Haematological and CD4 Parameters of Young Sportspersons (Pre- and Post-Exercise) in Ambrose Alli University (AAU), Ekpoma, Nigeria

Introduction

Sport is a physical activity carried out at any intensity for recreation, competition, or fitness [1]. Physical activity is defined as any bodily movement produced by skeletal muscles that results in energy expenditure [1]. In 1995, the US National Institute of Health (NIH) Concensus inserted “health benefits” into the definition of physical activity [2]. In 2018, the World Health Organization’s (WHO) Global Strategy on Physical Activity deployed a slight variation of Caspersen’s definition. Instead of activity resulting in energy expenditure, the WHO referred to bodily movement that requires energy expenditure [3]. The term exercise has been used interchangeably with “physical activity” [4] and in fact have several common elements.

Haematological parameters are those parameters that are related to the blood and blood forming organs [5]. Haematological components which consist of red blood cells, white blood cells, platelet and certain ratios of these values are valuable is monitoring the health status of an individual [6]. Red blood cells (erythrocytes) serve as a carrier of oxygen. It is this haemoglobin that reacts with oxygen carried in the blood to form oxyhaemoglobin during respiration. Packed cell volume, haemoglobin and mean corpuscular haemoglobin are major indices for evaluating circulating erythrocytes and are significant in the diagnosis of anaemia and serve as useful indices of the bone marrow capacity to produce red blood cells [7]. Blood platelets are implicated in blood clotting [8]. The major functions of the white blood cells and its differentials are to fight infections, defend the body by phagocytosis against invasion by foreign organisms and to produce or at least transport and distribute antibodies in immune response [9]. On the other hand, CD4 (Cluster of Differentiation 4) is a glycoprotein found on the surface of immune cells such as T helper cells, monocytes, macrophages, and dendritic cells. CD4+ T helper lymphocytes play a central role in the regulation of immune response [10]. They have the capacity to help B cells for generating antibodies to recruit and activate macrophages, to recruit neutrophils, eosinophils, and basophils to sites of infection and inflammation [11].

Regular physical activity can affect the haematological parameters. Thus, the haematological parameters can change, depending on the type, intensity, and duration of the sport [12]. Furthermore, the haematological profile values can change during and after vigorous sport, which can vary according to gender, age, environment, or nutrition [13]. Some researchers have found that haematological parameters increase after regular sports [14,15]. Whereas some researchers have indicated that there is no change [16]. Therefore, because of these conflicting reports, this present study was aimed at assessing the haematological and CD4 parameters of young sportspersons (pre-and post-exercise) in Ambrose Alli University, Ekpoma, Nigeria.

Materials and Methods

Study Area

This study was carried out in Ekpoma. Ekpoma is the capital of Esan West Local Government Area in Edo State which falls within the rain forest/savannah transitional zone of Southwestern Nigeria. The area lies between latitudes 6°431 and 6°451 North of the Equator and longitudes 6°51 and 6°81 East of the Greenwich Meridian. Ekpoma has a land area of 923 square kilometers with a population of 170,123 people as at the 2006 census [17]. The town has on official post office, and it is home of Ambrose Alli University

Study Population

A total of fifty (50) young healthy sportpersons between 16 to 28 years of age and of both sexes were recruited for this study.

Ethical Approval

Ethical approval was obtained from the Health Research Ethics Committee (NHREC Registration Number: NHREC 12/06/2013) of Ambrose Alli University, Ekpoma. Informed consent was sought from each participant before sample collection.

Inclusion Criteria

Apparently healthy and fit male and female students of Ambrose Alli University who engaged in active sports such as football, table tennis, jogging and gymnastics at the university sports complex that gave their consent were included in this study.

Exclusion Criteria

Sportsmen and sports women who reported sick, stressed and those who did not give their consent among others were excluded from this study.

Sample Collection

About 4ml of blood was collected from each subject via venepuncture before the commencement of exercise (pre-exercise) and dispensed in Ethylene Diamine Tetra Acetic Acid (E.D.T.A) bottle and mixed immediately by reverse uniform inversion. Another round of 4ml of blood sample was collected into E.D.T.A bottle also from each subject after one hour of physical exercise (postexercise). All the field samples were placed in cold transport boxes with a temperature range of 2°C 8°C before they were transported to the laboratory for analysis. All samples were collected between 9.00am-12.00 noon each day. Samples were analysed with minimal delay and not longer than 6 hours.

Sample Analyses

Haematology Assay using Sysmex KX-21N autoanalyzer: The haematology parameters were analyzed using Sysmex KX-21N Haematology autoanalyzer (Sysmex Corporation, Kobe, Japan). The Sysmex KX-21N is an automatic, 19-parameters, 3-part differential blood cell counter. The procedure was carried out according to the manufacturer’s instructions. The principle of this method is based on then DC (Direct Current) Detection method.

CD4 Count: CD4 cells counts were determined by flow cytometry using Partec cyflow counter (Partec GmbH, 2006) adapted to single platform technology. Forward and side scatter signals were measured using a linear scale. To ensure the optical alignment of the equipment and fluorescence compensation settings, count check bead green was run every day and the count was compared with the manufacturer’s range.

Statistical Analysis

The results obtained were presented as mean±standard deviation. Statistical analysis was carried out using Student’s t-test and one way analysis of variance (ANOVA). P<0.05 was considered significant.

Results

The results of the socio-demographic characteristics of the subjects studied are presented in Table 1. Distribution according to sex revealed that more male subjects (52%) were recruited for the study compared to female subjects (42%). In terms of age, subjects belonging to the age bracket of 20-23 were the most predominant (42%), followed by 16-19 years (30%) and the least being those in the age range of 24-28 years (28%). The subjects were drawn from different faculties which included Basic Medical Sciences (30%), Education (20%), Physical Sciences (20%), Management Sciences (12%) and Social Sciences (18%). The levels of study revealed that the 100, 200, 300, 400 and 500 students constituted the frequencies of 24%, 16%, 16%, 24% and 20% respectively. Most of the study subjects were Christians (88%) while the Muslims accounted for 12%. Based on the types of sports, Football constituted almost half (42%) of the study subjects, followed by Gymnastics (22%) while Table Tennis and Jogging recorded 18% each. In terms of social habits, 24% of the subjected consumed alcohol while 6% took medications and 4% smoked cigarette. None of the subjects took adrenaline injection and hard drugs. Table 2 reveals the haematological and CD4 parameters (pre- and post-exercise) of the study subjects. The HGB and HCT results of post-exercise subjects were statistically significantly reduced (P<0.05) in comparison to pre-exercise subjects. Whereas there was a statistically significant increase in the PLT of post-exercise subjects in relation to preexercise subjects. On the other hand, there was no significant difference (P>0.05) in the mean values of the WBC, MCV, MCH, MCHC, RBC, NEUT, LYM, MXD, RDW-CV, PDW, MPV P-LCR and CD4 of both pre- and post-exercise subjects in the study area.

Table 1. Socio-demographic characteristics of the subjects studied.

Table 2. Haematological and CD4 parameters of the subjects studied (pre- and post-exercise).

The haematological and CD4 parameters of sportspersons (pre- and post-exercise) with respect to sex is shown in Table 3. The results of the HGB, HCT, PLT and RDW-CV of the male subjects revealed a statistically significant difference (P<0.05) compared to female subjects. In contrast, there was no significant difference (P>0.05) in the mean values of the WBC, MCV, MCH, MCHC, RBC, NEUT, LYM, MXD, PLT, RDW-SD, PDW, MPV, P-LCR and CD4 results of the male subjects in relation to female subjects. Table 4 shows the haematological and CD4 parameters of the subjects studied according to age. There was not statistically significant (P>0.05) difference in the haematological and CD4 parameters of the subjects studied across the different age groups. Table 5 depicts the haematological and CD4 parameters of the subjects based on types of sports. The results of the statistical analysis showed there was no significant difference (P>0.05) in the haematological and CD4 parameters of the subjects with respect to the type of sports they engaged in.

Table 3.Haematological and CD4 parameters of the subjects studied with respect to sex.

Note*: KEYS: SD: Standard Deviation; WBC: White Blood Cells; RBC: Red Blood Cells; MCV: Mean Cell Volume; MCHC: Mean Cell Haemoglobin Concentration; PLT: Platelet count; P-LCR: Platelet Large Cell Ratio; HGB: Haemoglobin; HCT: Haematocrit; MCH: Mean Cell Haemoglobin; RDW: Red Cell Distribution Width; MPV: Mean Platelet Volume; PDW: Platelet Distribution Width; NEUT: Neutrophils; LYM: Lymphocytes; fl: Femtolitre; Pg: Picogram; %: Percentage; μl: Microlitre; RDW-CV: Red cell Distribution Width-Coefficient of Variation; RDW-SD: Red cell Distribution Width-Standard Deviation.

Table 4.Haematological and CD4 parameters of the subjects based on age.

ote*: Values in a row with the same superscript are significantly different at p<0.05

KEYS: SD: Standard Deviation; WBC: White Blood Cells; RBC: Red Blood Cells; MCV: Mean Cell Volume; MCHC: Mean Cell Haemoglobin Concentration; PLT: Platelet count; P-LCR: Platelet Large Cell Ratio; HGB: Haemoglobin; HCT: Haematocrit; MCH: Mean Cell Haemoglobin; RDW: Red cells Distribution Width; MPV: Mean platelet volume; PDW: Platelet distribution width; NEUT: Neutrophils; LYM: Lymphocyte; fl: Femtolitre; Pg: Picogram; %: Percentage; μl: Microlitre; RDW-CV: Red cell Distribution Width-Coefficient of Variation; RDW-SD: Red cell Distribution Width-Standard Deviation.

Table 5.Haematological and CD4 parameters of subjects based on the types of sports.

Note*: Values in a row with the same superscript are significantly different at p<0.05 KEYS: SD: Standard Deviation; WBC: White Blood Cells; RBC: Red Blood Cells; MCV: Mean Cell Volume; MCHC: Mean Cell Haemoglobin Concentration; PLT: Platelet count; P-LCR: Platelet Large Cell Ratio; HGB: Haemoglobin; HCT: Haematocrit; MCH: Mean Cell Haemoglobin; RDW: Red cells Distribution Width; MPV: Mean Platelet Volume; PDW: Platelet Distribution Width; NEUT: Neutrophils; LYM: Lymphocytes; fl: Femtolitre; Pg: Picogram;%: Percentage; μl: Microlitre; RDW-CV: Red cell Distribution Width-Coefficient of Variation; RDW-SD: Red cell Distribution Width-Standard Deviation.

Discussion

In the present study, the results of the mean values of the White Blood Cells Total Count (WBC), Red Blood Cells Count (RBC), Mean Cell Volume (MCV), Mean Cell Haemoglobin (MCH), Mean Cell Haemoglobin Concentration (MCHC), Lymphocytes Count (LYM), Middle Cells Count (MXD), Neutrophils Count (NEUT), Red Cells Distribution Width-Standard Deviation (RDW-SD), Red Cells Distribution Width-Coefficient Of Variation (RDW-CV), Platelet Distribution Width (PDW), Mean Platelet Volume (MPV) and platelet- large cell ratio (P-LCR) of pre-exercise and post-exercise subjects were statistically insignificant (P>0.05) in the study area. Whereas the results of the Haemoglobin Estimation (HGB) and Haematocrit (HCT) of post-exercise subjects were significantly decreased (P<0.05) compared to pre-exercise subjects. Our finding is line with the earlier reports of Schumacher, et al. [18] who found reduced HGB, HCT and RBC levels in END (Endurance) compared with POW (strength) and MIX (mixed-trained) categories of distinctive sporting. In another study, Ceylan, et al. [19] observed significant differences in the pre- and post-intervention scores for red blood cells and haematocrit in the step dance group after an exercise session of 3 times a week for 3 months. Ceylan, et al. [19] further observed that when they compared the levels of significantly decreasing haemoglobin (HGB), they found that the aerobic dance group was better than the step dance group. Elsewhere, Cicek [20] established that after the exercise program, some meaningful decreases were observed in the values of RBC, HGB, HCT and MCV of the strength exercise group compared to aerobic exercise. Londeann [21] reasoned that the decrease in HGB and HCT levels may have occurred in athletes that intensely exercise, a condition called “athlete’s anaemia”. Furthermore, Schumacher, et al. [18] attributed this to exercise-induced plasma volume expansion, and only to a less degree and in selected athlete populations, to haemolysis and suggested that the “traumatic” movement of running might trigger the destruction of red blood cells. However, other authors have reported a non-significant difference in the mean values of HGB and HCT. For example, after studying the RBC levels of 9 sedentary and 9 athletes before and after a two-week exercise program, Umit, et al. [22] did not find any significant change in the RBC values. In addition, Mashiko, et al. (2004) indicated that a 20- day exercise program did not significantly change the HCT values of the 25 athlete subjects they studied. Similarly, Pouramir, et al. [23] after studying the blood samples of 35 male gymnasts before and after a 10-week exercise program did not find a significant change in erythrocyte levels. Furthermore, also after evaluating the blood samples of 14 male and 23 female athletes, who were doing regular exercise for a period of 12 weeks, Yeh, et al. [24] did not find any significant change in RBC levels of their subjects. In a similar fashion, Ibis, et al. [25] also noticed no significant differences in the haematological values of the aerobic exercise subjects they studied. In like manner, Cengiz and Cinar [12] found that though there were positive changes in the haematological values of sedentary females after 8 weeks of core exercise program, these changes were not significant for HGB and HCT. The reason for this lack of significant change can be related to the intensity of the exercise embarked on by the subjects studied [12]. In contrast, Bezci and Kaya [12] reported that the haematological parameters of elite women Taekwondoers before and after training were significantly increased in HGB, HCT and RBC. Sazvar, et al. [26] also found that during an 8-aerobic morning exercise, the number of red blood cells, haemoglobin levels and haematocrit percentage increased in the subjects they studied. Similarly, Ceylan, et al. [19] also reported that the HCT level increased significantly more in the step dance group in comparison to aerobic dance group. Having conducted an 8-week long aerobic exercise program among adults (aged 18-29, normal diet and diet with supplements), Gallagher, et al. [27] found a significant increase in the levels of HGB of both groups.

Noushad, et al. [28] also established that immediately after the termination of the 30 minutes of jogging on treadmill exercise, the haemoglobin, haematocrit and erythrocyte levels of their subjects increased significantly when compared with pre-exercise values. According to Wardyn, et al. [29], exercise has been shown to increase haemoglobin and haematocrit numbers in young individuals and these haematological changes suggest that exercise possibly has physiologic impact by mobilizing stem cells thereby enhancing mechanisms that promote tissue repair. In this study, the PLT of post-exercise subjects was significantly increased (P<0.05) compared to pre-exercise subjects. Our result is supported by the findings of Bezci and Kaya [12] who observed a significant increase in the platelet count of sportswomen before and after training. Similarly, our observation conforms with the earlier findings of Ceylan, et al. [19] who reported that step dance caused more increment than aerobic dance in terms of platelet (PLT) level. As prior mentioned, exercise has been shown to increase haemoglobin, platelets and haematocrit numbers in young individuals and these haematological changes suggest that exercise possibly has physiologic impact by mobilizing stem cells thereby enhancing mechanisms that promote tissue repair [29]. In contrast, Sazvar, et al. [27] had found that during an 8-week aerobic morning exercise, the number of platelets decreased significantly. The effect of exercise on CD4 count is still under debate [30]. The findings of the present study demonstrated a decrease in the CD4 count of postexercise subjects, but this decrease was not statistically significant (P>0.05) compared to the pre-exercise group of the sportspersons studied. This is in concordance with the observations by O’Brien, et al. [31] who found no significant association in the subjects they studied. Similarly, in a meta-analysis that included most of the trials, Jones, et al. [32] reported no significant difference in change of CD4 for patients in the exercise intervention group compared with the non-exercising control group. In contrast, Yar’Zever, et al. [33] reported a significant improvement in CD4 cell counts of the experimental group they studied compared to the control group. Also, Poton, et al. [34] using a recent meta-analysis examined the effects of resistance training in HIV-infected individuals and reported a potential moderate effect of such intervention on CD4 count. Based on subgroup analysis, Silva, et al. [35] reported that only aerobic exercise proved to have a significant effect on CD4. They also observed that when exercise intensities were stratified, only intense training proved to have a significant effect on CD4. According to Pedersen and Pedersen [36] and Pedersen and Nieman [37], the increased lymphocyte concentration may be due to the recruitment of all lymphocyte subpopulations to the blood. Thus, the CD4 T cells, CD8 T cells, CD19 B cells, CD16 natural killer (NK) cells, and CD56 NK cells increase in number during intense exercise lasting at least one hour.

With respect to sex, the mean values of WBC, RBC, MCV, MCH, MCHC, LYM, MXD, NEUT, RDW-SD, PDW, and MPV were statistically insignificant (P>0.05) in both sexes. Whereas the mean values of HGB, HCT and RDW-CV of the male subjects were statistically increased (P<0.05) compared to female subjects. Our findings are in accord with the recent reports of Pradas, et al. [38] who found that after stimulated padel competition, significant gender differences were recorded in haematological responses involving HGB, HCT and RBC with men obtaining higher values (P<0.05) than women. Similarly, other authors have reported these differences. For example, in another study, Prada’s, et al. [39] had earlier reported significant gender difference with respect to HCT, HGB and RBC in professional padel players. The same differences have also been observed in swimmers [40] and in other sports [41-43]. Some authors have cited hormonal differences and differences in muscle mass and physical condition between genders to be responsible for this [41,43,44]. In contrast, the mean values of PLT were statistically significantly increased (P<0.05) in the female subjects compared to male subjects. Our finding is like the observations of Bezci and Kaya [12] who found a significantly increased (P<0.01) PLT count in sports women before and after training. Stevens and Alexander [45] reported that there may be a sex difference; thus, in women the platelet count has been reported to about 20% higher than in men.

Also, with respect to sex, the female subjects had a higher but not significant (P>0.05) CD4 count in comparison to their male counterparts. Our finding is in consonance with the earlier reports of Oladepo, et al. [46] and Miri-Dashe, et al. [47] who in their separate studies reported that female subjects recorded higher CD4 counts than male subjects. Somewhere else, other authors such as Tugume, et al. [48], Prins, et al. [49] and Njoku, et al. [50] have also reported similar findings. According to Prins, et al. [49], a sex hormone effect is one of the possible explanations for the reported difference in CD4 counts between genders.In terms of age, there was no statistically significant difference (P>0.05) in the haematological and CD4 parameters of the sportpersons studied in the study area. In terms of the haematolgical parameters of the sports- persons, our result is supported by Helman and Rubenstein [51] and Kelly and Munan [52] who have reported that the Haemoglobin content (HGB) and Red-Cell Count (RBC) normally rise gradually to almost adult levels by the time of puberty; thereafter the levels in women tend to be significantly lower than those of men. Alan and Alexander [53] and Cruickshank [54] have also reported that sex differences are insignificant in the total leucocyte count until after the age of fifty when the count becomes less in women than in women. In terms of platelets, Lewis [55] reported that within the wide normal range, there were no obvious age differences. With respect to CD4 count and age, our result is tandem with observations of Adoga, et al. [56] who reported the CD4 count did not correlate directly with age. This also agrees with the earlier studies in China and India that found no significant association between CD4 values and age [57-59]. Yan, et al. [60] also observed that there were no significant changes in the percentage of CD4+ cells according to age. In contrast, Ray, et al. [61] observed that changes in age influenced the subset values marginally in both sexes and stated that with advancement of age, the CD4 mean counts decreased consistently in males while an increase was seen in females with advancing age. Our finding was contradicted by Tomschi, et al. [62] who observed that when they separated the subjects they studied by age, the RBC deformability increased with age in male but not in female athletes. They also observed that MCV and HCT increased with increasing age.

The results of this study also showed that there was no significant difference (P>0.05) in the haematological and CD4 parameters of the subjects studied in relation to the type of sports they engaged in. Nevertheless, our findings were dissimilar to the earlier reports of Schumacher, et al. [22] who used three distinctive sporting categories of endurance strength and mixed-training exercises to observe reduction in the HGB, HCT and RBC levels in subjects in the endurance category compared with strength and mixed-training exercises. Similarly, Ceylan, et al. [19] have reported that the HGB was significantly decreased in aerobic dance group compared with the step dance group and they reasoned that this reduction may be associated with malnutrition rather than exercise. Furthermore, Cicek [20] observed a meaningful decrease in the values of RBC, HGB, HCT and MCV of the strength exercise group compared to aerobic exercise. In addition, Silva, et al. [35] noted that when exercise intensities were stratified, only intense training proved to have a significant effect on CD4 count. The different study groups recruited by these authors could be a possible explanation for the statistically significant results observed by them. The reason for the non-significant results we found in our study is not clear, but this may be attributed to the nature of subjects we recruited. For instance, while we recruited subjects involved mostly in aerobic exercises, other authors recruited subjects that were involved in different kinds of training exercises. In conclusion, there was a significant difference (P<0.05) in the mean values of HGB, HCT and PLT of post-exercise subjects compared to pre-exercise subjects. Furthermore, with respect to sex, the HGB and HCT of the female subjects were significantly reduced compared to male subjects. On the other hand, the PLT and RDW-CV of the female subjects were significantly increased compared to their male counterparts. Age and categories of sport did not affect the haematological and CD4 parameters of the subjects studied.

References

• Caspersen CJ, Powell KE, Christenson GM (1985) Physical activity, exercise and physical fitness: definitions and distinctions for health – related research. Public Health Rep 100(2): 126-131.
• (1995) National Institutes of Health (NIH) Physical activity and cardiovascular health. NIH consensus statement online, 18-20.
• (2018) World Health Organisation (WHO) More active people for a healthier world, Global action plan on physical activity 2018–2030: more active people for a healthier world.
• Taylor HL (1983) Physical activity: is it still a risk factor? Prev Med 12(1): 20-24.
• Patel KV, Ferruci L, Ershler WB, Longo DL, Guralnik JM, et al. (2009) Red Cell Distribution Width and the Risk of Death in Middle-aged and Older Adults. Arch Intern Med 169(5): 515-523.
• Hammarsten O, Jacobsson S, Fu M (2010) Red cell distribution width in chronic heart failure: a new independent marker for prognosis? Eur J Heart Fail 21(12): 213-214.
• Cetin M, Kocaman SA, Bostan M, Canga A, Cicek V, et al. (2012) Red Blood Cell Distribution Width (RDW) and its Association with Coronary Atherosclerotic Burden in Patients with Stable Angina Pectoris. Eur J Gen Med 9(1): 7-13.
• Chu SG, Becker RC, Berger PB, Bhatt DL, Eikelboom JW, et al. (2018) Mean platelet volume as a predictor of cardiovascular risk: a systematic review and meta-analysis. J Thromb Homeost 8(1): 148-156.
• Nubila T, Ukaejiofo EO, Nubila NI, Shu EN, Okwuosa CN, et al. (2014) Haematological profile of apparently healthy blood donors at a tertiary hospital in Enugu, South-East Nigeria: A pilot study. N J Exp Cli Bio 2(1): 33-36.
• Zhu J, Paul WE (2008) CD4 T cells: fates, functions, and faults. Blood 112 (5): 1557-1569.
• Mossman TR, Coffman RC (1989) Th1 and Th2 cells: different patterns of lymphokine secretion lead to different functional properties. Annu Rev Immunol 7: 145-173.
• Bezci S, Kaya Y (2010) The Analyze of Hematological Parameters of Elite Women Taekwondoers before and after Training. Pamukkale J Sport Sci 1(2): 1-16.
• Cengiz SS, Cinar V (2014) The effect of 8-week core exercises on some haematological parameters in sedentary females. TJ Sci Res 1(1): 1-5.
• Koushi MH, Mollanovruzib A, Rashidlamirc A (2013) The effect of wrestling exercise in morning and afternoon on some haematological indices. Int J Appl Exer Phy 2(1): 11-17.
• Duzova H, Karakoc Y, Gullu E, Gullu A, Koksal B, et al. (2016) The acute effects of single football match on whole blood viscocity and haematological variables in female soccer players. Bio Res 27(4): 1423-1426.
• Spiropoulos K, Trakada G (2003) Haematological and biochemical laboratory parameters before and after a marathon race. Lung 181(2): 89-95.
• (2007) World Gazzetteer Nigeria. Largest cities and towns statistics population.
• Ceylan HI, Irez GG, Saygin O (2014) Examining the effects of aerobic dance and step dance exercise on some haematological parameters and blood lipids. Int JH Sci 11(2): 980-991.
• Cicek G (2018) The effects of different exercise types on haematological parameters in sedentary women. J Edu T Stu 6(8): 96-101.
• Londeann R (1978) Low haematocrits during basic training athlete’s anaemia? N Engl J Med 299: 1191-1192.
• Schumacher YO, Schmid A, Grathowh D, Bultermann D, Berg A, et al. (2002) Haematological indices and iron status in athletes of various sports and performances. Med Sci Sports Exerc 34(5): 869-875.
• Umit KS, Yalcin O, Gunduz F, Kuru O, Herbert JM, et al. (2005) Effect of antioxidant vitamin treatment on the time course of haematological and haemorheological alterations after an exhaustive exercise episode in human subjects. J Appl Physiol 98(4): 1272-1279.
• Pouramir M, Haghshenas O, Sorkhi H (2014) Effects of Gymnastic Exercise on the Body Iron Status and Haematological Profile. Iranian Journal of Medical Sciences 29(3): 140-141.
• Yeh SH, Chuang H, Lin LE, Hsiao CY, Eng HL, et al. (2006) Regular tai chi chuan exercise enhances functional mobility and CD₄CD₂₅ regulatory T cells. Br J Sports Med 40(3): 239-243.
• Ibis S, Hazar S, Gokdemir K (2010) Effect of exercise on haematolgical parameters. Sports 7(1): 71-81.
• Sazvar A, Mohammadi M, Nazeem F, Farahpour N (2013) The Effect of Morning Aerobic Exercise on Some Haematological Parameters in Young Active Males. Iranian Journal of Health & Physical Activity 4(1): 23-28.
• Gallagher PM, Carrithers JA, Godard MP, Schulze KE, Trappe SW, et al. (2010) Effects of exercise on haematological parameters, hepatic and renal functions. Med Sci in Sports Exercise 32(12): 2116-2119.
• Noushad S, Ahmed S, Jafri H, Sherwani SK (2012) Effects of exercise on haematological parameters: a study on trained versus un-trained male subjects. Pakistani J Life Social Sci 10(1): 18-21.
• Wardyn GG, Rennard SI, Brusnahan SK, McGuire TR, Carlson MI, et al. (2008) Effects of exercise on haematological parameters, circulating side population cells, and cytokines. Exp Hematol 36(2): 216-223.
• Dianatinasab M, Fararouei M, Padehban V, Dianatinasab A, Alimohamadi Y, et al. (2018) The effect of a 12-week exercise program on CD₄ count and mental health among HIV infected women: A randomized control trial. J Exerc Sci Fit 16(1): 21-25.
• O Brien K, Nixon S, Tynan AM, Glazier RH (2004) Effectiveness of aerobic exercises in adults: systematic review. Medical Science & Sports Exercise 36(4): 1659-1666.
• Jones SP, Doran DA, Leatt PB, Maher B, Pirmohamed M, et al. (2001) Short-term exercise training improves body composition and hyperlipidaemia in HIV-positive individuals with lipodystrophy. AIDS 15(15): 2049-2051.
• Yar Zever I, Abubakar U, Toriola A, Igbokwe NU (2013) Effects of 12 weeks cycle exercise program on CD4 counts of adults in Kano, Nigeria. Journal of HIV/AIDS Research 5: 415-421.
• Poton R, Polito M, Firanatti P (2017) Effects of resistance training in HIV-infected patients: A meta-analysis of randomized controlled trials. J Sports Sci 35(24): 2380–2389.
• Silva BF, D Oliveira GH, Simoes CF, Vissoci JRN, Peres SB, et al. (2021) Effects of exercise modality and intensity on the CD₄ count in people with HIV: a systematic review and meta-analysis. AIDS Care, 34(2): 163-172.
• Pedersen BK, Pedersen BK (1997) Exercise Immunology. Austin, TX: RG Landes Bioscience. Pg 1-206.
• Pedersen BK, Nieman DC (1998) Exercise immunology: integration and regulation. Immunol Today 19(5): 204-206.
• Pradas F, Garcia GA, Toro RV, Ochiana N, Castellar C, et al. (2021) Gender Differences in Neuromuscular, Haematological and Urinary Responses during Padel Matches. Int J Environ Res Public Health 18(11): 5864.
• Pradas F, Garcia GA, Toro RV, Sanchez A BJ, Ochiana N, et al. (2020) Effect of a Padel Match on Biochemical and Haematological Parameters in Professional Players with Pegard to Gender- Related Differences. Sustainability, 12(20): 8633.
• Cai G, Qui J, Chen S, Pan Q, Shen X, et al. (2019) Haematological, Hormonal and Fitness Indices in Young Swimmers: Gender – Related Comparisons. Journal of Human Kinetics 70: 69-80.
• Telford R, Cunningham R (1991) Sex, sport, and body-size dependency of haematology in highly trained athletes. Med Sci Sport Exerc 23(7): 788-794.
• Malczewska-Leuczowska J, Sitkowski D, Orysiak J, Pokrywka A, Szygula Z, et al. (2013) Total haemoglobin mass, blood volume and morphological indices among athletes from different sport disciplines. Arch Med Sci 9(5): 780-787.
• Bachman E, Travison TG, Basaria S, Davda MN, Guo W, et al. (2014) Testosterone induces erythrocytosis and suppressed hepcidin: evidence for a new erythropoietin/ haemoglobin set point. J Gerontol A Biol Sci Med Sci 69(6) 725-735.
• Pluncevic Gligoroska J, Gontarev S, Manchevska S, Efremovska L, Shukova Stojimanovska D, et al. (2020) Red blood cell variables and correlations with body mass components in boys aged 10-17 years. Turk J Paediatr 62(1): 53-60.
• Stevens R, Alexander MK (1977) A sex difference in the platelet count. Br J Haematol 37(2): 295-300.
• Oladepo DK, Idigbe EO, Audu R, Inyang US, Imade GE, et al. (2009) Establishment of reference values of CD4 and CD8 lymphocyte subsets in healthy Nigerian adults. Clin Vaccine Immunol 16(9): 1374-1377.
• Miri-Dashe T, Osawe S, Tokdung M, Daniel N, Choji RP, et al. (2014) Comprehensive reference ranges for haematology and clinical chemistry laboratory parameters derived from normal Nigerian adults. PLoS One 9(5): e93919.
• Tugume SB, Piwowar EM, Lutalo T, Mugyenyi PN, Grant RM, et al. (1995) Haematological reference ranges among healthy Ugandans. Clinl Diagn Lab Immunol 2(2): 233-235.
• Prins MJ, Robertson RP, Brettle IH, Aguado B, Broers F, et al. (1999) Do gender differences in CD₄ counts matter? AIDS 13(2): 2361-2364.
• Njoku MO, Sirisena ND, Idoko JA, Jelpe D (2003) CD₄ T-lymphocyte counts in patients with human immunodeficiency virus type 1 (HIV-1) and healthy population in Jos, Nigeria. Niger Postgrad Med J 10(3): 135-139.
• Helman N, Rubenstein LS (1975) The effects of age, sex and smoking on erythrocytes and leukocytes. Am J Clin Pathol 63(1): 35-44.
• Kelly A, Munan L (1977) Haematologic profile of natural populations: red cell parameters. Br J Haematol 35(1): 153-160.
• Allan RS, Alexander MK (1968) A sex difference in the leucocyte count. J Clin Pathol 21(6): 691-694.
• Cruickshank JM (1970) The effects of parity on the leucocyte count in pregnant and non-pregnant women. Br J Haematol 18(5): 531-540.
• Lewis SM (2006) Reference ranges and normal values. In Dacie and Lewis Practical Haematol: Pp 11-24.
• Adoga MP, Pennap GR, John PA, Shawulu PT, Kaba SV, et al. (2012) CD₄- and CD₃-T lymphocytes reference values of inmmunocompetent urban and rural subjects in an African Nation. Scand J Immunol 76(1): 33-38.
• Uppal SS, Verma S, Dhot PS (2002) Normal values of CD₄ and CD8 lymphocyte subsets in healthy Indian adults and the effects of sex, age, ethnicity and smoking. Cytometry B Clin Cytom 52(1): 32-36.
• Bussmann H, Wester CW, Masupu KV, Peter T, Gaolekwe SM, et al. (2004) Low CD₄+T-lymphocyte values in human immunodeficiency virus-negative adults in Botswana. Clin Diagn Lab Immunol 11(5): 930-935.
• Jiang W, Kang L, Lu HZ, Pan X, Lin Q, et al. (2004) Normal values for CD₄ and CD8 lymphocyte subsets in healthy Chinese adults from Shanghai. Clin Diagn Lab Immunol 11(4): 811-813.
• Yan J, Greer JM, Hull R, O Sullivan JD, Henderson RD, et al. (2010). The effect of ageing on human lymphocyte subsets: Comparison of males and females. Immun Ageing 7:4.
• Ray K, Gupta SM, Bala M, Muralidhar S, Kumar J, et al. (2006). CD₄/CD8 lymphocyte counts in healthy, HIV-positive individuals and AIDS patients. Indian J Med Res 124(3): 319-330.
• Tomschi F, Bloch W, Grau M (2018) Impact of type of sport gender age on red cell deformability of elite athletes. Int J Sports Med 39(1): 12-20.