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The association of biological age and its trajectory with incident heart failure: a cohort study from China
Yuhao Hu1,2, Huayu Sun2,3,4, Chenrui Zhu2
1Hebei North University, Zhangjiakou, Hebei, China.
Insights
Accelerated biological aging increases heart failure (HF) risk, while decelerated aging reduces it. Consistently high biological age (BA) poses the greatest HF risk.
Area of Science:
- Gerontology
- Cardiovascular Medicine
- Biostatistics
Background:
- Biological age (BA) estimation using clinical parameters shows promise in predicting cardiovascular diseases.
- Limited evidence exists linking BA and its trajectories to heart failure (HF) incidence.
- This study addresses this gap by investigating the association between clinical-parameter-based BA, its trajectories, and incident HF.
Purpose of the Study:
- To develop a clinical-parameter-based biological age (BA) model.
- To examine the association between baseline BA status and incident heart failure (HF).
- To investigate the impact of different biological age trajectories on HF risk.
Main Methods:
- Utilized data from 76,908 Chinese adults in the Kailuan Study (2006-2007).
- Employed a deep neural network model to estimate BA from 32 clinical indicators.
- Analyzed baseline aging status (decelerated, accelerated, normal) and six aging trajectories using Cox proportional hazard models.
Main Results:
- Accelerated aging was associated with a 30% increased HF risk (HR: 1.30).
- A high-stable aging trajectory showed the highest HF risk (HR: 1.79).
- A high-descending trajectory was linked to a reduced HF risk compared to the high-stable trajectory (HR: 0.74).
Conclusions:
- Accelerated biological aging is a significant risk factor for heart failure (HF).
- Decelerated biological aging is associated with a reduced risk of HF.
- Individuals with consistently high biological age exhibit the highest risk for developing HF.
Background:
Research 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.
Methods:
This 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.
Results:
Participants 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).
Conclusions:
Accelerated 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.
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