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Can knowledge alone predict vegetable and fruit consumption among adolescents? A transtheoretical model perspective

Hussein, Rania Abd El Hamid

The Journal Of The Egyptian Public Health Association: December 2011 - Volume 86 - Issue 5 and 6 - p 95–103
doi: 10.1097/01.EPX.0000407136.38812.55
Original articles
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Background Nutrition clearly plays a role during adolescent development. Nutritional habits are not in line with the recommendations among adolescents. Food habits that are seen more frequently among teens than in other age groups include irregular consumption of meals, and eating away from home (especially fast-food venues). In addition, many young people do not eat enough fruits and vegetables (FVs).

Aim We aimed at exploring the knowledge, attitude, and behavior toward FV consumption among adolescent Saudi girls, using a transtheoretical model (TTM).

Participants and methods A cross-sectional study was conducted. The target group included adolescent girls aged 18–21 years, students at the Faculty of Applied Medical Sciences, at King Abdulaziz University, Kingdom of Saudi Arabia. Of a total sample of 205 participants, 73 were in the Clinical Nutrition Department. FV consumption was assessed among the whole sample, using a Food Frequency questionnaire, and then the TTM determinants were assessed.

Results The study detected significant differences between the two groups with regard to vegetable consumption. The most frequently reported stage of change in the nutrition department was action maintenance with regard to FV consumption; self-efficacy and pros were the most significant positive predictors for FV consumption, whereas the department type (determining knowledge) had a negligible effect. Finally, we detected that TTM determinants of FV intake and their stages of change clustered.

Conclusion and recommendations Knowledge alone cannot predict FV intake in adolescent girls. TTM stages of change and determinants seem to be somewhat related in FV consumption. Therefore, an integrated dietary change approach for both FV consumption is recommended among adolescents.

Department of Clinical Nutrition, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia

Correspondence to Rania Abd El Hamid Hussein, PhD, King Abdulaziz University, Al Jamea district, Faculty of Applied Medical Sciences, Department of Clinical Nutrition, PO box: 80200. Jeddah, Kingdom of Saudi Arabia Tel: +966 695 2000 x 24220e-mail: rahussein2002@yahoo.com

Received July 27, 2011

Accepted August 27, 2011

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Introduction

Diet and nutrition clearly play a critical role during childhood and adolescent development. Children and adolescents need to cover their nutrient and energy needs not only for the maintenance of metabolism and physical activities but also for growth 1.

To develop effective interventions, determinants of fruit and vegetable (FV) consumption should be identified 2. Intervention strategies must then be tailored to the target populations and to the most important and best modifiable determinants of behavior 3.

Adolescent dietary behavior is likely to be strongly influenced by environmental factors, such as availability and cost of healthy and unhealthy choices 4, and social groups including the family, friends, and the work group 5.

Accessibility and availability of food in schools are important physical environmental factors. Adolescents can find vending machines and snack food outlets at many schools 6. Moreover, peers at school have a pronounced effect on adolescents’ eating behavior 7.

The transtheoretical model (TTM) is one of the most popular models for studying behavioral determinants; it assesses an individual’s readiness to act on a new healthier behavior, and provides strategies or processes of change to guide the individual through the stages of change to action and maintenance 8. TTM, is also known by the term ‘stages of change model’ 9.

According to TTM, health behavior change involves progression through five stages:

Precontemplation (P) is the stage at which there is no intention to change behavior in the foreseeable future. Many individuals in this stage are unaware of their problems. Contemplation is the stage in which people are aware that a problem exists, and are seriously thinking about overcoming it, but have not yet made a commitment to take action. Preparation is a stage that combines intention and behavioral criteria. Individuals are intending to take action in the next month or have unsuccessfully taken action in the past year. Action is the stage in which individuals modify their behavior to overcome their problems. Maintenance is the stage in which people work to prevent relapse and consolidate the gains attained during action (duration) 10.

Specific TTM components include decisional balance and self-efficacy. Both should be applied in interventions to facilitate the progression to further stages of change. Decisional balance refers to an individual’s relative weighing of pros and cons 11, whereas perceived self-efficacy is concerned with individuals’ beliefs in their capability to exercise control over challenging demands 12.

Low self-efficacy may be due to a perceived lack of support from family, perceived inability to plan meals and snacks that include more FVs, or failures at previous attempts to change behavior 13. Previous researches suggested that dietary self-efficacy may have an important mediating role in the relationship between diet knowledge and behavior in the general population settings 14.

The aim of the present study is to explore the knowledge, attitude, and behavior toward FV consumption among adolescent Saudi girls, using a TTM. The specific objectives were to estimate the amount of FV consumption among adolescent female students at King Abdulaziz University, Kingdom of Saudi Arabia, to test the determinants of FV intake and their stages of change cluster, and to detect the correlation between stages of change for FV intake, and the presumed stage transition predictors, that is, decisional balance and self-efficacy.

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Participants and methods

A cross-sectional study was conducted during January to February 2011. Our target population included adolescent girls aged 18–21 years, students in 2nd, 3rd, and 4th years at the faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. Before conducting the study, an official approval was obtained from the vice dean of the Faculty of Applied Medical Sciences.

The study involved 205 adolescent girls, students at the faculty of applied medical science in KAU; 73 of them were clinical nutrition students and the remaining 132 were students of other departments (radiology, physiotherapy, and laboratories).

First, a member of the research team explained to the leader of each class the goal, objectives, and the steps needed to be understood before answering the questionnaire. Then at a convenient time, each respondent was handed a questionnaire, and asked to complete it while in the room. The questionnaire was completed in 15–20 min.

Bias was minimized by assembling students in their own classroom, assuming a high response rate, selecting the time convenient to them, allowing respondents to ask for clarification, at which time there was no interviewer bias, and assuring the respondents about anonymity and confidentiality, and declaring that participation is voluntary.

The questionnaire comprised the following data:

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Fruit and vegetable consumption

These two dietary behaviors were measured using food frequency questionnaires asking ‘how often did you consume the listed products in the past year?’ (ranging from ‘not consumed’ to ‘3 times daily’). FV consumption were assessed using the most commonly consumed products in Jeddah.

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Determinants (predictors) of transtheoretical model

Decisional balance

This was assessed by asking respondents how important each of the listed pros and cons was in their decision to eat recommended amounts of fruits or vegetables using five-point bipolar adjective pairs ranging from 1 (not at all important) to 4 (very important). The decisional balance was assessed with the following:

Pros: five pros for vegetables and six pros for fruit intake (see Appendix).

Response to pros importance ranged from 5 to 20 for vegetables. It was categorized as follows:

  • 5 to <10 was considered poor pros importance.
  • 10 to <15 was considered fair pros importance.
  • 15 to 20 was considered strong pros importance.

Response to pros importance ranged from 6 to 24 for fruits. It was categorized as follows:

  • 6 to <12 was considered poor pros importance.
  • 12 to <18 was considered fair pros importance.
  • 18–24 was considered strong pros importance.

Cons: In contrast, five cons for FV intake were used to assess the decisional balance (see Appendix).

Response to cons importance ranged from 5 to 20 for FVs. It was categorized as follows:

  • 5 to <10 was considered poor cons importance.
  • 10 to <15 was considered fair cons importance.
  • 15–20 was considered strong cons importance.
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Self-efficacy

Self-efficacy was assessed by asking respondents to rate on five-point bipolar adjective pairs ranging from 4 (very confident) to 1 (not confident at all) as to how they find themselves capable of eating according to the recommendations in seven high-risk situations, for each of the two dietary behaviors (see Appendix). Response to self-efficacy ranged from 7 to 28. It was categorized as follows:

  • 7 to <14 was considered poor self-efficacy.
  • 14 to <21 was considered fair self-efficacy.
  • 21–28 was considered strong self-efficacy.
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Stages of change of transtheoretical model

Stages of change for FV consumption were assessed with one-item staging instruments, with a five-choice response format. First, a description of the My Pyramid Food Guidance System recommendations for each of the dietary behaviors was presented to ensure a correct understanding of the target behavior. Next, respondents were asked whether they met the recommended intake levels for the dietary behaviors, by selecting one of five statements, each representing a stage of change (see Appendix).

For ease of statistical analysis, responses were categorized into three stages with regard to their stage of change:

  • P: for precontemplation stage
  • CP: for those in contemplation and preparation stages
  • AM: for those in action and maintenance

The Nutrition department group was coded 1, and the nonnutrition department groups were coded 2.

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Statistical analysis

Descriptive statistics

At the end of the study, data obtained were coded, tabulated, and presented by arithmetic mean and SD.

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Inferential statistics

Statistical analysis was performed using the statistical package for social sciences (SPSS), version 16 (Social Sciences Research Center, California, USA) 15.

Data were analyzed using the following:

  • Independent sample t-test for comparison of means.
  • χ2 test for testing the association between two categorical variables.
  • Spearman correlation test for detection of risk factors.

Differences were considered significant at the 0.05 level.

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Results

There was a significant difference between students of the nutrition and the nonnutrition departments with regard to the number of vegetable servings consumed per day (P=0.009). The majority of the nutrition department students (64.3%) were eating at least three servings of vegetables per day, whereas only 45.5% of the nonnutrition department students were eating the same number of servings of vegetables daily (Table 1).

Table 1

Table 1

In contrast, no significant difference was observed between the two categories of students, with regard to the number of fruit servings consumed per day. Most of the nutrition and the nonnutrition department students were eating at least two servings of fruits per day (61.64 and 51.51%, respectively, Table 2).

Table 2

Table 2

There was a significant difference between the nutrition and the nonnutrition department students with regard to their stages of TTM for vegetables (P=.005). The most frequently reported stage of change among the nutrition department was AM (63%), whereas none of them belonged to the P stage. In contrast, 10.6% of the nonnutrition department students were precontemplators, and the rest were nearly equally distributed between the CP and the AM stages (Fig. 1).

Figure 1

Figure 1

In contrast, there was no significant difference between students in the nutrition and the nonnutrition departments with regard to their stages of TTM for fruits. The most frequently reported stage of change among both departments was AM (55.6% of the whole sample). The most frequently reported stage of change among the nutrition department was AM (action maintenance) (63%). None of them was in the P stage.

Both AM and CP were nearly equally and frequently reported stages of change among the nonnutrition department (51.6 and 44%, respectively), whereas 4.5% of them belonged to the P stage (Fig. 2).

Figure 2

Figure 2

With regard to the predictors of the TTM staging for vegetable consumption, self-efficacy for vegetables and for fruits, followed by pros of vegetables and those of fruits, were the positive significant predictors (Table 3).

Table 3

Table 3

Similarly, in the TTM staging for fruit consumption, pros of fruits and those of vegetables, and the self-efficacy for vegetables and for fruits, predicted the TTM staging.

In addition, the TTM staging for vegetable consumption and that of fruit consumption were moderately correlated (r=0.451). There was a strong positive correlation between the pros of vegetables with those of fruits (0.607). Cons were not a risk factor predicting adolescent girls’ behavior with regard to vegetable or fruit consumption. However, they correlated strongly together (r=0.665).

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Discussion

The present study found a significant correlation between the type of department and the pattern of vegetable consumption, namely the number of servings and the TTM staging. P is the stage at which there is no intention to change behavior in the foreseeable future. Many individuals in this stage are unaware of the problem 10; this might explain the absence of precontemplators among the nutrition department students.

Knowledge can influence food-related behavior. Knowing why to eat healthfully, knowing what healthful foods are, and knowing the recommended intake levels may all be conditional for voluntary healthful eating 16.

In contrast, there was no significant difference between the two groups with regard to fruit intake and TTM staging. This can be explained by the fact that fruits are more delicious than vegetables, they are always available at home, and they make one feel better 17.

With regard to predictors of the TTM staging, self-efficacy and pros for FV intake were the positive significant predictors. This is consistent with TTM, which hypothesizes that the pros of changing must increase to progress from P, cons of changing must decrease to progress from contemplation 11, and that self-efficacy must increase monotonically from P to maintenance 18.

Positive self-efficacy is an important ability-related factor associated with daily FV intake 19. Moreover, studies in children and adolescents showed that food and nutrition-related self-efficacy is associated with healthful food choices and dietary behavior 20. Intention is influenced by a subjective weighing of expected positive and negative consequences of the behavior 21.

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 22. In addition, nutrient-dense diets are associated with higher costs 23. Youth may be less likely than adults to weigh the full costs of their food consumption decisions, placing too much emphasis on short-term utility gains and not enough emphasis on long-term health consequences 24.

However, in our study, cons did not predict stage transitions for FV intake. This might be explained by the current strategies that attempt to promote FV consumption in schools. Exposing students to quantities of a wide variety of attractively presented and affordable products, marketed in a way that appeals to adolescents, encourages greater consumption 24. Moreover, recent recommendations for intake of fruits emphasize their consumption in either fresh, frozen, canned, dried, or juice forms 25. Significant price reductions may also be a factor 24.

In the present study, knowledge was certainly not the only potential determinant of FV intake. This is consistent with studies showing that ability-related and opportunity-related factors such as self-efficacy 26, parental influence 5,6, and the pros and cons to FV consumption 27 were also associated with daily intake. Hence, knowledge alone is an insufficient condition for healthy food choice 16.

Yngve et al. found that only a small proportion of youth was meeting the current dietary recommendations for FV intake 28. Moreover, Di Noia et al. found that the highest concentration of youth was in the contemplation-preparation stage, followed by P stage 29. However, the present study showed that 52.19 and 55.12% of adolescent girls were following the current dietary recommendations for FV consumption, respectively. In addition, the most frequently reported stage of change for FV consumption among both departments was action maintenance (AM) (55.6% of the whole sample).

In fact, girls reported eating FVs more often than boys, and reported significantly more positive values for all the potential mediators 27. Bere et al. confirmed that sex is a strong correlate of FV intake. Perceived accessibility is higher among girls due to the fact that parents raise their daughters in a different way than they raise their sons where food is concerned. Parents of daughters participate more often in parental activities than parents of boys; this might also result in higher motivational factors such as taste preferences 30.

FVs are commonly eaten at different occasions, and some studies found that behavioral determinants differ for FV intake 3. According to the ‘My pyramid’, three to five servings of vegetables should be consumed per day, whereas two to four servings of fruit should be consumed per day 25. Certain countries such as the Netherlands separate the recommendations provided for fruits (two servings of fruit each day, which corresponds to 250 g a day) and those of vegetables (200 g each day) 31. However, in many other countries such as in the United States, FVs are considered one food category, and hold one recommendation for both FVs (e.g. the five a day recommendation) 3.

In the present study, the TTM staging for FV consumption correlated moderately (r=0.451). Moreover, there was a strong positive correlation between the pros and the cons of vegetables with those of fruits (0.607 and 0.665, respectively), hence supporting an integrated dietary change approach for improving the consumption of FV among adolescents.

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Implications

This is one of the first studies to examine the application of the TTM to FV consumption among adolescent girls in the middle east. The results of this study hopefully will aid future researchers in the development of effective nutrition education programs.

The fact that nearly half the participants of the nonnutrition departments were in contemplation-preparation stages (43.2 and 44% with regard to FV consumption regularly) suggests that, temporally, they are prepared to take action to improve their diets in the near future and are therefore ready for intervention.

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Conclusion and recommendations

Our findings indicate that knowledge alone cannot predict FV intake in adolescent girls. Therefore, future programs designed to improve diets for this population should not only be focused on increasing awareness of benefits, but also on seeking to increase the self-efficacy of eating FV. Use of peers, students, or parents to demonstrate FV intake is a common role-modeling strategy for enhancing self-efficacy.

Moreover, TTM components, stages of change, and determinants of FV consumption seem to be somewhat related. Hence, we recommend an integrated dietary change approach for both FV consumption among adolescents.

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Acknowledgements

We thank Afnan S. Azhari, Khadijh A. Al-zahran, Layla M. AL-Qahtani, Nedáa S. Al-Ahmadi, and the students at the Clinical Nutrition Department, Faculty of Applied Medical Sciences, King Abdulaziz university, for their efforts in data collection, coding, data entry, and tabulation.

Work attribution: Clinical Nutrition Department, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia.

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Conflicts of interest

There are no conflicts of interest.

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Appendix

A questionnaire on behavior and attitude toward consuming vegetables and fruits.

First: Selective food frequency questionnaire for vegetables, and fruits:

Second: To your opinion, what are advantages of eating the following food group?

Third: To your opinion, what are disadvantages of eating the following food group?

Forth: To what extent you trust your ability to consume the adequate quantity of vegetables and fruits in the following conditions:

Fifth: Select what describes your dietary behavior as regards vegetables and fruits ' consumption:

1 - I take 3 servings of vegetables a day, and have started this more than six months ago.

2 - I take 3 servings of vegetables a day , and have started this less than six months ago.

3 - I eat less than 3 servings of vegetables a day, but I intend to change next month.

4 - I eat less than 3 servings of vegetables a day , but I intend to change in six months.

5 - I eat less than 3 servings of vegetables a day, I do not intend to change.

1 - I take 2 servings of fruits a day, and have started this more than six months ago.

2 - I take 2 servings of fruits a day , and have started this less than six months ago.

3 - I eat less than 2 servings of fruits a day, but I intend to change next month.

4 - I eat less than 2 servings of fruits a day , but I intend to change in six months.

5 - I eat less than 2 servings of fruits a day, I do not intend to change.

Keywords:

attitude; cons; fruits; knowledge; pros; self-efficacy; transtheoretical model; vegetables

© 2011 Egyptian Public Health Association