Warning: mkdir(): Permission denied in /home/virtual/lib/view_data.php on line 81

Warning: fopen(upload/ip_log/ip_log_2024-11.txt): failed to open stream: No such file or directory in /home/virtual/lib/view_data.php on line 83

Warning: fwrite() expects parameter 1 to be resource, boolean given in /home/virtual/lib/view_data.php on line 84
Analysis of Factors Affecting Breakfast Eating Behavior of Children in Indonesia: An Application of the Health Belief Model
Skip Navigation
Skip to contents

Korean J Community Nutr : Korean Journal of Community Nutrition

OPEN ACCESS

Articles

Page Path
HOME > Korean J Community Nutr > Volume 25(1); 2020 > Article
Research Article
Korean Journal of Community Nutrition 2020;25(1):1-12.
DOI: https://doi.org/10.5720/kjcn.2020.25.1.1
Published online: January 20, 2020

1)Department of Food Science and Nutrition, Pusan National University, Busan, Korea, Graduate Student

2)Department of Food Science and Nutrition, Pusan National University, Research Institute of Ecology, Busan, Korea, Professor

†Corresponding author Ho Kyung Ryu Department of Food Science and Nutrition, Pusan National University, 2, Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan 46241, Korea Tel: (051) 510-7397 Fax: (051) 583-3648 E-mail: hokryu@pusan.ac.kr
• Received: August 20, 2019   • Revised: January 29, 2020   • Accepted: January 30, 2020

Copyright © 2020 Journal of the Korean Society of Community Nutrition

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 214 Views
  • 5 Download
  • 3 Crossref
next
  • Objectives
    This study investigates the current state of consuming breakfast among elementary school students residing in Malang, East Java, Indonesia, and to identify factors that influence breakfast behavior.
  • Methods
    The research model was set up as per the health belief model, and slightly modified by adding the subjective normative factors of the theory of planned behavior. The survey was conducted from July 17 to August 15, 2017 using a questionnaire, after receiving the permission PNU IRB (2017_60_HR).
  • Results
    The subjects were 77 boys (49.4%) and 79 girls (50.6%) suffering from malnutrition with anemia (21.2%) and stunting ratio of Height for Age Z Score (HAZ) (11.5%). Furthermore, moderate weakness (14.8%) and overweight and obesity (12.3%) by Body Mass Index for Age Z Score (BMIZ) were coexistent. According to the results obtained for breakfast, 21.8% did not eat breakfast before school, with 18.8% of the reasons for skipping breakfast being attributed to lack of food. Even for subjects partaking breakfast, only about 10% had a good balanced diet. The average score of behavioral intention on eating breakfast was 2.60 ± 0.58. The perceived sensitivity, perceived severity, perceived benefits, and self-efficacy of the health belief model correlated with breakfast behavior. Of these, self-efficacy (β=0.447, R2=0.200) and perceived sensitivity (β=0.373, R2=0.139) had the greatest effect on breakfast behavior. Mother was the largest impact person among children.
  • Conclusions
    In order to increase the level of breakfast behavior intention among children surveyed in Indonesia, we determined the effectiveness by focus on education which helps the children recognize to be more likely to get sick when they don't have breakfast, and increase their confidence in ability to have breakfast on their own. We believe there is a necessity to seek ways to provide indirect intervention through mothers, as well as impart direct nutrition education to children.
Fig. 1.
The study model based on health belief model and theory of planned behavior
kjcn-25-1f1.jpg
Table 1.
General characteristics of subjects
Variables   Frequency
Gender Boys 77 (849.4)
Girls 79 (850.6)
Age 99 14 (889.0)
10 51 (832.7)
11 57 (836.5)
12 30 (819.2)
13 or over 4 (882.6)
Tribe Java 150 (896.2)
The Others 6 (883.8)
Main meal preparation Grandfather 2 (881.3)
Grandmother 21 (813.5)
Father 6 (883.8)
Mother 138 (888.5)
Brothers and sisters 1 (886.0)
Father's education level College 14 (889.0)
High school 44 (828.2)
Middle school 24 (815.4)
Elementary school 31 (819.9)
No school 2 (881.3)
Non-response 38 (824.4)
Mother's education level College 7 (884.5)
High school 36 (823.1)
Middle school 42 (826.9)
Elementary school 28 (817.9)
No school 1 (880.6)
Non-response 39 (825.0)
Economic status High 2 (881.3)
Medium 135 (886.5)
Low 2 (881.3)
Non-response 17 (810.9)
Total 156 (100.0)

n (%)

Table 2.
Growth and development status and anemia of the subjects
  Variables Boys Girls Total t or χ2
Anthtropometric status
Height (cm)   136.8 ± 7.5 141.5 ± 6.5 139.1 ± 7.0 0.003∗∗
Weight (kg)   931.8 ± 7.2 933.2 ± 6.9 932.5 ± 7.0 0.366
Growth and development status
HAZ1) Severe stunting 0 (880.0) 0 (880.0) 0 (880.0) 6.574∗
Moderate stunting 14 (818.2) 4 (885.1) 18 (811.5)
Normal 63 (881.8) 75 (894.9) 138 (888.5)
BMIZ2) Severe weakness 2 (882.6) 3 (883.8) 5 (883.2) 0.844
Moderate weakness 9 (811.7) 9 (811.4) 18 (811.5)
Normal 55 (871.4) 59 (874.7) 114 (873.1)
Overweight 10 (813.0) 7 (888.9) 17 (810.9)
Obesity 1 (881.3) 1 (881.3) 2 (881.3)
Anemia
Anemia   18 (823.4) 15 (819.0) 33 (821.2) 0.883
Normal   59 (876.6) 64 (881.0) 123 (878.8)
Total   77 (100.0) 79 (100.0) 156 (100.0)

n (%) or Mean ± SD ∗ P<0.05, ∗∗ P<0.01 by student's t-test or χ

2test 1) Height for Age Z score 2) BMI for Age Z score

Table 3.
Breakfast eating status of subjects
Eating status Frequency
Frequency
Everyday 98 (862.8)
About once every two days 24 (815.4)
Hardly eat 34 (821.8)
Total 156 (100.0)
Reasons for skipping1)
Nothing to eat 12 (818.8)
No one to prepares meals 2 (883.1)
No time to eat 18 (828.1)
Poor appetite 17 (826.6)
Do not want to eat 15 (823.4)
Total 64 (100.0)
How to manage hunger1)
Home-made lunch box 33 (845.8)
Buy a meal around school 21 (829.2)
Snack 6 (888.3)
The others 12 (816.7)
Total 72 (100.0)

n (%) 1) Multiple response was allowed

Table 4.
Types of foods for breakfast
Types of foods Frequency
Carbohydrates1) 39 (825.6)
Meat and fish 4 (882.6)
Vegetables 29 (818.6)
Fruits 2 (881.3)
Beverage 2 (881.3)
Carbohydrates + meat and fish 11 (887.1)
Carbohydrates + meat and fish + beverage 3 (881.9)
Carbohydrates + meat and fish + vegetables 3 (881.9)
Carbohydrates + meat and fish + vegetables + beverage 7 (884.5)
Carbohydrates + meat and fish + vegetables + fruits + beverage 6 (883.8)
Carbohydrates + vegetables 11 (887.1)
Carbohydrates + vegetables + fruits 3 (881.9)
Carbohydrates + vegetables + beverage 9 (885.8)
Carbohydrates + vegetables + fruits + beverage 1 (880.6)
Carbohydrates + fruits 4 (882.6)
Carbohydrates + beverage 14 (889.0)
Meat and fish + beverage 7 (884.5)
Ratio of single-food meal 49.4%
Ratio of balanced meal 10.2%
Ratio of intakes of meat and fish 26.3%
Total 156 (100.0)
n (%)

1)Carbohydrates included rice, bread, noddles, casava, potatoes, etc.

Table 5.
Behavioral intention on eating breakfast
Construct Measurement questions Scores
Behavioral intention I will wake up earlier in the morning to eat breakfast for my health and go to school. 2.47 ± 0.66 2.60 ± 0.581)
I will make it a habit to eat breakfast. 2.60 ± 0.60
I will eat breakfast evenly for the sake of nutrition. 2.73 ± 0.50

Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point 1) Average of 3 questions

Table 6.
Health beliefs on eating breakfast
Health beliefs Measurement questions Scores
Perceived susceptibility If you skip breakfast, you will not feel cheerful and dizzy 2.46 ± 0.71 2.50 ± 0.701)
If you are hungry for a long time, you can be sick. 2.53 ± 0.70
If you do not eat breakfast, you may lose concentration. 2.51 ± 0.70
Perceived severity I think that obesity caused by snacking can be life-threatening. 2.33 ± 0.74 2.43 ± 0.70
I think severe anemia prevents proper growth. 2.42 ± 0.71
Chronic malnutrition is thought to reduce cognitive ability and brain function. 2.56 ± 0.67
Perceived benefits When you eat breakfast, you feel better. 2.67 ± 0.52 2.78 ± 0.43
If you eat breakfast, you can study well. 2.83 ± 0.42
If you eat breakfast consistently, it will help you grow. 2.85 ± 0.35
Perceived barriers I usually do not have enough food to eat breakfast at home. 2.18 ± 0.75 2.31 ± 0.72
There is no one to prepare breakfast, nor does it prepare. 2.48 ± 0.70
There is not enough time to get breakfast before school. 2.20 ± 0.70
I am afraid that eating breakfast every day will make me fat. 2.41 ± 0.74
Self-efficacy I can practice breakfast for my studies. 2.55 ± 0.60 2.44 ± 0.63
I can prepare my own meal without anyone preparing it. 2.34 ± 0.67

Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point 1) Average of questions

Table 7.
Subjective norms on eating breakfast
Measurement questions of each construct Scores
Normative belief
If I eat breakfast, my father will encourage me. 2.62 ± 0.61
If I eat breakfast, my mother will encourage me. 2.64 ± 0.60
If I eat breakfast, my teacher will encourage me. 2.57 ± 0.63
If I eat breakfast, my friend will encourage me. 2.28 ± 0.70
If I eat breakfast, my brother or sister will encourage me. . 2.47 ± 0.65
Motivation to comply
If my father encourage me, I will have breakfast. 2.19 ± 0.79
If my mother encourage me, I will have breakfast. 2.24 ± 0.79
If my teacher encourage me, I will have breakfast. 2.07 ± 0.81
If my friend encourage me, I will have breakfast. 2.00 ± 0.79
If my brother or sister encourage me, I will have breakfast. 2.15 ± 0.76
Subject norms
Father 5.85 ± 2.64
Mother 6.02 ± 2.71
Teacher 5.44 ± 2.69
Friend 4.66 ± 2.54
Brother & sister 5.42 ± 2.57

Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point

Table 8.
Correlation between constructs of health beliefs, subject norms, or behavioral intention on eating breakfast
  Pearson's correlation coefficients
Perceived susceptibility Perceived severity Perceived benefits Perceived barriers Self-efficacy Behavior intention  
Perceived susceptibility 1            
Perceived severity 0.620∗∗∗ 1          
Perceived benefits 0.394∗∗∗ 0.409∗∗∗ 1        
Perceived barriers 0.069 0.007 0.064 1      
Self-efficacy 0.109 0.109 0.361∗∗∗ 0.028 1    
Behavior intention 0.380∗∗∗ 0.264∗∗ 0.395∗∗∗ 0.063 0.461∗∗∗ 1  
            Behavior Subject
            intention norms
Behavior intention           1  
Subject norms     .     0.163∗ 1

P<0.05, ∗∗ P<0.01, ∗∗∗ P<0.001

Table 9.
Association between health beliefs and behavioral intention on eating breakfast
Health beliefs Behavioral intention on eating breakfast
R1) R2 2) F-value3) β 4) t-value 5)
Self-efficacy 0.447 0.200 38.260∗∗∗ 0.447 6.185∗∗∗
Perceived susceptibility 0.373 0.139 24.943∗∗∗ 0.373 4.994∗∗∗
Perceived benefits 0.302 0.091 15.338∗∗∗ 0.302 3.916∗∗∗
Perceived severity 0.231 0.053 98.490∗∗ 0.231 2.914∗∗
Subject norms 0.163 0.026 94.134 0.163 2.703∗
Perceived barriers 0.090 0.008 91.238 −0.090 1.113

P<0.05, ∗∗ P<0.01, ∗∗∗ P<0.001 1) Correlation coefficient between independent variable and dependent variable 2) Coefficient of determination, indicating how many percent of the total variability can be explained by independent variables 3) Test statistic of significance of the regression model 4) Regression coefficient, influence of independent variables on dependent variables, the closer to 1, the higher the influence 5) Test statistic of regression coefficient

  • 1. Stefani M, Harfika A, Anwar K, Humayah W, Pujilestari S, Azni IN, et al. An integrated healthy breakfast education for teachers, school children, and parents in West Java. ICCD 2018; 1(1): 165-170.ArticlePDF
  • 2. Hong JK. A study on the professional guidance and counseling for children in elementary schools. J Elementary Educ 2002; 15(1): 1-20.
  • 3. Susanto F. Breakfast skipper and breakfast eater: which is better. Int J Nutr Food Sci 2015; 4(5): 565-573.Article
  • 4. Brown JL, Beardslee WH, Prothrow-Stith D. Impact of school breakfast on children's health and learning: An analysis of the scientific research [Internet]. Sodexo Foundation; 2008. [cited 2019 Jul 1]. Available from:. http://us.stop-hunger.org/files/live/sites/stophunger-us/files/HungerPdf/Impact. %20of%20School %20Breakfast%20Study_tcm150–212606.pdf..
  • 5. Huang CJ, Hu HT, Fan YC, Liao YM, Tsai PS. Association of breakfast skipping with obesity and health-related quality of life: evidence from a national survey in Taiwan. Int J Obes 2010; 34(4): 720-725.ArticlePDF
  • 6. The national institute of health research and development, Ministry of health, Republic of Indonesia. Report on result of national basic health research (RISKESDAS) [Internet]. Jakarta, Indonesia: Ministry of health, Republic of Indonesia; 2007. [cited 2019 Jul 1]. Available from:. http://biofarmaka.ipb.ac.id/biofarmaka/2014/Riskesdas2007. %20-%20Report%20on%20Result%20of% 20National%20Basic%20Health%20Research.pdf..
  • 7. Trihono, MSc. Riset Kesehatan Dasar: Riskesdas 2013. Badan Penelitian dan Pengemb A Nagan Kesehatan Kementerian Kesehatan RI;. 2013; [cited 2019 Jul 1]. Available from:. http://www.depkes.go.id/resources/download/general/Hasil. %20Riskesdas%202013.pdf..
  • 8. Yang RJ, Wang EK, Hsieh YS, Chen MY. Irregular breakfast eating and health status among adolescents in Taiwan. BMC Public Health 2006; 6(1): 295.ArticlePubMedPMCPDF
  • 9. Nurul Fadhilah A, Teo PS, Huybrechts I, Foo LH. Infrequent breakfast consumption is associated with higher body adiposity and abdominal obesity in Malaysian school aged children. PLoS One 2013; 8(3): e59297.ArticlePubMedPMC
  • 10. WHO Working Group. Use and interpretation of anthropometric indicators of nutritional status. Bull World Health Organ 1986; 64(6): 929-941.PubMedPMC
  • 11. Mei Z, Grummer-Strawn LM. Standard deviation of anthropometric Z-scores as a data quality assessment tool using the 2006 WHO growth standards: a cross country analysis. Bull World Health Organ 2007; 85(6): 441-448.ArticlePubMedPMC
  • 12. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Strawn LM, Flegal KM, Mei Z, et al. 2000 CDC growth charts for the United States: Methods and development [Internet]. National Center for Health Statistics, USA;. 2002; [cited 2019 Jul 1]. Available from:. https://stacks.cdc.gov/view/cdc/6451.
  • 13. Hardinsyah H, Aries M. Jenis pangan sarapan dan perannya dalam asupan gizi harian anak usia 6–12 tahun di Indonesia. Jurnal Gizi dan Pangan 2012; 7(2): 89-96.ArticlePDF
  • 14. Sekiyama M, Roosita K, Othsuka R. Snack foods consumption contributes to poor nutrition of rural children in West Java, Indonesia. Asia Pac J Clin Nutr 2012; 21(4): 558-567.PubMed
  • 15. Februhartanty J. Nutrition education: It has never been an easy case for Indonesia. Food Nutr Bull 2005; 26(2): S267-274.ArticlePubMedPDF
  • 16. Lee KA. Elementary school children's perceptions of traditional Korean foods, based on the health belief model. Korean J Nutr 2013; 46(1): 86-97.Article
  • 17. Shin KO, Yoon JA, Je H, Hwang HJ, Lee Y, Choi JH. The effect of nutrition education based on health belief model for male college students in Seoul. Korean J Hum Ecol 2018; 27(4): 305-319.Article
  • 18. Fathi A, Sharifirad G, Gharlipour Z, Hakimelahi J, Mohebi S. Effects of a nutrition education intervention designed based on the health belief model (HBM) on reducing the consumption of unhealthy snacks in the sixth grade primary school girls. Int J Pediatr 2017; 5(2): 4361-4370.
  • 19. UNICEF. Child poverty and disparities in Indonesia: challenges for inclusive growth [Internet]. Jakarta UNICEF; 2013. [cited 2019 Jul 1]. Available from:. https://www.unicef.org/indonesia/Child_Poverty_Indonesia.pdf.
  • 20. Lee CH. The effect of locus of control and health belief model on handwashing: expanding health belief model [master's thesis]. Hanyang University;. 2015.
  • 21. Kim JE. Study on predicting behavioral intention of breastfeeding among primigravida [Master's thesis]. Dongguk University;. 2000.
  • 22. Kim JE. Microbiological analysis of hands and education of handwashing among preschool children in a day care center [master's thesis]. Hanyang University;. 2010.
  • 23. WHO. Iron deficiency anaemia: assessment, prevention and control. A guide for programme managers [Internet]. Geneva: World Health Organization; 2001. [cited 2019 Jul 1]. Available from:. http://www.who.int/nutrition/publications/micronutrients/anaemia_iron_deficiency/WHO_NHD_01.3/en/index.html.
  • 24. Insani PN, Rimbawan R, Palupi E. Dietary habits and nutritional status among school children in rural and urban area: a comparative study from Bogor, Indonesia. Future Food J Food Agric Soc 2018; 6(2): 55-66.
  • 25. OECD/World Health Organization. Health at a glance: Asia/Pacific 2012 [Internet]. OECD; 2013. [cited 2019 Jul 3]. Available from:. https://apps.who.int/iris/bitstream/handle/10665/87269/9789264183902_kor.pdf?sequence=3&isAllowed=y.
  • 26. WHO. The world health report 2002: Reducing risks, promoting healthy life [Internet]. World Health Organization, Geneva; 2002. [cited 2019 Jul 1]. Available from:. https://www.who.int/whr/2002/en/.
  • 27. Hardinsyah MS. Sarapan sehat salah satu pilar gizi seimbang [Internet]. Ketua umum pergizi pangan; 2013. [cited 2019 Jul 1]. Available from:. https://pergizi.org/images/stories/downloads/materi_PESAN/materi3.pdf.
  • 28. Rampersaud GC, Pereira MA, Girard BL, Adams J, Metzl JD. Breakfast habits, nutritional status, body weight, and academic performance in children and adolescents. J Am Diet Assoc 2005; 105(5): 743-760.ArticlePubMed
  • 29. Evers S, Taylor J, Manske S, Midgett C. Eating and smoking behaviours of school children in southwestern Ontario and Charlottetown, PEI. Can J Public Health 2001; 92(6): 433-436.ArticlePubMedPMCPDF
  • 30. Ming MF, Ying GC, Kassim M. Eating patterns of school children and adolescents in Kuala Lumpur. Malays J Nutr 2006; 12(1): 1-10.
  • 31. So HK, Nelson EA, Li AM, Guldan GS, Yin J, Ng PC, et al. Breakfast frequency inversely associated with BMI and body fatness in Hong Kong Chinese children aged 9–18 years. Br J Nutr 2011; 106(5): 742-751.ArticlePubMed
  • 32. Barker M, Robinson S, Wilman C, Barker DJ. Behaviour, body composition and diet in adolescent girls. Appetite 2000; 35(2): 161-170.ArticlePubMed
  • 33. Kosti RI, Panagiotakos DB, Zampelas A, Mihas C, Alevizos A, Leonard C, et al. The association between consumption of breakfast cereals and BMI in schoolchildren aged 12–17 years: the VYRONAS study. Public Health Nutr 2008; 11(10): 1015-1021.ArticlePubMed
  • 34. Kovarova M, Vignerova J, Blaha P, Osancova K. Bodily characteristics and lifestyle of Czech children aged 7.00 to 10.99 years, incidence of childhood obesity. Cent Eur J Public Health 2002; 10(4): 169-173.PubMed
  • 35. Sjoberg A, Hallberg L, Hoglund D, Hulthen L. Meal pattern, food choice, nutrient intake and lifestyle factors in The Goteborg Adolescence Study. Eur J Clin Nutr 2003; 57(12): 1569-1578.ArticlePubMedPDF
  • 36. Keski-Rahkonen A, Kaprio J, Rissanen A, Virkkunen M, Rose RJ. Breakfast skipping and health-compromising behaviors in adolescents and adults. Eur J Clin Nutr 2003; 57(7): 842-853.ArticlePubMedPDF
  • 37. O'Neil CE, Nicklas TA. A review of the relationship between 100% fruit juice consumption and weight in children and adolescents. Am J Lifestyle Med 2008; 2(4): 315-354.ArticlePDF
  • 38. Cotton PA, Subar AF, Friday JE, Cook A. Dietary sources of nutrients among US adults, 1994 to 1996. J Am Diet Assoc 2004; 104(6): 921-930.ArticlePubMed
  • 39. Whittaker P, Paul R. Tufaro PR, Rader JI. Iron and folate in fortified cereals. J Am Coll Nutr 2001; 20(3): 247-254.PubMed
  • 40. Rampersaud GC. Benefits of breakfast for children and adolescents: Update and recommendations for practitioners. Am J Lifestyle Med 2008; 3(2): 86-103.ArticlePDF
  • 41. Menteri Kesehatan Republik Indonesia. Peraturan menteri kesehatan republik Indonesia nomor 41 tahun 2014 [Internet]. Jakarta, Indonesia;. 2014; [cited 2019 Jul 1]. Available from:. http://hukor.depkes.go.id/uploads/produk_hukum/PMK. %20No.%2041%20ttg%20Pedoman%20Gizi%20Seimbang.pdf..
  • 42. Imanningsih N, Jahari AB, Permaesih ID, Chan P, Amarra S. Consumption and sources of added sugar in Indonesia: a review. Asia Pac J Clin Nutr 2018; 27(1): 47-64.PubMed
  • 43. Lee SJ, Ryu HK. Relationship between dietary intakes and the double burden of malnutrition in adults of Malang, Indonesia: An exploratory study. Nutr Res Pract 2018; 12(5): 426-435.ArticlePubMedPMCPDF

Figure & Data

REFERENCES

    Citations

    Citations to this article as recorded by  
    • Analysis of the factors that influence preschool children eating behavior by applying the health belief model: Seoul and Gyeonggi Province
      Sung-Mi Cha, Soo-Youn Kim
      Nutrition Research and Practice.2023; 17(3): 541.     CrossRef
    • Evaluation of dietary behavior and investigation of the affecting factors among preschoolers in Busan and Gyeongnam area using nutrition quotient for preschoolers (NQ-P)
      Soo-Youn Kim, Sung-Mi Cha
      Journal of Nutrition and Health.2020; 53(6): 596.     CrossRef
    • Psychoactive substance use among Chinese non-engaged youth: The application of the Health Belief Model
      Phoenix Kit-han Mo, Joseph Tak Fai Lau
      Children and Youth Services Review.2020; 113: 105008.     CrossRef

    • PubReader PubReader
    • ePub LinkePub Link
    • Cite
      CITE
      export Copy Download
      Close
      Download Citation
      Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

      Format:
      • RIS — For EndNote, ProCite, RefWorks, and most other reference management software
      • BibTeX — For JabRef, BibDesk, and other BibTeX-specific software
      Include:
      • Citation for the content below
      Analysis of Factors Affecting Breakfast Eating Behavior of Children in Indonesia: An Application of the Health Belief Model
      Korean J Community Nutr. 2020;25(1):1-12.   Published online February 29, 2020
      Close
    • XML DownloadXML Download
    Figure
    • 0
    We recommend
    Analysis of Factors Affecting Breakfast Eating Behavior of Children in Indonesia: An Application of the Health Belief Model
    Image
    Fig. 1. The study model based on health belief model and theory of planned behavior
    Analysis of Factors Affecting Breakfast Eating Behavior of Children in Indonesia: An Application of the Health Belief Model

    General characteristics of subjects

    Variables   Frequency
    Gender Boys 77 (849.4)
    Girls 79 (850.6)
    Age 99 14 (889.0)
    10 51 (832.7)
    11 57 (836.5)
    12 30 (819.2)
    13 or over 4 (882.6)
    Tribe Java 150 (896.2)
    The Others 6 (883.8)
    Main meal preparation Grandfather 2 (881.3)
    Grandmother 21 (813.5)
    Father 6 (883.8)
    Mother 138 (888.5)
    Brothers and sisters 1 (886.0)
    Father's education level College 14 (889.0)
    High school 44 (828.2)
    Middle school 24 (815.4)
    Elementary school 31 (819.9)
    No school 2 (881.3)
    Non-response 38 (824.4)
    Mother's education level College 7 (884.5)
    High school 36 (823.1)
    Middle school 42 (826.9)
    Elementary school 28 (817.9)
    No school 1 (880.6)
    Non-response 39 (825.0)
    Economic status High 2 (881.3)
    Medium 135 (886.5)
    Low 2 (881.3)
    Non-response 17 (810.9)
    Total 156 (100.0)

    n (%)

    Growth and development status and anemia of the subjects

      Variables Boys Girls Total t or χ2
    Anthtropometric status
    Height (cm)   136.8 ± 7.5 141.5 ± 6.5 139.1 ± 7.0 0.003∗∗
    Weight (kg)   931.8 ± 7.2 933.2 ± 6.9 932.5 ± 7.0 0.366
    Growth and development status
    HAZ1) Severe stunting 0 (880.0) 0 (880.0) 0 (880.0) 6.574∗
    Moderate stunting 14 (818.2) 4 (885.1) 18 (811.5)
    Normal 63 (881.8) 75 (894.9) 138 (888.5)
    BMIZ2) Severe weakness 2 (882.6) 3 (883.8) 5 (883.2) 0.844
    Moderate weakness 9 (811.7) 9 (811.4) 18 (811.5)
    Normal 55 (871.4) 59 (874.7) 114 (873.1)
    Overweight 10 (813.0) 7 (888.9) 17 (810.9)
    Obesity 1 (881.3) 1 (881.3) 2 (881.3)
    Anemia
    Anemia   18 (823.4) 15 (819.0) 33 (821.2) 0.883
    Normal   59 (876.6) 64 (881.0) 123 (878.8)
    Total   77 (100.0) 79 (100.0) 156 (100.0)

    n (%) or Mean ± SD ∗ P<0.05, ∗∗ P<0.01 by student's t-test or χ

    2test 1) Height for Age Z score 2) BMI for Age Z score

    Breakfast eating status of subjects

    Eating status Frequency
    Frequency
    Everyday 98 (862.8)
    About once every two days 24 (815.4)
    Hardly eat 34 (821.8)
    Total 156 (100.0)
    Reasons for skipping1)
    Nothing to eat 12 (818.8)
    No one to prepares meals 2 (883.1)
    No time to eat 18 (828.1)
    Poor appetite 17 (826.6)
    Do not want to eat 15 (823.4)
    Total 64 (100.0)
    How to manage hunger1)
    Home-made lunch box 33 (845.8)
    Buy a meal around school 21 (829.2)
    Snack 6 (888.3)
    The others 12 (816.7)
    Total 72 (100.0)

    n (%) 1) Multiple response was allowed

    Types of foods for breakfast

    Types of foods Frequency
    Carbohydrates1) 39 (825.6)
    Meat and fish 4 (882.6)
    Vegetables 29 (818.6)
    Fruits 2 (881.3)
    Beverage 2 (881.3)
    Carbohydrates + meat and fish 11 (887.1)
    Carbohydrates + meat and fish + beverage 3 (881.9)
    Carbohydrates + meat and fish + vegetables 3 (881.9)
    Carbohydrates + meat and fish + vegetables + beverage 7 (884.5)
    Carbohydrates + meat and fish + vegetables + fruits + beverage 6 (883.8)
    Carbohydrates + vegetables 11 (887.1)
    Carbohydrates + vegetables + fruits 3 (881.9)
    Carbohydrates + vegetables + beverage 9 (885.8)
    Carbohydrates + vegetables + fruits + beverage 1 (880.6)
    Carbohydrates + fruits 4 (882.6)
    Carbohydrates + beverage 14 (889.0)
    Meat and fish + beverage 7 (884.5)
    Ratio of single-food meal 49.4%
    Ratio of balanced meal 10.2%
    Ratio of intakes of meat and fish 26.3%
    Total 156 (100.0)
    n (%)

    1)Carbohydrates included rice, bread, noddles, casava, potatoes, etc.

    Behavioral intention on eating breakfast

    Construct Measurement questions Scores
    Behavioral intention I will wake up earlier in the morning to eat breakfast for my health and go to school. 2.47 ± 0.66 2.60 ± 0.581)
    I will make it a habit to eat breakfast. 2.60 ± 0.60
    I will eat breakfast evenly for the sake of nutrition. 2.73 ± 0.50

    Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point 1) Average of 3 questions

    Health beliefs on eating breakfast

    Health beliefs Measurement questions Scores
    Perceived susceptibility If you skip breakfast, you will not feel cheerful and dizzy 2.46 ± 0.71 2.50 ± 0.701)
    If you are hungry for a long time, you can be sick. 2.53 ± 0.70
    If you do not eat breakfast, you may lose concentration. 2.51 ± 0.70
    Perceived severity I think that obesity caused by snacking can be life-threatening. 2.33 ± 0.74 2.43 ± 0.70
    I think severe anemia prevents proper growth. 2.42 ± 0.71
    Chronic malnutrition is thought to reduce cognitive ability and brain function. 2.56 ± 0.67
    Perceived benefits When you eat breakfast, you feel better. 2.67 ± 0.52 2.78 ± 0.43
    If you eat breakfast, you can study well. 2.83 ± 0.42
    If you eat breakfast consistently, it will help you grow. 2.85 ± 0.35
    Perceived barriers I usually do not have enough food to eat breakfast at home. 2.18 ± 0.75 2.31 ± 0.72
    There is no one to prepare breakfast, nor does it prepare. 2.48 ± 0.70
    There is not enough time to get breakfast before school. 2.20 ± 0.70
    I am afraid that eating breakfast every day will make me fat. 2.41 ± 0.74
    Self-efficacy I can practice breakfast for my studies. 2.55 ± 0.60 2.44 ± 0.63
    I can prepare my own meal without anyone preparing it. 2.34 ± 0.67

    Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point 1) Average of questions

    Subjective norms on eating breakfast

    Measurement questions of each construct Scores
    Normative belief
    If I eat breakfast, my father will encourage me. 2.62 ± 0.61
    If I eat breakfast, my mother will encourage me. 2.64 ± 0.60
    If I eat breakfast, my teacher will encourage me. 2.57 ± 0.63
    If I eat breakfast, my friend will encourage me. 2.28 ± 0.70
    If I eat breakfast, my brother or sister will encourage me. . 2.47 ± 0.65
    Motivation to comply
    If my father encourage me, I will have breakfast. 2.19 ± 0.79
    If my mother encourage me, I will have breakfast. 2.24 ± 0.79
    If my teacher encourage me, I will have breakfast. 2.07 ± 0.81
    If my friend encourage me, I will have breakfast. 2.00 ± 0.79
    If my brother or sister encourage me, I will have breakfast. 2.15 ± 0.76
    Subject norms
    Father 5.85 ± 2.64
    Mother 6.02 ± 2.71
    Teacher 5.44 ± 2.69
    Friend 4.66 ± 2.54
    Brother & sister 5.42 ± 2.57

    Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point

    Correlation between constructs of health beliefs, subject norms, or behavioral intention on eating breakfast

      Pearson's correlation coefficients
    Perceived susceptibility Perceived severity Perceived benefits Perceived barriers Self-efficacy Behavior intention  
    Perceived susceptibility 1            
    Perceived severity 0.620∗∗∗ 1          
    Perceived benefits 0.394∗∗∗ 0.409∗∗∗ 1        
    Perceived barriers 0.069 0.007 0.064 1      
    Self-efficacy 0.109 0.109 0.361∗∗∗ 0.028 1    
    Behavior intention 0.380∗∗∗ 0.264∗∗ 0.395∗∗∗ 0.063 0.461∗∗∗ 1  
                Behavior Subject
                intention norms
    Behavior intention           1  
    Subject norms     .     0.163∗ 1

    P<0.05, ∗∗ P<0.01, ∗∗∗ P<0.001

    Association between health beliefs and behavioral intention on eating breakfast

    Health beliefs Behavioral intention on eating breakfast
    R1) R2 2) F-value3) β 4) t-value 5)
    Self-efficacy 0.447 0.200 38.260∗∗∗ 0.447 6.185∗∗∗
    Perceived susceptibility 0.373 0.139 24.943∗∗∗ 0.373 4.994∗∗∗
    Perceived benefits 0.302 0.091 15.338∗∗∗ 0.302 3.916∗∗∗
    Perceived severity 0.231 0.053 98.490∗∗ 0.231 2.914∗∗
    Subject norms 0.163 0.026 94.134 0.163 2.703∗
    Perceived barriers 0.090 0.008 91.238 −0.090 1.113

    P<0.05, ∗∗ P<0.01, ∗∗∗ P<0.001 1) Correlation coefficient between independent variable and dependent variable 2) Coefficient of determination, indicating how many percent of the total variability can be explained by independent variables 3) Test statistic of significance of the regression model 4) Regression coefficient, influence of independent variables on dependent variables, the closer to 1, the higher the influence 5) Test statistic of regression coefficient

    Table 1. General characteristics of subjects

    n (%)

    Table 2. Growth and development status and anemia of the subjects

    n (%) or Mean ± SD ∗ P<0.05, ∗∗ P<0.01 by student's t-test or χ

    test 1) Height for Age Z score 2) BMI for Age Z score

    Table 3. Breakfast eating status of subjects

    n (%) 1) Multiple response was allowed

    Table 4. Types of foods for breakfast

    Carbohydrates included rice, bread, noddles, casava, potatoes, etc.

    Table 5. Behavioral intention on eating breakfast

    Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point 1) Average of 3 questions

    Table 6. Health beliefs on eating breakfast

    Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point 1) Average of questions

    Table 7. Subjective norms on eating breakfast

    Mean ± SD Scoring criteria: ‘I don't think so' 1 point, ‘I think it's normal' 2 point, ‘I think so' 3 point

    Table 8. Correlation between constructs of health beliefs, subject norms, or behavioral intention on eating breakfast

    P<0.05, ∗∗ P<0.01, ∗∗∗ P<0.001

    Table 9. Association between health beliefs and behavioral intention on eating breakfast

    P<0.05, ∗∗ P<0.01, ∗∗∗ P<0.001 1) Correlation coefficient between independent variable and dependent variable 2) Coefficient of determination, indicating how many percent of the total variability can be explained by independent variables 3) Test statistic of significance of the regression model 4) Regression coefficient, influence of independent variables on dependent variables, the closer to 1, the higher the influence 5) Test statistic of regression coefficient


    Korean J Community Nutr : Korean Journal of Community Nutrition
    Close layer
    TOP