The Effect of Body Mass Index on Health-Related Parameters in University Students

 

Muhammad Zuhaili Suhaimi1, Rabiu Muazu Musa1, Muhammad Zulhusni Suhaimi2,

Mohamad Razali Abdullah3, Ahmad Bisyri Husin Musawi Maliki4

1Centre for Fundamental and Continuing Education,

Universiti Malaysia Terengganu, 21030, Kuala Nerus Terengganu, Malaysia.

2Department of Applied Health Sciences, Faculty of Science,

Universiti Tunku Abdul Rahman (UTAR), Kampar Campus, 31900 Kampar, Perak, Malaysia.

3East Coast Environmental Research Institute,

Universiti Sultan Zainal Abidin, 21300, Kuala Nerus, Terengganu, Malaysia.

4Faculty of Applied Social Science, Universiti Sultan Zainal Abidin, 21300, Kuala Nerus, Terengganu, Malaysia.

*Corresponding Author E-mail: rabiumuazu86@gmail.com

 

ABSTRACT:

Body mass index (BMI) is a significant marker in assessing the health risk factors of an individual. Although, the discovery of BMI is over 200 years, however, its application as a measure of health is fairly new. Hitherto, the prevalence of higher BMI amongst university students is on the rise. Consequently, the present study endeavor to investigate the association of BMI and other health-related parameters namely; per cent body fat, visceral fat, basal metabolic rate (BMR), systolic and diastolic blood pressure, resting heart rate, core and upper muscle endurance, maximum oxygen consumption (V02max) and metabolic equivalent (MET). A total number of 232 university students were enrolled and completed the physical fitness assessments and health indicator measurement of the variables. A multiple Linear Regression (MLR) was used to observe the association of the BMI as the dependent variable with the physical fitness as well as health parameters as independent variables. A significant regression model was obtained F (3.225, 5) = 301.104, P <0.0001, R2 = 0.869 demonstrating that the model has accounted for about 87% variability of the whole dataset. Sensitivity analysis demonstrated that per cent body fat, visceral fat, BMR, as well as VO2max, are the major contributors towards the model prediction P <0.001. Moreover, positive significant relationships were detected between the BMI, per cent body fat, visceral fat, BMR, systolic and diastolic blood pressure whilst negative association between the BMI and performance in upper muscle endurance and VO2max were noted. BMI index could be a potential marker of assessing university students’ health-related risks that would consequently reveal vital information about their overall health status.

 

KEYWORDS: Physical Activity, Health Risk Factors, BMI, University Students, Health Related Parameters.

 

 


INTRODUCTION:

Obesity is characterized by excessive body fat and it is classified by body mass index (BMI)1. The increase in the prevalence of obesity over the last few decades has become a worldwide major health problem in all generation of most countries2.

 

 

It is often reported that obesity is an important biological risk factor for the development of chronic diseases (CDs)3,4. Thus, obesity could be categorized as an important health indicator that poses a public health challenge globally. To this effect, many individuals have sought to engaging in behaviors that could lead to maintaining a desirable weight in order to convert the impact of obesity.

 

Obesity and its relationship with the volume of exercises and active lifestyle coupled with inadequate amount of physical activity have been analyzed in various populations5,6. Prior studies have shown that the trend of obesity could be tracked from childhood and adolescence to adulthood7. Thus, it is generally accepted that engage in adequate health-related physical activity counter the development of CD and metabolic risk in adulthood8,9. Therefore, encouraging positive lifestyle through the right amount of health-related physical fitness activity amongst university students is a major challenge to health personnel due to the negative effects of childhood obesity and lower fitness levels on health in adulthood when this active lifestyle is neglected10,11. However, in Malaysia, there is a relatively limited information with respect to the BMI and its corresponding relationship with some other essential health related parameters amongst university students. As such, the present study is aimed at investigating the association between BMI status as well as several essential health-related physical fitness parameters in university students.

 

MATERIALS AND METHODS:

Participants:

Two hundred and thirty-two students of Universiti Malaysia Terengganu were recruited to assess their anthropometric measurements and health-related fitness components. Individuals were excluded from the study if they had acute heart disease, or any chronic disease such as hypertension (>140/90mmHg), diabetes mellitus, renal failure, heart disease or any medical problems.

 

Study Procedure:

The participants were given a briefing about the nature and risk of testing protocols before the testing was started. Before the commencement of the research, each participant was asked to sign an informed consent form. It worth to mention that this has been reviewed and approved by the research ethics committee (Human) of Universiti Sains Malaysia in accordance with the Helsinki protocol (USMKK/PP/JEPeM (217.3,) (16.6).

 

Anthropometric measurement:

After recruitment, height, weight, Percent body fat, muscle percentage, body mass index (BMI), resting heart rate and blood pressure of the subjects were taken. Resting heart rate and blood pressure of the subjects was measured by using the Omron Automatic Pressure Monitor (SEM1 - Model) and the height of the subjects was measured by using Body meter 406 (SECA). While the weight, Percent body fat, muscle percentage and BMI of the subjects was measured by using Bioelectrical Impedance Analysis (Omron). All the tests were conducted following the standardized measurement of health parameters12,13.

 

 

 

 

Health-Related Parameters Measurement:

Muscle endurance:

The muscle endurance of the participant was assessed via 1-Minutes Push-up and 1-Minute Sit-up Test. The validity and reliability of the push-up and sit-up test were widely documented in the previous investigation14.

 

1 - Minute Push-up Test:

This test measures muscular endurance of the upper body (anterior deltoid, pectoralis major, and triceps). The hands of the subjects were placed slightly wider than shoulder width apart, with fingers pointing forward. The administrator was placed one fist on the floor below the subject’s chest. Starting from the up position (elbow extended), the subjects always kept the back straight and lower the body to the floor until the chest touches the administrator’s fist. Subjects then returned to the up position and this was counted as one repetition. Resting could be done only in the up position. The total number of correct push-up in 1 minute was recorded as the score.

 

1 - Minute Sit-up Test:

This test evaluates the endurance of the abdominal muscle. The procedure begins with the participants lying on the back, knees bent, heels flatted on the floor with the crossed on the chest whilst hands placed on the opposite shoulders. The buttocks remained on the floor with no thrusting of the tips. A partner holds the feet down firmly. Then, the subjects were performed as many correct sit-ups as possible in one minute. In the up position, the subjects touched the elbows to the knees and then returned until the shoulder blades touched the floor. Any resting was done in the up position. The neck of the subjects remains in a neutral position. The total number of correct sit-ups in 1 minute was recorded as the final score15.

 

Cardiorespiratory fitness:

The cardiorespiratory fitness of the subjects was assessed using the 20-meter Multistage Shuttle Run Test. The test was conducted according to previous research 16. Reliability and validity of this test for determining the VO2max among children and adolescent have been widely documented17,18. In Asian, the validity of 20-metre multistage shuttle run for predicting VO2max of adult Singaporean athletes has also been reported19. The location of the Multistage shuttle run test was performed at field track at the Sports Complex of University Malaysia Terengganu, Terengganu. The measurement involved a continual incline in running speed from 20-meter distance with the running velocity for each 20-meter distance instructed by audible ‘beep’. Each participant was instructed to finish the 20-meter distance prior to each noticeable beep.

 

 

Statistical Analysis:

In the current investigation, a multiple linear regression analysis was carried out to ascertain the association of the BMI and the fitness components namely; per cent body fat, visceral fat, basal metabolic rate (BMR), systolic and diastolic blood pressure, resting heart rate, core and upper muscle endurance, maximum oxygen consumption (V02max) and metabolic equivalent (MET). The BMI was used as the dependent variable whilst the aforesaid health-related parameters were utilized as the independent variables. The data was statistically analyzed using the XLSTAT 2014 add-in software USA at p ≤ 0.05 alpha level of confidence.

 

RESULTS:

Table 1 shows the descriptive statistics of the samples in the present investigation. It could be seen from the table the number of the participants, the minimum, maximum, mean scores, as well as the standard deviation, are projected.

 

Table 2 demonstrated the goodness of fit of the model in the present study. It could be seen that a significant model that accounted for approximately 87% of the whole dataset was obtained. Moreover, the mean square error (MSE), the root means square error (RMSE), as well as the mean percentage error (MAPE), are considerably low. This indicated that the model is effective in explaining the selected measured parameters in the present investigation.

 

Table 3 projects the contribution of the measured parameters towards the predictive efficacy of the model developed. It could be seen from the table that some health parameters namely, per cent body fat, visceral fat, BMR, as well as VO2max, are the major contributors towards the model prediction P < 0.001.

 

Table 1: Descriptive statistics of the study variables

Variables

Mean

Std. D

BMI

23.342

4.917

Body Fat%

25.667

8.049

Muscle Mass

28.875

5.752

Visceral Fat

5.878

5.184

BMR

1358.733

261.669

Systolic BP

114.252

12.281

Diastolic BP

75.474

8.700

Resting Heart Rate

82.030

12.238

Push-Up

24.961

12.342

Sit Up

23.909

11.055

V02Max

27.906

8.142

Met

4852.355

5468.353

 


 

Table 2: Model Goodness of fit parameters

Source

DF

MSE

RMSE

MAPE

Adj R²

F

Sig.

Model

5.00

3.225

1.796

5.038

0.867

0.869

301.104

0.001

 


Table 3: Variables contribution towards the model predictive efficacy

Source

Value

SE

t

Sig

Intercept

4.314

1.464

2.947

0.004*

Body Fat%

0.243

0.026

9.176

0.000**

Muscle Mass

0.000

0.000

Visceral Fat

0.327

0.046

7.122

0.000**

BMR

0.009

0.001

9.734

0.000**

Systolic BP

0.000

0.000

Diastolic BP

0.000

0.000

Resting Heart Rate

0.000

0.000

Push-Up

0.026

0.014

1.840

0.067 

Sit Up

0.000

0.000

V02max

-0.062

0.025

-2.509

0.013*

MET

0.000

0.000

 

 

** P < 0.001

*P < 0.05

Table 4 indicated the correlations metrics as well as the inferential statistics of the model in the measured parameters. It could be seen that some positive significant relationships were detected between BMI, per cent body fat, visceral fat, BMR, systolic and diastolic blood pressure whilst negative association between the BMI and performance in upper muscle endurance and VO2max were observed.

 

 

Table 4: Correlations metrics and inferential statistics of the measured variables

Variables

1

2

3

4

5

6

7

8

9

10

11

12

1. BMI

1

 

 

 

 

 

 

 

 

 

 

 

2. BODY FAT%

0.602

1

3. MUSCLE MASS

-0.097

-0.398

1

4. VISCERAL FAT

0.857

0.419

-0.018

1

5. BMR

0.721

0.064

0.202

0.779

1

6. STBP

0.250

-0.160

0.179

0.370

0.513

1

7. DSBP

0.290

0.229

-0.058

0.302

0.243

0.632

1

8. RHR

0.034

0.267

-0.013

0.018

-0.137

-0.058

0.248

1

9. PUSH-UP

-0.186

-0.524

0.229

-0.083

0.087

0.195

-0.189

-0.315

1

10. SIT UP

-0.106

-0.561

0.259

0.036

0.264

0.346

-0.021

-0.341

0.675

1

11. V02 Max

-0.220

-0.677

0.338

-0.049

0.271

0.275

-0.139

-0.329

0.591

0.685

1

12. MET

-0.074

-0.145

-0.141

-0.076

-0.030

0.049

-0.014

-0.094

0.157

0.187

0.160

1

*Values in bold are different from 0 with a significance level alpha=0.05


DISCUSSION:

The major finding of the present investigation demonstrated that per cent body fat, visceral fat, BMR as well as VO2max are the major contributors towards the prediction of the BMI in the studied population (Table 3). It has been generally speculated that a lean stomach (belly) is linked to a healthier life. Visceral fat is normally the fat that surrounds the abdominal organs of an individual. While it is normal to possess a certain level of visceral fat in the abdomen, nonetheless; a high volume of visceral fat could be a harbinger to some serious health problems19,20. Moreover, a high deposition of visceral fat could lead to a high blood pressure as well as inflammation that often increases the risk of central obesity. On the other hand, per cent body fat, basal metabolic rate as well as VO2max could describe the sedentary level of an individual and hence give rise to high BMI21,22. It is worth to highlight that per cent body fat, visceral fat, basal metabolic rate coupled with a low rate of VO2max could be a significant indicator of BMI score23,24.

 

Some significant relationships were observed between the BMI, per cent body fat, visceral fat, BMR, systolic and diastolic blood pressure whilst negative association between the BMI and performance in upper muscle endurance and VO2max were detected (Table 4). These correlations offer some data to recognize that excessive fat deposition, as well as less physical activity, increases the prevalence of obesity in youth. It has been reported in the previous study that blood pressure level is also connected to the BMI25,26. It is against this background that the previous researchers reported BMI as a better predictor of mortality than other health-related parameters in a population amounting to 60,000            adults 27.

 

CONCLUSION:

Although it is often perceived that BMI may not be a significant marker for health diagnosis, nonetheless, the increasing empirical evidence is demonstrating that BMI is still essential for population-level screening. Consequently, it is further emphasized in the current investigation that BMI is strongly associated with low health-related fitness of the young adults’ population specifically the university students. Hence, it is recommended that university students need to improve their participation in physical activities and exercises. It is also suggested the further study of this kind should be extended to all universities in Malaysia to acquire more information that could highlight the physical fitness status of the Malaysian university students. The finding from this research can be used as a baseline and guideline for government or private stakeholders in making future policies or strategic plans regarding the health status of university students.

ACKNOWLEDGEMENT:

The authors are grateful to Universiti Malaysia Terengganu, Malaysia for providing grant to support this study under the Talent and Publication Enhancement-Research Grant (55143, 2018-2020).

 

CONFLICT OF INTEREST:

The authors declare no conflict of interest.

 

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Received on 20.07.2020           Modified on 05.10.2020

Accepted on 13.11.2020         © RJPT All right reserved

Research J. Pharm. and Tech. 2021; 14(6):3271-3275.

DOI: 10.52711/0974-360X.2021.00569