Literature DB >> 25333247

Obtaining Accelerometer Data in a National Cohort of Black and White Adults.

Virginia J Howard1, J David Rhodes, Aleena Mosher, Brent Hutto, Margaret S Stewart, Natalie Colabianchi, John E Vena, Steven N Blair, Steven P Hooker.   

Abstract

PURPOSE: The objective of this study is to report methodological details and feasibility of conducting an accelerometer ancillary study in a large US cohort being followed for stroke and cognitive decline.
METHODS: Reasons for Geographic and Racial Differences in Stroke is a national population-based study of 30,239 blacks and whites, age ≥45 yr, enrolled January 2003 to October 2007. Baseline evaluations were conducted through computer-assisted telephone interview and an in-home visit. Participants are followed by computer-assisted telephone interview every 6 months. Starting with May 2009 follow-up, contingent on accelerometer availability, participants were invited to wear an accelerometer for 7 d. Device inventory was 1150. Accelerometer, instructions, log sheet, and stamped addressed return envelope were mailed to consenting participants. Postcard acknowledgement and reminders and two calls or less were made to encourage compliance.
RESULTS: Between May 2009 and January 2013, 20,076 were invited to participate; 12,146 (60.5%) consented. Participation rates by race-sex groups were similar: black women, 58.6%; black men, 59.6%; white women, 62.3%; and white men, 60.5%. The mean age of the 12,146 participants to whom devices were shipped was 63.5 ± 8.7 yr. Return rate was 92%. Of 11,174 returned, 1187 were not worn and 14 had device malfunction, and of 9973 with data, 8096 (81.2%) provided usable data, defined as ≥4 d of 10+ h of wear time, ranging from 74.4% among black women to 85.2% among white men.
CONCLUSIONS: Using mail and telephone methods, it is feasible to obtain objective measures of physical activity from a sizeable proportion of a national cohort of adults, with similar participation rates among blacks and whites. Linked with the clinical health information collected through follow-up, these data will allow future analyses on the association between objectively measured sedentary time, physical activity, and health outcomes.

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Mesh:

Year:  2015        PMID: 25333247      PMCID: PMC4404169          DOI: 10.1249/MSS.0000000000000549

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  33 in total

Review 1.  Physical activity and stroke. A meta-analysis of observational data.

Authors:  G C W Wendel-Vos; A J Schuit; E J M Feskens; H C Boshuizen; W M M Verschuren; W H M Saris; D Kromhout
Journal:  Int J Epidemiol       Date:  2004-05-27       Impact factor: 7.196

2.  Lessons learned from a collaborative field-based collection of physical activity data using accelerometers.

Authors:  Sara F Morris; Mary Bea Kolbe; Justin B Moore
Journal:  J Public Health Manag Pract       Date:  2014 Mar-Apr

3.  The reasons for geographic and racial differences in stroke study: objectives and design.

Authors:  Virginia J Howard; Mary Cushman; Leavonne Pulley; Camilo R Gomez; Rodney C Go; Ronald J Prineas; Andra Graham; Claudia S Moy; George Howard
Journal:  Neuroepidemiology       Date:  2005-06-29       Impact factor: 3.282

4.  The geography of stroke mortality in the United States and the concept of a stroke belt.

Authors:  D J Lanska; L H Kuller
Journal:  Stroke       Date:  1995-07       Impact factor: 7.914

Review 5.  Physical activity and cardiovascular disease: evidence for a dose response.

Authors:  H W Kohl
Journal:  Med Sci Sports Exerc       Date:  2001-06       Impact factor: 5.411

6.  Physical activity and risk of stroke in women.

Authors:  F B Hu; M J Stampfer; G A Colditz; A Ascherio; K M Rexrode; W C Willett; J E Manson
Journal:  JAMA       Date:  2000-06-14       Impact factor: 56.272

7.  Exercise and risk of stroke in male physicians.

Authors:  I M Lee; C H Hennekens; K Berger; J E Buring; J E Manson
Journal:  Stroke       Date:  1999-01       Impact factor: 7.914

8.  Physical activity and stroke risk: a meta-analysis.

Authors:  Chong Do Lee; Aaron R Folsom; Steven N Blair
Journal:  Stroke       Date:  2003-09-18       Impact factor: 7.914

9.  Physical activity and stroke risk: the Framingham Study.

Authors:  D K Kiely; P A Wolf; L A Cupples; A S Beiser; W B Kannel
Journal:  Am J Epidemiol       Date:  1994-10-01       Impact factor: 4.897

10.  Physical activity and stroke incidence in women and men. The NHANES I Epidemiologic Follow-up Study.

Authors:  R F Gillum; M E Mussolino; D D Ingram
Journal:  Am J Epidemiol       Date:  1996-05-01       Impact factor: 4.897

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  19 in total

1.  Association Between Objectively Measured Physical Activity and Cognitive Function in Older Adults-The Reasons for Geographic and Racial Differences in Stroke Study.

Authors:  Wenfei Zhu; Virginia J Howard; Virginia G Wadley; Brent Hutto; Steven N Blair; John E Vena; Natalie Colabianchi; David Rhodes; Steven P Hooker
Journal:  J Am Geriatr Soc       Date:  2015-12       Impact factor: 5.562

2.  Accelerometer measured sedentary behavior and physical activity in white and black adults: The REGARDS study.

Authors:  Steven P Hooker; Brent Hutto; Wenfei Zhu; Steven N Blair; Natalie Colabianchi; John E Vena; David Rhodes; Virginia J Howard
Journal:  J Sci Med Sport       Date:  2015-04-17       Impact factor: 4.319

3.  Objectively Measured Physical Activity and Cognitive Function in Older Adults.

Authors:  Wenfei Zhu; Virginia G Wadley; Virginia J Howard; Brent Hutto; Steven N Blair; Steven P Hooker
Journal:  Med Sci Sports Exerc       Date:  2017-01       Impact factor: 5.411

4.  Patterns of Sedentary Behavior in US Middle-Age and Older Adults: The REGARDS Study.

Authors:  Keith M Diaz; Virginia J Howard; Brent Hutto; Natalie Colabianchi; John E Vena; Steven N Blair; Steven P Hooker
Journal:  Med Sci Sports Exerc       Date:  2016-03       Impact factor: 5.411

5.  Classifiers for Accelerometer-Measured Behaviors in Older Women.

Authors:  Dori Rosenberg; Suneeta Godbole; Katherine Ellis; Chongzhi Di; Andrea Lacroix; Loki Natarajan; Jacqueline Kerr
Journal:  Med Sci Sports Exerc       Date:  2017-03       Impact factor: 5.411

6.  The Relationship Between Environmental Exposures and Post-Stroke Physical Activity.

Authors:  Erica Twardzik; Philippa J Clarke; Lynda L Lisabeth; Susan H Brown; Steven P Hooker; Suzanne E Judd; Natalie Colabianchi
Journal:  Am J Prev Med       Date:  2022-03-28       Impact factor: 6.604

7.  Daily physical activity patterns from hip- and wrist-worn accelerometers.

Authors:  E J Shiroma; M A Schepps; J Harezlak; K Y Chen; C E Matthews; A Koster; P Caserotti; N W Glynn; T B Harris
Journal:  Physiol Meas       Date:  2016-09-21       Impact factor: 2.833

8.  Association of Sedentary Behavior With Cancer Mortality in Middle-aged and Older US Adults.

Authors:  Susan C Gilchrist; Virginia J Howard; Tomi Akinyemiju; Suzanne E Judd; Mary Cushman; Steven P Hooker; Keith M Diaz
Journal:  JAMA Oncol       Date:  2020-08-01       Impact factor: 31.777

9.  Patterns of Sedentary Behavior and Mortality in U.S. Middle-Aged and Older Adults: A National Cohort Study.

Authors:  Keith M Diaz; Virginia J Howard; Brent Hutto; Natalie Colabianchi; John E Vena; Monika M Safford; Steven N Blair; Steven P Hooker
Journal:  Ann Intern Med       Date:  2017-09-12       Impact factor: 25.391

10.  Correlates of accelerometry non-adherence in an economically disadvantaged minority urban adult population.

Authors:  Matthew S Cato; Katarzyna Wyka; Emily B Ferris; Kelly R Evenson; Fang Wen; Joan M Dorn; Lorna E Thorpe; Terry T-K Huang
Journal:  J Sci Med Sport       Date:  2020-02-05       Impact factor: 4.597

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