Depressive Symptoms as a Predictor of Disability After New Medical Diagnoses in Older Adults
Year: 2017
Type: conference-abstract
Abstract: Study: Older adults face negative life adversities, such as the onset of new medical diagnoses, which leads to disability and increased mortality risk. In this study, we aim to investigate whether depressive symptoms and cognitive function predict disability after controlling demographic and health-related factors in older adults with new medical diagnoses. Methods: We conducted a cross-sectional secondary data analysis of Survey of the Health and Retirement Study. Sample included 3100 older adults who self-reported for having new medical diagnoses within last two years. The hierarchical logistic regression analysis was used to examine the model fit of two blocks of variables: 1) demographic (age, gender, partnership, education level, race, ethnicity) and health-related (comorbidity, recent hospitalization) and 2) cognitive function and depressive symptoms. Results: Older adults have an average of 69.9 year-old (SD=10.4) with 58.8% female. Older adults with disability were more likely to be female (OR = 1.86, p<.001), with lower education level (OR = 1.28, p=.018), having comorbidity (OR = 2.43, p<.001), and having recent hospitalization (OR = 1.70, p<.001). After controlling for demographic and health-related variables, depressive symptoms (OR=7.31, p<.001) and low cognitive function (OR=1.03, p=.001) were significant predictors of disability. Conclusion: Findings demonstrate that depressive symptoms and cognitive function are significantly associated with disability in older adults with new medical diagnosis. Depressive symptoms showed clinical meaningfulness by the high magnitude of effect size. Significance: Results will inform future investigations focused on interventions for older adults who are vulnerable to long-term disability to prevent by focusing on depressive symptoms.
Source: Innovation in Aging
Authors: C. Wu, E. Skidmore, J. Rodakowski
Institution: University of Pittsburgh
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,977
OpenAlex ID: W2740844288