Evidence map›Paper›PMID 39210251›Full record

ArticleBMC geriatrics2024

Associations between type 2 diabetes mellitus and risk of falls among community-dwelling elderly people in Guangzhou, China: a prospective cohort study.

Wei-Quan Lin, Ying-Xin Liao, Jing-Ya Wang, Li-Ying Luo, Le-Xin Yuan, Si-Yu Sun, Yue Xu, Min-Ying Sun, Chang Wang, Qin Zhou and 2 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

12 authors.

Wei-Quan Lin *Department of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Ying-Xin Liao *School of Public Health, Guangzhou Medical University, Guangzhou, 511436, China.
Jing-Ya WangInstitute of Applied Health Research, University of Birmingham, Birmingham, B152TT, UK.
Li-Ying LuoDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Le-Xin YuanBrain Hospital of Guangzhou Medical University, Guangzhou Huiai Hospital, Guangzhou, 510370, China.
Si-Yu SunSchool of Public Health, Southern Medical University, Guangzhou, 510515, China.
Yue XuDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Min-Ying SunDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Chang WangDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Qin ZhouDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Xiang-Yi LiuDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China.
Hui LiuDepartment of Basic Public Health, Center for Disease Control and Prevention of Guangzhou, Guangzhou, 510440, China. gzcdc_liuhui@163.com.

Funding

Basic and Applied Research Project of Guangzhou SL2022A03J01446Basic Research Project of Key Laboratory of Guangzhou No.202102100001National Natural Science Foundation of China 72104061Science and Technology Plan Project of Guangzhou 202201010022The Key Project of Medicine Discipline of Guangzhou No.2021-2023-12The Science Technology Project of Guangzhou Municipal Health Commission 20241A011055
6 · The paper itself

Abstract

backgroundSeveral studies have demonstrated that older adults with type 2 diabetes mellitus (T2DM) have a higher risk of falls compared to those without T2DM, which may lead to disability and a lower quality of life. While, limited prospective studies have quantified the associations in southern China. We conducted a longitudinal cohort study to quantify the associations between T2DM and falls and investigate the risk factors of falls among community-dwelling elderly people in Guangzhou, China.

methodsThe population-based study included 8800 residents aged 65 and over in 11 counties of Guangzhou at baseline in 2020 and then prospectively followed up through 2022. Of 6169 participants had complete follow-up and were included in the present study. A fall event was identified by self-reported. The Cox regression was applied to quantify the associations between T2DM and falls, and hazard ratios (HRs) were calculated to the factors associated with falls among participants.

resultsThe median follow-up time for participants was 2.42 years. During the follow-up period, the incidence of falls among all participants was 21.96%. After adjusting for covariates in Cox regression models, T2DM remained a significant risk factor for falls, with HR of 1.781 (95% CI: 1.600-1.983) in the unadjusted covariates model and 1.757 (1.577-1.957) in the adjusted covariates model. Female (1.286, 1.136-1.457), older age (≥ 80: 1.448, 1.214-1.729), single marital status (1.239, 1.039-1.477), lower education level (primary school and below: 1.619, 1.004-1.361), hypertension (1.149, 1.026-1.286) and stroke (1.619, 1.176-2.228) were associated with a higher risk of falls, whereas everyday physical exercise (0.793, 0.686-0.918) was associated with a lower risk of falls.

conclusionFalls are common, with risks between T2DM and falls quantified and several factors investigated in the longitudinal cohort study among community-dwelling elderly people in Guangzhou, China. Targeted action on the risk factors may reduce the burden of falls in elderly people with T2DM in the future.

Indexed as

Accidental FallsDiabetes Mellitus, Type 2Independent LivingAgedAged, 80 and overChinaFemaleHumansIncidenceLongitudinal StudiesMaleProspective StudiesRisk FactorsElderly peopleFallsRisk factorsType 2 diabetes mellitus

Identifiers

PMID39210251
PMCPMC11363668

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.