Nutritional Status, Blood Glucose, and Blood Pressure as Factors for

Early Detection of Metabolic Risk in College Students: Observational

Research

Adi Sucipto

1,* a

, Desty Ervira Puspaningtyas

, Puspita Mardika Sari

Silvia Dewi Styaningrum

, Dwita Mukti Rahmawati

, Getha Puji Lestari

Renata Deby Sintia

and Dhea Putri Ananda

Nursing Program, Faculty of Health Sciences, Respati University Yogyakarta. Yogyakarta 55281, Indonesia

Nutrition Program, Faculty of Health Sciences, Respati University Yogyakarta. Yogyakarta 55281, Indonesia

Keywords: Metabolic Syndrome, Body Mass Index, Blood Glucose, Blood Pressure.

Abstract: Metabolic health problems are increasingly receiving attention among students because modern lifestyles tend

to be less active and unhealthy eating habits. Nutritional status, random blood glucose, and blood pressure are

important indicators that can provide an overview of a person's metabolic health status. Low awareness of the

importance of metabolic disorders early detection and lack of understanding of the relationship between

nutritional status, random blood glucose, and blood pressure can cause delays in preventative action and

management of the risk of metabolic disorders. This study aims to determine the relationship between

nutritional status, random blood glucose, and blood pressure as factors for early detection of the risk of

metabolic disorders in students. This observational study with a cross-sectional approach was conducted in

July 2023 in Universitas Respati Yogyakarta and carried out on health students from several health study

programs taken by accidental sampling. The number of samples in the research was 35 respondents. The

instruments used were microtoise, body scales, digital blood pressure meter, glucometer, and recording sheet.

The respondents' average body mass index (BMI) was 25.84, with a body weight of 63.76 kg and a height of

157.31 cm. Respondents' average random blood glucose and blood pressure were respectively 89.63 mg/dL

and 112/80 mmHg. Body weight and BMI correlate fairly strongly with diastolic blood pressure, with r=0.394

(p=0.019) and r=0.414 (p=0.013). A relationship exists between body weight and BMI with diastolic blood

pressure. It is hoped that the research results will provide further insight into the importance of early detection

of metabolic risk in students so that it becomes a more effective prevention and health intervention strategy

in the campus environment.

1 INTRODUCTION

College is a critical phase of life, where students face

new academic, social, and environmental demands

that can impact their health. A health problem that is

often found is metabolic syndrome disorder.

Metabolic syndrome is a group of symptoms from

various cardiometabolic risk factors including insulin

resistance, glucose intolerance, dyslipidemia, and

central obesity. This condition increases the risk of

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https://orcid.org/0000-0003-2100-6703

Corresponding author

cardiovascular disease, type 2 diabetes, orthopedic

problems, and mental disorders (Djausal, 2015).

Someone is categorized to suffer from metabolic

syndrome if they experience at least three of five

conditions, namely hypertension (high blood

pressure), low HDL levels (dyslipidemia), high

triglyceride levels, high blood sugar levels or

prediabetes, and obesity with fat accumulation in the

abdomen (Rahma Listyandini, Fenti Dewi Pertiwi,

2020)

Sucipto, A., Puspaningtyas, D. E., Sari, P. M., Styaningrum, S. D., Rahmawati, D. M., Lestar i, G. P., Sintia, R. D. and Ananda, D. P.

Nutritional Status, Blood Glucose, and Blood Pressure as Factors for Early Detection of Metabolic Risk in College Students: Obser vational Research.

DOI: 10.5220/0013660300003873

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 1st International Conference on Medical Science and Health (ICOMESH 2023), pages 50-54

ISBN: 978-989-758-740-5

Metabolic diseases have increased significantly

among the global population. Previous research

showed that the prevalence of metabolic syndrome

among the global population is 20-25% (Rini, 2015).

College students, as a relatively young age group, are

often considered to be at low risk for these diseases.

However, lifestyle changes, unhealthy diets, and high

levels of stress can lead to increased metabolic risk in

this group. The results of a research study conducted

by Wohangara and Santoso showed that the majority

of the nutritional status of Tarumanagara University

students class of 2017 was obese (45.2%), did not

exercise (41.1%), and had the habit of consuming

junk food once per week (Wohangara and Santoso,

2021). Cases of metabolic syndrome in adolescents

have increased over the past year last decade.

Research conducted by Dieny et al found that the

increase in the incidence of metabolic syndrome in

adolescents was caused mainly by an increase in

obesity rates among adolescents (Dieny, Widyastuti

and Fitranti, 2015).

Some of the reasons for the increase in the

prevalence of metabolic syndrome in teenagers are

due to lack of physical activity, fast food, stress, lack

of sleep, and high sugar (Rochmah et al., 2014).

Students tend to spend a lot of time in front of screens,

whether studying, working, or socializing digitally,

which can lead to a decrease in physical activity.

Apart from that, unhealthy food choices and the habit

of consuming drinks high in sugar also contribute to

the increased risk of metabolic health problems

among students.

This situation is a serious concern because

metabolic health problems can impact academic

performance, psychological well-being, and overall

quality of life (Rochmah et al., 2014). Students who

experience metabolic health problems tend to face a

high risk of long-term illnesses, such as type 2

diabetes, heart disease, and other health problems.

Therefore, further understanding of the factors that

cause and influence metabolic health problems

among students is very important to develop effective

prevention and intervention strategies, one of which

is through early detection of the risk of metabolic

syndrome. Early detection can be done by carrying

out routine checks such as adolescent nutritional

status, blood pressure, and blood glucose levels in

adolescents. Therefore, regular examinations are key

in preventing and managing metabolic syndrome in

adolescents (Sihombing and Tjandrarini, 2015).

2 METHODS

This research is an observational study with a cross-

sectional approach. This study aims to determine the

relationship between nutritional status, random blood

glucose, and blood pressure as factors for early

detection of the risk of metabolic disorders in

students. Data collection was carried out at the

Anthropometry Laboratorium, Universitas Respati

Yogyakarta in July 2023. This research population

was active students of the Faculty of Health Sciences,

Universitas Respati Yogyakarta totaling 35 students.

The sampling process is carried out by accidental

sampling. The tools used in collecting data are

microtoise, body scales, digital sphygmomanometers,

glucometers, and recording sheets.

The data collection process is carried out by taking

anthropometric measurements (body weight and

height) first, after that measuring blood pressure and

checking blood glucose which are then recorded in an

observation sheet. The data collection process was

assisted by three student research assistants who

played a role in anthropometric measurements and

blood pressure checks. All assistants have obtained

previous perceptions to be able to carry out valid

measurements on respondents.

All respondents were explained the entire research

process, their rights, and obligations. Respondents

signed informed consent as an agreement to

participate in the research. The data collection

process is carried out after obtaining the ethical

clearance from the Health Research Ethics

Commission, Faculty of Health Sciences, Universitas

Respati Yogyakarta with number

056.3/FIKES/PL/V/2023 and research permit number

088/PPPMPL-Eks/V/2023. The data normality test

used Shapiro Wilk because the sample size was <50

people. Normality test results for body weight, body

height, body mass index (BMI), random blood

glucose, and diastolic blood pressure were normal

(>0.05). The bivariate variable test uses the Annova

because the data is from more than 2 categories and

is normally distributed. For the data not normally

distributed, the statistical analysis used is Kruskal-

Wallis.

3 RESULTS AND DISCUSSION

Table 1 presents the data on respondent

characteristics. Based on the characteristics of the

respondents, it is known that the normality test results

Nutritional Status, Blood Glucose, and Blood Pressure as Factors for Early Detection of Metabolic Risk in College Students: Observational

Research

with Shapiro-Wilk showed that age and systolic blood

pressure data were not normally distributed.

Table 1. Characteristics of Respondents

Variable Mean±SD p

Age (years) 22 (20

–

23)* <0.001

Bod

wei

(

63.76±15.16 0.064

Hei

(

)

157.31±6.12 0.395

BMI

(

)

25.84±6.41 0.083

Random blood glucose

(

/dL

)

89.63±12.78 0.497

stolic blood

ressure 112

(

–

136

)

* 0.004

Diastolic blood

ressure 80.54±8.42 0.093

*median (minimum-maximum)

#normality test with Shapiro-Wilk

The median age of respondents is 22 years with a

minimum age of 20 years and a maximum of 23 years.

The average body weight of respondents was 63.76

kg with a standard deviation (SD) of 15.16 kg. The

average height of respondents was 157.31 cm with an

SD of 6.12 cm. The average body mass index (BMI)

of respondents was 25.84 kg/m2 with a SD of 6.41

kg/m2. The mean random blood glucose (GDS) was

89.63 mg/dL with an SD of 12.78 mg/dL. The median

systolic blood pressure is 112 mmHg with a minimum

and maximum range of 99-136 mmHg, while the

average diastolic blood pressure is 80.54 mmHg with

an SD of 8.42 mmHg.

Based on Figure 1, there is a difference in

nutritional status based on Asian standards and

Indonesian standards. Based on Asian standards, the

number of respondents in the normal category is less

than the Indonesian standard. Meanwhile, the Asian

standard overweight category is higher than the

Indonesian standard. This is because the Asian

standard categorization range for normal BMI is

narrower than the Indonesian standard, in which the

Asian standard for normal BMI is 18.5 – 22.9 kg/m

while the Indonesian standard for normal BMI is 18.5

– 25 kg/m

(Iqbal and Puspaningtyas, 2018).

Table 2 shows differences in the characteristics of

health indicators based on nutritional status based on

Asian standards. The median age for underweight and

normal group is 21 years, with an age range between

20 and 23 years. Body weight increased along with

increasing nutritional status, with the highest value in

the obesity group (78.01 ± 11.66 kg) and the lowest

in the underweight (44.2 kg). The average height of

the normal group (159.13 ± 6.29 cm) tends to be

higher than the nutritional status of other groups. BMI

increased along with increasing nutritional status,

with the highest value in the obesity group (32.39 ±

4.57 kg/m2) and the lowest in the underweight group

(18.16 kg/m2).

Figure 1. Distribution of Nutritional Status Based on Asian

Standards and Indonesian Standards

The average random blood glucose in each group

was within the normal range (73-90 mg/dL). Median

systolic and diastolic blood pressure for each group

was within the normal range. There were no

significant differences in age, height, random blood

glucose, or systolic diastolic blood pressure between

the underweight, normal, overweight, and obese

groups (p=0.700; 0.378; 0.614; 0.693; 0.216). There

are significant differences in body weight and BMI

between the underweight, normal, overweight, and

obese nutritional status groups (p<0.001).

Table 2. Differences in Characteristics of Health Indicators Based on Asian Standard Nutritional Status

Variable

Mean ± SD

Underweight Normal Overweight Obesity p

Age (years) 21 21 (20-23)* 22 (20-23)* 22 (20-23)* 0.700*

Body weight (kg) 44.2 52.12± 6.74 62.68 ± 6.17 78.01± 11.66 <0.001*^

Height (cm) 156 159.13± 6.29 158.10 ± 6.18 155.16 ± 5.88 0.378**

BMI (kg/m

) 18.16 20.51± 1.43 25.03 ± 1.19 32.39 ± 4.57 <0.001*^

Random blood glucose (mg/dL) 73 89.93± 14.29 88.40 ± 7.23 90.93 ± 12.93 0.614**

Systolic blood pressure 112 113 (99-136)* 111 (104-116)* 116 (104-136)* 0.693*

Diastolic blood pressure 84 78.73± 7.29 76.00 ± 6.32 83.86 ± 9.56 0.216**

*median (minimum-maximum)

# kruskal-wallis

**Annova

^significant at p<0.001

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Table 3. Differences in Characteristics of Health Indicators Based on Indonesian Standard Nutritional Status

Variable

Mean ± SD

Underweight Normal Over

weight

Obesity

ears

)

21 22

(

20-23

)

*21

(

20-22

)

*22

(

20-23

)

* 0.568*

Bod

wei

(

44.2 52.89 ± 6.72 65.37 ± 6.61 78.01 ± 11.66 <0.001*^

Hei

(

)

156 158.82 ± 5.96 159.17 ± 8.43 155.16 ± 5.88 0.394**

BMI (kg/m

) 18.16 20.91 ± 1.77 25.77 ± 0.64 32.39 ± 4.57 <0.001*^

Random blood glucose

(

/dL

)

73 89.71 ± 13.38 88.67 ± 10.21 90.93 ± 12.93 0.622**

stolic blood

ressure 112 111

(

99-136

)

* 113

(

104-116

)

* 116

(

104-136

)

* 0.796*

Diastolic blood pressure 84 78.29 ± 6.97 76.67 ± 8.62 83.86 ± 9.56 0.247**

*median (minimum-maximum)

# kruskal-wallis

**Annova

^significant at p<0.001

Table 3 shows the differences in characteristics of

health indicators based on nutritional status based on

Indonesian standards. The median age for the

underweight and overweight group is 21 years old,

with an age range of 20 to 23 years. Similar to Asian

standards, body weight increased along with

increasing nutritional. The average height of the

overweight group (159.17±8.43 cm) is considered to

be higher than the nutritional status of other groups.

There is a difference in BMI for the normal group

(20.91 kg/m2) and overweight group (25.77 kg/m2)

based on the Indonesian standard and Asian standard,

in which the Indonesian standard is higher than the

Asian standard. There were no significant differences

in age, height, random blood glucose, or systolic

diastolic blood pressure between the underweight,

normal, overweight, and obese groups (p=0.568;

0.394; 0.622; 0.796; 0.247). There were significant

differences in body weight and BMI between the

underweight, normal, overweight, and obese

nutritional status groups (p<0.001).

Table 4 shows that there is no significant

correlation between body weight, height, and BMI

with random blood glucose levels and systolic blood

pressure. However, there is a significant positive

correlation between body weight and BMI with

diastolic blood pressure.

Table 4. Correlation Test Between Nutritional Status and

Blood Glucose Levels and Blood Pressure

*pearson

#spearman

^significant at p<0.05

The results of this research are in line with

research conducted by Utami and Ulumuddin et al,

which states that there is a relationship between body

mass index and systolic and diastolic blood pressure

with weak relationship strength. This shows that body

mass index is not the main factor that influences

blood pressure in type 2 diabetes mellitus patients

(Utami, 2019), (Ulumuddin and Yhuwono, 2018).

This is different from the results of research

conducted by Nurmalasari et al which shows that

there is no significant relationship between BMI and

fasting blood glucose levels in adults and the elderly

with a p-value> 0.05 (Efon Nurmalasari, Melvinawati

Kristina Naibaho and Ahmad Fitra Ritonga, 2021).

The results of research conducted by Rosiana et al on

differences in nutritional status and quality of food

intake in elderly people who took and did not follow

Prolanis showed that there were differences in

nutritional status between subjects who took and did

not take Prolanis (p=0.029), but there were no

differences in quality of food intake based on prolanis

participation (p=0.538) (Rosiana Dwi Astiti, Ani

Margawati, Ayu Rahadiyanti, 2019).

An increase in body weight and BMI will

contribute to blood pressure (Fadlilah, Sucipto and

Amestiasih, 2019). Increased body weight can affect

blood pressure through several mechanisms. Several

factors that can explain this relationship include an

increase in the amount of fat tissue, increased insulin

levels, increased heart rate, and genetic factors.

Increasing body weight can increase the amount of

fatty tissue in the body, which in turn can increase

blood volume and blood pressure. Additionally,

increased body weight is also associated with

increased insulin levels, which can cause sodium and

water retention, thereby increasing blood volume and

blood pressure. Apart from that, increasing body

weight can also cause an increase in heart rate and

genetic factors can also influence blood pressure

Nutritional Status, Blood Glucose, and Blood Pressure as Factors for Early Detection of Metabolic Risk in College Students: Observational

Research

(Efon Nurmalasari, Melvinawati Kristina Naibaho

and Ahmad Fitra Ritonga, 2021; Kalangie, Warouw

and Umboh, 2016). The indicators of nutritional

status that most influence blood pressure in male

adolescents are BMI and waist circumference, in

female adolescents it is neck circumference, and in

both genders, it is BMI (Novianingsih and Kartini,

2022). The results of the study showed that the

indicator of nutritional status that most influences

blood pressure in adolescent boys is BMI and in

adolescent girls is neck circumference.

4 CONCLUSIONS

There is a relationship between body weight and BMI

and diastolic blood pressure. It is hoped that the

research results will provide further insight into the

importance of early detection of metabolic risk in

students so that it can become a more effective

prevention and health intervention strategy in the

campus environment. By understanding the risk

factors involved, it is hoped that the results of this

research will provide better insight into the

development of health programs that can motivate

positive behavioral changes and improve metabolic

health among students. Through this effort, it is hoped

that positive changes in lifestyle and health can be

achieved, which in turn can have a positive impact on

students.

ACKNOWLEDGEMENTS

The researchers would like to thank the Research and

Community Service Institute (LPPM) of Universitas

Respati Yogyakarta, which has provided grant funds

through the internal research grant scheme for the

2023 fiscal year. The research contract agreement

letter is 01/Pen/Hibah.Int/PPPM/V/2023. The

researcher would also like to express his thanks to the

laboratory assistant for the assistance and permission

given as well as the enumerator friends who helped in

collecting research data

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