APPLIED PSYCHOLOGY: HEALTH AND WELL-BEING, 2015, 7 (1), 41–62 doi:10.1111/aphw.12036

Exploring the Association between Television Advertising of Healthy and Unhealthy Foods, Self-Control, and Food Intake in Three European Countries Helge Giese* and Laura M. König University of Konstanz, Germany

Diana Ta˘ut Babes¸-Bolyai University, Romania

Hanna Ollila National Institute for Health and Welfare, Helsinki, Finland

Adriana Ba˘ban Babes¸-Bolyai University, Romania

Pilvikki Absetz National Institute for Health and Welfare, Helsinki, Finland

Harald Schupp and Britta Renner University of Konstanz, Germany

Background: Building upon previous results, the present study explored the relationship between exposure to unhealthy and healthy food TV commercials, trait self-control, and food intake. Methods: In total, 825 Finns (53% female), 1,055 Germans (55% female), and 971 Romanians (55% female) aged 8–21 reported advertisement exposure, self-control, and food intake. Results: Altogether, participants indicated higher exposure to unhealthy compared to healthy food advertisements (F(1, 2848) = 354.73, p < .001, partial η2 = .111). Unhealthy food advertisement exposure was positively associated with unhealthy food intake (all β ≥ .16, p < .001). Healthy food advertisement exposure was positively associated with fruit and vegetable consumption (β = .10,

* Address for correspondence: Helge Giese, University of Konstanz, Department of Psychology, Psychological Assessment and Health Psychology, PO Box 47, D-78457 Konstanz, Germany. Email: [email protected] © 2014 The International Association of Applied Psychology

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p < .001). Self-control was associated with higher consumption of healthy (β ≥ .09, p < .001) and lower consumption of unhealthy foods (all β ≥ −.11, p < .001). Yet, findings of advertising and self-control were mainly independent (interactions: β ≤ |.07|, p ≥ .002). Conclusion: Even though the results suggest that healthy advertisement exposure and self-control might be beneficial for children’s and adolescents’ diet, self-control might be insufficient to alleviate the positive relationship between unhealthy food advertising and unhealthy eating. Keywords: adolescents, advertising, children, eating, self-control, TV

INTRODUCTION Numerous studies have investigated the relationship between television viewing behavior and healthy (i.e. fruit and vegetables) or unhealthy (i.e. sweets and soft drinks) food consumption. Studies in children and adolescents consistently reveal a positive relationship between hours of TV viewing and daily sweets and soft drink consumption as well as a negative relationship with fruit and vegetable consumption (e.g. Barr-Anderson, Larson, Nelson, Neumark-Sztainer, & Story, 2009; Boyland & Halford, 2013; Gebremariam et al., 2013; Lipsky & Iannotti, 2012; Pearson & Biddle, 2011; Utter, Neumark-Sztainer, Jeffery, & Story, 2003; Vereecken, Todd, Roberts, Mulvihill, & Maes, 2006; Woodward et al., 1997), despite some countryspecific differences in cross-national studies (Vereecken et al., 2006). One explanation is that the advertisements children are exposed to while watching TV might change the incentive value of the promoted foods (Harris, Pomeranz, Lobstein, & Brownell, 2009b; Klepp et al., 2007; McGinnis, Gootman, & Kraak, 2006), thereby increasing the likelihood of consumption. Because food advertisements predominantly promote low nutritional value food, with some differences between countries (Kelly et al., 2010; Lobstein & Dibb, 2005; Story & French, 2004), the consumption of unhealthy food items increases when children watch more TV (Hastings et al., 2003). To further investigate this notion, different approaches have been taken to assess children’s and adolescents’ exposure to advertisements more directly than TV hours viewed (Vandewater & Wartella, 2011). Several studies have assessed how much advertising is broadcast and which products are advertised (e.g. Bernhardt et al., 2013; Buijzen, Schuurman, & Bomhof, 2008; Kelly et al., 2010; Story & French, 2004), while others have examined advertising expenditure and reach (Andreyeva, Kelly, & Harris, 2011; Bolton, 1983; Story & French, 2004). These studies showed that children and adolescents are more exposed to unhealthy than healthy food items by revealing what type and how much advertising is aired. To curtail the effect of advertising on food choice, the consumers’ perspective needs to be taken into account since they might skip or ignore commercials (Hastings et al., 2003; Velazquez & Pasch, 2014). The effects of advertisement exposure on © 2014 The International Association of Applied Psychology

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consumers can be determined directly by advertisement recall (Hitchings & Moynihan, 1998; Klepp et al., 2007) or indirectly by brand recognition (Arredondo, Castaneda, Elder, Slymen, & Dozier, 2009; Ueda et al., 2012). Field studies show that while the consumption of low nutritional value food increased with recalled exposure to unhealthy food advertisements (Hitchings & Moynihan, 1998), the consumption of high nutritional value food increased with recalled exposure to healthy product advertisements (Klepp et al., 2007). Furthermore, experimental manipulation of exposure to food advertisements affected snack choices and consumption in children (Boyland et al., 2011; Galst, 1980; Gorn & Goldberg, 1982; Harris, Bargh, & Brownell, 2009a). Specifically, children more frequently selected high sugar snacks and drinks after exposure to advertisements for unhealthy products, whereas the selection of healthier products was more likely after healthy product advertisements or no advertisements at all (Gorn & Goldberg, 1982). It is important to note that it is often implicitly assumed that the consumption of products with high or low nutritional value acts as an “antidote”: an increase in one results in a decrease in the other (“replacement effect”; e.g. Vereecken et al., 2006). However, most studies focused only on one of the two food categories (e.g. Klepp et al., 2007; Hitchings & Moynihan, 1998), precluding the observation of cross-over effects. Interestingly, a large crossnational study observed an effect on the general consumption pattern consistent with the replacement effect: TV viewing was generally related to higher unhealthy food consumption, i.e. snacks and soft drinks, and lower healthy food consumption, i.e. fruit and vegetables (Vereecken et al., 2006). However, it cannot be ruled out that the findings reflect the differential base rate of unhealthy and healthy advertisements (Kelly et al., 2010; Lobstein & Dibb, 2005; Story & French, 2004). In order to further examine the specificity of the advertisement–food consumption relationship, the present study assessed exposure to healthy and unhealthy advertisements as well as the consumption of healthy and unhealthy food items. Previous research has primarily focused on how food advertising exposure, as an environmental factor, affects children’s and adolescents’ diets (Vandewater & Wartella, 2011). However, individual factors such as personality traits should also be taken into account as they can alleviate environmental effects on food intake. In particular, self-control, as the capacity to override one’s inner responses and resist impulses (de Ridder, Lensvelt-Mulders, Finkenauer, Stok, & Baumeister, 2012; Tangney, Baumeister, & Boone, 2004), is associated with healthier eating in adults (e.g. Sproesser, Strohbach, Schupp, & Renner, 2011). Likewise, highly selfcontrolled children and adolescents consume more high nutritional value foods and less low nutritional value foods (Gerrits et al., 2010; Wills, Isasi, Mendoza, & Ainette, 2007). In addition to generally improving the diet of children and adolescents, self-control might also moderate the influence © 2014 The International Association of Applied Psychology

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environmental factors exert on eating. For instance, it was shown that children and adolescents using multiple self-regulatory strategies which require some self-control (de Ridder et al., 2012) are less prone to environmental factors associated with an unfavorable diet (de Vet et al., 2013). Furthermore, experimental results indicate that self-control can moderate the influence of food items’ incentive value (Hofmann, Friese, & Wiers, 2008). Specifically, when self-control resources were depleted, the consumption of candies increased, reflecting the incentive value of candies. Conversely, when self-control resources were high, participants were able to resist the temptation to eat candies in accordance with dietary standards (Hofmann, Rauch, & Gawronski, 2007). In the present study, we examined whether the association of food advertising exposure and food consumption is moderated by children’s and adolescents’ self-control capacity. Specifically, while advertisements may change the incentive value of certain foods, increasing temptation (Klepp et al., 2007; McGinnis et al., 2006), the association between incentive value and food intake is hypothesised to be attenuated in highly selfcontrolled children and adolescents. Furthermore, based on the Hofmann et al. (2007) study, self-control may be particularly important for high incentive unhealthy food items, which are at odds with the goal of eating healthily. Differences between nations for eating behavior, daily television consumption, and the relationship between eating behavior and daily television consumption have been documented for Northern, Central, and Eastern European countries (Currie et al., 2012; Gibney, 1999; Vereecken et al., 2006). The present study was conducted in Finland, Germany, and Romania, for which a large cross-national survey (HBSC) revealed differences in TV consumption in 2009/10. Specifically, 59 per cent of Finnish, 62 per cent of German, and 76 per cent of Romanian 13-year-olds watched more than 2 hours of television daily (Currie et al., 2012), and a similar pattern arose for 11- and 15-year-old children. However, from a consumer perspective, it remains to be determined whether TV viewing is associated with differences in remembered healthy and unhealthy food advertisements. The observation that TV viewing is associated with a decrease in fruit and vegetable consumption in Finland and Germany but in almost no Eastern European country is suggestive of country differences in the airing of healthy and unhealthy food advertising (Vereecken et al., 2006). Furthermore, while food advertising expenditure has been rising extensively in Romania and other Eastern European countries for the past decade (Branca, Nikogosian, & Lobstein, 2007), little research has addressed food advertising and its relationship with eating in Romania. Accordingly, the countries selected for the present study enable assessment of the advertising–food intake relationship in Romania, which is undergoing rapid changes in its economy, eating habits, and food advertising. In addition, this procedure allows us to determine whether possible © 2014 The International Association of Applied Psychology

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moderator effects of self-control generalise across selected countries representing different regions in Europe. The present study aimed to advance the association between advertising exposure and food consumption in several ways. Given the attention paid to how the association between environment and eating behavior is moderated by individual factors (e.g. de Vet et al., 2013), the present study explored the association of self-control, eating behavior, and exposure to food advertisements. Specifically, we explored whether self-control is directly associated with food intake by taking different levels of food advertising exposure into account. Furthermore, we examined whether self-control moderates the association of advertising exposure with food intake. A further aim of the present study was to determine whether exposure to healthy and unhealthy food advertisements is systematically related to the consumption of food items with opposite hedonic value. To this end, the study measured exposure to healthy and unhealthy food advertisements as well as the consumption of healthy (i.e. fruit and vegetables) and unhealthy (i.e. sweets, fast food, and soft drinks) food products. Finally, to examine the observed pattern of findings for possible differences across countries, children and adolescents from Finland, Germany, and Romania participated in the present study. Furthermore, results were adjusted for several control variables including age, gender, and economic status (Klepp et al., 2007; Vereecken et al., 2006).

METHODS

Study Design and Participants In winter 2010, 825 Finnish (53% female), 1,055 German (55% female), and 971 Romanian (55% female) participants were recruited in schools to take part in this cross-sectional study. A broad sample of school classes was included covering childhood and adolescence, with age varying from 8 to 21 years and only a few participants (N = 13) older than 18 years.1 Similarly, school classes represented a wide range of BMI and socioeconomic backgrounds. Written informed consent was first collected from the participants, their parents, and governmental institutions. The questionnaire on food intake and exposure to TV advertising was then completed in the classroom. Demographic variables and trait self-control were also assessed. The questionnaire was developed in English as a “mother version” and translated into

1 Some older students took part in the study alongside their classmates. Although it is debatable whether these few 19- (N = 12) and 21- (N = 2) year-old participants can be considered adolescents, it is also questionable to exclude cases without a firm rationale.

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the respective languages by native speakers. Comparability of meaning across countries was achieved by reverse translations into English.

Measures Descriptive statistics and reliabilities (Cronbach α) are depicted in Table 1. Body Mass Index (BMI). Body Mass Index was computed from selfreported weight and height, and z-values for the BMI scores were derived from gender- and age-specific WHO standardised norms (de Onis et al., 2007).2 The resulting average transformed BMI was highly similar to the respective WHO norm (see Table 1). Social Affluence. Social affluence was assessed using a measure adapted from Wößmann (2003). Participants were asked to report the approximate number of books in their household not including school books, magazines, and newspapers on an illustrated scale. Response categories included (1) “no/few books (0–10)”, (2) “one bookshelf (11–25)”, (3) “one bookcase (26– 100)”, (4) “two bookcases (101–200)”, and (5) “more than two bookcases (more than 200)”. On average, participants had one bookcase (26–100) in their household (see Table 1). Self-Control. Self-control was measured using the brief self-control scale (BSCS) introduced by Tangney et al. (2004). All 13 items were coded from (1) “not at all like me” to (5) “very much like me”. All reversed items were recoded according to scaling instructions and items were averaged for the scale score. Exposure to TV Advertisements. Following Klepp et al. (2007), participants were asked whether they had seen any TV advertisements for the following nine food product categories the previous day: (1) fresh fruit or vegetables, (2) skimmed milk or low-fat dairy products, (3) diet colas and sugar-free soft drinks, (4) snacks, (5) fast food, (6) sweets, (7) energy drinks, (8) colas and sugary soft drinks, and (9) whole-fat milk or dairy products (“Did you watch TV advertisements yesterday for one of the following products?” (0) “No” (1) “Yes”). 2 Raw BMI scores of children and adolescents are highly age-dependent and their use across different age groups is problematic (e.g. Pietrobelli et al., 1998). Therefore, using the LMS approach (Cole & Green, 1992), each raw BMI score of the present sample was transformed into a z-value of the respective gender- and age-specific WHO norm, which has by definition a mean of 0.00 (de Onis et al., 2007). The resulting z-value denotes the deviation of each participant’s BMI from the mean of the WHO norm specific to his or her gender and age group.

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Healthyads

Water

Fruit & vegetables

Fast food

Snacks

Soft drinks

Self-control

Age

Social affluence

Standardised BMI

Gender

2

3

4

5

6

7

8

9

10

11

12

Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania Finland Germany Romania

Country

SD

.32 .36 .33 .32 .33 .33 2.03 2.77 2.70 1.81 1.89 2.02 1.02 1.70 1.96 1.23 1.74 2.00 1.61 1.85 2.33 .60 .61 .53 .50 2.14 2.58 1.08 1.26 1.22 1.06 1.07 1.00

M

.43a .56b .66c .41a .38a .48b 6.83b 6.08a 6.59b 3.39a 3.36a 3.60b .58a 1.14b 1.82c 1.30a 1.96b 2.20c 1.13a 1.33a 2.32b 3.26a 3.14a 3.22a 12.76a 12.65a 14.23b 3.37a 3.36a 3.04b −.06a −.11a −.07a .41*** .46*** .26***

2

4 −.02 −.06 −.05 .12*** .02 .10** .23*** .32*** .30*** (.74) (.69) (.70)

3 −.06 −.06* −.05 −.04 .00 −.01 .19*** .26*** .13*** .03 .22*** .05 .10** −.10** −.13*** −.07* −.05 .06 (.91) (.92) (.86)

5 .21*** .25*** .20*** .03 .13*** .05 −.12** −.06* −.04 −.08* .01 .09** .64*** .63*** .70*** (.84) (.85) (.87)

6 .22*** .24*** .15*** .04 .15*** .01 −.15*** −.18*** −.41*** −.16*** −.08* −.04 .58*** .58*** .46*** .51*** .49*** .45*** (.72) (.63) (.49)

7 −.13*** −.25*** −.16*** .01 −.08 .06 .07 .16*** .09** .26*** .26*** .18*** −.15*** −.24*** −.18*** −.22*** −.24*** −.19*** −.28*** −.29*** −.22*** (.78) (.81) (.68)

8 −.02 .17*** .05 −.15*** −.06 −.17*** .06 −.00 −.11** −.17*** .00 .21*** .06 −.03 .10** .18*** .04 .07* .17*** .15*** .16*** −.23*** −.29** −.13***

9 −.02 −.19*** −.03 .00 −.16*** −.03 .09** .17*** .16*** .24*** .20*** .20*** −.06 −.27*** −.01 −.08* −.19*** .00 −.15*** −.23*** −.15*** .09** .19*** .10** −.04 −.01 −.06

10 −.02 .00 .08* .02 .05 .11** .01 .03 −.02 −.06 .02 −.03 −.03 .03 −.08* −.03 −.07 −.11** .03 −.03 .00 −.11** −.20*** −.08 −.00 .01 −.05 −.00 −.13** −.06

11

.04 .07* .03 .02 .04 .02 −.07 −.07* −.16*** −.16*** −.17*** −.08* .15*** .15*** .18*** .02 .07* .08* .24*** .18*** .18*** −.04 −.11* −.04 −.02 −.04 .04 .00 −.07* −.00 .21*** .10** .14***

12

Correlation coefficients are presented for each variable. In addition, values in parentheses indicate Cronbach’s α. For each variable, mean values with different superscripts differ significantly from each other. Gender: 0 = female 1 = male. * p < .05; ** p < .01; *** p < .001.

Unhealthyads

1

Variable

TABLE 1 Descriptive Statistics for Study Variables

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Responses for fruit and vegetables, skimmed milk, and diet cola were averaged to yield a summary score for exposure to advertising showing “healthy” and “low in energy density or high nutritional value” food items. Similarly, responses to snacks, fast food, sweets, energy drinks, and cola were used to calculate a score for “unhealthy” and “high in energy density or low nutritional value” advertised foods. Exposure to whole-fat milk advertising was not included in the present analysis given that there were pronounced differences among the three countries investigated in categorising whole fat milk as a healthy or unhealthy food item. For readability, categorical labels of “healthy” and “unhealthy” were used as abbreviations for healthy/low energy/high nutritional value and unhealthy/high energy/low nutritional value categories, respectively.

Weekly Food Intake. Weekly food intake was assessed by a food frequency (FFQ) approach (Willett et al., 1985). This approach to assessing eating, in which participants give information about the frequency with which a portion of a food is eaten within a certain time frame, has been shown to be easily applicable and valid for adolescents and children (Rockett & Colditz, 1997). In this survey, participants indicated how often they eat or drink 17 different food products on a 7-point scale ((1) “never”, (2) “less than once a week”, (3) “once a week”, (4) “two to four days a week”, (5) “five to six days a week”, (6) “every day, once a day”, (7) “every day, more than once”). All items were recoded to yield the weekly consumption of the product. For the selection of food items, a two-step approach was pursued. First, important food categories were identified using a nationally representative, German dietary study (KIGGS; Truthmann, Mensink, & Richter, 2011; see also Giese, Juhász, Schupp, & Renner, 2013, for a description of the German FFQ version). Second, additional foods of special relevance for Romanian and Finnish food intake were added following national research in the respective countries. To ensure understanding of product categories, a picture presenting examples of the category was included along with the verbal description of the food category. Food categories were formed by aggregating multiple food items. Weekly consumption of fruit and vegetables was assessed using four items: (1) fruit, (2) salad, (3) cooked vegetables in soup, and (4) cooked side dish vegetables. To obtain the children’s weekly fast food consumption, the four items (1) hamburger, (2) pizza, (3) fries, and (4) chicken nuggets were aggregated. Snacking was assessed with six items: (1) candy, (2) snacks, (3) chocolate bars/chocolate, (4) cookies, (5) cake, and (6) ice cream. Finally, the weekly consumption of soft drinks was composed of two items: (1) cola and sugary soft drinks and (2) energy drinks. Weekly consumption of water was measured as a single item. © 2014 The International Association of Applied Psychology

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Statistical Analysis Missing values ranged from 0.9 per cent to 3.9 per cent out of 2,851 possible answers in each variable with the exception of self-control (29.1% missing) and BMI (24.6% missing) (total Md = 2.7%). This pattern can be partially explained by the fact that, due to technical reasons, self-control was not assessed in some of the schools in Germany. To estimate missing values, two methods that render analysis accessible and avoid problems of implementation were applied. First, EM estimates of SPSS 21 were employed to compute reliability and test differences in advertisement exposure in a mixed 2 healthiness (healthy / unhealthy advertisements) × 3 country (Finland/Germany/ Romania) ANOVA with simple effect computations (Bonferroni corrected). For all other computations and graphic illustrations, FIML estimates were applied via Mplus (Muthén & Muthén, 2012). Differences between countries with respect to demographic variables, selfcontrol, and the intake of different food categories were estimated via regression in a GLM approach. For this purpose, nationality was dummy coded. Analyses included Bonferroni-corrected planned comparison between all countries. Differences in dichotomous variables (gender, exposure to the advertising of single products) were tested via logistic regression. To test the relevance of advertisement exposure and self-control for food intake, a path analysis model was calculated in Mplus. Self-control and exposure to unhealthy and healthy food advertisements were regressed on weekly intake for all food categories assessed. Control variables included standardised BMI, gender, social affluence, and age. In addition, following the guidelines of Aiken and West (1991), interaction terms between advertisement exposure and self-control were analyzed to test for moderating effects. Furthermore, multi-group analyses of age and gender without control variables were conducted to test whether the model applies to specific age groups or gender. Finally, similarities between countries were illustrated using multi-group analysis.

RESULTS

Divergence in Demographic Variables and Self-Control between Countries All three countries were comparable with respect to the distribution of gender (χ2 (2) = .568, p = .753, R2 = .000), standardised BMI (F(2, 2848) = 1.43, p = .240, R2 = .001), and self-control (F(2, 2848) = 2.85, p = .058, R2 = .002). Finnish and German participants did not differ in age (β = .02, puncorrected = .368) or social affluence (β = .00, puncorrected = .849). Yet, Romanian participants were older (F(2, 2848) = 165.29, p < .001, R2 = .104) and reported © 2014 The International Association of Applied Psychology

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FIGURE 1. Advertisement exposure (proportion of participants who viewed advertisements in %). Figure A represents the proportion of children and adolescents in each country that recalled watching advertisements for that category. For each food category, values with different superscripts differ significantly from each other (Bonferroni corrected). Figure B represents the proportion of participants recalling advertisements aggregated across advertisements with low and high nutritional value with standard errors.

lower social affluence (F(2, 2848) = 23.15, p < .001, R2 = .016) compared to Finns (age: β = −.30, p < .001; affluence: β = .12, p < .001) and Germans (age: β = −.34, p < .001; affluence: β = .13, p < .001).

Advertising Exposure across Countries Figure 1 depicts advertising exposure: Figure 1a presents the ratio of participants that viewed advertisements for each product the previous day. Notably, children quite frequently recalled viewing advertisements promoting cola and other sugary soft drinks: 74.6 per cent of Romanian, 57.8 per cent of German, and 48.3 per cent of Finnish participants reported having seen at least one advertisement for this food category. Logistic regressions yielded country-specific differences with respect to all product categories (diet cola χ2 (2) = 37.65, p < .001, R2 = .017; skimmed milk χ2 (2) = 59.30, p < .001, R2 = .027; fruit and vegetables χ2 (2) = 71.08, p < .001, R2 = .031; snacks χ2 (2) = 165.86, p < .001, R2 = .071; fast food χ2 (2) = 13.46, p < .01, R2 = .006; sweets χ2 (2) = 155.81, p < .001, R2 = .069; energy drinks χ2 (2) = 81.90, p < .001, R2 = .037; cola χ2 (2) = 136.90, p < .001, R2 = .063). Summarising the effects presented in Figure 1a, Figure 1b depicts exposure to both healthy (diet cola and diet soft drinks, skimmed milk and low-fat dairy products, fruit and vegetables) and unhealthy (snacks, fast food, © 2014 The International Association of Applied Psychology

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sweets, energy drinks, colas, and sugary soft drinks) product advertisements, respectively. A 2 healthiness (healthy / unhealthy) × 3 country (Finland/ Germany/Romania) mixed ANOVA revealed a main effect for healthiness with a greater exposure to unhealthy (M = .55, SD = .34) compared to healthy food advertisements (M = .41, SD = .32; F(1, 2848) = 354.73, p < .001, partial η2 = .111). In addition, a main effect for country (F(2, 2848) = 70.72, p < .001, partial η2 = .047) emerged. However, both main effects were qualified by a healthiness × country interaction (F(2, 2848) = 55.07, p < .001, partial η2 = .037). Simple effect analyses revealed that children and adolescents were exposed to more unhealthy compared to healthy advertisements in Germany (F(1, 2848) = 264.89, p < .001, partial η2 = .085) and Romania (F(1, 2848) = 239.81, p < .001, partial η2 = .078), but not in Finland (F(1, 2848) = 3.56, p = .059, partial η2 = .001). Further simple contrasts show that Finns are less exposed to unhealthy advertisements compared to both Germans (F(1, 2848) = 70.77, p < .001, partial η2 = .024) and Romanians (F(1, 2848) = 208.41, p < .001, partial η2 = .068) and that Germans were less exposed compared to Romanians (F(1, 2848) = 43.28, p < .001, partial η2 = .015). For exposure to healthy advertisements, country differences were less pronounced. Specifically, Romanians were exposed to more healthy food advertisements than both Germans and Finns (Finns: F(1, 2848) = 21.48, p < .001, partial η2 = .007; Germans: F(1, 2848) = 47.63, p < .001, partial η2 = .016), while there were no differences between Finns and Germans (F(1, 2848) = 3.54, p = .18, partial η2 = .001).

Weekly Food Intake across Countries The three countries differed as to average weekly intake for all categories (water: F(2, 2848) = 21.69, p < .001, R2 = .015; fruit and vegetables: F(2, 2848) = 4.28, p = .013, R2 = .003; fast food: F(2, 2848) = 130.59, p < .001, R2 = .084; snacks: F(2, 2848) = 63.98, p < .001, R2 = .043; soft drinks: F(2, 2848) = 98.99, p < .001, R2 = .065). As Figure 2 depicts, Romanian participants consumed on average more fruit and vegetables than German or Finnish participants (German: β = .06, p = .014; Finnish: β = .05, p = .046). Considering unhealthy foods, Romanian participants consumed more fast food, snacks, and soft drinks compared to Finns (fast food: β = .33, p < .001; snacks: β = .23, p < .001; soft drinks: β = .27, p < .001) and Germans (fast food: β = .20, p < .001; snacks: β = .06, p = .002; soft drinks: β = .24, p < .001). Moreover, Germans indicated higher consumption of fast food and snacks than Finns (fast food: β = .14, p < .001; snacks: β = .17, p < .001). Yet, there was no difference in soft drink consumption (β = .06, p = .116). © 2014 The International Association of Applied Psychology

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FIGURE 2. Weekly food intake across countries. Average intake with standard errors for each food category; values with different superscripts differ significantly from each other (Bonferroni corrected).

Relation between Self-Control, Advertising Exposure, and Weekly Food Intake In a first analysis, associations between weekly food intake, advertisement exposure, and self-control were tested controlling for adjusted BMI, social affluence, age, and gender (see Figure 3 for a summary). Exposure to advertisements for healthy products was positively associated with fruit and vegetable (B = .57, β = .10, p < .001) and fast food consumption (B = .28, β = .05, p = .008). In contrast, exposure to advertisements for unhealthy products was associated with higher consumption of fast food (B = .90, β = .18, p < .001), snacks (B = 1.08, β = .22, p < .001), and soft drinks (B = .92, β = .16, p < .001) and slightly lower consumption of water (B = −.34, β = −.05, p = .033). Furthermore, participants with higher self-control generally ate more fruit and vegetables (B = .64, β = .19, p < .001), drank more water (B = .41, β = .09, p < .001), and consumed less fast food (B = −.32, β = −.11, p < .001), snacks (B = −.47, β = −.16, p < .001), and soft drinks (B = −.58, β = −.16, p < .001). For all food categories, the explained proportion of variance increased significantly when advertising exposure and self-control were included, compared to the model with only control variables (fruit and vegetables: ΔR2 = .044, Fchange(3, 2843) = 43.61, p < .001; water: ΔR2 = .011, Fchange(3, 2843) = 10.45, p < .001; fast food: ΔR2 = .059, Fchange(3, 2843) = 59.42, © 2014 The International Association of Applied Psychology

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FIGURE 3. Path diagram of the statistical effects of self-control and advertisement exposure on diets across countries. Beta weights (adjusted) of self-control and advertisement exposure for the total sample (n = 2,851). Beta weights (unadjusted) for Finland, Germany, and Romania, respectively, in parentheses. * p < .05; ** p < .01; *** p < .001.

p < .001; snacks: ΔR2 = .078, Fchange(3, 2843) = 80.17, p < .001; soft drinks: ΔR2 = .061, Fchange(3, 2843) = 61.56, p < .001). Moderation by Self-Control. In a further analysis, the previous model was extended to include interaction effects for self-control and advertisement exposure to test whether high self-control moderates the relationship between advertising exposure and food intake. Interestingly, the main effects of advertising exposure for unhealthy products were significantly moderated by selfcontrol for fast food (B = −.51, β = −.06, p = .012), snacks (B = −.47, β = −.05, p = .021), and soft drinks (B = −.67, β = −.07, p = .002). Furthermore, the interaction of self-control and advertising exposure for healthy foods was significant for soft drink consumption (B = .67, β = .06, p = .007). However, according to the definition provided by Aiken and West (1991), all interaction effects were ordinal and the main effects for advertisement exposure and self-control did not change substantially. Moreover, explanation of variance, © 2014 The International Association of Applied Psychology

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including interaction terms, changed minimally and was insignificant for water, fruit and vegetables, and snacks (fruit and vegetables: ΔR2 = .001, Fchange(2, 2841) = 1.42, p = .24; water: ΔR2 = .000, Fchange(2, 2841) = 0, p = 1; fast food: ΔR2 = .003, Fchange(2, 2841) = 4.27, p = .01; snacks: ΔR2 = .002, Fchange(2, 2841) = 2.85, p = .06; soft drinks: ΔR2 = .005, Fchange(2, 2841) = 7.14, p < .001).

Group Differences and Control Analyses To test for differences in the associations of self-control and advertisement exposure on children’s and adolescents’ weekly food intake, a model assuming differences for children and adolescents (younger and older than 13) was compared to an equality constrained model, yielding no age differences (χ2 (15) = 22.66, p = .092, better AIC, BIC, adjusted BIC for equality constrained model). The same comparison for gender revealed small differences between girls and boys (χ2 (15) = 50.16, p < .001, better BIC, adjusted BIC for equality constrained model). Unhealthy advertising exposure was negatively associated with water (β = −.11, p = .001) and fruit and vegetable (β = −.09, p = .003) consumption among boys but not among girls (water: β = .00, p = .925; fruit and vegetables: β = .03, p = .226). In contrast, water consumption was only associated with self-control among girls (girls: β = .18, p > .001; boys: β = .02, p = .637). In general, the associations with self-control were somewhat more pronounced for girls, whereas associations with advertisement exposure were somewhat more pronounced for boys. Furthermore, differences across countries were tested (see Figure 3). The comparison with the equality constrained model (χ2 (30) = 52.26, p = .007, better AIC, BIC, adjusted BIC for equality constrained model) indicated little divergence from the general model: As shown in Figure 3, the association between self-control and water consumption did not reach significance in Finland (β = .06, p = .087). Moreover, exposure to healthy product advertisements was not significantly related to fruit and vegetable consumption in Germany (β = .05, p = .179), but its positive relation to fast food consumption was only found in the German sample (β = .13, p < .001). The small negative relationship between exposure to unhealthy food advertising and water consumption was not found to be significant in any of the subsamples (all β < .05, all p > .22).

DISCUSSION The results of the present study demonstrate that viewing healthy and unhealthy food advertisements is associated with the consumption of both healthy and unhealthy foods. Similar to previous studies (e.g. Buijzen et al., © 2014 The International Association of Applied Psychology

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2008; Hitchings & Moynihan, 1998; Vereecken et al., 2006), the amount of advertising exposure of children and adolescents was associated with higher consumption of fast food, snacks, and soft drinks. Furthermore, replicating previous findings (e.g. Boynton-Jarrett et al., 2003; Klepp et al., 2007), participants exposed to healthy food advertisements consumed more fruit and vegetables. Both effect sizes were of similar magnitude. Participants exposed to all types of the assessed unhealthy food advertisements had a higher consumption of fast food, snacks, and soft drinks of up to 1 unit per week for each food item compared to unexposed participants. Accordingly, exposure to all types of assessed healthy food advertisements was associated with an increase of up to 0.6 fruit and vegetable units per week. Associations of food advertisement with food intake appeared to be predominantly domain specific. Thus, unhealthy advertising was related to unhealthy foods and healthy advertising to healthy ones. Only in the German sample was a significant positive association between healthy food advertising and fast food consumption observed. One possible explanation for the differential results might be that advertising of healthy food items differs between countries (e.g. conducted by fast food companies, public health authorities). However, this hypothesis is highly speculative and awaits future research. Yet, as the study was cross-sectional and advertising exposure was assessed via a recall measure, an alternative explanation of the pattern of results found needs to be acknowledged. Participants who eat more unhealthy foods might pay more attention to unhealthy advertisements and therefore have higher recall, and the same might be true for healthy foods (Velazquez & Pasch, 2014; for a review of advertising and experience see Vakratsas & Ambler, 1999). However, a large body of experiments observed effects of advertisement exposure on various measures of food consumption (Boyland et al., 2011; Galst, 1980; Gorn & Goldberg, 1982; Harris et al., 2009a; see also Boyland & Halford, 2013). To determine the directionality of these associations (i.e. people who pay more attention to food advertising prefer more unhealthy items versus people who prefer more unhealthy items pay more attention to advertising), longitudinal studies are needed (see also Velazquez & Pasch, 2014). One might also assume that both effects occur in a crosslagged manner. Another aspect that needs more detailed consideration in future studies is the broad range of advertising children and adolescents are confronted with: Even though TV advertisements are still the most prominent media type used, internet and other form of new media are becoming increasingly important for food advertising to children (Harris et al., 2009b; Martinez, 2007; Matthews, 2008). In addition, the present study observed a significant association between self-control and eating behavior. As self-control increases, the consumption © 2014 The International Association of Applied Psychology

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of fast food, snacks, and soft drinks decreases and the consumption of fruit and vegetables and water increases. These results are in accord with previous findings in children and adults reporting that high self-control is associated with more healthy food choices and diets (Gerrits et al., 2010; Wills et al., 2007). Interestingly, statistical effects of self-control on eating were largely independent of TV advertising exposure. Specifically, even though partially significant interactions were observed due to the large sample size, the effect sizes were negligibly small according to established criteria (Cohen, 1992), indicating findings of rather low practical relevance. Overall, the capacity for self-control does not seem to substantially moderate the advertisement–food intake relationship. Thus, even though the results show that high self-control was positively associated with a healthy diet on its own, the relationship between advertisement exposure and food intake is not effectively alleviated by trait self-control. Research on the effects of high and low self-control resources on snack consumption (Hofmann et al., 2008) has suggested that advertising might be buffered by self-control capacity. For instance, when self-control resources were depleted by a demanding emotional control task, participants’ eating behavior was regulated by the high incentive value of snacks rather than long-term dietary goals (Hofmann et al., 2007). Several reasons may account for differences between the present study and previous experimental research. For instance, it is possible that the pronounced experimental manipulation of self-regulation is not representative of typical daily experiences for the current sample. Future studies need to resolve this issue by measuring intraas well as inter-individual differences in self-control capacity. Alternatively, advertisements might mainly rely on mechanisms other than incentive value to affect behavior (Harris et al., 2009b). Systematic comparison between the three countries investigated in this study replicated and extended previous findings. Adding to the finding that the time spent watching TV differs between Romania and the other two countries (Currie et al., 2012), this study demonstrates specific differences in exposure to healthy and unhealthy advertisements. Similar to previous crossnational studies (Kelly et al., 2010; Lobstein & Dibb, 2005), exposure to unhealthy compared to healthy food advertising was significantly higher in Germany and Romania. Furthermore, Romanians were significantly more exposed to unhealthy food advertisements than Germans. A different picture emerged for Finland, which showed a lower level of unhealthy advertising and no significant difference in exposure to unhealthy and healthy food advertisements. Though the countries follow similar self-regulatory legislation (Matthews, 2008), Romanian legislation might be rather more liberal compared to Germany or Finland (Branca et al., 2007). While less exposure to unhealthy advertising might be found in countries with stricter advertising legislation, this hypothesis needs to be examined in future © 2014 The International Association of Applied Psychology

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research. Furthermore, these findings are complemented by self-reported food consumption which indicated that children and adolescents from Romania eat significantly more unhealthy food items compared to Germans and Finns, although Germans reported significantly higher consumption than Finns. The more favorable pattern within the Finnish sample also corresponds with previous findings demonstrating greater health awareness within Finnish samples (Gibney, 1999; Kafatos et al., 1999). Thus, on the country level, the overall advertising exposure and food intake pattern concurs with the assumption that unhealthy advertising exposure is related to unhealthy eating behavior (see also Lobstein & Dibb, 2005). However, with regard to the main aims of the present study, the relationship between food advertisement (healthy and unhealthy) and self-control regarding food consumption (healthy and unhealthy) on the individual level, results were similar across the three countries and therefore generalisable.

CONCLUSIONS The present study replicates and extends previous findings on the relationship between exposure to food advertisements and eating behavior. A main result was that unhealthy food advertising was mainly related to the consumption of unhealthy foods and, correspondingly, healthy food advertisements were primarily associated with the intake of healthy foods. Furthermore, although the relationship between TV food advertising and consumption was not effectively moderated by self-control, self-control was associated with healthier eating behavior. These findings were observed in Finland, Germany, and Romania although food consumption and hours of TV advertisement exposure indicated cross-country differences. Future prospective studies are required to assess the dynamics of commercial exposure and food consumption.

COMPETING INTERESTS The authors have no competing interests to declare.

AUTHORS’ CONTRIBUTIONS BR, PA, AB, and HS designed the study and planned the project. DT, HO, and BR collected data. HG, LMK, and BR conducted statistical analyses. HG, BR, HS, and LMK prepared the manuscript, including critical comments from PA, AB, DT, and HO. © 2014 The International Association of Applied Psychology

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ACKNOWLEDGEMENTS The research was supported by the European Community FP7 Research Program grant awarded to the TEMPEST consortium (Health-F2-2008223488). We thank all research partners and their collaborating organisations for their participation.

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Exploring the association between television advertising of healthy and unhealthy foods, self-control, and food intake in three European countries.

Building upon previous results, the present study explored the relationship between exposure to unhealthy and healthy food TV commercials, trait self-...
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