Relationship between motor abilities, physical activity, and cardiorespiratory endurance
Ivana Nikolić, Snježana Mraković, Tomislav Hublin1 Sveučilište u Zagrebu Učiteljski fakultet 2 The Polytechnic of Međimurje |
|
Kineziološka paradigma odgoja i obrazovanja |
Original scientific paper |
Abstract |
|
Cardiorespiratory fitness is a dimension of physical health associated with physical activity in a way that leads to many health benefits. The aim of this research was to determine the relationship between motor skills, physical activity (PA), and cardiorespiratory fitness (CRF). The sample consisted of 129 female students enrolled at the Faculty of Teacher Education, University of Zagreb - Department in Čakovec, with an average age of 21±0.12 years. The predictor set consisted of a variable body mass index (BMI), 7 Eurofit tests to assess motor abilities and three indices of PA of the Baecke questionnaire (sports, leisure and faculty index). The criterion variable for assessing CRF was the Beep test. The results were calculated by the regression stepwise method. Pearson's correlation coefficients between CRF and motor abilities, BMI, and physical activity index showed low to moderate correlations. Cardiorespiratory endurance significantly correlates negatively with the BMI, and positively with the sports and leisure time index and variables for assessing muscular endurance, agility, trunk strength and explosive leg power. However, regression analysis showed that significant predictors in explaining the variance in CRF were the variables bent arm hang (BETA=.20; p=.031), standing broad jump (BETA=.19; p=.043), sports index (BETA=.19; p=.020 and 10x5 m shuttle run test (BETA=-.17; p=.039) which explained 27% of the variance of the criterion variable. This research provides evidence that CRF is generally associated with BMI, TA in sports and leisure time, and motor abilities of energy regulation in female students. However, bent arm hang, standing broad jump, sports index and 10x5 m shuttle run were considered the most important predictors of cardiorespiratory endurance. |
|
Keywords |
|
cardiorespiratory endurance; motor abilities; physical activity |
Introduction
Physical activity (PA) is any body movement made by skeletal muscles and involves energy expenditure, while cardiorespiratory fitness (CRF) is a property and is also defined as the ability of the vascular, respiratory, and muscular systems to supply oxygen during prolonged moderate or vigorous dynamic exercise (Zeiher, Ombrellaro, Perumal, & Neil, 2019). Regular physical activity, high levels of cardiorespiratory capacity, and maintaining a normal weight are known to strongly contribute to positive health outcomes. It is also known that moderate and high intensity physical activity is an important means of maintaining adequate cardiorespiratory capacity and normal body weight (Tammelin, 2013). Cardiorespiratory fitness is a dimension of physical health associated with physical activity in a way that leads to healthy benefits such as prevention of various diseases such as cardiovascular disease, lung, osteoporosis, colon cancer, high cholesterol, high blood pressure, and prevention of obesity, anxiety, and depression (Laukkanen et al., 2001). Na et al. (2019) state that frequency, i.e., daily aerobic physical activity, has a more significant role in relation to maximum oxygen intake (VO2max) in the prevention of cardiovascular diseases and alleviation of aortic stiffness in people with hypertension. There are a number of cross-sectional studies showing that low CRF in youth is associated with a higher cardiometabolic risk, including higher fasting glucose, abdominal obesity, triglycerides, and blood pressure, regardless of sociodemographic factors, diet, and physical activity (Andersen et al., 2006; Lobelo, Pate, Dowda, Liese, & Ruiz, 2010; Ruiz et al., 2006). In addition, longitudinal studies have shown that healthy CRF in childhood and adolescence is associated with a healthier cardiometabolic profile later in life (Ortega, Ruiz, Castillo, & Sjostrom, 2008). Some research shows that CRF is related to sex, age, anthropometric characteristics, and level of habitual physical activity (Koch et al., 2009; Takken et al., 2019). Although sex, age, body composition, and health status of an individual can significantly affect the level of cardiorespiratory fitness, physical activity has the greatest impact (Parikh & Stratton, 2011). Regular physical activity has long been one of the most important components of healthy living, especially today, when the younger population is preoccupied with advanced technology and increasing use of various motor and electric vehicles, while the COVID-19 virus has contributed to inactivity in the last two years.
This research aims to determine the relationship between cardiorespiratory ability and body mass index, motor skills and physical activity in faculty, sports, and leisure.
Methods
The sample consisted of 129 female students enrolled at the Faculty of Teacher Education, University of Zagreb – Department in Čakovec, average age 21 ± 0.12 years. The predictor set of variables consisted of the body mass index calculated as the ratio of body mass and square of body height expressed in meters, then 7 motor Eurofit tests to assess agility (10x5 m shuttle run), flexibility (sit and reach), speed of limb movement (hand tapping), repetitive torso power (sit-ups), static arm power (bent arm hang), balance (Flamingo test), explosive leg power (standing broad jump). Physical activity was examined with the Baecke questionnaire (Baecke, Burema, & Frijters, 1982), which assesses normal physical activity in the last 12 months and contains 16 questions that check physical intensity during work, sports activity, and leisure time. For the purposes of this research, workplace-related questions were reformulated only on physical activity in college. Physical activity at the faculty contains seven questions (faculty index), sports physical activity contains four questions, or seven if a person is engaged in another sport (sports index), while physical activity during leisure time contains seven questions (leisure index). The higher the value of an individual index, the better the level of physical activity (Baecke, Burema, & Frijters, 1982). The criterion variable was the Beep test or the 20m shuttle run test assessing aerobic endurance (Léger, Mercier, Gadoury, & Lambert, 1988), showing satisfactory reliability and validity in estimating maximal oxygen uptake (VO2max) in children and adults (Léger & Lambert, 1982). To estimate the maximum oxygen uptake, the standard equation used was: VO2max (ml/kg/min) = 18.043461 + (0.3689295 x TS) + (-0.000349 x TS x TS), where TS is the total number of shuttles (Léger & Gadoury, 1989). Measurements were conducted in April 2021. The survey results were processed in IBM SPSS Statistics 23. Central and dispersive parameters were calculated for all variables: arithmetic mean (AS), standard deviation (SD), minimum (MIN) and maximum score (MAX), distribution asymmetry coefficient (SKEW), distribution curvature coefficient (KURT). The skewness-kurtosis normality distribution test was used to determine whether the measurements were suitable for normal distribution. According to Tabachnick and Fidell (2013), kurtosis-skewness values should be between +1.5 and -1.5. Previously, the variables that showed deviations from the normal distribution were subjected to the normalization of the distribution by the procedure (log 10) which enabled further processing using regression analysis. The interrelationship between predictor and criterion variables was calculated with Pearson’s correlation coefficient. To explain the variance of the criterion variable VO2max, stepwise regression analysis was applied using the stepwise method.
Results
Table 1. Descriptive and dispersive parameters of the predictor and criterion variable
|
|
Min |
Max |
AS±SD |
Skew |
Kurt |
|
BMI |
14.60 |
35.29 |
23.06±3.75 |
0.88 |
0.98 |
|
Flamingo (s) |
2.36 |
78.56 |
11.90±12.61 |
2.06 |
10.26 |
|
Hand tapping (number) |
21.00 |
39.00 |
32.25±3.42 |
-0.35 |
-0.02 |
|
Sit and reach (cm) |
43.00 |
103.00 |
74.75±11.60 |
-0.07 |
0.01 |
|
Standing broad jump (cm) |
70.00 |
220.00 |
159.81±23.05 |
-0.49 |
1.37 |
|
Sit up (30s) |
12.00 |
34.00 |
24.28±4.04 |
0.05 |
-0.07 |
|
Bent arm hang (s) |
1.00 |
72.00 |
18.68±16.17 |
1.48 |
2.35 |
|
10x5m (s) |
16.18 |
28.30 |
21.82±2.17 |
0.46 |
0.64 |
|
Sports index |
1.50 |
4.25 |
2.61±0.61 |
0.47 |
-0.05 |
|
Faculty index |
1.88 |
3.38 |
2.58±0.26 |
0.30 |
1.042 |
|
Leisure time index |
1.75 |
5.00 |
3.23±0.62 |
0.30 |
-0.214 |
|
Vo2max (ml/kg/min) |
19.60 |
33.30 |
23.71±2.95 |
1.06 |
0.97 |
Based on the research results shown in Table 1, the mean value of VO2max is 23.7 ml/kg/min. Furthermore, the highest average value (3.23) was obtained in the domain of leisure, while the lowest was in the domain of sports (2.61). The lowest result is visible in the sports index (1.58), and the highest in the leisure index whose value is the maximum of the possible (5). According to the asymmetry coefficients (Skew), the variables flamingo and bent arm hang show that most participants are grouped in the zone of lower results, and the roundness values (Kurt) of these variables show a homogeneous results distribution.
Table 2. Correlations between the predictor and criterion variables
|
|
BMI |
Flam |
tap |
flex |
standbj |
situp |
bentah |
10x5m |
IS |
IF |
ILT |
Vo2max |
|
BMI |
1 |
|
|
|
|
|
|
|
|
|
|
|
|
FLAM |
-.16 |
1 |
|
|
|
|
|
|
|
|
|
|
|
TAP |
-.16 |
.20 |
1 |
|
|
|
|
|
|
|
|
|
|
FLEX |
.16 |
.02 |
.19 |
1 |
|
|
|
|
|
|
|
|
|
STANBJ |
-.38 |
-.06 |
.15 |
.15 |
1 |
|
|
|
|
|
|
|
|
SITUP |
.01 |
.11 |
.05 |
.23 |
.08 |
1 |
|
|
|
|
|
|
|
BENTAH |
-.60 |
.18 |
.20 |
-.05 |
.52 |
.23 |
1 |
|
|
|
|
|
|
10x5m |
-.16 |
.19 |
.12 |
.09 |
.37 |
-.09 |
.25 |
1 |
|
|
|
|
|
IS |
-.20 |
.2 |
.09 |
.15 |
.21 |
.11 |
.32 |
.22 |
1 |
|
|
|
|
IF |
-.07 |
-.01 |
-.06 |
-.08 |
.08 |
.16 |
.05 |
.02 |
-.08 |
1 |
|
|
|
ILT |
-.09 |
.02 |
-.06 |
-.01 |
.09 |
.07 |
.14 |
.05 |
.35 |
.01 |
1 |
|
|
VO2max |
-.23 |
.12 |
.17 |
.11 |
.39 |
.18 |
.40 |
.33 |
.33 |
.03 |
.23 |
1 |
Table 2 shows the correlation coefficients of predictor and criterion variables. Significant associations of VO2max indicate a negative association with BMI (r = -.23) and a positive association with hand tapping (r = .17), standing broad jump (r = .39), sit-ups (r = .18), bent arm hang (r = .40), shuttle run 10x5m (r = .33), sports index (r = .33) and leisure time index (r = .23). Intercorrelations of predictor variables indicate low to moderate correlations. Thus, BMI shows low negative correlations with the sports index (r = -.20), standing broad jump (r = -.38), flamingo test (r = -0.16), hand tapping (r = -.16), and shuttle run 10x5 m (r = -.16) and moderately negative correlations with the bent arm hang (-.38). The sports index has a significant positive correlation with motor tests that are under the direct influence of the mechanism for energy regulation of movement; standing broad jump (r = .21), bent arm hang (r = .32), and shuttle run 10x5m (r = .22).
Table 3. Regression analysis for the cardiorespiratory endurance (VO2max)
|
R=.52; R2=.27; Adj.R=.25 F(4.124)=11.60; p=.00; SEE=2.55 |
B |
SE |
Beta |
t |
p |
|
Bent arm hang |
.03 |
.01 |
.20 |
2.185 |
.031 |
|
Shuttle run 10x5m |
.23 |
.13 |
.17 |
2.083 |
.039 |
|
Sports index |
.91 |
.39 |
.19 |
2.351 |
.020 |
|
Standing broad jump |
.02 |
.01 |
.19 |
2.041 |
.041 |
Based on the multiple correlation coefficient value (R = .52; p = .00), there is a statistically significant correlation between the predictor and criterion variables VO2max (Table 3). The value of the determination coefficient shows that the predictors explain 27% of the variance of the criterion variable, i.e., according to the corrected coefficient of determination 25% of the variance of the criterion variable. The bent arm hang has the highest partial impact (BETA = .22; p = .031), followed by the sports index (BETA = .19; p = .020), standing broad jump (BETA = .19; p = .041), and shuttle run 10x5 m (BETA = .17; p = .039).
Discussion
This research has found an association between VO2max and BMI, motor skills, and physical activity in sports, faculty, and leisure. The average value of the participants’ VO2max (23.70 ml/kg/min) in this research is lower compared to Indian female students (32.10) (Bandyopadhyay, 2013), as well as American 16-year-olds (34.2) (Gutin, Yin, Humphries, & Barbeau, 2005), Colombian 17-year-olds (32.70) (Ramos-Sepúlveda, Ramírez-Vélez, Correa-Bautista, Izquierdo, & García-Hermoso, 2016), and sedentary women aged 17-24 from Brazil (35.6) (Herdy & Uhlendorf, 2011). Norwegian women aged 20-29 show twice the average values (43.00) (Loe, Rognmo, Saltin, & Wisløff, 2013). The results of the participants in this research are consistent with medical students from India who are not engaged in sports (23.54) (Shete, Bute, & Deshmukh, 2014) and 64-year-old women (22.20) (Ogawa et al., 1992). The BMI shows a negative correlation with all tests that are directly influenced by the mechanism for energy regulation (standing broad jump, bent arm hang, shuttle run 10x5m), VO2max and sports index. Similar results were obtained in research conducted by Rausavljević (1995), which shows the negative impact of body weight and adipose tissue on the performance of motor tests that measure explosive power and the ability to solve complex motor tasks and endurance. Also, in a sample of healthy Israeli women (N = 181) aged 26–65 years, a significant negative correlation was obtained between BMI and VO2max (r = −.514) (Dagan, Segev, Novikov, & Dankneret, 2013). It seems that higher body fat mass can affect the result in the 20m shuttle run test. Goran, Fields, Hunter, Herd, and Weinsier (2000) stated that fat mass is partly metabolically inactive and constitutes an additional load to carry, increased fat mass will decrease VO2max, and excess fatness has a detrimental effect on submaximal aerobic capacity. It is also possible that increased fat mass will increase the oxygen cost of running at any given speed relative to the total body mass (Olds, Ridley, & Tomkinson, 2007), and peripherally located fat mass (on the arms and legs) increases both rotational and translational kinetic energy (Cavanagh & Kram, 1989). Also, the results in the 20m shuttle run test can depend on psychosocial factors, e.g., motivation, effort, and self-efficacy (Tomkinson et al., 2017).
The results of the regression analysis show that 27% of the VO2max variance was explained by the bent arm hang, standing broad jump, and shuttle run 10x5m tests and the sports index. Similar results on a large sample of Lithuanian children (N = 15,200) aged 11 to 18 years were obtained in research (Venckunas, Mieziene, & Emeljanovas, 2018) in which the highest association of the 20m shuttle run test was obtained with standing broad jump and shuttle run 10x5m test, and each of them explains 10% of the variance of cardiorespiratory capacity, while the bent arm hang test showed a slightly smaller share of the variance of 7%. According to the determination coefficient (r2), the standing broad jump test shows 15%, the bent arm hang shows 16%, and shuttle run 10x5m shows 11% of the variance of the 20m shuttle run test. An explanation for the significant impact of these tests could be found in similar patterns of movement in shuttle run tests and the involvement of the same muscle groups (leg extensors) that are important for locomotion, especially when accelerating and slowing the whole body. Also, Zamparo, Zadro, Lazzer, Beato, and Sepulcri (2014) state that cardiorespiratory parameters increase in shuttle run tests of 180° direction change, which is more demanding, and are the same effective means of improving VO2max. From the domain of physical activity, only the sports index showed significant predictive value in explaining the VO2max variance, and according to the correlation coefficient (r2), 11% of VO2max variance can be explained by moderate to high intensity physical activity. The Baecke questionnaire showed satisfactory validity of the sports index and total physical activity compared to accelerometry, and it can be used to assess moderate to high physical activity in adults (Garcia, Osti, Ribeiro, & Florindo, 2013). A lower proportion of the total variance (5.7%) of VO2max and self-assessed physical activity are reported by Loe et al. (2013). In a large sample of 8,002 children aged 10–16 years, physical activity measured by the questionnaire accounted for 36% of the VO2max-20mshutle run test variance (Newill, Duncan, & Sandercock, 2020). Similar correlation coefficients (r = .30) between cardiorespiratory endurance and moderate PA measured by accelerometers were obtained by the research carried out by Gutin et al. (2005). In the same research, the authors reported a higher correlation (r = .45) of VO2max and high-intensity PA. In the sample of women (N = 181) aged 26-65 only age, hours of training per week, and weekly caloric expenditure in physical activity were significantly associated with the cardiorespiratory fitness level (20% of the total CRF variance explained). In research by Dagan et al. (2013), on a sample of 123 women aged 60 to 91 years, the physical activity examined with the Baecke questionnaire was not significantly associated with VO2max. The sample of Brazilian male students at the Faculty of Kinesiology did not show significant correlations between VO2max and physical activity domains, nor the overall result of the Baecke questionnaire due to homogeneity of VO2max values, because the average group value was high with small variations, which impaired the analysis (Florindo & Latorre, 2003).
Conclusions
The low average values of the female students’ VO2max in this research can be explained by the COVID-19 pandemic because organized forms of indoor exercise were prohibited in the year prior to the testing, followed by a lack of contact classes in Kinesiology at the faculty, i.e., all classes were conducted online. Also, their movement in the social environment was reduced, and thus the time spent in sedentary activities was certainly increased. We can assume that only highly motivated individuals engaged in moderate to high intensity physical activity. On the other hand, the results in the 20m shuttle run test can depend on other parameters, such as mechanical efficiency, anaerobic capacity, agility, fat mass, as also motivation and effort. All of this may have affected the results of the association between VO2max and the body mass index, motor ability, and physical activity level in this research.
The testing of motor and cardiorespiratory fitness should be conducted throughout higher education in order to obtain feedback about their status and, finally, education about the consequences of an inactive lifestyle, as well as motivation to increase physical activity from moderate to high intensity.
References
Andersen, L. B., Harro, M., Sardinha, L. B., Froberg, K., Ekelund, U., Brage, S., & Anderssen, S.A. (2006). Physical activity and clustered cardiovascular risk in children: A cross-sectional study (the European youth heart study). The Lancet, 368, 299–304. DOI: 10.1016/S0140-6736(06)69075-2
Bandyopadhyay, A. (2013). Validity of the 20 meter multi-stage shuttle run test for estimation of maximum oxygen uptake in female university students. Indian Journal of Physiology and Pharmacology, 57, 77–83.
Cavanagh, P. R., & Kram, R. (1989). Stride length in distance running: velocity, body dimensions, and added mass effects. Medicine and Science in Sports and Exercise, 21(4), 467–479.
Dagan, S. S., Segev, S., Novikov, & Dankner, R. (2013). Waist circumference vs body mass index in association with cardiorespiratory fitness in healthy men and women: a cross sectional analysis of 403 subjects. Nutritional Journal, 12:12. doi: 10.1186/1475-2891-12-12
Florindo, A. A., & Latorre. M. R. D. O. (2003). Validation and reliability of the Baecke questionnaire for the evaluation of habitual physical activity in adult men. Revista Brasileira de Medicina do Esporte, 9(3). doi: 10.1590/S1517-86922003000300002
Garcia, L., Osti, R., Ribeiro, E., & Florindo, A. (2013). Validação de dois questionários para a avaliação da atividade física em adultos (Validation of two questionnaires to evaluate physical activity in adults). Revista Brasileira de Atividade Física e Saúde, 18(3), 317–331. 10.17533/udea.rfnsp.v38n1e334156.
Goran, M., Fields, D. A., Hunter, G. R., Herd, S. L., & Weinsier, R. L. (2000). Total body fat does not influence maximal aerobic capacity. International journal of obesity and related metabolic disorders: Journal of the International Association for the Study of Obesity, 24(7), 841–848. doi: 10.1038/sj.ijo.0801241
Gutin, B., Yin, Z., Humphries, M. C., & Barbeau, P. (2005). Relations of moderate and vigorous physical activity to fitness and fatness in adolescents, The American Journal of Clinical Nutrition, 81(4), 746–750, doi: 10.1093/ajcn/81.4.746
Herdy, A. H., & Uhlendorf, D. (2011). Reference values for cardiopulmonary exercise testing for sedentary and active men and women. Arquivos brasileiros de cardiologia, 96(1), 54–59. doi: 10.1590/s0066-782x2010005000155
Koch, B., Schäper, C., Ittermann, T., Spielhagen, T., Dörr, M., Völzke, H., Opitz, C. F., Ewert, R., & Gläser, S. (2009). Reference values for cardiopulmonary exercise testing in healthy volunteers: The SHIP study. The European Respiratory Journal, 33(2), 389–397. doi: 10.1183/09031936.00074208
Laukkanen, J. A., Lakka, T. A., Rauramaa, R., Kuhanen, R., Venäläinen, J. M., Salonen, R., & Salonen, J. T. (2001). Cardiovascular fitness as a predictor of mortality in men. Archives of Internal Medicine, 161(6), 825–831. doi: 10.1001/archinte.161.6.825
Léger, L. A, Mercier, D., Gadoury, C., & Lambert, J. (1988). The multi-stage 20 m shuttle runtest for aerobic fitness. Journal of Sports Sciences, 6(2), 93–101. DOI: 10.1080/02640418808729800
Léger, L., A., & Gadoury, C. (1989). Validity of 20m multistage fitness test to estimate maximal oxygen uptake. British Journal of Sports Medicine, 22, 141–52. doi: 10.1136/bjsm.2004.012500
Lobelo, F., Pate, R. R., Dowda, M., Liese, A. D., & Ruiz, J. R. (2009). Validity of cardiorespiratory fitness criterion referenced standards for adolescents. Medicine and Science in Sports and Exercise, 41, 1222–1229. DOI: 10.1249/MSS.0b013e318195d491
Léger, L. A., & Lambert, J. (1982). A maximal multistage 20-m shuttle run test to predict VO2 max. European Journal of Applied Physiology and Occupational Physiology, 49(1),1–12. DOI: 10.1007/BF00428958
Loe, H., Rognmo, Ø., Saltin, B., & Wisløff, U. (2013). Aerobic Capacity Reference Data in 3816 Healthy Men and Women 20–90 Years. PLoS ONE, 8. doi: 10.1371/journal.pone.0064319
Na, S. H., Kim, Y. S., Bae, J., Nah, D., Kim, Y. K., Lee, M. M., Kim, H., & Rhee, M. (2009). Effects of physical activity and aerobic exercise capacity on aortic stiffness in patients with untreated hypertension. Korean Circulation Journal, 39, 52–56. DOI:10.4070/KCJ.2009.39.2.52
Ogawa T., Spina R. J., Martin W. H. 3rd, Kohrt W. M., Schechtman K. B., Holloszy J. O., & Ehsani A. A. (Aug 1992). Effects of aging, sex, and physical training on cardiovascular responses to exercise. Circulation, 86(2), 494–503. DOI: 10.1161/01.cir.86.2.494
Olds, T. S., Ridley, K., & Tomkinson, G. R. (2007). Declines in aerobic fitness: are they only due to increasing fatness? Medicine and Sport Science, 50, 226–240. doi: 10.1159/000101394
Ortega, F. B., Ruiz, J. R., Castillo, M. J., & Sjostrom, M. (2008). Physical fitness in childhood and adolescence: A powerful marker of health. International Journal of Obesity, 32, 1–11. DOI: 10.1038/sj.ijo.0803774
Parikh, T., & Stratton, G. (2011). Influence of intensity of physical activity on adiposity and cardiorespiratory fitness in 5-18 year olds. Sports Medicine (Auckland, N.Z.), 41(6), 477–488. doi: 10.2165/11588750-000000000-00000
Ramos-Sepúlveda, J. A., Ramírez-Vélez, R., Correa-Bautista, J. E., Izquierdo, M., & García-Hermoso, A. (2016). Physical fitness and anthropometric normative values among Colombian-Indian schoolchildren. BMC Public Health, 16(1), 962. doi: 10.1186/s12889-016-3652-2
Rausavljević, N. (1995). Kanonička razmerja med morfološkimi značilnostmi in motoričnimi sposobnostmi učencev prvih razredov osnovnih šol. Šport, 43(2), 38–40.
Ruiz, J. R., Ortega, F. B., Meusel, D., Harro, M., Oja, P., & Sjostrom, M. (2006). Cardiorespiratory fitness is associated with features of metabolic risk factors in children. Should cardiorespiratory fitness be assessed in a European health monitoring system? The European Youth Heart Study. Journal of Public Health, 14, 94–102 DOI: 10.1007/s10389-006-0026-8
Shete, A. N., Bute, S. S., & Deshmukh, P. R. (2014). A study of VO2max and body fat percentage in female athletes. Journal of Xlinical and Diagnostic Research: JCDR, 8(12), BC01–BC3. doi: 10.7860/JCDR/2014/10896.5329
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. 6th Edn., Boston: Pearson Education.
Takken, T., Mylius, C. F., Paap, D., Broeders, W., Hulzebos, H. J., Van Brussel, M., & Bongers, B. C. (2019). Reference values for cardiopulmonary exercise testing in healthy subjects – An updated systematic review. Expert Review of Cardiovascular Therapy, 17(6), 413–426. doi: 10.1080/14779072.2019.1627874
Tammelin, T. (2013). Physical activity from adolescence to adulthood and health-related fitness at age 31: Cross-sectional and longitudinal analyses of the Northern Finland birth cohort of 1966. (Doctoral Dissertation). Finnish Institute of Occupational Health, Oulu Regional Institute of Occupational Health; University of Oulu, Faculty of Medicine, Department of Public Health Science and General Practice. Retrieved http://urn.fi/urn:isbn:9514272331 [05.03.2022]
Tomkinson, G. R., Lang, J. J., Tremblay, M. S., Dale, M., LeBlanc, A. G., Belanger, K., Ortega, F. B., & Léger, L. (2017). International normative 20 m shuttle run values from 1 142 026 children and youth representing 50 countries. British Journal of Sports Medicine, 51(21), 1545–1554. doi: 10.1136/bjsports-2016-095987
Venckunas, T., Mieziene, B., & Emeljanovas, A. (2018). Aerobic capacity is related to multiple other aspects of physical fitness: A study in a large sample of Lithuanian schoolchildren. Frontiers in Physiology, 9, 1797. doi: 10.3389/fphys.2018.01797
Zamparo, P., Zadro, I., Lazzer, S., Beato, M., & Sepulcri, L. (2014). Energetics of shuttle runs: the effects of distance and change of direction. International Journal of Sports Physiology and Performance, 9(6), 1033–1039. doi: 10.1123/ijspp.2013-0258
Zeiher, J., Ombrellaro, K. J., Perumal, N., Keil, T., Mensink, G., & Finger, J. D. (2019). Correlates and determinants of cardiorespiratory fitness in adults: A systematic review. Sports Medicine – Open, 5(1), 39. doi: 10.1186/s40798-019-0211-2
|
|
2nd International Scientific and Art Faculty of Teacher Education University of Zagreb Conference Contemporary Themes in Education – CTE2 - in memoriam prof. emer. dr. sc. Milan Matijević, Zagreb, Croatia |
Povezanost motoričkih sposobnosti, tjelesne aktivnosti i kardiorespiratorne sposobnosti |
Sažetak |
|
Kardiorespiratorna sposobnost je dimenzija tjelesnoga zdravlja povezana s tjelesnom aktivnošću tako da dovodi do mnogih zdravstvenih beneficija poput prevencije različitih kroničnih nezaraznih bolesti. Cilj ovoga istraživanja bio je utvrditi povezanost motoričkih sposobnosti, tjelesne aktivnosti i kardiorespiratorne sposobnosti. Uzorak ispitanika činilo je 129 studentica Učiteljskog fakulteta Sveučilišta u Zagrebu – Odsjeka u Čakovcu, prosječne dobi 21 ±0,12 godine. Prediktorski skup činile su varijable indeks tjelesne mase, zatim 7 Eurofit testova za procjenu motoričkih sposobnosti (agilnost – trčanje 10 x 5 m; fleksibilnost – pretklon u sjedu; brzina frekvencije pokreta – taping rukom; repetitivna snaga trupa – podizanje iz sjedu u 30 s; statička snaga ruku – izdržaj u visu zgibom; ravnoteža – flamingo test; eksplozivna snaga nogu – skok u dalj s mjesta) te tri indeksa tjelesne aktivnosti Baeckeova upitnika (indeks sporta, slobodnoga vremena i fakulteta). Kriterijsku varijablu za procjenu kardiorespiratorne sposobnosti činio je Beep test. Rezultati su izračunati regresijskom stepwise metodom. Pearsonovi koeficijenti korelacije između kardiorespiratorne izdržljivosti i motoričkih sposobnosti, indeksa tjelesne mase te indeksa tjelesnih aktivnosti pokazale su niske do umjerene povezanosti. Kardiorespiratorna izdržljivost značajno negativno korelira s indeksom tjelesne mase, a pozitivno s indeksom sporta i slobodnoga vremena te varijablama za procjenu statičke snage ruku, agilnosti, repetitivne i eksplozivne snage nogu. Međutim, regresijska analiza je pokazala da su značajni prediktori u objašnjenju varijance kardiorespiratorne sposobnosti varijable izdržaj u visu zgibom (BETA = .28; p = .00), indeks sporta (BETA = .21; p = .01) i trčanje 10 x 5 m (BETA = -.20; p = .02) kojima je objašnjeno 23 % varijance kriterijske varijable. Ovo istraživanje pokazuje da je kardiorespiratorna sposobnost općenito povezana s indeksom tjelesne mase, tjelesnim aktivnostima u sportu i slobodno vrijeme te motoričkim sposobnostima energetske regulacije kod studentica. Međutim, izdržaj u visu zgibom, indeks sporta i trčanje 10 x 5 m smatrani su najvažnijim prediktorima za kardiorespiratornu izdržljivost. |
|
Ključne riječi |
|
kardiorespiratorna sposobnost; motoričke sposobnosti; tjelesna aktivnost |