Introduction
Mental health is described as emotional, psychological and social well being. It influences how we feel, think and act. It helps in determining how one handles stress, makes choices and relate to others. A mental disorder is characterized by a clinically significant disturbance in an individual’s cognition, emotional regulation, or behavior.1 It is usually associated with distress or impairment in important areas of functioning. There are many different types of mental disorders. Mental disorders may also be referred to as mental health conditions. The latter is a broader term covering mental disorders, psychosocial disabilities and (other) mental states associated with significant distress, impairment in functioning, or risk of self-harm.2 In 2019, 1 in every 8 people, or 970 million people around the world were living with a mental disorder, where anxiety (301 million) and depressive disorders (280 million) were most common.3 In 2020, the number of people living with anxiety and depressive disorders rose significantly because of the COVID-19 pandemic. 4 Initial estimates show a 26% and 28% increase respectively for anxiety and major depressive disorders in just one year. When it comes to countries, India is the most depressed country in the world, according to the World Health Organization, followed by China and the USA. Depression is the most common mental disorder in India with 45.7 million people suffering from it. A higher prevalence of depressive disorders was seen in females (3.9 per cent) than males (2.7 per cent). National Mental Health Survey 2016 found that close to 14% of India’s population required active mental health interventions. Every year, about 2,00,000 Indians take their lives. 5 The statistics are even higher if one starts to include the number of attempted suicide.
Depression being a chronic debilitating condition, can impact a person’s living in all spheres—family, societal, and work; thus requiring early identification and treatment. Stress has increasingly become a common part of the urban lifestyle and has been found to be persistently prevalent among young adults. 6 Long term exposure to stress can have adverse effects on the musculoskeletal health, cardiovascular system and gastrointestinal system among other health issues, whereas short term stress can act as a trigger for fatal health events. In fact, chronic stress may cause depression and anxiety among individuals. Gender has been described as a critical determinant of mental health and mental illness. Depression is not only the most common women's mental health problem, but may be more persistent in women than men. 7 Women mental health can be conceptualized as having a wide range of related areas, including reproductive health, psychopharmacology, psychosocial determinants of mental health, and legal issues. Therefore, assessment of these factors is essential for preventive action. With this background, a community-based study was conducted with the objective to assess the burden of depression, anxiety and stress among women residing in urban slums of Jaipur and also to assess the factors affecting them.
Material and Methods
Study design and source of population
A community based cross-sectional study was conducted in an urban field practice area of the Department of Community Medicine, JNU Institute of Medical Sciences, Jaipur; Rajasthan among women aged 18-59 years. The study was carried out over a period of 2 months from March 2023 to April 2023. The Sample size was calculated as 503 using the formula 4pq/l2 and finite sample correction, taking the prevalence of depression 14.9% among women population according to Srinivasan M et al. study with 95% confidence interval, 3% allowable error and 10% non response rate. 8
Data Collection Procedures and Validity
All the 8 outreach areas which come under urban field practice area were included in the study. There are total 1042 households in the urban field practice area with a population of approximately 2760 eligible participants. Based on population proportionate to size method, the number of eligible participants in each area was visited. Data was collected by house ‑ to ‑ house survey in each area starting from the first house randomly selected till the required sample size for each area was attained in the community. Only 1 participant from each household was interviewed after taking the informed consent. If the house was locked, next house was included in the study. Participants were interviewed using a predesigned, pretested semi-structured questionnaire. The questionnaire consisted of socio-demographic details and other factors, such as the presence of debts, history of domestic violence, and addictions (alcohol/tobacco) among family members and also obstetric history. We used Depression Anxiety Stress Scale (DASS)-21 questionnaire to capture the primary outcomes—depression, anxiety, and stress. DASS-21 is a screening tool to measure depression, anxiety, and stress in the reference period of “past 1 week.” Questions in each of these three domains are based on the symptoms that would be reported by patients with above specified illnesses. The responses were captured in a four point Likert’s scale and the scores range between 0 and 42. Using the cut-offs for DASS tool, participants were classified into with/without the outcome under study. We used the Hindi version of DASS-21, which was translated to provide a better understanding of the participants. English version of DASS-21 was initially translated into Hindi version by a subject expert, which was then back-translated into English by another subject expert.
Data processing and analysis
Data was entered into Microsoft Excel and exported to Statistical Package for Social Science (SPSS) software version 22 for analysis. The categorical data was expressed as percentage/proportions and difference in proportions was compared using chi-square test. P-value < 0.05 was considered statistically significant. Results were interpreted in tables and figures.
Ethics Approval and Consent to Participate
Ethical approval was obtained from IEC of JNU Institute of Medical Sciences, Jaipur; Rajasthan. A verbal consent was obtained from the participants. All the respondents were assured that the information collected would be confidential.
Table 1
Socio-demographic characteristics of women from urban slum. (N = 505)
Table 2
Housing condition & environment of study participants, N=505.
Table 3
Behavioral health factors and obstetric history of women participants. N=505
Table 4
Association of mental health illness with socio-demographic factors, N=505.
Table 5
Association of mental health illness with housing, environmental factors and behavioral health risk factors. N=505
Results
In our study maximum participants were in the age group of 15-25 years (28.32%). 30.69% were illiterate and 52.87% were Muslims. Majority lived in nuclear family (45.15%) and belonged to class III (30.89%) socio-economic status according to modified B.G Prasad classification 2022. 75.25% women were home-makers and maximum were married (81.58%). Prevalence of any type of chronic disease among women was 25.94%. 39.41% of their family members were addicted to harmful substances. The maximum consumption was of tobacco. [Table 1]. Majority of them (82.97%) were residing in their own houses. Overcrowding was seen in 48.92% of the participant’s houses. 15.64% had financial debt in their family. 7.52% of their husband’s were working in different cities away from hometown. History of psychiatric illness in family was seen in 4.75% of them. 3.17% & 5.35% of them were ill treated by their in-laws and husband respectively. 5.94% of them were subjected to domestic violence and abuse by their family members. [Table 2]. Currently 14.26% of the women were addicted to any form of tobacco. 43.33% had complains of poor sleep and 32.87% had generalized pain in body. Most of them (46.14%) were married before the age of 18 years. 4.35% of the participants had suffered from pregnancy loss recently and 6.73% were currently pregnant but out of these pregnant women 20.59% of the pregnancy was unwanted and7.52% revealed that there was a pressure for male child from the in-laws. [Table 3]. In our study, the overall, the prevalence of anxiety, stress and depression was 38.22%, 9.11%, and 18.61%, respectively, and which ranged from mild to extremely severe. [Figure 1] There were meaningful correlations between probable factors like physical inactivity, poor sleep and generalized pain and DASS scores obtained by the participants. [Table 4] There was a significant association with the various housing, environmental and behavioral risk factors with the presence of mental health illness. [Table 5]
Discussion
In the present study, the overall, the prevalence of anxiety, stress and depression was 38.22%, 9.11%, and 18.61% respectively. A study conducted by Chauhan S et al., study, 5.1%, 8.7%, and 7.3% of participants were experiencing severe or extremely severe depression, anxiety, and stress levels, respectively. In our study, 0.99%, 6.93% and 6.79% were having severe depression, anxiety and stress DASS scores. In Pawar N et al., study in North India mental illness was prevalent slightly higher in the age group of 46 & 60 years whereas in our study it was more in the 15-45 years age group.9 In our study, the prevalence of anxiety, depression and stress among women was higher compared to Srinivasan M et al., study in South India where the prevalence of depression, anxiety, and stress was 15%, 10.6%, and 5% respectively.8 In a study by Verma S et al., the prevalence of depression was 25% and the reason for high prevalence could be because of COVID 19 pandemic and prolonged lockdown. 10 A study done in Gujarat found that the prevalence of stress was alarmingly high (26%) when compared with our finding.11 In this study, we found that there was a concomitant existence of depression, anxiety and stress.
The present study found that very few socio demographic factors were associated to mental illness among women in our urban field practice area. Mental illness was common in three generation and nuclear family compared to joint family which was similar to Pawar N et al., study.9 Having debts in family was statistically associated with anxiety. Depression was strongly associated with ill treatment by husband, by in laws and domestic abuse/violence in family with p-value 0.000. A systematic review of the epidemiological literature on common mental disorders and poverty in low and middle-income countries found that of the 115 studies reviewed, over 70% reported positive associations between a variety of poverty measures and common mental disorders. 12 A review of population surveys in European countries found that higher frequencies of common mental disorders (depression and anxiety) are associated with low educational attainment, material disadvantage and unemployment.13 However, other studies have shown a vast array of factors different from our study contributing to this mental illness. These differences might be due to the different studies are being set in different cultures and socio demographic status.
Conclusion
The study showed that the prevalence of anxiety was higher compared to other DAS symptoms. The DASS symptoms were poorly associated to demographic characteristics of the study participants although amongst the separated and widowed females there was significant statistical association. These women suffer from higher mental health problems due to stigmatization and lack of support from the family members and community. There was also a significant association with the behavioral health risk factors like lack of physical exercise, poor sleep. The study findings clearly indicate the importance of early detection as well as prevention of mental health problem among the female population. The establishment and strengthening of health care system locally can help in overcoming the alarming rise in mental health problem in the community.
Strength
The interview was conducted by trained and briefed MBBS interns who provided better clarifications for the doubts that came up during the interview.
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