Synergistic effects of triglyceride-glucose index and body mass index combined with depression in predicting stroke events: a study based on two national cohorts.

BACKGROUND

Stroke risk associated with the triglyceride-glucose index-body mass index (TyG-BMI) has been increasingly recognized. Depression has also been firmly established as a factor related to the development of stroke. However, there remains a research gap in evaluating the combined effect of TyG-BMI and depression on the risk of stroke. This study aims to address the inconsistency between TyG-BMI, depression, and stroke incidence.

METHODS

This study utilized longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS), involving 6,417 participants, and the National Health and Nutrition Examination Survey (NHANES) database, which included data from 17,754 participants. The analytical approach involved applying Multivariate logistic regression analysis to assess the risk of stroke with the combined evaluation of TyG-BMI and depression. Additionally, we conducted smoothing curve fitting, subgroup analysis, interaction tests, and predictive modeling for further evaluation.

RESULTS

A total of 24,171 participants from two national cohorts were included in the analysis. Among them, 1,223 individuals had a history of stroke. Compared to individuals with lower TyG-BMI and no depression, those with higher TyG-BMI and depression exhibited a significantly higher risk of stroke. The restricted cubic spline (RCS) model indicated that the combination of elevated TyG-BMI and depression had a strong predictive value for stroke occurrence.

CONCLUSION

The findings of this study suggest a positive interaction between TyG-BMI and depression in predicting stroke risk. The combined evaluation of TyG-BMI and depression should be emphasized to enhance primary prevention efforts for stroke.