Evidence map›Paper›PMID 40611180›Full record

ArticleDiabetology & metabolic syndrome2025

Cardiovascular-kidney-metabolic syndrome, systemic inflammation, and incident dementia: evidence from 400,740 UK Biobank participants.

Pingan Li, Haiping Zhang, Jianhua Ma, Jinqi Wang, Shiyun Lv, Xiaoyu Zhao, Xinghua Yang, Yanxia Luo, Xiuhua Guo, Lixin Tao and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetology & metabolic syndrome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

11 authors.

Pingan Li *Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Haiping Zhang *Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Jianhua MaDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Jinqi WangDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Shiyun LvDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Xiaoyu ZhaoDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Xinghua YangDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Yanxia LuoDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Xiuhua GuoDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China.
Lixin TaoDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China. taolixin@ccmu.edu.cn.
Bo GaoDepartment of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10 Xitoutiao, Youanmen Street, Fengtai District, Beijing, 100069, China. gaobo@ccmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough some studies examined the association of individual risk factors for cardiovascular-kidney-metabolic (CKM) syndrome (diabetes, chronic kidney disease, and stroke) with the risk of incident dementia, little is known about the impact of overall CKM health on dementia risk. This study investigated (1) the association between CKM syndrome and risk of incident dementia in 400,740 UK Biobank participants and (2) whether systemic inflammation mediated this association.

methodsThe association between CKM syndrome and the risk of dementia was assessed using Cox proportional hazards models. The mediating role of systemic inflammation markers was evaluated in 389,287 individuals.

resultsCompared with stage 0 CKM syndrome, stages 3 and 4 were significantly associated with an increased risk of dementia (hazard ratio [HR], 1.35; 95% confidence interval [CI], 1.14-1.59; HR, 1.80; 95% CI 1.57-2.07). A significant linear trend was observed between CKM syndrome stages and dementia risk. Stage 2 CKM syndrome with more than two risk factors for CKM significantly increased dementia risk (HR, 1.25; 95% CI 1.07-1.46). Advanced CKM syndrome was associated with an increased risk of dementia (HR, 1.62; 95% CI 1.53-1.71). Four systemic inflammation markers significantly mediated the association between CKM syndrome and the risk of dementia.

conclusionsHigher stages of CKM syndrome are associated with an increased risk of dementia, and systemic inflammation mediates this association. These results highlight the importance of early and comprehensive management of poor CKM health to reduce the risk of dementia.

Indexed as

Cardiovascular-kidney-metabolic syndromeDementiaRisk factorsSystemic inflammationUK Biobank

Identifiers

PMID40611180
PMCPMC12225178

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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.