Frailty in NHANES: Comparing the frailty index and phenotype
Introduction
Chronological age – the number of years since birth – differs from biological age – the active rate at which the body is aging (Searle, Mitnitski, Gahbauer, Gill, & Rockwood, 2008). Biological age may be better at describing quality of life, life expectancy and current level of health (Mitnitski, Graham, Mogilner, & Rockwood, 2002). The measurement of frailty could represent an assessment of biological age and thereby is a useful estimate of an individual's health status (Rockwood, 2005a, De Lepeleire et al., 2009). Frailty signifies an increased vulnerability to adverse health outcomes, reflecting an age-associated decline in multiple physiological systems (Fried et al., 2001, Rockwood and Theou, 2012, Rockwood, 2005b, Xue, 2011). The two most commonly used approaches to frailty differ, viewing frailty either as a syndrome (frailty phenotype approach) (Fried et al., 2001) or as a state (frailty index approach) (Mitnitski et al., 2002, Rockwood, 2005b). Although the frailty phenotype and frailty index have been compared (Kulminski et al., 2008, Malmstrom et al., 2014, Ravindrarajah et al., 2013, Rockwood et al., 2007, Theou et al., 2013, Woo et al., 2012), their similarities and differences are still not fully agreed upon. Many studies have demonstrated that frailty scores and characteristics from the two measures are comparable (Malmstrom et al., 2014, Woo et al., 2012, Mitnitski et al., 2011), while others have provided evidence that the frailty index can define the risk of adverse outcomes more precisely than does the phenotype (Hubbard et al., 2009, Malmstrom et al., 2014, Rockwood et al., 2007, Theou et al., 2013).
The majority of studies that compared the frailty phenotype and the frailty index have focused solely on people over the age of 65 (Theou et al., 2013, Kulminski et al., 2008, Rockwood et al., 2007, Woo et al., 2012, Mitnitski et al., 2011, Jung et al., 2014), despite emerging evidence suggesting that frailty begins much earlier than that (Rockwood, Song, & Mitnitski, 2011). Studies that have examined a younger age group have focused on a smaller sample that is not representative of the general population such as the European Male Aging Study (Ravindrarajah et al., 2013) or a the African American Health cohort (Malmstrom et al., 2014). Cesari, Gambassi, van Kan, and Vellas (2014) recently suggested that the two constructs should be considered complementary to one another rather than interchangeable and thus should not be compared. Even so, contrasting the two measures can help us understand the frailty construct, especially using data from a general population.
Fried et al. (2001) identify frailty as the presence of three or more of the five criteria: unintentional weight loss, low energy, slow gait, reduced grip strength and reduced physical activity. The frailty index (Rockwood et al., 1999) operationalizes frailty as the fraction of deficits present in an individual (Searle et al., 2008). Multiple studies have examined frailty in the National Health and Nutrition Examination Survey (NHANES), a large-scale series of cross-sectional surveys that have been used to extensively describe the health of the U.S population. The majority of these studies have followed an adapted version of the phenotype proposed by Wilhelm-Leen et al. (Bowling and Muntner, 2012, Eichholzer et al., 2013, Singh et al., 2012, Smit et al., 2012, Smit et al., 2013, Wilhelm-Leen et al., 2009, Wilhelm-Leen et al., 2010). This definition can no longer be used, as components of the phenotype were not measured in cohorts after 2002. Of note, no study has examined frailty using NHANES cohorts past 2002, suggesting that a validated adapted phenotype is necessary. Furthermore, although a frailty index is feasible, it has not yet been employed in the NHANES dataset.
This study compared two alternative measures of frailty using the NHANES data: a modified 4-item version of the frailty phenotype and a frailty index. The objectives were two-fold. First, to examine whether the frailty index and modified frailty phenotype demonstrate common characteristics in terms of distribution, mean score, sex differences in frailty scores, limit (99th percentile), relationship of frailty with age, prevalence of frailty, and second to examine the association between each definition of frailty and adverse health measures including disability, self-reported health, and healthcare utilization.
Section snippets
Sample and study design
We conducted secondary analysis of the cross-sectional data from the 2003–2004 and 2005–2006 cohorts of the United States National Health and Nutrition Examination Survey (NHANES) (CDC, 2014). This study was part of a larger study that examined the association between frailty and physical activity (Blodgett, Theou, Kirkland, Andreou, & Rockwood, 2014). Frailty was not directly measured, however frailty level could still be identified through the data available using the frailty index and
Results
Of 4874 participants over the age of 50, 4096 (mean age 63.4 ± 10.3; 53.5% women, 18.0% ADL disability) were included in this analysis. Characteristics were comparable for those who were excluded due to missing frailty data (mean age 64.6 ± 10.9, 52.3% women, 19.3% ADL disability). See Table 2 for the demographic characteristics of the sample. The distribution of scores on both frailty scales, measured as a proportion of deficits present out of total deficits possible, resembles a right skewed
Discussion
This secondary analysis of NHANES showed that the properties of both the frailty index and modified frailty phenotype were consistent with previously accepted characteristics of other frailty measures (Rockwood and Mitnitski, 2007, Theou et al., 2013) including the right skewed distribution of frailty, higher levels of frailty in women compared to men, an upper limit of deficit accumulation and an exponential increase with age. However the magnitude of these characteristics differed (e.g.
Funding
KR is supported by an operating grant from the Canadian Institutes of Health Research and receives funding from the Dalhousie Medical Research Foundation as Kathryn Allen Weldon Professor of Alzheimer Research. OT is supported by a Banting Postdoctoral Fellowship.
Conflict of interest
None.
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