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Psychosomatic Medicine 66:823-830 (2004)
© 2004 American Psychosomatic Society

ORIGINAL ARTICLES

Depressive Symptoms and Mortality Risk in a National Sample: Confounding Effects of Health Status

Susan A. Everson-Rose, PhD, MPH, James S. House, PhD and Richard P. Mero, MS

From the Departments of Preventive Medicine and Psychology and Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, IL (S.A.E-R.); Survey Research Center, Institute for Social Research, Ann Arbor, MI (J.S.H., R.P.M.); and the Department of Sociology, University of Michigan, Ann Arbor, MI (J.S.H.).

Address correspondence and reprint requests to Susan A. Everson-Rose, PhD, MPH, Department of Preventive Medicine, Rush University Medical Center, 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
 ACKNOWLEDGMENTS
 REFERENCES
 
OBJECTIVE: We examined the association between depressive symptoms and all-cause mortality in a population sample. Published findings on the relation between depressive symptoms and mortality risk point to an inconsistent association and one that is likely influenced by health status. Few studies have assessed this relation in randomly selected population samples.

METHODS: Participants were 3617 noninstitutionalized adults, age 25 years or older, from the Americans’ Changing Lives Study, an ongoing longitudinal study of a nationally representative sample. Depressive symptoms were measured by the 11-item version of the Center for Epidemiological Studies Depression Scale (CES-D). Cox proportional hazards models estimated the relative risk of mortality as a function of the CES-D scores at baseline.

RESULTS: In 7.5 years of follow-up, 542 deaths occurred. Each 1-standard unit increase on the CES-D predicted a 21% increased risk of all-cause mortality, adjusting for age, gender, and race (hazard ratio = 1.21, 95% confidence interval = 1.08 to 1.36, p = .001). This association was weakened somewhat following adjustment for education, income, body mass index, smoking and alcohol consumption (hazard ratio = 1.13, 95% confidence interval = 0.99 to 1.28, p = .06). However, control for self-reported functional limitations or chronic health conditions at baseline effectively eliminated the relationship. Analyses limited to participants with good to excellent health or no functional impairments at baseline showed no association between depressive symptoms and subsequent mortality risk. Secondary analyses showed no association between depressive symptoms and cardiovascular mortality.

CONCLUSIONS: These findings from a randomly selected, nationally representative sample do not support the hypothesis that depressive symptoms are independently related to mortality in the general population, after adequate adjustment for the confounding effects of physical health status.

Key Words: CES-D, • depressive symptoms, • mortality, • risk factors, • health status.

Abbreviations: ACL = Americans’ Changing Lives Study;; CES-D = Center for Epidemiological Studies Depression Scale;; CHD = coronary heart disease;; CI = confidence interval;; HR = hazard ratio.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Numerous studies have examined the impact of depressive symptoms on mortality risk, with varying results. Although the majority of studies has reported positive findings (1–5), a significant number has found inconsistencies (6–8) or no association (9–14). Critically, relatively few studies utilized random population-based samples. Moreover, it is interesting to note that most of the negative or inconsistent findings come from community studies (6,10,14). Studies vary widely in the degree to which statistical control was made for potentially important confounding variables as well as in the methods used to assess depressive symptoms and important covariates. Evidence linking depression to increased morbidity and mortality in cardiac patients and to incident coronary heart disease (CHD) has been more consistent (15–17), although not unequivocal (9,11,18). Nevertheless, many reports that have appeared recently in both the popular and scientific press imply that the evidence linking depression to mortality from all causes as well as CHD is strong and conclusive. A closer look at the evidence suggests that this conclusion may be premature, particularly with respect to mortality risk.

Two recent reviews are instructive. Wulsin et al. (19) reviewed the literature from 1966 through 1996 investigating the association between depression and mortality in different populations, including psychiatric patients, cardiac patients, medical inpatients, and community samples. They identified 57 studies that met their inclusion criteria and concluded that the majority (51% of the reviewed studies had positive findings) supports the hypothesis that depression increases the risk of mortality and especially deaths due to cardiovascular diseases, suicides, or other unnatural causes but that most studies were poorly controlled. Interestingly, 26% of the studies reviewed had mixed findings, and 23% had negative findings. Schulz et al. (20) completed a review of studies published from 1997 to 2001, using similar criteria to Wulsin et al. and focusing on reports that included older participants (ie, 60 years old or older). A rapid increase in the number of studies investigating the impact of depression on mortality risk resulted in 61 studies being identified for their review, 36% of which involved community samples. Of the 61 reviewed studies, 72% were positive and 28% were negative. A larger proportion of studies based on community populations were negative than studies based on psychiatric or medical populations. Schulz et al. concluded that further research is needed to understand behavioral and biological mechanisms as well as subclinical and prevalent disease, all of which potentially mediate the association between depression and mortality and highlighted the need for well-controlled studies. Thus, two major reviews in the past 5 years have reached similar conclusions regarding the mixed state of the evidence supporting the role of depressive symptoms in increasing mortality risk and noting the need for better statistical control of important covariates.

One focus of the present report is the importance of considering physical health status when assessing the impact of depressive symptoms on mortality. It is widely recognized that poor health can and often does lead to an increase in depressive symptoms (21–23) and the comorbidity of and reciprocal relationship between health status and depressive symptoms, particularly with increasing age, are well known (24). Symptoms of many health conditions mimic the somatic complaints of depression, and one feature of depression is a poor assessment of one’s health and functioning. Thus, it may be quite difficult to distinguish between depression and poor physical health status. The significance of health status in the association between depression and mortality can be seen in looking at the individual studies reviewed by Wulsin et al. (19) and Schulz et al. (20). The studies that were reviewed used widely varying measures of health status to control for physical health, and only a small proportion of studies used nonclinical populations. Of the 11 prospective studies identified by Wulsin et al. in which the relation between depression and mortality due to all causes was assessed in nonpatient samples and some measure of health status was included as a covariate, 8 had negative findings (13,14,25–30), 2 had mixed findings (31,32), and only 1 study had clear positive findings (33). Among the more recent studies reviewed by Schulz et al. (20), 17 studies (28%) included nonclinical (ie, community-based) samples and had some control for health status. Of these, 11 had positive findings (1,2,4,34–41), 5 had negative findings (10,12,18,42,43), and another found a positive association for men and no association for women (7). Thus, taken together, the evidence from nonclinical populations for the hypothesis that depressive symptoms are independently related to greater mortality risk is decidedly mixed.

To understand the population burden of disease associated with depression and the mechanisms underlying any associations between depression and mortality, we believe it is crucial to know whether the impact of depressive symptoms on risk of death operates independently of health status or chronic conditions. We investigated the association between depressive symptoms and increased risk of mortality in a randomly selected, nationally representative population sample of adults and examined the impact of health status on this association. We hypothesized that increasing depressive symptoms would be related to greater risk of dying and that this association would be attenuated by poor health conditions.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Overview
This report is from the Americans’ Changing Lives (ACL) study, an ongoing longitudinal study of a nationally representative sample of adults in the U.S. being conducted by the Survey Research Center of the Institute for Social Research at the University of Michigan. Begun in 1986, the ACL study is designed to investigate the impact of health risk behaviors, chronic and acute stress, social relationships and support, personality characteristics, religiosity, and involvement in major social roles (eg, parent, worker, volunteer, spouse, etc.) on health and functioning and productive activities over the lifespan. Details on the study sample and research methods have been published previously (44,45). For the present analyses, we examined the relation between scores on a commonly used measure of depressive symptoms (described below) assessed at the baseline or wave 1 exam of the ACL study and subsequent risk of mortality over 7.5 years of follow-up.

Participants
Participants were 3617 noninstitutionalized adults, age 25 years or older, living in the coterminous United States who were selected through a stratified, multistage process. Individuals aged 60 or older and blacks were both oversampled at twice the rate of persons under age 60 and nonblacks. Three waves of data collection with full mortality ascertainment have been completed to date in 1986 (wave 1), 1989 (wave 2), and 1994 (wave 3). At wave 1, response rates were 70% for households and 68% for individuals (households could contain multiple eligible respondents). Interviews were conducted in person only, and no proxy respondents were allowed at waves 1 and 2. At wave 3, however, interviews were conducted mainly via telephone and face-to-face, where necessary and proxy respondents were allowed for participants no longer able to complete a telephone or face-to-face interview. Data for the predictors and covariates in the current study come from the baseline or wave 1 interview only. Participant characteristics at baseline are presented in Table 1.


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  		TABLE 1. Wave 1 Participant Demographics: Americans’ Changing Lives Study, 1986
 
All data were appropriately weighted to adjust for differential initial selection probabilities, nonresponse, and poststratification adjustments to the June 1986 age-race-gender specific Census Bureau estimates of the U.S. population. After weighting, the ACL sample is representative of the population age 25 years and older living in the contiguous U.S. in 1986.

Measurement of Depressive Symptoms
Depressive symptoms were measured by an abbreviated 11-item version of the Center for Epidemiological Studies Depression scale (CES-D) developed and validated for use in the Established Populations for Epidemiological Studies of the Elderly (46). The full 20-item CES-D was designed to assess symptoms of depression in the general population (47). The 11-item version assesses symptoms of depression within the past week, such as "I felt depressed," "I felt everything I did was an effort," and "My sleep was restless." Responses range from 1 ("hardly ever") to 3 ("most of the time"), and individual item scores are summed to create a total score, with higher scores indicative of more depressive symptoms. For purposes of analyses, CES-D scores were standardized (mean 0.00, SD 1.0). Scores on the CES-D were modeled continuously and categorically in separate analyses. For the latter analyses, five CES-D categories were created that represented approximate quintiles of the weighted distribution of standardized CES-D scores.

Ascertainment of Mortality
Mortality of ACL respondents is ascertained through the National Death Index, the Social Security Death index, newspaper obituaries, and informants. Attempts are made to secure copies of death certificates for all decedents. Causes of death are classified by the International Statistical Classification of Diseases, 10th revision. For the present analyses, all-cause mortality was our main outcome of interest. Currently, ascertainment is complete through November 1994, with 542 deaths (15%) identified and verified. Of these, 96% were verified via death certificate. Of those not verified by death certificate (N = 22), actual death appears to be certain in each case based on informants’ report of month and year of death.

Measures of Health Status
Health status was measured in four ways. First, self-reported history of hypertension was assessed by one interview item in which respondents were asked whether a health care provider had ever told them they had high blood pressure or if they were currently taking antihypertensive medication. Responses were dichotomized, with those without a history of hypertension as the referent category. Second, respondents were asked a series of questions about chronic conditions and symptoms in the last 12 months. Lung disease, heart trouble or heart attack, diabetes, stroke and cancer were considered life-threatening, chronic conditions, and a dummy-coded variable represented these conditions as none, one, or two or more chronic conditions. Third, several items assessing activities of daily living and health-related activity limitations were used to create a four-category index of functional impairment, ranging from none to severe. Finally, participants were asked to rate their own health as excellent, very good, good, fair, or poor. Greater detail on these measures of health status and functioning are provided in House et al. (44).

Assessment of Covariates
Age was modeled categorically with dummy-coded variables representing ages 35 to 44, 45 to 54, 55 to 64, 65 to 74, and 75+ years, with ages 25 to 34 as the referent group. Other sociodemographic covariates included gender (male as the referent category), race (black vs. nonblack (referent)), education (less than 12 years of education, high school degree or some college (referent category), and college degree or higher), and income (less than $10,000 per year (in 1986 dollars) and $10,000 to $29,999 per year, with >$30,000 per year as the referent). Behavioral risk factors included body mass index (classified following Berkman and Breslow (48)) as underweight, ie, lowest 5% of the distribution of weighted gender-specific body mass index, normal weight (referent), and overweight, ie, upper 15% of the weighted gender-specific body mass index distribution), smoking (never (referent), former, and current smokers), and alcohol consumption (none, moderate–coded as less than three drinks per day (referent), and heavy–coded as three or more drinks per day).

Statistical Analyses
To test our first hypothesis that increasing depressive symptoms would be related to greater risk of dying, Cox proportional hazards models (49) were used to estimate the relative risk of all-cause mortality by self-reported depressive symptoms at baseline. The initial model included covariate adjustments for age, gender, and race. The second model added covariates for education and income, whereas the third model added covariates representing behavioral risk factors (body mass index, smoking, alcohol consumption).

To test our second hypothesis that the association between depressive symptoms and mortality risk would be attenuated by poor health status, we estimated a series of Cox proportional hazards models with covariates for history of hypertension, functional impairment, or life-threatening, chronic conditions at baseline in separate models, including adjustment for age, gender, race, education, and income. A fully adjusted Cox model then was estimated, with simultaneous adjustment for sociodemographics, the three indicators of health status, and behavioral risk factors. Depressive symptoms were modeled continuously and categorically in separate sets of models. We then examined the association between depressive symptoms and all-cause mortality in two subgroups of initially healthy participants: those who had rated their health as good, very good, or excellent at the baseline examination and those who reported no functional impairment at baseline.

All proportional hazards models were conducted in SUDAAN (Research Triangle Institute, Research Triangle Park, NC), which employs Taylor series linearization techniques to adjust the standard errors to account for the sample design complexity. Descriptive statistics were obtained using relevant univariate and frequency procedures in SAS (SAS Institute Inc., Cary, NC). As noted above and detailed elsewhere (44), all analyses were weighted to account for variations in the initial probability of being selected into the ACL sample and differential response rates and to ensure that the sample was nationally representative of the age, gender, and race distribution of the U.S. population age 25 years or older at the time of the baseline exam (ie, 1986).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Depressive Symptoms and All-Cause Mortality Risk
Table 2 presents results from the proportional hazards models testing our first hypothesis. Model 1 shows that for every 1-standard unit increase in CES-D score, the risk of mortality over 7.5 years of follow-up increased by 21% (hazard ratio (HR), 1.21; p = .001), following adjustment for age, gender, and race. Adjustment for education and income (model 2) and behavioral risk factors (model 3) diminished this association somewhat, although it remained significant or marginally significant in both models. Model 3 also shows that significantly greater mortality risk was observed with increasing age, black race, lower income, being underweight, and current smoking, whereas lower mortality risk was noted for females.


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  		TABLE 2. Depressive Symptoms and Risk of All-Cause Mortality: Americans’ Changing Lives Study, 1986 to 1994
 
With CES-D scores modeled categorically, participants with scores in the highest quintile (ie, a score greater than 0.836 SD above the mean) had an 85% greater risk of death due to any cause, relative to participants with the lowest CES-D scores (ie, a score more than 0.893 SD below the mean) and after taking into account the effects of age, gender, and race (HR 1.85; 95% confidence interval (CI), 1.18 to 2.90; p = .008). No other quintiles had increased mortality risk. Data from this model are graphed in Figure 1. Controlling for education and income reduced the HR among the top quintile of CES-D scores to 1.60, which remained significant (p < .05). However, further adjustment for smoking, alcohol consumption and body mass index weakened this association (HR 1.49; 95% CI, 0.92 to 2.42; p = .10).



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  		Figure 1. Categorical CES-D scores and hazards ratios for all-cause mortality, adjusted for age, sex, and race: Americans’ Changing Lives Study, 1986–1994. CES-D categories are approximate quintiles based on the weighted distribution of standardized CES-D scores (mean=0.00, SD=1.0); lowest quintile (referent): –1.18 to –0.894; 2nd quintile: –0.893 to –0.521; 3rd quintile: –0.520 to +0.009; 4th quintile: +0.010 to +0.836; highest quintile: +0.8361 to +4.47. **p = 0.008.

 
Depressive Symptoms, Mortality, and the Impact of Health Status
Table 3 presents the models that assessed whether poor health status attenuated the relationship between depressive symptoms and mortality. With adjustment for self-reported hypertension (model 1), depressive symptoms remain significantly associated with greater risk of all-cause mortality (p = .02). History of hypertension was not related to mortality. Adjustment for functional impairment at wave 1 effectively eliminated the association between depressive symptoms and all-cause mortality (model 2). The association between functional impairment and mortality was graded; participants who reported severe impairment at wave 1 had 2.52-fold greater risk of mortality (p = .001) than those with no impairment. Life-threatening, chronic conditions also attenuated the relationship between depressive symptoms and mortality (model 3) and made it nonsignificant. In a fully adjusted model that included all three indicators of health status, demographics, education, income and behavioral risk factors, there was no excess risk of mortality associated with CES-D score (model 4). This pattern of findings was similar with CES-D scores modeled categorically (data not shown).


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  		TABLE 3. Depressive Symptoms and All-Cause Mortality Risk With Adjustment for Health Status Indicators: Americans’ Changing Lives Study, 1986 to 1994
 
The healthy subgroup analyses showed that depressive symptoms were not significantly related to mortality risk in respondents reporting good to excellent health at baseline (N = 2833, including 306 deaths), with adjustment for age, gender, race, education, income, smoking, body mass index, and alcohol consumption (HR 1.09; 95% CI, 0.87–1.38). Similarly, depressive symptoms did not predict greater mortality in respondents without functional limitations at baseline (N = 2777, with 254 deaths; adjusted HR 1.07; 95% CI, 0.86–1.34).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
ACKNOWLEDGMENTS
 REFERENCES
 
We observed greater all-cause mortality over 7.5 years among participants with more depressive symptoms at baseline in a nationally representative population sample. Traditional sociodemographic factors diminished this association to a modest degree, but participants’ health status–particularly self-reported functional impairment–largely accounted for the excess mortality risk associated with higher CES-D scores. In other words, it appears that participants who were in poorer health at the start of the study also reported the greatest number of depressive symptoms at baseline and subsequently were at greatest risk of dying during the follow-up period. Consistent with this interpretation, we observed that depressive symptoms were unrelated to mortality risk among respondents reporting good to excellent health or no functional impairment at the start of the study.

The literature on mortality associated with depressive symptoms has continued to expand in the short time since the Schulz et al. (20) review was published, with continued mixed findings (50–52). Nevertheless, it is daunting to attempt to reconcile this mixed literature. One of the unique strengths of the present study is the inclusion of a randomly selected, nationally representative sample of adults from age 25 years to old age. To our knowledge, only one published study on the role of depression in mortality also used a nationally representative cohort of U.S. adults. Zheng et al. (6) used data from the National Health Interview Survey and found that self-reported history of major depression was associated with increased mortality over 2.5 years among men but not women. In that study, health status was not controlled, and analyses were limited to whites as too few deaths occurred among black respondents during the follow-up. Some of the variability in findings reported in the literature may be attributable to the more selected populations that have been studied. Consistent with this is the fact that evidence for an association between depression and mortality is strongest among both cardiac and psychiatric patient populations. Thus, depressive symptoms may not predict premature mortality in otherwise healthy, nonpatient populations.

In our study, a history of hypertension had no impact on the association between depressive symptoms and mortality. Hypertension frequently occurs with no or few physical symptoms and often is effectively managed with medications or lifestyle changes; consequently, people with hypertension may very well feel "healthy" and not experience low mood as a result of their disorder. In contrast, conditions that limit mobility, create impairments or are chronic and symptomatic are more likely to dampen one’s spirits and contribute to depressive symptoms. Thus, it is not surprising that these latter conditions attenuated the relation between depressive symptoms and mortality. Nevertheless, it should be noted that our measures of depressive symptoms and self-reported functional impairment do appear to assess relatively distinct constructs. We observed a small, though significant, association between the two measures (r = –0.22, p < .0001), which indicates that the shared variance between CES-D scores and functional impairment at baseline was less than 5%.

Studies of both community and patient populations demonstrate that poor health contributes to depression. Among initially healthy, nondepressed persons from a community sample, those who went on to develop a physical disability or suffer from chronic health problems were two to four times more likely to report increased depressive symptoms over time than their counterparts who remained healthy (14). Poor physical function also is related to greater depressive symptoms and increases in symptoms with time (22,53). Among patient populations, it is well recognized that mood disturbances and depressive symptoms are often a consequence of chronic or life-threatening illnesses (54).

On the other hand, depression clearly does affect some health outcomes. Depressive symptoms were associated with worsening physical impairment over time in our sample (data not shown) after controlling for demographic characteristics, socioeconomic status, and baseline levels of physical impairment. In older populations, depression has been associated with greater physical disabilities (55), chronic pain and arthritis (56), and poorer quality of life (57). Taken together, available evidence supports a bidirectional relationship between depressive symptomatology and ill health.

We assessed depressive symptoms with a frequently used questionnaire measure of depression. The CES-D has been used widely in epidemiological studies and is useful in identifying symptoms of depression that are commonly experienced. However, it does not measure clinical depression. It has been suggested that mortality and cardiovascular or other health risks are related to clinical depression (ie, Major Depressive Disorder), rather than subsyndromal depressive symptoms. There is some support for this notion (16,38,58); however, numerous studies have used a checklist-type measure of depressive symptoms and shown increasing morbidity with increasing symptoms (3,59,60). This suggests that there is not a "clinical threshold" that needs to be surpassed before risk increases. We found a linear association between depressive symptoms and mortality risk before controlling for health status and saw an essentially graded association with mortality risk when depressive symptoms were modeled categorically (Figure 1). Other studies have found that specific symptoms of depression, such as hopelessness, are independently related to mortality and cardiovascular morbidity (61–63). It is possible that general depressive symptomatology does not confer greater health risks but that specific components of depression have a "toxic" effect on health. We did not look at individual CES-D items in relation to mortality risk in the present study, and the 11-item CES-D used here does not include a specific item on hopelessness. We did, however, examine three factor analytically derived subscales of the CES-D (negative affect, somatic symptoms, and interpersonal rejection) in relation to mortality risk (data not shown). After taking into consideration the effects of age, gender, race, education, and income, negative affect was weakly associated (p < .07) and somatic symptoms were significantly associated with greater mortality risk (p < .0001). As with the full CES-D scale, these associations were eliminated after controlling for self-rated functional impairment (p > .40). Curiously, interpersonal rejection was unrelated to mortality risk in a model adjusted for demographic characteristics (p = .14) but protective in the model that further adjusted for functional impairment (p < .04). This latter finding is perplexing and likely due to chance, pending verification by others. Additional research should further explore whether a single depressive symptom or cluster of symptoms deleteriously impact health whereas other symptoms are more benign.

Depressive symptoms may increase specific health risks but not adversely affect general health status or mortality. As noted, depression has been related to increased cardiovascular morbidity and mortality (15–17), although not unequivocally (9,11,18). We conducted secondary analyses (data not shown) to examine whether CES-D scores predicted deaths due to cardiovascular and/or cerebrovascular causes and found no association in a model that included age, gender, and race as covariates (HR 0.98; p > .80). Thirty-eight percent of deaths in our sample were attributed to cardiovascular/cerebrovascular causes; however, an additional 9.2% of deaths could not be coded for the exact cause of death. Future studies may wish to examine cardiovascular outcomes in more detail to better understand whether and how depressive symptoms may impact these outcomes and to address inconsistencies in the literature.

This study relied on self-reported measures of health status and other covariates; objective measures potentially could give us better precision in our estimates. Depressed individuals may evaluate their health status more negatively than those who are not depressed, so it is possible that controlling for self-reported health status is overadjustment. We did not observe an association between depressive symptoms and mortality risk among those participants reporting good health at the start of the study. Given the recognized reciprocal association between depressive symptoms and physical health and our inability to truly establish the temporal order of ill health and the experience of depressive symptoms in our population, future studies will require clearer data on the timing or onset of depressive symptoms and health conditions.

This study did not examine the impact of other psychological or social factors in conjunction with depressive symptoms on mortality risk. Future research may benefit from adopting a broader perspective that takes into consideration interrelated psychological and social characteristics (eg, depression and social isolation) that can and do operate simultaneously in individuals’ lives to impact their health and well being.

In sum, these findings from the ACL do not support the hypothesis that depressive symptoms are independently related to greater mortality risk in a population sample. The current literature on the impact of depressive symptoms on mortality in nonclinical populations is decidedly mixed. We believe the present study is an important addition to this literature because our study population is a nationally representative, randomly selected sample, a strength that few other studies have had.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
REFERENCES
 
This study was supported by NIH grants P01AG05561, R01AG09978–01, and R01AG018418 from the National Institute on Aging, and a Health Investigator Award to James S. House (#030987) from the Robert Wood Johnson Foundation.

Received for publication March 19, 2004.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 

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