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Explore the U-shape between the stress hyperglycemia ratio and diabetes or prediabetes with depressive symptoms in United States adults: insights in NHANES 2005–2018

Mingzhu Wang,Chengchao Peng,Tingting Jiang,Danping Li,Chong Lu,Min Lu

Published 2025 in Diabetology & Metabolic Syndrome

ABSTRACT

Diabetes is a prevalent health problem worldwide, depression is a common psychological complication in diabetics, and studies have now confirmed that diabetes with depressive symptoms is associated with blood glucose levels. Stress hyperglycemic ratio (SHR) can reflect the collective transient elevation of blood glucose during acute stress. Meanwhile, the Triglyceride-Glucose (TyG) Index, a surrogate marker of insulin resistance, is associated with long-term metabolic dysfunction. This study explores and compares the predictive value of SHR and TyG in diabetes with depressive symptoms among adult Americans, aiming to provide insights into their clinical and metabolic implications. This is a cross-sectional study of adult participants from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. SHR values were calculated from fasting glucose (FPG) and glycosylated hemoglobin (HbA1c) measurements using a specific formula. The Triglyceride-Glucose (TyG) index is calculated as the natural logarithm of the product of fasting plasma glucose and triglyceride levels, divided by two, and is used as a marker of insulin resistance. Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Multivariate logistic regression modeling was used to explore the relationship between SHR and depressive symptoms, and the nonlinear relationship was explored by smoothed curve fitting. Comparing the predictive value of SHR and TyG for diabetes with depressive symptoms using ROC curves. This study included 13,905 U.S. participants who were at least 20 years old. Out of them, 358 individuals with diabetes or prediabetes had a diagnosis of depression. After controlling for variables, multifactorial logistic regression revealed an OR of 1.06, meaning that every unit rise in SHR was linked to a 6% increase in the risks of depressive symptoms. Quartile analysis showed that the risk of depressive symptoms was significantly higher in the Q4 of SHR compared to the Q1. When we adjusted for TYG in Model 4, the association between SHR and depressive symptoms became negatively significant (OR = 0.92, 95% CI: 0.87 0.97). Nonlinear analysis showed a “U”-shaped relationship, with a significant inflection point at an SHR value of 16.07. Above this point, the chance of having depressive symptoms is dramatically higher; otherwise, the risk is lower. In the prediction of depressive symptoms in patients with diabetes, the area under the curve (AUC) of the TyG index versus the SHR reached 0.663 and 0.534, respectively, suggesting that the TyG index may have superior predictive efficacy compared to the SHR. This study reveals a significant U-shaped relationship between SHR and depressive symptoms in individuals with diabetes. Likewise, a distinct non-linear association was identified between TyG and depressive symptoms. Both TyG and SHR show potential as simple and effective strategies for identifying diabetes-related depressive symptoms, with TyG demonstrating slightly greater predictive value compared to SHR. Nonetheless, the overall predictive performance of these markers remains limited.

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