Effect of physical activity and haemoglobin levels on cardiorespiration

Cardiac muscles can develop due to the influence of physical activity. A fit person's heart and lungs will supply more blood and oxygen to their body tissues, so they do not need to work too hard compared to people whose heart and lung systems are not fit. Exercise significantly increased absolute and relative cardiorespiration [15]. This is also consistent with the research results of Balagué et al. [5] and Pollock et al. [21] that improving the interpretation of cardiorespiration exercise is highly recommended in health care.

Another critical component that supports health is haemoglobin. In the haemoglobin in the blood, iron is a crucial element [8]. Haemoglobin in the blood binds to Oxygen and acts as a “delivery” mechanism for Oxygen [10, 22]. Lack of blood haemoglobin, blood distribution, or the ability to pump the heart can be increased through exercise [18, 23]. Internal haemoglobin can be greatly affected by physical activity because it will produce much oxygen when there is muscle movement, increasing VO2 Max.

Materials and Methods. This research is a correlational study using a survey method. This research design can be described in Fig. 1.

Fig. 1. Research Design: X1 – physical activity; X2 – haemoglobin level; Y – cardiorespiration

This study's research subjects were students of the Faculty of Sport Sciences, Yogyakarta State University. This study used a random sampling technique, namely, by taking a random sample. The samples taken were 194 students. This study has three variables consisting of 1 dependent variable and 2 independent variables. The dependent variable is cardiorespiration (Y), while the independent variable includes physical activity (X1) and haemoglobin level (X2). Operationally these variables can be defined as follows:

• 1.    Cardiorespiration is the ability of the heart and lung capacity to perform activities measured using a multi-stage test.

• 2.    Physical activity is the activity of sports education students starting from waking up to sleeping again in one day for seven days, as measured by using a questionnaire from the Physical Activity Questionnaire for Older Children (PAQ-C).

• 3.    Haemoglobin level is a measure of the respiratory pigment in red blood cell granules, which function as oxygen carriers, measured using a haemoglobin diaspect haemoglobin T.

Instruments of this study are:

• 1.    Cardiorespiration measurements were performed using a multi-stage test.

• 2.    Physical activity measurements were carried out using the Global Physical Activity Questionnaire (GPAQ).

• 3.    Measurement of haemoglobin levels, measured using a hemometer diaspect Haemoglobin T.

Data processing was performed using the SPSS Statistics 24 program with the following steps:

• 1.    Normality Test with Kolmogorov Smirnov.

• 2.    Linearity test.

• 3.    The hypothesis test is analyzed using a simple linear regression equation. A single correlation test or a simple linear regression equation using the Pearson product-moment correlation. The simple linear regression equation is used to test the first and second hypotheses, while the third hypothesis uses multiple regression.

Results. The included research data is a summary of the reduction data (difference), post-test (after) and pre-test (before). The explanation of the data can be seen in each of the following discussions:

Physical Activity of FIK UNY students. Physical activity data of FIK UNY students with a sample of 194 students had an average of 7.19; a standard deviation of 2.79; a maximum score of 9; a minimum score of 1.

Haemoglobin Levels of FIK UNY Students. Analysis results found that the Haemoglobin Level data of FIK UNY students with a sample of 194 students had an average of 13.33; the standard deviation of 1.34; a maximum score of 16; a minimum score of 1.

Cardiorespiration of FIK UNY Students. Based on the research analysis, it was found that the Cardiorespiration data of FIK UNY students with a sample of 194 students had an average of 35.80; a standard deviation of 6.84; a maximum score of 55.28; a minimum score of 22.06.

Hypothesis Test . The normality test uses the Kolmogorov-Smirnov Test. The calculation results can be seen in Table 1.

The Kolmogorov – Smirnov normality test using SPSS in table 1 is a significant value of Asiymp. Sig (2-tailed) of 0.902, which means that the value is greater than 0.05. It can be concluded that the data are usually distributed; thus, the assumptions or requirements for normality in the regression model have been met.

The linearity test uses deviation from linearity at the level of significance (α) = 0.05. If Sig < α means it is not linear, the rule applies if Sig > α means linear. The calculation of the haemoglobin levels linearity test with cardiorespiration obtained Sig > α (0.935 > 0.05), which means that the haemoglobin level data is linear to the cardiorespiration (Table 2).

The calculation of the linearity test of the haemoglobin level with cardiorespiration obtained Sig > α (0.02 > 0.05) means that the physical activity data is linear to the cardiorespiration (Table 3).

The results of the linearity test of physical activity data with haemoglobin levels Sig > α (0.01 > 0.05) means that the physical activity data is linear to the haemoglobin levels (Table 4).

Based on the output of the Regression Test, it is known that the significance value (Sig.) of 0.001 <0.05 probability, so it can be concluded that H0 is rejected and Ha is accepted, which means that there is an effect of physical activity (X2) on cardiorespiration (Y).

Based on Table 5, it is known that the significance value (Sig.) of 0.01 < 0.05 probability, so it can be concluded that H0 is rejected and Ha is accepted, which means that there is an effect of haemoglobin (X1) on cardiorespiration (Y). Physical activity can be walking, running, jumping, or others [16]. Walking in place or jumping jacks is a physical activity that, when done regularly, can increase heart rate and cardiorespiration endurance (after warming up but

Table 1

Normality test results

		Unstandardized residual
N		194
Normal parametersa	Mean	0
	Std. Deviation	3.716994
Most extreme differences	Absolute	0.041
	Positive	0.039
	Negative	–0.041
Kolmogorov – Smirnov Z		0.569
Asymp. Sig. (2-tailed)		0.902
a. Test distribution is normal

Table 2

Linearity test of haemoglobin levels by cardiorespiration

			Sum of squares	df	Mean square	F	Sig.
HB * Cardiorespiration	Between groups	(Combined)	155.444	74	2.101	1.32	0.089
		Linearity	71.768	1	71.768	45.081	0.005
	Within groups	Deviation from linearity	83.677	73	1.146	0.72	0.935
			189.442	119	1.592
	Total		344.887	193

Table 3

Linearity test of haemoglobin levels by cardiorespiration

			Sum of squares	df	Mean square	F	Sig.
Physical activity * Cardiorespiration	Between groups	(Combined)	1390.052	74	18.784	20.718	0,01
		Linearity	939.25	1	939.25	1.036	0.073
		Deviation from linearity	450.802	73	6.175	6.811	0.02
	Within groups		107.892	119	0.907
	Total		1497.943	193

Table 4

Linearity test of physical activity data with haemoglobin levels

Table 5

Effect of physical activity on cardiorespiration

Model		Unstandardized coefficients		Standardized coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	21.827	0.834		26.183	0.01
	Physicaly activity	1.943	0.108	0.792	17.966	0.001
a. Dependent variable: cardiorespiration

Table 6

Effect of Haemoglobin Levels on Cardiorespiration

Model		Unstandardized coefficients		Standardized coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	4.705	4.399		1.069	0.286
	HB	2.333	0.328	0.456	7.103	0.01
a. Dependent variable: cardiorespiration

Table 7

Effect of Physical Activity and Haemoglobin Levels on Cardiorespiration

Model		Unstandardized coefficients		Standardized coefficients	t	Sig.
		B	Std. error	Beta
1	(Constant)	3.519	2.696		1.305	0.193
	Physical activity	1.778	0.099	0.725	17.903	0.01
	HB	1.462	0.207	0.286	7.065	0.01
a. Dependent variable: cardiorespiration

Table 8

Model Summary

Model	R	R Square	Adjusted R Square	Std. error of the estimate
1	.839a	0.704	.701	3.73640
a. Predictors: (constant), HB, physic activity
b. Dependent variable: cardiorespiration

To determine the magnitude of the effect of physical activity (X1) and cardiorespiration haemoglobin (X2) levels in a simple linear regression analysis (Table 7), we can refer to R Square or R2's value in the SPSS output in the Model Summary section (Table 8). Physically active individuals, especially women, have iron requirements that are greater than the average. Strenuous exercise requires a higher than the recommended intake of iron because small amounts of iron are lost through sweat, urine, and stool. A small impact can also cause mechanical trauma during jogging, damaging red blood cells [28]. Physical activity affects cardiovascular function, including 1) increasing blood flow to active skeletal muscle, 2) increasing blood flow to the myocardium, 3) increasing the dissociation of oxyhaemoglobin, 4) sweating, which plays a role in temperature regulation, and 5) reducing occurrence of abnormal rhythm in the conduction system of the heart (dysrhythmias), which can cause abnormal heart function [20]. Oxygen is used to change food substrates, converting carbohydrates and fats through aerobic metabolism into adenosine triphosphate (ATP). These compounds provide energy for physical activity, bodily functions, and the maintenance of constant internal balance. During physical activity, it takes more ATP to perform activities. As a result, the lungs and heart send more oxygen to all muscle cells to supply the body's energy. During physical activity, a person with high cardiorespiration resistance can deliver the required oxygen to the tissues with relative ease. The cardiorespiration system is the heart, lungs, and blood vessels' ability to be used during the body's metabolic processes both at rest and during activity. Good cardiorespiration fitness causes an increase in the ability to work at high intensity for a long time to achieve fatigue [11, 13].

These results indicate that the R Square value is 0.839, which means that 83.9% of the influence of haemoglobin (X1) and physical activity (X1) on cardiorespiration (Y).

Conclusions. From the findings, it can be concluded that cardiorespiration activity is influenced by physical activity and haemoglobin levels by 83%.