kjcn Korean Journal of Community Nutrition Korean J Community Nutr 1226-0983 2287-1624 Journal of the Korean Society of Community Nutrition 10.5720/kjcn.2020.25.1.1 kjcn-25-1 Research Article Analysis of Factors Affecting Breakfast Eating Behavior of Children in Indonesia: An Application of the Health Belief Model KangRan Yi 1) LeeSoo Jin 1) RyuHo Kyung 2) † Department of Food Science and Nutrition, Pusan National University, Busan, Korea, Graduate Student 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 012020 20012020 251 112 20082019 29012020 30012020 Copyright © 2020 Journal of the Korean Society of Community Nutrition 2020 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. Abstract 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.

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The study model based on health belief model and theory of planned behavior

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

test 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 (%)

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