The Effects of Acute Exercise Bouts on IGF1 Plasma Concentrations and Body Composition in Athletes.

Introduction:

Plowman and Smith (2007) explain that aerobic exercise (also known as endurance activities, cardio, or cardio-respiratory exercise) is essentially an alternative name for physical exercise and It can vary from low to high depending on the specific aerobic energy-generating process. "Aerobic is a term that describes the use of oxygen in a sufficient quantity to meet energy demands during exercise through aerobic metabolism" (McArdle et al.; 2006). Typically, the aerobic exercise consists of repeating low-to-moderate intensity activities for extended periods (Plowman & Smith, 2007).

Also, The Insulin Like-Growth Factor can cause a number of small proteins (somatomedins) to be produced in the liver, significantly impacting bone growth (Hall, 2016) and the impacts of somatomedin on growth mirror the effects of insulin on growth, and thus they are sometimes known as insulin-like growth factors (IGFS). There are at least four isolated somatomedins that have been identified. However, somatomedin C is the most important (also known as insulin-like growth factor-1, or IGF-I).

As Exercise stimulates the release of pituitary growth hormone (GH), which causes plasma GH levels to rise within 15 minutes after exercise. GH plays a vital downstream mediatory role in producing, maintaining, and regenerating skeletal muscles. Moreover, insulin-like growth factor I (IGF-I) also plays a crucial role in this process. Thus, it is reasonable to associate exercise-induced GH activation with the hypertrophy seen in exercising muscles. IGF-I is stimulated by circulating (endocrine) and locally produced (peripheral) GH (Kraemer et al., 2010; Hoffman, 2009; Jan Frystyk, 2010).

And the perfusion of the contracting skeletal muscle is significantly boosted during exercise. The skeletal muscle may be the primary source of IGF-I, which causes elevated serum IGF-I levels. This may well be the case because IGF-I is primarily expressed in skeletal muscle and that IGF-I storage on IGFBPs in the muscle could be available for release (Berg and Bang, 2004). Moreover, Dall et al. (2001) suggest that the reported increases in total IGF-I seen in some studies may be due to changes in the plasma volume during exercise.

Many scientific opinions that discussed the topic of research indicate, including the following:

Moran et al. (2007) describe the growth hormone-insulin-like growth factor I (IGF-I) axis as a key component in regulating muscular development. Furthermore, recent studies have shown that IGF-I plays a critical role in both muscle hypertrophy and angiogenesis. These factors are essential features involved in muscular anabolic adaptation to exercise. IGF-I has also been a crucial regulator of gene expression in the skeletal muscle. These hormones activate protein synthesis in all muscles in the body (at least in some conditions).  Physical exercise heavily impacts the GH–IGF-I axis. LeRoith (1991) explains elevated GH and IGF-I levels can increase body weight, as well as bolster bone and muscle mass.

What’s more, the IGF-I response is determined mainly by training status, exercise type, intensity, and duration [Roelen et al .; 1997 & Rosendal et al.;, 2002& Bermon et al. (1999) ] carried out a strength test on 32 healthy senior volunteers (16 males aged 67–80 years old) to see how an acute bout of exercise affected total and free IGF-I and IGFBP-3 plasma concentrations. The subjects were subsequently allocated to either regular physical activity or an 8-week strength-training regimen at random. After eight weeks, blood samples were taken from both the sedentary and training groups under the same settings. There appeared to be an instant increase in the total and free IGF-I concentrations in the exercising group (+17.7 and +93.8%, respectively), which changed to +7.5 and +31.2% (respectively) 6 hours after the test. However, no significant changes in IGFBP-3 concentrations could be identified in the exercising or resting control groups. Moreover, strength training did not cause any substantial changes in baseline IGF-I and IGFBP-3 concentrations. Strength exercise was found to induce an early and sustained IGF-I release in elderly subjects, regardless of their training status, as shown by increased total and free IGF-I concentrations in both trained and sedentary groups. This suggests that strength exercises can induce an early and sustained IGF-I release in elderly subjects, irrespective of their training status.

What’s more, Shymaa et al. (2018) conducted a study to explore the impacts of moderate aerobic exercise on insulin-like growth factors and functional capacity in elderly participants. The sample consisted of thirty elderly subjects, each of whom had participated in a moderate-intensity aerobic exercise with a training fraction of 65% to 75% of their maximum heart rate. They carried out this training regime three times a week for eight weeks. The findings indicated that there was a significant rise in the insulin-like growth factor eight weeks after commencing aerobic training (32%), as well as an 18.5% increase in functional capacity.

 Meanwhile, Sagiv et al. (2007) revealed that physically active subjects had higher levels of IGF-1 than sedentary subjects and that IGF-1 serves as a crucial mediator in muscle hypertrophy and angiogenesis. These two factors characterise the anabolic adaptation of muscles during exercise. Additionally, a study performed by Rubin (2005) focused on healthy young individuals and found that various types of exercise (including aerobic, resistance, and heavy ergometer cycling) caused circulating IGF-1 levels to rise. Furthermore, Short et al.'s (2004) study revealed that continued bouts of moderate-intensity aerobic exercise could enhance muscle protein synthesis in both older and younger individuals.

According to the previous presentation of previous scientific studies, it is clear that, Several researchers have studied the impacts of aerobic exercise and/or resistance exercise on IGF1 plasma concentrations and its effects on the functional abilities of elderly individuals (Bermon et al., 1999; Shymaa et al., 2018). Many studies have explored the impacts of aerobic and/or resistance exercises on protein synthesis in the elderly and the young. One key example is the study performed by Short et al. (2004). On the other hand, several studies have investigated the impacts of one isolated bout of exercise on IGF1 plasma concentrations in the elderly. For instance, Ehrnborg et al. (2003) explored the hormonal responses in 120 elite athletes to the IGF-I axis. They also measured bone markers in response to maximum exercise. There appeared to be a somewhat uniform pattern in the hormonal response in the IGF-I axis, which peaked directly after exercise and then decreased to baseline values within 30–60 minutes. However, the pattern concerning the bone markers was less obvious. Very few studies have examined the impacts of one acute bout of exercise on IGF1 plasma concentrations and the effects on body composition. To date, controversy exists regarding the short- and long-term effects of physical activity on IGF-1 concentrations (Roli et al., 2018; Gregory et al., 2013; Frystyk, 2010a; Nindl and Pierce, 2010; Frystyk, 2010b; Healy et al., 2005; Ehrnborg et al., 2003). Thus, how exertion affects serum IGF-1 is unknown. Physical activity has been related to a rise in IGF-1 levels depending on body composition. As a result of this gap in the literature, the researchers of this study decided to examine this particular subject. They believe that this study is the first study into The Effects of Acute Exercise Bouts on IGF1 Plasma Concentrations and Body Composition in Athletes.

Aim:

 The study aims to examine the impact of acute episodes of exercise on plasma IGF-1 levels and body composition of athletes training for track and field events.

Hypotheses:

There are statistically significant measurements between IGF-1 levels and body composition pre and post effort of acute episodes of exercise.

Methodology:

Sample

Purposive sampling was used to select the participants for the present study. A total of 7 participants were chosen from a list of athletic players registered with the Egyptian Athletics Federation. This included 4x800-meter sprinters, 1x400-meter players, and 2x100-meter sprinters from the Athletics Club.

Sample selection Conditions

1. The athletes and coaches were given information forms to explain the nature and purpose of the study, after which they were asked to complete and return consent forms confirming that they were happy to participate in the study.
2. Participants had to be training for at least two years.
3. Participants had to be free of nutritional supplements.
4. Participants were not allowed to take part in any other research. 
5. The participants had to undergo medical examinations to ensure that they had no diseases. 

In the table (1) below, a statistical description of each variable is presented.

Sample Homogeneity:

Table (1)

Statistical description of the research sample data in the primary variables

(n = 7)

Table (1) shows the statistical description of the research sample data in the primary variables before the study. The Skewness coefficient ranged between (0.18 to 2.16), and these values are close to zero, and lie in the normal distribution curve between (±3), which confirms the data and that it is not dispersed.

Table (2)

Statistical description of the research sample data in the research variables

(n = 7)

Table (2) shows the statistical description of the research sample data in the research variables before the study. The Skewness coefficient ranged between (-1.49 to 2.56), and these values are close to zero, and lie in the normal distribution curve between (±3), which confirms the data and that it is not dispersed.

Time Range: The investigation was performed between 5th December 2020 and 5th January 2021.

-            Survey Studies: 5/12/2020 to 3/1/2021.

-            Primary study:  5/1/2021.

Spatial Field

1. Biochemical analyses were performed in Dr. Emad Mahfouz's laboratory.
2. Physical tests were performed at the fitness club.

Measurements

Except for the baseline measurements, all other measures were taken before and after the players had engaged in physical activity.

Basic Measurements:

1. Age to the nearest (year)
2. Height to the nearest (cm²)
3. Weight to the nearest (kg)
4. Years of training to the nearest (month)

Physiological Measurements:

1. Heart rate.
2. Rate of systolic and diastolic blood pressure.
3. Rate of respiration.

Body Components Measurement:

1. Muscle percentage (%).
2. Muscle mass (kg).
3. Moisture (%).
4. Bone mass (kg).
5. Percentage of proteins (%).
6. Percentage of subcutaneous fat %.
7. Fat mass (kg).
8. Weight without fat (kg) fat free mass.
9. Mass of proteins (kg).

Biochemical Measurements:

1. Insulin-like growth factor (IGF1).
2. Myoglobin (Mb).
3. Lactic dehydrogenase (LDH) enzyme.
4. Creatine phosphokinase (CpK) enzyme.

Tools and Equipment

Restmeter: Used to measure height.

Promed: Body Fat Scale Model F20E-B  (Germany Tech), used to measure body components.

Beurer medical BM40: Used to monitor blood pressure and pulse.

Tools for drawing blood samples: 5cm syringe/needle, alcohol (70% concentration), medical cotton, plaster, tubes for collecting blood samples (must contain Edita and Serum), icebox to store blood samples.

Surveys

The First Survey

This survey was carried out between 5th December 2020 and 28th December 2020. The key objective was to select the research sample based on the specifications. Personal interviews were held with the coaches and players from the Smouha, Sporting, Al-Ittihad and Olympic Clubs. The coach and the players all agreed to participate in the primary study survey. The sample was then narrowed down to 7 players who met the inclusion criteria.

The Second Survey:

The second survey took place between 2nd January 2021 and 3rd January 2021. The key objective was to select a laboratory suitable to carry out the biochemical measurements and a gym in which the physical exertion tasks would take place. Thus, the researcher visited the College of Physical Education for Girls in Fleming and reserved the hall for the players to carry out the physical exercise task on the treadmill.  Subsequently, they went to Mabrat Al Asafra laboratory (Rushdie branch) and Dr. Emad Mahfouz’s laboratory in Fleming to determine whether the laboratories met the specified requirements, and to ensure that there was a technical doctor present who specialized in taking blood samples before and after the physical exercise activities had taken place.

Due to the college's preventive precautions for the Covid-19 outbreak, the College of Physical Education for Girls in Fleming did not approve the request. However, the Fleming Fitness Club authorized the request to reserve the hall.

The required specifications were met by both the Mabaret Al-laboratory Asafra's in Rushdie and Dr. Emad Mahfouz's laboratory in Fleming. However, given its proximity to the club, Dr. Emad Mahfouz's facility was selected.

Primary Study:

Carried out on 5th January 2021.

First of all, the basic measurements were taken, after which physiological measurements, body composition and biochemical measurements were taken. These measurements were all taken before the players had engaged in any physical activity and while resting.

Players then warmed up on the treadmill for 10 minutes at (5 km / h) with an incline of (0). The speed was gradually increased every two minutes until a pulse rate of (170 beats/min) was achieved (or until fatigue was encountered). Once the physical exercise period is complete, physiological dimensional measurements are taken. Subsequently, body components and biochemical measurements were taken.

Statistics :

The statistical analysis was found using the SPSS version 25 program, as follows: Arithmetic Mean , Standard deviation , Median , Coefficient of Skewness , Paired Samples T test for differences between pre- and post-measurements , The percentage of Change rate , Effect size according to Cohen’s D equations , Effect size according to Eta square.

Results :

Table (3)

Statistical indications for the comparison between the measurement before effort and after effort for the variables under study.

 (n=7)

*P value <0.05

Eta square: less 0.3 = low                     0.3: 0.5 = medium                    up 0.5= high 

Table No. (3) of the variables under study, the statistical significance and the percentage of change before and after Effort: that there are statistically significant differences between the before and after efforts where P value less than 0.05 in variables (weight, total body water, heart rate, systolic blood pressure, breathing rate,  LDH, CPK, IGF1).

Discussion

The hypothesis was reinforced since, in comparison to baseline, post-exercise IGF-1 levels were elevated. IGF-1 concentrations were associated with body composition and positively correlated with body mass and total body water. These results are in keeping with Eklund et al. (2021), who reported that in contrast to control subjects, serum IGF-1 concentrations were raised in sportspeople, i.e., 277.5 ± 85.5 and 249.7 ± 73.3 µg/L, respectively (p <0.05). IGF-1 has been positively associated with muscle volume but not with aerobic capacity (Eliakim et al., 1996). A raised BMD, lean mass, and reduced proportion of fat have been noted in athletes (Eklund et al., 2017).

Several studies have concurred with the above results. Roli et al. (2018) reported increased reference values for IGF-1 in 58 female volleyball players when contrasted against a sex-matched reference cohort. When runners were considered in relation to gymnasts, Snow et al. (2000) documented higher IGF-1 levels in the former. Interestingly, Healy et al. (2014), who conducted a sizeable cross-sectional study, reported the most elevated IGF-1 levels in swimmers and cross-country skiers after competitive events.

The anabolic influence of IGF-1 on the remodeling of adult bone is well-established (Yakar et al., 2018); additionally, the growth factor triggers protein manufacture within the skeletal muscles (Velloso, 2008). There is a dearth of publications relating to the association between IGF-1 titres and body composition in sportswomen. Existing results have failed to demonstrate any relationship between IGF-1 concentrations and body fat (Healy et al., 2014). Nevertheless, Ehrnborg et al. (2003) evaluated sportswomen and reported a positive relationship between IGF-1 and body mass. Snow et al. (2000), documented a trend towards a positive association between IGF-1, and BMD and lean mass. In the current study, positive but only modest relationships were observed between IGF-1, BMD, and lean body mass in the amalgamated cohort of sportspeople and control subjects. A negative association with percentage fat was also noted.

When differing classes of sports were examined, individuals engaged in disciplines requiring power evidenced more elevated IGF-1 levels than those pursuing more technical events, i.e., 293.6 ± 78.4 vs. 221.5 ± 76.2 µg/L, respectively (p <0.01). Additionally, the former exhibited greater IGFSD, i.e., 0.37 ± 0.88, when judged against both endurance and technical specialists, i.e. -0.11 ± 1.18 (p < 0.05) and -0.44 ± 1.06 (p <0.05), respectively (Eklund et al., 2021).

The data from the present research additionally demonstrated that sudden onset exercise led to a rise in heart rate, systolic blood pressure and respiratory rate, and a fall in diastolic blood pressure. It was also demonstrated that mean serum IGF-1 levels were elevated following the exercise. There was a relationship between serum total IGF-1 and other biochemical parameters, i.e., LDH, MB, and CRP. Following the period of exertion to a heart rate of 170 beats per minute, IGF-1 became raised, which induced a rise in markers of muscle injury, i.e., LDH, MB and CRP, although this increase was within the normal range.

LDH is a constituent of the myosin heavy chains, i.e., troponin I and myoglobin, and is released in response to a skeletal muscle insult owing to its location within the cytosol and lack of ability to traverse the sarcoplasmic membrane (Gustavo et al., 2017; Willoughby et al., 2003). This facilitates the utilisation of LDH as a biomarker of muscle membrane and other tissue injuries (Foschini and Prestes, 2007).

A range of pathways and mediators governs muscular oxygen uptake. Myoglobin is associated with oxidative pathways and contributes in several ways to oxygen storage and the modulation of oxidative phosphorylation mechanisms. MB titres are related to enzyme functionality within the mitochondria and the capillary network (Kazumi Masuda et al., 1999).

It is well-recognized that exercise has a range of positive impacts on the human body. Nevertheless, high-intensity exertion leads to a rise in acute inflammatory markers, which promote the inflammatory process, potentially giving rise to reduced exercise ability (Minetto et al., 2007; Yoon et al., 2007). Inflammation can be described as an intrinsic cellular and systemic reaction to an insult through which the body endeavours to repair and to return affected tissues to their pre-harmed status.

Acute inflammation is characterised by hyperaemia, heightened permeability of blood vessels, fluid accrual, and the release and activation of white blood cells and inflammatory intermediaries, e.g., cytokines and CRP (Ward, 2010). The latter is a bioindicator that reflects the presence of long-term systemic inflammation; it is commonly utilised as a quantitative gauge of the degree of engagement with physical exercise schedules (Fedewa et al., 2016). If the acute inflammatory reaction were enduring or overwhelming, tissues and viscera might be notably compromised (Ward, 2010).

CRP is a well-recognised component of symptomatology relating to inflammation and dynamic exertion, both of which elevate the levels of this indicator (Jee and Jin, 2012). Vigorous physical activity has been observed to cause a significant rise in pro-inflammatory mediators (Jee and Jin, 2012). Muscle injury caused by exertion stimulates the immune system, which then contributes to muscle and connective tissue breakdown and renewal (Peake, Nosaka and Suzuki, 2005).

The data collected in the present research are in keeping with those presented by Tyler (2014), who failed to note any alterations in CRP levels after medium-intensity exercise. Other studies have reported similar findings. Fedewa et al. (2016) suggested that the modest rise in CRP which is seen after physical exertion occurs according to the particular schedule followed.

The present findings additionally revealed that CPK values were above the normal range both before and after the treadmill intervention. Creatinine is an end-product of muscle metabolism (Bacallao and Badell, 2015). Its functional level is associated with the muscle’s workload (Vassilis Mougios, 2007). The plasma concentration of CPK is higher in sportspeople than in those who are sedentary. The elevated CPK levels were ascribed to training regimes undertaken by the athletes on a daily basis at the Olympic Club, a theory confirmed by additional researchers (Carcía-Cardona et al., 2021; Gustavo et al., 2017; Koch et al., 2014; Vassilis  Mougios, 2007; Hubal, 2002; Rosendal et al., 2002).

Conclusion:

An acute episode of physical activity to a peak heart rate of 170 beats/min led to a post-exercise rise in plasma IGF-1 levels which impacted: (1) weight loss as a consequence of a reduction in percentage body fat, total body water, subcutaneous fat and fat mass; (2) a rise in bone, muscle and protein masses, respectively, and fat-free weight; (3) a decrease in the pH increases indicative of muscle injury, i.e., LDH, MB and CPK; and (4) a lowering of inflammatory markers, e.g. CRP.

Recommendations:

1. Training regimes for sportspersons should not promote a heart rate of greater than 170 beats per minute owing to the positive impact on body composition and fall in inflammatory and muscle damage biomarkers, respectively, as a consequence of the elevated plasma IGF-1 titres.
2. Complementary nutritional support should be utilised in order to diminish the symptoms arising from excessive workloads performed by sportspeople training within the various sections of sports clubs.
3. Additional research on this topic should be performed on larger-sized populations of sportspeople who compete in different disciplines.

References :

1. Berg U. · Bang P. (2004): Exercise And Circulating Insulin-Like Growth Factor I.Hormone Research In Paediatrics.Cianfarani, Stefano (Rome).
2. Bermon S, Ferrari F, Bernard P,. Altare S, &. Dolisi I (1999): Responses Of Total And Free Insulin-Like Growth Factor-I And Insulin-Like Growth Factor Binding Protein-3 After Resistance Exercise And Training In Elderly Subjects. Acta Physiologica Scandinavica. Volume 156, Issue 1 P. 51-56.
3. Ehrnborg, C., Lange, K. H. W., Dall, R., Christiansen, J. S., Lundberg, P. A., Baxter, R. C., ... & GH-2000 Study Group. (2003): The growth hormone/insulin-like growth factor-I axis hormones and bone markers in elite athletes in response to a maximum exercise test. The Journal of Clinical Endocrinology & Metabolism, 88(1), 394-401.
   1. Eklund E, Berglund B, Labrie F, Carlstrom K, Ekstrom L, Hirschberg AL. (2017) : Serum Androgen Profile and Physical Performance in Women Olympic Athletes. Br J Sports Med  51(17):1301–8.
   2. Eliakim A, Brasel JA, Mohan S, Barstow TJ, Berman N, Cooper DM. (1996) : Physical Fitness, Endurance Training, and the Growth Hormone-Insulin-Like Growth Factor I System in Adolescent Females. J Clin Endocrinol Metab 81(11):3986–92. 
   3. Emma Eklund,  Anton Hellberg,  Bo Berglund,  Kerstin Brismar ,  and gAngelica Lindén Hirschberg (2021) : IGF-I and IGFBP-1 in Relation to Body Composition and Physical Performance in Female Olympic Athletes , Journal List , Front Endocrinol (Lausanne) .
   4. Frystyk J. (2010) : Exercise and the Growth Hormone-Insulin-Like Growth Factor Axis. Med Sci Sports Exerc 42(1):58–66 .
   5. Gregory SM, Spiering BA, Alemany JA, Tuckow AP, Rarick KR, Staab JS, Hatfield DL,Kraemer WJ, Maresh CM, Nindl BC (2013) : Exercise-Induced Insulin-Like Growth  Factor I System Concentrations After Training in Women. Med Sci Sports Exerc 45(3):420–8.  
   6. Dall R, Lange Khw, Kjær M, Et Al. (2001) : No Evidence Of Insulin-Like Growth Factor-Binding Protein 3 Proteolysis During A Maximal Exercise Test In Elite Athletes. J Clin Endocrinol Metab.;86(2):669-74.
   7. Jan Frystyk (2010) : Exercise And The Growth Hormone-Insulin-Like Growth Factor Axis , Medicine And Science In Sports And Exercise 42(1):58-66
   8. John E. Hall (2016): Guyton And Hall Textbook Of Medical Physiology. Thirteenth Edition.
   9. Hoffman Jr, Kraemer Wj, Bhasin S, Storer T, Ratamess Na, Haff Gg, Willoughby Ds, Rogol Ad (2009): Position Stand On Androgen And Human Growth Hormone Use. J Strength Cond Res;23(5), S1-S59. Doi: 10. 1519/Jsc. 0b013e31819df2e6.
   10. Kraemer Wj, Dunn-Lewis C, Comstock Ba, Thomas Ga, Clark Je, Nindl Bc(2010): Growth Hormone, Exercise, And Athletic Performance: A Continued Evolution Of Complexity. Current Sports Medicine Reports;9(4):242.
   11. Leroith D (1991): Insulin-Like Growth Factors: Molecular And Cellular Aspects. Crc, Boca Raton, Fl, Pp 1–54.
   12. Nindl BC, Pierce JR. (2010) : Insulin-Like Growth Factor I as a Biomarker of Health, Fitness, and Training Status. Med Sci Sports Exerc  42(1):39–49.
   13. Marie-Louise Healy  , Rolf Dall, James Gibney, Eryl Bassett, Christer Ehrnborg, Claire Pentecost, Thord Rosen, Antonio Cittadini, Robert C Baxter, Peter H Sönksen (2005) : Toward the Development of a Test for Growth Hormone (GH) Abuse: A Study of Extreme Physiological Ranges of GH-Dependent Markers in 813 Elite Athletes in the Postcompetition Setting. J Clin Endocrinol Metab .
   14. Mcardle Wd, Katch Fi, Katch Vl (2006): Essentials Of Exercise Physiology. Lippincott Williams & Wilkins. P. 204. Isbn 978-0-7817-4991-6. Retrieved 13 October 2011.
   15. Plowman Sa, Smith Dl (2007): Exercise Physiology For Health, Fitness, And Performance. Lippincott Williams & Wilkins. P. 61.
   16. Roelen Ca, De Vries Wr, Koppeschaar Hp, Vervoorn C, Thijssen Jh, Blankenstein Ma (1997) :Plasma Insulin-Like Growth Factor-I And High Affinity Growth Hormone-Binding .
   17. Roli L, De Vincentis S, Rocchi MBL, Trenti T, De Santis MC, Savino G. (2018) : Testosterone, Cortisol, hGH, and IGF-1 Levels in an Italian Female Elite Volleyball Team. Health Sci Rep 1(4):e32.
   18. Rosendal L, Langberg H, Flyvbjerg A, Frystyk J, Ørskov H, Kjaer M (2002): Physical Capacity Influences The Response Of Insulin-Like Growth Factor And Its Binding Proteins To Training. J Appl Physiol 93:1669–1675.
   19. Sagiv Moran, Yamin Chen & Yenon Nir (2007): Alterations In Igf-I Affect Elderly: Role Of Physical Activity.European Review Of Aging And Physical Activity.Volume4, Pages77–84.
   20. Shymaa Y. Abo Zaid,Samah M. Ismail, Mariam E. Mohamed, & Farag A. Aly (2018): Efficacy Of Moderate Aerobic Training On Insulin Like Growth Factor And Functional Capacity In Elderly . Medical Journal Of Cairo University. Vol. 86, No. 2, March: 903-908.
   21. Snow CM, Rosen CJ, Robinson TL. (2000) :  Serum IGF-I is Higher in Gymnasts Than Runners and Predicts Bone and Lean Mass. Med Sci Sports Exerc  32(11):1902–7.
   22. Healy ML, Gibney J, Pentecost C, Wheeler MJ, Sonksen PH. (2014) : Endocrine Profiles in 693 Elite Athletes in the Postcompetition Setting. Clin Endocrinol (Oxf)  81(2):294–305.
   23. Velloso CP. (2008) :  Regulation of Muscle Mass by Growth Hormone and IGF-I. Br J Pharmacol 154(3):557–68.
   24. Yakar S, Werner H, Rosen CJ. (2018) : Insulin-Like Growth Factors: Actions on the Skeleton. J Mol Endocrinol  61(1):T115–t37.