Physiological Profiles of Recreational Runners and Cyclists Aged 20 to 60 Years
Faculty of Physical Education and Sport, Charles University, 162 52 Prague, Czech Republic
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(7), 3252; https://doi.org/10.3390/app12073252
Submission received: 21 February 2022
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Revised: 15 March 2022
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Accepted: 21 March 2022
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Published: 23 March 2022
(This article belongs to the Special Issue Sport Activity for Health Improvement and as an Injury Prevention Tool)
Abstract
:Featured Application
The study of men and women in middle and older middle age engaged in recreational cycling and running yielded data on the effects of these physical activities and showed an association between the physical activity, body composition, maximum oxygen consumption and maximum performance capacity during aging.
Abstract
Human physical activities may bring potential health benefits. The aim of our study was to compare body composition, lung function and aerobic fitness as a function of age in a cross-sectional study of 277 recreational cyclists (men: n = 163, women: n = 114) and 377 recreational runners (men: n = 239, women: n = 138) aged 20 to 60 years, with a training volume of about 2000 to 4000 km per year for cyclists and 25 to 60 km per week for runners. The survey focused on comparing the values of body composition, lung function and aerobic fitness in dependence on age. The results suggest that recreational cycling and running is associated with a favorable body composition and increased physical fitness, where the percentage of body fat in athletes corresponds to about 70–90% of the population norm, while physical fitness indices, maximum oxygen consumption and maximum exercise performance corresponded at about 140 to 150% of the population norms. The study confirms the assumption that the decrease in physiological functions and/or physical condition with age is much slower in those who participate in recreational sports than in the general nonsports population.
1. Introduction
Regular recreational cycling and recreational running can reduce the risk of cardiovascular and metabolic diseases and can contribute to maintaining good mental and biological health [1,2]. Recently, road, but especially trekking and mountain biking, has become a popular leisure activity for men and women of all ages.
Recreational running is mostly done by individuals, but recreational cycling is done by families, even extended families of several generations or informal groups of friends and acquaintances, where the intention of running is not oriented toward sports performances, but rather toward psychorelaxation. In contrast, creating or strengthening social ties is often the intention in joint cycling [3]. Recreational cycling with its bio-psycho-social dimensions is one of the current elements of an active lifestyle [4], and in different European countries it follows different historical and cultural traditions and different socioeconomic conditions [5].
In adolescents and young adults, there is strong evidence for improved cardiorespiratory endurance and muscular fitness, favorable body composition, bone health and improved cardiovascular and metabolic health biomarkers with physical activity and training [6]. In older adults, however, it still remains unclear to what extent recreational physical activities such as running and cycling may affect or slow physiological changes with increasing age. From these age-related changes, a decrease of fat-free mass, lung function and decreased work capacity are frequently discussed [7,8]. The extent to which a physically active individual can maintain high functional potential during aging remains a matter of considerable importance [9]. There is insufficient convincing evidence in the literature on the extent to which recreational running and cycling can affect an individual’s functional capacity from youth to old age [10]. There is also relatively little data on the health benefits and physiological effects of recreational cycling and running when comparing different age groups of men and women [3]. The aim of our study was therefore to compare body composition, lung function and aerobic fitness as a function of age in a cross-sectional study of 277 recreational cyclists (men: n = 163, women: n = 114) and 377 recreational runners (men: n = 239, women: n = 138) aged 20 to 60 years.
2. Materials and Methods
The research group consisted of a total of 654 recreational sports people, of which 402 were men and 252 were women aged 20 to 60 years, with a training volume of about 2000 to 4000 km per year for cyclists and 3 to 6 h of running per week in runners which corresponded to 25 to 60 km per week. These recreational athletes were selected from a wider range of people examined over the last few years in the biomedical laboratory, Faculty of Physical Education and Sport, Charles University. Subjects were eligible if they met all of the following inclusion criteria: (1) adhered to the regular recreational activities for at least three years, (2) provided written informed consent before being involved to the study, (3) were over 20 years of age. Subjects were excluded if they: (1) were beginners or adhered to the regular recreational activities less than three years, (2) were high performance cyclists or runners, i.e., organized in sports clubs and results-oriented in sports competitions, (3) had acute or chronic health problems that may alter their adherence to regular cycling or running. All the recreational athletes were examined at the end of the preparation period before the main cycling and/or running season. The average duration of training practice for the monitored recreational athletes was five years.
This study was approved by the ethics committee of the Faculty of Physical Education and Sport, Charles University (reference number 126/2015) and measurements were performed according to the ethical standards of the Helsinki Declaration. The subjects were fully informed in advance regarding the objectives of the study, the study methods involved no risks, and written informed consent was obtained from each subject for participation in this study.
All measurements were taken at the beginning of the preparatory season in October and November. During the preseason, subelite athletes had been training three sessions a week, 2.0 h per session on average. Body height (cm) was measured by digital Stadiometer Seca 242 (Vogel & Halke, Hamburg, Germany) to the nearest 0.1 cm. Body weight was measured on a digital scale to the nearest 0.1 kg, and body mass index (BMI, in kg/m2) was calculated. The percentage of body fat and the amount of fat-free mass was determined on the basis of measurements of 10 skinfolds [11]. Spirometric parameters, i.e., forced vital capacity (FVC), one-second forced expiratory flow (FEV1) and peak expiratory flow (PEF) were determined by the Pony Graphic spirometric system (Cosmed srl., Italy), and the results were expressed as absolute values and as a percentage of predicted values (% pred.) using European standards [12]. In cyclists, maximum oxygen consumption was determined by a graded maximum test on a bicycle ergometer. All the subjects were instructed to eat a light breakfast at least 3 h before the stress test. They were also instructed not to drink tea or coffee on the day of testing and to limit their drinking regimen prior to testing. The test itself was preceded by two four-minute submaximal loads (1.5 and 2.5 W/kg of body mass). Then, starting with the load at the PWC (physical work capacity) 170 level, the load was increased by 20 W each minute up to “vita maxima”. The PWC 170 value was determined by linear regression, which was part of software developed for stress test control and data processing. In runners, the maximum oxygen consumption was determined by a graded maximum test on a treadmill with 5% inclination [13]. Warming-up of the subjects was performed on a treadmill with 0% inclination for 4 min at speed 11.0 and 13.0 km/h. The initial testing speed of 13.0 km/h was increased every minute by 1.0 km/h until voluntary exhaustion. Respiratory parameters and respiratory gas exchange were measured in an open system (Servomex 1440, Crowborough, Sussex, UK). Heart rate was continuously monitored by short-range telemetry (Sport-Tester PE 4000, Polar Electro, Kempele, Finland).
The decisive criterion for VO2max was the achievement of a plateau in VO2 values, and the maximum values were of the four highest consecutive 15-s oxygen consumption values. A plateau in VO2 was defined as any two 30-s VO2 values in which the second was not higher that the first, provided an increase in ventilation at maximal effort. In addition, standard criteria of maximum physiologic effort as RER values > 1.00, 85% to 100% of the age-predicted HRmax and a Borg scale6–20 rating ≥ 17 RPEmax and ≥ 8 mmol/L for maximum blood lactate were also used [14].
Maximum blood lactate concentration was determined electrochemically with a Biovendor Super GL apparatus. Capillary blood samples (20 µL) were collected at the third minute of recovery after maximum exercise [15,16] and were diluted with systemic solution (1 mL) immediately after collection to ensure hemolysis and stabilization. The samples were subsequently analyzed by a biosensor using the amperometric principle [17]. Before each measurement, the analyzer was calibrated with a 12 mmol/L.
The results for recreational cyclists and runners were organized into four age groups, 20 to 29.9, 30 to 39.9, 40 to 49.9 and 50 to 60 years of age, separately for men and women. The basic anthropometric values were compared with the Czech population norms [18], and the results of the stress examination were compared with the national reference values according to the International Biological Program IBP [19], which are, despite having originated in 1968–1974, considered still valid and usable [20,21].
Data Analysis: Basic descriptive statistics (mean, standard deviation) were computed for all variables, which were subsequently tested for normality using Shapiro-Wilk tests. Differences between physical and physiological variables in recreational cyclists and runners were evaluated by an index of effect size—ES (Cohen’s “d”). The effect size (ES) was assessed as follows: ES < 0.20 as small effect; ES from 0.2 to 0.8 as medium effect and ES > 0.80 as large effect. Statistical analyses were performed using Microsoft Excel (2010), SPSS version 22 (SPSS Inc., Chicago, IL, USA). Power analysis for parameters were analyzed in separate age groups, the sample size at effect size 0.78 and power 0.80 around n = 40 to 50. Thus, the comparisons at the highest age groups (50 to 60 years) both in males and females did not correspond to the desired or satisfactory sample size needed to reject the null hypothesis. This fact is also mentioned in the limitations of the study.
3. Results
3.1. Results in Male Runners and Cyclists
A comparison of body mass, height, body mass index (BMI), body fat and fat-free-mass (FFM) in male recreational cyclists and runners is presented in Table 1. Values of body mass in cyclists were substantially higher (medium to large effect) than in runners, values of body height, however, were comparable in both groups of male recreational athletes. The values of BMI were comparable in younger cyclist and runners (up to 39.9 years), but in both older groups, BMI values in cyclists were substantially higher than in runners (large effect). Percentage of body fat in younger groups of athletes (up to 49.9 years) was similar. In the oldest group (50 to 60 years), however, the percentage of body fat in cyclists was higher than in runners (large effect). The values of FFM in all the age groups were slightly higher in cyclists than in runners.
Pulmonary function indices in male recreational cyclists and runners (Table 2) documented similar values of forced vital capacity and peak expiratory flow values in both groups of athletes (small to medium effect). The FEV1 values, however, were substantially higher in runners than in cyclists (large effect) in three older age groups. The values of VO2max in all age groups were slightly higher in male runners than in cyclists (medium to large effect). Maximum power output on a cycle ergometer (W/kg) and maximum running speed (km/h, at a slope 5% on a treadmill) slightly declined with age. The maximum values of blood lactate concentration were not substantially different in cyclists and in runners (small to medium effect).
3.2. Results in Female Runners and Cyclists
A comparison of body mass, height, body mass index (BMI), body fat and fat-free-mass (FFM) in female recreational cyclists and runners is presented in Table 3. Values of body mass, BMI and body fat in female cyclists were slightly higher (medium effect) than in runners. Values of body height, however, were slightly higher in female runners than in cyclists. The values of FFM in all the age groups of female recreational athletes were comparable in cyclists and in runners.
In female recreational athletes, the pulmonary function indices (FVC, FEV1 and PEF) were similar for cyclists and runners (Table 4). However, FEV1 values were higher in runners than in cyclists aged 40 to 49.9 years, and PEF values were higher in runners than in cyclists aged 50 to 60 years (large effect). The values of VO2max in all age groups of female athletes were higher in runners than in cyclists (large effect). Maximum power output on a cycle ergometer (W/kg) and maximum running speed (km/h, at a slope 5% on a treadmill) slightly declined with age. The maximum values of blood lactate concentration were not substantially different in female cyclists and runners (small to medium effect).
4. Discussion
The results of this study show that the values of body weight and body height in recreational athletes are comparable in all age groups with the values in the average Czech population [18,19], while cyclists and especially runners have a lower percentage of body fat from adolescence to the sixth decade than in the average population (12.5 to 16.7% in males and 19.5 to 24.1 in females). In general, the percentage of body fat in recreational athletes corresponded to about 70–90% of the population norm. The differences in body composition in cyclists and runners can be partially attributed to the findings that fat oxidation is significantly higher during running than during cycling at the same relative intensities [22]. The amount of fat-freemass in male cyclists was slightly higher, but in runners it was quite comparable with the average Czech male population—65 to 67 kg [18,19]. In female cyclists and runners, the values of fat-free mass were slightly higher than in the average Czech population—48 to 52 kg [18,19]. BMI values in male recreational cyclists were not different from the values of the average Czech population—23.5 to 26.1 kg/m2 [16], but the values in male runners tended to be lower. BMI values in female cyclists and runners were lower than in the average Czech female population—21.7 to 26.2 kg/m2 [18]. The values of BMI found in this study were, however, higher than in physically active male and female populations aged 19 to 70 years (22 to 23 kg/m2 and 21 to 22 kg/m2 in males and females, respectively [18]. The results of this study indicate that BMI values, especially in male recreational athletes increased with age, but this increase corresponded partly to an increase in the amount of fat-free mass rather than body fat, and the recorded increased BMI (above the stated limit of 25 kg/m2) may not be interpreted as so-called overweight [1].
Pulmonary function in the general population decreases with age [9], which is attributed to a decrease in lung tissue elasticity and an increase in chest wall stiffness. With a decrease in respiratory function with increasing age, it is thought that a higher incidence of respiratory distress during exercise may limit exercise tolerance as well as physical activity [7]. The results of this study show that in recreational physically active men and women, lung function is maintained, in general, at an adequate level, but the indices of pulmonary function may be affected by sports activity, i.e., different pulmonary demands and ventilatory patterns in running and cycling [22]. Test subjects appeared to breath at a higher lung volume during maximal exercise, while cycling was lower compared to running. It is possible that posture during exercise is responsible for this difference as hip flexion may force the diaphragm further up into the thoracic cavity [22]. On the other hand, it is worth recalling the well-known fact that maintaining an aerodynamic cycling position can limit lung ventilation [23], especially for untrained or less trained individuals [24].
As can be expected, the values of maximum oxygen consumption and maximum exercise performance decrease slightly from the third to the sixth decade similarly in male and female recreational athletes. The values of VO2max in runners in all the age groups were higher in runners than in cyclists which may be partly due to a different way of testing, in cyclists using cycle ergometry and in runners using treadmill ergometry. The sitting position during cycle ergometry involves less muscle mass than in running on a treadmill; therefore, the values of VO2max are lower than in running [25]. The differences may also be caused by differences in body composition and body mass in cyclist and runners. It is also worth mentioning comparative studies where running intervention programs were more effective than other types of exercise in a middle-aged population [6]. In general, the values found in recreational runners and cyclists exhibit a slight but permanent decrease in maximum oxygen consumption and maximum exercise performance. However, their values in all age groups are considerably higher (corresponding to 140 to 150%) than in the general nonsporting population [18,19,20,21]. A physiological decrease of these values with increasing age was smaller than in the general population. This decline can be offset by better labor economics [25]; older athletes generally have a higher percentage of VO2max corresponding to the anaerobic threshold than younger athletes. Absolute heart rate values corresponding to the anaerobic threshold also decrease with age, but the anaerobic threshold expressed as a percentage of the maximum heart rate tends to be similar at younger and older ages. A decrease in heart rate at standard, r. submaximal and maximum respiration load in the elderly is usually compensated for by an increase in systolic volume and by improving end-diastolic volume filling rates [25]. Similarly, the results of other studies in middle-aged and older athletes [7,10] document that the decrease in absolute values of work capacity due to increasing age can be compensated for by a number of physiological mechanisms that can maintain working capacity even in old age.
Regarding sex differences, VO2max values for female cyclists of the three younger age categories corresponded to approximately 81 to 84% of those of male cyclists, but in the highest age category, VO2max values for female cyclists corresponded to 97% of their male counterparts. Similarly, values of maximum power output and maximum blood lactate in female cyclists of the three younger age categories corresponded to approximately 78 to 83% and 86 to 91% those of male cyclists, respectively. In the highest age category, the values of maximum power output and maximum blood lactate in female cyclists corresponded to 98% and 96% of their male counterparts, respectively. VO2max values in female runners across all the age categories corresponded to approximately 90 to 99% those of male runners. The values of maximum power output and maximum blood lactate in female runners corresponded to 85 to 90% and 81 to 101% of their male counterparts, respectively. In the adult population, it is well established that physical activity participation decreases significantly as age increases, and motivation for physical activity may also vary with age [26]. One possible explanation for the above findings in female cyclists may be the assumption that recreational female cyclists over the age of 50 may attain different adherence and motivation for regular training and health outcomes than women of younger age categories [27].
Study limitations: This study is not without limitations. First, this was a cross-sectional study; therefore, longitudinal studies are needed to elucidate the long-term effect of regular physical activity on physiological variables. Second, exact data on physical exercise volume, frequency and intensity were not assessed as this would require complex monitoring of all relevant data over a longer period of time. Third, as mentioned in the Methods discussion, the number of participants in the highest age category was considerably limited, which may reduce the credibility of comparisons between cyclists and runners in the highest age category. Nevertheless, we believe that these limitations do not prevent the main conclusions from being drawn from the study.
5. Conclusions
The results of a cross-sectional study of men and women engaged in recreational cycling and running showed an association between these physical activities and favorable body composition, higher maximum oxygen consumption and maximum exercise performance from the third to the sixth decade. However, recreational cycling and running did not present the same at all levels of lung functions (FVC, FEV1 and PEF). The results suggest that recreational running in the third to sixth decades of life can be associated with improvements of FEV1. These results, of course, cannot be understood as a simplified causal relationship because the favorable health condition and good functional preconditions of the individual primarily allow performing the recreational physical activity and only secondarily can it be assumed that the event can be properly maintained due to physical activity. A cross-sectional study confirms that the decrease in the values of physiological functions with respect to physical condition with age is much slower in recreational sports than in the general nonsports population. It can be stated that recreational running and cycling at middle and older middle age is accompanied by favorable changes in body composition as well as above-average maximum exercise performance and high aerobic capacity.
Author Contributions
Conceptualization, J.H. and P.V.; methodology, J.H.; software, P.V.; validation, J.H. and P.V.; formal analysis, J.H.; investigation, J.H., P.V., I.K. and T.M.; resources, J.H.; data curation, J.H.; writing—original draft preparation, J.H.; writing—review and editing, J.H.; visualization, J.H.; supervision, J.H.; project administration, J.H.; funding acquisition, J.H. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by Charles University in Prague (Progress Q41/FTVS).
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Ethics Committee of the Ethics Committee of the Faculty of Physical Education and Sport, Charles University (reference number 126/2015, on 17 September 2015).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.
Conflicts of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
References
- Blair, S.N.; La Monte, M.J.; Nichaman, M.Z. The evolution of physical activity recommendations: How much is enough? Am. J. Clin. Nutr. 2004, 79, 913S–920S. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Carnall, D. Cycling and health promotion: A safer, slower urban road environment is the key. Brit. Med. J. 2000, 320, 888. [Google Scholar] [CrossRef] [PubMed]
- Oja, P.; Titze, S.; Bauman, A.; De Geus, B.; Krenn, P.; Reger-Nash, B.; Kohlberger, T. Health benefits of cycling: A systematic review. Scand. J. Med. Sci. Sports 2011, 21, 496–509. [Google Scholar] [CrossRef] [PubMed]
- Bunc, V. A movement intervention as a tool of the influence of physical fitness and health. Trends Sport Sci. 2018, 25, 209–216. [Google Scholar] [CrossRef]
- Pulcher, J.; Dijkstra, L. Promoting safe walking and cycling to improve public health: Lessons from the Netherlands and Germany. Am. J. Public Health 2003, 93, 1509–1516. [Google Scholar] [CrossRef]
- Bize, R.; Johnson, J.A.; Plotnikoff, R.C. Physical activity level and health-related quality of life in the general adult population: A systematic review. Prev. Med. 2007, 45, 401–415. [Google Scholar] [CrossRef]
- Hollmann, W.; Heiko, K.; Strüder, H.K.; Tagarakis, C.V.M.; King, G. Physical activity and the elderly. Eur. J. Cardiovasc. Prev. Rehabil. 2007, 14, 730–739. [Google Scholar] [CrossRef]
- Ruiz-Montero, P.J.; Castillo-Rodríguez, A. Body composition, physical fitness and exercise activities of elderly. J. Phys. Educ. Sport 2016, 16, 860–865. [Google Scholar] [CrossRef]
- Awais, M.; Chiari, L.; Ihlen EA, F.; Helbostad, J.L.; Palmerini, L. Physical activity classification for elderly people in free-living conditions. IEEE J. Biomed. Health Inform. 2018, 23, 197–207. [Google Scholar] [CrossRef]
- Andersen, L.B.; Schnohr, P.; Schroll, M.; Hein, H.O. All-cause cyclists mortality associated with physical activity during leisure time, work, sports, and cycling to Work. Arch. Intern. Med. 2000, 160, 1621–1628. [Google Scholar] [CrossRef]
- Eston, R.; Reilly, T. Kinanthropometry and Exercise Physiology Laboratory Manual, Volume 1: Anthropometry, Tests, Procedures and Data, 2nd ed.; Routledge: London, UK, 2001. [Google Scholar]
- Quanjer, P.H.; Tammeling, G.J.; Cotes, J.E.; Pedersen, O.F.; Peslin, R.; Yernault, J.C. Lung volumes and forced ventilatory flows. Report Working Party Standardization of Lung Function Tests, European Community for Steel and Coal. Official Statement of the European Respiratory Society. Eur. Respir. J. 1993, 6 (Suppl. S16), 5–40. [Google Scholar] [CrossRef] [PubMed]
- Bunc, V.; Heller, J.; Moravec, P.; Sprynarova, S. Ventilatory threshold and mechanical efficiency in endurance athletes. Eur. J. Appl. Physiol. 1989, 58, 693–698. [Google Scholar] [CrossRef] [PubMed]
- Edvardsen, E.; Hem, E.; Anderssen, S.A. End criteria for reaching maximal oxygen uptake must be strict and adjusted to sex and age: A cross-sectional study. PLoS ONE 2014, 9, e85276. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Janssen, P. Lactate Threshold Training; Elsevier: Amsterdam, The Netherlands, 2001. [Google Scholar]
- Shephard, R.J. Anaerobic Metabolism and Endurance Performance; Blackwell Science: Oxford, UK, 2000. [Google Scholar]
- Davidson, R.C.R.; Coleman, D.; Balmer, J.; Nunn, M.; Theakston, S.; Burrows, M.; Bird, S. Assessment of blood lactate: Practical evaluation of the Biosen 5030 lactate analyzer. Med. Sci. Sports Exerc. 2000, 32, 243–247. [Google Scholar] [CrossRef]
- Blaha, P.; Sedivy, V.; Cechovsky, K.; Kosova, A. Anthropometric Studies of the Czechoslovak Population from 6 to 55 Years, Volume I: Part 2; CSTV-UNZ VS: Prague, Czech Republic, 1986. [Google Scholar]
- Seliger, V.; Bartunek, Z. Mean Values of Various Indices of Physical Fitness in the Investigation of Czechoslovak Population Aged 12–55 Years; CSTV: Prague, Czech Republic, 1976; pp. 41–58. [Google Scholar]
- Macek, M.; Mackova, J. The values obtained in the International Biological Program between 1968 and 1974—Could be still applied today? Med. Sport. Bohem. Slovaca 1996, 5, 1–3. [Google Scholar]
- Novak, J.; Votik, J.; Stork, M.; Zeman, V. Czechoslovak physical fitness standards in 1976 compared to recent sporting and non-sporting population. Studia Kinanthropol. 2019, 20, 67–76. [Google Scholar] [CrossRef]
- Tanner, D.A.; Duke, J.W.; Stager, J.M. Ventilatory patterns differ between maximal running and cycling. Respir. Physiol. Neurobiol. 2014, 191, 9–16. [Google Scholar] [CrossRef]
- Dillon, H.T.; Dausin, C.; Claessen, G.; Lindqvist, A.; Mitchell, A.; Wright, L.; Willems, R.; la Gerche, A.; Howden, E.J. The effect of posture on maximal oxygen uptake in active healthy individuals. Eur. J. Appl. Physiol. 2021, 121, 1487–1498. [Google Scholar] [CrossRef]
- Ashe, M.C.; Scroop, G.C.; Frisken, P.I.; Amery, C.A.; Wilkins, M.A.; Khan, K.M. Body position affects performance in untrained cyclists. Br. J. Sports Med. 2003, 37, 441–444. [Google Scholar] [CrossRef] [Green Version]
- Kist, D.A.; Laws, R.; Burgess, K.; Rizvi, H.; Glasheen, M.E.; Dellwo, T. Comparison of sitting and sitting to standing cycle ergometry versus treadmill, on cardiorespiratory values in adult males and females. JEP Online 2013, 16, 95–114. [Google Scholar]
- Trujillo, K.; Brougham, R.; Walsh, D. Age differences in reasons for exercising. Curr. Psychol. 2004, 22, 348–367. [Google Scholar] [CrossRef]
- Molanorouzi, K.; Khoo, S.; Morris, T. Motives for adult participation in physical activity: Type of activity, age, and gender. BMC Public Health 2015, 15, 66. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table 1.
Physical characteristics and body composition in male recreational cyclists (C) and runners (R).
Table 1.
Physical characteristics and body composition in male recreational cyclists (C) and runners (R).
| Age Group [Years] | Age [Years] | Mass [kg] | Height [cm] | BMI [kg/m2] | Body Fat [%] | FFM [kg] |
|---|---|---|---|---|---|---|
| 20–29.9 | ||||||
| C (n = 42) | 25.8 (3.1) | 82.4 (12.8) | 185.3 (6.4) | 24.0 (2.5) | 11.5 (4.2) | 72.6 (8.6) |
| R (n = 50) | 26.6 (2.2) | 76.7 (8.8) | 181.8 (6.0) | 23.2 (2.3) | 11.9 (4.0) | 67.4 (6.8) |
| d-value | 0.302 | 0.528 | 0.566 | 0.334 | 0.098 | 0.678 |
| Effect size | medium | medium | medium | medium | small | medium |
| 30–39.9 | ||||||
| C (n = 40) | 35.0 (2.8) | 84.8 (11.0) | 183.2 (6.2) | 25.2 (2.6) | 14.5 (4.4) | 72.2 (7.1) |
| R (n = 94) | 35.0 (2.8) | 81.6 (9.8) | 181.2 (6.2) | 24.8 (2.2) | 14.6 (4.4) | 69.6 (7.9) |
| d-value | 0.007 | 0.315 | 0.323 | 0.172 | 0.023 | 0.339 |
| Effect size | small | medium | medium | small | small | medium |
| 40–49.9 | ||||||
| C (n = 41) | 44.6 (2.6) | 86.6 (9.9) | 180.9 (5.9) | 26.5 (2.5) | 15.9 (4.0) | 72.6 (6.5) |
| R (n = 63) | 43.8 (3.0) | 83.6 (10.7) | 182.6 (7.5) | 25.0 (2.2) | 15.5 (4.5) | 70.9 (7.3) |
| d-value | 0.281 | 0.289 | 0.246 | 0.646 | 0.093 | 0.243 |
| Effect size | medium | medium | medium | medium | small | medium |
| 50–60 | ||||||
| C (n = 28) | 55.1 (2.6) | 84.7 (9.6) | 180.1 (6.6) | 26.1 (2.8) | 16.3 (4.6) | 70.8 (7.2) |
| R (n = 20) | 55.3 (3.2) | 76.6 (6.1) | 179.9 (6.7) | 23.7 (2.0) | 12.4 (3.4) | 67.1 (5.2) |
| d-value | 0.07 | 0.972 | 0.03 | 0.96 | 0.941 | 0.574 |
| Effect size | small | large | small | large | large | medium |
Table 2.
Pulmonary function (FVC forced vital capacity; FEV1 forced expiratory volume in 1 s; PEF peak expiratory flow) and performance characteristics in male recreational cyclists (C) and runners (R).
Table 2.
Pulmonary function (FVC forced vital capacity; FEV1 forced expiratory volume in 1 s; PEF peak expiratory flow) and performance characteristics in male recreational cyclists (C) and runners (R).
| Age Group [Years] | FVC [% Pred.] | FEV1 [% Pred.] | PEF [% Pred.] | VO2max [mL/kg/min] | Power Output a | LAmax [mmol/L] |
|---|---|---|---|---|---|---|
| 20–29.9 | ||||||
| C (n = 42) | 94.3 (10.9) | 100.3 (11.0) | 91.4 (18.4) | 53.7 (7.2) | 4.26 (0.58) | 12.1 (2.2) |
| R (n = 50) | 91.7 (17.0) | 100.6 (10.4) | 94.9 (16.5) | 58.1 (4.8) | 15.4 (1.4) | 11.9 (2.5) |
| d-value | 0.182 | 0.028 | 0.2 | 0.719 | - | 0.085 |
| Effect size | small | small | medium | medium | - | small |
| 30–39.9 | ||||||
| C (n = 40) | 99.2 (12.7) | 84.8 (11.0) | 99.4 (15.6) | 52.7 (6.3) | 4.14 (0.49) | 11.7 (2.3) |
| R (n = 94) | 93.9 (11.1) | 102.6 (12.3) | 96.3 (17.8) | 55.4 (5.7) | 14.9 (1.1) | 11.6 (2.5) |
| d-value | 0.444 | 1.526 | 0.185 | 0.449 | - | 0.042 |
| Effect size | medium | large | small | medium | - | small |
| 40–49.9 | ||||||
| C (n = 41) | 98.0 (16.4) | 86.6 (9.9) | 107.6 (15.9) | 49.9 (5.8) | 3.95 (0.49) | 11.5 (2.4) |
| R (n = 63) | 97.7 (10.8) | 104.6 (12.0) | 101.1 (17.4) | 52.2 (6.4) | 14.7 (1.2) | 9.8 (2.5) |
| d-value | 0.022 | 1.636 | 0.39 | 0.377 | - | 0.238 |
| Effect size | small | large | medium | medium | - | medium |
| 50–60 | ||||||
| C (n = 28) | 96.1 (12.8) | 84.7 (9.6) | 103.3 (14.7) | 42.2 (8.8) | 3.32 (0.72) | 10.7 (2.4) |
| R (n = 20) | 97.0 (12.2) | 104.2 (15.2) | 96.2 (16.4) | 48.5 (3.4) | 13.8 (1.1) | 10.4 (2.8) |
| d-value | 0.072 | 1.534 | 0.456 | 0.944 | - | 0.115 |
| Effect size | small | large | medium | large | - | small |
a power output: maximum power output in cyclists in W/kg (top row); maximum power output on a treadmill is expressed as maximum running speed km/h on a treadmill with inclination 5%.
Table 3.
Physical characteristics and body composition in female recreational cyclists (C) and runners (R).
Table 3.
Physical characteristics and body composition in female recreational cyclists (C) and runners (R).
| Age Group [Years] | Age [Years] | Mass [kg] | Height [cm] | BMI [kg/m2] | Body Fat [%] | FFM [kg] |
|---|---|---|---|---|---|---|
| 20–29.9 | ||||||
| C (n = 35) | 25.6 (2.9) | 62.6 (8.7) | 166.5 (6.4) | 22.4 (3.1) | 16.4 (5.0) | 51.7 (6.0) |
| R (n = 36) | 26.9 (2.4) | 59.7 (6.4) | 168.0 (6.0) | 21.1 (1.6) | 13.5 (4.0) | 51.5 (4.8) |
| d-value | 0.488 | 0.38 | 0.242 | 0.527 | 0.641 | 0.037 |
| Effect size | medium | medium | medium | medium | medium | small |
| 30–39.9 | ||||||
| C (n = 35) | 34.7 (2.8) | 64.1 (9.8) | 168.2 (7.2) | 22.6 (2.3) | 16.1 (6.9) | 53.3 (5.7) |
| R (n = 43) | 34.1 (2.9) | 62.4 (5.6) | 170.4 (5.6) | 21.5 (1.9) | 12.9 (5.5) | 54.1 (3.7) |
| d-value | 0.21 | 0.213 | 0.341 | 0.521 | 0.513 | 0.166 |
| Effect size | medium | medium | medium | medium | medium | small |
| 40–49.9 | ||||||
| C (n = 23) | 44.4 (3.1) | 64.1 (7.6) | 165.5 (4.0) | 23.4 (2.8) | 16.2 (6.4) | 53.4 (4.4) |
| R (n = 29) | 44.2 (2.9) | 62.9 (7.3) | 167.1 (3.2) | 22.5 (2.3) | 14.2 (5.6) | 52.8 (7.1) |
| d-value | 0.067 | 0.161 | 0.442 | 0.351 | 0.333 | 0.102 |
| Effect size | small | small | medium | medium | medium | small |
| 50–60 | ||||||
| C (n = 21) | 55.5 (4.2) | 61.2 (9.6) | 161.5 (4.3) | 23.1 (3.3) | 14.6 (5.3) | 51.3 (5.2) |
| R (n = 18) | 54.5 (2.9) | 55.5 (3.7) | 163.3 (1.7) | 20.8 (1.6) | 12.2 (4.5) | 48.7 (2.7) |
| d-value | 0.277 | 0.784 | 0.551 | 0.887 | 0.488 | 0.628 |
| Effect size | medium | medium | medium | large | medium | medium |
Table 4.
Pulmonary function (FVC forced vital capacity; FEV1. forced expiratory volume in 1 s; PEF peak expiratory flow) and performance characteristics in female recreational cyclists (C) and runners (R).
Table 4.
Pulmonary function (FVC forced vital capacity; FEV1. forced expiratory volume in 1 s; PEF peak expiratory flow) and performance characteristics in female recreational cyclists (C) and runners (R).
| Age Group [Years] | FVC [% Pred.] | FEV1 [% Pred.] | PEF [% Pred.] | VO2max [mL/kg/min] | Power Output a | LAmax [mmol/L] |
|---|---|---|---|---|---|---|
| 20–29.9 | ||||||
| C (n = 35) | 90.2 (12.8) | 94.6 (10.8) | 89.9 (18.4) | 44.5 (5.6) | 3.33 (0.65) | 10.9 (2.2) |
| R (n = 36) | 85.4 (11.1) | 94.4 (9.6) | 90.8 (17.9) | 51.0 (5.4) | 13.3 (1.2) | 9.6 (2.2) |
| d-value | 0.401 | 0.215 | 0.049 | 7.162 | - | 0.591 |
| Effect size | medium | medium | small | large | - | medium |
| 30–39.9 | ||||||
| C (n = 35) | 95.3 (12.2) | 102.8 (13.3) | 101.1 (20.6) | 42.6 (6.5) | 3.43 (0.58) | 10.6 (2.0) |
| R (n = 43) | 95.9 (14.2) | 99.9 (11.9) | 93.4 (12.1) | 49.6 (5.2) | 13.2 (1.0) | 10.5 (2.2) |
| d-value | 0.044 | 0.23 | 0.456 | 1.189 | - | 0.048 |
| Effect size | small | medium | medium | large | - | small |
| 40–49.9 | ||||||
| C (n = 23) | 103.2 (12.2) | 101.4 (10.6) | 98.4 (10.9) | 42.1 (6.7) | 3.22 (0.76) | 9.9 (2.0) |
| R (n = 29) | 103.6 (11.7) | 109.7 (9.2) | 103.7 (12.8) | 48.7 (4.2) | 13.2 (1.2) | 9.9 (1.6) |
| d-value | 0.033 | 0.836 | 0.446 | 1.18 | - | 0 |
| Effect size | small | large | medium | large | - | small |
| 50–60 | ||||||
| C (n = 21) | 90.3 (12.6) | 97.9 (9.6) | 89.3 (10.7) | 40.9 (8.4) | 3.24 (0.40) | 10.3 (1.5) |
| R (n = 18) | 95.7 (12.5) | 97.9 (12.2) | 105.2 (14.8) | 48.2 (4.5) | 11.7 (0.8) | 9.0 (2.2) |
| d-value | 0.43 | 0 | 1.231 | 1.083 | - | 0.69 |
| Effect size | medium | small | large | large | - | medium |
a power output: maximum power output in cyclists in W/kg (top row), maximum power output on a treadmill is expressed as maximum running speed km/h on a treadmill with inclination 5%.
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Heller, J.; Kinkorova, I.; Vodicka, P.; Mika, T. Physiological Profiles of Recreational Runners and Cyclists Aged 20 to 60 Years. Appl. Sci. 2022, 12, 3252. https://doi.org/10.3390/app12073252
AMA Style
Heller J, Kinkorova I, Vodicka P, Mika T. Physiological Profiles of Recreational Runners and Cyclists Aged 20 to 60 Years. Applied Sciences. 2022; 12(7):3252. https://doi.org/10.3390/app12073252
Chicago/Turabian StyleHeller, Jan, Ivana Kinkorova, Pavel Vodicka, and Tomas Mika. 2022. "Physiological Profiles of Recreational Runners and Cyclists Aged 20 to 60 Years" Applied Sciences 12, no. 7: 3252. https://doi.org/10.3390/app12073252
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