The associations between TV viewing, food intake, and BMI. A prospective analysis of data from the Longitudinal Study of Australian Children
ABSTRACT a b s t r a c t Objective: Despite cross-sectional evidence of a link between TV viewing and BMI in early childhood, there has been limited longitudinal exploration of this relationship. The aim of the present study was to explore the potential bi-directionality of the relationship between TV viewing and child BMI. A second-ary aim was to evaluate whether this relationship is mediated by dietary intake. Study design: Parents of 9064 children (4724 recruited at birth, 4340 recruited at age 4) from the Longi-tudinal Study of Australian Children (LSAC) completed measures of their child's dietary intake and TV viewing habits at three equidistant time points, separated by 2 years. Objective measures of height and weight were also obtained at each time point to calculate BMI. Cross-lagged panel analyses were con-ducted to evaluate potential bi-directional associations between TV viewing and child BMI, and to eval-uate mediation effects of dietary intake for this relationship. Results: Our longitudinal findings suggest that the relationship between TV viewing and BMI is bi-direc-tional: Individuals who watch TV are more likely to gain weight, and individuals who are heavier are also more likely to watch TV. Interestingly, dietary intake mediated the BMI-TV viewing relationship for the older children, but not for the birth cohort. Conclusions: Present findings suggest that sedentary behaviours, particularly when coupled with unhealthy dietary habits, constitute a significant risk factor for excessive weight gain in early childhood. Interventions targeted at helping parents to develop healthy TV viewing and eating habits in their young children are clearly warranted.
ABSTRACT: Among Australian adults who met the public health guideline for the minimum health-enhancing levels of physical activity, we examined the dose-response associations of television-viewing time with continuous metabolic risk variables. Data were analyzed on 2031 men and 2033 women aged > or = 25 yr from the 1999-2000 Australian Diabetes, Obesity and Lifestyle study without clinically diagnosed diabetes or heart disease, who reported at least 2.5 h.wk of moderate- to vigorous-intensity physical activity. Waist circumference, resting blood pressure, and fasting and 2-h plasma glucose, triglycerides, and high-density-lipoprotein cholesterol (HDL-C) were measured. The cross-sectional associations of these metabolic variables with quartiles and hours per day of self-reported television-viewing time were examined separately for men and for women. Analyses were adjusted for age, education, income, smoking, diet quality, alcohol intake, parental history of diabetes, and total physical activity time, as well as menopausal status and current use of postmenopausal hormones for women. Significant, detrimental dose-response associations of television-viewing time were observed with waist circumference, systolic blood pressure, and 2-h plasma glucose in men and women, and with fasting plasma glucose, triglycerides, and HDL-C in women. The associations were stronger in women than in men, with significant gender interactions observed for triglycerides and HDL-C. Though waist circumference attenuated the associations, they remained statistically significant for 2-h plasma glucose in men and women, and for triglycerides and HDL-C in women. In a population of healthy Australian adults who met the public health guideline for physical activity, television-viewing time was positively associated with a number of metabolic risk variables. These findings support the case for a concurrent sedentary behavior and health guideline for adults, which is in addition to the public health guideline on physical activity.Medicine & Science in Sports & Exercise 05/2008; 40(4):639-45. · 4.48 Impact Factor
- The Medical journal of Australia 11/2003; 179(8):438-40. · 2.85 Impact Factor
The associations between TV viewing, food intake, and BMI. A prospective
analysis of data from the Longitudinal Study of Australian Childrenq
Matthew Fuller-Tyszkiewicza,⇑, Helen Skouterisa, Louise L. Hardyb, Christine Halsec
aSchool of Psychology, Deakin University, Victoria, Australia
bMedical School, University of Sydney, New South Wales, Australia
cEducation, Deakin University, Victoria, Australia
a r t i c l ei n f o
Received 10 August 2012
Accepted 11 September 2012
Available online 18 September 2012
a b s t r a c t
Objective: Despite cross-sectional evidence of a link between TV viewing and BMI in early childhood,
there has been limited longitudinal exploration of this relationship. The aim of the present study was
to explore the potential bi-directionality of the relationship between TV viewing and child BMI. A second-
ary aim was to evaluate whether this relationship is mediated by dietary intake.
Study design: Parents of 9064 children (4724 recruited at birth, 4340 recruited at age 4) from the Longi-
tudinal Study of Australian Children (LSAC) completed measures of their child’s dietary intake and TV
viewing habits at three equidistant time points, separated by 2 years. Objective measures of height
and weight were also obtained at each time point to calculate BMI. Cross-lagged panel analyses were con-
ducted to evaluate potential bi-directional associations between TV viewing and child BMI, and to eval-
uate mediation effects of dietary intake for this relationship.
Results: Our longitudinal findings suggest that the relationship between TV viewing and BMI is bi-direc-
tional: Individuals who watch TV are more likely to gain weight, and individuals who are heavier are also
more likely to watch TV. Interestingly, dietary intake mediated the BMI-TV viewing relationship for the
older children, but not for the birth cohort.
Conclusions: Present findings suggest that sedentary behaviours, particularly when coupled with
unhealthy dietary habits, constitute a significant risk factor for excessive weight gain in early childhood.
Interventions targeted at helping parents to develop healthy TV viewing and eating habits in their young
children are clearly warranted.
US, UK, and Europe (Baxter & Hayes, 2007; Bertrais et al., 2005;
Hardy, Dobbins, Denney-Wilson, Okely, & Booth, 2006; Jakes
et al., 2003; Marsh, 2005). In 2004, national Australian guidelines
were established which recommend children aged 5–18 spend
no more than 2 h a day on ST (Commonwealth Department of
Health & Ageing, 2004) and, more recently, that for children aged
2–5 years ST should be limited to <1 h per day (Commonwealth
of Australia, Department of Health and Ageing, 2010). In adults
there is strong evidence that prolonged TV viewing is associated
independently with obesity, type 2 diabetes, and biomarkers of
metabolic and cardiovascular disease (Healy et al., 2008). Recent
findings have also revealed that there is an increased risk of insulin
resistance among adolescent boys who exceed ST guidelines, inde-
pendent of body mass index (BMI), diet, fitness, and pubertal status
(Hardy, King, Kelly, Farrell, & Howlett, 2010). Furthermore, 11–
15 year olds who exceed the guidelines have significantly lower
cardio respiratory fitness (Hardy, Dobbins, Denney-Wilson, Okely,
& Booth, 2009).
A recent systematic literature review on the impact of TV on
preschoolers’ weight status revealed that of 26 relevant studies,
23 reported a positive association between hours of TV and child
2011). Five cross-sectional studies (Dubois, Farmer, Girard, & Pet-
erson, 2008; Jackson, Djafarian, Stewart, & Speakman, 2009; Janz
et al., 2002; Manios et al., 2009; Vandebosch & Van Cleemput,
2007) and four prospective studies (Epstein et al., 2008; Jago,
Baranowski, Baranowski, Thompson, & Greaves, 2005; Viner &
Cole, 2005; Zimmerman & Bell, 2010) assessed whether the effect
of TV on preschool child weight status is related to physical activity
and/or diet. Taken together, the findings of these studies suggest
from the primary caregiving parent via face-to-face interviews in
the home. Furthermore details about the LSAC design, methodol-
ogy and demographic details of the sample are available online
(The Longitudinal Study of Australian Children; LSAC, 2010).
Trained researchers measured children’s weight (kg) and height
(m2), from which BMI was calculated (kg/m2). Children’s BMI was
categorised according to international criteria (Cole, Bellizzi, Flegal,
& Dietz, 2000; Cole, Flegal, Nicholls, & Jackson, 2007).
Dietary intake and television viewing
Parents provided information on their child’s dietary intake.
Dietary scores were derived from the sum of scores from seven die-
tary items: total high fat food including full cream milk (five items:
pie, hot chips, potato chips, biscuits, and full-cream milk) and high
sugar drinks (two items: juice and soft drink). Parents indicated the
number of daily serves for each of these items. Parents also esti-
mated daily weekday and weekend TV viewing (in minutes) for
their children. Total weekly TV viewing was derived by summing
weekday and weekend viewing.
Data analytic strategy
An autoregressivecross-lagged panelmodel approach
(MacKinnon, 2008) was used to evaluate the possibility of recipro-
cal influences between child BMI and TV viewing. Models were
estimated using Mplus Version 6.1 (Muthén & Muthén, 2010), with
full information maximum likelihood estimation and robust stan-
dard errors. Missing data were imputed using the intention to treat
approach, which is considered the gold standard for longitudinal
assessment (Heritier, Gebski, & Keech, 2003). Unlike other ap-
proaches to missing data imputation which typically fit the
existing patterns in the data set (e.g., regression, expectation max-
imisation, etc.), the intention to treat approach provides a more
conservative estimate of change in variables over time as missing
data is imputed with values obtained from the preceding wave of
data collection (Heritier et al., 2003).
Adequacy of model fit was examined using the following crite-
ria: Comparative Fit Index (CFI) and Tucker–Lewis Index (TLI),
where; >.95 = good fit, >.90 = adequate fit), Root Mean Square Error
of Approximation (RMSEA) where 6.05 = good fit, <.08 = adequate
fit), and Standardised Root Mean Square Residual (SRMR) where
<.05 = good fit, <.08 = adequate fit) (Byrne, 2011; Hu & Bentler,
In the event that the longitudinal associations between TV
viewing and child BMI (and child BMI ? TV viewing) were found
to be significant, subsequent autoregressive models were con-
ducted to evaluate whether either of these relationships were
mediated by the child’s dietary intake. Mplus’ indirect effect com-
mand, with bootstrapping (n = 1000), was used to formally evalu-
ate the longitudinal mediational relationships between Wave 2
IV, Wave 3 MV, and Wave 4 DV in these models.
Descriptive statistics and correlations
2 provide means, standard deviations, and inter-correlations for TV
viewing (in minutes/week) and child BMI by Wave for Cohort B
and Cohort K, respectively. TV viewing and child BMI showed mod-
erate temporal stability across waves for both cohorts, rs P .59 for
BMI and rs P .40 for TV viewing. Inter-correlations between child
slightly higher correlations for the Cohort K.
Cross-lagged panel analyses
The cross-lagged model provided an adequate fit of the data for
both Cohort B [v2(df=17)= 184.13, p < .001, CFI = .96, SRMR = .04,
RMSEA = .10] and Cohort K [v2(df=17)= 215.18, p < .001, CFI = .95,
SRMR = .04, RMSEA = .09]. As shown in Fig. 1, TV viewing was a
small but significant positive predictor of child BMI both cross-sec-
tionally and longitudinally for both cohorts. Likewise, child BMI
predicted TV viewing within and across waves for Cohort B and Co-
hort K, with the exception of a non-significant association between
BMI and TV at Wave 2 for the younger cohort.
Tests of mediation models
Additional auto-regressive analyses were conducted to evaluate
the possibility that longitudinal associations between TV viewing
and child BMI were mediated by unhealthy eating habits. The
hypothesised paths in these models (as depicted in Fig. 2) provided
a reasonable fit to the data overall. The fit statistics for the TV view-
ing ? food intake ? BMI models were as follows for Cohort B;
v2(df=17)= 607.85, p < .001, CFI = .95, SRMR = .04, RMSEA = .09, and
for Cohort K; v2(df=17)= 450.12, p < .001, CFI = .97, SRMR = .04,
RMSEA = .07. The following fit statistics were obtained for the
BMI ? food intake ? TVviewing
v2(df=17)= 621.32, p < .001, CFI = .95, SRMR = .05, RMSEA = .09, and
for Cohort K; v2(df=17)= 439.17, p < .001, CFI = .97, SRMR = .04,
RMSEA = .08.
With respect to the mediation component of the models, the TV
viewing-BMI relationship was not mediated by food intake for
M. Fuller-Tyszkiewicz et al./Appetite 59 (2012) 945–948
Cohort B (indirect effect = .001, p = .20) or Cohort K (indirect ef-
fect = .001, p = .75). However, food intake was a significant media-
tor of the longitudinal relationship between child BMI and TV
viewing in Cohort K (indirect effect = ?.01, p < .05) but not in Co-
hort B (indirect effect = .001, p = .40). The significant mediation
model for Cohort K is shown in Fig. 2. All non-significant models
may be obtained from the first author upon request.
The present study evaluated the associations between TV
viewing, dietary intake, and child BMI in two separate samples of
Australian children. Consistent with prior research (Dubois et al.,
2008; Epstein et al., 2008; Jackson et al., 2009) small but significant
associations were found between TV viewing and BMI at each of
three waves of data collection. A longitudinal relationship between
these variables was also found. Whereas it is often assumed that
TV viewing habits influence BMI, key novel findings from our
cross-lagged autoregressive modelling suggest that the relation-
ship between TV viewing and BMI is bi-directional. This latter find-
ing may be driven by a general tendency towards sedentary
behaviour: general sedentariness may predispose children to lar-
ger BMIs which in turn may lead to greater engagement in specific
sedentary behaviours such as watching TV, and then to continued
excessive weight gain, and so on. Future research is needed to
assess the tenability of this assumption as the LSAC surveys did
not include a global index of child sedentariness.
tern of findings for the two cohorts. First, the correlations between
Means, standard deviations, and correlations among child BMI (kg/m2) and TV viewing (mins/week) for Cohort K (n = 4724).
Child BMITV viewing
Wave 2 Wave 3Wave 4 Wave 2 Wave 3 Wave 4
TV viewing (minutes/week)
All correlations r > .01 are significant.
Means, standard deviations, and correlations among child BMI (kg/m2) and TV viewing (minutes/week) for Cohort B (n = 4340).
Child BMITV viewing
Wave 2Wave 3Wave 4Wave 2 Wave 3Wave 4
TV viewing (minutes/week)
All correlations r > .01 are significant.
Fig. 1. Co-efficients from auto-regressive cross lag analysis on the reciprocal
influences between child BMI and TV viewing.
presented in these models. All coefficients above .01 are significant in this figure.
?Standardised coefficients are
Fig. 2. Coefficients for longitudinal associations between TV viewing and child BMI,
mediated by unhealthy eating habits (Cohort K only). Notes: Standardised coeffi-
cients are presented in this model. All coefficients above .01 are significant in this
M. Fuller-Tyszkiewicz et al./Appetite 59 (2012) 945–948
TV viewing and child BMI were stronger for the older subgroupwho
menced at birth (Cohort B). Second, the longitudinal association be-
tween BMI and TV viewing was mediated by dietary habits for
Cohort K, but this effect was not found for Cohort B. While it is pos-
sible that these group differences are simply an artefact of sampling
fluctuations, the direction of these age-related effects may be more
omy. As children age, they are more likely to be given freedom in
what they choose to eat and watch. In this light, it would not be sur-
ing habits better account for the relationship between BMI and TV
viewing habits, in the older cohort. Several studies have demon-
strated that increased energy intake, particularly during television
viewing, may contribute to overweight or obesity in preschool chil-
dren (Dubois et al., 2008; Epstein et al., 2008; Manios et al., 2009).
However, few studies have examined the mediating effects on the
longitudinal association between BMI and TV viewing over years
as we have done with the current dataset.
Strengths and limitations
Our findings should be placed within the context of strengths
and limitations of the current design. First, the present study uti-
lised a large sample (n = 4340 for Cohort B and n = 4724 for Cohort
K) that is nationally representative, with respect to gender distri-
bution and socioeconomic status of participants. To the authors’
knowledge, it is the first study to longitudinally analyse the rela-
tionship between TV viewing, BMI, and dietary intake of children
in an Australian population. It is also the first to statistically eval-
uate the possibility that dietary intake mediates the TV viewing-
BMI relationship (cf. Dubois et al., 2008; Epstein et al., 2008; Jack-
son, Djafarian, Stewart, & Speakman, 2009; Jago et al., 2005; Janz
et al., 2002; Manios et al., 2009; Vandebosch & Van Cleemput,
2007; Viner & Cole, 2005; Zimmerman & Bell, 2010). However,
while child BMI was measured objectively by trained experts, TV
viewing and dietary habits were reported retrospectively by the
child’s parents or guardians. This introduces potential error in
measurement that may serve to under-estimate or over-estimate
the true strength of association between variables in our study. Re-
lated to this, it would be ideal to include a separate measure of eat-
ing habits and types of food eaten while watching television, rather
than simply relying on estimates for daily intake. Additionally, the
present study did not control for child physical activity level. It is
possible that the effects of TV viewing on BMI may be reduced
for children who are highly physically active.
Present findings highlight the potential impact of TV viewing on
child BMI, and suggest that dietary intake mediates this association
for older children (aged 4+ years). Given the increasing prevalence
of, and health consequences associated with, obesity, these find-
ings of the co-occurrence of sedentary behaviours (TV viewing
and eating) in such a young population are alarming. Interventions
targeted at successfully alerting parents to the fact that TV viewing
and eating may be contributing to excessive weight gain when
combined, and helping parents to develop healthy TV viewing
and eating habits in their young children, are clearly warranted.
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