(PS2-25) Where the Body Meets the Mind: Exploring the Impact of Illness on Depression in Older Adults

Abstract Text: The relationship between physical health and depression is bidirectional such that poor health is related to increased depression, and depression predicts worse health over time (Kang et al., 2015). Depression is related to poor health behavior and non-adherence to medical recommendations, exacerbating difficulties for individuals with physical illness (DiMatteo et al., 2000). Older adults are disproportionately impacted by illness but are often overlooked and understudied in our youth-centric culture. There is a need for research on the specific impacts of physical illnesses on mental health among older adults. This research would drive interventions that target challenges unique to each illness, contributing, in turn, to better health behavior, treatment adherence, and overall wellness. The present study explores associations among common physical illnesses and depression in older adults (N = 15,021, Mage = 68.55, 41% male). Data are from the 2020 RAND HRS Fat File. The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan. The RAND HRS Fat Files take almost all the raw variables from the HRS survey and collapse them into a single respondent-level dataset for each wave. This file was developed at RAND with funding from the National Institute on Aging. Depression was measured by an 8-item version of the Center for Epidemiologic Studies Depression Scale, and single items identified whether participants had various illnesses. Binary logistic regression was used to examine the strength of associations between five illnesses (diabetes, cancer, lung disease, heart disease, and arthritis) and the likelihood of experiencing depression. Separate analyses were conducted for female- and male-identified participants to maintain independence. Results demonstrate that for both included sexes, diabetes, lung disease, heart disease, and arthritis were associated with increased odds of depression, while cancer was not a significant predictor. Lung disease had the strongest association with depression (females: B = 0.86, Exp(B) = 2.36; males: B = 0.66, Exp(B) = 1.94), followed by arthritis (females: B = 0.48, Exp(B) = 1.62; males: B = 0.58, Exp(B) = 1.79), diabetes (females: B = 0.30, Exp(B) = 1.35; males: B = 0.36, Exp(B) = 1.43), and heart disease (females: B = 0.22, Exp(B) = 1.25; males: B = 0.29, Exp(B) = 1.34). These findings call for research about common factors underlying illnesses that increase depression risk and greater insight into the complex and likely bidirectional associations between these illnesses and mental health. Future research should also explore how cancer differs from other illnesses and the potential mental health implications of cancer diagnosis and treatment. The present findings indicate a need for both transdiagnostic and illness-specific interventions targeting depression. Interventions must be tailored to the unique needs of older adults, who may be less receptive to traditional approaches because of the stigma around mental healthcare. CBT interventions are effective for reducing depression, and specializing these interventions by considering the impacts of illness and age may enhance treatment efficacy.