Comorbidity of depression and diabetes: an application of biopsychosocial model

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Abstract

Background

Type 2 diabetes (T2D) is one of the most psychologically demanding chronic medical illness in adult. Comorbidity between diabetes and depression is quite common, but most studies were based on developed country sample. Limited data exists to document biopsychosocial predictors of depressive symptoms in Ethiopian patients. Therefore, the aim of the study was to describe the association of depressive symptoms and T2D and explore the potential underlying associated biopsychosocial risk factors.

Methods

Institution based cross-sectional study was conducted on 276 patient with T2D at diabetic clinic, Black Lion General Specialized Hospital in Ethiopia. Patients were selected using systematic random sampling technique. Depressive symptoms score, which constructed from a validated nine-item Patient Health Questionnaire (PHQ-9), was an outcome variable. Finally, significant associated factors were identified using multiple linear regression analysis with backward elimination procedure. Statistical Package for Social Science (SPSS) version 22.0 (IBM SPSS Corp.) was used to perform all analysis.

Results

Total of 264 patient data was analyzed with 95.7% response rate. Patients mean (SD) current age and age at diagnosis was 55.9 (10.9) and 43.9 (10.9) years, respectively. Patients waist circumference (mean ± SD) was 98.9 ± 11.1 cm. The average PHQ-9 score was 4.9 (SD 4.1) and fasting blood glucose was 166.4 (SD 73.2). Marital status (divorced), occupation (housewife), diabetic complication (nephropathy), negative life event in the last six months, and poor social support significantly associated with increased mean PHQ-9 score after adjustment for covariates. Whereas not fearing diabetic-related complication and death significantly lower mean PHQ-9 score.

Conclusion

Biopsychosocial variables including marital status, negative life event in the last 6 months, occupation, diabetic complication, and poor social support significantly increase average depressive symptoms score. Evidence-based intervention focusing on these identified biopsychosocial factors are necessary to prevent the development of depressive symptoms.

Electronic supplementary material

The online version of this article (doi:10.1186/s13033-016-0106-2) contains supplementary material, which is available to authorized users.

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Most cited references 70

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The need for a new medical model: a challenge for biomedicine.

Andrew G. Engel (1977)

The dominant model of disease today is biomedical, and it leaves no room within tis framework for the social, psychological, and behavioral dimensions of illness. A biopsychosocial model is proposed that provides a blueprint for research, a framework for teaching, and a design for action in the real world of health care.

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Validity of the Patient Health Questionnaire-9 for depression screening and diagnosis in East Africa.

Bizu Gelaye, Michelle Williams, Seblewengel Lemma … (2013)

Depression is often underdiagnosed and undertreated in primary care settings, particularly in developing countries. This is, in part, due to challenges resulting from lack of skilled mental health workers, stigma associated with mental illness, and lack of cross-culturally validated screening instruments. We conducted this study to evaluate the reliability and validity of the Patient Health Questionnaire-9 (PHQ-9) as a screen for diagnosing major depressive disorder among adults in Ethiopia, the second most populous country in sub-Saharan Africa. A total of 926 adults attending outpatient departments in a major referral hospital in Ethiopia participated in this study. We assessed criterion validity and performance characteristics against an independent, blinded, and psychiatrist administered semi-structured Schedules for Clinical Assessment in Neuropsychiatry (SCAN) interview. Overall, the PHQ-9 items showed good internal (Cronbach's alpha=0.81) and test re-test reliability (intraclass correlation coefficient=0.92). A factor analysis confirmed a one-factor structure. Receiver Operating Characteristics (ROC) analysis showed that a PHQ-9 threshold score of 10 offered optimal discriminatory power with respect to diagnosis of major depressive disorder via the clinical interview (sensitivity=86% and specificity=67%). The PHQ-9 appears to be a reliable and valid instrument that may be used to diagnose major depressive disorders among Ethiopian adults.

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Association of depression and diabetes complications: a meta-analysis.

Jennifer M de Groot, R R Anderson, K Freedland … (2015)

The objective of this study was to examine the strength and consistency of the relationship between depression and diabetes complications in studies of type 1 and type 2 adult patients with diabetes. MEDLINE and PsycINFO databases were searched for articles examining depression and diabetes complications in type 1 and type 2 diabetes samples published between 1975 and 1999. Meta-analytic procedures were used. Studies were reviewed for diabetes type, sample size, statistical tests, and measures of diabetes complications and depression. Significance values, weighted effect sizes r, 95% confidence intervals (CI), and tests of homogeneity of variance were calculated for the overall sample (k = 27) and for subsets of interest. A total of 27 studies (total combined N = 5374) met the inclusion criteria. A significant association was found between depression and complications of diabetes (p < .00001, z = 5.94). A moderate and significant weighted effect size (r = 0.25; 95% CI: 0.22-0.28) was calculated for all studies reporting sufficient data (k = 22). Depression was significantly associated with a variety of diabetes complications (diabetic retinopathy, nephropathy, neuropathy, macrovascular complications, and sexual dysfunction). Effect sizes were in the small to moderate range (r = 0.17 to 0.32). These findings demonstrate a significant and consistent association of diabetes complications and depressive symptoms. Prospective, longitudinal studies are needed to identify the pathways that mediate this association.

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Author and article information

Contributors

Tesfa Dejenie Habtewold: tesfadej2003@gmail.com

Md. Atiqul Islam: atique.sta@gmail.com

Yosef Tsige Radie: josephtsige@yahoo.com

Balewgizie Sileshi Tegegne: bg.sileshi@gmail.com

Journal

Journal ID (nlm-ta): Int J Ment Health Syst

Journal ID (iso-abbrev): Int J Ment Health Syst

Title: International Journal of Mental Health Systems

Publisher: BioMed Central (London )

ISSN (Electronic): 1752-4458

Publication date (Electronic): 3 December 2016

Publication date PMC-release: 3 December 2016

Publication date Collection: 2016

Volume: 10

Electronic Location Identifier: 74

Affiliations

[1 ]Department of Nursing, Debre Berhan University, 445, Debre Berhan, Ethiopia

[2 ]Department of Epidemiology and Rob Giel Research Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

[3 ]Department of Statistics, Shahjalal University of Science and Technology, Sylhet, 3114 Bangladesh

[4 ]Centralized School of Nursing and Midwifery, Addis Ababa University, Addis Ababa, Ethiopia

[5 ]Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

[6 ]Department of Public Health, Haramaya University, Dire Dawa, Ethiopia

Article

Publisher ID: 106

DOI: 10.1186/s13033-016-0106-2

PMC ID: 5135819

SO-VID: b543e9fb-2423-4cd9-9152-14ca263c9d49

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 22 June 2016

Date accepted : 25 November 2016

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ScienceOpen disciplines: Neurology

Keywords: biopsychosocial model,comorbidity,depression,diabetes mellitus

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ScienceOpen disciplines: Neurology

Keywords: biopsychosocial model, comorbidity, depression, diabetes mellitus

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Comorbidity of depression and diabetes: an application of biopsychosocial model

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Abstract

Background

Methods

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Electronic supplementary material

Related collections

Karger: Neurology and Neuroscience

Most cited references 70

The need for a new medical model: a challenge for biomedicine.

Validity of the Patient Health Questionnaire-9 for depression screening and diagnosis in East Africa.

Association of depression and diabetes complications: a meta-analysis.

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Cited by 8

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