Associations of the bioimpedance-derived phase angle with early and advanced stages of dysglycemia: Cross-sectional findings from a large population-based study.

Authors

Feiling Ai, Marie-Theres Huemer, Beate Fischer, Violetta Ptushkina, Wolfgang Rathmann, Matthias B Schulze, Henry Völzke, Anke Hannemann, Karin Halina Greiser, Thomas Keil, Lilian Krist, Justine Tanoey, Hajo Zeeb, Stefanie Jaskulski, Nadia Obi, Katharina S Weber, Wolfgang Lieb, Sabine Schipf, Marcello Ricardo Paulista Markus, Michael Leitzmann, Michael Drey, Annette Peters, Barbara Thorand

Published in

Clinical nutrition (Edinburgh, Scotland). Volume 64. Pages 106729. Jul 20, 2026. Epub Jul 20, 2026.

Abstract

Bioelectrical impedance analysis (BIA) has been widely applied for assessing body composition. The phase angle (PhA), a raw parameter derived from BIA, reflects body cell mass, cellular hydration, and cell membrane integrity. Although the PhA has been proposed as a potential marker for various aspects of diseases, its role in dysglycemia remains uncertain. We therefore aimed to investigate its associations with early and advanced stages of dysglycemia in a large population-based sample.
This cross-sectional study used data from participants (19-74 years) enrolled at the baseline assessment (2014-2019) from a large population-based cohort. The whole-body PhA at 50 kHz was obtained from multi-frequency BIA. Two samples were analyzed. In the main sample (N = 178,097), the types of known diabetes (type 1, type 2, and a history of gestational diabetes vs. no diabetes) were ascertained. Among individuals with known type 2 diabetes, data on disease duration, current treatment, glycemic control (hemoglobin A1c levels), and diabetes-related microvascular complications were further analyzed. Additionally, in a random subsample without known diabetes (N = 16,153), oral glucose tolerance tests (OGTT) were performed to ascertain early stages of glucose dysregulation (prediabetes and newly detected diabetes vs. normoglycemia). Logistic regression was applied to assess sex-specific associations of the PhA with glucose dysregulation at different stages.
In the main sample (mean age: 49.5 years; 50.1% men), 309 individuals (0.2%) reported having known type 1 diabetes, 8234 (4.6%) type 2 diabetes, and 1044 (1.2% of women) a history of gestational diabetes. In the OGTT subsample, 2662 participants (16.5%) had prediabetes and 534 (3.3%) had newly detected diabetes. A higher PhA (per 1°) was associated with a lower odds of known type 1 diabetes (relative risk ratio [RRR] and 95% confidence intervals [CIs], men: 0.33 [0.27, 0.40]; women: 0.39 [0.29, 0.52]) and known type 2 diabetes (RRR [95% CIs], men: 0.72 [0.69, 0.76]; women: 0.88 [0.81, 0.96]) after adjustment for age, lifestyle factors, obesity, and disease markers. Stronger inverse associations of the PhA with known type 2 diabetes were observed for those with longer disease duration (i.e., > 10 years), advanced-stage treatment (i.e., insulin only), poorer glycemic control (i.e., hemoglobin A1c ≥ 64 mmol/mol), or microvascular complications. Men showed stronger inverse associations with advanced dysglycemia than women (p_{sex-interaction} < 0.001). In contrast to the inverse associations observed for known type 1 and type 2 diabetes, the PhA showed positive associations with early dysglycemia. Specifically, a higher PhA (per 1°) was associated with a higher odds of a history of gestational diabetes (RRR [95% CIs]: women: 1.69 [1.51, 1.88]), prevalent prediabetes (RRR [95% CIs]: men: 1.45 [1.32, 1.59]; women: 1.34 [1.13, 1.58]) and newly detected diabetes (RRR [95% CIs]: men: 1.33 [1.11, 1.60]; women: 1.37 [1.05, 1.79]).
The bioimpedance-derived PhA showed positive cross-sectional associations with early dysglycemia and inverse cross-sectional associations with advanced dysglycemia. The observed associations may partly reflect reverse causation and disease-related changes in body composition accompanying advanced dysglycemia. Longitudinal studies are warranted to assess temporal relationships between the PhA and dysglycemia.

PMID:
42537433
Bibliographic data and abstract were imported from PubMed on 01 Aug 2026.

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