Mediators of longitudinal associations between television viewing and eating behaviours in adolescents

Centre for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Victoria, 3125, Australia.
International Journal of Behavioral Nutrition and Physical Activity (Impact Factor: 4.11). 03/2011; 8(1):23. DOI: 10.1186/1479-5868-8-23
Source: PubMed


Television viewing has been associated with poor eating behaviours in adolescents. Changing unhealthy eating behaviours is most likely to be achieved by identifying and targeting factors shown to mediate the association between these behaviours. However, little is known about the mediators of the associations between television viewing and eating behaviours. The aim of this study was to examine mediators of the longitudinal associations between television viewing (TV) and eating behaviours among Australian adolescents.
Eating behaviours were assessed using a web-based survey completed by a community-based sample of 1729 adolescents from years 7 and 9 of secondary schools in Victoria, Australia, at baseline (2004-2005) and two years later. TV viewing and the potential mediators (snacking while watching TV and perceived value of TV viewing) were assessed via the web-based survey at baseline.
Adolescents who watched more than two hours of TV/day had higher intakes of energy-dense snacks and beverages, and lower intakes of fruit two years later. Furthermore, the associations between TV viewing and consumption of energy-dense snacks, energy-dense drinks and fruit were mediated by snacking while watching TV. Perceived value of TV viewing mediated the association between TV viewing and consumption of energy-dense snacks, beverages and fruit.
Snacking while watching TV and perceived value of TV viewing mediated the longitudinal association between TV viewing and eating behaviours among adolescents. The efficacy of methods to reduce TV viewing, change snacking habits while watching TV, and address the values that adolescents place on TV viewing should be examined in an effort to promote healthy eating among adolescents.

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    • "The numerous advertising that adolescences are exposed to were also found to stimulate unhealthy food consumption since advertising act as a distraction of actual food consumption(Pearson et al., 2011). For example, a survey was conducted on Australian children found that children who are heavy viewers of TV ads have more positive attitudes towards junk food (Grønhøj et al., 2013). "

    Research Handbook of Marketing in Emerging Economies (in press), Edited by Marin Marinov (Ed, 01/2015; Edward Elgar, Cheltenham, the United Kingdom.
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    • "Several studies have found a relationship between time spent viewing TV and dietary habits, such as a higher intake of sugary and fast foods as well as a lower intake of fruits and vegetables (Boynton-Jarrett et al. 2003; Giammattei et al. 2003; Lissner et al. 2012; McGowan et al. 2012; Miller et al. 2008). Longitudinal associations between television viewing and poor eating habits have also been observed (Barr-Anderson et al. 2009; Hare- Bruun et al. 2011; Pearson et al. 2011). Although studies have demonstrated that TV viewing predicts overweight and poor eating habits, this does not prove causality. "
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    ABSTRACT: Background/objectives: This longitudinal study describes the relationship between young children's screen time, dietary habits and anthropometric measures. The hypothesis was that television viewing and other screen activities at baseline result in increased consumption of sugar-sweetened beverages (SSB) and increased BMI, BMI z-score and waist to height ratio (WHtR) two years later. A second hypothesis was that SSB consumption mediates the association between the screen activities and changes in the anthropometric measures. Subjects/methods: The study is a part of the prospective cohort study IDEFICS ("Identification and prevention of dietary and lifestyle-induced health effects in children and infants"), investigating diet, lifestyle and social determinants of obesity in 2 to 9-year-olds in eight European countries (baseline n=16,225, two-year follow-up; n=11,038). Anthropometry was objectively measured, and behaviours were parent-reported. Results: The main hypothesis was supported, but the second hypothesis was not confirmed. The odds ratio of being in the highest quintile of % change in WHtR was 1.26 (95% CI: 1.17-1.36) and in BMI 1.22 (95% CI: 1.13-1.31), for each hour per day watching television. The odds ratio of having increased SSB consumption was 1.19 (95% CI: 1.09-1.29) for each hour per day watching TV. The associations for total screen time were slightly weaker. Conclusions: The results indicate substantial effects of TV viewing and other screen activities for young children, both on their consumption of sugary drinks and on an increase in BMI and central obesity. Our findings suggest that television viewing seems to have a stronger effect on food habits and anthropometry than other screen activities in this age group.
    European journal of clinical nutrition 11/2013; 68(2). DOI:10.1038/ejcn.2013.234 · 2.71 Impact Factor
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    • "However results have not been entirely consistent with other studies, that did not find an association between TV viewing time and cardiovascular risk factors [12,13].In addition, most previous studies that evaluated whether the association for TV viewing was independent of physical activity adjusted only for leisure time physical activity, but did not consider non-leisure physical activity[6-11]. Furthermore, it is possible that TV viewing, as an epidemiologic construct, comprises more than sedentary behaviour [14,15]. For example, food and beverage consumption during TV viewing and exposure to food commercials may lead to worse dietary habits. "
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    ABSTRACT: Background Recent evidence shows that sedentary behaviour may be an independent risk factor for cardiovascular diseases, diabetes, cancers and all-cause mortality. However, results are not consistent and different types of sedentary behaviour might have different effects on health. Thus the aim of this study was to evaluate the association between television screen time, computer/reading time and cardio-metabolic biomarkers in a multiethnic urban Asian population. We also sought to understand the potential mediators of this association. Methods The Singapore Prospective Study Program (2004–2007), was a cross-sectional population-based study in a multiethnic population in Singapore. We studied 3305 Singaporean adults of Chinese, Malay and Indian ethnicity who did not have pre-existing diseases and conditions that could affect their physical activity. Multiple linear regression analysis was used to assess the association of television screen time and computer/reading time with cardio-metabolic biomarkers [blood pressure, lipids, glucose, adiponectin, C reactive protein and homeostasis model assessment of insulin resistance (HOMA-IR)]. Path analysis was used to examine the role of mediators of the observed association. Results Longer television screen time was significantly associated with higher systolic blood pressure, total cholesterol, triglycerides, C reactive protein, HOMA-IR, and lower adiponectin after adjustment for potential socio-demographic and lifestyle confounders. Dietary factors and body mass index, but not physical activity, were potential mediators that explained most of these associations between television screen time and cardio-metabolic biomarkers. The associations of television screen time with triglycerides and HOMA-IR were only partly explained by dietary factors and body mass index. No association was observed between computer/ reading time and worse levels of cardio-metabolic biomarkers. Conclusions In this urban Asian population, television screen time was associated with worse levels of various cardio-metabolic risk factors. This may reflect detrimental effects of television screen time on dietary habits rather than replacement of physical activity.
    International Journal of Behavioral Nutrition and Physical Activity 05/2013; 10(1):70. DOI:10.1186/1479-5868-10-70 · 4.11 Impact Factor
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