Evidence map›Paper›PMID 35230671›Full record

ArticleEating and weight disorders : EWD2022

Relationship between dietary niacin intake and diabetes mellitus in the National Health and Nutrition Examination Survey (NHANES) 2003-2018.

Pan Ke, Heng Jiang, Rowan Dowling, Lirong Zhong, Li Ke, Minzhi Xu, Chao Wang, Qingfeng Tian, Yan He, Kai Lu and 1 more

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Eating and weight disorders : EWD, 2022. 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
1.2field-weighted citation impact, top 23% 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, 11 citations in OpenAlex.

  1. Article
  2. Nutrition Information Briefs - Niacin.Advances in nutrition (Bethesda, Md.) · 2026
    Article
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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

11 authors at 6 institutions in 2 countries.

Pan KeDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China.
Heng JiangCentre for Alcohol Policy Research, School of Psychology and Public Health, La Trobe University, Melbourne, VIC, Australia.
Rowan DowlingCentre for Alcohol Policy Research, School of Psychology and Public Health, La Trobe University, Melbourne, VIC, Australia.
Lirong ZhongSchool of Public Health, Hubei University of Medicine, Shiyan, Hubei, China.
Li KeNursing of School, Hubei University of Medicine, Shiyan, Hubei, China.
Minzhi XuDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China.
Chao WangDepartment of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China.
Qingfeng TianSchool of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Yan HeSchool of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Kai Lu *Tongji Hospital, Huazhong University of Science and Technology, Wuhan, Hubei, China. 1317794983@qq.com.
Zuxun Lu *Department of Social Medicine and Health Management, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, No. 13 Hangkong Road, Wuhan, 430030, Hubei, China. zuxunlu@yahoo.com.ORCID http://orcid.org/0000-0001-8432-5109
Huazhong University of Science and Technology · CNHubei University of Medicine · CNZhengzhou University · CNHuazhong University of Science and Technology Hospital · CNLa Trobe University · AUThe University of Melbourne · AU

Funding

Australian National Health and Medical Research Council GNT1141325Australian Research Council DP200101781National Social Science Foundation of China 18ZDA085
6 · The paper itself

Abstract

purposesPrevious studies show inconsistent associations between niacin supplementation and diabetes mellitus (DM) in high-risk population, but little is known about the relationship between dietary intake of niacin and DM in the generation population. Our study aimed to explore the associations of dietary niacin intake with the risk of DM in the United States (US) adult population.

methodsThese data were derived from the National Health and Nutrition Examination Survey (NHANES) 2003-2018 of 35,606 individuals aged 20 years or older. Niacin intake and food sources were measured by two 24-h dietary recall interviews. The diagnosis of DM was established according to the American Diabetes Association (ADA) criteria. Binary logistic regression and restricted cubic spline models were applied to evaluate the association of dietary niacin intake and DM.

resultsAmong the 35,606 individuals, the prevalence of DM was 11.47%. The full-adjusted odds ratio(aOR) of DM was 1.27(95%CI 1.06-1.52) for quartile (Q) 4 v. Q1 of dietary niacin intake. In the dose-response analysis, the shape of the association of niacin intake with the risk of DM was approximately J-shaped (non-linear, p < 0.05). Energy-adjusted niacin of 26.08 mg/day was the optimal cut-off value for predicting DM.

conclusionsHigh dietary niacin intake was positively associated with DM among US adults. LEVEL OF EVIDENCE: Level V: Opinions of authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees.

Indexed as

Diabetes MellitusNiacinAdultDietEatingHumansNutritional StatusNutrition SurveysUnited StatesNiacinAmericanDiabetes mellitusEpidemiologyNational Health and Nutrition Examination SurveyNiacin

Identifiers

PMID35230671
OpenAlexW4214717754

What OpenQuestion holds

Texttitle and abstract
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.