1. 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)
Female
(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)
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.