Evidence map›Paper›PMID 41387967›Full record

ArticleNPJ science of food2025

Relationships among dietary patterns and heterogeneous biological aging at system and organ-specific levels and mortality risks.

Xinming Xu, Yucan Li, Yunxin Wang, Berty Ruping Song, Jiada Zhan, Geng Zong, Xingdong Chen, Kelin Xu, Liang Sun, Chengwu Feng and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ science of food, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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

12 authors.

Xinming Xu *Department of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
Yucan Li *State Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Yunxin WangDepartment of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
Berty Ruping SongDepartment of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
Jiada ZhanNutrition & Health Sciences Doctoral Program, Laney Graduate School, Emory University, Atlanta, GA, USA.
Geng ZongCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Xingdong ChenState Key Laboratory of Genetics and Development of Complex Phenotypes, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai, China.
Kelin XuFudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China.
Liang SunDepartment of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China.
Chengwu FengCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China. fengchengwu2018@sinh.ac.cn.
Alice H LichtensteinJean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA.
Xiang GaoDepartment of Nutrition and Food Hygiene, School of Public Health, Institute of Nutrition, Fudan University, Shanghai, China. xiang_gao@fudan.edu.cn.

Funding

Fudan University IDF201026Y and JIF201068YKey disciplines in the three-year Plan of Shanghai municipal public health system GWVI-11.1-42Ministry of Science and Technology of the People's Republic of China 2023YFC2506704National Natural Science Foundation of China 82304239National Natural Science Foundation of China 82473622Natural Science Foundation of Shanghai Municipality 23ZR1414000
6 · The paper itself

Abstract

This study utilized data from the National Health and Nutrition Examination Survey (NHANES), to train mortality prediction-based phenotypic ages (PhenoAge [systemic] and organ-specific ages [cardiovascular, kidney, liver, and musculoskeletal]) from NHANES-III, and applied it in the continuous NHANES. Weighted linear regression analyses revealed significant associations between five diet scores-Healthy Eating Index 2020, Alternate Healthy Eating Index, Dietary Approaches to Stop Hypertension, Alternate Mediterranean Diet Score, and Dietary Inflammatory Index-derived from 24-hour diet recalls and accelerations in biological ages, encompassing both phenotypic and epigenetic measures (GrimAge2 and DunedinPoAm). Reduced rank regression was used to derive five aging-related diet scores that considered food groups within each previously established score as predictors and phenotypic age accelerations as response. The strongest food predictors of favorable aging-related diet scores included dietary patterns high in vegetables, fruits and high-quality protein (dairy, fish and legumes), and low in added sugar, sugar-sweetened beverages and red/processed meat. Weighted Cox regression models revealed that aging-related diet scores were more strongly associated with mortality risk than their respective diet scores alone.

Identifiers

PMID41387967
PMCPMC12701052

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.