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. 2026 Sep 21;13:1898248. doi: 10.3389/fcvm.2026.1898248

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© 2026 Neubauer, Freuer, Haupt, Linseisen, Meisinger and Fischer.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Conceptual regression framework showing body composition as the independent variable, arterial stiffness as the dependent variable and inflammatory markers as potential intermediate factors. Directional arrows represent the model-based regression paths: path a links body composition to inflammatory markers, path b links inflammatory markers to arterial stiffness, and path c' directly links body composition to arterial stiffness. Measured confounders are included in the regression models. The total effect c comprises the direct effect c' and the indirect effect a*b — Regression framework for the investigation of the association between body composition (visceral fat, total body fat, fat mass index, body mass index, waist circumference) and arterial stiffness (augmentation index, central pulse pressure) including inflammatory markers (tumor necrosis factor-alpha, human vascular cell adhesion molecule 1, interleukin-6) as potential intermediate factors. Measured confounders included in the models: age, sex, hypertension, heart rate, diabetes, smoking, physical activity, alcohol use disorder, LDL-cholesterol, intake antihypertensives. Arrows represent model-based regression paths. Unmeasured and residual confounding, bidirectional associations as well as reverse causation are not displayed but cannot be ruled out in this cross-sectional study design.