Skip to main navigation Skip to main content
  • KSCN
  • E-Submission

CNR : Clinical Nutrition Research

OPEN ACCESS
ABOUT
BROWSE ARTICLES
EDITORIAL POLICIES
FOR CONTRIBUTORS

Articles

Original Article

Effects of Multidisciplinary Health Promotion Program Among Children in Community Childcare Center

Clinical Nutrition Research 2024;13(1):8-21.
Published online: January 23, 2024

1Department of Medical Nutrition, Graduate School of East-West Medical Science, Kyung Hee University, Yongin 17104, Korea.

2Department of Medical Nutrition, Research Institute of Medical Nutrition, Kyung Hee University, Seoul 02447, Korea.

3Department of Sports Industry Studies, Yonsei University International Campus, Incheon 21983, Korea.

4Department of Family Medicine, Hallym University Sacred Heart Hospital, Anyang 14068, Korea.

Correspondence to Hyunjung Lim. Department of Medical Nutrition, Graduate School of East-West Medical Science and Research Institute of Medical Nutrition, Kyung Hee University, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Korea. hjlim@khu.ac.kr
Correspondence to Kyung Hee Park. Department of Family Medicine, Hallym University Sacred Heart Hospital, 22 Gwanpyeong-ro 170beon-gil, Dongan-gu, Anyang 14068, Korea. beloved920@naver.com
• Received: July 24, 2023   • Revised: November 30, 2023   • Accepted: December 22, 2023

Copyright © 2024. The Korean Society of Clinical Nutrition

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 8 Views
  • 0 Download
prev next
  • In this study, the effects of a 12-month multidisciplinary education program on the health status, dietary quality, and eating habits of children and adolescents attending community childcare centers were investigated. A total of 88 participants aged 7 to 17 years from 7 community childcare centers in Gyeonggi-do were enrolled. The intervention consisted of 12 multidisciplinary education sessions covering topics such as nutrition, exercise, and psychological education. All participants received the same education, and the effectiveness of the program was evaluated by categorizing them into a high participation group (HPG) and a low participation group (LPG) based on their participation rates. After intervention, in physical activities, moderate-intensity exercise was significantly reduced in the LPG, and there was no significant difference in psychological parameters. However, notable differences were observed in nutritional data. After intervention, intakes of calorie, carbohydrate, protein, and fat were significantly increased in both groups, and in particular, the change was found to be greater in HPG. Additionally, dietary fiber intake compared to the 2015 Korean Dietary Reference Intakes was increased in both groups. Daily food intake also increased dietary fiber intake in HPG, and meat and fruit intake was increased in LPG. In the nutrition quotient, there was a significant difference in HPG’s pre- and post-scores in the diversity category, and in nutrient adequacy ratio (NAR), the NAR of phosphorus was increased in both groups. The findings of this study suggest that multidisciplinary education implemented at community childcare centers primarily enhanced nutrition-related factors rather than physical activity or psychological aspects.
  • Trial Registration
    Clinical Research Information Service Identifier: KCT0002718
Childhood and adolescence are one of the most critical periods of life in terms of physical and psychological development [1]. Therefore, adopting appropriate lifestyle habits and engaging in health promotion activities is crucial during this period to establish the foundation for adult health [2, 3]. Adequate nutrition intake, physical activity, and emotional stability during this time can influence the development of dietary and lifestyle habits, as well as health promotion activities. Thus, it is particularly important for these aspects to be addressed appropriately and effectively [4, 5]. Recently, there has been an increase in the number of children and adolescents from economically disadvantaged households, such as single-parent families and multicultural backgrounds, attending community childcare centers [6]. These centers provide various programs, including meals, education, and emotional support, to assist in the physical and psychological changes that can occur during childhood and adolescence [7]. While some nutrition programs are offered for children and adolescents using community childcare centers [8], it is often challenging for them to voluntarily choose or effectively implement these programs due to the specific circumstances of the centers [9]. Due to this realistic situation, it is difficult for community childcare centers to conduct mid- to long-term or the multidisciplinary education related to compliance was rare.
Children and adolescents, especially those from vulnerable households who utilize community childcare centers, are exposed to relatively disadvantaged environments. The issues of obesity, ongoing and inappropriate weight control, as well as psychological and emotional problems, have emerged, leading to a polarization of physical development among children and adolescents in Korea [10, 11, 12]. To assess the nutrition and health status of children and adolescents, various factors such as individual factors (personality, secondary sexual characteristics), family factors (family dietary habits, genetics), and social factors (socioeconomic environment, food production and supply, school meals, popular culture) are interrelated [13]. However, there is limited research on children and adolescents using local community childcare centers.
Furthermore, community childcare centers often have a limited focus on physical activity compared to home environments, resulting in a tendency for children to not meet the recommended guidelines for physical activity and sedentary behavior, ultimately impacting their overall health status [14, 15]. Moreover, many children and adolescents using community childcare centers may experience low self-esteem, higher levels of depressive tendencies, low responsiveness, psychological anxiety resulting from social exclusion, and interaction with peers [16, 17, 18, 19, 20].
Currently, most studies conducted in community childcare centers regarding nutrition focus on the nutrition quotient (NQ) of children and adolescents utilizing these centers. Additionally, previous research on health promotion through physical activity has mainly targeted children from general households [14, 21], resulting in a lack of research specifically on physical activity among children using community childcare centers [22, 23]. Previous studies on children and adolescents utilizing community childcare centers have primarily concentrated on academic achievement or psycho-social development, with limited exploration of factors related to psychological characteristics, depression, anxiety, or distress [17, 18, 24, 25].
The aim of this study was to conduct 12 months of multidisciplinary education in nutrition, exercise and psychology to children and adolescents in community childcare centers, and to assess improvements in overall health status based on education participation level.
Participant and study design
This study selected community childcare centers through official communication with the local government of Gyeonggi province. Participants were recruited from children and adolescents registered in the selected community childcare centers, and subjects were assigned to respective groups based on their desired participation in the centers. A total of 118 individuals aged between 7 and 17 years were recruited, and information regarding their general characteristics was obtained. For the analysis, a total of 88 participants who did not withdraw from the community childcare centers or refuse to participate in the education were included. This study aimed to conduct a 12-month health education program, including nutrition, exercise, and psychological education, to improve lifestyle habits among children and adolescents using community childcare centers in South Korea. The study received approval from the Institutional Review Board of Hallym University Sacred Heart Hospital (approval No.: 2016-I135). All participants and their parents or guardians were informed about the study and provided consent. Previous studies have used the median visit to categorize participants into high participation group (HPG) and low participation group (LPG). In this study, referring to a previous research, the median participation ratio was determined as 83% [26]. Participants with a participation ratio higher than the median value were classified into the HPG, while those with a lower rate were classified into the LPG.
Multidisciplinary education
Table 1 describes multidisciplinary education according to nutrition, exercise and psychology education for participants in this study. The multidisciplinary education of this study, including nutrition education, exercise education, psychology education once a month, consisted of 3 times per month. All education in this study was conducted by experts in each field and the 1-time education lasted from 40 minutes to 1 hour.
Table 1

Composition of education program curriculum throughout the 12-month study

Table 1
Education sessions Educational theme
Nutrition Exercise Psychology
1 I eat evenly! Growth stretching Program/Self-/Mindfulness introduction listen to mindfulness
2 Healthy protein story Following exercise Listen to/Coloring/Collaborate with mindfulness
3 Vegetable every day Who is stronger? Mindfulness breathing
4 Adjusting meal by hand Learning my muscles Mindfulness stretching
5 Children’s health guard: traffic light meal Stretching with friends Mindfulness eating introduction and exercise
6 Nutrition activity day Outdoor activities Body scan
7 Safe snacks, choose smartly: high calorie, low nutrition food Get to know sports Mindfulness walking
8 Water vs. drinks, my choice? Learning our body Mindfulness eating
9 Reduce sodium, raise health Exercise quiz contest Mindfulness gratitude and charity meditation
10 Fat!! Knowing and eating right What is obesity? Create a message to me and my family
11 Norovirus food poisoning, be careful! Practice healthy exercise Mindfulness breathing
12 Nutrition activity day Should I walk? or run? Mindfulness eating

Nutrition education

Nutrition education aims at ultimately promoting health through acquiring concepts and knowledge about nutrition and education for the formation of correct eating habits. Nutrition education was carried out by nutrition experts. Nutrition education focused on education that can lead to a balanced diet of nutrients needed for growth. In 1st education, “I eat evenly,” the subjects took the time to explore the 5 food groups and the importance of nutrient intake. In 2nd education, the nutritionist taught about the types and roles of proteins, and the importance of proteins and amino acid. The 3rd educational theme was “Vegetable every day.” The goal of 3rd education was to get the 5 colors in the food. The 4th education was “Controlling the amount of food by hand” for the proper amount of food in all 5 food groups: cereals, proteins, vegetables, fruits, and oil. The 5th education was the theme of “Traffic light meal” for children’s health keeper. Teaching about food additives that can adversely affect children’s health, and nutritional labeling for choosing healthy foods. The 7th education, to identify high-calorie and low-fat foods, and select healthy snacks through nutrition labeling, taught about safe snacks and smart choices using high-calorie and low-nutrition foods. The 8th education was the subject of “Water vs. drinks, what is my choice?” The problem of excessive drinking in children and adolescents was identified and the correct method of drinking water was educated. The 9th education was conducted to improve health by ingesting it by taking the problem of excessive sodium intake. The 10th education was conducted to know and eat fat properly. The nutritionist identified the problems of trans-fat and saturated fat excess and taught them how to eat fat. The 11th education consisted of contents related to norovirus food poisoning. The nutritionists were trained on the characteristics of norovirus, prevention of norovirus food poisoning, and proper handwashing.

Exercise education

Exercise education established the concept of a healthy weight and taught the necessity of exercise and the importance of physical activity in daily life. Exercise education was carried out by exercise experts. Exercise education consisted of the following for each time this period: “Growth stretching,” “Following exercise,” “Who is stronger?,” “Learning my muscles,” “Stretching with friends,” “Outdoor activities,” “Get to know sports,” “Learning our body,” “Exercise quiz contest,” “What is obesity?,” “Practice healthy exercise,” and “Should I walk? or run?” This education encouraged them to be interested in outdoor activities and games and put them into practice.

Psychology education

Psychology education, including self-esteem improvement education, was conducted to establish proper awareness of food ingredients and good eating habits. Psychology education was carried out by psychology experts. Psychology education consisted of the following for each time: “Program introduction,” “Self-/Mindfulness introduction and listen to mindfulness,” “Listen to/coloring/collaborate with mindfulness,” “Mindfulness breathing,” “Mindfulness stretching,” “Mindfulness eating introduction and exercise,” “Body scan,” “Mindfulness walking,” “Mindfulness eating,” “Mindfulness gratitude and charity meditation,” “Create a message to me and family,” “Mindfulness breathing,” and “Mindfulness eating.” The education was organized into cooperative work and group activities that could lead to improved psychological stability and self-esteem (Table 1).
Assessment

General characteristics and anthropometrics measurement

In order to grasp the general characteristics of the participants, the name, age, date of birth, sex, grade of school, number of family members and monthly family income were investigated using the questionnaire, and the name was processed with initials. The subjects were measured anthropometrics to the nearest 0.1 kg or 0.1cm, all measurement data were gathered by trained researchers. The height was measured using a stadiometer (DS-103; Dong Sahn Jenix, Seoul, Korea), and the body weight (BW), body mass index (BMI) were measured using bioelectrical impedance analysis (BIA) (Inbody 720 Body composition Analyzer; BioSpace Co., Ltd., Seoul, Korea). Since maintaining a normal weight in childhood and adolescence can be seen as an improvement in overall health, weight status was analyzed using BMI z-score to analyze changes in the participants’ weight status before and after the intervention. BMI z-score was calculated based on the LMS data for each boys and girls’ monthly age provided by the Centers for Disease Control and Prevention and the BMI of the subjects in this study [27]. Weight status was classified into four categories based on the calculated BMI z-scores. BMI z-score of less than −2 was categorized as underweight, a BMI z-score greater than −2 but less than 1 was categorized as normal weight, a BMI z-score of 1 to less than 2 was categorized as overweight, and a BMI z-score of 2 or more was categorized as obesity.

Physical activity and psychological assessment

To evaluate the effects of exercise and psychological education, pre-education and post-education assessments were conducted among the participants. Valid questionnaires were used to assess physical activity, while reliable questionnaires were used for psychological factors, including the Children’s Depression Inventory (CDI), self-esteem, and self-efficacy. Participants completed the surveys to assess changes in physical activity through exercise education. The physical activity factors assessed included high-intensity exercise time, moderate-intensity exercise time, and sedentary time. The high-intensity, moderate-intensity, and sedentary times were converted into minutes. Participants also completed questionnaires regarding psychological factors. The psychological factors assessed in this study included family functioning, CDI, self-esteem, and self-efficacy. Scores were assigned to family functioning, CDI, self-esteem, and self-efficacy.

Nutrition assessment

Participants and their parents or guardians were taught how to record a 24-hour diet diary by trained nutritionists. All participants were provided with a booklet to freely record their diet diary for a total of 3 days (2 weekdays and 1 weekend day). Skilled nutritionists utilized measurements and weights from the food exchange table provided by the Korean Diabetes Association to convert and assess the food weights recorded in participants’ food diaries. The foods consumed by subjects were categorized into groups, including the grain group, fish/meat group, vegetable group, fruit group, and fat group. Food portions were estimated using small rice bowls, plates with a diameter of 16.5 cm, 200 mL cups, and baseballs. The dietary intake data obtained from the participants were analyzed using CAN-pro ver. 5.0 (Computer Aided Nutritional Analysis Program, 2016; Korean Nutrition Society, Seoul, Korea). The analysis results were compared with the Recommended Intake (RI) or Adequate Intake (AI) values and expressed as percentages based on the 2015 Korean Dietary Reference Intakes (2015 KDRIs) (published in 2016, Korean Nutrition Society). Additionally, a survey was conducted to investigate the average daily intake of food groups consumed by the participants. Baseline and 12-month follow-up surveys were conducted to assess habitual dietary patterns and recent dietary habits. The overall quality of food and dietary habits was evaluated using the NQ (published in 2012, Korean Nutrition Society), which comprehensively measures the dietary quality and habits of Korean children. The 19 items of the NQ were classified into five factors: balance, variety, moderation, regularity, and practice, based on grouping similar types of questions. Lastly, to evaluate the adequacy of nutrient intake, the nutrient adequacy ratio (NAR) was calculated for nine nutrients, including protein, vitamin A, thiamin, riboflavin, niacin, vitamin C, calcium, phosphorus, and iron. NAR was calculated as the ratio of individual nutrient intake to the recommended nutrient intake, and values equal to or greater than 1 were considered adequate. Mean adequacy ratio (MAR) was used to evaluate the overall dietary quality.
Statistical Analysis
The statistical software used for this study was SPSS ver. 23 (IBM Corp., Armonk, NY, USA). The significance level was set at p < 0.05. Significant differences between groups were analyzed using the chi-square test for categorical variables and the Student’s t-test for continuous variables. Significant differences before and after intervention were analyzed by paired t-test. Continuous variables were expressed as mean ± standard deviation, and categorical variables were expressed as number (%). Also, we used general linear model to analyze the results of the difference in change in physical activity, psychological and nutrition factors by between 2 groups after adjusting for age and sex.
Baseline characteristics by education participation level
In this study, a total of 88 children and adolescents were included in the analysis, with 45 participants in the HPG and 43 participants in the LPG. The general characteristics of the participants were examined (Table 2). The mean age of the HPG was 9.53 years, with 40.0% male and 60.0% female participants. The mean age of the LPG was 10.76 years, with 34.9% male and 65.1% female participants. There was a significant difference in age between the 2 groups (p < 0.01). The majority of participants in both groups had 4–5 family members, and the monthly household income was mostly less than 4 million won. There were no significant differences in sex, family size, and monthly household income between the 2 groups.
Table 2

General characteristics of subjects according to education participation level at baseline

Table 2
Variables All (n = 88) HPG (n = 45) LPG (n = 43) p*
Age (yr) 10.13 ± 2.16 9.53 ± 1.84 10.76 ± 2.30 0.007
Sex 0.620
Boys 33 (37.5) 18 (40.0) 15 (34.9)
Girls 55 (62.5) 27 (60.0) 28 (65.1)
Number of family members 0.393
≤ 3 16 (18.2) 10 (22.2) 6 (13.9)
4–5 40 (45.4) 22 (48.9) 18 (41.9)
≥ 6 10 (11.4) 5 (11.1) 5 (11.6)
No response 22 (25.0) 8 (17.8) 14 (32.6)
Monthly family income (₩) 0.911
≤ 2,000,000 28 (31.8) 14 (31.1) 14 (32.6)
> 2,000,000 and ≤ 4,000,000 30 (34.1) 17 (37.8) 13 (30.2)
> 4,000,000 and ≤ 6,000,000 8 (9.1) 4 (8.9) 4 (9.3)
> 6,000,000 0 (0.0) 0 (0.0) 0 (0.0)
No response 22 (25.0) 10 (22.2) 12 (27.9)
Weight status 0.750
Underweight 1 (1.1) 0 (0.0) 1 (2.3)
Normal weight 56 (63.7) 28 (62.2) 28 (65.1)
Overweight 20 (22.7) 10 (22.2) 10 (23.3)
Obesity 11 (12.5) 7 (15.6) 4 (9.3)
Values are presented as number (%) or mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%. Weight status was classified into four categories based on the calculated BMI z-scores: underweight < −2; −2 ≤ normal weight < 1; 1 ≤ overweight < 2; obesity ≥ 2.
HPG, high participation group; LPG, low participation group.
*Significant difference between the groups by Student’s t-test at p < 0.05 (bold-face).
Comparison of weight status by education participation level
In the HPG, the percentage of normal weight was 64.4% compared to 62.2%, and the percentage of obesity was 13.3% compared to 15.6%. However, in the LPG, the obesity rates at baseline and after 12 months remained the same, with underweight at 2.3%, normal weight at 65.1%, overweight at 23.3%, and obesity at 9.3%. However, there were no significant differences between baseline and post-data (Table 2).
Comparison of physical activity and psychological factors by education participation level
Comparing the differences in physical activity and psychological factors between baseline and after 12 months according to education participation level provides insights into the changes in physical activity and psychological well-being (Table 3). In the HPG, there were no differences observed between groups, and there were no significant changes noted in any of the physical activity factors between baseline and post-data. On the other hand, moderate-intensity exercise significantly decreased from 40.51 ± 84.66 min/day to 16.37 ± 28.01 min/day in the LPG (p < 0.05). In terms of psychological factors, there were no significant differences between groups and no significant differences baseline and post-data. Also, a general linear model used to compare the amount of change before and after in physical and psychological factors in the two groups. We adjusted for age and sex, which may affect the results. The results showed no significant differences between the data of the 2 groups.
Table 3

Comparison of physical activities and psychology difference between the baseline and after 12-month by education participation level

Table 3
Variables All (n = 88) HPG (n = 45) LPG (n = 43) p
Pre- Post- Pre- Post- Pre- Post-
Physical activities
High strength (min/day) 32.97 ± 51.30 22.11 ± 43.10 19.24 ± 31.58 16.89 ± 33.70 47.33 ± 63.19 27.58 ± 50.97 0.323
Moderate strength (min/day) 35.17 ± 96.74 14.10 ± 26.57* 30.07 ± 107.75 11.93 ± 25.23 40.51 ± 84.66 16.37 ± 28.01* 0.198
Sedentary time (min/day) 268.45 ± 264.75 305.67 ± 250.82 231.33 ± 262.77 267.56 ± 214.14 307.30 ± 264.27 345.56 ± 281.22 0.459
Total MET score (points) 3,005.36 ± 4,874.14 2,462.30 ± 3,604.78 2,020.36 ± 3,563.75 1,948.80 ± 3,090.05 4,036.19 ± 5,811.95 2,999.67 ± 4,041.76 0.355
Psychology
Family function 6.84 ± 2.75 7.05 ± 3.37 6.96 ± 2.69 6.56 ± 3.56 6.72 ± 2.84 7.56 ± 3.13 0.449
CDI 11.58 ± 7.24 9.36 ± 8.37* 12.00 ± 6.74 8.51 ± 8.46 11.14 ± 7.78 10.26 ± 8.38 0.185
Self-esteem 25.23 ± 7.82 26.30 ± 9.99 25.49 ± 6.81 26.29 ± 11.02 24.95 ± 8.82 26.30 ± 8.92 0.874
Self-efficacy 39.82 ± 12.24 41.14 ± 16.08 41.56 ± 11.50 39.71 ± 17.85 38.00 ± 12.85 42.63 ± 14.04 0.450
Values are presented as mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%.
HPG, high participation group; LPG, low participation group; MET, metabolic equivalent of task; CDI, Children’s Depression Inventory.
*Significant difference between the times by paired t-test at p < 0.05.
Significant difference between the times by Student’s t-test at p < 0.05.
p value presented as pre- and post- comparison of the amount of change between 2 groups adjusted age and sex by general linear model.
Comparison of total energy and macronutrient intake, ratios to 2015 KDRIs, and daily food group consumption by education participation level
Table 4 compares the total energy and macronutrient intake, ratios to the 2015 KDRIs, and daily food group consumption for nutrient analysis. Energy (kcal) significantly increased in both groups, with the HPG increasing from 1,523.54 ± 480.76 kcal to 1,834.95 ± 652.82 kcal, and the LPG increasing from 1,328.74 ± 395.22 kcal to 1,594.50 ± 436.60 kcal (p < 0.05). Energy (%) increased significantly in the HPG from 83.41% ± 25.15% to 94.09% ± 30.52% (p < 0.05). Dietary fiber (%) increased significantly in both groups, with the HPG increasing from 66.04% ± 30.46% to 76.32% ± 20.68%, and the LPG increasing from 58.55% ± 24.16% to 72.14% ± 28.46% (p < 0.05). Daily average food intake increased in the LPG from 975.90 ± 300.33 g to 1,176.93 ± 344.15 g (p < 0.05). Especially, Vegetable consumption increased in HPG from 136.68 ± 67.39 g to 178.94 ± 84.80 g (p < 0.05). After adjusting for age and gender by using a general linear model, the amount of changes in total energy and macronutrient intake was significantly greater in HPG compared to LPG. In comparison to the 2015 KDRIs, after adjustment, the amount of changes in protein (%) and sodium (%) in HPG were significantly greater than those in LPG. Meanwhile, in the LPG group, the amount of changes in energy (%), dietary fiber (%), and folic acid (%) were significantly greater than those in HPG. In daily food intakes, LPG showed a significantly greater amount of changes in total food intake and grains, while HPG exhibited a significantly greater in vegetable intake.
Table 4

Comparison of total energy and macronutrient intake, ratios compared to 2015 KDRIs, and daily food group consumption between baseline and after 12- month by education participation level

Table 4
Variables All (n = 88) HPG (n = 45) LPG (n = 43) p
Pre- Post- Pre- Post- Pre- Post-
Total energy and macronutrient intake
Energy (kcal) 1,428.87 ± 449.43 1,717.46 ± 567.60*† 1,523.54 ± 480.76 1,834.95 ± 652.82* 1,328.74 ± 395.22 1,594.50 ± 436.60*† 0.000
Carbohydrate (g) 215.30 ± 67.72 247.48 ± 72.99*† 230.42 ± 72.05 263.97 ± 75.76* 199.48 ± 59.68 230.21 ± 66.53*† 0.000
Protein (g) 49.67 ± 16.61 61.37 ± 25.33* 52.82 ± 17.59 64.69 ± 28.36* 46.37 ± 15.02 57.90 ± 21.50* 0.001
Fat (g) 39.49 ± 15.62 53.30 ± 28.31* 42.44 ± 17.15 57.30 ± 31.85* 37.02 ± 13.48 49.12 ± 23.70* 0.000
C:P:F ratio 61:14:25 59:14:27 61:14:25 59:14:27 60:14:26 59:14:27
Compared to 2015 KDRIs
Energy (%) 77.28 ± 25.42 85.95 ± 28.28*† 83.41 ± 25.15 94.08 ± 30.52* 70.86 ± 24.36 77.43 ± 23.14 0.000
Protein (%)§ 13.88 ± 1.66 14.15 ± 2.50 147.32 ± 47.99 156.64 ± 66.48 120.42 ± 53.90 127.81 ± 54.24 0.009
Dietary fiber (%)ll 62.38 ± 27.67 74.27 ± 24.73* 66.04 ± 30.46 76.32 ± 20.68* 58.55 ± 24.16 72.14 ± 28.46* 0.011
Vitamin C (%)§ 95.56 ± 174.53 88.37 ± 69.56 128.36 ± 238.29 82.66 ± 53.71 61.23 ± 35.40 94.35 ± 83.25* 0.114
Vitamin D (%)ll 22.42 ± 29.99 27.01 ± 29.21 25.94 ± 33.56 32.39 ± 30.99 18.74 ± 25.62 21.38 ± 26.41 0.145
Vitamin E (%)ll 33.30 ± 26.11 38.56 ± 22.90 36.99 ± 31.35 43.39 ± 23.80 29.44 ± 18.77 33.50 ± 21.02 0.053
Folic acid (%)§ 21.88 ± 25.41 26.57 ± 14.42 27.70 ± 32.96 30.42 ± 14.96 15.80 ± 11.18 22.53 ± 12.80*† 0.005
Zinc (%)§ 64.47 ± 35.23 58.97 ± 31.06 70.20 ± 33.81 63.76 ± 30.83 58.47 ± 36.07 53.95 ± 30.86 0.118
Calcium (%)§ 45.08 ± 22.03 45.47 ± 23.16 47.58 ± 24.60 47.52 ± 22.47 42.45 ± 18.92 43.32 ± 23.94 0.595
Sodium (%)l 185.68 ± 66.94 191.40 ± 61.74 196.52 ± 66.72 209.37 ± 59.35 174.33 ± 66.05 172.58 ± 59.13 0.016
Daily food intakes (g) 1,075.71 ± 442.04 1,195.87 ± 340.82* 1,171.09 ± 530.30 1,213.98 ± 340.50 975.90 ± 300.33 1,176.93 ± 344.15* 0.022
Grains (g) 278.03 ± 117.49 283.72 ± 102.80 307.46 ± 118.29 309.01 ± 101.89 247.24 ± 109.71 257.26 ± 98.05 0.008
Meats (g) 98.81 ± 58.03 119.16 ± 93.01* 109.91 ± 65.28 120.74 ± 100.52 87.40 ± 47.40 117.52 ± 85.62* 0.184
Vegetables (g) 141.66 ± 69.88 171.28 ± 80.65* 136.68 ± 67.39 178.94 ± 84.80* 146.87 ± 72.83 163.26 ± 76.24 0.047
Fruits (g) 139.82 ± 298.91 171.11 ± 153.05 178.63 ± 402.43 150.51 ± 153.47 99.20 ± 110.07 192.67 ± 151.38* 0.271
Milk and dairy (g) 149.49 ± 143.64 149.06 ± 155.92 153.04 ± 155.23 154.63 ± 165.83 145.78 ± 132.17 143.22 ± 146.57 0.981
Values are presented as mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%.
KDRIs, Korean Dietary Reference Intakes; HPG, high participation group; LPG, low participation group; C:P:F ratio, ratio of carbohydrates, proteins, and fats to total calories; RNI, Recommended Nutrient Intake; AI, Adequate Intake.
*Significant difference between the times by paired t-test at p < 0.05.
Significant difference between the times by Student’s t-test at p < 0.05.
Significant difference for pre- and post- comparison of the amount of change between 2 groups adjusted age and sex by general linear model at p < 0.05 (bold-face).
§Ratio of RNI to actual intake; RNI is an intake estimate that meets 97%–98% of the nutrient requirements of a healthy population.
llRatio of AI to actual intake; AI is used when accurate data on nutrient requirements are lacking or the RNI amount cannot be calculated.
Comparison of diet quality and diversity by education participation level
Table 5 shows the changes in diet quality and diversity assessed by NQ scores, NAR, and MAR. Diversity factors shows a significant increase from 63.64 ± 22.37 to 69.91 ± 19.24 in the HPG (p < 0.05). NAR results were examined for protein, vitamin A, thiamin, riboflavin, niacin, vitamin C, calcium, phosphorus, and iron. NAR of phosphorus increased from 0.84 ± 0.20 to 0.96 in the HPG (p < 0.05), and, in the LPG, it increased from 0.76 ± 0.26 to 0.93 ± 0.14 (p < 0.05). There were no significant differences between baseline and post-data in terms of MAR. As a result of analysis by adjusting for age and sex using a general linear model, the amount changes in NAR of protein, thiamin, niacin, phosphorus, and iron increased significantly greater in HPG than LPG. However, In the case of riboflavin, HPG increased significantly greater than LPG.
Table 5

Comparison of NQ score, NAR, and MAR changes between baseline and after 12-month by education participation level

Table 5
Variables All (n = 88) HPG (n = 45) LPG (n = 43) p
Pre- Post- Pre- Post- Pre- Post-
Total NQ score 60.72 ± 12.31 61.64 ± 10.08 60.37 ± 13.07 62.46 ± 9.25 61.09 ± 11.61 60.79 ± 10.93 0.835
Balance 52.11 ± 18.76 52.08 ± 20.37 54.49 ± 18.67 54.21 ± 17.56 49.62 ± 18.75 49.85 ± 22.95 0.486
Diversity 66.20 ± 23.03 71.06 ± 18.40* 63.64 ± 22.37 69.91 ± 19.24* 68.89 ± 23.67 72.26 ± 17.62 0.260
Moderation 64.10 ± 21.48 64.74 ± 18.94 62.26 ± 23.01 62.41 ± 17.58 66.03 ± 19.83 67.18 ± 20.18 0.567
Regularity 68.44 ± 24.62 66.42 ± 21.09 69.66 ± 26.46 71.69 ± 18.22 67.17 ± 22.79 60.90 ± 22.64 0.139
Practice 52.76 ± 21.14 53.92 ± 18.22 51.82 ± 22.72 54.08 ± 18.17 53.73 ± 19.57 53.74 ± 18.48 0.948
NAR
Protein 0.93 ± 0.15 0.95 ± 0.12 0.98 ± 0.06 0.97 ± 0.11 0.89 ± 0.19 0.93 ± 0.13 0.005
Vitamin A 0.73 ± 0.25 0.78 ± 0.23 0.76 ± 0.22 0.83 ± 0.20 0.70 ± 0.27 0.72 ± 0.25 0.056
Thiamin 0.97 ± 0.10 0.99 ± 0.06 0.98 ± 0.07 1.00 ± 0.01 0.95 ± 0.13 0.97 ± 0.09 0.036
Riboflavin 0.87 ± 0.19 0.85 ± 0.19 0.92 ± 0.15 0.90 ± 0.17 0.81 ± 0.22 0.80 ± 0.21 0.003
Niacin 0.73 ± 0.25 0.76 ± 0.23 0.79 ± 0.21 0.82 ± 0.21 0.68 ± 0.28 0.71 ± 0.23 0.018
Vitamin C 0.65 ± 0.30 0.65 ± 0.31 0.71 ± 0.30 0.67 ± 0.29 0.58 ± 0.29 0.64 ± 0.33 0.197
Calcium 0.50 ± 0.24 0.53 ± 0.28 0.51 ± 0.25 0.56 ± 0.27 0.49 ± 0.22 0.50 ± 0.28 0.598
Phosphorus 0.80 ± 0.24 0.95 ± 0.13* 0.84 ± 0.20 0.96 ± 0.11* 0.76 ± 0.26 0.93 ± 0.14* 0.000
Iron 0.85 ± 0.20 0.87 ± 0.19 0.90 ± 0.16 0.93 ± 0.14 0.79 ± 0.23 0.81 ± 0.22 0.002
MAR 0.78 ± 0.16 0.82 ± 0.13 0.82 ± 0.12 0.85 ± 0.10 0.74 ± 0.18 0.78 ± 0.14 0.001
Values are presented as mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%.
NQ, nutrition quotient; NAR, nutrition adequacy ratio; MAR, the mean adequacy ratio; HPG, high participation group; LPG, low participation group.
*Significant difference between the times by paired t-test at p < 0.05.
Significant difference between the groups by Student’s t-test a p < 0.05.
Significant difference for pre- and post- comparison of the amount of change between 2 groups adjusted age and sex by general linear model at p < 0.05 (bold-face).
This study aimed to examine the impact of a 12-month multidisciplinary education program on the health of children and adolescents utilizing community childcare centers, with a specific focus on the participation rate. Previous studies have demonstrated the therapeutic effects of education participation for various conditions such as hypertension, diabetes, osteoporosis, and obesity. However, there is a lack of research specifically investigating the suitability of education for children and adolescents, as well as verifying their participation and compliance in community childcare centers. Therefore, this study provided multidisciplinary education in nutrition, exercise, and psychological education to participants from community childcare centers. Based on a median participation rate of 83%, the participants were classified into HPG and LPG.
In a previous study involving children and adolescents from community childcare centers, energy consumption was reported to be 1,567 kcal [28]. However, in this study, the participants’ pre-training energy intake was found to be lower at baseline, indicating an overall nutrient-poor diet. Following the training program, there was a greater improvement in energy intake compared to previous studies [28].
Regardless of the participation rate group, both groups experienced a decrease in exercise time and an increase in sedentary time after the exercise education, which aligns with findings from previous studies [29]. Notably, the LPG exhibited a significant decrease in the duration of moderate-intensity exercise. This decline may be attributed to the lack of interest in physical activities at home among children and adolescents utilizing community childcare centers [14]. Regarding psychological factors, there was no statistically significant change between both 2 groups.
Baseline data indicated that the overall nutrient intake and dietary adequacy of the HPG were higher than those of the LPG. This difference may be attributed to the HPG's existing interest in nutrition and their strong motivation to practice healthy nutritional behaviors. On the other hand, baseline data revealed higher durations of high-intensity exercise in the LPG compared to the HPG. Psychological factors did not show significant changes regardless of the group, potentially because there is minimal difference between home and school environments in terms of psychological aspects. Furthermore, significant differences were observed before and after education based on the participation rate. Children and adolescents utilizing community childcare centers tend to have significantly lower nutritional status in terms of calories, protein, fat, calcium, vitamin A, and thiamine [30]. However, many of these nutritional factors showed improvements or positive changes after the education program, regardless of the group. The findings suggest that both the LPG and HPGs made efforts to acquire and implement basic nutritional knowledge through education.
Children from low-income families face challenges in accessing support for physical activities, such as participating in physical education classes and after-school sports activities. Factors such as dual income, absence of guardians, lack of safe living environments, limited availability of nearby sports facilities or programs, and increased sedentary behaviors act as barriers to the establishment of exercise habits [29, 31]. Compared to the lifestyle patterns of children and adolescents in other countries, Korean children and adolescents have longer learning hours and less time allocated to exercise [32]. Previous studies have shown that Korean children and adolescents spend an average of 8.9 hours per day in sedentary activities [33], although the sitting time in this study was slightly lower. It is recommended that community childcare centers organize and implement diverse physical activity programs to enhance the level of physical activity among children and adolescents. Additionally, they should work on establishing partnerships with local governments to secure appropriate spaces for such activities.
Previous research has demonstrated that children and adolescents utilizing community childcare centers have higher self-esteem compared to those who do not [34]. In this study, self-esteem was higher in both groups compared to previous studies. However, in low-income families, parents spend a significant amount of time working, resulting in shorter conversations and limited supervision with their children/adolescents, which may contribute to a decrease in their self-esteem [35].
In a previous study [36] conducted on the NQ of elementary school students in certain regions of Gyeonggi-do, the scores for balance, diversity, moderation, regularity, and practice were reported as 55.63, 71.48, 67.28, 59.36, and 61.68, respectively. However, in this study, both groups showed lower scores for most NQ items compared to the previous study. Considering the characteristics of children and adolescents utilizing community childcare centers who may lack education regarding eating habits in their daily lives, it is deemed that promoting healthy eating habits is more important than merely attempting to improve and establish eating habits.
In a previous study [37] targeting infants and toddlers in community childcare centers, the NAR for protein, vitamin A, and phosphorus was reported to be 0.95 or higher, while calcium had an NAR of 0.84, iron 0.85, and the MAR was 0.92. However, in this study focusing on children and adolescents utilizing community childcare centers, the intake of vitamin A was lower, iron content was slightly higher, and calcium intake was significantly lower compared to previous studies. Calcium is a crucial nutrient for bone and tooth formation, especially during growth and development [38]. However, in this study, the calcium intake did not reach the recommended levels in both groups, indicating a very low intake. A previous study investigating the intake patterns of adolescents aged 13 to 19 years found that approximately 21.3% of individuals did not consume the minimum reference amount for milk and dairy products and fruits [39]. However, both groups in this study exhibited a 10% higher consumption of milk and dairy products compared to the previous study.
Furthermore, this study demonstrated a significant increase in the NAR for phosphorus approaching 1. Phosphorus plays a role in increasing the proportion of calcium in the body's skeleton, which impacts bone mineralization [40]. However, excessive phosphorus intake can hinder calcium absorption, potentially affecting the growth of children and adolescents. Given the recent increase in phosphorus intake [41], children and adolescents should limit their consumption of processed foods. Food sources of phosphorus include meat, fish, eggs, milk, as well as nuts, grains, vegetables, and tofu. In this study, the reason for the NAR approaching 1 for phosphorus seems to be an increase in the consumption of food groups such as grains, meat, vegetables, and milk and dairy products, rather than processed foods.
Additionally, sodium is a mineral necessary for maintaining the body’s homeostasis, regulating osmotic pressure, neurotransmitters, and muscle contraction. Unlike other nutrients, only a minimal amount of sodium is required. However, in this study, sodium intake in the HPG was more than twice as high. Prolonged intake of excessive sodium can lead to high blood pressure and cardiovascular diseases, highlighting the importance of consuming an appropriate amount of sodium [42]. Calcium deficiency and excessive sodium intake can negatively impact growth due to increased calcium excretion from the body [38]. Therefore, continuous nutrition education at community childcare centers is crucial, and childcare teachers should also receive periodic training on promoting calcium intake and reducing phosphorus and sodium intake. Through such measures, it is deemed necessary to provide systematic education considering individualized needs for children and adolescents utilizing community childcare centers.
This study has several limitations. Firstly, it is challenging to generalize the results as it involved only community childcare centers in specific areas of Gyeonggi-do, and the total number of training sessions was relatively small, despite achieving a participation rate of 83% (more than 10 out of 12 sessions). Secondly, the education provided in this study was not tailored based on age, gender, or obesity rate. An individualized approach considering the physical, cognitive, and emotional development differences among participants is necessary [13]. However, participating in group activities within a shared space like a local children’s center can have a synchronizing effect, particularly for obese children and adolescents. Therefore, the education activities were designed to include interactive elements and encourage individual questions, regardless of age, sex, or obesity rate. Thirdly, there was no control group in this study. Comparison was made between the 2 groups based on the participation rate, but without a control group, it is challenging to generalize the effects of the multidisciplinary education.
Despite these limitations, this study offered multidisciplinary education for children and adolescents utilizing community childcare centers in the medium to long term. The findings are expected to contribute to improving and maintaining body composition, food quality, and eating habits among children and adolescents attending community childcare centers. It can also serve as a program for promoting health management and healthy lifestyles in the increasing number of community childcare centers.
In future research, considering the limitations of this study that focused on community childcare centers in specific regions, it is recommended to conduct multidisciplinary education for children and adolescents utilizing community childcare centers across various locations. Additionally, the development of supplementary programs is deemed necessary.
In conclusion, this study provided multidisciplinary education, including nutrition, exercise, and psychological education, and observed significant improvements in nutrition-related factors after the education program. Particularly in terms of nutrition, the HPG at baseline showed significantly higher food intake, intake rate compared to the 2015 KDRIs, NAR, and MAR compared to the LPG, which aligns with previous studies [26]. However, physical activity and psychological factors did not show significant changes regardless of the participation rate in this study. These findings suggest the need for long-term educational programs that can improve especially eating habits, exercise habits, and psychological factors through behavioral changes in the health management of children and adolescents utilizing community childcare centers. Furthermore, future research should focus on developing diverse programs to enhance physical activity and address psychological and emotional factors among children and adolescents using community childcare centers.
The participation rate in education was found to be a factor that influenced the research outcomes to some extent. Therefore, it is important to explore various approaches to enhance participation and develop complementary programs based on the findings of this study. Additionally, considering that low participation rates have been associated with negative effects on eating habits, reduced physical activity, increased stress, mental disorders, and depression in previous studies, it is crucial to investigate the factors influencing participation rates among the target population [26].
Korea Disease Control and Prevention Agencyhttps://doi.org/10.13039/100018688 2016-ER6405-00 Hallym Universityhttps://doi.org/10.13039/501100002632

Funding: This research was funded by the Korea Disease Control and Prevention Agency, grant number 2016-ER6405-00, Hallym University Research Fund.

Conflict of Interest: The authors declare that they have no competing interests.

Author Contributions:

  • Conceptualization: Kim Y, Kim YM, Park KH, Lim H.

  • Data curation: Kim Y.

  • Methodology: Kim Y, Kim YM, Park KH, Lim H.

  • Writing - original draft: Kim Y, Shin GS, Park J, Kang M, Son K.

  • Writing - review & editing: Kim Y, Shin GS, Park J, Kang M, Son K, Kim YM, Park KH, Lim H.

  • 1. Lee JY, Park SK, Oh BT, Hwang YS, Hong SW, Kim DH, Suh YS. Factors influencing overweight in Korean adolescents: analysis of 2015 Korean Youth Risk Behavior Web-based Survey. Korean J Fam Pract 2017;7:653-659.
  • 2. Kim KY, Park SW, Kim JY, Bae JS, Lee WK, Jeong SH, Kim KS, Kim YH, Park SM. Trends in the prevalence of health risk behaviors among Korean adolescents, 2005-2009 : the Korea Youth Risk Behavior Web-based Survey. Korean J Health Educ Promot 2012;29:13-25.
  • 3. Kwon HJ, Cho KO, Oh JW, Lee O, Kim YS. Association between levels of physical activity and self-rated health in Korean adolescents: the 2009 Korea Youth Risk Behavior Web-based Survey. Korean J Phys Educ 2012;51:253-261.
  • 4. Kim OH, Park JK. The effects of participation in exercise and nutrition education program on physical fitness, dietary habits and nutrition intake status for adolescent. Korean J Obes 2012;21:158-165.
  • 5. Oh SY. The association of dietary life, nutrition and mental health in Korean adolescents. J Korea Entertain Ind Assoc 2016;10:235-250.
  • 6. Lee SE, Shim JE, Kwon SY, Yeoh YJ, Yoon JH. Recommendation of serving size of the meal service of community child centers in Korea. Korean J Community Nutr 2014;19:361-371.
  • 7. Lee JY, Park JY, Kim HS, Kim WS, Hwang GH. Barriers to promoting physical activity among overweight and obese children from low-income families using community child care centers. J Korean Public Health Nurs 2017;31:327-340.
  • 8. Lee SB, Jeong YR, Ahn HJ, Ahn MJ, Ryu SA, Kang NE, Oh SY. The development of a nutrition education program for low-income family children by applying the social cognitive theory and health belief model. Korean J Community Nutr 2015;20:165-177.
  • 9. Jang EJ, Kang CH. Study on after-school service systems for low income families: focused on after-school by school and community child center. Korean J Local Gov Adm Stud 2009;23:483-508.
  • 10. Kim MH. Eating habits, self perception of body image, and weight control behavior by gender in Korean adolescents: using data from a 2010 Korea Youth Risk Behavior Web-based Survey. J East Asian Soc Diet Life 2012;22:720-733.
  • 11. Im YJ, Oh WO, Suk MH. Adolescent health behaviors according to body mass index. Child Health Nurs Res 2017;23:1-9.
  • 12. Yu KH. A study on the dietary behaviors, physical development and nutrient intakes in preschool children. Korean J Nutr 2009;42:23-37.
  • 13. Moon JS. Current nutritional status of Korean adolescents and countermeasures. Korean J Pediatr Gastroenterol Nutr 2010;13(Suppl 1):10-14.
  • 14. Park JY, Hwang GH, Cho JH. Barriers and improvements to promoting physical activity among children using community child care centers: perspectives of service providers. J Korean Public Health Nurs 2018;32:109-121.
  • 15. Kim SY, Choo JN. Health behaviors and health-related quality of life among vulnerable children in a community. J Korean Acad Community Health Nurs 2015;26:292-302.
  • 16. Cho KM. An analysis survey on physical development and health status of elementary children in poverty in Incheon area. Korean Parent Child Health J 2009;12:147-159.
  • 17. Kim JH, Choi BY. Comparison of emotional intelligence of elementary school students in low-income family and general family: focusing on gender differences. J Adolesc Welf 2013;15:319-342.
  • 18. Kim JI, Lee JH, Yang JN, Lee SJ. The relation of internalizing problems and stress, self-esteem, social support for poorly-fed children. Korea J Couns 2007;8:621-637.
  • 19. Kim YE, Park MR. Research on the self-respect awareness of children in regional children’s centers. Korean J Clin Soc Work 2007;4:61-89.
  • 20. Suh HJ, Rho SH. Children-youths and parents’ selection criteria of community children’s center. Korean J Youth Stud 2013;20:167-189.
  • 21. Kim BY. The effects of perceived self-confidence of youths participating in ree climbing on physical self-efficacy and self-esteem in local children’s center. Korean J Sports Sci 2018;16:557-567.
  • 22. Park JY, Baek SY, Im MH. Trends in health-related interventions on children attending community child care centers in South Korea. Child Health Nurs Res 2018;24:241-251.
  • 23. Jang JE. Individual and environmental factors on physical activity of children using community child center [master’s degree]. Seoul: Yonsei University; 2018.
  • 24. Kim HK, Lee YJ, Moon SY, Kwon EJ. Demographic characteristics and health problems of low income children in underserved area. Korean J Health Educ Promot 2007;24:65-85.
  • 25. Kim JK, Kang YS, Ahn SW, Park JK, Hwang SY, Kim JY, Kang HJ, Woo SK. The cognitive, academic, adaptive behavior and emotional-behavioral characteristics of at-risk children and adolescents in community child centers. Korean J Phys Mult Health Disabil 2013;56:43-64.
  • 26. Lee HS, Lee JW, Kim JM, Chang N. The effect of nutrition education and exercise program on body composition and dietary intakes, blood lipid and physical fitness in obese women (2) - relationship between participation rates and effectiveness of obesity management program -. Korean J Nutr 2010;43:260-272.
  • 27. Korea Centers for Disease Control and Prevention (KCDC). The 2017 Korean National Growth Charts for children and adolescents [Internet]. Cheongju: KCDC; 2017, cited 2023. Available from: https://knhanes.kdca.go.kr/knhanes/sub08/sub08_02.do
  • 28. Kwon SY. Needs for improving quality of foodservice management at community child centers in Korea. Korean J Food Nutr 2017;30:749-758.
  • 29. Ra JS, Gang MH. Physical activity and metabolic syndrome related factors on low income school aged children. J Korean Soc Matern Child Health 2014;19:121-133.
  • 30. Lyu ES, Lee KA. Comparison of the dietary behavior of children at community child center between metropolitan city and medium-sized city using the nutrition quotient. Korean J Food Cook Sci 2019;35:653-663.
  • 31. Kim HK, Hyun SM, Kwon EJ, Kim HC. The stages of change distribution for health behaviors among low income children in underserved area. J Korean Soc Health Educ Promot 2008;25:59-75.
  • 32. Kim BJ, Shin JY, Lee MH. Physical activity and obesity risk of adolescents: based on 12th(2016) Korea Youth Risk Behavior Web-based Survey(KYRBS). J Sport Leis Stud 2017;70:635-647.
  • 33. Lee EY, Yi KJ. Physical activity, sedentary behaviour and sleep among children and adolescents: towards and integrative approach to health promotion. J Health Social Sci 2016;42:59-84.
  • 34. Kim YJ, Choi EY. Community child center users’ parents-child relationship, social capital, and self-esteem: application of mixed research methods. Health Soc Welf Rev 2014;34:239-267.
  • 35. Lee H, Shin HJ. Regional children’s center as a positive factor to the self-esteem of the children from the low income family in a small city. J Soc Sci 2008;14:167-193.
  • 36. Oh KM, Kim HS. Evaluation of dietary behavior of elementary school students in the Gyunggi using nutrition quotient. J Korea Contents Assoc 2019;19:494-499.
  • 37. Sin EK, Lee YK. Evaluation of food and nutrient intake of preschool children in day-care centers. J Korean Soc Food Sci Nutr 2005;34:1008-1017.
  • 38. Lee JH, Son EY, Kim YS, Lim YS. Dietary habits and nutrition knowledge of children using community food service centers according to family type. Korean J Nutr 2011;44:255-263.
  • 39. Kim MH, Bae YJ. Evaluation of diet quality of children and adolescents based on nutrient and food group intake and Diet Quality Index-International (DQI-I). Korean J Community Nutr 2010;15:1-14.
  • 40. Lee KH, Oh SH. The effect of combined estrogen / calcium therapy on bone metabolism in ovariectomized rats - II. A study on metabolism of calcium, phosphorus and nitrogen in ovariectomized rats. J Korean Soc Food Sci Nutr 1996;25:1006-1015.
  • 41. Park JH. The correlation of dietary calcium and phosphorus intake with DMFT among Korean schoolchildren. J Korean Soc Dent Hyg 2017;17:1215-1223.
  • 42. Kim NH, Lee IS. Assessment of nutritional status of children in Community child center by nutrition quotient (NQ) - Gyeongju -. J East Asian Soc Diet Life 2015;25:73-86.

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:

Include:

Effects of Multidisciplinary Health Promotion Program Among Children in Community Childcare Center
Clin Nutr Res. 2024;13(1):8-21.   Published online January 23, 2024
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:
Include:
Effects of Multidisciplinary Health Promotion Program Among Children in Community Childcare Center
Clin Nutr Res. 2024;13(1):8-21.   Published online January 23, 2024
Close
Effects of Multidisciplinary Health Promotion Program Among Children in Community Childcare Center
Effects of Multidisciplinary Health Promotion Program Among Children in Community Childcare Center
0.007 Sex0.620Boys33 (37.5)18 (40.0)15 (34.9)Girls55 (62.5)27 (60.0)28 (65.1)Number of family members0.393≤ 316 (18.2)10 (22.2)6 (13.9)4–540 (45.4)22 (48.9)18 (41.9)≥ 610 (11.4)5 (11.1)5 (11.6)No response22 (25.0)8 (17.8)14 (32.6)Monthly family income (₩)0.911≤ 2,000,00028 (31.8)14 (31.1)14 (32.6)> 2,000,000 and ≤ 4,000,00030 (34.1)17 (37.8)13 (30.2)> 4,000,000 and ≤ 6,000,0008 (9.1)4 (8.9)4 (9.3)> 6,000,0000 (0.0)0 (0.0)0 (0.0)No response22 (25.0)10 (22.2)12 (27.9)Weight status0.750Underweight1 (1.1)0 (0.0)1 (2.3)Normal weight56 (63.7)28 (62.2)28 (65.1)Overweight20 (22.7)10 (22.2)10 (23.3)Obesity11 (12.5)7 (15.6)4 (9.3) 22.11 ± 43.1019.24 ± 31.5816.89 ± 33.7047.33 ± 63.19 27.58 ± 50.970.323Moderate strength (min/day)35.17 ± 96.7414.10 ± 26.57*30.07 ± 107.7511.93 ± 25.2340.51 ± 84.6616.37 ± 28.01*0.198Sedentary time (min/day)268.45 ± 264.75305.67 ± 250.82231.33 ± 262.77267.56 ± 214.14307.30 ± 264.27345.56 ± 281.220.459Total MET score (points)3,005.36 ± 4,874.142,462.30 ± 3,604.782,020.36 ± 3,563.751,948.80 ± 3,090.054,036.19 ± 5,811.952,999.67 ± 4,041.760.355PsychologyFamily function6.84 ± 2.757.05 ± 3.376.96 ± 2.696.56 ± 3.566.72 ± 2.847.56 ± 3.130.449CDI11.58 ± 7.249.36 ± 8.37*12.00 ± 6.748.51 ± 8.4611.14 ± 7.7810.26 ± 8.380.185Self-esteem25.23 ± 7.8226.30 ± 9.9925.49 ± 6.8126.29 ± 11.0224.95 ± 8.8226.30 ± 8.920.874Self-efficacy39.82 ± 12.2441.14 ± 16.0841.56 ± 11.5039.71 ± 17.8538.00 ± 12.8542.63 ± 14.040.450 1,717.46 ± 567.60*†1,523.54 ± 480.761,834.95 ± 652.82*1,328.74 ± 395.22 1,594.50 ± 436.60*† 0.000 Carbohydrate (g)215.30 ± 67.72 247.48 ± 72.99*†230.42 ± 72.05263.97 ± 75.76*199.48 ± 59.68 230.21 ± 66.53*† 0.000 Protein (g)49.67 ± 16.6161.37 ± 25.33*52.82 ± 17.5964.69 ± 28.36*46.37 ± 15.0257.90 ± 21.50* 0.001 Fat (g)39.49 ± 15.6253.30 ± 28.31*42.44 ± 17.1557.30 ± 31.85*37.02 ± 13.4849.12 ± 23.70* 0.000 C:P:F ratio61:14:2559:14:2761:14:2559:14:2760:14:2659:14:27Compared to 2015 KDRIsEnergy (%)77.28 ± 25.42 85.95 ± 28.28*†83.41 ± 25.1594.08 ± 30.52*70.86 ± 24.36 77.43 ± 23.14 0.000 Protein (%)§ 13.88 ± 1.66 14.15 ± 2.50 147.32 ± 47.99156.64 ± 66.48120.42 ± 53.90 127.81 ± 54.24 0.009 Dietary fiber (%)ll 62.38 ± 27.6774.27 ± 24.73*66.04 ± 30.4676.32 ± 20.68*58.55 ± 24.1672.14 ± 28.46* 0.011 Vitamin C (%)§ 95.56 ± 174.53 88.37 ± 69.56128.36 ± 238.2982.66 ± 53.7161.23 ± 35.4094.35 ± 83.25*0.114Vitamin D (%)ll 22.42 ± 29.9927.01 ± 29.21 25.94 ± 33.5632.39 ± 30.9918.74 ± 25.6221.38 ± 26.410.145Vitamin E (%)ll 33.30 ± 26.1138.56 ± 22.90 36.99 ± 31.3543.39 ± 23.8029.44 ± 18.7733.50 ± 21.02 0.053Folic acid (%)§ 21.88 ± 25.41 26.57 ± 14.42 27.70 ± 32.9630.42 ± 14.9615.80 ± 11.18 22.53 ± 12.80*† 0.005 Zinc (%)§ 64.47 ± 35.2358.97 ± 31.0670.20 ± 33.8163.76 ± 30.8358.47 ± 36.0753.95 ± 30.860.118Calcium (%)§ 45.08 ± 22.0345.47 ± 23.1647.58 ± 24.6047.52 ± 22.4742.45 ± 18.9243.32 ± 23.940.595Sodium (%)l 185.68 ± 66.94191.40 ± 61.74 196.52 ± 66.72209.37 ± 59.35174.33 ± 66.05172.58 ± 59.13 0.016 Daily food intakes (g)1,075.71 ± 442.04 1,195.87 ± 340.82*1,171.09 ± 530.301,213.98 ± 340.50975.90 ± 300.33 1,176.93 ± 344.15* 0.022 Grains (g)278.03 ± 117.49 283.72 ± 102.80 307.46 ± 118.29309.01 ± 101.89247.24 ± 109.71 257.26 ± 98.05 0.008 Meats (g)98.81 ± 58.03119.16 ± 93.01*109.91 ± 65.28120.74 ± 100.5287.40 ± 47.40117.52 ± 85.62*0.184Vegetables (g)141.66 ± 69.88171.28 ± 80.65*136.68 ± 67.39178.94 ± 84.80*146.87 ± 72.83163.26 ± 76.24 0.047 Fruits (g)139.82 ± 298.91171.11 ± 153.05178.63 ± 402.43150.51 ± 153.4799.20 ± 110.07192.67 ± 151.38*0.271Milk and dairy (g)149.49 ± 143.64149.06 ± 155.92153.04 ± 155.23154.63 ± 165.83145.78 ± 132.17143.22 ± 146.570.981 69.66 ± 26.4671.69 ± 18.2267.17 ± 22.7960.90 ± 22.64 0.139Practice52.76 ± 21.1453.92 ± 18.2251.82 ± 22.7254.08 ± 18.1753.73 ± 19.5753.74 ± 18.480.948NARProtein0.93 ± 0.15 0.95 ± 0.120.98 ± 0.060.97 ± 0.110.89 ± 0.19 0.93 ± 0.13 0.005 Vitamin A0.73 ± 0.250.78 ± 0.23 0.76 ± 0.220.83 ± 0.200.70 ± 0.270.72 ± 0.25 0.056Thiamin0.97 ± 0.100.99 ± 0.060.98 ± 0.071.00 ± 0.010.95 ± 0.130.97 ± 0.09 0.036 Riboflavin0.87 ± 0.19 0.85 ± 0.19 0.92 ± 0.150.90 ± 0.170.81 ± 0.22 0.80 ± 0.21 0.003 Niacin0.73 ± 0.25 0.76 ± 0.23 0.79 ± 0.210.82 ± 0.210.68 ± 0.28 0.71 ± 0.23 0.018 Vitamin C0.65 ± 0.30 0.65 ± 0.310.71 ± 0.300.67 ± 0.290.58 ± 0.29 0.64 ± 0.330.197Calcium0.50 ± 0.240.53 ± 0.280.51 ± 0.250.56 ± 0.270.49 ± 0.220.50 ± 0.280.598Phosphorus0.80 ± 0.240.95 ± 0.13*0.84 ± 0.200.96 ± 0.11*0.76 ± 0.260.93 ± 0.14* 0.000 Iron0.85 ± 0.20 0.87 ± 0.19 0.90 ± 0.160.93 ± 0.140.79 ± 0.23 0.81 ± 0.22 0.002 MAR0.78 ± 0.16 0.82 ± 0.13 0.82 ± 0.120.85 ± 0.100.74 ± 0.18 0.78 ± 0.14 0.001
Table 1 Composition of education program curriculum throughout the 12-month study
Table 2 General characteristics of subjects according to education participation level at baseline

Values are presented as number (%) or mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%. Weight status was classified into four categories based on the calculated BMI z-scores: underweight < −2; −2 ≤ normal weight < 1; 1 ≤ overweight < 2; obesity ≥ 2.

HPG, high participation group; LPG, low participation group.

*Significant difference between the groups by Student’s t-test at p < 0.05 (bold-face).

Table 3 Comparison of physical activities and psychology difference between the baseline and after 12-month by education participation level

Values are presented as mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%.

HPG, high participation group; LPG, low participation group; MET, metabolic equivalent of task; CDI, Children’s Depression Inventory.

*Significant difference between the times by paired t-test at p < 0.05.

Significant difference between the times by Student’s t-test at p < 0.05.

p value presented as pre- and post- comparison of the amount of change between 2 groups adjusted age and sex by general linear model.

Table 4 Comparison of total energy and macronutrient intake, ratios compared to 2015 KDRIs, and daily food group consumption between baseline and after 12- month by education participation level

Values are presented as mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%.

KDRIs, Korean Dietary Reference Intakes; HPG, high participation group; LPG, low participation group; C:P:F ratio, ratio of carbohydrates, proteins, and fats to total calories; RNI, Recommended Nutrient Intake; AI, Adequate Intake.

*Significant difference between the times by paired t-test at p < 0.05.

Significant difference between the times by Student’s t-test at p < 0.05.

Significant difference for pre- and post- comparison of the amount of change between 2 groups adjusted age and sex by general linear model at p < 0.05 (bold-face).

§Ratio of RNI to actual intake; RNI is an intake estimate that meets 97%–98% of the nutrient requirements of a healthy population.

llRatio of AI to actual intake; AI is used when accurate data on nutrient requirements are lacking or the RNI amount cannot be calculated.

Table 5 Comparison of NQ score, NAR, and MAR changes between baseline and after 12-month by education participation level

Values are presented as mean ± standard deviation. Participation rate for a total of 12 sessions: HPG ≥ 83%; LPG < 83%.

NQ, nutrition quotient; NAR, nutrition adequacy ratio; MAR, the mean adequacy ratio; HPG, high participation group; LPG, low participation group.

*Significant difference between the times by paired t-test at p < 0.05.

Significant difference between the groups by Student’s t-test a p < 0.05.

Significant difference for pre- and post- comparison of the amount of change between 2 groups adjusted age and sex by general linear model at p < 0.05 (bold-face).