 |
 |

Reducing Children's Television Viewing to Prevent Obesity
A Randomized Controlled Trial
Thomas N. Robinson, MD, MPH
JAMA. 1999;282:1561-1567.
ABSTRACT
 |  |
Context Some observational studies have found an association between television viewing and child and adolescent adiposity.
Objective To assess the effects of reducing television, videotape, and video game use on changes in adiposity, physical activity, and dietary intake.
Design Randomized controlled school-based trial conducted from September 1996 to April 1997.
Setting Two sociodemographically and scholastically matched public elementary schools in San Jose, Calif.
Participants Of 198 third- and fourth-grade students, who were given parental consent to participate, 192 students (mean age, 8.9 years) completed the study.
Intervention Children in 1 elementary school received an 18-lesson, 6-month classroom curriculum to reduce television, videotape, and video game use.
Main Outcome Measures Changes in measures of height, weight, triceps skinfold thickness, waist and hip circumferences, and cardiorespiratory fitness; self-reported media use, physical activity, and dietary behaviors; and parental report of child and family behaviors. The primary outcome measure was body mass index, calculated as weight in kilograms divided by the square of height in meters.
Results Compared with controls, children in the intervention group had statistically significant relative decreases in body mass index (intervention vs control change: 18.38 to 18.67 kg/m2 vs 18.10 to 18.81 kg/m2, respectively; adjusted difference -0.45 kg/m2 [95% confidence interval {CI}, -0.73 to -0.17]; P=.002), triceps skinfold thickness (intervention vs control change: 14.55 to 15.47 mm vs 13.97 to 16.46 mm, respectively; adjusted difference, -1.47 mm [95% CI, -2.41 to -0.54]; P=.002), waist circumference (intervention vs control change: 60.48 to 63.57 cm vs 59.51 to 64.73 cm, respectively; adjusted difference, -2.30 cm [95% CI, -3.27 to -1.33]; P<.001), and waist-to-hip ratio (intervention vs control change: 0.83 to 0.83 vs 0.82 to 0.84, respectively; adjusted difference, -0.02 [95% CI, -0.03 to -0.01]; P<.001). Relative to controls, intervention group changes were accompanied by statistically significant decreases in children's reported television viewing and meals eaten in front of the television. There were no statistically significant differences between groups for changes in high-fat food intake, moderate-to-vigorous physical activity, and cardiorespiratory fitness.
Conclusions Reducing television, videotape, and video game use may be a promising, population-based approach to prevent childhood obesity.
INTRODUCTION
The United States has experienced alarming increases in obesity among children and adolescents.1 However, most available treatments for obese children have yielded only modest, unsustained effects.2 Consequently, prevention is considered to hold the greatest promise.3 Unfortunately, most prevention programs that specifically attempt to reduce fat and energy intake and increase physical activity have been ineffective at changing body fatness.4-5 As a result, there is a need for innovative approaches to prevent obesity.
There is widespread speculation that television viewing is one of the most easily modifiable causes of obesity among children. American children spend more time watching television and videotapes and playing video games than doing anything else except sleeping.6 Two primary mechanisms by which television viewing contributes to obesity have been suggested: reduced energy expenditure from displacement of physical activity and increased dietary energy intake, either during viewing or as a result of food advertising.
Cross-sectional epidemiological studies have consistently found relatively weak positive associations between television viewing and child and adolescent adiposity.7-21 Prospective studies are less common and have produced mixed results.7, 14 The consistently weak associations found in epidemiological studies may be due to the measurement error in self-reports of television viewing. As a result, additional epidemiological studies would not be expected to clarify the true nature of this relationship.22
A causal relationship can only be demonstrated in an experimental trial, in which manipulation of the risk factor changes the outcome.23 Therefore, we conducted a randomized, controlled, school-based trial of reducing third- and fourth-grade children's television, videotape, and video game use to assess the effects on adiposity and the hypothesized mechanisms of physical activity and dietary intake. We hypothesized that compared with controls, children exposed to the television reduction intervention would significantly decrease their levels of adiposity.
METHODS
All third- and fourth-grade students in 2 public elementary schools in a single school district in San Jose, Calif, were eligible to participate. Schools were sociodemographically and scholastically matched by district personnel. School principals and teachers agreed to participate prior to randomization. Parents or guardians provided signed written informed consent for their children to participate in assessments and for their own participation in telephone interviews. One school was randomly assigned to implement a program to reduce television, videotape, and video game use. The other school was assigned to be an assessments-only control. Participants and school personnel, including classroom teachers, were informed of the nature of the intervention but were unaware of the primary hypothesis. The study was approved by the Stanford University Panel on Human Subjects in Research, Palo Alto, Calif.
Intervention
To test the specific role of television, videotape, and video game use in the development of body fatness, as well as effects on dietary intake and physical activity, it was necessary to design an intervention that decreased media use alone without specifically promoting more active behaviors as replacements. This was accomplished by limiting access to television sets and budgeting use while simultaneously becoming more selective viewers or players.
The intervention, which was based in Bandura's social cognitive theory,24 consisted of incorporating 18 lessons of 30 to 50 minutes into the standard curriculum that was taught by the regular third- and fourth-grade classroom teachers. The teachers were trained by the research staff, and the majority of lessons were taught during the first 2 months of the school year. Early lessons included self-monitoring and self-reporting of television, videotape, and video game use to motivate children to want to reduce the time they spent in these activities. These lessons were followed by a television turnoff,25 during which children were challenged to watch no television or videotapes and play no video games for 10 days. After the turnoff, children were encouraged to follow a 7-hour per week budget. Additional lessons taught children to become "intelligent viewers" by using their viewing and video game time more selectively. Several final lessons enlisted children as advocates for reducing media use. The entire curriculum consisted of approximately 18 hours of classroom time. Newsletters that were designed to motivate parents to help their children stay within their time budgets and that suggested strategies for limiting television, videotape, and video game use for the entire family were distributed to parents.
To help with budgeting, each household also received an electronic television time manager (TV Allowance, Mindmaster, Inc, Miami, Fla). This device locks onto the power plug of the television set and monitors and budgets viewing time for each member of the household through use of personal identification codes. Because it controls power to the television, it also controls video cassette recorder (VCR) and video game use. Families could request additional units for every television in their homes, at no cost.
Outcome Measurements
Assessments were performed by trained staff, blinded to the experimental design, at baseline (September 1996) and after the completion of the intervention (April 1997). At each time point, on the same days in both schools, children completed self-report questionnaires on 2 non-Monday weekdays. A research staff member read each question out loud. Classroom teachers did not participate in the assessments. Physical measures were performed during 2 physical education periods at each time point, by the same staff in both schools. Parents were interviewed by telephone at baseline and after the intervention by trained interviewers following a standardized protocol. Parents, children, and teachers were not aware that the primary outcome was adiposity.
Body mass index (BMI), defined as the weight in kilograms divided by the square of the height in meters, was the primary measure of adiposity.26-27 Standing height was measured using a portable direct-reading stadiometer and body weight was measured using a digital scale, according to established guidelines.28-29 Test-retest reliabilities were high (intraclass Spearman r>0.99 for height, r>0.99 for weight). Triceps skinfold thickness was included as a measure of subcutaneous fat and was measured on the right arm, according to established guidelines.28-29 Test-retest reliability was r>0.99 and skinfold thickness was highly correlated with BMI (r=0.82).
Waist and hip circumferences were measured with a nonelastic tape at the level of the umbilicus and the maximal extension of the buttocks, respectively, according to established guidelines.28-29 Test-retest reliabilities were r>0.99. Waist and hip circumferences were correlated with BMI (r=0.87, r=0.90, respectively) and triceps skinfold thickness (r=0.72, r=0.78, respectively). The waist-to-hip ratio was calculated as a measure of body fat distribution.
Children reported the time they spent "watching television," "watching movies or videos on a VCR," and "playing video games," separately for before school and after school, "yesterday" and "last Saturday" on the first assessment day, and "yesterday" on the second assessment day. Prior to reading these items, the research staff led children through several participatory time-estimating exercises. This instrument was adapted from a similar instrument previously used in young adolescents with high test-retest reliability (r=0.94).15
Parents estimated the amount of time their child spent watching television, watching videotapes on the VCR, and playing video games on a typical school day and on a typical weekend day. Similar items have produced accurate estimates compared with videotaped observation.30 There was moderate agreement between parent and child reports of children's media use (Spearman r=0.31, P<.001 for television viewing; r=0.17, P=.03 for videotape viewing; r=0.49, P<.001 for video game playing). A previously validated 4-item instrument was used to assess overall household television viewing.31
Children and parents also estimated the amount of time the child spent in other sedentary behaviors, including, using a computer, doing homework, reading, listening to music, playing a musical instrument, doing artwork or crafts, talking with parents, playing quiet games indoors, and at classes or clubs (parent-child agreement Spearman r=0.16, P<.05).
On both days children reported their previous day's out-of-school physical activities, using a previously validated activity checklist.32 Responses from the 2 days were averaged and weighted for levels of intensity using standard energy expenditure estimates.33 Parents estimated the amount of time their child spent in organized physical activities (such as teams or sports classes) and nonorganized physical activities (such as playing sports, bicycling, rollerblading, etc) (parent-child agreement Spearman r=0.16, P=.05).
On both days, children completed 1-day food frequency recalls for 60 foods in 26 food categories, based on instruments previously validated in third- through sixth-grade children.34-35 High-fat foods were those previously identified as the major contributors of fat in the diets of children35 and adults,36 and were identified through focus groups with children, parents, and school lunch personnel. Highly advertised foods included 3 categories representing sugary cereals, carbonated soft drinks, and foods from fast-food restaurants.
Children also reported how often they ate breakfast and dinner in a room with the television turned on during the past week, on 4-point scales ranging from never to every day, and they reported the proportion of time they were eating or drinking a snack (not including meals) while watching television or videotapes or playing video games, on a 3-point scale. Parents responded to the same questions about their children, reporting the number of days in the last week for meals (parent-child agreement Spearman r=0.24, P=.003) and the percentage of time for snacking (parent-child agreement Spearman r=0.02, P>.05).
The maximal, multistage, 20-m, shuttle run test (20-MST) was used to assess cardiorespiratory fitness.37 The 20-MST has been found to be reliable (test-retest r=0.73-0.93),37-39 a valid measure of maximum oxygen consumption as measured by treadmill testing (r=0.69-0.87),38-42 and sensitive to change42 in children.
Statistical Analysis
Baseline comparability of intervention and control groups was assessed using nonparametric Wilcoxon rank sum tests for scaled variables and 2 tests for categorical variables. As a primary prevention program, the intervention was designed to target the entire sample. Effects were expected and intended to occur throughout the entire distribution of adiposity in the samplenot just around a defined threshold. Thus, for purposes of establishing the efficacy of this intervention, it is most appropriate to compare the full distributions of BMI between intervention and control groups. Therefore, to test the primary hypothesis, accounting for the design with school as the unit of randomization (adjusting for intraclass correlation), a mixed-model analysis of covariance approach was used, with postintervention BMI as the dependent variable; the intervention group (intervention vs control) as the independent variable; and baseline BMI, age, and sex as covariates (SAS MIXED procedure, SAS version 6.12, SAS Institute Inc, Cary, NC).43 The same analysis approach was used for all secondary outcome variables, triceps skinfold thickness, waist and hip circumferences, waist-to-hip ratio, and measures of dietary intake and physical activity. Each outcome also was tested for intervention by sex and intervention by age interactions. All analyses were completed on an intention-to-treat basis, and all tests of statistical significance were 2-tailed with =.05.
With an anticipated sample size of approximately 100 participants per group and using the above analysis, the study was designed to have 80% power to detect an effect size of 0.20 or greater. This corresponded to estimated differences between groups of about 0.75 BMI units, 1.2 mm of triceps skinfold, 1.8 cm of waist circumference, and 2 hours per week of television, videotape, and video game use.
In children of this age, BMI, triceps skinfold thickness, waist circumference, and hip circumference were all expected to increase over the course of the experiment, as part of normal growth, in both the intervention and control groups. Therefore, effect sizes are reported as changes in the intervention group relative to changes in the controls (relative differences). A negative difference is termed a relative decrease in comparison with the controls, even if the actual value increased as a result of normal growth and development.
RESULTS
The study design and participation are shown in Figure 1. Ninety-two (86.8%) of 106 eligible children in the intervention school and 100 (82.6%) of 121 eligible children in the control school participated in baseline and postintervention assessments. Intervention and control participants, respectively, were comparable in age (mean [SD], 8.95 [0.64] vs 8.92 [0.70] years, P=.69), sex (44.6% vs 48.5% girls, P=.59), mean (SD) number of televisions in the home (2.7 [1.3] vs 2.7 [1.1], P=.56), mean (SD) number of video game players (systems) (1.5 [2.3] vs 1.2 [1.7], P=.49) and percentage of children with a television in their bedroom (43.5% vs 42.7%, P=.92). Physical measures but not self-reports were included in the analysis for 11 children who were classified by their teachers as having limited English proficiency or having a learning disability.
|
|
|
|
Figure. Study Design and Participant Flow
|
|
|
Baseline and postintervention telephone interviews were completed by 68 (71.6%) and 75 (72.8%) of the parents of participating children in the intervention and control schools, respectively. Intervention school parents reported greater maximum household education levels than participating control school parents (45% vs 21% college graduates, P=.01) but did not differ significantly in ethnicity (80% vs 70% white, P=.19), sex of respondent (82% vs 88% female, P=.33) or marital status (77% vs 67% married, P=.22).
Participation in the Intervention
Teachers reported teaching all lessons, although we did not collect detailed data determining whether the lessons were delivered as they were intended. Ninety-five (90%) of 106 students in the intervention school participated in at least some of the television turnoff and 71 (67%) completed the entire 10 days without watching television or videotapes or playing video games. During the budgeting phase of the intervention, 58 (55%) of the students turned in at least 1 signed parent confirmation that they had stayed below their television and videotape viewing and video game playing budget for the previous week. Forty-four parents (42%) returned response cards reporting they had installed the TV Allowance and 29 families (27%) requested 1 or more additional TV Allowances.
Effects on Adiposity
Results of anthropometric measures are presented in Table 1. At baseline, both groups were comparable (P>.10) on all baseline measures of body composition. As expected for children of this age, BMI, triceps skinfold thickness, waist circumference, and hip circumference all increased in both intervention and control children during the course of the school year. However, compared with controls, children in the intervention group had statistically significant relative decreases in BMI, triceps skinfold thickness, waist circumference, and waist-to-hip ratio (Table 1). There were no significant interventions by sex or intervention by age interactions for any of the body composition outcomes. The results did not change when ethnicity and parent education were included as additional covariates for children with completed parent interviews.
|
|
|
|
Table 1. Children's Anthropometric Measures*
|
|
|
Although the sample size was insufficient to formally test for effects within subgroups, it was desirable to further characterize the effects of the intervention on participants with varying levels of adiposity, with a descriptive analysis. Intervention and control group changes were compared within strata defined by baseline levels of BMI, triceps skinfold, waist circumference, and waist-to-hip ratio. For all body composition measures, effects of the intervention occurred across the entire distribution of baseline adiposity, with greater intervention vs control differences evident among the middle and higher strata of body fatness.
Effects on Media Use, Diet, and Physical Activity
Child measures are presented in Table 2 and parent measures are presented in Table 3. Both groups were well matched at baseline, although intervention group children reported eating significantly more meals while watching television, and participating intervention group parents reported significantly less overall household television use and that their children spent significantly more time in other sedentary behaviors at baseline.
|
|
|
|
Table 2. Child Measures of Television Viewing, Diet, and Physical Activity and Fitness*
|
|
|
|
|
|
|
Table 3. Parent Reports of Children's Television Viewing, Diet, and Physical Activity*
|
|
|
The intervention significantly decreased children's television viewing, compared with controls, according to both child and parent reports (relative reductions of about one third from baseline). Intervention group children also reported significantly greater reductions in video game use than controls. The intervention also resulted in greater, but not statistically significant, decreases in parent reports of children's video game use, parent and child reports of videotape viewing, and parent reports of overall household television viewing. There were no significant intervention by sex or intervention by age interactions for any of the media use outcomes.
The intervention significantly reduced the frequency of children eating meals in a room with the television turned on. Intervention group children also reported relative reductions in servings of high-fat foods compared with controls, although these differences were not statistically significant. There were no significant intervention effects on reports of children's physical activity levels or performance on the 20-MST of physical fitness. There were no significant intervention by sex or intervention by age interactions for any of the diet or activity outcomes.
COMMENT
This is the first experimental study to demonstrate a direct association between television, videotape, and video game use and increased adiposity. Because the intervention targeted reduction of media use alone, without substituting alternative behaviors, a causal inference might be made.23 In one previous obesity treatment study, obese children who were reinforced (ie, rewarded) for decreasing sedentary activity (including television viewing and computer games, as well as imaginative play, talking on the telephone, playing board games, etc) along with following an energy-restricted diet lost significantly more weight than obese children reinforced for increasing physical activity or those reinforced for both.44 Although that study did not directly test the role of television, videotape, and video game use, the similar findings support our results.
This experiment was designed to overcome the dependence of epidemiological studies on error-prone measures of television viewing behaviors by using BMI as the primary outcome. However, the intervention did produce statistically significant decreases in reported television viewing and video game use, compared with controls. Previous studies of reducing children's television viewing have been uncontrolled and limited to a small number of families.45-47 This study, therefore, also represents a promising model for studying other hypothesized effects of television and videotape viewing and video game use.
Because this study involved children in only 2 elementary schools, the possibility that the results were due to differences in the groups that were unrelated to the intervention cannot be ruled out completely. This possibility is made less likely, however, because the schools were in a single school district and participants were comparable at baseline on almost all measured variables. In addition, the patterns of the results strengthen the case for causal inference. The crossover patterns of the changes in BMI, triceps skinfold thickness, waist circumference, and waist-to-hip ratio lessen the likelihood of scaling (a "ceiling effect"), regression, and selection-maturation biases as alternative interpretations of the results.48-49
Effects of the intervention on diet and activity were less clear. Compared with controls, children in the intervention group significantly reduced the number of meals they reportedly ate in front of the television set. There were no significant effects on reports of snacking while watching television or intake of high-fat and highly advertised foods. However, because snacking while watching television was assessed as a proportion, even no change in this variable might result in decreased energy intake as total viewing was decreased. Epidemiological studies have found associations among hours of television viewing and children's fat and energy intakes,15, 50 and experimental studies have shown that food advertising affects children's snack choices and consumption.51-52
Some epidemiological studies have found weak inverse associations between hours of television viewing and physical activity14, 18 and fitness.8, 16 Our intervention did not result in a significant change in physical activity or cardiorespiratory fitness. However, because only moderate- and vigorous-intensity activities were assessed, it is also possible that reductions in television viewing resulted in increased energy expenditure via more low-intensity activity. This is consistent with the finding that reductions in television, videotape, and video game use did not result in compensatory increases in other sedentary pursuits. Larger experimental studies and improved measures of diet and activity are needed to more definitively assess the specific mechanisms that account for changes in adiposity in response to reduced television, videotape, and video game use.
With a few exceptions, previous prevention interventions that have attempted to increase physical activity and decrease dietary fat and energy intake have been relatively ineffective at reducing body fatness.4-5 In contrast, this intervention targeting only television, videotape, and video game use produced statistically significant and clinically significant relative changes in BMI, triceps skinfold thickness, waist circumference, and waist-to-hip ratio over a period of 7 months. These changes occurred over the entire sample, shifting the entire distribution of adiposity downward. Even a small shift downward in the population distribution of adiposity would be expected to have large effects on obesity-related morbidity and mortality.53 Additional experimental studies with larger and more sociodemographically diverse samples are needed to evaluate the generalizability of these findings. However, this study indicates that reducing television, videotape, and video game use may be a promising, population-based approach to help prevent childhood obesity.
AUTHOR INFORMATION
Funding/Support: This work was funded by a grant from the American Heart Association, California Affiliate, and by grant RO1 HL54102 from the National Heart, Lung, and Blood Institute, Bethesda, Md. The study was completed during the tenure of a Clinician-Scientist Award from the American Heart Association.
Acknowledgment: I thank Marta Luna Wilde, MA, Joel D. Killen, PhD, Dina L. G. Borzekowski, EdD, K. Farish Haydel, Ann Varady, MS, Sally McCarthy, and the students, teachers, and administrators who participated in this project.
Corresponding Author and Reprints: Thomas N. Robinson, MD, MPH, Stanford Center for Research in Disease Prevention, Stanford University School of Medicine, 1000 Welch Rd, Palo Alto, CA 94304 (e-mail: tom.robinson{at}stanford.edu).
Author Affiliation: Departments of Pediatrics and Medicine, Stanford Center for Research in Disease Prevention, Stanford University School of Medicine, Palo Alto, Calif.
REFERENCES
 |  |
1. Troiano RP, Flegal KM. Overweight children and adolescents: description, epidemiology, and demographics. Pediatrics. 1998;101:497-504.
FREE FULL TEXT
2. Epstein LH, Myers MD, Raynor HA, Saelens BE. Treatment of pediatric obesity. Pediatrics. 1998;101:554-570.
FREE FULL TEXT
3. Hill JO, Peters JC. Environmental contributions to the obesity epidemic. Science. 1998;280:1371-1374.
FREE FULL TEXT
4. Resnicow K. School-based obesity prevention: population versus high-risk interventions. Ann N Y Acad Sci. 1993;699:154-166.
ISI
| PUBMED
5. Resnicow K, Robinson TN. School-based cardiovascular disease prevention studies: review and synthesis. Ann Epidemiol. 1997;7(suppl 7):S14-S31.
6. The Annenberg Public Policy Center of the University of Pennsylvania. Television in the Home: The 1997 Survey of Parents and Children. Philadelphia: University of Pennsylvania; 1997.
7. Dietz WH, Gortmaker SL. Do we fatten our children at the TV set? television viewing and obesity in children and adolescents. Pediatrics. 1985;75:807-812.
FREE FULL TEXT
8. Pate RR, Ross JG. The national children and youth fitness study II: factors associated with health-related fitness. J Phys Educ Recreation Dance. 1987;58:93-95.
9. Obarzanek E, Schreiber GB, Crawford PB, et al. Energy intake and physical activity in relation to indexes of body fat: the National Heart, Lung, and Blood Institute Growth and Health Study. Am J Clin Nutr. 1994;60:15-22.
FREE FULL TEXT
10. Shannon B, Peacock J, Brown MJ. Body fatness, television viewing and calorie-intake of a sample of Pennsylvania sixth grade children. J Nutr Educ. 1991;23:262-268.
ISI
11. Locard E, Mamelle N, Billette A, Miginiac M, Munoz F, Rey S. Risk factors of obesity in a five-year-old population: parental versus environmental factors. Int J Obes. 1992;16:721-729.
ISI
| PUBMED
12. Gortmaker SL, Must A, Sobol AM, Peterson K, Colditz GA, Dietz WH. Television viewing as a cause of increasing obesity among children in the United States, 1986-1990. Arch Pediatr Adolesc Med. 1996;150:356-362.
FREE FULL TEXT
13. Andersen RE, Crespo CJ, Bartlett SJ, Cheskin LJ, Pratt M. Relationship of physical activity and television watching with body weight and level of fatness among children: results from the Third National Health and Nutrition Examination Survey. JAMA. 1998;279:938-942.
FREE FULL TEXT
14. Robinson TN, Hammer LD, Killen JD, et al. Does television viewing increase obesity and reduce physical activity? cross-sectional and longitudinal analyses among adolescent girls. Pediatrics. 1993;91:273-280.
FREE FULL TEXT
15. Robinson TN, Killen JD. Ethnic and gender differences in the relationships between television viewing and obesity, physical activity and dietary fat intake. J Health Educ. 1995;26:S91-S98.
16. Tucker LA. The relationship of television viewing to physical fitness and obesity. Adolescence. 1986;21:797-806.
ISI
| PUBMED
17. Wolf AM, Gortmaker SL, Cheung L, Gray HM, Herzog DB, Colditz GA. Activity, inactivity, and obesity: racial, ethnic, and age differences among schoolgirls. Am J Public Health. 1993;83:1625-1627.
FREE FULL TEXT
18. DuRant RH, Baranowski T, Johnson M, Thompson WO. The relationship among television watching, physical activity, and body composition of young children. Pediatrics. 1994;94:449-455.
FREE FULL TEXT
19. DuRant RH, Thompson WO, Johnson M, Baranowski T. The relationship among television watching, physical activity, and body composition of 5- or 6-year-old children. Pediatr Exerc Sci. 1996;8:15-26.
20. Dwyer JT, Stone EJ, Yang M, et al. Predictors of overweight and overfatness in a multiethnic pediatric population. Am J Clin Nutr. 1998;67:602-610.
ABSTRACT
21. Armstrong CA, Sallis JF, Alcaraz JE, Kolody B, McKenzie TL, Hovell MF. Children's television viewing, body fat, and physical fitness. Am J Health Promotion. 1998;12:363-368.
ISI
| PUBMED
22. Robinson TN. Does television cause childhood obesity? JAMA. 1998;279:959-960.
FREE FULL TEXT
23. Kraemer HC, Kazdin AE, Offord DR, Kessler RC, Jensen PS, Kupfer DJ. Coming to terms with the terms of risk. Arch Gen Psychiatry. 1997;54:337-343.
FREE FULL TEXT
24. Bandura A. Social Foundations of Thought and Action. Englewood Cliffs, NJ: Prentice-Hall; 1986.
25. Winn M. Unplugging the Plug-in Drug. New York, NY: Penguin Books; 1987.
26. Kraemer HC, Berkowitz RI, Hammer LD. Methodological difficulties in studies of obesity, I: measurement issues. Ann Behav Med. 1990;12:112-118.
FULL TEXT
27. Dietz WH, Robinson TN. Use of the body mass index (BMI) as a measure of overweight in children and adolescents. J Pediatr. 1998;132:191-193.
FULL TEXT
|
ISI
| PUBMED
28. Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual. Champaign, Ill: Human Kinetics Publishers; 1988.
29. National Center for Health Statistics. NHANES III Anthropometric Procedures [videotape]. Washington, DC: US Government Printing Office; 1996. Stock No. 017-022-01335-5.
30. Anderson DR, Field DE, Collins PA, Lorch EP, Nathan JG. Estimates of young children's time with television: a methodological comparison of parent reports with time-lapse video home observation. Child Dev. 1985;56:1345-1357.
ISI
| PUBMED
31. Medrich EA. Constant television: a background to daily life. J Communication. 1979;29:171-176.
FULL TEXT
|
ISI
32. Sallis JF, Strikmiller PK, Harsha DW, et al. Validation of interviewer- and self-administered physical activity checklists for fifth grade students. Med Sci Sports Exerc. 1996;28:840-851.
ISI
| PUBMED
33. Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc. 1993;25:71-80.
ISI
| PUBMED
34. Baranowski T, Dworkin R, Henske JC, et al. The accuracy of children's self reports of diet: family health project. J Am Diet Assoc. 1986;86:1381-1385.
ISI
| PUBMED
35. Simons-Morton BG, Baranowski T, Parcel GS, O'Hara NM, Matteson RC. Children's frequency of consumption of foods high in fat and sodium. Am J Prev Med. 1990;6:218-227.
ISI
| PUBMED
36. Block G, Clifford C, Naughton MD, Henderson M, McAdams M. A brief dietary screen for high fat intake. J Nutr Educ. 1989;21:199-207.
ISI
37. Leger LA, Mercier D, Gadoury C, Lambert J. The multistage 20 metre shuttle run test for aerobic fitness. J Sports Sci. 1988;6:93-101.
PUBMED
38. Liu NY-S, Plowman SA, Looney MA. The reliability and validity of the 20-meter shuttle test in American students 12 to 15 years old. Res Q Exerc Sport. 1992;63:360-365.
ISI
| PUBMED
39. Mahoney C. 20-MST and PWC170 validity in non-Caucasian children in the UK. Br J Sports Med. 1992;26:45-47.
FREE FULL TEXT
40. Boreham CAG, Paliczka VJ, Nichols AK. A comparison of the PWC170 and 20-MST tests of aerobic fitness in adolescent schoolchildren. J Sports Med Phys Fitness. 1990;30:19-23.
ISI
| PUBMED
41. van Mechelen W, Hlobil H, Kemper HCG. Validation of two running tests as estimates of maximal aerobic power in children. Eur J Appl Physiol. 1986;55:503-506.
42. Ahmaidi SB, Varray AL, Savy-Pacaux AM, Prefaut CG. Cardiorespiratory fitness evaluation by shuttle test in asthmatic subjects during aerobic training. Chest. 1993;103:1135-1141.
FREE FULL TEXT
43. Murray DM. Design and Analysis of Group-Randomized Trials. New York, NY: Oxford University Press; 1998.
44. Epstein LH, Valoski AM, Vara LS, et al. Effects of decreasing sedentary behavior and increasing activity on weight change in obese children. Health Psychol. 1995;14:109-115.
FULL TEXT
|
ISI
| PUBMED
45. Wolfe DA, Mendes MG, Factor D. A parent-administered program to reduce children's television viewing. J Appl Behav Anal. 1984;17:267-272.
PUBMED
46. Jason LA. Using a token-actuated timer to reduce television viewing. J Appl Behav Anal. 1985;18:269-272.
PUBMED
47. Jason LA, Johnson SZ, Jurs A. Reducing children's television viewing with an inexpensive lock. Child Fam Behav Ther. 1993;15:45-54.
FULL TEXT
48. Bracht GH, Glass GV. The external validity of experiments. Am Educ Res J. 1968;5:437-474.
FREE FULL TEXT
49. Cook TD, Campbell DT. Quasi-Experimentation: Design & Analysis Issues for Field Settings. Boston, Mass: Houghton Mifflin Co; 1979.
50. Taras HL, Sallis JF, Patterson TL, Nader PR, Nelson JA. Television's influence on children's diet and physical activity. J Dev Behav Pediatr. 1989;10:176-180.
ISI
| PUBMED
51. Gorn GJ, Goldberg ME. Behavioral evidence for the effects of televised food messages on children. J Consumer Res. 1982;9:200-205.
52. Jeffrey DB, McLellarn RW, Fox DT. The development of children's eating habits: the role of television commercials. Health Educ Q. 1982;9:78-93.
53. Rose G. Strategies of prevention: the individual and the population. In: Marmot M, Elliott P, eds. Coronary Heart Disease Epidemiology: From Aetiology to Public Health. Oxford, England: Oxford University Press; 1992.
CiteULike Connotea Del.icio.us Digg Reddit Technorati Twitter
What's this?
RELATED ARTICLE
October 27, 1999
JAMA. ;282():1593-1594.
FULL TEXT
THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES
 |
Perinatal risk factors for childhood obesity and metabolic dysregulation
Catalano et al.
Am. J. Clin. Nutr. 2009;90:1303-1313.
ABSTRACT
| FULL TEXT
Obesity in the Transition to Adulthood: Predictions Across Race/Ethnicity, Immigrant Generation, and Sex
Harris et al.
Arch Pediatr Adolesc Med 2009;163:1022-1028.
ABSTRACT
| FULL TEXT
The CHEER Study to Reduce BMI in Elementary School Students: A School-Based, Parent-Directed Study in Framingham, Massachusetts
Resnick et al.
The Journal of School Nursing 2009;25:361-372.
ABSTRACT
| FULL TEXT
Relation Between Socioeconomic Status and Body Mass Index: Evidence of an Indirect Path via Television Use
Morgenstern et al.
Arch Pediatr Adolesc Med 2009;163:731-738.
ABSTRACT
| FULL TEXT
By how much would limiting TV food advertising reduce childhood obesity?
Veerman et al.
Eur J Public Health 2009;19:365-369.
ABSTRACT
| FULL TEXT
Early Child Care and Adiposity at Ages 1 and 3 Years
Benjamin et al.
Pediatrics 2009;124:555-562.
ABSTRACT
| FULL TEXT
Factors associated with television viewing time in toddlers and preschoolers in Greece: the GENESIS study
Kourlaba et al.
J Public Health (Oxf) 2009;31:222-230.
ABSTRACT
| FULL TEXT
Television Viewing and Symptoms of Inattention and Hyperactivity Across Time: The Importance of Research Questions
Stevens et al.
Journal of Early Intervention 2009;31:215-226.
ABSTRACT
Increased television viewing is associated with elevated body fatness but not with lower total energy expenditure in children
Jackson et al.
Am. J. Clin. Nutr. 2009;89:1031-1036.
ABSTRACT
| FULL TEXT
Dutch Obesity Intervention in Teenagers: Effectiveness of a School-Based Program on Body Composition and Behavior
Singh et al.
Arch Pediatr Adolesc Med 2009;163:309-317.
ABSTRACT
| FULL TEXT
Implementing American Heart Association Pediatric and Adult Nutrition Guidelines: A Scientific Statement From the American Heart Association Nutrition Committee of the Council on Nutrition, Physical Activity and Metabolism, Council on Cardiovascular Disease in the Young, Council on Arteriosclerosis, Thrombosis and Vascular Biology, Council on Cardiovascular Nursing, Council on Epidemiology and Prevention, and Council for High Blood Pressure Research
Gidding et al.
Circulation 2009;119:1161-1175.
FULL TEXT
Television Viewing in Infancy and Child Cognition at 3 Years of Age in a US Cohort
Schmidt et al.
Pediatrics 2009;123:e370-e375.
ABSTRACT
| FULL TEXT
Heart Disease and Stroke Statistics--2009 Update: A Report From the American Heart Association Statistics Committee and Stroke Statistics Subcommittee
WRITING GROUP MEMBERS et al.
Circulation 2009;119:e21-e181.
FULL TEXT
Prevention in the first place: schools a setting for action on physical inactivity
Naylor and McKay
Br. J. Sports. Med. 2009;43:10-13.
ABSTRACT
| FULL TEXT
Effect of a family-based intervention on electronic media use and body composition among boys aged 8--11 years: a pilot study
Todd et al.
J Child Health Care 2008;12:344-358.
ABSTRACT
Behavioral Interventions to Prevent Childhood Obesity: A Systematic Review and Metaanalyses of Randomized Trials
Kamath et al.
J. Clin. Endocrinol. Metab. 2008;93:4606-4615.
ABSTRACT
| FULL TEXT
Prevention and Treatment of Pediatric Obesity: An Endocrine Society Clinical Practice Guideline Based on Expert Opinion
August et al.
J. Clin. Endocrinol. Metab. 2008;93:4576-4599.
ABSTRACT
| FULL TEXT
Preventing childhood obesity: the sentinel site for obesity prevention in Victoria, Australia
Bell et al.
HEALTH PROMOT INT 2008;23:328-336.
ABSTRACT
| FULL TEXT
Reducing overweight and obesity: closing the gap between primary care and public health
Anderson
Fam Pract 2008;25:i10-i16.
ABSTRACT
| FULL TEXT
A Public Health Approach to Winning the War Against Cancer
Frieden et al.
The Oncologist 2008;13:1306-1313.
ABSTRACT
| FULL TEXT
Perception, Intention, and Action in Adolescent Obesity
Bittner Fagan et al.
J Am Board Fam Med 2008;21:555-561.
ABSTRACT
| FULL TEXT
A National Longitudinal Study of the Association Between Hours of TV Viewing and the Trajectory of BMI Growth Among US Children
Danner
J Pediatr Psychol 2008;33:1100-1107.
ABSTRACT
| FULL TEXT
Physically Active Video Gaming: An Effective Strategy for Obesity Prevention?
Pate
Arch Pediatr Adolesc Med 2008;162:895-896.
FULL TEXT
Population-Based Prevention of Obesity: The Need for Comprehensive Promotion of Healthful Eating, Physical Activity, and Energy Balance: A Scientific Statement From American Heart Association Council on Epidemiology and Prevention, Interdisciplinary Committee for Prevention (Formerly the Expert Panel on Population and Prevention Science)
Kumanyika et al.
Circulation 2008;118:428-464.
ABSTRACT
| FULL TEXT
Why Young Adults Hold the Key to Assessing the Obesity Epidemic in Children
Lee
Arch Pediatr Adolesc Med 2008;162:682-687.
ABSTRACT
| FULL TEXT
A Review of TV Viewing and Its Association With Health Outcomes in Adults
Williams et al.
AMERICAN JOURNAL OF LIFESTYLE MEDICINE 2008;2:250-259.
ABSTRACT
Risk factors associated with obesity in children of different racial backgrounds
Urrutia-Rojas et al.
Health Education Journal 2008;67:121-133.
ABSTRACT
Relationship between screen time and metabolic syndrome in adolescents
Mark and Janssen
J Public Health (Oxf) 2008;30:153-160.
ABSTRACT
| FULL TEXT
Clinical Profile of the Overweight Child in the New Millennium
Carvalho et al.
CLIN PEDIATR 2008;47:476-482.
ABSTRACT
Randomised controlled trial adapting US school obesity prevention to England
Kipping et al.
Arch. Dis. Child. 2008;93:469-473.
ABSTRACT
| FULL TEXT
Watching Social Science: The Debate About the Effects of Exposure to Televised Violence on Aggressive Behavior
Glymour et al.
American Behavioral Scientist 2008;51:1231-1259.
ABSTRACT
Characteristics Associated With Older Adolescents Who Have a Television in Their Bedrooms
Barr-Anderson et al.
Pediatrics 2008;121:718-724.
ABSTRACT
| FULL TEXT
Childhood Obesity Prevention Programs: How Do They Affect Eating Pathology and Other Psychological Measures?
Carter and Bulik
Psychosom. Med. 2008;70:363-371.
ABSTRACT
| FULL TEXT
A Policy-Based School Intervention to Prevent Overweight and Obesity
Foster et al.
Pediatrics 2008;121:e794-e802.
ABSTRACT
| FULL TEXT
Public Health Interventions for Addressing Childhood Overweight: Analysis of the Business Case
Finkelstein and Trogdon
AJPH 2008;98:411-415.
ABSTRACT
| FULL TEXT
Team Sports for Overweight Children: The Stanford Sports to Prevent Obesity Randomized Trial (SPORT)
Weintraub et al.
Arch Pediatr Adolesc Med 2008;162:232-237.
ABSTRACT
| FULL TEXT
A Randomized Trial of the Effects of Reducing Television Viewing and Computer Use on Body Mass Index in Young Children
Epstein et al.
Arch Pediatr Adolesc Med 2008;162:239-245.
ABSTRACT
| FULL TEXT
Innovations to Reduce Television and ComputerTime and Obesity in Childhood
Gortmaker
Arch Pediatr Adolesc Med 2008;162:283-284.
FULL TEXT
Themed Review: Clinical Interventions to Promote Physical Activity in Youth
Meriwether et al.
AMERICAN JOURNAL OF LIFESTYLE MEDICINE 2008;2:7-25.
ABSTRACT
The choice of cutoffs for obesity and the effect of those values on risk factor estimation
Toschke et al.
Am. J. Clin. Nutr. 2008;87:292-294.
ABSTRACT
| FULL TEXT
Children, Television Viewing, and Weight Status: Summary and Recommendations from an Expert Panel Meeting
Jordan and Robinson
The ANNALS of the American Academy of Political and Social Science 2008;615:119-132.
ABSTRACT
Peer Influence on Children's Physical Activity: An Experience Sampling Study
Salvy et al.
J Pediatr Psychol 2008;33:39-49.
ABSTRACT
| FULL TEXT
Special Article: Physical Activity, Physical Fitness, and Cardiovascular Risk Factors in Childhood
Gidding
AMERICAN JOURNAL OF LIFESTYLE MEDICINE 2007;1:499-505.
ABSTRACT
Physical activity for the prevention and management of youth-onset type 2 diabetes mellitus: focus on cardiovascular complications
Mcgavock et al.
Diabetes and Vascular Disease Research 2007;4:305-310.
ABSTRACT
Targeting obesity to reduce the risk for type 2 diabetes and other co-morbidities in African American youth: a review of the literature and recommendations for prevention
Nwobu and Johnson
Diabetes and Vascular Disease Research 2007;4:311-319.
ABSTRACT
The status of health-promoting schools in Hong Kong and implications for further development
Lee et al.
HEALTH PROMOT INT 2007;22:316-326.
ABSTRACT
| FULL TEXT
Assessment of Child and Adolescent Overweight and Obesity
Krebs et al.
Pediatrics 2007;120:S193-S228.
ABSTRACT
| FULL TEXT
Recommendations for Prevention of Childhood Obesity
Davis et al.
Pediatrics 2007;120:S229-S253.
ABSTRACT
| FULL TEXT
Recommendations for Treatment of Child and Adolescent Overweight and Obesity
Spear et al.
Pediatrics 2007;120:S254-S288.
ABSTRACT
| FULL TEXT
Violent Television Viewing During Preschool Is Associated With Antisocial Behavior During School Age
Christakis and Zimmerman
Pediatrics 2007;120:993-999.
ABSTRACT
| FULL TEXT
Making a difference: the clinical research programme for children
Smyth
Arch. Dis. Child. 2007;92:835-837.
FULL TEXT
Tioga County Fit for Life: A Primary Obesity Prevention Project
Gombosi et al.
CLIN PEDIATR 2007;46:592-600.
ABSTRACT
Safe Play Spaces To Promote Physical Activity in Inner-City Children: Results from a Pilot Study of an Environmental Intervention
Farley et al.
AJPH 2007;97:1625-1631.
ABSTRACT
| FULL TEXT
Primary Prevention of Cardiovascular Disease in Nursing Practice: Focus on Children and Youth: A Scientific Statement From the American Heart Association Committee on Atherosclerosis, Hypertension, and Obesity in Youth of the Council on Cardiovascular Disease in the Young, Council on Cardiovascular Nursing, Council on Epidemiology and Prevention, and Council on Nutrition, Physical Activity, and Metabolism
Hayman et al.
Circulation 2007;116:344-357.
FULL TEXT
Promoting Physical Activity Participation among Children and Adolescents
Salmon et al.
Epidemiol Rev 2007;0:mxm010v1.
ABSTRACT
| FULL TEXT
Evidence-Based Practice Guideline: Increasing Physical Activity in Schools--Kindergarten Through 8th Grade
Bagby and Adams
The Journal of School Nursing 2007;23:137-143.
ABSTRACT
| FULL TEXT
Persistence of Overweight among Young Children Living in Low Income Communities in Ontario
Evers et al.
J. Am. Coll. Nutr. 2007;26:219-224.
ABSTRACT
| FULL TEXT
Strong Association Between Time Watching Television and Blood Glucose Control in Children and Adolescents With Type 1 Diabetes
Margeirsdottir et al.
Diabetes Care 2007;30:1567-1570.
ABSTRACT
| FULL TEXT
Physical activity levels in children and adolescents are reduced after the Fontan procedure, independent of exercise capacity, and are associated with lower perceived general health
McCrindle et al.
Arch. Dis. Child. 2007;92:509-514.
ABSTRACT
| FULL TEXT
State of the Art Reviews: Changing and Adhering to Lifestyle Changes: What Are the Keys?
Harris et al.
AMERICAN JOURNAL OF LIFESTYLE MEDICINE 2007;1:214-219.
ABSTRACT
Office-Based Motivational Interviewing to Prevent Childhood Obesity: A Feasibility Study
Schwartz et al.
Arch Pediatr Adolesc Med 2007;161:495-501.
ABSTRACT
| FULL TEXT
Childhood Overweight: Parental Perceptions and Readiness for Change
Howard
The Journal of School Nursing 2007;23:73-79.
ABSTRACT
| FULL TEXT
From Tastes Great to Cool: Children's Food Marketing and the Rise of the Symbolic
Schor and Ford
J Law Med Ethics 2007;35:10-21.
Addressing the Epidemic of Childhood Obesity Through School-Based Interventions: What Has Been Done and Where Do We Go From Here?
Peterson and Fox
J Law Med Ethics 2007;35:113-130.
Television watching increases motivated responding for food and energy intake in children
Temple et al.
Am. J. Clin. Nutr. 2007;85:355-361.
ABSTRACT
| FULL TEXT
Longitudinal Relationship Between Television Viewing and Leisure-Time Physical Activity During Adolescence
Taveras et al.
Pediatrics 2007;119:e314-e319.
ABSTRACT
| FULL TEXT
Emergence of Sex Differences in Prevalence of High Systolic Blood Pressure: Analysis of a Longitudinal Adolescent Cohort
Dasgupta et al.
Circulation 2006;114:2663-2670.
ABSTRACT
| FULL TEXT
Physical activity to prevent obesity in young children: Authors' reply
Reilly et al.
BMJ 2006;333:1171-1172.
FULL TEXT
Interventions to promote young people's physical activity: Issues, implications and recommendations for practice
Cale and Harris
Health Education Journal 2006;65:320-337.
ABSTRACT
Taking part counts: adolescents' experiences of the transition from inactivity to active participation in school-based physical education
Brooks and Magnusson
Health Educ Res 2006;21:872-883.
ABSTRACT
| FULL TEXT
Prevention of obesity and eating disorders: a consideration of shared risk factors
Haines and Neumark-Sztainer
Health Educ Res 2006;21:770-782.
ABSTRACT
| FULL TEXT
Effects of a Life Skills Intervention for Increasing Physical Activity in Adolescent Girls
Young et al.
Arch Pediatr Adolesc Med 2006;160:1255-1261.
ABSTRACT
| FULL TEXT
Longitudinal and Secular Trends in Physical Activity and Sedentary Behavior During Adolescence
Nelson et al.
Pediatrics 2006;118:e1627-e1634.
ABSTRACT
| FULL TEXT
Estimating the Energy Gap Among US Children: A Counterfactual Approach
Wang et al.
Pediatrics 2006;118:e1721-e1733.
ABSTRACT
| FULL TEXT
Physical activity to prevent obesity in young children: cluster randomised controlled trial
Reilly et al.
BMJ 2006;333:1041-1041.
ABSTRACT
| FULL TEXT
Reducing Children's Television-Viewing Time: A Qualitative Study of Parents and Their Children
Jordan et al.
Pediatrics 2006;118:e1303-e1310.
ABSTRACT
| FULL TEXT
Food cravings, ethnicity and other factors related to eating out.
Siwik and Senf
J. Am. Coll. Nutr. 2006;25:382-388.
ABSTRACT
| FULL TEXT
Promoting Physical Activity in Children and Youth: A Leadership Role for Schools: A Scientific Statement From the American Heart Association Council on Nutrition, Physical Activity, and Metabolism (Physical Activity Committee) in Collaboration With the Councils on Cardiovascular Disease in the Young and Cardiovascular Nursing
Pate et al.
Circulation 2006;114:1214-1224.
FULL TEXT
Improving Pediatric Prevention via the Internet: A Randomized, Controlled Trial
Christakis et al.
Pediatrics 2006;118:1157-1166.
ABSTRACT
| FULL TEXT
Media and Child Health: Pediatric Care and Anticipatory Guidance for the Information Age.
Schmidt and Rich
Pediatr. Rev. 2006;27:289-298.
FULL TEXT
What Constitutes Successful Weight Management in Adolescents?
Dietz
ANN INTERN MED 2006;145:145-146.
FULL TEXT
Effects of Open-Loop Feedback on Physical Activity and Television Viewing in Overweight and Obese Children: A Randomized, Controlled Trial
Goldfield et al.
Pediatrics 2006;118:e157-e166.
ABSTRACT
| FULL TEXT
Obesity in childhood and adolescence: evidence based clinical and public health perspectives.
Reilly
Postgrad. Med. J. 2006;82:429-437.
ABSTRACT
| FULL TEXT
Translational Research in Childhood Obesity Prevention
Reynolds and Spruijt-Metz
Eval Health Prof 2006;29:219-245.
ABSTRACT
The APPLE project: An investigation of the barriers and promoters of healthy eating and physical activity in New Zealand children aged 5-12 years
Williden et al.
Health Education Journal 2006;65:135-148.
ABSTRACT
Active Healthy Living: Prevention of Childhood Obesity Through Increased Physical Activity
Council on Sports Medicine and Fitness and Council
Pediatrics 2006;117:1834-1842.
ABSTRACT
| FULL TEXT
Does Children's Screen Time Predict Requests for Advertised Products?: Cross-sectional and Prospective Analyses
Chamberlain et al.
Arch Pediatr Adolesc Med 2006;160:363-368.
ABSTRACT
| FULL TEXT
Television Viewing and Risk of Sexual Initiation by Young Adolescents
Ashby et al.
Arch Pediatr Adolesc Med 2006;160:375-380.
ABSTRACT
| FULL TEXT
Social Interactions in Adolescent Television Viewing
Fletcher
Arch Pediatr Adolesc Med 2006;160:383-386.
ABSTRACT
| FULL TEXT
Television Exposure and Overweight Risk in Preschoolers
Lumeng et al.
Arch Pediatr Adolesc Med 2006;160:417-422.
ABSTRACT
| FULL TEXT
|