Depression and its associated factors among elderly in Asajayya District in Samarahan division, Sarawak

Sharifah Norashikin, Binti Wan Ahmad (2010) Depression and its associated factors among elderly in Asajayya District in Samarahan division, Sarawak. Masters thesis, Universiti Malaysia Sarawak, (UNIMAS).

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Abstract

The demographic shift with an increased elderly population in Malaysia presents a major challenge for the health care system to meet the demand for health care services for the aged. Depression is a common illness in the older population and yet the recognition in practice is low. Depression is associated with declining in general health of the elderly and it tends to be more severe in nature. This cross-sectional study assesses the prevalence of depression and its associated factor among elderly residing in Asajaya district of Samarahan division. Specifically, this study examined the association between socio-demographic factors, functional status, self-rated health status and self-reported medical illness with depressive symptoms and determined the predictors of depression in elderly pOPulatio~ Data were collected from 582 elderly respondents in eleven selected villages during two months study period study from 15 January 2010 until 15 March 2010 using face-to-face interview. Depression was measured by the Malay version of Geriatric Depression Scale-14 item (MGDS-14). The study finding showed overall prevalence of elderly depression was 65.1 % (n= 379) of total respondents, with 18.0% (n= 105) had moderate depression and 47.1 % (n= 274) had major depression. Significant associations were found between depression and socio. demographic factors (gender, age group, marital status, educational level, monthly income, source of income and living arrangement), functional status, self-rated health and self-reported medical illness. Hypertension, stroke, vision impairment, hearing deficit, joint pain! arthritis, hand! feet numbness and other medical illness were also significantly associated with VIII depression. From the multivariate logistic regression analysis, the predictors of depression were educational level, living arrangement, functional status and self-rated health status.

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