Examining the Effect of the Relationship Between Falls and Mild Cognitive Impairment on Mobility and Executive Functions in Community‐Dwelling Older Adults

To the Editor: Cognitive impairment and falls are geriatric "giants" that significantly increase morbidity and mortality in older adults. Even mild cognitive impairment (MCI) is a significant risk factor for falls.1 Clinical gait abnormalities including slow gait and falls are early biomarkers of cognitive impairment,2 suggesting that impaired cognitive function and mobility share common underlying pathophysiology. Despite the strong interest in the interplay between impaired cognitive function and mobility, few studies have investigated whether their co-manifestation results in a broader and greater degree of deficits, potentially because of greater burden of pathology, than single-domain (cognitive or mobility) impairment. Understanding the specific deficits may facilitate the development of effective screening and prevention strategies. Therefore, the independent and synergistic effects of MCI status (defined as a Montreal Cognitive Assessment (MoCA) score <26/303) and fall status (faller (≥2 falls), nonfaller (≤1 fall)) on measures of cognitive function and mobility were examined over a 12-month period. For cognitive function, executive functions were focused on because they are highly associated with impaired mobility, including falls. This was a 12-month prospective study (baseline and 12-month visits) with 149 women and men, aged 70 to 80 years with a score of 24 or greater on the Mini-Mental State Examination4 living independently in their own homes. Ethics approval was obtained from the Vancouver Coastal Research Health Institute and University of British Columbia clinical research ethics board. All participants provided informed written consent. Selective attention and conflict resolution were assessed using the Stroop Test,5 set shifting was assessed using the Trail-Making Tests (TMT) Parts A and B,6 the Verbal Digits Tests Forward and Backward were used to assess working memory.7 Lower scores indicate better set shifting performance and working memory. Mobility and balance were assessed using the Short Physical Performance Battery (SPPB)8 and the Timed-Up-and-Go Test (TUG).9 For the SPPB, each component is rated out of 4 points, for a maximum of 12 points; a score less than 9/12 predicts subsequent disability. A TUG performance time of 13.5 seconds of greater correctly classified persons as fallers in 90% of cases. Physiological falls risk was assessed using the short form of the Physiological Profile Assessment (PPA), a valid and reliable measure of falls risk.10 The higher the PPA z-score, the greater the risk. Participants were divided into the following four groups: no MCI (MoCA score ≥26 (range 0–30 points)) and non-faller (≤1 displacement falls (with or without syncope) in the previous 12 months; reference group), MCI (MoCA score <26) and nonfaller, no MCI and faller (≥2 minimal displacement nonsyncopal falls in the previous 12 months), and MCI and faller. Using SPSS 22.0 (SPSS, Inc., Chicago, IL), the primary analyses consisted of linear mixed models in which time (baseline vs follow-up) was a within-subject repeated measure, and group membership was a between-subjects fixed effect. An unstructured covariance matrix provided the best model fit (based on the Bayesian Information Criterion), and denominator degrees of freedom were calculated from the Satterthwaite approximation. Separate models were fitted for the following dependent variables: Stroop, TMT, Verbal Digit Span, SPPB, TUG, and PPA. Models were adjusted for (main effect and interaction with time) age, sex, instrumental activities of daily living, and Activities-Specific Balance Confidence scale. Of the 149 participants (mean age 75 ± 3), 81 were nonfallers, 68 were fallers, 58 had no MCI, and 91 had MCI. At baseline, the following ranges of scores were observed for the outcome variables: Stroop Test (12–152 seconds), TMT (−1 to 301 seconds), Verbal Digits Test (−3 to 9), SPPB (5–12), TUG (5–24 seconds), and PPA (−1.3 to 4.7). Figure 1 details results from six adjusted linear mixed models. There was a trend toward nonfallers with MCI showing greater decline over time than nonfallers without MCI (P = .06, Cohen D = 0.51). Including covariates nullified this trend. Nonfallers with MCI had significant improvements from baseline to follow-up. No group differed in the amount of change over time. This pattern of results held in the partially and fully adjusted models. No group showed significant increases or decreases in performance over time in the partially or fully adjusted models. Fallers with MCI had greater improvements in SPPB scores over time than nonfallers without MCI (Cohen D = 0.66). All results were nonsignificant in the fully adjusted model. Nonfallers without MCI made greater improvements than fallers with MCI in the adjusted model (Cohen D = 0.50). There was a trend toward greater improvements in the reference group than in fallers without MCI (P = .06, Cohen D = 0.48). There was no longitudinal within- or between-group difference in change in falls risk in the unadjusted, partially adjusted, or fully adjusted models. This study highlights that the combination of MCI and a history of falls may be a significant predictor of future deterioration in mobility. MCI alone is a more important predictor of concurrent executive deficits than falling. Future research should further explore the unique and synergistic effects of falls and MCI as an "early" indicator of future decline in mobility and executive function to accurately customize future intervention and prevention strategies for older adults. Conflict of Interest: None. Canadian Institutes of Health Research Grant MOB-93373 to Teresa Liu-Ambrose. Teresa Liu-Ambrose is a Canada Research Chair in Physical Activity, Mobility, and Cognitive Neuroscience, a Michael Smith Foundation for Health Research (MSFHR) Scholar, a Canadian Institutes of Health Research (CIHR) New Investigator, and a Heart and Stroke Foundation of Canada's Henry J.M. Barnett Scholarship recipient. Jennifer Davis and John Best are CIHR and MSFHR postdoctoral fellows. Lindsay Nagamatsu is a CIHR postdoctoral fellow. Elizabeth Dao is a CIHR doctoral trainee. Author Contributions: TLA: study concept and design; acquisition, analysis, and interpretation of data; preparation and critical review of manuscript. JCD and JB: analysis and interpretation of data, writing and critical review of manuscript. CLH, ED: acquisition of data, critical review of manuscript. LN: writing, critical review of manuscript. All authors had full access to all of the data (including statistical reports and tables) in the study and can take responsibility for the integrity of the data and the accuracy of the data analysis. Sponsor's Role: None.

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