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Psychosomatic Medicine 67:609-615 (2005)
© 2005 American Psychosomatic Society

ORIGINAL ARTICLES

Do Depressive Symptoms Predict Declines in Physical Performance in an Elderly, Biracial Population?

Susan A. Everson-Rose, PhD, MPH, Kimberly A. Skarupski, PhD, MPH, Julia L. Bienias, ScD, Robert S. Wilson, PhD, Denis A. Evans, MD and Carlos F. Mendes de Leon, PhD

From the Rush Institute for Healthy Aging (S.A.E-R., K.A.S., J.L.B., R.S.W., D.A.E., C.F.M.d.L.), and the Departments of Preventive Medicine (S.A.E-R., C.F.M.d.L.), Internal Medicine (K.A.S., J.L.B., D.A.E., C.F.M.d.L.), and Neurological Sciences (R.S.W., D.A.E.), Rush University Medical Center, Chicago, Illinois.

Address correspondence and reprint requests to Susan A. Everson-Rose, PhD, MPH, Rush University Medical Center, Department of Preventive Medicine, 1700 West Van Buren Street, Suite 470, Chicago, IL 60612. E-mail: Susan_Everson{at}rush.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: We investigated whether depressive symptoms, assessed by the 10-item Center for Epidemiological Studies Depression Scale (CES-D), predicted change in physical function in elderly adults.

Methods: Participants were from a biracial, population-based sample of adults aged 65 and older (N: 4069; 61% black; 61% female). Physical function was assessed as a summary performance measure of tandem stand, measured walk, and repeated chair stand (mean [standard deviation], 10.3 [3.5]; range, 0–15), commonly used measures of overall physical health in older adults. Generalized estimating equation models estimated physical function across 3 assessments over 5.4 years of follow up as a function of CES-D scores at baseline.

Results: Adjusting for age, sex, race, and education, each 1-point higher CES-D score was associated with a 0.34-point lower absolute level of physical performance (p < .0001), but there was no evidence of a CES-D by time interaction (p = .84), indicating that depressive symptoms at baseline were not associated with greater physical performance decline over time. In secondary analyses, with CES-D scores modeled in 4 categories, overall physical performance showed a graded, inverse association across CES-D categories (p’s < .0001). However, we observed no threshold effect for depressive symptoms in relation to change in physical performance. Compared with the referent group (CES-D = 0), the 2 middle CES-D categories (CES-D = 1 or 2–3) evidenced some decline in physical performance over time, but the highest CES-D group (CES-D ≥4) showed no significant physical decline over time (p = .89).

Conclusion: We observed a strong cross-sectional association between depressive symptoms and overall physical performance. Physical function declined over time, yet depressive symptoms did not consistently contribute to greater decline over an average of 5.4 years of follow up among older adults. Findings highlight the importance of longitudinal models in understanding the relation between depressive symptomatology and physical health.

Key Words: depressive symptoms • physical function • white • black • health • longitudinal

Abbreviations: CES-D = Center for Epidemiological Studies Depression Scale; CHAP = Chicago Health and Aging Project; CI = confidence interval; GEE = generalized estimating equation; MMSE = Mini-Mental Status Examination.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
The exact role of depression in the physical health of older adults remains an issue of continuing controversy. Although poor health has been consistently associated with greater depressive symptomatology, the degree to which depressive symptoms contribute to changes in health in older populations remains largely unclear. A number of studies have found that depressive symptoms are independently related to increased morbidity and mortality risk (1–7), whereas other studies have failed to find evidence for this association (8–11).

Changes in overall health in older adults often are characterized by measures of impaired physical function and disability. One reason for this is that most chronic conditions become much more prevalent with increasing age, and older adults often have multiple conditions at the same time. Impaired physical function and disability are a common consequence of comorbid disease processes and are therefore a useful overall aggregate indicator of age-related declines in physical health (12). Assessment of disability-related outcomes typically focuses on self-reported limitations in basic activities such as activities of daily living and performance-based tests of physical function.

Previous studies have reported that depressive symptoms are associated both cross-sectionally and prospectively with increased risk of disability or physical impairment (13–17). Conversely, poor physical function itself is associated with higher levels of depressive symptoms and worsening of symptoms over time (18–21), suggesting a reciprocal association between depression and disability (22–24). Most of this research has used self-report measures of disability, which raises the possibility that evaluations of physical abilities are influenced by depressed affect, leading to spurious associations between depression and disability. This problem is most likely to affect studies that either have used dichotomous definitions of depression or disability status, or have relied on limited longitudinal data (i.e., 2 waves of data), which allows only an imperfect assessment of change from basal levels.

There have been few systematic studies of depressive symptoms and changes in performance-based assessment of physical function among older adults. One study found a significant association between chronic depression and concomitant decline in physical function in a subset of older adults, but the findings were inconclusive with regard to the temporal order of this relationship (25). A second study found that an elevated level of depressive symptoms was predictive of decline in performance-based assessment of physical function after 4 years of follow up in the Iowa cohort of the Established Populations for Epidemiologic Studies of the Elderly (EPESE) (26). Another study found that depression and selected medical conditions were associated with more disability and worse performance on tests of physical function over 3.4 years of follow up among a cohort of approximately 2500 elders recruited from a health maintenance organization (27). All of these studies included relatively homogeneous populations and relied on dichotomous indicators of depressed mood, thus failing to use their full spectrum of data on depressive symptoms. Two of the studies (25,26) were further limited by data obtained at only 2 points in time.

To our knowledge, no published studies have examined the longitudinal association between depressive symptoms and change in physical function using more than 2 assessments in a randomly selected, population-based cohort. Multiple assessments in a longitudinal study enable us to better characterize changes in physical health that occur over time and more fully separate change from basal levels, and offer more precision in estimating associations between putative risk factors and changes in physical health. Accordingly, we investigated the relationship between depressive symptoms assessed at baseline and change in physical function over time in a biracial community sample of men and women aged 65 years and older. We hypothesized that higher levels of depressive symptoms at the start of the study would be associated with greater decline in physical function over time.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Study Population
Participants were from the Chicago Health and Aging Project (CHAP), an ongoing longitudinal study of risk factors for incident Alzheimer disease and other age-related chronic conditions (28). The CHAP study includes 6158 (78.9% of eligible) participants (60.7% female) aged 65 years and older from 3 adjacent neighborhood areas located on the south side of Chicago, Illinois. Participants were predominantly black (61.6%) or white (38.2%), with 0.2% reporting another racial category. Respondents were categorized as black or nonblack for the purpose of analyses. Study details have been published previously (28–30). Baseline assessments, conducted between 1993 and 1997, included the Center for Epidemiological Studies Depression Scale (CES-D) and other psychosocial factors, medical and medication history, anthropometric measurements, health behaviors, socioeconomic factors, self-rated health status, cognitive activities in adulthood and childhood, and a battery of cognitive tests. Two follow-up assessments have been completed in 3-year intervals, on average, with 86.7% (N = 4320) and 72.9% (N = 2943) of surviving respondents participating at the first and second follow ups, respectively. Before the first follow up, 1182 participants died; an additional 942 participants died before the second follow up, for an overall mortality rate of 34.5%. At the first follow up, 8% refused further participation and 5.3% had relocated or could not be contacted. At the second follow up, nonparticipation resulting from refusals was 23.2% and 3.9% had relocated or could not be contacted. The Institutional Review Board of Rush University Medical Center approved the study and all participants provided written, informed consent at each assessment. Because the present study was focused on the longitudinal changes in physical function associated with depressive symptoms, we limited the analyses to 4069 participants with valid CES-D data at the baseline assessment and valid physical performance data at baseline and at least 1 follow-up interview. Those who were included in the analyses reported fewer depressive symptoms and had better physical performance scores at baseline and were younger and better educated (all p < .0001), but did not differ by sex or race compared with those who were excluded for any reason.

Measurement of Depressive Symptoms
Depressive symptoms were measured using the 10-item, yes/no version of the CES-D (31). The original CES-D includes 20 self-report items and was developed for use in epidemiologic studies in the general population (32). The 10-item form, developed and tested at the East Boston EPESE site and used with a 65 and older population, was found to retain acceptable reliability and tap the same 4 dimensions as the original 20-item CES-D. One point is assigned for each "depressed" response and points are summed across the 10 items (range, 0–10). Six of the 10 items had to be nonmissing for the summary score to be nonmissing. The continuous CES-D summary forms our primary measure of depressive symptoms in this analysis. We also computed a categorical CES-D variable for a secondary analysis to explore the gradient association between depressive symptoms and physical function in greater detail. To that end, we created 4 CES-D categories: scores of 0, 1, 2 to 3, and 4 or higher. The highest level, a score of 4 or higher, corresponds to the cutoff score of this version of the CES-D, which has shown excellent specificity and sensitivity in identifying older adults with major depression (33).

Assessment of Covariates
Age at baseline was assessed through self-report of birthdate and modeled continuously centered at age 75 years. An age-squared term also was entered into every model to account for nonlinear effects of age on physical performance. Sex was modeled as a binary variable with female as the referent. Race was measured by the same questions that were used in the 1990 U.S. Census and was modeled as a binary variable with nonblack as the referent. Education was reported as the highest grade or year of regular school completed and modeled continuously, centered at 12.

Assessment of Physical Function
Physical function was assessed at baseline and each follow-up assessment by 3 performance tests that focus on lower-extremity strength, balance, and gait, including tandem stand, measured walk, and repeated chair stand. These are commonly used tests of physical function in elderly populations with reasonable reliability (34) and well-established predictive validity (35,36). The tandem stand test measures the duration a full tandem stand can be maintained (up to 10 seconds). The measured walk tests the time to complete an 8-foot walk, and the chair stand measures the time to complete 5 repeated chair stands. In keeping with procedures established previously (35), recorded times for all 3 tests are converted into quintiles of timed performance, with an additional category for those who are unable to complete the test. This results in scores ranging from 0 to 5, which are summed across the 3 tests for an overall summary measure of physical performance (range, 0–15). Higher scores indicate a higher level of physical function.

Data Analyses
We used generalized estimating equation (GEE) models (37) to model physical performance scores at each interview as a function of depressive symptoms at baseline and time since baseline. GEE fits the vector of observations for each participant, accounting for correlated within-person errors across repeated measurements. These models are highly flexible and allow choices in 1) the relationship between the outcome and the predictor; 2) the relationship of the variance to the expected outcome; and 3) the within-person correlation. Physical performance scores were modeled as a linear function of predictor variables, assuming the error term to be normally distributed. Terms representing age, sex, race, education, age-squared, time-squared, and 3 interaction terms representing the effects of age x sex, time x age, and time x sex were included as covariates in all models. These interaction terms were added to fit additional heterogeneity in physical performance scores among men and women of different ages, and in change in physical performance over time by age and sex, respectively.

The primary analysis consisted of testing the relationship of level of depressive symptoms, represented by the continuous CES-D measure, with changes in physical function. We first examined the main effect of baseline CES-D scores on physical performance scores across all 3 interviews (model 1). This model represents the absolute or cross-sectional association of depressive symptoms with physical function. We next added the baseline CES-D score by time interaction term to test whether CES-D scores were associated with change in physical performance scores (model 2). The interaction term forms the formal test of our hypothesis that depressive symptoms are prospectively associated with greater decline in physical function. We also explored the gradient association between depressive symptoms and change in physical function by replacing the continuous CES-D scores with a categorical CES-D variable (models 3 and 4), using 0 symptoms as the referent category and 3 dummy-coded variables representing CES-D scores of 1, 2 to 3, and 4 or higher. Model assumptions were tested both analytically and graphically, and were found to be adequately met. All models were computed using the PROC GENMOD procedure in SAS (SAS Institute Inc., Cary, NC).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
Participant Characteristics
Participant characteristics are presented in Table 1. Of the 4069 participants included in the present analyses, the majority were female (61.2%) and black (61.3%). On average, participants were nearly 74 years old at baseline and had a high school education. Follow-up time ranged from 1.8 to 9 years, with an average of 5.4 years. The average CES-D score at baseline was 1.5 (standard deviation [SD], 1.9) and the majority of participants reported less than two depressive symptoms (66.1%), with 14% reporting 4 or more symptoms. The average physical performance score was 10.3 (SD, 3.5) and scores were lower for successive CES-D categories.


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  		TABLE 1. Participant Characteristics: Chicago Health and Aging Project (1993–2003)

 

Baseline CES-D and physical performance summary scores varied by demographic characteristics (Table 2). Older participants, blacks, women, and less educated participants had significantly higher CES-D scores and significantly lower physical performance scores at the baseline examination than their respective counterparts (all p’s < .0001).


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  		TABLE 2. Baseline Depressive Symptoms and Physical Performance Score by Demographic Characteristics Among 4069 Participants From the Chicago Health and Aging Project (1993–2003)

 

Depressive Symptoms and Physical Performance
Table 3 presents results from the GEE models examining the association between baseline depressive symptoms and changes in physical performance, adjusted for age, time in the study, sex, and their interactions, as well as race and education. The significant time and time x time terms (all models) indicate that physical performance scores showed a significant (p < .0001) nonlinear, accelerating pattern of decline during follow up. Baseline CES-D scores were significantly associated with physical performance scores (ß = –0.34, p < .0001) across the 3 interviews (model 1). Thus, each additional depressive symptom was associated with a 0.34-point lower physical performance score at each point in time. However, the CES-D by time interaction term was not significant (ß = –0.001, p = .84), indicating that baseline depressive symptoms were not associated with decline in physical function over time (model 2).


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  		TABLE 3. Generalized Estimating Equation Models for Depressive Symptoms and Change in Physical Performance Over 5.4 Years of Follow Up in the Chicago Health and Aging Project, 1993–2003

 

Our analysis using categories of depressive symptoms lends further support to a gradient cross-sectional association between depressive symptoms and physical function. Compared with the lowest CES-D group, each of the higher CES-D categories was associated with significantly lower physical performance scores (p’s < .0001), and the difference with the referent group increased with each successive category (model3). The interaction terms for CES-D category by time suggest a nonlinear pattern of associations (model 4). Relative to the referent group, the second (ß = –0.05, p = .07) and third (ß = –0.06, p = .035) CES-D categories each showed a greater decline in physical performance scores over time, although the effect was only marginally significant for the second group. The highest CES-D category, however, did not differ significantly from the referent group in terms of change in physical function over time (ß = –0.00, p = .89).

To further examine these results, we graphed the predicted physical performance scores by year of follow up for each of the CES-D categories separately. As an example, predicted scores were computed for a 75-year-old black woman with 12 years of education (Fig. 1). Physical performance scores declined over time by 1.9, 2.2, 2.3, and 2.0 points, respectively, from lowest to highest CES-D categories. Thus, each category showed small but consistent decreases in physical performance over time, with the greatest decline seen among the second and third CES-D categories.



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  		Figure 1. Predicted physical performance values over time for a 75-year-old black woman with 12 years of education by CES-D categories.

 

Effect of Sociodemographic Characteristics on Physical Performance
We observed main effects of race (ß = –1.31, 95% confidence interval [CI] = –1.51, –1.10) and education (ß = 0.12, 95% CI = 0.09, 0.14) on physical performance (p’s < .0001), with blacks and less educated participants having lower physical performance scores. Main effects of age (ß = –0.19, 95% CI = –0.21, –0.17) and sex (ß = 0.90, 95% CI = 0.69, 1.11) also were significant (p’s < .0001), indicating that older participants and women had lower physical performance scores at baseline. A significant age-squared term (ß = –0.004, 95% CI = –0.006, –0.002, p < .0001) showed that baseline age had a nonlinear effect on physical performance. In addition, a baseline age-by-sex interaction (ß = 0.04, 95% CI = 0.005, 0.075) revealed that sex differences in physical performance scores were larger with older age at baseline (p < .03). A time x age interaction indicated that physical performance declined more rapidly in older than younger participants (ß = –0.021, 95% CI = –0.024, –0.017, p < .0001).

Weighted Analyses
To examine whether the loss to follow up that occurred in this study influenced the main findings, we reestimated our primary models and examined the effect of excluding from our analyses people who failed to provide data at at least two time points resulting from death, refusals, relocation, or missing data on key variables. We did this by refitting the models shown in Table 3, using the propensity weighting method to weight the observations (38,39), with propensities of being in the analysis determined from a logistic regression model adjusting for age, sex, race, education, CES-D score, income, and score on the Mini-Mental Status Examination (MMSE). All 6158 participants in the CHAP study were included in the logistic regression model, which included indicator variables to describe those missing education, CES-D, income, or MMSE data. These propensity-weighted models were essentially the same as our primary models. The main effect of CES-D scores on overall level of physical performance was highly significant (p < .0001) after adjusting for missing persons. We did find that the quadratic effect of age on level of physical performance was diminished and became marginally significant (p = .08). Also, the model that examined the gradient effects of CES-D scores showed a weaker effect of CES-D category on change in physical performance than in the primary model, with the middle 2 CES-D category-by-time interactions only marginally significant (p = .07 and p = .09, respectively).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
In this study, we found that depressive symptoms were strongly associated with overall physical function in an elderly, biracial population sample. However, we did not find clear support for our primary hypothesis that depressive symptoms were associated with a greater decline in physical function over time. Thus, although these results demonstrate a pronounced, cross-sectional association between depressive symptoms and absolute level of physical function, they show little consistent evidence for a prospective relationship. This pattern of associations highlights the important contributions that longitudinal models can make to our understanding of the impact of psychosocial factors on health.

Our findings differ from those of Penninx and colleagues who reported that participants with a higher level of depressive symptoms showed significant physical decline over 4 years in the Iowa EPESE cohort (26) and over 3 years in a longitudinal Dutch study (25). The discrepancy in results may be the result of several factors. The prior studies by Penninx and colleagues included whites only, whereas our population was biracial. However, we repeated our analyses separately within each racial group and found the same pattern of associations (results not shown) as in the full sample. Another difference is that we considered the full spectrum of depressive symptoms in our analysis, whereas other studies have typically focused on comparing the most depressed relative to all others. The latter method may be more efficient in the context of a clear nonlinear or "threshold" effect of depressive symptoms on changes in physical function. However, our secondary analysis of the grouped CES-D categories did not reveal any evidence for a presumed threshold effect. In fact, the highest CES-D group, based on a cutoff point that has been used to identify those most at risk for clinical depression (33), did not show a different rate of decline in physical function compared with the lowest group. In contrast, the middle 2 CES-D categories showed a decline in physical function over time, although this effect was relatively weak, and the absolute change in physical performance scores differed by less than half of a point (range, 1.9–2.3 points) across the 4 CES-D categories (Fig. 1).

In the absence of a consistent prospective association, the cross-sectional association between depressive symptoms and poor physical performance that we observed in this study raises the issue of temporality. Other studies found that depressive symptoms are a consequence of declines in physical health (18–21). A similar pattern of findings also could be the result of depressed people being more likely to underperform on physical performance tests relative to their actual abilities. In this case, depression would adversely affect performance scores but would be unrelated to the processes that result in declining physical function. However, the lack of a clear prospective effect also could be the result of the fact that the association between depressive symptoms and overall physical health in older adults is more complex and involves reciprocal effects between depression and physical function. For example, declining physical health may cause depressive reactions, which in turn may aggravate the disease processes that give rise to declining physical health and function. Similar patterns of association have been noted previously for psychosocial factors and self-reported disability (40–42).

It is possible that certain features of our study design have contributed to our failure to find more consistent evidence for a prospective association between depressive symptoms and decline in physical function. Serial physical performance tests were administered at approximately 3-year intervals. Because our sample was elderly, significant attrition resulting from death and nonparticipation occurred, although participation rates remained very good. The extent to which these sources of attrition are associated with greater decline in physical function as well as with higher levels of depressive symptoms at baseline may have biased our estimates of the longitudinal effect toward the null. Of all CHAP participants at baseline, those with the highest CES-D scores (≥4) were more than 50% more likely to have been excluded from the analysis as a result of missing follow-up data relative to those with the lowest CES-D score. This group also had greater mortality over the course of the study (hazard ratio = 1.59; 95% CI = 1.41, 1.80; p < .0001). It is possible that we may have missed some of the decline in physical function that occurred over time as a result of the length of the follow-up intervals, which may have differentially affected the most depressed. Nevertheless, the propensity-weighted analyses that accounted for missing people in the analysis revealed essentially the same pattern of associations as our primary models, indicating that attrition in this study did not unduly influence the results. The pattern of decline associated with the 2 middle CES-D categories (model 4, Table 3) is suggestive of a gradient prospective effect, although these effects were weak and not statistically significant in the propensity-weighted models. Future studies with more frequent assessment of physical function will be able to more fully evaluate this pattern of association.

Although depressive symptoms were not associated with more rapid decline in physical function in this study, the fact that higher levels of depressive symptoms were associated with lower physical function overall in this elderly population has important implications. Prevalence of depression (clinically defined) is estimated to be 8% to 16% in late life (43,44) and frequently is underdiagnosed and undertreated (45). Subsyndromal depression also is highly prevalent in elderly populations (46,47). In addition to functional outcomes, depressive symptoms have been associated with chronic pain and arthritis (48), poorer quality of life (49), self-reported disability (50), and mortality (2,3) in older adults. Clearly, depression is an important public health concern and has significant deleterious effects on several parameters of health and quality of life in our aging population. Taken together, the breadth of evidence highlights the importance of early detection and treatment of depressive symptoms in the elderly.

One strength of our study is the use of a performance-based measure of physical function. Indeed, this measure was chosen to provide a more objective assessment of physical health than self-report. We were concerned that more depressed people would provide more negative self-reports about their health conditions, leading to potentially spurious correlations. This performance-based measure is a useful and well-accepted summary measure of overall physical health in an aging population (12). In CHAP, this measure is associated with mortality; each 1-point higher score at baseline (i.e., better performance) is related to a 12% decreased risk of dying (p < .0001). Because we were interested in the impact of depressive symptoms on decline in overall physical health, rather than functional decline in response to prevalent medical conditions, we did not separately adjusted for chronic diseases or comorbid health conditions in our analyses. Other strengths of the present study are the use of repeat assessments over the follow-up period, a biracial, population-based sample of elders, and good participation rates.

One potential limitation of our study is the lack of clinical assessment of depression. Although the CES-D is widely used and accepted as an instrument that records the spectrum of depressive symptoms as it occurs in the general population, it does not provide a clinical diagnosis of major depression. It is possible that individuals who have clinical depression experience a more rapid decline in health over time compared with individuals without clinical depression. This implies that some threshold of symptoms needs to be reached before the adverse health consequences of depression are manifest; however, the extant literature does not support this notion. Although some studies have shown that clinically assessed major depression has a significant impact on subsequent health (51–53), a large number of studies have demonstrated that increasing depressive symptoms, assessed by a variety of checklist-type measures, are associated with poorer health outcomes and greater morbidity (5,54,55). Indeed, it has been reported that subsyndromal depression and clinically significant depressive symptomatology that do not meet DSM-IV criteria are more prevalent than major depression among the elderly and have concomitant negative effects on functional ability and general medical burden (46,47,56,57).

In summary, we failed to find clear evidence for a prospective association between depressive symptoms and change in physical function, suggesting that depressive symptoms do not lead to declining physical function in older adults. The lack of a prospective finding is at odds with prior work but, to our knowledge, this is one of the first studies to explore the association between depressive symptoms and change in physical function over time with multiple waves of data. However, we do not exclude the possibility that a prospective association exists, because our negative findings may have been in part the result of the design limitations of our study. We further note that the relationship between depression and change in physical health conceivably involves reciprocal effects, and it may require studies with more frequent assessment of depression and physical function to disentangle the exact nature of this relationship. Nevertheless, our findings add to the literature demonstrating that depressive symptoms constitute an important health concern among elders that is associated with poorer physical function.

We thank Ann Marie Ryan Stewart for community development and oversight of project coordination Michelle Bos, Flavio Lamorticella, and Jennifer Tarpey for study coordination; and Linyun Zhou for data analysis.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 

This study was funded by grants AG11101 and ES10902 from the National Institutes of Health.

DOI:10.1097/01.psy.0000170334.77508.35


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

  1. Wilson RS, Bienias JL, Mendes de Leon CF, Evans DA, Bennett DA. Negative affect and mortality in older persons. Am J Epidemiol 2003;158:827–35.[Abstract/Free Full Text]
  2. Schulz R, Beach SR, Ives DG, Martire LM, Ariyo AA, Kop WJ. Association between depression and mortality in older adults: the Cardiovascular Health Study. Arch Intern Med 2000;160:1761–8.[Abstract/Free Full Text]
  3. Black SA, Markides KS. Depressive symptoms and mortality in older Mexican Americans. Ann Epidemiol 1999;9:45–52.[CrossRef][Medline]
  4. Fuhrer R, Dufouil C, Antonucci TC, Shipley MJ, Helmer C, Dartigues JF. Psychological disorder and mortality in French older adults: do social relations modify the association? Am J Epidemiol 1999;149:116–26.[Abstract/Free Full Text]
  5. Everson SA, Roberts RE, Goldberg DE, Kaplan GA. Depressive symptoms and increased risk of stroke mortality over a 29-year period. Arch Intern Med 1998;158:1133–8.[Abstract/Free Full Text]
  6. Whooley MA, Browner WS. Association between depressive symptoms and mortality in older women. Study of Osteoporotic Fractures Research Group. Arch Intern Med 1998;158:2129–35.[Abstract/Free Full Text]
  7. Anda R, Williamson D, Jones D, Macera C, Eaker E, Glassman A, Marks J. Depressed affect, hopelessness, and the risk of ischemic heart disease in a cohort of US adults. Epidemiology 1993;4:285–94.[Medline]
  8. Fredman L, Magaziner J, Hebel JR, Hawkes W, Zimmerman SI. Depressive symptoms and 6-year mortality among elderly community-dwelling women. Epidemiology 1999;10:54–9.[CrossRef][Medline]
  9. Mendes de Leon CF, Krumholz HM, Seeman TS, Vaccarino V, Williams CS, Kasl SV, Berkman LF. Depression and risk of coronary heart disease in elderly men and women: New Haven EPESE, 1982–1991. Established Populations for the Epidemiologic Studies of the Elderly. Arch Intern Med 1998;158:2341–8.[Abstract/Free Full Text]
  10. Thomas C, Kelman HR, Kennedy GJ, Ahn C, Yang CY. Depressive symptoms and mortality in elderly persons. J Gerontol Soc Sci 1992;47:80–7.
  11. Everson-Rose SA, House JS, Mero R. Depressive symptoms and mortality risk in a national sample: confounding effects of health status. Psychosom Med 2004;66:823–30.[Abstract/Free Full Text]
  12. Manton KG, Corder L, Stallard E. Chronic disability trends in elderly United States populations: 1982–1994. Proc Natl Acad Sci U S A 1997;94:2593–8.[Abstract/Free Full Text]
  13. Bruce ML, Seeman TE, Merrill SS, Blazer DG. The impact of depressive symptomatology on physical disability: MacArthur studies of successful aging. Am J Public Health 1994;84:1796–9.[Abstract/Free Full Text]
  14. Ormel J, Kempen GI, Deeg DJ, Brilman EI, van Sonderen E, Relyveld J. Functioning, well-being, and health perception in late middle-aged and older people: comparing the effects of depressive symptoms and chronic medical conditions. J Am Geriatr Soc 1998;46:39–48.[Medline]
  15. Penninx BW, Leveille S, Ferrucci L, van Eijk JT, Guralnik JM. Exploring the effect of depression on physical disability: longitudinal evidence from the established populations for epidemiologic studies of the elderly. Am J Public Health 1999;89:1346–52.[Abstract/Free Full Text]
  16. Menchetti M, Fava C, Berardi D. Disability associated with depressive symptoms in elderly primary care attenders. Arch Gerontol Geriatr 2001;33(suppl 1):261–6.[CrossRef]
  17. Geerlings SW, Beekman ATF, Deeg DJH, Twisk JWR, van Tilburg W. The longitudinal effect of depression on functional limitations and disability in older adults: an eight-wave prospective community-based study. Psychol Med 2001;31:1361–71.[Medline]
  18. Kennedy GJ, Kelman HR, Thomas C. The emergence of depressive symptoms in late life: the importance of declining health and increasing disability. J Community Health 1990;15:93–104.[CrossRef][Medline]
  19. Zeiss AM, Lewinsohn PM, Rohde P, Seeley JR. Relationship of physical disease and functional impairment to depression in older people. Psychol Aging 1996;11:572–81.[CrossRef][Medline]
  20. Roberts RE, Kaplan GA, Shema SJ, Strawbridge WJ. Prevalence and correlates of depression in an aging cohort: the Alameda County Study. J Gerontol B Psychol Sci Soc Sci 1997;52:252–8.
  21. Turner RJ, Noh S. Physical disability and depression: a longitudinal analysis. J Health Soc Behav 1988;29:23–37.[CrossRef][Medline]
  22. Graney MJ. The reciprocal relationship between disability and depression. J Am Geriatr Soc 2000;48:452–3.[Medline]
  23. Lenze EJ, Rogers JC, Martire LM, Mulsant BH, Rollman BL, Dew MA, Schulz R, Reynolds CF III. The association of late-life depression and anxiety with physical disability: a review of the literature and prospectus for future research. Am J Geriatr Psychiatry 2001;9:113–35.[Abstract/Free Full Text]
  24. Ormel J, Rijsdijk FV, Sullivan M, van Sonderen E, Kempen GI. Temporal and reciprocal relationship between IADL/ADL disability and depressive symptoms in late life. J Gerontol B Psychol Sci Soc Sci 2002;57:338–47.
  25. Penninx BW, Deeg DJ, van Eijk JT, Beekman AT, Guralnik JM. Changes in depression and physical decline in older adults: a longitudinal perspective. J Affect Disord 2000;61:1–12.[CrossRef][Medline]
  26. Penninx BW, Guralnik JM, Ferrucci L, Simonsick EM, Deeg DJ, Wallace RB. Depressive symptoms and physical decline in community-dwelling older persons. JAMA 1998;279:1720–6.[Abstract/Free Full Text]
  27. Wang L, van Belle G, Kukull WB, Larson EB. Predictors of functional change: a longitudinal study of nondemented people age 65 and older. J Am Geriatr Soc 2002;50:1525–34.[CrossRef][Medline]
  28. Evans DA, Bennett DA, Wilson RS, Bienias JL, Morris MC, Scherr PA, Hebert LE, Aggarwal N, Beckett LA, Joglekar R, Berry-Kravis E, Schneider J. Incidence of Alzheimer disease in a biracial urban community: relation to apolipoprotein E allele status. Arch Neurol 2003;60:185–9.[Abstract/Free Full Text]
  29. Wilson RS, Bennett DA, Beckett LA, Morris MC, Gilley DW, Bienias JL, Scherr PA, Evans DA. Cognitive activity in older persons from a geographically defined population. J Gerontol B Psychol Sci Soc Sci 1999;54:155–60.
  30. Bienias JL, Beckett LA, Bennett DA, Wilson RS, Evans DA. Design of the Chicago Health and Aging Project (CHAP). J Alzheimers Dis 2003;5:349–55.[Medline]
  31. Kohout FJ, Berkman LF, Evans DA, Cornoni-Huntley J. Two shorter forms of the CES-D depression symptoms index. J Aging Health 1993;5:179–93.[Abstract/Free Full Text]
  32. Radloff LS. The CES-D Scale: a self-report depression scale for research in the general population. In: Applied Psychological Measurement. New York: West Publishing Co; 1977:385–401.
  33. Irwin M, Artin KH, Oxman MN. Screening for depression in the older adult, criterion validity of the 10-item CES-D. Arch Intern Med 1999;159:1701–4.[Abstract/Free Full Text]
  34. Tager IB, Swanson A, Satariano WA. Reliability of physical performance and self-reported functional measures in an older population. J Geronotol Med Sci 1998;53A:M295–300.
  35. Guralnik JM, Seeman TE, Tinetti ME, Nevitt MC, Berkman LF. Validation and use of performance measures of functioning in a non-disabled older population: MacArthur studies of successful aging. Aging 1994;6:410–9.[Medline]
  36. Guralnik JM, Ferrucci L, Pieper CF, Leveille SG, Markides KS, Ostir GV, Studenski S, Berkman LF, Wallace RB. Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery. J Gerontol A Biol Sci Med Sci 2000;55:M221–31.
  37. Diggle PJ, Heagert P, Liang K-Y, Zeger SL. Analysis of Longitudinal Data, 2nd ed. New York: Oxford University Press; 2002.
  38. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983;70:41–55.[Abstract/Free Full Text]
  39. Little RJA. Survey nonresponse adjustments for estimates of means. Intl Stat Rev 1986;54:139–57.
  40. Verbrugge LM, Reoma JM, Gruber-Baldini AL. Short-term dynamics of disability and well-being. J Health Soc Behav 1994;35:97–117.[CrossRef][Medline]
  41. Mendes de Leon CF, Gold DT, Glass TA, Kaplan L, George LK. Disability as a function of social networks and support in elderly African Americans and Whites: the Duke EPESE 1986–1992. J Gerontol B Psychol Sci Soc Sci 2001;56:S179–90.[Abstract/Free Full Text]
  42. Mendes de Leon CF, Glass TA, Berkman LF. Social engagement and disability in a community population of older adults: the New Haven EPESE. Am J Epidemiol 2003;157:633–42.[Abstract/Free Full Text]
  43. Berkman LF, Berkman CS, Kasl S, Freeman DH Jr, Leo L, Ostfeld AM, Cornoni-Huntley J, Brody JA. Depressive symptoms in relation to physical health and functioning in the elderly. Am J Epidemiol 1986;124:372–88.[Abstract/Free Full Text]
  44. Blazer DG, Burchett B, Service C, George L. The association of age and depression among the elderly: an epidemiologic exploration. J Gerontol Med Sci 1991;46:M210–5.
  45. Blazer DG, Hughes DC, George LK. The epidemiology of depression in an elderly community population. Gerontologist 1987;27:281–7.[Medline]
  46. Lyness JM, King DA, Cox C, Yoediono Z, Caine ED. The importance of subsyndromal depression in older primary care patients: prevalence and associated functional disability. J Am Geriatr Soc 1999;47:647–52.[Medline]
  47. Caine ED, Lyness JM, King DA. Reconsidering depression in the elderly. Am J Geriatr Psychiatry 1994;1:4–20.
  48. Lin EH, Katon W, Von Korff M, Tang L, Williams JW Jr, Kroenke K, Hunkeler E, Harpole L, Hegel M, Arean P, Hoffing M, Della Penna R, Langston C, Unutzer J. Effect of improving depression care on pain and functional outcomes among older adults with arthritis: a randomized controlled trial. JAMA 2003;290:2428–34.[Abstract/Free Full Text]
  49. Ruo B, Rumsfeld JS, Hlatky MA, Liu H, Browner WS, Whooley MA. Depressive symptoms and health-related quality of life: the Heart and Soul Study. JAMA 2003;290:215–21.[Abstract/Free Full Text]
  50. Kivela SL, Pahkala K. Depressive disorder as a predictor of physical disability in old age. J Am Geriatr Soc 2001;49:290–6.[CrossRef][Medline]
  51. Carney RM, Rich MW, Freedland KE, Saini J, teVelde A, Simeone C, Clark K. Major depressive disorder predicts cardiac events in patients with coronary artery disease. Psychosom Med 1988;50:627–33.[Abstract/Free Full Text]
  52. Pulska T, Pahkala K, Laippalla P, Kivela SL. Major depression as a predictor of premature deaths in elderly people in Finland: a community study. Acta Psychiatr Scand 1998;97:408–11.[Medline]
  53. Lesperance F, Frasure-Smith N, Talajic M. Major depression before and after myocardial infarction: its nature and consequences. Psychosom Med 1996;58:99–110.[Abstract/Free Full Text]
  54. Vaccarino V, Kasl SV, Abramson J, Krumholz HM. Depressive symptoms and risk of functional decline and death in patients with heart failure. J Am Coll Cardiol 2001;38:199–205.[Abstract/Free Full Text]
  55. Wilson RS, Barnes LL, Mendes de Leon CF, Aggarwal NT, Schneider JS, Bach J, Pilat J, Beckett LA, Arnold SE, Evans DA, Bennett DA. Depressive symptoms, cognitive decline, and risk of AD in older persons. Neurology 2002;59:364–70.[Abstract/Free Full Text]
  56. Koenig HG, Blazer DG. Minor depression in late life. Am J Geriatr Psychiatry 1996;4(suppl 1):S14–21.
  57. Romanoski AJ, Folstein MF, Nestadt G, Chahal R, Merchant A, Brown CH, Gruenberg EM, McHugh PR. The epidemiology of psychiatrist-ascertained depression and DSM-III depressive disorders. Results from the Eastern Baltimore Mental Health Survey Clinical Reappraisal. Psychol Med 1992;22:629–55.[Medline]



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