Bodegom, David van

Cameron, Ian D

Kurrle, Susan E

Loevezijn, Ariane A. van

Leiden University Scholary Publications

Sheryl Zimmerman, PhDSchool of Social Work, Cecil G. Sheps Center for HealthServices Research, University of North Carolina at ChapelHill, Chapel Hill, North CarolinaKimberly Ward, BADavid Reed, PhDCecil G. Sheps Center for Health Services Research,University of North Carolina at Chapel Hill, Chapel Hill,North CarolinaRobert Rodriguez, BASchool of Medicine, University of North Carolina atChapel Hill, Chapel Hill, North CarolinaChristine E. Kistler, MD, MAScDepartment of Family Medicine, Cecil G. Sheps Center forHealth Services Research, School of Medicine, Universityof North Carolina at Chapel Hill, Chapel Hill, NorthCarolinaACKNOWLEDGMENTSThis manuscript was presented as a poster at the John B.Graham Student Research Day at the University of NorthCarolina at Chapel Hill School of Medicine on January17, 2013, and on May 3–4, 2013, at the American Geriat-rics Society annual conference at the Presidential postersession and student poster session.Conflict of Interest: The editor in chief has reviewedthe conflict of interest checklist provided by the authors andhas determined that the authors have no financial or anyother kind of personal conflicts with this paper. Dr. Kistlerwas supported by Award K12 HS19468–01 from theAgency for Healthcare Research and Quality awarded to theUniversity of North Carolina (UNC) Mentored CareerDevelopment Program in Comparative EffectivenessResearch and by the UNC Lineberger ComprehensiveCancer Center. This research also was supported by theNational Center for Research Resources and the NationalCenter for Advancing Translational Sciences, NationalInstitutes of Health, through Grant KL2TR000084. It wasconducted as one of the Collaborative Studies in Long-TermCare through the Cecil G. Sheps Center for Health ServicesResearch, University of North Carolina at Chapel Hill.Author Contributions: Kathryn Moore and ChristineKistler had full access to all of the data in the study andtake responsibility for the integrity of the data and theaccuracy of the data analysis. Study concept and design:Kistler, Lewis, Zimmerman. Acquisition of data: Moore,Ward, Rodriguez, Kistler. Analysis and interpretation ofdata: Moore, Lewis, Zimmerman, Reed, Kistler. Draftingof the manuscript: Moore, Lewis, Zimmerman, Kistler.Critical revision of the manuscript for important intellec-tual content: Moore, Lewis, Zimmerman, Reed, Ward,Rodriguez, Kistler. Statistical analysis: Reed, Kistler.Obtained funding: Moore, Kistler. Administrative, techni-cal, and material support: Ward.Sponsor’s Role: The content is solely the responsibilityof the authors and does not necessarily represent the offi-cial views of the National Institutes of Health.REFERENCES1. Preventive US. Services Task Force. Screening for colorectal cancer: U.S.Preventive Services Task Force recommendation statement. Ann Intern Med2008;149:627–637.2. Walter LC, Covinsky KE. Cancer screening in elderly patients: A frame-work for individualized decision making. JAMA 2001;285:2750–2756.3. Bellizzi KM, Breslau ES, Burness A et al. Prevalence of cancer screening inolder, racially diverse adults: Still screening after all these years. ArchIntern Med 2011;171:2031–2037.4. Kistler CE, Kirby KA, Lee D et al. Long-term outcomes following positivefecal occult blood test results in older adults: Benefits and burdens. ArchIntern Med 2011;171:1344–1351.5. Schonberg MA, Leveille SG, Marcantonio ER. Preventive health careamong older women: Missed opportunities and poor targeting. Am J Med2008;121:974–981.6. Katz JN, Chang LC, Sangha O et al. Can comorbidity be measured byquestionnaire rather than medical record review? Med Care 1996;34:73–84.7. Walter LC, Lindquist K, Nugent S et al. Impact of age and comorbidity oncolorectal cancer screening among older veterans. Ann Intern Med2009;150:465.8. Carlson CM, Kirby KA, Casadei MA et al. Lack of follow-up after fecaloccult blood testing in older adults: Inappropriate screening or failure tofollow up? Arch Intern Med 2011;171:249–256.FEASIBILITY OF MEASURING PHYSICAL ACTIVITYUSING ACCELEROMETRY IN HOSPITALIZED ANDCOMMUNITY-LIVING OLDER PEOPLE WITHCOGNITIVE IMPAIRMENTTo the Editor: Physical activity has clear benefits for olderpeople, including older people with cognitive impair-ment.1–4 Precise, valid, reliable measurements of physicalactivity are required for research purposes.5 Accelerometryis increasingly being used as a method of quantifying phys-ical activity. The current study was designed to assess thefeasibility of using an accelerometer (activPAL; PALtech-nologies Ltd, Glasgow, UK) in older people with cognitiveimpairment in hospital and community settings. Twogroups of participants were recruited. The first was from ahospital rehabilitation ward in Sydney, Australia. The sec-ond was from community-living older people in the Horns-by Ku-ring-gai region of Sydney, Australia. A Mini-MentalState Examination score of <25 was defined as cognitiveimpairment. In the rehabilitation ward sample, participantswere recovering from significant injury or illness with theaim of improving functioning and returning to community.Each group wore the device on their thigh for at least7 days (Figure 1). The device was wrapped in the finger ofa latex glove for waterproofing and affixed to the thighusing a transparent dressing and left in place for a numberof days. This attachment provided 2 to 7 days of continu-ous use, allowing the wearer to shower without removingthe device. Participants were asked to wear the accelerom-eter for 2 weeks. The device recorded the amount of timein minutes per hour spent sitting or lying, the number ofsit-to-stand movements, time spent standing, time spentstepping, and the metabolic equivalents of the physicalbehavior (METS). The device has been validated for use inan elderly population.6–8 Data were extracted from thedevice to a spreadsheet and manually coded for eachparameter. The relevant health research ethics committeeapproved the study.388 LETTERS TO THE EDITOR FEBRUARY 2014–VOL. 62, NO. 2 JAGSTable 1 shows characteristics and device use for thestudy. There were 24 cognitively impaired participants inthe hospital rehabilitation group (54% female, mean age86) and 21 cognitively impaired participants in the com-munity group (43% female, mean age 82). Eighteen of 24participants (75%) in the hospital group and 20 of 21(95%) in the community group completed the study. Twoaccelerometers had to be rebooted because they did notseem to operate according to function. Failure of the twodevices did not lead to major loss of data. There is signifi-cant data processing time required for data checking andsummarizing, estimated as 2 minutes per day of measuredactivity downloaded from the device. In this study,approximately 30 minutes of data processing was requiredto calculate mean activity scores for 2 weeks of recordeddata per participant.This pilot study shows that it is feasible to measurephysical activity using accelerometry in older people withcognitive impairment in hospital and community settings.To the authors’ knowledge, this is the first study toconfirm this with this type of device. This is consistent withprevious observations in another study using a differentaccelerometer worn on the arm (Sense Wear; Body Media,Pittsburgh, PA).9 The results recorded in the current studyin cognitively impaired older people are comparable withthose of other studies using pedometers and accelerometersto assess physical activity in older people.8–10 It is feasibleto measure physical activity using an accelerometer in cog-nitively impaired older people, but these conclusions maynot be generalizable to people with severe cognitive impair-ment, who may not tolerate the device. For people who tol-erate the device, the recordings were successful, butsignificant time is required to extract and summarize thedata, which will limit the use of the current device toresearch settings.Ariane A. van Loevezijn, MScLeyden Academy on Vitality and Ageing, Leidenthe NetherlandsIan D. Cameron, MB, BS, PhDRehabilitation Studies Unit, University of Sydney, SydneyAustraliaSusan E. Kurrle, MB, BS, PhDCurran Ageing Research Unit, Hornsby Ku-ring-gaiHospital, Hornsby, AustraliaDavid van Bodegom, MD, PhDLeyden Academy on Vitality and Ageing, Leidenthe NetherlandsDepartment of Gerontology and Geriatrics, LeidenUniversity Medical Centre, Leiden, the NetherlandsACKNOWLEDGMENTSConflict of Interest: This project was funded by theCurran Ageing Research Unit. The authors have nofinancial involvement or interest in the activPAL device.A.A. van Loevezijn was granted a scholarship, “DOO in-ternationaliserings beurs,” by the Leiden University Medi-cal Center. The scholarship is intended for students doingpart of their medical training abroad.Author Contributions: All authors contributed to thestudy concept and design, preparation of manuscript andanalysis and interpretation of data. van Loevezijn: datacollection.Sponsor’s Role: The sponsor had no role in the design,methods, subject recruitment, data collection or analysis,or preparation of the paper.REFERENCES1. Manini TM, Pahor M. Physical activity and maintaining physical functionin older adults. Br J Sports Med 2009;43:28–31.Figure 1. Device in place on the right thigh of a studyparticipant.Table 1. Participant Characteristics and Device UseCharacteristicsand FeasibilityHospitalRehabilitation,n = 24CommunityLiving,n = 21Participant characteristicFemale, n (%) 13 (54) 9 (43)Age, mean  SD 86  5 82  7Mini-Mental State Examinationscore, mean  SD20  5 21  4EuroQol 5D score, mean  SD 9  2 6  3Short Physical PerformanceBattery score, mean  SD4  3 6  3Device UseParticipants who completedstudy, n (%)18 (75) 20 (95)Upright time in minutesper day, mean  SD87  39 353  115Walking time in minutesper day, mean  SD15  10 62  34Number of steps perday, mean  SD921  678 4,653  2,756SD = Standard Deviation.JAGS FEBRUARY 2014–VOL. 62, NO. 2 LETTERS TO THE EDITOR 3892. Batty GD. Physical activity and coronary heart disease in older adults. Asystematic review of epidemiological studies. Eur J Public Health2002;12:171–176.3. Liu CK, Fielding RA. Exercise as an intervention for frailty. Clin GeriatrMed 2011;27:101–110.4. Angevaren M, Aufdemkampe G, Verhaar HJ et al. Physical activity andenhanced fitness to improve cognitive function in older people withoutknown cognitive impairment. Cochrane Database Syst Rev 2008:CD005381.5. Forbes D, Forbes S, Morgan DG et al. Physical activity programs for per-sons with dementia. Cochrane Database Syst Rev 2008:CD006489.6. Grant PM, Dall PM, Mitchell SL et al. Activity-monitor accuracy inmeasuring step number and cadence in community-dwelling older adults.J Aging Phys Act 2008;16:201–214.7. Mutrie N, Doolin O, Fitzsimons CF et al. Increasing older adults’ walkingthrough primary care: Results of a pilot randomized controlled trial. FamPract 2012;29:633–642.8. Lord S, Chastin SF, McInnes L et al. Exploring patterns of daily physicaland sedentary behaviour in community-dwelling older adults. Age Ageing2011;40:205–210.9. Erickson KI, Barr LL, Weinstein AM et al. Measuring physical activityusing accelerometry in a community sample with dementia. J Am GeriatrSoc 2013;61:158–159.10. Bohannon RW. Number of pedometer-assessed steps taken per day byadults: A descriptive meta-analysis. Phys Ther 2007;87:1642–1650.MOBILE GERIATRIC TEAM ADVICE: EFFECT ONLENGTH OF HOSPITAL STAY IN OLDER ADULTSTo the Editor: Older adults have longer length of hospitalstay (LHS) in medical acute care units than youngerindividuals.1,2 Early intervention of a mobile geriatric team(MGT) combining a brief geriatric assessment (BGA) andsubsequent standardized advice reduces the LHS of olderadults hospitalized after an admission to the emergencydepartment (ED).3 It has recently been reported that MGTgeriatric advice (medical advice for the diagnosis and treat-ment of polymorbid older adults) but not gerontologicaladvice combining geriatric and social (organization ofhome-help services) advice was associated with early dis-charge from the ED.4 Because LHS is longer in medicalacute care units than in the ED, which allows more timeto implement adapted gerontological advice, it washypothesized that MGT gerontological advice would beassociated with shorter LHS in older adults. The aim ofthis study was to determine whether MGT gerontologicaladvice was associated with shorter LHS of older adultshospitalized in nongeriatric acute care medical unitsthrough the ED than of controls who did not receivegerontological advice.Between February and June 2011, 106 older adults(mean age 85.2  5.0; 70.8% female) who visited the EDof Angers University Hospital were prospectively includedin this cohort study. Inclusion criteria were aged 75 andolder and admission to the ED. Participants were dividedinto three groups based on MGT advice (geriatric, geron-tological, or no advice). All participants were matched forage, sex, and reason for admission to the ED to improvecomparability between those that the MGT did and didTable 1. Baseline Characteristics of Older Adults Categorized According to the Nature of Advice Provided by aMobile Geriatric Team, and Multiple Cox Regression Models Showing the Association Between the Length of Hos-pital Stay (Dependent Variable) and the Nature of Mobile Geriatric Team Advice (Independent Variable) Adjustedon Baseline Clinical Characteristics (n = 106)CharacteristicMobile Geriatric Team Advice, n (%)P-ValueaFully Adjusted Cox RegressionNone,n = 58Geriatric,n = 16Gerontological,n = 32Hazard Ratio (95%Confidence Interval) P-ValueMobile geriatric team intervention (reference none)Brief geriatric assessmentwith geriatric advice1.26 (0.64–2.46) .50Brief geriatric assessmentwith gerontological advice1.98 (1.10–3.58) .02Aged ≥85 31 (53.4) 10 (62.5) 22 (68.8) .35 0.60 (0.36–1.00) .05Male 20 (34.5) 6 (37.5) 5 (15.6) .12 1.35 (0.70–2.60) .36≥5 drugs taken daily 40 (76.9) 12 (75.0) 28 (87.5) .43 1.08 (0.55–2.13) .82No use of formal or informalhome services9 (15.5) 4 (25.0) 4 (12.5) .53 1.24 (0.61–2.51) .55History of falls in previous6 months19 (52.8) 8 (50.0) 23 (76.7) .08 1.01 (0.50–2.02) .98Temporal disorientation 16 (27.6) 5 (31.3) 8 (25.0) .90 1.50 (0.83–2.73) .18Living at home 47 (81.0) 12 (75.0) 24 (75.0) .75 0.62 (0.35–1.11) .11Reason for admission to emergency departmentAcute organ failureb 18 (31.0) 3 (18.8) 6 (18.8) .35 ReferenceGait or balance disorders 16 (27.6) 5 (31.3) 16 (50.0) .10 1.16 (0.54–2.51) .70Neuropsychiatric disordersc 2 (3.4) 2 (12.5) 3 (9.4) .33 0.88 (0.28–2.75) .83Social-related conditions 8 (13.8) 2 (12.5) 4 (12.5) .98 0.66 (0.28–1.60) .36Other 14 (24.1) 4 (25) 3 (9.4) .21 0.92 (0.42–2.00) .84aBetween-group comparison based on chi-square test.bCongestive heart failure, chronic lung disease, chronic kidney disease, or cirrhosis.cDelirium, dementia, or mental behavioral disorder.390 LETTERS TO THE EDITOR FEBRUARY 2014–VOL. 62, NO. 2 JAGS

Feasibility of Measuring Physical Activity Using Accelerometry in Hospitalized and Community-Living Older People with Cognitive Impairment

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Feasibility of Measuring Physical Activity Using Accelerometry in Hospitalized and Community-Living Older People with Cognitive Impairment

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