Evidence map›Paper›PMID 39744239›Full record

ArticleFrontiers in nutrition2024

Waist-to-height ratio and body roundness index: superior predictors of insulin resistance in Chinese adults and take gender and age into consideration.

Anxiang Li, Yunwei Liu, Qi Liu, You Peng, Qingshun Liang, Yiming Tao, Yunyi Liu, Chongsong Cui, Qiqi Ren, Yingling Zhou and 4 more

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 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

14 authors.

Anxiang Li *Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Yunwei Liu *School of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
Qi LiuGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
You PengSchool of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
Qingshun LiangGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Yiming TaoGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Yunyi LiuSun Yat-sen University, Guangzhou, China.
Chongsong CuiSchool of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
Qiqi RenSchool of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
Yingling ZhouSchool of Second Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.
Jieer LongGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Guanjie FanGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Qiyun LuGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.
Zhenjie LiuGuangdong Provincial Hospital of Chinese Medicine, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: Metabolic disease has become a global health concern, and insulin resistance (IR) is a crucial underlying mechanism in various metabolic diseases. This study aims to compare the ability of seven anthropometric indicators in predicting IR in the Chinese population, and to find more sensitive and simple anthropometric indicator for early identification of IR. Methods: This prospective cross-sectional study obtained participants' medical history, anthropometric indicators, and serum samples from three hospitals in China. Various anthropometric indicators were calculated, including body mass index (BMI), Waist-to-hip ratio (WHR), waist-to-height ratio (WtHR), conicity index (CI), A Body Shape Index (ABSI), body roundness index (BRI), abdominal volume index (AVI). The evaluation of IR is performed using the homeostasis model assessment-insulin resistance (HOMA-IR). Logistic regression analysis examined the relationship between indicators and HOMA-IR. The ability of the anthropometric indicators to predict IR was analyzed using the receiver operating characteristic (ROC) curve. Additionally, a stratified analysis was performed to evaluate the ability of the indicators in different age and gender groups. Results: The study included 1,592 adult subjects, with 531 in the non-IR group and 1,061 in the IR group. After adjusting for confounding factors, the anthropometric indicators showed a positive correlation with IR in the general population and across different genders and age groups (OR > 1, Conclusion: WtHR and BRI demonstrated a better ability to predict IR in the overall study population, making them preferred indicators for screening IR, and gender and age are important considerations. In the stratified analysis of different genders or age, BMI, WtHR, BRI, and AVI are also suitable for detecting IR in women or individuals under 60 years old in this study. Clinical trial registration: www.chictr.org.cn, ChiCTR2100054654.

Indexed as

anthropometric indicatorsbody roundness indexinsulin resistanceobesityrisk predictionwaist-to-height ratio

Identifiers

PMID39744239
PMCPMC11688232

What Socratic holds

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LicenceCC BY
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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 Socratic graph.