Evidence map›Paper›PMID 36100971›Full record

ArticleThe American journal of clinical nutrition2022

Associations of dietary diversity with the gut microbiome, fecal metabolites, and host metabolism: results from 2 prospective Chinese cohorts.

Congmei Xiao, Jia-Ting Wang, Chang Su, Zelei Miao, Jun Tang, Yifei Ouyang, Yan Yan, Zengliang Jiang, Yuanqing Fu, Menglei Shuai and 12 more

Open access · greenAbstract read
In one paragraph

Article in The American journal of clinical nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
4.5field-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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 53 citations in OpenAlex.

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  18. The gut microbiome connects nutrition and human health.Nature reviews. Gastroenterology & hepatology · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 3 institutions in 2 countries.

Congmei XiaoCollege of Life Sciences, Zhejiang University, Hangzhou, China.
Jia-Ting WangGuangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Chang SuChinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China.
Zelei MiaoKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Jun TangKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Yifei OuyangChinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China.
Yan YanGuangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Zengliang JiangKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Yuanqing FuKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.ORCID 0000-0002-3955-9376
Menglei ShuaiKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Wanglong GouKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Fengzhe XuKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Evan Y-W YuKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Yuhui LiangKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Xinxiu LiangKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Yunyi TianKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.ORCID 0000-0002-7084-5813
Jiali WangKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Feifei HuangChinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China.
Bing ZhangChinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China.
Huijun WangChinese Center for Disease Control and Prevention, National Institute for Nutrition and Health, Beijing, China.
Yu-Ming ChenGuangdong Provincial Key Laboratory of Food, Nutrition and Health; Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
Ju-Sheng ZhengKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.ORCID 0000-0001-6560-4890
Westlake University · CNChinese Center For Disease Control and Prevention · CNSun Yat-sen University · CN

Funding

UNIV OF NORTH CAROLINA CLINICAL NUTRITION RESEARCH UNITP30DK056350 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Venkata Saroja Voruganti · 1999 to 2026
$31.6M
MONITORING SOCIAL CHANGE: HEALTH, REPRODUCTION, AGINGR01HD030880 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ADAIR, LINDA S, POPKIN, BARRY M · 1994 to 2024
$27.0M
Carolina Population CenterR24HD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MORGAN, SAMUEL PHILIP · 2005 to 2014
$10.0M
Transition to a Western diet and cardiometabolic risk: biomarkers derived from the microbiomeR01DK104371 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI GORDON-LARSEN, PENNY · 2015 to 2018
$2.5M
CHILD HEALTH EFFECTS OF RAPID SOCIO-DEMOGRAPHIC CHANGER01HD038700 · NICHD · UNIVERSITY OF NORTH CAROLINA CHAPEL HILL · PI POPKIN, BARRY M · 2000 to 2004
$1.5M
NICHD NIH HHS R01 HD030880NICHD NIH HHS R01 HD038700NICHD NIH HHS R24 HD050924NIDDK NIH HHS P30 DK056350NIDDK NIH HHS R01 DK104371NIH HHS R01-HD30880
6 · The paper itself

Abstract

backgroundDietary diversity is essential for human health. The gut ecosystem provides a potential link between dietary diversity, host metabolism, and health, yet this mechanism is poorly understood.

objectivesHere, we aimed to investigate the relation between dietary diversity and the gut environment as well as host metabolism from a multiomics perspective.

methodsTwo independent longitudinal Chinese cohorts (a discovery and a validation cohort) were included in the present study. Dietary diversity was evaluated with FFQs. In the discovery cohort (n = 1916), we performed shotgun metagenomic and 16S ribosomal ribonucleic acid (rRNA) sequencing to profile the gut microbiome. We used targeted metabolomics to quantify fecal and serum metabolites. The associations between dietary diversity and the microbial composition were replicated in the validation cohort (n = 1320).

resultsDietary diversity was positively associated with α diversity of the gut microbiota. We identified dietary diversity-related gut environment features, including the microbial structure (β diversity), 68 microbial genera, 18 microbial species, 8 functional pathways, and 13 fecal metabolites. We further found 332 associations of dietary diversity and related gut environment features with circulating metabolites. Both the dietary diversity and diversity-related features were inversely correlated with 4 circulating secondary bile acids. Moreover, 16 mediation associations were observed among dietary diversity, diversity-related features, and the 4 secondary bile acids.

conclusionsThese results suggest that high dietary diversity is associated with the gut microbial environment. The identified key microbes and metabolites may serve as hypotheses to test for preventing metabolic diseases.

Indexed as

Gastrointestinal MicrobiomeBile Acids and SaltsChinaEcosystemFecesHumansProspective StudiesRNA, Ribosomal, 16SBile Acids and SaltsRNA, Ribosomal, 16Sbile acidsdietary diversitygut environmentgut microbiotahost metabolismmetabolomics

Identifiers

PMID36100971
PMCPMC9535526
OpenAlexW4295751215

What OpenQuestion holds

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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.