Evidence map›Paper›PMID 35565766›Full record

ArticleNutrients2022

Association of Serum Magnesium with Insulin Resistance and Type 2 Diabetes among Adults in China.

Weiyi Li, Yingying Jiao, Liusen Wang, Shaoshunzi Wang, Lixin Hao, Zhihong Wang, Huijun Wang, Bing Zhang, Gangqiang Ding, Hongru Jiang

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.6field-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

27 citing papers in PubMed, 37 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

10 authors at 1 institution in 1 country.

Weiyi LiOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.ORCID 0000-0002-9988-797X
Yingying JiaoOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.ORCID 0000-0003-0244-3537
Liusen WangOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Shaoshunzi WangOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Lixin HaoOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Zhihong WangOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Huijun WangOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Bing ZhangOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Gangqiang DingOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Hongru JiangOffice of National Nutrition Plan, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, 27 Nanwei Road, Beijing 100050, China.
Chinese Center For Disease Control and Prevention · CN

Funding

Active Health and Aging Technologic Solutions Major Project of National Key R&D Program No. 2020YFC2006300Carolina Population Center, the University of North Carolina at Chapel Hill 5 R24 HD050924Ministry of Finance of the People's Republic of China 13103110700015005the Fogarty International Center, National Institutes of Health 5D43TW007709 and 5D43TW009077the National Institutes of Health R01-HD30880, DK056350, R24 HD050924, R01-HD38700
6 · The paper itself

Abstract

Magnesium is an essential mineral for the human body and a cofactor or activator for more than 300 enzymatic reactions, including blood glucose control and insulin release. Diabetes is a well-known global burden of disease with increasing global prevalence. In China, the prevalence of diabetes in adults is higher than the global average. Evidence shows that magnesium is a predictor of insulin resistance and diabetes. However, the majority of studies focus on dietary magnesium instead of serum magnesium concentration. We study the correlation of serum magnesium levels with insulin resistance and Type 2 diabetes. In this prospective cohort study, we included 5044 participants aged 18 years and older without insulin resistance (IR) and diabetes at the baseline from China Health and Nutrition Survey (CHNS). A fasting blood sample was taken for the measurement of both types of magnesium, fasting blood glucose, hemoglobin A1c (HbA1c), and fasting insulin. The homeostatic model (HOMA-IR) was calculated. Demographic characteristics of participants, and risk factors such as intensity of physical activities, smoking status, drinking habit, and anthropometric information were recorded. IR was defined as HOMA-IR ≥ 2.5, and Type 2 diabetes mellitus was defined as fasting plasma glucose ≥ 7.0 mmol/L or HbA1c ≥ 6.5%, or a self-reported diagnosis or treatment of diabetes. A total of 1331 incident insulin resistance events and 429 incident diabetic events were recorded during an average follow-up of 5.8 years. The serum magnesium concentration was categorized into quintiles. After adjusting for relevant covariates, the third quintile of serum magnesium (0.89−0.93 mmol/L) was correlated with 29% lower risk of incident insulin resistance (hazard ratio = 0.71, 95% CI 0.58, 0.86) and with a lower risk of Type 2 diabetes. Multivariable-adjusted hazard ratios (95% confidence intervals) for insulin resistance were compared with the lowest quintile of serum magnesium (<0.85). We found similar results when evaluating serum magnesium as a continuous measure. Restricted cubic spline (RCS) curves showed a nonlinear dose−response correlation in both serum magnesium levels and insulin resistance, and in serum magnesium levels and Type 2 diabetes. Lower serum magnesium concentration was associated with a higher risk of insulin resistance and diabetes.

Indexed as

Diabetes Mellitus, Type 2Insulin ResistanceAdultBlood GlucoseChinaGlycated HemoglobinHumansInsulinMagnesiumProspective StudiesRisk FactorsBlood GlucoseGlycated HemoglobinInsulinMagnesiumChinadiabetesinsulin resistanceserum magnesium

Identifiers

PMID35565766
PMCPMC9104014
OpenAlexW4224929194

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.