Analysis of Factors Affecting Breakfast Eating Behavior of Children in Indonesia: An Application of the Health Belief Model

Article information

Korean J Community Nutr. 2020;25(1):1-12

Publication date (electronic) : 2020 January 20

doi : https://doi.org/10.5720/kjcn.2020.25.1.1

Ran Yi Kang ¹⁾, Soo Jin Lee ¹⁾, Ho Kyung Ryu ²⁾^,

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 2019 August 20; Revised 2020 January 29; Accepted 2020 January 30.

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.

Keywords: breakfast eating behavior; health beliefs model; Indonesia; elementary school students

Fig. 1.

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

Table 1.

General characteristics of subjects

Table 2.

Growth and development status and anemia of the subjects

Table 3.

Breakfast eating status of subjects

Table 4.

Types of foods for breakfast

Table 5.

Behavioral intention on eating breakfast

Table 6.

Health beliefs on eating breakfast

Table 7.

Subjective norms on eating breakfast

Table 8.

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

Table 9.

Association between health beliefs and behavioral intention on eating breakfast

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Fig. 1.

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

Table 1.

General characteristics of subjects

Variables		Frequency
Gender	Boys	77 (849.4)
Gender	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)
Tribe	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

test 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
Self-efficacy	I can prepare my own meal without anyone preparing it.	2.34 ± 0.67	2.44 ± 0.63

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
Health beliefs	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