Research papera Geriatric Medicine Center, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan b Division of Neurology, Department of Internal Medicine, Kaohsiung Veterans General Hos
Trang 1Research paper
a
Geriatric Medicine Center, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
b
Division of Neurology, Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
c
Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan
d Aging and Health Research Center, National Yang Ming University, Taipei, Taiwan
e
Department of Family Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
f
Department of Emergency Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
g
Department of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
1 Introduction
Taiwanhasbecomeanagingsocietyin1993andisestimatedto
becomeanagedsocietyby2017,whichmakesTaiwanthefastest
agingcountryintheworld[1].Populationagingmaycausevarious
challengestothehealthcaresystems,andfallshavebeenassociated withstrongriskstothehealthofolderpeople.Generallyspeaking, nearlyathirdofelderlypeoplemayexperiencefallseveryyear,and more than 50% of these falls occurred during certain form of locomotion[2].Fallsarethemostcommoncauseofinjury-related deathsamongpeopleaged75andolder,whichisthesameasin non-fatalinjuriesamongfemalesaged85yearsandolder[3].Fallsarealso
aseriouspublichealth issuethatarehighlyassociatedwithmorbidity andmortalityofolderpeople[4],andamultifactorialapproachis consideredthemosteffectivestrategytopreventfalls[5]
Infallpreventionprograms,screeningtheriskoffallsisthefirst andthemostcriticalsteptostoptheviciouscycle.Screeningthe historyofpreviousfallsisaquick,simple,andeffectivetoolforthe first step of risk assessment, which was supported by both theAmericanGeriatricsSociety(AGS)and theBritishGeriatrics
A R T I C L E I N F O
Article history:
Received 20 April 2014
Accepted 6 June 2014
Available online xxx
Keywords:
Gait speed
Fall
Oldest old
Men
History of falls
A B S T R A C T
* Corresponding author Geriatric Medicine Center and Division of Neurology,
Kaohsiung Veterans General Hospital, Taiwan; No 386, Ta-Chung 1st RD, Zuoying
District, Kaohsiung 813, Taiwan Tel.: +886 7 342 2121x2091; fax: +886 7 348 1478.
** Corresponding author Center for Geriatrics and Gerontology, Taipei Veterans
General Hospital, No 201, Sec 2, Shih-Pai Road, Taipei, Taiwan Tel.: +886 2 2875 7830;
fax: +886 2 2875 7711.
E-mail addresses: ck.vghks@gmail.com (C.-K Liang), mychou@vghks.gov.tw
(M.-Y Chou), lining.peng@gmail.com (L.-N Peng), lmeichen@vghks.gov.tw
(M.-C Liao), mdjim0814@gmail.com (C.-L Chu), ytlin@vghks.gov.tw (Y.-T Lin),
lkchen2@vghtpe.gov.tw (L.-K Chen).
Available online at
ScienceDirect
www.sciencedirect.com
http://dx.doi.org/10.1016/j.eurger.2014.06.034
1878-7649/ß 2014 Published by Elsevier Masson SAS.
Trang 2Society (BGS) [6] History of fall is the strongest predictor for
subsequentfalls [7–9], as well as therisk for fractures among
peopleaged45yearsandover[10].IntheAGS-BGSguideline,after
screening the history of falls, evaluating the gait/balance
disturbancewasthesecond step in therisk assessment, and a
numberoftestswererecommended,suchasGetupandGotest,
Timed Up and Go test, the Berg Balance Scale, and the
Performance-Oriented Mobility Assessment [6] However,
cur-rently,nosufficientevidencesupportedusinga specifictestfor
balanceandgaitdisturbancetopredictsubsequentfalls[6].Among
allthesetests,gaitspeedhasbeenrecognizedasasimplescreening
testforvariousadversehealthoutcomesofolderpeople,suchas
mobility disability, institutionalization, death, and cognitive
decline[11].Ithasbeen reported thatthegait speed0.8m/s
wasassociated with a higher risk of adverse health outcomes,
[11,12]andagaitspeedslowerthan1.0m/smayincreasetherisk
ofmortality[13,14].However,studiesfocusedontheeffectofgait
speedinpredictingfallsamongpeopleagedover80years were
scarce.Moreover,somepreviousstudiessuggestedtore-definethe
cut-offofslowergaitspeedamongoldestoldpopulationdue to
their survivaleffect [15,16].Although thehistory of fallsis an
effectivescreeningtoolforfalls,itdoesnotcompletelyreflectthe
currenthealthstatus,physicalfunctionandriskforfallsofolder
people.Therefore,themainaimofthisstudywastoevaluatethe
roleofgaitspeedinhistoryofpreviousfallstopredictsubsequent
fallsamongpeopleaged80yearsandolderinTaiwan
2 Methods
2.1 Participantsandstudydesign
This prospective observationalcohort study invited all
resi-dentsliving intheVeterans Home,a retirementcommunity,in
southernTaiwaninJanuaryof2012.Forthosewhoparticipatedin
thestudy,demographicdatawerecollectedandthe
comprehen-sivegeriatricassessmentswerepreformedtothemtwiceayear
aftertheenrollment.Subjectswiththefollowingconditionswere
excludedforstudy:
unabletowalkwithawalkingaid;
unabletocommunicatewithresearchstaff;
unabletoobtaininformedconsentfromparticipants;
subjects with their expected life expectancy shorter than
12months
Atotalof278peopleaged80yearsandolderwerescreened,
and7ofthemwereexcluded(5peoplewereunabletowalk,2
person withincomplete fall history) for study Among eligible
studysubjects(n=271),41peopledidnotcompletethe6-mwalk
test,so,onlyatotalof230residentswereenrolledinthisstudy
ThewholestudywasapprovedbytheInstitutionalReviewBoard
ofKaohsiungVeteransGeneralHospital
2.2 Datacollection
2.2.1 Demographiccharacteristics
Threewell-trainedresearchnursesinterviewedallparticipants
tocollect thedemographic data,including age, smoking habit,
habitual alcohol use status, presence of pain, sleep problems,
urinary incontinence, medical history, co-morbidities by using
CharlsonComorbidityIndex[17],andbodymassindex(BMI)were
obtainedforeachstudysubject
2.2.2 ComprehensiveGeriatricAssessment(CGA)
TheresearchnursesperformedCGAforallparticipants,which
includedvisualandhearingimpairment,polypharmacy(defined
as currently using>4 prescription drugs for over 2weeks), depressive symptoms using the 15-item Chinese Geriatric DepressionScale(GDS-15,ascoreof5andmorewasdefinedas depressive) [18], nutritional status using the Mini Nutritional Assessment-shortform(MNA-SF,malnutritionwasdefinedasthe MNA-SFscoresof11andless)[19],cognitivefunctiondetermined
by the Chinese version of the Mini-Mental State Examination (MMSE, the scores less than 24 was defined as cognitive impairment)[20],theinstrumentalactivitiesofdailyliving(using theLawton-BrodyInstrumentalADLscale,IADL)[21],andquality
oflife(usingEuropeanqualityoflife–fivedomains,EQ5D)[22] 2.2.3 Gaitspeedmeasurement
Atimed6-mwalkwasperformedforallparticipantsattheir usualwalkingspeedwithastaticstartthroughouta6-mdistance withoutdeceleration[23,24],andthetimeconsumedwastaken
by a fixed study nurse with a stop watch (HS-70W, Casio computerco.LTC,Tokyo,Japan).Thetestallowedthesubjectsto startwithacaneorawalkerasneeded.Threedifferentcut-offsfor slowergaitspeed(<0.5m/s[25],0.8m/s[11,12],and<1m/s [13,14]) were tested to evaluate the effect in improving fall preventionamongthestudysubjects
2.2.4 Definitionsoffalls
Inthisstudy,afallwasdefinedasanunintentionalchangein positionresultingincomingtorestonthegroundorotherlower levels [26] For all study subjects, the occurrence of falls was carefullyrecordedduringthe12-monthfollow-upperiod 2.3 Statisticalanalysis
Inthisstudy,continuousvariablesinthetextandtableswere expressedasmeanswithstandarddeviation,andcategoricaldata wereexpressed aspercentages Comparisons between dichoto-mousand ordinalvariables weredonebyusingtheChi2test or Fisher’sexact testwhen appropriate,andcomparisonsbetween continuousvariablesweredoneusingtheindependentStudent’s t-test or Mann-Whiney U test when appropriate Multivariate logisticregressionanalysiswasusedtodeterminetheindependent predictivefactorsforsubsequentfallsinthefollowing yearand the candidate predictors with a P value<0.2 in univariate analysis were selected to enter the regression model For the interaction of history of falls and gait speed, we combined the history of falls and slower gait speeds using different definitions, i.e.<0.5m/s,0.8m/s or<1m/s The predictive effect was also analyzing by multivariate stepwise logistic regressionanalysisafteradjustingconfounders
3 Results 3.1 Demographiccharacteristicsandfunctionalstatus Overall, 230 subjects (mean age: 85.54.0years, range: 80–101years, all males) participated in this study and 27.4% of them(63/230)reportedfallsinthepreviousyear.Amongthem,26.1% (60/230)reportedfalleventsduring thefollow-upperiod.Table1 summarizedthedemographiccharacteristicsandfunctionalstatusof thestudyparticipants.Approximately40%ofthestudysubjectshad sleepingproblems,urinaryincontinence,cognitiveimpairment,or depressivesymptoms Thosewhodevelopedfallsinthefollow-up periodhadsignificantlyslowergaitspeedthanthosewhodeveloped
nofall event(0.670.33m/svs0.780.32m/s,P=0.021),lower scores inEQ5D(61.122.9vs68.115.7,P=0.039),andhigher prevalence of urinary incontinence (46.7% vs 27.6%, P=0.007), presence of pain (61.7% vs 41.2%, P=0.001), and depressive symptoms(43.3%vs24.7%,P=0.007)
Trang 33.2 Independentriskfactorsforfalls
All candidate predictors with the P value<0.2 in the
univariate analysis were entered into the logistic regression
analysis, including age, polypharmacy, hearing impairment,
urinaryincontinence,historyoffalls,EQ5Dscores,presenceof
pain, IADL, depressive symptoms, and gait speed Results
showed that history of falls in the previous year (odds ratio
[OR]: 4.255, 95% confidence interval [CI]: 2.089–8.667;
P<0.001), presence of pain (OR: 2.674, 95%CI: 1.332–5.369;
P=0.006) and older age (OR: 1.128, 95% CI 1.031–1.234;
P=0.008)wereall independent riskfactorsforfalls (Table 2)
Although the gait speed per se was not an independent
predictive factor for falls, but the slower gait speed (defined
by<0.5m/s) was independently associated with falls in the
subsequentyear(OR:2.964,95%CI:1.394–6.300;P=0.005)
3.3 Synergiceffectofhistoryoffallsandgaitspeed
Adjustedforage,polypharmacy,hearingimpairment,urinary
incontinence,EQ5Dscores,presenceofpain,IADL,anddepressive
symptoms,weevaluatedthepotentiallysynergiceffectofhistory
offallsandslowergaitspeedinfallprediction(Table3 Aslower
gaitspeeddidnotsignificantlyaddpredictivevalueonhistoryof
falls if it was defined as0.8m/s (OR: 4.044, 95% CI: 1.504–
10.869,P=0.006forsubjectswithhistoryoffallsandslowergait
speed;OR:4.290,95%CI:1.379–13.346,P=0.012forsubjectswith
historyoffallsandfastergaitspeed).Moreover,ifslowergaitspeed
wasdefinedas<0.5m/s,astrong synergiceffectwasidentified
(OR:3.308,95%CI:1.280–8.549,P=0.014forsubjectswithslow gait speed without history of falls; OR: 4.423, 95% CI: 1.857– 10.535;P=0.001forsubjectswithhistoryoffallsandnoslowgait speed;OR:10.920,95%CI:3.423–34.839,P<0.001forsubjects with history of falls and slow gait speed) In addition, among subjectswithhistoryofpreviousfalls,afastergaitspeed(1m/s) wasasignificantprotectivefactorforsubsequentfalls
4 Discussion 4.1 Riskforfallsamongolderpeople This prospective cohort studyevaluated theeffectiveness of addinggaitspeedtohistoryofpreviousfallsinpredictingfallsin thesubsequentyearamongmalepeopleaged80yearsandolderin Taiwan Results of this study provided risk stratification for octogenarianswiththesamehistory offallsinsubsequentfalls, which highlighted the benefits of this combined approach to improveidentifyingpeoplewithhigherriskoffalls.Inthisstudy, 26.1%ofallstudysubjectsfellatleastonceinthefollow-upperiod Olderage,historyoffallsinthepreviousyear,andpresenceofpain wereallindependentriskfactorsforfallsinthisstudy,whichwere similar to previous studies However, subjects with previous historyoffallplusslowergaitspeed(definedas<0.5m/s)wereat
averyhighriskoffalls.Onthecontrary,subjectswiththeirgait speed1m/swerenotatahigherriskoffallseveniftheyhada previoushistoryoffalls.ThesefindingsstrengthenedtheAGS-BGS guidelinesinthefallpreventionprograms,andwereasimpleand efficientapproachtostratifyriskoffallsforpeopleaged80years andolder
Table 1
Comparisons of baseline characteristics among subjects with or without falls during the 12-month follow-up.
Variables % or mean SD (n) % or mean SD (n) % or mean SD (n)
Age 85.5 4.0 (n = 230) 86.1 4.2 (n = 60) 85.3 3.9 (n = 170) 0.110 Current smoker (yes) 43/230 (18.7%) 10/60 (16.7%) 33/170 (19.4%) 0.639 Current drinker (yes) 65/230 (28.3%) 15/60 (25.0%) 50/170 (29.4%) 0.514 Sleep problems (yes) 88/230 (38.3%) 26/60 (43.3%) 62/170 (36.5%) 0.347 Urine incontinence (yes) 75/230 (32.6%) 28/60 (46.7%) 47/170 (27.6%) 0.007
Hx of fall in past 1 year 63/230 (27.4%) 29/60 (48.3%) 34/170 (20.0%) < 0.001 Presence of pain (yes) 107/230 (46.5%) 37/60 (61.7%) 70/170 (41.2%) 0.001 BMI 24.1 3.5 (n = 169) 24.2 3.9 (n = 37) 24.1 3.4 (n = 132) 0.850 CCI 1.01 1.48 (n = 230) 1.08 1.52 (n = 60) 0.99 1.46 (n = 170) 0.669 Polypharmacy (yes) 146/230 (63.5%) 45/60 (75.0%) 101/170 (59.4%) 0.031 Visual impairment (yes) 183/230 (79.6%) 48/60 (80.0%) 135/170 (79.4%) 0.923 Hearing impairment (yes) 149/230 (64.8%) 44/60 (73.3%) 105/170 (61.8%) 0.107 Baseline IADL 6.9 1.3 (n = 230) 6.6 1.6 (n = 60) 7.1 1.1 (n = 170) 0.038 EQ5D VAS Scores 66.2 18.1 (n = 203) 61.1 22.9 (n = 54) 68.1 15.7 (n = 149) 0.039 Cognitive impairment (yes) 88/230 (38.3%) 24/60 (40.0%) 64/170 (37.6%) 0.747 Depressive symptoms (yes) 68/230 (29.6%) 26/60 (43.3%) 42/170 (24.7%) 0.007 Risk of malnutrition (yes) 51/230 (22.2%) 12/60 (20.0%) 39/170 (22.9%) 0.637 Gait speed (m/s) 0.75 0.32 (n = 230) 0.67 0.33 (n = 60) 0.78 0.32 (n = 170) 0.021 BMI: Body mass index; CCI: Charson Comorbisity Index.
Table 2
Independent risk factors for falls among men aged 80 years and older during 12-month follow-up.
Independent Variables a
Unadjusted OR 95% CI P value Adjusted OR 95% CI P value History of falls in past 1 year 3.742 1.992–7.030 < 0.001 4.255 2.089–8.667 < 0.001
Presence of pain (yes) 2.298 1.257–4.202 0.007 2.674 1.332–5.369 0.006
Gait speed with cut-off point < 0.5 m/s 2.987 1.577–5.656 0.001 2.964 1.394–6.300 0.005
a
Covariates adjusting for age, polypharmacy, hearing impairment, urine incontinence, history of falling in past 1 year, EQ5D VAS scores, with symptoms of pain, IADL, and depressive symptoms based on GDS-15, and gait speed (m/s).
Trang 44.2 Gaitspeedandfalls
Slower gaitspeedhasbeenrecognizedtobeassociatedwith
riskoffallsfortheelderly,whichwasasimpleandeffectivetestin
clinicalpractice[8,23,27,28].TheE´pidemiologiedel’Osteoporose
study, EPIDOS, surveyed 7575 community-dwelling French
womenaged75yearsandoldershowingthatthelowestquartile
ofgaitspeedhada1.4higherrisk(95%CI1.1–1.6)offemoralneck
fracturethanthehighestquartileduringamean1.9years
follow-up[27].Besides,Chuetal.enrolled1517elderlyHongKongpeople
anddisclosedthatthefastergaitspeedwasasignificantprotective
factor against falls [8] Despite all the supporting evidences,
the cut-off of gait speed in predicting falls remained unclear,
especiallyforthosewhoaged80yearsandolder.Montero-Odasso
et al reported that the gait speed<0.7m/s was significantly
predictiveforfallsinthecomingtwoyears(RR=5.4,95%CI:2.0–
4.3)byastudysamplewithsimilaragetoours(102participants
aged75yearsandolder)[28].Comparedtothepreviousstudies,
CGA wasperformed for allstudy subjects toidentify potential
confoundersinpredictingsubsequentfalls,includingvisualand
hearing impairment, malnutrition, presence of pain, and
co-morbidities In 2012,Taekema et al found that thegait speed
of<0.46m/sinmenwasassociatedwithahigherriskofmortality
during 12-year follow-up [14] In this study, a gait speed
of<0.5m/s was a stronger predictive factor for falls than the
slowergaitspeedusingthecut-offof0.8or1m/s
4.3 Combinedapproachofhistoryoffallsandgaitspeed
The ‘‘historyoffall’’wasastrongriskfactorforsubsequent
fallstraditionally,butphysicalconditions ofolderpeoplewith
thesamehistoryoffallsmaydifferextensively.Rekeneireetal
reported thatfallers mighteventuallyhavecertainsubclinical
deficits that were overlooked by clinicians [29] Moreover,
analysis of gait characteristics among older people with a
previous history of falls showed that their gait speed varied
extensively from 0.18 to 1.07m/s [30],which clearly
demon-strated the great heterogeneity of these people that were
classified as at the same risk for falls due to the history of
previous falls Therefore, adding the dynamic gait speed
measurement to the static history of falls improved the
effectivenessin riskstratificationfor fallpreventionprograms
Inparticular,historyoffallsisnotamodifiableriskfactor,buta
slowergaitspeedmaybeimprovedthroughcertainintervention
programs In this study, the history of fall remained to be a
strong independently riskfactor for falls no matter slow gait
speed was defined as<0.5 or0.8m/s It has been reported
thatadequateresistancetrainingwouldimprovethegaitspeed,
evenamong people aged90years and older [31], and the
6-month multidimensional training program may sustain the
beneficialeffectsupontheincreasinggaitspeed,aswellasthe
physiological, functional and psychological conditions of old womenwitharecenthistoryoffalls[32].Resultsofthisstudy showedthatolderpeoplewithhistoryoffallseventuallywereat
nohigherriskforfallswhentheirgaitspeedexceeded1.0m/s,
so they may not be the most prioritized population for fall prevention programs even though they reported a previous historyoffalls.Inparticular,thosewhohadaprevioushistoryof falls and the gait speed of<0.5m/s, a stronger intervention program should be introduced to prevent subsequent falls becausetheywereatveryhighriskoffalls
4.4 Limitations Despitealltheresearcheffortswentintothisstudy,therewere stillseverallimitations.First,thestudysamplewashomogenous
intheirdemographiccharacteristicsthattheywereallmales,and all veterans were living in the same retirement community However, we believe results of this study were still of great implicationstoeffectivelyconductfallpreventionprogramsin thecommunities.Second, amongalleligiblestudysubjects,27 refused theevaluationofEQ5D, and61of them refusedbeing measured for their BMI These conditions may lessened the statisticpower,however,resultsofthisstudystillclearlyshowed thebenefitsofaddinggaitspeedmeasurementstohistoryoffalls
inpredictingfalls.Third,a self-reportbiasoffallepisodesmay existin thisstudybecauseolder veteransmaybereluctant to reportfallsduetotheirself-esteem
4.5 Conclusions Amongmenaged80yearsandolderlivingintheretirement communities,thehistoryofpreviousfallsalonewasnotasingle best risk factor for subsequent falls A gait speed1m/s was protective against subsequent falls in spite of the presence of historyofpreviousfalls.Ontheotherhand,forsubjectswiththe history of previous falls and a slow gait speed (<0.5m/s), a strongerinterventionprogram shouldbeintroducedduetothe disproportionatelyhighriskoffallinthefollowingyear Disclosureofinterest
The authors declare that they have no conflicts of interest concerningthisarticle
Acknowledgement ThestudywassupportedbytheVeteranAffairsCouncil,R.O.C (Grant number: VAC101-C1 and VAC102-C1) and all authors declarenoconflictsofinterest.Thestudygroupthanksallstaffin the Gangshan Veterans Home for their valuable assistance in obtainingtheinformation
Table 3
Synergistic effect of history of falls and slow gait speed in predicting subsequent falls.
Cut-off point of slower gait speed < 1 m/s
Cut-off point of slower gait speed 0.8 m/s
Cut-off point of slower gait speed < 0.5 m/s Dependent variables a Adjusted OR 95% CI P value Adjusted OR 95% CI P value Adjusted OR 95% CI P value History of falls (–) and slow gait speed (–) Reference – – Reference – – Reference – – History of falls (–) and slow gait speed (+) – – – – – – 3.308 1.280–8.549 0.014 History of falls (+) and slow gait speed (–) – – – 4.290 1.379–13.346 0.012 4.423 1.857–10.535 0.001 History of falls (+) and slow gait speed (+) 3.052 1.054–8.840 0.040 4.044 1.504–10.869 0.006 10.920 3.423–34.839 < 0.001
a
Covariates adjusting for age, polypharmacy, hearing impairment, urine incontinence, EQ5D VAS scores, with symptoms of pain, IADL, and depressive symptoms based on GDS-15.
Trang 5Institu-tionalReviewBoardofKaohsiungVeteransGeneralHospital,Taiwan
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