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Poor balance and lower gray matter volume predict falls in older adults with mild cognitive impairment Makizako, Hyuma; Shimada, Hiroyuki; Doi, Takehiko; Park, Hyuntae; Yoshida, Daisuke; Uemura, Kazuki; Tsutsumimoto, Kota; Liu-Ambrose, Teresa; Suzuki, Takao Aug 5, 2013

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RESEARCH ARTICLE Open AccessPoor balance and lower gray matter volumepredict falls in older adults with mild cognitiveimpairmentHyuma Makizako1,2*†, Hiroyuki Shimada1†, Takehiko Doi1,2†, Hyuntae Park3, Daisuke Yoshida1, Kazuki Uemura1,2,Kota Tsutsumimoto1, Teresa Liu-Ambrose4,5,6 and Takao Suzuki7AbstractBackground: The risk of falling is associated with cognitive dysfunction. Older adults with mild cognitiveimpairment (MCI) exhibit an accelerated reduction of brain volume, and face an increased risk of falling. The currentstudy examined the relationship between baseline physical performance, baseline gray matter volume and fallsduring a 12-month follow-up period among community-dwelling older adults with MCI.Methods: Forty-two older adults with MCI (75.6 years, 43% women) underwent structural magnetic resonanceimaging and baseline physical performance assessment, including knee-extension strength, one-legged standingtime, and walking speed with normal pace. ‘Fallers’ were defined as people who had one or more falls during the12-month follow-up period.Results: Of the 42 participants, 26.2% (n = 11) experienced at least one fall during the 12-month follow-up period.Fallers exhibited slower walking speed and shorter one-legged standing time compared with non-fallers (both p< .01). One-legged standing time (sec) (standardized odds ratio [95% confidence interval]: 0.89 [0.81, 0.98], p = .02)was associated with a significantly lower rate of falls during the 12-month follow-up after adjusting for age, sex,body mass index, and history of falling in the past year at baseline. Voxel-based morphometry was used to examinedifferences in baseline gray matter volume between fallers and non-fallers, revealing that fallers exhibited asignificantly greater reduction in the bilateral middle frontal gyrus and superior frontal gyrus.Conclusions: Poor balance predicts falls over 12 months, and baseline lower gray matter densities in the middlefrontal gyrus and superior frontal gyrus were associated with falls in older adults with MCI. Maintaining physicalfunction, especially balance, and brain structural changes through many sorts of prevention strategies in the earlystage of cognitive decline may contribute to decreasing the risk of falls in older adults with MCI.BackgroundFalls and fall-related injuries are a common healthcareproblem, and represent important causes of morbidityand mortality in older populations. One-third of allcommunity-dwelling adults age 65 years and older ex-perience at least one fall annually [1]. Many distinctcauses for falls in older people have been reported by alarge number of studies [1-4]. Impaired physical func-tion, particularly muscle weakness and problems withgait and balance, are the most important contributors tothe risk of falling [5]. The ageing of the worldwide popu-lation in recent decades has resulted in an increasingnumber of older adults with cognitive decline [6], andcognitive impairment has also been found to increasethe risk of falling [7-10]. As such, correctly identifyingthe risk factors for falling among older adults with cog-nitive impairment is an important research question.In addition, people with cognitive impairment recoverless well after a fall than those without cognitiveimpairment [11]. Therefore, the falling may have nega-tive impact on health in older people with cognitive* Correspondence: makizako@ncgg.go.jp†Equal contributors1Section for Health Promotion, Department for Research and Developmentto Support Independent Life of Elderly, Center for Gerontology and SocialScience, National Center for Geriatrics and Gerontology, 35 Gengo, Morioka-machi, Obu, Aichi 4748511, Japan2Japan Society for the Promotion of Science, Tokyo, JapanFull list of author information is available at the end of the article© 2013 Makizako et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the CreativeCommons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, andreproduction in any medium, provided the original work is properly cited.Makizako et al. BMC Neurology 2013, 13:102http://www.biomedcentral.com/1471-2377/13/102impairment compare with those without cognitive im-pairment. In older individuals with mild cognitive im-pairment (MCI) in particular, consideration of a broadrange of causes of falls could play a role in reducingthe fall risk and providing strategies to prevent fallsamong the high-risk population.Several studies have examined falling in older adultswith dementia, such as Alzheimer’s disease [11,12].However, little research has focused on falling amongpeople with MCI, even though mild declines in cognitivefunction have been reported to be an important factorassociated with falling [13]. Liu-Ambrose et al. demon-strated that older community-dwelling people with MCIbut not dementia were at greater risk of falling thanthose without MCI [14]. Brain structural changes repre-sent one of the key clinical features associated withMCI, including gray matter volume loss [15] and whitematter hyperintensities (WMH) [16]. A recent prospect-ive study indicated that greater WMH burden predictsfalls over 12 months in non-demented community-dwelling older adults [17].Although prospective evidence suggests that WMHare an important risk factor for falls in community-based older populations [17,18], it remains unclearwhether gray matter volume predicts falls and which re-gions are related to a greater risk of falls in older adultswith MCI. Structural changes in the brain have beenlinked to motor performance deficits [19]. WMH wasreported to exhibit a negative correlation with posturalstability involved balance, stepping and gait [20], whilereduced gray matter density is associated with impairedgait performance [21-23] and postural instability [24].Kido et al. [24] suggested that postural instability is asso-ciated with gray matter volume loss, and is related topathological cognitive decline, such as MCI and AD.Lower gray matter volume has been found to be relatednot only to cognitive decline, but also to decreased phys-ical function. Thus, gray matter volume loss may in-crease the risk of falls in older adults with MCI. Inparticular, a smaller volume of the prefrontal area mightbe associated with poor physical performance [22,23],such as slower gait and poor balance, but no evidencehas been reported that smaller brain volume of specificregions is related to the occurrence of subsequent fallsin older adults with MCI. In the current study, wesought to examine whether physical performance andgray matter volume were related to falls during a 12-month follow-up period among community-dwellingolder adults with MCI.MethodsParticipantsThe sample for this longitudinal study consisted of42 community-dwelling older adults with MCI whocompleted a randomized controlled trial (RCT) (trialregistration: UMIN-CTR UMIN000003662) evaluatingthe effects of multicomponent exercise on cognitivefunction. The Ethics Committee of the National Centerfor Geriatrics and Gerontology approved the studyprotocol. The study design and the primary results ofthe RCT have been described previously [25]. All partici-pants gave written informed consent prior to taking partin the study. Briefly, participants enrolled in the RCTwere: aged 65 years and over, community dwelling, anddid not suffer from dementia. All participants met thePetersen criteria for MCI [26]. Participants who had aClinical Dementia Rating (CDR) = 0, or a CDR of 1–3, ahistory of neurological, psychiatric, or cardiac disordersor other severe health issues, use of donepezil, impair-ment in basic activities of daily living (ADL), and partici-pation in other research projects were excluded from theRCT study. A total of 100 participants took part in theRCT and completed neuropsychological assessments in-cluding language, memory, attention, and executivefunction tests. All subjects in this study had objectiveimpairments at least 1.5 standard deviations below theage-adjusted mean for at least one of the neuropsycho-logical tests. The participants were classified to anamnestic MCI (aMCI) group (n = 50) with neuroimagingmeasures, and other MCI group (n = 50) before therandomization. The subjects in each group were thenrandomly assigned to either a multicomponent exercisegroup or an education control group using a ratio of 1:1.The sample for this longitudinal study involved partici-pants in a control group. Of the 50 participants in thecontrol group, 42 completed fall follow-up assessmentsduring the 12-month follow-up period.Physical performance measuresAt baseline, all participants underwent an extensive as-sessment of measures by licensed and well-trained phys-ical therapists.Knee-extension strengthIsometric knee extension strength was tested twice usinga dynamometer (Model MDKKS, Molten Co Ltd,Hiroshima, Japan) from the dominant leg (self-reportedside they would use to kick a ball as far as possible).Knee extension was measured while the participant wassitting on a chair with a backrest and the knee flexed to90°. A testing pad was attached to the front lower leg ofthe participant and strapped to the leg of the chair.The participant was instructed to push the padwith maximal strength. Licensed and well-trained phys-ical therapists confirmed compensatory movement andassessed muscle strength. Participants practiced severaltimes before data collection. Two trials were conducted,Makizako et al. BMC Neurology 2013, 13:102 Page 2 of 8http://www.biomedcentral.com/1471-2377/13/102and the maximal isometric strength was determined asthe peak torque (Nm) in the data analysis.One-legged standing (OLS) testThe OLS test is a commonly used balance assessment ofpostural stability. For the OLS test, we asked participantsto look straight ahead at a dot 50 cm in front of them,then to stand on their preferred leg with their eyes openand hands down alongside the trunk. OLS balance wasmeasured as the length of time (0–60 s) participantswere able to stand on one leg. The better of the two tri-als was used for statistical analysis.Walking speedWS was measured using a 5-m walking test. The partici-pants’ usual WS was measured over an 11-m straightand level path. The time taken (in seconds) to pass the5-m mark on the path was used as the participant’sscore. A 3-m approach was allowed before the startingmarker, and an additional 3 m of space was providedafter the end marker of the 5-m path to ensure a usualwalking pace throughout the task. Participants wereinstructed to walk the 11-m path at their usual walkingpace. The time to complete the 5-m walking test wasmeasured once and was used to calculate walking speed(m/min).Falls follow-upFall frequency during the 12-month follow-up periodwas measured with two face-to-face interviews at6 months and 12 months after baseline measurements.A fall was defined as “an unexpected event in which theperson comes to rest on the ground, floor, or lowerlevel” [27]. In this study, ‘fallers’ were defined as peoplewho had at least one fall during the 12-month follow-upperiod [28].Magnetic resonance imaging (MRI) procedureMagnetic resonance imaging (MRI) was performedusing a 1.5-T system (Magnetom Avanto, Siemens,Germany). Three-dimensional volumetric acquisition ofa T1-weighted gradient-echo sequence was then usedto produce a gapless series of thin sagittal sectionsusing a magnetization preparation rapid-acquisitiongradient-echo sequence (repetition time, 1,700 ms;echo time, 4.0 ms; flip angle 15°, acquisition matrix256 × 256, 1.3-mm slice thickness). Tissue segmenta-tion, regulation, registration, and normalization wereconducted in the VBM8 toolbox (http://dbm.neuro.uni-jena.de/vbm/), which is incorporated in the SPM8 soft-ware (http://www.fil.ion.ucl.ac.uk/spm/), running onMATLAB R2010a (Mathworks). Diffeomorphic Ana-tomical Registration using Exponentiated Lie algebra(DARTEL) [29] was conducted for the image analysis.The normalized images were transformed into MontrealNeurological Institute space. The gray matter images werethen smoothened using a Gaussian kernel of 12-mm full-width at half-maximum.Statistical analysisFor baseline comparisons, basic characteristics andphysical performance tests including knee-extensionstrength, OLS, and WS were compared between fallersand non-fallers using t-tests. Chi-square tests for differ-ences in proportions were used to compare differencesin sex and history of falling in the past year at baselinebetween the faller and non-faller groups. To describevariations in different physical performance factors re-lated to falls, multivariate logistic regression analyseswere performed to reveal the physical performance fac-tors independently related to falls during the 12-monthfollow-up after adjusting for age, sex, body mass index(kg/m2), and history of falling in the past year at base-line. We calculated the odds ratios (OR) with 95% confi-dence intervals (CI). These statistical analyses werecalculated using SPSS for Windows version 19.0 (SPSSInc., Chicago, IL).In the voxel-based morphometry (VBM) analysis, datapreprocessing and analysis was performed with theVBM8 toolbox, which is incorporated in the SPM8 soft-ware. VBM [30] was used to examine differences inbaseline gray matter volume between fallers and non-fallers. We used unpaired t-tests in SPM8 to identify thelocations of smaller gray matter volume in fallers com-pared to non-fallers during the 12-month follow-upperiod using MRI data at baseline. Age and sex were in-cluded as covariates. The statistical threshold selectedfor these analyses was P < .001 (uncorrected), with an ex-tent threshold of 100 voxels.ResultsThe characteristics and physical performance tests atbaseline are presented in Table 1. Over the 12-monthfollow-up period, 11 of the 42 participants (26.2%) expe-rienced at least one fall. Fallers exhibited poorer one-legged standing time (p < .01) and slower walking speed(p < .01) compared with non-fallers. In addition, thefaller group had a significantly higher rate of fall historyat baseline compared with the non-faller group (p < .01).In the multivariate logistic regression, OLS time (sec)(OR [95% CI]: 0.89 [0.81, 0.98], p = .02) was associatedwith a significantly lower rate of falls during the 12-month follow-up after adjusting for age, sex, body massindex, and history of falling in the past year at baseline.There was no statistical evidence of associations betweenfalls and knee-extension strength (Nm) (1.02 [0.96, 1.08],p = .59) and walking speed (m/min) (0.91 [0.81, 1.03],p = .13) (Table 2).Makizako et al. BMC Neurology 2013, 13:102 Page 3 of 8http://www.biomedcentral.com/1471-2377/13/102The gray matter density profiles used for examiningdifferences between fallers and non-fallers at baselineare shown in Figure 1. VBM analysis revealed that fallersexhibited lower gray matter density compared with non-fallers in the bilateral middle frontal gyrus and superiorfrontal gyrus (Table 3). These regions correspond to thepremotor cortex and supplementary motor area.DiscussionThe present study examined whether baseline physicalperformance and gray matter volume are related to fallsduring a 12-month follow-up period in community-dwelling older adults with MCI. Our results indicatedthat older adults with MCI exhibiting poor balance hada greater risk of falls during the 12-month follow-upperiod, while adjusting for age, sex, body mass index,and history of falling at baseline. In addition, baselinelower gray matter volume in the middle frontal gyrusand superior frontal gyrus was associated with the oc-currence of subsequent falls. To our knowledge, this isthe first study to examine the association betweenlower gray matter density and risk of falls in olderadults with MCI.Problems with gait and balance have been reported tohave the strongest association with falling [2,31]. Slowerwalking speed has been found to be an independent pre-dictor of falling [32,33]. Poor balance represented by in-creased postural sway and gait asymmetry has beenreported to approximately triple the risk of falling [2]. Aprevious systematic review and meta-analysis provided asummary estimate for falls due to balance impairment ata relative risk of 1.42 [34]. Therefore, an assessment ofbalance and gait for older adults, particularly those with-out a history of falling, has been recommended [35].Moreover, cognitive impairment has been associatedwith the risk of falls as well as deficits of physical func-tion [2]. A recent systematic review and meta-analysisconfirmed that cognitive deficits detected in clinical as-sessment are associated with an increased fall risk incommunity and institution-dwelling older adults [36]. Anumber of studies have examined the risk of falls inolder adults with dementia [37]. However, little researchhas focused on individuals with MCI. MCI is increas-ingly recognized as a substantial clinical problem inolder populations [38], so it is important to determinerisk factors for falling among older individuals withMCI, and to develop effective fall-prevention strategies.A previous study showed that older women with MCIdemonstrated a greater number of risk factors for fallingcompared with older women without MCI [14]. The re-sults of the present study indicate that poor balanceassessed by one-legged standing time predicts fallsin people with MCI prospectively over 12 months.Although fallers exhibited slower walking speed com-pared with non-fallers, walking speed was not associatedwith the occurrence of subsequent falls after adjustingfor age, sex, body mass index, and history of falling atbaseline. There was no difference in the extensionstrength between fallers and non-fallers. The results ofthis study indicate that poor balance is the importantfactor related to an increased risk of falling amongpeople with MCI. Muscle weakness and problems withmobility had been considered to be the important con-tributors to the risk of falling in older people [5], andthere are presumably some relationships. In study co-horts including older people with MCI and similar lowermuscle strength, like the present study, poor balancemay have a greater impact on increased risk of fallingTable 1 Comparison of characteristics and physical performance tests between non-fallers and fallers at baselineTotal (n = 42) Non-fallers (n = 31) Fallers (n = 11) P-valueAge, years 75.6 ± 6.3 75.2 ± 6.5 76.8 ± 5.9 0.462Female, n (%) 18 (42.9) 12 (38.7) 6 (54.4) 0.362History of falling in the past year, n (%) 13 (31.0) 6 (19.4) 7 (63.6) 0.006Knee-extension strength, Nm 60.5 ± 26.8 63.4 ± 23.3 52.3 ± 34.7 0.242One-legged standing time, sec 32.3 ± 24.2 38.9 ± 22.3 13.8 ± 19.7 0.002Walking speed, m/m 66.7 ± 12.6 70.0 ± 11.8 57.5 ± 10.4 0.004Mini-mental state examination, score 26.3 ± 2.7 26.6 ± 2.0 25.5 ± 3.9 0.112Table 2 Multivariate logistic regression summary for physical performance on falls (n = 42)Variables Odds ratio 95% confidence intervals p ValueKnee-extension strength, Nm 1.017 0.957-1.080 0.588One-legged standing time, sec 0.891 0.809-0.981 0.019Walking speed, m/m 0.911 0.806-1.029 0.133Notes: Age, sex, body mass index (kg/m2) and history of falling in the past year at baseline were included as covariates.Makizako et al. BMC Neurology 2013, 13:102 Page 4 of 8http://www.biomedcentral.com/1471-2377/13/102than walking performance. Certainly, poor balance couldbe one of the predictors of walking decline among olderpeople [39]. Balance ability may be an important dimen-sion of physical functioning to predict the occurrence ofsubsequent falls among older people with MCI, as wellas those with intact cognition. The present study has ad-vantages including the examination of occurrence ofsubsequent falls during a 12-month follow-up periodand neuroimaging assessments in older adults with MCI.However, our sample was not large, and selection biasmay affect the results of the relationships between phys-ical performance and occurrence of subsequent falls.Therefore, future studies with larger numbers of MCIsubjects and a longitudinal design are needed to add evi-dence to the present results.Unlike previous investigations, the current study in-cluded MRI scanning and a follow-up assessment of fallsin community-dwelling older adults with MCI. The re-sults provide the first evidence that lower gray mattervolume in the middle and superior frontal gyrus is re-lated to the occurrence of subsequent falls among olderadults with MCI. Age-related changes in the brain maycontribute to the subtle onset of motor disturbancesin older people. Previous brain-imaging studies of olderadults have reported that age-related changes in thebrain, such as lower global brain volume, WMH, andmicrobleeds, are associated with clinical measures ofpoor balance and slow gait [40-43]. The association be-tween MRI-detected lower brain volume and falls inolder adults with MCI has not been examined longitu-dinally. In the present study, fallers exhibited decreasedgray matter density compared with non-fallers in the bi-lateral middle frontal gyrus and superior frontal gyruscorresponding to premotor cortex and supplementarymotor area. These particular regions are likely to play animportant role in predicting fall-risk because the middlefrontal gyrus is involved in controlling behavior withspatial and sensory guidance.Growing evidence suggests that brain function is asso-ciated with physical function, as confirmed by neuroim-aging techniques. Structural changes of the brain inolder people are reported to be related to physical per-formance, such as gait dysfunction [44,45], posturalinstability [24], and lack of cardiorespiratory fitness [46].X = 29 Y = 8 Z = 51X = -29 Y = 9 Z = 42X = -17 Y = 12 Z = 46Right Middle Frontal GyrusLeft Middle Frontal GyrusLeft Superior Frontal GyrusFigure 1 Gray matter density in fallers versus non-fallers. Regions of gray matter reduction in fallers compared to non-fallers (p < 0.001,uncorrected). Fallers exhibited a greater reduction of gray matter loss in the bilateral middle frontal gyrus and superior frontal gyrus.Table 3 VBM results including age and sex as covariatesMNI coordinatesLocation Cluster size (K) Peak T Z score P (uncorrected) X Y ZRight middle frontal gyrus 594 4.87 4.27 < 0.001 29 8 51Left middle frontal gyrus 165 4.35 3.90 < 0.001 −29 9 42Left superior frontal gyrus 4.78 4.20 < 0.001 −17 12 46Note: VBM voxel-based morphometry.Makizako et al. BMC Neurology 2013, 13:102 Page 5 of 8http://www.biomedcentral.com/1471-2377/13/102Activation in the frontal cortex, including the premotorcortex and the supplementary motor areas, have beenreported to increase during human gait by studies usingnear-infrared spectroscopic imaging [47-50]. Previousstudies have reported that lower brain volume inthe prefrontal areas is associated with slower gait inhigh-functioning or cognitively normal older adults[23,40,51]. Other neuroimaging studies have indicatedthat gait requires complex visuo-sensorimotor coordin-ation, and is associated with activation of the medialfrontoparietal region, e.g. the primary sensory and motorareas, supplementary motor area, lateral premotor cor-tex, cingulate cortex, superior parietal lobule, precuneus,and the infratentorial region including the dorsal region[52-54]. The middle frontal gyrus is involved in motoroutput and the direct control of behavior, as well asplanning, spatial guidance, and sensory guidance ofmovement [55]. Lower gray matter volume in the pre-motor cortex and supplementary motor area may be riskfactors for falls in older adults. Falls often occur whenolder individuals attempt to avoid an obstacle in theirpath, requiring the control of behavior and the planningof movement under sensory guidance. The premotorcortex and supplementary motor area may play an im-portant role in preventing falls when spatial and sensoryguidance are required for movement.Several limitations of the current study should benoted. First, fall experience during the 12-month follow-up period were confirmed with two face-to-face inter-views at 6-months and 12-months after baseline, whileprevious studies have reported that monthly fall diariesand follow-up telephone calls provide more accuratemeasures of fall frequency [56,57]. Second, participantswho had at least one fall during the 12-month follow-upperiod were categorized as fallers in this study. A previ-ous study reported that single fallers are more similar tononfallers than to recurrent fallers on a range of med-ical, physical, and psychological risk factors [58]. Otherstudies defined fallers as people who had at least one in-jurious or two non-injurious falls [17,59]. In addition,our MRI scans were performed using a 1.5-T systemwith relatively low resolution. We performed the VBManalysis to identify the locations of group differences ingray matter volume. Therefore, we consider that our re-sults cannot provide evidence for whether the effects ofphysical performance are independent of the gray mattervolume or whether the latter confounds the associationbetween the former and the fall risk. Although it is un-clear whether lower gray matter volume is related topoor balance in older adults with MCI, the current studyrevealed that poor balance and lower gray matter vol-ume in the middle frontal gyrus and superior frontalgyrus were associated with falls. To clarify these points,we consider that future studies including larger numbersof subjects and countable data for structural changes inthe brain (e.g., described volumes in cubic millimeters)are needed.ConclusionsThe current findings indicate that poor balance predictsfalls over a 12-month period, and that lower gray mattervolume in the middle frontal gyrus and superior frontalgyrus was associated with falls in older adults with MCI.Maintaining physical function, especially balance, andbrain structural changes through many sorts of preven-tion strategies in the early stage of cognitive decline maycontribute to decreasing the risk of falls in older adultswith MCI.Competing interestsThe authors declare that they have no competing interests.Authors’ contributionsHM has made substantial contributions to conception and design, subjectrecruitment, analysis and interpretation of data, and writing the manuscript.HS has made substantial contributions to conception and design, subjectrecruitment, interpretation of data, and writing the manuscript. TD has madesubstantial contributions to subject recruitment, acquisition of data,interpretation of data, and manuscript preparation. HP has made substantialcontributions to conception and design, interpretation of data, and writingthe manuscript. DY contributed subject recruitment and manuscriptpreparation. KU and KT contributed subject recruitment and acquisition ofdata. TLA has been involved in drafting the manuscript or revising it criticallyfor important intellectual content. TS has made substantial contributions toconception and design and writing the manuscript. All authors read andapproved the final manuscript.AcknowledgementsThis study was supported in part by a grant from the Japanese Ministry ofHealth, Labour and Welfare (Project for optimizing long-term care, B-3) and aGrant-in-Aid for JSPS Fellows (23–9862) from the Japan Society for thePromotion of Science.Author details1Section for Health Promotion, Department for Research and Developmentto Support Independent Life of Elderly, Center for Gerontology and SocialScience, National Center for Geriatrics and Gerontology, 35 Gengo, Morioka-machi, Obu, Aichi 4748511, Japan. 2Japan Society for the Promotion ofScience, Tokyo, Japan. 3Section for Physical Functioning Activation,Department of Functioning Activation, Center for Gerontology and SocialScience, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan.4Aging, Mobility, and Cognitive Neuroscience Laboratory, Department ofPhysical Therapy, University of British Columbia, Vancouver, BC, Canada.5Brain Research Centre, University of British Columbia, Vancouver, BC,Canada. 6Centre for Hip Health and Mobility, Vancouver Coastal HealthResearch Institute, University of British Columbia, Vancouver, BC, Canada.7Research Institute, National Center for Geriatrics and Gerontology, Obu,Aichi, Japan.Received: 6 November 2012 Accepted: 2 August 2013Published: 5 August 2013References1. 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J Am Geriatr Soc 2010, 58(9):1679–1685.doi:10.1186/1471-2377-13-102Cite this article as: Makizako et al.: Poor balance and lower gray mattervolume predict falls in older adults with mild cognitive impairment.BMC Neurology 2013 13:102.Submit your next manuscript to BioMed Centraland take full advantage of: • Convenient online submission• Thorough peer review• No space constraints or color figure charges• Immediate publication on acceptance• Inclusion in PubMed, CAS, Scopus and Google Scholar• Research which is freely available for redistributionSubmit your manuscript at www.biomedcentral.com/submitMakizako et al. BMC Neurology 2013, 13:102 Page 8 of 8http://www.biomedcentral.com/1471-2377/13/102


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