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Determining the Profile of People with Fall Risk in Community-Living Older People in Algarve Region: A Cross-Sectional, Population-Based Study

Author

Listed:
  • Carla Guerreiro

    (Algarve Biomedical Center Research Institute (ABCRI), University of Algarve, 8005-139 Faro, Portugal)

  • Marta Botelho

    (Algarve Biomedical Center Research Institute (ABCRI), University of Algarve, 8005-139 Faro, Portugal)

  • Elia Fernández-Martínez

    (Department of Nursing, University of Huelva, 21004 Huelva, Spain
    Department of Nursing, University of Sevilla, 41009 Sevilla, Spain)

  • Ana Marreiros

    (Algarve Biomedical Center Research Institute (ABCRI), University of Algarve, 8005-139 Faro, Portugal
    Faculty of Medicine and Biomedical Sciences, University of Algarve, 8005-139 Faro, Portugal)

  • Sandra Pais

    (Algarve Biomedical Center Research Institute (ABCRI), University of Algarve, 8005-139 Faro, Portugal
    Faculty of Medicine and Biomedical Sciences, University of Algarve, 8005-139 Faro, Portugal
    Comprehensive Health Research Center (CHRC), 1150-082 Lisboa, Portugal)

Abstract

One in three people aged 65 years or older falls every year. Injuries associated with this event among the older population are a major cause of pain, disability, loss of functional autonomy and institutionalization. This study aimed to assess mobility and fall risk (FR) in community-living older people and to determine reliable and independent measures (health, social, environmental and risk factors) that can predict the mobility loss and FR. In total, 192 participants were included, with a mean age of 77.93 ± 8.38. FR was assessed by EASY-Care (EC) Standard 2010, the Tinetti Test and the Modified Falls Efficacy Scale (MFES). An exploratory analysis was conducted using the divisive non-hierarchical cluster method, aiming to identify a differentiator and homogeneous group of subjects (optimal group of variables) and to verify if that group shows differences in fall risk. Individually, the health, social, environmental and risk factor categories were not found to be an optimal group; they do not predict FR. The most significant predictor variables were a mix of the different categories, namely, the presence of pain, osteoarthritis (OA), and female gender. The finding of a profile that allows health professionals to be able to quickly identify people at FR will enable a reduction in injuries and fractures resulting from falls and, consequently, the associated costs.

Suggested Citation

  • Carla Guerreiro & Marta Botelho & Elia Fernández-Martínez & Ana Marreiros & Sandra Pais, 2022. "Determining the Profile of People with Fall Risk in Community-Living Older People in Algarve Region: A Cross-Sectional, Population-Based Study," IJERPH, MDPI, vol. 19(4), pages 1-10, February.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:4:p:2249-:d:750859
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    References listed on IDEAS

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    1. Pierpaolo Palumbo & Luca Palmerini & Stefania Bandinelli & Lorenzo Chiari, 2015. "Fall Risk Assessment Tools for Elderly Living in the Community: Can We Do Better?," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-13, December.
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