Hostname: page-component-cd9895bd7-jkksz Total loading time: 0 Render date: 2024-12-22T23:16:30.017Z Has data issue: false hasContentIssue false

Taste preferences, liking and other factors related to fruit and vegetable intakes among schoolchildren: results from observational studies

Published online by Cambridge University Press:  01 February 2008

Johannes Brug*
Affiliation:
EMGO Institute, VU University Medical Centre, Amsterdam, The Netherlands
Nannah I. Tak
Affiliation:
EMGO Institute, VU University Medical Centre, Amsterdam, The Netherlands
Saskia J. te Velde
Affiliation:
EMGO Institute, VU University Medical Centre, Amsterdam, The Netherlands
Elling Bere
Affiliation:
Agder University College, Kristiansand, Norway
Ilse de Bourdeaudhuij
Affiliation:
Department of Movement Sciences, Ghent University, Belgium
*
*Corresponding author: J. Brug, fax +31 20 4448181, Tel: +31 20 4448180, email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

The present paper explores the relative importance of liking and taste preferences as correlates of fruit and vegetable (FV) intakes among schoolchildren in Europe. The paper first provides an overview of potential determinants of food choice among children and subsequently summarizes the results of two recent observational studies on determinants of FV intakes among school-aged children. It is proposed that taste preferences and liking are important for children's food choices as part of a broader spectrum of nutrition behaviour determinants. Taste preferences and liking are important for motivation to eat certain foods, but social-cultural and physical environmental factors that determine availability and accessibility of foods, as well as nutrition knowledge and abilities should also be considered.

Study 1 shows that children with a positive liking for FV have a greater likelihood to eat fruits (odds ratio (OR) = 1·97) or vegetables (OR = 1·60) every day, while ability and opportunity related factors such as knowledge, self-efficacy, parental influences and accessibility of FV were also associated with likelihood of daily intakes (ORs between 1·16 and 2·75). These results were consistent across different countries in Europe. Study 2 shows that taste prerences were the stongest mediator of gender differences in FV intakes among children; the fact that girls eat more could for a large extend be explained by there stronger taste preferences.

Type
Full Papers
Copyright
Copyright © The Authors 2008

Diet and nutrition clearly play a critical role during childhood and adolescent development. First of all, children and adolescents need to cover not only their nutrient and energy needs for maintenance metabolism and physical activities, but also for growth(Reference Koletzko, de la Guéronnière, Toschke and von Kries1). Furthermore, eating habits may be less established in childhood and adolescence, and may therefore be better modifiable(Reference Birch2), and food preferences and habits adopted in childhood and adolescence may track to a certain extend into adulthood(Reference Kelder, Perry, Klepp and Lytle3Reference te Velde, Twisk and Brug5).

Nutritional habits are not in line with recommendations among children and adolescents. Many young people eat not enough fruits and vegetables, too much saturated fat, and more energy than they need(Reference Yngve, Wolf and Poortvliet6). In order to promote more healthful eating, we need to know why children and adolescents eat what they eat(Reference Brug, Oenema and Ferreira7, Reference Baranowski, Baranowski, Cullen, Marsh, Islam, Zakeri, Honess-Morreale and de Moor8).

What, when and how much children eat is influenced by a complex, interrelated set of so-called behavioural ‘determinants’ and successful dietary behaviour change interventions are dependent on the identification of the most important and best changeable determinants, because intervention strategies, methods and materials need to be selected or developed that are tailored to the target populations and to the most important and best modifiable determinants of behaviour change.

In this paper we will first give a brief overview of different important categories of determinants of food choice and dietary intake among children and adolescents. Secondly, we will present and discuss the results of two recent observational studies on determinants of fruit and vegetable (FV) intakes that illustrate the relative importance of taste preferences and liking as compared to other potential determinants of FV consumption among school-aged children across Europe(Reference Klepp, Pérez-Rodrigo and De Bourdeaudhuij9).

Determinants of food intake: motivation, ability and opportunity

In affluent countries, most people can generally choose what, when and how much they eat. To induce dietary change, one needs to change people's food choices. Studies on personal determinants of food choice have primarily made use of psychological theories to explain food choice and nutrition behaviours(Reference Conner and Armitage10). It has, however, been argued that, since children may have less autonomy in making food choices, environmental rather than personal factors may be more important determinants of their nutrition behaviours. More recently, social-ecological models of health behaviour(Reference Sallis, Owen, Glanz, Rimer and Lewis11) have drawn more attention to such environmental influences on nutrition behaviours. A framework proposed by Rothschild(Reference Rothschild12) provides a simple, integrative framework to categorise the large and diverse number of potential personal and environmental determinants from various more specific behaviour theories. Rothschild identifies three distinct categories of determinants: motivation, ability and opportunity. These categories of determinants are interrelated. For example, in environments with few opportunities for healthful eating, higher motivation and more abilities are needed to maintain a healthful diet.

Motivation

Behavioural decision, motivation or intention have been identified as primary determinants of behaviour(Reference van Trijp, Brug, van der Maas and Mela13). Motivation or intention is influenced by a subjective weighing of expected positive and negative consequences of the behaviour. In general, expectations about short-term outcomes are more important than longer-term outcomes. Taste, satiety and pleasure are short-term consequences of major importance. Taste preferences and liking are regarded as key determinants of food choice(Reference Capaldi and Capaldi14). People, and young people maybe more so, eat what they like, and disliked foods are avoided(Reference Birch2). Certain taste preferences are innate, such as a liking for sweet and salt, and a dislike for bitter and sour. However, taste preferences can be learned and unlearned(Reference Rozin15). ‘Hunger’ or appetite is also a strong motivator to eat. In Maslov's hierarchy of human needs, the need to cover physiological energy requirements, i.e. overcoming hunger, is among the highest human priorities, and the urge to eat and drink when hungry is an inborn trait.

Since eating is primarily a way to cover the basic physiological nutrient requirements and calorie requirements, satiety, i.e. the feeling that energy requirements have successfully been met, is a strong reinforcer for eating specific foods and we therefore quickly learn to like and appreciate energy-dense foods(Reference Birch2). Children are therefore ‘programmed’ to like, or to learn to like, the taste of high-energy, sweet and fatty foods. Nevertheless, many acquire a taste for coffee, tea or beer during childhood and adolescence, which shows that we can even unlearn our innate dislike of bitter.

Some specific types of taste preference learning strategies have been identified. The aforementioned example of learning to like high-energy foods is referred to as ‘taste-nutrient learning’. Taste-nutrient learning is an example of operant or instrumental conditioning: a stimulus (eating energy dense, sweet and fatty food) is positively reinforced (‘rewarded’) by the pleasant feeling of satiety. In the last decades palatable energy-dense foods have become readily available and accessible for most children in western countries. This abundance combined with our innate preference for energy-dense foods may be an important cause for the present-day obesity epidemic. Research shows that high-fat and sugar-rich foods are indeed among the most preferred foods among children and adolescents(Reference Cooke and Wardle16). Most fruits and especially vegetables have low-energy densities, and many vegetables have a somewhat bitter taste. Preferences for these foods are therefore not so easily learned.

Two other food preference-learning strategies are examples of classical conditioning and are referred to as ‘taste–taste learning’ and ‘taste–environment learning’. If a new, unfamiliar, taste is combined with a taste for which a preference already exists, children will more easily learn to like the new taste. For example, children will more easily learn to like the somewhat bitter taste of tea or the sour taste of yoghurt or grapefruit, if these are first served with sugar. Similarly, a liking for tastes that people are exposed to in pleasant physical or social environments are also learned. Foods first encountered as a child in a friendly, pleasant family environment, may become favourite foods for a lifetime.

A fourth important learning strategy is observational learning or modelling: children learn to like the taste of foods that they see their parents, siblings, friends or other ‘important others’ eat.

Health related beliefs may also be important. If people are asked about what they find important in their diet and food choice, ‘health’ usually comes second (or third) after ‘taste’ (and cost), especially among women(Reference Lennernäs, Fjellström, Becker, Giachetti, Schmitt, Remaut de Winter and Kearney17). Nevertheless, 40 % of Americans and 57 % of Europeans indicated rarely or never to compromise on taste to improve the healthfulness of their diets(18). This is probably even more likely among children(Reference Story, Neumark-Sztainer and French19).

Motivation and intentions are important determinants of nutrition behaviours, and taste preferences and liking importantly influence motivation to eat. But not all behaviour is intentional, and we not always act on our intentions(Reference Sheeran, Hewstone and Stroebe20). Lack of abilities or lack of environmental opportunities can be important barriers. Environmental cues may also trigger automatic behavioural responses.

Ability

Self-efficacy, or perceived behavioural control (PBC), refers to one's confidence in one's abilities and skills to engage in certain behaviour. PBC is behaviour and context specific. A person can, for example, be confident to be able to eat less fat, but not to increase vegetable intake; and confidence to cut back on fat may be high for regular meals prepared at home, but not for eating out. PBC is strongly related to abilities and skills. Studies in children and adolescents show that food and nutrition-related self-efficacy is associated with healthful food choices and dietary behaviour(Reference Heatey and Thombs21Reference Wind, De Bourdeaudhuij, te Velde, Sandvik, Klepp, Due and Brug23). Skills and abilities are to some extent dependent on practical knowledge. For example, knowing why to eat healthfully, knowing what healthful foods are, and knowing the recommended intake levels may all be conditional for voluntary healthful eating. Although knowledge in itself is unlikely to result in healthful food and nutrition choices – knowledge may be a necessary but insufficient condition for healthy food choice(Reference Story, Neumark-Sztainer and French19) – some recent studies show that knowledge of recommended intake levels of FV was associated with higher intakes in 11-year old school children(Reference Wind, De Bourdeaudhuij, te Velde, Sandvik, Klepp, Due and Brug23).

Environmental opportunities

Children and adolescents' opportunities to make healthful dietary choices strongly depend on the opportunities their environments have to offer. For example, children's social environment, such as their parents and school staff, importantly influences their range of food choices; their physical environment, such as where they live or go to school, importantly influences what foods are available and accessible to them.

Classifying the food environment

The ANGELO framework(Reference Swinburn, Egger and Raza24), which was specifically developed to conceptualise health behaviour environments related to obesity, distinguishes four ‘types’ of environments: physical, economic, political and socio-cultural. The physical environment refers to availability of healthy and unhealthy choices, such as points-of-purchase for FV and soft drink vending machines in schools. The economic environment refers to the costs related to healthy and unhealthy behaviours, such as the price of soft drinks, FV or energy-dense snacks in school cafeterias. The political environment refers to the rules and regulations that may influence food choice and eating behaviour. Bans on soft drink vending machines in schools, rules on what treats can and cannot be brought to school, as well as family food rules are micro-level political environmental factors. Other examples are national school food policies or national legislation regarding food-marketing efforts aimed at children. The socio-cultural environment refers to the social and cultural subjective and descriptive norms and other social influences such as social support for adoption of health behaviour and social pressure to engage in unhealthy habits.

Evidence for environmental determinants of nutrition behaviours in youth

Child and adolescent dietary behaviour is likely to be strongly influenced by environmental factors, since children may have less autonomy in food choice. From the age of about three years, children's eating behaviour is influenced by their responsiveness to environmental cues, and a variety of family and social factors start to influence children's eating behaviours(Reference Patrick and Nicklas25). The role of parents and schools is considered to be of particular importance.

Parent and family influences

Parents directly and importantly determine the child's micro-level social, political, physical as well as economical nutrition environments. Eating is a social behaviour, especially for children(Reference Birch2), and observing eating behaviours of others, especially parents, influences their own preferences and behaviour. Such modelling of eating behaviours can even result in establishing preferences for foods or substances that are inherently disliked. A recent review of the literature on environmental correlates of nutrition behaviours in youth indicates that children and adolescents' nutrition behaviours are consistently associated with their parents' behaviours(Reference Brug, Van Lenthe and Kremers26). Parents further influence their offspring's nutrition behaviours by actively encouraging, discouraging or controlling certain behaviours. Restricting children's access to, for example high fat or sugar-rich foods, may encourage rather than discourage preferences for such foods, especially if these same foods are also used to reward children for good behaviour and for celebrations(Reference Birch2). However, a study conducted in Belgium indicated that clear restrictive family rules about high fat foods during childhood were associated with healthier food choices in adolescence(Reference De Bourdeaudhuij and Van Oost27), and a recent cross-European study showed that parental demand as well as facilitation to eat FV were associated with higher intake levels in 11 year old children, while ‘parental allowance’ (i.e. parents allowing children to eat as much as they like), was not(Reference Wind, De Bourdeaudhuij, te Velde, Sandvik, Klepp, Due and Brug23, Reference De Bourdeaudhuij, te Velde and Brug28).

From studies on the association between general parenting styles and children's health behaviours, it appears that authoritative parenting, i.e. a parenting style characterised by high parental involvement as well as strictness, is associated with more positive health behaviours including higher FV intakes(Reference Kremers, Brug, de Vries and Engels29, Reference Patrick, Nicklas, Hughes and Morales30), compared to adolescents who reported authoritarian (high strictness, low involvement) or neglectful (low strictness, low involvement) parenting styles.

As a result of these parenting practices and rules, as well as parents' own food preferences and choices, parents influence what foods are available and accessible within the home environment. Availability and accessibility of foods have repeatedly been found to be associated with intake levels in children and adolescents(Reference Cullen, Baranowski, Owens, Marsh, Rittenberry and de Moor31).

Finally, family socio-economic position is important. A recent review of the literature confirmed that low parental education, as well as parental income is associated with less healthful diets in children and adolescents(Reference Wardle, Jarvis, Steggles, Sutton, Williamson, Farrimond, Cartwright and Simon32, Reference van der Horst, Kremers, Ferreira, Singh, Oenema and Brug33).

School influences

A second important setting for children and adolescent nutrition is the school environment. Children spend much time at school; consume a large proportion of their daily intakes there, and schools offer nutrition education as part of the regular curriculum.

Accessibility and availability of foods in schools are important physical environmental factors. In many countries across Europe, schools provide lunch or other foods for the students, with great differences between countries. For example, in Belgium school lunches are offered in a majority of primary and secondary schools. Parents need to pay for their children to have a school lunch, children are allowed to bring their own lunch to school, and the school lunches are not required to meet official dietary guidelines. Most secondary schools do have vending machines and snack food outlets. In The Netherlands, a neighbouring country, school lunches are not offered. In primary schools, children go home for lunch or children need to bring their lunch to school. In secondary schools, adolescents bring their lunch to school, or they can buy lunch in the school a la carte cafeteria. In Sweden and the UK primary and secondary schools do offer free school lunches but while Swedish schools are required to meet official recommended intake levels, nutrition requirements for school lunches in the UK only state that meals in primary schools should contain at least one item from four major food groups (starchy foods; FV; dairy products; meat, fish or alternative protein source) and in secondary school lunches at least two items from each of these groups should be offered. Preliminary evidence from the European Pro Children study indicates that school lunches can make a difference; Swedish kids eat more vegetables at school than children from other countries across Europe, and have a relatively high total daily vegetable intake.

Macro-level environment

An important macro-level factor is how foods are marketed to children and adolescents. Children and adolescents are increasingly seen as an important target group for food marketing(Reference Story and French34). Young people in affluent countries have money to spend themselves, they may also influence food-buying behaviours of their parents, and they are the future adult buyers and consumers. Foods that are most intensively marketed by means of advertisement and marketing campaign are foods that are high in sugar and fats, and often low in micronutrients. In the US fast food restaurants and soft drink companies spent most on marketing their products. The large portion sizes offered at ‘value pricing’ (i.e. larger portions cost relatively less), especially in the US, is a marketing strategy that has probably contributed to higher caloric intakes and unnecessary weight gain. Television still is the most important channel for marketing food products, especially for younger children, but food marketing among youth also includes, for example, school-based marketing, Internet advertising, and sponsoring of events. Recent research confirmed that food adverts exposure promotes consumption and that obese children in particular have heightened responsiveness to these food-promotion adverts(Reference Halford, Boyland, Hughes, Oliveira and Dovey35).

Although most countries do regard children as a special vulnerable group for television advertising, there are striking differences between countries in rules and regulations for food marketing to children. Only few countries have a complete ban on television advertising for younger children. But most countries (85 % of 73 countries surveyed by the WHO) do have statutory regulations for food television advertising to children; regulations that define, for example, in what ways foods can be promoted at what broadcasting times. The principle underlying many regulations is that advertising may not be misleading. At the ministerial conference on counteracting obesity organised by WHO Europe, all ministers of countries in the European region signed a charter in which they recognized the importance of marketing(Reference Brug36).

The relative importance of liking and preferences: evidence from observational studies

To explore how important taste-preferences and liking are as population correlates of food intakes among children two recently published studies on correlates of FV intakes, the Pro Children study and the Fruits and Vegetables Make the Mark study are illustrative(Reference De Bourdeaudhuij, te Velde and Brug28, Reference Bere, Brug and Klepp37).

The Pro Children project

A cross-sectional survey was conducted as part of the Pro Children project in nine European countries (Austria, Belgium, Denmark, Iceland, The Netherlands, Norway, Portugal, Spain and Sweden) during October – December 2003.

Schools constituted the sampling unit, and from each country random samples of at least 20 schools and a minimum of 1300 11-year old eligible children were recruited. A participation rate of 90·4 % was reached in the participating schools; mean age was 11·4 years (range 8·8–13·8, SD = 0·48; 79 % of the children was born in 1992). The final sample sizes varied from 1105 for The Netherlands to 2134 for Portugal, with a total sample size of 13 305. A detailed description of the Pro Children project, including the sampling and data collection procedure is given elsewhere(Reference Yngve, Wolf and Poortvliet6, Reference Klepp, Pérez-Rodrigo and De Bourdeaudhuij9). All protocols and questionnaires of the Pro Children projects can be accessed at www.prochildren.org

A self-report questionnaire in all applicable languages was developed to measure FV intake, and possible determinants informed by a social-ecological model(Reference Klepp, Pérez-Rodrigo and De Bourdeaudhuij9), a literature review(Reference Rasmussen, Krolner, Klepp, Lytle, Brug, Bere and Due38), focus group interviews with children(Reference Wind, Bobelijn, De Bourdeaudhuij, Klepp and Brug39), individual interviews with parents and school staff, and thorough pre-testing as well as a rigorous translation – back translation procedure(Reference Wind, Bobelijn, De Bourdeaudhuij, Klepp and Brug39, Reference De Bourdeaudhuij, Klepp, Due, Rodrigo, De Almeida, Wind, Krolner, Sandvik and Brug40). The questionnaire included questions that were analogous for FV intake on motivational factors such as liking and preferences, and attitudes; ability-related factors such as knowledge of recommended intake levels, self-efficacy and perceived barriers. The questionnaire also included items on opportunity-related factors related to the social-cultural environment: parental and peer modeling, active parental encouragement, parental demands to eat FV, whether parents allow the child to eat as much FV as they like (parental allowances), whether parents actively facilitate FV intake by preparing/cutting FV (parental facilitation) and by giving their children FV to bring to school; and related to the perceived physical environment: availability of FV at home, at school, and at friends' home. An overview of the items, constructs, scaling and psychometrics is reported elsewhere(Reference De Bourdeaudhuij, Klepp, Due, Rodrigo, De Almeida, Wind, Krolner, Sandvik and Brug40, Reference Sandvik, De-Bourdeaudhuij and Due41). Usual FV intake was measured using a validated food-frequency questionnaire (FFQ)(Reference Haraldsdottir, Thorsdottir, de Almeida, Maes, Perez Rodrigo, Elmadfa and Frost Andersen42).

Multilevel logistic regression analysis was used to investigate the associations of daily fruit (dichotomous) intake and daily vegetable intake (dichotomous) with the different motivational, ability and opportunity factors. The predictors were also dichotomized into 0 (negative or neutral, response category − 2 to 0·49) or 1 (positive, response category>0·49)(Reference Sandvik, De-Bourdeaudhuij and Due41). Adjusted odds ratios (OR) and 98 % confidence intervals (CI) were calculated for the total sample, both gender groups and all nine countries separately(Reference De Bourdeaudhuij, te Velde and Brug28).

Differences in daily intake of FV

In the total sample 43·2 % of the children reported to eat fruit every day, 46·1 % reported to eat vegetables every day. A significant gender difference was found for both outcome measures: 47·7 % of the girls and only 38·9 % of the boys reported to eat fruit daily (OR:1·44, 98 % CI:1·33–1·56), while 51·8 % of the girls and 40·5 % of the boys reported to eat vegetables every day (OR:1·58, 98 % CI:1·45–1·71). Significant differences were also found between the nine participating countries (p < 0·001). For daily fruit intake, the lowest rates were found in the Nordic countries of Norway, Iceland and Sweden, while the highest proportion of children with daily fruit intake was found in Portugal. For daily vegetable intake, low rates were again found in Norway, Iceland and Spain, and the highest rates were in The Netherlands, Belgium and Portugal.

Correlates of daily FV intakes

For daily fruit intake, motivation, ability as well as opportunity factors appeared to be of relevance. Daily fruit intake was more likely to be reported by children with a positive liking for fruit, with a preference for many different fruits and a positive attitude towards fruit intake. Furthermore, daily fruit intake was more likely among children who knew the national recommendation for fruit intake and with positive self-efficacy. In addition, 4 of the 6 social-environmental factors yielded significance. Daily fruit intake was more likely to be reported by children who experienced positive role models, by those with parents who demand them to eat fruit every day, by children with parents who facilitate fruit intake by cutting up fruit, and by those bringing fruit to school. None of the physical environmental factors was significantly associated with likelihood of daily intake (see Table 1).

Table 1 Odds ratios (ORs1) and 98 % confidence intervals (CI) derived from multilevel logistic regression analyses of the Pro Children Study with daily fruit and vegetabale intakes as dependent variables and motivation, ability and opportuinty factors as independent variables

1 ORs are adjusted for gender, school and country level.

Daily vegetable intake was also related to a positive liking of the taste of vegetables, a preference for different vegetables and a positive attitude towards vegetable consumption. Knowing the national guidelines for adequate vegetable intake and a positive self-efficacy to eat vegetables were also significantly associated with daily vegetable intake. All six social-environmental factors were significantly associated with eating vegetables every day. Finally, children who frequently have available vegetables they like at their home were more likely to report daily vegetable consumption.

In country specific analyses a preference for many fruits was significant in 5 out of 9 countries, a liking of the taste of fruit in 3 countries. Regarding ability-related factors, knowledge of the recommendation was significant in all countries, and in 7 countries daily fruit intake was significantly associated with positive self-efficacy. Of the opportunity-related factors, modeling was significant in all countries, bringing fruit to school was significant in 8 of the 9 countries, and parental demand to eat fruit daily was significant in 6 countries.

Liking the taste of vegetables was significantly associated with daily vegetable intake in 6 out of 9 countries, while preference for many vegetables was significant in 8 countries. Among the ability-related factors, self-efficacy and knowledge of recommendations yielded significance in 6 and 5 countries respectively. Parental demand (7 countries) and modeling (5 countries) were the opportunity factors that were positively associated with daily vegetable intake in a majority of countries (see Table 1).

These analyses indicate that liking and preferences are associated with daily intake of FV among school-aged children in Europe. However, other factors related to ability and opportunity were also important with effect sizes of a similar magnitude as preferences and liking. Effect sizes were in general somewhat larger for fruit intake than for vegetable intake.

Gender differences and liking FV: Fruit and Vegetables Make the Marks (FVMM)

A recent comprehensive review of studies on determinants of children's FV intake stated that gender is among the strongest determinants of adolescents' FV intake(Reference Rasmussen, Krolner, Klepp, Lytle, Brug, Bere and Due38); in 14 of 17 reviewed European studies girls reported to eat more FV than boys. A study was conducted to explore why boys eat less FV than girls and if differences in preferences for these foods explain consumption differences between boys and girls.

This study was part of the FVMM intervention project including 38 randomly selected elementary schools in two Norwegian counties. The pupils within the 20 control schools were used for the study presented here(Reference Bere, Brug and Klepp37). Data from survey questionnaires completed in May 2002 and May 2005 were used for the analyses. The questionnaire surveys were completed by the pupils in the classroom in the presence of a trained project worker, within one school-lesson (45 minutes). The FVMM control group is a cohort of 896 pupils (response 84 %), of which 813 and 728 respectively participated in the May 2002 (mean age 12·5) and May 2005 (mean age 15·5) surveys and also reported same gender at both surveys.

FV intake was measured with a validated short FFQ comparable to the Pro Children Study(Reference Andersen, Bere, Kolbjornsen and Klepp43). Potential mediators for the gender differences in intakes were motivation-related (preferences for FV; intention to eat 5-a-day), ability-related (self-efficacy to eat 5-a-day, knowledge about the 5-a-day recommendation) and opportunity-related (accessibility of FV at home and modelling). These variables were assessed with one to five statements with response alternatives ranging from ‘I fully disagree’ to ‘I fully agree’, except for the knowledge question which had seven response alternatives (for details see(Reference Bere and Klepp44)). These scales have been analysed showing good reliability(Reference Bere and Klepp45).

A variable functions as a mediator when it is associated with the dependent variable (FV intake) and with the indepenent variable, i.e. the potential distal determinant (gender), and when the association between the independent variable (gender) and the dependent variable (FV intake) becomes non-significant or weakens after controlling for the potential mediator(Reference Baron and Kenny46).

All analyses conducted were different mixed models of repeated measures (i.e. both 2002 and 2005 data were included in the same analyses), all adjusting for school and time (survey), using SPSS 14. The analyses carefully tested each of the steps necessary to establish mediation. The proportions mediated by the mediators were calculated by subtracting the adjusted relationship between gender and FV intake (e.g. τ ′) from the unadjusted (τ), and dividing the sum by the unadjusted value (i.e. τ − τ ′/τ)(Reference MacKinnon, Cazares and Beatty47).

Girls reported to eat FV more often than boys and reported significantly more positive values for all the potential mediators (see Table 2).

Table 2 Gender differences in fruit and vegetable intake and in determinants of intake at the first measurement in 2002

In the single mediation analyses all determinants mediated part of the gender differences, but only adjustment for preferences decreased the gender difference to a level below statistical significance (see Table 3). Preferences alone explained 81 % of the gender difference. In the multiple mediation analyses the six mediators together explained 91 % of the gender difference, with preferences contributing with the largest amount (25 %). In addition, perceived accessibility contributed with 10 % of the explanation (data not shown).

Table 3 Single mediator analyses: effect of gender on FV intake after adjusting for accessibility, modelling, intention, preferences, self-efficacy OR knowledge

τ′ = difference in FV intake between boys and girls, while adjusting for single potential mediators.

β′ = difference in the single potential mediators between boys and girls, while adjusting for FV intake.

Mediated′ = proportion of the gender difference in fruit and vegetable intake mediated by the respectively factors.

Discussion

FV intakes among schoolchildren are associated with preferences and liking, and the differences in intakes between girls and boys is strongly mediated by preferences. However, preferences are certainly not the only potential determinant of intakes. Ability and opportunity related factors such as knowledge, self-efficacy, parental influences and accessibility of FV are also associated with daily intake. These results were consistent across different countries in Europe. Accessibility of FV further mediates gender differences in intakes and recent research indicates that socio-economic differences in schoolchildren's FV intakes are more strongly related to accesibility differences than preference differences (Bere et al., unpublished data).

The fact that liking and preferences were related to likelihood of daily intake of both FV has been found in earlier studies(Reference Resnicow, Davis-Hearn, Smith, Baranowski, Lin, Baranowski, Doyle and Wang22, Reference Domel, Thompson, Davis, Baranowski, Leonard and Baranowski48Reference Neumark-Sztainer, Wall, Perry and Story51) and confirms the importance of these motivation-related factors among children. Repeated exposure to many different kinds of FV at early age might be a good strategy to improve liking(Reference Patrick and Nicklas25, Reference Wardle, Herrera, Cooke and Gibson52) and increased intakes have been found to be associated with increased liking (Tak et al., unpublished data). Especially parents can promote preferences for FV in such a way. The results indeed confirm earlier studies that show that parental social environmental factors are important for dietary behaviors among school-aged children(Reference Hanson, Neumark-Sztainer, Eisenberg, Story and Wall53). In line with previous research, perceived modeling was a predictor of daily FV intake(Reference Patrick and Nicklas25, Reference Bere and Klepp50, Reference Gibson, Wardle and Watts54Reference Cullen, Baranowski, Rittenberry, Cosart, Hebert and de Moor56). Such social learning strategies are also important for learning to like the taste of FV. Next to this rather ‘passive’ influence of parental modeling, more active parental encouragement and facilitation was also associated with daily intakes.

Knowledge of the prevailing recommendations was positively related to daily FV intake which indicates that teaching these recommendations in primary schools may help to promote daily intake. School and family influences are very important to influence taste preferences and liking of FV and therefore these are ideal settings for interventions.

Positive self-efficacy was another ability-related factor associated with daily FV intake. The literature is inconsistent about the relationship between self-efficacy and FV intake(Reference Resnicow, Davis-Hearn, Smith, Baranowski, Lin, Baranowski, Doyle and Wang22, Reference Domel, Thompson, Davis, Baranowski, Leonard and Baranowski48, Reference Lien, Jacobs and Klepp49, Reference Young, Fors and Hayes55, Reference Reynolds, Hinton, Shewchuk and Hickey57), probably due to different possible operationalisations of the self-efficacy construct. Self-efficacy can probably be improved by making FV as available and accessible as possible and thus improve opportunity factors, and the Pro Children Study indicates that bringing FV to school is a good strategy to encourage daily FV intakes.

In the present study only home availability appeared to be a significant physical environmental correlate of daily vegetable consumption but not of daily fruit intake, although the association was close to reaching statistical significance. Earlier studies consistently showed positive associations between availability and FV intakes(Reference Bere and Klepp50, Reference Neumark-Sztainer, Wall, Perry and Story51, Reference Hanson, Neumark-Sztainer, Eisenberg, Story and Wall53, Reference Young, Fors and Hayes55, Reference Reynolds, Hinton, Shewchuk and Hickey57, Reference Kratt, Reynolds and Shewchuk58).

Bere et al. confirmed that gender is a strong correlate of FV intake and additionally showed that the gender difference in FV intake could be explained by differences in preferences and asseccibility between boys and girls. That perceived accessibility is higher among girls might be due to the fact that parents raise their daughters in a different way than they raise their sons where foods are concerned, which is also illustrated by observations in the Pro Children study: parents of daughters were more involved in the intervention and participate more often in parental activities than parents of boys (Wind et al., unpublished data). That opportunities for girls to eat FV are better than for boys, might also result in higher motivational factors such as taste preferences. However, from this cross sectional study we cannot conclude on causal relationships between determinants.

The two observational studies and the literature indicate that a wide range of determinants are important in children's FV consumption. However, which determinants of FV are exacly the most important ones is still difficult to answer because determinants are interrelated and from a complex pattern.

Conclusion

The present paper showed that the framwork proposed by Rothshild can help to categorize important determinants of FV intake and dietary intake in general. Furthermore, we showed that motivation factors, such as preferences, are among the most important determinants of FV intake among adolescents and that differences in prefences could also explain discrepancies in FV intake levels between boys and girls.

Moreover, opportunities, such as availability and asseccibility of FV, are important as well and more research is needed to assess potential moderating roles of availabity and/of motivational factors.

Conflict of interest statement

None of the authors has any conflicts of interest to report.

References

1Koletzko, B, de la Guéronnière, V, Toschke, AM & von Kries, R (2004) Nutrition in children and adolescents in Europe: what is the scientific basis? Introduction. Br J Nutr 92, Suppl. 2, S67S73.CrossRefGoogle ScholarPubMed
2Birch, LL (1999) Development of food preferences. Annu Rev Nutr 19, 4162.CrossRefGoogle ScholarPubMed
3Kelder, SH, Perry, CL, Klepp, KI & Lytle, LL (1994) Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors. Am J Public Health 84, 11211126.CrossRefGoogle ScholarPubMed
4Lien, N, Lytle, LA & Klepp, KI (2001) Stability in consumption of fruit, vegetables, and sugary foods in a cohort from age 14 to age 21. Prev Med 33, 217226.CrossRefGoogle Scholar
5te Velde, SJ, Twisk, JWR & Brug, J (2007) Tracking of fruit and vegetable consumption from adolescence into adulthood and its longitudinal association with overweight. Br J Nutr 98, 431438.CrossRefGoogle ScholarPubMed
6Yngve, A, Wolf, A, Poortvliet, E, et al. (2005) Fruit and vegetable intake in a sample of 11-year-old children in 9 European countries: the Pro Children cross-sectional survey. Ann Nutr Metab 49, 236245.CrossRefGoogle Scholar
7Brug, J, Oenema, A & Ferreira, I (2005) Theory, evidence and Intervention Mapping to improve behavioral nutrition and physical activity interventions. Int J Behav Nutr Phys Act 2, 2.CrossRefGoogle ScholarPubMed
8Baranowski, T, Baranowski, J, Cullen, KW, Marsh, T, Islam, N, Zakeri, I, Honess-Morreale, L & de Moor, C (2003) Squire's Quest!: dietary outcome evaluation of a multimedia game. Am J Prev Med 24, 5261.CrossRefGoogle ScholarPubMed
9Klepp, KI, Pérez-Rodrigo, C, De Bourdeaudhuij, I, et al. (2005) Promoting fruit and vegetable consumption among European schoolchildren: rationale, conceptualization and design of the Pro Children Project. Ann Nutr Metab 49, 212220.CrossRefGoogle ScholarPubMed
10Conner, M & Armitage, CJ (2002) The Social Psychology of Food. Buckingham, UK: Open University Press.Google Scholar
11Sallis, JF & Owen, N (2002) Ecological models of health behavior. In Health Behavior and Health Education: Theory, Research, and Practice, 3rd ed., pp. 462484 [Glanz, K, Rimer, BK and Lewis, FM, editors]. San Francisco: Jossey-Bass.Google Scholar
12Rothschild, ML (1999) Carrots, sticks, and promises: a conceptual framework for the management of public health and the social issue behaviors. J Mark 63, 2437.CrossRefGoogle Scholar
13van Trijp, HCM, Brug, J & van der Maas, R (2005) Consumer determinants and intervention strategies for obesity prevention. In Food, Diet and Obesity, pp. 331356 [Mela, DJ, editor]. Woodhead Publishing in Food Science and Technology: Cambridge, UK.CrossRefGoogle Scholar
14Capaldi, ED (1996) Why We Eat What We Eat: The Psychology of Eating, pp. 5380 [Capaldi, ED, editor]. Washington, DC: American Psychological Association.CrossRefGoogle Scholar
15Rozin, P (1990) Development in the food domain. Dev Psychol 26, 555562.CrossRefGoogle Scholar
16Cooke, LJ & Wardle, J (2005) Age and gender differences in children's food preferences. Br J Nutr 93, 741746.CrossRefGoogle ScholarPubMed
17Lennernäs, M, Fjellström, C, Becker, W, Giachetti, I, Schmitt, A, Remaut de Winter, A & Kearney, M (1997) Influences on food choice perceived to be important by nationally-representative samples of adults in the European Union. Eur J Clin Nutr 51, Suppl. 2, S8S15.Google ScholarPubMed
18Health Focus (2005) 2005 Health Focus US trend report. Health Focus International, St. Petersburg, FL. Available fromwww.healthfocus.com.Google Scholar
19Story, M, Neumark-Sztainer, D & French, S (2002) Individual and environmental influences on adolescent eating behaviors. J Am Diet Assoc 102, Suppl. 3, S40S51.CrossRefGoogle ScholarPubMed
20Sheeran, P (2002) Intention-behavior relations: a conceptual and empirical review. In European Review of Social Psychology, vol. 12, pp. 136 [Hewstone, M and Stroebe, W, editors]. Chichester, UK: Wiley.Google Scholar
21Heatey, KR & Thombs, DL (1997) Fruit–vegetable consumption self-efficacy in youth. Am J Health Behav 21, 172177.Google Scholar
22Resnicow, K, Davis-Hearn, M, Smith, M, Baranowski, T, Lin, LS, Baranowski, J, Doyle, C & Wang, DT (1997) Social-cognitive predictors of fruit and vegetable intake in children. Health Psychol 16, 272276.CrossRefGoogle ScholarPubMed
23Wind, M, De Bourdeaudhuij, I, te Velde, SJ, Sandvik, C, Klepp, KI, Due, P & Brug, J (2006) Correlates of fruit and vegetable consumption among 11-year-old Belgian-Flemish and Dutch schoolchildren. J Nutr Educ Behav 38, 211221.CrossRefGoogle ScholarPubMed
24Swinburn, B, Egger, G & Raza, F (1999) Dissecting obesogenic environments: the development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med 29, 563570.CrossRefGoogle ScholarPubMed
25Patrick, H & Nicklas, TA (2005) A review of family and social determinants of children's eating patterns and diet quality. J Am Coll Nutr 24, 8392.CrossRefGoogle ScholarPubMed
26Brug, J, Van Lenthe, FJ & Kremers, SPJ (2006) Revisiting Kurt Lewin: how to gain insight into environmental correlates of obesogenic behaviors. Am J Prev Med 31, 525529.CrossRefGoogle ScholarPubMed
27De Bourdeaudhuij, I & Van Oost, P (1996) De relatie tussen op jonge leeftijd aangeleerde voedingsregels en voedingskeuze in de adolescentie (The relation between in childhood acquired dietary habits and dietary choices in adolescence). Gedrag en Gezondheid 24, 215223.Google Scholar
28De Bourdeaudhuij, I, te Velde, SJ, Brug, J, et al. (2007) Personal, social and environmental predictors of daily fruit and vegetable intake in 11-year-old children in nine European countries. Eur J Clin Nutr, advance online publication 16 May 2007; doi: 10.1038/sj.ejcn.1602794.Google ScholarPubMed
29Kremers, SPJ, Brug, J, de Vries, H & Engels, RCME (2003) Parenting style and adolescent fruit consumption. Appetite 41, 4350.CrossRefGoogle ScholarPubMed
30Patrick, H, Nicklas, TA, Hughes, SO & Morales, M (2005) The benefits of authoritative feeding style: caregiver feeding styles and children's food consumption patterns. Appetite 44, 243249.CrossRefGoogle ScholarPubMed
31Cullen, KW, Baranowski, T, Owens, E, Marsh, T, Rittenberry, L & de Moor, C (2003) Availability, accessibility, and preferences for fruit, 100 % fruit juice, and vegetables influence children's dietary behavior. Health Educ Behav 30, 615626.CrossRefGoogle ScholarPubMed
32Wardle, J, Jarvis, MJ, Steggles, N, Sutton, S, Williamson, S, Farrimond, H, Cartwright, M & Simon, AE (2003) Socioeconomic disparities in cancer-risk behaviors in adolescence: baseline results from the Health and Behaviour in Teenagers Study (HABITS). Prev Med 36, 721730.CrossRefGoogle ScholarPubMed
33van der Horst, K, Kremers, S, Ferreira, I, Singh, A, Oenema, A & Brug, J (2007) Perceived parenting style and practices and the consumption of sugar-sweetened beverages by adolescents. Health Educ Res 22, 295304.CrossRefGoogle ScholarPubMed
34Story, M & French, S (2004) Food advertising and marketing directed at children and adolescents in the US. Int J Behav Nutr Phys Act 1, 3.CrossRefGoogle ScholarPubMed
35Halford, JC, Boyland, EJ, Hughes, G, Oliveira, LP & Dovey, TM (2007) Beyond-brand effect of television (TV) food advertisements/commercials on caloric intake and food choice of 5–7-year-old children. Appetite 49, 263267.CrossRefGoogle ScholarPubMed
36Brug, J (2007) The European charter for counteracting obesity: a late but important step towards action. Observations on the WHO-Europe ministerial conference, Istanbul, November 15–17, 2006. Int J Behav Nutr Phys Act 4, 11.CrossRefGoogle ScholarPubMed
37Bere, E, Brug, J & Klepp, KI (2007) Why do boys eat less fruit and vegetables than girls? Public Health Nutr, In press.Google ScholarPubMed
38Rasmussen, M, Krolner, R, Klepp, KI, Lytle, L, Brug, J, Bere, E & Due, P (2006) Determinants of fruit and vegetable consumption among children and adolescents: systematic review of the literature. Int J Behav Nutr Phys Act 3, .CrossRefGoogle Scholar
39Wind, M, Bobelijn, K, De Bourdeaudhuij, I, Klepp, KI & Brug, J (2005) A qualitative exploration of determinants of fruit and vegetable intake among 10- and 11-year-old schoolchildren in the low countries. Ann Nutr Metab 49, 228235.CrossRefGoogle ScholarPubMed
40De Bourdeaudhuij, I, Klepp, KI, Due, P, Rodrigo, CP, De Almeida, MDV, Wind, M, Krolner, R, Sandvik, C & Brug, J (2005) Reliability and validity of a questionnaire to measure personal, social and environmental correlates of fruit and vegetable intake in 10–11-year-old children in five European countries. Public Health Nutr 8, 189200.CrossRefGoogle ScholarPubMed
41Sandvik, C, De-Bourdeaudhuij, I, Due, P, et al. (2005) Personal, social and environmental factors regarding fruit and vegetable intake among schoolchildren in nine European countries. Ann Nutr Metab 49, 255266.CrossRefGoogle ScholarPubMed
42Haraldsdottir, J, Thorsdottir, I, de Almeida, MD, Maes, L, Perez Rodrigo, C, Elmadfa, I & Frost Andersen, L (2005) Validity and reproducibility of a precoded questionnaire to assess fruit and vegetable intake in European 11- to 12-year-old schoolchildren. Ann Nutr Metab 49, 221227.CrossRefGoogle ScholarPubMed
43Andersen, LF, Bere, E, Kolbjornsen, N & Klepp, KI (2004) Validity and reproducibility of self-reported intake of fruit and vegetable among 6th graders. Eur J Clin Nutr 58, 771777.CrossRefGoogle Scholar
44Bere, E & Klepp, KI (2005) Changes in accessibility and preferences predict children's future fruit and vegetable intake. Int J Behav Nutr Phys Act 2, 15.CrossRefGoogle ScholarPubMed
45Bere, E & Klepp, KI (2004) Reliability of parental and self-reported determinants of fruit and vegetable intake among 6th graders. Public Health Nutr 7, 353356.CrossRefGoogle Scholar
46Baron, RM & Kenny, DA (1986) The moderator–mediator variable distinction in social psychological research: conceptual strategic, and statistical considerations. J Pers Soc Psych 51, 11731182.CrossRefGoogle ScholarPubMed
47MacKinnon, DP (1994) Analysis of mediating variables in prevention and intervention research. In Scientific Methods for Prevention Intervention Research (NIDA research monograph no. 139 DHHS Pub. no. 94-3631). pp. 127153 [Cazares, A and Beatty, LA, editors]. Washington, DC: US Department of Health and Human Services.Google Scholar
48Domel, SB, Thompson, WO, Davis, HC, Baranowski, T, Leonard, SB & Baranowski, J (1996) Psychosocial predictors of fruit and vegetable consumption among elementary school children. Health Educ Res 11, 299308.CrossRefGoogle Scholar
49Lien, N, Jacobs, DR & Klepp, KI (2002) Exploring predictors of eating behaviour among adolescents by gender and socio-economic status. Public Health Nutr 5, 671681.CrossRefGoogle ScholarPubMed
50Bere, E & Klepp, KI (2004) Correlates of fruit and vegetable intake among Norwegian schoolchildren: parental and self-reports. Public Health Nutr 7, 991998.CrossRefGoogle ScholarPubMed
51Neumark-Sztainer, D, Wall, M, Perry, C & Story, M (2003) Correlates of fruit and vegetable intake among adolescents: findings from Project EAT. Prev Med 37, 198208.CrossRefGoogle ScholarPubMed
52Wardle, J, Herrera, ML, Cooke, L & Gibson, EL (2003) Modifying children's food preferences: the effects of exposure and reward on acceptance of an unfamiliar vegetable. Eur J Clin Nutr 57, 341348.CrossRefGoogle ScholarPubMed
53Hanson, NI, Neumark-Sztainer, D, Eisenberg, ME, Story, M & Wall, M (2005) Associations between parental report of the home food environment and adolescent intakes of fruits, vegetables and dairy foods. Public Health Nutr 8, 7785.CrossRefGoogle ScholarPubMed
54Gibson, EL, Wardle, J & Watts, CL (1998) Fruit and vegetable consumption, nutritional knowledge and beliefs in mothers and children. Appetite 31, 205228.CrossRefGoogle ScholarPubMed
55Young, EM, Fors, SW & Hayes, DM (2004) Associations between perceived parent behaviors and middle school student fruit and vegetable consumption. J Nutr Educ Behav 36, 28.CrossRefGoogle ScholarPubMed
56Cullen, KW, Baranowski, T, Rittenberry, L, Cosart, C, Hebert, D & de Moor, C (2001) Child-reported family and peer influences on fruit, juice and vegetable consumption: reliability and validity of measures. Health Educ Res 16, 187200.CrossRefGoogle ScholarPubMed
57Reynolds, KD, Hinton, AW, Shewchuk, R & Hickey, CA (1999) Social cognitive model of fruit and vegetable consumption in elementary school children. J Nutr Educ 31, 2330.CrossRefGoogle Scholar
58Kratt, P, Reynolds, KD & Shewchuk, R (2000) The role of availability as a moderator of family fruit and vegetable consumption. Health Educ Behav 27, 471482.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Odds ratios (ORs1) and 98 % confidence intervals (CI) derived from multilevel logistic regression analyses of the Pro Children Study with daily fruit and vegetabale intakes as dependent variables and motivation, ability and opportuinty factors as independent variables

Figure 1

Table 2 Gender differences in fruit and vegetable intake and in determinants of intake at the first measurement in 2002

Figure 2

Table 3 Single mediator analyses: effect of gender on FV intake after adjusting for accessibility, modelling, intention, preferences, self-efficacy OR knowledge