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TRANSCRIPT
Depression and its association with socio-demographic characteristics among type 2
diabetes mellitus patients of Bangladesh
Abstract
Diabetes mellitus is being increasingly recognized as a serious global health problem and
it is frequently associated with comorbid depression. A cross sectional study was
conducted among 178 adult type 2 diabetes mellitus patients attending Institute of
Research and Rehabilitation in Diabetes, Endocrine and Metabolic Disorders (BIRDEM),
Dhaka, Bangladesh to find out influence of socio-demographic characteristics for
occurrence of depression among them. Data were collected through face-to-face
interview. Depressive symptoms were measured using Centre for Epidemiological
Studies Depression Scale. Proportion of depression was found 34.8% which included
20.2% with severe depression and rest with mild to moderate depression. Both mild to
moderate and severe depression were significantly more common in female, odds ratios
were 2.72 (95% CI=1.13-6.53) and 5.94 (95% CI=2.49-14.20), respectively. Currently
not married respondents were also suffered from higher depressive symptoms. For mild
to moderate depression odds ratio was 4.38 (95% CI=1.46-13.18) and for severe
depression odds ratio was 9.51 (95% CI=3.69-24.50). Among socio-demographic
characteristics marital status was identified as the best predictor of depression, which was
followed by education upto secondary level, female sex and primary education.
Depression was identified as a significant health problem among adult type 2 diabetes
mellitus patients. Its association with socio-demographic characteristics should be
considered while planning therapeutic approaches for diabetic patients.
Key words: depression, socio-demographic characteristics, type 2 diabetese mellitus,
Bangladesh
Introduction
Diabetes mellitus is being increasingly recognized as a serious global health problem and
it is frequently associated with comorbid depression, contributing double burden for the
individual and society.1 The course of depression in patients with both diabetes and
depression is chronic and severe. Up to 80% of patients with diabetes and depression will
experience a relapse of depressive symptoms over a 5-year period.2 Native Americans
with Type 2 diabetes mellitus are three times more likely to have coexisting depression.3
The prevalence of depression, diagnosed using the Beck Depression Inventory, was
found to be 46% in patients with type 2 diabetes in Mexico.4 In a rural Bangladesh 29.0%
of male and 30.5% of female with diabetes were found having depressive symptoms
rating ≥ 20 on the Montgomery and Asberg Depression Rating Scale (MADRS).5
Depression in diabetes mellitus patients frequently associated with their socio-
demographic characteristics. Depression among them found to be associated with sex,
age, marital status, occupation, economic status and duration of education.4,6,7,8
Depression plays an important role in non-adherence to medical treatment. Depressed
patients are three times more likely not to comply with medical regimens than non-
depressed patients.9 This strong relationship suggests that medical patients, particularly
those who are noncompliant, should be routinely screened and, if necessary, treated for
depression.10 Diabetes and depression should be treated simultaneously for proper
management of the individual and to limit the burden of the disease for the family and
society. This study has been designed with expectation to provide information regarding
association of socio-demographic characteristics with depression among urban and semi-
urban diabetic patients in clinical settings. This study is expected to help service
providers to set strategies considering socio-demographic characteristics during planning
therapeutic approaches for depressed type 2 diabetic patients.
Materials and Methods
Study area and study population
A cross-sectional study was undertaken from January to June 2009 in Outpatient
Department (OPD) of Bangladesh Institute of Research and Rehabilitation in Diabetes,
Endocrine and Metabolic Disorders (BIRDEM), Shahbagh, Dhaka. Availability of a large
number of patients with diabetes mellitus, being the largest tertiary level diabetic care
hospital of Bangladesh and well coverage for all kind of diabetic patients were among the
prime reasons for selecting the particular hospital as the study place. Diagnosed type 2
diabetic patients aged ≥ 18 years attending the OPD of BIRDEM, who agreed to
participate were included in the study. A total of 178 respondents were included using the
purposive sampling technique.
Ethical issues
Written informed consent was received from each individual prior to inclusion. They
were informed of their right to withdraw from the study at any stage or to restrict their
data from the analysis. Assurance had been given that the data would be collected
anonymously and the confidentiality concerning their information would be maintained
strictly. The protocol was approved by the BIRDEM Ethical Review Committee for data
collection.
Measurements
A semi-structured questionnaire was developed to collect data from face-to-face
interview incorporating CES-D (Centre for Epidemiological Studies Depression) scale to
assess depressive status. The CES-D contain 20-item to measure the frequency with
which participants have experienced a specific symptom within the preceding week,
using a four-point rating scale (0-3 response set). Scores range from 0 to 60, with higher
score indicating more severe depressive symptoms.11
CES-D has been found to be both reliable and valid measure of depression in the
medically ill. A score of 16 or greater differentiate depressed from non-depressed
adults.11 CES-D has got sensitivity of 61.4, specificity 81.0, positive predictive value
(PPV) 57.7 and negative predictive value (NPV) 83.3.12 A second cut off point of 22 was
used to differentiate severity of depression: 16-21 (mild to moderate depression) and ≥ 22
(severe depression).13,14 Cronbach’s α of Bangla version of CES-D was calculated 0.89,
which indicated sufficient internal consistency of that scale.
Data analysis and statistical methods
Data were registered using Statistical Package for Social Sciences (SPSS) for windows
version 16. As depression score did not follow normal distribution, for statistical analysis
log transformation of the depression score was done and geometric mean of the
depression score was used for comparison.
Depression score was constructed by summation of all 20 items of depression score. The
proportion of presence and level of depression were determined by percentages.
Statistical comparisons between different groups were made using t-test, ANOVA for
depression scores and chi-square tests for level of depression. The odds ratio (OR) with
95% confidence interval (CI) for risk factors was calculated taking the least proportionate
clinically relevant criteria as reference value. All the tests were two tailed and p<0.05 was
considered to be statistically significant.
Results
Among 178 respondents, 51.1% were male and aged 54.96 9.76 years (mean SD).
Almost two-third of them (62.9%) belonged to the age group of 50 to 69 years. Most of
them were from urban area (71.9%) and married (82.0%). Most of the respondents were
graduate or above (65.4%) and majority were housewives (41.2%). The average monthly
family incomes for more than half of the respondents (52.2%) were between Tk.20000 to
less than Tk.30000 with mean + SD of Tk.26556.18 + Tk.12410.57. (Table 1)
Mean depression score was calculated 10.50 with SD + 9.08. The proportion of
depression among the study population was 34.8% (CES-D score ≥ 16) which included
20.2% with severe depression (CES-D score ≥ 22) and rest with mild to moderate
depression (CES-D score 16 to 21). Mean depression score found higher among female
respondents, in age group of 60 to 69 years, among respondents living in urban areas,
those who were single, with lower level of education, among housewives and among
those with income of TK. 30000 to <40000. (Table 1)
Females were suffering from both mild to moderate and severe form of depression more
than males. More than half of the female respondents were suffering from some kind of
depressive symptoms; where as less than one fifth of the male were suffering from
depressive symptoms. Respondents belonged to the 60 to 69 years age group had highest
percentages of depressive symptoms (42.3%). They also experienced highest percentage
of mild to moderate depression. But 40 to 49 years age group suffered from highest
percentage of severe depression. Respondents who were single (which included
widow/widower and separated) had more depressive symptoms than those who were
married (26.7% vs 71.9% for presence of depression). Highest percentages of depressed
persons were found in primary education group (56.0%) and lowest percentage in group
who were graduate or above (20.6%). Low education levels increased the likelihood of
presence of more severe depression. Housewives suffered more from severe depression
and retired persons from mild to moderate depression. Overall housewives were suffering
most from some sort of depressive symptoms (49.7%), which was followed by retired
persons (34.1%). Severe depression occurred more in income group TK. 30000 to
<40000 and TK. < 20000 and mild to moderate depression was comparatively more
prevalent in income group TK. > 40000. (Table 2)
Binary logistic regression model was constructed by forward LR method. Among the
socio-demographic characteristics marital staus found as the best predictor of depression
after adjustment of other variables. It was followed by secondary education, female sex
and primary education. (Table 3)
Discussion
In this study, high proportion of depression (34.8%) was found, which was consistent
with Asghar S, et al., where they found prevalence of depression in rural diabetic
population in community level was 29.7%.5
Mean depression score among female was found significantly higher than male
counterpart. This finding was supported by most of the other previous studies5,15 but not
all.16 After controlling effect of other sociodemographic variables, sex still was
significantly associated with presence of depressive symptoms [OR = 5.11, 95% CI
(1.20-21.79); p < 0.05].
The mean age of the respondents was calculated as 54.96 years and 60% of the
respondents were in the 45 to 64 age group. Age range accord with the age distribution of
type 2 diabetes in developing countries.17 We could not detect any statistical significant
age differences for proportion and severity of depression. It is consistent with other
studies among the same population.16,18 Larijani B. et al. found that major depressive
disorder was associated with the 31-59 year old group.19 We also found 40-49 years age
group suffered from highest percentages of severe depression, though 60 – 69 years
group had highest percentages of overall depressive symptoms.
Respondents of the study were belonged to urban or semi-urban areas. Urban people had
higher depression score than semi-urban people, but it showed no statistical significance.
Respondents who were single had higher depression score than those currently married
which supported other studies.18,20 Among the 32 single respondents 31 were
widow/widower and one was separated. Again among the unmarried respondents 28 were
female (statistically significant, p < 0.001), most had low level of education (60% had
upto secondary education) and half of them engaged in non-paid occupation (house wife
or retired). These might also influenced relationship between marital status and level of
depression. After adjusting other potential sociodemographic variables statistically
significant association exist between current marital status and higher depressive
symptoms [OR = 4.24, 95% CI (1.62-11.10); p < 0.005]. These findings remind about the
importance of social and economical support for the type 2 diabetic patients.
Educational status of the respondents was found much better than the national figure.21
Selection of study place and residence of the respondents might explain this. Mean
depression score found higher in lower education group. After adjustment of other
sociodemographic variables this association remained no more statistically significant.
Association of level of education with depression was supported by most other studies22,23
except few.18
Depression is more common in unemployed than the employed persons. Mean depression
score found highest among housewives and lowest among businessmen. This finding
might be explained by interaction of sex, economic status, family harmony, education
level and age. After blocking potential effects of other sociodemographic variables
occupational status no more remained as a potential predictor of depression. Miyaoka Y,
et el. had detected the correlation of unemployment to depression score in their study.18
Housewives and retired or aged persons are treated as unemployed in our society. This
finding had important implication regarding formulation of appropriate intervention
addressing unemployment problem and change of social concept of occupation to meet
problem of depression and diabetes. The average monthly family income of the
respondents was TK 26556.18 + 12410.57. This was quite high in relation to per capita
income of Bangladesh.21 This might be due to location of study place. This high income
status explained overall higher educational status of the respondents. The mean monthly
incomes of depressed and non-depressed group were almost equal (26290.32 TK. vs.
26698.28 TK.). We failed to find any association between income status and depression.
It might indicate the difficulty to measure economic status. Most of the other studies were
successful to explore the relation of prevalence of depression with low income.7,18,20
Conclusion
This study has identified depression as a significant health problem among type 2
diabetes mellitus patients and has marked some of the socio-demographic characteristics
as important factors associated with depression among them. This study has recognized
the need for future work in this area. Depression and its association with socio-
demographic characteristics in type 2 diabetes mellitus patients should be borne in mind
when formulating therapeutic management for the said population.
References
1. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care 2001;24(6):1069-78.
2. Lustman PJ, Griffith LS, Clouse RE. Depression in adults with diabetes. Semin Clin Neuropsychiatry 1997;2:15-23.
3. Warnock JK, Mutzig EM. Diabetic mellitus and major depression: considerations for treatment of Native Americans. Oklahoma State Med Assoc 1998;91:488–93.
4. Garduno EJ, Tellez ZJF, Hernandez RL. Frequency of depression in patients with diabetes mellitus type 2. Revista Invest Clinica 1998;50:287–91.
5. Asghar S, Hussain A, Ali SMK, Khan AKA, Magnusson A. Prevalence of depression and diabetes: a population-based study from rural Bangladesh. Diabetic Medicine 2007;24:872–7.
6. Lioyd CE, Matthews KA, Wing RR, Orchard TJ. Psychosocial factors and complications of IDDM. The Pittsburgh Epidemiology of Diabetes Complications Study VIII. Diabetes Care 1992;15:166-72.
7. Thomas J, Glenn Jones G, Scarinci I, Brantley P. A Descriptive and Comparative Study of the Prevalence of Depressive and Anxiety Disorders in Low-Income Adults With Type 2 Diabetes and Other Chronic Illnesses. Diabetes Care 2003;26(8):2311-17.
8. Larijan B, Bayat MKS, Gorgani MK, Bandarian F, Akhondzadeh S, Sadjadi SA. Association Between Depression and Diabetes. German J Psychiatry 2004;7:62-5.
9. Dimatteo MR, Lepper HS, Croghan TW. Depression is a risk factor for noncompliance with medical treatment. Archives of Internal Medicine 2000;160:2101–7.
10. World Health Organization. The World Health Report: 2001: Mental Health: New Understanding, New Hope. Geneva: World Health Organization; 2001.
11. Radloff LS. The CES-D Scale: A self-report depression scale for research in the general population. Applied Psychological Measurement 1977;1:385-401.
12. Mchale M, Hendrikz J, Dann F, Dcp, Kenardy J. Screening For Depression In Patients With Diabetes Mellitus. Psychosomatic Medicine 2008;70:869–74.
13. Zhang X, Norris SL, Gregg EW, Cheng YJ, Beckles G, Kahn HS. Depressive Symptoms and Mortality among Persons with and without Diabetes. Am J Epidemiol 2005;161(7):652-60.
14. Lyness JM, Noel TK, Cox C, King DA, Cornwell Y, Caine ED. Screening for depression in elderly primary care patients: a comparison of the Center for Epidemiological Studies Depression Scale and the Geriatric Depression Scale. Archives of Internal Medicine 1997;157:449–54.
15. Ali S, Stone MA, Peters JL, Davies MJ, Khunti K. The prevalence of co-morbid depression in adults with Type 2 diabetes: a systematic review and meta analysis. Diabetic Medicine 2006;23:1165-73.
16. Lioyd CE, Dyer PH, Barnett AH. Prevalence of symptoms of depression and anxiety in a diabetic clinic population. Diabet Med 2000;17:198–202.
17. Wild S, Roglic G, Green A, Sicree R, King H. Global Prevalence of Diabetes: Estimates for the year 2000 and projections for 2030. Diabetes Care 2004;27:1047-53.
18. Miyaoka Y, Miyaoka H, motomiya T, Kitamura S, Asai M. Impact of sociodemographic and diabetes-related characteristics on depressive state among non-insulin-dependent diabetic patients. Psychiatry and Clinical Neurowienm 1997;51:203-6.
19. Larijani B, Bayat MKS, Gorgani MK, Bandarian F, Akhondzadeh S, Sadjadi SA. Association Between Depression and Diabetes. German J Psychiatry 2004;7:62-5.
20. Egede LE, Zheng D, Simpson K. Comorbid depression is associated with increased health care use and expenditures in individuals with diabetes. Diabetes Care 2002;25: 464–70.
21. Bangladesh Bureau of Statistics. Statistical Pocket Book of Bangladesh 2008. Dhaka: Planning Division, Ministry of Planning, Government of the People’s Republic of Bangladesh; January 2009. p. 2,6,10,38.
22. Fisher L, Chesla CA, Mullan JT, Skaff MM, Kanter RA. Contributors to Depression in Latino and European-American Patients With Type 2 Diabetes. Diabetes Care 2001;24:1751–7.
23. Pouwer F, Snoek FJ. Association between symptoms of depression and glycaemic control may be unstable across gender. Diabetic Medicine 2001;18:595-8.