The study investigated the association between body mass index (BMI) and depression based upon glycated hemoglobin levels (HBA1C) among United States veterans. Based on Bandura's social cognitive theory, a cross-sectional analysis examined the association between BMI and depression on HBA1C regulation, and if the interaction between BMI and depression affects HBAIC regulation among veterans. Multiple regression analysis was used to test the multivariate associations between depression and BMI on the outcome variable of HBA1C. Linearity, normality, and homoscedasticity were assessed using normal probability plots and residual analysis. Durbin-Watson statistics were used to test for autocorrelations, and variance inflation factor was used to check for multicollinearity. There was not a statistically significant difference between those who were depressed (Mdn = 32.76, IQR = 7.8) and those who were not depressed (Mdn = 33.27, IQR = 5.0) in terms of BMI (U = 774.0, p = 0.47). When depression, BMI, an interaction term for depression*BMI, and other predictor variables were entered into the regression model, these variables did not account for a significant increase in shared variance in HBA1C (Î?R2 = 0.17, F (14, 74) = 0.17, p = 0.37). Social change implications generated from this study include better resource utilization, improved quality of care, increased veteran satisfaction and improved veteran experience across the healthcare system. The findings from the study can be used to expand access to specialized services for chronically ill veterans, coordinate resources, better outcomes and facilitate seamless care coordination between mental health and primary care providers