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Associations of Television Content Type and Obesity in Children

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We tested the associations of content types of children's television viewing with subsequent body mass index (BMI) to assess the plausibility of different causal pathways. We used time-use diary data from the Panel Survey of Income Dynamics to measure television viewing categorized by format and educational and commercial content. Analyses were stratified by age because children younger than 7 years are less able to understand the persuasive intent of advertising. BMI z scores in 2002 were regressed on television viewing, sociodemographic variables, mother's BMI, and BMI in 1997 (for older children only). Among children aged 0 to 6 years in 1997, commercial viewing in 1997 was significantly associated with BMI z scores in 2002 in fully adjusted regressions. Among children older than 6 years, commercial viewing in 2002 was associated with 2002 BMI. These results were robust after adjustment for exercise and eating while watching television. The evidence does not support the contention that television viewing contributes to obesity because it is a sedentary activity. Television advertising, rather than viewing per se, is associated with obesity.
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Associations of Television Content Type and Obesity in Children
Frederick J. Zimmerman, PhD, and Janice F. Bell, PhD, MN, MPH
Obesity continues to be a major public health
concern for America’s children, with obesity
rates for preschool children tripling in the past
30 years and quadrupling for children aged 6
to 11 years.
1
Television viewing has been shown to be
associated with obesity cross-sectionally
2–8
and in longitudinal data in many,
9–14
but not
all,
15–17
studies. Comprehensive literature re-
views of these disparate results conclude that the
association between television viewing and
obesity is on average small, but negative.
18,19
A constructive way to reconcile the dispa-
rate findings is to recognize that different
kinds of television content may exert different
effects on obesity. Television might lead to
obesity through 3 primary pathways
20,21
:by
displacing time that would otherwise be spent in
physical activity; by promoting eating while
viewing, which may foster both lower-quality
and higher-quantity food intake; and by exposing
children to food advertising, which adversely
affects their diets.
These pathways have quite different impli-
cations for the ways different kinds of televi-
sion content might affect obesity. The hy-
potheses involving displacement of physical
activity and eating while viewing suggest that
all types of television have an equal and
significant effect on obesity. If the adver-
tising hypothesis is more accurate, only com-
mercial television viewing should be associ-
ated with obesity and not noncommercial
television or DVD viewing. Of course, all
pathways might be operative, in which case we
would expect significant associations between
all types of content and obesity but associa-
tions of greater magnitude for commercial
content.
A review of the literature on the role of
media in childhood obesity identified no
scholarly articles analyzing the associations of
different types of television content with obe-
sity status in children.
22
We used nationally
representative longitudinal data to analyze the
effects of different kinds of television content on
body mass index (BMI).
METHODS
We used data from the Panel Survey of
Income Dynamics, a longitudinal study over-
seen by the National Science Foundation that
began in 1968 with a variety of funding sources
and 4800 families. In 1997 the study added
the Child Development Supplement, a ques-
tionnaire administered to the primary care-
givers of 3563 children aged 0 to 12 years.
23
The questionnaire, funded by the National In-
stitute of Child Health and Human Development,
included detailed demographic data, psycholog-
ical and behavioral assessment of parents and
children, and time-use diary data from1 ran-
domly chosen weekday and 1 randomly chosen
weekend day during a school year (September–
May). Such time-use diaries have been used
extensively in research and have shown excellent
validity in comparisons with direct observation of
activities.
24,25
In 2002, the respondents to the
first questionnaire were followed up with a sec-
ond, similar instrument.
Time-use diaries were completed by 2569
families in 2002. Of these, 376 did not com-
plete the 1997 diaries, and an additional 92
were not assessed for BMI or were missing data
for important covariates. Missing values were
dealt with by case-wise deletion, which in
observational data results in minimal bias.
Twenty-four underweight children (BMI <12
kg/m
2
) were dropped from the analyses, leav-
ing an analysis sample of 2037.
Outcomes and Variables
The outcome measure was BMI (defined as
weight in kilograms divided by height in meters
squared), converted to zscores according to
2000 growth charts published by the Centers
for Disease Control and Prevention.
26
We used
BMI zscores rather than absolute BMI because
children’s height and weight increase as part of
normal development and because our sample
comprised boys and girls of different ages. In the
2002 wave of the Child Development Supple-
ment, both height and weight were measured. In
1997, the height of children 5 years and older
was measured, and their weight was recorded
from parental report. BMI data were not avail-
able for children younger than 5 years in 1997.
The time-use diaries in both 1997 and 2002
asked parents to report their child’s activities
throughout the course of an entire weekday
and an entire weekend day. When the activity
Objectives. We tested the associations of content types of children’s television
viewing with subsequent body mass index (BMI) to assess the plausibility of
different causal pathways.
Methods. We used time-use diary data from the Panel Survey of Income
Dynamics to measure television viewing categorized by format and educational
and commercial content. Analyses were stratified by age because children
younger than 7 years are less able to understand the persuasive intent of
advertising. BMI zscores in 2002 were regressed on television viewing, socio-
demographic variables, mother’s BMI, and BMI in 1997 (for older children only).
Results. Among children aged 0 to 6 years in 1997, commercial viewing in 1997
was significantly associated with BMI zscores in 2002 in fully adjusted re-
gressions. Among children older than 6 years, commercial viewing in 2002 was
associated with 2002 BMI. These results were robust after adjustment for
exercise and eating while watching television.
Conclusions. The evidence does not support the contention that television
viewing contributes to obesity because it is a sedentary activity. Television
advertising, rather than viewing per se, is associated with obesity. (Am J Public
Health. 2010;100:334–340. doi:10.2105/AJPH.2008.155119)
RESEARCH AND PRACTICE
334 |Research and Practice |Peer Reviewed |Zimmerman and Bell American Journal of Public Health |February 2010, Vol 100, No. 2
involved watching television in any format, the
parents were asked to report the format (i.e.,
television or DVD or video) and the name of
the show watched. We used these data to
classify hours of television viewing per day into
5 collectively exhaustive and mutually exclu-
sive categories.
27,28
Educational viewing on broadcast or cable.
The content of these programs was determined
to have an educational objective. The majority
of these shows were aired by the Public
Broadcasting System. The others were pre-
sented without in-program commercials. Many
of these shows, including Sesame Street,Barney,
and Blue’s Clues, included content about nutri-
tion or the value of physical activity.
29
The
shows often included sponsorship messages in
interstitials (brief announcements between pro-
grams), and the sponsors were sometimes food
corporations such as McDonald’s. Children
viewing this content type were exposed to
potentially beneficial anti-obesity messages
but also to pseudo-advertising through inter-
stitials.
Educational viewing on video or DVD. Only
the format differed from the first category; the
content was educational by the same definition.
Although DVDs occasionally included adver-
tising trailers, they rarely included food adver-
tising. Children viewing this content type were
exposed to potentially beneficial anti-obesity
messages and not to pseudo-advertising
through interstitials.
Entertainment viewing on video or DVD.
Examples of noneducational programs were
Scooby Doo and The Little Mermaid. Children
viewing this content type were not exposed to
commercials during or between programs, but
they were also not exposed to anti-obesity
messages, and they may have been exposed to
marketing tie-ins to food products.
Children’s entertainment viewing on broadcast
or cable. Noneducational programming almost
always included in-program commercials.
Product placement was banned in shows tar-
geted at children. Children viewing this content
type were exposed to in-program commercials
but not product placement.
General-audience entertainment viewing on
broadcast or cable. Children viewing this con-
tent type were exposed to in-program com-
mercials and to product placement of obeso-
genic foods.
If the association between television viewing
and obesity operates by reducing physical
activity, the association should be weakened
when the amount of the child’s physical activity
is controlled. Accordingly, we included mea-
sures of exercise in our analyses. Physical
exercise was captured through the time-use
diaries. We categorized a child’s exercise time,
the average number of minutes per day spent
in either moderate or vigorous physical activity,
as (1) no reported exercise, (2) total moderate
and vigorous activity averaging 1to 30 minutes
per day, or (3) total moderate and vigorous
activity averaging more than 30 minutes per
day.
Our analyses controlled for several other
children’s and family attributes that may affect
both television viewing and a variety of health
behaviors associated with obesity: the child’s
gender, age, and race/ethnicity, and the
mother’s BMI (self-reported in 1999) and edu-
cation. We included the average duration of
sleep, calculated from time-use diary data, to
control for the possibility that television view-
ing reduces sleep time,
30
whichinturnmaylead
to obesity. Sampling weights were used to permit
inferences valid for the population.
Statistical Analysis
We split the sample into 2 age groups,
younger than 7 years and 7 years and older,
with separate multivariate linear regressions
for each group. Young children are unable to
distinguish television advertising from the
program that surrounds it, and children youn-
ger than 7 years are not able to understand that
the intent of advertising is to sell them things
they would otherwise not want.
31–3 3
The differences in the 5 content types would
be expected to exert different effects on obe-
sity: if sponsorship interstitials have a mean-
ingful effect on obesity, associations of obesity
should be significantly greater with broadcast
educational television than with video educa-
tional television. If the anti-obesity messages
of educational television have a meaningful
effect on obesity, associations should be sig-
nificantly greater with video entertainment
television than with video educational televi-
sion. If product placement has a meaningful
effect on obesity, associations should be sig-
nificantly greater with children’s broadcast
entertainment than with general-audience
broadcast entertainment. If in-program com-
mercials have a meaningful effect on obesity,
associations should be significantly greater with
the video and educational categories than with
the broadcast entertainment categories. We
tested these expectations statistically and com-
bined categories when coefficients did not
differ significantly.
To test whether the effect of television
content types was independent of the effects of
exercise, we included the 1997 and 2002
values of these variables in subsequent re-
gressions. To test whether the television–obe-
sity relationship was mediated by eating in
front of the television, subsequent regressions
included a variable for 2002 indicating how
often the child was permitted to eat in front of
the television.
It is possible that an association between
early television viewing and subsequent obe-
sity reflects an unmeasured preference of
obese children to watch television. To mitigate
this possibility, we controlled for baseline BMI
of older children.
RESULTS
Table 1 shows the descriptive statistics of the
variables. Children younger than 7 years in
1997 watched an average of 0.88 hours per
day of commercial television and 0.74 hours
per day of noncommercial television. Children
aged 7 years and older in 1997 watched an
average of 1.47 hours per day of commercial
television in 1997 and 0.48 hours per day of
noncommercial television. Between 1997 and
2002, viewing of noncommercial television
decreased and viewing of commercial televi-
sion increased.
Among the younger children, associations
with obesity did not differ significantly between
broadcast educational television and video
educational television (P=.42), between video
entertainment television and video educational
television (P=.61), or between children’s
broadcast entertainment television and general
audience broadcast entertainment television
(P=.33).
Among the older children, associations with
obesity did not differ significantly between
broadcast educational television and video
educational television (P=.06), video enter-
tainment television and video educational
RESEARCH AND PRACTICE
February 2010, Vol 100, No. 2 |American Journal of Public Health Zimmerman and Bell |Peer Reviewed |Research and Practice |335
television (P=.33), or children’s broadcast
entertainment television and general audience
broadcast entertainment television (P= .37;
data not shown but available on request).
To improve model efficiency, we consoli-
dated the viewing categories into 2 categories:
commercial viewing (consisting of children’s
broadcast entertainment and general-audience
broadcast entertainment) and noncommercial
viewing (consisting of broadcast educational
television, video educational television, and
video entertainment television).
Table 2 shows the results of regressions of
BMI zscores on these 2 viewing categories. For
children younger than 7 years in 1997, each
hour per day of commercial viewing in1997 was
significantly associated with a 0.11 increase in
BMI zscores in 2002, after control for socio-
demographic covariates, including mother’s BMI
(Table 2). No other category of television viewing
had a significant association with zscores.
These results were robust to the inclusion of
physical activity and eating while watching tele-
vision (Table 2). The frequency of eating infront
of the television was not itself significant.
For children aged 7 years or older in 1997,
none of the television-viewing variables had
significant effects when included without the
child’s baseline BMI or the potential mediators,
although the effect of commercial television
viewing in 2002 showed a trend toward
significance (P=.06). Because of the concern
that more obese children may favor watching
television, we performed a regression that
included the child’s baseline BMI (Table 3).
In this regression, the magnitude of the
association with 2002 commercial content
was similar, but the effect became statistically
significant. None of the other content
categories had significant effects. These
results remained significant when physical
activity and eating while watching television
were controlled. Eating in front of the televi-
sion was not independently associated with
obesity.
DISCUSSION
Television has often been presented as
a sedentary activity in academic research and
policy pronouncements. In the popular
imagination this presumption is conveyed in
the term couch potato.
19
Our results strongly
challenge this perception. In our analysis, only
viewing of commercial content—programs in
which children are exposed to in-program
advertisements—was associated with obesity.
Moreover, this result remained when we con-
trolled for several potential confounders (the
mother’s BMI, the mother’s educational level,
and the amount of the child’s sleep).
In these regressions, the mother’s BMI was
a proxy for both the diet and physical activity
patterns in the household, as well as genetic
factors that might influence the child’s BMI.
For the older children, the results were not
moderated when the child’s baseline BMI
was controlled. Commercial viewing was
a significant predictor of children’s obesity
even with these controls, strongly suggesting
that the viewing–obesity relationship is not
confounded by other variables but is in fact
causal.
By contrast, viewing of noncommercial
television (educational television presented
without in-program commercials or videos
or DVDs) had no statistically significant
association with subsequent or concurrent
obesity.
Our findings are consistent with previous
research.
15, 3 4
Most convincingly, 2 randomized
trials of interventions to reduce television
viewing found statistically significant effects on
calorie intake and obesity but not on physical
activity.
35,36
Theresultsofthesetrials,
together with the evidence from our very dif-
ferent approach, make a strong case that televi-
sion viewing does not affect obesity through
a pathway involving reduced physical activity.
These results imply that it is the viewing of
television advertisements for foods of low nutri-
tional quality that leads to obesity, not television
watching per se.
Consistent with expectations that children’s
cognitive ability to understand advertising dif-
fers by age—roughly before and after age 7
years—we found a slightly stronger association
of commercial content with obesity before 7
years of age than after.
Food marketers spend $10 billion a year on
their efforts to influence children’s diets, and
most of this is for television advertising.
37
Food
is the most commonly advertised product on
TABLE 1—Children’s BMI and Television Viewing: Panel Survey of Income Dynamics,
1997–2002
Children Aged 0–6 Years in 1997 Children Aged 7–13 Years in 1997
Children
Observed, No.
%or
Mean (SD)
Children
Observed, No.
%or
Mean (SD)
BMI zscore in 1997 836 0.28 (1.34)
BMI zscore in 2002 1118 0.60 (1.14) 915 0.58 (1.13)
Television viewing in 1997, h/d
Commercial 1118 0.88 (1.11) 915 1.47 (1.25)
Noncommercial 1118 0.74 (0.95) 915 0.48 (0.70)
Television viewing in 2002, h/d
Commercial 1118 1.54 (1.25) 915 1.75 (1.58)
Noncommercial 1118 0.49 (0.73) 915 0.45 (0.77)
Physical activity in 1997, min/d
None 1118 27.3 915 22.2
1–30 1118 19.1 915 17.0
> 30 1118 53.6 915 60.8
Physical activity in 1997, min/d
None 1118 39.9 915 51.1
1–30 1118 17.8 915 10.9
> 30 1118 42.3 915 38.0
Eating in front of the television in 2002
a
1114 2.50 (1.31) 914 2.77 (1.40)
Note. BMI = body mass index.
a
Frequency score on a 5-point Likert scale.
RESEARCH AND PRACTICE
336 |Research and Practice |Peer Reviewed |Zimmerman and Bell American Journal of Public Health |February 2010, Vol 100, No. 2
children’s television.
38–42
Children younger than
5 years see an average of more than 4000
television commercials for food each year, or
about 30 hours’ worth.
38
During Saturday
morning cartoons, children see an average of 1
food ad every 5 minutes.
43
The vast majority of
foods commonly advertised on television—up
to 95% in 1 study
39
—are of poor nutritional
value.
37,38,40,41,44–49
Abundant short-term experimental
evidence shows that advertising for food of
poor nutritional quality has a strong influence
on children’s food preferences. Randomized
experiments with children in preschool and
first grade have shown that children ex-
perimentally exposed even to relatively few
commercials are more likely than unexposed
children to have positive attitudes toward
and to choose the advertised foods over alter-
natives.
50–53
Moreover, 1 study found that
children exposed to advertising were also
more likely than were participants in a control
group to choose nonadvertised sugary foods.
52
The effect of the advertising was thus not limited
to the specifically advertised brands but had
a more general adverse influence on their food
choices.
The context for any relationship between
television viewing and obesity at this age is
alarming. Marketers target very young
children, and children start watching
television at very young ages. Almost 90%
of children begin watching television
regularly before age 2, and the average age of
initiation is 9 months.
54
Marketing efforts begin
withchildrenasyoungas2years,inorderto
build brand awareness and brand sympa-
thy.
45,55,56
The typical first-grade child can
already recognize and respond to more than 200
brands.
57
Implications
Our results have several important implica-
tions for research in obesity prevention. First,
the current emphasis on reducing sedentary
activities—particularly television—may be
misplaced. It may be more effective to focus on
promoting physical activity directly than to try
to limit television viewing generally.
7,34,58,59
Our evidence strongly suggests that steering
children away from commercial television may
have a meaningful effect in reducing childhood
obesity.
This conclusion has implications for both
policy and practice. It may be appropriate to
limit the advertising of obesogenic foods on
television programs targeted to children.
Advertisers spend huge sums to fund com-
mercial children’s programming, making such
a policy change politically difficult; the enor-
mous costs to society of obesity, however, may
make such a policy worth pursuing. In practice,
primary care providers and others who advise
parents may find it easier—and just as effective
for obesity outcomes—to steer parents away
from commercial programming rather than
away from television altogether. The existence
of many high-quality, enjoyable, and educa-
tional programs available on DVD for all ages
should make it relatively easy for health edu-
cators and care providers to nudge children’s
viewing toward less obesogenic television
content.
How parents talk to their children about
advertising can be an important mediator of
advertising’s influence on children’s choices.
Our results suggest that parents should take
their role as media literacy educators seriously.
Although our data did not assess the media
savviness of parents, nor their discussions with
their children, presumably some parents in the
data set effectively communicated the dangers
of advertising to their children, possibly ren-
dering them more resistant to its effects. If so,
our results reflected an average effect across
parents who were media savvy—whose chil-
dren might be less likely to be affected by
advertising—and parents who were less
knowledgeable—in whose children the associ-
ation of commercial content with obesity would
be greater than we reported. It is plausible that
children could become less susceptible to the
influence of advertisements through family
discussions about their limitations, purpose,
and dangers.
Strengths and Limitations
Our study had several important strengths.
To our knowledge, it was the first study to
TABLE 2—Fully Adjusted Regression of 2002 BMI zScores on Television Viewing Among
Children Aged 0–6 Years in 1997: Panel Survey of Income Dynamics
Model 1,
a
b (95% CI) Model 2,
b
b (95% CI) Model 3,
c
b (95% CI)
Television viewing in 1997, h/d
Commercial 0.11**(0.00, 0.21) 0.11**(0.00, 0.21) 0.10**(0.00, 0.21)
Noncommercial 0.03 (–0.07, 0.14) 0.03 (–0.08, 0.13) 0.04 (–0.07, 0.14)
Television viewing in 2002, h/d
Commercial 0.06 (–0.04, 0.16) 0.06 (–0.04, 0.16) 0.06 (–0.04, 0.17)
Noncommercial 0.00 (–0.10, 0.11) 0.01 (–0.10, 0.11) 0.00 (–0.10, 0.11)
Physical activity in 1997, min/d
None (Ref)
1–30 –0.06 (–0.34, 0.22)
> 30 0.01 (–0.21, 0.23)
Physical activity in 2002, min/d
None (Ref)
1–30 –0.19 (–0.43, 0.05)
> 30 0.02 (–0.18, 0.21)
Eating in front of the television
in 2002
0.03 (–0.04, 0.10)
Adjusted R
2
0.07 0.07 0.07
Note. BMI = body mass index; CI = confidence interval. Regressions were also adjusted for child’s gender, age, race, ethnicity,
mother’s education level, and mother’s BMI. Sampling weights were applied to produce population-level inferences. The
sampling variance was estimated by the Huber–White method to reflect common variance among siblings.
a
Base model, n = 1118.
b
Model 1 plus physical activity mediators, n = 1118.
c
Model 1 plus eating while viewing mediator, n = 1114.
**
P< .05.
RESEARCH AND PRACTICE
February 2010, Vol 100, No. 2 |American Journal of Public Health Zimmerman and Bell |Peer Reviewed |Research and Practice |337
disaggregate the types of television viewing to
which children are exposed. This disaggrega-
tion was consistent with distinct possible causal
pathways in the television–obesity link. The
use of a US-based nationally representative
longitudinal data set ensured generalizable
findings and permitted analysis that exploited
temporality to make a more convincing causal
case. In particular, the ability to control for
baseline BMI and thereby reduce the
potential for reverse causality among older
children was an important strength of the
analysis, in particular because it showed that
omitting baseline BMI introduced a conserva-
tive bias.
Observational data have well-known
limitations. Our study had several other
limitations as well. Adequate measures of
diet were not available to test whether the
effects of advertising might be mediated
through changes to children’s diet. Eating in
frontofthetelevisionhadnosignicant
association with obesity, and the differ-
ences in associations that would be
expected because of the possible effect of
product placement and food company in-
terstitials on public television were not
strong enough to have a measurable impact
in our analysis.
These negative findings do not completely
rule out the mechanisms investigated. It
could be that our measure of eating in front
of the television was too weak to adequately
pick up its effects. The television environment
has changed since 2002 and has changed
dramatically since 1997—today more intersti-
tials are aired and more products are featured
than appeared in turn-of-the-century program-
ming. It is possible that an analysis of more
recent data would have detected more pro-
nounced effects of product placement and in-
terstitials. Similarly, it is possible that the
pronutritional content of educational
television has become both more common
and more effective since our data were
collected.
The time-use diaries that provided our
viewing data represented both a strength and
a weakness for our study. It allowed us to
categorize viewing by content in a form that
was relatively accurate and free of
systematic bias. However, data collection
for only 2 days per child per wave left con-
siderable room for measurement error, and
this error may have been stronger for the
separate viewing categories than for overall
viewing.
As food advertisers increasingly flock to
alternative formats, future research should
attempt to analyze the longer-term and real-
world effects of advertising directly, that is,
outside of small-scale lab experiments. Food
advertisers have extensive presence on the
Internet, where advergames are becoming
common,
60
and product placement is becoming
more common and more sophisticated in
broadcast television, movies, and video games.
Advertisers are also expanding their reach to
novel venues such as Web advertising, cell
phone advertising, stand-alone screens in gas
stations, and the Scholastic Book Club Flyer
sent home periodically with grade school
children.
61
Conclusions
Television viewing may be a sedentary ac-
tivity, but it is not for that reason that it is
associated with obesity in children. The re-
lationship between television viewing and
obesity among children is limited to commer-
cial television viewing and probably operates
through the effect of advertising obesogenic
foods on television. j
About the Authors
Frederick J. Zimmerman is with the Department of Health
Services, University of California, Los Angeles. Janice F.
Bell is with the Department of Health Services, University of
Washington, Seattle.
Correspondence can be sent to Frederick J. Zimmerman,
Box 951772, UCLA, Los Angeles, CA 90095-1772
(e-mail: fredzimmerman@ucla.edu). Reprints can be or-
dered at http://www.ajph.org by clicking on the ‘‘Reprints/
Eprints’’ link.
This article was accepted May 21, 2009.
TABLE 3—Fully Adjusted Regression of 2002 BMI zScores on 1997 and 2002 Television
Viewing Among Children Aged 7–13 Years in 1997: Panel Survey of Income Dynamics
Model 1,
a
b (95% CI) Model 2,
b
b (95% CI) Model 3,
c
b (95% CI) Model 4,
d
b (95% CI)
Child’s BMI zscore in 1997 0.45**(0.38, 0.51) 0.45**(0.38, 0.51) 0.44**(0.38, 0.51)
Television viewing in 1997, h/d
Commercial –0.02 (–0.10, 0.06) –0.03 (–0.10, 0.04) –0.03 (–0.10, 0.04) –0.03 (–0.10, 0.04)
Noncommercial –0.08 (–0.22, 0.05) –0.02 (–0.12, 0.09) –0.01 (–0.11, 0.10) –0.02 (–0.12, 0.08)
Television viewing in 2002, h/d
Commercial 0.06*(0.00, 0.12) 0.06**(0.01, 0.12) 0.06**(0.01, 0.12) 0.06**(0.00, 0.12)
Noncommercial 0.04 (–0.08, 0.16) 0.09 (–0.03, 0.21) 0.09 (–0.03, 0.21) 0.09 (–0.03, 0.21)
Physical activity in 1997, min/d
None (Ref)
1–30 –0.19 (–0.44, 0.06)
> 30 0.00 (–0.20, 0.20)
Physical activity in 2002, min/d
None (Ref)
1–30 –0.18 (–0.47, 0.10)
> 30 –0.09 (–0.25, 0.06)
Eating in front of the television
in 2002
0.04 (–0.02, 0.10)
Adjusted R
2
0.10 0.37 0.37 0.37
Note. BMI = body mass index; CI = confidence interval. Regressions were also adjusted for child’s gender, age, race, ethnicity,
mother’s education level, and mother’s BMI. Sampling weights were applied to produce population-level inferences. The
sampling variance was estimated by the Huber–White method to reflect common variance among siblings.
a
Base model, n = 915.
b
Model 1 with baseline BMI controlled, n = 836.
c
Model 2 plus physical activity mediators, n = 836.
d
Model 2 plus eating while viewing mediator; n = 835.
*
P< .10;
**
P< .05.
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338 |Research and Practice |Peer Reviewed |Zimmerman and Bell American Journal of Public Health |February 2010, Vol 100, No. 2
Contributors
F. J. Zimmerman designed the analysis and obtained the
data. The authors collaborated on extracting the data,
planning and executing the analysis, interpreting the
results, and writing the article.
Acknowledgments
This study was funded in part by the Health Resources
and Services Administration/Maternal and Child
Health Bureau (grant 1R40MC08965-01-00 to
Janice F. Bell).
Human Participant Protection
The data used are in the public domain. The research
was approved by the institutional review board of
Children’s Hospital and Regional Medical Center, Seattle,
WA.
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... As they ate in front of the television more frequently, their overall food preference deteriorated (Marquis, 2005) [35] . Watching obesogenic food promoted on television entices the child to request it, thereby indirectly increasing the risk of obesity in some children (Zimmerman & Bell, 2010) [63] . Following extensive research, it was discovered that social media influenced children to purchase them. ...
... As they ate in front of the television more frequently, their overall food preference deteriorated (Marquis, 2005) [35] . Watching obesogenic food promoted on television entices the child to request it, thereby indirectly increasing the risk of obesity in some children (Zimmerman & Bell, 2010) [63] . Following extensive research, it was discovered that social media influenced children to purchase them. ...
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... A major part of this is for fast-food restaurants. These adverts can be very successful in inducing the target group to consume the advertised foods [51][52][53]. Not surprisingly, evidence suggests that this advertising is one more factor linked to obesity [53,54]. ...
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Concern is growing about the effectiveness of television advertising regulation in the light of technological developments in the media. The current rapid growth of TV platforms in terrestrial, sattelite, and cable formats will soon move into digital transmission. These all offer opportunities for greater commercialization through advertising on media that have not previously been exploited. In democratic societies, there is a tension between freedom of speech rights and the harm that might be done to children through commercial messages. This book explores all of these issues and looks to the future in considering how effective codes of practice and regulation will develop. © 2005 by Lawrence Erlbaum Associates, Inc. All rights reserved.
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Objectives To examine the relationship between television watching, energy intake, physical activity, and obesity status in US boys and girls, aged 8 to 16 years.Methods We used a nationally representative cross-sectional survey with an in-person interview and a medical examination, which included measurements of height and weight, daily hours of television watching, weekly participation in physical activity, and a dietary interview. Between 1988 and 1994, the Third National Health and Nutrition Examination Survey collected data on 4069 children. Mexican Americans and non-Hispanic blacks were oversampled to produce reliable estimates for these groups.Results The prevalence of obesity is lowest among children watching 1 or fewer hours of television a day, and highest among those watching 4 or more hours of television a day. Girls engaged in less physical activity and consumed fewer joules per day than boys. A higher percentage of non-Hispanic white boys reported participating in physical activity 5 or more times per week than any other race/ethnic and sex group. Television watching was positively associated with obesity among girls, even after controlling for age, race/ethnicity, family income, weekly physical activity, and energy intake.Conclusions As the prevalence of overweight increases, the need to reduce sedentary behaviors and to promote a more active lifestyle becomes essential. Clinicians and public health interventionists should encourage active lifestyles to balance the energy intake of children.
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