Depression Risk in Older Adults with Chronic Disease: A Cross-Sectional Analysis of the Americans' Changing Lives Study

Background and Purpose:
Approximately 92% of older adults have at least one chronic disease with 77% having two. Chronic disease can come in a variety of forms. From diabetes to heart disease, chronic conditions can cause devastating outcomes, impacting an individual physically, financially, and mentally. Despite popular misconceptions, depression is not a normal part of aging. Currently, 2 million older adults suffer from some form of depression. Although older adults makes up 14% of the population, they make up 18% of suicides. Research indicates an association between chronic illness and clinical depression. Yet there is still need to further investigate this association. This study attempts to recognize the impact of chronic disease on depression within an aging representative sample. We hypothesize that greater incidence of chronic disease will be related to a greater risk of depression.

Methods:
The cross-sectional study used data from the American’s Changing Lives (ACL) Longitudinal Study, the oldest ongoing national representative study supported by the National Institute of Aging. ACL covers a broad range of social, psychological, and behavior factors in health and the way health changes over the adult life course. In this study, we used the survey information collected in 2011 with a subsample of 1,237 participants who completed the depression questionnaire. The dependent variable is depression measured by an 11-item scale of the Center for Epidemiological Studies Depression Scale. We created a dichotomous variable of depression, with a score ≥9 indicating depression. The independent variable is the number of chronic diseases each person experienced recorded via self-report (Range: 0-6; e.g. diabetes, arthritis). Logistic regression analysis was run to test the relation between chronic disease and depression controlling for demographic and socioeconomic characteristics, such as covariates: gender, age, race, marital status, education, social support (number of friends that can count on) and income.

Results:
The mean age of sample participants was 64.5 years (SD=11.13 years). The sample was 61% female and 68% Caucasian. Fourteen percent of participants were depressed (CESD-11 score ≥9) and 41.75% of participants had 1 or more chronic diseases. The bivariate analysis suggested that, for every 1 additional chronic disease, there is a 59% increase in the odds of developing depression. After controlling for demographic, socioeconomic characteristics, and social support in multivariate model, with each additional chronic disease, there is a 58% increase in the odds of developing depression. The inclusion of additional control variables did not change the association between chronic disease and depression. 

Conclusion and Implications:
When controlling for age, sex, race, marital status, income, education, and social support chronic disease statistically significantly predicts depression in an older adult population. Professionals with older adult clients must remain cognizant of not only the loss of physical capabilities and health due to chronic disease but the potential development of depression. With only 3% of older adults seeking help from mental health professionals, the social work profession must take initiative in recognizing chronic disease as predictors of depression. Future research should investigate other predictors of depression as well as protective factors.