Evidence map›Paper›PMID 42386741›Full record

ArticleNPJ science of food2026

BHOD: a bone health optimized dietary pattern designed for osteoporosis prevention.

Yi Zheng, Yucan Li, Yawen Gao, Xiao Liang, Jincheng Li, Chen Suo, Yanfeng Jiang, Li Jin, Kelin Xu, Xingdong Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ science of food, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yi Zheng *State Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Yucan Li *State Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Yawen GaoDepartment of Epidemiology, School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Xiao LiangState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Jincheng LiState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Chen SuoDepartment of Biostatistics, School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China.
Yanfeng JiangState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Li JinState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China.
Kelin XuDepartment of Biostatistics, School of Public Health, and the Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China. xukelin@fudan.edu.cn.ORCID http://orcid.org/0000-0002-6788-4256
Xingdong ChenState Key Laboratory of Genetics and Development of Complex Phenotypes, School of Public Health, Human Phenome Institute, and National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China. xingdongchen@fudan.edu.cn.

Funding

Brain Science and Brain-like Intelligence Technology - National Science and Technology Major Project 2022ZD0211600Natural Science Foundation of Shanghai, China 23ZR1414000the National Natural Science Foundation of China 82304239
6 · The paper itself

Abstract

Existing dietary patterns were not specifically designed to target osteoporosis and lack the precision required for effective prevention. We aimed to develop a Bone Health Optimized Diet (BHOD) that is tailored to more precisely reduce the risk of osteoporosis. Using dietary data from 183,092 UK Biobank (UKB) participants, we combined food-wide association analysis with machine learning to develop the BHOD. We identified 10 important osteoporosis-related food groups and integrated them to construct the BHOD. The protective association was observed between BHOD and the risk of osteoporosis, which was validated in both the UKB validation set and the NHANES population. Furthermore, the BHOD showed broad protective associations with other musculoskeletal disorders, such as rheumatoid arthritis and osteoarthritis. Importantly, high adherence to the BHOD mitigated the negative impact of genetic susceptibility on osteoporosis, with particularly pronounced benefits observed among individuals at high genetic risk. The multi-omics analysis identified multiple biomarkers (7 proteins, 66 metabolites, and 5 inflammatory markers) jointly associated with BHOD and osteoporosis risk, highlighting immune-inflammatory regulation and lipid metabolism as key biological pathways linking diet to bone loss.

Identifiers

PMID42386741
PMCPMC13687097

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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.