Frailty prevalence in Australia: Findings from four pooled Australian cohort studies

Thompson, Mark Q.; Theou, Olga; Karnon, Jonathan; Adams, Robert; Visvanathan, Renuka

doi:10.1111/ajag.12483

Cited by 48 publications

(55 citation statements)

References 19 publications

(38 reference statements)

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“…Anyhow, this issue might play a minor role because our main aim was to investigate the accuracy of different health indicators, which are based on participants’ clinical and functional characteristics. Furthermore, we found the prevalence of MM, WS, and FP to be similar to those described in previous studies [55, 66, 67]. Our study has also several major strengths.…”

Section: Discussionsupporting

confidence: 86%

Comparing the prognostic value of geriatric health indicators: a population-based study

Zucchelli

Vetrano

Grande

et al. 2019

BMC Med

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Background The identification of individuals at increased risk of poor health-related outcomes is a priority. Geriatric research has proposed several indicators shown to be associated with these outcomes, but a head-to-head comparison of their predictive accuracy is still lacking. We therefore aimed to compare the accuracy of five geriatric health indicators in predicting different outcomes among older persons: frailty index (FI), frailty phenotype (FP), walking speed (WS), multimorbidity, and a summary score including clinical diagnoses, functioning, and disability (the Health Assessment Tool; HAT). Methods Data were retrieved from the Swedish National Study on Aging and Care in Kungsholmen, an ongoing longitudinal study including 3363 people aged 60+. To inspect the accuracy of geriatric health indicators, we employed areas under the receiver operating characteristic curve (AUC) for the prediction of 3-year and 5-year mortality, 1-year and 3-year unplanned hospitalizations (1+), and contacts with healthcare providers in the 6 months before and after baseline evaluation (2+). Results FI, WS, and HAT showed the best accuracy in the prediction of mortality [AUC(95%CI) for 3-year mortality 0.84 (0.82–0.86), 0.85 (0.83–0.87), 0.87 (0.85–0.88) and AUC(95%CI) for 5-year mortality 0.84 (0.82–0.86), 0.85 (0.83–0.86), 0.86 (0.85–0.88), respectively]. Unplanned hospitalizations were better predicted by the FI [AUC(95%CI) 1-year 0.73 (0.71–0.76); 3-year 0.72 (0.70–0.73)] and HAT [AUC(95%CI) 1-year 0.73 (0.71–0.75); 3-year 0.71 (0.69–0.73)]. The most accurate predictor of multiple contacts with healthcare providers was multimorbidity [AUC(95%CI) 0.67 (0.65–0.68)]. Predictions were generally less accurate among younger individuals (< 78 years old). Conclusion Specific geriatric health indicators predict clinical outcomes with different accuracy. Comprehensive indicators (HAT, FI, WS) perform better in predicting mortality and hospitalization. Multimorbidity exhibits the best accuracy in the prediction of multiple contacts with providers.

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Section: Discussionsupporting

confidence: 86%

Comparing the prognostic value of geriatric health indicators: a population-based study

Zucchelli

Vetrano

Grande

et al. 2019

BMC Med

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“…Previous studies found that marital status was related to frailty but only a few studies have shown a gender-based effect. 18) Moreover, no study has explored the additional effect of living with children on frailty. In our study, we analyzed gender separately and observed differences based on gender.…”

Section: Discussionmentioning

confidence: 99%

Older Men Living with Spouse and Older Women Living with Spouse and Children Have Lower Frailty Prevalence: The Korean Frailty and Aging Cohort Study (KFACS)

Shim

Kim

et al. 2020

Ann Geriatr Med Res

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The most common index is the frailty phenotype by Fried et al., 5) which defined frailty as the presence of three or more of the following five components: self-reported exhaustion, decreased grip strength, slow walking speed, low physical activity, and unintended weight loss. 5) It is important to define frailty based on physical and social determinants for the early detection of people at a high risk of frailty, as well as for prevention of frailty. 6) Statistics Korea reported that 34.2% of individuals aged above 65 years were living in one-person

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“…Like many countries, Australia's population of older adults is expanding rapidly. It has been estimated that by 2031, 3.9 million Australians aged 65 years and over will be either frail or at-risk of becoming frail [10]. As a result, support for the clinical operationalization of frailty is growing, including policy and practice recommendations to screen older adults for frailty using validated measurement tools.…”

mentioning

confidence: 99%

Orthopaedic surgeons’ perceptions of frailty and frailty screening

2020

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Background: Over the past decade, there has been significant growth in the awareness and understanding of fragility among orthopaedic surgeons in the context of osteoporotic fractures and with it, improvements in the recognition and management of fragility fractures. Emerging as a major clinical and research focus in aged care is the concept of frailty and its associations with fragility, sarcopenia, falls and rehabilitation. Currently, research is lacking on how orthopaedic surgeons perceive frailty and the role of frailty screening. A baseline understanding of these perceptions is needed to inform integration of frailty identification and management for patient optimization in orthopaedic practices, as well as research and education efforts of patients and healthcare professionals in orthopaedic contexts. Methods:We used an exploratory design guided by qualitative description to conduct 15 semi-structured telephone and in-person interviews across three orthopaedic surgeon subgroups (Registrars, Junior Consultants, and Senior Consultants). Data collection and analysis occurred iteratively and was guided by thematic saturation.Results: Orthopaedic surgeons have a disparate understanding of frailty. Between colleagues, frailty is often referred to non-specifically to suggest a general state of risk to the patient. Frailty screening is regarded positively but its specific utility in orthopaedic environments is questioned. Easy-to-administer frailty screening tools that are not exclusive assessments of functional status are viewed most satisfactorily. However these tools are rarely used. Conclusions: There is little understanding among orthopaedic surgeons of frailty as a phenotype. Beliefs around modifiability of frailty were dissimilar as were the impact of related risk factors, such a cognitive status, chronic disease, social isolation, and environmental influences. This in turn may significantly impact on the occurrence and treatment outcomes of fragility fracture, a common orthopaedic problem in older populations. This study highlights need for knowledge translation efforts (e.g. education) to achieve cohesive understanding of frailty among health professionals.

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Frailty prevalence in Australia: Findings from four pooled Australian cohort studies

Abstract: If frailty could be prevented or reversed, it would have an impact on a larger number of older people.

Cited by 48 publications

References 19 publications

Comparing the prognostic value of geriatric health indicators: a population-based study

Comparing the prognostic value of geriatric health indicators: a population-based study

Older Men Living with Spouse and Older Women Living with Spouse and Children Have Lower Frailty Prevalence: The Korean Frailty and Aging Cohort Study (KFACS)

Orthopaedic surgeons’ perceptions of frailty and frailty screening

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