Introduction
The Kerala govt announced a lockdown on 23rd march and the rest of the state declared a lockdown on 25th march 2020.1 Following that, the number of cases increased, and a nationwide lockdown was enforced in India. The socio-economic damage has affected people who were poor and had no proper shelter or roof. Metropolitan cities like Mumbai which has a huge migratory population living in the slums and chawls have faced difficulty in daily earnings. Residential mobility increased during the lockdown at the least in Northeastern states while extreme in the Northern state of India. 2 The mental health of people had also been affected due to high death tolls, unemployment, financial crisis, family and socialization, business, and lack of opportunity. Mental health was affected in various dimensions as parent-child interaction and stigma and isolation of COVID-positive family members especially elderly persons with comorbidities.
During COVID-19 Pandemic there were Human Behavior Changes which has caused depression among Humans. 3 About 14% of the global burden of disease has been attributed to neuropsychiatric disorders, mostly due to the chronically disabling nature of depression and other common mental disorders. 4 Mental health during the pandemic has been long neglected even though it causes substantial loss of disability-adjusted life years. India spends <2% of its annual health budget on mental health. 5 Resilience to poor mental health varies across demographics, most notably by age, gender, employment status, financial situation, and socioeconomic status. Young people, those living alone, those with lower socioeconomic status, and those who were unemployed were more likely to be in mental distress. The previous study showed the behavior changes in the Covid-19 pandemic situation towards the local people and their work like close contact mask-wearing has resulted in depression among humans which accounts for 15.97% to 20.86% prevalence. 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21
Materials and Methods
It is a cross-sectional analytical study with a sample size of 156. All COVID-19 RTPCR positive and negative patients of a containment zone during the period of 18 days (12th September 2020 to 1st October 2020). Through consecutive sampling 78 individuals having COVID-19 RTPCR reported Positive were included as cases and 78 detected negative for COVID-19 RTPCR as a comparative group in the ratio of 1:1. The prevalence of depression was studied in both positive and negative cases of COVID-19 by applying the DSM 5 scale (Fifth edition of Diagnostic and Statistical Manual of Mental Disorders used). Cognitive, emotional, behavioural and physiological processes are far more complex than what can be described in forms. The general convention in DSM-5 is to allow multiple diagnoses to be assigned to meet the criteria for more than one DSM-5 disorder. As per the DSM-5 scale questionnaire was formed with responses graded as ‘Not at all=0’, ‘Rare, less than a day or two=1’, ‘More than half a day=2’, ‘several days=3’and ‘nearly every day=4’. The total score of each question was calculated with a scoring scale. A score equal to or less than 8 is concluded as a depressive state. 22 A significant cause for depression in COVID -19 positive and negative cases was further analysed with Logistic Regression. After getting consent, a questionnaire was used as a tool for data collection and responses collected. Due to COVID appropriate precaution was taken while interacting with study subjects.
Results
As per the data analyzed, 42.95% (n=67) of the respondents were females while 57.05% (n=89) were males.Equal set (n=78) of COVID positive and negative respondents were selected under the study. The population under study were analyzed for indicators like social behavior changes noticed by family members, effects of urbanization on mental health, fear of survival, fear if anyone visits home, fear of going outside for basic necessities like groceries, decreased social-interaction and its impact on mental health,any financial crisis arising in the family or increased expenditure due to pandemic situation. The respondents belonged to varied age groups.The lowest aged respondents in both the groups, namely the covid positive and covid negative group were of 19 years while the respondent aged 80 years was highest in covid negative group and 87 years in the covid positive group. The average in covid positive group was 44.79 years while in covid negative group it was 40.37 years. All the major findings of the study are enlisted in depth in form of tables (Table 1, Table 2, Table 3, Table 4) and figures (Figure 1, Figure 2) at the end of the article.
Table 1
Depression status and socio-demographic variables
Table 2
Depression status and socio-demographic variables in COVID 19 Positive and Negative Cases
Table 3
Logistic regression COVID 19 positive and depression causes
Table 4
Logistic regression COVID 19 negative and depression causes
Discussion
The present study aimed at identifying the prevalence of depression and associated causes leading to depression among the common public in a metropolitan city like Mumbai during the period of the COVID-19 pandemic. The prevalence of depression in the study was observed to be 49.35% which was higher compared to the previous studies which were ranging from 15.95% to 20.86%. 6, 7, 8, 9, 10 High economic burden, urbanization and expanded small-scale industries and a good number of the migratory population might attribute to this variation in prevalence in Mumbai. This also indicates various factors such as socio-demographic state, health-related risk, community and interpersonal factors also have a significant influence on the mental health of the people including depression.
The socio-demographic variables associated with depression status showed some interesting results. Taking gender into consideration, the prevalence of depression is more among females (63%) than males (39%) and this difference in prevalence is statistically significant when the chi-square test is applied (p= 0.002). The same variation is seen in COVID positive and negative participants. Attitude towards urbanization stays an important factor in mental health as people tend to adapt to their urban living setup in a metropolitan city like Mumbai. While analysing the attitude toward urbanization, the prevalence of depression is more among those who feel unhappy about urbanization (60%) than those who are happy with urbanization and this difference is statistically significant (p=0.047). The COVID-19 pandemic has left a greater impact on the economic survival of people especially, those who work for daily wages, small roadside shops, restaurants and labourers of small and middle-scale industries. Thus there existed a fear of survival and such participants who feared that their survival is in danger showed a higher prevalence of depression (63%) than others (45%) with a p-value of 0.026. social distancing is one of the well-intended interventions in breaking the chain of transmission which restricts people's mobility in highly crowded places and family celebrations. It was observed that people who fear visiting someone or being visited had a higher prevalence of depression (63%) with p=0.034. Also, joint families and families with higher budget expenditures also showed a higher prevalence of depression (Table 1).
Conclusion
As it is clearly evident from the foregoing discussion, the COVID-19 pandemic has brought havoc on both the physical and mental health of common people. The physical illness has led to significant fear among the public due to higher infectivity rate, lack of adequate admission facilities higher death tolls at peaks of the pandemic. While, the mental state has been disturbed due to fear of acquiring infection, poor neighbour interaction, and economic loss that affects daily living. But unfortunately, mental illness has not acquired as much attention and effort to combat it as the physical illness of COVID-19. The pandemic has brought out the pressing necessity of paying more attention to mental disorders which have been normally ignored in India, the fact which is substantiated by less than 2 per cent allocation of the national health budget to mental disorders altogether. Further analysis shows that people who stay alone, those with limited or no socialization, poor and unsettled and uneducated people have had to bear the brunt of the disease the most. The pandemic has also deeply and adversely affected the relationship of all hues resulting in the worsening of mental health prominently depression. Now the hour demands to pay more attention to mental disorders, particularly depression. Appropriate interventions and behaviour change communication between medical professionals and the common public has to be improvised. Policymakers should consider giving special attention to identifying mental health disorders in the community.
