Findings from the 2001–2 Health Behaviour in School Aged Children survey, a broad international health and lifestyle survey in thirty-five countries and regions, indicate a need to promote healthy eating habits among adolescents across Europe(Reference Vereecken, De Henauw and Maes1). However, in order to develop effective nutrition interventions to improve adolescents’ food habits, factors influencing these behaviours have to be identified and better understood(Reference Story, Neumark-Sztainer and French2, Reference Cusatis and Shannon3).
For this, sound and youth-appropriate measurement instruments are needed not only for measurement of the dependent variables (dietary intake) but also for assessing the independent variables (psychosocial predictors)(Reference Baranowski, Cullen and Baranowski4, Reference Birnbaum, Lytle, Murray, Story, Perry and Boutelle5). Validation of psychometric properties of eating behaviour is typically limited to a combination of face validity (the questions make sense in relation to the construct), internal validity (the items are inter-correlated), test–retest reliability (there is stability of response over several test occasions), concurrent validity (scores are correlated with scores on a related measure)(Reference Carnell and Wardle6) or predictive validity. However, little work has been done to investigate and describe the psychometric properties of psychosocial constructs influencing food habits in adolescents.
Turconi et al.(Reference Turconi, Celsa, Rezzani, Biino, Sartirana and Roggi7) described the test–retest reliability and internal consistency of scales measuring self-efficacy, barriers to change food habits and nutrition knowledge among 13–17-year-old Italian adolescents. Hagler et al.(Reference Hagler, Norman, Radick, Calfas and Sallis8) investigated the reliability of change strategies, self-efficacy, decisional balance, family and peer influences related to fruit and vegetable consumption and dietary fat intake in a sample of 11–15-year-olds for both paper- and computer-based format of the questionnaire. Birmbaum et al.(Reference Birnbaum, Lytle, Murray, Story, Perry and Boutelle5) described the development and psychometric testing of a 147-item questionnaire assessing subjective norms, perceived barriers, parenting, outcome expectations, valuation of health, appearance and achievement, behavioural intentions, knowledge and perceived influence of eating behaviour. Neumark-Sztainer et al.(Reference Neumark-Sztainer, Wall, Story and Fulkerson9) reported the test–retest reliability of questions regarding family meal environment and parental encouragement to diet in a sample of 7th and 10th graders.
The purpose of the present paper is to describe the development, test–retest reliability, internal consistency and predictive validity of a new, relatively short questionnaire including a wide range of personal (attitudes, self-efficacy, perceived barriers and benefits of a healthy diet), social (perceived parents’ and peers’ behaviour and support) and environmental factors (availability at home/school) in relation to healthy eating in an adolescent population. As the final questionnaire would be used in a cohort of more than 3000 adolescents in ten European cities as a part of the HELENA Study (Healthy Lifestyle in Europe by Nutrition in Adolescence)(Reference Moreno, Gonzalez-Gross and Kersting10), it had to be brief, easy to read, self-explanatory and trans-European. In addition, in line with the aims of the HELENA Study, the determinants questionnaire had to focus on the broad behavioural category ‘healthy diet’ instead of sub-behaviours (fruit intake, soft drink consumption, fat intake, etc.).
Methods
Instruments
Healthy diet determinants questionnaire
The healthy diet determinants questionnaire was based largely on the literature(Reference Neumark-Sztainer, Story, Perry and Casey11–Reference Croll, Neumark-Sztainer and Story14) and the experience of the authors(Reference De Bourdeaudhuij, Klepp, Due, Rodrigo, de Almeida, Wind, Krolner, Sandvik and Brug15, Reference Vereecken, Van Damme and Maes16). For a review of individual and environmental key factors influencing adolescents’ eating behaviour, see Story et al.(Reference Story, Neumark-Sztainer and French2).
As we were interested in the influences on the overall eating pattern of adolescents, the target behaviour of the psychosocial questions was the overall ‘healthy diet’. Focusing on each relevant individual food item would lead to an unrealistically large questionnaire. However, as people might differ in what they mean by ‘healthy diet’(Reference Baranowski, Cullen and Baranowski4), a definition of the concept was given as an introduction to the questionnaire: ‘A healthy diet is a well balanced diet which contains a lot of fruit, vegetables and dairy products, a good portion of starchy foods like bread, potatoes and pasta, a moderate portion of meat or fish, and not too much fat and sugar. Also the intake of a large amount of fluid is very important in a healthy diet. The energy content of a healthy diet is in accordance with the needs of the human body’. This definition was reviewed and modified by five health professionals of the Ghent University until consensus was reached.
The key factors identified in the literature were translated into the Attitude–Social Influences–Self-efficacy (ASE) model(Reference Brug, Lechner and de Vries17) and the stages of change from the Transtheoretical Model(Reference Prochaska, Redding and Evers18). According to the ASE model, behaviour is considered to be a result of behavioural intention, which in turn is predicted by attitudes, social influences and self-efficacy(Reference Brug, Lechner and de Vries17). Barriers and abilities can further determine whether intentions will be put into practice. The Transtheoretical Model categorizes respondents into five stages (from precontemplation to maintenance), which are theorized to describe the temporal process that one goes through when making a behaviour change(Reference Moser, Green, Weber and Doyle19).
The first four items of the questionnaire asked about the perception of the healthiness of the respondent’s diet and intention to change. Using a theoretical algorithm and the Transtheoretical Model, the first two questions were grouped into five mutually exclusive groups representing the stages of change (does not eat healthily and has no intention to change; does not eat healthily but intends to change within the next 6 months; does not eat healthily but intents to change within the next month; eats healthily but not for longer than 6 months; eats healthily for more than 6 months).
Further, the questionnaire contained eight attitude items: adolescents were asked to which degree they agreed with statements that related healthy diet with taste, health and appearance. Social influences were queried with five items that asked about their parents’ and peers’ behaviour (social norms) and five items that asked about parents’ and peers’ support to eat healthily (social support). The self-efficacy scale was the mean of three items which asked how hard it was to eat healthily in general and in two more specific situations (at home, at school). Eight items asked about barriers, which could be grouped into three subscales relating to self-discipline, social and practical aspects (time, convenience, expertise and price). Finally, five items asked about availability of healthy and less healthy items (fruit, soft drinks) at home and at school.
The questionnaire was sent for comments and suggestions to all HELENA partners. A pilot study was conducted with ten adolescents to identify lack of clarity of the healthy diet definition and the items. Because it was a pilot study, the adolescents were encouraged to ask questions, to give remarks and identify missing concepts. The definition was clear and no additional concepts were identified. The data presented in the current paper were collected and a pilot study was done in one class of each of the participating cities of the HELENA Study. Based on these results suggestions for modification were proposed.
Food consumption
Detailed information regarding the respondents’ food consumption was assessed using a software program called Young Adolescents’ Nutrition Assessment on Computer (YANA-C)(Reference Vereecken, Covents, Matthys and Maes20, Reference Vereecken, Covents and Sichert-Hellert21), which was administered four times. YANA-C is a computer-based 24 h dietary recall instrument structured according to six meal occasions (breakfast, mid-morning snack, midday meal, afternoon snack, evening meal and evening snack) embedded within questions that take the respondent through a range of sequential activities (when the respondent woke up, what the respondent did during the morning, etc.).
The validity of the instrument has been investigated against food records and interviews and is described in detail elsewhere(Reference Vereecken, Covents, Matthys and Maes20). Spearman correlations for energy and nutrient intake ranged between 0·44 and 0·79 against the food records and between 0·44 and 0·86 against the interviews. Spearman correlations of the eighteen investigated food groups were on average 0·74 (ranging between 0·43 for sauces and butter and 0·91 for fish and cereals) against the food record and 0·72 (ranging between 0·33 for sauces and butter and 0·86 for fruit juice, cereals and milk) against the interview.
Sample and procedure
A convenience sample of fifty-five adolescents (44 % girls), with a mean age of 14·6 (sd 1·1) years, was recruited by eleven university students of the Master in Social Medical Sciences of the Ghent University for course credits. The students were given an introduction and instructions during a 2 h classroom session. Each student had to recruit five pupils. Criteria for participation included age between 13 and 17, access to Internet, and willingness to complete several paper-and-pencil and computer-based food and physical activity questionnaires during six survey sessions (February–May 2006). Informed consent was obtained from the participants and their parents.
The questionnaires were administered at the students’ or the pupils’ homes, while the student was present. The students were asked to observe the pupils completing the questionnaires and to note and report on difficulties and questions raised during the administration.
At the last visit, the participants received a small gift (a book token for 10 €).
To assess the test–retest reliability, participants completed the determinants questionnaire twice with a test–retest interval of 2 weeks. To assess the predictive validity, participants completed four self-administered 24 h dietary recalls (YANA-C)(Reference Vereecken, Covents, Matthys and Maes20) on four non-consecutive days over a period of 2 months. Three of the four YANA-C recalls were administered before completing the first determinants questionnaire.
Analyses
The mean and standard deviation were calculated for each item. Internal consistency (Cronbach’s α) and mean scores were calculated for items that belonged to a concept. Temporal stability (test–retest reliability) was estimated by calculating Spearman’s correlation coefficients between test and retest for each item and for the different constructs. Wilcoxon’s tests were used to investigate systematic differences between test and retest. Spearman’s rank correlations were calculated between the psychosocial constructs and a selection of dietary variables to investigate the predictive validity. The selected dietary variables were the subjects’ consumption of fruit, vegetables, soft drinks (including energy and sport drinks), snacks (including all forms of biscuits and cakes, sweets, chocolates and savoury snacks), non-sugared milk, energy intake, percentage of energy from fat, fibre, ascorbic acid and Ca.
Results
Fifty-eight per cent of the respondents indicated to eat ‘rather healthily’, 36 % to eat ‘not unhealthily/not healthily’ and 5 % to eat ‘rather unhealthily’.
Measures of internal consistency, Spearman correlations between the two administrations and means and standard deviations of the items/constructs are reported in Table 1. The item means indicated that eight of the items were highly skewed (score <2 or >4).
Table 1 Description of the items, internal consistency (Cronbach’s α) of constructs, Spearman’s test–retest correlations (r) and mean item scores and their standard deviations for the healthy diet determinants questionnaire among fifty-five Belgian-Flemish adolescents, 2006
Cronbach’s α was poor for social barriers (0·48), perceived peers’ behaviour (0·31) and availability of unhealthy items (0·52), but sufficient for all other constructs (>0·60).
Thirteen items had test–retest correlations <0·60; when mean scores of the items belonging to the same concept were computed, test–retest correlations were acceptable ranging between 0·59 and 0·78. Systematic differences were found for two constructs with higher values for both on the second measurement occasion (taste attitudes: 3·24 (sd 0·93) at T1, 3·48 (sd 0·64) at T2; practical barriers: 1·95 (sd 0·61) at T1, 2·12 (sd 0·70) at T2).
Eleven of the eighteen final constructs produced statistically significant results in the expected direction with one or more of the selected food items, ranging between −0·38 and 0·47 (Table 2).
Table 2 Spearman’s correlations between the psychosocial constructs, the food variables, nutrient and energy intake for the healthy diet determinants questionnaire among fifty-five Belgian-Flemish adolescents, 2006
Correlation was statistically significant: *P < 0·05, **P < 0·01, ***P < 0·001.
The results showed a relationship between adolescents’ awareness of the healthiness of their own diet and the consumption of fruit and soft drinks: adolescents who consumed more fruit and less soft drinks perceived their diet as more healthy; a parallel trend was noticed for respectively vegetables and snacks. Notable for the other constructs was that most significant associations with the five food items were found for taste, perceived peers’ behaviour and availability of soft drinks at home. None of the support and barriers constructs, the appearance factor or the availability of fruit at school was associated with any of the food items.
Fresh fruit and soft drinks were correlated with most constructs (i.e. with seven constructs: both were correlated with awareness, taste, health, perceived peers’ behaviour and unhealthy availability at home; fruit was additionally correlated with stages of change and availability of fruit at home; soft drinks additionally with availability of unhealthy items at school and awareness of the importance of a healthy diet); the consumption of snacks was significantly correlated with five constructs (taste, self-efficacy, perceived peers’ behaviour, availability of unhealthy items at school and at home); vegetable and milk consumption were significantly correlated with only one construct (respectively perceived peers’ and parents’ behaviour).
Concerning the nutrient and energy variables, the findings were less clear and less straightforward. Most associations were found for fibre: all in the expected direction. Availability of soft drinks at home was positively associated with energy intake. Unexpected was the positive association between parents’ support and percentage of energy from fat and the negative association between peers’ support and Ca intake.
Discussion
Before a questionnaire is used in large-scale studies, its reliability and validity need to be tested. In the present study, the psychometric properties of a determinants questionnaire with ‘healthy diet’ as target variable, developed for use in the HELENA Study(Reference Moreno, Gonzalez-Gross and Kersting10), were investigated.
Based on these results and the students’ reported remarks, a number of modifications were suggested (see Appendix).
The internal consistency (α) values of the scales measuring peers’ behaviour (0·31), social barriers (0·48) and availability of unhealthy food at school (0·52) were rather low, indicating that it might be worthwhile to consider each of these items individually in future research. The values of most other scales were acceptable considering that most concepts were measured with only two, three or four variables (0·61–0·88).
The test–retest reliability coefficients were rather low for the stages of change construct (0·55) and the self-perception of the healthiness of their diet (awareness 1; 0·51) but acceptable for the remaining constructs (0·59–0·78). Comparison with the literature is difficult because the constructs, the number of items per construct as well as the statistical methods used for analyses differ. Nevertheless, the test–retest values found in the literature are in the same range: in the study of Turconi et al.(Reference Turconi, Celsa, Rezzani, Biino, Sartirana and Roggi7) intra-class correlation coefficients of the constructs ranged between 0·46 and 0·85 for their paper version; Hagler et al.(Reference Hagler, Norman, Radick, Calfas and Sallis8) reported Pearson correlations of 0·81, 0·79 and 0·80 for respectively their self-efficacy, barriers to change food habits and nutrition knowledge scales. Test–retest Spearman correlations of the psycho-environmental scales in the study of Birnbaum et al.(Reference Birnbaum, Lytle, Murray, Story, Perry and Boutelle5) ranged between 0·41 and 0·82. Test–retest reliabilities of the individual items of Neumark-Stainer et al.’s study(Reference Neumark-Sztainer, Wall, Story and Fulkerson9) ranged between 0·54 and 0·82.
The correlations of the constructs with the hypothesized food variables were investigated to have an indication of the predictive validity of the instrument. The literature suggests that the prediction tends to be higher when narrower categories of behaviour (e.g. fruit consumption) are used(Reference Baranowski, Cullen and Baranowski4). In our study the target behaviour was a broad behavioural category (‘healthy diet’); nevertheless, significant associations were found in the expected direction between the constructs and the selected food variables for eleven of the eighteen constructs.
As expected, the pattern of associations was different for the different food items(Reference Woodward, Boon, Cumming, Ball, Williams and Hornsby22). Most associations were found with fruit, soft drinks and snacks. This may suggest that these food items are more influenced by the queried concepts or that adolescents consider these items as more important components of a healthy diet. Future research including both the current questions and questions directed at more specific food items (e.g. fruit) can give more insight.
Perceived barriers (practical, social, discipline), the appearance factor, perceived support, and availability of fruit at school were not significantly related to any of the selected food items.
There are several possible explanations for these findings. First, the results indicate that the respondents experience few practical barriers (mean = 1·95). At this age, most adolescents’ parents are still responsible for the purchase of fruit and vegetables and the preparation of meals; hence, practical barriers – such as cost and preparation – are less important and seem to have no significant influence on adolescents’ behaviour. Also, the lack of an association between fruit consumption and availability at school might be explained by the fact that most pupils get most fruit from home.
The lack of an association with social barriers and peers’ encouragement might be due to the fact that the adolescents seem to experience few social barriers (mean = 1·94) and little encouragement from their peers (mean = 2·02). The latter has also been found in previous studies of 11–12-year-olds(Reference Vereecken, Van Damme and Maes16) and 4th–6th graders(Reference Cullen, Baranowski, Rittenberry, Cosart, Owens, Hebert and de Moor23).
The lack of an association with parental encouragement might be explained by the adolescents’ growing independence and their need to explore, take risks and seek self-identity and individuation(Reference Story, Neumark-Sztainer and French2, Reference Sturdevant and Spear24), which might conflict with any attempt trying to influence their behaviour. Additionally, those who enjoy eating healthily do not require any encouragement to do so; on the other hand, these youngsters may well be those who are receiving strong, effective encouragement from an early age(Reference Vereecken, Keukelier and Maes25).
No association was found with the appearance factor. Previous studies among adolescents have found that weight-control behaviours in adolescents may result in healthier dietary intake patterns or less healthy patterns depending on the weight-control method used (e.g. eliminating sweets and high-fat foods, eating more fruits and vegetables v. skipping meals, fasting, using laxatives)(Reference Story, Neumark-Sztainer, Sherwood, Stang and Murray26, Reference Neumark-Sztainer, Hannan, Story and Perry27).
The picture with the nutrient and energy variables is much less clear: for less than half of the constructs a significant association was found. This might again indicate that some food variables or some components of the diet receive much more attention when people think about healthy diet. In addition, some components of the diet – like fat – are also much less visible.
A limitation of our study is the convenience sample used, selected by the university students. Additionally, the students might have differed in how they administered the questionnaires, despite the joint introduction and instruction session. Finally, the reliability and validity were tested only in Belgium, although a pilot study in one class of each of the ten participating HELENA cities did not reveal any problems.
To conclude, the results of the short healthy diet determinants questionnaire are promising: the test–retest stability proved to be moderate to good and, despite the broad behavioural category ‘healthy diet’, most of the psychosocial constructs were significantly associated with one or more of the selected dietary variables. To obtain a detailed understanding of what influences adolescents’ ‘healthy diet’, future work in a larger sample of European adolescents is warranted.
Acknowledgements
Sources of funding:C.V. is postdoctoral researcher funded by the Research Foundation – Flanders (Fonds voor Wetenschappelijk Onderzoek – Vlaanderen). The HELENA Study takes place with the financial support of the European Community Sixth RTD Framework Programme (Contract FOOD-CT-2005-007034). The content of this article reflects only the authors’ views and the European Community is not liable for any use that may be made of the information contained herein. Conflict of interest:There are no conflicts of interest. Authorship responsibilities:The questionnaire was developed by I.D.B. and reviewed by the Helena Study Group, including the authors; C.V., I.D.B. and L.M. designed the study; C.V. coordinated the data collection, analysed the data and wrote the manuscript; all authors reviewed the paper and approved the final version submitted for publication; L.M. is international coordinator of the HELENA Study. Acknowledgements:The HELENA Study Group comprises the following individuals and institutions. Co-ordinator: Luis A. Moreno; Core Group members: Luis A. Moreno, Fréderic Gottrand, Stefaan De Henauw, Marcela González-Gross, Chantal Gilbert; Steering Committee: Anthony Kafatos (President), Luis A. Moreno, Christian Libersa, Stefaan De Henauw, Jackie Sánchez, Fréderic Gottrand, Mathilde Kersting, Michael Sjöstrom, Dénes Molnár, Marcela González-Gross, Jean Dallongeville, Chantal Gilbert, Gunnar Hall, Lea Maes, Luca Scalfi; Project Manager: Pilar Meléndez; Universidad de Zaragoza (Spain): Luis A. Moreno, Jesús Fleta, José A. Casajús, Gerardo Rodríguez, Concepción Tomás, María I. Mesana, Germán Vicente-Rodríguez, Adoración Villarroya, Carlos M. Gil, Ignacio Ara, Juan Revenga, Carmen Lachen, Juan Fernández Alvira, Gloria Bueno, Aurora Lázaro, Olga Bueno, Juan F. León, Jesús Ma Garagorri, Manuel Bueno, Juan Pablo Rey López, Iris Iglesia, Paula Velasco, Silvia Bel; Consejo Superior de Investigaciones Científicas (Spain): Ascensión Marcos, Julia Wärnberg, Esther Nova, Sonia Gómez, Esperanza Ligia Díaz, Javier Romeo; Université de Lille (France): Laurent Beghin, Christian Libersa, Frédéric Gottrand, Catalina Iliescu, Juliana Von Berlepsch; Research Institute of Child Nutrition Dortmund, Rheinische Friedrich-Wilhelms-Universität Bonn (Germany): Mathilde Kersting, Wolfgang Sichert-Hellert, Ellen Koeppen; Pécsi Tudományegyetem (University of Pécs) (Hungary): Dénes Molnar, Eva Erhardt, Katalin Csernus, Katalin Török, Szilvia Bokor, Mrs. Angster, Enikö Nagy, Orsolya Kovács, Judit Répasi; University of Crete School of Medicine (Greece): Anthony Kafatos, Caroline Codrington, María Plada, Angeliki Papadaki, Katerina Sarri, Anna Viskadourou, Christos Hatzis, Michael Kiriakakis, George Tsibinos, Constantine Vardavas Manolis Skobos, Eva Protoyeraki, Maria Fasoulaki; Institut für Ernährungs- und Lebensmittelwissenschaften – Ernährungphysiologie, Rheinische Friedrich Wilhelms Universität (Germany): Peter Stehle, Klaus Pietrzik, Marcela González-Gross, Christina Breidenassel, Andre Spinneker, Jasmin Al-Tahan, Miriam Segoviano, Christine Bierschbach, Erika Blatzheim, Adelheid Schuch, Petra Pickert, Petra von Bülow; University of Granada (Spain): Manuel J. Castillo Garzón, Angel Gutiérrez Sáinz, Jonatan Ruiz, Francisco B. Ortega Porcel, Enrique García Artero, Francisco Carreño Gálvez, Vanesa España Romero, Cristóbal Sánchez Muñoz, Victor Soto, Palma Chillón, Jose M. Heredia, Virginia Aparicio, Pedro Baena, Claudia M. Cardia, Ana Carbonell, Antonio J. González, Estefanía Sánchez; Istituto Nazionalen di Ricerca per gli Alimenti e la Nutrizione (Italy): Davide Arcella, Elena Azzini, Emma Barrison, Noemi Bevilacqua, Pasquale Buonocore, Giovina Catasta, Laura Censi, Donatella Ciarapica, Paola D’Acapito, Marika Ferrari, Myriam Galfo, Cinzia Le Donne, Catherine Leclercq, Giuseppe Maiani, Beatrice Mauro, Lorenza Mistura, Antonella Pasquali, Raffaela Piccinelli, Angela Polito, Raffaella Spada, Stefania Sette, Maria Zaccaria; University of Napoli ‘Federico II’ Dept of Food Science (Italy): Luca Scalfi; Ghent University (Belgium): Ilse De Bourdeaudhuij, Stefaan De Henauw, Tineke De Vriendt, Lea Maes, Christophe Matthys, Carine Vereecken, Mieke de Maeyer, Charlene Ottevaere; Medical University of Vienna (Austria): Kurt Widhalm, Katharina Phillipp, Sabine Dietrich; Harokopio University (Greece): Yannis Manios, Eva Grammatikaki, Zoi Bouloubasi, Tina Louisa Cook, Sofia Eleutheriou, Orsalia Consta, George Moschonis, Ioanna Katsaroli, George Kraniou, Stalo Papoutsou, Despoina Keke, Ioanna Petraki, Elena Bellou, Sofia Tanagra, Kostalenia Kallianoti, Dionysia Argyropoulou, Katerina Kondaki, Stamatoula Tsikrika, Christos Karaiskos; Institut Pasteur de Lille (France): Jean Dallongeville, Aline Meirhaeghe; Karolinska Institutet (Sweden): Michael Sjöstrom, Patrick Bergman, María Hagströmmer, Lena Hallström, Mårten Hallberg, Eric Poortvliet, Julia Wärnberg, Linda Bergman, Anita Hurting Wennlöf, Lars Cernerud; Asociación de Investigación de la Industria Agroalimentaria (Spain): Jackie Sánchez-Molero, Elena Picó, Maite Navarro, Blanca Viadel, José Enrique Carreres, Gema Merino, Rosa Sanjuán, María Lorente, María José Sánchez; Campden & Chorleywood Food Research Association (UK): Chantal Gilbert, Sarah Thomas, Peter Burguess; SIK – Institutet foer Livsmedel och Bioteknik (Sweden): Annika Astrom, Gunnar Hall; Meurice Recherche & Development asbl (Belgium): Annick Masson, Claire Lehoux, Pascal Brabant, Philippe Pate, Laurence Fontaine; Campden & Chorleywood Food Development Institute (Hungary): Andras Sebok, Tunde Kuti, Adrienn Hegyi; Productos Aditivos SA (Spain): Cristina Maldonado, Ana Llorente; Cárnicas Serrano SL (Spain): Emilio García; Cederroth International AB (Sweden): Holger von Fircks, Marianne lilja Hallberg, Maria Messerer; Lantmännen Food R&D (Sweden): Mats Larsson, Helena Fredriksson, Viola Adamsson, Ingemar Gröön, Ingmar Börjesson; European Food Information Council (Belgium): Laura Fernández, Laura Smillie.
Appendix Suggested changes to the healthy diet determinants questionnaire resulting from pilot studies
