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Falls in Parkinson’s Disease Subtypes: Risk Factors, Locations and Circumstances

Author

Listed:
  • Paulo H. S. Pelicioni

    (Neuroscience Research Australia, NSchool of Public Health and Community Medicine, University of New South Wales, Sydney, NSW 2052, Australia)

  • Jasmine C. Menant

    (Neuroscience Research Australia, NSchool of Public Health and Community Medicine, University of New South Wales, Sydney, NSW 2052, Australia)

  • Mark D. Latt

    (Department of Aged Care, Royal Prince Alfred Hospital, Sydney, NSW 2050, Australia)

  • Stephen R. Lord

    (Neuroscience Research Australia, NSchool of Public Health and Community Medicine, University of New South Wales, Sydney, NSW 2052, Australia)

Abstract

People with Parkinson’s disease (PD) can be classified into those with postural instability and gait difficulty (PIGD subtype) and those manifesting tremor as the main symptoms (non-PIGD subtype). In a prospective cohort study of 113 people with PD we aimed to contrast fall rates and circumstances as well as a range of disease-related, clinical, and functional measures between the PD subtypes. Compared with non-PIGD participants, PIGD participants were significantly more likely to suffer more falls overall as well as more falls due to freezing of gait, balance-related falls and falls at home. The PIGD group also performed significantly worse in a range of fall-related clinical and functional measures including general cognitive status, executive function, quadriceps muscle strength, postural sway and the timed up and go test. These findings document the extent to which people with the PIGD subtype are at increased risk of falls, the circumstances in which they fall and their disease-related, clinical and functional impairments.

Suggested Citation

  • Paulo H. S. Pelicioni & Jasmine C. Menant & Mark D. Latt & Stephen R. Lord, 2019. "Falls in Parkinson’s Disease Subtypes: Risk Factors, Locations and Circumstances," IJERPH, MDPI, vol. 16(12), pages 1-9, June.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:12:p:2216-:d:242286
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    Citations

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    Cited by:

    1. Amit Salomon & Eran Gazit & Pieter Ginis & Baurzhan Urazalinov & Hirokazu Takoi & Taiki Yamaguchi & Shuhei Goda & David Lander & Julien Lacombe & Aditya Kumar Sinha & Alice Nieuwboer & Leslie C. Kirsc, 2024. "A machine learning contest enhances automated freezing of gait detection and reveals time-of-day effects," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    2. Paulo Henrique Silva Pelicioni & Marcelo Pinto Pereira & Juliana Lahr & Paulo Cezar Rocha dos Santos & Lilian Teresa Bucken Gobbi, 2021. "Assessment of Force Production in Parkinson’s Disease Subtypes," IJERPH, MDPI, vol. 18(19), pages 1-8, September.

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