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BMC Public Health
Published in: BMC Public Health 1/2017

Open Access 01-12-2017 | Study protocol

The Objective Physical Activity and Cardiovascular Disease Health in Older Women (OPACH) Study

Authors: Andrea Z. LaCroix, Eileen Rillamas-Sun, David Buchner, Kelly R. Evenson, Chongzhi Di, I-Min Lee, Steve Marshall, Michael J. LaMonte, Julie Hunt, Lesley Fels Tinker, Marcia Stefanick, Cora E. Lewis, John Bellettiere, Amy H. Herring

Published in: BMC Public Health | Issue 1/2017

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Abstract

Background

Limited evidence exists to inform physical activity (PA) and sedentary behavior guidelines for older people, especially women. Rigorous evidence on the amounts, intensities, and movement patterns associated with better health in later life is needed.

Methods/Design

The Objective PA and Cardiovascular Health (OPACH) Study is an ancillary study to the Women’s Health Initiative (WHI) Program that examines associations of accelerometer-assessed PA and sedentary behavior with cardiovascular and fall events. Between 2012 and 2014, 7048 women aged 63–99 were provided with an ActiGraph GT3X+ (Pensacola, Florida) triaxial accelerometer, a sleep log, and an OPACH PA Questionnaire; 6489 have accelerometer data. Most women were in their 70s (40%) or 80s (46%), while approximately 10% were in their 60s and 4% were age 90 years or older. Non-Hispanic Black or Hispanic/Latina women comprise half of the cohort. Follow-up includes 1-year of falls surveillance with monthly calendars and telephone interviews of fallers, and annual follow-up for outcomes with adjudication of incident cardiovascular disease (CVD) events through 2020. Over 63,600 months of calendar pages were returned by 5,776 women, who reported 5,980 falls. Telephone interviews were completed for 1,492 women to ascertain the circumstances, injuries and medical care associated with falling. The dataset contains extensive information on phenotypes related to healthy aging, including inflammatory and CVD biomarkers, breast and colon cancer, hip and other fractures, diabetes, and physical disability.

Discussion

This paper describes the study design, methods, and baseline data for a diverse cohort of postmenopausal women who wore accelerometers under free-living conditions as part of the OPACH Study. By using accelerometers to collect more precise and complete data on PA and sedentary behavior in a large cohort of older women, this study will contribute crucial new evidence about how much, how vigorous, and what patterns of PA are necessary to maintain optimal cardiovascular health and to avoid falls in later life.

Clinical trials registration

ClinicalTrials.gov identifier NCT00000611. Registered 27 October 1999.
Appendix
Available only for authorised users
Literature
1.
2.
3.
Crimmins EM, Beltran-Sanchez H. Mortality and morbidity trends: is there compression of morbidity? J Gerontol B Psychol Sci Soc Sci. 2011;66(1):75–86.CrossRefPubMed
4.
Harris-Kojetin L, Sengupta M, Park-Lee E, Valverde R, Caffrey C, Rome V, et al. Long-term care providers and services users in the United States: data from the national study of long-term care providers, 2013–2014. National center for health statistics. Vital Health Stat 3. 2016;38(38):1–118.
5.
6.
Spillman BC, Lubitz J. The effect of longevity on spending for acute and long-term care. N Engl J Med. 2000;342(19):1409–15.CrossRefPubMed
7.
U.S. Department of Health and Human Services. Physical Activity Guidelines for Americans. Washington, DC: U.S. Dept. of Health and Human Services; 2008.
8.
Tucker JM, Welk GJ, Beyler NK. Physical activity in U.S.: adults compliance with the physical activity guidelines for Americans. Am J Prev Med. 2011;40(4):454–61.CrossRefPubMed
9.
Dunlop DD, Song J, Arnston EK, Semanik PA, Lee J, Chang RW, et al. Sedentary time in US older adults associated with disability in activities of daily living independent of physical activity. J Phys Act Health. 2015;12(1):93–101.CrossRefPubMed
10.
Matthews CE, Chen KY, Freedson PS, Buchowski MS, Beech BM, Pate RR, et al. Amount of time spent in sedentary behaviors in the United States, 2003–2004. Am J Epidemiol. 2008;167(7):875–81.CrossRefPubMedPubMedCentral
11.
Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008;40(1):181–8.CrossRefPubMed
12.
Design of the Women’s Health Initiative clinical trial and observational study. The Women’s Health Initiative Study Group. Control Clin Trials. 1998; 19(1):61–109.
13.
Anderson GL, Manson J, Wallace R, Lund B, Hall D, Davis S, et al. Implementation of the women’s health initiative study design. Ann Epidemiol. 2003;13(9 Suppl):S5–17.CrossRefPubMed
14.
Guralnik JM, Ferrucci L, Pieper CF, Leveille SG, Markides KS, Ostir GV, et al. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci. 2000;55(4):M221–31.CrossRefPubMed
15.
Simonsick EM, Newman AB, Nevitt MC, Kritchevsky SB, Ferrucci L, Guralnik JM, et al. Measuring higher level physical function in well-functioning older adults: expanding familiar approaches in the health ABC study. J Gerontol A Biol Sci Med Sci. 2001;56(10):M644–9.CrossRefPubMed
16.
Curb JD, McTiernan A, Heckbert SR, Kooperberg C, Stanford J, Nevitt M, et al. Outcomes ascertainment and adjudication methods in the women’s health initiative. Ann Epidemiol. 2003;13(9 Suppl):S122–8.CrossRefPubMed
17.
Meyer AM, Evenson KR, Morimoto L, Siscovick D, White E. Test-retest reliability of the women’s health initiative physical activity questionnaire. Med Sci Sports Exerc. 2009;41(3):530–8.CrossRefPubMedPubMedCentral
18.
Rillamas-Sun E, Buchner DM, Di C, Evenson KR, LaCroix AZ. Development and application of an automated algorithm to identify a window of consecutive days of accelerometer wear for large-scale studies. BMC Res Notes. 2015;8:270.CrossRefPubMedPubMedCentral
19.
McVeigh JA, Winkler EAH, Healy GN, Slater J, Eastwood PR, Straker LM. Validity of an automated algorithm to identify waking and in-bed wear time in hip-worn accelerometer data collected with a 24-hour wear protocol in young adults. Physiol Meas. 2016. (in press).
20.
Tracy DJ, Xu Z, Choi L, Acra S, Chen KY, Buchowski MS. Separating bedtime rest from activity using waist or wrist-worn accelerometers in youth. PloS One. 2014;9(4):e92512.CrossRefPubMedPubMedCentral
21.
Choi L, Liu Z, Matthews CE, Buchowski MS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011;43(2):357–64.CrossRefPubMedPubMedCentral
22.
Choi L, Ward SC, Schnelle JF, Buchowski MS. Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. Med Sci Sports Exerc. 2012;44(10):2009–16.CrossRefPubMedPubMedCentral
23.
Ware Jr JE, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–83.CrossRefPubMed
24.
Evenson KR, Wen F, Herring AH, Di C, LaMonte MJ, Tinker LF, Lee IM, et al. Calibrating physical activity intensity for hip-worn accelerometry in women age 60 to 91 years: The women’s health initiative OPACH calibration study. Prev Med Rep. 2015;2:750–6.CrossRefPubMedPubMedCentral
25.
Evenson KR, Buchner DM, Morland KB. Objective measurement of physical activity and sedentary behavior among US adults aged 60 years or older. Prev Chronic Dis. 2012;9:E26.PubMed
26.
Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc accelerometer. Med Sci Sports Exerc. 1998;30(5):777–81.CrossRefPubMed
27.
Hall KS, Howe CA, Rana SR, Martin CL, Morey MC. METs and accelerometry of walking in older adults: standard versus measured energy cost. Med Sci Sports Exerc. 2013;45(3):574–82.CrossRefPubMed
28.
Kozey S, Lyden K, Staudenmayer J, Freedson P. Errors in MET estimates of physical activities using 3.5 ml x kg(−1) x min(−1) as the baseline oxygen consumption. J Phys Act Health. 2010;7(4):508–16.CrossRefPubMed
29.
Buchner DM, Campbell AJ. Inactivity as a risk factor for activity-related injuries. Am J Prev Med. 2010;39(1):102–3.CrossRefPubMed
30.
Sherrington C, Whitney JC, Lord SR, Herbert RD, Cumming RG, Close JC. Effective exercise for the prevention of falls: a systematic review and meta-analysis. J Am Geriatr Soc. 2008;56(12):2234–43.CrossRefPubMed
31.
Kerr J, Marshall SJ, Godbole S, Chen J, Legge A, Doherty AR, et al. Using the SenseCam to improve classifications of sedentary behavior in free-living settings. Am J Prev Med. 2013;44(3):290–6.CrossRefPubMed
32.
Lee IM, Sesso HD, Oguma Y, Paffenbarger Jr RS. Relative intensity of physical activity and risk of coronary heart disease. Circulation. 2003;107(8):1110–6.CrossRefPubMed
33.
Wisen AG, Farazdaghi RG, Wohlfart B. A novel rating scale to predict maximal exercise capacity. Eur J Appl Physiol. 2002;87(4–5):350–7.PubMed
34.
Gibbs BB, Reis JP, Schelbert EB, Craft LL, Sidney S, Lima J, et al. Sedentary screen time and left ventricular structure and function: the CARDIA study. Med Sci Sports Exerc. 2014;46(2):276–83.CrossRefPubMedPubMedCentral
35.
Rosenberg DE, Norman GJ, Wagner N, Patrick K, Calfas KJ, Sallis JF. Reliability and validity of the Sedentary Behavior Questionnaire (SBQ) for adults. J Phys Act Health. 2010;7(6):697–705.CrossRefPubMed
36.
Kempen GI, Yardley L, van Haastregt JC, Zijlstra GA, Beyer N, Hauer K, et al. The short FES-I: a shortened version of the falls efficacy scale-international to assess fear of falling. Age Ageing. 2008;37(1):45–50.CrossRefPubMed
37.
Cummings SR, Nevitt MC, Kidd S. Forgetting falls. The limited accuracy of recall of falls in the elderly. J Am Geriatr Soc. 1988;36(7):613–6.CrossRefPubMed
38.
Berrigan D, Troiano RP. The association between urban form and physical activity in U.S. adults. Am J Prev Med. 2002;23(2 Suppl):74–9.CrossRefPubMed
39.
Saelens BE, Sallis JF, Black JB, Chen D. Neighborhood-based differences in physical activity: an environment scale evaluation. Am J Public Health. 2003;93(9):1552–8.CrossRefPubMedPubMedCentral
40.
Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. CHAMPS physical activity questionnaire for older adults: outcomes for interventions. Med Sci Sports Exerc. 2001;33(7):1126–41.CrossRefPubMed
Metadata
Title
The Objective Physical Activity and Cardiovascular Disease Health in Older Women (OPACH) Study
Authors
Andrea Z. LaCroix
Eileen Rillamas-Sun
David Buchner
Kelly R. Evenson
Chongzhi Di
I-Min Lee
Steve Marshall
Michael J. LaMonte
Julie Hunt
Lesley Fels Tinker
Marcia Stefanick
Cora E. Lewis
John Bellettiere
Amy H. Herring
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2017
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-017-4065-6

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