Prevalence of depressive symptoms in patients with chronic physical illness: A single institutional cross-sectional study from Nepal

Namrata Mahara Rawal; Suman Prasad Adhikari; Sabin Rajbhandari; Santosh Bhusal; Sonali Gupta; Shreya Bhasu Piya; Soniya K.C; Susan Lama; Dhan Bahadur Shrestha

doi:10.12688/f1000research.107813.1

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Research Article

Prevalence of depressive symptoms in patients with chronic physical illness: A single institutional cross-sectional study from Nepal

[version 1; peer review: 2 approved with reservations]

Namrata Mahara Rawal¹, Suman Prasad Adhikari¹, Sabin Rajbhandari², [...] Santosh Bhusal ³, Sonali Gupta³, Shreya Bhasu Piya³, Soniya K.C³, Susan Lama³, Dhan Bahadur Shrestha⁴

Namrata Mahara Rawal¹, Suman Prasad Adhikari¹, [...] Sabin Rajbhandari², Santosh Bhusal ³, Sonali Gupta³, Shreya Bhasu Piya³, Soniya K.C³, Susan Lama³, Dhan Bahadur Shrestha⁴

PUBLISHED 11 Mar 2022

Author details Author details

¹ Department of Psychiatry, Nepalese Army Institute of Health Sciences (NAIHS), Shree Birendra Hospital, Kathmandu, Bagmati, Nepal
² Department of Internal Medicine, Nepalese Army Institute of Health Sciences (NAIHS), Shree Birendra Hospital, Kathmandu, Bagmati, Nepal
³ Intern doctor, Nepalese Army Institute of Health Sciences (NAIHS), Shree Birendra Hospital, Kathmandu, Bagmati, Nepal
⁴ Department of Internal Medicine, Mount Sinai Hospital, Chicago, Illinois, USA

Namrata Mahara Rawal
Roles: Methodology, Project Administration, Supervision, Validation

Suman Prasad Adhikari
Roles: Conceptualization, Data Curation, Methodology, Project Administration, Supervision, Writing – Original Draft Preparation

Sabin Rajbhandari
Roles: Conceptualization, Methodology, Project Administration

Santosh Bhusal
Roles: Conceptualization, Data Curation, Methodology, Project Administration, Writing – Original Draft Preparation

Sonali Gupta
Roles: Conceptualization, Methodology, Writing – Original Draft Preparation

Shreya Bhasu Piya
Roles: Conceptualization, Methodology, Writing – Original Draft Preparation

Soniya K.C
Roles: Conceptualization, Methodology, Writing – Original Draft Preparation

Susan Lama
Roles: Conceptualization, Methodology, Writing – Original Draft Preparation

Dhan Bahadur Shrestha
Roles: Data Curation, Formal Analysis, Methodology, Project Administration, Supervision

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REVIEWER STATUS

Abstract

Background
Depression is a global public health problem. Studies show comorbid depression increases morbidity, mortality, and associated risk of poor adherence compared to those without depression.
Materials and Method
An analytical cross-sectional study was conducted among 326 patients who met the inclusion criteria. They were selected following simple random sampling from medical OPD and ward of Shree Birendra Hospital Kathmandu, Nepal. Semi-structured interview schedule (SSIS), Beck Depression Inventory-II (BDI-II), and Kuppuswamy’s Scale (KS) were used for data collection. Data analysis was done using SPSS version 26 and STATA version 15. Simple frequency distribution of attributes presented in tables and association assessed using Chi-square/ Fisher’s exact test. Further, the relation between depression and other independent factors is quantified using multivariate/ multivariable logistics regression analyses.
Result
Using Beck depression inventory (BDI-II) as a tool to determine depression 52.1% (n=170) had minimal or no depression, 16.9% (n=55) had mild depression, 18.7 %( n=61) had moderate depression and 12.3% (n=40) had severe depression i.e. 47.9% of population had some form of depression. Prevalence of depression among patient with single comorbidity found to be 30.9% (n=25, N=81) for hypertension, 43.3% (n=13, N=30) for diabetes mellitus, 45.6% (n=31, N=68) for chronic obstructive pulmonary disease, 77.5% (n=31, N=40) for chronic kidney disease, and 60 %( n=9, N=15) for chronic heart disease. Depression among patient with multiple comorbidities (more than one disease above mention) was found to be 51.1% (n=47, N=92). Prevalence of depression was more among patients with history of longer duration of illness; 11 years and above 52.9 % (n=36, N=68); 6-10 years 48.3 % (n=43, N=89); 1-5 years 45.6 %( n=77, N=169).
Conclusion
This study showed that the prevalence of depression has a significant relationship with the duration of illness. Therefore, early recognition and treatment play a crucial role in reducing the effects of depression.

Keywords

Depression, Hypertension, Diabetes Mellitus, Chronic Obstructive, Renal Insufficiency, Chronic, Heart Diseases, Nepal

Corresponding author: Santosh Bhusal

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2022 Mahara Rawal N 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 work is properly cited.

How to cite: Mahara Rawal N, Adhikari SP, Rajbhandari S et al. Prevalence of depressive symptoms in patients with chronic physical illness: A single institutional cross-sectional study from Nepal [version 1; peer review: 2 approved with reservations]. F1000Research 2022, 11:302 (https://doi.org/10.12688/f1000research.107813.1) First published: 11 Mar 2022, 11:302 (https://doi.org/10.12688/f1000research.107813.1) Latest published: 11 Mar 2022, 11:302 (https://doi.org/10.12688/f1000research.107813.1)

Introduction

Depression is a major evolving health problem imposing a significant disease burden globally and is one of the leading causes of morbidity and mortality worldwide across all age groups. In addition, it is one of the important risk factors for increasing the incidence of suicides, drug abuse, and social and educational dysfunctions.¹ Furthermore, depression is more common in women, more so over in younger age groups, in people with low socioeconomic backgrounds, and people who spend their life alone.²

With lifestyle modifications, the prevalence of chronic physical illnesses has been sharply rising, which causes an increase in depression in these patients. People with chronic physical illnesses like diabetes, hypertension, chronic obstructive pulmonary disease (COPD), and so on experience a greater risk for comorbid depression than those who do not have these diseases. Moreover, depression over time impair the quality of life and alters treatment adherence compared to those without depression.³^–⁵

A meta-analysis by Solano et al., shows a prevalence of depression between 13 and 79% in people with different chronic physical diseases (cancer, heart disease, renal disease, and COPD).⁶ Other studies show the prevalence of depression among chronic kidney disease (CKD) patients is 44.1%,⁷ 26.8% among hypertensive patients,³ and 33.3% among COPD patients.⁸ In addition, studies in Nepal shows the prevalence of diabetes mellitus (DM) type II is 29.2%,⁹ among COPD patient is 69.2%.¹⁰

In developing countries like Nepal, where health care facilities and human resources are limited, no conclusive research explains depression in this region. Therefore, the general objective of this research is to determine the prevalence and correlation of depressive symptoms in patients with chronic physical illness and relation to attributes of depressive symptoms. Thus, this research will help provide baseline information on depression among patients with chronic diseases and its characteristics, which will help recognize and treat underlying depression early, improve patient quality of life, lower morbidity, and mortality of the disease, hence lower the burden of depression.

Methods

Ethics statement

All the participants were explained about the research, and the process was carried out only after obtaining informed written consent from the patient and the primary caretaker. The study was conducted following the protocol and approval by the Ethical Review Committee of the Nepalese Army Institute of Health Sciences (NAIHS; Reference no: 385).

Study design

This cross-sectional analytical study was conducted among the patients receiving out-patient and in-patient services for chronic medical illnesses from the medical department of the Shree Birendra Hospital, a multidisciplinary tertiary-level hospital. It is a 635 bedded central and referral hospital that caters for the medical and healthcare needs of people affiliated to the Nepalese army and their dependents. This hospital was selected for the survey as this is a multidisciplinary well equipped tertiary level referral center with adequate patient flow from all over Nepal especially for the Nepalese army and their families, and also a working center for most of the authors. Data for the analysis was collected over four months (February - May 2021). This survey was made among the patients who visit the medical OPD for regular follow-up and those who get admitted to the medical ward with complications because of the disease condition mentioned above. At the time of data collection, all the participants were informed about the study and its objectives, and informed written consent was obtained from those participants who were willing to volunteer for the study (Extended data/ file 1).¹¹ As the participants were surveyed once, a follow-up session of cases was not done. The authors had surveyed the participants physically using the pre-structured interview questionnaire in an English format by translating it into Nepali without disturbing the actual meaning of the sentence (Extended data/ file 3).¹¹ Translation of the questionnaire was completed by the authors. A semi-structured proforma and Kuppuswamy’s scale modified for Nepalese context by Joshi and Acharya (2019)¹² was used to obtain the socio-demographic and clinical variables (Extended data/ file 2).¹¹ To assess the prevalence of depressive symptoms the Beck depression Inventory-II questionnaire, a 21-item self-reporting questionnaire was used (Extended data/file 2).¹¹^,¹³

Sample size

The sample size was 326, which was determined using Cochran’s formula:

n = (z^{2} * p * q) / e^{2}

Where p is the prevalence of depression in chronic physical illness taken from the previous study by Sharma S et al., i.e., 69.2%,¹⁰ z is 1.96 at 95% confidence level, q is (1-p), and e is the margin of error, i.e., 5%.

Participants

After reviewing the Shree Birendra Hospital annual record sheet, patients diagnosed with hypertension, DM, COPD, CKD, and congestive heart disease (CHD) (the five most prevalent chronic illnesses at this hospital) were included. Participants who were diagnosed by the treating physician of Shree Birendra Hospital and receiving medication for at least a year who could respond/express well and give consent were eligible for participation. The patients too unwell to participate were excluded from the study. The cases were selected by simple random sampling adopting the lottery method from the medical in-patient and out-patient departments of Shree Birendra Hospital. Participants were interviewed physically by authors at the outpatient and inpatient department respectively using the pre-structured interview questionnaire. Collected data were then entered in IBM SPSS statistics data editor, and then analysis was done partly using SPSS version 26 and STATA version 15 (https://www.stata.com/).

Exposure variables

Demographic and socio-economic variables such as gender (male/female), residence (rural/urban), education (illiterate/literate/primary/secondary/higher secondary), marital status (married/widowed/separated/unmarried), religion (Hindu/Buddhist/Christian/Others), Kuppuswamy’s score (upper middle/lower middle/upper lower/lower), physical activity (sedentary/non-sedentary), sleep (adequate/inadequate), substance abuse (alcohol/smoking/both/none/missing), comorbidities (Hypertension/DM/COPD/CKD/CHD/multiple comorbidities), duration of illness (1-5 years/6-10 years/11 years and above), and past history of depression (yes/no) were included in the survey questionnaire (Extended data/file 2).¹¹

Outcome variable

This study used the BDI-II questionnaire¹³ along with the socio-demographic questionnaire.¹¹ The internal consistency BDI-II questionnaire was positively correlated with the Hamilton depression rating scale.¹⁴ The BDI can be used for ages 13 to 80.¹³ The validity and reliability of the BDI have been tested across populations, worldwide.¹⁵^–¹⁹

The inventory contains items on a four-point scale ranging from zero to three (symptoms absent to severe symptoms), and the total score varies from 0 to 63. Thus total score in patients diagnosed with depression is classified as (0–13) minimal, (14-19) mild, (20-28) moderate, and (29-63) severe depression.¹³^,¹⁴ Cases with scores 14 and above were considered to have some form of depression in our study.

The socio-demographic questionnaire was standardized based on 13 variables as provided by GESIS survey guidelines²⁰ and harmonization of the questionnaire was based on the socio-cultural practice of Nepal.

Since Nepal does not have a standardized socio-economic scale for its population, Kuppuswamy’s scale modified for the Nepalese context by Joshi and Acharya, 2019 was used.¹¹^,¹² It comprises three parameters with a score range for education (1-7), occupation of the head of the family (1-10), and total monthly family income (1-12). The modified Kuppuswamy scale differs from Kuppuswamy socioeconomic scale (1976) only in the context of total monthly family income which has been updated using the latest national consumer price index of Kathmandu valley (NCPI) provided by the Nepal Rastra Bank. The total scores vary from 3 to 29 and based on the scoring the population is grouped into five different socio-economic classes: upper (26-29), upper-middle (16-25), lower-middle (11-15), upper-lower (5-10), and lower (less than 5).¹²

Statistical analysis

Data analysis was done partly using a statistical package for the social sciences (SPSS) version 26 and STATA version 15. This analysis can be made alternatively with PSPPIRE data editor (PSPP) a freely accessible statistical software. First, a simple descriptive analysis was done, and socio-demographic variables determining the depression were presented in table and text as appropriate. Then chi-square/Fisher’s exact test was employed to check the association between Beck scales-based diagnosis of depression with other independent socio-demographic variables studied. Finally, multivariate logistic regression was performed considering the diagnosis of depression as an outcome of interest (with 1 = depression and 0 = no depression). Gender, education, residential setting, other socio-demographic variables, and chronic illness were considered independent variables, and diagnosis of depression was taken as the dependent variable. The pseudo-R² value for the logistic model was 0.2341, indicating an acceptable model fit.

The treatment record book of the patients was thoroughly studied and those cases receiving treatment for additional comorbidities other than the aforementioned diseases were excluded which helped to minimize the confounding bias. As the selected cases in the study were not followed-up, there was an increasing chance of repetition of the cases which was avoided by asking every participant if they had participated in the same study recently. Furthermore, a meticulous study of all the data set recorded aided in preventing case repetition.

Results

A total of 326 patients took part in the survey.²¹ All socio-demographic variables and outcomes are presented in frequency distribution (Table 1). Out of 326 patients, 175 (53.7%) were male while 151 (46.3%) were female, 189 (59%) were residents of rural regions and 137 (42%) from urban regions. The majority of the patients were illiterate 142 (43.6%), while 95 (29.1%) were literate, 32 (9.8%) had primary level education, 38 (11.7%) had secondary level education, and only 19 (5.8%) had higher secondary level education. More than 260 (79.8%) patients were married, while 66 (20.2%) were widowed. The bulk of patients, 300 (92%), were Hindu by religion, followed by 22 (6.7%) Buddhism, 3 (0.9%) Christian. On the Kuppuswamy scale, 164 (50.3%) fall under the upper lower class category and 139 (42.6%) under the lower middle class. 173 (53.1%) had a sedentary lifestyle while 153 (46.9%) had a non-sedentary lifestyle. On sleep habits, 180 (55.2%) had adequate sleep while the remaining 146 (44.8%) had inadequate sleep (< 7 hours a day). About substance abuse, in most of the cases, 161 (49.4%) didn’t use any abusive substance, followed by 80 for cigarette smoking (24.5%), 47 with both smoking and alcohol abuse (14.4%), and 32 for alcohol (9.8%). From the cases we had selected, the majority of the patients suffered from multiple comorbidities in the study with 92 (28.2%) followed by hypertension 81 (24.8%), COPD 68 (20.9%), CKD 40 (12.3%), DM 30 (9.2%) and CHD 15 (4.6%). The majority of the patients, 169 (51.8%), have had their disease for 1-5 years, and 318 (97.5%) have had a history of depression in the past. With the use of the BDI-II screening tool for depression, we found that 170 (52.1%) had minimal depression, 55 (16.9%) had a mild form of depression, 61 (18.7%) had a moderate form of depression, and 40 (12.3%) had severe depression. In total 47.9% of the study population had some form of depression.

Table 1. Frequency distribution of baseline sociodemographic variables for study participants.

Variables		Frequency	Percent
Gender	Male	175	53.7
Gender	Female	151	46.3
Residency	Rural	189	58.0
Residency	Urban	137	42.0
Education	Illiterate	142	43.6
	Literate	95	29.1
	Primary	32	9.8
	Secondary	38	11.7
	Higher secondary	19	5.8
Marital status	Married	260	79.8
Marital status	Widowed	66	20.2
Religion	Hindu	300	92.0
	Buddhist	22	6.7
	Christian	3	.9
	Others	1	.3
KS	Upper middle	17	5.2
	Lower middle	139	42.6
	Upper lower	164	50.3
	Lower	6	1.8
Physical activities	Sedentary	173	53.1
Physical activities	Non-Sedentary	153	46.9
Sleep	Adequate (>7 hours a day)	180	55.2
Sleep	Inadequate (< 7 hours a day)	146	44.8
Substance abuse	Alcohol	32	9.8
	Smoking	80	24.5
	Both	47	14.4
	None	161	49.4
	Missing	6	1.8
Comorbidities	Hypertension (HTN)	81	24.8
	Diabetes mellitus (DM)	30	9.2
	Chronic obstructive pulmonary disease (COPD)	68	20.9
	Chronic kidney disease (CKD)	40	12.3
	Congestive heart disease (CHD)	15	4.6
	Multiple comorbidities	92	28.2
Duration of illness	1-5 years	169	51.8
	6-10 years	89	27.3
	11 years and above	68	20.9
History of depression	Yes	8	2.5
History of depression	No	318	97.5
Depression	Minimal (0-13)	170	52.1
	Mild (14-19)	55	16.9
	Moderate (20-28)	61	18.7
	Severe (29-63)	40	12.3

Data evaluation with cross-tabulation of depression with nature of illness of individuals, the prevalence of depression among hypertension, diabetes mellitus, chronic obstructive pulmonary disease, chronic kidney disease, congestive heart disease was 30.9%, 43.3%, 45.6%, 77.5%, and 60.0%, respectively. While the prevalence of depression among patients with multiple comorbidities (more than one disease mentioned above) was 51.1% (Table 2).

Table 2. Cross-tabulation of depression with nature of the illness.

Chronic physical illness	No. of patients (N)	Minimal or no depression [n (%)]	Depressed [n (%)]
Hypertension (HTN)	81	56 (69.1)	25 (30.9)
Diabetes mellitus (DM)	30	17 (56.7)	13 (43.3)
Chronic obstructive pulmonary disease (COPD)	68	37 (54.4)	31 (45.6)
Chronic kidney disease (CKD)	40	9 (22.5)	31 (77.5)
Congestive heart disease (CHD)	15	6 (40.0)	9 (60.0)
Multiple comorbidities	92	45 (48.9)	47 (51.1)

Data evaluation with cross-tabulation of depression with a duration of illness, the prevalence of depression among patients with duration of illness 1 to 5 years, 6 to 10 years, and 11 years and above was found to be 45.6%, 48.3%, and 52.9% respectively (Table 3).

Table 3. Cross-tabulation of depression with duration of illness.

Duration of illness (Years)	No. of patients (N)	Minimal or no depression [n (%)]	Depressed [n (%)]
1-5	169	92 (54.4)	77 (45.6)
6-10	89	46 (51.7)	43 (48.3)
11 years and above	68	32 (47.1)	36 (52.9)

Using chi-square/Fisher’s exact test to check the association between depression (dependent variable) and other independent variables showed a statistically significant association between education, physical activities, sleep, substance abuse, and comorbidities (p<0.05). Both male and female with (23.9%), living in the rural region (27.6%), illiterate (23.6%), married (37.7%), following Hindu religion (44.5%), falling under Kaposi scale of lower/upper lower class (22.7%), with a sedentary lifestyle (32.8%). Furthermore, those having inadequate sleep (30.1%) and not using any form of substance abuse (21.6%) with multiple comorbidities (14.4%) and a duration of illness about 1-5 years (23.6%) and no history of depression (46.9%) were found to be depressed (Table 4).

Table 4. Cross-tabulation of depression with socio-demographic variables using Chi-square/Fisher exact test.

Variables		Depression		p-value
Variables		Minimal or no depression	Depressed	p-value
Gender	Male	97(29.8)	78(23.9)	.202
Gender	Female	73(22.4)	78(23.9)	.202
Residency	Rural	99(30.4)	90(27.6)	.921
Residency	Urban	71(21.8)	66(20.2)	.921
Education	Illiterate	65(19.9)	77(23.6)	.017
	Literate	47(14.4)	48(14.7)
	Primary	17(5.2)	15(4.6)
	Secondary	26(8.0)	12(3.7)
	Higher secondary	15(4.6)	4(1.2)
Marital status	Married	137(42.0)	123(37.7)	.696
Marital status	Widowed	33(10.1)	33(10.1)	.696
Religion	Hindu	155(47.5)	145(44.5)	.965*
	Buddhist	12(3.7)	10(3.1)
	Christian	2(.6)	1(.3)
	Others	1(.3)	0(0.0)
KS	Upper middle	8(2.5)	9(2.8)	.653*
	Lower middle	70(21.5)	69(21.2)
	Upper lower	90(27.6)	74(22.7)
	Lower	2(.6)	4(1.2)
Physical activity	Sedentary	66(20.2)	107(32.8)	.000
Physical activity	Non Sedentary	104(31.9)	49(15.0)	.000
Sleep	Adequate (> 7 hours a day)	122(37.4)	58(17.8)	.000
Sleep	Inadequate (< 7 hours a day)	48(14.7)	98(30.1)	.000
Substance abuse	Alcohol	16(5.0)	16(5.0)	.048
	Smoking	43(13.4)	37(11.6)
	Both	16(5.0)	31(9.7)
	None	92(28.8)	69(21.6)
Comorbidities	Hypertension (HTN)	56(17.2)	25(7.7)	.000
	Diabetes Mellitus (DM)	17(5.2)	13(4.0)
	Chronic obstructive pulmonary disease (COPD)	37(11.3)	31(9.5)
	Chronic kidney disease (CKD)	9(2.8)	31(9.5)
	Congestive heart disease (CHD)	6(1.8)	9(2.8)
	Multiple comorbidities	45(13.8)	47(14.4)
Duration of illness	1-5 years	92(28.2)	77(23.6)	.586
	6-10 years	46(14.1)	43(13.2)
	11 years and above	32(9.8)	36(11.0)
Past history of depression	Yes	5(1.5)	3(.9)	.725*
Past history of depression	No	165(50.6)	153(46.9)	.725*

* Fisher exact test.

Multivariate logistic regression analysis showed, in comparison to illiterate patients, those with secondary and higher secondary level education had 72% (aOR, 0.28; 95% CI, 0.096-0.82) and 89% (aOR, 0.11, 95% CI, 0.025-0.52) lower odds for depression. Similarly, compared to those with active lifestyles, individuals living sedentary lifestyles had 2.97 higher odds of having depression (95% CI, 1.67-5.29). Additionally, individuals with inadequate sleeping (< 7 hours a day) had 4.34 higher odds of having depression (95% CI, 2.47-7.61) in comparison to those with adequate sleep. Interestingly, people with CKD only seem to have a higher rate of depression than people with hypertension; however, for other comorbidities, no significant differences were observed (Table 5).

Table 5. Cross-tabulation of the different variables with depression using multivariate Logistic regression analysis.

Depression	Adjusted Odds Ratio (aOR)	[95% Conf. Interval]		z	Std. Error	p-value
Gender (Male^®)
Female	1.729803	.9004463	3.323041	1.65	.5762051	0.100
Residence (Rural^®)
Urban	1.167929	.6471864	2.107676	0.52	.3517876	0.606
Education (Illiterate^®)
Literate	.6610418	.3243987	1.347035	-1.14	.2400853	0.254
Primary	.683752	.2440105	1.91597	-0.72	.3594592	0.470
Secondary	.2801866	.0957966	.8194924	-2.32	.1534235	0.020
Higher secondary	.1130048	.024623	.5186234	-2.80	.0878541	0.005
Marital status (Married^®)
Widowed	.8487277	.4168471	1.728064	-0.45	.3078941	0.651
Religion (Hindu^®)
Buddhist	.4678298	.1453953	1.505308	-1.27	.2789482	0.203
Christian	1.040163	.0744586	14.53073	0.03	1.39941	0.977
Socioeconomic status (Upper middle^®)
Lower middle	.5344678	.1224121	2.333559	-0.83	.4019159	0.405
Upper lower	.2847329	.0657868	1.232358	-1.68	.2128465	0.093
Lower	.3006669	.0264915	3.412432	-0.97	.3726463	0.332
Physical Activities (Non-sedentary^®)
Sedentary	2.969955	1.666664	5.292388	3.69	.8754297	0.000
Sleep (Adequate^®)
Inadequate (< 7 hours a day)	4.338688	2.474334	7.607793	5.12	1.243192	0.000
Substance Use (Alcohol^®)
Smoking	.8494603	.2921824	2.469631	-0.30	.4625409	0.764
Both	1.532005	.4934687	4.756205	0.74	.8855094	0.461
None	.5506143	.2046736	1.481266	-1.18	.2780142	0.237
Illness (Hypertension^®)
Diabetes mellitus (DM)	1.560417	.5332527	4.56613	0.81	.854832	0.417
Chronic obstructive pulmonary disease (COPD)	.8800115	.3735131	2.073342	-0.29	.3847795	0.770
Chronic kidney disease (CKD)	6.266627	2.140172	18.34928	3.35	3.435045	0.001
Chronic heart disease (CHD)	1.441304	.3569168	5.820286	0.51	1.026434	0.608
Multiple Comorbidities	1.903552	.9024173	4.015338	1.69	.7249168	0.091
Duration of illness (1-5 years^®)
6-10 years	1.233696	.6441552	2.362795	0.63	.4090347	0.526
11 and above	1.260739	.5993931	2.651788	0.61	.4782766	0.541
Past history of depression (Yes^®)
No	2.00365	.4323598	9.285355	0.89	1.567648	0.374
Constant	.3109793	.0266738	3.62558	-0.93	.3896901	0.351

Discussion

This study divulged that most patients with chronic physical illness had minimal depression followed by mild depression. In the present study, the prevalence of depressive symptoms was equal among males and females (23.9%) and was more prevalent among illiterate individuals (23.6 %); however, a study by Lam M et al., among adults of Nepal reported a higher prevalence of depressive symptoms among females (24.1%) and disclosed that adults who had no formal education had a higher prevalence of depression (28.8%).²² Moreover, this study revealed that 23.6% of the patients with chronic medical illness developed symptoms of depression within 1-5 years of diagnosis.

Here, we found that the depression rate was higher among participants with multiple illnesses, i.e., 14.4%, than those with a single illness. In this study, 45.6% of participants with COPD were depressed, and this finding was compared to the finding from the study by Sharma S et al., in 2018 in which 69.2% of participants had depression.¹⁰ Also, the study by Negi H et al. reported 53.9% of participants were depressed.⁸ In this study, 77.5% of participants with CKD had depressive symptoms. A cross-sectional study by Ahlawat R et al. revealed that 44.8 % of patients with CKD were depressed.⁷

According to this study, 43.3% of participants with type 2 diabetes mellitus had depressive symptoms similar to the finding from the study by Joshi S et al. in 2015, where 44.1 % of participants had depressive symptoms.²³ A cross-sectional study done among persons with type 2 diabetes mellitus by Niraula K et al., revealed that 40.3 % of participants had clinical depression, which supported this study.²⁴ A cross-sectional study conducted among persons with hypertension in urban Nepal by Neupane D et al. disclosed that 15 % of participants had undiagnosed depression,²⁵ which was lower than this study where 30.9% of participants with hypertension had depressive symptoms.

In the present study, 60% of participants with chronic heart disease showed depressive symptoms; this finding was found to be higher than the finding of a study done among patients with cardiac disease in public health institute in 2019 by Bahall M which revealed 40% of hospitalized patients with cardiac disease had clinically significant depression.²⁶ According to a study by Dhital P et al., all among patients with coronary artery disease, 23.8% of participants had depression.²⁷

Our study showed a higher prevalence of depressive symptoms among patients with CKD; therefore, CKD patients have higher odds of having depressive symptoms in comparison to hypertensive patients. Moreover, participants with secondary education have more odds of having depression than illiterate ones. In addition, people with a sedentary lifestyle and inadequate sleep have more odds of acquiring depression when compared to the ones with a non-sedentary lifestyle and adequate sleep, respectively. The findings from our study were similar to other studies conducted in Nepal and those conducted in other countries. In the present study, we evaluated socioeconomic, clinical, and behavioral factors for the prevalence of depressive symptoms among patients with chronic physical illness. In addition, the presence of such symptoms was evaluated using the BDI-II scale.

Limitations

Our study is a small single-center study; therefore, the findings might not be applicable around the country/globally. Also, this simple cross-sectional study could not establish the determining causal relationship. Furthermore, the lack of comparison groups limits its control over unobserved heterogeneity among the respondents. Chronic physical illness includes a myriad of diseases; therefore, it was only feasible for us to include the top five chronic physical illnesses prevalent in Shree Birendra Hospital. Many chronic diseases were bound to be missed in this study.

Conclusion

In conclusion, this study established that depressive symptoms were more prevalent among illiterate and married individuals with chronic illnesses living in rural areas. People with inadequate sleep and following a sedentary lifestyle are prone to be depressed. Patients with multiple illnesses were more depressed than those with only one illness but the symptoms were found to be higher among CKD and CHD patients. Hence, patients with CKD have a higher odds ratio of having depressive symptoms in comparison to hypertension. Similarly, patients with a history of duration of illness 1-5 years were more depressed but the symptoms were found to be higher among patients with a history of duration of illness of 11 years and above.

Data availability

Underlying data

Figshare: Prevalence of depressive symptoms in patients with chronic physical illness: A single institutional cross-sectional study from Nepal. DOI: https://doi.org/10.6084/m9.figshare.19032668.v3.²¹

The project contains the following underlying data:

• Working data.sav: (Data set with quantitative data on age, gender, residence, chronic illness, socioeconomic status, BDI-II score, past history of depression, physical activities, sleep, substance abuse, education, marital status, and religion data gathered in this study)

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

Extended data

Figshare: Prevalence of depressive symptoms in patients with chronic physical illness: A single institutional cross-sectional study from Nepal. DOI: https://doi.org/10.6084/m9.figshare.17307074.v6¹¹

The project contains the following extended data:

• File 1: Informed consent form (in English and Nepali)
• File 2: Questionnaire English format (socio-demographic and BDI-II questionnaire and Kuppuswamy’s socioeconomic scale in context to Nepal used in this study in English)
• File 3: Questionnaire Nepali Format (socio-demographic and BDI-II questionnaire and Kuppuswamy’s socioeconomic scale in context to Nepal used in this study in Nepali)

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

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VERSION 1 PUBLISHED 11 Mar 2022