TY - JOUR
T1 - Trajectories of frailty with aging
T2 - Coordinated analysis of five longitudinal studies
AU - Jenkins, Natalie D.
AU - Hoogendijk, Emiel O.
AU - Armstrong, Joshua J.
AU - Lewis, Nathan A.
AU - Ranson, Janice M.
AU - Rijnhart, Judith J.M.
AU - Ahmed, Tamer
AU - Ghachem, Ahmed
AU - Mullin, Donncha S.
AU - Ntanasi, Eva
AU - Welstead, Miles
AU - Auais, Mohammad
AU - Bennett, David A.
AU - Bandinelli, Stefania
AU - Cesari, Matteo
AU - Ferrucci, Luigi
AU - French, Simon D.
AU - Huisman, Martijn
AU - Llewellyn, David J.
AU - Scarmeas, Nikolaos
AU - Piccinin, Andrea M.
AU - Hofer, Scott M.
AU - Muniz-Terrera, Graciela
N1 - Funding Information:
This work was supported by the National Institutes of Health (P01AG043362, R01AG067621) awarded to S. M. Hofer; the Netherlands Organisation for Scientific Research ZonMw-Veni fellowship (91618067) awarded to E. O. Hoogendijk; Age UK (MR/M01311/1) awarded to M. Welstead; the Halpin Trust awarded to J. M. Ranson and D. J. Llewellyn; Alzheimer’s Research UK awarded to J. M. Ranson and D. J. Llewellyn; Mary Kinross Charitable Trust awarded to D. J. Llewellyn; the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care for the South West Peninsula awarded to D. J. Llewellyn; the National Institute on Aging/National Institutes of Health (RF1AG055654) awarded to D. J. Llewellyn; and the Alan Turing Institute under the Engineering and Physical Sciences Research Council grant (EP/N510129/1) awarded to D. J. Llewellyn.
Publisher Copyright:
© The Author(s) 2022.
PY - 2022/2/27
Y1 - 2022/2/27
N2 - Background and Objectives: There is an urgent need to better understand frailty and its predisposing factors. Although numerous cross-sectional studies have identified various risk and protective factors of frailty, there is a limited understanding of longitudinal frailty progression. Furthermore, discrepancies in the methodologies of these studies hamper comparability of results. Here, we use a coordinated analytical approach in 5 independent cohorts to evaluate longitudinal trajectories of frailty and the effect of 3 previously identified critical risk factors: sex, age, and education. Research Design and Methods: We derived a frailty index (FI) for 5 cohorts based on the accumulation of deficits approach. Four linear and quadratic growth curve models were fit in each cohort independently. Models were adjusted for sex/gender, age, years of education, and a sex/gender-by-age interaction term. Results: Models describing linear progression of frailty best fit the data. Annual increases in FI ranged from 0.002 in the Invecchiare in Chianti cohort to 0.009 in the Longitudinal Aging Study Amsterdam (LASA). Women had consistently higher levels of frailty than men in all cohorts, ranging from an increase in the mean FI in women from 0.014 in the Health and Retirement Study cohort to 0.046 in the LASA cohort. However, the associations between sex/gender and rate of frailty progression were mixed. There was significant heterogeneity in within-person trajectories of frailty about the mean curves. Discussion and Implications: Our findings of linear longitudinal increases in frailty highlight important avenues for future research. Specifically, we encourage further research to identify potential effect modifiers or groups that would benefit from targeted or personalized interventions.
AB - Background and Objectives: There is an urgent need to better understand frailty and its predisposing factors. Although numerous cross-sectional studies have identified various risk and protective factors of frailty, there is a limited understanding of longitudinal frailty progression. Furthermore, discrepancies in the methodologies of these studies hamper comparability of results. Here, we use a coordinated analytical approach in 5 independent cohorts to evaluate longitudinal trajectories of frailty and the effect of 3 previously identified critical risk factors: sex, age, and education. Research Design and Methods: We derived a frailty index (FI) for 5 cohorts based on the accumulation of deficits approach. Four linear and quadratic growth curve models were fit in each cohort independently. Models were adjusted for sex/gender, age, years of education, and a sex/gender-by-age interaction term. Results: Models describing linear progression of frailty best fit the data. Annual increases in FI ranged from 0.002 in the Invecchiare in Chianti cohort to 0.009 in the Longitudinal Aging Study Amsterdam (LASA). Women had consistently higher levels of frailty than men in all cohorts, ranging from an increase in the mean FI in women from 0.014 in the Health and Retirement Study cohort to 0.046 in the LASA cohort. However, the associations between sex/gender and rate of frailty progression were mixed. There was significant heterogeneity in within-person trajectories of frailty about the mean curves. Discussion and Implications: Our findings of linear longitudinal increases in frailty highlight important avenues for future research. Specifically, we encourage further research to identify potential effect modifiers or groups that would benefit from targeted or personalized interventions.
KW - Age-related changes
KW - Latent growth curve
KW - Longitudinal
UR - http://www.scopus.com/inward/record.url?scp=85135120927&partnerID=8YFLogxK
U2 - 10.1093/geroni/igab059
DO - 10.1093/geroni/igab059
M3 - Article
AN - SCOPUS:85135120927
SN - 2399-5300
VL - 6
JO - Innovation in Aging
JF - Innovation in Aging
IS - 2
M1 - igab059
ER -