Table 1_The association of biological age and its trajectory with incident heart failure: a cohort study from China.docx

BackgroundResearch on biological age focused on the optimization and upgrading of aging clocks, which can now prospectively predict a variety of diseases. The biological age (BA) based on clinical parameters has shown predictive value for cardiovascular disease. However, evidence linking BA and its trajectories with heart failure (HF) remained limited. This study aimed to construct a clinical-parameter-based BA and to investigate its association, along with BA trajectories, with incident heart failure.
MethodsThis study utilized data from the Kailuan Study, which included 76,908 Chinese adults who underwent their first health examination between 2006 and 2007. A deep neural network model was employed to estimate BA based on 32 clinical indicators. Participants were stratified into three groups-decelerated aging, accelerated aging, and normal aging-according to their baseline BA values. Six distinct aging trajectories were subsequently identified using data from the first three follow-up examinations. Cox proportional hazard models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between aging status or BA trajectories and HF incidence.
ResultsParticipants exhibiting accelerated aging demonstrated a 30% higher risk of HF (HR: 1.30; 95%CI: 1.19–1.43) compared to those with normal aging. Conversely, those following a high-stable trajectory demonstrated the highest risk of HF (HR: 1.79; 95%CI: 1.48–2.17). Additionally, when compared to the high-stable trajectory, the high-descending trajectory was linked to a significantly lower risk of HF (HR: 0.74; 95%CI: 0.60–0.91).
ConclusionsAccelerated biological aging significantly increased the risk of HF, whereas decelerated biological aging was linked to a reduced risk of HF. Individuals who consistently exhibited a higher level of biological aging were at the greatest risk for HF.