Journal of Diabetes & Metabolism

ISSN - 2155-6156

+441518081309

Research Article - (2012) Volume 3, Issue 7

Relationship between Depression and Treatment Satisfaction among Patients with Type 2 Diabetes

Jon Bassett1, Alan Adelman2, Robert Gabbay3,4* and Raquel M Aňel-Tiangco4
1University of Nebraska Medical Center and Ehrling Bergquist at Offutt AFB, USA
2Penn State Hershey Medical Group Fishburn Road, Hershey, PA, USA
3Penn State Hershey Diabetes Institute, Hershey, PA, USA
4Division of Endocrinology, Diabetes and Metabolism, Penn State College of Medicine, PA, USA
*Corresponding Author: Robert Gabbay, Penn State Hershey Diabetes Institute, 500 University Drive, H044, Hershey, PA 17033, USA, Tel: 717-531-3592, Fax: 717- 531-5726 Email:

Abstract

Background: Depression has been shown to adversely affect glycemic control. The purpose of this study is to examine the association between depression and treatment satisfaction in patients with diabetes.
Materials and methods: Baseline data was collected on 545 patients with poorly controlled type 2 diabetes enrolled in a study that examined the effectiveness of diabetes nurse case managers. Depression was measured using the Center for Epidemiologic Studies Depression (CES-D) questionnaire, and treatment satisfaction, using the Diabetes Treatment Satisfaction Questionnaire (DTSQ).
Results: The majority of participants (59%) were female, with a high percentage (41%) of Hispanic/Latino participants with a mean HbA1C of 8.4%. The prevalence of depression in this population was 35.6%. High CES-D scores were associated with elevated levels of HbA1C and LDL cholesterol (p<0.001). The relationship between depression and treatment satisfaction was significant (p<0.001), indicating that as depression increases, treatment satisfaction decreases.
Discussion: We identified a significant relationship between depression and treatment satisfaction in this group of poorly controlled type 2 diabetes patients. Although causation cannot be determined, it is possible that patients who are depressed are less likely to be satisfied with their treatment. This could lead to decreased patient adherence, ultimately resulting in poor glycemic control.

Introduction

Depression is prevalent in the diabetes population. A systematic meta-analysis by Anderson et al. indicated that the odds of comorbid depression doubled for patients with diabetes compared to those without it. The prevalence of depression was also significantly higher among women than in men with diabetes [1]. A more recent metaanalysis reported the prevalence of depression in patients with type 2 diabetes to be 17.6%, compared with 9.8% among control subjects [2].

This apparent increased risk of comorbid depression amongst the diabetes population can have many worrisome outcomes. Depression has been associated with hyperglycemia in patients with both type 1 and type 2 diabetes in a meta-analysis by Lustman et al. [3]. Comorbid depression has also been associated with increased risk of diabetic retinopathy, nephropathy, neuropathy, macrovascular complications, and sexual dysfunction [4].

Although an association exists between depression and hyperglycemia, causality is less clear. Studies have shown that reducing depression leads to improvement in hemoglobin A1C levels in diabetes patients [3]. Likewise, improving HbA1C levels with aggressive hypoglycemic pharmacotherapy has been shown to improve depression [5,6]. Thus, an improvement in glycemic control or depression consequently leads to an improvement in the other. However, the reason for this association remains unclear. A meta-analysis has shown that patients who are depressed are 3 times more likely to be nonadherent with treatment compared to their non-depressed counterparts [7]. It has become increasingly important to assess patient satisfaction as it relates to adherence, and it is unclear what factors influence treatment satisfaction. Amongst patients with diabetes, lower treatment satisfaction resulted in greater difficulties with adherence to treatment [8]. The purpose of this study was to explore the relationship between depression, diabetes treatment satisfaction, and health outcomes.

Materials and Methods

Population

Baseline data on 545 participants was collected as part of a randomized National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) funded clinical trial known as the DYNAMIC study (Diabetes nurse case management and motivational interviewing for change) [9]. Patients eligible for the study were identified based on billing data, searching the Penn State Diabetes Registry and subsequent chart review from nine Penn State Hershey Medical Center primary care offices and three Reading Hospital-affiliated primary care clinics that serve a predominantly Hispanic population [10]. Inclusion criteria consisted of patients’ age >18 years with poorly controlled type 2 diabetes or its comorbidities as indicated by one of the following: HbA1C >8.5, LDL >130, or blood pressure (BP)>140/90. Patients who were pregnant, unable to communicate in English or Spanish, or were in nursing homes were excluded from the study.

Data collection

Patients completed the Center for Epidemiologic Studies Depression (CES-D) questionnaire. The CES-D is a standardized, self report questionnaire with a maximum score of 60 points. Higher scores indicate greater psychological distress. A score ≥ 16 is indicative of clinically significant psychological distress. In the general population it would be expected that ~20% of people would record a score ≥ 16 [11].

The 8-item Diabetes Treatment Satisfaction Questionnaire (DTSQ) was used to determine patient treatment satisfaction. It is the most widely used and psychometrically evaluated measure of patient satisfaction with diabetes treatment [12,13]. Four items of the questionnaire specifically assess satisfaction, convenience, flexibility, and understanding of treatment. Two additional questions address the patients’ willingness to continue with treatment as well as the likelihood that they would recommend such treatment to others. The final two questions of the survey tool address the patients’ awareness of hyperand hypoglycemia. There is a maximum score of 36 points, with higher scores indicating higher satisfaction with treatment [13].

Clinical data (HbA1C, LDL, BP) were collected through the Penn State Diabetes Registry [10]. Chart abstractors were used to ensure that all the information was up to date.

Analysis

Minitab version 15.1.2 (Minitab, Inc., State College, Pennsylvania) was used for the analysis. We initially performed univariate analyses on all demographic variables (age, gender, race, education level, income, and marital status), health outcome variables (BMI, HbA1C, LDL, BP), and survey data (CES-D and DTSQ scores). Next, Pearson’s correlation coefficient was calculated, searching for relationships between demographic variables, health outcomes, and survey data. Pearson’s correlation statistics were then calculated comparing CES-D and DTSQ in greater detail. To compare categorical variables with health outcomes and survey results a one-way ANOVA was used. Depression was then looked at as a categorical variable, with CES-D scores ≥ 16 used to indicate depression. A two-sample T test was used to observe differences in health outcomes and survey data between patients who were considered depressed and those who did not meet the criteria. Finally, a stepwise regression model was used to assess the statistically significant relationships between CES-D scores and demographic variables, health outcomes, and other survey data, with an alpha-toenter of 0.15 and an alpha-to-remove of 0.15.

Results

The baseline demographics and clinical measures data on a total of 545 patients who participated in the study are shown in Table 1. The majority of the patients were female and middle-aged. Most were Caucasian, although there was also a large number of Hispanic/Latino patients (n=212, 41%). Most of them reported making less than $35,000 annually/$3,000 monthly.

Characteristic Results N*
Gender    
Female 59% 320
Male 41% 225
Age in years, mean (SD) 58 (11.41) 531
Race    
Caucasian 49% 254
Hispanic/Latino 41% 212
Black/African American 7% 37
Other 3% 19
Highest Education    
No High School Degree 34% 168
High School Degree or Equivalent 31% 156
College and Beyond 35% 173
Annual Household Income    
Less than $35,000/$36,000 71% 332
$35,000/$36,000-$65,000/$66,000 15% 70
Greater than $65,000/$66,000 14% 68
Marital Status    
Married 52% 268
Single 20% 103
Other 28% 148
Clinical Measures    
BMI, mean (SD) 34.4 (8.25) 490
A1C, mean (SD) 8.4 (2.15) 485
LDL, mean (SD) 114 (39.41) 497
Systolic BP, mean (SD) 137 (19.33) 296
Diastolic BP, mean (SD) 77 (11.73) 296
A1C control (<7) 33% 159
LDL control (<100 mg/dL) 42% 210
Systolic BP control (<130 mmHg) 42% 125
Diastolic BP control (<80 mmHg) 70% 208
Overall Control (A1C, LDL, BP) 3.9% 10
Survey Data    
CES-D score, mean (SD) 14.8 (15.02) 523
DTSQ score, mean (SD) 26.6 (8.23) 538

*Total of 545 patients. Missing data were excluded from analysis.

Table 1: Baseline Demographics, Outcome Data, and Survey Results.

One-third (33%) of the patients had a baseline HbA1C measurement of ≤ 7%, indicating good glycemic control. In addition, 42% of patients had LDL ≤ 100 mg/dL, 42% had a systolic BP ≤ 130 mmHg, and 70% had a diastolic BP ≤ 80 mmHg, all of which are target levels for diabetes patients. The study was designed specifically to look at poorly controlled patients. As such, only 10 patients (3.9%) were well-controlled in all three parameters of HbA1C, LDL, and blood pressure.

HbA1C was lowest in Caucasians (8.1%, p<0.01) and in patients who had some form of college degree (8.1%, p<0.01). Conversely, HbA1c was highest in Hispanic patients (8.84%, p<0.01) and in those with no high school degree (8.85%, p<0.01). CES-D scores were significantly lower (indicating lower levels of distress) in Caucasians, in patients with some educational degree, in those who reported an annual income >$65,000/$66,000, and in those who were married. The patient groups that were more likely to be satisfied with their treatment included the Hispanic patients, those without a high school degree, and those with an annual household income of <$35,000/$36,000.

A total of 186 patients (35.6%) scored ≥ 16 on the CES-D questionnaire, indicating clinically significant psychological distress. As shown in Table 2, CES-D was found to be significantly correlated to some of the clinical outcome variables. Specifically, as CES-D scores increased, HbA1c, LDL, and diastolic BP increased, and treatment satisfaction decreased.

Outcomes CES-D
A1C 0.158
LDL 0.153
SBP 0.002
DBP 0.139*
DTSQ -0.201

*p ≤ 0.05
p ≤ 0.001

Table 2: Pearson’s correlation coefficients of CES-D and clinical outcome variables.

An analysis of the correlation between CES-D and DTSQ by demographic factors is shown in Table 3. Overall, as CES-D scores increased, treatment satisfaction decreased. This relationship was stronger in men than women, in Caucasian than in Hispanic/Latino participants, and was strongest in male Caucasian participants.

Variables Pearson Correlation
Female -0.146*
Males -0.286
Hispanic/Latino -0.139*
Caucasian -0.325
Female Hispanic/Latino -0.107*
Male Hispanic/Latino -0.239*
Female Caucasian -0.297
Male Caucasian -0.333
Results after adjusting for the effects of age, gender, BMI, income, race, marital status, and education -0.255

*p<0.05
p<0.01
p<0.001

Table 3: Correlation between CES-D and DTSQ by demographic factors.

Discussion

The purpose of this study was to examine the association of depression and treatment satisfaction in a population of individuals with type 2 diabetes. The prevalence of depression amongst this group of poorly controlled type 2 diabetes patients (mean HbA1C=8.4% was 35.6% using a CES-D score ≥ 16 as a cutoff for depression). Roughly 20% of the general population typically would record a score ≥ 16. Therefore, the prevalence of depression is nearly double in this population, which is consistent with the literature regarding the high prevalence of depression among persons with diabetes [2].

There was a clear relationship between depression and treatment satisfaction. As scores on the CES-D rose, indicating higher levels of distress, treatment satisfaction scores decreased. Similar results have been described among depressed patients with coronary artery disease [14]. It is unknown whether poor treatment satisfaction leads to greater distress or whether greater distress negatively impacts the patient’s view of his or her diabetes treatment satisfaction. Further trials aimed at examining the impact of depression on treatment satisfaction will need to be performed to explore this relationship and potential point of intervention.

While this study has much strength including a diverse population, validated surveys, and inclusion of clinical parameters, this study has several limitations. First, because of its cross-sectional study design, causation cannot be determined. Although the demonstrated relationship between depression and diabetes treatment satisfaction has face validity, the current study design cannot determine causation. Second, this study may be limited because it focused on patients who are uncontrolled, with the inclusion criteria being that they are uncontrolled in HbA1C levels, LDL levels, and/or blood pressure. This may not be representative of the general diabetes population. As the literature suggests, poorer glycemic control can be a risk factor for depression and depression can also be a risk factor for developing diabetes [1,2]. By focusing on a specific population of diabetes patients who are not well-controlled, the results from our study could be skewed and cannot be generalized to the population of individuals with type 2 diabetes. Third, we do not know whether the subjects were diagnosed as being clinically depressed and whether they were receiving medication and/or counseling. This would be very important for a longitudinal study that examined prospectively the effect of treatment on depression and diabetes treatment satisfaction. And finally, treatment adherence was not measured in this study. Again this will be an important factor to include in any prospective study.

In conclusion, there is still a need for further research to assess the relationship between depression and treatment satisfaction among diabetes patients. If improving treatment satisfaction leads to improvement in depression scores, then treatment satisfaction can be targeted as an area of improvement. It would also be interesting to see whether addressing either depression or treatment satisfaction would affect patient adherence and ultimately, if this will improve clinical outcomes.

Acknowledgements

Support was provided by the National Institute of Diabetes and Digestive and Kidney Diseases grant R18-DK067495.

References

  1. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ (2001) The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care 24: 1069-1078.
  2. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K (2006) The prevalence of co-morbid depression in adults with Type 2 diabetes: a systematic review and meta-analysis. Diabet Med 23: 1165-1173.
  3. Lustman PJ, Anderson RJ, Freedland KE, de Groot M, Carney RM, et al. (2000) Depression and poor glycemic control: a meta-analytic review of the literature. Diabetes Care 23: 934-942.
  4. de Groot M, Anderson R, Freedland KE, Clouse RE, Lustman PJ (2001) Association of depression and diabetes complications: a meta-analysis. Psychosom Med 63: 619-630.
  5. Mazze RS, Lucido D, Shamoon H (1984) Psychological and social correlates of glycemic control. Diabetes Care 7: 360-366.
  6. Testa MA, Simonson DC (1998) Health economic benefits and quality of life during improved glycemic control in patients with type 2 diabetes mellitus: a randomized, controlled, double-blind trial. JAMA 280: 1490-1496.
  7. DiMatteo MR, Lepper HS, Croghan TW (2000) Depression is a risk factor for noncompliance with medical treatment: Meta-analysis of hte effects of anxiety and depression on patient adherence. Arch Intern Med 160: 2101-2107.
  8. Biderman A, Noff E, Harris SB, Friedman N, Levy A (2009) Treatment satisfaction of diabetic patients: what are the contributing factors? Fam Pract 26: 102-108.
  9. Stuckey HL, Dellasega C, Graber NJ, Mauger DT, Lendel I, et al. (2009) Diabetes nurse case management and motivational interviewing for change (DYNAMIC): study design and baseline characteristics in the Chronic Care Model for type 2 diabetes. Contemp Clin Trials 30: 366-374.
  10. Khan L, Mincemoyer S, Gabbay RA (2009) Diabetes registries: where we are and where are we headed? Diabetes Technol Ther 11: 255-262.
  11. Radloff LS (1977) The CES-D scale: a self report depression scale for research in the general population. Appl Psychol Meas 1: 385-401.
  12. Witthaus E, Stewart J, Bradley C (2001) Treatment satisfaction and psychological well-being with insulin glargine compared with NPH in patients with Type 1 diabetes. Diabet Med 18: 619-625.
  13. Bradley C (1994) Handbook of Psychology and Diabetes: A Guide to Psychological Measurement in Diabetes Research and Practice. Harwood Academic Publishers, Chur, Switzerland.
  14. Spertus JA, McDonell M, Woodman CL, Fihn SD (2000) Association between depression and worse disease-specific functional status in outpatients with coronary artery disease. Am Heart J 140: 105-110.
Citation: Bassett J, Adelman A, Gabbay R, Aňel-Tiangco RM (2012) Relationship between Depression and Treatment Satisfaction among Patients with Type 2 Diabetes. J Diabetes Metab 3: 210.

Copyright: © 2012 Bassett J, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.