Evidence map›Paper›PMID 39683559›Full record

ArticleNutrients2024

The Mediating Role of Body Mass Index in the Association Between Dietary Index for Gut Microbiota and Biological Age: A Study Based on NHANES 2007-2018.

Shuli An, Jian Qin, Xinjie Gong, Shuangshuang Li, Haiyan Ding, Xue Zhao, Hongqi He, Linwei Zhou, Xinrui Deng, Xia Chu

Abstract 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 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–field-weighted citation impact
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

33 citing papers in PubMed.

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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.

Shuli AnDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Jian QinDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Xinjie GongDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Shuangshuang LiDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Haiyan DingDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Xue ZhaoDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Hongqi HeDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Linwei ZhouDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.
Xinrui DengCollege of Food Science, Northeast Agricultural University, Harbin 150030, China.ORCID 0000-0002-4922-7711
Xia ChuDepartment of Nutrition and Food Hygiene, School of Public Health, Key Laboratory of Precision Nutrition and Health, Ministry of Education, Harbin Medical University, Harbin 150081, China.

Funding

The Postgraduate Research & Practice Innovation Program of Harbin Medical University YJSCX2023-134HYD
6 · The paper itself

Abstract

objectiveThe dietary index for gut microbiota (DI-GM) is a newly proposed metric for assessing diet quality, and its relationship with biological age is unclear. We hypothesize that consuming foods conducive to a healthy gut microbiota environment may decelerate aging.

methodsThis cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2007 to 2018. The DI-GM was calculated by averaging the intakes from two 24-h dietary recall interviews. The biological age indicators were assessed using the Klemera-Doubal Method (KDM), phenotypic age (PA), and homeostasis disorder (HD). Logistic regression, restricted cubic splines (RCS), and mediation analysis were employed to explore the association between DI-GM and KDM, PA, and HD.

resultsThe study included 20,671 participants. According to the logistic regression model, adjusting for all covariates, a negative association was observed between the DI-GM score and biomarkers of biological aging. Compared to participants in the lowest quartile for DI-GM scores, those in the highest quartile exhibited reduced odds ratio (OR) for all of the biological age indicators, namely biological age assessed via KDM (OR: 0.69, 95% CI: 0.60-0.79), PA (OR: 0.84, 95% CI: 0.73-0.97), and HD (OR: 0.86, 95% CI: 0.76-0.98). Additionally, RCS analysis revealed a nonlinear association between DI-GM and biological age. Mediation analysis showed that the body mass index (BMI) partly mediated the association between DI-GM and biological age.

conclusionsTherefore, we concluded that a higher DI-GM score is associated with a lower risk of accelerated aging, with BMI mediating this association. Future research should validate these findings through the use of longitudinal studies.

Indexed as

AgingBody Mass IndexDietGastrointestinal MicrobiomeNutrition SurveysAdultAgedCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle Agedbiological agebody mass indexdietgut microbiotamediationNHANES

Identifiers

PMID39683559
PMCPMC11643866

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.