Evidence mapPaperPMID 42287049Full record

ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2026

[Application of biological age for cardiovascular risk prediction in a community-based Chinese cohort].

Mengxi Lu, Binghan Wang, Jiali Kang, Qiuping Liu, Yifan Zhou, Yexiang Sun, Peng Shen, Hongbo Lin, Xun Tang, Pei Gao

Abstract readEnglish Abstract
In one paragraph

Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Mengxi LuDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Binghan WangDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Jiali KangDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Qiuping LiuDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Yifan ZhouDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Yexiang SunYinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China.
Peng ShenYinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China.
Hongbo LinYinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China.
Xun TangDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.
Pei GaoDepartment of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo independently evaluate the discrimination of the light version of biological age (Light BioAge) model for predicting all-cause mortality, to explore the association of the difference on Light BioAge and chronological age (AgeDiff) with the composite outcomes of cardiovascular disease (CVD), and to assess the performance of CVD risk prediction using the Light BioAge instead of chronological age in a large Chinese population-based cohort.

methodsParticipants aged 40-79 years without a history of CVD at baseline were drawn from the CHinese Electronic health Records Research in Yinzhou (CHERRY) study. Harrell' s concordance index (C-index) was employed to assess the discrimination of Light BioAge in predicting all-cause mortality across the overall population and sex-specific subgroups. Cox proportional hazards models were used to assess the association between AgeDiff and the composite outcome of CVD onset and death, adjusting for chronological age, sex, education, region, smoking status, body mass index, systolic blood pressure, total cholesterol, and high-density lipoprotein cholesterol. Hazard ratios (

resultsA total of 226 406 adults were included, with a mean age of 55.0 years at baseline, 53.2% of whom were women. During a median follow-up of 7.39 years (cumulative 1 562 141 person-years), 11 703 deaths (7.49 per 1 000 person-years) and 9 815 CVD events (6.30 per 1 000 person-years) occurred. The median Light BioAge and AgeDiff were 49.31 and -5.19 years, respectively, suggesting an underestimation of chronological age. Although the Light BioAge model demonstrated good discrimination for predicting all-cause mortality in the overall population (C-index: 0.742, 95%

conclusionThe discrimination of the Light BioAge in predicting all-cause mortality seems good, and a wider AgeDiff indicates higher cardiovascular risk in this large population-based Chinese cohort. Replacing chronological age with biological age in the WHO non-laboratory model significantly improved calibration for women.

Indexed as

Cardiovascular DiseasesAdultAgedAge FactorsChinaCohort StudiesEast Asian PeopleFemaleHeart Disease Risk FactorsHumansMaleMiddle AgedProportional Hazards ModelsRisk AssessmentBiological ageCardiovascular diseaseCohort studyRisk assessmentSex disparity

Identifiers

PMID42287049
PMCPMC13268843

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.