Relationship of Macronutrient Intake and Sedentary Activity with
Overweight Status Among Primary School Children in Surabaya
Elvina Amelindah
a
, Lailatul Muniroh
b
and Riza Amalia
c
Department of Nutrition, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia
Keywords: Macronutrient Intake, Overweight, Primary School Children, Sedentary Activity.
Abstract: The consequences of energy imbalance have resulted in a high prevalence of overweight students in primary
schools, reaching 39.8%. Several factors contribute, including macronutrient intake and sedentary activity.
This study aimed to analyze the relationship between macronutrient intake and sedentary activity among
overweight primary school students. The study was conducted using a cross-sectional design. Proportional
random sampling was employed to select a sample of 98 students from Pacar Kembang IV Surabaya Primary
School. Data collection included parent and student characteristics, macronutrient intake (assessed using a
semi-quantitative food frequency questionnaire), and sedentary activity (measured using a sedentary behavior
questionnaire). Bivariate analysis was conducted using the Chi-Square test and the contingency coefficient
relationship. Most respondents with high levels of sedentary activity (44.4%), excessive intake of energy
(50%), protein (44.8%), fat (51.9%), and carbohydrates (46.2%) were overweight. The bivariate analysis
revealed no relationship between energy intake (p = 0.189), fat intake (p = 0.236), carbohydrate intake (p =
0.279), and sedentary activity (p = 0.414) with overweight. However, a relationship was found between
protein intake and overweight status (p = 0.036, r = 0.252). A higher protein intake is associated with an
increased likelihood of being overweight. On the other hand, there is no relationship between intake of energy,
fat, carbohydrate, and sedentary activity and being overweight.
1 INTRODUCTION
Obesity and overweight have become major health
problems worldwide, with a huge increase in
prevalence. Global obesity rates have tripled since
1975, according to the World Health Organization
(WHO, 2021). This increase is due to changes in
dietary patterns, lifestyles, and environmental
impacts (Ermona & Wirjatmadi, 2018). Ng et al.
(2014) conducted a study that highlighted the
increasing prevalence of obesity in Indonesia and
underlined the need for focused interventions. As one
of the big cities in Indonesia, Surabaya illustrates the
increasing obesity rates in Indonesia.
Overweight is not solely an issue affecting adults
but has become a significant health concern among
children as well. Based on data from the World
Health Organization (WHO) for 2021, there were 340
million schoolchildren who were overweight. From
2010 to 2018, there was an increase in the prevalence
a
https://orcid.org/0009-0009-9184-0833
b
https://orcid.org/0000-0003-0130-7031
c
https://orcid.org/0009-0003-3685-9968
of overweight in school-age children in Indonesia by
9.2%, 18.8%, and 20% (Kemenkes RI, 2018). Data
from Riskesdas (2013) showed that the prevalence of
obesity in East Java was higher than the national
prevalence rate of 19.3% and reached 24.27% in
2018. This figure will continue to increase, especially
among school-aged children in Surabaya.
Childhood overweight is a major public health
concern, as it is associated with the onset of many
health problems. Overweight children are more prone
to developing chronic diseases such as type 2
diabetes, cardiovascular disease, and metabolic
syndrome early in life (Singh et al., 2008). Childhood
obesity may have an impact on academic
achievement. Taras and Potts-Datema (2005) found
that overweight and obese students had difficulty
concentrating in class, leading to lower academic
achievement. Childhood overweight and obesity have
far-reaching consequences due to the risk of
intergenerational transmission. Robinson et al. (2015)
Amelindah, E., Muniroh, L. and Amalia, R.
Relationship of Macronutrient Intake and Sedentary Activity with Overweight Status Among Primary School Children in Surabaya.
DOI: 10.5220/0012902800004564
Paper published under CC license (CC BY-NC-ND 4.0)
In Proceedings of the 5th International Conference on Social Determinants of Health (ICSDH 2023), pages 173-180
ISBN: 978-989-758-727-6; ISSN: 2975-8297
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.
173

found that children who grow up to be obese have a
higher likelihood of becoming obese adults, so the
cycle continues. Thus, it is important to study the
phenomenon of obesity in school-aged children.
The physical size of a person is closely tied to
their nutritional health. As a result, anthropometric
measurements are good and reliable for assessing
nutritional status (Gibson, 2005). BMI for age can be
used as a simple technique to assess nutritional status.
According to the Indonesian Ministry of Health in
2020, overweight status is indicated by the body mass
index according to age, which is > +1 SD. Based on
the World Health Organization standard for 2021, the
age of schoolchildren ranges from 7 to 15 years.
Meanwhile, the Indonesian Ministry of Health's
forecast for 2017 ranges from 7 to 12 years.
Maisyarah et al. (2021) state that the nutritional
status of school-age children can be caused by direct
and indirect factors. Direct factors such as
environmental, economic, and socio-cultural factors.
Meanwhile, indirect factors such as genetics, religion,
medical history, and nutrient intake Suharsa &
Sahnaz (2016) stated that most overweight children
are caused by excessive macronutrient intake and a
lack of physical activity.
Nutrient intake is a necessity for school-age
children in the process of growth and development.
Children who eat more frequently, in larger portions,
less varied food, and are not nutritionally balanced
tend to be overweight (Hardinsyah & Supariasa,
2016). Previous research at SDN Pacar Kembang I
Surabaya showed that children with overweight status
consumed more macronutrients than average, namely
energy (24.3%), protein (28.8%), fat (24.24%), and
carbohydrates (21.21%) (Qamariyah & Nindya,
2018). Therefore, school-age children are encouraged
to consume foods that provide sufficient energy
through protein, fat, and carbohydrate sources to
grow and develop, as well as move well every day
(Sutriani & Ngadiarti, 2013).
A systematic review by Tremblay et al. (2011)
states that today's modern environment greatly
reduces children's opportunities for physical activity.
The convenience of transportation, computers, and
television has encouraged lazy living habits.
Sedentary activity is an activity that involves little or
no body movement, which can affect nutritional
status (Rahmad et al., 2021). It is explained that long-
term inactivity can lead to an energy imbalance where
energy input exceeds energy production, which can
affect children's nutritional status (Amrynia &
Prameswari, 2022).
While some literature has studied the relationship
between macronutrient intake, physical activity, and
overweight in children globally, few studies have
specifically focused on the context of school-aged
children, particularly primary schools. This research
gap aims to identify the factors contributing to
childhood overweight in this specific context,
considering culture, environment, and lifestyle.
Based on this description, this study aims to analyze
the relationship between macronutrient intake,
sedentary activity, and overweight in schoolchildren
at Pacar Kembang IV Surabaya Primary School.
2 SUBJECTS & METHODS
This study was an analytic observational study with a
cross-sectional design. The present study allowed for
the examination of associations and relationships
between variables within a specific timeframe from
February to June 2022. The selection of Pacar
Kembang IV Primary School in Surabaya as the
research site was purposeful and based on a
representation of the target population. This school
was chosen due to the diverse composition of students
in grades 3, 4, and 5, thus providing a comprehensive
sample to draw meaningful conclusions.
Proportional random sampling was conducted
exclusively at the school level to ensure a balanced
representation of children across different grade
levels. A sample size of 98 children was determined
using this technique, with 37 children from grade 3,
37 children from grade 4, and 24 children from grade
5, contributing to the overall diversity of the group.
Data collected included characteristics of parents
and schoolchildren, macronutrient intake, and
sedentary activity. The independent variables studied
were macronutrient intake (energy, fat, protein, and
carbohydrate) and sedentary activity. Macronutrient
intake was obtained from main meals and snacks
obtained from the Semi-Quantitative Food Frequency
Questionnaire (SQ-FFQ).
Before this study, the SQ-FFQ underwent
validation procedures. The compilation of foods
utilized in the questionnaire was curated through
observations and discussions with several
schoolchildren at Pacar Kembang IV Primary School,
Surabaya. Macronutrient intake from SQ-FFQ was
calculated through a Nutrisurvey application with the
Indonesian Food Composition Database and then
compared with the recommended Nutrition
Adequacy Rate (RDA) according to age. The data
were then grouped based on the WNPG in 2014,
namely insufficient if <80% of the RDA, sufficient if
80–110% of the RDA, and excessive if >110% of the
RDA.
ICSDH 2023 - The International Conference on Social Determinants of Health
174

Sedentary activity was measured through
interviews using the Sedentary Behavior
Questionnaire (SBQ), which was divided into two
questionnaires (weekday and weekend) with a total of
18 questions. The dependent variable in this study
was nutritional status. The nutritional status is
determined by the calculation of the weight and
height of school-age children, which is then
calculated with an age-adjusted BMI to determine the
Z-score. The measurement results were processed
using the WHO AnthroPlus application, and then the
data was grouped into BMI for age categories,
including overweight if > +1SD and not overweight
if ≤ +1SD (Kemenkes RI, 2020). Furthermore, the
data was analyzed using the Chi-Square test and
relationship of contingency coefficients in the SPSS
application, then presented in tables and narratives to
describe the study results.
3 RESULTS
3.1 Characteristics
The characteristics of school children studied
included age, gender, and pocket money. Based on
Table 1, the average age of school children was 10.2
(± 0.9) years old, with a range of 9–12 years old. Most
of the school children were 10-year-old school
children totaling 43.9%. More than half (54.1%) of
the children were girls.
The average pocket money of school children was
Rp. 5,000 (± Rp1,877.7), the minimum value was Rp.
2000, and the maximum value was Rp. 10,000. Then
grouping was done based on the mean results
consisting of school children's pocket money per day
more if ≥ Rp. 5,000 and school children's pocket
money per day less if < Rp. 5,000. Based on Table 1,
almost all schoolchildren have pocket money ≥ Rp.
5,000, which is 77.6%.
Schoolchildren's nutritional status is obtained
through measurements of body weight and height,
then calculated using the WHO AnthroPlus
application and viewed based on BMI/A. Nutritional
status is categorized based on Permenkes RI 2020,
namely underweight if the BMI/A Z-score is -3SD to
<-2SD, normal if the Z-score is BMI/A -2SD to
+1SD, overweight if the Z-score is BMI/A +1SD to
+2SD, and obese if the BMI/A Z-score is >+2SD. The
average nutritional status of schoolchildren was
normal, with an IMT/U Z-score value of 0.15 SD ±
1.88 SD. Based on Table 1, most schoolchildren had
normal nutritional status, which is 46.9%; 21.4%
were overweight; 18.4% were obese; and 13.3% were
underweight.
This study also examined the characteristics of
parents, including their latest education, occupation,
and family income. The latest education of parents is
categorized into not going to school, primary school,
junior high school, senior high school, and diploma
or bachelor. Table 2 showed that most of the parents
with the latest education were in senior high school,
with 71.4% of fathers and 60.2% of mothers.
Furthermore, the types of employment of parents
are grouped into does not work, civil servant,
entrepreneur, and employee. It showed in Table 2 that
most respondents' fathers' occupations were
employees (57.1%). Meanwhile, more than half
(52%) of the mothers were not working.
Income in this study is the income earned by the
families of schoolchildren within one month. The
family income was categorized based on the Surabaya
city minimum wage. It was high if ≥ Surabaya
minimum wage (≥ Rp. 4,375,479.00) and low if <
Surabaya minimum wage (< Rp. 4,375,479.00). The
average family income of schoolchildren was Rp.
4,061,377.5 (± Rp. 2,390,687.1). Table 2 shows that
more than half (67.3%) of the schoolchildren's family
income was lower than the Surabaya minimum wage
(< Rp. 4,375,479.00).
Table 1: Distribution of Children Characteristics at Pacar Kembang IV Surabaya Primary School in 2022.
School Children Characteristics n % Mean±SD
Age (year)
9
10
11
12
23
43
25
7
23,5
43,9
25,5
7,1
10,2 ± 0,9
Gender
Boy
Girl
45
53
45,9
54,1
-
Pocket Money
< Rp. 5.000
≥ Rp. 5.000
22
76
22,4
77,6
Rp. 5.000 ± Rp. 1.877,7
Z-Score (BMI for Age)
- 3SD to - 2SD (Underweight) 13 13,3
0,15 ±1,88
Relationship of Macronutrient Intake and Sedentary Activity with Overweight Status Among Primary School Children in Surabaya
175

School Children Characteristics n % Mean±SD
- 2SD to + 1SD (Normal)
+ 1SD to + 2SD (Overweight)
> + 2SD (Obesity)
46
21
18
46,9
21,4
18,4
Table 2: Distribution of Parent Characteristics at Pacar Kembang IV Primary School Surabaya in 2022.
Parent Characteristics
Father Mother
n % n %
Education
Not going to school
Primary school
Junior high school
Senior high school
Diploma/Bachelo
r
0
7
9
70
12
0
7,1
9,2
71,4
12,2
3
2
20
59
14
3,l
2
20,4
60,2
14,3
Occupation
Does not work
Civil servant
Entrepreneur
Employee
10
5
27
56
10,2
5,2
27,6
57,1
51
4
19
24
54
4,1
19,4
24,5
Famil
y
Income n % Mean
High (≥ UMK)
Low
(
< UMK
)
32
66
32,7
67,3
Rp. 4.061.377,5
(
± R
p
. 2.390.687,1
)
Table 3: Distribution of Nutritional Status, Macronutrient Intake, and Sedentary Activity of Pacar Kembang IV Primary
School Surabaya Children in 2022.
Variable n %
Nutritional Status
Overweight (BMI for Age > + 1SD)
Not Overwei
g
ht
(
BMI for A
g
e ≤ + 1SD
)
39
59
39,8
60,2
Daily Food Intake
Energy (kcal)
Protein (gram)
Fat (gram)
Carboh
y
drates
(g
ram
)
Mean
1876,77 ± 579,05
71,89 ± 27,46
53,65 ± 22,03
277,75 ± 86,53
Energy Intake (kcal)
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
28
30
40
28,6
30,6
40,8
Protein Intake (gram)
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
9
22
67
9,2
22,4
68,4
Fat Intake (gram)
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
47
24
27
48,0
24,5
27,6
Carbohydrate Intake (gram)
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
26
33
39
26,5
33,7
39,8
Sedentary Activity
High (≥ 6 hours per day)
Low (< 6 hours per day)
45
53
45,9
54,1
3.2 Nutritional Status, Macronutrient
Intake, and Sedentary Activity
The nutritional status of schoolchildren obtained from
BMI for age is categorized into two categories.
Overweight if the BMI/A Z-score was > +1SD and
not overweight if the BMI/A Z-score was ≤ +1SD.
Presented in Table 3, the nutritional status of
schoolchildren at Pacar Kembang IV Primary School
Surabaya was overweight, which was 39.8%.
ICSDH 2023 - The International Conference on Social Determinants of Health
176

The dietary intake of schoolchildren in this study
was obtained from their daily food intake. Based on
the results of interviews using SQ-FFQ, the average
intake of energy, protein, fat, and carbohydrates from
schoolchildren's daily meals was obtained. Based on
Table 3, the average intake of energy, protein, fat, and
carbohydrates from the daily diet of schoolchildren is
1876.77 kcal ± 579.05; 71.89 grams ± 27.46; 53.65
grams ± 22.03; and 277.75 grams ± 86.53.
Furthermore, macronutrient intake was obtained
from the sum of daily food intake within the last 30
days using the SQ-FFQ method. Table 3 shows that
most of the schoolchildren's energy, protein, and
carbohydrate intake was excessive, which amounted
to 40.8%, 68.4%, and 39.8%. Meanwhile, fat intake
was mostly insufficient, at 48%.
The sedentary activity score of schoolchildren
was obtained from sedentary activity during the past
week in hours per day. This study showed that the
average sedentary activity of schoolchildren was 5
hours and 57 minutes, so sedentary activity was
categorized as high if ≥6 hours per day and low if <6
hours per day. Table 3 indicated that more than half
of the schoolchildren, or 54.1%, had low sedentary
activity.
3.3 Relationship Between Variables
Macronutrient intake is the total intake of energy,
protein, fat, and carbohydrates from food per day. The
nutritional status of schoolchildren was analyzed
using the Chi-Square test. Based on Table 4,
schoolchildren with excessive daily intakes of energy
(50%), fat (51.9%), and carbohydrate (46.2%) were
overweight. Meanwhile, children with insufficient
daily intake of energy (71.4%), fat (68.1%), and
carbohydrate (73.1%) were not overweight.
The p-values from the Chi-Square test described
in Table 4 were energy (0.189), fat (0.236), and
carbohydrate (0.279), where the p-value >0.05. This
showed that there was no significant relationship
between energy, fat, and carbohydrate intake and
overweight among primary school children.
Schoolchildren with excessive daily protein
intake (44.8%) were overweight. Meanwhile,
schoolchildren with insufficient (100%) and adequate
(59.1%) daily protein intake were not overweight.
Table 4 below shows that the p-value of the protein
Chi-Square test was (0.036), where the p-value was
<0.05, so there was a significant association between
protein intake and overweight status. In addition, the
correlation value of the contingency coefficient (r)
was shown to be 0.252, meaning that the protein
intake variable had a low strength of association with
the incidence of overweight status.
The last result in Table 4 showed that the
difference in sedentary activity of children in the high
and low groups was not much different, which were
20.4% and 19.4%, where both schoolchildren had an
overweight status. The Chi Square test for sedentary
activity and overweight status resulted in a p-value of
0.414, which was >0.05, so there was no significant
relationship between sedentary activity and
overweight status.
Table 4: Relationship between Macronutrient Intake and Sedentary Activity with Nutritional Status School Children at Pacar
Kembang IV Primary School Surabaya in 2022.
Variable
Nutrition Status
Total
P-value r
Overweight Not Overweight
n % n % N %
Energy Intake
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
8
11
20
28,6
36,7
50,0
20
19
20
71,4
63,3
50,0
28
30
40
100
100
100
0,189
-
Protein Intake
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
0
9
30
0,0
40,9
44,8
9
13
37
100
59,1
55,2
9
22
67
100
100
100
0,036 0,252
Fat Intake
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
15
10
14
31,9
41,7
51,9
32
14
13
68,1
58,3
48,1
47
24
27
100
100
100
0,236 -
Carbohydrate Intake
Insufficient (<80% RDA)
Sufficient (80-110% RDA)
Excessive (>110% RDA)
7
14
18
26,9
42,4
46,2
19
19
21
73,1
57,6
53,8
26
33
39
100
100
100
0,279 -
Sedentary Activity
High (≥ 6 hours per day)
Low (< 6 hours
p
er day)
20
19
44,4
35,8
25
34
55,6
64,2
45
53
100
100
0,414 -
Relationship of Macronutrient Intake and Sedentary Activity with Overweight Status Among Primary School Children in Surabaya
177

4 DISCUSSIONS
Schoolchildren at Pacar Kembang IV Surabaya
Primary School have an average age of 10.2 years, in
the range of 9–12 years. Children aged 9–12 years are
in pre-adolescence, with an age division of 9–12 years
for girls and 10–12 years for boys. This age is a
crucial time to maintain a good intake to support
growth and development (Brown et al., 2017).
In this study, it was found that most children had
pocket money greater than Rp. 5,000. The higher the
pocket money of schoolchildren, the higher their
ability to buy food, thus affecting their intake (Desi et
al., 2018). This can be influenced by the occupation
of parents, which is related to the amount of family
income. If the family income is high, then the pocket
money given to children is also high. However, this
does not necessarily fulfill the food intake given to
children according to their needs (Wicaksana &
Nurrizka, 2019). The latest education of parents
indirectly affects the nutritional status of school
children. The higher the education of the parents, the
more favorable the variety and amount of food given
to the family (Jannah & Utami, 2018).
In this study, 60.2% of schoolchildren had
overnutrition or were overweight. Compared to the
obesity rate of 18% reported by the WHO in 2021, the
nutritional status rate in this study was higher at
39.8%. 6 Abnormal nutritional status occurs due to an
imbalance between nutrient intake and the body's
needs (Par’i et al., 2017).
Dietary intake in this study showed that
schoolchildren with overnutrition and undernutrition
had less fat intake and more protein intake. The mean
daily energy intake from food was 1876.77 kcal,
which was less than the Energy Adequacy Rate
required for boys and girls aged 10 to 12 years (2000
kcal and 1900 kcal, respectively) but more than the
Energy Adequacy Rate for children aged 7-9 (1650
kcal). The daily protein requirement of school-age
children was 71.89 grams, higher than the
recommended protein adequacy rate for boys and
girls aged 9 to 12 years (40 grams, 50 grams, and 55
grams). A total of 53.65 grams of fat were consumed
by the children daily, which is less than the Fat
Adequacy Intake of 55 grams and 65 grams for both
boys and girls aged 9 to 12 years. Carbohydrate intake
from the daily diet of schoolchildren is 277.7 grams,
which exceeds the needs of schoolchildren aged 7-9
years (250 grams) but is still less than the needs of the
Carbohydrate Adequacy Rate for children aged 10 to
12 years for both boys and girls, which is 300 grams
and 280 grams.
This study shows that there is no relationship
between energy, fat, and carbohydrate intake and
overnutrition status, and there is a relationship
between protein intake and overnutrition status. This
happened because the SQ-FFQ instrument
questionnaire has limitations so that the results of
energy, protein, fat, and carbohydrate intake from
daily meals depend on memory and do not describe
the actual food consumption of schoolchildren. The
physical activity of schoolchildren in this study
mostly had low sedentary activity, meaning moderate
to high activity levels. There was no relationship
between energy, fat, and carbohydrate intake and
overnutrition because energy derived from food is
used for physical activity. This means that energy is
obtained through food consumption and expended
through physical activity (Sari et al., 2018).
Meanwhile, there is a relationship between
protein intake and overnutrition because protein is
used for growth and development as well as physical
activity. The types of proteins that support children's
activity are actin, myosin, dynein, and tubulin.
Protein plays a role in converting chemical energy
into mechanical energy involved in movement. The
protein acts as a catalyst in the decomposition of ATP
as an energy source for activity (Suhartono, 2017).
Physical activity is all body movement due to muscle
contraction, and one of the functions of protein is to
play a role in muscle contraction. Muscle contraction
occurs due to the interaction between actin and
myosin muscle proteins that require ATP with the
help of enzymes known as ATPase enzymes (Welis
& Rifki, 2013). So, protein intake affects nutritional
status through growth and development.
This study shows there is no significant
relationship between sedentary activity and
overweight status. The results of the study are not
related because schoolchildren who are overweight or
not overweight have moderate to high levels of
physical activity. Schoolchildren go to school and
return home from school on foot, play soccer on the
sports field, and do extracurricular activities such as
dance, poetry, and samroh. When doing activity,
calories are burned, which can affect the basal
metabolic system (Tanjung & Bate’e, 2019).
Therefore, sedentary activity is not associated with
overweight status because schoolchildren still engage
in high- to moderate-level physical activity in their
daily lives. As a result, the basal metabolism of
schoolchildren increased.
This study certainly has both strengths and
weaknesses. Its main strengths lay in its
comprehensive approach, using a large and diverse
sample population, and using standardized
ICSDH 2023 - The International Conference on Social Determinants of Health
178

measurement tools. However, the weaknesses of this
study may be due to the limited dietary data, which
may lead to recall bias among schoolchildren. In
addition, the cross-sectional design of this study made
it challenging to determine cause-and-effect
relationships. The lack of association between
macronutrient intake and obesity could be attributed
to the complexity of individual metabolic responses,
genetic factors, or the need for a more nuanced
analysis of diet rather than isolated macronutrients.
Similarly, the absence of a significant association
between sedentary activity and obesity could be
influenced by factors such as compensatory physical
activity at other times, individual variation in
metabolic rate, or the need for a more nuanced
exploration of sedentary behavior beyond a simple
dichotomy. These limitations underscore the
importance of considering different approaches and
recognizing the intricacies of dietary and activity
influences on overweight and obesity.
5 CONCLUSIONS
Macronutrient intake of energy, fat, carbohydrate,
and nutritional status did not have a significant
correlation with overweight in this research.
However, there was a substantial correlation between
protein intake and overweight. Being overweight
results from a higher intake of protein from the daily
diet, which is a macronutrient. There was no
significant correlation between sedentary activity and
overweight.
The study suggests that protein intake, rather than
overall macronutrient composition or sedentary
activity, is significantly correlated with overweight in
school-age children. This highlights the importance
of considering protein consumption as a potential
factor in understanding childhood overweight and
obesity, while emphasizing the need for further
investigation into a broader range of variables.
Further research is needed into variables that may
be associated with the prevalence of overweight in
school-age children, ranging from internal variables
that influence nutritional status, such as genetics and
family history of obesity, to external variables that
influence sedentary activities, such as technology,
physical activity, and sedentary hobbies.
ACKNOWLEDGMENTS
Our gratitude goes to Pacar Kembang IV Primary
School Surabaya for providing the supportive
academic atmosphere required to finish this research.
The resources, facilities, and assistance from the staff
and students were crucial in enabling the research
process.
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