Evidence map›Paper›PMID 27537684›Full record

ArticlePloS one2016

Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

Shu-Yu Lin, Wei-Ju Lee, Ming-Yueh Chou, Li-Ning Peng, Shu-Ti Chiou, Liang-Kung Chen

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shu-Yu LinAging and Health Research Center, National Yang Ming University, Taipei, Taiwan.
Wei-Ju LeeAging and Health Research Center, National Yang Ming University, Taipei, Taiwan.
Ming-Yueh ChouAging and Health Research Center, National Yang Ming University, Taipei, Taiwan.
Li-Ning PengAging and Health Research Center, National Yang Ming University, Taipei, Taiwan.
Shu-Ti ChiouInstitute of Public Health, National Yang Ming University, Taipei, Taiwan.
Liang-Kung ChenAging and Health Research Center, National Yang Ming University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFrailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors.

methodsAnalytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form.

resultsDuring an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile (< 0.18), those in the uppermost tertile (> 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them.

conclusionAlthough both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

Indexed as

MortalityAgedAged, 80 and overAgingExerciseFactor Analysis, StatisticalFemaleFrail ElderlyGeriatric AssessmentHealth PromotionHealth StatusHumansKaplan-Meier EstimateMaleMiddle AgedPersonal Satisfaction

Identifiers

PMID27537684
PMCPMC4990295

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.