Possible sarcopenia risk and future diabetes development in Chinese adults: a 10-year prospective cohort study

Authors

Xiaodong Feng (ORCID: https://orcid.org/0000-0003-2716-1827)
Ting Dai (ORCID: https://orcid.org/0000-0002-5488-2251)
Lili Gao (ORCID: https://orcid.org/0000-0003-0627-0530)
Yan Chen
Jing Gao
Jin Huang
Jun Chen

Institutions

Henan University of Traditional Chinese Medicine (CN)
First Affiliated Hospital of Henan University (CN)
Henan Provincial Center for Disease Control and Prevention (CN)

Publication Details

Journal: BMC Public Health
Published: 2026-09-01
DOI: https://doi.org/10.1186/s12889-026-28993-8
Primary Topic: Nutrition and Health in Aging
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Possible sarcopenia risk and future diabetes development in Chinese adults: a 10-year prospective cohort study

Xiaodong Feng, Ting Dai, Lili Gao, Yan Chen et al.

Sep 1, 2026

BMC Public Health

Nutrition and Health in Aging

article

Possible sarcopenia risk and future diabetes development in Chinese adults: a 10-year prospective cohort study

Xiaodong Feng, Ting Dai, Lili Gao, Yan Chen, Jing Gao, Jin Huang, Jun Chen

September 1, 2026article en

Abstract

No abstract available for this paper.

BMC Public Health

Henan University of Traditional Chinese Medicine (CN), First Affiliated Hospital of Henan University (CN), Henan Provincial Center for Disease Control and Prevention (CN)

Openalex Percentile: Top 11%

Nutrition and Health in Aging

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.