Logistic Regression on Factors Affecting Depression among the Elderly
Background: Mental health problems, especially depression, have a major impact on the elderly. Depression is a major contributor to the burden of disease globally which can cause suicide. This study aimed to determine the factors that influence depression in the elderly.
Subjects and Method: This was an analytic observational study with a cross-sectional design. It was conducted from October to December 2018. A total of 200 elderly was selected by simple random sampling. The dependent variable was depression. The independent variables were income, history of chronic illness, family function, social interaction, social support, social isolation, and loneliness. Data on depression was measured by Geriatric Depression Scale 15 (GDS-15). The other data were collected by questionnaire and analyzed by multiple logistic regression.
Results: The risk of depression in elderly increased with history of chronic illness (OR= 8.03; 95% CI= 1.48 to 43.42; p= 0.016), social isolation (OR= 6.05; 95% CI= 1.41 to 25.98; p= 0.015), and loneliness (OR= 7.14; 95% CI= 1.62 to 31.41; p= 0.009). It decreased with high income (OR= 0.14; 95% CI= 0.03 to 0.60; p= 0.008), strong family function (OR= 0.13; 95% CI= 0.02 to 0.67; p= 0.014), strong social interaction (OR= 0.11; 95% CI= 0.02 to 0.48; p= 0.003), and strong social support (OR= 0.16; 95% CI= 0.04 to 0.65; p= 0.011).
Conclusion: The risk of depression in the elderly increases with a history of chronic illness, social isolation, and loneliness. It decreases with high income, strong family function, strong social interaction, and strong social support.
Keywords: depression, elderly, income, chronic illness, family function, social factors, loneliness
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