A Prevalence of Depression and Their Risk Factors among the Elderly Population in the Slum Area of Chennais

Yamuna Devi Ravi^1*, B. Narmatha Devi², A.R. Adhilakshmi³ and P.Seenivasan¹

^*Correspondence: Yamuna Devi Ravi, Department of Community medicine, Government Stanley Medical College, Chennai, Tamil Nadu, India, Email:

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Introduction

Aging is an universal multifactorial process that involves diverse changes occurring at the cellular level, various tissues, organs and the body as a whole in a person over a period of time. People more than 60 years of age is considered as elderly, according to United Nations Cut off1. According to National Policy on Older persons in India, which came into act in 2011, persons who are more than 60 years of age are considered as Senior Citizens2,3.

The elderly population in India shows a steady increase from 5.63% in 1961, 6.58 % in 1991 and 7.5 in 2001 to 8% 5 in 2010. It is projected in 2025, that the number of elderly population is expected to rise more than 1.2 billion with about 840 million of these in developing countries4,6. There is a shift in the age pyramid and the dependency population has increased. This rise of population is mainly due to the increase in life expectancy and improvement in services provided health sector. As a result of this, the mortality and morbidity have decreased leading to increase in life expectancy of the elderly. Many National programs are functioning in such a way to improve the quality of life of the elderly.

Mental disorders are seen more in this age group and depression is the most common presentation among them. According to many community based studies7,8, the prevalence of depression among elderly in India varies from 13-25% . Globally 4.4% of depression cases are reported among elderly9. Depression is considered as a “silent killer” which is the major reason in morbidity and mortality among the elderly population. Urbanization and lifestyle changes leads to more cases of depression in urban areas. In addition to the above said factors overcrowding, pollution, abuse, reduction in social support are the additional factors which increases the chances of developing depression. This study is performed to find out the prevalence of depression among the elderly population in the slum area.

Aim Of The Study

• To find out the prevalence of depression among the elderly population in the slum

• area in Chennai.

• To find out the risk factors associated with the depression.

Methodology

Study design:

Community based cross sectional study

Study area:

Slum areas in North Chennai

Study period:

February 2019-August 2020

Study population:

Elderly people >60 years of age.

Inclusion Criteria:

All elderly people>60 years of age including both males and females.

Exclusion Criteria:

Elderly people with existing mental disorders

Stroke with aphasia

Loss of hearing

Sampling method:

Among the 32 districts of Tamilnadu, through multistage random sampling method Chennai was chosen. Chennai comprises of 15 Zones. Zone 3 was randomly selected by lot method. Zone 3, Consists of 60 slums of which 5 slums were selected randomly. Among the 5 slums, 92 participants were selected randomly from each slum through stratification.

Sample size:

Based on Barua A et al16 study, the sample size was calculated, keeping the prevalence as 21.7, with 95% confidence interval and 4% as absolute precision with 10% of non-responders. Sample arrived is 452 which is rounded of to 460.

Data collection:

After obtaining Institutional Ethical Committee Clearance, data was collected. Participant’s baseline characteristics like Name, Age, Sex, Occupation, Socio economic status by modified B.G.Prasad scale. Type of family was assessed through a pretested questionnaire. In addition, a 15 item Geriatric depression scale (GDS-15) was used. Score is given based on the answered questions. Scores of 0-4 are considered normal, depending on age, education, and complaints; 5-8 indicate mild depression; 9-11 signifies moderate depression and 12-15 specifies severe depression. Any positive score above 5 on the GDS-15 should prompt an in-depth psychological assessment and evaluation.

Statistical analysis:

Once the data was collected, it was entered in MS excel Windows 10. Statistical analysis was done by SPSS 23. Continuous variable was expressed in terms of Mean and Standard deviation. Categorical variables was expressed in terms of numbers(percentages). Association between categorical variables were done using Chi square tests. A p value <0.05 will be considered as statistically significant.

Results

In our study data was collected from 420 elderly people in the slum area. The prevalence of depression was found to be 17%. The mean age of the population was 69. Majority of the population belong to the lower socio economic status.

Table 1: Prevalence of depression among the elderly slum dwellers.

In our study population, majority of the elderly suffers mild depression 49(61.25%), followed by moderate depression 23(28.75%). Severe depression is least contributing 10%.

Table 2: Demographic characteristics of the population (N=80).

Among the study population, majority 56 (70%) were less than 70 years of age. Female predominance 61(76.3%) noted in our study. Most of the population belong to the lower socioeconomic group 68(85%). More than half of the people 44(55%) were not working. 54(67.5%) of study population were illiterate. More than 62(77.5%) population are suffering from more than two diseases. 47(58.75%) were living alone and most of the people 63(78.75%) are financially dependent on their sons or daughters for their living.

Table 3: Association of factors with geriatric depression: (N=80).

When we see the association between the baseline characteristics and depression, less than 70 years age are more prone for depression. Females are noticed to have more depression when compared to males. Socioeconomic status, Occupation, Education, Type of family and the comorbidities are found to be more associated with depression and the association was found to be statistically significant.

Discussion

T The results from our study are comparable to the ones performed in western population, but the prevalence of depression is much lesser in our study population compared to the western literature. Among the total 420 participants we studied, the observed prevalence was 17%, which is comparable to the study by Saikia et al12. The various studies in literature by Nirmal et al10,Jain et al14 and Pracheth et al 11 showed the prevalence of depression as 44.6%, 45.9%& 27.71% respectively. The observed variation in the prevalence may be due to the usage of different scales such as WHO Wellbeing index5, Anxiety and Stress scale, ,Depression inventory Scale. Increasing age is not a significant risk factor for onset of depression in our study which is comparable to the study by Nirmal et al10.

The various risk factors which are significantly associated with depression in our study are education status, occupation, type of family, comorbidities, social economic status. These are comparable to the study done by Mamta et al 13,14,15. In addition she also attributes increasing age as a factor, claiming that, as age increases, they tend to develop many comorbidities which make them dependent on others, making them vulnerable to suffer depression. The role of co-morbids in depression is further reiterated by Pracheth et al11 as he found strong association between chronic diseases and depression. We found in our study that depression is more prevalent in people with poor economic status which was in line with saikia et al12 observations. Substance abuse and sleep deprivation also significantly associated with depression14.

In our study, we noticed an increasing trend of depression among females. This may be due to the fact that many of the studied females were widows and are living alone, with no one to take care of them.

Conclusion

The prevalence of our study is 17%, which is low compared to other studies. Comorbidity, Educational status, Occupation, Type of family, Socio economic status are all independent risk factors associated with depression. Depression should be diagnosed and treated as early as possible. The vulnerable population with risk factors should be screened to diagnose depression at the earliest. Recreational homes should be started for them, so that it will provide mental rehabilitation. Behavioural therapy and medications play a major role in treating depression.

Limitation

• Our study included only slum area population, so it cannot be generalized.

• Mood swings may affect the performance during the study.

References

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3. Dasappa, Hemavathi, Fathima Farah Naaz, Prabhakar Rugmani, and Sarin Sanjay. "Prevalence of diabetes and pre-diabetes and assessments of their risk factors in urban slums of Bangalore." J fam med prim car 4, (2015): 399.
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5. Imchen, Temjenyangla, Longkumer Tsungrosenla, and Murry Khumjanbeni. "Prevalence of Depression and the associated risk factors among the Elderly." Asi J Nurs Edu Res 9, (2019): 552-554.