Intake-balance assessments measure energy intake (EI) by summing energy expenditure (EE) with concurrent change in energy storage (DELAES). Prior work has not examined the validity of such ...calculations when EE is estimated via open-source techniques for research-grade accelerometry devices. The purpose of this study was to test the criterion validity of accelerometry-based intake-balance methods for a wrist-worn ActiGraph device. Healthy adults (n = 24) completed two 14-day measurement periods while wearing an ActiGraph accelerometer on the non-dominant wrist. During each period, criterion values of EI were determined based on DELAES measured by dual X-ray absorptiometry and EE measured by doubly labeled water. A total of 11 prediction methods were tested, 8 derived from the accelerometer and 3 from non-accelerometry methods (e.g., diet recall; included for comparison). Group-level validity was assessed through mean bias, while individual-level validity was assessed through mean absolute error, mean absolute percentage error, and Bland-Altman analysis. Mean bias for the three best accelerometry-based methods ranged from -167 to 124 kcal/day, versus -104 to 134 kcal/day for the non-accelerometry-based methods. The same three accelerometry-based methods had mean absolute error of 323-362 kcal/day and mean absolute percentage error of 18.1-19.3%, versus 353-464 kcal/day and 19.5-24.4% for the non-accelerometry-based methods. All 11 methods demonstrated systematic bias in the Bland-Altman analysis. Accelerometry-based intake-balance methods have promise for advancing EI assessment, but ongoing refinement is necessary. We provide an R package to facilitate implementation and refinement of accelerometry-based methods in future research (see paulhibbing.com/IntakeBalance).
The FitnessGram® program has provided teachers with practical tools to enhance physical education programming. A key to the success of the program has been the systematic application of science to ...practice. Strong research methods have been used to develop assessments and standards for use in physical education, but consideration has also been given to ensure that programming meets the needs of teachers, students, parents, and other stakeholders. This essay summarizes some of these complex and nuanced intersections between science and practice with the FitnessGram® program. The commentaries are organized into 5 brief themes: science informing practice; practice informing science; balancing science and practice; promoting evidence-based practice; and the integration of science and practice. The article draws on personal experiences with the FitnessGram® program and is prepared based on comments shared during the 37th Annual C. H. McCloy Research Lecture at the 2017 SHAPE America - Society of Health and Physical Educators Convention. (Autor).
The utility of self-report measures of physical activity (PA) in youth can be greatly enhanced by calibrating self-report output against objectively measured PA data.This study demonstrates the ...potential of calibrating self-report output against objectively measured physical activity (PA) in youth by using a commonly used self-report tool called the Physical Activity Questionnaire (PAQ).
A total of 148 participants (grades 4 through 12) from 9 schools (during the 2009-2010 school year) wore an Actigraph accelerometer for 7 days and then completed the PAQ. Multiple linear regression modeling was used on 70% of the available sample to develop a calibration equation and this was cross validated on an independent sample of participants (30% of sample).
A calibration model with age, gender, and PAQ scores explained 40% of the variance in values for the percentage of time in moderate-to-vigorous PA (%MVPA) measured from the accelerometers (%MVPA = 14.56 - (sex*0.98) - (0.84*age) + (1.01*PAQ)). When tested on an independent, hold-out sample, the model estimated %MVPA values that were highly correlated with the recorded accelerometer values (r = .63) and there was no significant difference between the estimated and recorded activity values (mean diff. = 25.3 ± 18.1 min; p = .17).
These results suggest that the calibrated PAQ may be a valid alternative tool to activity monitoring instruments for estimating %MVPA in groups of youth.
The establishment of formal physical activity (PA) guidelines has led to considerable interest in quantifying participation in moderate to vigorous PA (MVPA). However, evidence on the context of MVPA ...at the population level is scarce. The aim of this study was to provide information on the type, location, and purpose of MVPA in a representative sample of adults.
Data from a representative sample of 1234 Iowa adults were included in this study. Each participant performed a telephone-administered 24-h PA recall method to recall PA in the previous 24 h. Self-reported data from the recall instrument included time and types of reported activities across five distinct location and purpose codes. Reported activities were matched with corresponding metabolic equivalent (MET) scores from a reduced list of compendium of physical activities. MVPA was defined as any activity with assigned MET ≥ 3.0.
Of the top 30 most frequently reported MVPA, 16 were lifestyle activities involving walking, and only 4 can be regarded as traditional "exercises." Occupational activities (41% for purpose and 40% for location) and household activities (37% for purpose and 39% for location) accounted for nearly 80% of total reported MVPA time. Time allocations across purpose and location codes considerably differed by sociodemographic indicators.
Lifestyle activities are more frequently reported than sports and/or recreational activities. Individuals with varying levels of sociodemographic indicators exhibit different patterns of use of time within a given day. A multidomain approach is needed to better understand and increase MVPA in diverse populations of US adults.
Aerobic Fitness Percentiles for U.S. Adolescents Eisenmann, Joey C., PhD; Laurson, Kelly R., PhD; Welk, Gregory J., PhD
American journal of preventive medicine,
10/2011, Letnik:
41, Številka:
4
Journal Article
Recenzirano
Background Although aerobic fitness has been well studied, establishing developmental patterns from previous studies has some limitations including selection bias and the statistical modeling of ...growth-related data. Purpose The purpose of this study was to develop age-, gender-, and race-specific smoothed percentiles for aerobic fitness using the LMS (L=skewness, M=median, and S=coefficient of variation) statistical procedure in a large, multiethnic, nationally representative sample of U.S. adolescents aged 12–18 years. Methods Data from the National Health and Nutrition Examination Survey (NHANES 1999–2000 and 2001–2002) were combined. In all, 2997 subjects (1478 boys and 1519 girls) completed a treadmill exercise test from which maximal oxygen consumption (VO2 max) was estimated from heart rate response. Percentile curves were determined by using the LMS procedure, which fits smooth percentile curves to reference data. Results Separate LMS curves were initially prepared for each gender and race; however, since the overall distribution of the data was not different for whites, blacks, and Hispanics, the participants were combined, and separate centile curves were prepared for boys and girls. Specific percentile values were created from the LMS curves, and the age- and gender-specific values for LMS are provided for calculation of individual z-scores (SD scores). In general, there is a slight increase in estimated VO2 max of boys aged 12–15 years and then it remains stable. In girls, there is slight decrease in estimated VO2 max across ages 12–18 years. Boys have higher values than girls at every age-specific percentile. Conclusions This study presents age- and gender-specific percentiles for U.S. youth aged 12–18 years based on NHANES (1999–2002), and adds to the recent application of the LMS statistical procedure for the construction of growth percentiles for a variety of outcomes. Comparisons are made to current FITNESSGRAM® thresholds.
Data from clinical trials have justified the promotion of fitness as a means to enhance facets of cognitive control and academic achievement in youth. However, such associations, when tested under ...real-world conditions, are equivocal. The purpose of this study, therefore, was to evaluate longitudinal associations between aerobic capacity (AC), weight status, and academic achievement within a large urban county.
Longitudinal data were obtained from a sample of third, fifth, and seventh grade students in schools within an urban county in Georgia. Data on body mass index (BMI) were available from 11,639 students; AC data from 5735 students. Data on both indicators were obtained through the established FitnessGram assessment battery with 2-yr changes calculated using standardized Z scores. Academic achievement data were available from three subjects (math, science, and reading) for third, fifth, and seventh grade students, and 2-yr changes were computed using changes in Z scores for each test. Data were analyzed using generalized logistic models to test associations between change in BMI and AC in relation to changes in academic achievement.
Positive associations were observed between improvements in weight status and academic achievement for the fifth grade boys and girls (reading odds ratio OR, 1.47; 95% confidence interval CI, 1.25-1.72; science OR, 1.22; 95% CI, 1.04-1.42). Maintaining weight status was associated with improved scores in the third grade (math OR, 1.16; 95% CI, 1.012-1.327; reading OR, 1.47; 95% CI, 1.25-1.72) and fifth grade cohorts (math OR, 1.20; 95% CI, 1.00.1.43). For AC, no significant associations were found for any age cohort.
Modest associations between improvements in weight status, AC, and academic achievement are noteworthy, despite the lack of statistical significance for AC. The results provide a robust evaluation of associations between fitness and academic achievement.
OBJECTIVE: Accelerometers offer considerable promise for improving estimates of physical activity (PA) and energy expenditure (EE) in free-living subjects. Differences in calibration equations and ...cut-off points have made it difficult to determine the most accurate way to process these data. The objective of this study was to compare the accuracy of various calibration equations and algorithms that are currently used with the MTI Actigraph (MTI) and the Sensewear Pro II (SP2) armband monitor. RESEARCH METHODS AND PROCEDURES: College-age participants (n = 30) wore an MTI and an SP2 while participating in normal activities of daily living. Activity patterns were simultaneously monitored with the Intelligent Device for Estimating Energy Expenditure and Activity (IDEEA) monitor to provide an accurate estimate (criterion measure) of EE and PA for this field-based method comparison study. RESULTS: The EE estimates from various MTI equations varied considerably, with mean differences ranging from -1.10 to 0.46 METS. The EE estimates from the two SP2 equations were within 0.10 METS of the value from the IDEEA. Estimates of time spent in PA from the MTI and SP2 ranged from 34.3 to 107.1 minutes per day, while the IDEEA yielded estimates of 52 minutes per day. DISCUSSION: The lowest errors in estimation of time spent in PA and the highest correlations were found for the new SP2 equation and for the recently proposed MTI cut-off point of 760 counts/min (Matthews, 2005). The study indicates that the Matthews MTI cut-off point and the new SP2 equation provide the most accurate indicators of PA.
Objective To assess age- and sex-specific patterns of 6 health-related fitness components in youth, baseline data from the NFL PLAY 60 FITNESSGRAM Partnership Project were analyzed. Study design A ...total of 192 848 students from 1st through 12th grade in 725 schools completed the standard FITNESSGRAM testing in 2010-2014, including assessments of aerobic capacity (AC), body mass index (BMI), upper body strength and endurance, trunk extensor strength and flexibility, abdominal strength and endurance, and flexibility. Individual data were aggregated by grade and sex. Age- and sex-specific health-related criterion-referenced standards were used to classify fitness results into the healthy fitness zone (HFZ), needs improvement zone, or needs improvement health risk. Results The proportion of youth meeting the HFZ for AC varied considerably by grade for both boys (62.1%-37.6%) and girls (49.1%-26.1%) among 1st-12th grade. There was less variability by age and sex for achievement of the BMI HFZ (ranged from 52.7%-65.0%). The prevalence of achievement was similar for the remaining fitness components. Significantly lower achievement was found in the middle school years for BMI HFZ in both sexes and for AC HFZ achievement in boys. Continuous age-related lower HFZ achievement was evident in girls for AC. Conclusions The results provide updated health-related fitness profiles for US youth and identify the critical ages when youth fitness levels start to decline.
Sedentary behaviour (SB) has emerged as a modifiable risk factor, but little is known about measurement errors of SB. The purpose of this study was to determine the validity of 24-h Physical Activity ...Recall (24PAR) relative to SenseWear Armband (SWA) for assessing SB. Each participant (n = 1485) undertook a series of data collection procedures on two randomly selected days: wearing a SWA for full 24-h, and then completing the telephone-administered 24PAR the following day to recall the past 24-h activities. Estimates of total sedentary time (TST) were computed without the inclusion of reported or recorded sleep time. Equivalence testing was used to compare estimates of TST. Analyses from equivalence testing showed no significant equivalence of 24PAR for TST (90% CI: 443.0 and 457.6 min · day-1) relative to SWA (equivalence zone: 580.7 and 709.8 min · day-1). Bland-Altman plots indicated individuals that were extremely or minimally sedentary provided relatively comparable sedentary time between 24PAR and SWA. Overweight/obese and/or older individuals were more likely to under-estimate sedentary time than normal weight and/or younger individuals. Measurement errors of 24PAR varied by the level of sedentary time and demographic indicators. This evidence informs future work to develop measurement error models to correct for errors of self-reports. (Autor).
The use of Comprehensive School Physical Activity Program (CSPAP) has been recommended to help students achieve 60-minutes of physical activity each day. Implementing a CSPAP requires planning, ...coordination, and ongoing oversight, but an understudied factor is how principal support influences CSPAP implementation. The purpose of this study was to evaluate the impact of principal support on CSPAP implementation. Method. Schools in the Iowa FitnessGram Initiative (n = 84), a participatory network of schools committed to supporting physical education and wellness efforts, were invited to participate in the study. Physical education teachers from 42 schools completed a survey assessing CSPAP implementation and principal support for school wellness. Descriptive statistics and correlation analyses were used to report associations between the variables. A regression analysis was conducted to evaluate the impact of principal support on CSPAP implementation. Results. Almost half of the schools were reported to be fully implementing just one CSPAP component and no school was reported to be fully implementing all five. The CSPAP component with the highest reported level of implementation was quality physical education, while the lowest level of implementation was reported for family and community engagement and staff involvement. The regression analysis identified that principal support was a significant predictor of CSPAP implementation, b = 0.55, t(37) = 3.10, p < .004. Conclusions. Principal support is associated with implementation of CSPAP initiatives. Strategies that focus on how to attain principal support for CSPAP initiatives are needed and could have a significant impact on student physical activity and health.
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