Impact of Television Viewing Patterns on Fruit and Vegetable Consumption Among Adolescents
,||
* Health and Social Behavior
Epidemiology
Maternal and Child Health
|| Nutrition, Harvard School of Public Health, Boston, Massachusetts
 |
ABSTRACT |
|---|
 TOP ABSTRACT METHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
Background. National data indicate that children and youth do not meet Healthy People 2010 objectives for fruit and vegetable intake. Television viewing is hypothesized as a contributing factor because of its documented role in encouraging consumption of highly advertised foods that may lead to the replacement of fruits and vegetables.
Methods. A sample of 548 ethnically diverse students (average age: 11.7 ± 0.8 years) from public schools in 4 Massachusetts communities were studied prospectively over a 19-month period from October 1995 to May 1997. We examined the associations between baseline and change in hours of television and video viewing per day (the predictor variables) and change in energy-adjusted intake of fruits and vegetables by using linear regression analyses to control for potentially confounding variables and the clustering of observations within schools.
Findings. For each additional hour of television viewed per day, fruit and vegetable servings per day decreased (–0.14) after adjustment for anthropometric, demographic, dietary variables (including baseline percent energy from fat, sit-down dinner frequency, and baseline energy-adjusted fruit and vegetable intake), and physical activity. Baseline hours of television viewed per day was also independently associated with change in fruit and vegetable servings (–0.16).
Conclusions. Television viewing is inversely associated with intake of fruit and vegetables among adolescents. These associations may be a result of the replacement of fruits and vegetables in youths’ diets by foods highly advertised on television.
Key Words: television • adolescent • diet • fruits • vegetables
Abbreviations: CSFII, Continuing Surveys of Food Intakes by Individuals • BMI, body mass index • YAQ, Youth Activity Questionnaire • CI, confidence interval
Epidemiologic evidence indicates protective benefits of fruit and vegetable consumption against cardiovascular disease,1–4 diabetes,5,6 and various forms of cancer.7–9 The promotion of adequate dietary intake of fruit and vegetables by youth is reflected in Healthy People 2010 objectives for persons 
2 years old.10 However, recent national surveys indicate that children and adolescents in the United States fail to meet public health guidelines.11–15 The mean daily intake of vegetables among children 6 to 11 years old in 1989–1991 and 1994–1996 Continuing Surveys of Food Intakes by Individuals (CSFII) ranged from 2.2 to 2.4 servings daily, well below the US Department of Agriculture Food Guide Pyramid recommendation of 3 to 5 servings daily.15 Among adolescents 12 to 19 years old, males increased mean vegetable intakes from 3.4 to 3.7 servings over the 2 CSFII, whereas females continued to have inadequate intakes (2.7–2.8 servings). Moreover, 25% of the reported vegetables consumed by children and adolescents were french fries.14 Intakes of fruit documented in the 2 CSFIIs ranged from 1.1 to 1.5 servings daily among children and youth 6 to 19 years old, below the Food Guide Pyramid recommendation for 2 to 4 servings daily.15 Overall, only 1 in 5 children consumes 5 or more servings of fruit and vegetables daily.14
Various social and environmental factors are thought to contribute to the development of dietary habits among youth, including television viewing.12 However, to our knowledge, there are no studies that have examined the association between television viewing and fruit and vegetable intake among youth. Television is a ubiquitous source of entertainment and education among virtually all children and youth in the United States. Children spend more time viewing television than engaging in any other activity except sleep.16 Children 2 to 17 years old watch on average 22 hours/week of television.17 Television viewing has been linked to obesity in adolescents through cross-sectional18 and prospective observational studies19–21 as well as randomized, controlled trials.22,23 Television also seems to contribute to higher dietary fat intake.24,25 However, potential mechanisms through which television viewing leads to these health outcomes are only partially understood. Television viewing by children and youth is correlated with consumption of less nutrient-rich foods, and time spent viewing television is linked to consumption of foods advertised on television and children’s attempts to influence their parent’s food purchases.17,26 Because dietary habits formed in childhood are known to influence adult eating patterns,27 improved understanding of factors that influence children’s dietary behavior may guide interventions that reduce preventable morbidity and decrease the prevalence of premature mortality caused by chronic disease.
In the current study, we examined prospective observational evidence to determine the association between patterns of television viewing and fruit and vegetable consumption patterns in a cohort of 6th- and 7th-grade students from 4 communities in Massachusetts during 1995–1997.
|
METHODS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
Subjects
Data for this investigation were collected at baseline and 19 months later in Planet Health, a randomized, controlled intervention and evaluation project. Planet Health is an interdisciplinary health education program developed to reduce obesity by reducing television viewing, increasing moderate and vigorous physical activity, reducing intake of saturated fat, and increasing fruit and vegetable consumption. This analysis is limited to adolescents from the 5 control schools.22 Ten schools from 4 communities in the Boston, Massachusetts, metropolitan area were enrolled for the study between October 1995 and May 1997. Schools were matched by town or school size and ethnic composition and randomly assigned to either intervention (n = 5) or control (n = 5) status. The Committee on Human Subjects at the Harvard School of Public Health approved the study.
The median household income of the zip code areas where the control schools were located averaged $36 020 according to 1990 Census data. This median is lower than for all households in Massachusetts in the 1990 Census ($41 000) but similar to the US figure ($33 952).28 Subjects included in the present analysis 1) did not change schools at baseline, 2) were not in special education classes, 3) were in 6th or 7th grade at baseline, 4) had parental consent, and 5) completed the English-language version of the questionnaire.
Study Design
This prospective study utilizes data from the control arm of the randomized, controlled trial. Analyses evaluate the impact of television viewing on daily intake of fruits and vegetables among students in the 5 control schools. Surveys were administered to 6th and 7th graders, collecting demographic, physical activity, dietary, and television-viewing behavior measures at baseline (fall 1995) and follow-up (spring 1997). The primary hypothesis was that baseline television viewing and change in television viewing would be inversely associated with a change in daily intake of fruits and vegetables. In contrast to studies that involve the independent variable measured at one point in time, demonstrating that change in an independent variable predicts change in a dependent variable provides stronger evidence for causality.29
Measures
Demographic information on race/ethnicity, age, and gender were collected from students in participating schools. Ethnic origin was established on the basis of student responses to a multiple-choice question. Categories included white, black, Hispanic, Asian, American Indian, and other. Age was determined from date of birth and date of anthropometry. In the case of missing birth date, self-report of age from the student survey was used. Sex was established at the time of examination except in the case of missing data, where sex was obtained from school lists.
Baseline and follow-up anthropometry of 6th and 7th graders and follow-up anthropometry were collected in October 1995 and May 1997, respectively. Height without shoes was measured to the nearest 0.1 cm by using a Shorr stadiometer (Irwin Shorr, Olney, MD). Weight in light clothes was measured to the nearest 0.1 kg using a portable electronic scale calibrated with the Seca standard weights step-up test (Seca Model 770, Seca Corporation, Hanover, MD). Body mass index (BMI) was calculated by dividing weight in kilograms by the square of height in meters (kg/m2).
Exposure to television viewing was assessed by using an 11-item television and video measure.22 Questions were asked about typical hours of television viewed every day of the week in addition to use of videocassette recorders, movies, and video/computer games. The question concerning television asked: "Think for a moment about a typical weekday. Tell us how many hours you usually spend watching television shows on each day listed below. Include morning, afternoon, and evening programs. Don’t include videos and movies." Additional questions also asked about video games, computer games, and videos and movies. Question items were weighted and summed to obtain a total hour per day viewing estimate. A 9-item measure of only television viewing was also estimated. The relationship between the television measure and repeated 24-hour recalls in 1997 was estimated, and a deattenuated30 correlation for hours of television viewing per day (r = 0.54) was calculated.
Dietary intake, physical activity, and television viewing were measured by using a student food and activity questionnaire, which students completed independently in class under the supervision of teachers who participated in a 1-hour training session. Dietary measures and lifestyle patterns were obtained by using the Youth Food-Frequency Questionnaire. This questionnaire was adapted and validated for use in ethnically31 and socioeconomically32 diverse populations. The Youth Food-Frequency Questionnaire was used to assess dietary patterns such as percent energy from fat and fruit and vegetable consumption, total energy intake (in kJ), and percent energy intake from dietary fat. To be consistent with National Cancer Institute nutrition education guidelines, when calculating fruit and vegetable intake, we excluded french-fried potatoes.33 Additional behaviors of interest included measures of physical activity and frequency of family sit-down dinners.
Physical activity was assessed by using the Youth Activity Questionnaire (YAQ), which is a 16-item measure that estimates hours per day spent performing moderate and vigorous activities, defined as energy expenditure 3.5 metabolic equivalents34 over the past month. Walking was excluded because of suggestions of low validity found for this activity.35 The YAQ was adapted from a 14-item physical activity questionnaire that has demonstrated good reproducibility in a validation study of adults.36,37 In a repeat 24-hour validation sample among participants in Planet Health 1 month apart, the YAQ was correlated (deattenuated30) with the average of these 2 24-hour recalls at r = 0.80, with equivalent means. (Deattenuation provides a more accurate estimate of the relationship between variables by adjusting for the random error seen in measures.30) Although not a gold standard, the results comparing estimates with those based on repeat 24-hour recalls provide evidence of validity of the YAQ relative to other self-report measures.30 The YAQ question assessing physical activity reads as follows: "Think about these activities over the past 30 days. On average, how much time did you spend doing the following?" Activities in question include baseball or softball (with ranges of hours per week from none to 6), basketball, biking, etc (16 items).
Frequency of family sit-down dinners was based on a single question covering the number of dinners per week where the family eats together. Family dinner has been associated with healthful dietary patterns in children and youth 9 to 14 years old.38
Statistical Analysis
Statistical analyses were performed by using the statistical software SAS. The procedure SURVEYREG was used to estimate regressions that control for the design of the study with students clustered within schools. This procedure uses the same estimation approach as SUDAAN, an implicit Taylor linearization method, and takes into account the intraclass correlation of responses within schools.
We estimated regressions to control for variables that might confound associations between television viewing and fruit and vegetable intake. Fruit and vegetable intake measures were energy-adjusted by using the regression approach.39 To control for the potential confounding of the association between television viewing and fruit and vegetable intake with total energy intake, we adjusted for total energy intake (kJ daily) in all models.39 The rationale for this adjustment takes into account the fact that we are interested in the contribution of fruits and vegetables to a youths’ total dietary intake and the fact that total energy intake is associated with both television viewing and fruit and vegetable intake.
For descriptive purposes in Table 1 we report the mean servings of fruits and vegetables per day. Paired t tests were calculated to evaluate the change in daily servings between baseline and follow-up. The correlation between hours of television viewing at baseline and follow-up was evaluated, as was the percentage of the cohort who changed hours of viewing. All analyses were prospective and controlled for baseline fruit and vegetable consumption, baseline television viewing, and change in television viewing (follow-up in 1997 minus baseline in 1995). The dependent variable in both models was fruit and vegetable intake at follow-up (1997), and because we also controlled for baseline fruit and vegetable consumption, the models essentially predicted change in consumption. Model 1 included baseline energy-adjusted fruit and vegetable intake (1995), baseline television viewing (1995), and change in television viewing (between 1995 and 1997, BMI, demographic characteristics [age, sex, and ethnicity], school indicator variables [the largest school was the omitted variable]). Model 2 included the variables in model 1 plus baseline percent energy from fat (1995), frequency of sit-down dinners with parents, and hours of strenuous physical activity per day. We adjusted for the aforementioned covariates because of theoretical and empirical relationships to both diet and television viewing: frequency of sit-down dinners because of its association with healthy eating patterns;38 physical activity is theoretically associated with both more dietary intake as well as less television time; schools can be related to dietary habits because of differences in food services and access to vending machines; and, finally, percent energy from fat has been a focus of much dietary change in recent years and may be associated with fruit and vegetable intake. Regression analyses of change in fruit and vegetable intake separately were also conducted. All P values are 2-tailed.
|
|
RESULTS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
In October 1995, 780 children (64.5% of those eligible) completed the baseline evaluation, and follow-up data were obtained in May 1997 for 84% (654) of the baseline sample. Loss to follow-up was 18% (69) for girls and 14% (57) for boys. Lack of follow-up was most often caused by school transfer (50% of those not followed-up) and school absence (25%). Although complete data were available for 571 children, we excluded 23 children because of implausible daily energy intakes (
2090 kJ or 29 260 kJ), leaving 548 individuals for analysis. At baseline, the cohort was 48% (263) female, 63% (348) white, 15% (84) Hispanic, 14% (76) black, 8% (42) Asian, and 8% (46) American Indian or other. Additional descriptions of the school recruitment process, sampling plan, and comparison of those followed-up versus those who were not are detailed elsewhere.22 Informed consent was obtained from parents of all individuals as previously described.22
Table 1 displays baseline and follow-up anthropometric, dietary, and activity data (including television viewing and physical activity), and race/ethnicity. The mean age of participants at baseline was 11.7 years, with an average BMI of 20.7. Students reported an average of 4.23 servings/day of fruits and vegetables, which is below the recommendation of 5 servings/day. Subjects reported 
1.3 hours/day of moderate to vigorous physical activity. Follow-up measurements indicated mean total fruit and vegetable servings per day decreased from baseline by 0.33 servings/day or by 8%. This change in total servings of fruits and vegetables per day was statistically significant (P = .007). As expected, mean BMI increased between baseline and follow-up; however, reported strenuous physical activity and television viewing decreased. Approximately 29% of the cohort increased and 30% decreased hours of television viewing between baseline and follow-up. The baseline and follow-up viewing times were correlated (r = 0.51; P < .0001).
The regression coefficients in Table 2 demonstrate the association between change in television viewing (measured as the difference in total screen time reported at baseline and follow-up) and change in fruit and vegetable servings per day, controlling for baseline television viewing (measured as total screen time), baseline fruit and vegetable consumption, and with additional adjustment for potential confounders in each model. Controlling for physical activity, frequency of sit-down dinners, and percent fat intake had little effect on these relationships. In the fully adjusted model 2, fruit and vegetable intake decreased by 0.16 servings/day with each additional hour increase in television viewing at baseline (95% confidence interval [CI]: –0.22 to –0.10; P = .008) and decreased further by 0.14 servings/day (95% CI: –0.22 to –0.07; P = .025) for every hour increase in television viewing between baseline and follow-up.
|
We estimated the same regressions by using the variable measuring only television viewing (not including videos and computer games), and the results were essentially unchanged. By using the variable measuring television viewing only, model 1, the change in servings per 1 hour/day television at baseline was –0.20 (95% CI: –0.29 to –0.11; P = .01), and the change in servings per 1 hour/day television increase was –0.12 (95% CI: –0.21 to –0.03; P = .05). In model 2, the change in servings per 1 hour/day television at baseline was –0.19 (95% CI: –0.19 to –0.03; P = .05), and the change in servings per 1 hour/day television increase was –0.11 (95% CI: –0.28 to –0.10; P = .04). These results were expected given that the overall viewing variable was correlated with the television-only variable at r = 0.96.
We also performed regression analyses for change in fruit and vegetable intake separately. In the analyses of energy-adjusted fruit intake at baseline, the final model revealed that each additional hour of television viewing was associated with a decline in fruit intake of 0.074 servings/day (95% CI: –0.08 to –0.06; P = .0004). Each hourly increase in television viewing between baseline and follow-up was associated with decreased fruit intake of 0.053 servings/day (95% CI: –0.09 to –0.01; P = .06). The results of regression analyses for the relationship between television viewing and energy-adjusted vegetable intake were insignificant. In the final model, controlling for baseline BMI, demographic characteristics, percent fat, sit-down dinner, and hours of strenuous activity, vegetable intake decreased by 0.054 servings/day (95% CI: –0.12 to –0.01; P = .18) with each additional hour of television viewing at baseline and decreased by 0.061 servings/day (95% CI: –0.12 to –0.004; P = .11) for each hour increase in television viewing between baseline and follow-up.
|
DISCUSSION |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
Adolescent dietary behaviors may ultimately have a decisive impact on chronic disease risk in adulthood. It is already known that the atherosclerotic process associated with cardiovascular disease begins in childhood.40–42 Additionally, dietary habits formed in adolescence are known to influence adult eating patterns.27 From a public health perspective, improved understanding of the determinants of adolescent dietary behaviors is critical to the promotion of dietary habits that will reduce youth chronic disease risk. Our findings suggest that television viewing may contribute to a decline in fruit and vegetable consumption among adolescents. Each hourly increment of television viewing at baseline was associated with a decrease in energy-adjusted fruit and vegetable servings/day of 0.16 (or 1 serving every 6 days). Each additional hour increase in television viewing during the study period was associated with a decline of 0.14 energy-adjusted fruit and vegetable servings/day. Essentially, a young person who watched 3 hours/day of television at baseline (the mean in our study) and increased his/her television viewing by 1 hour/day had, on average, 2.25 fewer servings of fruits and vegetables per week, or
110 servings/year than those who did not watch television. In sum, fruit and vegetable consumption was negatively associated with hours of television viewing. Our prospective analyses indicated that both baseline television viewing and change in television viewing independently predicted a reduction in fruit and vegetable consumption.
What are the potential mechanisms through which television viewing may decrease fruit and vegetable consumption? Consider the role of televised advertisements. Children 2 to 11 years old are exposed to an average of 150 to 200 hours of commercial messages, or 20 000 commercials a year.43 Of these advertisements, studies have shown that 56% are for food.17 Television advertising includes intense marketing aimed at shaping nutritional beliefs, attitudes, and consumption patterns of youth, and little of this marketing is aimed at fruit and vegetables. Thus televised food advertisements may lead to misconceptions about the nutritional value of certain foods. Many food advertisements have misleading messages about the nutritional value of the products. A study of children’s television programming revealed that 49% of food advertisements had implicit messages that the food was nutritious or healthy,17 a second study found that >90% of cereal advertisements asserted that the food was part of a "balanced" or "complete" breakfast, and over half of all advertisements were for cereals and candies or other sweets.44 Kotz and Story replicated these findings over a decade later and found that 57% of all advertisements were for food, and of those, 44% of the foods advertised were classified in the fats, oils, and sweet food group.17 Children’s nutritional knowledge may be biased by these marketing strategies.45 Moreover, if television commercials prioritize non-nutritional characteristics of food as the most important food selection criteria, the consumer values of young viewers may be influenced negatively.43–46 These marketing strategies may encourage youth to replace fruits and vegetables with other products marketed as "nutritious" that in fact have low nutritional value. Research data demonstrate that the foods that are advertised most heavily are those that are overconsumed.25 Moreover, fruits and vegetables are rarely, if ever, advertised during children’s programming. Finally, youth may have unrealistic expectations of the consequences of poor dietary habits, because television stars are rarely obese and/or suffer from health conditions related to poor dietary habits.45
In interpreting the findings of the present study, it is important to acknowledge several limitations. First, causality cannot be proven because of the observational nature of the data we present. Although we have no reason to expect that decreased fruit and vegetable intake could lead to an increase in television viewing, a randomized, controlled trial that altered television viewing would provide the strongest proof of causality. Although we attempted to control for theoretically relevant predictors of fruit and vegetable consumption, there is a possibility that there are unmeasured factors that influence dietary practices. Because of the limited measures available, we were not able to control for all individual habits/behaviors nor all social and environmental influences that could potentially influence both television viewing and fruit and vegetable intake. Although it is possible that health behaviors are clustered among youth (ie, youth with lower television viewing also have better health behaviors generally but not causally), our analyses demonstrate a relationship between change in television viewing over time and fruit and vegetable intake, which makes this explanation less probable. In addition, assessment of television viewing by self-report is potentially error-prone or limited by the validity of the measures. Alternatively, random error in the measurement of television viewing could lead to underestimation of actual effects. Finally, the generalizability of the study sample to all adolescents may be limited because of the nature of our sample.
There are several strengths of this study. The prospective research design allows us to demonstrate a temporal association between television viewing and dietary patterns. Moreover, we were able to control for baseline fruit and vegetable consumption and television viewing as well as other empirically and theoretically relevant determinants of fruit and vegetable consumption. Finally, the results of our study are consistent with a plausible mechanism whereby television viewing can affect food preferences and/or intake.
This study contributes to the literature on the impact of television viewing on health outcomes. Given the findings in the current study, greater attention to the form and content of advertising during television programming for minors should be encouraged. Television can be used as a medium for disseminating healthy national diet and nutritional recommendations rather than persuading children to adopt eating practices contrary to national recommendations.47 Increasing healthful infomercials to encourage fruit and vegetable consumption may be one approach to counteracting advertising. However, as long as market forces determine the content of televised advertisements, the promotion of healthy dietary practices will likely be undermined.
The Annenberg reports have shown consistently that >75% of parents interviewed are unconcerned with the amount of television their children watch.48 It is essential that parents are informed of the potential impact television viewing may have on their children to limit viewing to 2 hours/day as recommended by the American Academy of Pediatrics49 and encourage reduced consumption of advertised foods. Pediatricians can play a crucial role in this effort.50,51 Second, youth should be aware of the goal of advertisements to become informed consumers. In 1992, the American Academy of Pediatrics recommended the eradication of televised food advertising toward children.52 A primary prevention strategy might reduce or regulate the food industry’s targeted social marketing to children by revisiting this proposal on a national level. Perhaps one of the most easily modifiable causes of poor dietary habits would begin with evaluation of targeted social marketing by the food industry toward children and youth. This study suggests that the development of a population-based approach to improving dietary habits may benefit from additional investigation into the effect of televised advertisements on adolescents’ attitudes, food preferences, and diet.
Future research studies should attempt to disentangle the extent to which the influence of televised commercial advertisements is related to the amount of television viewed in a dose-response or if there is a threshold effect. Another important research question concerns the ages or developmental stages during which television advertising has the greatest impact on current and future eating behaviors. Clearly, there is a need to develop a theoretical framework able to encompass the role of social and environmental influences such as television on dietary habits. In particular, this framework should consider the influence of political and economic institutions on health outcomes. The social production of disease framework, as articulated by Doyal,53 would posit that fruit and vegetable consumption is influenced by targeted social marketing toward children through commercials and advertisements commissioned by the food manufacturers. Social marketing by the food industry is targeted at children and youth with the intention of obtaining their consumer support. The social production of disease framework is particularly suited to evaluate the effect of political and economic forces and institutions on health outcomes including preventive health behaviors.
|
CONCLUSIONS |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
Studies have demonstrated that the content commercial advertisements broadcast during children’s television programming promotes food-consumption patterns that contradict the national dietary recommendations.17 This article has presented empirical evidence for and outlined several mechanisms through which unhealthy dietary habits can be reinforced by these advertisements. Future studies are needed to provide empirical evidence of the relationship between the content of television programming and nutritional intake.
|
ACKNOWLEDGMENTS |
|---|
This work was supported by the National Institutes of Child Health and Human Development (HD-30780), Centers for Disease Control and Prevention (Prevention Research Centers grant U48/CCU115807), and National Institutes of Health (Public Health Training grant R25 GM55353).
|
FOOTNOTES |
|---|
Received for publication Oct 1, 2002; Accepted Mar 27, 2003.
Reprint requests to (R.B.-J.) Department of Society, Human Development, and Health, 677 Huntington Ave, Boston, MA 02115. E-mail: rboynton{at}hsph.harvard.edu
This work is solely the responsibility of the authors and does not represent official views of the Centers for Disease Control and Prevention or other granting institutions.
|
REFERENCES |
|---|
|
TOPABSTRACTMETHODSRESULTSDISCUSSIONCONCLUSIONSREFERENCES |
|---|
- Renaud S. Diet and stroke. J Nutr Health Aging.2001; 5 :167 –172[Medline]
- Renaud S, Lanzmann-Petithory D. Coronary heart disease: dietary links and pathogenesis. Public Health Nutr.2001; 4 :459 –474[Medline]
- Hu F, Leitzmann M, Stampfer M, et al. Physical activity and television watching in relation to risk for type 2 diabetes mellitus in men.
Arch Intern Med.2001; 161
:1542
–1548
[Abstract/Free Full Text] - Hu F, Manson JE, Willett WC. Types of dietary fat and risk of coronary heart disease: a critical review.
J Am Coll Nutr.2001; 20
:5
–19
[Abstract/Free Full Text] - Ford E, Mokdad AH. Fruit and vegetable consumption and diabetes mellitus incidence among U. S. adults. Prev Med.2001; 32 :33 –39[CrossRef][Web of Science][Medline]
- Lindquist C, Gower B, Goran M. Role of dietary factors and ethnic differences in early risk of cardiovascular disease and type 2 diabetes.
Am J Clin Nutr.2000; 71
:725
–732
[Abstract/Free Full Text] - Harvard report on cancer prevention. Causes of human cancer. Dietary factors. Cancer Causes Control.1996; 7(suppl 1) :S7 –S9
- La Vecchia C, Tavani A. Fruit and vegetables, and human cancer. Eur J Cancer Prev.1998; 7 :3 –8[Web of Science][Medline]
- Steinmetz K, Potter J. Vegetables, fruit, and cancer. I. Epidemiology. Cancer Causes Control.1991; 2 :325 –357[CrossRef][Web of Science][Medline]
- US Department of Health and Human Services. Healthy People 2010: Understanding and Improving Health. Washington, DC: US Department of Health and Human Services, Government Printing Office; 2000
- Kann L, Warrren C, Harris W, et al. Youth risk behavior surveillance—United States 1993. J Sch Health.1995; 65 :163 –171[Web of Science][Medline]
- Neumark-Sztainer D, Story M, Resnick M, Blum R. Correlates of inadequate fruit and vegetable consumption among adolescents. Prev Med.1996; 25 :497 –505[CrossRef][Web of Science][Medline]
- Patterson B, Block B, Rosenberger W, et al. Fruit and vegetables in the American diet: data from the NHANES II survey.
Am J Public Health.1990; 80
:1443
–1449
[Abstract/Free Full Text] - Krebs-Smith S, Cook A, Subar A, et al. Fruit and vegetable intakes of children and adolescents in the United States.
Arch Pediatr Adolesc Med.1996; 150
:81
–86
[Abstract/Free Full Text] - Dixon LB, Cronin FJ, Krebs-Smith SM. Let the pyramid guide your food choices: capturing the total diet concept.
J Nutr.2001; 131
:461S
–472S
[Abstract/Free Full Text] - Dietz W, Strasburger VC. Children, adolescents, and television. Curr Probl Pediatr Adolesc Health Care.1991; 21 :8 –32
- Kotz K, Story M. Food advertisements during children’s Saturday morning television programming: are they consistent with dietary recommendations? J Am Diet Assoc.1994; 94 :1296 –1300[CrossRef][Web of Science][Medline]
- Andersen RE, Crespo CJ, Bartlett SH, 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; 278 :938 –942
- Dietz W, Gortmaker SL. Do we fatten our children at the TV set? Obesity and television viewing in children and adolescents.
Pediatrics.1985; 75
:807
–812
[Abstract/Free Full Text] - Gortmaker S, 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
[Abstract/Free Full Text] - Berkey C, Rockett HR, Field AE, et al. Activity, dietary intake, and weight changes in a longitudinal study of preadolescent and adolescent boys and girls. Pediatrics.2000; 105(4) . Available at: http://www.pediatrics.org/cgi/content/full/105/4/e56
- Gortmaker S, Peterson K, Wiecha J, et al. Reducing obesity via a school-based interdisciplinary intervention among youth.
Arch Pediatr Adolesc Med.1999; 153
:409
–418
[Abstract/Free Full Text] - Robinson T. Reducing children’s television viewing to prevent obesity, a randomized controlled trial.
JAMA.1999; 282
:1561
–1567
[Abstract/Free Full Text] - French S, Story M, Jeffery R. Environmental influences on eating and physical activity. Annu Rev Public Health.2001; 22 :309 –335[CrossRef][Web of Science][Medline]
- Jeffery R, French S. Epidemic obesity in the United States: are fast foods and television viewing contributing?
Am J Public Health.1998; 88
:277
–280
[Abstract/Free Full Text] - Story M. Study group report on the impact of television on adolescent nutritional status. J Adolesc Health Care.1990; 11 :82 –85[CrossRef][Medline]
- Kelder S, Perry C, Klepp K, Lytle L. Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors.
Am J Public Health.1994; 84
:1121
–1126
[Abstract/Free Full Text] - Anonymous. Statistical Abstract of the United States: 1996. Washington, DC: US Bureau of the Census; 1998
- Cook T, Campbell D. Quasi-Experimentation: Design and Analysis for Field Settings. New York, NY: Rand McNally; 1979
- Rosner B, Willett WC. Interval estimates for correlation coefficients corrected for within-person variation: implications for study design and hypothesis testing.
Am J Epidemiol.1988; 127
:377
–386
[Abstract/Free Full Text] - Fields A, Peterson KE, Gortmaker SL, et al. Reproducibility and validity of a food frequency questionnaire among fourth to seventh grade inner-city school children: implications for day to day variation in dietary intake. Public Health Nutr.1999; 2 :293 –300[Medline]
- Rockett H, Breitenbach M, Frazier AL, et al. Validation of a youth/adolescent food frequency questionnaire. Prev Med.1997; 26 :808 –816[CrossRef][Web of Science][Medline]
- Subar A, Heimendinger J, Patterson BH, Krebs-Smith SM, Pivonka E, Kessler R. Fruit and vegetable intake in the United States: the baseline survey of the five-a-day for better health program. Am J Health Promot.1995; 9 :352 –360[Web of Science][Medline]
- Ainsworth B, 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[Web of Science][Medline]
- Peterson K, Field AE, Fox MK, et al. Validation of YRBSS Questions on Dietary Behaviors and Physical Activity Among Adolescents in Grades 9–12. Atlanta, GA: Prepared for Centers for Disease Control and Prevention, Division of Adolescent and School Health; 1996
- Wolf A, Hunter DJ, Colditz GA, et al. Reproducibility and validity of a self-administered physical activity questionnaire.
Int J Epidemiol.1994; 23
:991
–999
[Abstract/Free Full Text] - Chasen-Taber S, Rimm EB, Stampfer MJ, et al. Reproducibility and validity of a self-administered physical activity questionnaire for male health professionals. Epidemiology.1996; 7 :81 –86[Web of Science][Medline]
- Gillman MW, Rifas-Shiman SL, Frazier AL, et al. Family dinner and diet quality among older children and adolescents.
Arch Fam Med.2000; 9
:235
–240
[Abstract/Free Full Text] - Willett WC. Nutritional Epidemiology. 2nd ed. New York, NY: Oxford University Press; 1998
- Berenson G, Srinivasan SR. Emergence of obesity and cardiovascular risk for coronary artery disease: the Bogalusa heart study. Prev Cardiol.2001; 4 :116 –121[Medline]
- Daniels S. Cardiovascular disease risk factors and atherosclerosis in children and adolescents. Curr Atheroscler Rep.2001; 3 :479 –485[Medline]
- American Academy of Pediatrics, Committee on Nutrition. Cholesterol in childhood.
Pediatrics.1998; 101
:141
–147
[Abstract/Free Full Text] - Schneider C. Children’s Television. Lincolnwood, IL: NTC Business Books; 1989
- Barcus FE. Children’s Television: An Analysis of Programming and Advertising. New York, NY: Praeger Publishers; 1977
- Gunter B, McAleer J. Children and Television. London, United Kingdom: Routledge; 1990
- Macklin M, Carlson L. Advertising to Children. Thousand Oaks, CA: Sage; 1999
- Foerster S, Kizer KW, Disogra LK, Bal DG, Krieg BF, Bunch KL. Links. California’s "5 a day—for better health!" campaign: an innovative population-based effort to effect large-scale dietary change. Am J Prev Med.1995; 11 :124 –131[Web of Science][Medline]
- Stanger J, Gridina N. Media in the Home 1999: The Fourth Annual Survey of Parents and Children. Philadelphia, PA: University of Pennsylvania, Annenberg Public Policy Center; 1998
- American Academy of Pediatrics. Television and the Family. Elk Grove Village, IL: American Academy of Pediatrics; 1986
- American Academy of Pediatrics, Committee on Communications. Children, adolescents, and advertising.
Pediatrics 1995; 95
:295
–297
[Abstract/Free Full Text] - American Academy of Pediatrics, Committee on Public Education. Children, adolescents, and television.
Pediatrics 2001; 107
:423
–426
[Abstract/Free Full Text] - American Academy of Pediatrics, Committee on Communications. The commercialization of children’s television.
Pediatrics 1992; 89
:343
–344
[Abstract/Free Full Text] - Doyal L. The Political Economy of Health. Boston, MA: South End Press; 1979
PEDIATRICS (ISSN 1098-4275). ©2003 by the American Academy of Pediatrics
CiteULike 
Connotea 
Del.icio.us 
Digg 
Facebook 
Reddit 
Technorati 
Twitter What's this?
This article has been cited by other articles:
|
|
 |
|
  C. Lazarou and E. S. Soteriades Children's physical activity, TV watching and obesity in Cyprus: the CYKIDS study Eur J Public Health, June 25, 2009; (2009) ckp093v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. Ball, A. MacFarlane, D. Crawford, G. Savige, N. Andrianopoulos, and A. Worsley Can social cognitive theory constructs explain socio-economic variations in adolescent eating behaviours? A mediation analysis Health Educ. Res., June 1, 2009; 24(3): 496 - 506. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S V Galcheva, V M Iotova, and V K Stratev Television food advertising directed towards Bulgarian children Arch. Dis. Child., October 1, 2008; 93(10): 857 - 861. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Tanner, S. Duhe, A. Evans, and M. Condrasky Using Student-Produced Media to Promote Healthy Eating: A Pilot Study on the Effects of a Media and Nutrition Intervention Science Communication, September 1, 2008; 30(1): 108 - 125. [Abstract] [PDF]
|
|
|
|
 |
|
 D. J. Barr-Anderson, P. van den Berg, D. Neumark-Sztainer, and M. Story Characteristics Associated With Older Adolescents Who Have a Television in Their Bedrooms Pediatrics, April 1, 2008; 121(4): 718 - 724. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Chernin The Effects of Food Marketing on Children's Preferences: Testing the Moderating Roles of Age and Gender The ANNALS of the American Academy of Political and Social Science, January 1, 2008; 615(1): 101 - 118. [Abstract] [PDF]
|
|
|
|
|
|
N. F. Krebs, J. H. Himes, D. Jacobson, T. A. Nicklas, P. Guilday, and D. Styne Assessment of Child and Adolescent Overweight and Obesity Pediatrics, December 1, 2007; 120(Supplement_4): S193 - S228. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
B. A. Spear, S. E. Barlow, C. Ervin, D. S. Ludwig, B. E. Saelens, K. E. Schetzina, and E. M. Taveras Recommendations for Treatment of Child and Adolescent Overweight and Obesity Pediatrics, December 1, 2007; 120(Supplement_4): S254 - S288. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. Caballero The Global Epidemic of Obesity: An Overview Epidemiol. Rev., June 13, 2007; (2007) mxm012v1. [Full Text] [PDF]
|
|
|
|
 |
|
 L. M. Mauriello, M. M. H. Driskell, K. J. Sherman, S. S. Johnson, J. M. Prochaska, and J. O. Prochaska Acceptability of a School-Based Intervention for the Prevention of Adolescent Obesity The Journal of School Nursing, October 1, 2006; 22(5): 269 - 277. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. E. Schmidt and M. Rich Media and Child Health: Pediatric Care and Anticipatory Guidance for the Information Age. Pediatr. Rev., August 1, 2006; 27(8): 289 - 298. [Full Text] [PDF]
|
|
|
|
 |
|
 J. L. Wiecha, K. E. Peterson, D. S. Ludwig, J. Kim, A. Sobol, and S. L. Gortmaker When Children Eat What They Watch: Impact of Television Viewing on Dietary Intake in Youth Arch Pediatr Adolesc Med, April 1, 2006; 160(4): 436 - 442. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
American Heart Association, S. S. Gidding, B. A. Dennison, L. L. Birch, S. R. Daniels, M. W. Gilman, A. H. Lichtenstein, K. T. Rattay, J. Steinberger, N. Stettler, et al. Dietary Recommendations for Children and Adolescents: A Guide for Practitioners Pediatrics, February 1, 2006; 117(2): 544 - 559. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Endorsed by the American Academy of Pediatrics, S. S. Gidding, B. A. Dennison, L. L. Birch, S. R. Daniels, M. W. Gilman, A. H. Lichtenstein, K. T. Rattay, J. Steinberger, N. Stettler, et al. Dietary Recommendations for Children and Adolescents: A Guide for Practitioners: Consensus Statement From the American Heart Association Circulation, September 27, 2005; 112(13): 2061 - 2075. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Kline Countering Children's Sedentary Lifestyles: An evaluative study of a media-risk education approach Childhood, May 1, 2005; 12(2): 239 - 258. [Abstract] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
