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Sensorimotor, Cognitive, and Affective Functions Contribute to the Prediction of Falls in Old Age and Neurologic Disorders: An Observational Study

  • Kimberley S. van Schooten
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia

    School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia
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  • Morag E. Taylor
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia

    Prince of Wales Clinical School, Medicine, University of New South Wales, Sydney, Australia
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  • Jacqueline C.T. Close
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia

    Prince of Wales Clinical School, Medicine, University of New South Wales, Sydney, Australia
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  • Jennifer C. Davis
    Affiliations
    Faculty of Management, University of British Columbia-Okanagan, Kelowna, British Columbia, Canada

    Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
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  • Serena S. Paul
    Affiliations
    Faculty of Health Sciences, University of Sydney, Sydney Lidcombe, Sydney, New South Wales, Australia
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  • Colleen G. Canning
    Affiliations
    Faculty of Health Sciences, University of Sydney, Sydney Lidcombe, Sydney, New South Wales, Australia
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  • Mark D. Latt
    Affiliations
    Geriatric Medicine Department, University of Sydney, Royal Prince Alfred Hospital, Camperdown, Sydney, New South Wales, Australia
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  • Phu Hoang
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia
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  • Nicole A. Kochan
    Affiliations
    Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
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  • Perminder S. Sachdev
    Affiliations
    Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia

    Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, New South Wales, Australia

    Dementia Centre for Research Collaboration, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
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  • Henry Brodaty
    Affiliations
    Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia

    Dementia Centre for Research Collaboration, School of Psychiatry, Faculty of Medicine, University of New South Wales, Sydney, Australia
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  • Catherine M. Dean
    Affiliations
    Department of Health Professions, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, Sydney, New South Wales, Australia
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  • Femke Hulzinga
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia

    Department of Rehabilitation Sciences, Biomedical Sciences Group, KU Leuven University, Leuven, Belgium
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  • Author Footnotes
    ∗ Delbaere and Lord contributed equally as senior authors to this work.
    Stephen R. Lord
    Footnotes
    ∗ Delbaere and Lord contributed equally as senior authors to this work.
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia

    School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia
    Search for articles by this author
  • Author Footnotes
    ∗ Delbaere and Lord contributed equally as senior authors to this work.
    Kim Delbaere
    Correspondence
    Corresponding author Kim Delbaere, PhD, NeuRA Margarete Ainsworth Building, 139 Barker St, Randwick NSW 2031, Australia.
    Footnotes
    ∗ Delbaere and Lord contributed equally as senior authors to this work.
    Affiliations
    Falls, Balance and Injury Research Centre, Neuroscience Research Australia, University of New South Wales, Sydney, Australia

    School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia
    Search for articles by this author
  • Author Footnotes
    ∗ Delbaere and Lord contributed equally as senior authors to this work.
Published:November 27, 2020DOI:https://doi.org/10.1016/j.apmr.2020.10.134

      Abstract

      Objective

      To determine whether impairments across cognitive and affective domains provide additional information to sensorimotor deficits for fall prediction among various populations.

      Design

      We pooled data from 5 studies for this observational analysis of prospective falls.

      Setting

      Community or low-level care facility.

      Participants

      Older people (N=1090; 74.0±9.4y; 579 female); 500 neurologically intact (NI) older people and 3 groups with neurologic disorders (cognitive impairment, n=174; multiple sclerosis (MS), n=111; Parkinson disease, n=305).

      Interventions

      None.

      Main Outcome Measures

      Sensorimotor function was assessed with the Physiological Profile Assessment, cognitive function with tests of executive function, affect with questionnaires of depression, and concern about falling with falls efficacy questionnaires.
      These variables were associated with fall incidence rates, obtained prospectively over 6-12 months.

      Results

      Poorer sensorimotor function was associated with falls (incidence rate ratio [95% CI], 1.46 [1.28-1.66]). Impaired executive function was the strongest predictor of falls overall (2.91 [2.27-3.73]), followed by depressive symptoms (2.07 [1.56-2.75]) and concern about falling (2.02 [1.61-2.55]). Associations were similar among groups, except for a weaker relationship with executive impairment in NI persons and a stronger relationship with concern about falling in persons with MS. Multivariable analyses showed that executive impairment, poorer sensorimotor performance, depressive symptoms, and concern about falling were independently associated with falls.

      Conclusions

      Deficits in cognition (executive function) and affect (depressive symptoms) and concern about falling are as important as sensorimotor function for fall prediction. These domains should be included in fall risk assessments for older people and clinical groups.

      Keywords

      List of abbreviations:

      FAB (Frontal Assessment Battery), FES (Falls Efficacy Scale), IRR (incidence rate ratio), MMSE (Mini-Mental State Examination), MS (multiple sclerosis), NI (neurologically intact), PD (Parkinson disease), PPA (Physiological Profile Assessment), SF-36 (Short Form-36 Health Survey), TMT-B (Trail Making Test part B)
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