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Catrine Tudor-Locke, Barbara E. Ainsworth, Tracy L. Washington and Richard Troiano

Background:

The Current Population Survey (CPS) and the American Time Use Survey (ATUS) use the 2002 census occupation system to classify workers into 509 separate occupations arranged into 22 major occupational categories.

Methods:

We describe the methods and rationale for assigning detailed Metabolic Equivalent (MET) estimates to occupations and present population estimates (comparing outputs generated by analysis of previously published summary MET estimates to the detailed MET estimates) of intensities of occupational activity using the 2003 ATUS data comprised of 20,720 respondents, 5323 (2917 males and 2406 females) of whom reported working 6+ hours at their primary occupation on their assigned reporting day.

Results:

Analysis using the summary MET estimates resulted in 4% more workers in sedentary occupations, 6% more in light, 7% less in moderate, and 3% less in vigorous compared with using the detailed MET estimates. The detailed estimates are more sensitive to identifying individuals who do any occupational activity that is moderate or vigorous in intensity resulting in fewer workers in sedentary and light intensity occupations.

Conclusions:

Since CPS/ATUS regularly captures occupation data it will be possible to track prevalence of the different intensity levels of occupations. Updates will be required with inevitable adjustments to future occupational classification systems.

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Mark Abel, James Hannon, David Mullineaux and Aaron Beighle

Background:

Current recommendations call for adults to be physically active at moderate and/or vigorous intensities. Given the popularity of walking and running, the use of step rates may provide a practical and inexpensive means to evaluate ambulatory intensity. Thus, the purpose of this study was to identify step rate thresholds that correspond to various intensity classifications.

Methods:

Oxygen consumption was measured at rest and during 10 minute treadmill walking and running trials at 6 standardized speeds (54, 80, 107, 134, 161, and 188 m·min-1) in 9 men and 10 women (28.8 ± 6.8 yrs). Two observers counted the participants’ steps at each treadmill speed. Linear and nonlinear regression analyses were used to develop prediction equations to ascertain step rate thresholds at various intensities.

Results:

Nonlinear regression analysis of the metabolic cost versus step rates across all treadmill speeds yielded the highest R 2 values for men (R 2 = .91) and women (R 2 = .79). For men, the nonlinear analysis yielded 94 and 125 step·min-1 for moderate and vigorous intensities, respectively. For women, 99 and 135 step·min-1 corresponded with moderate and vigorous intensities, respectively.

Conclusions:

Promoting a step rate of 100 step·min-1 may serve as a practical public health recommendation to exercise at moderate intensity.

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Marieke J.G. van Heuvelen, Martin Stevens and Gertrudis I.J.M. Kempen

This study investigated differences in physical-fitness test scores between actively and passively recruited older adults and the consequences thereof for norm-based classification of individuals. Walking endurance, grip strength, hip flexibility, balance, manual dexterity, and reaction time were measured in participants age 57 years or older: 1 sample recruited through media announcements (passively recruited) and 1 sample recruited through personal contact (actively recruited). Classifications on a 5-point scale based on norms were cross-tabulated. Compared with the actively recruited sample, performance of the passively recruited sample was significantly better on all tests except, for women, hip flexibility and manual dexterity. Cross-tabulation of the 2 classifications showed that percentages of agreement varied from 27.4% to 87.4%. Cohen's Kappa varied from .11 to .84. Caution should be used when giving feedback on test performance and subsequently making physical activity recommendations if norms are based on the performance of passively recruited older adults.

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Carolina F. Wilke, Felipe Augusto P. Fernandes, Flávio Vinícius C. Martins, Anísio M. Lacerda, Fabio Y. Nakamura, Samuel P. Wanner and Rob Duffield

in multifaceted conditions (eg, disease diagnosis) assists professionals in selecting the most effective intervention. 9 , 10 Similar methods in sport have reported; whereby the application of a statistical classification tool to 8 screening tests classified 28 professional rugby union players into

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David R. Howell, Jessie R. Oldham, Melissa DiFabio, Srikant Vallabhajosula, Eric E. Hall, Caroline J. Ketcham, William P. Meehan III and Thomas A. Buckley

Gait impairments have been documented following sport-related concussion. Whether preexisting gait pattern differences exist among athletes who participate in different sport classifications, however, remains unclear. Dual-task gait examinations probe the simultaneous performance of everyday tasks (ie, walking and thinking), and can quantify gait performance using inertial sensors. The purpose of this study was to compare the single-task and dual-task gait performance of collision/contact and noncontact athletes. A group of collegiate athletes (n = 265) were tested before their season at 3 institutions (mean age= 19.1 ± 1.1 years). All participants stood still (single-task standing) and walked while simultaneously completing a cognitive test (dual-task gait), and completed walking trials without the cognitive test (single-task gait). Spatial-temporal gait parameters were compared between collision/contact and noncontact athletes using MANCOVAs; cognitive task performance was compared using ANCOVAs. No significant single-task or dual-task gait differences were found between collision/contact and noncontact athletes. Noncontact athletes demonstrated higher cognitive task accuracy during single-task standing (P = .001) and dual-task gait conditions (P = .02) than collision/contact athletes. These data demonstrate the utility of a dual-task gait assessment outside of a laboratory and suggest that preinjury cognitive task performance during dual-tasks may differ between athletes of different sport classifications.

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Ronald W. Davis

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Frederico R. Neto, Guilherme H. Lopes, Rodrigo R. Gomes Costa, Asuman Saltan and Handan Ankarali

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Jorge E. Morais, António J. Silva, Daniel A. Marinho, Ludovic Seifert and Tiago M. Barbosa

Purpose:

To apply a new method to identify, classify, and follow up young swimmers based on their performance and its determinant factors over a season and analyze the swimmers’ stability over a competitive season with that method.

Methods:

Fifteen boys and 18 girls (11.8 ± 0.7 y) part of a national talent-identification scheme were evaluated at 3 different moments of a competitive season. Performance (ie, official 100-m freestyle race time), arm span, chest perimeter, stroke length, swimming velocity, speed fluctuation, coefficient of active drag, propelling efficiency, and stroke index were selected as variables. Hierarchical and k-means cluster analysis were computed.

Results:

Data suggested a 3-cluster solution, splitting the swimmers according to their performance in all 3 moments. Cluster 1 was related to better performances (talented swimmers), cluster 2 to poor performances (nonproficient swimmers), and cluster 3 to average performance (proficient swimmers) in all moments. Stepwise discriminant analysis revealed that 100%, 94%, and 85% of original groups were correctly classified for the 1st, 2nd, and 3rd evaluation moments, respectively (0.11 ≤ Λ ≤ 0.80; 5.64 ≤ χ2 ≤ 63.40; 0.001 < P ≤ .68). Membership of clusters was moderately stable over the season (stability range 46.1–75% for the 2 clusters with most subjects).

Conclusion:

Cluster stability is a feasible, comprehensive, and informative method to gain insight into changes in performance and its determinant factors in young swimmers. Talented swimmers were characterized by anthropometrics and kinematic features.

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Eric L. Sauers