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Development of Quarter-Mile Walk Tests to Estimate Aerobic Fitness in Children

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Title: Development of Quarter-Mile Walk Tests to Estimate Aerobic Fitness in Children
Language: English
Authors: Matthew T. Mahar, Hoyong Sung
Source: Measurement in Physical Education and Exercise Science. 2025 29(2):212-219.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 8
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Physical Fitness, Test Construction, Exercise, Early Adolescents, Physical Activities, Test Validity, Measurement Techniques, Exercise Physiology, Body Composition, Preadolescents
DOI: 10.1080/1091367X.2024.2440072
ISSN: 1091-367X
1532-7841
Abstract: Field-based tests of aerobic fitness that can be administered quickly and do not require maximal effort are desirable. The purpose was to develop and validate quarter-mile walk tests for 10--13-year-olds. Participants (N = 59) walked one mile on two different days. Walk times, heart rates, body mass, physical activity, and aerobic fitness were assessed. Multiple regression was used to develop models to estimate VO[subscript 2max]. Quarter-mile walk models provided estimates of aerobic fitness that were similar in accuracy to previously published walk tests. The recommended model that balances accuracy and ease of administration was: VO[subscript 2max] = 119.691-(13.744*quarter-mile walk time [min])-(0.168*heart rate), R=0.73, SEE = 6.84 mL·kg[superscript -1]·min[superscript -1]. Walk times, heart rates, and estimated VO[superscript 2max] values were highly reliable. The walk tests developed provide valid estimates of VO[superscript 2max], are easy to administer, and could be particularly useful for unmotivated or overweight children when this equation is confirmed with a larger sample in group testing conditions.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1468494
Database: ERIC
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  Value: <anid>AN0184594852;7mm01apr.25;2025Apr22.02:30;v2.2.500</anid> <title id="AN0184594852-1">Development of Quarter-Mile Walk Tests to Estimate Aerobic Fitness in Children </title> <p>Field-based tests of aerobic fitness that can be administered quickly and do not require maximal effort are desirable. The purpose was to develop and validate quarter-mile walk tests for 10–13-year-olds. Participants (N = 59) walked one mile on two different days. Walk times, heart rates, body mass, physical activity, and aerobic fitness were assessed. Multiple regression was used to develop models to estimate VO<sub>2max</sub>. Quarter-mile walk models provided estimates of aerobic fitness that were similar in accuracy to previously published walk tests. The recommended model that balances accuracy and ease of administration was: VO<sub>2max</sub> = 119.691–(13.744*quarter-mile walk time [min])–(0.168*heart rate), R=.73, SEE = 6.84 mL·kg<sup>−1</sup>·min<sup>−1</sup>. Walk times, heart rates, and estimated VO<sub>2max</sub> values were highly reliable. The walk tests developed provide valid estimates of VO<sub>2max</sub>, are easy to administer, and could be particularly useful for unmotivated or overweight children when this equation is confirmed with a larger sample in group testing conditions.</p> <p>Keywords: submaximal test; fitness test; estimated VO2max; youth fitness; field test</p> <p>Aerobic fitness (VO<subs>2max</subs>) is difficult to assess directly in field-based settings on large numbers of participants. School-based fitness tests, in particular, must be able to assess multiple students in a limited time. Several field-based tests, such as the PACER (Mahar et al., [<reflink idref="bib22" id="ref1">22</reflink>]), one-mile run (Cureton et al., [<reflink idref="bib8" id="ref2">8</reflink>]), and one-mile walk (Sung et al., [<reflink idref="bib26" id="ref3">26</reflink>]) are available. To obtain valid estimates of aerobic fitness from the PACER and one-mile run tests, participants must provide maximal effort, which can be challenging for unmotivated children. The one-mile walk test can be performed at a submaximal effort, but the time to walk one mile may be too long (approximately 15 minutes) for feasible use in some settings.</p> <p>A walk test shorter than one mile that does not require maximal effort may provide a practical alternative test of aerobic fitness. Limited research has been conducted on walk tests for children, especially for children under 14 years of age. The first one-mile walk test was developed by Kline et al. ([<reflink idref="bib15" id="ref4">15</reflink>]) on participants aged 30–69 years. Accuracy of the Kline et al. equation was supported on high-school students (<emph>SEE</emph> = 4.99 mL·kg<sups>−1</sups>·min<sups>−1</sups>; McSwegin et al., [<reflink idref="bib23" id="ref5">23</reflink>]), but was less accurate for lower-fit college-age participants (systematic overestimation of measured VO<subs>2max</subs> and low to moderate correlations between measured and estimated VO<subs>2max</subs>; Dolgener et al., [<reflink idref="bib10" id="ref6">10</reflink>]). Dolgener et al. ([<reflink idref="bib10" id="ref7">10</reflink>]) developed one-mile walk equations to estimate aerobic fitness in college-age participants. These equations used one-mile walk time, the heart rate response, age, sex, and body mass to estimate VO<subs>2max</subs>.</p> <p>Few studies have examined the validity of walk tests for distances shorter than one mile (Greenhalgh et al., [<reflink idref="bib12" id="ref8">12</reflink>]). Greenhalgh et al. ([<reflink idref="bib12" id="ref9">12</reflink>]) multiplied quarter-mile walk time by four to achieve one-mile walk equivalents and then cross-validated the Kline et al. ([<reflink idref="bib15" id="ref10">15</reflink>]) and the Dolgener et al. ([<reflink idref="bib10" id="ref11">10</reflink>]) one-mile walk equations on college-age participants. They concluded that the prediction accuracy for VO<subs>2max</subs> was similar for the one-mile walk and the quarter-mile walk (Total Error = 4.12 and 4.80 mL·kg<sups>−1</sups>·min<sups>−1</sups> for the Kline et al. model and Total Error = 7.93 and 7.07 mL·kg<sups>−1</sups>·min<sups>−1</sups> for the Dolgener et al. model, for the one-mile and quarter-mile walk models, respectively).</p> <p>The 6-minute walk test was developed to assess functional capacity for individuals with various heart or lung diseases (American Thoracic Society, [<reflink idref="bib2" id="ref12">2</reflink>]). The few studies that provide validity evidence for the ability of this test to estimate VO<subs>2max</subs> in children report low correlations between distance walked and measured VO<subs>2max</subs>. Calders et al. ([<reflink idref="bib6" id="ref13">6</reflink>]) reported correlations of.33 and.46 (<emph>SEE</emph> not reported; mean distance walked = 6.53 ± 96 m) between 6-minute walk test performance and measured VO<subs>2max</subs> in 65 obese children and adolescents. Li et al. ([<reflink idref="bib19" id="ref14">19</reflink>]) reported a correlation of.44 (<emph>SEE</emph> not reported; mean distance walked = 660 ± 58 m) between 6-minute walk test performance and measured VO<subs>2max</subs> in 74 healthy adolescents. The few other studies that examined the validity evidence for the estimation of VO<subs>2max</subs> from 6-minute walk test performance were conducted on small samples of diseased patients (Gulmans et al., [<reflink idref="bib13" id="ref15">13</reflink>] [<emph>N</emph> = 15]; Lelieveld et al., [<reflink idref="bib18" id="ref16">18</reflink>] [<emph>N</emph> = 22]; Nixon et al., [<reflink idref="bib24" id="ref17">24</reflink>] [<emph>N</emph> = 17]).</p> <p>The purpose of this study was to develop and examine the validity and reliability of quarter-mile walk test regression equations to predict aerobic fitness in children aged 10–13 years.</p> <hd id="AN0184594852-2">Methods</hd> <p></p> <hd id="AN0184594852-3">Participants</hd> <p>Sixty-one participants (30 boys and 31 girls) aged 10–13 years were recruited for the study. This sample size is slightly lower than the sample sizes used in the 6-minute walk test studies cited above. The necessary sample size for regression studies interested in accurate estimation of regression coefficients, standard errors, and confidence intervals has been shown to be as low as two subjects per variable (Austin & Steyerberg, [<reflink idref="bib4" id="ref18">4</reflink>]). Various rules-of-thumb for sample size for regression studies have been proposed, with Tabachnick and Fidell ([<reflink idref="bib27" id="ref19">27</reflink>]) suggesting a minimum subject-per-variable ratio of five. Green ([<reflink idref="bib11" id="ref20">11</reflink>]) provided a rule-of-thumb that incorporated estimates of effect size (quantified using R<sups>2</sups> as proposed by Cohen, [<reflink idref="bib7" id="ref21">7</reflink>]) and based on their rule-of-thumb assuming a large effect size (i.e.,.26), a sample size of 38 is recommended for five predictor variables (and <emph>N</emph> = 44 is recommended for seven predictor variables). While it is acknowledged that larger sample sizes generally yield more stable results, the sample size for this study, though relatively small, is sufficient for the purpose of proposing the initial quarter-mile walk test model to estimate VO<subs>2max</subs> within this specific age group. The study's largest model (Model 1 in Table 3) examines up to five predictors simultaneously, maintaining a subject-per-variable ratio greater than 10. Although the sample size was small compared to other studies of field tests used to estimate VO<subs>2max</subs>, it is the largest sample of this age group to be studied relative to walking tests used to estimate aerobic fitness. In addition, the predicted residual error sum of squares (PRESS) statistic (Holiday et al., [<reflink idref="bib14" id="ref22">14</reflink>]) was used for cross-validation so that the sample did not have to be divided into validation and cross-validation groups.</p> <p>Participants received $20 for participation, and parents received $5 for transporting their children to the research site. The study was approved by the university Institutional Review Board. Written informed consent was obtained from the participant's parent or guardian and assent was obtained from the participant. Participants were screened for cardiovascular and orthopedic contraindications to a maximal treadmill test with the Physical Activity Readiness Questionnaire (American College of Sports Medicine, [<reflink idref="bib1" id="ref23">1</reflink>]). No participants had contraindications, and none were taking medication that could influence the heart rate response during exercise.</p> <hd id="AN0184594852-4">Procedures and measurements</hd> <p>Testing took place in two sessions with at least 1 week between sessions. During the first session, height, body mass, and percent body fat were assessed. Participants also completed the first trial of the walk test. During the next session, the second trial of the walk test was administered. A maximal treadmill test was completed either during the first or second session (the visit for the maximal treadmill test was randomly selected) following adequate rest after the walk test. Self-reported physical activity was assessed at both sessions with the 30-Day Physical Activity Recall (30-Day PAR) (Baumgartner et al., [<reflink idref="bib5" id="ref24">5</reflink>]) to examine the reliability of responses over 1 week. The 30-Day PAR asks participants to rate their overall level of physical activity for the previous month on a 0 to 7 scale, with higher scores representing higher levels of physical activity (see Figure 1). Height was measured with a stand-alone stadiometer to the nearest 0.1 cm (model 217, Seca Corporation, Birmingham, UK). Body mass was measured with an electronic scale (COSMED USA, Inc., Concord, CA) to the nearest 0.1 kg. Percent body fat was assessed with the BOD POD (BOD POD Body Composition System, COSMED USA, Inc. Concord, CA). The Lohman ([<reflink idref="bib20" id="ref25">20</reflink>]) density model was used to estimate the percentage of body fat.</p> <p>Graph: Figure 1. 30-day physical activity recall.</p> <hd id="AN0184594852-5">Walk test</hd> <p>Participants walked one mile indoors on a measured course. The course was oval with approximately eight laps per mile. Times and heart rates (Polar Electro Incorporation, Woodbury, NY) were recorded at quarter-mile, half-mile, and one-mile walk distances. The tester timed the walk with a stopwatch and used the heart rate monitor receiver to record heart rates. Preparation for the walk test included asking participants to walk at slow, medium, and fast paces. The tester then asked, "which pace do you think you can keep constant for one mile?" Participants were instructed to walk at the chosen pace constantly for the entire distance. The tester walked with the participant and provided verbal encouragement.</p> <hd id="AN0184594852-6">Maximal treadmill test</hd> <p>VO<subs>2max</subs> was measured during a graded exercise test for volitional exhaustion on a Trackmaster (model TMX425C, Carrollton, TX) treadmill following the procedures of Mahar et al. ([<reflink idref="bib21" id="ref26">21</reflink>]). Treadmill speed was set at 2.5 mph (2.0 mph for unfit participants) for the first minute and increased by 0.5 mph each minute until 5.0 mph (4.0 mph for unfit) was reached. Treadmill grade was maintained at 0% until 5.0 or 4.0 mph was reached. After reaching 5.0 mph (4.0 mph for unfit), speed was maintained, and grade was increased by 3% (2% for unfit) each minute until the participant was no longer able to continue. For the purposes of treadmill testing, unfit was defined as a participant with a body mass index (BMI) over 30 kg·m<sups>−2</sups> or a participant who took more than 20 min to complete the one-mile walk. VO<subs>2</subs> of participants was measured during the treadmill test using a COSMED K4b<sups>2</sups> portable metabolic system (COSMED USA, Inc., Concord, CA). VO<subs>2max</subs> was accepted as a maximal index if two of the following three conditions were satisfied: (a) signs of intense effort such as hyperpnea, facial flushing and grimacing, unsteady gait, and sweating; (b) maximal heart rate reaching a value of at least 90% of age-predicted maximal heart rate (208–0.7*age); and (c) respiratory exchange ratio greater than or equal to 1.0 (Armstrong & Welsman, [<reflink idref="bib3" id="ref27">3</reflink>]; Mahar et al., [<reflink idref="bib21" id="ref28">21</reflink>]; Tanaka et al., [<reflink idref="bib28" id="ref29">28</reflink>]).</p> <hd id="AN0184594852-7">Statistical analysis</hd> <p>Data from the quarter-mile and half-mile of the first walk test were used to develop new equations. Initial predictor variables included sex, body mass, BMI, percent body fat, 30-Day PAR, walk time, and heart rate. Because correlations between measured and estimated VO<subs>2max</subs> were similar for the quarter-mile and half-mile distances and because quarter-mile walk distance is more practical to administer than the half-mile distance, current results focus on the quarter-mile walk data. Walk time, heart rate, sex, body mass, and 30-Day PAR were used as final predictors.</p> <p>Reliability estimates for the following variables for the two test sessions were calculated with an intraclass correlation using a one-way model (Baumgartner et al., [<reflink idref="bib5" id="ref30">5</reflink>]): 30-Day PAR, quarter-mile walk time, heart rate, and estimated VO<subs>2max</subs>. Equivalence testing (Dixon et al., [<reflink idref="bib9" id="ref31">9</reflink>]; Lakens et al., [<reflink idref="bib16" id="ref32">16</reflink>]) was used to determine whether differences between the first and second sessions for these variables were statistically equivalent. Effect size (<emph>ES</emph>) was calculated using Cohen's delta as shown below.</p> <p> <emph>ES</emph> = (Mean of 1<sups>st</sups> session – Mean of 2<sups>nd</sups> session)/(Mean of standard deviations of 1<sups>st</sups> and 2<sups>nd</sups> sessions)</p> <p>Multiple regression was used to estimate measured VO<subs>2max</subs>. The variables of heart rate, sex, body mass, and 30-Day PAR were excluded from or added to other variables to examine whether that variable contributed significantly to the prediction of measured VO<subs>2max</subs>. Visual inspection of bivariate scatterplots demonstrated no multivariate outliers. In addition, inspection of the scatterplots between the estimated and measured VO<subs>2max</subs> showed no multivariate outliers. A plot of the residuals vs. predicted values showed no pattern of increasing or decreasing variance, suggesting that the assumption of homoscedasticity was not violated.</p> <p>The developed equations were cross-validated with the PRESS-related statistic (Holiday et al., [<reflink idref="bib14" id="ref33">14</reflink>]). Prediction accuracy of newly developed equations were examined by producing PRESS <emph>R</emph><sups><emph>2</emph></sups> (<emph>R</emph><subs><emph>p</emph></subs><sups><emph>2</emph></sups>) and PRESS <emph>SEE</emph> (<emph>SEE</emph><subs><emph>p</emph></subs>) from cross-validation on all of the data. <emph>R</emph><subs><emph>p</emph></subs><sups><emph>2</emph></sups> was calculated as: <emph>R</emph><subs><emph>p</emph></subs><sups><emph>2</emph></sups> = 1 – [Sum of Squares of PRESS residual/Sum of Squares (total)]. <emph>SEE</emph><subs><emph>p</emph></subs> was calculated as: <emph>SEE</emph><subs><emph>p</emph></subs> = √Sum of Squares of PRESS residual/N. Data were analyzed using IBM SPSS Statistics version 24.</p> <hd id="AN0184594852-8">Results</hd> <p>Among 61 participants, two participants did not reach the criteria for maximal exertion during the maximal treadmill test (American College of Sports Medicine, [<reflink idref="bib1" id="ref34">1</reflink>]). Thus, data from the remainder of the participants (<emph>n</emph> = 59) were used to develop the quarter-mile walk regression equations.</p> <p>Participant characteristics are described in Table 1. Based on BMI percentile, 14% of the participants were obese (BMI ≥ 95<sups>th</sups> percentile), 8% were overweight (85<sups>th</sups> percentile ≤ BMI ≤ 94<sups>th</sups> percentile), 5% were underweight (BMI ≤ 4<sups>th</sups> percentile), and the rest (73%) were healthy weight (5<sups>th</sups> percentile ≤ BMI ≤ 84<sups>th</sups> percentile).</p> <p>Table 1. Participant characteristics (<emph>M ± SD</emph>).</p> <p> <ephtml> <table><thead><tr><td>Variable</td><td>Boys (<italic>n</italic> = 29)</td><td>Girls (<italic>n</italic> = 30)</td><td>Combined (<italic>N</italic> = 59)</td></tr></thead><tbody><tr><td>Age (years) Height (cm)</td><td>11.5 ± 1.2</td><td>11.8 ± 1.1</td><td>11.6 ± 1.1</td></tr><tr><td>151.2 ± 9.1</td><td>151.8 ± 8.7</td><td>151.5 ± 8.8</td></tr><tr><td>Body Mass (kg) BMI (kg/m<sup>2</sup>) BMI percentile BMI z-score</td><td>43.5 ± 12.9</td><td>51.6 ± 22.1</td><td>47.6 ± 18.5</td></tr><tr><td>18.7 ± 3.7</td><td>22.2 ± 9.6</td><td>20.5 ± 7.4</td></tr><tr><td>49.9 ± 32.8</td><td>56.8 ± 28.9</td><td>53.3 ± 30.8</td></tr><tr><td>0.01 ± 1.12</td><td>0.33 ± 1.11</td><td>0.17 ± 1.14</td></tr><tr><td>Body Fat (%)</td><td>20.9 ± 9.2</td><td>25.0 ± 11.6</td><td>23.0 ± 10.6</td></tr><tr><td>30-Day PAR</td><td /><td /><td /></tr><tr><td> 1<sup>st</sup> session</td><td>4.2 ± 2.0</td><td>4.6 ± 2.3</td><td>4.4 ± 2.1</td></tr><tr><td> 2<sup>nd</sup> session</td><td>4.7 ± 1.9</td><td>4.5 ± 2.2</td><td>4.6 ± 2.1</td></tr><tr><td>Measured VO<sub>2max</sub> (mL·kg<sup>−1</sup>·min<sup>−1</sup>)</td><td>46.1 ± 7.7</td><td>39.4 ± 10.9</td><td>42.7 ± 10.0</td></tr><tr><td>Estimated VO<sub>2max</sub> (mL·kg<sup>−1</sup>·min<sup>−1</sup>)</td><td>44.3 ± 4.4</td><td>41.1 ± 9.02</td><td>42.7 ± 7.3</td></tr><tr><td>Maximal heart rate (b·min<sup>−1</sup>)</td><td>196.8 ± 6.5</td><td>201.3 ± 9.3</td><td>199.1 ± 8.3</td></tr><tr><td>Maximal RER</td><td>1.15 ± 0.10</td><td>1.15 ± 0.13</td><td>1.15 ± 0.12</td></tr></tbody></table> </ephtml> </p> <p>1 Percent body fat was measured from BOD POD; 30-Day PAR, 30-Day Physical Activity Recall; Estimated VO<subs>2max</subs> was estimated by quarter-mile Model 5 using 1<sups>st</sups> session data; RER, respiratory exchange ratio. The range of scores for measured VO<subs>2max</subs> was 15 to 60 mL·kg<sups>−1</sups>·min<sups>−1</sups>.</p> <p>The differences between the first and second sessions for the 30-Day PAR, walk time, heart rate, and estimated VO<subs>2max</subs> were compared and reliability was estimated as shown in Table 2. The <emph>ICCs</emph> were high, ranging between.82 and.95. Using standard 10% equivalence zones, the means from session 1 and session 2 were statistically equivalent. The effect sizes for the differences between session 1 and session 2 were small (≤0.20). Mean heart rates were similar at the quarter-mile, half-mile, and one-mile distances, indicating that participants maintained a steady walking pace.</p> <p>Table 2. Comparison of Quarter-mile Walk Time, heart rate, and VO<subs>2</subs> max estimation between 1<sups>st</sups> and 2<sups>nd</sups> sessions.</p> <p> <ephtml> <table><thead><tr><td>Variable</td><td>1<sup>st</sup> session</td><td>2<sup>nd</sup> session</td><td><italic>ICC</italic> (2 trials)</td><td><italic>ICC</italic> (1 trial)</td><td><italic>ES</italic></td><td><italic>Min-Max</italic></td></tr></thead><tbody><tr><td>30-day PAR</td><td>4.41 ± 2.13</td><td>4.59 ± 2.05</td><td>.86</td><td>.76</td><td>0.09</td><td>0–7</td></tr><tr><td>Walk Time ¼-mile (min)</td><td>3.85 ± 0.49</td><td>3.75 ± 0.58</td><td>.88</td><td>.81</td><td>0.20</td><td>3.02–5.95</td></tr><tr><td>HR ¼-mile (b.min<sup>−1</sup>)</td><td>143 ± 19</td><td>146 ± 19</td><td>.82</td><td>.69</td><td>0.11</td><td>112–189</td></tr><tr><td>Estimated VO<sub>2</sub>max (mL.kg<sup>−1.</sup>min<sup>−1</sup>)</td><td>42.7 ± 7.3</td><td>43.7 ± 8.0</td><td>.95</td><td>.91</td><td>0.14</td><td>11–53</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>M ± SD</emph>; <emph>ICC</emph> is intra-class correlation coefficient (consistency model); <emph>ES</emph> is effect size; <emph>Min-Max</emph> is the range of values; HR is heart rate; Estimated VO<subs>2</subs>max was estimated by Model 5, which included ¼-mile Walk Time and Heart Rate as predictors.</p> <p>Correlations between the measured VO<subs>2max</subs> and predictor variables were as follows: body mass (<emph>r</emph> = −.84), quarter-mile walk time (<emph>r</emph> = −.65), 30-Day PAR (<emph>r</emph> =.53), sex [F = 0, <emph>M</emph> = 1] (<emph>r</emph> =.34), and heart rate (<emph>r</emph> = −.26). All predictor variables were significantly correlated with the measured VO<subs>2max</subs> (<emph>p</emph> <.05).</p> <p>Regression coefficients to estimate measured VO<subs>2max</subs> for the quarter-mile walk test at the first session are described in Table 3. For Model 1, in which all predictor variables were entered, the multiple <emph>R</emph> and <emph>SEE</emph> were.92 and 4.03 mL·kg<sups>−1</sups>·min<sups>−1</sups>, respectively. Model 2 excluded 30-Day PAR as a predictor and accuracy was only slightly diminished relative to Model 1.</p> <p>Table 3. Regression coefficients to estimate VO<subs>2</subs>max (mL.kg<sups>−1.</sups>min<sups>−1</sups>) for quarter-mile data (<emph>N</emph> = 59).</p> <p> <ephtml> <table><thead><tr><td>Variable</td><td>Model 1</td><td>Model 2</td><td>Model 3</td><td>Model 4</td><td>Model 5</td><td>Model 6</td></tr></thead><tbody><tr><td>Intercept</td><td>65.534 (48.592, 82.476)</td><td>82.840 (65.041, 100.639)</td><td>87.518 (65.232, 109.803)</td><td>112.915 (91.598, 134.233)</td><td>119.691 (98.897, 140.485)</td><td>93.423 (77.696, 109.149)</td></tr><tr><td>Time (min)</td><td>−4.031* (−7.063, −0.998)</td><td>−5.214* (−8.718, −1.710)</td><td>−10.640* (−14.067, −7.212)</td><td>−13.061* (−16.741, −9.382)</td><td>−13.744* (−17.460, −10.028)</td><td>−13.177* (−17.227, −9.128)</td></tr><tr><td>HR (b.min<sup>−1</sup>)</td><td>−0.003 (−0.070, 0.064)</td><td>−0.036 (−0.113, 0.040)</td><td>−0.096* (−0.183, −0.009)</td><td>−0.152* (−0.246, −0.057)</td><td>−0.168* (−0.264, −0.072)</td><td>–</td></tr><tr><td>Sex (<italic>M</italic> = 1, F = 0)</td><td>3.950* (1.625, 6.275)</td><td>2.868* (0.198, 5.538)</td><td>4.959* (1.711, 8.207)</td><td>3.691* (0.052, 7.331)</td><td>–</td><td>–</td></tr><tr><td>Body Mass (kg)</td><td>−0.310* (−0.395, −0.226)</td><td>−0.343* (−0.441, −0.245)</td><td>–</td><td>–</td><td>–</td><td>–</td></tr><tr><td>30-Day PAR</td><td>1.344* (0.760, 1.928)</td><td>–</td><td>1.696* (0.885, 2.506)</td><td>–</td><td>–</td><td>–</td></tr><tr><td><italic>R</italic></td><td>.92</td><td>.88</td><td>.82</td><td>.75</td><td>.73</td><td>.65</td></tr><tr><td><italic>R</italic><sup><italic>2</italic></sup></td><td>.84</td><td>.77</td><td>.67</td><td>.56</td><td>.53</td><td>.43</td></tr><tr><td><italic>SEE</italic> (mL.kg<sup>−1.</sup>min<sup>−1</sup>)</td><td>4.03</td><td>4.78</td><td>5.73</td><td>6.60</td><td>6.84</td><td>7.55</td></tr><tr><td><italic>R</italic><sub><italic>p</italic></sub><sup><italic>2</italic></sup></td><td>.80</td><td>.71</td><td>.61</td><td>.49</td><td>.48</td><td>.39</td></tr><tr><td><italic>SEE</italic><sub><italic>p</italic></sub> (mL.kg<sup>−1.</sup>min<sup>−1</sup>)</td><td>4.47</td><td>5.34</td><td>6.19</td><td>7.03</td><td>7.16</td><td>7.75</td></tr></tbody></table> </ephtml> </p> <p>3 HR is heart rate; <emph>SEE</emph> is standard error of estimate; <emph>R</emph><subs><emph>p</emph></subs><sups><emph>2</emph></sups> and <emph>SEE</emph><subs><emph>p</emph></subs> are PRESS <emph>R</emph><sups><emph>2</emph></sups> and PRESS <emph>SEE</emph> respectively; * <emph>p</emph> <.05, statistically significant variable for prediction. 95% CI of regression coefficients are shown within parentheses.</p> <p>Models 3 through 6 excluded body mass as a predictor so that prediction of VO<subs>2max</subs> in heavy participants was not unduly influenced by body mass. In Model 3, all variables were significant predictors of measured VO<subs>2max</subs>. The multiple <emph>R</emph> and <emph>SEE</emph> for Model 3 were.82 and 5.73 mL·kg<sups>−1</sups>·min<sups>−1</sups>, respectively. Model 3 was less accurate compared to Model 1, which included body mass as a predictor.</p> <p>Model 6, which included only quarter-mile walk time in the model, had lower prediction accuracy than the other models examined. Model 5, which included quarter-mile walk time and heart rate in the model, had a prediction accuracy similar to that of Model 4, which also included sex as a predictor. Note that the multiple <emph>R</emph> in Model 5 was lower than for Model 3 (.73 vs..82) and the <emph>SEE</emph> was higher (6.84 vs. 5.73 mL·kg<sups>−1</sups>·min<sups>−1</sups>), indicating that excluding self-reported physical activity and sex from the model decreased prediction accuracy.</p> <p>The prediction models in Table 3 were estimated from data collected during the first session. To allow an estimate of reliability, VO<subs>2max</subs> was estimated from Model 5 using data from the first and second sessions. Estimated VO<subs>2max</subs> and <emph>ICC</emph> reliability estimates are presented in Table 2. Estimated VO<subs>2max</subs> was highly reliable (<emph>ICC</emph> ≥.95) and mean estimated VO<subs>2max</subs> for the first and second sessions differed by only 1 mL·kg<sups>−1</sups>·min<sups>−1</sups>.</p> <hd id="AN0184594852-9">Discussion</hd> <p>This study aimed to develop and validate regression equations to estimate VO<subs>2max</subs> in young children using quarter-mile walk tests. The results demonstrate that quarter-mile walk tests can provide accurate and reliable estimates of VO<subs>2max</subs> in this age group. The most accurate model, which includes body mass, heart rate, and self-reported physical activity, offers a practical and efficient tool for assessing aerobic fitness in children.</p> <p>Six different models were developed to examine the effect of various predictors on the estimated VO<subs>2max</subs>. Because practitioners in some field-based settings (e.g., schools) may prefer models that do not require body mass (e.g., because of feasibility, acceptance, and participant embarrassment), four models without body mass as a predictor were evaluated. In general, models without body mass were less accurate than those with body mass. Models with body mass as a predictor variable explain about 15% to 20% more variance in VO<subs>2max</subs> than comparable models without body mass as a predictor. In this study, participants rated their physical activity for the previous month using the 30-Day PAR, a self-rating that can be quickly administered. Models without the 30-Day PAR measure of self-reported physical activity were less accurate than models with the 30-Day PAR as a predictor. Models with the 30-Day PAR as a predictor variable explain about 7% to 11% more variance in VO<subs>2max</subs> than comparable models without the 30-Day PAR as a predictor. Children's perception of their physical activity levels was relatively highly related to their aerobic fitness level, and self-reported physical activity was a significant predictor in the regression models.</p> <p>The quarter-mile models developed in the current study provide several options for the estimation of VO<subs>2max</subs> in young children. Model 1 is the most accurate model developed in the current study and could be appropriately used in a clinical setting where children would be more likely than in a mass testing environment to provide a true answer for their self-reported physical activity. In a school setting, where it might be difficult to assess many students on self-reported physical activity or where students might be tempted to overestimate their physical activity to achieve a higher predicted VO<subs>2max</subs>, Models 5 or 6 provide potential options. The most feasible model is Model 6 which requires only the measurement of time to walk a quarter mile, but Model 5 should be considered because it provides the opportunity to teach children about the relationship between exercise heart rate and aerobic fitness. Because the use of body mass and sex in prediction models can make explanation of results difficult for teachers and because the inclusion of sex in the models (i.e., Model 4 compared to Model 5) did not substantially enhance prediction accuracy, it appears that Model 5 is an appropriate model to use in school settings.</p> <p>Accuracy of the newly developed regression equations was similar to 1-mile walk equations presented by Sung et al. ([<reflink idref="bib26" id="ref35">26</reflink>]) and more accurate than other previously published one-mile walk equations. For the full model (Model 1) in the current study, the correlation between measured and estimated VO<subs>2max</subs> was.92 (<emph>SEE</emph> = 4.03 mL·kg<sups>−1</sups>·min<sups>−1</sups>), which was as high or higher than the multiple correlations reported by Sung et al. (<emph>R</emph> =.90, <emph>SEE</emph> 3.99 mL·kg<sups>−1</sups>·min<sups>−1</sups>), Kline et al. (<emph>R</emph> =.88; <emph>SEE</emph> 4.4 mL·kg<sups>−1</sups>·min<sups>−1</sups>), and Dolgener et al. (<emph>R</emph> =.71, <emph>SEE</emph> 5.33 mL·kg<sups>−1</sups>·min<sups>−1</sups>) for their full models.</p> <p>The accuracy of the quarter-mile walk test developed in this study compares favorably to other field tests of aerobic fitness, such as the one-mile run/walk and PACER tests. The one-mile run/walk equation developed by Cureton et al. ([<reflink idref="bib8" id="ref36">8</reflink>]) has been used to estimate VO<subs>2max</subs> for children in the FITNESSGRAM<sups>Ⓡ</sups>. Cureton et al. reported a multiple <emph>R</emph> =.71 and <emph>SEE</emph> = 4.78 mL·kg<sups>−1</sups>·min<sups>−1</sups> for the 1-mile run/walk regression equation in a large sample aged 8–25 years. Mahar et al. ([<reflink idref="bib22" id="ref37">22</reflink>]) reported a multiple <emph>R</emph> =.71 and <emph>SEE</emph> = 6.52 for a PACER model in a 10–18-year-old sample. The newly developed quarter-mile walk test (Model 1) had a multiple <emph>R</emph> =.92 and <emph>SEE</emph> = 4.03 mL·kg<sups>−1</sups>·min<sups>−1</sups> for 10–13-year-old children in the current study. <emph>SEEs</emph> from different studies are not directly comparable because the standard deviation of the predicted variable, which differs from study to study, is used in the calculation of the <emph>SEE</emph>, but correlations and multiple-correlation coefficients from different studies may provide some indication about relative accuracy.</p> <p>Heart rate responses were similar among the quarter-mile, half-mile, and one-mile distances (data not shown). This indicates that participants maintained a relatively steady walking pace throughout the entire distance. The average time to walk one mile was about 16 minutes. This is much longer than other aerobic fitness field tests and likely limits its use in some situations. The quarter-mile distance is a more appropriate distance for young children than 1-mile and accuracy for the quarter-mile models was similar to that of the half-mile and one-mile models (Sung et al., [<reflink idref="bib26" id="ref38">26</reflink>]).</p> <p>Heart rate was a significant predictor of VO<subs>2max</subs>, except in the models in which body mass was included. Measured VO<subs>2max</subs> and heart rate were significantly correlated, but the correlation was weak (<emph>r</emph> = −.26). Kline et al. ([<reflink idref="bib15" id="ref39">15</reflink>]) reported a weak correlation between measured VO<subs>2</subs> (L·min<sups>−1</sups>) and heart rate (<emph>r</emph> = −.14) but did not state whether heart rate was a significant predictor of VO<subs>2max</subs> in their regression equation. Similarly, Dolgener et al. ([<reflink idref="bib10" id="ref40">10</reflink>]) did not state whether heart rate was a significant predictor of VO<subs>2max</subs> or was significantly correlated with VO<subs>2max</subs>. In the current study, inclusion of the walk time and heart rate interaction term did not add significantly to the prediction of VO<subs>2max</subs> after walk time and heart rate were entered into the model. Overall, including heart rate (e.g., Model 5) as a predictor adds significantly to accuracy of the regression model and is both logical (i.e., higher submaximal heart rates at the same walking pace suggests lower levels of aerobic fitness) and a useful teaching tool in school settings. Measurement of heart rate during walking tests, however, increases the burden on the tester, and Model 6 provides an equation to estimate VO<subs>2max</subs> only from quarter-mile walk time. Model 6 should only be used in testing situations in which the walk remains at a submaximal level (average heart rate in the current study was only 143 b·min<sups>−1</sups>) and participants do not perceive competition with other participants causing them to walk faster and faster.</p> <p>Reliability of estimated VO<subs>2max</subs> (<emph>ICC</emph> =.95) in the present study was higher than that reported by Léger et al. ([<reflink idref="bib17" id="ref41">17</reflink>]) from the PACER test (<emph>ICC</emph> =.89). In addition, the heart rate (<emph>ICC</emph> =.82) and walk time for the quarter-mile (<emph>ICC</emph> ≥.88) between first and second session were highly reliable. The <emph>ICC</emph> for walk time in the current study was similar to the <emph>ICC</emph> for one-mile run/walk time (<emph>ICC</emph> ≥.85) from grade 4 children reported by Rikli et al. ([<reflink idref="bib25" id="ref42">25</reflink>]). Therefore, the newly developed quarter-mile walk tests appear to provide reliable estimates of VO<subs>2max</subs> in children.</p> <p>This is the first study to develop quarter-mile walk tests for 10–13-year-old children. A major strength of the study is that practical and accurate quarter-mile walk tests for children were developed. The quarter-mile walk test is simple to take and can be administered in a short amount of time, making it practical for use in schools. Another strength of this study is that six different models were developed, so teachers or researchers can choose one of the models depending on their circumstances. Reliability and validity evidence were provided for the new walk test equations. Additionally, evidence of some degree of representativeness of the sample used in the current study can be provided by comparison with data from the National Health and Nutrition Examination Survey (NHANES; Welk et al., [<reflink idref="bib29" id="ref43">29</reflink>]). The estimated VO<subs>2max</subs> from this large, nationally representative sample aged 12–18 years was similar to the measured VO<subs>2max</subs> in the current study. For example, although the NHANES sample was older than the sample in the current study, the mean VO<subs>2max</subs> for boys of 47.3 mL·kg<sups>−1</sups>·min<sups>−1</sups> was similar to the mean for boys in the current study of 46.1 mL·kg<sups>−1</sups>·min<sups>−1</sups>. For girls, the mean VO<subs>2max</subs> from the NHANES sample was 39.6 mL·kg<sups>−1</sups>·min<sups>−1</sups>, which is comparable to the mean for girls in the current study of 39.4 mL·kg<sups>−1</sups>·min<sups>−1</sups>.</p> <p>Potential limitations of the current study include participant motivation and pacing, use of self-reported physical activity, and sample size. Motivation to walk fast at the same pace was not always apparent in a small number of children in the present study and pacing ability differed slightly among children. Self-report measures of physical activity in children may lack absolute validity. However, the self-report measure used in model development was highly reliable and significantly correlated with the measured VO<subs>2max</subs>. The sample size was small compared to some other studies of field tests of aerobic fitness but does represent the largest sample of this age group to be studied with respect to walking tests used to estimate aerobic fitness. It is recommended that this study be replicated with a larger sample to cross-validate the proposed equations.</p> <p>In conclusion, the new quarter-mile walk test regression equations developed in the current study provide valid and reliable estimates of VO<subs>2max</subs> in children aged 10–13 years. The regression equations developed in the current study were as accurate or more accurate than previously published equations. The quarter-mile walk test is easy to administer and time efficient compared to other field tests and might be particularly useful when estimates of aerobic fitness are desired for unmotivated or unfit children. Future research should examine the effect of motivation and pacing education on the validity of walk tests for children. In addition, the impact of walking just one-quarter mile, rather than an entire mile, when developing a quarter-mile walk test should be examined. Development of a quarter-mile walk test with more overweight children should be examined because such a test may be most appropriate for this population of children. 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  Data: Development of Quarter-Mile Walk Tests to Estimate Aerobic Fitness in Children
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  Data: <searchLink fieldCode="AR" term="%22Matthew+T%2E+Mahar%22">Matthew T. Mahar</searchLink><br /><searchLink fieldCode="AR" term="%22Hoyong+Sung%22">Hoyong Sung</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Measurement+in+Physical+Education+and+Exercise+Science%22"><i>Measurement in Physical Education and Exercise Science</i></searchLink>. 2025 29(2):212-219.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: 8
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  Data: 2025
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  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
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  Data: <searchLink fieldCode="DE" term="%22Physical+Fitness%22">Physical Fitness</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Construction%22">Test Construction</searchLink><br /><searchLink fieldCode="DE" term="%22Exercise%22">Exercise</searchLink><br /><searchLink fieldCode="DE" term="%22Early+Adolescents%22">Early Adolescents</searchLink><br /><searchLink fieldCode="DE" term="%22Physical+Activities%22">Physical Activities</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Validity%22">Test Validity</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+Techniques%22">Measurement Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Exercise+Physiology%22">Exercise Physiology</searchLink><br /><searchLink fieldCode="DE" term="%22Body+Composition%22">Body Composition</searchLink><br /><searchLink fieldCode="DE" term="%22Preadolescents%22">Preadolescents</searchLink>
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  Group: ID
  Data: 10.1080/1091367X.2024.2440072
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  Data: 1091-367X<br />1532-7841
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Field-based tests of aerobic fitness that can be administered quickly and do not require maximal effort are desirable. The purpose was to develop and validate quarter-mile walk tests for 10--13-year-olds. Participants (N = 59) walked one mile on two different days. Walk times, heart rates, body mass, physical activity, and aerobic fitness were assessed. Multiple regression was used to develop models to estimate VO[subscript 2max]. Quarter-mile walk models provided estimates of aerobic fitness that were similar in accuracy to previously published walk tests. The recommended model that balances accuracy and ease of administration was: VO[subscript 2max] = 119.691-(13.744*quarter-mile walk time [min])-(0.168*heart rate), R=0.73, SEE = 6.84 mL·kg[superscript -1]·min[superscript -1]. Walk times, heart rates, and estimated VO[superscript 2max] values were highly reliable. The walk tests developed provide valid estimates of VO[superscript 2max], are easy to administer, and could be particularly useful for unmotivated or overweight children when this equation is confirmed with a larger sample in group testing conditions.
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  Data: 2025
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      – Text: English
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      Pagination:
        PageCount: 8
        StartPage: 212
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      – SubjectFull: Physical Fitness
        Type: general
      – SubjectFull: Test Construction
        Type: general
      – SubjectFull: Exercise
        Type: general
      – SubjectFull: Early Adolescents
        Type: general
      – SubjectFull: Physical Activities
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      – SubjectFull: Test Validity
        Type: general
      – SubjectFull: Measurement Techniques
        Type: general
      – SubjectFull: Exercise Physiology
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      – SubjectFull: Body Composition
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      – SubjectFull: Preadolescents
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      – TitleFull: Development of Quarter-Mile Walk Tests to Estimate Aerobic Fitness in Children
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            NameFull: Matthew T. Mahar
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            NameFull: Hoyong Sung
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