Abstract
BackgroundFried’s Phenotype Model of Frailty (PMF) postulates that frailty is a syndrome. Features of a syndrome are a heterogeneous population that can be split into at least two classes, those presenting and those not presenting the syndrome. Syndromes are characterized by a specific mixture of signs and symptoms which increase in prevalence, from less to more severe classes. So far, the null hypothesis of homogeneity – signs and symptoms of frailty cannot identify at least two classes – has been tested using Latent Class Analysis (LCA) on the five dichotomized components of PMF (unintentional weight loss, exhaustion, weakness, slowness, and low physical activity). The aim of this study is to investigate further the construct validity of frailty as a syndrome using the extension offered by Factor Mixture Models (FMM).MethodsLCA on dichotomized scores and FMM on continuous scores were conducted to test homogeneity on the five PMF components in a sample of 1643 community-dwelling older adults living in Québec, Canada (FRéLE).ResultsWith dichotomized LCA, three frailty classes were found: robust, prefrail and frail, and the hypothesis of homogeneity was rejected. However, in FMM, frailty was better represented as a continuous variable than as latent heterogeneous classes. Thus, the PMF measurement model of frailty did not meet the features of a syndrome in this study.ConclusionUsing the FRéLE cohort, the PMF measurement model validity is questioned. Valid measurement of a syndrome depends on an understanding of its etiological factors and pathophysiological processes, and on a modelling of how the measured components are linked to these processes. Without these features, assessing frailty in a clinical setting may not improve patient health. Research on frailty should address these issues before promoting its use in clinical settings.
Highlights
Fried’s Phenotype Model of Frailty (PMF) postulates that frailty is a syndrome
Do FRéLE and Women’s Health and Aging Studies (WHAS) results differ on Latent Class Analysis (LCA) with dichotomous representation of frailty components? Adding the frailty components that are met for each respondent, and grouping the scores in three frailty classes, frequencies of frail respondents in the WHAS, Caridiovascular Health Study (CHS) [3] and FRéLE studies (Table 1) are almost the same (11.3 to 12.0%)
Using LCA procedures with dichotomized items on the FRéLE sample, the null hypothesis of a homogeneous population was rejected, making the FRéLE sample an acceptable starting point for revisiting the 5 components Phenotype Model of Frailty (5c-PMF) even though some components were not measured in FRéLE on the same scales as the WHAS or the CHS
Summary
Fried’s Phenotype Model of Frailty (PMF) postulates that frailty is a syndrome. Features of a syndrome are a heterogeneous population that can be split into at least two classes, those presenting and those not presenting the syndrome. Syndromes are characterized by a specific mixture of signs and symptoms which increase in prevalence, from less to more severe classes. The null hypothesis of homogeneity – signs and symptoms of frailty cannot identify at least two classes – has been tested using Latent Class Analysis (LCA) on the five dichotomized components of PMF (unintentional weight loss, exhaustion, weakness, slowness, and low physical activity). The PMF 3-class model hypothesizes [2, 3] that individuals are homogeneous within each frailty class, but heterogeneous between classes. The 5c-PMF measurement model, based on a model of the cycle of frailty from which syndrome components were identified, is one of the most widely used instruments in clinical practice [4] and can be considered foundational in the biological approach to frailty. Most instruments measuring frailty were validated only as risk assessment tools [4,5,6]
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