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Mazloomy Mahmoodabad S S, Mohammad Yousefivardanjani Z, Fallahzadeh H, Farrokhian A. Predictors of Fast Food Consumption Based on Prototype/Willingness Model among Students of Yazd University of Medical Sciences. JNFS 2019; 4 (2) :76-82
URL: http://jnfs.ssu.ac.ir/article-1-253-en.html
Professor of Biostatistics, Department of Biostatistics and Epidemiology, Research Center of Prevention and Epidemiology of Non-Communicable Disease, Faculty of Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
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Predictors of Fast Food Consumption Based on Prototype/Willingness Model among Students of Yazd University of Medical Sciences
Seyed Saeed Mazloomy Mahmoodabad; PhD1,2, Zahra Mohammad Yousefivardanjani; MSc*2, Hossein Fallahzadeh; PhD3,4 & Asma Farrokhian; MSc2
1 Social Determinants of Health Research Center, School of Public Health, Shahid Sadoughi Yazd University of Medical Sciences, Yazd, Iran.
2 Department of Health Education and Promotion, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
3Department of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
4Research Center of Prevention and Epidemiology of Non-Communicable Disease, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
 
ARTICLE INFO   ABSTRACT
ORIGINAL ARTICLE Background: Consumption of fast food, as a consequence of the modern industrial society, has increased in recent years among teenagers and young people. The purpose of this study was to investigate the effect of fast food consumption on female students in Yazd University of Medical Sciences based on the Prototype/Willingness Model. Methods: In this descriptive-analytic study, 245 female dormitory students were selected from Yazd University of Medical Sciences by stratified sampling from six dorms. Data were collected using a valid, reliable, and self-reporting questionnaire including demographic information and constructs of Prototype/Willingness Model. To analyze the data, correlation, regression, and ANOVA were applied using SPSS18. Results: Participants' maximum scores of intention with regard to non-consumption of fast foods, subjective norms, attitude, willingness, and prototype were 57, 53, 51, 67.5, and 66.2 percent, respectively. Intention to non-consumption of fast foods had a positive significant correlation with subjective norms, attitude, willingness, and prototype of fast food consumption. The combination of attitude and subjective norms accounted for 0.17 percent of the variance in intention. Moreover, attitude was the most significant predictor of intention (β = 0.38). Conclusion: According to the predictability of attitudes towards behavioral intention about fast food consumption, the individuals' negative attitudes should be enhanced towards fast food consumption in designing education programs for youth.
Keywords: Fast food; Students; Prototype/Willingness model.
Article history:
Received: 21 Jan 2018
Revised: 18 Mar 2018
Accepted: 14 May 2018
 
*Corresponding author
zahrayousefi93@yahoo.com
School of Public Health, Shahid Sadoughi University of Medical Sciences,Yazd, Iran.
 
Postal code: 8915173160
Tel: +98- 9139787449
 
Introduction
 
Over the last 30 years, fast food (already-prepared food) consumption has developed dramatically in the United States and Europe (Yarmohammadi et al., 2011). These changes are the result of people's lifestyle changes. Currently, with the development of science and industry, people's lifestyles changed, indigenous food habits decreased, and prevalence of fast food consumption developed in most societies, including Iran (Dadipoor et al., 2014, Fazelpour et al., 2011).
Fast food and trans fatty acids are so fattening due to their high amounts of calories (Dadipoor et al., 2014). According to the World Health Organization (WHO), in a healthy diet, less than 30 percent of energy should be fed from fats and unsaturated fats are preferred over the saturated fats. Industrial trans-fats processed food, fast food, fried food, and Pizza are part of an unhealthy diet (Fats, 2010, Hooper et al., 2012, World Health Organization, 2003). Consumption of high-fat foods (including fast food) is often associated with obesity, increased cholesterol, cardiovascular disease, type 2 diabetes, and some cancers (Bowman et al., 2004, Key et al., 2004).
The prevalence of fast food is due to the fact that they changed the traditional family structure; fast foods are delicious, low-cost, and available (Driskell et al., 2006, French et al., 2000). In fact, today's standard for food consumption is taste and fast foods are more desirable and delicious for people considering their additives and salt, which provide a good flavor (Fazelpour et al., 2011). Therefore, fast foods are very popular among teenagers and young people. Furthermore, research showed that about a third of these people have daily consumption of  fast foods (Bowman et al., 2004, Fazelpour et al., 2011). In the study by Paeratakul, 37 percent of teenagers and 42 percent of children consumed fast foods (Paeratakul et al., 2003). A study by Fazelpour et al. in Yazd indicated that 90.8 percent of participants used fast foods at least once a day. Moreover, consumption of already-made foods in students, self-employed, and unemployed individuals was higher than other groups (Fazelpour et al., 2011).
The main goal of health education is to change the behavior of participants since behavioral acceptance including nutritional behavior depends on the individuals' beliefs. Selection of a model for health education is the first step in the planning process of educational programs (Mainbolagh et al., 2012) In addition, some scholars believe that one reason for the failure of educational programs is the lack of attention to cognitive studies and their design, regardless of psychosocial models, which are considered as a specific framework for educational planning (Barati et al., 2015). The incidence of obesity and other complications can be reduced by changing nutritional behaviors, especially by reducing fast food consumption (Brownell, 2005).
In terms of behavior change, models and theories provide guidelines to take measures about health education. These models and theories can answer the questions of program designers, such as why people do not behave desirably? How should the mentioned behavior change? and what factors should be considered in appraisal of programs? (Glanz et al., 1990).
For the high-risk behaviors of young people, two decision-making hypotheses exist. The first hypothesis is that the decision making process includes an analytical and logical process. It states that the individual is treating by considering all parts of the behavior such as the theory of reasoned action (TRA) and the theory of planned behavior (TBP). However, the second hypothesis indicates that the decision-making process has a mental state and originates from the person's mental prototype in a particular situation. According to this model, the individuals' attitude towards a behavior changes positively and they perceive that the meaningful factors are leading them to conduct that behavior. Therefore, their intention increases to conduct that behavior. Furthermore, this model indicates that people have a set of basic beliefs (prototypes), which play a role in conducting high-risk behaviors. Individuals' attitudes to conduct behaviors are directly related to such basic beliefs or prototypes (Gerrard M, 2002). This model includes the constructs of attitude, subjective norms, behavioral willingness, as well as prototype and intents of behavior (Mirzaei Alavijeh et al., 2013).
Several studies have been carried out using a model of perceptions/tendencies in predicting high-risk behaviors such as smoking (Morowatisharifabad et al., 2012), drug use (Mirzaei Alavijeh et al., 2013), unauthorized speed (Chaleshgar et al., 2013), hookah consumption (Abedini et al., 2014), alcohol consumption (Gerrard et al., 2002), etc. Considering the daily consumption of fast foods by young people, especially students, the role of the prototype/ willingness model in predicting the high-risk behaviors, and the fact that no study has ever investigated this issue, the current study was conducted.  The aim was to determine the predictors of the intention to non-consumption of fast foods based on the prototype/willingness model among the dormitory female students in Yazd University of Medical Sciences.
Materials and Methods
Participants and study design: This descriptive-analytic study was conducted on 245 dormitory female students of Yazd University of Medical Sciences in the academic year of 2017-2018. The sample size was determined using a previous similar research (Morowatisharifabad et al., 2012) and the formula of  with 95 percent confidence level, S = 8, and D =1. In order to collect the participants from the university dormitory students, all six dormitories of females in Yazd University of Medical Sciences were selected. Then, according to the approximate equal numbers of students in dormitories, 45 students were randomly selected from each dormitory. Later, The questionnaire was distributed among the eligible individuals (those with no restriction on fast food consumption). Students were asked to complete the questionnaires by self-report.
Measurements: The data collection tool was a researcher-made questionnaire designed based on a model of prototype/willingness, which included two parts of demographic information and the main questions based on the model's constructs. The second part of the questionnaire dealt with intentions intention to non-consumption of fast foods: 4 questions, prototype of a fast food consumer: 7 questions, one's attitude towards fast food consumption: 4 questions, subjective norms about not consuming fast food: 4 questions, and finally the willingness to consume fast food: 4 scenarios and 12 questions. The answers to the questions of model constructs were determined using the 5-point Likert scale (very high 2+, high 1+, average 0, low -1, and not at all -2), except for the willingness construct.
The validity of this questionnaire was determined by a panel of experts including five health education and nutrition experts and its reliability was confirmed according to the preliminary study conducted on 30 dormitory students with a Cronbach's alpha coefficient of 0.7.
Ethical considerations: the researcher referred to the selected student's room in the dormitory and explained the study goals. In this regard, all participants were informed and ensured about the study process and information confidentiality, respectively. In addition, all students indicated their willingness to cooperate in the study.
Data analysis: Data was performed by SPSS 18 and Pearson correlation test was run to determine the correlation between model components and regression to determine the predictability of the model with regard to the intention for not consuming fast food.
Results
The mean age of the participants was 24.7 ± 3.8 years. Of the total number of respondents, 202 (82.8%) were single and 42 (17.2%) were married. Considering the education level, 6 (2.4%) participants were undergraduate students, 147 (60%) were graduate students, 50 (20.4%) were studying to get the Masters' degree, and 10 (4.1%) were at the PhD level (Table 1).
Regarding the participants' mean scores of the prototype/willingness model constructs, the attitude toward fast food consumption (51%) and the willingness (67.5%) constructs gained the highest ranks (Table 2).
According to Pearson correlation test, a positive and significant correlation was found between the constructs of tendencies and intention to non-consumption of fast foods (P = 0.001, r = 0.27)
(P < 0.05) (Table 3).
Regarding the predictability of intention to non-consumption of fast foods, the results of regression showed that attitude and subjective norms could predict 0.174 percent of the variance for not consuming fast foods. Attitude was the strongest predictor in this regard (Table 4).
 
 
Table 1. Frequency distribution of participants' demographic data
 
Percent Number Variables
  2.4 6 Under graduated Education
  60.0 147 Graduated
  20.4 50 Master
  4.1 10 Doctorate(PhD)
  13.1 32 General practitioner
              82.8 202 Single Marital status
  17.2 42 Married
 
Table 2. The participants' mean scores of the prototype/willingness model constructs
 
Achievable score range Mean percentage of max Mean ± SD Variables
4-20 57 11.5 ± 7.07 Intent
7-35 66.2 23.1 ± 4.9 Prototype
4-20 51 10.3 ± 3.6 Attitude
4-20 53 10.6 ± 3.6 Subjective norms
3-12 67.5 8.1 ± 1.6 Willingness
 
Table 3. Correlation coefficient among structures of prototype/willingness model
 
Subjective norms attitude prototype intention  
        Intention
      0.13
0.03a
Prototype
    0.09
0.1
0.37
0.001
Attitude
  0.03
0.6
0.19
0.002
0.16
0.008
Subjective norms
0.23
0.001
0.36
0.001
0.19
0.002
0.27
0.001
Willingness
a: P-value
Table 4. Regression analysis to predict the intention for not consuming fast food
in constructs of prototype/willingness model
 
Dependent variable R2 p-value β Independent variable
Intention of non-use fast food 0.174 0.001 0.38 attitude
0.002 -0.18 Subjective norms
 
 
Discussion
In this study, 97.1 percent of students used fast food. Fazelpour et al. conducted a study on fast food consumption in Yazd. They mentioned that the weekly fast food consumption in students was 18.8 percent and the highest consumption rate was attributed to other occupations (Fazelpour et al., 2011). This discrepancy can be due to the variety among the studied participants and students' residence in dormitory. Studies by Nicklas and Driskell showed that students consumed fast foods more than twice a week (Driskell et al., 2005, Nicklas et al., 2001). In the study of Dadipour et al. in Bandar Abbas, university students used fast foods more than the students of other educational levels. They showed that 39.1 percent of students consumed fast foods once a week and 20.2 percent used fast foods more than once a week (Dadipoor et al., 2014).
Based on the results of Pearson correlation test, the intention to non-consumption of fast foods had a significant correlation with attitudes, tendencies, and prototype towards fast food consumption. The positive correlation between these constructs suggests that higher desire for fast food consumption leads to the individual's higher intention to consume fast food. In the same line, positive attitudes toward a fast-food consumer, that is using words such as smart and regular to describe a fast-food consumer increase the intention of fast food consumption. In this regard, Morrovattisharifabad et al. reported that the intention for not smoking cigarettes had a correlation with the constructs of tendencies and prototype toward smoking, which is consistent with the results of this study (Morowatisharifabad et al., 2012).
Application of linear regression analysis showed that subjective norms and attitudes could predict the intention of not consuming fast foods. In this study, attitude was a stronger predictor of the intention to non-consumption of fast foods. This result was consistent with the studiy by Yarmohammadi et al. on fast food consumption among students (Yarmohammadi et al., 2011), the study of Chaleshgar et al. over the speed of unauthorized drivers (Chaleshgar et al., 2013), and the study by Abedini et al. regarding the use of hookah in students (Abedini et al., 2014). In the study of Dunn et al., the subjective norms were the strongest predictors of the intention to non-consumption of fast foods (Dunn et al., 2011).
Conclusion
The results of this study showed that the intention to non-consumption of fast foods is predicted by the prototype/willingness model. Based on these results, in order to reduce the fast food consumption in students, as important future-makers of our country, more attention should be paid to their attitudes and subjective norms. Unfortunately, people's attitudes toward fast food have changed as a result of the changes in lifestyle. This should be taken into consideration by the relevant authorities in educational planning for Iranian families.
One of the limitations of this study was that sampling was conducted among Yazd medical students; therefore, generalizability of the results should be considered with caution. Furthermore, the information was collected using a self-report method that could affect the results of the study. Moreover, lack of assessing the individuals' attitudes toward traditional foods and comparing consumption of fast foods with traditional foods in the family was another limitation of the present study, which can be considered in future studies.
Acknowledgments
This study was part of the research project No. 4545 approved by the Social Factors Research Center in Health Faculty of Yazd University of Medical Sciences. In this way, we appreciate the educational and cultural deputy and students of Shahid Sadoughi University of Yazd. We also appreciate the guidance of distinguished professors and students who participated in this study.
Authors’ Contributions
 Mazloomy Mahmoodabad SS and Mohammad Yousefivardanjani Z, and Fallahzadeh H contributed in designing the study. Farrokhian A and Mohammadyousefi Vardanjani Z contributed in data collection and wrote the first draft of the manuscript. All authors studied and approved the final version of the manuscript.
Conflict of interest
The authors declare no conflict of interests. 
 
References
 
Abedini S, MorowatiSharifabad M, Kordasiabi MC & Ghanbarnejad A 2014. Predictors of non-hookah smoking among high-school students based on prototype/willingness model. Health promotion perspectives. 4 (1): 46.
Barati M, Allahverdipour H, Hidarnia A, Niknami S & Bashirian S 2015. Belief-based tobacco smoking scale: evaluating the psychometric properties of the Theory of Planned Behavior’s Constructs. Health promotion perspectives. 5 (1): 59.
Bowman SA, Gortmaker SL, Ebbeling CB, Pereira MA & Ludwig DS 2004. Effects of fast-food consumption on energy intake and diet quality among children in a national household survey. Pediatrics. 113 (1): 112-118.
Brownell KD 2005. Does a" toxic" environment make obesity inevitable? Obssity management. 1 (2): 52-55.
Chaleshgar M, Morowaty MA & Abedini S 2013. Predictors of speeding among drivers based on Prototype Willingness Model. Journal of research and health. 3 (3): 436-444.
Dadipoor S, et al. 2014. Effective Factors related to Fast-foods Consumption in Bandar Abbas: A Community-Based Study. Iranian journal of health Eeucation and health promotion. 2 (2): 77-86.
Driskell JA, Kim Y-N & Goebel KJ 2005. Few differences found in the typical eating and physical activity habits of lower-level and upper-level university students. Journal of the American dietetic association. 105 (5): 798-801.
Driskell JA, Meckna BR & Scales NE 2006. Differences exist in the eating habits of university men and women at fast-food restaurants. Nutrition research. 26 (10): 524-530.
Dunn KI, Mohr P, Wilson CJ & Wittert GA 2011. Determinants of fast-food consumption. An application of the Theory of Planned Behaviour. Appetite. 57 (2): 349-357.
Fats F 2010. fatty acids in human nutrition. Report of an expert consultation. Food and nutrition paper. 91.
Fazelpour S, et al. 2011. Assessment of fast food concumption among people of Yazd city. Toloo-e-behdasht. 10 (2): 25-34.
French SA, Harnack L & Jeffery RW 2000. Fast food restaurant use among women in the Pound of Prevention study: dietary, behavioral and demographic correlates. International journal of obesity. 24 (10): 1353.
Gerrard M GF, Reis-Bergan M, Trudeau L, Vande Lune LS, Buunk B. 2002. Inhibitory effects of drinker and nondrinker prototypes on adolescent alcohol consumption. Health Psychology. Health psychology. 21 (6): 601.
Gerrard M, et al. 2002. Inhibitory effects of drinker and nondrinker prototypes on adolescent alcohol consumption. Health psychology. 21 (6): 601.
Glanz KE, Lewis FME & Rimer BK 1990. Health behavior and health education: Theory, research, and practice. Jossey-Bass.
Hooper L, et al. 2012. Effect of reducing total fat intake on body weight: systematic review and meta-analysis of randomised controlled trials and cohort studies. British medical journal. 345: e7666.
Key TJ, et al. 2004. Diet, nutrition and the prevention of cancer. Public health nutrition. 7 (1a): 187-200.
Mainbolagh BL, et al. 2012. The effect of peer education based on health belief model on nutrition behaviors in primary school boys. Journal of research & health social development & health promotion research center. 2 (2): 214-225.
Mirzaei Alavijeh M, et al. 2013. Predictors of drug abuse among students with application of Prototype/Willingness Model. Journal of police medicine. 2 (2): 111-118.
Morowatisharifabad M, Fadaeevash N, Allahverdipour H & Fallahzadeh H 2012. Study Of Smoking Predictors Based On Prototype/Willingness Model Omong High School Students In Maragheh. Toloo-e-behdash. 11 (3): 25-35.
Nicklas TA, Baranowski T, Cullen KW & Berenson G 2001. Eating patterns, dietary quality and obesity. Journal of the American college of nutrition. 20 (6): 599-608.
Paeratakul S, Ferdinand DP, Champagne CM, Ryan DH & Bray GA 2003. Fast-food consumption among US adults and children: dietary and nutrient intake profile. Journal of the American dietetic association. 103 (10): 1332-1338.
World Health Organization 2003. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO.
Yarmohammadi P, Sharifirad Gr, Azadbakht L, Morovati SMA & Hassanzadeh A 2011. Predictors of fast food consumption among high school students based on the theory of planned behavior. Health system research. 7 (4): 449-458(persian).
 

 
Type of article: orginal article | Subject: public specific
Received: 2018/01/21 | Published: 2019/05/1 | ePublished: 2019/05/1

References
1. Abedini S, MorowatiSharifabad M, Kordasiabi MC & Ghanbarnejad A 2014. Predictors of non-hookah smoking among high-school students based on prototype/willingness model. Health promotion perspectives. 4 (1): 46.
2. Barati M, Allahverdipour H, Hidarnia A, Niknami S & Bashirian S 2015. Belief-based tobacco smoking scale: evaluating the psychometric properties of the Theory of Planned Behavior’s Constructs. Health promotion perspectives. 5 (1): 59.
3. Bowman SA, Gortmaker SL, Ebbeling CB, Pereira MA & Ludwig DS 2004. Effects of fast-food consumption on energy intake and diet quality among children in a national household survey. Pediatrics. 113 (1): 112-118.
4. Brownell KD 2005. Does a" toxic" environment make obesity inevitable? Obssity management. 1 (2): 52-55.
5. Chaleshgar M, Morowaty MA & Abedini S 2013. Predictors of speeding among drivers based on Prototype Willingness Model. Journal of research and health. 3 (3): 436-444.
6. Dadipoor S, et al. 2014. Effective Factors related to Fast-foods Consumption in Bandar Abbas: A Community-Based Study. Iranian journal of health Eeucation and health promotion. 2 (2): 77-86.
7. Driskell JA, Kim Y-N & Goebel KJ 2005. Few differences found in the typical eating and physical activity habits of lower-level and upper-level university students. Journal of the American dietetic association. 105 (5): 798-801.
8. Driskell JA, Meckna BR & Scales NE 2006. Differences exist in the eating habits of university men and women at fast-food restaurants. Nutrition research. 26 (10): 524-530.
9. Dunn KI, Mohr P, Wilson CJ & Wittert GA 2011. Determinants of fast-food consumption. An application of the Theory of Planned Behaviour. Appetite. 57 (2): 349-357.
10. Fats F 2010. fatty acids in human nutrition. Report of an expert consultation. Food and nutrition paper. 91.
11. Fazelpour S, et al. 2011. Assessment of fast food concumption among people of Yazd city. Toloo-e-behdasht. 10 (2): 25-34.
12. French SA, Harnack L & Jeffery RW 2000. Fast food restaurant use among women in the Pound of Prevention study: dietary, behavioral and demographic correlates. International journal of obesity. 24 (10): 1353.
13. Gerrard M GF, Reis-Bergan M, Trudeau L, Vande Lune LS, Buunk B. 2002. Inhibitory effects of drinker and nondrinker prototypes on adolescent alcohol consumption. Health Psychology. Health psychology. 21 (6): 601.
14. Gerrard M, et al. 2002. Inhibitory effects of drinker and nondrinker prototypes on adolescent alcohol consumption. Health psychology. 21 (6): 601.
15. Glanz KE, Lewis FME & Rimer BK 1990. Health behavior and health education: Theory, research, and practice. Jossey-Bass.
16. Hooper L, et al. 2012. Effect of reducing total fat intake on body weight: systematic review and meta-analysis of randomised controlled trials and cohort studies. British medical journal. 345: e7666.
17. Key TJ, et al. 2004. Diet, nutrition and the prevention of cancer. Public health nutrition. 7 (1a): 187-200.
18. Mainbolagh BL, et al. 2012. The effect of peer education based on health belief model on nutrition behaviors in primary school boys. Journal of research & health social development & health promotion research center. 2 (2): 214-225.
19. Mirzaei Alavijeh M, et al. 2013. Predictors of drug abuse among students with application of Prototype/Willingness Model. Journal of police medicine. 2 (2): 111-118.
20. Morowatisharifabad M, Fadaeevash N, Allahverdipour H & Fallahzadeh H 2012. Study Of Smoking Predictors Based On Prototype/Willingness Model Omong High School Students In Maragheh. Toloo-e-behdash. 11 (3): 25-35.
21. Nicklas TA, Baranowski T, Cullen KW & Berenson G 2001. Eating patterns, dietary quality and obesity. Journal of the American college of nutrition. 20 (6): 599-608.
22. Paeratakul S, Ferdinand DP, Champagne CM, Ryan DH & Bray GA 2003. Fast-food consumption among US adults and children: dietary and nutrient intake profile. Journal of the American dietetic association. 103 (10): 1332-1338.
23. World Health Organization 2003. Diet, nutrition and the prevention of chronic diseases: report of a joint WHO.
24. Yarmohammadi P, Sharifirad Gr, Azadbakht L, Morovati SMA & Hassanzadeh A 2011. Predictors of fast food consumption among high school students based on the theory of planned behavior. Health system research. 7 (4): 449-458(persian).

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