Evidence map›Paper›PMID 36465637›Full record

Observational studyFrontiers in endocrinology2022

Linear and nonlinear analyses of the association between low-density lipoprotein cholesterol and diabetes: The spurious U-curve in observational study.

Yujia Ma, Zechen Zhou, Xiaoyi Li, Kexin Ding, Han Xiao, Yiqun Wu, Tao Wu, Dafang Chen

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

Observational study in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

8 authors at 1 institution in 1 country.

Yujia MaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Zechen ZhouDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Xiaoyi LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Kexin DingDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Han XiaoDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yiqun WuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Tao WuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Dafang ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. Methods: We tested the shape of association between LDL-C and diabetes and created polygenic risk scores of LDL-C and generated linear Mendelian randomization (MR) estimates for the effect of LDL-C and diabetes. We evaluated for nonlinearity in the observational and genetic relationship between LDL-C and diabetes. Results: Traditional observational analysis suggested a complex non-linear association between LDL-C and diabetes while nonlinear MR analyses found no evidence for a non-linear association. Under the assumption of linear association, we found a consistently protective effect of LDL-C against diabetes among the females without lipid-lowering drugs use. The ORs were 0.84 (95% CI, 0.72-0.97, Conclusions: We verified the liner protective effect of LDL-C against diabetes among the females without lipid-lowering drug use. Non-linear associations between LDL-C against diabetes in observational analysis are not causal.

Indexed as

Diabetes MellitusCholesterol, LDLFemaleHumansMendelian Randomization AnalysisRisk FactorsCholesterol, LDLcardiometabolic diseasediabetesfasting blood glucose (FBG)linear causal associationlow-density lipoprotein cholesterol (LDL-C)

Identifiers

PMID36465637
PMCPMC9714469
OpenAlexW4309614826

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.