An Assessment of Predictors of Depression Among the Elderly Residents in Old People’s Homes in Nairobi County, Kenya

Abstract

Depression is a public health challenge particularly in developing nations. Senior citizens or the elderly above the age of 60 years have a much higher risk of mental health challenges like depression due to various life circumstances such as chronic illnesses and loneliness. Consequently, the research focused on elucidating depression among the elderly and investigating the psychosocial factors that act as predicators of depression among the elderly living in old people’s homes in Nairobi County. Research goals were assessing the effect of family break-up as a predictor of depression among the elderly, effects of cultural values as predictors of depression among the elderly, effect of sociodemographic variables as a predictor of depression among the elderly and effect of socio factors as a predicator of depression among the elderly in old people’s care homes in Nairobi County, Kenya. The research was anchored in two theories: the Social Production Theory (Lindernberg (1989) and Hierarchical Compensatory Theory by Antonucci (1986). The study targeted 177 individuals aged above 60 years and are residents in old people’s homes. Cross sectional descriptive research technique was used where 7 old people’s homes was used. Interviews and self-administered questionnaire were adopted in data gathering from respondents selected through a simple random sampling process. Once data was collected, it was analyzed using the Statistical Package for Social Sciences (SPSS) version 22. To present the information, tables were utilized. Findings from descriptive statistics and regression analysis revealed a significant relationship between family break-up and depression among the sample. Descriptive statistics indicated that a substantial proportion of respondents have personally experienced family break-ups (88.9%), and that their family members have also experienced break-ups (88.9%). The regression coefficient of 0.846 showed a positive and significant (p=0.000) relationship between family break-up and depression. The standardized coefficients show cultural values having a positive and significant effect on depression (Beta = 0.304, p = 0.013), suggesting that individuals who adhere strongly to traditional cultural values may be at a higher risk of experiencing depressive symptoms. The standardized coefficient for socio factors was found to be positive but non-significant (Beta = 0.166, p = 0.322), indicating that the influence of socio factors on depression may not be as pronounced as other variables in the model. As per research outcomes it was recommended that it is crucial to develop comprehensive support programs that address family break-up and improve communication within families, and efforts should be made to enhance social support networks within elderly homes. Future research should explore the longitudinal effects of family break-up, cultural values, and socio factors on depression among the elderly.