Int J Ment Health Addiction DOI 10.1007/s11469-015-9582-x
Prevalence and Associated Factors of Depression Among Post-Stroke Patients in Bangladesh Md. Ariful Islam 1 & Anisur Rahman 2 & Mohammad Abdul Aleem 1 & Sheikh Mohammed Shariful Islam 1,3,4
# Springer Science+Business Media New York 2015
Abstract To assess the prevalence of depression and its associated factors among patients with stroke in Bangladesh. We conducted a cross-sectional study among 164 post-stroke patients attending two hospitals in Dhaka city between January and June 2011. Depression was measured using the Hamilton Depression Rating Scale. Factors associated with depression were analyzed using multivariate logistic regression. Results: The prevalence of depression was 70 and 32 % had severe depression. The mean ± sd age of the participants was 58.91 ± 7.03 years. Multivariate regression analysis revealed that factors significantly associated with depression were living in a joint family (OR = 13.5, 95 % CI = 1.3–145.7, p = 0.032), those unable to perform daily activities by themselves (OR = 14.9, 95 % CI = 2.0–108.1, p = 0.008) and those with comorbid dysphasia (OR = 9.5, 95 % CI = 1.0– 86.9, p = 0.046) and hypertension (OR = 5.2, 95 % CI = 2.3–15.4, p = 0.012). Depression is a
* Sheikh Mohammed Shariful Islam
[email protected];
[email protected] Md. Ariful Islam
[email protected] Anisur Rahman
[email protected] Mohammad Abdul Aleem
[email protected] 1
Center for Control of Chronic Disease (CCCD), International Center for Diarohheal Disease Research, Bangladesh (ICDDR, B), 68, Shaheed Tajuddin Ahmed Sarani, Mohakhali, Dhaka 1212, Bangladesh
2
Department of Epidemiology, National Institute of Preventive and Social Medicine (NIPSOM), Dhaka, Bangladesh
3
Center for International Health (CIH), Ludwig-Maximilians-Universität (LMU), Munich, Germany
4
Cardiovascular Division, The George Institute for Global Health, Sydney, Australia
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significant health problem among post-stroke patients in Bangladesh. This leads to careful management of depression for social support to achieve better patient outcome. Keywords Depression . Stroke . Prevalence . Risk factors . Bangladesh
Introduction Globally non-communicable diseases (NCDs) are recognized as the leading cause of morbidity and mortality, accounting for more than 60 % of all deaths, including 80 % in developing countries (Alwan 2011; Islam et al. 2014b). Bangladesh and other countries of South-East Asia are facing a double burden with a higher load of infectious diseases and an increasing burden of NCDs (Islam et al. 2014b). Stroke is the second leading cause of death in the world after ischaemic heart disease and the most common cause of severe physical disability (World Health Organization 2011). Poststroke depression (PSD) is a common and serious complication after stroke and about one third of stroke survivors experience significant symptoms of depression, either in the early or in the late stage after stroke (Brainin et al. 2011; Hackett et al. 2005). The recent advancements in medical science and increasing life expectancy has resulted in decrease in stroke mortality and subsequent increase in stroke survivors with residual impairment and disabilities affecting the patients’ quality of life to various extent (Mirzaei et al. 2012). Considerable evidence suggests that, depression is significantly more prevalent in people with stroke compared with the general population and is associated with stroke severity (De Ryck et al. 2014). In addition to stroke-related factors, patient-related and socioeconomic factors, including age, sex, education, income, personality, coping abilities may be associated with PSD (De Ryck et al. 2014; Sienkiewicz-Jarosz et al. 2010). Moreover, PSD is associated with an increased disability and cognitive impairment (Herrmann et al. 1998), increased mortality both on short long term (Williams et al. 2004), increase risk of falls and finally, with worse rehabilitation and clinical outcome (Gillen et al. 2001). In particular, depression is considered as the strongest predictor of quality of life (QoL) in stroke survivors and is associated with a significant increase in total healthcare expenditure (Guajardo et al. 2014; Pan et al. 2008). Information about the prevalence and risk factors for depression among post stroke patients is essential to develop strategies for prevention, early detection and appropriate management resulting in improved outcomes. However, data on PSD in South Asia are inadequate, particularly for stroke patients. Therefore, this study aimed to determine the prevalence of depression and assess the association between demographic, socioeconomic and clinical factors with depression among post-stroke patients in Bangladesh. Our hypothesis was that the prevalence of depression in post stroke patients would be higher compared to normal adults.
Subjects and Methods Study Design and Population A cross-sectional study was conducted among 164 consecutive first-ever stroke patients attending the outpatient department (OPD) of Physical Medicine Unit, Dhaka Medical College Hospital (DMCH) and Center for Rehabilitation of the Paralyzed (CRP) between January to June 2011. DMCH is one of the largest tertiary level government hospital in Bangladesh and on an average about 30–40 stroke patients visit the OPD daily. CRP is a non-government specialized centre for rehabilitation of disabled and paralyzed people and on an average about 20–30 stroke patients attend the
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OPD for consultation and physiotherapy. The inclusion criteria were: patients with a first stroke diagnosed by a physician, age 18–70 years, willing to provide written informed consent. The exclusion criteria were: patients with a history of psychiatric problems (diagnosed by physician) such as dementia, psychosis, confusion, family history of depression, taking anti-depressant drugs and patients who were seriously ill during the period of data collection, such as aphasia.
Ethics The respondents were informed about the objectives, purpose of the study and written informed consent was obtained. No drug trial or invasive procedure was done in this study. Confidentiality was maintained. All other ethical issues were considered as per Helsinki Declaration. The study was approved by the institutional review board of National Institute of Preventive and Social Medicine (NIPSOM), Dhaka, Bangladesh. Data Collection and Variables Data were collected by a trained physician (MAI) through face-to-face interviews using structured questionnaire. Medical records of the respondents were reviewed to confirm first-ever diagnosis of stroke according to WHO criteria and reports of computed tomography (CT) scans, determine the type of stroke, current use of medicines and other comorbid conditions. The questionnaire was developed in English, translated into Bengali and back-translated to English to check for consistency. It was pre-tested in a private clinic in Dhaka among 25 post-stroke patients and modified for data collection in this study. It contained questions related to socio-demographic characteristics (age, sex, marital status, education, occupation, family type, family size, monthly family income, caregiver, social contact), current illness and other relevant information such as smoking status, duration of stroke, type of stroke, hemiparesis, side of hemiparesis, dysphasia, activity of daily life, depression score, level of depression, history of hypertension, ischaemic heart disease and diabetes. Depression was measured using the Hamilton Depression Rating Scale (HDRS), which is a 17-item interviewer-administered questionnaire (Hamilton 1960). Eight items are scored on a 5-point scale (ranging from 0 = not present to 4 = severe) and rest nine items are scored from 0 to 2 (0 = not present to 2 = severe). A total score was calculated for each participant with the following cut-off points: 0–9 = No depression, 10–13 = Mild depression; 14–17 = Moderate depression and ≥18 = Severe depression. The HDRS scale is used to assess the severity of depression in patients with diagnosed illness. Validity of the HDRS has been reported to range from 0.65 to 0.90 with global measures of depression severity, and to be highly correlated with other clinician-rated measures. Data Analysis Each questionnaire was checked for consistently and entered into Statistical Package for Social Sciences (SPSS) for windows version 17 (SPSS Corporation, Tx. USA). Data were cleaned and frequency distribution was checked. Frequency and percentages were calculated and data were presented as Mean ± SD. Statistical comparisons between different groups were made using t-test, chi-square tests and Fisher’s exact tests as appropriate for types of depression. Univariate analysis was performed for factors associated with depression (dependent variable). Factors which were significant in univariate analysis were modeled in multivariate analysis adjusting for age, sex, education, occupation. Multi-colinearity was checked for each factors before including in the models to avoid bias. Results were presented as Odds Ratios (OR) with 95 % Confidence Intervals (CI). All tests were two tailed and a p value < 0.05 was considered to be statistically significant.
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Results Socio-demographic and clinical characteristics of the study participants are shown in Table 1. The mean age of the respondents was 58.91 ± 7.03 years (age range 38–70 years). The older age group (≥61 years) constituted the highest portion (42.7 %) of the respondents, which was followed by the age group of ‘51–60 years’ (39.6 %). Majority of the respondents were males (68.3 %), resided in urban areas (91.5 %), Muslims (91.5 %), married (85.4 %), completed graduation degree or above (46.6 %), main occupation as housewives (28.7 %), living in nuclear family (54.9 %). The mean family members were 5.34 ± 1.5 persons. Family having 4–6 members was the highest group (65.9 %) followed by ≥7 members group (22.6 %). The average monthly family income for almost half of the respondents (44.5 %) was between BDT 20,000 to less than 30,000 (mean ± SD BDT 26378.05 ± 10,427.24). Most of the respondents had ischaemic stroke (78.7 %), duration of 1–3 months since last attack (43.9 %), right-sided hemiparesis (55.5 %), dependent on others for daily life activities (65.2 %), and had co-morbid hypertension (85.4) and diabetes (53 %). Overall, 70.1 % of the participants had some level of depression (HDRS score ≥ 10), 18.3 % had mild and 19.5 % had moderate depression, 32.3 % had severe depression (HDRS score ≥ 18). About four-fifth of the females were suffering from some kind of depression; whereas two-third of the males were suffering from depression. Females were also more sufferers of severe depression than males (p > 0.05). Higher depression was found among participants in the age group ≥61 years (42.7 %, p < 0.001), living in rural areas (71.4 %), single (75 %), p < 0.001), illiterate p < 0.001) and agricultural workers (p < 0.001). A greater number of the housewives and retired persons had severe depression. Most of the respondents (54 %) of joint families were suffering from severe depression (p < 0.001). Respondents living in families having 7 or more members had higher prevalence of severe depression (59.5 %) than other groups (p < 0.001). Respondents with monthly family income ≤20,000 BDT were relatively more sufferer (50 %) of severe depression (p > 0.05). Respondents who were cared by their spouse were less depressed (65.1 %) than those cared by their children/others (p < 0.005). Patients with no social contacts were more (90.3 %) depressed than the patients with social contact and 54.8 % of them had severe depression. Majority of the patients (82.9 %) with ischaemic stroke had some depression and 38 % had severe depression, which was higher than other types of stroke (p < 0.001). Most of the patients having stroke 3 months back had severe depression (75.8 %) compared to participants with less duration since last attack (p < 0.001). Depression was higher among those with aphasia compared to those without aphasia (p < 0.001). Participants who were unable to perform daily activities (92.6 %) had more severe depression p < 0.001). Table 2 shows the characteristics of the study participants by depression score. The mean ± SD depression score was 14.42 ± 6.65 (ranging from 4 to 34). Participants in the age group ≥61 years had highest mean depression score and those in ≤50 years had lowest depression score (p < 0.05). The mean depression score was higher for the respondents who were single (widow/widower), illiterate, living in joint families, ≥7 family members, time since last stroke ≥3 months, had ischaemic stroke, dysphasia, unable to perform daily activity alone, no social contact and with comorbid diabetes, hypertension and ischaemic heart disease (all p value < 0.001), as well as those who lived in rural areas, agricultural workers, monthly income ≤20,000 BDT and cared by their children/others (all p value < 0.005). Figs. 1 and 2 presents the depression score of the participants and correlation of depression score with age, respectively.
Int J Ment Health Addiction Table 1 Socio-demographic and clinical characteristics of the study participants according to type of depression Variables
Level of depression
Total n (%) Test statistics
No n (%) Mild n (%) Moderate n (%) Severe n (%) Sex Male
38 (33.9)
21 (18.8)
20 (17.9)
33 (29.5)
112 (68.3)
Female 11 (21.2) Age (in completed years) ≤ 50 18 (62.1)
9 (17.3)
12 (23.1)
20 (38.5)
52 (31.7)
4 (13.8)
6 (20.7)
1 (3.4)
29 (17.7)
51 to 60 ≥ 61 Residential status Urban
24 (36.9) 7 (10.0)
12 (18.5) 14 (20.0)
14 (21.5) 12 (17.1)
15 (23.1) 37 (52.9)
65 (39.6) 70 (42.7)
50 (33.3)
56 (37.3)
44 (29.3)
150 (91.5)
Rural Marital status Married
0
4 (28.6)
10 (71.4)
14 (8.5)
49 (35.0)
25 (17.9)
31 (22.1)
35 (25.0)
140 (85.4)
Single Educational status Illiterate
0 (0)
5 (20.8)
1 (4.2)
18 (75.0)
24 (14.6)
0
5 (26.3)
1 (5.3)
13 (68.4)
19 (11.6)
Up to SSC Up to HSC Graduate or above Occupational status Service
6 (17.1) 8 (23.5) 35 (46.1)
4 (11.4) 7 (20.6) 14 (18.4)
5 (14.3) 12 (35.3) 14 (18.4)
20 (57.1) 7 (20.6) 13 (17.1)
35 (21.3) 34 (20.7) 76 (46.3)
27(64.2)
6 (14.3)
7 (16.7)
2 (4.8)
42 (25.6)
Agriculture Business Retired House wife Type of family Nuclear
0 8 (29.6) 6 (15.4) 8 (17.0)
2 (22.2) 5 (18.5) 9 (23.1) 8 (17.0)
1 (11.1) 5 (18.5) 8 (20.5) 11 (23.4)
6 (66.7) 9 (33.3) 16 (41.0) 20 (42.6)
9 (5.5) 27 (16.5) 39 (23.8) 47 (28.7)
42(46.7)
16 (17.8)
19 (21.1)
13 (14.4)
90 (54.9)
Joint 7 (9.5) Family size (in number) 1 to 3 10 (52.6)
14 (18.9)
13 (17.6)
40 (54.0)
74 (45.1)
2 (10.5)
6 (31.6)
1 (5.3)
19 (11.6)
19 (17.5) 7 (18.9)
30 (27.8) 22 (59.5)
108(65.9) 37 (22.5)
7 (18.4)
19 (50.0)
38 (23.2)
13 (17.8) 9 (25.0)
17 (23.3) 11 (30.6)
73 (44.5) 36 (22.0)
4 to 6 37 (34.3) 22 (20.4) ≥7 2 (5.4) 6 (16.2) Monthly Family Income (000, BDT) < 20 8 (21.1) 4 (10.5) 20- < 30 30- < 40
29(39.7) 8 (22.2)
14 (19.2) 8 (22.2)
χ 2 = 3.36 p > 0.05
χ2 = 39.52 p < 0.001
Fisher’s exact test =11.81 p < 0.005
χ2 = 27.74 p < 0.001
χ2 = 44.44 p < 0.001
χ2 = 42.14 p < 0.001
χ2 = 38.82 p < 0.001
χ2 = 27.42 p < 0.001
χ2 = 12.45 p > 0.05
Int J Ment Health Addiction Table 1 (continued) Variables
Level of depression
Total n (%) Test statistics
No n (%) Mild n (%) Moderate n (%) Severe n (%) ≥ 40 Type of stroke Ischaemic
4 (23.5)
4 (23.5)
3 (17.6)
6 (35.4)
17 (10.4)
22(17.1)
26(20.2)
31 (24.0)
50 (38.8)
129(78.7)
Haemorrhagic 21(75.0) 4 (14.3) 1 (3.6) Sub-arachnoid 6 (85.7) 0 0 Duration since attack of stroke (in completed month) Up to 1 29(49.2) 12(20.3) 13 (22.0)
2 (7.1) 1 (14.3)
28 (17.1) 7 (4.3)
5 (8.5)
59 (36.0)
> 1 to 3 >3 Side of hemiparesis Left side
17(23.6) 3 (9.1)
15(20.8) 3 (9.1)
17 (23.6) 2 (6.1)
23 (31.9) 25 (75.8)
72 (43.9) 33 (20.1)
20 (27.4)
14 (19.2)
16 (21.9)
23 (31.5)
73 (44.5)
29 (31.8)
16 (17.6)
16 (17.6)
30 (33.0)
91 (55.5)
45 (44.1)
22 (21.6)
16 (15.7)
19 (18.6)
102(62.2)
Yes 4 (6.5) 8 (12.9) 16 (25.8) Ability to perform activity of daily life (without others help) Can perform 41(71.9) 8 (14.1) 4 (7.0)
34 (54.8)
62 (37.8)
4 (7.0)
57 (34.8)
Cannot perform Caregiver Spouse
Right side Dysphasia No
8 (7.4)
22 (20.6)
28 (26.2)
49 (45.8)
107 (65.2)
8 (12.9)
16 (25.8)
18 (29.0)
21 (32.3)
63 (59.0)
Children/others Social contact No
0
6 (14.0)
9 (20.9)
29 (65.1)
44 (41.0)
6 (9.7)
9 (14.5)
13 (21.0)
34 (54.8)
62 (37.8)
Yes Smoking status Never smoked
43 (42.2)
21 (20.6)
19 (18.6)
19 (18.6)
102 (62.2)
35 (31.3)
21 (18.8)
22 (19.6)
34 (30.4)
112 (68.3)
14 (26.9)
9 (17.3)
10 (19.2)
19 (36.5)
52 (31.7)
41 (53.2)
13 (16.9)
13 (16.9)
10 (13.0)
77 (47.0)
8 (9.2)
17 (19.5)
19 (21.8)
43 (49.4)
87 (53.0)
15 (62.5)
3 (12.5)
1 (4.2)
5 (20.8)
24 (14.6)
34 (24.3)
27 (19.3)
31 (22.1)
48 (34.3)
140 (85.4)
Past smoker Diabetes mellitus No Yes Hypertension No Yes
Fisher’s Exact test = 43.57 p < 0.001
χ2 = 70.54 p < 0.001
χ2 = 0.74 p > 0.05
χ2 = 37.56 p < 0.001
χ2 = 76.86 p < 0.001
χ2 = 13.89 p < 0.005
χ2 = 30.14 p < 0.001
χ2 = 0.68 p > 0.05
χ2 = 43.98 p < 0.001
χ2 = 15.07 p < 0.005
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Table 3 presents the univariate logistic regression analysis of factors associated with depression. Participants in the age group 51–60 and ≥61 years, living in a joint family, those with duration of stroke 1–3 and >3 months, those who cannot perform daily activities by themselves, have no social contact, and those with dysphagia, diabetes and hypertension had significantly higher depression. In the multivariate analysis, factors significantly associated with depression were living in a joint family (OR = 13.5, 95 % CI = 1.3–145.7, p = 0.032), those who cannot perform daily activities by themselves (OR = 14.9, 95 % CI = 2.0–108.1, p = 0.008) and those with comorbid dysphasia (OR = 9.5, 95 % CI = 1.0–86.9, p = 0.046) and hypertension (OR = 5.2, 95 % CI = 2.3–15.4, p = 0.012). (Table 4).
Discussion This is the first study to assess the prevalence and factors associated with depression among post-stroke patients in Bangladesh, to the best of our knowledge. Our results show that more than two-thirds of patients (70 %) with stroke had some form of depressive symptoms and 32 % had severe depression. A recent systematic review showed depressive disorders ranging from 25 to 79 % among people suffering from a stroke and the prevalence of post-stroke major depression ranged from 3 to 40 %, which is similar to our findings (Bartoli et al. 2013). A study on depression among stroke survivors in India reported that the prevalence of PSD was 36.98 % (95 % CI 31.89–42.06 %) using geriatric depression scale (Paul et al. 2013). This variation may be due to the fact that majority of the studies were performed in the developed countries. Socio-demographic characteristics of developed countries including modern and developed treatment and rehabilitation facilities may play an important role in reducing the frequency of depression. Also various depressions measuring scale may influence in differing the proportion of depression. A greater number of our study participants were males, which is similar to other studies in neighboring countries (Pandian et al. 2012; Srivastava et al. 2010). In our study, the mean depression score and proportion of mild, moderate and severe depression were also higher among female than male, which is in line with previous studies (Eriksson et al. 2004; Sun et al. 2014). The mean ± SD of age of the respondents was 58.91 ± 7.03, which is lower than the average age (73 years) at which stroke occurs in developing countries (T Truelsen et al. 2006). Older participants in our study had more severe depression. Kotila and colleagues also found higher prevalence of severe depression in older age groups (Kotila et al. 1998). However, older age was not significantly associated with depression in our study, which might be due to smaller sample size. In this study, we found socio-economic status was associated with PSD. Almost half of our respondents had higher education which is higher than the national average and was a protective factor for PSD (Bangladesh Bureau of Statistics 2014; Paul et al. 2013). Similarly, the average monthly family income of the respondents (26,378.05 ± 10,427.24 BDT) was quite high in relation to per capita income of Bangladesh and people with less income showed higher depression (Bangladesh Bureau of Statistics 2014). Similarly, those with no education had higher prevalence of depression. Though the agricultural workers were very small part of the respondents (5.5 %) all of them were sufferer of some level of depression. Single persons and those living alone had higher depression in our study, which is similar to findings from Astrom and colleagues (Aström et al. 1993). A recent study in India showed that compared to the non-depressed group, PSD subjects were significantly older, had higher age at first stroke,
Int J Ment Health Addiction Table 2 Characteristics of participants by depression score (n = 164) Characteristics
Sex Age Groups
Residence Marital status Education status
Main occupation
Type of family Family size (in number)
Monthly family income (000, BDT)
Duration since attack of stroke
Type of Stroke
Care giver Social contacts Smoking status Diabetes Hypertension IHD
No.
Depression score Mean
SD
Male
112
14.13
6.97
Female
52
15.04
5.93
≤ 50
29
9.55
4.58
51–60
65
13.02
5.70
Above 60
70
17.74
6.56
Urban
150
13.97
6.64
Rural
14
19.21
4.82
Married
140
13.62
6.58
Single
24
19.08
5.11
Illiterate
19
19.63
6.36
Up to SSC
35
16.60
6.02
Up to HSC
34
14.21
5.25
Graduate and above
76
12.21
6.63
Service
42
9.90
4.39
Agriculture
8
19.00
5.24
Business
27
14.22
6.35
Housewife
47
15.51
5.98
Retired
40
17.05
7.52
Nuclear
90
12.01
6.18
Joint
74
17.35
6.04
1 to 3
19
11.16
6.99
4 to 6
108
13.69
6.35
7 and above
37
18.22
5.85
< 20
38
17.16
7.12
20- < 30
73
12.40
5.40
30- 3 months
33
19.03
5.72
Ischaemic
129
19.99
6.38
Haemorrhagic
28
16.54
3.67
Sub-arachnoid
7
15.00
5.10
Spouse
63
15.89
5.70
Children/others
44
19.33
5.26
No
62
17.95
6.40
Yes
102
12.27
5.87
Never
112
13.97
6.52
Past smoker
52
15.38
6.90
Yes
87
19.49
6.07
No
77
10.95
5.50
Yes
140
19.11
6.60
No
24
10.42
5.53
Yes
14
19.86
5.54
No
150
13.91
6.54
P-value
ns
