Literature DB >> 26288333

Ankle Accelerometry for Assessing Physical Activity Among Adolescent Girls: Threshold Determination, Validity, Reliability, and Feasibility.

Erin R Hager1, Margarita S Treuth2, Candice Gormely1, LaShawna Epps1, Soren Snitker1, Maureen M Black1.   

Abstract

PURPOSE: Ankle accelerometry allows for 24-hr data collection and improves data volume/integrity versus hip accelerometry. Using Actical ankle accelerometry, the purpose of this study was to (a) develop sensitive/specific thresholds, (b) examine validity/reliability, (c) compare new thresholds with those of the manufacturer, and (d) examine feasibility in a community sample (low-income, urban adolescent girls).
METHOD: Two studies were conducted with 6th- through 7th-grade girls (aged 10-14 years old): First was a laboratory study (n = 24), in which 2 Actical accelerometers were placed on the ankle and worn while measuring energy expenditure (Cosmed K4b2, metabolic equivalents [METs]) during 10 prescribed activities. Analyses included device equivalence reliability (intraclass correlation coefficient [ICC], activity counts of 2 Acticals), criterion-related validity (correlation, activity counts and METs), and calculations of sensitivity, specificity, kappa, and receiver-operating characteristic curves for thresholds. The second was a free-living study (n = 459), in which an Actical was worn for more than 7 days on the ankle (full 24-hr days retained). Analyses included feasibility (frequencies, missing data) and paired t tests (new thresholds vs. those of the manufacturer).
RESULTS: In the laboratory study, the Actical demonstrated reliability (ICC = .92) and validity (r = .81). Thresholds demonstrated sensitivity (91%), specificity (84%), kappa = .73 (p = .043), area under curve range = .81-.97. In the free-living study, 99.6% of participants wore the accelerometer; 84.1% had complete/valid data (mean = 5.7 days). Primary reasons for missing/invalid data included: improper programming/documentation (5.2%), failure to return device (5.0%), and wear-time ≤ 2 days (2.8%). The moderate-to-vigorous physical activity threshold (> 3,200 counts/minute) yielded 37.2 min/day, 2 to 4.5 times lower than that of the manufacturer's software (effect size = 0.74-4.05).
CONCLUSIONS: Validity, reliability, and feasibility evidences support Actical ankle accelerometry to assess physical activity in community studies of adolescent girls. When comparing manufacturers' software versus new thresholds, a major difference was observed.

Entities:  

Keywords:  Actical; African American; community studies; moderate-to-vigorous physical activity

Mesh:

Year:  2015        PMID: 26288333      PMCID: PMC4775231          DOI: 10.1080/02701367.2015.1063574

Source DB:  PubMed          Journal:  Res Q Exerc Sport        ISSN: 0270-1367            Impact factor:   2.500


  34 in total

1.  Defining accelerometer thresholds for activity intensities in adolescent girls.

Authors:  Margarita S Treuth; Kathryn Schmitz; Diane J Catellier; Robert G McMurray; David M Murray; M Joao Almeida; Scott Going; James E Norman; Russell Pate
Journal:  Med Sci Sports Exerc       Date:  2004-07       Impact factor: 5.411

Review 2.  Statistical considerations in the analysis of accelerometry-based activity monitor data.

Authors:  John Staudenmayer; Weimo Zhu; Diane J Catellier
Journal:  Med Sci Sports Exerc       Date:  2012-01       Impact factor: 5.411

Review 3.  Calibration of accelerometer output for children.

Authors:  Patty Freedson; David Pober; Kathleen F Janz
Journal:  Med Sci Sports Exerc       Date:  2005-11       Impact factor: 5.411

4.  Distributed lag and spline modeling for predicting energy expenditure from accelerometry in youth.

Authors:  Leena Choi; Kong Y Chen; Sari A Acra; Maciej S Buchowski
Journal:  J Appl Physiol (1985)       Date:  2009-12-03

5.  Predicting activity energy expenditure using the Actical activity monitor.

Authors:  Daniel P Heil
Journal:  Res Q Exerc Sport       Date:  2006-03       Impact factor: 2.500

6.  Differences in demographic, behavioral, and biological variables between those with valid and invalid accelerometry data: implications for generalizability.

Authors:  Paul D Loprinzi; Bradley J Cardinal; Carlos J Crespo; Gary R Brodowicz; Ross E Andersen; Ellen Smit
Journal:  J Phys Act Health       Date:  2012-02-29

7.  A comprehensive evaluation of commonly used accelerometer energy expenditure and MET prediction equations.

Authors:  Kate Lyden; Sarah L Kozey; John W Staudenmeyer; Patty S Freedson
Journal:  Eur J Appl Physiol       Date:  2010-09-15       Impact factor: 3.078

8.  Age-related change in physical activity in adolescent girls.

Authors:  Russell R Pate; June Stevens; Larry S Webber; Marsha Dowda; David M Murray; Deborah R Young; Scott Going
Journal:  J Adolesc Health       Date:  2008-10-29       Impact factor: 5.012

9.  Valid and invalid accelerometry data among children and adolescents: comparison across demographic, behavioral, and biological variables.

Authors:  Paul D Loprinzi; Ellen Smit; Bradley J Cardinal; Carlos Crespo; Gary Brodowicz; Ross Andersen
Journal:  Am J Health Promot       Date:  2013-07-22

10.  Physical activity in the United States measured by accelerometer.

Authors:  Richard P Troiano; David Berrigan; Kevin W Dodd; Louise C Mâsse; Timothy Tilert; Margaret McDowell
Journal:  Med Sci Sports Exerc       Date:  2008-01       Impact factor: 5.411

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  11 in total

1.  A Dyadic Analysis on Source Discrepancy and a Mediation Analysis via Self-Efficacy in the Parental Support and Physical Activity Relationship among Black Girls.

Authors:  Yan Wang; Erin R Hager; Laurence S Magder; Raquel Arbaiza; Samantha Wilkes; Maureen M Black
Journal:  Child Obes       Date:  2019-01-17       Impact factor: 2.992

2.  Waking up to sleep's role in obesity and blood pressure among Black adolescent girls in low-income, US urban communities: A longitudinal analysis.

Authors:  Angela Cristina Bizzotto Trude; Bridget Armstrong; Adriana Kramer Fiala Machado; Emerson M Wickwire; Lauren B Covington; Yan Wang; Erin Hager; Maureen M Black
Journal:  Sleep Health       Date:  2022-02-11

3.  "Wellness Champions for Change," a multi-level intervention to improve school-level implementation of local wellness policies: Study protocol for a cluster randomized trial.

Authors:  Hannah G Lane; Rachel Deitch; Yan Wang; Maureen M Black; Genevieve F Dunton; Linda Aldoory; Lindsey Turner; Elizabeth A Parker; Shauna C Henley; Brit Saksvig; Hee-Jung Song; Erin R Hager
Journal:  Contemp Clin Trials       Date:  2018-10-18       Impact factor: 2.226

4.  Associations between elementary and middle school teachers' physical activity promoting practices and teacher- and school-level factors.

Authors:  Ann Pulling Kuhn; Edward Kim; Hannah G Lane; Yan Wang; Rachel Deitch; Lindsey Turner; Erin R Hager; Elizabeth A Parker
Journal:  Int J Behav Nutr Phys Act       Date:  2021-05-19       Impact factor: 6.457

5.  Toddler physical activity study: laboratory and community studies to evaluate accelerometer validity and correlates.

Authors:  Erin R Hager; Candice E Gormley; Laura W Latta; Margarita S Treuth; Laura E Caulfield; Maureen M Black
Journal:  BMC Public Health       Date:  2016-09-06       Impact factor: 3.295

6.  Toddler obesity prevention: A two-generation randomized attention-controlled trial.

Authors:  Maureen M Black; Erin R Hager; Yan Wang; Kristen M Hurley; Laura W Latta; Margo Candelaria; Laura E Caulfield
Journal:  Matern Child Nutr       Date:  2020-09-04       Impact factor: 3.092

7.  An ecological momentary assessment study of physical activity behaviors among mothers of toddlers from low-income households.

Authors:  Katherine L Campbell; Yan Wang; Ann Pulling Kuhn; Maureen M Black; Erin R Hager
Journal:  BMC Womens Health       Date:  2021-03-22       Impact factor: 2.809

8.  On the Move or Barely Moving? Age-Related Changes in Physical Activity, Sedentary, and Sleep Behaviors by Weekday/Weekend Following Pandemic Control Policies.

Authors:  Ann Pulling Kuhn; Alysse J Kowalski; Yan Wang; Rachel Deitch; Helina Selam; Zahra Rahmaty; Maureen M Black; Erin R Hager
Journal:  Int J Environ Res Public Health       Date:  2021-12-28       Impact factor: 3.390

Review 9.  Accuracy of Accelerometers for Measuring Physical Activity and Levels of Sedentary Behavior in Children: A Systematic Review.

Authors:  Brian A Lynch; Tara K Kaufman; Tamim I Rajjo; K Mohammed; Seema Kumar; M Hassan Murad; Natalie E Gentile; Gabriel A Koepp; Shelly K McCrady-Spitzer; James A Levine
Journal:  J Prim Care Community Health       Date:  2019 Jan-Dec

10.  Home and Neighborhood Physical Activity Location Availability among African American Adolescent Girls Living in Low-Income, Urban Communities: Associations with Objectively Measured Physical Activity.

Authors:  Ann Pulling Kuhn; Alexandra Cockerham; Nicole O'Reilly; Jacob Bustad; Victor Miranda; Tatiana V Loboda; Maureen M Black; Erin R Hager
Journal:  Int J Environ Res Public Health       Date:  2021-05-09       Impact factor: 3.390

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