Evidence map›Paper›PMID 38481272›Full record

ArticleBMC medicine2024

Investigating the nexus of metabolic syndrome, serum uric acid, and dementia risk: a prospective cohort study.

Tara Sr Chen, Ning-Ning Mi, Hubert Yuenhei Lao, Chen-Yu Wang, Wai Leung Ambrose Lo, Yu-Rong Mao, Yan Tang, Zhong Pei, Jin-Qiu Yuan, Dong-Feng Huang

Open access · goldAbstract read
In one paragraph

Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
5.8field-weighted citation impact, top 3% of its field
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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. 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

10 authors at 4 institutions in 2 countries.

Tara Sr Chen *Department of Rehabilitation Medicine, Guangdong Engineering and Technology Research Centre for Rehabilitation Medicine and Translation, The Seventh Affiliated Hospital, Sun Yat-Sen University, WHO Collaborating Centre for Rehabilitation CHN-50, Shenzhen, Guangdong, China.
Ning-Ning Mi *The First School of Clinical Medicine, Lanzhou University, Lanzhou, Gansu, China.
Hubert Yuenhei LaoState Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, WHO Collaborating Centre for Eye Care and Vision CHN-151, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, 510060, China.
Chen-Yu WangBrain and Mind Centre, The University of Sydney, Sydney, Australia.
Wai Leung Ambrose LoDepartment of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Yu-Rong MaoDepartment of Rehabilitation Medicine, Guangdong Engineering and Technology Research Centre for Rehabilitation Medicine and Translation, The Seventh Affiliated Hospital, Sun Yat-Sen University, WHO Collaborating Centre for Rehabilitation CHN-50, Shenzhen, Guangdong, China.
Yan TangDepartment of Rehabilitation Medicine, Guangdong Engineering and Technology Research Centre for Rehabilitation Medicine and Translation, The Seventh Affiliated Hospital, Sun Yat-Sen University, WHO Collaborating Centre for Rehabilitation CHN-50, Shenzhen, Guangdong, China.
Zhong PeiDepartment of Neurology, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, 510080, China. peizhong@mail.sysu.edu.cn.
Jin-Qiu YuanDepartment of Epidemiology and Biostatistics, Clinical Big Data Research Centre, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, Guangdong, China. yuanjq5@mail.sysu.edu.cn.
Dong-Feng HuangDepartment of Rehabilitation Medicine, Guangdong Engineering and Technology Research Centre for Rehabilitation Medicine and Translation, The Seventh Affiliated Hospital, Sun Yat-Sen University, WHO Collaborating Centre for Rehabilitation CHN-50, Shenzhen, Guangdong, China. huangdf_sysu@163.com.
Sun Yat-sen University · CNThe Seventh Affiliated Hospital of Sun Yat-sen University · CNLanzhou University · CNUniversity of Sydney · AU

Funding

5010 Planning Project of Sun Yat-sen University, China 20140001
6 · The paper itself

Abstract

backgroundThe global dementia prevalence is surging, necessitating research into contributing factors. We aimed to investigate the association between metabolic syndrome (MetS), its components, serum uric acid (SUA) levels, and dementia risk.

methodsOur prospective study comprised 466,788 participants without pre-existing MetS from the UK Biobank. We confirmed dementia diagnoses based on the ICD-10 criteria (F00-03). To evaluate the dementia risk concerning MetS, its components, and SUA levels, we applied Cox proportional hazards models, while adjusting for demographic factors.

resultsOver a median follow-up of 12.7 years, we identified 6845 dementia cases. Individuals with MetS had a 25% higher risk of all-cause dementia (hazard ratio [HR] = 1.25, 95% confidence interval [CI] = 1.19-1.31). The risk increased with the number of MetS components including central obesity, dyslipidemia for high-density lipoprotein (HDL) cholesterol, hypertension, hyperglycemia, and dyslipidemia for triglycerides. Particularly for those with all five components (HR = 1.76, 95% CI = 1.51-2.04). Dyslipidemia for HDL cholesterol, hypertension, hyperglycemia, and dyslipidemia for triglycerides were independently associated with elevated dementia risk (p < 0.01). MetS was further linked to an increased risk of all-cause dementia (11%) and vascular dementia (VD, 50%) among individuals with SUA levels exceeding 400 μmol/L (all-cause dementia: HR = 1.11, 95% CI = 1.02-1.21; VD: HR = 1.50, 95% CI = 1.28-1.77).

conclusionsOur study provides robust evidence supporting the association between MetS, its components, and dementia risk. These findings emphasize the importance of considering MetS and SUA levels in assessing dementia risk, offering valuable insights for prevention and management strategies.

Indexed as

DementiaDyslipidemiasHyperglycemiaHypertensionMetabolic SyndromeCholesterol, HDLHumansProspective StudiesRisk FactorsTriglyceridesUric AcidCholesterol, HDLTriglyceridesUric AcidAlzheimer’s dementiaDementiaMetabolic syndromeRisk factorsSerum uric acidVascular dementia

Identifiers

PMID38481272
PMCPMC10938845
OpenAlexW4392740330

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.