrics; NLSY,National Longitudinal Survey of Youth; HOME, Home Observa-tion for Measurement of the Environment; OR, odds ratio; CI,confidence interval.

The substantial amount of television watched byschool-aged children16 and the associated ad-verse effects726 are increasingly well docu-mented. Although a few researchers highlight thebenefits of television,1214 the majority link increasedtelevision viewing with higher rates of violence,1517obesity,1823 and poor school performance.2426Moreover, recent randomized, controlled trials haveshown that decreasing the amount of televisionviewed leads to relative decreases in aggression15and body fat.19,23 Recognizing the adverse healtheffects of television, the American Academy of Pedi-atrics (AAP) recommends that children 2 years andolder limit their time with entertainment media (tele-vision, video games, the Internet) to 2 hours per dayand that children younger than 2 watch no televi-sion.27,28 Little is known, however, about the amountof television viewed by infants and toddlers. Thevast majority of research has remained focused ontelevision viewing in older children.1,29

Delineating patterns of early childhood televisionviewing may be important for several reasons. First,it may provide insight into the earliest behavioralantecedents of obesity and other health outcomeslinked to excessive television viewing. Second, a de-scription of social differences in early childhood tele-vision viewing may illuminate the mechanisms bywhich social disparities in these health outcomesemerge. If school-age television habits begin to de-velop early in life, then the roots of social disparitiesin obesity and violence may be explained in part bythese early experiences. Finally, if indeed very youngchildren watch substantial amounts of television,then the findings raise important questions about theconstraints that parents may face in choosing alter-native activities for their children.

The present study had 2 objectives. First, we de-scribed the prevalence and correlates of televisionviewing that exceeded the AAP guidelines for anational sample of 0- to 35-month-olds. Second, weexamined the trajectory of a childs viewing overtime. Data came from the National Longitudinal Sur-vey of Youth (NLSY).

METHODS

Sample and DesignThe NLSY began in 1979 as a national sample of young men

and women aged 14 to 21, oversampled for blacks, Hispanics, andlow-income whites. This original cohort has been surveyed almostevery year since 1979, with 84% of the original respondents still inthe sample as of 1998.30 Data on children of the women in thecohort have been collected every other year since 1986. This study

From the Division of General and Community Pediatrics, Childrens Hos-pital Medical Center, Cincinnati, Ohio.Received for publication Jun 14, 2001; accepted Oct 15, 2001.Reprint requests to (R.S.K.) Division of General and Community Pediatrics,TCHRF 6549, Childrens Hospital Medical Center, 3333 Burnet Ave, Cin-cinnati, OH 45229. E-mail: [email protected] (ISSN 0031 4005). Copyright 2002 by the American Acad-emy of Pediatrics.

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focused on the 5 child surveys from 1990 to 1998 that includedquestions about child television viewing.

Cross-Sectional DesignFor determining the prevalence and correlates of television

viewing that exceeded the AAP guidelines, a cross-sectional de-sign was used. Our sample for this objective (the Cross-SectionalSample) consisted of children who were 0 to 35 months of age inany survey year from 1990 to 1998 (N 3556). Because televisionviewing is strongly correlated with age, this sample was dividedinto 3 subgroups: 0- to 11-month-olds (Youngest), 12- to 23-month-olds (Middle), and 24- to 35-month-olds (Oldest). Sib-ling pairs existed within these subgroups, so we randomly chose1 child for each mother. Five percent of children were missingoutcome data. Children who were excluded because of missingdata did not differ significantly from those who were includedwith respect to maternal education level or survey year. The finalsample sizes were 1084 for the Youngest, 1254 for the Middle, and1247 for the Oldest. These are not mutually exclusive samples; forexample, a child who was 5 months old at the 1992 survey and 30months old at the 1994 survey was included in both the Youngestsample and the Oldest sample.

Longitudinal DesignFor examining the trajectory of a childs viewing over time, a

longitudinal design was used. The Longitudinal Sample was asubset of the Cross-Sectional Sample. Children who were 0 to 23months of age in 1990 or 1992 were followed for 6 years (until 1996or 1998); 5% were lost to follow-up. As above, this sample wasdivided by age into subgroups: children 0 to 11 months of age atbaseline (n 554) and children 12 to 23 months of age at baseline(n 666).

Outcome MeasureFor both of the designs, the outcome variable was hours of

television per weekday, assessed by maternal response to thefollowing question: How much time would you say your childspends watching television on a typical weekday (either in yourhome or elsewhere)? A separate question with parallel wordingassessed television on a typical weekend day. Mothers reportedthe hours of viewing in whole numbers; watching 1 hour oftelevision per day was considered equivalent to watching notelevision. Following the AAP guidelines, we dichotomized theoutcome variable as 0 versus 1 hour per day for children 0 to 23months of age and 0 to 2 versus 3 hours per day for children 24months and older. The Spearman correlation between weekdayand weekend viewing was 0.7 for each age group, and theaverage amount of television on a typical weekend day was thesame as on a typical weekday for all ages. Therefore, only theresults for weekday viewing are shown. There was no questionspecific to video viewing, so mothers may have included videos intheir estimate of television viewing.

Independent VariablesBecause of the limited information available on television view-

ing among infants and toddlers, we chose predictors based onother studies of parenting style and home environment.3134 Wecalculated the average annual household income across the 5surveys and divided the resulting value into quintiles. Childrenwhose household income was missing in 3 or more of the surveyyears (11%) were given a missing value. Mothers who reportedworking, going to school, or serving in the active armed forceswere considered to be employed out of the home; women whowere on leave from their jobs, unemployed, out of the labor force,or keeping house were considered in the home; all otherswere considered unknown. For the paternal variables, we usedthe data for the person whom the mother identified as both amember of her household and a spouse or partner. The quality ofthe home environment was determined by the Short Form of theHome Observation for Measurement of the Environment (HOME-SF).35 Both the total standardized score and the 2 standardizedsubscale scores (cognitive stimulation and emotional support)were analyzed as continuous variables.

Additional VariablesData on child care, maternal depression, and neighborhood

quality were available only in selected years; therefore, thesevariables were analyzed separate from the main analysis.

Child CareBecause child care information was collected retrospectively,

complete data were available for children in 1990 and 1992 only.Mothers were asked about any regular child care during theirchilds first, second, and third years of life. We classified child careresponses as none (besides maternal), in a (private) home, andin a center/preschool.

Maternal Depressive SymptomsMaternal depressive symptoms were measured only in 1992

and 1994. In 1992, the NLSY included the full Center for Epide-miologic Studies Depression Scale, a 20-item self-report instru-ment.3638 In 1994, the survey included only 7 questions from theCenter for Epidemiologic Studies Depression Scale. The scores foreach year were divided into quintiles for analysis. Within the 1992data, the Spearman correlation between the full 20 questions andthe 7 questions was 0.9.

Neighborhood QualityNeighborhood quality was assessed in 2 ways, beginning in

1992. First, mothers were asked the following question: Howwould you rate your neighborhood as a place to raise children?Would you say it is excellent, very good, good, fair, or poor? Inaddition, mothers rated the following problems in their neighbor-hood: lack of respect for rules and laws; crime and violence;abandoned or run-down buildings; not enough police protection;not enough public transportation; too many unsupervised chil-dren; people keep to themselves, dont care about the neighbor-hood; and lots of people who cant find jobs. Mothers rated theseproblems on a 3-point scale, and the answers were summed into acomposite score.

Analysis

Cross-SectionalThe 2 test and t test were used in the cross-sectional analysis to

examine the associations between the independent variables andtelevision viewing. Any predictors that were significantly (P .05) correlated with television viewing in the bivariate analyseswere included in multivariate logistic regression models that ex-amined the odds of viewing 1 hour/d for the Youngest andMiddle groups and 3 hours/d for the Oldest group. In thelongitudinal analyses, a logistic regression model was used toexamine the odds of watching 3 hours of television per day atage 6. The predictor of interest was television viewing as an infantor toddler, but models also controlled for maternal education,marital status, employment, race, household income, child ageand birth order.

Weighting and Design EffectsAs recommended when combining data across survey years,30

we did not use sample weights to make our results nationallyrepresentative of children born to mothers who were 14 to 22 yearsof age in 1979.30 However, an exploratory comparison of weightedresults to our unweighted results for any given individual yearshowed no difference in the amount of television viewed at eachage.

The data were collected through a multistage stratified clusterrandom sampling procedure, and consequently the standard er-rors may be underestimated. The information required to adjustfor such design effects is not in the public use data; however,respondent movement out of their original sampling units hasreduced such design effects.30 We present significance at the 95%confidence level, but a conservative approach is to focus on find-ings significant at P .01.39 All analyses were conducted usingSAS 8.1 for Windows 95 (SAS Institute, Inc, Cary, NC).

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RESULTS

Cross-Sectional ResultsApproximately 25% of the mothers were black,

20% were Hispanic, 75% were married, 10% had notfinished high school, and 20% to 25% had finished 4years of college (Table 1). The median householdincome was $41 000/y.

Seventeen percent of the Youngest sample werereported to exceed AAP television viewing guide-lines, watching at least 1 hour of television on atypical weekday (Fig 1). Among the Middle sample,

48% were reported to watch at least 1 hour per day,and 22% were reported to watch 3 or more hours perday. In the Oldest sample, 41% were reported towatch 3 or more hours per day, and 16% were re-ported to watch 5 or more hours per day.

Bivariate ResultsIn bivariate analyses, the most consistent corre-

lates of increased television viewing were black ma-ternal race, lower maternal education, and having anunmarried mother (Table 2). For example, 51% of

TABLE 1. Description of the Cross-Sectional Sample*

Characteristic Youngest Middle Oldest

N % N % N %

Total sample 1084 100.0 1254 100.0 1247 100.0Gender

Female 537 49.5 640 51.0 604 48.4Male 547 50.5 614 49.0 643 51.6

Maternal raceBlack 283 26.1 310 24.7 333 26.7Hispanic 223 20.6 236 18.8 252 20.2White/other 578 53.3 708 56.5 662 53.1

Maternal education12 y 112 10.4 137 11.0 137 11.012 y 423 39.2 491 39.3 541 43.51315 y 272 25.2 310 24.8 299 24.116 y or more 273 25.3 312 25.0 266 21.4

Household income$22 000/y 181 18.7 220 19.7 217 19.9$22 00035 000/y 195 20.1 205 18.4 231 21.1$35 00047 000/y 197 20.3 228 20.4 242 22.1$47 00066 000/y 196 20.2 228 20.4 216 19.8$66 000/y 201 20.7 236 21.1 187 17.1

Maternal age at delivery2225 33 3.0 72 5.7 158 12.72630 453 41.8 624 49.8 646 51.83135 494 45.6 499 39.8 401 32.23640 104 9.6 59 4.7 42 3.4

Maternal employmentOut of the home 499 46.6 710 57.0 698 56.8In the home 572 53.4 535 43.0 530 43.2

Marital statusFormerly married 123 11.4 146 11.6 163 13.1Never married 151 13.9 156 12.4 166 13.3Married 809 74.7 952 75.9 917 73.6

Birth order of childFirst 292 26.9 368 29.3 377 30.2Second 377 35.8 449 35.8 452 36.2Third or higher 415 38.3 437 34.8 418 33.5

Number of children in house1 276 26.6 341 27.8 294 24.023 616 59.5 728 59.4 767 62.74 or more 144 13.9 157 12.8 162 13.2

Paternal education12 y 100 9.4 116 9.4 110 9.012 y 316 29.6 366 29.8 389 31.71315 y 202 18.9 213 17.3 214 17.416 y or more 256 24.0 307 25.0 264 21.5No father figure in house 193 18.1 228 18.5 250 20.4

Paternal employmentEmployed 833 78.7 960 78.1 938 76.5Unemployed 33 3.1 41 3.3 39 3.2No father figure in house 192 18.1 228 18.6 249 20.3

Survey year1990 324 29.9 375 29.9 339 27.21992 267 24.6 319 25.4 317 25.41994 200 18.5 258 20.6 244 19.61996 167 15.4 166 13.2 207 16.61998 126 11.6 136 10.8 140 11.2

* Number of women responding to individual questions may vary.

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mothers who had not graduated from high schoolreported that their 2-year-olds watched at least 3hours of television on a typical weekday, comparedwith only 27% of college graduates (P .0001). Al-though maternal education was associated with tele-vision viewing, paternal education was not.

Lower HOME scores were associated with in-creased television viewing in some children (data notshown). In the Oldest group, the average HOMEscore for children who exceeded AAP televisionviewing guidelines was a third of a standard devia-tion worse than the average score for children whowere within the guidelines (95.0 vs 99.4; P .0001);in the Youngest group, the average score for thosewho exceeded the guidelines was a quarter standarddeviation better (100.6 vs 97.0; P .007). There wereno differences in HOME scores for the Middle group(97.0 vs 97.5; P .6).

Of the variables that were available only in se-lected years, none were consistent correlates of tele-vision viewing. Child care was significantly associ-ated with television viewing for the Oldest sampleonly; children in center-based child care were theleast likely to watch more than the AAP recommends(P .02). Similarly, increased maternal depressivesymptoms were significantly associated with in-creased television viewing for the Oldest sampleonly (P .02). Poor neighborhood quality was sig-nificantly associated with increased television view-ing in the Youngest and Oldest samples (P .05 forboth neighborhood assessments).

Multivariate ResultsIn logistic regression models, maternal race, ma-

ternal education, and child age were consistent pre-dictors of high television viewing (Table 3). A blackmother was twice as likely as a white/other motherto report that her 2-year-old watched at least 3 hoursof television per day (odds ratio [OR]: 2.0; 95% con-fidence interval [CI]: 1.42.8). A woman who had notgraduated from high school was almost 4 times aslikely as a woman who had graduated from collegeto report that her 0- to 11-month-old watched at least1 hour of television per day (OR: 3.7; 95% CI: 1.77.7).Survey year was also a significant predictor of child

television viewing, particularly for the Youngestsample. Infants in 1998 were more likely to watchtelevision than infants in preceding years. TheHOME score was significant for the Youngest chil-dren only; higher total and subscale scores wereassociated with increased viewing.

In separate regression models for the variables thatwere available only in selected years, child care andneighborhood retained significance but maternal de-pression did not. Compared with children in center-based child care, 2-year-olds with no formal childcare were more likely to watch more than the AAPrecommends (OR: 1.6; 95% CI: 1.02.6; P .04), aswere 2-year-olds who were cared for in a privatehome (OR: 1.6; 95% CI: 1.02.6; P .05). Comparedwith a mother who rated her neighborhood as ex-cellent for raising children, a mother in a poorneighborhood was more likely to report that herinfant watched at least 1 hour of television per day(OR: 3.6; 95% CI: 1.58.3; P .003), adjusting forcovariates. Using the composite scale, infants in theworst quartile of neighborhoods were twice as likelyas infants in the top quartile to watch at least 1 hourper day (OR: 2.2; 95% CI: 1.14.5; P .03).

To determine whether neighborhood quality con-founded the relationship between television viewingand race or education, we looked for changes in the-coefficients for race and education on enteringneighborhood quality in the model. Including neigh-borhood quality did not substantially change thecoefficients of either, suggesting that perceivedneighborhood quality was not a confounder of theseassociations.

Longitudinal ResultsThe trajectory of television viewing with age is

shown in Fig 2. Daily television viewing increased byroughly 1 hour per year during the first 3 years oflife, then leveled off. Differences between children ofless-educated mothers and children of well-educatedmothers were significant at an early age and becamemore pronounced as the children got older. By age 4,children of less-educated mothers were watching anadditional 2 hours of television per day, on average,a nearly 2-fold difference.

Fig 1. Reported hours of televisionviewed on a typical weekday. Percentagesmay not sum to 100 because of rounding.


Given the varying trajectories for different sub-groups, we investigated whether early factors, par-ticularly early television viewing, were associatedwith television viewing at school age (age 6). Wefound that television viewing at 24 to 35 monthspredicted school-age television viewing, but televi-sion viewing at 0 to 11 months did not, adjusting formaternal education, race, income, marital status, andemployment. Children who watched at least 3 hoursof television per day at age 2 were almost 3 times aslikely as other children to watch at least 3 hours perday at age 6 (OR: 2.7; 95% CI: 1.83.9; P .0001).

Maternal education was also a significant predictorof television viewing at age 6, controlling for viewingat age 2. Children of high school graduates weremore than twice as likely as children of college grad-uates to watch more television than the AAP recom-mends (3 hours per day) at age 6 (OR: 2.3; 95% CI:1.43.9; P .002).

DISCUSSIONThis study presents the first national data on the

prevalence, correlates, and trajectory of televisionviewing habits for infants and toddlers. Seventeen

TABLE 2. Percentage of the Youngest, Middle, and Oldest Children Reported to Exceed the AAPGuidelines for Television Viewing (1 Hour, 1 Hour, 3 Hours, Respectively)


N % N % N %

Total sample 189 17.4 603 48.1 516 41.4Gender

Female 93 17.3 298 46.6 248 41.1Male 96 17.6 305 49.7 268 41.7

Maternal raceBlack 68 24.0 184 59.4 189 56.8Hispanic 32 14.4* 108 45.8* 109 43.3*White/other 89 15.4 311 43.9 218 32.9

Maternal education12 y 32 28.6 74 54.0 70 51.112 y 77 18.2 243 49.5 247 45.71315 y 43 15.8* 153 49.4 127 42.5*16 y or more 37 13.6 131 42.0 71 26.7

Household income$22 000/y 35 19.3 123 55.9 115 53.0$2235 000/y 39 20.0 97 47.3 114 49.4$3547 000/y 34 17.3 98 43.0 98 40.5*$4766 000/y 37 18.9 109 47.8 78 36.1$66 000/y 21 10.5 109 46.2 54 28.9

Maternal age at delivery2225 10 30.3 31 43.1 75 47.52630 67 14.8 298 47.8 262 40.63135 93 18.8 245 49.1 165 41.23640 19 18.3 29 49.2 14 33.3

Maternal employmentOut of home 90 18.0 323 45.5 275 39.4In home 96 16.8 276 51.6 234 44.2

Marital statusNever married 33 21.9 100 64.1 89 53.6Formerly married 28 22.8 78 53.4* 84 51.5*Married 128 15.8 425 44.6 343 37.4

Birth order of childFirst 50 17.1 190 51.6 139 36.9Second 53 14.1 208 46.3 187 41.4Third or higher 86 20.7 205 46.9 190 45.5

Number of children in house1 46 16.7 178 52.2 111 37.823 110 17.9 332 45.6 320 41.74 or more 26 18.1 80 51.0 74 45.7

Paternal education12 y 19 19.0 49 42.2 43 39.112 y 52 16.5 158 43.2 163 41.91315 y 32 15.8 105 49.3 87 40.716 y or more 34 13.3 144 46.9 84 31.8

Paternal employmentEmployed 132 15.9 437 45.5 361 38.5Unemployed 4 12.1 21 51.2 17 43.6

Survey year1990 47 14.5 152 40.5 132 38.91992 41 15.4 158 49.5 128 40.41994 34 17.0* 136 52.7 106 43.41996 30 18.0 86 51.8 95 45.91998 37 29.4 71 52.2 55 39.3

* P .01. P .05; 2 test for any difference between categories.


percent of 0- to 11-month-olds, 48% of 12- to 23-month-olds, and 41% of 24- to 35-month-olds werereported by their mothers to watch more televisionthan the AAP recommends. Less-educated mothersreported that their children viewed more television;29% of mothers with 12 years of education re-ported that their infants watched television, com-

pared with only 14% of college graduates. Thesedifferences, apparent at an early age, increased as thechildren grew older. Both early television viewingand maternal education had significant, independenteffects on television viewing at school age.

Children in our study were reported to watchslightly more than those in a national cross-sectional

TABLE 3. Odds of Exceeding the AAP Guidelines for the Youngest, Middle, and Oldest (N 939,N 1091, and N 1114, Respectively)


OR 95% CI OR 95% CI OR 95% CI

Age (mo) 1.16* 1.101.24 1.16* 1.121.20 1.04 1.001.08Maternal race

Black 1.60 1.002.56 1.88* 1.302.71 2.01* 1.442.81Hispanic 0.75 0.441.28 1.14 0.801.63 1.38 0.981.93White/other 1.00 1.00 1.00

Maternal education12 y 3.66* 1.747.70 1.84 1.093.11 2.18* 1.283.7112 y 1.45 0.842.51 1.49 1.032.16 2.00* 1.362.921315 y 1.28 0.712.29 1.41 0.962.07 1.69 1.122.5516 y or more 1.00 1.00 1.00

Household income$22 000/y 0.91 0.431.89 0.87 0.521.45 1.45 0.872.42$2235 000/y 1.28 0.652.51 0.84 0.531.34 1.55 0.962.48$3547 000/y 1.34 0.692.61 0.84 0.551.29 1.19 0.751.87$4766 000/y 1.65 0.873.14 0.95 0.621.44 1.22 0.771.93$66 000/y 1.00 1.00 1.00

Maternal employmentIn the home 1.18 0.791.74 1.35 1.031.77 1.11 0.861.44Out of the home 1.00 1.00 1.00

Marital statusFormerly married 1.58 0.882.84 1.42 0.902.22 1.02 0.691.52Never married 1.31 0.732.34 1.77 1.122.81 0.97 0.631.49Married 1.00 1.00 1.00

Birth order of childThird or higher 0.79 0.481.30 0.60* 0.420.85 0.84 0.601.19Second 0.67 0.411.09 0.74 0.541.03 0.99 0.721.37First 1.00 1.00 1.00

Survey year1990 0.26* 0.150.47 0.56 0.350.90 0.76 0.481.201992 0.37* 0.210.65 0.86 0.531.39 0.85 0.541.351994 0.38* 0.210.70 0.96 0.591.56 1.03 0.641.651996 0.50 0.270.92 1.04 0.611.76 1.24 0.772.021998 1.00 1.00 1.00

HOME-total score 1.02 1.001.03 1.01 1.001.02 0.99 0.991.00

* P .01. P .05.

Fig 2. Trajectory of television viewingover time. The error bars show thestandard error of the mean.


study, in which the average 1-year-old watched 6hours per week and the average 3-year-old watched13 hours per week.6 Children in our study watchedslightly less than children surveyed in 2 pediatricclinics.40 These differences are probably attributableto differences in sample composition, data collectionmethods, and the inclusion of videos. For example,the national study used diaries to determine theamount of time spent with television, and the clinicstudy separated television from video viewing.

Children of black and less-educated motherswatched more television at all ages. These socialgradients in television viewing were our most per-sistent findings and were consistent with studies ofolder children1,18 and adults.29 Because it is unlikelythat race and education directly influence televisionviewing, there must be other contributing factors.For example, it has been suggested that concernsabout safety might present a barrier to childrensgoing outside to play and that blacks are more likelyto live in neighborhoods perceived as unsafe.18 Sur-prisingly, adding perceived neighborhood quality toour regression models did not change the estimatesfor race or maternal education, perhaps because thequestions in the NLSY did not capture the relevantneighborhood characteristics.41,42 In addition toneighborhood quality, other factors potentially re-lated both to television viewing and to race or edu-cation need to be considered, such as residentialstability,42 wealth,43 and the accessibility of play-grounds, museums, and libraries. Our results canspeak only indirectly to the many constraints thatdisadvantaged families and their children may facein pursuing beneficial alternatives to television.

Our longitudinal analysis indicates that greatertelevision viewing in early childhood is associatedwith greater viewing at school age. The persistenceof this behavior pattern may reflect continuing envi-ronmental influences, the development of child pref-erences or habits, or, most likely, an interactionbetween the 2. Regardless, prevention research di-rected at much younger children and their families iswarranted, especially because successful preventiveintervention studies by Robinson and colleagues15,19and Gortmaker et al23,44 strongly suggest a causalrelationship between school-age viewing and obesityand aggression. Our analyses also indicate that, liketelevision viewing in general, the social gradients intelevision viewing emerge at an early age, increase,and persist into childhood. These viewing gradientsmay be among the earliest antecedents of social dis-parities in health, offering potential insight into pre-disease pathways45 and suggesting earlier opportu-nities to address these disparities.

Surprisingly, child care, maternal employment,and marital status were not among the strongestindependent predictors of increased television view-ing, which runs counter to the notion that televisionoften serves as a babysitter for busy parents tryingto juggle jobs, children, and taking care of a home.Similarly, one would expect a measure of the homeenvironment to capture parenting style and thereforeto correlate with the amount of television watched.However, the HOME score was not a strong predic-

tor of television viewing. This could be attributableto 2 factors: first, the HOME-SF may be a less accu-rate measure of parenting style for children youngerthan 346; second, overall parenting style may notcorrelate with parental approaches to child televisionviewing. If a parent believes that television is bene-ficial, then letting an infant or toddler watch televi-sion may reflect a desire to do what is best for thechild. The surprising positive association betweenHOME scores and viewing in the Youngest groupmay be reasonably explained by such parental be-liefs. Indeed, 1 study found that the majority of par-ents of 0- to 35-month-olds believed that televisioncould improve a childs vocabulary,40 highlightingthe need to study parental knowledge about andattitudes toward television. Future studies shouldfocus on untangling the interactive effects of thehome environment, parenting style, and child pref-erence on child television viewing.

An important limitation of this study is the reli-ance on maternal response to single questions re-garding weekday and weekend day television view-ing. Studies comparing parental estimates withdiaries or with direct observation (video) suggestthat parents may overestimate their childrens timewith television.4749 However, when we analyzedchildren 2 to 11 years of age in 1998 and comparedour (weighted) findings to data collected using theNielsen People Meter in 1999,29 NLSY mothers re-ported only a half-hour more per day, on average, adifference that may be explained by NLSY mothersinclusion of videos. In addition, parental estimates oftelevision viewing in older children were used in therandomized, controlled trials that linked televisionwith obesity,19 indicating that parental estimateshave some predictive validity.

Another limitation is that we do not know howmothers defined watching television for their in-fants and toddlers. This is particularly an issue forthe Youngest sample. Although 6-month-olds willattend to television roughly half the time that it ison,50 qualitative observation of infants in a smallstudy suggested that they look at television contin-uously for only short periods of time.51 By 15months, children can imitate what they see,52,53 andby 18 months attention to television can last as longas 30 minutes,51 but more information on the earlydevelopment of television viewing is needed. Thematernal estimates are further limited by the fact thatviewing was reported in whole numbers. Any childwho views 1 hour a day was reported as watchingno television, and older children who watch televi-sion between 2 and 3 hours per day may have beenreported as 2 hours per day. Both could result insome underestimation relative to the AAP viewingguidelines. Additional work, based on both detaileddiaries and direct observation, is clearly needed toconfirm our results.

A final limitation is that the NLSY sample designmakes it difficult to generalize the findings to allyoung children. The survey oversampled disadvan-taged groups, and the requirements for our samplemeant that no mothers were younger than 22 years atdelivery, and most were older than 30. It is not clear


whether or in what direction these sample character-istics might bias the results.

This study could not address the content of chil-drens viewing. The relative consumption by andeffects on infants and toddlers of educational versusentertainment television are not known. A study ofthe relationships between preschool television view-ing and adolescent achievement, behavior, and atti-tudes found that the effects of television dependedon the content of the programs viewed.54 Studies ofelementary school children, however, have shownpositive effects of reducing television without refer-ence to the quality of programs viewed.15,19,23

CONCLUSIONA substantial number of children begin watching

television at an earlier age and in greater amountsthan the AAP recommends. Furthermore, theseviewing patterns persist into childhood, when thedirect adverse effects of television are better docu-mented. Important research questions remain re-garding television program content and possible di-rect effects on infants and toddlers. Nevertheless,these findings should encourage parents and pedia-tricians to discuss young childrens television view-ing (and beneficial alternatives) and should alert re-searchers to the potential window of opportunity forpreventive interventions before age 2.

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ARROGANCE ENCOURAGED

I was appalled by the way arrogance and overconfidence were encouragedduring medical training. Indeed, during clinical training I was frequently criticizedfor expressing uncertainty and humility to patients or teachers. It struck me asironic that awareness of the limits of ones knowledge or data are encouraged ingraduate school (I have a PhD in biology), where the degree of uncertainty is farless than in clinical practice. Perhaps the level of certainty in professional discourseis inversely proportional to a professions scientific rigor?

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Submitted by Student


DOI: 10.1542/peds.109.4.634 2002;109;634Pediatrics

Laura K. Certain and Robert S. KahnToddlers

Prevalence, Correlates, and Trajectory of Television Viewing Among Infants and

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