Evidence map›Paper›PMID 31401596›Full record

ArticleBMJ open2019

Association between normal triglyceride and insulin resistance in US adults without other risk factors: a cross-sectional study from the US National Health and Nutrition Examination Survey, 2007-2014.

Chunli Bi, Lijuan Wang, Chong Sun, Mengzi Sun, Pingping Zheng, Zhiqiang Xue, Li Shen, Pan Pan, Jiagen Li, Yaogai Lv and 5 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

10 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  3. Review
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  10. Metabolic Syndrome and Prediabetes Among Yemeni School-Aged Children.Diabetes, metabolic syndrome and obesity : targets and therapy · 2020
    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

15 authors at 1 institution in 1 country.

Chunli BiKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Lijuan WangDepartment of Neurology, The Neuroscience Center, The First Hospital of Jilin University, Jilin University First Hospital, Changchun, China.
Chong SunKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Mengzi SunKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Pingping ZhengKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Zhiqiang XueKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Li ShenKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Pan PanKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Jiagen LiKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Yaogai LvKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Anning ZhangKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Bo LiKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China.
Xinyao ZhangDepartment of Social Medicine and Health Management, Jilin University School of Public Health, Changchun, China.
Yan YaoKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China jinln@jlu.edu.cn yaoyan@jlu.edu.cn.ORCID 0000-0002-1823-3684
Lina JinKey Laboratory of Zoonosis Research & Department of Epidemiology and Biostatistics, Jilin University School of Public Health, Changchun, China jinln@jlu.edu.cn yaoyan@jlu.edu.cn.
Jilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTraditionally, the absence of insulin resistance risk factors (IRRFs) was considered a low risk for insulin resistance (IR). However, IR also existed in certain individuals without IRRFs; thus this study aims to explore predictors of IR targeted at the population without IRRFs.

designCross-sectional survey.

settingNational Health and Nutrition Examination Survey.

participantsParticipants without regular IRRFs (IRRF-Free, n=2478) and a subgroup without optimal IRRFs (IRRF-Optimal, n=1414) were involved in this study. PRIMARY AND SECONDARY OUTCOME MEASURE: IRRFs and the optimal cut-off value of triglyceride (TG) to predict IR.

resultsOverall, the prevalence of IR was 6.9% and 5.7% in the IRRF-Free group and the IRRF-Optimal group, respectively. TG and waist circumference were independently associated with the prevalence of IR in both the groups (OR=1.010 to 10.20; p<0.05 for all), where TG was positively associated with IR. The area under the receiver operating characteristic curve of TG was 0.7016 (95% CI: 0.7013 to 0.7018) and 0.7219 (95% CI: 0.7215 to 0.7222), and the optimal cut-off value of TG to predict IR was 79.5 mg/dL and 81.5 mg/dL in the IRRF-Free group and the IRRF-Optimal group, respectively.

conclusionThere is an association between TG and IR even in the normal range of TG concentration. Therefore, normal TG could be used as an important indicator to predict the prevalence of IR in the absence of IRRFs.

Indexed as

Insulin ResistanceAdultCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedNutrition SurveysPrevalenceRisk FactorsROC CurveTriglyceridesUnited StatesTriglyceridesinsulin resistanceNHANESrisk factorsROC curvetriglyceride

Identifiers

PMID31401596
PMCPMC6701626
OpenAlexW2968042804

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.