Abstract
Background
frailty, a multi-dimensional geriatric syndrome, confers a high risk for falls, disability, hospitalisation and mortality. The prevalence and correlates of frailty in the UK are unknown.
Methods
frailty, defined by Fried, was examined among community-dwelling young-old (64-74 years) men (n = 320) and women (n = 318) who participated in the Hertfordshire Cohort Study, UK.
Results
the prevalence of frailty was 8.5% among women and 4.1% among men (P = 0.02). Among men, older age (P = 0.009), younger age of leaving education (P = 0.05), not owning/mortgaging one’s home (odds ratio [OR] for frailty 3.45 [95% confidence interval {CI} 1.01-11.81], P = 0.05, in comparison with owner/mortgage occupiers) and reduced car availability (OR for frailty 3.57 per unit decrease in number of cars available [95% CI 1.32, 10.0], P = 0.01) were associated with increased odds of frailty. Among women, not owning/mortgaging one’s home (P = 0.02) was associated with frailty. With the exception of car availability among men (P = 0.03), all associations were non-significant (P > 0.05) after adjustment for co-morbidity.
Conclusions
frailty is not uncommon even among community-dwelling young-old men and women in the UK. There are social inequalities in frailty which appear to be mediated by co-morbidity.
Keywords: frailty, prevalence, older people, social inequalities, co-morbidity, elderly
Introduction
Frailty is a multi-dimensional geriatric syndrome [1]; it may be described as a state of increased vulnerability which results from decreased physiological reserves, multi-system dysregulation and limited capacity to maintain homeostasis [2]. Although overlapping, frailty is not synonymous with either co-morbidity or disability [3, 4]; rather, co-morbidity may be considered a risk factor for frailty and disability, a consequence of frailty [5]. Frailty confers high risk for falls, disability, hospitalisation and mortality [5].
However, frailty remains an evolving concept lacking unique diagnostic criteria for use in clinical practice and epidemiological research [6-10]. Approaches to the characterisation of frailty have included: an index based on the proportion of accumulated deficits [11]; presence of problems in at least two of the physical, nutritive, cognitive and sensory domains [12]; a 7-point Clinical frailty scale [13]; dependency, e.g. needing assistance from another person for bathing or taking medications [14]; and grip strength has been proposed as a useful single marker of frailty [15]. However, the Fried criteria [5] are the most widely implemented objective approach to the classification of frailty as a biological functional limitation or impairment [16], defining frailty as present if a person has at least three of the following criteria: weight loss, weakness, exhaustion, slowness and low activity [5]. Frailty defined by Fried has predictive validity for adverse health outcomes, including disability [5, 17].
Data on the prevalence and correlates of frailty (defined by Fried) are largely from US studies. The prevalence of frailty among 5,317 community-dwelling men and women aged 65 years and older who participated in the American Cardiovascular Health Study was 6.9% with a 4 year incidence of 7.2% [5]; frailty was associated with older age, male gender, being African American, having lower education and income, poorer health and higher rates of comorbid chronic disease and disability. In the Women’s Health and Aging Study-I, the prevalence of frailty among 749 community-dwelling women aged 65 years and older who were moderately to severely disabled was 25%, and frailty was associated with incident difficulties in performing activities of daily living [18]. Ottenbacher [19] studied frailty among 621 Mexican Americans, average age 78 years: 22% of women and 17% of men were classified as frail and upper extremity strength, disability, co-morbidities, and mental status scores predicted frailty among men, and lower extremity strength, disability and body mass index predicted frailty among women. The prevalence of frailty in the Women’s Health Initiative Observational Study [20] was 16.3%, and older age, co-morbidity, smoking, depressive symptoms, lower income, living alone and poorer self-reported health were associated with increased frailty. Cawthorn et al. [21] estimated a frailty prevalence of 4% among American men aged 65 years and older and the seven and a half year incidence of frailty among 420 community-dwelling women aged 70–79 years who participated in the Women’s Health and Aging Study II and were not frail at baseline was 9% [22].
European studies on the prevalence and determinants of frailty are limited. The French Three-City Study demonstrated a frailty prevalence of 7% among 6,078 community-dwelling men and women aged 65 years and older [17]; frailty was associated with older age, female gender, lower education, lower income, poorer self-reported health status and more chronic diseases in addition to incident disability. The recent Survey of Health, Aging and Retirement in Europe (SHARE) [23], which did not include UK data, studied 16,584 men and women aged 50 years and older; the prevalence of frailty was 4.1% among participants aged 50-64 years and 17% among those aged 65 and older, with a higher prevalence of frailty among women. The SHARE study demonstrated higher prevalences of frailty in southern than northern Europe and concluded that education contributed to this geographical variation. We are not aware of any prevalence data on frailty defined by the Fried criteria from the United Kingdom.
The United Kingdom has an ageing population [24]. Within the context of this demographic change, the UK government’s ageing strategy recognises the importance of building a society which enables individuals to live a healthy and independent old age [25]. The UK government also acknowledges the need for effective planning to enable health and social systems to have the capability to support and care for inevitably increasing numbers of frail older people over time [26]. Although social factors such as lower education and income are broadly acknowledged as playing an important role in frailty [27], research focused on the social patterning of frailty is limited [5, 17, 20, 23]. Understanding of the social context in which frailty occurs would (i) inform local and national public health policy and planning by identifying subgroups of the population in which the burden of frailty is focused and (ii) would provide clues to aetiology and give direction for where best to target initiatives and interventions which aim to reduce frailty.
The objective of the current study was to describe the prevalence of frailty and to examine its associations with lifestyle and social characteristics, among community-dwelling young-old men and women who participated in the Hertfordshire Cohort Study (HCS), UK [28].
Methods
Study participants comprised 322 men and 320 women aged 64–74 years who participated in home interviews and clinic visits for a musculoskeletal follow-up component of the HCS [28] in 2004–5. At the follow-up clinic visit, medical and social histories were updated. Information was collected on frailty status using the Fried criteria [5]. Self-assessed health-related quality of life was ascertained using the short-form 36 (SF-36) questionnaire, and SF-36 data were mapped to eight domain scores including physical function. Hand grip strength was measured three times on each side using a Jamar handgrip dynamometer, and participants completed a timed 3 metre walk. Please see Appendix 1 in the supplementary data on the journal website (http://www.ageing.oxfordjournals.org/) for a full description of the study population and methodology.
The Fried frailty criteria define frailty as presence of three or more of the following items: unintentional weight loss (greater than 10lb over the past year), weakness, self-reported exhaustion, slow walking speed and low physical activity. In this study, these criteria were operationalised as follows: weakness was defined as a maximum grip strength of ≤30kg for men and ≤20kg for women [29]; exhaustion was identified if the participant felt that everything they did was an effort for either moderate amounts or most of the time in the past week; slow walking speed was defined as a 3 m walk time in the slowest fifth of the HCS sex-specific distribution (≥3.82 s for men and ≥3.98 s for women); and low physical activity was identified if the participant had an SF-36 physical functioning score in the bottom fifth of the HCS sex-specific distribution (≤75 for men and ≤60 for women). Four participants had missing data for the Fried frailty score and were excluded from all analyses.
Statistical methods
Cross-tabulations of frequencies and percentages and univariate and multiple logistic regression models were used to analyse the relationships between frailty and the characteristics of the study participants. Univariate analyses were conducted initially, followed by mutually adjusted, and comorbidity adjusted, analyses for lifestyle and social variables that were significantly associated with frailty (P < 0.05) in the univariate analyses. Categories of age, smoking status, alcohol intake, age left full-time education, social class and number of cars were used for presentational purposes, but P values for association were obtained from continuously distributed variables. All analyses were conducted for men and women separately using Stata, release 10.0 (Stata Corporation 2007).
Results
Table 1 shows the summary characteristics of the study participants who were aged 64–74 years at the time of the follow-up clinic visit. Table 2 shows the prevalence of each of the components of the Fried frailty criteria according to gender; the overall prevalence of frailty was 8.5% for women and 4.1% for men (P = 0.02 for gender difference).
Table 1.
Summary characteristics of study participants
| n (%) | Men (n = 320) | Women (n = 318) | |
|---|---|---|---|
| Age (years)a | 69.2 (2.5) | 69.5 (2.6) | |
| Smoking status | Never | 120 (37.5) | 200 (63.5) |
| Ex | 173 (54.1) | 98 (31.1) | |
| Current | 27 (8.4) | 17 (5.4) | |
| Alcohol (units per week) | Non-drinker | 17 (5.3) | 78 (24.7) |
| Very low (<1) | 44 (13.8) | 72 (22.8) | |
| Low (1–10 men, 1–7 women) | 139 (43.4) | 120 (38.0) | |
| Moderate (11–21 men, 8–14 women) | 67 (20.9) | 36 (11.4) | |
| Fairly high (22–35 men, 15–21 women) | 36 (11.3) | 5 (1.6) | |
| High (>35 men, >21 women) | 17 (5.3) | 5 (1.6) | |
| Age left full-time education (years)b | 15 (15,16) | 15 (15,16) | |
| Left full-time education aged ≤14 years | 62 (19.4) | 62 (19.5) | |
| Social class in adulthoodc | I Professional | 16 (5.3) | 21 (6.6) |
| II Management and Technical | 78 (25.7) | 70 (22.0) | |
| III NM Skilled non-manual | 37 (12.2) | 45 (14.2) | |
| III M Skilled manual | 115 (37.8) | 129 (40.6) | |
| IV Partly skilled | 52 (17.1) | 41 (12.9) | |
| V Unskilled | 6 (2.0) | 12 (3.8) | |
| Housing tenure | Owned/mortgaged | 281 (87.8) | 266 (83.7) |
| Rented/other | 39 (12.2) | 52 (16.4) | |
| Number of cars available | None | 12 (3.8) | 40 (12.6) |
| 1 | 168 (52.5) | 192 (60.4) | |
| 2 | 116 (36.3) | 77 (24.2) | |
| 3 | 24 (7.5) | 9 (2.8) |
Mean and standard deviation.
Median and interquartile range.
Based on social class of the husband for ever married women.
Table 2.
Prevalence of Fried frailty and its component items
| n (%) | Men (n = 320) | Women (n = 318) |
|---|---|---|
| Unintentional weight loss (>10lb over the past year) | 17 (5.3) | 11 (3.5) |
| Weaknessa | 22 (6.9) | 68 (21.5) |
| Self-reported exhaustionb | 18 (5.6) | 32 (10.1) |
| Slow walking speedc | 63 (19.8) | 63 (19.9) |
| Low physical activityd | 85 (26.6) | 69 (21.7) |
| Frail on the Fried score (presence of three or more of above criteria) | 13 (4.1) | 27 (8.5) |
Maximum grip strength ≤30kg men and ≤20kg for women.
The participant felt that everything they did was an effort for moderate amounts to most of the time in the past week.
Timed up and go 3 metre walk ≥3.82 s for men and ≥3.98 s for women.
SF-36 physical functioning score in the bottom fifth of the sex-specific distribution (≤75 for men and ≤60 for women).
Table 3 shows the univariate associations between the characteristics of the HCS participants and Fried frailty status. Among men, older age, younger age of leaving full-time education, not owning or mortgaging one’s home and having fewer cars available for household use were all associated with increased odds of being frail. Among women, lower alcohol intake and not owning or mortgaging one’s home were associated with increased odds of being frail.
Table 3.
Univariate associations between frailty and the lifestyle and social characteristics of HCS participants
| Men |
Women |
||||
|---|---|---|---|---|---|
|
n (%) frail on the Fried score |
Univariate odds ratios (95% CI) for frailty |
n (%) frail on the Fried score |
Univariate odds ratios (95% CI) for frailty |
||
| Age (years) | ≤67.7 | 1 (0.9) | 1.39 (1.09, 1.78) | 7 (6.6) | 1.07 (0.92, 1.24) |
| −70.8 | 5 (4.3) | P = 0.009, per year of age | 12 (12.1) | P = 0.40, per year of age | |
| ≥70.9 | 7 (7.4) | 8 (7.1) | |||
| Smoking status | Never | 4 (3.3) | 12 (6.0) | ||
| Ex | 8 (4.6) | 1.18 (0.48, 2.89) | 14 (14.3) | 1.62 (0.89, 2.96) | |
| Current | 1 (3.7) |
P = 0.72, per increased band of smoking |
1 (5.9) |
P = 0.12, per increased band of smoking |
|
| Alcohol intake (units per week) | Non-drinker | 3 (17.7) | 10 (12.8) | ||
| Very low (<1) | 1 (2.3) | 7 (9.7) | |||
| Low (1–10 men, 1–7 women) | 5 (3.6) | 9 (7.5) | |||
| Moderate (11–21 men, 8–14 women) |
3 (4.5) | 0.71 (0.42, 1.17) | 1 (2.8) | 0.66 (0.45, 0.97) | |
| Fairly high (22–35 men, 15–21 women) |
0 (0.0) |
P = 0.18, per increased band of intake |
0 (0.0) |
P = 0.04, per increased band of intake |
|
| High (>35 men, >21 women) | 1 (5.9) | 0 (0.0) | |||
| Age left full-time education (years) | ≤14 | 6 (9.7) | 0.50 (0.25, 1.01) | 5 (8.1) | 0.85 (0.59, 1.22) |
| ≥15 | 7 (2.7) | P = 0.05, per year older | 22 (8.6) | P = 0.37, per year older | |
| Social class in adulthood | I Professional | 0 (0.0) | 1 (4.8) | ||
| II Management and Technical | 0 (0.0) | 6 (8.6) | |||
| III NM Skilled non-manual | 1 (2.7) | 1.65 (0.99, 2.77) | 3 (6.7) | 1.19 (0.86, 1.64) | |
| III M Skilled manual | 10 (8.7) |
P = 0.06, per lower band of social class |
9 (7.0) |
P = 0.30, per lower band of social class |
|
| IV Partly skilled | 2 (3.9) | 7 (17.1) | |||
| V Unskilled | 0 (0.0) | 1 (8.3) | |||
| Housing tenure | Owned/mortgaged | 9 (3.2) | Reference | 18 (6.8) | Reference |
| Rented/other | 4 (10.3) | 3.45(1.01, 11.81) P = 0.05 |
9 (17.3) | 2.88 (1.22, 6.84) P = 0.02 |
|
| Number of cars available | None | 2 (16.7) | 6 (15.0) | ||
| 1 | 9 (5.4) | 0.28 (0.10, 0.76) | 15 (7.8) | 0.64 (0.35, 1.19) | |
| 2 | 2 (1.7) | P = 0.01, per extra car | 6 (7.8) | P = 0.16, per extra car | |
| 3 | 0 (0.0) | 0 (0.0) | |||
95% CI, 95% confidence interval.
Among men, a mutually adjusted logistic regression model for frailty versus all of the variables that were significant in univariate analyses showed that the associations between frailty and age of leaving education (P = 0.58) and home ownership (P = 0.23) were attenuated. The adjusted odds ratios for frailty in relation to age (odds ratio [95% confidence interval {CI}] per year older 1.27 [0.96, 1.69], P = 0.10) and car availability (odds ratio [95% CI] per extra car 0.35 [0.11, 1.04], P = 0.06) remained sizeable, but the associations were not significant at the 5% level.
Among women, a mutually adjusted logistic regression model for frailty versus alcohol intake and home ownership demonstrated that the association with home ownership remained significant (odds ratio for frailty for not owning or mortgaging one’s home [95% CI] 2.47 [1.01, 6.03], P = 0.05), whilst the association with alcohol intake was attenuated (P = 0.10).
Finally, we analysed the associations between frailty and co-morbidities among men and women (ischaemic heart disease, stroke/TIA, high blood pressure, bronchitis, diabetes, minor trauma fracture, hand osteoarthritis and history of falling) to identify which co-morbidities should be included as adjustment factors in the analyses of frailty versus lifestyle and social factors. Ischaemic heart disease (P < 0.001), stroke/TIA (P = 0.04) and high blood pressure (P = 0.02) were associated with frailty among men, and ischaemic heart disease (P < 0.001), high blood pressure (P = 0.01) and diabetes (P = 0.05) were associated with frailty among women. The association between car availability and frailty among men was strengthened by adjustment for these significant co-morbidities (P = 0.03), but the associations between frailty and age (P = 0.14), education (P = 0.72) and home ownership (P = 0.64) were further attenuated. The association between frailty and home ownership among women was attenuated by adjustment for ischaemic heart disease, high blood pressure and diabetes (P = 0.21).
Discussion
We have shown that the prevalence of frailty, as defined by Fried, among community-dwelling young-old men and women aged 64–74 years who participated in the HCS, UK, was 8.5% for women and 4.1% for men. Among men, frailty was associated with older age, younger age of leaving full-time education, not owning or mortgaging one’s home and having fewer cars available for household use. Among women, not owning or mortgaging one’s home was associated with increased frailty. However, with the exception of reduced car availability and frailty among men, these associations were not significant (P > 0.05) after adjustment for co-morbidity. These findings, the first from a UK study, have two important implications. First, frailty is not uncommon even among young-old community-dwelling men and women in the UK. Second, there are social inequalities in frailty which appear to be largely mediated by the variety of chronic disorders and co-morbidities that occur with greater frequency among socially disadvantaged individuals. Our results identify subgroups of the population in which the burden of frailty is focused and could inform planning for the capability of health and social systems to care for increasing numbers of frail older people over time. Our results also provide some direction for where best to target initiatives and interventions which aim to reduce frailty.
Our prevalence statistics, the first to be published from a UK study, are broadly comparable with published US and European prevalence data for frailty defined by the Fried criteria (4–25% [5, 17-23]), although the relatively young age of the HCS participants has perhaps lead to a relatively low prevalence of frailty in the current study. However, our results highlight the need for increased planning of geriatric medicine services if frailty, even in this relatively young cohort, is already approaching 10% prevalence in at least one gender group. The wide variation in published frailty prevalence estimates is unsurprising owing to different: study designs and geographical locations; inclusion and exclusion criteria; gender, age and ethnicity of study participants; and variations in the implementation of the Fried criteria. However, it is perhaps of note that the prevalence found in this study was more similar to that reported by the French Three-City Study [17] and the European-wide SHARE study [23] than to that reported by the US studies.
Home ownership and car availability are useful markers of social and material advantage [30] which reflect the amount and stability of household income [31]. Our univariate findings support the argument that social factors play a role in frailty [27] and are consistent with the limited literature on social influences on frailty [5, 17, 23]. Further, our adjusted results suggest that social inequalities in frailty may be largely attributable to the variety of chronic disorders and co-morbidities that occur with greater frequency among socially disadvantaged individuals [32]. Our results identify subgroups of the population in which the burden of frailty is focused and could inform planning for the capability of health and social systems to care for increasing numbers of frail older people over time.
The observed gender difference in frailty (8.5% among women, 4.1% among men) in this study is consistent with available literature [17, 19, 23, 33] and is not unexpected given that women have lower average lean mass and strength than men [5, 34] and that older women are more likely than men to live alone with consequence for poorer nutrition, sarcopenia and frailty [34]. Other explanations for the gender difference in frailty prevalence include: differences in patterns of physical activity and physical performance, the fact that men of a given age have higher mortality rates but women have more morbidity and disability and women having lower baseline levels of muscle mass and lower levels of neuroendocrine and hormonal factors such as testosterone which may predispose them to reaching frailty [33].
This study had some limitations. Firstly, we have only considered cross-sectional relationships between lifestyle and social factors and frailty. However, follow-up of the HCS cohort is ongoing (e.g. postal and clinical follow-ups are planned and the cohort are flagged with the National Health Services Central Registry for ongoing notification of deaths) and will yield valuable longitudinal information on frailty incidence and progression. Secondly, additional information on social factors such as household income or receipt of benefits would have been useful. Thirdly, Hertfordshire is in the relatively less deprived South Eastern area of England, and we studied community-dwelling young-old men and women who might reasonably be expected to be at the less frail end of the spectrum among older people. Finally, response bias analyses (data not shown) demonstrated that baseline age, health behaviours such as smoking and social factors such as not owning one’s home or lower social class influenced likelihood of taking part in the follow-up study, although co-morbidity and frailty components such as grip strength did not. However, our analyses were internal; unless the association between e.g. home ownership and frailty is systematically different among subgroups of the population defined by health behaviours, social factors and frailty level, no major bias should have been introduced.
Our study also had many strengths. Firstly, the data were rigorously collected according to strict protocols by trained research nurses and doctors [28]. Secondly, we operationalised frailty using the accepted and objective Fried criteria [16]. Finally, we are confident that our results are generalisable to the wider population of older people in England, because the cohort have been shown to be broadly comparable with participants in the nationally representative Health Survey for England [28].
In conclusion, we have shown that frailty (operationalised by the Fried criteria) is not uncommon even among young-old community-dwelling men and women in the United Kingdom and that there are social inequalities in frailty which appear to be largely mediated by co-morbidity.
Key points.
Frailty confers a high risk for falls, disability, hospitalisation and mortality. However, research in to the prevalence of frailty and its correlates, particularly social influences, is limited.
Using data from the HCS, we have shown that frailty, defined by the Fried criteria, is not uncommon even among young-old community-dwelling men and women, aged 64-74 years, in the UK (prevalences: 8.5% women; 4.1% men).
We have demonstrated social inequalities in frailty (across levels of education, home ownership and car availability) which are largely mediated by co-morbidity.
Acknowledgments
Funding
The study was funded by the Medical Research Council and the University of Southampton. The named authors are independent of the sources of funding.
Footnotes
Conflicts of interest
None declared.
Supplementary data
Supplementary data mentioned in the text is available to subscribers at the journal website http://ageing.oxfordjournals.org.
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