Association of phase angle versus skeletal muscle mass profiling with body fat mass in relation to glycemic control in type 2 diabetes: a cross-sectional study.

Authors

Shuhei Nakanishi, Masashi Shimoda, Tomohiko Kimura, Junpei Sanada, Yoshiro Fushimi, Yuichiro Iwamoto, Masato Kubo, Ryo Inaba, Yui Okamoto, Hideyuki Iwamoto, Kohei Kaku, Hideaki Kaneto

Published in

Endocrine journal. Aug 26, 2026. Epub Aug 26, 2026.

Abstract

While preserving skeletal muscle mass (SMM) is advocated in type 2 diabetes mellitus (T2DM), mass-based assessments often overlook muscle quality. This study aimed to investigate whether the balance between cellular integrity (phase angle [PhA]) and metabolic load (body fat mass [BFM]) is more clinically relevant to glycemic control than SMM-based profiling in patients with T2DM. In this cross-sectional study of 622 patients, participants were stratified into four groups based on sex-specific medians of PhA and BFM, and similarly for SMM and BFM. Multivariate logistic regression evaluated associations with glycemic targets (HbA1c <8.0% and <7.0%), adjusting for confounders. Sensitivity analyses utilized continuous Z-scores and interaction terms. High-PhA/High-BFM and High-PhA/Low-BFM groups showed significantly higher odds of HbA1c <8.0% compared with the Low-PhA/High-BFM reference group (adjusted odds ratio [OR] 2.05, 95% confidence interval [CI] 1.22-3.44; OR 2.10, 95% CI 1.21-3.64, respectively). Conversely, SMM/BFM combinations showed no significant associations. Neither profile was significantly associated with the stricter HbA1c <7.0% target. In continuous models, the PhA × BFM interaction was significantly associated with achievement of HbA1c <8.0% (p = 0.025), whereas SMM × BFM interaction was not. In conclusion, the PhA/BFM interplay shows a clearer association with glycemic control than SMM/BFM profiling in T2DM. Higher PhA may reflect a more favorable metabolic phenotype against adiposity and is associated with a lower likelihood of severe hyperglycemia (HbA1c ≥8.0%). PhA/BFM profiling offers a novel approach to identify high-risk patients overlooked by conventional mass-based assessments.

PMID:
42649047
Bibliographic data and abstract were imported from PubMed on 27 Aug 2026.

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