Predictors of Depression and Insomnia in Community-Dwelling Elderly People: A Cross-Sectional Evidence of Their Bidirectional Relationship

Objective The aim of this study was to examine associated factors of depression and insomnia in community-dwelling elderly people in order to identify independent predictors. Materials and methods A cross-sectional study was conducted among 250 older people aged 60 years and over living in an urban area. A stratified random sampling method was used for recruiting samples from five Open Care Centers for Elderly People of the Municipality of Larissa, Greece. Data were obtained through a questionnaire that included demographic, socioeconomic, and health-related characteristics, 15-item Geriatric Depression Scale (GDS-15), and Athens Insomnia Scale (AIS). Simple and multiple logistic regression analysis was performed. Results The prevalence of depression and insomnia was 28.4% (95% CI: 22.9-33.9) and 39.2% (95% CI: 33.0-45.4), respectively. Our findings showed that the overall GDS-15 score was positively related to the overall AIS score (r = 0.405; p < 0.001). The best-fit regression analysis demonstrated four significant predictors (marital status, monthly income, body weight status, and insomnia) explaining 31.6% of the variance in depression risk. Moreover, community-dwelling elderly Greek people with insomnia symptoms were females, had a lower monthly income, and more likely to suffer from chronic diseases and depression. Conclusion These findings point to the importance of recognizing risk factors for both depression and insomnia in attempting to apply preventive interventions in the elderly and optimize their quality of life.

Automated summary

This study aimed to identify independent predictors of depression and insomnia in community-dwelling elderly people. The prevalence of depression and insomnia was found to be 28.4% and 39.2%, respectively, with a significant positive correlation between the two. Significant predictors of depression risk included marital status, monthly income, body weight status, and insomnia.