Evidence map›Paper›PMID 39624421›Full record

ArticleFrontiers in public health2024

Longitudinal analysis of insulin resistance and sarcopenic obesity in Chinese middle-aged and older adults: evidence from CHARLS.

Chunyan Xu, Ling He, Yansong Tu, Canhui Guo, Hurong Lai, Caifeng Liao, Chuyang Lin, Huaijun Tu

Abstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chunyan Xu *The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Ling He *The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Yansong TuFaculty of Science, The University of Melbourne, Parkville, VIC, Australia.
Canhui GuoThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Hurong LaiThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Caifeng LiaoThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Chuyang LinThe Department of Geriatrics, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Huaijun TuThe Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The correlation between surrogate insulin resistance (IR) indices and sarcopenic obesity (SO) remains uncertain. This study aimed to assess the association between six IR surrogates-triglyceride-glucose (TyG), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), triglyceride-to-high-density lipoprotein-cholesterol ratio (TG/HDL), metabolic score for insulin resistance (METS-IR), and Chinese visceral adiposity index (CVAI)-and SO risk in a middle-aged and older population in China. Methods: The study employed longitudinal data obtained from the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2015, involving 6,395 participants. We used multivariate logistic regression models to examine the link between six surrogates and SO. Nonlinear relationships were evaluated using restricted cubic spline analysis, and subgroup analyses were conducted for validation. Receiver operating characteristic (ROC) curves were used to assess predictive capabilities. Results: Over the course of a 4-year follow-up period, 319 participants (5.0%) developed SO. In the fully adjusted model, all six surrogates were significantly associated with SO. The adjusted odds ratios (ORs) with a 95% confidence interval (95% CI) per standard deviation increase were 1.21 (1.08-1.36) for TyG, 1.56 (1.39-1.75) for TyG-WC, 2.04 (1.81-2.31) for TyG-WHtR, 1.11 (1.01-1.21) for TG/HDL, 1.67 (1.50-1.87) for METS-IR, and 1.74 (1.55-1.97) for CVAI. Notably, TyG-WC, TyG-WHtR, TG/HDL, METS-IR, and CVAI exhibited nonlinear correlations with SO. Conversely, TG/HDL did not exhibit a significant association during subgroup analysis. Furthermore, TyG-WHtR had a significantly larger area under the receiver operating characteristic curve than other indices. Conclusion: The results indicated that TyG, TyG-WC, TyG-WHtR, METS-IR, and CVAI were significantly and positively associated with SO incidence. Meanwhile, TyG-WC, TyG-WHtR, METS-IR, and CVAI showed nonlinear relationships with SO. Specifically, TyG-WHtR may be the most appropriate indicator for predicting SO among middle-aged and older Chinese adults.

Indexed as

Insulin ResistanceObesitySarcopeniaAgedBlood GlucoseChinaEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedRisk FactorsTriglyceridesWaist CircumferenceBlood GlucoseTriglyceridesChina Health and Retirement Longitudinal StudyChinese middle-aged and older adultssarcopenic obesitysurrogate insulin resistance indicesTyG-waist-to-height ratio

Identifiers

PMID39624421
PMCPMC11609067

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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.