The relationship between METS-IR and the risk of diabetes incidence in rural adults in China: A retrospective cohort study based on dynamic population

Z Zihao Li (State Key Laboratory of Solidification Processing, Center for Nano Energy Materials, School of Materials Science and Engineering) X Xuejiao Chen W Wanli Hu G Gefei Li X Xiaoke Zhang D Datian Gao H Haiyun Gao S Songhe Shi

Abstract

Objective To evaluate the longitudinal association between the Metabolic Score for Insulin Resistance (METS-IR) and the risk of diabetes mellitus in rural Chinese adults. Methods This retrospective cohort study included 53,120 participants aged ≥18 years from 2018 to 2023. Participants were stratified by quartiles of the METS-IR metrics. Cox proportional hazards models assessed the association between METS-IR and incident diabetes. Restricted cubic spline (RCS) models examined nonlinear trends. Subgroup analysis, interaction tests, and multiple sensitivity analyses were performed. Predictive ability was evaluated using time-dependent receiver operating characteristic (ROC) curves. Results During 176,413.4 person-years of follow-up (median 3.83 years), 14,397 participants developed diabetes. After multifactorial adjustment, METS-IR was significantly and positively associated with diabetes onset (hazard ratio (HR)=1.094,95% confidence interval (CI): 1.076–1.112, P < 0.001); those in the highest quartile group had a 1.435-fold higher risk compared to the lowest. RCS analysis revealed a nonlinear dose-response relationship. Kaplan-Meier curves confirmed increasing cumulative risk with higher METS-IR. Results remained robust across subgroups and sensitivity analyses. The area under the curve (AUC) for METS-IR predicting diabetes was 0.601 (1 year), 0.586 (3 years), and 0.599 (5 years). Conclusion METS-IR is significantly correlated with the onset of diabetes, and the relationship is nonlinear. While it demonstrates limited discriminatory performance as a standalone screening tool, it remains suitable for initial risk stratification in primary health care institutions with limited resources.

Article Details

Journal PLoS ONE
Volume / Issue Vol. 21, Issue 1
Published January 28, 2026
Pages e0341612
ISSN 1932-6203
Publisher Public Library of Science

Journal Info

PLoS ONE

Public Library of Science

ISSN: 1932-6203 Open Access Health Sciences

Authors (8)

Z

Zihao Li

State Key Laboratory of Solidification Processing, Center for Nano Energy Materials, School of Materials Science and Engineering

X

Xuejiao Chen

W

Wanli Hu

G

Gefei Li

X

Xiaoke Zhang

D

Datian Gao

H

Haiyun Gao

S

Songhe Shi