Evidence map›Paper›PMID 37754214›Full record

ArticleThe journal of nutrition, health & aging2023

Transitional Dynamics of Sarcopenia and Associations of Nutritional Indices with State Transitions in Chinese aged ≥ 50.

Y Li, Q Xiang, B Dong, R Liang, Q Song, L Deng, N Ge, J Yue

Abstract read
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Article in The journal of nutrition, health & aging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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0cells of the map it votes in
5citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Y LiDr. Jirong Yue, Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, 37 GuoXue Lane, Chengdu, Sichuan 610041, P.R. China, E-mail: yuejirong11@hotmail.com; Dr. Ning Ge, Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, 37 GuoXue Lane, Chengdu, Sichuan 610041, P.R. China, E-mail: grace7733@163.com.
Q Xiang
B Dong
R Liang
Q Song
L Deng
N Ge
J Yue

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSarcopenia's temporal profile can be regarded as a dynamic process with distinct states, in which malnutrition plays an important role. This study aimed to address two research gaps: sarcopenia's transitional dynamics and associations of nutritional indices with state transitions in community-dwelling Chinese adults aged 50 and older.

designA prospective population-based cohort study.

settingCommunity-based setting in western China.

participantsThe analytic sample included data from 1910 participants aged ≥ 50 in the West China Health and Aging Trend study between 2018-2022. MEASUREMENTS: We defined three states: the initial normal state (normal muscle strength, physical performance and muscle mass), the worst sarcopenia state (low muscle mass plus low muscle strength and/or low physical performance) and the intermediate subclinical state (the other scenarios). The relevant measurement methods and cut-off points were based on the 2019 AWGS consensus. Using a continuous-time multistate Markov model, we calculated probabilities of transitions between different states over 1, 2 and 4 years; we also examined associations between nutritional indices and transitions, including body mass index (BMI), calf circumference (CC), mid-arm circumference (MAC), triceps skinfold thickness (TST), albumin (ALB), geriatric nutrition risk index (GNRI), vitamin D (VitD) and prealbumin (PA).

resultsFor individuals in the normal state, their probabilities of remaining stable versus progressing to a subclinical state were 53.4% versus 42.1% at 2 years, and 40.6% versus 49.0% at 4 years. In the subclinical population, their 2- and 4-year chances were 60.2% and 51.2% for maintaining this state, 11.8% and 16.2% for developing sarcopenia, 28.0% and 32.6% for reverting to normal. For sarcopenic individuals, the likelihood of staying stable versus retrogressing to the subclinical state were 67.0% versus 26.3% at 2 years, and 48.3% versus 36.3% at 4 years. Increased BMI, CC, MAC, TST, ALB, GNRI and PA correlated with reversion from the subclinical state, among which increased TST, ALB and PA were also paralleled with reversion from sarcopenia, while decreased BMI, CC, MAC, TST and GNRI were associated with progression to sarcopenia. VitD was not significantly associated with any transitions.

conclusionThis study reveals how sarcopenia changes over time in a Chinese population. It also highlights the usefulness of simple and cost-effective nutritional status indices for indicating state transitions, which can help identify individuals at risk of sarcopenia and guide targeted interventions within the optimal time window.

Indexed as

SarcopeniaAgedCohort StudiesHand StrengthHumansMiddle AgedMuscle StrengthNutrition AssessmentProspective Studiescontinuous-time multistate Markov modelnutritional indicesSarcopeniatransitional dynamics

Identifiers

PMID37754214
PMCPMC12275563

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LicenceCC BY-NC-ND
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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.