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

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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.

Section snippets

Methods

We pooled data from 5 prospective cohort studies12,14, 15, 16, 17 (fig 1) in 1090 English-speaking people aged 50 years and older. All studies obtained data on prospective falls, sensorimotor function, cognitive function, depressive symptoms, and concern about falling. All participants provided written informed consent and were able to comply with the assessment protocols. Studies were approved by the Human Research Ethics committees of the University of New South Wales, the University of

Results

Participants had a mean age of 74.0±9.4 years, and 53.1% of participants were female (table 1). Age, body mass index, sex distribution, and MMSE scores differed significantly between groups; hence, all further analyses were corrected for these factors. Participants had an average PPA score of 1.33±1.52, indicating a moderate physiological fall risk; compared with the NI participants, PPA scores were significantly worse in the participants with cognitive impairment and MS. Executive impairment

Discussion

We investigated whether impairments across cognitive and affective domains and concern about falling provide additional information to sensorimotor deficits for fall prediction in older people and people with chronic neurodegenerative diseases. Our multifactorial model confirmed that we should consider the triad of sensorimotor, cognitive, and affective symptoms and concern about falling when assessing fall risk, both in healthy older populations and in people with neurologic disorders. While

Conclusions

In conclusion, our findings indicate that deficits in cognition (executive function) and affect (depressive symptoms) are at least equally as important as sensorimotor function for fall prediction and should be included in fall risk assessments for older people and clinical groups. An individual’s concern about falling provides information that is possibly not provided by the PPA, cognitive, and affective assessments, so it should also be part of the assessment process. This reinforces previous

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    This work was supported by the Australian National Health and Medical Research Council (NHMRC) through grants 400941, 455368, 1093083, 512326, the Harry Secom Foundation, and a Multiple Sclerosis Research Australia Grant. Kim van Schooten, PhD, is supported by a Human Frontier Science Program fellowship. Kim Delbaere, PhD, Morag Taylor, PhD, and Stephen Lord, PhD, are supported by NHMRC fellowships. Phu Hoang, PhD, is supported by MSRA Project Grant 16-104.

    The PPA (NeuRA FallScreen) is commercially available through Neuroscience Research Australia.

    ∗

    Delbaere and Lord contributed equally as senior authors to this work.

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    © 2020 by the American Congress of Rehabilitation Medicine