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*Corresponding author: E-mail: nwokekyrian@yahoo.com; 
 
 
 

Asian Journal of Immunology 
 
3(1): 23-29, 2020; Article no.AJI.54405 
 

 
 
 

 

Impact of Exercise on Some Haematological and 
Cellular Immune Markers in Male Athletes 

 
K. U. Nwoke1*, F. S. Amah-Tariah1 and A. N. Chuemere1  

 
1
Department of Human Physiology, Faculty of Basic Medical Sciences, College of Health Sciences, 

University of Port-Harcourt, Rivers State, Nigeria. 
 

 Authors’ contributions  
 

This work was carried out in collaboration among all authors. Author KUN designed the study, 
performed the statistical analysis, wrote the protocol and wrote the first draft of the manuscript. Author 

ANC managed the analyses of the study and author FSAT managed the literature searches. All 
authors read and approved the final manuscript. 

 
Article Information 

 
Editor(s): 

(1) Dr. Jaffu Othniel Chilongola, Department of Biochemistry and Molecular Biology, Kilimanjaro Christian Medical University 
College, Tumaini University, Tanzania. 

Reviewers: 
(1) Danish Kadir, University of Rajshahi, Bangladesh. 

(2) Awofadeju Stephen Olajide, Obafemi Awolowo University Teaching Hospitals Complex, Nigeria. 
Complete Peer Review History: http://www.sdiarticle4.com/review-history/54405 

 
 
 
 

Received 22 November 2019  
Accepted 27 January 2020 

Published 03 February 2020 

 
 

ABSTRACT 
 

Due to conflicting reports on the impact of exercise on haematological and immunological indices, 
this study investigated the effects of exercise on some haematological and cellular immune 
markers in male athletes. Blood samples were collected from 86 apparently healthy male athletes 
before and after exercise training using standardized methods. Similarly, blood samples were 
obtained from 100 male non-athletes and served as control. Blood samples collected from athletes 
and non-athletes were subjected to experimental evaluation of some haematological and cellular 
immune biomarkers using standard techniques. Results showed that, with the exception of 
neutrophils that significantly increased after exercise in athletes, lymphocytes, monocytes, 
eosinophils and clusters of differentiation counts significantly (p<0.05) decreased in athletes after 
exercise. Also, with the exception of platelets, other haematological parameters assayed in this 
study significantly (p<0.05) decreased in athletes after exercise.  However, there was no significant 
change in these parameters between athletes at rest and non-athletes. This study concludes that 
heavy training could lead to an open window of immunodepression leading to susceptibility to 
infection in athletes and non-athletes alike.  
 

Original Research Article 



 
 
 
 

Nwoke et al.; AJI, 3(1): 23-29, 2020; Article no.AJI.54405 
 
 

 
24 

 

Keywords: Immuno-physiological; immunodepression; haematological; immune biomarkers. 
 

1. INTRODUCTION 
 

It is widely believed that physical activity 
enhances the cardiovascular system. However; 
new studies have pointed to what seemed like 
adverse effects of prolonged heavy exercise 
upon both resistance to and the course of 
various viral and bacterial diseases [1]. Upper 
respiratory tract infection (URTI) is a major 
ailment that have been reported in athletes 
following participation in marathon or ultra- 
marathon events [2,3]. Examinations show that 
the pathogens normally responsible for URTI 
could not be identified in these athletes, 
suggesting that changes in the immune system 
and not pathogens could be responsible for 
these post exercise traumas [4]. To further 
explain this, some studies targeted at the specific 
immune response to exercise, have reported that 
light regular physical exercises have favourable 
effects on the physiological, psychological and 
immunological functions [5] and therefore could 
increase resistance of the body against infections 
[6]. Conversely, vigorous exercise produces 
negative effects on the aforementioned functions. 
Moderate exercise has been reported to boosts 
immune functions via chemotaxis and 
phagocytosis whereas extreme exercise on the 
other hand reduces these functions, with the 
exception of chemotaxis and degranulation [7]. 
Increased lymphocyte concentration has been 
reported to be likely due to the recruitment of all 
lymphocyte subpopulations (CD41 T cells, CD81 
T cells, CD191 B cells, CD161 natural killer (NK) 
cells, and CD561 NK cells) to the vascular 
compartment [8,9]. Earlier studies have shown 
that NK cells with a high IL-2 response capacity 
were recruited to the blood during bicycle 
exercise [10].  
 

On immunoglobulin, lower concentrations of the 
salivary IgA have been reported in cross-country 
skiers after a race [11]. This finding was 
confirmed by a 70% decrease in salivary IgA that 
persisted for several hours after completion of 
intense, long-duration ergometer cycling [12]. 
Decreased salivary IgA was also found after 
intense swimming [13] and after incremental 
treadmill running to exhaustion [14]. Submaximal 
exercise had no effect on salivary IgA [14]. The 
percentage of B cells among blood mononuclear 
cells (BMNC) does not change in relation to 
exercise; suggesting that the suppression of 
immunoglobulin-secreting cells is not due to 
changes in numbers of B cells. Many of these 
reported studies were on Caucasian non-athletes 

in the temperate environment. Research needs 
to be extended to performing athletes especially 
in the tropical environment. This is therefore 
partly covered in this study.   

 
2. MATERIALS AND METHODS 
 
2.1 Study Population and Sample Size 
 
With ethical approval from the University of Port 
Harcourt Research ethics committee, the 
targeted population for this study was the 112 
registered Nigerian athletes that partook in the 
14th West African University Games (WAUG) 
held at the University of Port Harcourt between 
October and November, 2018. The sampling 
adopted was total population purposive-sampling 
technique, in which case, there is the possibility 
of selection all the elements in the study 
population. The basis for purposive sampling is 
to concentrate on subjects with particular desired 
characteristics that would be able to assist with 
the generation of relevant information to achieve 
the research objectives. Therefore, the 
justification for the adoption of total population 
purposive sampling technique is because it is a 
non-probability sampling technique that could 
include all members, within the population of 
interest. Hence, all the elements in the 
population were given equal opportunity to 
participate in the selection. Based on the 
sampling technique, 86 apparently healthy 
subjects between the ages of 22 and 30 years 
volunteered and were recruited for the study. The 
subjects were drawn from the following sporting 
events: fitness exercises, soccer, long-distance 
running, short-distance running and swimming. 
The athletes have been in the profession for not 
less than two years; and were at the peak of their 
training, in preparation for the West African 
University games (WAUG) held at the University 
of Port Harcourt between October and 
November, 2018. Training sessions were not 
less than 3 days per week for a minimum of 60 
minutes per session as recommended by the 
[15].  In addition, the subjects were encouraged 
to avoid smoking, use of tobacco products or 
anti-inflammatory drugs. Subjects also completed 
a health history, drug usage, and physical activity 
questionnaires to determine eligibility. Also, 100 
volunteer non-athletes were recruited and served 
as the control. Prior to participation in this study, 
each subject was informed of all procedures, 
potential risks, and benefits associated with the 
study and an informed consent form was signed. 



 
 
 
 

Nwoke et al.; AJI, 3(1): 23-29, 2020; Article no.AJI.54405 
 
 

 
25 

 

2.2 Anthropometrics 
 

For the participants that met the selection 
criteria, weight was measured using an electronic 
scale (Hanover, MD) while the subjects were 
wearing shorts with bare feet. Height was 
measured using a Seca stadiometer with 1 cm 
spaced leaned to the wall. Body mass index 
(BMI) for each participant was calculated using 
the formula: weight/height². All measurements 
were taken in the morning from 7 a.m. to 8 a.m.  
 

2.3 Collection of Blood Sample and 
Analysis of Biomarkers 

 

Using standard venipuncture procedures [16], 
About 5 ml of blood was collected from the 
antecubital veins of subjects using sterile 
syringes before exercise; between the hours of 7 
am-8 am and immediately after exercise between 
10-11 am. The blood was dispensed in 
Ethylenediaminetetraacetic Acid (EDTA) and 
stored at -4C pending analysis. 
 

The cells that make up the cellular immune 
system; namely: lymphocytes, neutrophils, 
monocytes and eosinophils were assayed. Also, 
total white blood cell (WBC) count, red blood cell 
(RBC) count, hemoglobin (Hb), packed cell 
volume (PCV), platelets (PLT) were also 
assayed. These parameters were assayed using 
the hematology autoanalyzer (CellDyn 3700 
(Abbott, Chicago, IL, USA), which makes use of 
the Coulter principle [17]. The CD4 count was 
determined manually by microbead separation of 
CD4 T lymphocytes from other blood cells, 
followed by standard manual cell counting 
techniques using a light microscope.  
 

2.4 Statistical Analysis 
 

Data collated on selected variables from the 
study were statistically analyzed using statistical 
package and service solution (SPSS, version 
20.0). The mean of descriptive statistics was 
recorded as mean± standard deviation. 
Comparison of parameters between athletes and 
non-athletes were done using paired t-test with 
the level of statistical significance accepted at 
p<0.05. Multiple comparison between non-
athletes, athletes before exercise and athletes 
after was done using post-hoc multiple 
comparison test (LSD).  

 
3. RESULTS 
 

The result of the study is presented in tables and 
the figure below. Table 1 showed the 

anthropometric measurement of the athletes and 
non-athletes. Table 2 showed the effect of 
exercise on haematological parameters. Table 3 
showed the effect of exercise on cellular 
immuno-physiological marker while Fig. 1 
showed percentage changes in both 
haematological and some immuno-physiological 

parameters of male athletes after exercise. 
 
4. DISCUSSION 
 
Body Mass Index (BMI): The BMI is a 
calculation that compares weight relative to 
height. The index however, is not perfect 
because a body builder’s BMI may indicate 
overweight, but the extra weight is muscle rather 
than fat [18]. For everyone else, however, BMI is 
a reasonable measure of fitness level, 
demonstrating whether one is overweight, 
underweight or just right. The result of this study 
showed that there was no statistically significant 
p<0.05 difference between the BMI of male 
athletes compared with male non-athletes (Table 
1); suggesting that BMI alone cannot be used to 
determine fitness levels in athletes because 
hypertrophied muscle may give perception of 
overweight. This agrees with a study of which 
concluded that the intensity of physical activity 
does not matter in lowering or maintaining BMI 
[19]; therefore, one can appear to be fat and yet 
be fit. 
 
Haematological parameters: Investigators have 
suggested that the value of haematological 
indices in athletes varies as a result of different 
training regimes [20,21]; usually higher at the 
beginning of the competition, then declined in 
well-trained athletes [22]. Therefore, 
haematological indices is key determinants of 
optimal exercise performance in athletes. Result 
of this study showed that with the exception of 
platelets, haemoglobin, PCV, RBC and WBC 
diminished significantly in athletes after exercise; 
as shown in Table 2. This result is consistent 
with a study which reported low values of 
haematological variables in athletes during 
intensive training periods compared with clinical 
norms [23].  However, the study disagrees with 
other investigations that reported normal 
concentrations of hematological indices 
throughout training programmes [20,24]. 
 

The significant decrease in Hb, PCV and RBC 
immediately after heavy exercise might be due to 
training induced haemodilution as a result of 
plasma volume expansion associated with 
aerobic sports, endurance and ultra-endurance 



 
 
 
 

Nwoke et al.; AJI, 3(1): 23-29, 2020; Article no.AJI.54405 
 
 

 
26 

 

events.  Plasma volume expansion is a 
compensatory mechanism to increase cardiac 
output and reduces blood viscosity, thereby 
optimizing microcirculation and improving oxygen 
delivery to the working muscles. 
 

Innate immunological markers: Figure 1 
showed that lymphocyte, monocyte, esinophil 
and CD4 counts significantly p<0.05 decreased 
after exercise. However, there was significant 
p<0.05 increase in neutrophils count. The 
significant decrease in lymphocyte and Cd4 
(cluster of differentiation) cells seen in this study 
is consistent with the studies which reported a 
rapid exercise-induced decrease in lymphocyte 
number within 30 minutes following a prolonged 
or high-intensity exercise [25,26]. However, there 
are contrary reports of lymphocytosis occurring 
during or immediately after exercise; depending 
on the intensity and the duration of the exercise 
[25,27]. The significant decrease in lymphocyte 
count, rather than being a real reduction, may be 
secondary to lymphocyte redeployment to 
peripheral tissues as a result of stress induced 
cortisol release. 
 

Monocytes are mobilized during exercise; they 
are rapidly redeployed to skeletal muscle and 

differentiate into tissue-resident macrophages 
that facilitate repair and regeneration after an 
intensive bouts of exercise that cause significant 
skeletal muscle damage [28]. This redeployment 
of monocytes to muscles may account for the 
significant decrease in monocyte count 
immediately after exercise. 
 

Eosinophils are a type of white blood cells that 
defend against parasites and infectious agents. 
In this study, we observed a significant decrease 
in eosinophil count which is consistent with a 
similar study in the elderly. However, it differs 
with the result of a similar study in asthmatic 
subjects [29]. 
 

The significant increase in neutrophil count seen 
in this study agrees with a report which showed 
that running at 75% of maximum heart rate 
(HRmax.) for 15 min increased neutrophil 
number [30]. Neutrophils recruited into circulation 
during exercise may be responsible for 
controlling the elevated levels of oxidative stress 
in plasma after exercise [31]. This impact of 
exercise on neutrophil count may be mediated by 
the activation of catecholamine and cortisol 
which are known to have adverse effect on the 
immune system [32,33].  

 

Table 1. Anthropometric measurement of athletes and non-athletes 
 

Variables Male athletes (n=86) Male NON-athletes (n=100) Percentage change (%) 
Weight (kg) 72.43±5.76 75.20±6.47 3.68 
Height (m) 1.69±0.05 1.7101±0.06 1.18 
BMI (kg/m

2
) 25.41±1.52 25.69±1.56 1.09 

values are expressed as Mean ± S.D. *=statistically significant at p < 0.05, n= sample size 
 

 
 

Fig. 1. Changes in haematological and some immuno-physiological parameters of male 
athletes after exercise 

* shows that there was a statistically significant change at p≤0.05 



 
 
 
 

Nwoke et al.; AJI, 3(1): 23-29, 2020; Article no.AJI.54405 
 
 

 
27 

 

Table 2. Effect of exercise on haematological parameters 
 

Variables Non-athletes 
( n=100) 

Athletes before 
exercise (n=86) 

Athletes after 
exercise (n=86) 

Change in athletes 
after exercise (%) 

Change between 
athletes after exercise 
and non-athletes(%) 

Change between athletes 
before exercise and non-
athletes(%) 

RBC (x10^12/L) 6.22±0.29 6.19±0.27 5.08±0.40* -21.85 -22.44 -0.48 
PCV (%) 40.59±1.71 41.76±1.68 39.45±1.16 -5.89 -2.89 2.80 
HB(g/dl) 13.91±0.41 13.98±0.46 12.37±0.55* -13.02 -12.45 0.50 
Platelets (x10^7/L) 210.52±11.71 210.06±12.24 253.20±6.20* 17.04 16.85 -0.22 
WBC(x10^9/L) 6.40±0.21 6.39±0.19 4.07±0.38* -57.00 -57.25 -0.16 

All values are expressed as Mean ± S.D. *=statistically significant at p < 0.05, n= sample size 

 
Table 3. Effect of exercise on cellular immuno-physiological markers 

 
Variables  Non-

athletes 
(n=100)  

Athletes before 
exercise(n=86) 

Athletes after 
exercise(n=86) 

Change in athletes 
before and after 
exercise (%) 

Change between athletes 
after exercise and non-
athletes(%) 

Change between athletes 
before exercise and non-
athletes(%) 

NEUT (%) 46.15±4.97 46.20±4.77 60.17±3.45* 23.23 23.30 0.11 
LYMPH (%) 32.69±1.95 32.95±2.14 22.98±1.62* -43.39 -42.25 0.79 
MONO (%) 6.10±1.11 6.08±1.23 4.07±0.27* -49.39 -49.88 -0.33 
EOSINO (%) 2.09±0.85 2.09±0.85 2.07±0.82 -0.97 -0.97 0 
CD4(cells/�L) 704.21±31.96 688.05±54.14* 508.98±38.85* -35.18 -38.36 -2.35 
Results are presented as mean±standard deviation; n= sample size; * shows that there was a statistically significant change at p<0.05 when compared with the non-athletes



 
 
 
 

Nwoke et al.; AJI, 3(1): 23-29, 2020; Article no.AJI.54405 
 
 

 
28 

 

5. CONCLUSION  
 
The available evidence from this study showed 
that exercise decreases hematological indices in 
the vascular compartment and also has 
modulatory effects on immunocyte dynamics. 
These effects may cause a temporary decline in 
the cellular immune system and create an open 
window, during which the exerciser may be 
susceptible to infections.  
 

CONSENT 
 

Prior to participation in this study, each subject 
was informed of all procedures, potential risks, 
and benefits associated with the study through 
both verbal and written form and signed an 
informed consent form. 
 
ETHICAL APPROVAL 
 
With ethical approval from the University of Port 
Harcourt Research ethics committee. 
 

COMPETING INTERESTS 
 
Authors have declared that no competing 
interests exist. 
 

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(http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, 
provided the original work is properly cited. 

 
 

 
 

 

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