Psychosomatics 47:435-439, September-October
doi: 10.1176/appi.psy.47.5.435
© 2006 Academy of Psychosomatic Medicine
The Relationship of Medical Comorbidity and Depression in Older, Primary Care Patients
Jeffrey M. Lyness, M.D.,
Aurelian Niculescu, M.D.,
Xin Tu, Ph.D.,
Charles F. Reynolds, III, M.D., and
Eric D. Caine, M.D.
Received August 30, 2005; revised November 14, 2005; accepted November 30, 2005. From the Program in Geriatrics and Neuropsychiatry, Dept. of Psychiatry and Dept. of Biostatistics and Computational Biology, Univ. of Rochester Medical Center; and the Advanced Center in Interventions and Services Research for Late-Life Mood Disorders, Dept. of Psychiatry, Univ. of Pittsburgh School of Medicine, Pittsburgh, PA. Address correspondence and reprint requests to Dr. Lyness, Dept. of Psychiatry, Univ. of Rochester Medical Center, 300 Crittenden Blvd., Rochester, NY 14642. e-mail: Jeffrey_Lyness{at}urmc.rochester.edu
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ABSTRACT
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Comorbid medical illnesses are a key feature of geriatric mood disorders, yet the specificity of such associations remains unclear. In a sample of 546 primary care patients age  65 years, pathology in several organ systems (respiratory, eye/ear/nose/throat, gastrointestinal, central nervous system, endocrine) and several chronic conditions (neurological disease, low vision, chronic obstructive pulmonary disease, diabetes) were associated with depression. However, notwithstanding these specific associations, global (overall) medical burden was most powerfully and independently associated with depression, largely independent of functional status. This generates the hypothesis that, in general primary care populations, the relationship of medical illness to depression may be multimodal and/or may involve shared pathobiological or psychosocial mechanisms.
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INTRODUCTION
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Depressive conditions in elderly patients are an important public health problem.1 Study of comorbid medical illnesses, a hallmark of geriatric depression, may yield crucial insights into the pathogenesis of depression in old age.2 However, although high rates of depression have been found in studies of a number of common chronic medical conditions, including cardiovascular and cerebrovascular disorders, it remains unclear whether any specific medical illness has a uniquely powerful association with depression.3–5 One recent study found that anemia was independently associated with depression (defined as scoring above a cutoff on a depressive symptom severity scale), controlling for a number of specified other chronic medical conditions, in a large, population-based, older cohort.6 The PROSPECT clinical trial examined the predictive role of several specific medical illnesses in older primary care patients, finding that only pulmonary disease was associated with poorer outcomes, and atrial fibrillation with better outcomes, in the Usual Care group.7 Although no individual illness was associated with outcome in PROSPECT’s intervention group, remission rates were lower in patients with four or more medical conditions. To our knowledge, no previous published work has examined the specificity of depression’s association with diseases across all body-organ systems.
Accordingly, we examined whether diseases of any particular organ system, or any of several specified common chronic medical conditions, were associated with depression independent of overall medical burden. We also examined whether such associations were independent of functional status, laying the groundwork for future longitudinal work testing whether functional disability mediates the relationship between medical burden and depression. To overcome the sample biases inherent in patients selected from medical and psychiatric subspecialty settings, we studied older patients from primary care practices. This approach allowed us to include a broad range of medical conditions, to examine their relationships to a broad range of depressive severities, and to better understand these relationships in the settings in which most older adults present for care for both medical and psychiatric conditions.8
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METHOD
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As described previously,9,10 subjects were all patients age 65 years, capable of giving informed consent, who presented for primary care on selected recruitment days in several private internal-medicine practices and University-affiliated internal-medicine or family-medicine clinics. After patients were given a complete description of the study, we obtained written informed consent, using procedures approved by the University of Rochester Research Subjects Review Board.
Trained raters conducted interviews based on the Structured Clinical Interview for DSM-IV11 to ascertain depression diagnoses, defined as: 1) current major depression; 2) current minor depression (using DSM-IV Appendix criteria); or 3) nondepressed (all others). To capture "subsyndromal" symptoms, depressive symptom severity was assessed with the 24-item Hamilton Rating Scale for Depression (Ham-D),12 an examiner-rated instrument widely used and validated in older and medically ill populations.
Medical burden was rated by a physician-investigator (JML) on the basis of subject interviews and medical chart reviews, using the Cumulative Illness Rating Scale (CIRS).13 This reliable scale, previously validated by comparison of interview/chart review scores with scores obtained from autopsy data,14 assesses the severity of pathology in each organ system by use of all available history, examinations, and laboratory data. Analyses examined overall medical burden and individual items for the following organ systems: cardiac, vascular, respiratory, EENT (eyes, ears, nose, throat), gastrointestinal (sum of three items), renal/genitourinary (sum of two items), musculoskeletal-integumental, neurological, and endocrine/metabolic. Also, the following conditions were rated "Yes/No:" arthritis, cancer, CNS (brain) disease, COPD (chronic obstructive pulmonary disease), hypothyroidism, impaired hearing, low vision, diabetes mellitus, hypertension, and cardiovascular disease. Overall functional status was assessed by the Instrumental Activities of Daily Living and Physical Self-Maintenance scales,15 and disability judged to be due to physical causes by the Karnofsky Performance Status Scale.16
To determine the independent association of medical burden variables to depression, we used linear-regression models for continuous responses (Hamilton Rating Scale for Depression [Ham-D]) and generalized linear models with logit link for categorical responses (depression diagnosis),17 also covarying age, gender, and education. Analyses using the CIRS subscales could not also covary total CIRS score because of multicollinearity, but total CIRS score was additionally covaried in analyses using the 10 "Yes/No" conditions. We conservatively report two-tailed p values, with significance set at p< 0.05. Power analyses for the linear regressions, with N=546, setting the number of predictors to 13, two-tailed  =0.05, and 80% power, would allow us to determine an effect size as small as f2=0.03, which is slightly larger than a small effect size, consistent with detecting a predictor whose F statistic is >4.3.18 For the logistic regressions, using the same parameters applied to Whittemore’s formula,19 we would, on average, be able to detect an odds ratio (OR) <0.62 or >1.6, although, in some cases, p values were not significant with ORs <0.62, because power also depends on the multiple correlation coefficients of the remaining predictors in the models.
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RESULTS
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Of the 546 subjects enrolled, 333 (61%) were women. There were 510 whites (93%), 21 African Americans (4%), and 15 of mixed or other races (3%). Mean age was 74.6 years (standard deviation [SD]: 6.6; range: 65–94); mean Ham-D score was 8.8 (SD: 6.5; range: 0–37), and mean total CIRS score was 7.3 (SD: 2.9; range: 1–17). Thirty-two subjects (5.9%) had major depression; 34 (6.2%) had minor depression; and 480 (87.9%) were in the nondepressed group (Table 1).
Table 2 shows the results of the regression analysis, with Ham-D score as the dependent variable and all the CIRS sub-items as independent variables; the respiratory, EENT, gastrointestinal, neurological, and endocrine/metabolic items had significant independent associations with Ham-D score. The other regression, examining the 10 chronic medical illnesses, found that CNS disease, COPD, and diabetes mellitus were independently associated with severity of depressive symptoms. After adding total CIRS score to the latter model (not shown in the table), only total CIRS score (ß=0.67; SE: 0.13; F=27.0, df=1, 528; p<0.0001) and the absence of cardiovascular disease (ß = –1.56; SE: 0.66; F=5.6, df=1, 528; p=0.02) were significantly associated with the Ham-D score.
Table 2 also shows that, in a separate regression, CIRS sub-items for the respiratory, EENT, and endocrine/metabolic systems had significant independent associations with depression diagnosis. Also, of the 10 chronic conditions, only low vision was significantly associated with depression diagnosis. When total CIRS score was added to the latter model (not shown in the table), only total CIRS score had an independent association (OR: 0.9; 95% confidence interval [CI]: 0.8–0.96; p=0.01).
The association between total CIRS score and Ham-D remained significant after controlling in separate regressions for scores on the Instrumental Activities of Daily Living (IADL scale; ß=0.47; standard error of the mean [SE]: 0.10; F=21.1, df=1, 538; p<0.0001), the Physical Self-Maintenance Scale (ß =0.39; SE: 0.10; F=15.7, df=1, 539; p<0.0001), and the Karnofsky Performance Status Scale (ß=0.26; SE: 0.11; F=5.8, df=1, 540; p=0.016). The association between total CIRS score and depression diagnosis remained significant after controlling for IADL score (OR: 0.88; 95% CI: 0.80–0.97; p=0.01) and Physical Self-Maintenance Scale score (OR: 0.90; 95% CI: 0.82–0.99; p=0.03), but not after covarying the Karnofsky Performance Status Scale score for physical disability (OR: 0.92; 95% CI: 0.83–1.02; p=0.11).
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DISCUSSION
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These data demonstrate only modest independent associations of any specific medical condition or organ system pathology with depression. Almost none retained a significant association after controlling for aggregate burden of comorbid medical illnesses (total CIRS score), which was independently associated with both the Ham-D score and the depression diagnosis. The seemingly paradoxical finding regarding the absence of cardiovascular disease may reflect the complexities of the regression model, also controlling for other comorbid conditions that may themselves influence cardiovascular disease (e.g., diabetes mellitus, hypertension). These results, together with recent findings from the PROSPECT study,7 suggest that overall medical burden, rather than any specific pathology, is most importantly associated with depressive conditions in a broad group of primary care elderly patients. They also are consistent with previous study of a subgroup of this subject cohort,10 and some (but not all) previous work with other subject groups20–25 finding that cerebrovascular risk factors’ cross-sectional association with depression is not independent of overall medical burden.
However, interpretation of our findings must be tempered by recognition of the study’s limitations. In trying to understand our "negative" findings regarding the association of depression with a number of medical conditions commonly linked to depression in previous studies, it is important to recognize that the CIRS is a broad and clinically-based measure of medical illness severity. As such, it is relatively insensitive to potentially important qualitative or quantitative differences in the severity of specific conditions, differences often measurable by more focused or physiologically-based methods for particular diseases. Given this, and the fact that we intentionally studied a clinically heterogeneous patient group, the results cannot address whether more specific and even causal relationships exist in particular medical illness subgroups. Also, our findings may not generalize to other populations. Statistical power was reasonable, but small differences may not have been detectable. The study was cross-sectional; longitudinal investigation is required to inform inferences about potentially causal pathways between medical illnesses and depression, and indeed is currently underway with this cohort.
Nonetheless, our findings generate the hypothesis that, among a broadly diverse group of primary care older patients, medical illnesses’ associations with depression may be either multimodal, or involve a "final common pathway" that includes pathobiological elements common to many diseases (e.g., the potential role of inflammatory cytokines) or common psychosocial factors (e.g., personality traits, altered social-role functioning). Illness-associated functional disability may play an important role in such common pathways, an idea that is supported by our finding regarding the role of physical disability (Karnofsky Performance Status Scale score), but longitudinal study is required to directly assess the mediator role.26 It must be noted that data from some medical-illness groups, particularly brain diseases such as stroke, have demonstrated that functional disability does not play as important a role in depression as disease-severity factors such as brain-lesion size or location.27 Yet the role of functional disability in many other conditions, or in broadly heterogeneous groups such as primary care patients, remains to be defined. Testing such models is of paramount importance to identifying pathogenic mechanisms and is essential to devising the more effective interventions for later-life depression that are so sorely needed.1,28
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ACKNOWLEDGMENTS
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This work was presented in part at the Annual Meeting of the American Association for Geriatric Psychiatry, San Diego, CA, March 5, 2005.
The authors thank the following: UR Departments of Medicine and Family Medicine, Pulsifer Medical, East Ridge Family Medicine, RGH Twig Center, Olsan Medical, Clinton Crossings Medical, Wilson-Lifetime, Panorama Internal Medicine, HH Geriatrics, Culver Medical, K. Gibson, M.S.Ed., C. Bowen, M.A., J. Evinger, M.Div., A. Niculescu, M.D., J. Sauvain, B.S., J. Scheltz, B.A., LMT, Arthur Watts, B.S., and J. Woodhams, M.F.A.
The work was supported by NIMH grant R01MH61429 (JML) and P30MH71944 (CFR).
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ABSTRACT
INTRODUCTION
