The Relationship Between Energy Intake, Macro Nutrition, and

Other Factors with the Incidence of Obesity in Students of Senior

High School 11 South Tangerang

Sri Laksmi Fitriyani

and Nunung Cipta Dainy

Faculty of Medicine and Health, University of Muhammadiyah Jakarta, Central Jakarta, Indonesia

Keywords: Adolescents, Nutrient Intake, Obesity.

Abstract: The prevalence of obesity in South Tangerang is quite high at 15.9%. Factors causing obesity in adolescents

are excessive macronutrient intake, increased consumption of junk food, decreased physical activity, and lack

of nutrition knowledge. This study aims to analyze the relationship between energy intake, macronutrients

and other factors with the incidence of obesity in students of SMAN 11 South Tangerang. This study used

Cross Sectional design with a Random Sampling Techniqueand obtained 66 samples of X and XI grade

students of SMAN 11 South Tangerang. Data were collected by 24-hour recall interview, distribution of

nutritional knowledge questionnaire, FFQ (Food Frequency Questionnaire),and IPAQ (International Physical

Activity Questionnaire), and measurement of height and weight. Bivariate data analysis using Chi-Square

test. Students of SMAN 11 South Tangerang were obese as much as 24.2%. The results of the relationship

test with obesity obtained energy intake (p=0.563), protein intake (p=0.462), fat intake (p=0.202),

carbohydrate intake (p=0.143), junk food consumption (p=572), nutritional knowledge (p=0.712), and

physical activity (p=0.002). The conclusion is that there is no relationship between energy intake,

macronutrient intake, junk food consumption, and nutritional knowledge with the incidence of obesity in

students of SMAN 11 South Tangerang with a P>0.05. There is a relationship between physical activity and

the incidence of obesity in students of SMAN 11 South Tangerang with a p-value of (>0.05).

1 INTRODUCTION

Nutritional status is a condition caused by a balance

between intake of nutrients from food and the body's

need for nutrients. Obesity is an indicator of

nutritional status where the intake of nutrients from

food consumed exceeds the nutrients needed by the

body. Obesity occurs due to excessive accumulation

of fat due to an imbalance between energy intake and

energy used for a long time. The problem of obesity

has become a big problem in Indonesia. Obesity in

adolescents can continue into adulthood because it is

a serious problem(Telisa, Hartati, & Haripamilu,

2020). Based on data from the 2018 Riskesdas, there

is a prevalence of obesity or overweight in

adolescents aged 13-15 years, namely 16.0% and in

adolescents aged 16-18 years, namely 13.5%. Banten

Province is one of the provinces with a prevalence

rate of obesity in adolescents above the Indonesian

national average, which is 22.1%. South Tangerang is

one of the cities in Banten Province which has a high

prevalence of obesity, which is 15.9%.

Lifestyle changes are currently occurring in

society, especially among adolescents in the form of

decreased physical activity and changes in eating

patterns that can cause nutritional status instability,

namely increased body weight. Other factors that can

cause obesity in adolescents include excessive intake

of macronutrients, increased consumption of junk

food, age and gender(Telisa et al., 2020). In addition,

the level of knowledge of adolescents is also one of

the factors that cause obesity(A. Dewi et al., 2023).

Factors such as decreased physical activity, excessive

intake of macronutrients, increased consumption of

junk food, and this level of nutritional knowledge, if

carried out in a sustainable manner, can lead to the

risk of obesity. Adolescents who are obese and who

are not treated until adulthood can increase the risk of

metabolic diseases and non-communicable diseases

(NCDs) such as coronary heart disease, hypertension,

stroke, cholesterol, and diabetes mellitus(Suha &

Rosyada, 2022).

According to research conducted by Sembiring

(2022), there is a relationship between physical

activity and obesity in adolescents at Cerdas Bangsa

Fitriyani, S. L. and Dainy, N. C.

The Relationship Between Energy Intake, Macro Nutrition, and Other Factors with the Incidence of Obesity in Students of Senior High School 11 South Tangerang.

DOI: 10.5220/0012919900004564

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 225-231

ISBN: 978-989-758-727-6; ISSN: 2975-8297

225

Private High School, Deli Tua District, Deli Serdang

Regency, Medan with a p-value of 0.021(Sembiring,

Rosdewi, & Yuningrum, 2022). Research conducted

by Telisa (2020), shows that factors that are

significantly related and become risk factors for

obesity in adolescents are energy, protein, fat, and

carbohydrate intake, fast food consumption, and

physical activity(Telisa et al., 2020).

According to research conducted by Dewi, et al

(2023), there is a relationship between diet, level of

knowledge, and consumption of fast food with the

incidence of obesity with the results of 67.1% of

students experiencing obesity, 71.1% of students

experiencing poor diet, 67.1% of students

experiencing a low level of knowledge, and 57.8% of

students choosing fast food consumption(A. Dewi et

al., 2023).

The researcher chose the research location at

SMAN 11 South Tangerang because it is located in

an urban area, there has never been any previous

research, and the survey results can describe many

students who have obesity nutritional status. Based on

previous studies which stated that there are many

factors that cause obesity in adolescents and see the

prevalence rate of obesity in South Tangerang is quite

high. This study aims to determine the relationship

between energy intake, intake of macronutrients

(protein, fat, and carbohydrates), consumption of

junk food, physical activity, and knowledge of

nutrition with the incidence of obesity.

2 METHODS

This research is a type of observational research with

a cross-sectional research design. The population in

this study were all students of class X and XI at

SMAN 11 South Tangerang with a total of 783

students who met the inclusion and exclusion criteria.

Samples were taken using the Simple Random

Sampling technique with a hypothesis testing formula

with a population proportion approach of 2

(Lemeshow, 1997) and a total sample of 66 was

obtained.This research has obtained ethical eligibility

and has been approved by the KEPK FKK-UMJ.

The instrument testing in this study, namely:

a. Body weight was obtained by measuring using

standard The scales with an accuracy of 0.1. The

scales were placed on a flat floor, and the

respondents who were weighed did not use

footwear. Body height was obtained by

measuring using a microtoise that was attached

to the wall with a height of 2 meters from the

floor (accuracy 0.1).The respondents were

measured in an upright standing position with

their shoulders and heels against the wall and

did not use footwear. Then the data obtained is

calculated using the BMI formula to determine

a person's nutritional status.

b. In terms of energy intake and intake of

macronutrients, researchers and enumerators

with a background in nutrition education

conducted 2x24 hour recall interviews with

respondents by asking what food and drink they

had consumed the previous day. This 1x24 hour

recall is carried out 2 times on different days.

c. For the consumption of junk food, researchers

used a modified FFQ (Food Frequency

Questionnaire) questionnaire(Irawan, 2022)

and(Arifin, 2019).

d. In measuring physical activity, researchers used

a questionnaire regarding physical activity or

what activities were carried out during the last 7

days using a questionnaire(IPAQ., 2004)short

form version.

e. In terms of nutritional knowledge, researchers

used a questionnaire regarding knowledge of

balanced nutrition that had been tested for

validity and reliability tests.

Data analysis was performed using the SPSS

application to obtain univariate and bivariate analysis

test results. Bivariate analysis in this study was the

relationship between energy intake, protein intake, fat

intake, carbohydrate intake, consumption of junk

food, physical activity, and knowledge of nutrition

with the incidence of obesity using the Chi-Square

Test.

3 RESULTS

3.1 Overview of Respondent

Characteristics

Table 1: Characteristics of Respondents.

Characteristics

Amount

n %

15 years

16 years

17 years

18 years

ears ol

6,1

40,9

45.5

6,1

1.5

Gender

Man

Woman

25,8

74,2

Total 66 100.0%

ICSDH 2023 - The International Conference on Social Determinants of Health

226

This research was conducted on 66 students of

SMAN 11 South Tangerang, which consisted of

students in class X and class XI. Based on Table 1,

most of the age of the respondents in this study were

16 and 17 years old. The gender characteristics of the

respondents were mostly female (74.2%), while

25.8% were male.

3.2 Univariate Analysis Results

Obesity is one of the health problems of adolescent

nutritional status. To find out, it can be calculated

using a z-score by looking at the age, gender, weight

and height of the student. To find out the distribution

data of the variable description, it can be seen in the

table below.

Table 2: Distribution of Respondents Based on Research

Variables.

Variable Category

Amount

n %

Nutritional

status

Obesity (BMI/U > +2SD)

Not Obese (BMI/U ≤

+2SD)

24,2

75.8

Total 66 100.0

Energy

Intake

More (>110% AKG)

Enough (80-110% RDA)

Less (<80% DDA)

1.5

12,1

86.4

Total 66 100.0

Protein

Intake

More (>110% AKG)

Enough (80-110% RDA)

Less (<80% DDA)

9,1

16,7

74,2

Total 66 100.0

Fat Intake

More (>30% AKE)

Enough (20-30% AKE)

Less (<20% AKE)

9,1

30,3

60,6

Total 66 100.0

Carbohydr

ate Intake

Enough (80-110% RDA)

Less (<80% DDA)

4,5

95.5

Total 66 100.0

Consumpti

on of Junk

Foo

Often (≥26.34)

Rarely (<26.34)

51.5

48.5

Total 66 100.0

Physical

Activity

Low (<600 METs)

Moderate (≥600

METs)

High (≥3000 METs)

19,7

68,2

12,1

Total 66 100.0

Nutrition

Knowledge

Less (<60%)

Enough (60-75%)

Good (>75%)

18,2

39,4

42,4

Total 66 100.0

Based on the research results obtained in Table 2,

there were 24.2% of respondents in the obese

nutritional status category. This figure far exceeds the

prevalence of obesity in South Tangerang, which is

15.9%.(Ministry of Health RI Banten, 2013).

According to WHO (2018) the prevalence of obesity

in adolescents has increased to 18%.

Respondents' intake of energy and macronutrients

was calculated based on the results of a 24-hour food

recall interview and compared with the AKG

(Nutrition Adequacy Rate)(Kemenkes, 2019). Based

on the results obtained in Table 2, it can be seen that

most of the respondents received energy, protein, fat

and carbohydrate intake which were categorized as

lacking (respectively: 86.4%; 74.2%; 60.6%; 95.5%).

The habit of consuming junk food is categorized

into rarely and often by using the cut off point in the

form of the mean from the distribution of the

respondent's data as was done by(Arifin, 2019).From

the results of the data in Table 2, it can be seen that

the consumption of junk food in the frequent category

is 51.5%.

Respondents' physical activity was obtained using

MET calculations and divided into three categories,

namely low/inactive (<600 MET minutes/week),

moderate/minimum active (≥600 MET

minutes/week), and high/active HEPA (≥3000 MET

minutes /Sunday). Data on the distribution of physical

activity can be seen in Table 2. It was found that some

respondents had moderate physical activity (68.2%).

There are respondents with low activity as much as

19.7% and high activity as much as 12.1%.

Respondents' nutritional knowledge was obtained

by filling out a nutritional knowledge questionnaire.

Based on Table 2, it can be seen that most of the

respondents have good nutrition knowledge (42.4%).

However, there are still respondents who have less

nutritional knowledge, namely as much as 18.2%.

3.3 Results of Bivariate Analysis

In this study, bivariate analysis was used to see if

there was a significant relationship between the

dependent variable (obesity) and the independent

variables (energy intake, intake of macronutrients,

physical activity, consumption of junk food, and

knowledge of nutrition). In this bivariate analysis, the

data were processed using the chi-square test with a

significance limit of α = 0.05. If the p-value <0.05 it

can be concluded that there is a relationship between

the two variables.

The Relationship Between Energy Intake, Macro Nutrition, and Other Factors with the Incidence of Obesity in Students of Senior High

School 11 South Tangerang

227

Table 3: The results of the relationship test between the

independent variables and obesity.

Varia bl e

Nutritional Status Total

P-value

Obesity Not Obese

n % n % n %

Ener

Intake

(>110%

AKG

)

0 0.0 1 100 1 100

0.563

Enough

(80-110%

RDA

)

3 37.5 5 62.5 8 100

Less

(<80%

DDA)

13 22.8 44 77.2 57 100

Total 16 24.2 50 75.8 66 100

Protein Intake

(>110%

AKG

)

2 33.3 4 66.7 6 100

0.462

Enough

(80-110%

RDA

)

4 36.4 7 63.6 11 100

Less

(<80%

DDA)

10 20.4 39 79.6 49 100

Total 16 24.2 50 75.8 66 100

Fat intake

(>30%)

2 33.3 4 66.7 6 100

0.202

Enough

(

20-30%

)

2 10.0 18 90.0 20 100

Less

(

<20%

)

12 30.0 28 70.0 40 100

Total 16 24.2 50 75.8 66 100

Carbohydrate intake

Enough

(80-110%

RDA)

2 66.7 1 33.3 3 100

0.143

Less

(<80%

DDA)

14 22.2 49 77.8 63 100

Total 16 24.2 50 75.8 66 100

Junk food Consum

tion

Often

(

≥26.34

)

9 26.5 25 73.5 34 100

0.442

Rarely

(<26.34)

7 21.9 25 78.1 32 100

Total 16 24.2 50 75.8 66 100

sical Activit

Low

(<600

METs

)

8 61.5 5 38.5 13 100

0.002*

Moderate

(≥600

METs

)

7 15.6 38 84.4 45 100

High

(≥3000

METs)

1 12.5 7 87.5 8 100

Total 16 24.2 50 75.8 66 100

Nutrition Knowledge

Not

enough

4 33.3 8 66.7 12 100

0.712

Enough 6 23.1 20 76.9 26 100

Goo

6 21.4 22 78.6 28 100

Total 16 24.2 50 75.8 66 100

*Significant at α<0.05

3.3.1 Relationship of Energy Intake with

Obesity

Based on the results of the bivariate test in Table 3, it

shows that there is no significant relationship between

energy intake and the incidence of obesity with a p-

value >0.05. All respondents with more, sufficient, or

less energy intake categories have the same

proportion of obese and not obese.

3.3.2 Relationship of Macronutrient Intake

with Obesity

Based on Table 3, the results of statistical tests show

that there is no significant relationship between the

variables of protein, fat and carbohydrate intake and

the incidence of obesity in adolescents with a p-value

>0.05. The distribution of the data shows that all

respondents in the category of more, sufficient, or less

protein and fat intake have the same proportion of

obese and non-obese.

In contrast to protein and fat intake, the

distribution of data on carbohydrate intake shows that

respondents with sufficient intake have a higher

tendency to be obese compared to respondents who

have less carbohydrate intake. However, the results of

the chi-square test showed that the p-value was 0.143

(P>0.05), which means that there was no significant

relationship between carbohydrate intake and the

incidence of obesity in adolescents.

3.3.3 Relationship Between Junk Food

Consumption and Obesity

Based on the results of the bivariate test in Table 3, it

shows that there is no significant relationship between

the variable consumption of junk food and the

incidence of obesity with a P>0.05. All respondents

in the category of frequent or infrequent consumption

of junk food had the same proportion of obesity and

non-obesity.

ICSDH 2023 - The International Conference on Social Determinants of Health

228

3.3.4 Relationship of Physical Activity with

Obesity

The statistical test results obtained a p-value of 0.002

(P<0.05), so there is a significant relationship

between physical activity and obesity. Based on the

data distribution in Table 3, it can be seen that most

of the respondents with low physical activity category

were obese (61.5%), while most of the respondents

with moderate and severe physical activity had

nutritional status not obese (respectively: 84.4 %;

87.5%).

3.3.5 Relationship of Nutrition Knowledge

with Obesity

Based on Table 3, the results of the statistical test

obtained a p-value of 0.712 (P>0.05), which means

that there is no significant relationship between

nutritional knowledge and obesity in adolescents. The

distribution of the data shows that respondents with

poor, sufficient, and good nutrition knowledge

categories have the same proportion of obesity and

non-obesity.

4 DISCUSSIONS

4.1 Relationship of Energy and

Macronutrient Intake with Obesity

Energy intake is not related to obesity, these results

are in line with Fridawanti's research (2016) which

states that there is no relationship between energy

intake and obesity. Based on the results of 2x24 hour

food recall interviews with respondents, it shows that

respondents consumed food in small quantities and

types and had irregular eating patterns (eating 1 to 2

times a day), eating small portions, and the food

consumed was not varied. thus affecting the amount

of energy consumed. This is in accordance with the

respondents in Fridawanti's study (2016) which

showed that the food consumed by respondents in

their daily lives was lacking and not in accordance

with the RDA (Nutritional Adequacy Rate)

(Fridawanti, 2016).

Protein intake is not related to obesity, the results

of data on the distribution of protein intake are in line

with research conducted by Rahmani and Dewi

(2018) which shows that there is no significant

relationship between protein intake and obesity. This

is evidenced by the p-value obtained, namely 0.120

(>0.05). It is also similar to Pramono's research

(2015) which states that there is no relationship

between protein intake and the incidence of obesity

with a p value = 0.32 (>0.05). If energy intake is

lacking for various reasons, protein intake will be

used to meet energy needs, so that there is not enough

protein available for the formation of new tissue or

for repairing damaged tissue. Aside from being a

source of energy, protein also has a function that

cannot be replaced by other nutrients. which builds

and maintains the cells of the body's tissues. Protein

also functions to regulate fluid balance, maintain

body neutrality, form antibodies and also transport

nutrients(Pramono Dwi Sasmito, 2015).

Fat intake is not related to obesity, the results of

data on the distribution of fat intake are in line with

Praditasari's research (2018) which states that there is

no relationship between fat intake and obesity with a

p value = 0.240 (>0.05). Fat intake is not associated

with obesity status in adolescents, but the

contribution of fat to the RDA which is higher allows

obesity to occur. Food intake is one of the factors that

causes obesity, but besides fat intake, there are

intakes of carbohydrates, protein, water consumption,

and other micronutrients that can also cause obesity.

In addition to fatty acid composition, overweight and

obesity can be affected by the energy balance in the

body. In addition, food intake and energy expenditure

can be influenced by diet, hereditary

history(Praditasari & Sumarmik, 2018).

This research is not in line with Ainun (2022)

which states that there is a significant relationship

between fat intake and obesity, this is evidenced by

the p value <0.05, namely p = 0.0001. Excessive fat

intake over a long period of time can lead to obesity.

Accumulation of fat in the body will be stored in

adipose tissue which can cause obesity if it occurs

continuously(Ainun, 2022).

Carbohydrate intake is not related to obesity, the

results of the distribution of carbohydrate intake data

are in line with research conducted by Ainun (2022),

namely there is no relationship between carbohydrate

intake and obesity in adolescents with a p-value of

0.06 (>0.05). Excess carbohydrate intake will be

stored in muscle or fat. Excessive carbohydrate intake

in adolescents can increase insulin secretion, increase

fat storage, and increase serum triglyceride levels.

This will cause obesity if allowed to accumulate for a

long time(Ainun, 2022). It is also similar to the

research conducted by Pramono (2015) which states

that there is no relationship between carbohydrate

intake and the incidence of obesity. Adequate intake

is important to maintain the glycogen reserves

required for long-term physical activity. An increase

in muscle glycogen with the accumulation of

The Relationship Between Energy Intake, Macro Nutrition, and Other Factors with the Incidence of Obesity in Students of Senior High

School 11 South Tangerang

229

carbohydrates will increase stamina for 30-60

minutes longer(Pramono Dwi Sasmito, 2015).

4.2 Relationship Between Junk Food

Consumption and Obesity

Consumption of junk food is not related to obesity,

the results of this analysis test are in line with research

conducted by Indriawati and Soraya (2009) which

states that there is no significant relationship between

the frequency of consumption of junk food and

obesity with P>0.05(Indriawati & Soraya, 2009).

This research is not in line with research conducted

by Nugroho and Hikmah (2020) which states that

there is a significant relationship between the

frequency of consumption of junk food and the

incidence of obesity in adolescents with a p-value of

0.001 (<0.05)(Nugroho & Hikmah, 2020).

This happens because with the advancement of

technology, teenagers can find various kinds of

information, one of which is from social media. The

effects of using social media are various, one of

which is that many teenagers follow the trend that is

circulating. Junk food is one of the trends that is

usually followed by teenagers, because the marketing

of junk food on social media is quite extensive. The

rise of junk food marketing makes teenagers have a

high sense of curiosity to try these junk food products,

so that every time there is a new type of junk food,

teenagers have the desire to try it without thinking

about the impact or effects of frequent consumption

of junk food. Frequent consumption of junk food can

increase fat in the body which is not balanced, thus

increasing degenerative diseases(Tanjung et al.,

2022).

4.3 Relationship of Physical Activity

with Obesity

Physical activity is associated with the incidence of

obesity, this is in line with research conducted by

Ayu, Paramita, and Indonesiani et al. (2023) that there

is a significant relationship between physical activity

and the incidence of obesity in adolescents at SMAN

4 Denpasar with a p-value (<0.05)(Ayu, Paramita,

Indonesiani, & Gede, 2023). Similar to the research

conducted by Prima et al. (2018) which shows that

there is a relationship between physical activity and

the incidence of obesity in adolescents. This happens

because most adolescents who are obese do less

physical activity or do more light physical activity at

higher risk of developing obesity due to lack of

energy expenditure. Sedentary behavior in

adolescents is a strong risk factor for obese

adolescents(Mahasiswa, Biomedis, Prima, Andayani,

& Abdullah, 2018).

4.4 Relationship of Nutritional

Knowledge with Obesity

Nutritional knowledge is not related to obesity, this

result is in line with research conducted by Dewi and

Kartini (2017) which states that there is no

relationship between nutritional knowledge and the

incidence of obesity with a p-value of 0.076 (>0.05).

Nutritional knowledge is an indirect factor that can

affect a person's nutritional status, so if there is no

relationship between nutritional knowledge and the

incidence of obesity, then this can be influenced by

the direct factor, namely food consumption(P. L. P.

Dewi & Kartini, 2017).

This research is not in line with the research

conducted by Sineke et al. (2019) to students of SMK

Negeri 1 Biaro which stated that there was a very

strong relationship between the level of nutritional

knowledge and the incidence of obesity in students

with a p value = 0.042 (P<0.05) (Sineke, Kawulusan,

Purba, & Dolang, 2019).

5 CONCLUSIONS

Students of SMAN 11 South Tangerang have a

nutritional status of obesity as much as 24.2%. Intake

of energy and macronutrients (protein, fat, and

carbohydrates) of SMAN 11 South Tangerang

students are mostly in the less category, namely

86.4%, 74.2%, 60.6%, and 95.5%, respectively.

Some students of SMAN 11 South Tangerang have a

habit of consuming junk food frequently, namely

51.5%. As many as 68.2% of students at SMAN 11

South Tangerang have moderate physical activity.

There are 18.2% of students at SMAN 11 South

Tangerang who have poor nutritional knowledge.

There is no significant relationship between energy

intake, intake of macronutrients, consumption of junk

food, and knowledge of nutrition with the incidence

of obesity in students of SMAN 11 South Tangerang

with a p-value (>0.05).

ACKNOWLEDGMENTS

The author would like to thank all parties involved,

especially SMA Negeri 11 Tangerang Selatan who

have given permission to conduct research. In

addition, the author would like to thank the

ICSDH 2023 - The International Conference on Social Determinants of Health

230

Muhammadiyah University ICSDH committee Prof.

Dr. Hamka who has facilitated the author to convey

the results of this research.

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