Evidence map›Paper›PMID 42880123›Full record

ArticleClinics (Sao Paulo, Brazil)2026

Association between android-to-gynoid lean mass ratio and advanced cardiovascular-kidney-metabolic syndrome, and the cross-sectional association decomposition of estimated glucose disposal rate.

Ye Zhang, Rui Zhuang, Zheng Zhuo, Chaofeng Niu, Chenxi Xu, Xuetong Wang, Bing Li, Ce Wang, Lijing Zhang, Meng Li

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Article in Clinics (Sao Paulo, Brazil), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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10 authors.

Ye ZhangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Rui ZhuangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Zheng ZhuoBeijing Institute of Petrochemical Engineering, Beijing, China.
Chaofeng NiuDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Chenxi XuDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Xuetong WangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Bing LiDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Ce WangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Lijing ZhangDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China. Electronic address: dzmyyccu@163.com.
Meng LiDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China. Electronic address: 15201328277@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Android-to-Gynoid Lean Mass (LM) Ratio (AGLR) reflects the distribution of body LM and may influence the risk of advanced Cardiovascular-Kidney-Metabolic (CKM) syndrome. However, the extent to which Insulin Resistance (IR), as indicated by the estimated Glucose Disposal Rate (eGDR), explains the association between AGLR and advanced CKM syndrome remains unclear. This study aims to elucidate the relationship between AGLR and advanced CKM syndrome and to determine the contribution of eGDR to this association.

methods7,399 participants from the 2003‒2006 and 2011‒2018 cycles of the National Health and Nutrition Examination Survey (NHANES) were included in this cross-sectional study. The association between AGLR and advanced CKM syndrome was assessed using weighted Logistic Regression (LR) and subgroup analyses. The potential relationship was further examined using Restricted Cubic Splines (RCS). Sensitivity analyses were conducted to evaluate the robustness of the findings. Cross-sectional decomposition analysis was performed to quantify the contribution of eGDR to the observed associations.

resultsHigher AGLR was associated with stage 4 of CKM syndrome (OR = 1.83, 95% CI: 1.34‒2.50, p < 0.001). For stage 3, the overall trend across quartiles was not significant, indicating a less robust association. Reverse causality cannot be excluded. RCS analysis revealed a positive linear relation (p for nonlinear = 0.681). Subgroup analyses suggested that interactions were statistically insignificant across subgroups. Cross-sectional decomposition analysis showed that eGDR statistically accounted for 33.71% of the association. Notably, given shared components and the cross-sectional design, this should not be interpreted as causal mediation.

conclusionLM distribution is relevant to CKM syndrome progression. IR, as reflected by eGDR, may represent a key underlying pathological mechanism.

Indexed as

AGLRCKM SyndromeeGDRNHANESRCS

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