|Year : 2020 | Volume
| Issue : 1 | Page : 17-21
Assessment of mental health status using patient health questionnaire-9 in patients attending outpatient department at a block primary health center in Patna, Bihar
Pragya Kumar, Ditipriya Bhar, Geetika Singh, Shamshad Ahmad
Department of Community and Family Medicine, All India Institute of Medical Sciences, Patna, Bihar, India
|Date of Submission||29-May-2019|
|Date of Decision||18-Oct-2019|
|Date of Acceptance||02-Apr-2020|
|Date of Web Publication||5-Jun-2020|
Department of Community and Family Medicine, All India Institute of Medical Sciences, Phulwari Sharif - 801 505, Patna
Source of Support: None, Conflict of Interest: None
Introduction: Identification of untreated depression could be a chance of opportunity in outdoor settings. Earlier findings show a high proportion of depression among patients visiting outdoor at the tertiary level of care. We want to estimate its burden in an outdoor setting at the primary level of care.
Material and Methods: The current study was a facility-based cross-sectional study which was conducted for 3 months at a primary health center (PHC) in a rural area of Patna (Naubatpur), Bihar. Patient health questionnaire (PHQ)-9, along with sociodemographic variables, was included in the development of a semi-structured questionnaire. A trained data collector took one-to-one interview using this questionnaire.
Results: The proportion of male and female were almost equal (49% vs. 51%). The mean age of the study subjects was 38.80 ± 13 years. Most study subjects were suffering from depression (59.60%). One-third of them had mild, one-fourth had moderate, and rest had a moderately severe and severe category of depression. The mean score was 6.67 ± 5.08. In mild to the moderate category of depression, higher age group of the study subjects was more affected. In the severe category of depression, younger age group was affected worse. The prevalence of depression was almost doubled in females as compared to males in all category of depression, and this was statistically significant. The prevalence of moderately severe depression was highest in the study subjects who were illiterate.
Conclusion: PHQ-9 can be used at PHC to screen the patients with depression.
Keywords: Depression, mental health, patient health questionnaire-9
|How to cite this article:|
Kumar P, Bhar D, Singh G, Ahmad S. Assessment of mental health status using patient health questionnaire-9 in patients attending outpatient department at a block primary health center in Patna, Bihar. Indian J Community Fam Med 2020;6:17-21
|How to cite this URL:|
Kumar P, Bhar D, Singh G, Ahmad S. Assessment of mental health status using patient health questionnaire-9 in patients attending outpatient department at a block primary health center in Patna, Bihar. Indian J Community Fam Med [serial online] 2020 [cited 2020 Sep 28];6:17-21. Available from: http://www.ijcfm.org/text.asp?2020/6/1/17/286028
| Introduction|| |
Depression is known to exist in society for ages. It is an illness that affects the mental status of the person, workplace absenteeism, decreased work capacity, and high suicide rates. An estimate that 14% of the global burden of disease could be due to neuropsychiatric disorders. It may be due to the disabling nature of depression and other common mental disorders., Although depression can be reliably diagnosed, and effective pharmacological and psychotherapeutic treatments are available, it remains under-recognized and under-treated.
The primary health centers (PHCs) are the first-level contact between the patients and the doctors for the diagnosis and treatment of depression. However, only a relatively small proportion of primary care patients present specifically for the treatment of depression, indicating the need for screening of depression in this setting. Physicians may not pursue medical workup of cases that appear to be psychiatric. Patient health questionnaire (PHQ)-9 may be used to assess the severity of the depression.
The PHQ-9 is a nine-question item to patients in a primary care setting to screen for the presence and severity of depression.
The outcome of PHQ-9 is used to make a diagnosis of depression according to the DSM-IV criteria and takes <3 min.
The PHQ-9 tool takes <3 min to complete the assessment. The results are used to make a depression diagnosis based on the DSM-IV criteria. There is a total of nine items in the PHQ-9. They aim to predict the presence as well as the severity of depression. At primary care setup, PHQ-9 is frequently used to screen the patients. The questionnaire asks about the patients' personal experience in the last 2 weeks. Each item responses in the PHQ-9 range from “0” (not at all) to “3” (nearly every day).
Hence, the current study was planned with a primary objective to estimate the proportion of depression in the clients attending the outpatient department (OPD) of a PHC of rural Patna, Bihar. The secondary objective was to access the association between various degrees of depression with sociodemographic correlates.
| Material and Methods|| |
It was a facility-based observational analytical cross-sectional study.
The study was conducted at a PHC in a rural area of Patna (Naubatpur), Bihar. Naubatpur is a satellite town in Patna metropolitan region of Bihar. It is located 15 km west of Patna. It has total population of 203,594 as per the Census 2011, of which 107,103 are males while 96,491 are females.
All the persons aged between 18 and 60 years residing in Naubatpur area.
All the clients attending the OPD of Naubatpur PHC, aged between 18 and 60 years.
Adults aged between 18 and 60 years and people who will give consent to participate in the study.
People less than 18 years and more than 60 years and the clients who are already on medication for any mental illness.
The study was conducted from November 2017 to January 2018 for 3 months.
A total of 160 clients were interviewed, of which complete data were available for 151 study subjects. Hence, they were included in the final analysis. We have included all the clients in the 3-month period. Taking the proportion of mild depression as 40% from the previous study (reference), the calculated precision of the study was 7.5%.
We used nonprobability convenient sampling technique to enroll the participants for the interview.
The PHQ-9 is the nine-question depression scale of PHQ. It consists of nine multiple-choice items. Each item is scored between 0 and 3 denoting “not at all,” “some days,” and “nearly every day,” respectively. This tool is being validated in multiple settings, as well as a telephone assessment tool. The proposed cutoff points for the scores are 5, 10, 15, and 20 for mild, moderate, moderately severe, and severe depression, respectively.
An exit interview of the patients was taken by one medical student after receiving training in administering the questionnaire. We used one-to-one interview technique. Informed written consent was obtained from the participants after explaining the nature of the research. Each interview took an average of 20 min per participants.
Owing to ethical considerations, the permission was obtained from the Institutional Ethical Committee of the AIIMS, Patna, before the commencement of the study. Study subjects having scores >10 were referred to the Department of Psychiatry, AIIMS, Patna.
The data were analyzed using IBM SPSS statistical licensed SPSS 22.0 (IBM Corp. in Armonk, NY, USA). The mean with standard deviation and proportions with 95% confidence interval (CI) are used to express the results. For the ease of analysis, the five depression categories had been merged into three. As dependent variable has three levels, we applied multinomial logistic regression to know its association with independent variables. The level of significance put at 0.05.
| Results|| |
[Table 1] depicts the sociodemographic characteristics of the study subjects. The proportion of male and female were almost equal (49% vs. 51%). The mean age of the study subjects was 38.80 ± 13 years. The maximum number of the study subjects were educated up to high school (23.20%) followed by graduate and postgraduate education (20%). The least proportion of study subjects were educated up to primary school (8.60%). The largest proportion of the clients belonged to the Hindu religion (91.4%), followed by Muslim (8.6%). Most of them belonged to Other Backward Class (OBC) followed by a General category. The large proportion of the study subjects hailed from low-middle socioeconomic status (29.10%) followed by lower class (23.10%).
Most study subjects were suffering from depression (59.50%). One-third of them had mild, one-fourth had moderate, and the rest had a moderately severe and severe category of depression [Table 2]. The proportion of moderately severe and severe was very low. The mean PHQ score was 6.67 ± 5.08.
|Table 2: Distribution of study subjects according to depression categories(n =151)|
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The study subjects consulted the PHC with various morbidities. Most of them were suffering from respiratory tract infections (17.22%) followed by low backache (15.90%). The other morbidities were gastritis, body ache, and viral fever [Figure 1].
|Figure 1: Distribution of various comorbidities among respondents (n = 151)|
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The maximum number of the study subjects belonged to the age group of 50–60 years (31.82%) in the mild category of depression. In moderate one, the majority hailed from 40 to 50 years of the age category (30.55%); and in moderately severe, the majority hailed from 50 to 60 years of the age category (50%). In contrast, the severe category of depression affected younger age group category of 18–30 (50%) and 30–40 years (50%). The numbers of affected individuals were very few (6 and 4, respectively, in these categories). However, multivariate regression analysis [Table 3] did not show any significant association with the various categories of age group. The prevalence of depression was almost doubled in females as compared to males in all categories of depression, and this was statistically significant (adjusted odds ratio for moderate-to-severe category - 0.4). The prevalence of mild depression was maximum in the study subjects who were educated up to high school (34.09%) whereas moderate depression was highest in the study subjects who were either graduate or postgraduate (25%). The prevalence of moderately severe depression was highest in the study subjects who were illiterate. The prevalence of mild and moderate depression was maximum in low-middle socioeconomic class (31.81% and 41.66%, respectively). The most of the moderately severe study subjects belonged to the upper-middle socioeconomic class. The severe depressed study subjects were from lower socioeconomic class (50%). The multinomial logistic regression analysis revealed that education, cast, social class, and occupation were not significantly associated with the mild or moderate-to-severe depression [Table 3].
|Table 3: Multinomial logistic regression analysis showing association of sociodemographic characteristics and depression categories|
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| Discussion|| |
Inagaki et al. in their study estimated the prevalence of major and minor depressive as 7.4% (95% CI: 3.4–11.4) and 6.8% (95% CI: 2.6–10.9), respectively. The present study reported the prevalence of major depression as 6.6% (95% CI: 3.4–11.4), but of minor depression, it was very high (52.9%, 95% CI: 45.0–60.8). Similarly, Obadeji et al. assessed the depression on 172 patients, of which 47.8% were suffering from significant depression with approximately half of them being classified as mild which is in line with the finding of the current study. The study was done by Mahmood et al. also reported a high prevalence of depression (40%) like the current study.
The prevalence of mild depression was 29.15% by which is in line with the study done by Thour et al. The prevalence of moderate and moderately severe depression was also in line with the study done by Thour et al., which was done on type 2 diabetes mellitus patient. In the severe category of depression, younger age group was affected worse, which shows the extreme nature of illness in the younger age group. The prevalence of depression was almost doubled in females as compared to males in all categories of depression, and this was statistically significant.
The mean age of the study subjects was 38.8 ± 13 years, which is slightly less than the study done by Thour et al. The proportion of male and female were almost equal in the current study, where other study has reported greater proportion of females.
Most study subjects were suffering from depression (59.60%), whereas they did not come primarily for the complaints of depression to the PHC. This could be due to ignorance regarding the symptoms of depression or the need to treat these symptoms. The study subjects consulted the PHC with various morbidities which were respiratory tract infections (17.22%) followed by low backache (15.90%), which indicated the primary complaint for which they came to the facility.
Although mild depression was more into high school passed out (34.09%) and moderate depression was highest in graduates and postgraduates, the multinomial analysis failed to establish this association. The multinomial regression analysis did not show any significant association between depression and other sociodemographic variables, except gender. The females were at a higher risk of depression as compared to their male counterparts. Obadeji et al. found a significant association between depression and age, gender, marital status, and clinical diagnoses.
| Conclusion|| |
Patients coming to the PHC with morbidities other than psychiatric should be screened for depression using PHQ-9 and should be referred appropriately.
We acknowledge Interns of 2017 Batch, who facilitated the data collection process.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]