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1 Division of Geriatrics, University of California at San Francisco.
2 Departments of Psychiatry, Neurology and Epidemiology, University of California, San Francisco.
3 Division of General Medicine, Department of Medicine, University of Michigan Medical School, Ann Arbor.
4 Veterans Affairs Center for Practice Management and Outcomes Research, Ann Arbor, Michigan.
5 Department of Medicine, University of California, San Francisco.
6 Department of Veterans Affairs Medical Center, San Francisco.
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Abstract |
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Methods. We studied 6301 elderly adults (mean age, 77 years; 62% women; 81% white) enrolled in the Asset and Health Dynamics Among the Oldest Old (AHEAD) study, a prospective study of community-living participants conducted from 1993 to 1995. Cognitive function and depressive symptoms were measured using two validated measures developed for the AHEAD study. On each measure, participants were divided into tertiles representing the best, middle, and worst scores, and then placed into one of nine mutually exclusive groups ranging from best functioning on both measures to worst functioning on both measures. Mortality rates were assessed in each of the nine groups. Cox proportional hazards models were used to control for potentially confounding characteristics such as demographics, education, income, smoking, alcohol consumption, comorbidity, and baseline functional impairment.
Results. During 2 years of follow-up, 9% (548) of the participants died. Together, cognitive function and depressive symptoms differentiated between elderly adults at markedly different risk for mortality, ranging from 3% in those with the best function on both measures to 16% in those with the worst function on both measures (p <.001). Furthermore, for each level of cognitive function, more depressive symptoms were associated with higher mortality rates, and for each level of depressive symptoms, worse cognitive function was associated with higher mortality rates. In participants with the best cognitive function, mortality rates were 3%, 5%, and 9% in participants with low, middle, and high depressive symptoms, respectively (p <.001 for trend). The corresponding rates were 6%, 7%, and 12% in participants with the middle level of cognitive function (p <.001 for trend), and 10%, 13%, and 16% in participants with the worst level of cognitive function (p <.001 for trend). After adjustment for confounders, participants with the worst function on both measures remained at considerably higher risk for death than participants with the best function on both measures (adjusted hazard ratio, 3.1; 95% confidence interval, 2.0–4.7).
Conclusions. Cognitive function and depressive symptoms can be used together to stratify elderly adults into groups that have significantly different rates of death. These two risk factors are associated with an increased risk in mortality in a progressive, additive manner.
IN older persons, adverse outcomes, including mortality, are often better explained by the cumulative and combined impact of multiple conditions that increase a person's vulnerability rather than by the impact of any one condition alone (1,2). Poor cognitive function and depressive symptoms independently increase mortality in the elderly (3–19). However, although poor cognitive function and depressive symptoms are interrelated and often coexist (20), it is unclear how the combination of poor cognitive function and depressive symptoms contribute to increase an older person's risk for mortality.
Many prior studies of the association of poor cognitive function and depressive symptoms with mortality have focused on one of these risk factors to the exclusion of the other (3–10). A few studies that have measured both cognitive function and depression (11–19) have provided only limited insight into how the combination of these conditions affects mortality. Most studies have examined the effect of either cognitive impairment or depression on mortality, and viewed the other condition only as a confounder in adjustment models. In some instances, controlling for one of these two risk factors eliminates the effect of the other (21,22). Also, some studies have not considered the full range of depressive symptoms and cognitive impairment, and have assessed only the impact of major depression and advanced dementia (7,23). In addition, some studies have been limited to special subgroups such as the medically ill or hospitalized elderly adults (11,12,14).
To better understand the combined effect of poor cognitive function and depressive symptoms on mortality, we examined survival in participants in the Asset and Health Dynamics Among the Oldest Old (AHEAD) study, a population-based study of more than 6000 community-dwelling elderly adults. The aims of this study were to determine whether cognitive function and depressive symptoms are independently associated with mortality after adjustment for each other and potential confounders such as demographic characteristics, education, income, smoking, alcohol consumption, comorbidity, and baseline functional impairment. In addition to assessing statistical interaction, our analytic approach assesses how varying levels of cognitive function and depressive symptoms contribute to mortality over 2 years.
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Methods |
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For the current study, we excluded the 791 participants for whom a proxy respondent was used (N = 6656). Proxy respondents were used when the subject declined an interview or was too ill to be interviewed. An additional 291 were missing cognitive information, 12 were missing depressive symptom information, and 43 were missing covariate information. Therefore, the analytic sample for this study was 6310 elderly adults (95% of self respondents).
Cognitive Function and Depressive Symptoms Measurement
Cognitive function was measured at baseline with a 35-point scale developed for the AHEAD study (COG) (27,28). This scale shares questions with the Mini-Mental State Examination (29) and with the Telephone Interview for Cognitive Status (30). Evidence supporting the validity of this scale has been previously published (27,28,31). The scale includes questions that test memory, calculation/attention, and orientation. Memory was tested using an immediate and delayed free-recall test in which 10 common nouns were recited. The participant was asked to verbally recall as many of the nouns as possible immediately and after a 5-minute delay. Both the immediate and delayed recall conditions were scored between 0 and 10, with a score of 10 reflecting perfect recall of all 10 words. Calculation/attention was assessed using the serial 7's test in which participants start with 100 and consecutively subtract 7 five times. Participants were given 1 point for each correct subtraction for a total of 5 points. Additional assessment included counting backwards from 20 to 10 and from 86 to 76, and naming the month, day, year, and day of the week; the object used to cut paper (scissors); the plant that lives in the desert (cactus); and the president and vice president of the United States, for a total of 10 points. An overall cognitive score was calculated as the sum of all test values for a total of 35 points, with lower scores indicating worse cognitive function (31). We grouped the individuals based on tertiles of the cognitive function scale score: worst [0–17], middle [18–22], and best [23–35].
Depressive symptoms were assessed using eight items from the Center for Epidemiologic Study Depression scale (CES-D8) (32). The CES-D has been shown to reliably measure depressive symptoms in older adults, even in people with mild cognitive impairment (33). A modified version of the CES-D has been used in other population-based studies of the elderly (21), and the CES-D8 has a similar factor structure to the CES-D20 scale (34). Specifically, participants were asked if the following feelings occurred during the prior week (yes or no): depressed mood, loneliness, sadness, happiness (reverse scored), that everything was an effort, that sleep was restless, could not "get going," and not having a lot of energy. Each question was assigned 1 point for a total of 8 points, with a high score indicating more depressive symptoms. We grouped individuals based on approximate tertiles of CES-D8 score: worst (3–8), middle (1–2) and best (0).
Mortality
We assessed mortality over 2 years using the AHEAD survey follow-up procedures (35). Deaths were confirmed by checking the U.S. National Death Index. Survival time was defined as the number of days between the baseline interview and the date of death, or December 31, 1995, at which point surviving participants were censored.
Other Measurements
We also considered a series of variables, based on prior literature, that could confound the associations between poor cognitive function and depressive symptoms, and mortality. These included demographic characteristics (age, gender, race, and marital status); years of education; total net worth of less than $38,300 (lowest tertile); self-reported smoking and alcohol consumption; body mass index (lowest tertile); and self-reported history of comorbid medical conditions (presence of hypertension, diabetes, cancer, heart disease, lung disease, arthritis, stroke, vision problems, hearing problems); we also determined whether participants reported needing assistance in any of the five activities of daily living (ADL dependence) (36).
Statistical Analyses
All statistical analyses used the AHEAD sampling and design weights to account for the study's complex design. The main objective of this study was to determine the relative contributions of poor cognitive function and depressive symptoms to mortality. For our bivariate analyses, we used unadjusted survival analysis using the method of Kaplan-Meier to determine whether cognitive function tertiles and depressive symptom tertiles were associated with mortality. To describe the contributions of cognitive function and depressive symptoms as predictors of mortality, we classified participants into nine mutually exclusive exposure groups, representing each combination of the best, middle, and worst tertile on cognitive function and depressive symptoms. We then used unadjusted Cox proportional hazards regression models to examine the relationship between the nine mutually exclusive exposure groups and survival time. Next, we again used Cox proportional hazards regression to examine the relation between the nine exposure groups and survival time after adjusting for significant (p <.10) confounders. Adjusted models included age, gender, education, race, total net worth, marital status, comorbid conditions (presence of high blood pressure, diabetes, cancer, lung disease, and heart disease, as well as the total number of comorbid conditions), body mass index, and ADL dependence. For these analyses, the outcome was survival time censored at December 31, 1995, and the independent variables were the nine mutually exclusive exposure groups. Finally, to determine if there was an interaction between depressive symptoms and cognitive function, we then performed a survival analysis with the CES-D8 scale, the COG scale, and an interaction term (CES-D8 x COG).
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Discussion |
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Although many prior studies have examined the relation between either cognitive function or depressive symptoms and mortality, few studies have examined the impact of both of these risk factors in combination (3–10). Most prior studies that examined both risk factors found that either cognitive impairment or depressive symptoms are associated with mortality, although the magnitude of the association has varied considerably, depending on the differences in definitions of cognitive impairment and depressive symptoms, and the length of follow-up (11–19). Some studies have suggested that the association between depression and mortality may not be significant after the adjustment for confounders. For example one study did not report a relationship in controlled analyses (21). Similarly, one recent review showed that not all studies report an association between depression and mortality, especially if the study adjusted for multiple confounders (22).
A few prior studies did not examine the effects of a wide range of cognitive function and depressive symptoms. However, in the community, the spectrum of cognitive function and depressive symptoms includes a wide range of functioning. Our analytic approach separated individuals with high, middle, and low depressive symptoms and cognitive function scores. This approach is useful for describing the additive effects of cognitive impairment and depressive symptoms in a clinically meaningful manner beyond an approach that uses the scores as a continuum. This separation allowed us to quantify that for each level of cognitive function, greater degrees of depressive symptoms were associated with a higher rate of mortality. Similarly, for each level of depressive symptoms, worse cognitive function was associated with a higher rate of mortality. Thus, our study adds to prior studies by demonstrating that cognitive function and depressive symptoms increase mortality risk over a wide range of symptomatology.
Further, our study included more extensive adjustment for potential confounders of the relation between poor cognitive function, depressive symptoms, and mortality than previous studies. This is important because participants with poor cognitive function or depressive symptoms generally have more comorbid illness, more functional impairment, worse socioeconomic status, more sensory impairment, and higher rates of smoking, any of which could partially confound the relationship with mortality. We have demonstrated that these two risk factors are independent of each other, as well as independent of the other confounders we assessed, in their contribution to mortality. However, it is possible that if we had controlled for a higher-level measure of functional status, such as instrumental ADLs, the relationship between cognitive function, depressive symptoms, and mortality may have been reduced as instrumental changes may be the mechanism by which these two risk factors affect mortality.
Our results are consistent with a common theme in geriatric medicine: the risk for poor outcomes is best explained by the additive effects of two or more risk factors acting together, rather than by any single risk factor acting alone (2,37). For example, Gill and colleagues (37) have described how the additive effects of physical impairment and cognitive impairment contribute to the risk for ADL decline in a progressive, additive manner. Similarly, Tinetti and colleagues (2) have demonstrated that the additive effects of risk factors encompassing multiple domains best explain the risk for geriatric syndromes such as falls, incontinence, and functional dependence. Although depressive symptoms and cognitive impairment are interrelated and often coexist, our study demonstrates that an older person's risk for death is better explained by considering the additive effects of both risk factors, than by considering either risk factor alone.
To understand the possible mechanism explaining why poor cognitive function and depressive symptoms increase the risk of mortality, one can consider recent changes in the view of the complex relationship between depression and dementia. Until recently, much emphasis was placed on the importance of distinguishing between depression and dementia. It was commonly thought that depression could often masquerade as dementia and that some elderly adults with cognitive impairment and depression had "pseudodementia" (38). More recent conceptualizations have expanded this view by not only considering the possibility that depression could masquerade as cognitive impairment, but also by emphasizing the need to view cognitive impairment and depressive symptoms as coexisting conditions. Although there may be some elderly adults in whom cognitive impairment is entirely explained by depressive symptoms, it is probably more common that depressive symptoms are a complicating comorbidity in patients with cognitive impairment, or that depressive symptoms are an early predictor of impending cognitive loss (39).
These alternative frameworks for considering the relation between poor cognitive function and depressive symptoms suggest three plausible mechanisms by which these two risk factors could both increase the risk for mortality. First, it is possible that it is primarily poor cognitive function that predicts mortality, and depressive symptoms only seem to predict mortality because depressive symptoms predict subsequent cognitive impairment (20). Second, it is possible that it is primarily depressive symptoms that predict mortality, and poor cognitive function only seems to predict mortality because participants with cognitive function are likely to be depressed as a result of their poor cognitive function. Third, it is possible that poor cognitive function and depressive symptoms each increase the risk for mortality independently and that both have true etiologic roles in increasing the risk for mortality.
Although our results do not definitively distinguish between these three possibilities, we believe they are most consistent with the third hypothesis. First, poor cognitive function and depressive symptoms contribute almost equally to the risk for mortality. If depressive symptoms only predicted mortality because they were a predictor of future poor cognitive function, one would expect the relation between depressive symptoms and mortality to have been smaller for the worst levels of cognitive function. Conversely if poor cognitive function acted via depressive symptoms, the effect would have been smaller in the groups with the worst depressive symptoms. Instead the relation between depressive symptoms and mortality is consistent across all levels of cognitive function, and the relation between cognitive function and mortality is consistent across all levels of depressive symptoms. This finding is most consistent with the hypothesis that both depressive symptoms and cognitive impairment contribute to an increased risk for mortality.
The primary strength of this study is that it is representative of a population-based sample of more than 6000 older adults in whom cognitive function and depressive symptoms were measured with validated scales at baseline. Further, we adjusted for many confounders that could be associated with cognitive function and depressive symptoms, making it less likely that our findings could be explained by greater comorbid illness and functional impairment. However, a few methodologic considerations deserve comment. First, although the scales used to measure cognitive function and depressive symptoms are not widely used, they underwent extensive validity testing and are strongly correlated with commonly used instruments (27,28,34). Second, since no clinical measurements of cognitive impairment and depressive symptoms were taken in the AHEAD study, we cannot determine to what extent our findings represent specific clinical diagnoses such as dementia or major depressive disorder. However, since only a small number of people would have met clinical criteria for dementia or mild cognitive impairment, the scales used allow us to consider the full range of function, in line with the goals of this study. Third, another potential limitation is that participants who were cognitively impaired were more likely to have proxy interviews and therefore to be excluded from this study. This could potentially underestimate the true effect of poor cognitive function on mortality risk. Fourth, we did not have standardized cause of death information. Fifth, although the AHEAD study assessed a wide range of potential predictors of mortality, we were not able to control for all potential confounders of mortality. For example, future studies of this topic may wish to include psychological covariates such as social support as they may play an important role in the development of depressive symptoms and are also correlated with both poor cognitive function and mortality (40).
In summary, poor cognitive function and depressive symptoms are independent predictors of mortality over 2 years, and these associations remain after adjustment for multiple potential confounders. In participants with the best, middle, and worst cognitive function, more depressive symptoms are associated with increased mortality, and in participants with low, middle, and high depressive symptom counts, poor cognitive function is associated with higher levels of mortality. Thus the combination of depressive symptoms and worse cognitive function increases mortality risk in a progressive, additive manner. Cognitive function and depressive symptoms together stratify elderly adults into groups with widely differing 2-year rates of mortality, ranging from 3% to 16%. Our results highlight the need to consider both of these measures of mental well-being as important indicators of vulnerability in community-living elderly adults.
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Acknowledgments |
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Address correspondence to Kala M. Mehta, DSc, Division of Geriatrics, University of California, San Francisco, 4150 Clement St., Box 181G, San Francisco, CA 94121. E-mail: kala{at}itsa.ucsf.edu
Received September 3, 2002
Accepted October 11, 2002
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hrswww/docs/impute.html. Accessed November 26, 2002.
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