Dataset Information

Living Longer But Frailer? Temporal Trends in Life Expectancy and Frailty in Older Swedish Adults.

ABSTRACT:

Background

This study aims to examine temporal trends in frailty state transitions, and years spent frail, in older Swedish adults.

Methods

We followed the Swedish National Study on Aging and Care in Kungsholmen participants from baseline (2001-2004) for 15 (median: 9.6) years. A 40-deficit frailty index (FI) was constructed to identify 3 frailty states: robust (FI ≤ 0.125), mild frailty (0.125 < FI ≤ 0.25), and moderate and severe frailty (FI > 0.25). Multistate survival analyses were implemented to obtain hazard ratios (HRs) for frailty state transitions, with birth year and sex as predictors. To examine temporal trends, frailty state-specific life expectancies at age 60 were forecasted for robust persons born in different years (1900, 1910, 1920, 1930, and 1940), also by sex.

Results

At baseline, the 2 941 participants' mean age was 75 years and 65% were women. Predicted life expectancy and time spent frail from age 60 followed an increasing trend by birth year. Hazards of transitioning from mild frailty to death (HR: 0.89; 95% confidence interval [CI]: 0.83-0.97) and moderate and severe frailty to death (HR: 0.98; 95% CI: 0.97-1.00) were lower for those born later. Women were less likely to transition from robust to mild frailty (HR: 0.81; 95% CI: 0.70-0.93), mild frailty to moderate and severe frailty (HR: 0.80; 95% CI: 0.68-0.93), and moderate and severe frailty to death (HR: 0.68; 95% CI: 0.59-0.78), but spent more time frail.

Conclusions

Our results point to an expansion of time spent frail among older Swedish adults over time.

SUBMITTER: Tazzeo C

PROVIDER: S-EPMC10733192 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Living Longer But Frailer? Temporal Trends in Life Expectancy and Frailty in Older Swedish Adults.

Tazzeo Clare C Rizzuto Debora D Calderón-Larrañaga Amaia A Dekhtyar Serhiy S Zucchelli Alberto A Xia Xin X Fratiglioni Laura L Vetrano Davide Liborio DL

The journals of gerontology. Series A, Biological sciences and medical sciences 20240101 1

<h4>Background</h4>This study aims to examine temporal trends in frailty state transitions, and years spent frail, in older Swedish adults.<h4>Methods</h4>We followed the Swedish National Study on Aging and Care in Kungsholmen participants from baseline (2001-2004) for 15 (median: 9.6) years. A 40-deficit frailty index (FI) was constructed to identify 3 frailty states: robust (FI ≤ 0.125), mild frailty (0.125 < FI ≤ 0.25), and moderate and severe frailty (FI > 0.25). Multistate survival analyse ...[more]

PMID: 37725986

Similar Datasets

Project description:BackgroundThe purpose of this study was to estimate individuals' expected longevity based on self-assessed survival probabilities and determine the predictors of such subjective life expectancy in a sample of elderly people (50 years and older) in Côte d'Ivoire.MethodsPaper-based questionnaires were administered to a sample (n = 267) of older adults residing in the city of Dabou, Côte d'Ivoire in May 2017. Information on subjective expectations regarding health, comorbidities, and self-assessed survival probabilities was collected. We estimated self-assessed life expectancy and its determinants using a two-pronged approach by: (i) estimating individuals' life expectancy using the self-assessed survival probabilities (SSPs), and (ii) applying a finite mixture of regression models to form homogenous groups of individuals (clusters/components) and investigate the determinants. A spline-based approach was used to estimate the overall distribution of life expectancy for each individual using two to four points of self-assessed survival probabilities. A finite mixture of regression models was used to identify homogeneous groups of individuals (i.e. clusters/components) of the overall subjective life expectancy distribution of the study participants.ResultsThe mean subjective life expectancy in older people varied according to four components/clusters. The average subjective life expectancy among the elderly was 79.51, 78.89, 80.02, and 77.79 years in the first, second, third, and fourth component of the subjects' overall subjective life expectancy, respectively. The effect of sociodemographic characteristics, comorbidities, and lifestyle on subjective life expectancy varied across components. For instance, a U-shape relationship between household per capita income and subjective life expectancy was found for individuals classified into the third component, and an inverse U-shape relationship was found for individuals classified into the fourth component.ConclusionsWe extended the estimation of subjective life expectancy by accounting for heterogeneity in the distribution of the estimated subjective life expectancy. This approach improved the usual methods for estimating individual subjective life expectancies and may provide insight into the elderly's perception of aging, which could be used to forecast the demand for health services and long-term care needs.

Project description:ImportanceExamining life expectancy by county allows for tracking geographic disparities over time and assessing factors related to these disparities. This information is potentially useful for policy makers, clinicians, and researchers seeking to reduce disparities and increase longevity.ObjectiveTo estimate annual life tables by county from 1980 to 2014; describe trends in geographic inequalities in life expectancy and age-specific risk of death; and assess the proportion of variation in life expectancy explained by variation in socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.Design, setting, and participantsAnnual county-level life tables were constructed using small area estimation methods from deidentified death records from the National Center for Health Statistics (NCHS), and population counts from the US Census Bureau, NCHS, and the Human Mortality Database. Measures of geographic inequality in life expectancy and age-specific mortality risk were calculated. Principal component analysis and ordinary least squares regression were used to examine the county-level association between life expectancy and socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors.ExposuresCounty of residence.Main outcomes and measuresLife expectancy at birth and age-specific mortality risk.ResultsCounties were combined as needed to create stable units of analysis over the period 1980 to 2014, reducing the number of areas analyzed from 3142 to 3110. In 2014, life expectancy at birth for both sexes combined was 79.1 (95% uncertainty interval [UI], 79.0-79.1) years overall, but differed by 20.1 (95% UI, 19.1-21.3) years between the counties with the lowest and highest life expectancy. Absolute geographic inequality in life expectancy increased between 1980 and 2014. Over the same period, absolute geographic inequality in the risk of death decreased among children and adolescents, but increased among older adults. Socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors explained 60%, 74%, and 27% of county-level variation in life expectancy, respectively. Combined, these factors explained 74% of this variation. Most of the association between socioeconomic and race/ethnicity factors and life expectancy was mediated through behavioral and metabolic risk factors.Conclusions and relevanceGeographic disparities in life expectancy among US counties are large and increasing. Much of the variation in life expectancy among counties can be explained by a combination of socioeconomic and race/ethnicity factors, behavioral and metabolic risk factors, and health care factors. Policy action targeting socioeconomic factors and behavioral and metabolic risk factors may help reverse the trend of increasing disparities in life expectancy in the United States.

Dataset Information

Living Longer But Frailer? Temporal Trends in Life Expectancy and Frailty in Older Swedish Adults.

Background

Methods

Results

Conclusions

Publications

Living Longer But Frailer? Temporal Trends in Life Expectancy and Frailty in Older Swedish Adults.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets