| Title: | The Association Between Accelerated Biological Aging and the Physical, Psychological, and Cognitive Multimorbidity and Life Expectancy: Cohort Study |
| Journal: | Aging Cell |
| Published: | 13 Jul 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40652396/ |
| DOI: | https://doi.org/10.1111/acel.70142 |
| URL: | https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/acel.70142 |
Publication 16988
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Abstract
As the global population ages, multimorbidity has become a critical public health issue. We analyzed 332,012 adults from the UK Biobank (2006-2022) to investigate the association between biological age-measured by the Klemera-Doubal method (KDM-BA) and phenotypic age (PhenoAge)-and a new comorbidity model encompassing physical, psychological, and cognitive disorders, with overall mortality outcomes over a median follow-up of 13.6 years. Logistic regression models examined the association between baseline health status and accelerated aging, while Cox proportional hazards models assessed mortality risk and disorder development. Cross-sectional analysis showed that accelerated aging was linked to higher comorbidity prevalence. Longitudinal follow-up revealed that individuals in the highest quartile (Q4) of aging speed (residual difference between estimated biological age and chronological age) had a 16%-17% higher risk of developing a single disorder, a 41%-44% higher risk of multimorbidity, and a 54% higher overall mortality risk compared with the lowest quartile (Q1). Among those with baseline single disorder, dual comorbidity, and triple morbidity, Q4 mortality risk increased by 89%-116%, 118%-166%, and 119%-156%, respectively. Multistate Markov models confirmed that accelerated aging (residual > 0) increased the risk of transitioning to disorder, comorbidity, and death by 12%-37%. Individuals aged 45 with triple comorbidity lost an average of 5.3 years in life expectancy (LE), further reduced by 5.8 to 7.0 years due to accelerated aging. This study highlights that KDM-BA and PhenoAge robustly predict multimorbidity trajectories, mortality, and shortened LE, supporting their integration into risk stratification frameworks to optimize interventions for high-risk populations.</p>
8 Authors
- Zuliyaer Talifu
- Ziyang Ren
- Chen Chen
- Shuai Guo
- Yu Wu
- Yuling Li
- Binbin Su
- Xiaoying Zheng
1 Application
| Application ID | Title |
|---|---|
| 105435 | Exploring the Attributable Risk of Multi-Omics, Genetic, Environmental, and Socio-Economic Factors on Age-Related Diseases and Their Impact |
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