Search Results

You are looking at 11 - 20 of 31 items for

  • Author: Gregory Welk x
Clear All Modify Search
Restricted access

Michelle Ihmels, Gregory J. Welk, James J. McClain and Jodee Schaben

Background:

Advances in BIA offer practical alternative approaches to assessing body composition in young adolescents and have not been studied for comparability.

Methods:

This study compared reliability and convergent validity of three field tests (2-site skinfold, Omron and Tanita BIA devices) on young adolescents. Reliability was determined using intraclass correlation coefficients, convergent validity was examined by computing correlations among the three estimates, differences in estimated body fat values were evaluated using repeated-measures ANOVA, and classification agreement was computed for achieving FITNESSGRAM ® Healthy Fitness Zone.

Results:

ICC values of all three measures exceeded .97. Correlations ranged from .74 to .81 for males and .79 to .91 for females. Classification agreement values ranged from 82.8% to 92.6%.

Conclusions:

Results suggest general agreement among the selected methods of body composition assessments in both boys and girls with the exception that percent body fat in boys by Tanita BIA is significantly lower than skinfold estimation.

Restricted access

Russell R. Pate, Gregory J. Welk and Kerry L. McIver

Restricted access

Eric E. Wickel, Joey C. Eisenmann and Gregory J. Welk

Background:

This study compared physical activity levels among early, average, and late maturing boys and girls.

Methods:

Physical activity was assessed with an Actigraph accelerometer in 161 (76 boys, 85 girls) 9 to 14 year olds over 7 consecutive days. Anthropometric variables were measured and the maturity offset (ie, years from peak height velocity) was predicted. Biological maturity groups (early, average, and late) were created based on the mean estimated age at peak height velocity for boys and girls separately.

Results:

Levels of moderate-to-vigorous physical activity (MVPA) were similar between early, average, and late maturing boys and girls after adjusting for differences in chronological age. Levels of MVPA progressively declined across chronological age in boys and girls (P < .001) and gender differences existed at 10-, 12-, and 13-years, with boys having higher levels than girls (P < .05). When aligned according to biological age, gender-related differences in MVPA did not exist.

Conclusions:

Within this sample of 9 to 14 year old boys and girls, there were no significant differences in MVPA among early, average, and late maturing individuals.

Restricted access

Jodee A. Schaben, Gregory J. Welk, Roxane Joens-Matre and Larry Hensley

Understanding physical activity (PA) correlates in youth is challenging due to the inherent changes in activity patterns, activity preferences, and social norms that occur during the normal developmental transition from childhood into adolescence. This study examines possible age-related differences in physical activity correlates using the Children’s Physical Activity Correlates Scale (CPAC). The Children’s Physical Activity Questionnaire (PAQ) was used to measure typical levels of PA. Results indicate high school youth had lower levels of PA and lower levels on the psychosocial correlates than middle school youth. Parental influence accounted for ~ 15% of the variance in PA while the predisposing factors (perceived competence, attraction to PA) accounted for 20% and 17% of the variance for middle and high school students, respectively. CPAC has similar predictive validity across the age range. The CPAC scale offers potential to help understand factors that influence physical activity behavior during the transition from childhood into adolescence.

Restricted access

Gregory J. Welk, Joey C. Eisenmann, Jodee Schaben, Stewart G. Trost and Darren Dale

The unique physical and movement characteristics of children necessitate the development of accelerometer equations and cut points that are population specific. The purpose of this study is to develop an ecologically valid cut point for the Biotrainer Pro monitor that reflects a threshold for moderate-intensity physical activity in elementary school children. A sample of 30 children (ages 8−12) wore a Biotrainer monitor while completing a series of 7 movement tasks (calibration phase) and while participating in an organized group activity (cross-validation phase). Videotapes from each session were processed using a computerized direct-observation technique to provide a criterion measure of physical activity. Analyses involved the use of mixed-model regression and receiver operator characteristic (ROC) curves. The results indicated that a cut point of 4 counts/min provides the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of activity as inactivity). Results with the cross-validation data demonstrated that this value yielded the best overall kappa (.58) and a high classification agreement (84%) for activity determination. The specificity of 93% demonstrates that the proposed cut point can accurately detect activity; however, the lower sensitivity value of 61% suggests that some minutes of activity might be incorrectly classified as inactivity. The cut point of 4 counts/min provides an ecologically valid cut point to capture physical activity in children using the Biotrainer Pro activity monitor.

Open access

Jung-Min Lee, Pedro F. Saint-Maurice, Youngwon Kim, Glenn A. Gaesser and Gregory Welk

Background:

The assessment of physical activity (PA) and energy expenditure (EE) in youth is complicated by inherent variability in growth and maturation during childhood and adolescence. This study provides descriptive summaries of the EE of a diverse range of activities in children ages 7 to 13.

Methods:

A sample of 105 7- to 13-year-old children (boys: 57%, girls: 43%, and Age: 9.9 ± 1.9) performed a series of 12 activities from a pool of 24 activities while being monitored with an indirect calorimetry system.

Results:

Across physical activities, averages of VO2 ml·kg·min-1, VO2 L·min-1, EE, and METs ranged from 3.3 to 53.7 ml·kg·min-1, from 0.15 to 3.2 L·min-1, from 0.7 to 15.9 kcal·min-1, 1.5 MET to 7.8 MET, respectively.

Conclusions:

The energy costs of the activities varied by age, sex, and BMI status reinforcing the need to consider adjustments when examining the relative intensity of PA in youth.

Restricted access

Matthew T. Mahar, Gregory J. Welk, David A. Rowe, Dana J. Crotts and Kerry L. McIver

Background:

The purpose of this study was to develop and cross-validate a regression model to estimate VO2peak from PACER performance in 12- to 14-year-old males and females.

Methods:

A sample of 135 participants had VO2peak measured during a maximal treadmill test and completed the PACER 20-m shuttle run. The sample was randomly split into validation (n = 90) and cross-validation (n = 45) samples. The validation sample was used to develop the regression equation to estimate VO2peak from PACER laps, gender, and body mass.

Results:

The multiple correlation (R) was .66 and standard error of estimate (SEE) was 6.38 ml·kg−1·min−1. Accuracy of the model was confirmed on the cross-validation sample. The regression equation developed on the total sample was: VO2peak = 47.438 + (PACER*0.142) + (Gender[m=1, f=0]*5.134) − (body mass [kg]*0.197), R = .65, SEE = 6.38 ml·kg–1·min–1.

Conclusions:

The model developed in this study was more accurate than the Leger et al. model and allows easy conversion of PACER laps to VO2peak.

Restricted access

Adam Šimůnek, Jan Dygrýn, Lukáš Jakubec, Filip Neuls, Karel Frömel and Gregory John Welk

Purpose: Activity trackers are useful tools for physical activity promotion in adolescents, but robust validity evaluations have not been done under free-living conditions. This study evaluated the validity of the Garmin Vívofit 1 (G1) and Garmin Vívofit 3 (G3) in different settings and contexts. Methods: The participants (girls: 52%, age: 15.9 [1.9] y) wore the G1 and G3 on their nondominant wrist and the Yamax pedometer on their right hip for a period of 1 week. Validity was examined in 4 discrete segments (before school, in school, after school, and whole day). The criterion method was the Yamax pedometer. Results: Both the G1 and G3 could be considered equivalent to the Yamax pedometer regarding the before school, in school, and whole day segments. The G1 showed wider limits of agreement than G3. Conclusions: The G1 and G3 trackers exhibited acceptable validity for 3 of the 4 segments (before school, in school, and whole day measurements). The results were less accurate during the after-school segment. The evidence that the validity of the monitors varied depending on the setting and context is an important consideration for research on adolescent activity patterns.

Restricted access

Bradley J. Cardinal, Minsoo Kang, James L. Farnsworth II and Gregory J. Welk

Kinesiology leaders were surveyed regarding their views of the (re)emergence of physical activity and public health. Their views were captured via a 25-item, online survey conducted in 2014. The survey focused on four areas: (a) types of affiliation with public health; (b) program options and course coverage; (c) outreach programming; and (d) perspectives on integration. Member and nonmember institutions of the American Kinesiology Association received the survey. Responses were received from 139 institutional leaders, resulting in an overall response rate of 21.4%. Key findings included that the combination of physical activity and public health was seen as both a stand-alone subdisciplinary area within kinesiology and also an area that has a great deal of potential for collaboration, the acquisition of external funding, and further strengthening of community outreach and engagement. The survey results are placed in historical context and interpreted with various caveats and limitations in mind.

Restricted access

David Martínez-Gómez, M. Andres Calabro, Gregory J. Welk, Ascension Marcos and Oscar L. Veiga

Recess is a frequent target in school-based physical activity (PA) promotion research but there are challenges in assessing PA during this time period. The purpose of this study was to evaluate the reliability and validity of a recess PA recall (RPAR) instrument designed to assess total PA and time spent in moderate to vigorous PA (MVPA) during recess. One hundred twenty-five 7th and 8th-grade students (59 females), age 12–14 years, participated in the study. Activity levels were objectively monitored on Mondays using different activity monitors (Yamax Digiwalker, Biotrainer and ActiGraph). On Tuesdays, 2 RPAR self-reports were administered within 1-hr. Test-retest reliability showed ICC = 0.87 and 0.88 for total PA and time spent in MVPA, respectively. The RPAR was correlated against Yamax (r = .35), Biotrainer (r = .40 and 0.54) and ActiGraph (r = .42) to assess total PA during recess. The RPAR was also correlated against ActiGraph (r = .54) to assess time spent in MVPA during recess. Mean difference between the RPAR and ActiGraph to assess time spent in MVPA during recess was no significant (2.15 ± 3.67 min, p = .313). The RPAR showed an adequate reliability and a reasonable validity for assessing PA during the school recess in youth.