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Slow Processing Speed Predicts Falls in Older Adults With a Falls History: 1-Year Prospective Cohort Study

Authors

  • Jennifer C. Davis PhD,

    1. Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
    2. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    3. Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
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  • John R. Best PhD,

    1. Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
    2. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    3. Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
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  • Karim M. Khan MD, PhD,

    1. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    2. Department of Family Practice, University of British Columbia, Vancouver, British Columbia, Canada
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  • Larry Dian MD,

    1. Division of Geriatrics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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  • Stephen Lord PhD,

    1. Falls, Balance and Injury Research Centre, Neuroscience Research Australia, Sydney, New South Wales, Australia
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  • Kim Delbaere PhD,

    1. Falls, Balance and Injury Research Centre, Neuroscience Research Australia, Sydney, New South Wales, Australia
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  • Chun Liang Hsu MSc,

    1. Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
    2. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    3. Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
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  • Winnie Cheung BSc,

    1. Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
    2. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    3. Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
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  • Wency Chan BSc,

    1. Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
    2. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    3. Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
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  • Teresa Liu-Ambrose PhD

    Corresponding author
    1. Aging, Mobility, and Cognitive Neuroscience Lab, Department of Physical Therapy, University of British Columbia, Vancouver, British Columbia, Canada
    2. Center for Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
    3. Djavad Mowafaghian Centre for Brain Health, Vancouver, British Columbia, Canada
    • Address correspondence to Teresa Liu-Ambrose, 2211 Wesbrook Mall, University of British Columbia, Vancouver, British Columbia, V6T 2B5, Canada. E-mail: teresa.ambrose@ubc.ca

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Abstract

Background/Objectives

A previous fall is a strong predictor of future falls. Recent epidemiologic data suggest that deficits in processing speed predict future injurious falls. Our primary objective was to determine a parsimonious predictive model of future falls among older adults who experienced ≥1 fall in the past 12 months based on the following categories: counts of (1) total, (2) indoor, (3) outdoor or (4) non-injurious falls; (5) one mild or severe injury fall (yes vs no); (6) an injurious instead of a non-injurious fall; and (7) an outdoor instead of an indoor fall.

Design

12-month prospective cohort study.

Setting

Vancouver Falls Prevention Clinic, Canada (www.fallsclinic.ca).

Participants

Two-hundred and eighty-eight community-dwelling older adults aged ≥70 years with a history of ≥1 fall resulting in medical attention in the previous 12 months.

Measurements

We employed principal component analysis to reduce the baseline predictor variables to a smaller set of five factors (i.e., processing speed, working memory, emotional functioning, physical functioning and body composition/fall risk profile). Second, we used the extracted five factors as predictors in regression models predicting the incidence of falls over a 12-month prospective observation period. We conducted regression analyses for the seven falls-related categories (defined above).

Results

Among older adults with a falls history, processing speed was the most consistent predictor of future falls; poorer processing speed predicted a greater number of total, indoor, outdoor, and non-injurious falls, and a greater likelihood of experiencing at least one mild or severe injurious fall (all P values < .01).

Conclusion

Poorer performance on the processing speed factor, a trainable factor, was independently associated with the most costly type of falls–injurious falls.

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