Evidence map›Paper›PMID 40501355›Full record

ArticleThe Journal of international medical research2025

Association between long-term changes in obesity-related anthropometric indicators and the risk of type 2 diabetes mellitus in the older population.

Xiaomin Xu, Lirong Li, Fengmei Chen, Zhirong Guo

Abstract read
In one paragraph

Article in The Journal of international medical research, 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
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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

4 authors.

Xiaomin XuDepartment of Clinical Medicine, Suzhou Vocational Health College, China.
Lirong LiDepartment of Clinical Medicine, Suzhou Vocational Health College, China.
Fengmei ChenDepartment of Public Health, Suzhou Vocational Health College, China.ORCID 0009-0000-4454-3881
Zhirong GuoDepartment of Epidemiology, School of Public Health, Soochow University, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ObjectiveTo investigate the association of long-term changes in body mass index, waist circumference, and waist-to-height ratio with the risk of type 2 diabetes mellitus in the older population.MethodsWe conducted a prospective cohort study in Jiangsu Province, China. Data from 593 participants who were aged ≥60 years were analyzed. The hazard ratios and 95% confidence intervals were estimated using the Cox proportional hazards model.ResultsOver a median follow-up period of 5.08 years, 70 participants (11.80%) developed type 2 diabetes mellitus. Compared with participants with persistently normal body mass index, waist circumference, and waist-to-height ratio, those in whom these parameters changed from normal to abnormal and those in whom these parameters were persistently abnormal had a significantly higher risk of type 2 diabetes mellitus, with adjusted hazard ratios of 2.11 (95% confidence interval: 1.05-4.26) and 2.37 (95% confidence interval: 1.21-4.63) for body mass index, 2.75 (95% confidence interval: 1.16-6.51) and 2.32 (95% confidence interval: 1.29-4.16) for waist circumference, and 2.24 (95% confidence interval: 1.14-5.91) and 4.11 (95% confidence interval: 2.21-7.68) for waist-to-height ratio, respectively.ConclusionLong-term changes in obesity-related anthropometric indicators are strongly associated with the risk of type 2 diabetes mellitus in the older population.

Indexed as

Diabetes Mellitus, Type 2ObesityAgedAnthropometryBody Mass IndexChinaFemaleFollow-Up StudiesHumansMaleMiddle AgedProportional Hazards ModelsProspective StudiesRisk FactorsWaist CircumferenceWaist-Height Ratiobody mass indexObesityolder populationtype 2 diabetes mellituswaist circumferencewaist-to-height ratio

Identifiers

PMID40501355
PMCPMC12163288

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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.