Evidence map›Paper›PMID 42839994›Full record

ArticleFrontiers in public health2026

Longitudinal associations of dynamic transitions of multidimensional health vulnerability with cardiovascular disease risk: evidence from UK Biobank.

Jie Wu, Linlin Chen, Siyuan Sun, Yanru Jia, Tingting Hou, Yaogeng Chen, Chenglei Zhang, Jiangping Li, Yu Zhao

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Article in Frontiers in public health, 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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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

9 authors.

Jie Wu *School of Public Health, NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, Ningxia, China.
Linlin Chen *School of Public Health, NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, Ningxia, China.
Siyuan Sun *School of Public Health, NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, Ningxia, China.
Yanru JiaDepartment of Medical Laboratory, Cardiovascular and Cerebrovascular Disease Hospital, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.
Tingting HouDepartment of Medical Laboratory, Cardiovascular and Cerebrovascular Disease Hospital, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.
Yaogeng ChenSchool of Medical Information and Engineering, Ningxia Medical University, Yinchuan, Ningxia, China.
Chenglei ZhangDepartment of Medical Laboratory, Cardiovascular and Cerebrovascular Disease Hospital, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China.
Jiangping LiSchool of Public Health, NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, Ningxia, China.
Yu ZhaoSchool of Public Health, NHC Key Laboratory of Metabolic Cardiovascular Diseases Research, Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, Ningxia Medical University, Yinchuan, Ningxia, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Health vulnerability (HV), an intrinsic multidimensional construct integrating physiological, psychological, and social domains, may be associated with cardiovascular disease (CVD) risk. However, existing HV assessments lack integration and temporal dynamics change. This study identifies the dynamic association between the HV and risk of CVD. Methods: This longitudinal cohort study included 16,072 participants from the UK Biobank with HV assessments at baseline (2006-2010) and repeat assessment (2014). Latent class analysis and latent transition analysis were used to identify HV transition patterns. Cox proportional hazards models were applied to evaluate associations between HV transitions and incident CVD, with follow-up initiated from baseline assessment. Sensitivity analyses included alternative HV transitions classification, exclusion of hypertensive diseases from the composite outcome, and competing risk analyses considering non-CVD death. Results: During a median follow-up of 8.9 years, 3,033 incident CVD events were identified. Compared with persistently low vulnerability, increasing vulnerability and persistently elevated vulnerability were associated with higher CVD risk after multivariable adjustment (HR = 2.14, 95% CI: 1.74-2.63 and HR = 1.18, 95% CI: 1.08-1.29, respectively). Subgroup analyses identified significant effect modification by age and smoking status, indicating that the associations between HV transitions and CVD risk differed across these populations. The main findings remained consistent in sensitivity analyses. Conclusion: Dynamic changes in HV were associated with subsequent CVD risk, with increasing and persistently elevated vulnerability showing higher risks. These findings highlight the potential importance of monitoring multidimensional vulnerability changes for cardiovascular risk assessment.

Indexed as

Cardiovascular DiseasesVulnerable PopulationsAgedBiological Specimen BanksFemaleHeart Disease Risk FactorsHumansLongitudinal StudiesMaleMiddle AgedProportional Hazards ModelsUK BiobankUnited Kingdomcardiovascular diseasedynamic transitionshealthy aginglongitudinal cohortmultidimensional health vulnerability

Identifiers

PMID42839994
PMCPMC13638419

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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.