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17 Is Phenotypical Prefrailty all the Same? A Longitudinal Investigation of Two Prefrailty Subtypes in a Population-Based Longitudinal Study of Ageing
Author(s) -
Román RomeroOrtuño,
Siobhán Scarlett,
Rose Anne Kenny
Publication year - 2019
Publication title -
age and ageing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.014
H-Index - 143
eISSN - 1468-2834
pISSN - 0002-0729
DOI - 10.1093/ageing/afz102.03
Subject(s) - gee , longitudinal study , medicine , activities of daily living , slowness , weakness , population , comorbidity , body mass index , gerontology , generalized estimating equation , physical therapy , physical medicine and rehabilitation , surgery , statistics , physics , mathematics , quantum mechanics , environmental health , pathology
Background Fried’s frailty phenotype is defined by five criteria: exhaustion, unexplained weight loss, weakness, slowness and low physical activity. Pre-frailty (PF) meets one or two criteria. PF is of interest as a target for preventative strategies, but it is not known if it is a homogenous syndrome. The objective of this study was to compare the longitudinal trajectories of two PF groups: one defined by exhaustion and/or unexplained weight loss (PF1) and one defined by one or two of the following: weakness, slowness, low physical activity (PF2). Methods: Design and setting  population-based longitudinal study of ageing. Subjects  1,660 PF participants aged ≥50 years from wave 1 of the study (2010), followed 2-yearly over 4 longitudinal waves (2012, 2014, 2016, 2018). Methods  Generalised Estimating Equations (GEE) were used to assess the effect of PF type across waves to predict cumulative mortality and disability in basic (ADL) and independent (IADL) activities of daily living, adjusting for baseline characteristics (age, sex, education, living alone, self-rated health, comorbidity, body mass index). Results In wave 1, there were 687 PF1 and 973 PF2 participants. By wave 5, 64 (9.3%) PF1 and 145 (14.9%) PF2 participants had died. In PF1 participants, mean numbers of ADL and IADL disabilities both increased from 0.2 to 0.3 from wave 1 to wave 5, whilst in PF2 increases were from 0.2 to 0.5. Adjusted GEE models suggested significantly divergent trajectories of IADL disability by wave 2, ADL disability by wave 3, and mortality by wave 4. Conclusion Prefrailty may not be a homogenous biological syndrome. This may have relevance for the design of interventions to delay or reverse frailty in populations.

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