Predicting the intention to eat healthier food among young adults

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1 HEALTH EDUCATO RESEARCH Theory & Practice Vol.11 no Pages Predicting the intention to eat healthier food among young adults Lisbet 0ygard and Jostein Rise Abstract The purpose of this study was to investigate which factors predicted the intention to eat healthier food. The empirical data stem from a questionnaire survey carried out among 527 young adults aged -26 years living in Oslo, orway. The study was carried out in September The Theory of Planned Behavior (TPB) was used as a guiding theoretical framework. The components of the TPB accounted for 32% of the variance in behavioral intention. Attitude was the strongest predictor, followed by perceived behavioral control. Subjective norm received the lowest weight A detailed analysis of the underlying cognitive structures revealed that the outcomes which discriminated most strongly between those who intended to eat healthier food, those who were undecided and those who had no intention, were that healthier food would improve the shape of the body, increase enjoyment of food and reduce weight n addition, the control beliefs 'weight', 'able to make healthier dishes', 'social eating' and 'busy' discriminated mostly between the three intender groups. These outcomes might preferably be addressed in persuasive communications to change intentions to eat healthier food. ntroduction Evidence abounds that unsatisfactory diets contribute to increased risk of contracting a number of Research Center for Health Promotion, University of Bergen, Oistensgate 3, Bergen, orway detrimental conditions (James etal., 1988). Despite this compelling evidence, a substantial proportion of the population continues to consume unsatisfactory diets in terms of, for example, food containing too much fat, sugar and salt Furthermore, studies have demonstrated that the fat content of the diet has increased progressively in European countries over the last years (James et al., 1988; WHO, 1990). Although this trend seems to have stabilized since 1980, this was only the case where the fat intake was already very high, e.g. in orway. Considering salt intake, European adults of both genders are eating approximately twice the 5 g salt per day that WHO considered as a goal for national averages (WHO, 1990). Sugar consumption is clearly excessive in many countries, with most European countries lying above the ideal goal of sugar intake, including orway. Compared to all European countries, people in northern countries and the UK eat less vegetable products and fruits (WHO, 1990). The main strategy which seems to be relied upon by public authorities responsible for nutrition education is provision of traditional information and advice about the relationship between diet and health. Although these efforts have obviously contributed to increased nutrition knowledge and awareness, there is growing evidence that people do not translate this kind of knowledge and awareness into motivations to act in a more healthy direction (for review, see Sheeshka et al., 1993; Wardle, 1993). As noted by Wardle (1993) the available evidence seems to have led to a devaluation of nutrition education as a public health tool and to the discouragement of the role of cognitive factors in research on dietary choices. On the O Oxford University Press 453

2 L.0ygard and J.Rise other hand, one might argue that the educational strategies have failed to take into account the entire range of relevant cognitions upon which people base their dietary choices. Health beliefs, as defined in a narrow sense, may have only negligible contributions to the service of behavioral change. evertheless, knowledge related to nutrition issues remains important in health education strategies based upon informed choices. Theories of Reasoned Action and Planned Behavior The Theory of Planned Behavior (TPB) is an extension of Fishbein and Ajzen's Theory of Reasoned Behavior (TRA) (Fishbein and Ajzen, 1975; Ajzen and Fishbein, 1980; Ajzen, 1988). TRA posits that the performance of a particular behavior is seen as determined by intention to perform it Behavioral intention is in turn a function of two factors. First, the person's attitude towards the behavior, which refers to the extent to which the person has a favorable or unfavorable evaluation of the behavior. Second, the subjective norm or perceived social pressure to perform or not perform the behavior. These two factors are underpinned by sets of beliefs. For the attitude component the beliefs are behavioral beliefs concerned with the perceived likelihood that performing the behavior will lead to certain outcomes multiplied by the extent to which these outcomes are valued. For the subjective norm component, the beliefs are normative beliefs focusing on die perceived social pressure from certain referents multiplied by the person's motivation to comply with these referents. The assumption of TRA, that all relevant social behaviors are under volitional control, has been challenged in terms of not being applicable to behaviors which are subject to outside control in terms of resources, cooperation and skills (Ajzen, 1991). Thus Ajzen proposed to include the concept of perceived behavioral control into TRA, which is compatible with Bandura's concept of selfefficacy in terms of 'judgment of how well one can execute courses of action required to deal with prospective situations' (Bandura, 1982). Bandura (1986) has suggested that self-efficacy varies along the dimensions of magnitude, generality and strength. Kok et al. (1991) suggested that if one measures a person's perceived ability to perform a particular behavior in a number of different situations then one captures the dimensions of both strength and magnitude. This measurement procedure was adhered to in this study, but nevertheless we also adhered to the notational convention of TPB denoting the concept of perceived behavioral control. TPB therefore posits that to the extent that people intend to engage in more healthy eating, they need to believe that they have control over performance of these specific behaviors, in addition to what they personally get out of it (attitude) and others' approval of it (subjective norm). The relative importance of the three components is assumed to differ with regard to the particular behavior in question and the target population. Fishbein and Middelstadt (1987, 1989) have argued for the utility of the TRA in the development of successful health education programs. They suggest that the more one knows about the factors underlying a decision to perform a particular behavior, the greater the probability that one can change that behavior. From this perspective, TPB is even more useful since it also concentrates on control beliefs. The first step is to identify whether the particular behavior is influenced by attitude, subjective norm or behavioral control. n the second step, changing the behavioral intention becomes a matter of producing change in accessible beliefs or introducing new beliefs. Thus it has been recommended to perform a molecular analysis of the beliefs and evaluations underlying the components of the model as a strategy for constructing persuasive messages which should be targeted in a communication directed to potential message recipients (Fishbein and Middelstadt, 1987, 1989; Sutton et al., 1990; Eagly and Chaiken, 1993). The present paper deals with these two issues related to healthy eating behavior. Previous research The original TRA has been used in a number of earlier studies to focus on behavioral intentions 454

3 Predicting intentions to eat healthier food related to performance of a number of dietary behaviors in terms of selection of milks with varying fat contents (Tuorila, 1987), selection of low salt bread (Tuorila-Ollikainen et al., 1986), eating at a fast-food hamburger restaurant (Axelson et al., 1983) and consumption of high-fat foods (Shepherd and Stockley, 1985; Tuorila and Pangbom, 1988). The latter study also included a number of other nutritional behaviors like milk, cheese, ice cream and chocolate. The most consistent finding from these studies was that attitudes was a better predictor of behavioral intention and actual behavior than subjective norms. Furthermore, a number of studies which have included self-efficacy (or perceived behavioral control) have demonstrated that this factor was an important predictor of eating behavior (Slater, 1989; Shannon, 1990). On the other hand, a study concerning intention to eat wholemeal bread indicated that the addition of perceived control did not contribute to a significant improvement of behavioral intention (Sparks, 1991). A number of studies have also investigated which specific beliefs distinguish between intenders and non-intenders to provide better information about the cognitive structure underlying the nutritional decision (Brinberg and Durand, 1983; Axelson et al., 1983; Shepherd, 1988). n relation to election of high-fat foods the most consistent finding was the discrimatory power of hedonic preference in terms of enjoyment of taste (Shepherd and Stockley, 1985; Tuorila and Pangbom, 1988). However, a more systematic analysis of the underlying cognitive motivations, including expectancy value reasoning to provide clues to which cognition might be targeted in a persuasive communication (see Sutton etal., 1990), seems to be lacking. Research questions n the present study, two research goals were posed. First, to report the relative contribution of attitude, subjective norm and perceived behavioral control in predicting the decision to eat healthier food. Second, to give a detailed analysis of the underlying cognitions with particular reference to which of them discriminated between those who intend, those who had not decided and those who did not intend to eat healthier food. Sample Methods This study is part of the 'Oslo Youdi Study', a longitudinal study which started in 1979 designed to obtain epidemiological data about cardiovascular disease, cancer risk factors and related behaviors among adolescents (Tell, 1987). Six schools in Oslo participated { = 1016), and three of the schools received an intervention program focusing on eating patterns, smoking behavior and physical activity. The main objectives of the nutrition program were to reduce students' intake of sugar, salt and fat, and to increase their intake of complex carbohydrates. n September 1991, the same subjects, now -26 years of age, were invited to participate in a follow-up study. A total of 703 subjects participated (339 males and 264 females) (participation rate of 75.1%). Results presented elsewhere demonstrated that there was no longterm impact of the nutrition education program (Klepp et al., 1994), and in this paper intervention and control subjects have been combined. Data presented in this paper stem from the 1991 investigation. Variables n order to yield accurate prediction, constructs of the model should correspond with regard to action, target, context and time (Ajzen and Fishbein, 1980). We have identified the behaviors in terms of eating (action) healthier food (target) during the next 4 weeks (time). The context factor was not specified. The respondents were required to define 'healthy food' as 'foods containing a low quantity of fat, sugar and salt'. The dependent variable, behavioral intention, was measured by means of the question: 'How likely is it that you will eat healthier food during the next 4 weeks?', using a five-point probability scale ranging from very likely (1) to very unlikely (5). One problem with the dependent 455

4 L.0ygard and J.Rise variable might be that people who are eating healthy food have no plans to change and thus would be classified as having low intention. To solve this problem, we constructed an index consisting of 17 healthy and unhealthy food items, and the subjects with the healthiest eating patterns (25%) were excluded from the analyses. The sample was therefore reduced from 707 to 527 individuals. For the analysis of the underlying cognitions, participants were divided into three categories: (1) intenders ( = 99), (2) neutrals (those who reported they had not decided) ( = 221) and (3) non-intenders ( = 204). Behavioral beliefs n order to obtain the salient beliefs for the study, seven beliefs were elicited and assessed in terms of five-point probability scales from very unlikely (1) to very likely (5): 'For me to eat healthier food during the next 4 weeks will: decrease the cholesterol level ('cholesterol'), reduce my risk of cancer ('cancer'), reduce my risk of heart disease ('heart'), get me into better shape ('shape'), help me reduce weight ('weight'), make me look young longer ('younger') and make me enjoy the food more ('enjoy')'. Outcome evaluations Evaluation of the outcomes listed above was measured in terms of 'How important is...' ranging from not important at all (1) to very important (4). Subsequently, the probability that each outcome would occur under healthier eating was multiplied by the corresponding behavioral belief. The resulting products were summed across all outcomes to constitute an indirect measure of attitude (Cronbach's a = 0.76). ormative beliefs A five-point probability scale was used to measure the extent to which the participants believed that parents, friends, partners, siblings, doctor and coworkers/student fellows ('co-workers') thought they should engage in healthier eating: 'Do you believe that your... think you should eat healthier food during the next 4 weeks? 1. These variables also had 'do not know' and 'do not have' categories. Parents, friends, partners, siblings and coworkers represent groups salient to individuals, in that they arc expected to have a pre-eminent influence on consumer behavior (Zaltman and Wallendorf, 1979; Loudon and Bitta, 1993). Doctors do not usually represent a salient group, but it is interesting to investigate whether they have any influence on this particular action. Motivation to comply Motivation to comply with the above referents was measured by means of the following question: 'How important is it for you to comply with...?' in terms of a four-point scale from not important at all (1) to very important (4). The strength of each normative belief was multiplied by the corresponding motivation to comply. The resulting products were summed across all salient referents to constitute subjective norm (Cronbach's a = 0.79). Perceived behavioral control Control expectations were assessed by nine question measuring people's beliefs in eating healthier food in several specific prospective situations. Participants were asked to evaluate to what extent they felt able to eat healthier food when: depressed, alone, busy, tired, trying to reduce weight ('weight'), unhealthy food tastes better ('taste'), with people who eat unhealthy food ('social eating') and at parties where both healthy and unhealthy food are available ('in parties'). n addition, a global question was asked about the extent to which they felt able to prepare healthier dishes ('able'). The internal consistency of the efficacy scale was Statistics and procedures Pearson's r was used to investigate the relationship between attitude, subjective norm, perceived behavioral control and behavioral intention. Because attitude, subjective norm and perceived behavioral control were intercorrelated, we used hierarchical, multivariate regression analysis to examine the unique associations of each component 456

5 Predicting intentions to eat healthier food of the model with behavioral intention. Firstly, the components of TRA were entered, attitude and norm; secondly, perceived behavioral control was included. One-way analysis of variance was used to study which beliefs discriminated intenders, neutrals and non-intenders to eat healthier food during the next 4 weeks. These associations were quantified using T values P values. Gender has been linked to a variety of health behaviors, including healthy eating (see Waldron, 1988). n the present study, there was little evidence that the differences between the intender groups varied depending on their gender. Only two significant interactions were obtained in two instances: gender by intention interaction on the outcome evaluation of how important the participants rated enjoyment of food and motivation to comply with the doctor. Hence there was no empirical rationale for presenting gender-specific results. Results Correlations between behavioral intention, attitude, subjective norm and perceived behavioral control Table shows that behavioral intention was significantly associated with attitude (r = 0.51), subjective norm (r = 0.) and perceived behavioral control (r = 0.37). n addition, there were substantial correlations between some of the concepts in the model. Attitude correlated with both subjective norm (r = 0.30) and perceived behavioral control (r = 0.36). The relative contribution of attitude, subjective norm and perceived behavioral control Table demonstrates the relative contribution of attitude, subjective norm and perceived behavioral control in predicting behavioral intention in terms of standardized regression coefficients. Hierarchical regression analyses showed that the constructs of TRA accounted for 26% of the variance in the decision to eat healthier food during the next 4 weeks. When perceived behavioral control was included in the equation, the explained variance Table. Correlations (Pearson i x) among attitude, subjective norm, perceived behavioral control ('control') and intention to eat healthier food during the next 4 weeks ( => 527) Attitude Subjective norm Control **P < Subjective nonn 0.30" Self-efficacy 0.36** 0.06 ntention 0.51** 0.** 037** Table L Prediction of intention to eat healthier food during the next 4 weeks from attitude (A), subjective norm (S) and perceived behavioral control (PBC): hierarchical multivariate regression analysis ( = 527) R Adj. R2 B t B a fipfcc A+S ** A+S+PBC ** 0.10* 0.26** P < 0.01; /»< increased to 32%. Given that the P weights in the last step can be used as estimates of the relative contribution of the three components, it can be seen that attitude was the most important, followed by perceived behavioral control. Subjective norm was insignificant in the first step, although it retained its statistically significant effect throughout (P = 0.10). Analyses of the underlying cognitions Univariate tests (one-way analysis of variance) of the individual items demonstrated that for all items intenders rated the outcomes as significantly more important than both neutrals and non-intenders. The greatest difference between the three categories occurred for 'shape' (T = 0.38), 'enjoy' (T = 0.38) and 'weight' (T = 0.24). Regarding the products of belief strength and their outcome evaluation of healthy eating, 'shape' discriminated strongest between the intender groups (T) = 0.43) followed by 'enjoy' (r = 0.40) and 'weight' (11 = 0.39). Table V demonstrates the cognitions underlying subjective norm. There was a consistent tendency in the direction that intenders believed that it was 457

6 L.0ygard and J.Rise Table Hi- Mean scores of beliefs strength (BS) and outcome evaluation (OE) intenders (), and r\ coefficients BS x OE/or intenders (), neutrals () and non- BS n OE n BS X OE n Heart Cholesterol Cancer Shape Weight Young Enjoy Z ** 0.19* 0.26** 038** 034** 0.27** 038** ** 0.21** 0.20** 027** 0.33** 0.21** 0.22** " 025** 0.19** 0.43** 0.39** 0.30** 0.40** P < 0.01; **P < Table V. Mean scores for normative beliefs (B) and motivation to comp/y faf C) and B : < MCfor intenders (1), neutrals () and non-intenders (S), and V coefficients B T MC n BS X OE 1 Parents Partner Friends Doctor Siblings Co-workers *** 0.20*** 0.21*** 0.15* 0.12* 0.18** * J21*** 0.19** 0.25"* 0.16* 0.16* 0.06 *P < 0.05; **P < 0.001; ***P < more likely that the referents expected them to improve their healthy eating than the other two categories. There were significant differences regarding the normative beliefs of all referent groups. However, the differences between the three intender groups concerning motivation to comply with referents were small or insignificant. Regarding the products consisting of normative beliefs and motivations to comply, the results indicate that 'friends' (t = 0.25) discriminated strongest between the intender groups, followed by 'parents' and 'partners' (for both groups, TJ = 0.21). Table V demonstrates the control beliefs for the intender groups. The beliefs which discriminated most between the intender groups were, in descending order 'weight' (j\ = 0.29), 'able' (T = 0.29), 'social eating' (T = 0.) and 'busy' (T = 0.22). However, for all items intenders expressed significantly higher confidence in their ability to change their eating behaviors in a more healthy direction than neutrals and non-intenders. Discussion This study has shown the advantage of TPB as compared with TRA in accounting for the intention to improve one's healthy eating in terms of a significant increase in multiple R from 0.51 to However, this level of prediction is below the usual figures observed in studies using TPB (Ajzen, 1991). Generally, the low predictive ability of the model could not be explained by a violation of the rules of correspondence, thus each component of TRA was assessed in terms of action (eat), target (more healthy food) and over a range of occasions 458

7 Predicting intentions to eat healthier food Table V. Mean scores for control beliefs for Menders (), neutrals () and non-intenders, and r\ coefficients Weight Able Alone Taste Tired Social eating Busy At party Depressed Z *P < 0.01; **P < 0.001; P < l n 029" 0.29** 0.19" 0.17** 0." 0." 0.22" 0.14* 0.13* (time; next 4 weeks), while context was left unspecified. However, perceived behavioral control was measured by specifying one's ability to perform the behavior in a number of situations, while no reference was made to a specific time interval. This procedure makes the concept of perceived behavioral control a more global construct than attitudes and subjective norms in terms of being specific only with regard to the particular action involved. This circumstance might have underestimated its predictive ability in relation to intention. The relative contribution of attitude, subjective norm and perceived behavioral control The results of this study corroborate those of other studies related to predicting intentions of healthy eating in that attitudes turned out to be a stronger determinant of behavioral intention than subjective norm (Shepherd and Stockley, 1985; Tuorila, 1987; Shepherd, 1988; Rosin et al., 1992). Thus the decision of whether to engage in healthier eating in this group of young adults is determined more by calculation of personal pay-offs than by what they believe others may think of this issue. This conclusion is at variance with the results presented by Kristal et al. (1990), who observed that the selection of low-fat diets was predictable from perceived norms and, to a lesser extent, from attitudes. However, one should bear in mind that their conceptualization of norms in terms of perceptions of the opinions of others (termed interpersonal norms) and appropriateness about specific behaviors (termed behavioral norms) deviated from the normative component of TRA (or TPB). This might indicate that the normative component of TRA in a number of behavioral situations suffers from limited theoretical elaboration and faulty measurement As noted above, several studies predicting healthy eating behaviors have adopted the social cognitive theory as their guiding theoretical framework (Shannon, 1990; Sheeshka et al., 1993). A consistent observation of these studies is that self-efficacy (or perceived behavioral control) is a stronger determinant than outcome expectations and in one study (Sheeshka et al., 1993) this concept also appeared to mediate the effect of a number of social variables. The results of this study confirm the importance of perceived behavioral control for the prediction of healthy eating intentions in terms of having significant regression weights (p* = 0.26). On the other hand, attitudes denoted outcome expectations in the language of social cognitive theory appeared to be a stronger determinant of intention than perceived behavioral control. However, as discussed above, the effect of perceived behavioral control may have been underestimated as compared with attitudes and subjective norm in terms of being operationalized as a more global cognition than the other two. mplications for health education The detailed study of the underlying cognitive structures provides us with information about which cognition should be targeted in a persuasive communication. First, those beliefs which discriminated between those who intended to eat healthier food, the neutrals and those who did not intend to do so are candidates for such communications. n addition, such an analysis gives clues about which beliefs should not be addressed, i.e. information which is already part of their cognitive structure. According to expectancy value theory, subjective probabilities determine 459

8 L.0ygard and J.Rise which direction the behavior will take, while evaluations indicate whether this particular behavior will occur. Believing that healthy eating reduces the risk of heart disease does not in itself guarantee that a person will pursue this particular course of action; in addition, the risk reduction of, for example, heart disease should be highly valued. n mathematical terms this assumption proposes that subjective probabilities and evaluative ratings are multiplied. This reasoning means that the product scores of the various single items (outcomes) constitute incentives and disincentives for engaging in healthier eating (Sutton et al., 1990). n the construction of persuasive messages to strengthen or increase the intention to engage in healthier eating, the most promising candidates would preferably be those outcomes which discriminated strongest between intenders and non-intenders, i.e. 'shape', 'enjoy' and 'weight'. This group of beliefs may be linked to a concern with one's appearance and seems not to be emphasized in traditional nutritional campaigns, where nutritional beliefs dominate as arguments. On the other hand, this study does not indicate that messages related to improvements in health are redundant information. Thus the cognition related to outcomes which have health implications do indeed have motivational properties for healthier eating behavior. Health beliefs like 'heart disease' and 'cancer' significantly differentiated between intenders, neutrals and non-intenders, but not to the same extent as outcomes related to concern about appearance. There is thus no reason to exclude traditional health risk information from messages in nutritional campaigns aimed at improving healthier eating behaviors. The third category of outcomes which could possibly be included in a nutritional persuasive message are those related to hedonic preference in terms of enjoyment of taste. The importance of hedonic preference or liking factor in food choices is a consistent finding (Tuorila-OUikainen et al., 1986; Wardle, 1993). Thus the message should be constructed so as to attempt to convince people that healthy food may also be tasty. n fact it has been suggested to include hedonic response or overall liking in TRA to improve its predictive power in relation to foodrelated behaviors (Tuorila-OUikainen, 1986). Our findings also indicate that control beliefs preferably might be included in nutritional persuasive messages in order to enhance people's confidence in their ability to eat healthier food. Given that the most important control beliefs are 'weight', 'able', 'tired', 'social eating' and 'busy', nutritional health campaigns should probably also address such situations. The fact that the indirect measure of subjective norm received the lowest regression weight for predicting behavioral intention makes this component of less interest for providing insight into the motivation to engage in healthy eating and hence for arguments which can be used ih a persuasive communication to alter this intention. Conclusion This study has shown that the ability of the components of the original TRA to predict behavioral intention in terms of eating healthier food was relatively low. The inclusion of perceived behavioral control significantly improved the predictive power, thus demonstrating the advantage of the TPB as compared to TRA. Consistent with previous research on nutritional behaviors, attitude was a stronger determinant than subjective norm. A more finely grained analysis of the individual cognitions also suggests that there is no reason to exclude traditional health motives from persuasive nutritional messages. n addition, the importance of hedonic preferences and concern about appearance and control beliefs in relation to healthy food choices should be paid attention to when constructing persuasive nutritional messages. Acknowledgements Funding for this study was provided by the orwegian Cancer Society and the orwegian Research Council. 460

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