Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Criterion-Related Validity of the Distance- and Time-Based Walk/Run Field Tests for Estimating Cardiorespiratory Fitness: A Systematic Review and Meta-Analysis

Abstract

Objectives

The main purpose of the present meta-analysis was to examine the criterion-related validity of the distance- and time-based walk/run tests for estimating cardiorespiratory fitness among apparently healthy children and adults.

Materials and Methods

Relevant studies were searched from seven electronic bibliographic databases up to August 2015 and through other sources. The Hunter-Schmidt’s psychometric meta-analysis approach was conducted to estimate the population criterion-related validity of the following walk/run tests: 5,000 m, 3 miles, 2 miles, 3,000 m, 1.5 miles, 1 mile, 1,000 m, ½ mile, 600 m, 600 yd, ¼ mile, 15 min, 12 min, 9 min, and 6 min.

Results

From the 123 included studies, a total of 200 correlation values were analyzed. The overall results showed that the criterion-related validity of the walk/run tests for estimating maximum oxygen uptake ranged from low to moderate (rp = 0.42–0.79), with the 1.5 mile (rp = 0.79, 0.73–0.85) and 12 min walk/run tests (rp = 0.78, 0.72–0.83) having the higher criterion-related validity for distance- and time-based field tests, respectively. The present meta-analysis also showed that sex, age and maximum oxygen uptake level do not seem to affect the criterion-related validity of the walk/run tests.

Conclusions

When the evaluation of an individual’s maximum oxygen uptake attained during a laboratory test is not feasible, the 1.5 mile and 12 min walk/run tests represent useful alternatives for estimating cardiorespiratory fitness. As in the assessment with any physical fitness field test, evaluators must be aware that the performance score of the walk/run field tests is simply an estimation and not a direct measure of cardiorespiratory fitness.

Introduction

Physical fitness constitutes an integrated measure of all the functions and structures involved in the performance of physical activity [1]. Particularly cardiorespiratory fitness reflects the overall capacity of the cardiovascular and respiratory systems to supply oxygen during sustained physical activity [2]. Currently there is strong evidence that cardiorespiratory fitness constitutes an important predictor of morbidity and mortality [3]. Therefore, it is considered one of the most powerful markers of health, even above other traditional indicators such as weight status, blood pressure or cholesterol level [4].

Cardiorespiratory fitness testing may help to identify a target population for primary prevention and health promotion policies [5]. The maximal oxygen uptake (VO2max) attained during a laboratory and graded maximal exercise test is commonly considered the criterion measure [6]. Nevertheless, since the direct determination of VO2max by laboratory testing requires sophisticated and expensive equipment, qualified examiners, and long testing sessions, this technique is not feasible in several settings such as in sports clubs, physical education lessons, or large scale research studies [7]. In these settings, the performance score obtained during cardiorespiratory fitness field tests could be a useful alternative to estimate VO2max [7]. Since the early interest in physical fitness testing in the 1950-60s, many field tests have been proposed [8]. The walk/run field tests are probably the most widely used [8,9], but there is still no consensus regarding the most appropriate distance or time of the walk/run test for estimating cardiorespiratory fitness [10].

Each primary study about the criterion-related validity of the distance- and time-based walk/run tests only constitutes a single piece of evidence [11]. For example, when Cooper [12] studied the criterion-related validity of the 12 min walk/run test, he found a high correlation coefficient, however, later other authors found a moderate [13] or even low association [14]. To make sense of the often conflicting results found, meta-analyses must be conducted [11,15,16]. Recently some meta-analytic studies have examined the criterion-related validity of different widely used physical fitness field tests such as the sit-and-reach [17], toe-touch [18], and 20-m shuttle run [7]. Regarding the distance- and time-based walk/run field tests, Safrit, Hooper, Ehlert, Costa, and Patterson [19] carried out the first meta-analysis almost 30 years ago. However, from that date many primary research studies have been published. Additionally, some walk/run tests were not taken into account. Since these authors performed the analysis combining all the tests, besides the well-known methodological problem of dependency, a key issue such as which test is “long enough” could not be addressed. Finally, apart from the sex and age of individuals, the potential moderator effects of other important issues on the criterion-related validity such as the individuals’ fitness levels, adding some other individuals’ characteristics to the performance score, or the measurement unit of the criterion test were not examined.

Unfortunately, to our knowledge there is not any recent meta-analysis examining the criterion-related validity of the distance- and time-based walk/run tests, and there is not any meta-analysis addressing all the above mentioned issues. Examining these questions would help to select the best feasible and valid test for estimating cardiorespiratory fitness. Consequently, the purposes of the present meta-analysis were: (a) to estimate and compare the overall population of the criterion-related validity of the distance- and time-based walk/run tests for estimating cardiorespiratory fitness among apparently healthy children and adults (for only performance score and performance score with other variables); (b) to examine the influence of individuals’ sex (men and women), age (children and adults), and level of VO2max (low and high) on criterion-related validity of the walk/run tests (between-study analyses); and (c) to compare the criterion-related validity between the only performance score and the performance score combined with other variables, as well as between the VO2max relative to body mass and the VO2max absolute, VO2max relative to fat-free mass and maximal aerobic speed (within-study analyses).

Materials and Methods

The methodological procedure followed in the present study was based on previous general literature about meta-analyses [11,15,16], and specifically in the meta-analyses of the criterion-related validity of physical fitness field tests [7,17,18]. Although the present manuscript is original (including all the results, figures and tables) and data are from an independent study, it reproduces some parts of the text already published elsewhere [7,17,18].

Data sources and search strategy

Seven electronic bibliographic databases were searched through until August 2015: Web of Science (all databases), Scopus, SPORTDiscus with Full Text, CINAHL, Cochrane Library, ProQuest Social Sciences Premium Collection, and ProQuest Dissertations & Theses Global. The searches were carried out in the search field type “Title, abstract, and keywords” or equivalent. The search terms used were based on two concepts: (1) walk/run field test, and (2) validity. The terms of the same concept were combined together with the Boolean operator “OR” and then the two concepts were combined using the Boolean operator ‘‘AND” [11]. The truncated root of certain terms was followed by an asterisk to include multiple variants. The keywords with more than one word were enclosed in quotes. Due to the large number of terms, from one to four independent searches were carried out for each walk/run field test. No publication format, language or date restrictions were imposed. See S1 Appendix for all the specific syntaxes used.

Based on the results of the Boolean-based database search, additional records were identified through other sources: (1) searching the reference lists of original studies and some related study reviews (i.e. “snowballing”); (2) examining the reference citations and the researchers publications (first authors) in the Web of Science and Scopus databases; (3) contacting by email with the corresponding authors (if they were not defined, the first author was used), and (4) screening the researchers’ personal lists in ResearchGate and Google Scholar (first authors). For practical reasons, the search was carried out for one researcher.

Study selection

The selection criteria were the following: (1) studies with participants who did not present any injury, physical and/or mental disabilities; (2) studies with field tests performed on a track or similar (i.e. but not on a treadmill) that consisted of walking/jogging, walking/running, only jogging or only running (i.e. but not only walking) as much as possible during a fixed distance (i.e. 5,000 m, 3 miles, 2 miles, 3,000 m, 1.5 mile, 1 mile, 1,000 m, ½ mile, 600 m, 600 yd, and ¼ mile) or time (i.e. 15 min, 12 min, 9 min and 6 min); (3) studies in which for the criterion measure the VO2max (or VO2peak–see potentials and limitations section–) was measured in a standardized and laboratory-based graded exercise test to exhaustion, and (4) studies which reported (or could be computed from raw data reported in the study) the Pearson’s r zero-order correlation coefficient or simple/multiple linear regression (R2) of performance scores of the field test (or the performance score with other variables) with the measured VO2max.

Although there are many standard scales to assess the overall risk of bias in the included studies, empirical evidence has shown that they are misleading and unhelpful [20]. According to PRISMA and Cochraneʹs guidelines [21,22], the present meta-analysis followed a component approach on a case-by-case basis where it was described specific methodological domains that it was assessed. Both domains related to markers of the validity of the included studies (i.e. risk of bias in individual studies) and domains related to the research topic were included [21]. In addition to guaranteeing that the included studies met the selection criteria, in the present meta-analysis it was also ensured that there was a complete reporting of relevant outcomes. The sample size, protocol of the walk/run field test, unit and protocol of the criterion measure test, statistical test, and value of the criterion-related validity were considered to be critical. In the event that the authors failed to identify any critical study feature and it could not be retrieved, the study was not included in the meta-analysis. The selection criteria were examined by two independent researchers. When doubt or disagreement occurred (< 5%), a consensus was always achieved through discussion.

Data extraction

From each selected study the following data were coded: Identification number, study reference, type of publication (1 = journal paper, 2 = grey literature–any document reporting some scientific finding, except the journal papers: e.g. doctoral dissertation, masterʹs thesis, conference proceeding, or technical report–), sample size (n), sex (1 = men, 2 = women, 3 = men and women), age (1 = children and adolescents–onwards the term “children” is used to simplify-, < 18 years, 2 = adults, ≥ 18 years, 3 = children and adults), field test (1 = 5,000 m, 2 = 3 miles, 3 = 2 miles, 4 = 3,000 m, 5 = 1.5 miles, 6 = 1 mile, 7 = 1,000 m, 8 = ½ mile, 9 = 600 m, 10 = 600 yd, 11 = ¼ mile, 12 = 15 min, 13 = 12 min, 14 = 9 min, 15 = 6 min), criterion measure protocol (1 = treadmill test, 2 = cycle ergometer test, 3 = other), measurement unit of the criterion test (1 = VO2max relative to body mass, 2 = VO2max absolute, 3 = VO2max relative to fat-free mass, 4 = maximal aerobic speed, 5 = other), mean and standard deviation values of the measurement criterion, reliability of the field test and the measurement criterion (intraclass correlation coefficient), statistical test (1 = Pearson’s r correlation coefficient, 2 = R2 simple/multiple linear regression), and criterion-related validity value (separately for only performance score and multiple predictors). Observations were also registered when special issues were found. In the event that the authors failed to identify any study feature, they were contacted to retrieve it. If the study feature was not retrieved, the information was omitted. Coding studies were carried out by two independent researchers. When doubt or disagreement occurred (< 5%), a consensus was always achieved through discussion.

Data analyses

A detailed description of the data analyses carried out in the present meta-analysis [16], as well as a brief description of the main formulas [11], can be found elsewhere. According to Schmidt and Hunter [16], Pearson’s zero-order correlation coefficient (r) was considered the unit of the criterion-related validity of the walk/run field tests. When the validity values were reported as R2, it was previously transformed by the square root. After verifying that in all the primary studies a better performance in the walk/run field tests (i.e. more distance in the time-based tests, less time in the distance-based tests or higher average speed in both tests) was associated with a better score in the criterion measure, the correlation coefficients between the time score of the distance-based walk/run tests and the criterion measure (i.e. negative values) were previously transformed to positive (i.e. absolute values). The studies carried out with a small sample (defined as less than 10 participants) were not included.

Dependency issues.

An exhaustive examination of the selected studies was carried out to avoid dependency issues. Since the most studies used the VO2max relative to body mass as the measurement criterion, the correlation coefficients with this variable were used for the main analyses. When these studies also reported the results of criterion-related validity using additional variables (i.e. the VO2max absolute, VO2max relative to fat-free mass and/or the maximal aerobic speed), these validity coefficients were only used for the within-study analyses to compare with the VO2max relative to body mass. Since some studies used multiple performance scores of the field tests for examining the criterion-related validity, the average value was used. When authors reported the results of criterion-related validity from the combination of different multiple predictors, only the best model (i.e. higher coefficient value) was used.

If a single study reported more than one r value within the same field test, but from different subsamples, each r value from different subsamples was assumed to be independent [15]. When, in the same study, data for men/women or children/adults were expressed both separately and together, only the separate data were selected. However, when data for the whole sample and subsamples with respect to sex and age categories were expressed, only the whole sample was used. When data were expressed for different trials, the average value of the coefficients was selected. When data were expressed for pre- and post-intervention, only the pre-intervention value was used.

Publication bias.

Besides the search strategy followed to avoid availability bias, a deep examination of the selected studies was first carried out to avoid any potential duplication of the information retrieved. Similarities between studies of the same authors, with the same correlation coefficients and/or the same sample size were examined. When the selected studies had full or partial duplicated information, these particular correlations were not analyzed. Then, to identify the impact of any potential publication bias, the scatter plots and the Spearman’s rank order correlations between r values and sample size were carried out [23]. Cumulative meta-analyses by year of publication were also examined through forest plots to assess the evolution of the summary of the criterion-related validity coefficients over time [23]. Finally, for assessing the impact of any potential publication bias, file drawer analyses based on effect size were performed [23]. According to Cohen’s [24] benchmarks, in the file drawer analyses a small correlation coefficient was defined as r = 0.29.

Computation of correlations.

The Hunter-Schmidt’s psychometric meta-analysis approach [16] was conducted to obtain the population estimates of the criterion-related validity of the walk/run field tests. These authors advocate a single method (a random-effects model) on the basis of their belief that a fixed-effects model is inappropriate for real world data and the type of inferences that researchers usually want to make [16]. Schmidt and Hunter [16] also argue that when the random-effects model is applied to data in which the same p value (i.e. population parameter of r) underlies all studies (i.e. SDp = 0), it becomes mathematically a fixed-effects model. That is, while the random-effects model is a more general method that allows for any possible value of SDp, the fixed-effects model allows for only one special case, i.e. when SDp = 0.

The “bare-bone” mean r (rc), corrected for only sampling error was first calculated by weighting each r with the respective sample size. Then, the corrected mean r at the population level (rp) that was unaffected by both sampling error and measurement error was calculated. Since the reliability coefficients of the field tests were unavailable in most of the included primary studies, the measurement error was corrected using artifact distributions. The measurement error of the criterion test could not be corrected because the reliability was almost unavailable. Finally, the 95% confidence intervals of rp (95% CI) were calculated.

Moderator analyses.

According to Schmidt and Hunter [16], to determine the presence of heterogeneity in the population estimation of the criterion-related validity of the field tests (rp), three different criteria were simultaneously examined: (a) the 95% credibility interval (95% CV) is relatively large or includes the value zero; (b) the percentage of variance accounted for by statistical artefacts is less than 75% of the observed variance in rp, and (c) the Q homogeneity statistic is statistically significant at p < 0.05. If at least one of the three criteria was met, it was concluded that the results were potentially affected by moderator effects.

Based on a priori hypothesized moderators, partial hierarchical analyses were also carried out (i.e. subgroups or stratified analyses). The criterion-related validity of the walk/run field tests were analyzed by: (a) sex (i.e. men and women); (b) age (i.e. children and adults); and (c) level of VO2max (i.e. low average level, < P50, and high average level, ≥ P50) (between-study analyses). Additionally, the criterion-related validity of the field tests for the only performance score and multiple predictors was compared; and the criterion-related validity with the VO2max relative to body mass were compared to the VO2max absolute, VO2max relative to fat-free mass, and maximal aerobic speed (within-study analyses).

The meta-analyses were performed using the software Hunter and Schmidt Meta-Analysis Programs version 2.0 for Windows (Iowa, 2014). All the others statistical analyses and graphs were performed using the SPSS version 20.0 for Windows (IBM® SPSS® Statistics 20).

Results

Study description

Of the 9,546 bibliographic databases search results, potentially relevant publications were retrieved for a more detailed evaluation. Afterward, based on the studies of the Boolean-based database search, additional records were identified through other sources. From the 547 potentially eligible studies, 159 studies met the selection criteria. However, due to full duplication issues, not reporting the criterion-related validity of the VO2max relative to body mass and/or carrying out the study with a small sample, only 123 studies were included [10,1214,25143]. From the included studies, 200 r values across the walk/run field tests were retrieved, being 178 correlation coefficients for the criterion-related validity using the only performance score and 22 for multiple predictors (Fig 1).

Regarding the criterion-related validity for only performance score, a total of 178 r values across 15 walk/run tests were retrieved, ranging from 1 to 34 values (median = 9). Total sample sizes for each field test ranged from 28 to 1,856 (median = 367). The individual criterion-related validity ranged from 0.03 to 0.99 (median = 0.70). Regarding the criterion-related validity for performance with other variables, a total of 22 r values across eight walk/run tests were retrieved, ranging from 1 to 6 values (median = 1). Total sample sizes for each field test ranged from 44 to 1,156 (median = 87). The individual criterion-related validity ranged from 0.65 to 0.99 (median = 0.81) (S1 Table).

Publication bias

Avoiding duplicated information.

Although 16 research studies met the selection criteria, the correlation coefficients were not analyzed. Some grey literature sources were not included because they were published later in a journal paper, e.g. [144146]. From the Cureton’s et al. [51] study the correlation coefficient with the only performance score was not included because the data came from the sum of some samples that had been reported in other journal papers [49,50,96]. However, since these papers did not report the correlation coefficient with multiple predictors, the correlation coefficient with multiple predictors for the overall results and both the only performance score and multiple predictors for the within-study analysis from the Cureton’s et al. [51] study were used.

Identifying publication bias.

The following analyses were calculated only for the tests with a K equal to 10 or more [147]. The scatter plots of sample size against criterion-related validity coefficients suggest that for the distance-based walk/run tests there was not publication bias (Fig 2). For the time-based walk/run tests explored, however, the figures suggest the presence of publication bias because of the absence of r values in the lower left hand corner (Fig 3). Similarly, while the results of Spearman’s rank order correlation between r values and sample size did not show any statistically significant correlation for the distance-based walk/run tests (p > 0.05), a statistically significant correlation was found for the 9 min walk/run test (p < 0.05). However, for the 12 min walk/run test a statistically significant correlation was not found (p > 0.05). Due to the small K found for most of the tests, the results of both methods must be interpreted with caution [11,23]. Empirical evaluations of the funnel plots also suggest that their interpretation can be limited [148].

thumbnail
Fig 2. Scatter plot of sample size against criterion-related validity coefficients (r) of distance-based walk/run tests for estimating maximal oxygen uptake: (a) 5,000 m walk/run test; (b) 2 miles walk/run test; (c) 3,000 m walk/run test; (d) 1.5 mile walk/run test; and (e) 1 mile walk/run test.

Dashed line represents median values of validity coefficients.

https://doi.org/10.1371/journal.pone.0151671.g002

thumbnail
Fig 3. Scatter plot of sample size against criterion-related validity coefficients (r) of time-based walk/run tests for estimating maximal oxygen uptake: (a) 12 min walk/run test; and (b) 9 min walk/run test.

Dashed line represents median values of validity coefficients.

https://doi.org/10.1371/journal.pone.0151671.g003

In the walk/run tests analyzed (i.e. K ≥ 10), the cumulative meta-analysis plots (S1 Fig) suggest a fairly constant estimate of the criterion-related validity coefficients over time with only some fluctuations in the first studies may be simply due to chance [23]. Although a large correlation coefficient in the first primary study was found for the 12 min walk/run test (S1F Fig), the summary value was diminished after the 3rd-4th study. Additionally, no transiently lose formal significance nor complete reverse of the initial association was found. Finally, it is worth mentioning that in most plots (i.e. S1C–S1F Fig) the addition of new primary studies did not materially change the estimates, consequently the final criterion-related validity values of these walk/run tests seem to be quite robust. On the other hand, for the other walk/run tests (i.e. S1A, S1B and S1G Fig and K < 10) the final criterion-related validity values should be considered with special caution.

Assessing the impact of publication bias.

The results of the file drawer analyses are shown in the following lines (in parenthesis the unlocated/located percentage): 5,000 m 28 (147%), 3 miles 6 (100%), 2 miles 19 (136%), 3,000 m 16 (133%), 1.5 miles 30 (167%), 1 mile 36 (106%), 1,000 m 3 (150%), 600 m 1 (100%), 600 yd 8 (100%), ¼ mile 5 (63%), 15 min 1 (50%), 12 min 42 (162%), 9 min 14 (127%), and 6 min 7 (88%). The results showed an unlikely number of “lost” studies for most of the walk/run tests, especially if the percentage of unlocated/located studies is considered (73–167%).

Criterion-related validity

The overall results showed that the criterion-related validity of the walk/run tests with the only performance score ranged from low to moderate and no 95% CI included the value zero. The results also showed that the criterion-related validity of the 1.5 mile and 12 min walk/run tests was statistically significantly higher than the 3 miles, 1 mile, ½ mile, 600 yd, ¼ mile, 15 min, and 6 min walk/run tests (p < 0.05). The 5,000 m walk/run test was statistically significantly greater than the ¼ mile, 15 min and 6 min walk/run tests (p < 0.05). And the 2 miles and 3,000 m walk/run tests showed a statistically significant higher mean r than the 6 min walk/run test (p < 0.05). For the other comparisons statistically significant differences were not found (p > 0.05) (Table 1). Since for most of the tests at least one heterogeneity criterion was met (Table 1), follow-up moderator analyses were conducted. Due to the small K, moderator analyses were not conducted for the 1,000 m, 600 m and 15 min walk/run tests.

thumbnail
Table 1. Results of meta-analyses for overall criterion-related validity correlation coefficients across the distance- and time-based walk/run field tests.

https://doi.org/10.1371/journal.pone.0151671.t001

Regarding the multiple predictors, the overall results showed that when the performance score of the walk/run field tests was combined with other variables the criterion-related validity values were moderate-to-very-high and no 95% CI included the value zero. The results also showed that the criterion-related validity of the 1.5 mile walk/run test was statistically significantly higher than the 1 mile and 9 min walk/run tests (p < 0.05). However, statistically significant differences between the 1.5 mile and 12 min walk/run tests were not found (p > 0.05), as well as neither between the 1 mile, 12 min, and 9 min walk/run tests (p > 0.05) (Table 1). Although at least one heterogeneity criterion was met in three of the four tests (Table 1), due to the small K the between-study moderator analyses were not conducted for multiple predictors. The within-study analyses were conducted as it was hypothesized (see moderator analyses).

Moderator analyses

Between-study moderator analyses.

The results of the between-study moderator analyses showed that the criterion-related validity of the analyzed walk/run field tests ranged from low to moderate for all the subcategories. No 95% CI included the value zero, except for the 600 yd walk/run test in women and the ¼ mile walk/run test in individuals with high level of VO2max. Regarding the within-test comparisons between men-women, children-adults and low-high level of VO2max, statistically significant differences were not found (p > 0.05) (except for the 9 min walk/run test in the level of VO2max category). As regards the between-test comparisons among each subcategory, in general the results showed that the criterion-related validity of the 1.5 mile and 12 min walk/run tests was statistically significantly higher than those tests with shorter protocols (p < 0.05). Nevertheless, no statistically significant differences were found between the criterion-related validity of the 1.5 mile and 12 min walk/run tests and the walk/run tests with longer protocols (except among the adults in which for the 1.5 mile walk/run test was statistically significantly higher than the 3 mile walk/run tests, p < 0.05). According to heterogeneity analyses, at least one criterion was met in most of the walk/run tests, indicating that the criterion-related validity of these tests separately for sex, age and level of VO2max was still heterogeneous. Because some studies grouped subcategories together or values were missing, overall K for the categories is lower (Table 2).

thumbnail
Table 2. Results of the between-study moderator analyses for criterion-related validity correlation coefficients across the distance- and time-based walk/run field tests.

https://doi.org/10.1371/journal.pone.0151671.t002

Within-study moderator analyses.

Because of the low K for each field test, the within-study analyses were carried out with all the tests together. As regards the analyses for the number of predictors, the results showed that meanwhile the only performance score had a moderate criterion-related validity, when other variables were added the criterion-related validity values were moderate-to-high. No 95% CI included the value zero. The criterion-related validity of the performance score with other variables (i.e. multiple predictors) was statistically significantly higher than only the performance score (rpΔ = 0.14; p < 0.05) (Table 3).

thumbnail
Table 3. Results of the within-study moderator analyses for criterion-related validity correlation coefficients across the distance- and time-based walk/run field tests.

https://doi.org/10.1371/journal.pone.0151671.t003

Regarding the analyses for the unit of the criterion measure, the results showed that the criterion-related validity values of the walk/run tests with the VO2max relative to body mass and maximal aerobic speed were moderate, but when the VO2max absolute and relative to fat-free mass was used instead it was low. No 95% CI included the value zero. The criterion-related validity of the walk/run tests with the VO2max relative to body mass was statistically significantly higher than when the VO2max absolute (rpΔ = 0.27; p < 0.05) or relative to fat-free mass was used (rpΔ = 0.20; p < 0.05). However, statistically significant differences between the VO2max relative to body mass and maximal aerobic speed were not found (rpΔ = - 0.12; p > 0.05). According to heterogeneity analyses, at least one criterion was met in each subcategory, indicating that the criterion-related validity of the walk/run tests was heterogeneous (Table 3). The fact that the different walk/run tests were put together must be also taken into account.

Discussion

A cardiorespiratory fitness test must be chosen based on its feasibility and validity [7]. Although many distance- and time-based walk/run field tests have been proposed [8], according to the results of the present meta-analysis, the 1.5 mile and 12 min walk/run tests showed the greater criterion-related validity for estimating the cardiorespiratory fitness. The overall criterion-related validity of both tests has shown to be similar to other cardiorespiratory fitness tests such as the 20-m shuttle run test (rp = 0.84, 0.80–0.89) [7].

According to the findings of the present meta-analysis, sex, age, and fitness levels of individuals do not seem to affect the criterion-related validity. Therefore, the walk/run tests can be used interchangeably for any subcategory. Similarly, recently Mayorga-Vega et al. [7], carrying out a meta-analytic study about the criterion-related validity of the 20-m shuttle run test, found that sex and fitness levels did not affect the validity. However, they found out that the criterion-related validity of the Léger’s protocol was statistically significantly higher among adults than among children. Although among children the 1.5 mile and 12 min walk/run tests showed a similar validity than the 20-m shuttle run test (rp = 0.78, 0.72–0.85), among adults the 20-m shuttle run test was statistically significantly higher (rp = 0.94, 0.87–1.00). Therefore, among adults the 20-m shuttle run test should be used instead the walk/run field tests.

A potential reason for these differences could be inherent to the protocols of the field tests. Meanwhile in the walk/run tests individuals have to run as much as possible maintaining a self-pace, the 20-m shuttle run test is characterized to have a rigid standardized protocol where individuals cannot choose their own pace. Specifically, it has been suggested that the starting speed of the 20-m shuttle run test could be too high for children [149]. Current evidence suggests that to elicit valid VO2max values, continuous incremental tests should last at least five minutes [150]. However, Castro-Piñero et al. [151] in a population-based study carried out with the Léger’s protocol (i.e. starting speed at 8.5 km/h) found that most children lasted less than five minutes. Thus, meanwhile with the walk/run tests both children and adults can adjust the running pace to their own possibilities, the most widely used protocols of the 20-m shuttle run test [152154] could be too high for children. In this line, recent studies have proposed modifications of the 20-m shuttle run test for children with a drastically reduced starting speed (e.g. 4 km/h or 6.5 km/h) [107,149]. Future studies should compare the criterion-related validity of 1.5 mile and/or 12 min walk/run field tests and a modified version of the 20-m shuttle run test with a lower starting speed among children.

For both men-women, children-adults and low-high level of VO2max subgroups, the 1.5 mile and 12 min walk/run tests seem to be the most appropriate distance- and time-based walk/run field tests, respectively. Although longer distance-based field tests showed similar criterion-related validity results, performing a longer distance seems to be an unnecessary extra time and effort. However, due to their lower criterion-related validity, the use of shorter walk/run tests should be avoided. Surprisingly, among children the 1 mile walk/run test (followed by the ½ mile and ¼ mile walk/run tests) is the cardiorespiratory fitness test more often proposed by the field-based physical fitness batteries [8]. For instance, the FITNESSGRAM® test battery proposes the use of either the 20-m shuttle run or 1 mile walk/run tests [9]. According to the results of the present meta-analysis, however, in addition to the 20-m shuttle run test, the 1.5 mile and/or 12 min walk/run tests should be proposed instead of the 1 mile walk/run test for estimating cardiorespiratory fitness among children.

The results of the present meta-analysis also showed that when multiple predictors were used, the criterion-related validity was statistically significantly higher than for the only performance score. Therefore, apart from the running performance score, adding other individuals’ variables significantly improves the estimation of the VO2max. Similarly, Mayorga-Vega et al. [7] found that for the 20-m shuttle run test with multiple predictors the correlation coefficient was considerably higher than for the only performance score (rpΔ = 0.11). However, probably because of the low number of correlations, this difference was not statistically significant. Another potential reason for these differences could be due to the fact that the validity of the walk/run tests was lower than the 20-m shuttle run test and, therefore, the change to increase the explained variance was greater.

Finally, the results of the present meta-analysis showed that the criterion-related validity of the walk/run tests with the VO2max relative to body mass as the measurement unit was statistically significantly higher than when the VO2max absolute or relative to fat-free mass was used. According to Meredith and Welk [9], the criterion-related validity of walk/run tests with VO2max relative to body mass should not be interpreted only in terms of cardiorespiratory fitness, but they also reflect the influence of differences on body fat. In this line, empirical evidence has demonstrated that part of the association of VO2max relative to body mass with the walk/run tests reflects the influence of anthropometric variables [155]. Therefore, it is not surprising the fact that the correlation of the walk/run tests with the VO2max expressed relative to body mass is higher than with the VO2max expressed absolute or relative to fat-free mass. On the other hand, statistically significant differences between the VO2max relative to body mass and maximal aerobic speed were not found. The maximal aerobic speed defined as the lowest speed at which VO2max occurs, besides the differences in body mass previously mentioned, it reflects other factors such as running economy. Although running economy influences the running performance in a walk/run test, it has shown not to increase the variance explained between the walk/run test score and the VO2max relative to body mass [50].

Potentials and limitations

The meta-analysis is a useful tool to assess scientific evidence, but an understanding of its potentials and limitations is needed. An exhaustive review of the general potentials and limitations of meta-analyses, e.g. [11], as well as specifically in the meta-analysis of the criterion-related validity of cardiorespiratory fitness field tests has been published elsewhere [7]. Regarding the potentials of the present meta-analysis, numerous measures to avoid, or at least to reduce, publication bias were followed. Then, several exploratory analyses were conducted to identify and assess the impact of any potential publication bias. Another potential was related to the statistical approach used. Since the Hunter-Schmidt’s psychometric meta-analysis approach [16] estimates the population correlation by correcting the observed correlations due to various artefacts, empirical evidence has shown this to be the most accurate method [156,157].

As regards the limitations of the present meta-analysis, the main ones were related to the small number of criterion-related validity coefficients found. Estimating the population parameters based on small samples is simply less accurate than in a large-sized meta-analysis. Due to the low K found, a partial hierarchical breakdown had to be used instead of a full. Additionally, due to the low K found, the criterion-related validity of potentially different subcategories such as children (< 12 years) and adolescents (12–18 years) had to be examined together. Therefore, misleading results due to confounding and interaction effects might also be produced [16]. When a greater number of studies are accumulated, a large sized meta-analysis with more specific subcategories and a full hierarchical analysis approach should be carried out.

Another potential limitation could be related to the statistical metric. The correlation coefficient is a measure of relationship rather than agreement which it might be also highly influenced by the range of individual measurements [158]. The performance scores of the field tests (i.e. distance, time or speed) and the criterion measure (i.e. VO2max) are expressed in two different units and, therefore, logically an agreement statistical approach could not be performed. To solve this methodological limitation, another kind of validity such as the cross-validity or criterion-referenced validity could be followed instead [159]. However, these approaches assess a different kind of validity and they were not the scope of the present meta-analysis. For instance, although the criterion-referenced validity could be useful for screening if individuals are or not in a “health fitness zone”, the criterion-related validity is more appropriate for other purposes such as analyzing the effects of an intervention program. Future research studies should examine the cross-validity and criterion-referenced validity of the walk/run field tests. The validity of other field tests such as the walk or step tests should be also examined.

As regards the potential influence of the range of individuals’ measurement on criterion-related validity, the results of Spearman’s rank order correlations between the criterion-related validity coefficients and the standard deviation of the VO2max did not show any statistically significant association (p > 0.05), except for the 2 miles walk/run test (r = 0.71, p = 0.009). Therefore, in the present meta-analysis the empirical outcomes showed that the criterion-related validity of the most walk/run tests was not biased by the variability of the sample measurements.

Another limitation could be related to the criterion measure. Although only primary studies in which the criterion measure used the VO2max relative to body mass during a laboratory incremental test to exhaustion were selected, researchers employed different equipment, ergometers and protocols, as well as criteria to determine VO2max. It must be also highlighted the fact that the peak oxygen uptake (VO2peak) was used interchangeably with VO2max. Although the VO2peak simply refers to the highest value of oxygen uptake attained in a particular exercise test, due to the fact that the tests in the primary studies were maximal it can be reasonably sure that values were the highest value of oxygen uptake that is deemed attainable by individuals, i.e. the VO2max [160]. Therefore, the criterion measure of cardiorespiratory fitness should be standardized and reexamined [161].

Finally, coding some study features was problematic due to different reasons. Some study features simply could not be coded because the authors did not report them. Although authors were contacted by email and/or ResearchGate, many of them did not reply and the particular study feature had to be omitted. Also noting that many studies were published several years ago and, therefore, no contact email address and/or ResearchGate profile was found. Moreover, because the level of VO2max was classified based on the average scores, some individuals with low VO2max could be classified as high VO2max and vice versa. Finally, although there could be other potentially moderating features such as physical activity levels, coding for them was not possible because it was not reported in most of the studies.

Conclusions

The overall criterion-related validity of the distance- and time-based walk/run field tests for estimating cardiorespiratory fitness ranged from low to moderate. The results of the present meta-analysis also showed that sex, age and VO2max levels do not seem to affect their criterion-related validity. The 1.5 mile and 12 min walk/run tests seem to be the best option of distance- and time-based field tests, respectively. Meanwhile performing longer walk/run tests could be an unnecessary extra time and effort, shorter tests showed poorer results of criterion-related validity.

When the evaluation of individual’s VO2max attained during a laboratory test is not feasible, the 1.5 mile and 12 min walk/run tests represent useful alternatives to estimate cardiorespiratory fitness. As in the assessment with any physical fitness field test, evaluators must be aware that the performance score of the walk/run field tests is simply an estimation and not a direct measure of cardiorespiratory fitness. Additionally, due to the relatively low number of r values found and that criterion-related validity values of walk/run field tests within most categories were still heterogeneous, the results of the present study should be considered with caution and firmer conclusions should await the accumulation of a larger number of studies.

Supporting Information

S1 Appendix. Syntaxes used in the present study for the search with the electronic bibliographic databases.

https://doi.org/10.1371/journal.pone.0151671.s001

(DOC)

S1 Fig. Results of the cumulative meta-analyses by year of publication for criterion-related validity coefficients (rp) across the walk/run field tests: (a) 5,000 m walk/run test; (b) 2 miles walk/run test; (c) 3,000 m walk/run test; (d) 1.5 mile walk/run test; (e) 1 mile walk/run test; (f) 12 min walk/run test; and (g) 9 min walk/run test.

https://doi.org/10.1371/journal.pone.0151671.s002

(DOC)

S1 Table. Summary of the included studies examining the criterion-related validity of walk/run field tests for estimating cardiorespiratory fitness.

https://doi.org/10.1371/journal.pone.0151671.s003

(DOC)

Acknowledgments

We gratefully acknowledge all the authors of the original research studies for their contribution, without whom the present meta-analysis could not be done. Authors also thank the head of the library, Mrs. Ana M. Peregrín González, for her technical assistance and great help to retrieve unavailable manuscripts. Additionally, we thank the librarians Mrs. María Sagrario Avilés Rodríguez and Mr. Francisco Moldero Espejo for their great help to digitalize some manuscripts. Authors also thank Anna Szczesniak and Aliisa Hatten-Viciana for the English revision.

Author Contributions

Conceived and designed the experiments: DMV RBP MO JV. Performed the experiments: DMV RBP MO JV. Analyzed the data: DMV RBP MO JV. Contributed reagents/materials/analysis tools: DMV RBP MO JV. Wrote the paper: DMV RBP MO JV. Funding: DMV.

References

  1. 1. Castillo Garzón MJ, Ortega Porcel FB, Ruiz Ruiz J. [Improvement of physical fitness as anti-aging intervention]. Med Clin (Barc). 2005;124:146–55. Spanish.
  2. 2. Taylor HL, Buskirk E, Henschel A. Maximal oxygen intake as an objective measure of cardio-respiratory performance. J Appl Physiol. 1955;8:73–80. pmid:13242493
  3. 3. Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, et al. Cardiorespiratory fitness as a quantitative predictor of all-cause mortality and cardiovascular events in healthy men and women: A meta-analysis. JAMA. 2009;301:2024–35. pmid:19454641
  4. 4. Blair SN. Physical inactivity: The biggest public health problem of the 21st century. Br J Sports Med. 2009;43:1–2. pmid:19136507
  5. 5. Ruiz JR, Castro-Pinero J, Artero EG, Ortega FB, Sjostrom M, Suni J, et al. Predictive validity of health-related fitness in youth: A systematic review. Br J Sports Med. 2009;43:909–23. pmid:19158130
  6. 6. Pescatello LS, Arena R, Riebe D, Thompson PD. ACSM’s guidelines for exercise testing and prescription. 9th ed. Philadelphia: Wolters Kluwer/ Lippincott Williams & Wilkins; 2014.
  7. 7. Mayorga-Vega D, Aguilar-Soto P, Viciana J. Criterion-related validity of the 20-m shuttle run test for estimating cardiorespiratory fitness: A meta-analysis. J Sports Sci Med. 2015;14:536–47. pmid:26336340
  8. 8. Castro-Piñero J, Artero EG, España-Romero V, Ortega FB, Sjöström M, Ruiz JR. Criterion-related validity of field-based fitness tests in youth: A systematic review. Br J Sports Med. 2010;44:934–43. pmid:19364756
  9. 9. Meredith MD, Welk GJ, editors. FITNESSGRAM® & ACTIVITYGRAM® test administration manual. 4th ed. Champaign: Human Kinetics; 2010.
  10. 10. Ruiz JR, Ortega FB, Castro-Piñero J. Validity and reliability of the 1/4 mile run-walk test in physically active children and adolescents. Nutr Hosp. 2015;31:875–82.
  11. 11. Cooper H, Hedges LV, Valentine JC. The handbook of research synthesis and meta-analysis. 2nd ed. New York: Sage; 2009.
  12. 12. Cooper KH. A means of assessing maximal oxygen intake. Correlation between field and treadmill testing. J Am Med Assoc. 1968;203:201–4.
  13. 13. O'Gorman D, Hunter A, McDonnacha C, Kirwan J. Validity of field tests for evaluating endurance capacity in competitive and international-level sports participants. J Strength Cond Res. 2000;14:62–7.
  14. 14. Casajus JA, Castagna C. Aerobic fitness and field test performance in elite Spanish soccer referees of different ages. J Sci Med Sport. 2007;10:382–9. pmid:17116419
  15. 15. Lipsey MW, Wilson DB. Practical meta-analysis. Newbury Park: Sage; 2001.
  16. 16. Schmidt FL, Hunter JE. Methods of meta-analysis: Correcting error and bias in research findings. 3nd ed. California: Sage; 2015.
  17. 17. Mayorga-Vega D, Merino-Marban R, Viciana J. Criterion-related validity of sit-and-reach tests for estimating hamstring and lumbar extensibility: A meta-analysis. J Sports Sci Med. 2014;13:1–14. pmid:24570599
  18. 18. Mayorga-Vega D, Viciana J, Cocca A, Merino-Marban R. Criterion-related validity of toe-touch test for estimating hamstring extensibility: A meta-analysis. J Human Sport Exerc. 2014;9:188–200.
  19. 19. Safrit MJ, Hooper LM, Ehlert SA, Costa MG, Patterson P. The validity generalization of distance run tests. Can J Sport Sci. 1988;13:188–96. pmid:3064901
  20. 20. Jüni P, Witschi A, Bloch R, Egger M. The hazards of scoring the quality of clinical trials for meta-analysis. JAMA. 1999;282:1054–60. pmid:10493204
  21. 21. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JPA, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. PLoS Med. 2009;6:e1000100. pmid:19621070
  22. 22. Higgins JPT, Green S. Cochrane handbook for systematic reviews of interventions version 5.1.0 [updated March 2011]. The Cochrane Collaboration, Available: http://handbook.cochrane.org/. Accessed 15 February 2016.
  23. 23. Rothstein HR, Sutton AJ, Borenstein M. Publication bias in meta-analysis: Prevention, assessment and adjustments. USA: Wiley; 2005.
  24. 24. Cohen JA. Power primer. Psychol Bull. 1992;112:155–9. pmid:19565683
  25. 25. Almarwaey OA, Jones AM, Tolfrey K. Physiological correlates with endurance performance in trained adolescents. Med Sci Sports Exerc. 2003;35:480–7. pmid:12618579
  26. 26. Anderson GS. The 1600-m run and multistage 20-m shuttle run as predictive tests of aerobic capacity in children. Pediatr Exerc Sci. 1992;4:312–8.
  27. 27. Arabas JL, Anderson MMEP, Arabas JR, Arabas CD, Mayhew JL. Estimation of VO2max from 9-minute run performance. Am J Health Educ. 1996;29:11.
  28. 28. Baldwin DL. Prediction of VO2 values from 9-minute run distances in young males, 9–14 years [dissertation]. La Crosse: University of Wisconsin-La Crosse; 1983.
  29. 29. Bandyopadhyay A. Validity of Cooper's 12-min run test for estimation of maximum oxygen uptake in female university students. Indian J Physiol Pharmacol. 2014;58:184–6. pmid:25509974
  30. 30. Bandyopadhyay A. Validity of Cooper's 12-minute run test for estimation of maximum oxygen uptake in male university students. Biol Sport. 2015;32:59–63. pmid:25729151
  31. 31. Barbineau C, Léger L. Physiological response of 5/1 intermittent aerobic exercise and its relationship to 5 km endurance performance. Int J Sports Med. 1997;18:13–9. pmid:9059899
  32. 32. Bergmann GG, de Araújo Bergmann ML, Mattos de Castro AA, Del’Corona Lorenzi T, dos Santos Pinheiro E, Moreira RB, et al. Use of the 6-minute walk/run test to predict peak oxygen uptake in adolescents. Rev Bras Ativid Fís Saúde. 2014;19:64–73.
  33. 33. Bergmann GG, de Araújo Bergmann ML, Mattos de Castro AA, Del’Corona Lorenzi T, dos Santos Pinheiro E, Moreira RB, et al. Prediction of peak oxygen uptake in adolescents from 9 minutes run/walk test. Gazz Med Ital. 2015;174:15–22.
  34. 34. Borghols EAM, Dresen MHW, Poulus AJ. [Cooper test: Useful or not?]. Geneeskd Sport. 1981;14:74–7. Dutch.
  35. 35. Brandon LJ, Boileau RA. Influence of metabolic, mechanical and physique variables on middle distance running. J Sports Med Phys Fitness. 1992;32:1–9. pmid:1405567
  36. 36. Buono MJ, Roby JJ, Micale FG, Sallis JF, Shepard WE. Validity and reliability of predicting maximum oxygen uptake via field tests in children and adolescents. Pediatr Exerc Sci. 1991;3:250–5.
  37. 37. Burger SC, Bertram SR, Stewart RI. Assessment of the 2,4 km run as a predictor of aerobic capacity. S Afr Med J. 1990;78:327–9. pmid:2396155
  38. 38. Burke EJ. Validity of selected laboratory and field tests of physical working capacity. Res Q. 1976;47:95–104. pmid:1062835
  39. 39. Burns RD, Hannon JC, Brusseau TA, Eisenman PA, Saint-Maurice PF, Welk G, et al. Cross-validation of aerobic capacity prediction models in adolescents. Pediatr Exerc Sci. 2015;27:404–11. pmid:26186536
  40. 40. Burns RD, Hannon JC, Brusseau TA, Eisenman PA, Shultz BB, Saint-Maurice PF, et al. Development of an aerobic capacity prediction model from one-mile run/walk performance in adolescents aged 13–16 years. J Sports Sci. Forthcoming 2015.
  41. 41. Calders P, Deforche B, Verschelde S, Bouckaert J, Chevalier F, Bassle E, et al. Predictors of 6-minute walk test and 12-minute walk/run test in obese children and adolescents. Eur J Pediatr. 2008;167:563–8. pmid:17726615
  42. 42. Castro-Piñero J, Mora J, González-Montesinos JL, Sjöström M, Ruiz JR. Criterion-related validity of the one-mile run/walk test in children aged 8–17 years. J Sports Sci. 2009;27:405–13. pmid:19191063
  43. 43. Castro-Piñero J, Ortega FB, Mora J, Sjöström M, Ruiz JR. Criterion related validity of 1/2 mile run-walk test for estimating VO2peak in children aged 6–17 years. Int J Sports Med. 2009;30:366–71. pmid:19277941
  44. 44. Cisar CJ, Thorland WG, Johnson GO, Housh TJ. The effect of endurance training on metabolic responses and the prediction of distance running performance. J Sports Med Phys Fitness. 1986;26:234–40. pmid:3795916
  45. 45. Chiou LA. A study of correlationship among maximal oxygen uptake, anaerobic threshold vs 12 minutes running and 400m running perfomance. Asian J Phys Educ. 1991;14:32–3.
  46. 46. Conley DS, Cureton KJ, Dengel DR, Weyand PG. Validation of the 12-min swim as a field test of peak aerobic power in young men. Med Sci Sports Exerc. 1991;23:766–73. pmid:1886488
  47. 47. Coolbaugh CL, Anderson IB, Wilson MD, Hawkins DA, Amsterdam EA. Evaluation of an exercise field test using heart rate monitors to assess cardiorespiratory fitness and heart rate recovery in an asymptomatic population. PLoS One. 2014;9:e97704. pmid:24848378
  48. 48. Cunningham LN, Cama G, Cilia G, Bazzano C. Relationship of VO2max with the 1-mile run and 20 meter shuttle test VO2 with youth aged 11 to 14 years. Med Sci Sports Exerc. 1994;26:S209.
  49. 49. Cureton KJ, Boileau RA, Lohman TG, Misner JE. Determinants of distance running performance in children: Analysis of a path model. Res Q. 1977; 48:270–9. pmid:267964
  50. 50. Cureton KJ, Sloniger MA, Black DM, McCormack WP, Rowe DA. Metabolic determinants of the age-related improvement in one-mile run/walk performance in youth. Med Sci Sports Exerc. 1997;29:259–67. pmid:9044232
  51. 51. Cureton KJ, Sloniger MA, O'Bannon JP, Black DM, McCormack WP. A generalized equation for prediction of VO2peak from 1-mile run/walk performance. Med Sci Sports Exerc. 1995;27:445–51. pmid:7752874
  52. 52. Da Silva SG, Moyna NM, Robertson RJ, Goss FL, Metz KF. Prediction of 3000m endurance performance in male and female distance runners using velocity at VO2max. Med Sci Sports Exerc. 1992;24:S102.
  53. 53. Dal Pupo J, Arins FB, Guglielmo LGA, Da Silva RCR, Moro ARP, Dos Santos SG. Physiological and neuromuscular indices associated with sprint running performance. Res Sports Med. 2013;21:124–35. pmid:23541099
  54. 54. Damitz SR, Ebbeling CE, Ward A, Freedson P, Rippe JM. Validity of the one mile run/walk test in children ages 6 to 13 years. Med Sci Sports Exerc. 1994;26:S209.
  55. 55. De Almeida JA, Campbell CSG, Pardono E, Sotero RC, Magalhães G, Simões HG. [Predictive equations validity in estimating the VO2max of young Brazilians from performance in a 1600 m run]. Rev Bras Med Esporte. 2010;16:57–60. Portuguese.
  56. 56. Díaz FJ, Montaño JG, Melchor MT, Guerrero JH, Tovar JA. [Validation and confiability of aerobic test of 1,000 meters]. Rev Invest Clin. 2000;52:44–51. Spanish. pmid:10818810
  57. 57. Dorociak JJ. Validity of running tests of 4, 8, and 12 minutes duration in estimating aerobic power for college women of different fitness levels [dissertation]. South Carolina: University of South Carolina; 1981.
  58. 58. Dorociak JJ, Nelson JK. The 1 mile and 2 mile runs as measures of cardiovascular fitness in college women. J Sports Med Phys Fitness. 1983;23:322–5. pmid:6656231
  59. 59. Drinkard B, McDuffie J, McCann S, Uwaifo GI, Nicholson J, Yanovski JA. Relationships between walk/run performance and cardiorespiratory fitness in adolescents who are overweight. Phys Therapy. 2001;81:1889–96.
  60. 60. Epperson CE, Buono MJ, Kolkhorst FW, Reynolds KK, Nanista JA, Sheffield RD. Correlation of lactate threshold, VO2max, and running economy with 4.8 kilometer running performance. Med Sci Sports Exerc. 1999;31:S104.
  61. 61. Fay L, Londeree BR, LaFontaine TP, Volek MR. Physiological parameters related to distance running performance in female athletes. Med Sci Sports Exerc. 1989;21:319–24. pmid:2733582
  62. 62. Ferfila N, Milić R, Škof B. [Influence of the energy profile of children on their results in the 600-metre run]. Sport: Revija Za Teoreticna in Prakticna Vprasanja Sporta. 2014;62:201–6. Slovenian.
  63. 63. Fontana KE. [Comparison of VO2max in direct and indirect measurements on treadmill and field test]. Rev Bras Ciênc Esporte. 1983;4:78–90. Portuguese.
  64. 64. Foster C, Costill DL, Daniels JT, Fink WJ. Skeletal muscle enzyme activity, fiber composition and VO2 max in relation to distance running performance. Eur J Appl Physiol Occup Physiol. 1978;39:73–80. pmid:689010
  65. 65. George JD, Larsen GE, Alexander JL, Fellingham GW, Aldana SG. Combining walking, jogging, and running into a single VO2max prediction test. Med Sci Sports Exerc. 2001;33:S45.
  66. 66. George JD, Vehrs PR, Allsen PE, Fellingham GW, Fisher AG. VO2max estimation from a submaximal 1-mile track jog for fit college-age individuals. Med Sci Sports Exerc. 1993;25:401–6. pmid:8455458
  67. 67. Getchell LH, Kirkendall D, Robbins G. Prediction of maximal oxygen uptake in young adult women joggers. Res Q. 1977;48:61–7. pmid:266255
  68. 68. Ghosh AK, Ahuja A, Khanna GL. Distance run as a predictor of aerobic endurance (VO2max) of sportsmen. Indian J Med Res. 1987;85:680–4. pmid:3679322
  69. 69. Grant S, Craig I, Wilson J, Aitchison T. The relationship between 3 km running performance and selected physiological variables. J Sports Sci. 1997;15:403–10. pmid:9293417
  70. 70. Grant JA, Joseph AN, Campagna PD. The prediction of VO2max: A comparison of 7 indirect tests of aerobic power. J Strength Cond Res. 1999;13:346–52.
  71. 71. Guo-jun W, Han W, Ya-qiong W. [Running economy versus maximal oxygen uptake to evaluate the endurance level of ordinary people]. Chin J Tissue Engineering Res. 2013;17:1265–72. Chinese.
  72. 72. Gutin B, Fogle RK, Stewart K. Relationship among submaximal heart rate, aerobic power, and running performance in children. Res Q. 1976;47:536–9. pmid:1069346
  73. 73. Gutin B, Torrey K, Welles R, Vytvytsky M. Physiological parameters related to running performance in college trackmen. J Hum Ergol (Tokyo). 1975;4:27–34.
  74. 74. Haines DA, Wilby K. Relationship between lung function and physical fitness in 9 to 15 year old Australian children. Aust J Sci Med Sport. 1993;25:35–9.
  75. 75. Hamlin MJ, Fraser M, Lizamore CA, Draper N, Shearman JP, Kimber NE. Measurement of cardiorespiratory fitness in children from two commonly used field tests after accounting for body fatness and maturity. J Hum Kinet. 2014;40:83–92. pmid:25031676
  76. 76. Hergenroeder AC, Schoene RB. Predicting maximum oxygen uptake in adolescents. Am J Dis Child. 1989;143:673–7. pmid:2729210
  77. 77. Howald H, Ehrsam R, Rüegger B, Meienhofer R, Mohler H, Oertli M, et al. [Conception and evaluation of a simple fitness test]. Schweiz Z Sportmed. 1975;23:57–92. German. pmid:1154006
  78. 78. Ingham SA, Whyte GP, Pedlar C, Bailey DM, Dunman N, Nevill AM. Determinants of 800-m and 1500-m running performance using allometric models. Med Sci Sports Exerc. 2008;40:345–50. pmid:18202566
  79. 79. Ishiko T. Aerobic capacity and external criteria of performance. CMAJ. 1967;96:746–9.
  80. 80. Jackson AS, Coleman AE. Validation of distance run tests for elementary school children. Res Q. 1976;47:86–94. pmid:1062833
  81. 81. Jackson A, der Weduwe K, Schick R, Sánchez R. An analysis of the validity of the three-mile run as a field test of aerobic capacity in college males. Res Q Exerc Sport. 1990;61:233–7. pmid:2097678
  82. 82. Jessup GT, Tolson H, Terry JW. Prediction of maximal oxygen intake from Astrand-Rhyming test, 12-minute, and anthropometric variables using stepwise multiple regression. Am J Phys Med. 1974;53:200–7. pmid:4843347
  83. 83. Katch FI, McArdle WD, Czula R, Pechar GS. Maximal oxygen intake, endurance running performance, and body composition in college women. Res Q. 1973;44:301–12.
  84. 84. Kirk SM, Weiglein L, Herrick J, Kirk EP. The one-mile walk and 1.5 mile run are valid assessments of cardiovascular fitness in air force servicemen. Med Sci Sports Exerc. 2014;46:S116.
  85. 85. Kitagawa K, Yamamoto K, Miyashita M. Maximal oxygen uptake, body composition and running performance in Japanese young adults of both sexes. In: Landry F, Orban WAR, editors: Proceedings of the International Congress of Physical Activity Sciences; 1976; Quebec, Canada: Symposia Specialist; 1978. p. 553–61.
  86. 86. Krahenbuhl GS, Pangrazi RP. Characteristics associated with running performance in young boys. Med Sci Sports Exerc. 1983;15:486–90. pmid:6656557
  87. 87. Krahenbuhl GS, Pangrazi RP, Burkett LN, Schneider MJ, Petersen G. Field estimation of VO2max in children eight years of age. Med Sci Sports. 1977;9:37–40. pmid:558493
  88. 88. Kumagai S, Tanaka K, Matsuura Y, Matsuzaka A, Hirakoba K, Asano K. Relationships of the anaerobic threshold with the 5 km, 10 km, and 10 mile races. Eur J Appl Physiol Occup Physiol. 1982;49:13–23. pmid:7201924
  89. 89. Larsen GE, George JD, Alexander JL, Fellingham GW, Aldana SG, Parcell AC. Prediction of maximum oxygen consumption from walking, jogging, or running. Res Q Exerc Sport. 2002;73:66–72. pmid:11926486
  90. 90. Lawrenz W, Stemper T. [Comparison of the 6-minute-jog-walk and maximal oxygen uptake in 8-10-year old school children]. Dtsch Z Sportmed. 2012;63:102–5. German.
  91. 91. Li LW, Shang YJ, Chorng LJ. Relationship between twelve minute walk-run and maximal oxygen consumption in university male students. Asian J Phys Educ. 1985;14:46–7.
  92. 92. Mahon AD, Del Corral P, Howe CA, Duncan GE, Ray ML. Physiological correlates of 3-kilometer running performance in male children. Int J Sports Med. 1996;17:580–4. pmid:8973978
  93. 93. Marsh HW, Ridge BR. The construct validity and generalisability of VO2max for boys and girls aged 9–15. Aust J Sci Med Sport. 1993;25:73–9.
  94. 94. Massicotte DR, Gauthier R, Markon P. Prediction of VO2max from the running performance in children aged 10–17 years. J Sports Med Phys Fitness. 1985; 25:10–7. pmid:4021462
  95. 95. Mayhew JL, Andrew J. Assessment of running performance in college males from aerobic capacity percentage utilization coefficients. J Sports Med Phys Fitness. 1975;15:342–6. pmid:1219212
  96. 96. McCormack WP, Cureton KJ, Bullock TA, Weyand PG. Metabolic determinants of 1-mile run/walk performance in children. Med Sci Sports Exerc. 1991;23:611–7. pmid:2072840
  97. 97. McCreight GA. Field estimation of cardiorespiratory fitness in young females, eight to eleven years of age [dissertation]. Vancouver: The University of British Columbia; 1982.
  98. 98. Mello RP, Murphy MM, Vogel JA. Relationship between the army two mile run test and maximal oxygen uptake. Fort Detrick (US): Army Research Institute of Environmental Medicine; 1984 Dec. Report No.: T3/85.
  99. 99. Myles WS, Brown TE, Pope JI. A reassessment of a running test as a measure of cardiorespiratory fitness. Ergonomics. 1980;23:543–7. pmid:7202398
  100. 100. Nevill AM, Ramsbottom R, Nevill ME, Newport S, Williams C. The relative contributions of anaerobic and aerobic energy supply during track 100-, 400-, and 800-m performance. J Sports Med Phys Fitness. 2008;48:138–42. pmid:18427406
  101. 101. Ong TC, Sothy SP. Exercise and cardiorespiratory fitness. Ergonomics. 1986;29:273–80. pmid:3956476
  102. 102. Paludo AC, Batista MB, Gobbo LA, Ronque ERV, Petroski EL, Serassuelo H. [Development of equations to estimate the VO2peak by the 9-minute test]. Rev Bras Med Esporte. 2014;20:176–80. Portuguese.
  103. 103. Paludo AC, Batista MB, Serassuelo H, Cyrino ES, Ronque ERV. Estimation of cardiorespiratory fitness in adolescents with the 9-minute run/walk test. Rev Bras Cineantrop Desemp Hum. 2012;14:401–8.
  104. 104. Penry JT. Validity and reliability analysis of Cooper's 12-minute run and the multistage shuttle run in healthy adults [dissertation]. Oregon: Oregon State University;2008.
  105. 105. Plowman SA, Liu NYS. Norm-referenced and criterion-referenced validity of the one-mile run and PACER in college age individuals. Meas Phys Educ Exerc Sci. 1999;3:63–84.
  106. 106. Pomerants T. Indirect measurement of maximal oxygen consumption in 14-16-year old adolescent girls [dissertation]. Tartu: University of Tartu; 2004.
  107. 107. Quinart S, Mougin F, Simon-Rigaud ML, Nicolet-Guénat M, Nègre V, Regnard J. Evaluation of cardiorespiratory fitness using three field tests in obese adolescents: Validity, sensitivity and prediction of peak VO2. J Sci Med Sport. 2014;17:521–5. pmid:23948247
  108. 108. Ramsbottom R, Brewer J, Williams C. A progressive shuttle run test to estimate maximal oxygen uptake. Br J Sports Med. 1988;22:141–4. pmid:3228681
  109. 109. Ramsbottom R, Nute MGL, Williams C. Determinants of five kilometre running performance in active men and women. Br J Sports Med. 1987; 21:9–13.
  110. 110. Ramsbottom R, Williams C, Boobis L, Freeman W. Aerobic fitness and running performance of male and female recreational runners. J Sports Sci. 1989;7:9–20. pmid:2733082
  111. 111. Ramsbottom R, Williams C, Kerwin DG, Nute MLG. Physiological and metabolic responses of men and women to a 5-km treadmill time trial. J Sports Sci. 1992;10:119–29. pmid:1588682
  112. 112. Rasch PJ. Maximal oxygen intake as a predictor of performance in running events. J Sports Med Phys Fitness. 1974;14:32–9. pmid:4847320
  113. 113. Redkva PE, Zagatto AM, Gomes EB, Kalva-Filho CA, Loures JP, Kaminagakura EI, et al. Prediction of aerobic performance in distance from 1200 to 2800 m for laboratory testing with military runners. J Exerc Physiol. 2012;15:107–14.
  114. 114. Rowland T, Kline G, Goff D, Martel L, Ferrone L. One-mile run performance and cardiovascular fitness in children. Arch Pediatr Adolesc Med. 1999;153:845–9. pmid:10437758
  115. 115. Scott BK, Houmard JA. Peak running velocity is highly related to distance running performance. Int J Sports Med. 1994;15:504–7. pmid:7890465
  116. 116. Slattery KM, Wallace LK, Murphy AJ, Coutts A. Physiological determinants of three-kilometer running performance in experienced triathletes. J Strength Cond Res. 2006;20:47–52. pmid:16506865
  117. 117. Sloniger MA, Cureton KJ, O'Bannon PJ. One-mile run-walk performance in young men and women: Role of anaerobic metabolism. Can J Appl Physiol. 1997;22:337–50. pmid:9263618
  118. 118. Soong PX, Leng YW, Hu QC. Validation of 1600-m run as a predictor of VO2max in Singapore children aged 10–12 years. Med Sci Sports Exerc. 2005;37:S17.
  119. 119. Sparling PB, Cureton KJ. Biological determinants of the sex difference in 12-min run performance. Med Sci Sports Exerc. 1983;15:218–23. pmid:6621309
  120. 120. Sporiš G. Validity of 2-mile run test for determination of VO2max among soldiers. J Sport Hum Perform. 2013;1:15–22.
  121. 121. Sporiš G, Harasin D, Baić M, Krističević T, Krakan I, Milanović Z, et al. The effects of basic fitness parameters on the implementation of specific military activities. Coll Antropol. 2014;38:165–71. pmid:25643545
  122. 122. Stratton E, O'Brien BJ, Harvey J, Blitvich J, McNicol AJ, Janissen D, et al. Treadmill velocity best predicts 5000-m run performance. Int J Sports Med. 2009;30:40–5. pmid:19202577
  123. 123. Sucec AA, Black DG, Mittleman KD. The interrelationship of VO2max, anaerobic threshold and 15 minute run performance. Int J Sports Med. 1982;3:66.
  124. 124. Sucec AA, Burks J, Buffington S, Trone D. Gender differences in prediction accuracy for lactate threshold and VO2max for middle distance races. Med Sci Sports Exerc. 1999;31:S379.
  125. 125. Suh SH, Kim KB. [Validity analysis and estimation for aerobic fitness of 3000m distance run in military fitness test]. Korean J Meas Eval Phys Educ Sport Sci. 2010;12:25–33. Korean.
  126. 126. Swisher AK, Goldfarb AH. Use of the six-minute walk/run test to predict peak oxygen consumption in older adults. Cardiopulm Phys Ther J. 1998;9:3–5.
  127. 127. Tanaka K, Matsuura Y, Moritani T. A correlational analysis of maximal oxygen uptake and anaerobic threshold as compared with middle and long distance performances. Jpn J Phys Fit Sports Med. 1981;30:94–102.
  128. 128. Tanaka K, Nakadomo F, Maeda K. Effects of jogging/running training on cardiorespiratory fitness, serum lipids, and body composition in healthy males. Ann Physiol Anthropol. 1988;7:31–8. pmid:3267244
  129. 129. Tanaka K, Takeshima N, Kato T, Niihata S, Ueda K. Critical determinants of endurance performance in middle-aged and elderly endurance runners with heterogeneous training habits. Eur J Appl Physiol Occup Physiol. 1990;59:443–9. pmid:2303049
  130. 130. Turley KR, Wilmore JH, Simons-Morton B, Williston JM, Epping JR, Dahlstrom G. The reliability and validity of the 9-minute run in third-grade children. Pediatr Exerc Sci. 1994;6:178–87.
  131. 131. Unnithan VB, Timmons JA, Paton JY, Rowland TW. Physiologic correlates to running performance in pre-pubertal distance runners. Int J Sports Med. 1995;16:528–33. pmid:8776207
  132. 132. Van Mechelen W, Hlobil H, Kemper HCG. Validation of two running tests as estimates of maximal aerobic power in children. Eur J Appl Physiol Occup Physiol. 1986;55:503–6. pmid:3769907
  133. 133. Vehrs PR, Quail JW, Jackson AS. VO2max estimation from self administration of the 1-mile track jog test. Med Sci Sports Exerc. 1996;28:S182.
  134. 134. Vodak PA, Wilmore JH. Validity of the 6-minute jog-walk and the 600-yard run-walk in estimating endurance capacity in boys, 9–12 years of age. Res Q. 1975;46:230–4. pmid:1056071
  135. 135. Von Haaren B, Härtel S, Seidel I, Schlenker L, Bös K. [Validity of a 6-min endurance run and a 20-m shuttle run in 9- to 11-year old children]. Dtsch Z Sportmed. 2011;62:351–5. German.
  136. 136. Walker LA, Sharp MA, Knapik JJ, Marín RE, Mello RP. Army physical fitness test 2-mile run correlates with peak oxygen uptake in infantry soldiers. Med Sci Sports Exerc. 2009;41:S101–S102.
  137. 137. Weiglein L, Herrick J, Kirk S, Kirk EP. The 1-mile walk test is a valid predictor of VO2max and is a reliable alternative fitness test to the 1.5-mile run in U.S Air Force males. Mil Med. 2011;176:669–73. pmid:21702386
  138. 138. Weltman A, Seip R, Bogardus AJ, Snead D, Dowling E, Levine S, et al. Prediction of lactate threshold (LT) and fixed blood lactate concentrations (FBLC) from 3200-m running performance in women. Int J Sports Med. 1990;11:373–8. pmid:2262230
  139. 139. Weltman J, Seip R, Levine S, Snead D, Rogol A, Weltman A. Prediction of lactate threshold and fixed blood lactate concentrations from 3200-m time trial running performance in untrained females. Int J Sports Med. 1989;10:207–11. pmid:2674038
  140. 140. Weltman A, Snead D, Seip R, Schurrer R, Levine S, Rutt R, et al. Prediction of lactate threshold and fixed blood lactate concentrations from 3200-m running performance in male runners. Int J Sports Med. 1987;8:401–6. pmid:3429086
  141. 141. Weyand PG, Cureton KJ, Conley DS, Sloniger MA, Liu YL. Peak oxygen deficit predicts sprint and middle-distance track performance. Med Sci Sports Exerc. 1994;26:1174–80. pmid:7808253
  142. 142. Wiley JF, Shaver LG. Prediction of maximum oxygen intake from running performances of untrained young men. Res Q. 1972;43:89–93. pmid:4503121
  143. 143. Yoshida T, Ishiko T. Physiological studies on cardiorespiratory response to exercise and validity of endurance tests in ten-year-old boys. In: Landry F, Orban WAR, editors: Proceedings of the International Congress of Physical Activity Sciences; 1976; Quebec, Canada: Symposia Specialist; 1978. p. 541–5.
  144. 144. Burns RD. Development and cross-validation of aerobic capacity prediction models in adolescent youth [dissertation]. Utah: University of Utah; 2014.
  145. 145. Castro-Piñero J, Mora J, González-Montesinos JL, Sjöström M, Ruiz JR. Criterion-related validity of 1-mile run/walk test in children aged 8–17 years. Med Sci Sports Exerc. 2009;41:S121.
  146. 146. Hamlin MJ, Fraser M, Lizamore CA, Fryer S, Draper N, Shearman JP, Kimber NE. Criterion-related validity of the 20-m shuttle and the 550-m distance run in 8–13 year-old children. Proceedings of the British Association for Sport and Exercise Science 2013 Conference; 2013 Sep 3–5; Preston; 2013
  147. 147. Sterne JAC, Gavaghan D, Egger M. Publication and related bias in meta-analysis: Power of statistical tests and prevalence in the literature. J Clin Epidemiol. 2000;53:1119–29. pmid:11106885
  148. 148. Terrin N, Schmid CP, Lau J. In an empirical evaluation of the funnel plot, researchers could not visually identify publication bias. J Clin Epidemiol. 2005;58:894–901. pmid:16085192
  149. 149. Cadenas-Sánchez C, Alcántara-Moral F, Sánchez-Delgado G, Mora-González J, Martínez-Téllez B, Herrador-Colmenero M, et al. [Assessment of cardiorespiratory fitness in preschool children: Adaptation of the 20 metres shuttle run test]. Nutr Hosp. 2014;30:1333–43. 0.3305/nh.2014.30.6.7859. Spanish. pmid:25433116
  150. 150. Midgley AW, Bentley DJ, Luttikholt H, McNaughton LR, Millet GP. Challenging a dogma of exercise physiology. Does an incremental exercise test for valid VO2max determination really need to last between 8 and 12 minutes? Sports Med. 2008;38:441–7. pmid:18489192
  151. 151. Castro-Piñero J, Ortega FB, Keating XD, González-Montesinos JL, Sjöstrom M, Ruiz JR. Percentile values for aerobic performance running/walking field tests in children aged 6 to 17 years; influence of weight status. Nutr Hosp. 2011; 26:572–8. pmid:21892577
  152. 152. Léger LA, Mercier D, Gadoury C, Lambert J. The multistage 20 meter shuttle run test for aerobic fitness. J Sports Sci. 1988;6:93–101. pmid:3184250
  153. 153. Council of Europe Committee for the Development of Sport. Eurofit Handbook for the EUROFIT tests of physical fitness. Rome: Edigraf Editoriale Grafica; 1988.
  154. 154. Riddoch CJ. The Northern Ireland health and fitness survey-1989: The fitness, physical activity, attitudes and lifestyles of Northern Ireland post-primary schoolchildren. The Queen’s University of Belfast, Belfast; 1990.
  155. 155. Fernhall B, Tymeson GT. Validation of cardiovascular fitness field tests for adults with mental retardation. Adapt Phys Activ Q. 1988;5:49–59.
  156. 156. Field AP. Meta-analysis of correlation coefficients: A Monte Carlo comparison of fixed- and random-effects methods. Psychol Methods. 2001;6:161–80. pmid:11411440
  157. 157. Field AP. Is the meta-analysis of correlation coefficients accurate when population correlations vary? Psychol Methods. 2005;10:444–67. pmid:16392999
  158. 158. Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med. 1998;26:217–38. pmid:9820922
  159. 159. Baumgartner TA, Jackson AS, Mahar MT, Rowe DA. Measurement for evaluation in kinesiology. 9th ed. Burlington: Jones & Bartlett Learning; 2015.
  160. 160. Rowland TW. Does peak VO2 reflect VO2max in children?: Evidence from supramaximal testing. Med Sci Sports Exerc. 1993;25:689–93. pmid:8321105
  161. 161. Midgley AW, McNaughton LR, Polman R, Marchant D. Criteria for determination of maximal oxygen uptake. Sports Med. 2007;37:1019–28. pmid:18027991