Literature DB >> 11399784

Assessment of free-living physical activity in humans: an overview of currently available and proposed new measures.

Y Schutz1, R L Weinsier, G R Hunter.   

Abstract

The number of physical activity measures and indexes used in the human literature is large and may result in some difficulty for the average investigator to choose the most appropriate measure. Accordingly, this review is intended to provide information on the utility and limitations of the various measures. Its primary focus is the objective assessment of free-living physical activity in humans based on physiological and biomechanical methods. The physical activity measures have been classified into three categories: Measures based on energy expenditure or oxygen uptake, such as activity energy expenditure, activity-related time equivalent, physical activity level, physical activity ratio, metabolic equivalent, and a new index of potential interest, daytime physical activity level. Measures based on heart rate monitoring, such as net heart rate, physical activity ratio heart rate, physical activity level heart rate, activity-related time equivalent, and daytime physical activity level heart rate. Measures based on whole-body accelerometry (counts/U time). Quantification of the velocity and duration of displacement in outdoor conditions by satellites using the Differential Global Positioning System may constitute a surrogate for physical activity, because walking is the primary activity of man in free-living conditions. A general outline of the measures and indexes described above is presented in tabular form, along with their respective definition, usual applications, advantages, and shortcomings. A practical example is given with typical values in obese and non-obese subjects. The various factors to be considered in the selection of physical activity methods include experimental goals, sample size, budget, cultural and social/environmental factors, physical burden for the subject, and statistical factors, such as accuracy and precision. It is concluded that no single current technique is able to quantify all aspects of physical activity under free-living conditions, requiring the use of complementary methods. In the future, physical activity sensors, which are of low-cost, small-sized, and convenient for subjects, investigators, and clinicians, are needed to reliably monitor, during extended periods in free-living situations, small changes in movements and grade as well as duration and intensity of typical physical activities.

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Year:  2001        PMID: 11399784     DOI: 10.1038/oby.2001.48

Source DB:  PubMed          Journal:  Obes Res        ISSN: 1071-7323


  42 in total

1.  Accelerometer use in a physical activity intervention trial.

Authors:  Melissa A Napolitano; Kelley E Borradaile; Beth A Lewis; Jessica A Whiteley; Jaime L Longval; Alfred F Parisi; Anna E Albrecht; Christopher N Sciamanna; John M Jakicic; George D Papandonatos; Bess H Marcus
Journal:  Contemp Clin Trials       Date:  2010-08-17       Impact factor: 2.226

2.  Effect of BMI on prediction of accelerometry-based energy expenditure in youth.

Authors:  Joshua Warolin; Amanda R Carrico; Lauren E Whitaker; Li Wang; Kong Y Chen; Sari Acra; Maciej S Buchowski
Journal:  Med Sci Sports Exerc       Date:  2012-12       Impact factor: 5.411

3.  Measuring Physical Activity and Sedentary Behavior in Youth with Type 2 Diabetes.

Authors:  Bonny Rockette-Wagner; Kristi L Storti; Sharon Edelstein; Linda M Delahanty; Bryan Galvin; Alexandra Jackson; Andrea M Kriska
Journal:  Child Obes       Date:  2016-02-09       Impact factor: 2.992

4.  Physical activity in aging: comparison among young, aged, and nonagenarian individuals.

Authors:  Darcy L Johannsen; James P DeLany; Madlyn I Frisard; Michael A Welsch; Christina K Rowley; Xiaobing Fang; S Michal Jazwinski; Eric Ravussin
Journal:  J Appl Physiol (1985)       Date:  2008-06-12

5.  Work pattern causes bias in self-reported activity duration: a randomised study of mechanisms and implications for exposure assessment and epidemiology.

Authors:  L H Barrero; J N Katz; M J Perry; R Krishnan; J H Ware; J T Dennerlein
Journal:  Occup Environ Med       Date:  2008-09-19       Impact factor: 4.402

6.  Weight suppression and risk of future increases in body mass: effects of suppressed resting metabolic rate and energy expenditure.

Authors:  Eric Stice; Shelley Durant; Kyle S Burger; Dale A Schoeller
Journal:  Am J Clin Nutr       Date:  2011-04-27       Impact factor: 7.045

7.  Elevated objectively measured but not self-reported energy intake predicts future weight gain in adolescents.

Authors:  Eric Stice; Shelley Durant
Journal:  Appetite       Date:  2014-06-12       Impact factor: 3.868

8.  Ageing and physical function in East African foragers and pastoralists.

Authors:  M Katherine Sayre; Herman Pontzer; Gene E Alexander; Brian M Wood; Ivy L Pike; Audax Z P Mabulla; David A Raichlen
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-09-21       Impact factor: 6.237

9.  Energy expenditure and adiposity in Nigerian and African-American women.

Authors:  Kara E Ebersole; Lara R Dugas; Ramon A Durazo-Arvizut; Adebowale A Adeyemo; Bamidele O Tayo; Olayemi O Omotade; William R Brieger; Dale A Schoeller; Richard S Cooper; Amy H Luke
Journal:  Obesity (Silver Spring)       Date:  2008-09       Impact factor: 5.002

10.  Does physical activity change predict functional recovery in low back pain? Protocol for a prospective cohort study.

Authors:  Paul Hendrick; Stephan Milosavljevic; Melanie L Bell; Leigh Hale; Deirdre A Hurley; Suzanne M McDonough; Markus Melloh; David G Baxter
Journal:  BMC Musculoskelet Disord       Date:  2009-11-06       Impact factor: 2.362

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