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Submitted: 30.10.2017 Received: 03.11.2017
Authors information:
Dariya V. Fedulova — Teacher Ural Federal University named after the First President of Russia B.N. Yeltsin, 4, Kominterna str. 4, Ekateriburg, 620078, Russia, E-mail: [email protected] Galina A. Yamaletdinova — Doctor of Pedagogics, Professor Ural Federal University named after the First President of Russia B.N. Yeltsin, 4, Kominterna str. 4, Ekateriburg, 620078, Russia
For citations: Fedulova D.V., Yamaletdinova G.A. Psychological - pedagogical influence on sportsmen's adaptation formation after a serious sports injury,The Russian journal of physical education and sport (pedagogico-pshycological and medico-biological problems ofphysical culture and sports), 2017, Vol. 12, No. 4, pp. 97-106. DOI 10/14526/04_2017_271.
DOI 10/14526/04_2017_272
ASSESSMENT OF SPIROMETRIC AND CARDIO-RESPIRATORY VALUES OF
KENYAN DISTANCE RUNNERS
Francis Mundia Mwangi (PhD) Lecturer, Department of Recreation Management and Exercise Science, Kenyatta University, P. O. Box 43844 - 00100, Nairobi, Kenya.
Tel. +254722761379 Email Address; [email protected]
Abstract
Background: Some studies have reported significant relationships between some spirometric, cardiorespiratory and endurance performance variables. This study therefore sought to determine the status of these values among Kenyan distance runners who have dominated endurance running events internationally. Methods: Fifteen (10 male, 5 female) purposively selected elite Kenyan runners were instrumented in baseline spirometry and an incremental treadmill test to exhaustion with respiratory gasses and heart rate assessments. Results: One sample t test showed that most spirometric values are not significantly differentfrom predicted (p > .05). Relative maximum oxygen consumption (VO2max) for males (64.4 ± 4.9) and females (50.0 ± 1.9) [ml/kg/min] rated superior and excellent on cardio-respiratory fitness classification norms, while maximum heart rate was significantly lower than predicted. Pearson correlation analyses showed that some spirometric variables have significant relationship with oxygen consumption at submaximal level; VE; r= .792, p=001, FEV1; r=.658, p=.010, FVC; r=.741, p=.002 andPEF; r=.625, p=.017. Conclusions: Kenyan distance runners' spirometric values can be predicted by commonly used equations for general population. However, the runners have superior to excellent rating of aerobic capacity as well as high sustainable percentage of the same. These may point to enhanced gaseous exchange capacity/properties such as more pulmonary capillarisation, less shunts, and / or favourable hemodynamics. Recommendations: More studies are needed to explore how spirometric and cardio-respiratory variables contribute to overall endurance running performance. Keywords; Endurance exercise, somatotype, reference values
Introduction Some studies have reported positive
relationships between some spirometric
variables and endurance performance (Fatemi et al., 2012; Pringle et al., 2005; Adegoke & Arogundade, 2002). Use of equations derived from other population may lead to development of research instruments which have not been validated for the particular population, and may underrate or overrate test parameters. This can have adverse implication in health, training, as well as in performance. According to Sood et al (2007), ancestral background, altitude, and area of residence are some of the factors that may contribute to biological variation which may cause lack of agreement with reference values from different population.
In the last several decades (since 1968) athletes from East Africa have dominated international distance running events (Prommer, et al., 2010; Scott and Pitsiladis, 2007; Onywera, 2006; Larsen, 2003; Saltin et al., 2003). This is especially the case for runners from Kenya. Noakes (2001) noted that no international sport has ever been dominated by athletes from one country to the extent the Kenyans have done in international competitions from 800 m to the marathon, winning between 40 and 50% of all medals.
The reason as to why the Kenyans and other East African athletes perform so extraordinarily well in endurance races is a question which has inspired considerable interest, speculation and debate amongst athletes, coaches and academics (Prommer, et al., 2010; Scott and Pitsiladis, 2007; Onywera, 2006; Saltin et al, 2003). Those interested in understanding the dominance of these athletes have wondered whether the 'secret' can be found in the socialization experiences and lifestyles of Kenyan children (e.g. the effects of running to school as children), impacts of living and growing up at high altitude, and/or to the nutrition/diet of these athletes (Fudge et al., 2006; Onywera et al., 2006; Saltin et al., 2003). Others suggest that Kenyans benefit from genetic advantages over groups in other regions of the world (Scott and Pitsiladis, 2007). Favourable anthropometric
characteristics have also been touted as contributing to success of Kenyan (East African) runners. Lucia et al., (2008) and Saunders et al., (2004) observe that reduced muscle mass below the centre of gravity (i.e. thin calves compared with Caucasians) can increase efficiency of
running, and seems to be the main determinants of efficiency of human locomotion. However, the extent to which various factors contribute to Kenyan runners dominating the field remains as yet to be determined (Scott and Pitsiladis, 2007; Onywera et al., 2006; Scott et al., 2005; Pitsiladis et al., 2004). This study therefore sought to determine the relationships between spirometric and respiratory values, and endurance performance indicators (sub-maximal and maximal oxygen consumption and velocity/speed) among Kenyan distance runners.
Methods
Fifteen (10 male, 5 female) purposively selected elite Kenyan runners were instrumented in baseline spirometry and an incremental treadmill running test to exhaustion with respiratory assessments. Prior to instrumentation and baseline testing sessions, each participant included in the study signed an informed consent form. Then they completed a screening questionnaire, a physical activity readiness questionnaire (PAR-Q), and a Running history questionnaire. After the inclusion criteria were met, the participants uderwent measurements in; resting physiological measurements (ventilation [tidal volume and frequency], respiratory gases, blood pressure and heart rate), baseline spirometric tests. Then they were taken through treadmill test to exhaustion with respiratory measures recorded. Spirometric variables measured included forced vital capacity (FVC), forced expiratory volume in one second (FEV1), forced expiratory volume in one second as a proportion of forced vital capacity (FEV1/FVC) and maximum inspiratory pressure (MIP). Respiratory measures obtained during treadmill test included tidal volume (VT), breathing frequency (Fb), minute ventilation (VE), oxygen consumption (VO2), carbon dioxide production (VCO2) and respiratory exchange ratio (RER) was calculated.
Spirometric and respiratory variables were measured using the following equipment/apparatus; Spirometer system (ML 311, ADInstruments, Australia),
Pneumotachograph (HR800L, HansRudolph, USA), respiratory gasses (oxygen and carbon dioxide) analyzers (17625 and 17630, Vacumed, Ventura, California, USA), automated blood
pressure system (BPM-100, VSM Medtech Ltd, Vancouver, Canada), and heart rate monitor (S610i, Polar Electro, Kempele, Finland).
Participants performed 3-6 forced vital capacity maneuvers. This test involved breathing on a turbine from a portable spirometer system (ML 311, ADInstruments, Australia) and taking several normal breaths followed by a large inspiration to total lung capacity and a full forceful expiration to residual volume. From this maneuver, values were recorded for the forced vital capacity (FVC), the forced expiratory volume in 1 second (FEV1) and peak expiratory flow rates (PEF). Maximal Inspiratory (MIP) was also taken to measure the strength of the respiratory muscles using a pressure manometer (Raytech Instruments, Vancouver, BC). The measurements required the subject to breathe in as hard as possible for at least 1 second at functional residual volume.
The participants begun the running test on a treadmill (h/p/cosmos COS10199, Germany) at a starting speed of 14 Kmh-1 (9 Kmh-1 for women) and no elevation (after a 5 minute warm-up at a speed of 5-8 Kmhr-1). Every three minutes the treadmill speed was increase by 1 Km hr-1 until exhaustion. The participants were made to breathe through a mouthpiece of spirometer system with nose clip fixed, allowing the measurement of ventilation to be made. In addition, the respired gases were analyzed such that the amount of carbon dioxide produced and oxygen consumed was determined. Heart rate was measured and monitored using Polar heart rate monitor.
Participants' Characteristics
The age of the participants was 25.40 ± 4.64 (Mean ± SD) (n = 15) which is within the range at which endurance athletes are in their prime
(Schulz & Curnow, 1988), while the BMI value is typical of values reported for Kenyan distance runners (Kong & Heer, 2008). The participants' ethnic subgroup distribution was a representative of where majority of elite Kenyan runners come from (Kalenjin sub-tribes) as established by Onywera et al., (2006). The participants' training attributes included running training frequency of 5.33±0.62 per week, duration of competitive running of 4.43±1.95 years, average training distance 11.20±5.00 km, and weekly training mileage 99.07±42.30 km. This is high training volume and frequency, typical of successful endurance training as reported by several authors (Kong & Heer, 2008; Karp, 2007).
Results and Interpretation
Baseline Spirometry values
The spirometry values are summarised in descriptive measures of mean and standard deviation in Table 1. One sample t test was used to compare the baseline spirometric values against their corresponding predicted values. Prediction equations from the National Health and Nutrition Examination Survey (NHANES III) for African American were used as presented by Hankinson et al., (1999). These reference standards are based on measurements of normal subjects of similar age, height, and race. The t statistic values and the corresponding alpha values showed no significant difference between the recorded and the predicted spirometric values for the male athletes (p > .05). For the female runners, a few parameters (peak expiratory flow, forced vital capacity, and forced expiratory volume in one second) rated lower than predicted values (p < .05).
Spirometric variable Mean Statistic Std. Err Std. Dev. Statistic
Subject's peak inspiratory flow [L/s] 4.22 .43 1.65
Subject's peak expiratory flow [L/s] 7.28 .72 2.80
Subject's forced vital capacity [L] 3.64 .19 .72
Subject's forced expiratory volume in one second [L] 3.01 .19 .74
Subject's forced expiratory volume in one second as a proportion of forced vital capacity [%] 85.34 1.73 6.69
Subject's maximum inspiratory pressure 79.76 4.88 18.91
Treadmill Running Speed The last five stages leading to maximal / termination of exercise were considered in the analyses of exercise respiratory data. Average speed for these five exercise stages leading to termination of exercise were 14.72±1.35, 15.60±1.51, 16.70±1.34, 17.70±1.34, 18.70±1.34 and 11.50±1.91, 12.50±1.91, 13.50±1.91, 14.50±1.91, 15.50±1.91for male («=10), and female (n=4) participants (Mean±SD) [km/h] respectively. At the time of termination of the incremental exercise, the subjects reached maximum speed of 18.7 ± 1.34 Km/hr and 15.5 ± 1.91 Km/hr (Mean ± SD), for
Table 2. Respiratory values for athletes at rest, at sub-maximal
± SD), (n = 14).
Respiratory Variable At Rest At submaximal exercise At maximal exercise Peak
VT [L/br] .50±.15 1.70±.35 1.73±.34 1.76±.35
Fb [br/min] 21.39±3.94 57.30±10.77 58.60±9.99 59.93±10.28
VE [L/min] 7.80±2.00 71.94±15.58 75.33±16.59 76.41±15.71
VO2 [L/min] .26±.08 3.08±.58 3.11±.62 3.17±.59
VCO2 [L/min] .22±.07 3.09±.65 3.18±.67 3.23±.66
RER .86±.07 1.00±.07 1.02±.07 1.02±.07
Relative VO2 [ml/kg/min] 4.89±1.33 58.35±7.48 59.06±9.07 60.20±8.10
male and female athletes respectively. Peak speed recorded was 21 Km/hr and 17 Km/hr for male and female athletes respectively.
Respiratory Variables
Respiratory variables assessed were Tidal Volume (VT), Breathing Frequency (Fb), Minute Ventilation (VE), Oxygen Consumption (VO2), Carbon dioxide production VCO2, and Respiratory Exchange Ratio (RER). The values recorded at rest and during treadmill incremental exercise tests are summarized in Table 2, outlining values recorded at rest, sub-maximal and maximal levels, for all the participants.
exercise, maximal exercise, and peak values recorded (Mean
Peak values can be differentiated from maximal values in that the latter are the values recorded at the termination of exercise with or without a plateau, while the former are the highest recorded values during the exercise test duration. Repeated measures / paired t test was performed for the different respiratory variables to compare sub-maximal and maximal values. Significant difference between a given variable's sub-maximal and maximal values may indicate that the variable is a critical limiting factor for endurance performance among Kenyan runners. This is particularly the case if the maximal value of this same variable is not significant from peak value. Only minute ventilation and Respiratory exchange ratio values showed significant difference (t = -2.250; p = .042 and t = -4.553; p = .001 for VE and RER respectively). The maximal values for these variables are not significantly different from peak values. Significant difference between a given variable's maximal and peak values may indicate that the
variable may have been affected at (or reduced prior to) maximal level after reaching peak at sub-maximal stage. It can also indicate that there is reserve potential which can be utilized, and there is greater tolerance of any adverse effects associated with this variable. Only breathing frequency recorded significant difference between maximal and peak values (t = 2.950; p =.011). This may have been affected when the striding patterns in higher running intensity (towards maximal stage) got unsynchronized with breathing rhythm. Minute Ventilation (VE)
Minute ventilation (VE) maximal values (recorded during the maximal stage of the test) are significantly different from sub-maximal values (p = .042), and do not differ significantly from peak (highest recorded during the test) values (p = .229). This indicates that VE (or variable/s associated with it) is a critical limiting factor to endurance performance in the Kenyan runners.
Breathing Frequency (Fb)
Breathing frequency (Fb) recorded significant difference between maximal and peak values (p = .011) and no significant difference between sub-maximal and maximal values (p = .189). The high pace of running at maximal stage may have reached a rhythm beyond that which breathing action can keep up with. The breathing frequency variable is normally expected to increase with increasing exercise intensity. Together with increased tidal volume, the variables account for the increased VE.
Respiratory exchange ratio (RER)
RER maximal values (recorded during the maximal stage of the test) were significantly different from sub-maximal values (p = .001), and do not differ significantly from peak (highest recorded during the test) values (p = .112). This indicates that RER (or variable/s associated with it) is a critical limiting factor to endurance performance in the runners. Oxygen Consumption (VO2)
Absolute VO2 peak values for males (3.50±.26) and females (2.26±.26) [L/min] were significantly higher than predicted values (p
= .001), for people of similar age and height in general population. Relative VO2max for males (64.4±4.9) and females (50.0±1.9) [ml/kg/min] rated superior and excellent, judged on cardio-respiratory fitness classification from The Physical Fitness Specialist Manual as presented in Heyward, (2006). VO2 maximal values (recorded during the maximal stage of the test) are not significantly different from sub-maximal values (p = .427), and do not differ significantly from peak (highest recorded during the test) values (p = .105)
Correlation Analyses Correlation analysis between spirometric and cardio-respiratory variables against performance indices such as VO2submax, and speed showed significant correlation in some variables as shown in Table 3. FVC and VE had significant correlation with rVO2 both at sub-maximal and maximal levels. PEF, FVC, FEV1, VE and Velocity had higher correlation with rVO2 at submaximal than at maximal levels. Fb had significant correlation with rVO2 at maximal level but no significant correlation at submaximal level.
Table 3; Correlation between VO2 and spirometric cardiorespiratory & exercise variables, at exercise sub-maximal level (a)
and at maximal level (b)
Variable a) Sub-maximal stage b) Maximal stage
Pearson Correlation Sig. Pearson Correlation Sig.
(2-tailed) (2-tailed)
PIF .366 .198 .318 .268
PEF .625 .017* .447 .109
FVC .741 .002** .608 .021*
FEV1 .658 .010* .520 .056
FEV1/FVC .182 .533 .083 .778
MIP -.038 .897 .054 .855
Vt .518 .058 .460 .098
Fb .450 .106 .535 .049*
VE .792 .001** .762 .002**
RER -.191 .513 -.350 .220
%MHR .241 .429 .420 .154
Speed/Velocity .670 .009** .515 .060
* Correlation is significant at the 0.05 level (2-tailed). "Correlation is significant at the 0.01 level (2-tailed).
Running Economy Running economy (RE) can be taken as VO2 for a given sub-maximal speed (Noakes, 2001; Jones, 1998). VO2 values at 14.0-18.0 km/h (16 km/h and 14 km/h for male and female respectively) have been used as measures of running economy among endurance runners (Scholz et al., 2008; Noakes, 2001; Jones, 1998). In the current study, values of 57.95±2.35 (for
male at 16 km/hr) and 42.18±7.28 (for female at 14 km/hr) were recorded. Values of 52.4 ml/kg/min have been reported for elite male runners (Saunders et al., 2004), and 53 to 47.6 ml/kg/min have been reported for elite female world marathon champion (Jones, 1998).
Heart Rate Values
Heart rate increases proportionately with exercise intensity (linearly with VO2) (Haff & Dumke, 2012; Plowman & Smith, 1997). The variable values are influenced by an individual's age and level of cardio-respiratory fitness. Percent of maximum heart rate (%MHR) at rest and during exercise have been used to predict cardio-respiratory fitness, with the maximum heart rate (MHR) measured directly, or estimated from age-based formulae. In the current study, MHR was estimated from 220 - age formula.
The one sample t test comparing the heart rate values recorded and age-predicted values indicate that the participants had significantly lower HRM and %HRM (p = .001) at different exercise stages. Lower heart rate is a hallmark of adaptation to endurance training (Haff & Dumke, 2012; Plowman & Smith, 1997). According to the authors, the reduction of HR following training results from increased stroke volume rather than reduction in VO2 or cardiac output. It is therefore logical to say that the subjects in the current study had high stroke volume.
Discussion
Spirometric measures have been used to evaluate the status of lung capacity and the concomitant effects on external and internal respiration in human (Stanojevic et al., 2008; O'Donnell, Lam & Webb, 1999). In exercise, some studies have shown high correlation of some spirometric measures and performance in endurance events (Fatemi et al., 2012; Pringle et al., 2005; Adegoke & Arogundade, 2002), while some have shown weak or no significant relationships (Knechtle and Kohler, 2008; Amonette & Dupler, 2002).
Results in the current study suggest that most spirometric values of Kenyan runners are not different from those of general population. Prediction equations from the National Health and Nutrition Examination Survey (NHANES III) for African American were used as presented by Hankinson et al (1999). These equations have been widely used, especially where there are no locally established norms. According to Mackenzie (2004), Caucasians have the largest FEV1 and FVC, and Polynesians are among those with lowest. The values for people of African origin are 10 to 15% lower than for
Caucasians of similar age, sex and height because for a given standing height their thorax is shorter. Chinese have been found to have an FVC about 20% lower and Indians about 10% lower than matched Caucasians. There is little difference in PEF between ethnic groups (Mackenzie, 2004). Given that the results shown that most spirometric values of Kenyan runners are not significantly different from those of general population and yet they are able to cope with demands of high oxygen delivery, it is logical to say that they may be enjoying enhanced gaseous exchange status. However, this requires more studies utilising larger sample size to be confirmed. This study agrees with recommendations by Orie (1999) that there is need to establish local norms in order to make more accurate health diagnosis and decisions.
Some spirometric variables (FVC and VE) recorded significant Pearson correlation with performance indicators, more so during the submaximal running (tables 4 a & b). Some other studies have shown correlation between some spirometric measures and VO2max (Fatemi et al., 2012; Pringle et al., 2005). However, it is the sub-maximal VO2 which determines the performance in an endurance race than the VO2 max (Larsen, 2003). Therefore, correlating variables with sub-maximal VO2 is more relevant than with VO2 max. The current study data is in agreement with this fact, with the running speed recording significant correlation with sub-maximal VO2 and no correlation with VO2 max (see Table 4 a and b). Any variable that correlates highly with sub-maximal VO2 is thus expected to be a good predictor of performance in an endurance race. In this study, several spirometric variables recorded significant correlation with sub-maximal VO2 (FVC [r = .741; p = .002], VE [r = .792; p = .001], FEV1 [r = .658;p = .010] and PEF [r = .625,p = .017]) as indicated in Table 4 a. It logical to say therefore that, these variables can be used to predict endurance running performance, but in cohort with other factor/s which are not yet known / which may not have been exposed by this study.
Incremental treadmill exercise is routinely used to mimic endurance running in studies of this nature. Similar approach was taken by the current study, with athletes being encouraged to
push themselves to attain maximum effort. Respiratory exchange ratio (RER) of 1.00±.07 and 1.02±.07 were reached in this study (Table 3), at exercise stage 4/sub-maximal and exercise stage 5/maximal respectively. According to Plowman & Smith (1997) and Haff & Dumke (2012), RER equal or greater than 1.0 indicates (is a criterion for determining) that the tests were truly maximal.
Running economy (RE), defined as the energy cost (VO2) of sub-maximal running, contributes to endurance running performance (Saunders et al., 2004; Noakes, 2001; Jones, 1998). It can discriminate performance capability in athletes of similar/ homogeneous in VO2 max. Subjects with good running economy can outperform subjects with higher VO2 max values. Factors involved in the determination of RE include biomechanical factors involved in running style, and physiological such as greater oxidative capacity in endurance trained muscles (including proportion of Type 1 fibers) (Saunders et al., 2004; Noakes, 2001).
RE and VO2 max has been shown to be separately related to enduarance running performance. RE (VO2 for a given sub-maximal speed) expressed as a percentage of VO2 max (% VO2 max) has been used to account for individual differences in running economy and VO2 max in relation to performance, and referred to as the fractional utilization of VO2 max and/or aerobic running capacity of a runner (Svedenhag, 2001). The % VO2 max value expresses the combined effects of VO2 max and of running economy on performance. High correlation has been reported among marathon runners between this measure (% VO2 max) and performance (race times) (r = -0.94, «=35) at sub-maximal speed of 15 km/hr (Svedenhag, 2001). In the current study, values of 57.95±2.35 (for male at 16 km/hr) and 42.18±7.28 (for female at 14 km/hr) were recorded. When expressed as a percentage of VO2 max, these values translate to 90.46±6.99 and 84.81±15.20 respectively, and 88.85±9.70 when combined. These values are superior to some reported values for elite runners; 52.4/70.3*100 = 74.54% (Saunders et al., 2004), and for a highly trained world marathon champion; 53/72.8*100 = 72.80% (Jones, 1998).
Increased intensity of the exercise as one approaches maximal level produces lactic acid which takes up bicarbonate ions to make carbonic acid, which in turn dissociates to water and carbon dioxide (Haff & Dumke 2012). To avoid accumulation of these metabolites and the ensuing metabolic acidosis, the increasing carbon dioxide has to be eliminated through increased ventilation. Results of respiratory data analysis in the current study showed that tidal volume (Vt) and breathing frequency (Fb) increased only marginally between sub-maximal and maximal stages, but the combined effects increases minute ventilation (VE) significantly. Adequate ventilatory responses are needed to support relatively high intensity endurance performance in order to adequately removed carbon dioxide from blood and to compensation for metabolic acidosis associated with high submaximal and maximal exercise intensities.
Highest Fb values recorded during exercise were significantly higher than values recorded at maximal exercise, and no significant difference between sub-maximal and maximal values. This may indicate some potential which can be tapped for better performance in endurance exercise through training. Plowman & Smith (1997) observe that Vt increases with exercise up to moderate intensity after which it may plateau or decrease. Any further increase in ventilation towards maximal exercise is achieved through an increase in Fb. It is logical to say that practicing using proportion of maximum voluntary ventilation (which involves deep and fast breathing) for a few minutes (or using commercially produced inspiratory muscle training devices) during endurance training programmes, may enhance Fb to match higher pace and rhythm of running, and probably lead to more complete respiratory compensation for metabolic acidosis. This is in concurrence with the findings by Pringle et al., (2005) that maximum voluntary ventilation (MVV) explained high proportion of variance in distance running performance. However, it is possible, that more ventilation would have lowered level of CO2 and result to alkaline status. But it could also offset the overall acidosis status of the arterial blood caused by metabolic processes associated with the high intense work in the
muscle tissues, thus allowing the runner to achieve higher intensity/speed.
The physiological sequence of ventilatory responses to exercise is not fully understood as yet. Oxygen, carbon dioxide and pH receptors are said to be the primary initiators as they are stimulated by the changing levels of the respective elements in the blood (Plowman & Smith, 1997; West, 2008). However, during exercise ventilation adjusts before changes in oxygen, carbon dioxide and/or pH reach a magnitude that can increase ventilation. Only at severe exercises levels that changes in these parameters are noticeable in the arterial blood (VanDeGraaff & Fox, 1995). VanDeGraaff & Fox (1995) observe that exercise hyperpnea (increase in pulmonary ventilation during exercise) is ordinarily enough to prevent marked changes in the composition of arterial blood. The author suggests that neurogenic and chemical mechanism may be involved in hyperpnea (which is different from hyperventilation as PaCO2 remains within normal range). This agrees with Landau (1980) who notes that carbon dioxide is lost in the lungs during exercise hyperpnea, and therefore no signals to be detected by arterial chemoreceptors. The author cites the possible causes of exercise hyperpnea as including; reflexes from moving limbs, increased temperature, action of epinephrine, and cortical (psychic) influences.
From the results of the current study, indications are that perhaps the most important respiratory factor in Kenyan elite running is the ability to sustain relatively high sub-maximal VO2 for long period and the corresponding relatively high speed, rather than the absolute VO2 max. This is indicated by the fact that there is no significant difference between VO2 at penultimate stage /sub-maximal stage 4 and maximal stage 5 (p = .427), while the level of acidosis is significantly lower at high submaximal level / stage 4 than at maximal level stage 5 (p = .020). These indicate that the speed/intensity associated with the relatively high VO2 can be sustained given the less acidic internal environment. This is in agreement with other studies which have reported high lactic acid tolerance at high VO2 max among Kenyan runners (Tam et al., 2012; Larsen, 2003). It is also in line with observations by Mackenzie
(2010) that VO2 max on its own is a poor predictor of performance but using the velocity and duration that an athlete can operate at their VO2 max provides better indication of performance. Less acidic internal environment in exercising athlete is majorly maintained by respiratory system (renal system being the other, is slow). This means that ventilatory responses in Kenyan runners were able to largely offset the metabolic acidosis caused by the high submaximal intensity work in the muscle tissues. Favourable enzymatic activity in the active muscles can also be responsible for sustaining high VO2 max by ensuring low lactic acid accumulation as reported by Weston, et al., (1999), but studies comparing the response to training of Kenyans and Caucasians have shown similar trainability with respect to oxidative enzymes (Larsen, 2003; Saltin et al., 1995).
Possible explanation of high sub-maximal VO2 and VO2 max in Kenyan runners could also be more effective blood supply as indicated by relatively low % HR Max during exercise compared to predicted values. Efficiency of blood supply may be facilitated by higher stroke volume and higher capillarisation. According to the authors (Haff & Dumke, 2012; Plowman & Smith, 1997), lower heart rate is a hallmark of adaptation to endurance training, with the reduction in HR following training resulting from increased stroke volume (rather than reduction in VO2 or cardiac output). Higher stroke volume without capillarisation would result to faster transit time of blood through pulmonary circulation, resulting to reduced time for gaseous exchange. This could worsen during exercise if there are shunts which would allow higher volume of blood to pass through the lungs without gaseous exchange taking place. Dempsey et al., (2008) and Nielsen (2003) reports a diffusion limitation attributable to a ventilation-perfusion mismatch affects the transportation of O2 from alveoli to the pulmonary capillaries, leading to some deoxygenated mixed venous blood getting back to circulation. The authors note that with the marked increase in cardiac output during high intensity exercise, diffusion limitation is aggravated by the fast transit time and compounds the O2 transport problem. Higher stroke volume (as opposed to high heart rate)
coupled with higher systemic and pulmonary capillarisation and less (or absence of) pulmonary shunts can therefore ensure more efficient blood circulation and gaseous exchange during exercise. The relatively low HR (%MHR) at all exercise intensities in the current study may be indicative of the above circumstances being present in the subjects. This is subject for further investigation. It is worth noting that Saltin (2003) reported higher muscle capillarisation compared to Scandinavian runners.
The current study does not identify a single factor that is responsible for success of Kenyan runners but gives some insight into pulmonary factors that may work in cohort with others to favour better endurance performance. It agrees with Noakes (2001) and Joyner & Coyle (2008) who asserts that elite athletic performance involves integration many factors that function cooperatively to efficiently transfer the energy from aerobic and anaerobic ATP turnover into velocity and power. The authors note that the challenge for physiologist is in establishing the relative importance of the different variables involved, with Joyner & Coyle (2008) adding that complex motivational and sociological factors also play important roles in determining success of athletes. It is worth noting that the performance indicators (VO2 and running speeds at VO2 max) in the current study were reached while running at moderate altitude (1,661m [5,450ft] a.s.l.). Therefore, the athletes would record higher performance indices at low altitude / sea level. In addition, some athletes were not used to running on treadmill. The subjects can be expected to score higher values when running on track (where they are used to), and with greater motivation such as financial rewards that goes with winning major competitions, than on treadmill.
Conclusions
From the findings of the study the researcher concludes that Kenyan distance runners' spirometric values are can be approximated using commonly used regression equations. However, there is need to establish local norms for more accurate interpretations of these data. Ventilatory responses of Kenyan runners can be able to support relatively high intensity endurance performance through both increased
breathing rate and tidal volume. Breathing frequency however indicates some potential which may be tapped for better performance in endurance exercise through training. Oxygen consumption (rVO2) rated excellent and superior against commonly used norms. There is relatively high rate of oxygen consumption which can be sustained, given that sub-maximal value of rVO2 do not differ significantly from maximal value (p = .739).
Kenyan endurance runners utilised relatively low percentage of their maximum heart rate during sub-maximal and maximal endurance exercise. This must have been accompanied by large stroke volume. With their pulmonary function being able to support delivery demands of superior oxygen consumption at sub-maximal and maximal endurance exercise despite being comparable to values from other population, it is possible that they could be having enhanced gaseous exchange capacity/properties such as more pulmonary capillarisation, less shunts, and / or favourable hemodynamics. More studies need to be done in this area to determine the cardio-respiratory parameters of Kenyan distance runners compares to those of runners from other regions, and effects on endurance race performances.
Acknowledgement
This article is derived from my PhD dissertation (Kenyatta University, December, 2013). I appreciate support and contribution of my study supervisors, the support from Kenyatta University, University of British Columbia, and Kenya National Council for Science and Technology. I am grateful to the study volunteer athletes and the research assistants for their sacrifice and job well done. Adegoke, OA. & Arogundade, O. (2002). The effect of chronic exercise on lung function and basal metabolic rate in some Nigerian athletes: African Journal of Biomedical Research, Vol. 5, No. 1-2, pp. 9-11.
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Submitted: 13.12.2017 Received: 16.12.2017
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Authors information:
Francis Mundia Mwangi (PhD) Lecturer, Department of Recreation Management and Exercise Science, Kenyatta University, P. O. Box 43844- 00100, Nairobi, Kenya. Tel. +254722761379, Email Address; mwangi.francis@,ku.ac.ke
For citations: Francis Mundia Mwangi Assessment of spirometric and cardio-respiratory values of kenyan distance runners, The Russian Journal of Physical Education and Sport (Pedagogi-co-Phycological and Medico-Biological Problems of Physical Culture and Sports), 2017, Vol. 12, No. 4, pp. 106-116. DOI 10/14526/04_2017_272
DOI 10/14526/04_2017_273
EVALUATION OF THE FUNCTIONAL STATUS OF OLDER MEN ENGAGED IN
SPORTS AND RECREATION GROUPS
Alexsandr V. Dorontsev - Candidate of Pedagogical Sciences, Associate Professor, Astrakhan State Medical University, Baku str., House 121, Astrakhan, Russia, 414000 Nina A. Zinchuk - Candidate of Pedagogical Sciences, Associate Professor Alevtina P. Yaroshinskaya - doctor of biological Sciences
