Evidence map›Paper›PMID 38337620›Full record

ArticleNutrients2024

Antioxidant Minerals Modified the Association between Iron and Type 2 Diabetes in a Chinese Population.

Teng Xu, Sitong Wan, Jiaxin Shi, Tiancheng Xu, Langrun Wang, Yiran Guan, Junjie Luo, Yongting Luo, Mingyue Sun, Peng An and 1 more

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
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 3 institutions in 1 country.

Teng XuCollege of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China.
Sitong WanKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.
Jiaxin ShiKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.
Tiancheng XuSchool of Food and Health, Beijing Technology & Business University, Beijing 100048, China.
Langrun WangKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.
Yiran GuanKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.
Junjie LuoKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.ORCID 0000-0002-8987-0533
Yongting LuoKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.ORCID 0000-0001-7834-8742
Mingyue SunXiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing 100091, China.
Peng AnKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.ORCID 0000-0002-0421-0035
Jingjing HeKey Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing 100190, China.
China Agricultural University · CNBeijing Technology and Business University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

Beijing Municipal Natural Science Foundation 7222111China Academy of Chinese Medical Sciences CI2021A04708Chinese Universities Scientific Fund 2020TC015National Natural Science Foundation of China 32371229;31970717;82170429
6 · The paper itself

Abstract

Inconsistent findings exist regarding the relationship between heme iron intake and type 2 diabetes (T2D) among Western and Eastern populations. Easterners tend to consume a plant-based diet which is abundant in antioxidant minerals. To examine the hypothesis that antioxidant mineral may modify the relationship between iron and T2D, we performed a case-control study by measuring the serum mineral levels in 2198 Chinese subjects. A total of 2113 T2D patients and 2458 controls were invited; 502 T2D patients and 1696 controls were finally analyzed. In the total population, high serum iron showed a positive association with T2D odds (odds ratio [OR] = 1.27 [1.04, 1.55]); high magnesium (OR = 0.18 [0.14, 0.22]), copper (OR = 0.27 [0.21, 0.33]), zinc (OR = 0.37 [0.30, 0.46]), chromium (OR = 0.61 [0.50, 0.74]), or selenium concentrations (OR = 0.39 [0.31, 0.48]) were inversely associated with T2D odds. In contrast, in individuals with higher magnesium (>2673.2 µg/dL), zinc (>136.7 µg/dL), copper (>132.1 µg/dL), chromium (>14.0 µg/dL), or selenium concentrations (>16.8 µg/dL), serum iron displayed no association with T2D (

Indexed as

Diabetes Mellitus, Type 2SeleniumAntioxidantsCase-Control StudiesChinaChromiumCopperHumansIronMagnesiumMineralsZincAntioxidantsChromiumCopperIronMagnesiumMineralsSeleniumZincantioxidant mineralmicronutrientsnutritional interventiontype 2 diabetes

Identifiers

PMID38337620
PMCPMC10857573
OpenAlexW4391174642

What OpenQuestion holds

Textmetadata
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.