Evidence map›Paper›PMID 41404570›Full record

Observational studyFrontiers in public health2025

U-shaped association between BMI and cognitive impairment in middle-aged and older adults with type 2 diabetes: effect modification by lifestyle and exercise.

Juan Ge, Yuqin Han, Shuzhi Peng, Shan Zhang, Limei Zheng

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in public health, 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. Article
  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

5 authors.

Juan GeCollege of Health Management, Shanghai Jian Qiao University, Shanghai, China.
Yuqin HanShanghai Fengxian District Central Hospital, Shanghai, China.
Shuzhi PengCollege of Health Management, Shanghai Jian Qiao University, Shanghai, China.
Shan ZhangShanghai Fengxian District Central Hospital, Shanghai, China.
Limei ZhengShanghai Fengxian District Central Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the correlation between body mass index (BMI) and cognitive impairment in type 2 diabetes patients through a cross-sectional observational study. Methods: Data on basic information and cognitive impairment of type 2 diabetes were collected through questionnaires, and the correlation between BMI and cognitive impairment of type 2 diabetes was analyzed using logistic regression model, restricted cubic spline (RCS) model and subgroup analysis. At the same time, the interaction between BMI and exercise, living status and other factors was tested. Results: A total of 565 valid samples were included in this study and 51.15% had cognitive impairment. The mean BMI score was 24.51 ± 2.16 kg/m Conclusion: Observations indicate that the U-shaped relationship between cognitive impairment and BMI observed in middle-aged and older adults with type 2 diabetes was more pronounced in those who live alone and are physically inactive. Although the interaction test was not significant, the subgroup analysis suggested that middle-aged and older adults with type 2 diabetes who live alone and are physically inactive may need to manage their BMI more rigorously.

Indexed as

Body Mass IndexCognitive DysfunctionDiabetes Mellitus, Type 2ExerciseLife StyleAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and Questionnairesbody mass index (BMI)cognitive impairmentcross-sectional studydiabetesnonlinear associationrestricted cubic splines (RCS)

Identifiers

PMID41404570
PMCPMC12702732

What OpenQuestion holds

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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.