Dataset Information

Longitudinal Quantiles of Frailty Trajectories Considering Death: New Insights into Sex and Cohort Differences in the Reference Curves for Frailty Progression of Older European.

ABSTRACT:

Background

Most previous studies of frailty trajectories in older adults focus on the average trajectory and ignore death. Longitudinal quantile analysis of frailty trajectories permits the definition of reference curves, and the application of mortal cohort inference provides more realistic estimates than models that ignore death.

Methods

Using data from individuals aged 65 or older (n = 25 446) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) from 2004 to 2020, we derived repeated values of the Frailty Index (FI) based on the accumulation of health deficits. We applied weighted Generalized Estimating Equations to estimate the quantiles of the FI trajectory, adjusting for sample attrition due to death, sex, education, and cohort.

Results

The FI quantiles increased with age and progressed faster for those with the highest level of frailty (β^a0.9 = 0.0229, p < .001; β^a0.5 = 0.0067, p < .001; H0: βa0.5=βa0.9, p < .001). Education was consistently associated with a slower progression of the FI in all quantiles (β^ae0.1 = -0.0001, p < .001; β^ae0.5 =-0.0004, p < .001; β^ae0.9 = -0.0003, p < .001) but sex differences varied across the quantiles. Women with the highest level of frailty showed a slower progression of the FI than men when considering death. Finally, no cohort effects were observed for the FI progression.

Conclusions

Quantile FI trajectories varied by age, sex, education, and cohort. These differences could inform the practice of interventions aimed at older adults with the highest level of frailty.

SUBMITTER: Marroig A

PROVIDER: S-EPMC10965030 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Longitudinal Quantiles of Frailty Trajectories Considering Death: New Insights into Sex and Cohort Differences in the Reference Curves for Frailty Progression of Older European.

Marroig Alejandra A Massa Fernando F Robitaille Annie A Hofer Scott M SM Stolz Erwin E Muniz-Terrera Graciela G

The journals of gerontology. Series A, Biological sciences and medical sciences 20240401 4

<h4>Background</h4>Most previous studies of frailty trajectories in older adults focus on the average trajectory and ignore death. Longitudinal quantile analysis of frailty trajectories permits the definition of reference curves, and the application of mortal cohort inference provides more realistic estimates than models that ignore death.<h4>Methods</h4>Using data from individuals aged 65 or older (n = 25 446) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) from 2004 to 2020 ...[more]

PMID: 38394173

Similar Datasets

Project description:BackgroundTimely recognition of the end of life allows patients to discuss preferences and make advance plans, and clinicians to introduce appropriate care. We examined changes in frailty over 1 year, with the aim of identifying trajectories that could indicate where an individual is at increased risk of all-cause mortality and may require palliative care.MethodsElectronic health records from 13,149 adults (cases) age 75 and over who died during a 1-year period (1 January 2015 to 1 January 2016) were age, sex and general practice matched to 13,149 individuals with no record of death over the same period (controls). Monthly frailty scores were obtained for 1 year prior to death for cases, and from 1 January 2015 to 1 January 2016 for controls using the electronic frailty index (eFI; a cumulative deficit measure of frailty, available in most English primary care electronic health records, and ranging in value from 0 to 1). Latent growth mixture models were used to investigate longitudinal patterns of change and associated impact on mortality. Cases were reweighted to the population level for tests of diagnostic accuracy.ResultsThree distinct frailty trajectories were identified. Rapidly rising frailty (initial increase of 0.022 eFI per month before slowing from a baseline eFI of 0.21) was associated with a 180% increase in mortality (OR 2.84, 95% CI 2.34-3.45) for 2.2% of the sample. Moderately increasing frailty (eFI increase of 0.007 per month, with baseline of 0.26) was associated with a 65% increase in mortality (OR 1.65, 95% CI 1.54-1.76) for 21.2% of the sample. The largest (76.6%) class was stable frailty (eFI increase of 0.001 from a baseline of 0.26). When cases were reweighted to population level, rapidly rising frailty had 99.1% specificity and 3.2% sensitivity (positive predictive value 19.8%, negative predictive value 93.3%) for predicting individual risk of mortality.ConclusionsPeople aged over 75 with frailty who are at highest risk of death have a distinctive frailty trajectory in the last 12 months of life, with a rapid initial rise from a low baseline, followed by a plateau. Routine measurement of frailty can be useful to support clinicians to identify people with frailty who are potential candidates for palliative care, and allow time for intervention.

Dataset Information

Longitudinal Quantiles of Frailty Trajectories Considering Death: New Insights into Sex and Cohort Differences in the Reference Curves for Frailty Progression of Older European.

Background

Methods

Results

Conclusions

Publications

Longitudinal Quantiles of Frailty Trajectories Considering Death: New Insights into Sex and Cohort Differences in the Reference Curves for Frailty Progression of Older European.

Similar Datasets

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