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Depression and its predictors among geriatric population in the urban slum of Bankura town of Eastern India
Article | IMSEAR | ID: sea-201185
ABSTRACT

Background:

Depression is the leading cause of disease burden ranked as third worldwide and also common among elderly people. The study was conducted to find out the prevalence of depression and its correlates among geriatric slum dwellers.

Methods:

This community based cross-sectional, an observational analytical epidemiological study was conducted from January 2018 to April 2018 among geriatric people residing in the urban slums of Bankura town. Out of 295 slums, 30 slums were selected by cluster sampling method. From each cluster 7 geriatric people were selected by systematic random sampling method and data were collected by interview method using interviewer-administered both close and open-ended, the predesigned pretested questionnaire which included 15 items Geriatric depression scale short form (GDS-SF). To reveal the ultimate predictor variables, bivariate analysis and followed by logistic regression was done.

Results:

Out of 210 people 59.1% was suffering from depression. In multiple logistic regression, we found that people who were suffering from chronic illness were 10.3 times more depressed. Married people were 6 times more depressed than others and 60 to 69 years people were found 4.4 times more depressed than elder geriatrics. People who belonged to poor socio-economic status (IV+V), were found as 2.7 times more depressed. Decision maker within the family was observed more depressed 1.8 times than others.

Conclusions:

Chronic illness, economic insecurity due to lower socio-economic status, over-thinking of marital people for their spouse’s security and health and newer identity as ‘senior citizen’ attributed to depression among geriatrics people.

Full text: Available Index: IMSEAR (South-East Asia) Type of study: Prognostic study Year: 2019 Type: Article

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Full text: Available Index: IMSEAR (South-East Asia) Type of study: Prognostic study Year: 2019 Type: Article