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    This chapter has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Tuerk, Carola Zhang, Haobo Sachdev, Perminder Lord, Stephen R. Brodaty, Henry Wen, Wei and Delbaere, Kim 2016. Regional Gray Matter Volumes Are Related to Concern About Falling in Older People: A Voxel-Based Morphometric Study. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 71, Issue. 1, p. 138.

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    Caetano, Maria Joana D. Menant, Jasmine C. Schoene, Daniel Pelicioni, Paulo H. S. Sturnieks, Daina L. and Lord, Stephen R. 2016. Sensorimotor and Cognitive Predictors of Impaired Gait Adaptability in Older People. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, p. glw171.

    Butler, Annie A. Lord, Stephen R. Taylor, Janet L. and Fitzpatrick, Richard C. 2015. Ability Versus Hazard: Risk-Taking and Falls in Older People. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 70, Issue. 5, p. 628.

    Callisaya, Michele L. Beare, Richard Phan, Thanh Blizzard, Leigh Thrift, Amanda G. Chen, Jian and Srikanth, Velandai K. 2015. Progression of White Matter Hyperintensities of Presumed Vascular Origin Increases the Risk of Falls in Older People. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 70, Issue. 3, p. 360.

    Liston, M. B. Bamiou, D.-E. Martin, F. Hopper, A. Koohi, N. Luxon, L. and Pavlou, M. 2014. Peripheral vestibular dysfunction is prevalent in older adults experiencing multiple non-syncopal falls versus age-matched non-fallers: a pilot study. Age and Ageing, Vol. 43, Issue. 1, p. 38.

    Schoene, D. Smith, S. T. Davies, T. A. Delbaere, K. and Lord, S. R. 2014. A Stroop Stepping Test (SST) using low-cost computer game technology discriminates between older fallers and non-fallers. Age and Ageing, Vol. 43, Issue. 2, p. 285.

    Merom, D. Stanaway, F. F. Handelsman, D. J. Waite, L. M. Seibel, M. J. Blyth, F. M. Naganathan, V. and Cumming, R. G. 2014. Swimming and Other Sporting Activities and the Rate of Falls in Older Men: Longitudinal Findings From the Concord Health and Ageing in Men Project. American Journal of Epidemiology, Vol. 180, Issue. 8, p. 830.

    Swift, C. G. and Iliffe, S. 2014. Assessment and prevention of falls in older people - concise guidance. Clinical Medicine, Vol. 14, Issue. 6, p. 658.

    2014. A Novel Methodology for Assessing the Fall Risk Using Low-Cost and Off-the-Shelf Devices. IEEE Transactions on Human-Machine Systems, Vol. 44, Issue. 3, p. 406.

    Lacherez, P. Wood, J. M. Anstey, K. J. and Lord, S. R. 2014. Sensorimotor and Postural Control Factors Associated With Driving Safety in a Community-Dwelling Older Driver Population. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 69A, Issue. 2, p. 240.

    Taylor, M. E. Delbaere, K. Lord, S. R. Mikolaizak, A. S. Brodaty, H. and Close, J. C. T. 2014. Neuropsychological, Physical, and Functional Mobility Measures Associated With Falls in Cognitively Impaired Older Adults. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 69, Issue. 8, p. 987.

    Delbaere, K. Close, J. C. T. Taylor, M. Wesson, J. and Lord, S. R. 2013. Validation of the Iconographical Falls Efficacy Scale in Cognitively Impaired Older People. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68, Issue. 9, p. 1098.

    Odonkor, C. A. Thomas, J. C. Holt, N. Latham, N. vanSwearingen, J. Brach, J. S. Leveille, S. G. Jette, A. and Bean, J. 2013. A Comparison of Straight- and Curved-Path Walking Tests Among Mobility-Limited Older Adults. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68, Issue. 12, p. 1532.

    Martin, K. L. Blizzard, L. Srikanth, V. K. Wood, A. Thomson, R. Sanders, L. M. and Callisaya, M. L. 2013. Cognitive Function Modifies the Effect of Physiological Function on the Risk of Multiple Falls--A Population-Based Study. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 68, Issue. 9, p. 1091.

    Shany, Tal Redmond, Stephen J. Narayanan, Michael R. and Lovell, Nigel H. 2012. Sensors-Based Wearable Systems for Monitoring of Human Movement and Falls. IEEE Sensors Journal, Vol. 12, Issue. 3, p. 658.

    Zheng, J. J. J. Lord, S. R. Close, J. C. T. Sachdev, P. S. Wen, W. Brodaty, H. and Delbaere, K. 2012. Brain White Matter Hyperintensities, Executive Dysfunction, Instability, and Falls in Older People: A Prospective Cohort Study. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, Vol. 67, Issue. 10, p. 1085.

    Ying Liu Redmond, S. J. Ning Wang Blumenkron, F. Narayanan, M. R. and Lovell, N. H. 2011. Spectral Analysis of Accelerometry Signals From a Directed-Routine for Falls-Risk Estimation. IEEE Transactions on Biomedical Engineering, Vol. 58, Issue. 8, p. 2308.

    Ying Liu Redmond, S. J. Narayanan, M. R. and Lovell, N. H. 2011. Classification between non-multiple fallers and multiple fallers using a triaxial accelerometry-based system. p. 1499.

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  • Print publication year: 2007
  • Online publication date: May 2010

16 - A physiological profile approach to falls risk assessment and prevention

Summary

As outlined in Chapter 6, research studies have identified a broad range of medical conditions which contribute to falls risk. These include chronic and degenerative diseases, such as stroke, Parkinson's disease, arthritis, foot problems, cognitive impairment peripheral neuropathy and diabetes cataracts and vestibular disorders. However, attributing a degree of falls risk to a specific medical diagnosis is often problematic because the severity of these conditions varies considerably among individuals. Furthermore, impairments in sensorimotor function and balance associated with increased age, inactivity, medication use or minor pathology, may be evident in older people without diagnosed medical conditions.

To address this issue, we have devised a Physiological Profile Assessment (PPA) for assessing falls risk that involves quantitative assessment of sensorimotor and balance abilities. Physiological factors that are the important contributors to stability are shown in Figure 16.1. Functioning in each of these factors declines with age and impairments in each factor increases the risk of falling. A marked deficit in any one of these factors may be sufficient to predispose an older person to fall; however, a combination of mild or moderate impairments across physiological domains also may increase the risk of falling. By assessing an individual's physiological abilities, impairments in one or more physiological domains can be identified and cumulative falls risk can be determined.

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Falls in Older People
  • Online ISBN: 9780511722233
  • Book DOI: https://doi.org/10.1017/CBO9780511722233
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