Evidence map›Paper›PMID 38508640›Full record

ArticleBMJ open2024

Relationship between social isolation and glycaemic control of people previously diagnosed with diabetes: secondary analysis from the CHARLS.

Qiuping Lu, Liyuan Qu, Cuihua Xie, Yi Shu, Fang Gao, Mengchen Zou, Xinzhao Fan, Xiangrong Luo, Jianfu Meng, Yaoming Xue and 1 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Qiuping LuDepartment of Endocrinology, The Sixth Affiliated Hospital ,School of Medicine, South China University of Technology, Foshan City, Guangdong, China.
Liyuan QuDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Cuihua XieDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Yi ShuDepartment of Endocrinology, The Sixth Affiliated Hospital ,School of Medicine, South China University of Technology, Foshan City, Guangdong, China.
Fang GaoDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Mengchen ZouDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID 0000-0003-1409-4645
Xinzhao FanDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Xiangrong LuoDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Jianfu MengDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Yaoming XueDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Ying CaoDepartment of Endocrinology and Metabolism, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China nfcy123@126.com.ORCID 0000-0002-8129-7621
Nanfang Hospital · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSocial isolation may affect diabetes self-management. This study aimed to explore the relations between social isolation and glycaemic control in patients with diabetes and to explore lifestyle differences among individuals with different levels of social isolation.

methodsThe relevant data of 665 people previously diagnosed with diabetes included in the China Health and Retirement Longitudinal Study from 2011 to 2015 were extracted and analysed. The study included patient general information, blood glucose, lipids, glycosylated haemoglobin, social isolation index, health-related lifestyle factors and diabetes-related factors. Differences in metabolic abnormalities and modifiable lifestyles were compared among patients with varying levels of social isolation.

resultsMultiple linear regression analysis demonstrated that among men aged 45-64 years, the high social isolation group had significantly higher glycosylated haemoglobin levels compared with the low isolation group (7.29±1.81 vs 6.59±1.63, p=0.026). A positive correlation was observed between social isolation and blood glucose (β=14.16; 95% CI 2.75 to 25.57; p=0.015) and glycosylated haemoglobin (β=0.35; 95% CI 0.10 to 0.60; p=0.006), indicating that higher social isolation was associated with higher fasting blood glucose and glycosylated haemoglobin levels. However, no significant associations were observed in other age groups. Notably, men aged 45-65 years with high social isolation had higher depression rates (44.10% vs 24.60%, p=0.024), lower engagement in moderate exercise (5.70% vs 23.50%, p=0.019) and shorter 10-minute walks (17.10% vs 36.80%, p=0.027). Differences in other health-related and diabetes-related factors were not statistically significant.

conclusionMiddle-aged men with diabetes with higher social isolation tend to have higher blood glucose and glycosylated haemoglobin levels. This subset of patients requires targeted attention to provide social support from family and friends for improved glycaemic control. If necessary, education on diabetes should be made available to family members and friends.

Indexed as

Blood GlucoseDiabetes Mellitus, Type 2Glycated HemoglobinGlycemic ControlHumansLongitudinal StudiesMaleMiddle AgedSocial IsolationBlood GlucoseGlycated HemoglobinDiabetes & endocrinologyLipid disordersSocial Interaction

Identifiers

PMID38508640
PMCPMC10953297
OpenAlexW4393011533

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.