Saturday, November 3, 2007

This presentation is part of : Acute and Chronic Adult Healthcare Issues
Patient Characteristics Predict Depression in Type 2 Diabetes
Deborah W. Chapa, PhD, ACNP-BC1, Chi-Wen Kao, PhD, RN2, Hyeon Joo Lee, MS, RN3, Deborah Jones, PhD, RN3, Jane Kapustin, PhD, CRNP3, Joan Davenport, PhD, RN3, Erika Friedmann, PhD3, Sue A. Thomas, PhD, RN, FAAN3, Catherine M. Krichten, RN, MS, CRNP, CDE4, and Thomas W. Donner, MD5. (1) School of Nursing, Florida Gulf Coast University, Fort Myers, FL, USA, (2) School of Nursing, National Defense Medical Center, Taiwan, Taipei, Taiwan, (3) School of Nursing, University of Maryland, Baltimore, MD, USA, (4) Joslin Diabetes Center, Division of Endocrinology, Nutrition & Diabetes, University of Maryland, Baltimore, MD, USA, (5) School of Medicine, University of Maryland, Baltimore, MD, USA
Learning Objective #1: list patient characteristics that predict depression in type 2 diabetes.
Learning Objective #2: justify the importance of assessing depression in type 2 diabetes.

Problem:  Depression occurs in 27% of type 2 diabetics and is more prevalent in women (28%) than in men (18%), in clinical (32%) than in community (20%) samples. Younger diabetics have an increased incidence of depression. Depression leads to poorer outcomes and increased risk of complications in diabetics.  Depression is frequently unrecognized, untreated or under-treated in diabetics. 

Objective: This study was conducted using the biopsychosocial model to examine whether demographic characteristics and diabetes-related co-morbidities predict depression in type 2 diabetes?

Design: Cross sectional survey

Population, Sample, Setting: Type 2 diabetics (N=55) aged  ³35 years, 42% female, 36% African American were recruited by convenience sample from an inner city Joslin diabetes clinic.

Variables: Dependent: depression: Independent: demographics, diabetes-related macro (coronary artery disease, hyperlipidemia, hypertension, obesity) and micro (nephropathy, neuropathy and retinopathy) co-morbidities

Methods: After informed consent patients completed Beck Depression Inventory-II (BDI, depression) and demographic questionnaires.  Complications, height and weight were obtained from the medical record. 

Findings: 41% were depressed (BDI >13); 27% moderately or severely depressed (BDI³20). All patients had at least 1 diabetes-related co-morbidity; 58% had ³1 micro co-morbidity; 64% had 2-3 macro co-morbidities.  Lower age [β=-.388, t=-3.050, p=.004] and being female [β=.300, t=2.359, p=.023] were significant independent predictors of depression score (R2=16.4).   Race and interactions of age, gender and race did not add to the prediction.  Neuropathy [F(1,45)=3.492, p=.068] tended to add to the prediction of depression score beyond age and gender; other co-morbidities did not .  Further examination revealed that both lower age [β=-.502, t=-3.876, p<.001] and neuropathy [β=.344, t=2.654, p=.011] were independent predictors of depression score (R2=24.9%); gender was not. 
Conclusion:  In type 2 diabetics younger age and neuropathy predicted depression.  Clinicians need to assess depression in type 2 diabetics especially younger patients and those with signs of neuropathy.