A Growth Curve Analysis Participant Baseline Characteristics A1c Predicts Depressive Symptoms Over Time in People with Type I Diabetes: A Growth Curve Analysis Laura L. Mayhew,1 Heather L. McGinty,1,2 Brian D. Gonzalez,1,2 & William P. Sacco1 1University of South Florida; 2H. Lee Moffitt Cancer Center Results: Tables Background & Aims Methods: Measures Fixed Effects Estimates for Models 1-5 Symptom Checklist-90 Revised (SCL-90-R) Depression Subscale 13-item self-report of past week depressive symptoms Higher scores indicate greater depressive symptomatology A1c Measured with blood assays & aggregated for mean value over the 6 year (baseline to year 5 follow-up) study period A1c, a measure of blood glucose over time, is associated with depressive symptoms in people with diabetes. Evidence indicates that depression may be an antecedent or a consequence of poor glycemic control. Most studies have been cross-sectional and do not provide information about temporal sequence. This study examined whether A1c predicts change in depressive symptoms over time in a large longitudinal sample using multilevel modeling. Parameter Model 1 Model 2 Model 3 Model 4 Model 5 Intercept 3.89*** (0.00) 3.90*** (0.00) 3.73*** (0.04) 3.75*** (0.03) 3.76*** (0.03) Smoker 0.05*** (0.01) Age (centered) 0.01*** (0.00) BMI 0.00* (0.00) 0.00 (0.00) Female -0.01 (0.01) Group Slope -0.00 (0.00) 0.02** (0.01) -0.01** (0.00) -0.01*** (0.00) -0.00*** (0.00) -0.00 (0.00) Mean A1c 0.00** (0.00) Methods: Procedure The DCCT, a randomized controlled trial, investigated the role of intensive insulin treatment on the development and progression of diabetes complications over time Participants attended quarterly clinic visits for an average of 6.5 years. The current study utilizes data from baseline to year 5. A1c was measured quarterly. Depressive symptoms were measured annually. 2 –level Hierarchical Linear Modeling was used to determine relationships of the predictor variables to initial depression scores and individual change in depressive symptoms over time Level-1: Time (baseline through year 5 follow-up) Level-2: Individual characteristics including demographics (age, gender, BMI, smoking status), treatment group (standard care vs. intensive insulin treatment) & mean A1c levels over time Hypothesis Higher mean hemoglobin A1C levels will predict worse depression over time even after controlling for demographics and treatment . Methods: Participants The Diabetes Control & Complications Trial (DCCT) participants (N = 1441) Participants were randomized into Standard (n = 730) or Intensive Insulin (n = 711) treatment groups Eligibility Criteria: Diagnosed with type 1 diabetes Noa or minimalb background diabetic retinopathy Diabetes duration of 1-5a or 1-15b years No previous intensive insulin treatment No diabetic neuropathy No serious or chronic medical conditions requiring medication No serious psychological conditions or substance abuse aPrimary prevention group. bSecondary intervention group. Participant Baseline Characteristics Note. *p < .05, **p < .01, ***p < .001 Variance-Covariance Estimates for Models 1-5 Random Parameters Parameter Model 1 Model 2 Model 3 Model 4 Model 5 Intercept, τ00 0.02*** Slope 0.00*** Intercept, σ2 0.01 Results Depression data were significantly skewed so outliers were removed and scores were log-transformed for all analyses. Model 1- fully unconditional model Model 2- time as predictor (growth model) Model 3- time, demographic, treatment predictors Model 4- only significant predictors (time, smoking, BMI, age) Model 5- time, smoking status, BMI, age, mean A1c Model 5 was selected as the final model: Older age and being a smoker predicted higher depression scores at baseline; no effect of BMI or treatment on initial depression. Older age and being a smoker predicted lower depression scores over time; no effect of BMI or treatment on change in depression. Greater mean A1c across study participation significantly predicted an increase in depressive symptoms over time (p < .01). Note. *p < .05, **p < .01, ***p < .001 Conclusions Findings support our hypothesis that average hemoglobin A1C levels would predict change in depressive symptoms. Patients with higher mean hemoglobin A1C levels had significantly more depressive symptoms over the course of the study. Potential mechanisms for this relationship include decreased self-efficacy resulting from ineffective control of blood glucose levels and increased medical complications that lead to poorer quality of life. This study improves upon the existing literature by examining a large longitudinal sample and is one of the first to employ multilevel modeling in this sample, which enables the simultaneous examination of differences at baseline and differences in rates of change over time. Characteristic Mean (SD) Age 27.08 (7.11) Body Mass Index (BMI) 23.37 (2.82) Education (in years) 14.09 (2.28) A1c 8.89 (1.59) Depressive symptoms 5.32 (5.05) Characteristic N (%) Male 761 (52.8) Married 706 (49.0) Caucasian 1391 (96.5) Current smoker 304 (21.1) Intensive treatment 711 (49.3) The Diabetes Control and Complications Trial (DCCT) and its follow-up the Epidemiology of Diabetes Interventions and Complications (EDIC) study were conducted by the DCCT/EDIC Research Group and supported by National Institute of Health grants and contracts and by the General Clinical Research Center Program, NCRR. The data from the DCCT/EDIC study were supplied by the NIDDK Central Repositories. This presentation was not prepared under the auspices of the DCCT/EDIC study and does not represent analyses or conclusions of the DCCT/EDIC study group, the NIDDK Central Repositories, or the NIH.