Background
Successful ageing seeks to optimise health and independence [
1]. Indicators for successful ageing include minimal chronic disease, physical decline or depressive symptoms, and optimised social support, social participation and economic satisfaction [
2]. Bowling & Dieppe suggest that
‘a forward looking policy for older age would be a programme to promote successful ageing from middle age onwards, rather than simply aiming to support elderly people with chronic conditions’ [
3]. Successful ageing thereby avoids or delays the onset of frailty as people grow older [
1].
Frailty is a broad term that incorporates a reduction in health, energy levels or cognition leading to increased susceptibility to further illness or decline in physical or cognitive function [
4]. Its’ presentation is multi-factorial and varies across individuals. Frailty manifests as reduced performance and capacity in multiple body systems [
5]; across physical, psychological, social [
6] and cognitive [
7] domains. Xue suggests that frailty is a precursor for
‘poor health outcomes including falls, incident disability, hospitalization, and mortality’ [
8]. There is common agreement in the medical literature that frailty, frailty syndrome or declining function are associated with increased age and that prevention of frailty is a positive outcome of successful ageing.
A number of tools have been proposed to detect frailty in community dwelling older people [
9]. These tools variably include data derived from self-reports, direct observations or measurement of performance, and clinical assessments. Examples of community-based frailty assessment tools are:
-
self-report (PRISMA 7 questionnaire [
10]; Groningen Frailty Index [
11,
12]);
-
self-reports and objective measurement (Edmonton Frail Scale [
13]; Gérontôpole [
14]; Frail Non-Disabled (FiND) Scale [
15], Fried frailty phenotypes [
16]); and
-
subjective clinical determination of a person’s frailty state (Clinical Frailty Scale (CFS)) [
4].
Most of the frailty assessment instruments include one or more elements of the five Fried frailty phenotypes; unintentional weight loss, feeling exhausted, weak grip strength, slow walking speed and low levels of physical activity [
16]. While frailty is multi-factorial there is evidence that decline in physical function precedes cognitive decline [
17‐
20]. A 10-year longitudinal study has provided evidence that slow gait or low handgrip are predictors of cognitive decline [
21]. Hence the use of a physical based frailty tool such as the Fried phenotype was considered appropriate for pre-frail and frailty assessment of middle-aged people who are less likely to have cognitive decline. As well the Fried frailty phenotype provides an accepted definition of pre-frailty when one or two of the elements of the Fried frailty phenotype are detected [
16]. It is not expected that people aged 40 to 75 years will be mostly frail rather the intent is to identify and understand factors which contribute to pre-frailty and ultimately may progress to frailty. Previous research developing frailty indicators has largely missed the opportunity to identify contributors to pre-frailty and frailty in the middle years by the consistent exclusion of younger people.
The World Health Organisation (WHO) proposed a trajectory of age-related disability in 2001, which hypothesised that without intervention, declining function could be detected in middle age, defined as prior to 60 years [
22]. More recently, Theou et al. [
23] found that age was not a significant predictor of frailty in a large Irish community-dwelling population aged 50+ years. Hanlon et al. [
24] assessed frailty phenotype data extracted from the UK Biobank on 493,737 people aged 37–73 years, and identified one or more frailty markers across all ages, and both genders. Globally reports of pre-frailty and frailty using the Fried phenotype have reported that in England 3.9% of 8095 people aged 50 to 65 years were frail and 31.6% prefrail [
25], across 10 European countries of 9074 people aged 50 to 64 years 4.1% were frail and 37.4% were prefrail [
26] and in Taiwan 33.3% of 12 people aged 50–64 years were pre-frail [
27]. The progression from pre-frailty to frailty in older adults has been reported recently [
28,
29]. These authors suggested that self-reported and test-based measures should be combined to determine sensitively the level of frailty.
For successful ageing to become a reality in policy, public health, health promotion and clinical practice, a better understanding is required of how pre-frailty manifests and progresses to frailty, and how pre-frailty might be mitigated by population-based interventions. This paper explores the occurrence of Fried frailty phenotypes in Australians aged 40–75 years living independently in the community. It also reports factor analysis of 25 predictor variables from not frail to pre-frailty and frailty in this group.
Discussion
To our knowledge, this is the first Australian study to report on pre-frailty in presumed healthy, independently living community-dwellers aged 40 to 75 years. We used an established frailty phenotype with two objective components (grip strength, walking speed) and three self-report measures (unintentional weight loss, physical activity, exhaustion) [
16]. This phenotype was developed on people aged 65+ years and has been reported to sensitively identify pre-frailty and frailty states in this population [
16]. Our research indicates that using this frailty phenotype, pre-frailty is detectable as a separate state of health to ‘not frail’, or ‘frail’, in younger community dwellers aged 40–75 years. Moreover, neither age nor gender was significantly associated with any frailty state. Thus, our findings not only add support to the theoretical WHO trajectory of frailty [
22], but they also suggest that frailty is not necessarily a corollary of older age.
Our frailty rates are comparable with those published recently from analysis of data from a large UK biobank, reporting on 493 737 people aged 37–73 years (3% frail, 38% pre-frail, and 59% not frail [
24] (compared with our Fig.
1.8% frail, 39% pre-frail, and 59.2% not frail). Nevertheless, we were alarmed by the prevalence of ‘pre-frailty’ in our sample and its occurrence in people aged 40–59 years. A designation of ‘pre-frailty’ requires one or two components of the Fried phenotype to be present. Given that the two most common components in the Fried frailty phenotype in our sample were related to poor grip strength, and slow walking speed, we hypothesised that at least one of these would be present in most people who were classified as ‘pre-frail’. Whilst Table
2 supports this hypothesis (33.6% pre-frail people had poor grip strength, and 55.9% had slow walking speed), this table also shows that the other three frailty components (exhaustion, poor exercise behaviours, unintentional weight loss) were found in some people designated as ‘pre-frail’.
This study essentially correlated multiple indicators of frailty, by assembling an outcome measure from the five components in the Fried frailty phenotype and testing it against latent variables constructed from a range of other measures reported in the literature as relevant to frailty. The Fried frailty phenotype components were not double counted in predictor variables. For instance, the total K10 psychological distress score was modified by removing Question 1 because this question about exhaustion was already accounted for in the Fried criteria. The seven latent frailty factors provided new information on clusters of frailty attributes, particularly as the components in each factor were justifiably related on a priori bases. For instance, the best predicting factors for pre-frailty (Factors 1 and 7), accounted for 30% variance, combining attributes of safety and stability (poor dynamic trunk stability and lower limb strength, poor balance, poor foot sensation, being underweight (Factor 1) and continence and nutrition (Factor 7)). Factor 3, the only one which significantly (albeit moderately) predicted frailty from pre-frailty in this sample, accounted for 11.5% variance, dealing with important factors associated with poor mental state i.e. living alone, high psychological distress, poor lung function and poor sleep quality.
The Fried frailty phenotype is based on two objective measures (grip strength, walking speed), and three self-report components (exhaustion, usual exercise behaviours, unintentional weight loss) [
16]. It was developed for, and tested on, people aged 65 years and older, and one or more of its elements have been incorporated into other frailty descriptors (which have also been tested only on older people [
4,
10‐
16]). It appears from our study, that the Fried frailty phenotypes may also be relevant to younger community-dwellers. However, the Fried pre-frail classification requires further examination in younger people to better understand causality and onset of pre-frailty. It may be that requiring one or two components of the Fried frailty phenotype to designate pre-frailty state may be too liberal for people younger than 65 years. If two components, rather than one or two, were required to identify ‘pre-frailty’, this would have reduced the prevalence of pre-frailty to 10.5% in our sample. On the other hand, by identifying the presence of one frailty attribute (any of the Fried frailty criteria), this may assist in identifying people early who are at risk of developing other frailty attributes. We did not test for reliability, and thus we have no evidence of the repeatability over time of the self-report data included in the phenotype (unintentional weight loss, and the amount of physical activity undertaken each week). However, as weight is notoriously under-reported and physical activity is notoriously over-reported [
59] it is likely that some of our sample inaccurately estimated usual physical activity patterns, as well as weight change. For instance, the notion of unintentional weight loss may have been lost in our sample in the desire to be seen to be losing weight.
Factor 1 was the best predictor of change in status from not-frail to pre-frail. Risk of early frailty could potentially be reduced by increasing exercise behaviours to improve balance, dynamic stability and muscle strength. The significant predictive capacity of Factors 3, 5 and 7 for pre-frailty to frailty (high psychological distress, living alone, having health worries, and poor sleep quality; stair climbing, appetite, hydration; continence, total food intake) highlights issues which may alter more insidiously than balance, dynamic stability and muscle strength. Given that there was no age difference between pre-frail and frail people (despite the common belief that ageing and frailty is related to body systems decline), it appears that screening people aged 40 years and older not only for physical activity, balance, hearing, foot sensation and muscle strength, but also for mental health, continence, health concerns and poor sleep quality would seem to be important in preventing or delaying frailty onset.
The components of the Fried frailty phenotype, and most variables included in the important predictive factors are potentially modifiable by active interventions. Setting unintentional weight loss aside (which requires medical investigation), our findings suggest that there are many people aged 40 years or older whose frailty status could potentially be addressed by increasing physical activity, building muscle, improving exercise tolerance, nutrition and mental health. The presence of chronic health conditions and concerns about health can be managed actively by supported behaviour change strategies [
60]. Reasons for poor foot sensation like diabetes or peripheral neuropathy can be identified following assessment for chronic disease, and solutions for improved foot health and better footwear proposed. Poor hearing can be addressed by audiological or medical intervention and/or hearing aids.
It is reasonable to propose that chronic disease self-management and population health interventions to improve physical activity, such as workplace or community wellbeing programs, could significantly attenuate reverse or slow the onset of pre-frailty in community dwellers aged 40 years or more, and their subsequent risk of progression to frailty [
1‐
3,
6].
Limitations
Interpretation
The authors acknowledge significant potential for respondent bias. Participants were sufficiently literate to read, understand and respond to the recruitment material, and complete the online surveys (98% submitted online). Participants had the time to attend testing and acknowledged strong personal incentives to obtain comprehensive individual health status information, currently unavailable from other sources. It is not known how well these findings reflect people who were less well educated, less health or computer literate, and/or who were not interested in participating in population health screening. Thus, these recruitment strategies, and study findings, require further testing in other community samples. The TMIG study [
30] on which our research is partly modelled, recruit participants through the local Tokyo prefecture, using birthdates. The local prefecture office recruit people who have turned 65 years or older since the previous biennial TMIG study. Whilst this rigorous independent recruitment approach has significantly contributed to the size, longevity and impact of the TMIG study, it does not recruit people younger than 65 years. Our multi-pronged recruitment approaches, and strong community partnerships, provided rare access to younger people who would not normally make themselves available, or be targeted, for population health screening initiatives. The health assessments available for analysis in this study while comprehensive were not exhaustive and other factors such as employment status, social connectedness and oral health could be included for future analysis.
Generalisability
The study methodology was successful in recruiting a robust sample of volunteers aged 40 to 75 years, from a range of postcodes in one Australian capital city. The sample age, gender and socioeconomic index distribution is thus generalizable to other urban Australians [
61,
62]. The similarity in findings of pre-frailty in community dwellers over 50 years in our study with UK [
24], English [
25], European [
26] and Taiwanese [
27] studies supports the believability of our findings, particularly as our sample reflects people who are notoriously difficult to comprehensively recruit for community-based population screening [62].
Acknowledgements
Professor Ronald C Kessler of the Department of Health Care Policy, Harvard Medical School is thanked for the use of research on the K10 funded by US Public Health Service Grants RO1 MH46376, R01 MH52861, RO1 MH49098, and K05 MH00507 and by the John D and Catherine T MacArthur Foundation Network on Successful Midlife Development (Gilbert Brim, Director).
The Cities of Marion, Holdfast Bay and Salisbury, and the National Australia Bank provided venues for assessment and assisted with recruitment and administration of the project.
Dr. Ellena King is acknowledged for independent editing of the final manuscript.
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