A community-based study of prevalence and functional status of major depressive disorder in an industrial area.

BACKGROUND: Depression is a significant public health issue that needs to be taken care of, as it poses a great economic burden on the society at large. Early identification and treatment of the patients will reduce mental morbidity and disability. AIM: The aim is to study the prevalence and functional status of subjects with major depressive disorder in the community.
MATERIALS AND METHODS: After identification of the sample population, the sociodemographic details were recorded. Subsequently, assessment was carried out by General Health Questionnaire (GHQ), Patient Health Questionnaire-9 (PHQ-9), Functional Status Questionnaire (FSQ), and Mini Mental State examination (MMSE).
RESULTS: A total of 2000 subjects were screened using the GHQ and PHQ and 544 subjects were selected. These 544 subjects were further assessed with FSQ and MMSE. Out of the 544 subjects, 65.1% had a GHQ score of <14, 22.1% had a score between 15 and 19, and 12.9% had a score of >20. The PHQ-9 score was found to be <5 in 28.9% subjects, 5-14 in 64.3% subjects, and >14 in 6.8% subjects. Majority of the sample population was in the warning zone according to the FSQ. The MMSE scores were ≥23 in 86% and ≤22 in 14% of the patients. Over 65% of the subjects were relatively mentally healthy. Out of the remaining 35%, 22% of the subjects required screening for psychiatric disorders and 13% of them did require active psychiatric intervention.
CONCLUSIONS: It would be beneficial to the community if a database is created regarding the psychiatric disorders such as depression prevalent in the community and their functional status so that the effective measures can be implemented to minimize the suffering by providing effective psychiatric care at the earliest and follow them up in the long run. Copyright:

Community-based studies from higher income countries of America and Europe have shown that only 22%–32% of mentally ill consult mental health professionals. The patients from rural parts of India are less fortunate as they have to take time to see a psychiatrist in an urban area. Mental illness is a significant public health issue that needs to be taken care of, as it poses a great economic burden on the society at large. Point prevalence for neuropsychiatric conditions is about 10% for adult population.[12]

National Mental Health Program was started by the Government of India so that mental health services can be provided to the district mental health program.[3] Pimpri-Chinchwad Municipal Corporation is one of the richest and fastest growing municipal corporations in Asia.[4] In India, depression leads to significant morbidity and socioeconomic loss.[5] It not only has a huge impact on individuals and his family but also leads to poor quality of life. It affects all spheres of one's life including day-to-day functioning, planning, and organizing executive skills and renders consistent deterioration in performance.[67] According to the survey of the World Health Organization (WHO), around 36% of Indian population is affected by depression, and by 2020, depression would rank second among disorders with significant morbidity and the most common disorder among females.[6] One in 20 individuals (5.25%) in India aged 18 years and above have suffered from depressive episode at least once in their lifespan.[34] National Mental Health Survey data reveal that most of the individuals suffering from depressive disorder are either not diagnosed early or not treated appropriately, which leads to a vicious cycle of social and functional impairment with financial crisis and increase in the severity of depression.[89]

Depression affects people irrespective of their age group, gender, and socioeconomic status. It would be beneficial to the community if a database is created regarding the psychiatric disorders such as depression prevalent in the community and their functional status so that effective measures can be implemented to minimize the suffering by providing effective psychiatric care at the earliest and follow them up in the long run. The aim of the study was to evaluate the presence of depression and assess the functional status in the community of an Urban and rural Industrial areas of Pimpri-Chinchwad.

MATERIALS AND METHODS

This cross-sectional study was carried out at Urban Health Training Center Ajmera and Rural Health Training Center Alandi affiliated to a tertiary care center located in an industrial locale of Pimpri-Chinchwad. Duration of the study was 1 year. This research project obtained the consent of the Dr D Y Patil Vidyapeeth Ethics Committee (vide letter no DYPV/EC/299/14 dated October 16, 2014). The health workers took informed consent of the study population before administering the tests.

Sample

By purposive sampling, 2000 patients were screened with the General Health Questionnaire (GHQ) and Patient Health Questionnaire (PHQ). Those identified suffering from depression were examined at the tertiary care center where investigations and definitive treatment were given.

Inclusion criteria

All cases irrespective of age were screened to find the existence of a depressive illness.

Exclusion criteria

All subjects with medical and surgical disorders.

Tools

Sociodemographic data sheet

This self-made questionnaire was used for recording demographic characteristics of the subjects.

General Health Questionnaire 12

GHQ 12 is a short, self-administered screening test. It is used to screen for the presence of psychiatric disorders in primary care centers.[10]

The Patient Health Questionnaire 9

The PHQ-9 consists of nine questions to evaluate the presence of depression and its severity.[11]

Functional Status Questionnaire

It is a self-administered functional assessment for a patient's physical, psychological, social, and role functions. It can be used both to screen the patient and monitor over time.[12]

Mini Mental Status Examination (MMSE)

MMSE was carried out to rule out any patient suffering from dementia.[13]

Procedure

After identification of the sample population, trained research assistants recorded the sociodemographic details. Subsequently, assessment was carried out by using GHQ, PHQ-9, Functional Status Questionnaire (FSQ), and MMSE. The scales were scored as per the test manuals.

Statistical analysis

The data were entered in Microsoft Excel and analyzed by SPSS Software (IBM, Chicago, USA). Descriptive statistics were presented in the form of mean, slandered deviation, percentage, etc., and test of significance used was Chi-square. Statistical analysis was carried out with the help of both descriptive and inferential statistics.

Descriptive statistics

Data summarization was carried out with the help of percentages and summary statistics was with mean, range, and standard deviation.

Inferential statistics

In inferential statistics, the analysis was done with SPSS using nonparametric tests Chi-square and Mann–Whitney U-test at 5% significance.

RESULTS

Out of 2000 subjects who were screened, 544 subjects were selected and assessed for the study. The mean age of the case group was 34.35 ± 12.61 years (range 18–88 years). Distribution of cases as per the demographic characteristics and scores on the rating scales are shown in Tables 1 and 2, respectively. Spearman's correlations between age, scores on GHQ, PHQ, FSQ, and MMSE of the study population are given in Table 3. Association of levels of depression and scores on GHQ, PHQ-9, FSQ scores (physical, psychological, role, and social), and MMSE is shown in Table 4.

Table 1

Demographic characteristics and rating scale scores of subjects with depression (n=544)

Characteristics	Frequency, n (%)
Age
<18	10 (1.8)
19-35	344 (63.2)
36-60	162 (29.8)
>61	28 (5.1)
Gender
Female	355 (65.3)
Male	189 (34.7)
Education
Graduate	75 (13.8)
Higher secondary	132 (24.3)
Illiterate	56 (10.3)
Matriculation	178 (32.7)
Primary	103 (18.9)
Occupation
Employed	352 (64.7)
Homemaker	87 (15.99)
Student	9 (1.7)
Unemployed	96 (17.6)
Marital status
Married	439 (80.7)
Single	105 (19.3)

Table 2

Rating scale scores of subjects with depression (n=544)

Rating scale	Frequency n (%)
GHQ score
<14	354 (65.1)
15-19	120 (22.1)
>20	70 (12.9)
PHQ-9 score
<4	157 (28.9)
>5-14	350 (64.3)
>15	37 (6.8)
Physical category
Warning zone	541 (99.4)
Good	3 (0.6)
FSQ: Psychological category
Warning zone	444 (81.6)
Good	100 (18.4)
FSQ: Role category
Warning zone	521 (95.8)
Good	23 (4.2)
FSQ: Social category
Warning zone	517 (95.0)
Good	27 (5.0)
MMSE
≤22	76 (14.0)
≥23	468 (86.0)

FSQ - Functional Status Questionnaire; GHQ - General Health Questionnaire; PHQ - Patient Health Questionnaire; MMSE - Mini Mental State Examination

Table 3

Spearman’s correlations between age and scores on General Health Questionnaire, Personal Health Questionnaire, Functional Status Questionnaire (physical, psychological, role, social), and Mini Mental State Examination of the study population

Spearman’s rho	Age	GHQ	PHQ	Physical	Psychological	Role	Social	MMSE
Age
Correlation coefficient	1.000	0.053	0.010	0.024	0.030	−0.092*	−0.005	0.101*
Significance (two-tailed)		0.216	0.821	0.578	0.480	0.031	0.916	0.018
GHQ
Correlation coefficient	0.053	1.000	0.526**	−0.388**	−0.381**	0.052	−0.323**	−0.199**
Significance (two-tailed)	0.216		0.000	0.000	0.000	0.220	0.000	0.000
PHQ
Correlation coefficient	0.010	0.526**	1.000	−0.334**	−0.273**	−0.002	−0.237**	−0.234**
Significance (two-tailed)	0.821	0.000		0.000	0.000	0.955	0.000	0.000
Physical
Correlation coefficient	0.024	−0.388**	−0.334**	1.000	0.550**	−0.018	0.497**	0.157**
Significance (two-tailed)	0.578	0.000	0.000		0.000	0.678	0.000	0.000
Psychological
Correlation coefficient	0.030	−0.381**	−0.273**	0.550**	1.000	0.034	0.501**	0.141**
Significance (two-tailed)	0.480	0.000	0.000	0.000		0.420	0.000	0.001
Role
Correlation coefficient	−0.092*	0.052	−0.002	−0.018	0.034	1.000	0.039	−0.025
Significance (two-tailed)	0.031	0.220	0.955	0.678	0.420		0.355	0.562
Social
Correlation coefficient	−0.005	−0.323**	−0.237**	0.497**	0.501**	0.039	1.000	0.270**
Significance (two-tailed)	0.916	0.000	0.000	0.000	0.000	0.355		0.000
MMSE
Correlation coefficient	0.101*	−0.199**	−0.234**	0.157**	0.141**	−0.025	0.270**	1.000
Significance (two-tailed)	0.018	0.000	0.000	0.000	0.001	0.562	0.000

*<0.05, **<0.01. GHQ - General Health Questionnaire; PHQ - Patient Health Questionnaire; MMSE - Mini Mental Status Examination

Table 4

Association of levels of depression and scores on General Health Questionnaire, Patient Health Questionnaire-9, Functional Status Questionnaire scores (physical, psychological, role, social), and Mini Mental State Examination

	Mean±SD								K/W (P)
	Group I		Group II		Group III	Group IV		Group V
GHQ	9±4.08		>12.71±4.99		16.37±4.80	>17.07±6.70		13.67±11.57	>157.10 (0.000)
PHQ 9	>2.29±1.59		>6.83±1.51		11.85±1.47	>16.29±2.10		24.17±2.14	>511.38 (0.000)
Physical	>23.28±8.05		>20.10±8.53		15.88±6.16	>17.36±6.19		21.33±7.31	>64.679 (0.000)
Psycho-logical	>18.34±6.22		>15.38±5.81		14.10±5.53	>13.65±4.45		20.17±9.83	>46.370 (0.000)
Role	>16.86±8.01		>17.70±6.95		17.01±6.60	>18.26±6.98		14.83±4.26	>3.650 (0.000)
Social	>23.05±9.09		>20.47±9.06		18.24±6.61	>17.29±7.55		23.33±5.47	>28.563 (0.000)
MMSE	>27.10±2.08		>26.22±2.76		25.34±2.82	>25.58±3.05		25.83±3.49	>26.974 (0.000)
	MW (P)
	I versus II	I versus III	I versus IV	I versus V	II versus III	II versus IV	II versus V	III versus IV	III versus V	IV versus V
GHQ	11759.5 (0.00)	2752 (0.00)	2752 (0.00)	2752 (0.00)	2752 (0.00)	2100.5 (0.00)	704 (0.89)	1790 (0.597)	328 (0.6)	328 (0.64)
PHQ 9	0 (0.00)	28.5 (0.00)	28.5 (0.00)	28.5 (0.00)	28.5 (0.00)	0 (0.00)	0 (0.00)	206 (0.00)	0 (0.00)	0 (0.00)
Physical	16516.5 (0.00)	5018 (0.00)	5018 (0.00)	5018 (0.00)	5018 (0.00)	3145 (0.134)	655 (0.67)	1592 (0.15)	199 (0.1)	199 (0.06)
Psycho-logical	15259.5 (0.00)	6552 (0.00)	6552 (0.00)	6552 (0.00)	6552 (0.00)	3214 (0.182)	495 (0.18)	1892 (0.95)	212 (0.1)	212 (0.08)
Role	20035.5 (0.27)	10806.5 (0.98)	10806 (0.98)	10806.5 (0.98)	10806.5 (0.98)	3679 (0.833)	483 (0.16)	1724 (0.41)	286 (0.4)	286 (0.35)
Social	17722.5 (0.003)	7403 (0.00)	7403 (0.00)	7403 (0.00)	7403 (0.00)	2919 (0.041)	523 (0.24)	1668 (0.282)	202.50 (0.006)	202 (0.06)
MMSE	117989.5 (0.005)	7115 (0.00)	7115 (0.00)	7115 (0.00)	7115 (0.00)	3348.5 (0.31)	711 (0.92)	1820 (0.69)	312 (0.5)	312 (0.51)

The sample was divided into the following groups based on the PHQ-9 scores: Group I - No depression; Group II - Mild depression; Group III - Moderate depression; Group IV - Moderately severe depression; Group V - Severe depression; KW - Kruskal-Waalis test; MW - Mann-Whitney U-test; GHQ - General Health Questionnaire; PHQ-9 - Patient Health Questionnaire; MMSE - Mini Mental Status Examination; SD - Standard deviation

DISCUSSION

The study included individuals who were between 18 and 88 years of age, with a mean age of 34.35 ± 12.61 years. In a study conducted in psychiatric patients in Pondicherry, the mean age was 39.7 ± 8.66 years, with most of the patients belonging to 35–44 years of age.[14] Yet, another group from South India reported the mean age of the psychiatry patients to be 37.51 ± 9.7 years, mostly belonging to 30–39 years of age.[15] An outpatient department-based study from South Africa reported that the mean age of their psychiatric referral subjects was 36.1 ± 11.6 years.[16] Thus, multiple studies show that the mean age at which psychiatric patients turn to the hospital is more of less the same, which is at 30–40 years. Ninety-three percent of the patients belonged to 20–60 years of age. Only 5.1% were in the older age group beyond 61 years of age. Only 1.8% were below the age of 20 years. The study group contained females, nearly double (355, 65.3%) compared to males (189, 34.7%). This is consistent with previous studies which show that depression is higher in females when compared to males.[1718]

General Health Questionnaire, Patient Health Questionnaire, Functional Status Questionnaire, MMSE

Out of the 544 subjects, 354 (65.1%) had a GHQ score of <14, 120 (22.1%) had a score between 15 and 19, and 70 (12.9%) had a score of >20. The PHQ-9 score was found to be <4 in 157 (28.9%) subjects, 5–14 in 350 (64.3%) subjects, and >15 in 37 (6.8%) subjects. The following were the findings in the FSQ scores: The physical category showed that 541 (99.4%) of the people in the warning zone and only three people in the good zone. The psychological category showed that 444 (81.6%) of subjects were in the warning zone while 100 (18.4%) in the good zone. The role category was found to have 521 (95.8%) people in the warning zone while only 23 (4.2%) in the good zone. The social category showed 517 (95%) in the warning zone. Thus, the majority of the sample population was in the warning zone according to the FSQ which shows the disability in functional status in psychiatric patients. The MMSE scores were mostly normal, i.e., ≥23 in 468 (86%) and ≤22 in 76 (14%) of the patients. These patients were evaluated for dementia and referred to dementia clinics accordingly.

Correlations between the variables

The Spearman's rho [Table 3] showed positive correlations between age and GHQ, PHQ, physical category, psychological category, and MMSE, as well as negative correlation between role and social category. Thus, the risk of depression and functional disability in the physical and psychological category increases with age. Kruskal–Wallis test [Table 4] showed that there was a significant difference in all the variables, except the role category. Furthermore, Mann–Whitney U-test [Table 4] revealed that there is a significant difference between all the variables (GHQ, FSQ scores, and MMSE), when compared between patients with no depression and mild depression. However, when comparison was carried out between patients with no depression versus those with moderate, moderately severe, and severe depression, significant difference was found in all the variables except role category. Thus, from these findings, we can establish that subjects suffering from depression are functionally at a disadvantage when compared to nondepressed subjects. Comparison between patients with mild depression and moderate depression revealed a significant difference in all variables except role category. Hence, even mild and moderate depression patients differ in their functional capabilities. Comparison between patients with mild depression and moderately severe depression revealed a significant difference in GHQ scores but no significant difference in other variables. When patients with mild depression and severe depression were compared, no significant difference in all the variables was found.

Comparison between patients with moderate depression and moderately severe depression, between patients with moderate depression and severe depression, and patients with moderately severe depression and severe depression showed no significant difference.

The WHO has estimated that depression might be the most common illness after diabetes, when we calculate the disability adjusted life years among people of all age groups.[19] Depression leads to maximum disability in the whole world when we look at the total years lost due to disability.[19] Studies have indicated that depression and neurological disorder share a two-way interlink with neurological insults increasing the risk of depression and vice versa being that persistent history of depression reflects an underlying neurological disorder.[2021] This makes screening of patients for the presence of comorbid depressive disorder as a must and reduces the negative impact of depressive disorder on the course of neurological illness and also its prognosis and treatment.[2122] National Mental Health Survey data reveals that most of the individuals suffering from depressive disorder are either not diagnosed early or not treated appropriately. This leads to a vicious cycle of social and functional impairment with financial loss and worsening of depression.[8923] Subjecting these individuals to various kinds of investigative tools revealed that some of the findings did concur with those scales that measured the psychiatric morbidity and it strengthened the diagnosis. Using the right kind of investigative scales is important in community-related projects to understand the gravity of psychological morbidity in the community so that early diagnosis and treatment can be given to those in need.

CONCLUSIONS

A total of 544 subjects were evaluated through well-established investigative tools to ascertain the psychological state of the individuals. A database was created regarding depressive disorders prevalent in the community so that effective measures can be implemented to minimize the suffering by providing effective psychiatric care at the earliest and follow them up in the long run.

Financial support and sponsorship

DPU project DPU/26/2016 supported the study.

Conflicts of interest

There are no conflicts of interest.