Accelerometer steps/day translation of moderate-to-vigorous activity

Tudor-Locke, Catrine; Leonardi, Claudia; Johnson, William D.; Katzmarzyk, Peter T.; Church, Timothy S.

doi:10.1016/j.ypmed.2011.01.014

Cited by 116 publications

(60 citation statements)

References 10 publications

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“…Many research studies and consumer electronic articles have focused on step count as an output for measuring physical activity [11, 15, 16]. Many national and international health organizations have provided recommendations on step count goals in line with improving population health.…”

Section: Discussionmentioning

confidence: 99%

When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors

2017

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IntroductionPhysical activity is an essential aspect of a healthy lifestyle for both physical and mental health states. As step count is one of the most utilized measures for quantifying physical activity it is important that activity-monitoring devices be both sensitive and specific in recording actual steps taken and disregard non-stepping body movements. The objective of this study was to assess the specificity of five activity monitors during a variety of prescribed non-stepping activities.MethodsParticipants wore five activity monitors simultaneously for a variety of prescribed activities including deskwork, taking an elevator, taking a bus journey, automobile driving, washing and drying dishes; functional reaching task; indoor cycling; outdoor cycling; and indoor rowing. Each task was carried out for either a specific duration of time or over a specific distance. Activity monitors tested were the ActivPAL micro™, NL-2000™ pedometer, Withings Smart Activity Monitor Tracker (Pulse O2)™, Fitbit One™ and Jawbone UP™. Participants were video-recorded while carrying out the prescribed activities and the false positive step count registered on each activity monitor was obtained and compared to the video.ResultsAll activity monitors registered a significant number of false positive steps per minute during one or more of the prescribed activities. The Withings™ activity performed best, registering a significant number of false positive steps per minute during the outdoor cycling activity only (P = 0.025). The Jawbone™ registered a significant number of false positive steps during the functional reaching task and while washing and drying dishes, which involved arm and hand movement (P < 0.01 for both). The ActivPAL™ registered a significant number of false positive steps during the cycling exercises (P < 0.001 for both).ConclusionAs a number of false positive steps were registered on the activity monitors during the non-stepping activities, the authors conclude that non-stepping physical activities can result in the false detection of steps. This can negatively affect the quantification of physical activity with regard to step count as an output. The Withings™ activity monitor performed best with regard to specificity during the activities of daily living tested.

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Section: Discussionmentioning

confidence: 99%

When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors

2017

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“…Physical activity was measured with the CARDIA Physical Activity History questionnaire, which assesses 13 categories of varying intensity over the past 12 months calculated into weighted exercise units and has been shown to have excellent validity and reliability 18, 19. Optimal physical activity was defined and examined in 2 ways: (1) as ≥300 exercise units, which corresponds most closely to the AHA goal of ≥150 minutes of moderate to vigorous activity per week,20 and (2) as being in the top quartile of reported exercise units for the overall sample because ≈25% of US adults meet the AHA definition when activity is measured by accelerometer 21. Dietary intake over the previous 28 days was assessed with the CARDIA dietary history interview,22 shown to have reasonable reliability and validity in white participants but less favorable psychometric properties in black participants 23.…”

Section: Methodsmentioning

confidence: 99%

Optimal Lifestyle Components in Young Adulthood Are Associated With Maintaining the Ideal Cardiovascular Health Profile Into Middle Age

Gooding

Shay

Ning

et al. 2015

JAHA

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BackgroundMiddle‐aged adults with ideal blood pressure, cholesterol, and glucose levels exhibit substantially lower cardiovascular mortality than those with unfavorable levels. Four healthy lifestyle components—optimal body weight, diet, physical activity, and not smoking—are recommended for cardiovascular health (CVH). This study quantified associations between combinations of healthy lifestyle components measured in young adulthood and loss of the ideal CVH profile into middle age.Methods and ResultsAnalyses included 2164 young adults in the Coronary Artery Risk Development in Young Adults study with the ideal CVH profile (defined as untreated blood pressure <120/80 mm Hg, total cholesterol <200 mg/dL, fasting blood glucose <100 mg/dL, and absence of cardiovascular disease) at baseline. Cox proportional hazards regression models estimated hazard ratios for loss of the ideal CVH profile over 25 years according to 4 individual and 16 combinations of optimal healthy lifestyle components measured in young adulthood: body mass index, physical activity, nonsmoking status, and diet quality. Models were adjusted for age, sex, race, education, study center, and baseline blood pressure, cholesterol, and glucose. Eighty percent (n=1737) of participants lost the ideal CVH profile by middle age; loss was greatest for young adults with no optimal healthy lifestyle components at baseline. Relative to young adults with no optimal healthy lifestyle components, those with all 4 were less likely to lose the ideal CVH profile (hazard ratio 0.59, 95% CI 0.44–0.80). Combinations that included optimal body mass index and nonsmoking status were each associated with lower risk.ConclusionsOptimal body mass index and not smoking in young adulthood were protective against loss of the ideal CVH profile through middle age. Importance of diet and physical activity may be included through their effects on healthy weight.

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“…During screening, informed consent will be obtained from each eligible participant by study staff. Staff members will also verify that eligible participants are not currently meeting public health physical activity guidelines (that is, sedentary: <8,000 steps/day over the course of 1 week) [15] by having them wear SenseWear Armband (BodyMedia, Pittsburgh, PA, USA) accelerometers.…”

Section: Methodsmentioning

confidence: 99%

Examination of mechanisms (E-MECHANIC) of exercise-induced weight compensation: study protocol for a randomized controlled trial

Myers

Johnson

Earnest

et al. 2014

Trials

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BackgroundWeight loss induced only by exercise is frequently less than expected, possibly because of compensatory changes in energy intake and/or energy expenditure. The purpose of the Examination of Mechanisms (E-MECHANIC) of Exercise-Induced Weight Compensation trial is to examine whether increased energy intake and/or reduced spontaneous activity or energy expenditure (outside of structured exercise) account for the less than expected, exercise-associated weight loss.Methods/DesignE-MECHANIC is a three-arm, 6-month randomized (1:1:1) controlled trial. The two intervention arms are exercise doses that reflect current recommendations for (1) general health (8 kcal/kg body weight per week (8 KKW), about 900 kcal/wk) and (2) weight loss (20 KKW, about 2,250 kcal/wk). The third arm, a nonexercise control group, will receive health information only. The sample will include a combined total of 198sedentary, overweight or obese (body mass index: ≥25 kg/m2 to ≤45 kg/m2) men and women ages 18 to 65 years. The exercise dose will be supervised and tightly controlled in an exercise training laboratory. The primary outcome variables are energy intake, which will be measured using doubly labeled water (adjusted for change in energy stores) and laboratory-based food intake tests, and the discrepancy between expected weight loss and observed weight loss. Secondary outcomes include changes in resting metabolic rate (adjusted for change in body mass), activity levels (excluding structured exercise) and body composition. In an effort to guide the development of future interventions, the participants will be behaviorally phenotyped and defined as those who do compensate (that is, fail to lose the amount of weight expected) or do not compensate (that is, lose the amount of weight expected or more).DiscussionIn this study, we will attempt to identify underlying mechanisms to explain why exercise elicits less weight loss than expected. This information will guide the development of interventions to increase exercise-induced weight loss and maximize weight loss retention and related health benefits.Trial registrationClinicalTrials.gov ID: NCT01264406 (registration date: 20 December 2010).

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Accelerometer steps/day translation of moderate-to-vigorous activity

Cited by 116 publications

References 10 publications

When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors

When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors

Optimal Lifestyle Components in Young Adulthood Are Associated With Maintaining the Ideal Cardiovascular Health Profile Into Middle Age

Examination of mechanisms (E-MECHANIC) of exercise-induced weight compensation: study protocol for a randomized controlled trial

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