Evidence map›Paper›PMID 34035089›Full record

ArticleBMJ open2021

Association between dyslipidemia and risk of type 2 diabetes mellitus in middle-aged and older Chinese adults: a secondary analysis of a nationwide cohort.

Jieru Peng, Fei Zhao, Xue Yang, Xiongfei Pan, Jue Xin, Mengjun Wu, Yong G Peng

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 3 pooled it
11.0field-weighted citation impact, top 1% 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

60 citing papers in PubMed, 3 syntheses or guidelines pooled it, 102 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

7 authors at 4 institutions in 2 countries.

Jieru Peng *Department of Medical Records Statistics, Chengdu Women and Children' s Central Hospital, School of medicine, University of Electronic Science and Technology, Chengdu, Sichuan, China.ORCID 0000-0002-2789-3019
Fei Zhao *Department of Infection Control, Sichuan University West China Second University Hospital, Chengdu, Sichuan, China.
Xue YangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiongfei PanDepartment of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China.
Jue XinDepartment of Medical Records Statistics, Chengdu Women and Children' s Central Hospital, School of medicine, University of Electronic Science and Technology, Chengdu, Sichuan, China.
Mengjun WuDepartment of Anesthesiology, Chengdu Women and Children' s Central Hospital, School of medicine, University of Electronic Science and Technology, Chengdu, Sichuan, China 397550004@qq.com.
Yong G PengDepartment of Anesthesiology, University of Florida College of Medicine, Gainesville, Florida, USA.
Chengdu Women's and Children's Central Hospital · CNSichuan University · CNTongji Hospital · CNUniversity of Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsTo evaluate the type 2 diabetes mellitus (T2DM) risk of individuals with different types of dyslipidaemia and compare the predictive value of distinct lipid parameters in predicting T2DM.

methodsWe conducted a secondary analysis of data from the China Health and Retirement Longitudinal Study (CHARLS). 17 708 individuals over 45 years old were interviewed, and 11 847 blood samples were collected at the baseline survey (2011-2012). Outcome of T2DM was confirmed during two follow-up surveys (2013-2014 and 2015-2016). The HRs and 95% CI of T2DM associated with dyslipidaemia were estimated by Cox proportional hazards regressions model. The discriminatory value of eight lipid parameters were compared by the area under the receiver operating characteristic (ROC) curve (AUC).

resultsA total of 7329 participants were enrolled in our analysis; during the mean follow-up time of 3.4 years, 387 (5.28%) participants developed new-onset diabetes. Compared with participants in normal lipid levels, the T2DM risk of those with hypercholesterolaemia, hypertriglyceridaemia and low high-density lipoprotein cholesterol (HDL-C) were significantly increased (HRs (95% CI) were 1.48 (1.11 to 1.96), 1.92 (1.49 to 2.46) and 1.67 (1.35 to 2.07), respectively). The AUCs of non-HDL-C (0.685, 95% CI 0.659 to 0.711), triglyceride (TG) (0.684, 95% CI 0.658 to 0.710), total cholesterol (TC)/HDL-C (0.685, 95% CI 0.659 to 0.712) and TG/HDL-C (0.680, 95% CI 0.654 to 0.706) were significantly (p<0.005) larger than that of other lipid parameters.

conclusionMiddle-aged and elderly adults with hypertriglyceridaemia, hypercholesterolaemia and low HDL-C were at higher risk for developing diabetes. Non-HDL-C, TG, TC/HDL and TG/HDL have greater performance than other lipid parameters in predicting T2DM incidence.

Indexed as

Diabetes Mellitus, Type 2DyslipidemiasAdultAgedChinaCholesterol, HDLHumansLongitudinal StudiesMiddle AgedRisk FactorsTriglyceridesCholesterol, HDLTriglyceridesdiabetes & endocrinologyepidemiologylipid disorders

Identifiers

PMID34035089
PMCPMC8154929
OpenAlexW3165739268

What OpenQuestion holds

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LicenceCC BY-NC
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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.