Adiposity, mortality, and disease risk: insights from bioimpedance analysis and magnetic resonance imaging

A new study led by researchers from the International Agency for Research on Cancer (IARC), in collaboration with Centre Léon Bérard (Lyon, France) and the University of Regensburg (Germany), conducted an in-depth analysis of different anthropometric indicators for assessing disease risks. The research findings were published in BMC Medicine.

The study was based on data from more than 40 000 participants in the UK Biobank imaging substudy, with an average follow-up of 6.6 years. The researchers found that, compared with models based on commonly used indicators of body size such as body mass index (BMI) and waist circumference, the inclusion of organ volume indicators derived from magnetic resonance imaging (MRI) (such as the volumes of the liver, pancreas, spleen, and kidney) improved risk prediction for all-cause mortality, overall cancer, obesity-related cancer, and type 2 diabetes but not for cardiovascular diseases. The study also found that the inclusion of anthropometric indicators derived from bioelectrical impedance analysis (BIA) generally did not improve the discriminatory power compared with commonly used indicators of body size.

This study emphasizes that MRI-derived organ volume measurements may provide information beyond traditional anthropometric indicators for understanding obesity-related health risks. The research results suggest that functional and morphological changes in organs caused by excessive adiposity may be key to discriminating certain disease risks. These findings align with the emerging diagnostic framework for clinical obesity, which is defined as a chronic systemic disease characterized by functional changes in tissues and organs due to excessive adiposity, as distinguished from obesity as a phenotype characterized by excess body fat.

Gan Q, Freisling H, Peruchet-Noray L, Fontvieille E, Matta K, Zhai Y, et al.
Adiposity, mortality, and disease risk: insights from bioimpedance analysis and magnetic resonance imaging
BMC Med. Published online XX October 2025;
https://doi.org/10.1186/s12916-025-04356-9

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