Abstract
Objective: To examine the effects of chronic health conditions and functional status limitations on depression scores in a large representative sample of Americans. Method: The data included 27,461 respondents ages 50 to 90 who completed up to eight test occasions from the Health and Retirement Study. Multivariate adaptive regression splines (MARS) modeling was applied. Possible covariates of depression included arthritis, lung disease, back pain, diabetes, heart disease, high blood pressure, cancer, 28 pairwise combinations of the aforementioned conditions, ADL functional limitations, age, education and being female, being white, and being Hispanic. Results: The best fitting model had a GRSq of 0.18 (comparable to R2 ) and included 12 of 42 covariates. Depression score was predicted by: 1) ADL limitations, 2) education, 3) back pain, 4) lung disease, 5) being female, 6) being Hispanic, 7) heart disease, 8) being white, 9) high blood pressure plus stroke, 10) age, 11) back pain plus arthritis, and 12) back pain plus diabetes. Conclusions: Functional limitations was the strongest predictor of depression; reporting one limitation increased depression scores by nearly double the increase associated with two or more limitations. Back pain and lung disease were the strongest chronic disease predictors of depression; both are associated with considerable discomfort.
Highlights
The interaction between depression and chronic disease is an important predictor of health outcomes
Model fit was indexed by the magnitude of the generalized cross validation (GCV) index, where smaller GCVs indicate better model fits (Milborrow, 2011)
The chronic conditions that were most strongly associated depression tended to be the ones that were associated with the greatest pain or discomfort
Summary
The interaction between depression and chronic disease is an important predictor of health outcomes. Studies have shown that the onset of various chronic diseases correlate with future depression (Dubovsky et al, 2005; Roberts, Kaplan, Shema, & Strawbrige, 1997). Studies have shown that depression can negatively affect treatment outcomes for treatment of chronic diseases (see for example Wulsin et al, 2005). The cause and effect relationship between depression and disease appears to be complex and often bidirectional (for a comprehensive review see, Freedland & Carney, 2005). The identification of directionality between disease and depression can be a tricky issue involving several factors including temporal ordering and proximity. While many studies have been reported on these issues, few studies have examined such relationships with large population-based (representative) samples
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