Literature DB >> 22462794

Using cadence to study free-living ambulatory behaviour.

Catrine Tudor-Locke1, David A Rowe.   

Abstract

The health benefits of a physically active lifestyle across a person's lifespan have been established. If there is any single physical activity behaviour that we should measure well and promote effectively, it is ambulatory activity and, more specifically, walking. Since public health physical activity guidelines include statements related to intensity of activity, it follows that we need to measure and promote free-living patterns of ambulatory activity that are congruent with this intent. The purpose of this review article is to present and summarize the potential for using cadence (steps/minute) to represent such behavioural patterns of ambulatory activity in free-living. Cadence is one of the spatio-temporal parameters of gait or walking speed. It is typically assessed using short-distance walks in clinical research and practice, but free-living cadence can be captured with a number of commercially available accelerometers that possess time-stamping technology. This presents a unique opportunity to use the same metric to communicate both ambulatory performance (assessed under testing conditions) and behaviour (assessed in the real world). Ranges for normal walking cadence assessed under laboratory conditions are 96-138 steps/minute for women and 81-135 steps/minute for men across their lifespan. The correlation between mean cadence and intensity (assessed with indirect calorimetry and expressed as metabolic equivalents [METs]) based on five treadmill/overground walking studies, is r = 0.93 and 100 steps/minute is considered to be a reasonable heuristic value indicative of walking at least at absolutely-defined moderate intensity (i.e. minimally, 3 METs) in adults. The weighted mean cadence derived from eight studies that have observed pedestrian cadence under natural conditions was 115.2 steps/minute, demonstrating that achieving 100 steps/minute is realistic in specific settings that occur in real life. However, accelerometer data collected in a large, representative sample suggest that self-selected walking at a cadence equivalent to ≥100 steps/minute is a rare occurrence in free-living adults. Specifically, the National Health and Nutrition Examination Survey (NHANES) data show that US adults spent ≅4.8 hours/day in non-movement (i.e. zero cadence) during wearing time, ≅8.7 hours at 1-59 steps/minute, ≅16 minutes/day at cadences of 60-79 steps/minute, ≅8 minutes at 80-99 steps/minute, ≅5 minutes at 100-119 steps/minute, and ≅2 minutes at 120+ steps/minute. Cadence appears to be sensitive to change with intervention, and capitalizing on the natural tempo of music is an obvious means of targeting cadence. Cadence could potentially be used effectively in epidemiological study, intervention and behavioural research, dose-response studies, determinants studies and in prescription and practice. It is easily interpretable by researchers, clinicians, programme staff and the lay public, and therefore offers the potential to bridge science, practice and real life.

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Year:  2012        PMID: 22462794     DOI: 10.2165/11599170-000000000-00000

Source DB:  PubMed          Journal:  Sports Med        ISSN: 0112-1642            Impact factor:   11.136


  95 in total

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4.  Isotemporal substitution paradigm for physical activity epidemiology and weight change.

Authors:  Rania A Mekary; Walter C Willett; Frank B Hu; Eric L Ding
Journal:  Am J Epidemiol       Date:  2009-07-07       Impact factor: 4.897

5.  Walking behaviors reported in the American Time Use Survey 2003-2005.

Authors:  Catrine Tudor-Locke; Sandra A Ham
Journal:  J Phys Act Health       Date:  2008-09

6.  Patterns of adult stepping cadence in the 2005-2006 NHANES.

Authors:  Catrine Tudor-Locke; Sarah M Camhi; Claudia Leonardi; William D Johnson; Peter T Katzmarzyk; Conrad P Earnest; Timothy S Church
Journal:  Prev Med       Date:  2011-06-25       Impact factor: 4.018

Review 7.  Effects of external rhythmical cueing on gait in patients with Parkinson's disease: a systematic review.

Authors:  I Lim; E van Wegen; C de Goede; M Deutekom; A Nieuwboer; A Willems; D Jones; L Rochester; G Kwakkel
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8.  Timed walking tests correlate with daily step activity in persons with stroke.

Authors:  Suzie Mudge; N Susan Stott
Journal:  Arch Phys Med Rehabil       Date:  2009-02       Impact factor: 3.966

9.  Physical activity monitoring in obese people in the real life environment.

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10.  The effect of exercise on gait patterns in older women: a randomized controlled trial.

Authors:  S R Lord; D G Lloyd; M Nirui; J Raymond; P Williams; R A Stewart
Journal:  J Gerontol A Biol Sci Med Sci       Date:  1996-03       Impact factor: 6.053

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  48 in total

1.  Prospective change in daily walking over 2 years in older adults with or at risk of knee osteoarthritis: the MOST study.

Authors:  D K White; C Tudor-Locke; Y Zhang; J Niu; D T Felson; K D Gross; M C Nevitt; C E Lewis; J Torner; T Neogi
Journal:  Osteoarthritis Cartilage       Date:  2015-08-28       Impact factor: 6.576

2.  Aerobic system analysis based on oxygen uptake and hip acceleration during random over-ground walking activities.

Authors:  Thomas Beltrame; Richard L Hughson
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2016-11-16       Impact factor: 3.619

3.  Cadence-based Classification of Minimally Moderate Intensity During Overground Walking in 21- to 40-Year-Old Adults.

Authors:  Elroy J Aguiar; Zachary R Gould; Scott W Ducharme; Chris C Moore; Aston K McCullough; Catrine Tudor-Locke
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4.  Extracting aerobic system dynamics during unsupervised activities of daily living using wearable sensor machine learning models.

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5.  Step Rate and Worsening of Patellofemoral and Tibiofemoral Joint Osteoarthritis in Women and Men: The Multicenter Osteoarthritis Study.

Authors:  Harvi F Hart; K Douglas Gross; Kay M Crossley; Christian J Barton; David T Felson; Ali Guermazi; Frank Roemer; Neil A Segal; Cora E Lewis; Michael C Nevitt; Joshua J Stefanik
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6.  Gait characteristics associated with walking speed decline in older adults: results from the Baltimore Longitudinal Study of Aging.

Authors:  Gerald J Jerome; Seung-uk Ko; Danielle Kauffman; Stephanie A Studenski; Luigi Ferrucci; Eleanor M Simonsick
Journal:  Arch Gerontol Geriatr       Date:  2015-01-13       Impact factor: 3.250

7.  Sex Differences in Physical Activity in People After Stroke: A Cross-sectional Study.

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8.  Does the intensity of daily walking matter for protecting against the development of a slow gait speed in people with or at high risk of knee osteoarthritis? An observational study.

Authors:  S A M Fenton; T Neogi; D Dunlop; M Nevitt; M Doherty; J L Duda; R Klocke; A Abhishek; A Rushton; W Zhang; C E Lewis; J Torner; G Kitas; D K White
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9.  Relationships among subjective patient-reported outcome, quality of life, and objective gait characteristics using wearable foot inertial-sensor assessment in foot-ankle patients.

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10.  Responsiveness of Device-Based and Self-Report Measures of Physical Activity to Detect Behavior Change in Men Taking Part in the Football Fans in Training (FFIT) Program.

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