Changes in the metabolic score for insulin resistance index for risk prediction of stroke in middle-aged and older Chinese population.

Abstract

As a major noncommunicable disease, stroke poses a major threat to public health. In the context of predictive, preventative, and personalised medicine (PPPM/3PM), early identification of high-risk individuals is crucial for targeted prevention and personalised treatment for stroke. This study aimed to investigate the association between changes in the Metabolic Score for Insulin Resistance Index (METS-IR) and incident stroke. From the perspective of PPPM/3PM, we hypothesised that monitoring dynamic changes of the METs-IR levels and targeting cumulative METs-IR index contribute to risk prediction, targeted prevention, and personalised management of stroke. All data were obtained from the China Health and Retirement Longitudinal Study (CHARLS), a nationwide prospective cohort study. The individuals were categorised into four subgroups based on the quartiles (Q) of the cumulative METS-IR index as a reflection of changes in the METS-IR values from 2012 to 2015. Logistic regression was employed to examine the association between cumulative METS-IR index and stroke incidence. Additionally, restricted cubic spline regression analysis was used to assess potential linearity. Among the 4288 participants, 275 (6.4%) experienced a stroke. The risk of stroke events increased with higher cumulative METS-IR index levels. Compared with the lowest quartile (Q1), the OR of having a stroke was 1.20 (0.81, 1.78) for Q2, 1.51 (1.04, 2.21) for Q3 and 2.17 (1.52, 3.10) for the highest quartile (Q4). After adjusting for multiple potential confounders, Q4 (OR: 1.57, 95% CI: 1.04, 2.35) remained significantly associated with stroke. The association between the cumulative METS-IR index and stroke incidence was linear in males, females, and the overall population (all P values for nonlinearity > 0.05). A higher cumulative METS-IR index was associated with an increased risk of incident stroke among middle-aged and older Chinese individuals. In the context of PPPM/3PM, incorporating metabolic health into stroke risk assessment advances the prediction, prevention and personalised management of stroke. The online version contains supplementary material available at 10.1007/s13167-024-00388-y.