Evidence map›Paper›PMID 42697165›Full record

ArticleThe journal of nutrition, health & aging2026

Healthy ageing trajectories and incident cardiovascular disease in adults aged 50 years and older: a multi-cohort study.

Rule Du, Ruixia Niu, Yang Xu, Qian Gao, Tong Wang

Abstract read
In one paragraph

Article in The journal of nutrition, health & aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Rule DuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, Shanxi, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan, Shanxi, China.
Ruixia NiuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, Shanxi, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan, Shanxi, China.
Yang XuDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, Shanxi, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan, Shanxi, China.
Qian GaoDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, Shanxi, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan, Shanxi, China. Electronic address: gaoqian@sxmu.edu.cn.
Tong WangDepartment of Health Statistics, School of Public Health, Shanxi Medical University, 56 Xinjian South Road, Taiyuan, Shanxi, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan, Shanxi, China. Electronic address: tongwang@sxmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe dynamic patterns of healthy ageing may be an important risk factor for chronic diseases including cardiovascular disease (CVD). However, evidence remains limited.

objectiveTo identify associations between healthy ageing trajectories and incident CVD risk.

methodsThis study was based on three large longitudinal ageing cohorts: the Survey of Health, Ageing and Retirement in Europe (SHARE), the English Longitudinal Study of Ageing (ELSA), and the China Health and Retirement Longitudinal Study (CHARLS). Participants aged ≥50 years at baseline and free of CVD during the trajectory period were included. The ATHLOS healthy ageing score was derived using an item response theory model based on 41 indicators of intrinsic capacity and functional ability assessed through questionnaires and performance tests. Group-based trajectory modeling was applied to identify long-term patterns of the healthy ageing. Incident CVD was ascertained from self-reported physician diagnoses of heart disease or stroke. Cox proportional hazards models were applied to examine associations between trajectory groups and incident CVD risk, with adjustment for potential confounders.

resultsParticipants included 10,847 from SHARE (58.4% women; median age, 59.0 years), 5,611 from ELSA (55.7% women; median age, 57.0 years), and 7,238 from CHARLS (49.9% women; median age, 59.0 years), with median follow-up durations of 8, 7, and 5 years, respectively. Three declining healthy ageing trajectories (low, middle, and high) were identified in each cohort. Compared with the low trajectory group, participants in the middle trajectory group were associated with lower risks of CVD (SHARE, HR = 0.89, 95% CI: 0.77-1.02; ELSA, HR = 0.66, 95% CI: 0.53-0.82; CHARLS, HR = 0.67, 95% CI: 0.58-0.76), whereas the high trajectory group was associated with further reductions in CVD risk (SHARE, HR = 0.61, 95% CI: 0.52-0.71; ELSA, HR = 0.36, 95% CI: 0.28-0.46; CHARLS, HR = 0.39, 95% CI: 0.33-0.45). No consistent significant modifying effects of socioeconomic status (SES) or healthy lifestyle score (HLS) were observed.

conclusionHigher healthy ageing trajectories were significantly associated with lower risks of incident CVD, and this association was generally consistent across populations with different SES and HLS levels.

Indexed as

Cardiovascular diseaseHealthy ageing trajectoriesMiddle-aged and older adultsMulti-country study

Identifiers

PMID42697165
PMCPMC13572067

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.