Diabetes Obesity and Metabolism, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 28, 2025
Abstract Aims The aims of the study were to develop and validate WHOLISTIIC, a data‐driven cluster analysis for identifying anthropometric metabolic subtypes. Materials Methods K‐means was performed in 397 424 UK Biobank participants based on five domains, that is, central obesity (waist‐to‐height ratio), general (body mass index [BMI]), limb strength (handgrip strength), insulin resistance (triglyceride high‐density lipoprotein cholesterol [HDLc] ratio) inflammatory condition (neutrophil‐to‐lymphocyte ratio). Replication done NHANES. Cox proportional hazards regression models used estimate associations clusters with incident adverse health outcomes. Results Six replicable identified. Compared individuals 1 (lowest BMI preserved handgrip 2 (highest strength) not at increased risk all‐cause mortality despite higher BMI, but had small yet significant risks cardiovascular mortality, major events (MACE), chronic renal failure decreased due respiratory disease, as well dementia; 3 borderline elevated BMI), 4 triglyceride‐to‐HDLc ratio moderately 5 neutrophil‐to‐lymphocyte BMI) 6 substantially all‐cause, cardiovascular, cancer MACE failure. replicated NHANES cohort. Conclusions Anthropometric subtypes identified easily accessible parameters reflecting multifaceted pathology overweight associated distinct long‐term
Language: Английский