Evidence map›Paper›PMID 42774023›Full record

ArticleFrontiers in endocrinology2026

Associations of diabetes subgroups and lifestyle with incident dementia: insights from unsupervised phenotype clustering analysis.

Xuan Zhao, Kan Wang, Zhiping Tan, Siyu Wang, Xi Meng, Yu Xiang, Yueyue Wang, Xiaoyun Zhang, Hong Lin, Shuangyuan Wang and 10 more

Abstract read
In one paragraph

Article in Frontiers in endocrinology, 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

What it found

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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

20 authors.

Xuan Zhao *Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Kan Wang *Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhiping Tan *Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Siyu WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xi MengDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yu XiangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yueyue WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaoyun ZhangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hong LinDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Shuangyuan WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Mian LiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tiange WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Zhiyun ZhaoDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jie ZhengDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Min XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jieli LuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Weiqing WangDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Guang NingDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yufang BiDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yu XuDepartment of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To investigate heterogeneity in dementia risk across diabetes subgroups and examine whether lifestyle mitigates this risk. Methods: We did an unsupervised clustering analysis (self-organizing maps) in patients with diabetes from the Health and Retirement Study (HRS). Clustering variables included age at diabetes onset, body mass index (BMI), hemoglobin A1c (HbA1c), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), systolic blood pressure (SBP), estimated glomerular filtration rate (eGFR), and C-reactive protein (CRP). Healthy lifestyle factors included never smoking, low to moderate alcohol consumption, and top tertile of physical activity. Incident dementia was defined as a self-reported diagnosis or Telephone Interview for Cognitive Status (TICS) scores ≤6. Results: We included 10,705 participants (40.2% men and mean age 67.6 years) in this analysis. Three subgroups were identified among diabetes: subgroup 1 (high BMI and elevated CRP), subgroup 2 (late-onset diabetes, high blood pressure, and low eGFR), and subgroup 3 (early-onset diabetes, high HbA1c, and high cholesterol levels). Compared to normoglycemia, subgroup 3 of diabetes showed a significantly higher risk of dementia (hazard ratio [HR] 1.43, 95% confidence interval [CI] 1.15-1.77), while the other subgroups did not. However, adopting a favorable lifestyle was associated with a reduced risk of dementia in participants with normoglycemia (HR 0.70, 95% CI 0.57-0.87), prediabetes (HR 0.67, 95% CI 0.50-0.90), and subgroup 1 of diabetes (HR 0.33, 95% CI 0.14-0.79). Conclusions: Diabetes-related dementia risk is heterogeneous, and benefits of lifestyle may vary by diabetes subgroups.

Indexed as

DementiaDiabetes MellitusDiabetes Mellitus, Type 2Life StyleAgedBody Mass IndexCluster AnalysisClustering AlgorithmsFemaleGlycated HemoglobinHumansIncidenceMaleMiddle AgedPhenotypeRisk FactorsGlycated Hemoglobinclustering analysisdementiadiabetes subgroupslifestyleself-organizing maps (SOMs)

Identifiers

PMID42774023
PMCPMC13593420

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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.