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CN 34-1304/RISSN 1674-3679

Volume 29 Issue 7
Jul.  2025
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Article Contents
LI Yi, YE Bingqi, YANG Jialu, XU Qianyi, CHEN Yuliang, LEI Zekai, ZHANG Jiayu, ZHOU Xirui, LIU Yan, XIA Min. Association between accelerated aging identified by biological age and cardiometabolic diseases[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2025, 29(7): 758-764. doi: 10.16462/j.cnki.zhjbkz.2025.07.003
Citation: LI Yi, YE Bingqi, YANG Jialu, XU Qianyi, CHEN Yuliang, LEI Zekai, ZHANG Jiayu, ZHOU Xirui, LIU Yan, XIA Min. Association between accelerated aging identified by biological age and cardiometabolic diseases[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2025, 29(7): 758-764. doi: 10.16462/j.cnki.zhjbkz.2025.07.003

Association between accelerated aging identified by biological age and cardiometabolic diseases

doi: 10.16462/j.cnki.zhjbkz.2025.07.003
Funds:

National Key Research and Development Program of China 2022YFC3600600

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  • Corresponding author: XIA Min, E-mail: xiamin@mail.sysu.edu.cn
  • Received Date: 2025-03-07
  • Rev Recd Date: 2025-05-13
  • Available Online: 2025-08-11
  • Publish Date: 2025-07-10
  •   Objective  To investigate the association between biological age and the risk of cardiometabolic diseases among residents in South China, providing evidence for early risk prediction.  Methods  This study utilized baseline data (March 2018 to December 2020) from the South China Cohort. Biological age was computed using biomarkers, including alkaline phosphatase, total cholesterol, creatinine fasting glucose, systolic blood pressure, blood urea nitrogen, serum uric acid, lymphocyte percentage, mean corpuscular volume, and white blood cell count. Participants were classified into two groups: healthy aging (biological age < chronological age) and accelerated aging (biological age > chronological age). Logistic regression models were employed to evaluate the associations between biological age and the prevalence of cardiometabolic diseases. Odds ratios (ORs) with 95% CI were calculated to compare disease risks between the two groups, with age- and gender-stratified analyses conducted to address potential confounding.  Results  The study included 51 045 participants: 28 762 (56.3%) in the healthy aging group and 22 283 (43.7%) in the accelerated aging group. Logistic regression analysis using chronological age, gender, body mass index, education level, smoking and drinking as covariates showed that compared with the healthy aging group, the accelerated aging group had a significantly higher likelihood of cardiovascular disease (OR=2.38, 95% CI: 2.25-2.51), hypertension (OR=2.55, 95% CI: 2.41-2.70), stroke (OR=1.39, 95% CI: 1.14-1.71), coronary heart disease (OR=1.18, 95% CI: 1.06-1.32), and diabetes (OR=3.27, 95% CI: 3.01-3.55). Stratified analysis revealed consistently higher cardiometabolic disease risks in the accelerated aging group versus the healthy aging group across age and female.  Conclusions  Biological age effectively identifies individuals at high risk of accelerated aging and demonstrates strong associations with cardiometabolic diseases, offering a novel approach for early screening and intervention.
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