Evidence map›Paper›PMID 39668900›Full record

ArticleFrontiers in nutrition2024

Correlation of insulin resistance-related indicators and obesity-related indicators with sarcopenic obesity and development of diagnostic models: NHANES 1999-2006.

Chen Zhang, Xintao Huang, Hao Lu, Mo Chen, Junyu Wang, Huisheng Deng

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Chen Zhang *Department of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xintao Huang *Department of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Hao Lu *Department of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Mo ChenDepartment of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Junyu WangDepartment of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Huisheng DengDepartment of General Practice, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the correlation between insulin resistance and obesity indicators with sarcopenic obesity (SO) and develops diagnostic models. Utilizing the 1999-2006 National Health and Nutrition Examination Survey (NHANES) database, the research included 5,574 adults. Sarcopenic obesity was defined following the 2022 consensus by ESPEN and EASO. The study analyzed indicators such as the triglyceride-glucose index (TyG), homeostasis model assessment of insulin resistance (HOMA-IR), body roundness index (BRI), and lipid accumulation product (LAP). Results indicated a significant positive correlation between these indicators and SO, with the strongest association observed for TyG-WHtR. Predictor variables were identified through logistic and Lasso regression, including age, sex, weight-height ratio (WHtR), and TyG-WCR. The diagnostic model demonstrated good predictive performance with AUC values of 0.897 for internal validation and 0.853 for external validation. The study underscores the importance of early identification of SO patients and provides a theoretical foundation for future prevention and management strategies. Limitations include the cross-sectional study design and the potential limited generalizability of the model based on the American population.

Indexed as

diagnostic modelLassoNHANESrandom forestsarcopenic obesity

Identifiers

PMID39668900
PMCPMC11635994

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Registered trials

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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.