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Purpose <p>Frailty is a well-established risk factor for adverse health outcomes, yet its dynamic nature and predictors remain partially understood. This study aimed to investigate factors influencing frailty transitions and mortality risk among community-dwelling older adults.</p> Methods <p>We conducted a longitudinal study using a 9-year follow-up data from the Health, Well-being, and Aging Study (SABE, as known in Portuguese). A Markov model, fitted via multinomial logistic regression, identified factors independently associated with frailty transitions between waves. Four trajectory groups were identified: stable, worsening, improving, and fluctuating.</p> Results <p>A total of 1399 individuals aged 60 and older (61.8% female) were enrolled, with a mean age of 73.9 (SD ± 9.2) years. Among frailty transitions, 37.8% remained stable, 56.4% worsened, 1.3% improved, and 4.4% fluctuated. After adjusting for baseline variables, we found that older age, cognitive impairment, multimorbidity, and depressive symptoms were significantly linked to a higher risk of being frail at the next visit. The mortality risk was associated with male sex, older age, frailty, cognitive impairment, and multimorbidity.</p> Conclusion <p>Sociodemographic and health-related factors contribute to increased risk of experiencing frailty and mortality among community-dwelling older adults. Further research is needed to identify modifiable factors influencing frailty transitions.</p>

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Frailty trajectories and mortality risk in community-dwelling older adults: a 9-year follow-up study

  • 期刊论文

  • 发表日期：

    2025年3月11日

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  • Gabriela Cabett Cipolli,
  • Daniela de Assumpção,
  • Ivan Aprahamian,
  • Mallak Khalid Alzahrani,
  • Ligiana Pires Corona,
  • Yeda Aparecida de Oliveira Duarte,
  • Mônica Sanches Yassuda,
  • Qian-Li Xue

摘要

Purpose

Frailty is a well-established risk factor for adverse health outcomes, yet its dynamic nature and predictors remain partially understood. This study aimed to investigate factors influencing frailty transitions and mortality risk among community-dwelling older adults.

Methods

We conducted a longitudinal study using a 9-year follow-up data from the Health, Well-being, and Aging Study (SABE, as known in Portuguese). A Markov model, fitted via multinomial logistic regression, identified factors independently associated with frailty transitions between waves. Four trajectory groups were identified: stable, worsening, improving, and fluctuating.

Results

A total of 1399 individuals aged 60 and older (61.8% female) were enrolled, with a mean age of 73.9 (SD ± 9.2) years. Among frailty transitions, 37.8% remained stable, 56.4% worsened, 1.3% improved, and 4.4% fluctuated. After adjusting for baseline variables, we found that older age, cognitive impairment, multimorbidity, and depressive symptoms were significantly linked to a higher risk of being frail at the next visit. The mortality risk was associated with male sex, older age, frailty, cognitive impairment, and multimorbidity.

Conclusion

Sociodemographic and health-related factors contribute to increased risk of experiencing frailty and mortality among community-dwelling older adults. Further research is needed to identify modifiable factors influencing frailty transitions.