Association of loneliness and social connectedness with geriatric depression in urban and rural areas: A cross-sectional study

Geriatric depression is increasingly concerning due to aging populations and its overlap with age-related diseases. Loneliness and social connection are key factors, but their impact on elderly mental health varies across different regions. To investigate the association between loneliness, social connectedness, and geriatric depression among urban and rural elderly populations. A sample of 160 senior citizens, equally divided between urban and rural areas, aged 60 years or older, was selected for the study. Data were collected using validated questionnaires that assessed depression, social connection, and loneliness. Statistical analysis was performed using SPSS, employing Chi-square tests, independent sample t-tests, and descriptive statistics. A P value of less than 0.05 was considered statistically significant. The mean age of the participants was 68.68 years (SD 6.52), with 64.4% being female. The prevalence of geriatric depression varied significantly across demographic and geographic factors. Rural areas exhibited higher rates of severe depression (73.8%) compared to urban areas (59.9%, P < 0.05). Illiteracy was associated with higher depression rates (78.9%) compared to literacy (21.1%, P < 0.01). In addition, lower socioeconomic status was linked to increased depression severity (P < 0.001). A notable association was also observed between joint family structures and milder depression (P < 0.03). The research emphasizes the need for targeted interventions to address loneliness, enhance social connections, and reduce depression among older adults, especially in remote areas. By understanding and addressing the complex factors affecting geriatric mental health, policymakers and healthcare providers can improve the well-being and quality of life for seniors. Further longitudinal studies are needed to explore these relationships and develop effective mental health interventions for aging populations.