Individuals with a discordant inflammatory state relative to their BMI had a higher risk of incident heart failure compared to BMI-concordant individuals (HR 1.59 in males, HR 2.03 in females).
Cohort (n=394,198)
Yes
Does cardiometabolic biomarker discordance from BMI predict incident heart failure risk in a general population?
Subclassifying BMI based on cardiometabolic biomarkers identifies individuals at varying risks of incident heart failure, highlighting the importance of metabolic health beyond BMI alone.
Hazard Ratio: 1.59 (95% CI 1.4–1.8)
BACKGROUND: Obesity is a major risk factor for heart failure (HF). However, individuals with similar body mass index (BMI), the main diagnostic measure of obesity, exhibit considerable heterogeneity in developing HF. OBJECTIVE: This study aimed to investigate the association between metabolically discordant subgroups characterized by cardiometabolic biomarkers deviated from those predicted by BMI and risk of incident HF. METHODS: Data from 394,198 participants in the UK Biobank were analyzed. A data-driven cluster approach was used to classify BMI subgroups according to cardiometabolic biomarker profiles. Incident HF during the follow-up was ascertained using the International Classification of Diseases, Tenth Revision codes. Cox proportional hazards models were applied to assess the association of the subclassified BMI with HF risk. RESULTS: Over a median follow-up of 12.3 years, 5,176 (2.94%) males and 3,602 (1.65%) females developed the first incidence of HF. Compared with participants in BMI-concordant subgroups, individuals with C-reactive protein or blood glucose deviating from the expected risk based on their BMI showed a higher risk of HF. The fully adjusted hazard ratios (95% confidence intervals) for HF in relation to discordant inflammatory state and discordant hyperglycemic status were 1.59 (1.40, 1.80) and 1.39 (1.22, 1.60) in males and 2.03 (1.77, 2.34) and 1.80 (1.53, 2.12) in females, respectively. In contrast, individuals with discordantly high blood pressure (only in females) or adverse blood lipid levels demonstrated a lower risk of HF than those in BMI-concordant subgroups. No significant association with HF was observed for discordant liver transaminase subgroups. CONCLUSIONS: Metabolically distinct BMI subgroups exhibit varying risks of HF, suggesting that subclassifying BMI based on cardiometabolic biomarkers may facilitate the precision prevention of HF.
Zhang et al. (Mon,) conducted a cohort in Heart failure (n=394,198). Cardiometabolic biomarkers deviating from BMI-predicted risk (discordant inflammatory or hyperglycemic state) vs. BMI-concordant subgroups was evaluated on Incident heart failure (HR 1.59, 95% CI 1.40-1.80). Individuals with a discordant inflammatory state relative to their BMI had a higher risk of incident heart failure compared to BMI-concordant individuals (HR 1.59 in males, HR 2.03 in females).