Background
Physical fitness has become an important non-communicable factor associated with well-being and health in the past two decades [
1,
2]. It is often defined as ‘an integrated measure of most, if not all, the body functions (skeletomuscular, cardiorespiratory, hematocirculatory, psychoneurological and endocrine–metabolic) involved in the performance of daily physical activity and/or physical exercise’ [
2]. Evidence suggests that higher levels of physical fitness in youth may prevent from cardiovascular, metabolic and mental diseases later in life [
3‐
7], highlighting the importance of tracking characteristics of physical fitness from childhood to adulthood [
8]. Moreover, studies have recognized that most risk factors attributed to chronic diseases in adulthood begin during childhood [
2,
9,
10], pointing out that interventions aiming to enhance physical fitness at younger age for future health benefits are warranted [
11].
Physical fitness represents a multifactorial construct and an integrated measure of body composition, functional endurance capacity, muscular fitness, speed/agility and flexibility [
2]. Although all aspects of physical fitness seem to be important [
2], functional endurance capacity has been the strongest predictor of morbidity and mortality in both men and women independently of other risk factors [
12,
13]. In recent years, the level of functional endurance capacity has declined dramatically in school-aged children, increasing the prevalence of overweight/obesity [
14] and not meeting the recommended levels of physical activity [
15]. Of note, the ‘EUROFIT’, the’ ALPHA-FIT’ and the ‘FITNESS GRAM’ test batteries are the most widely applied in primary and secondary school students to assess the level of physical fitness.
Although functional endurance capacity has been associated with fundamental movement skill proficiency [
16], a small proportion of studies have been provided regarding associations to other physical fitness components [
11]. In general, evidence suggests that standing broad jump and agility shuttle run are the strongest predictors of functional endurance capacity (number of completed endurance shuttle run stages) with ≈10% of the variance shared in performance in these tests, followed by bent arm hang time, sit-ups (≈6–7%) and sit-and-reach test (≈3%) [
11]. According to aforementioned, functional endurance capacity has been only weakly associated with multiple other aspects of physical fitness, concluding that this measure should be tested as a separate physical fitness component within the school system. Moreover, biological and environmental changes in functional endurance capacity do not follow the changes in other physical fitness components [
11], i.e. the associations between functional endurance capacity and other aspects of physical fitness remain unclear. Specifically, a rather linear increase of absolute maximal oxygen uptake (VO
2max) from childhood to adolescence has been observed previously, while speed has two separate growth spurts and muscle strength increases linearly during childhood, but has a remarkable growth spurt in boys during puberty and is more stable and reaches a plateau in girls [
2].
Therefore, the main purpose of the study was to test the associations between functional endurance capacity with other physical fitness components in 7–14-year-old children, stratified by gender. We hypothesized, that functional endurance capacity would be positively associated with muscular and motor physical fitness, yet inversely associated with body size. If the associations happen to be weak, this will imply that functional endurance capacity is a single construct of overall physical fitness, which should be measured independently of multiple other physical fitness components.
Results
Basic descriptive statistics of the study participants are presented in Table
1. Boys were taller, heavier and had higher body-mass index values. Boys performed better in all physical fitness tests, except for sit-and-reach test in favor to girls.
Table 1
Basic descriptive statistics of the study participants (N = 1612)
Age (years) | 9.7 (2.4) | 9.8 (2.4) | 9.6 (2.3) | 0.148 |
Height (cm) | 151.0 (176) | 152.0 (19.4) | 150.2 (15.7) | 0.046 |
Weight (kg) | 45.1 (19.1) | 46.5 (13.3) | 43.9 (14.04) | 0.006 |
Body-mass index (kg/m2) | 20.2 (3.4) | 21.6 (3.6) | 19.9 (3.3) | < 0.001 |
Sit-and-reach test (cm) | 20.4 (8.3) | 17.6 (8.3) | 23.0 (7.3) | < 0.001 |
Standing broad jump (cm) | 158.5 (43.5) | 164.4 (38.9) | 153.1 (46.7) | < 0.001 |
Sit-ups in 30 s (reps) | 17.1 (7.0) | 17.8 (7.2) | 16.5 (6.8) | < 0.001 |
10 × 5 shuttle run (sec) | 23.1 (3.0) | 22.6 (3.2) | 23.6 (2.8) | < 0.001 |
20-m shuttle run (level) | 4.3 (1.9) | 4.9 (2.2) | 3.9 (1.4) | < 0.001 |
The associations between functional endurance capacity and multiple other physical fitness components in boys are presented in Table
2. In unadjusted model, variance of performance in standing broad jump (40.0%), 10 × 5 shuttle run (36.0%) and sit-ups in 30 s (32.5%) were each explained by functional endurance capacity the strongest, followed by weaker but still significant association by functional endurance capacity with sit-and-reach test (1.2%). When models were adjusted for age, variance of performance in standing broad jump (34.8%), 10 × 5 shuttle run (31.4%) and sit-ups in 30 s (28.1%) remained the strongest predictors of functional endurance capacity, followed by sit-and-reach test (1.7%). Body – mass index was not significantly associated with functional endurance capacity in both unadjusted and adjusted models.
Table 2
The associations between functional endurance capacity and multiple other physical fitness components in boys (N = 765)
Body-mass index (kg/m2) |
Unadjusted model | 0.01 | 0.118 | 0.906 |
Model adjusted by age | 0.02 | 0.361 | 0.718 |
Sit-and-reach test (cm) |
Unadjusted model | 0.11 | 2.897 | 0.004 |
Model adjusted by age | 0.13 | 3.497 | < 0.001 |
Standing broad jump (cm) |
Unadjusted model | 0.63 | 21.127 | < 0.001 |
Model adjusted by age | 0.59 | 19.900 | < 0.001 |
Sit-ups in 30 s (reps) |
Unadjusted model | 0.57 | 18.332 | < 0.001 |
Model adjusted by age | 0.53 | 17.369 | < 0.001 |
10 × 5 shuttle run (sec) |
Unadjusted model | −0.60 | −19.739 | < 0.001 |
Model adjusted by age | −0.56 | −18.165 | < 0.001 |
The associations between functional endurance capacity and multiple other physical fitness components in girls are presented in Table
3. In unadjusted model, variance of performance in 10 × 5 shuttle run (22.1%) was the strongest predictor explained by functional endurance capacity, followed by sit-ups in 30 s (16.8%), standing broad jump (9.6%) and sit-and-reach test (7.3%). When models were adjusted for
age, variance of performance in 10 × 5 shuttle run (16.3%), sit-ups in 30 s (13.0%) and standing broad jump (6.3%) remained the strongest predictors of functional endurance capacity, followed by sit-and-reach test (4.4%) and body-mass index (1.4%).
Table 3
The associations between functional endurance capacity and multiple other physical fitness components in girls (N = 857)
Body-mass index (kg/m2) |
Unadjusted model | −0.05 | −1.283 | 0.200 |
Model adjusted by age | −0.12 | −3.597 | < 0.001 |
Sit-and-reach test (cm) |
Unadjusted model | 0.27 | 7.851 | < 0.001 |
Model adjusted by age | 0.21 | 6.528 | < 0.001 |
Standing broad jump (cm) |
Unadjusted model | 0.31 | 8.838 | < 0.001 |
Model adjusted by age | 0.25 | 7.698 | < 0.001 |
Sit-ups in 30 s (reps) |
Unadjusted model | 0.41 | 12.403 | < 0.001 |
Model adjusted by age | 0.36 | 11.457 | < 0.001 |
10 × 5 shuttle run (sec) |
Unadjusted model | −0.47 | −14.899 | < 0.001 |
Model adjusted by age | −0.40 | −12.531 | < 0.001 |
In the whole sample, variance of performance in standing broad jump run (35.1%) was the strongest predictor explained by functional endurance capacity, followed by 10 × 5 shuttle run (31.4%), sit-ups in 30 s (25.0%), sit-and-reach test (0.4%) and body – mass index (0.0%). When models were adjusted for age, variance of performance in standing broad jump (38.6%), 10 × 5 shuttle run (34.4%) and sit-ups in 30 s (31.1%) remained the strongest predictors of functional endurance capacity, followed by sit-and-reach test (11.5%) and body-mass index (11.5%).
Discussion
The main purpose of the study was to test the associations between functional endurance capacity with other physical fitness components in 7–14-year-old children, stratified by gender. The main findings are: 1) functional endurance capacity predicts between 1 and 40% of the variance in performance in multiple other physical fitness components in boys, 2) in girls, functional endurance capacity predicts between 7 and 22% of the variance in performance in multiple other physical fitness components and 3) when adjusting for
age, the percentage of variance shared between functional endurance capacity and multiple other physical fitness components slightly declines. Regarding gender differences in the associations between functional endurance capacity and other physical fitness components, girls not participating in sport tend to improve the level of functional endurance capacity much slower, compared to boys [
1], while functional endurance capacity before puberty improves very slow in school – aged boys [
21].
Our results of functional endurance capacity being most strongly associated to 10 × 5 shuttle run, standing broad jump and sit-ups in 30 s are in line with previous findings obtained among a large sample of Lithuanian school aged children [
11]. Specifically, a study by Venckunas et al. [
11] has shown that variance of performance in 10 × 5 shuttle run and standing broad jump were each explained by functional endurance capacity the strongest (> 10%), followed by the association between Functional endurance capacity with the abilities in bent arm hang and sit-ups (functional endurance capacity explaining ∼6.5% of the variance of the performance in these tests), as well as in balance and sit-and-reach tasks (functional endurance capacity significantly explaining ∼3% of the variance). It has been hypothesized, that for 10 × 5 shuttle run and standing broad jump performance, movement patterns are similar and the same muscle groups (i.e. leg extensors) need to be involved for locomotion [
11]. Another potential mechanism may be the nature of these activities, which require different jumping, accelerating and decelerating performances deserving for intrinsic musculoskeletal characteristics, synchronizing upper and lower body and gaining appropriate momentum [
11]. Also, the aforementioned tasks fall under weight-bearing exercises, which share similar moving patterns. Indeed, studies have shown that functional endurance capacity is associated with anaerobic functional capacities required for performing agility and power/strength tasks [
20].
The strongest associations between functional endurance capacity and muscular fitness are not surprising, since higher levels of these components reduce the risk of all-cause mortality [
22,
23] and are often interrelated [
11]. From the perspective in sport, evidence suggests that low functional endurance capacity may be compensated for additional muscle training stimulus in aerobic endurance athletes [
24], pointing out that all physical fitness components should be equally developed and enhanced across the lifespan. This supports the findings from previous studies, stating that being involved in endurance sport is not associated with an increased life expectancy [
6]. Therefore, physical fitness, as a multifactorial construct, is the best non-communicable factor remotely associated to health [
3‐
7]. Nevertheless, the critical period when physical fitness (especially functional endurance capacity) should be trained is during the childhood period, since it successfully predicts the development of cardiovascular diseases in later life [
4].
This study has a few limitations. First, by using a cross-sectional design, we cannot determine the causality of the association, that is multiple other physical fitness components were associated to functional endurance capacity. Second, we randomly selected schools and classes for the purpose of this study and achieved an acceptable response rate. Nevertheless, more physically active families are more prone to participating in the studies of such nature [
25]. Thus, potential selection bias cannot be excluded. Third, the proxy of functional endurance capacity was assessed through the 20-m shuttle run test. Although this test has been widely used and the reliability and validity properties have been confirmed [
4], treadmill or bicycle ergometers may have given somewhat different maximal oxygen uptake values and associations between functional endurance capacity with multiple other physical fitness components. Studies have shown that the 20-m shuttle run test is designed to determine the maximal aerobic power [
26], while more direct measurements assess VO
2max. Thus, Fourth, body – mass index was used as a proxy of body composition. However, body – mass index cannot discriminate between fat mass and fat – free mass and more sophisticated tools, like dual X – ray absorptiometry must be used to assess the level of body composition in school – aged children. Finally, we did not assess the level of maturity. Although previous studies have recommended equations for maturity offset [
27], standard errors of the equations are 0.53 years in girls and 0.54 years in boys. Also, a lack of fit between predicted and observed ages at peak height velocity (PHV) within each chronological age group and within each year before and after PHV has been observed previously [
27]. Therefore, future research on the same topic needs to be longitudinal with more objective methods to assess the level of functional endurance capacity in school aged children.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (
http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.