Evidence map›Paper›PMID 41044581›Full record

ArticleBMC medicine2025

Changes in accelerated aging and risk of cardiovascular disease and mortality: three cohort studies.

Ji-Juan Zhang, Han-Cheng Yu, Ting-Ting Geng, Shuo-Hua Chen, Yu-Xiang Wang, Huan Guo, Xiao-Min Zhang, Mei-An He, Jing-Li Gao, Gang Liu and 3 more

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Ji-Juan Zhang *Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Han-Cheng Yu *Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ting-Ting GengDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shuo-Hua ChenDepartment of Cardiology, Kailuan General Hospital, North China University of Science and Technology, Tangshan, China.
Yu-Xiang WangDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Huan GuoDepartment of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiao-Min ZhangDepartment of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Mei-An HeDepartment of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Jing-Li GaoDepartment of Cardiology, Kailuan General Hospital, North China University of Science and Technology, Tangshan, China.
Gang LiuDepartment of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yun-Fei Liao *Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. yunfeiliao2012@163.com.
Shou-Ling Wu *Department of Cardiology, Kailuan General Hospital, North China University of Science and Technology, Tangshan, China. drwusl@163.com.
An Pan *Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environment Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. panan@hust.edu.cn.

Funding

National Key R&D Program of China 2023YFC3606300 and 2022YFC3600600National Natural Science Foundation of China 82325043 and 82021005
6 · The paper itself

Abstract

backgroundAccelerated aging is a dynamic process, yet few studies examined the association of changes in accelerated aging with cardiovascular disease (CVD) and mortality. This study aims to evaluate this association in three prospective cohorts from China and the UK.

methodsData were drawn from the Kailuan cohort (n = 107,830), the Dongfeng-Tongji (DFTJ) cohort (n = 14,032), and the UK Biobank (n = 316,087). Accelerated aging was assessed by PhenoAge and Klemera-Doubal method (KDM) age, measured at baseline (Kailuan cohort: 2006-2009; DFTJ cohort: 2008-2010; UK Biobank: 2006-2010) and the first follow-up (Kailuan cohort: 2010-2013; DFTJ cohort: 2013; UK Biobank: 2012-2013). Changes in accelerated aging were classified as persistent accelerated aging, recovery from accelerated aging, delayed accelerated aging, and stable non-accelerated aging. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Meta-analysis was performed to summarize estimates across three cohorts.

resultsMedian follow-up periods were 10.3-15.9 years across three cohorts. When defining accelerated aging by PhenoAge, baseline accelerated aging was significantly associated with increased risks of CVD (pooled HR: 1.41, 95% CI: 1.25, 1.60) and mortality (pooled HR: 1.47, 95% CI: 1.33, 1.63). Compared to participants with persistent accelerated aging, participants recovering from accelerated aging (pooled HR of CVD: 0.76, 95% CI: 0.72, 0.81; pooled HR of mortality: 0.84, 95% CI: 0.78, 0.89), delaying accelerated aging (pooled HR of CVD: 0.75, 95% CI: 0.70, 0.79; pooled HR of mortality: 0.77, 95% CI: 0.72, 0.83) or maintaining non-accelerated aging (pooled HR of CVD: 0.59, 95% CI: 0.48, 0.71; pooled HR of mortality: 0.58, 95% CI: 0.55, 0.62) exhibited decreased risks of both CVD and mortality. When defining accelerated aging by KDM age, the results remained consistent with those of PhenoAge.

conclusionsAccelerated aging is a significant risk factor for CVD and mortality. Recovering from or delaying accelerated aging, or maintaining non-accelerated aging, was associated with reduced risks of CVD and mortality.

Indexed as

AgingAging, PrematureCardiovascular DiseasesAdultAgedChinaCohort StudiesFemaleHumansMaleMiddle AgedProportional Hazards ModelsProspective StudiesRisk FactorsUnited KingdomAccelerated agingBiological ageCardiovascular diseaseCohortMortality

Identifiers

PMID41044581
PMCPMC12495707

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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 OpenQuestion graph.