Psychosomatic Medicine
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Published online before print , 10.1097/PSY.0b013e31803130ae
This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Wilson, R. S.
Right arrow Articles by Bennett, D. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Wilson, R. S.
Right arrow Articles by Bennett, D. A.
Psychosomatic Medicine 69:131-137 (2007)
© 2007 American Psychosomatic Society

ORIGINAL ARTICLES

Terminal Cognitive Decline: Accelerated Loss of Cognition in the Last Years of Life

Robert S. Wilson, PhD, Todd L. Beck, MS, Julia L. Bienias, ScD and David A. Bennett, MD

From the Rush Alzheimer’s Disease Center (R.S.W., D.A.B.) and Rush Institute for Healthy Aging (T.L.B., J.L.B.) and the Departments of Neurological Sciences (R.S.W., D.A.B.), Behavioral Sciences (R.S.W.), and Internal Medicine (J.L.B.), Rush University Medical Center, Chicago, IL.

Address correspondence and reprint requests to Robert S. Wilson, Rush Alzheimer’s Disease Center, Rush University Medical Center, Suite 1038, Chicago, IL 60612. E-mail: rwilson{at}rush.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Objective: To test the hypothesis that rate of cognitive decline accelerates in the last years of life.

Methods: Participants are 853 older persons without dementia at study onset. For up to 8 years, they underwent annual clinical evaluations that included a battery of 19 cognitive tests from which previously established composite measures of global cognition and specific cognitive domains were derived. In analyses, we used linear mixed-effects models that allowed rate of cognitive decline to change at a given point before death to estimate the onset of a terminal decline period and rate of cognitive decline before and after that point. In subsequent analyses, we tested potential modifiers of terminal decline.

Results: There were 115 deaths. Those who died did not differ from survivors in their level of global cognitive function at study onset, but beginning a mean of 42 months before death, their rate of global cognitive decline sharply increased. The duration and rapidity of terminal decline in global cognition differed from person to person. Terminal cognitive decline was not modified by age, sex, education, or the presence of mild cognitive impairment, but it was not present in those with vascular disease (e.g., stroke and heart attack) or in those without at least one copy of the apolipoprotein E {varepsilon}4 allele, suggesting that Alzheimer’s disease pathology may contribute to the phenomenon.

Conclusions: In old age, cognitive decline markedly accelerates during the last 3 to 4 years of life, consistent with the terminal decline hypothesis.

Key Words: mortality • longitudinal studies • cognitive function • terminal decline • apolipoprotein E

Abbreviations: SD = standard deviation; SE = standard error.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
A longstanding question in cognitive aging research is whether cognitive function precipitiously declines at some point before death. The hypothesis was proposed more than 40 years ago by Kleemeier, who suggested that factors related to death may cause cognitive decline beginning several years before death (1). Kleemeier could not be more specific because his hypothesis was based on longitudinal observations of only 13 people of whom only four died. Although many longitudinal studies have subsequently tried to identify terminal cognitive decline, the results have been mixed, with a recent review questioning the existence of the concept (2). The main problem is that these studies were not designed to investigate terminal decline and lack, in varying degrees, the ingredients needed to test it: multiple closely spaced assessments of cognition (to capture nonlinear change) over a several year period in a group of older persons of varying cognitive ability with some deaths during the observation period. One previous study meeting these criteria found evidence of a sharp acceleration in global cognitive decline beginning in the last 3 to 4 years of life (3). Participants were highly educated Catholic clergy members; however, the generalizability of the results remains to be demonstrated.

In the present study, we investigated the terminal decline hypothesis with data from the Rush Memory and Aging Project, a longitudinal clinical-pathologic study of risk factors for common chronic conditions of old age. Community dwelling older persons without dementia at baseline had annual cognitive function testing for up to 8 years. We constructed a series of linear mixed-effects models to test if cognitive decline tended to accelerate at some point before death and to examine factors that might modify terminal cognitive decline.


   METHODS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 
Participants
Subjects are from the Rush Memory and Aging Project, a longitudinal clinical-pathologic study of risk factors for common chronic conditions of old age (4). The study began in 1997, expanded in 2001, and is continuing. The subjects were recruited from continuous care retirement communities, subsidized senior housing, local churches, and social service agencies in the Chicago area. At each site, a presentation about the project stressed the public health burden posed by late life dementia and the need for clinical-pathologic research to better understand its neurobiologic bases and help reduce the burden for future generations. After the presentation, persons expressed their level of interest in participation. Interested persons were later contacted by project staff, who explained the study in detail, answered questions, and obtained informed consent. The study was approved by the Institutional Review Board of Rush University Medical Center.

At enrollment, each participant completed a uniform clinical evaluation that was repeated annually thereafter. The evaluation included a medical history, complete neurological examination, and detailed testing of cognitive function. On the basis of this evaluation and an in-person examination of the participant, an experienced clinician diagnosed dementia using the criteria of the joint working group of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (5), which require a history of cognitive decline and impairment in at least two cognitive domains (6).

At the time of these analyses, 1068 people had completed the baseline clinical evaluation. We excluded 48 people who met the dementia criteria at baseline. Of the remaining 1020 individuals, 26 died before the first annual follow-up evaluation and 85 had been enrolled for <1 year. This left 909 people eligible for follow-up, and 853 (93.8%) completed at least one follow-up evaluation (range, 2–9 completed evaluations per individual). Analyses are based on this group. They had a mean age at baseline of 80.4 years (SD = 6.8), a mean of 14.5 years of schooling (SD = 3.0), and a mean baseline score of 27.9 (SD = 2.1) on the Mini-Mental State Examination; 74.4% were women, 91.6% were white and non-Hispanic, and 27.6% had mild cognitive impairment, defined as having impaired cognition on testing but not meeting the criteria for dementia, as applied in this (7) and other (8) cohorts.

Assessment of Cognitive Function
A set of 21 cognitive tests was administered at each annual evaluation in an approximately 1-hour session. The Mini-Mental State Examination was used only to describe the cohort and another test, Complex Ideational Material, was used only in clinical classification. Analyses are based on the remaining 19 tests, which included seven measures of episodic memory: Word List Memory, Word List Recall, and Word List Recognition (9) and immediate and delayed recall of the East Boston Story (10,11) and of Story A from Logical Memory of the Wechsler Memory Scale-Revised (12). Semantic memory was assessed with a 15-item form (9) of the Boston Naming Test (13), Verbal Fluency (9), and a 15-item version of the National Adult Reading Test (14). Working memory was evaluated with Digit Span Forward and Digit Span Backward from the Wechsler Memory Scale-Revised (12) and Digit Ordering (15). There were four measures of perceptual speed: the oral version of the Symbol Digit Modalities Test (16), Number Comparison (17), and two indices from a modified Stroop Neuropsychological Screening Test (18): the number of color names correctly read minus the names incorrectly read in a 30-second trial and the number of colors correctly named minus the colors incorrectly named in a 30-second trial. Two measures of visuospatial ability were administered: a 15-item form of Judgment of Line Orientation (19) and a 16-item form of Standard Progressive Matrices (20).

To minimize floor and ceiling artifacts and other sources of measurement error, we used a composite measure of global cognition based on all 19 tests as the primary outcome. Raw scores on each test were converted to z scores, using the baseline mean and standard deviation for the entire cohort, and averaged to yield the composite score. In secondary analyses, we used similarly constructed composite measures of episodic memory (n = 7 tests), semantic memory (n = 3 tests), perceptual speed (n = 4 tests), and visuospatial ability (n = 2 tests), based in part on previous factor analyses of the tests at baseline. Further information on the individual tests and the derivation and computation of the composite measures are contained in previous publications (21–23).

Assessment of Other Variables
Disability was assessed at baseline with the Katz scale (24). Persons indicated whether they needed assistance with each of six basic activities of daily living (e.g., dressing, toileting). The number of activities requiring assistance was used in the analyses (3).

We constructed two previously established (25) composite measures of vascular burden from the baseline medical history and clinical evaluation. Vascular risk factors included the number of three factors present (i.e., hypertension, diabetes, smoking) and vascular conditions included the number of four conditions present (i.e., heart attack, congestive heart failure, stroke, claudication).

Apolipoprotein E genotyping was done (Agencourt Bioscience Corporation, Beverly, MA) using high-throughput sequencing of codon 112 (position 3937) and codon 158 (position 4075) of exon 4 of the apolipoprotein E gene on chromosome 19. For analyses, persons were divided into those with versus without at least one copy of the {varepsilon}4 allele.

Ascertainment of Vital Status
Because all participants in the Rush Memory and Aging Project agreed to brain autopsy at the time of their death, the study has numerous procedures designed to ensure that the coordinator is promptly informed of deaths. If the coordinator were not notified at the time of death, the information is obtained from regular telephone contacts which precede the annual clinical evaluations. We also check internet geneology sites such as rootsweb (available at http://www.rootsweb.com/) to determine vital status for the few persons lost to follow-up. As a result, information on vital status was available for all persons in the study.

Data Analysis
To test if cognitive decline accelerated during some period before death, we constructed a series of linear mixed-effects regression models (26). Initial analyses were conducted on the measure of global cognition. Each model allowed the rate of change in cognitive function to shift (27) in the last n days before death and yielded estimated rates of cognitive decline before and after this change point. We tested models with n ranging from 180 to 2220 days in 30-day intervals. All models were adjusted for age, sex, and education and included an indicator for whether or not the person died. They also included a term for time squared to capture curvilinear cognitive decline. From these analyses, we selected the model with the highest log likelihood value (indicating best model fit). The terms for time and time squared capture the primary cognitive decline over the entire period. The term for death indicates the association of mortality with baseline level of cognition. The term for "terminal shift for time" is the shift in the linear component of cognitive decline during the terminal period. Because preliminary analyses did not show the need for a terminal shift for time squared, this term was not included in the final models.

To test if sex, education, or age modified terminal decline, in separate analyses we added a term for the interaction of the demographic variable by death by time. For analyses of each remaining covariate, we added terms for the covariate, its interaction with time, and the interaction of the covariate by death by time. To test if terminal decline varied in different cognitive domains, we repeated the original analyses with specific cognitive function measures. Programming was done in the SAS Institute Inc. (Cary, NC) (28).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
DISCUSSION
 NOTES
 REFERENCES
 
During up to 8 years of observation, 115 deaths occurred. At the time of the baseline evaluation, those who died were older and more apt to be men than survivors were, and they had a lower level of cognitive function (Table 1).


View this table:
[in this window]
[in a new window]

  		TABLE 1. Baseline Information on Participants Who Survived and Those Who Died

 

Terminal Decline in Cognitive Function
To capitalize on all available cognitive data, we used the composite measure of global cognition as the primary outcome. At baseline, scores ranged from –1.82 to 1.40 (mean = 0.11, SD = 0.53), with higher scores indicating better function. During the study, the surviving participants completed a mean of 3.7 annual evaluations (range 2–9), and those who died completed a mean of 4.0 (range 2–9).

To assess the association of change in global cognition with impending death, we fit a series of mixed-effects models that allowed the rate of cognitive decline to change at points ranging from 6 to 60 months before death. All analyses controlled for the potentially confounding effects of age, sex, and education. From each model, we plotted the log-likelihood value, a goodness of fit statistic, as a function of the number of months before death used as a change point. As shown in Figure 1 (upper left panel), the best fitting model (as indicated by the highest log-likelihood value) had a change point occurring 42 months before death. In this model (Table 2), there was a gradually accelerating rate of global cognitive decline for those not within 42 months of death, as shown by the term for time squared. Those who died did not differ from survivors in their level of cognition at baseline, as shown by the term for death, but their rate of linear cognitive decline increased by 0.054 unit per year in the last 42 months of life, as shown by the terminal shift for time term.


Figure 13
View larger version (12K):
[in this window]
[in a new window]

  		Figure 1. Log-likelihood, an indicator of goodness of fit, from a series of analyses allowing terminal decline to begin at different points before death in global cognition (upper left), episodic memory (upper right), semantic memory (middle left), working memory (middle right), perceptual speed (lower left), and visuospatial ability (lower right).

 

View this table:
[in this window]
[in a new window]

  		TABLE 2. Change in Global Cognition Allowing for an Accelerated Rate of Change in the Last 42 Months of Life

 

To visually examine this effect, we plotted the predicted 5-year paths of change in global cognition for a person who died at the 5-year point and for a person who survived (Figure 2). The paths are initially indistinguishable and then begin to diverge after the person who died (dotted line) reaches the terminal period.


Figure 23
View larger version (5K):
[in this window]
[in a new window]

  		Figure 2. Predicted 5-year paths of change for two typical participants, one who survived (solid line) and one who died after 5 years (dotted line).

 

To assess individual differences in terminal cognitive decline, we plotted the estimated paths of change in global cognition as a function of age for each person who died (Figure 3, upper panel) and an equal number of persons randomly selected from survivors (Figure 3, lower panel). Substantial heterogeneity is evident among those who died, with rapid decline in a large subgroup but more gradual decline or relatively stable cognition in many others. Nonetheless, substantially more cognitive decline is seen in the deceased subgroup compared with survivors.


Figure 33
View larger version (16K):
[in this window]
[in a new window]

  		Figure 3. Predicted paths of global cognitive decline in those who died (upper panel) and an equal number of persons randomly selected from survivors (lower panel).

 

Modification of Terminal Decline
We next considered factors that might modify terminal decline. Given sex differences in mortality, we began by adding a term for the interaction of sex with the terminal shift term. No interaction was observed (estimate = 0.021, SE = 0.030, p = .48). In subsequent analyses, there was no indication that terminal decline varied by education (estimate = –0.001, SE = 0.004, p = .84) or age (estimate = –0.005, SE = 0.003, p = .11).

Mild cognitive impairment has been associated with increased risk of death and more rapid cognitive decline (7,8). We found no evidence, however, that mild cognitive impairment (present in 27.6%) modified the terminal decline effect (estimate = –0.004, SE = 0.028, p = .90).

To see if health-related factors affected terminal decline, we constructed an additional model that tested for interactions of three variables with terminal decline: disability on the Katz scale, a composite measure of vascular risk factors, and a composite measure of vascular conditions. There was no modifying effect of disability (estimate = 0.005, SE =0.021, p = .82) or vascular risk factors (estimate = –0.030, SE = 0.019, p = .11). There was a modifying effect of vascular disease (estimate = 0.058, SE = 0.024, p = .01) such that the terminal decline effect was absent in the presence of vascular disease.

Apolipoprotein E genotype was available in 646 participants. To test if genotype was related to terminal decline, we divided participants into 154 (23.0.8%) with ({varepsilon}2/4 = 17, {varepsilon}3/4 = 130, {varepsilon}4/4 = 7) and 492 without ({varepsilon}2/2 = 6, {varepsilon}2/3 = 102, {varepsilon}3/3 = 384) an {varepsilon}4 allele and constructed a model with terms for {varepsilon}4 and its interactions with time and the terminal shift term. In this analysis, {varepsilon}4 was not related to baseline level of cognition (estimate = –0.060, SE = 0.043, p = .16) or rate of cognitive decline outside of the terminal period (estimate = –0.015, SE = 0.013, p = .25). However, decline during the terminal period was sharply enhanced in those with an {varepsilon}4 allele (estimate = –0.210, SE = 0.033, p < .001) and not accelerated in those without one, as shown in Figure 4, which is based on this analysis.


Figure 43
View larger version (6K):
[in this window]
[in a new window]

  		Figure 4. Predicted 5-year paths of change in global cognition for two typical participants who died after 5 years, one with (dotted line) and one without (solid line) an apolipoprotein E {varepsilon}4 allele.

 

Terminal Decline in Specific Cognitive Domains
We conducted identical analyses using composite measures of specific cognitive domains in place of the global cognitive measure. As shown in Figure 1 (upper right panel), there was a clear change point in episodic memory about 40 months before death resembling that seen in global cognition. Results for the other domains (Figure 1, middle and lower panels) were less straightforward, however, with no clear change point in perceptual speed and possibly shorter terminal periods in the other three domains.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
NOTES
 REFERENCES
 
In a cohort of >800 older persons without dementia at study onset, >100 persons died during up to 8 years of observation. Those who died began the study with about the same level of cognition as survivors, but they experienced a marked increase in cognitive decline beginning about 3.5 years before death. The results suggest that cognitive decline in old age sharply accelerates in the last few years of life, consistent with the terminal decline hypothesis.

The hypothesis that cognition undergoes accelerated decline before death has been controversial. The present results provide strong support for the hypothesis and are remarkably similar to the findings from a study of older Catholic clergy members, which involved annual administration of a similar battery of cognitive tests for several years before their death (3). In each study, the rate of global cognitive decline increased markedly in the final 3.5 years of life, not only supporting Kleemeier’s hypothesis but also providing a timeline for the effect (1). By contrast, the results of other longitudinal research have been inconsistent, with an association between impending death and cognitive decline in some studies (29–32) but there has been mixed (33–38) or no (39–43) evidence of the association in others. These inconsistencies likely reflect several factors. In particular, testing the hypothesis requires multiple observations in the years before death, but most previous research on terminal cognitive decline has been based on ≤3 observations per individual (29–31,33–36,38–43) and a study period of ≤3 years (29,34,39–41). Also, many previous studies of terminal cognitive decline have had low (30,38) or indeterminate (1,33,34,39,42) rates of participation in follow-up evaluations, possibly attenuating the association between cognition and death due to the association of attrition with cognitive decline and mortality (44). In addition, many studies ascertain mortality after ending cognitive testing so that cognitive data are not sufficiently proximal to death. Other problems include intertest intervals of ≥5 years (33,43) and cohorts with relatively few participants (1,37,39,41,42) or deaths (28).

The basis of terminal decline in cognitive function is unknown, but the present data provide some clues. We observed much heterogeneity in terminal decline, with little change in some and mild to precipitous decline in others. This variability implies that terminal decline is not some inevitable or uniform developmental process preceding death, suggesting that person-specific factors are contributing. We examined several potential modifiers of terminal decline. It did not vary by age, sex, or education, but it was strongly related to possession of an apolipoprotein E {varepsilon}4 allele. Because the association of {varepsilon}4 with dementia appears to be largely mediated by Alzheimer’s disease pathology (45), particularly amyloid-ß plaques (46), this finding implies that Alzheimer’s disease pathology contributes to terminal decline in cognitive function. The heterogeneity in terminal decline is consistent with this hypothesis, and the natural history of Alzheimer’s disease (47,48) is similar to the temporal course of terminal decline. Mild cognitive impairment, which often represents early Alzheimer’s disease, was not related to terminal cognitive decline, but this may have been because analyses already controlled for the level of cognition at baseline. Clinical-pathologic data on a large number of older persons will likely be needed to establish the role of Alzheimer’s disease pathology in terminal cognitive decline.

Terminal decline was not modified by disability status, but it was substantially diminished in the presence of vascular disease. Although vascular disease can be chronic, it can abruptly impair cognition and acutely cause death, perhaps thereby providing an exception to the more typical pattern of accelerating cognitive decline for several years before death.

Another question about terminal decline is whether it affects some forms of cognition more than others. Although selective effects have been reported (32,33), no particular domain is consistently spared (49), and some studies (3,50), like this one, have observed clear global effects. In the present study, there was evidence of terminal decline in a composite measure of episodic memory during the last 3 to 4 years of life. Evidence in other cognitive domains was less straightforward, however, with no clear effect in some domains and a suggestion of shorter terminal decline periods in others. The differential effects may reflect the stronger psychometric properties of the episodic memory measure, based on seven individual tests, compared with other composite measures that are based on two to four individual tests. Alternatively, episodic memory impairment is a hallmark of Alzheimer’s disease (5) and of the {varepsilon}4 allele (51), consistent with terminal cognitive decline being a manifestation of Alzheimer’s disease pathology. In the religious orders study with very similar cognitive measures, neither the magnitude nor the temporal course of terminal decline strongly varied across domains, possibly due to the longer observation period compared with the present study or to the socioeconomic homogeneity among the Catholic clergy members in the religious orders study providing additional control of the potentially confounding influence of socioeconomic status.

Confidence in these findings is strengthened by several factors. Persons with dementia at study onset were eliminated based on a uniform evaluation and application of widely accepted criteria by an experienced clinician. Cognition was assessed with previously established composite measures. Participation in follow-up evaluations by survivors exceeded 90%. Use of mixed-effects models with a change point allowed us not only to test for terminal decline but also to characterize its temporal course and examine potential modifiers.

The principal limitation of the study is that participants are selected. Research on terminal cognitive decline in defined populations is needed. In addition, a longer period of observation would likely have improved our ability to identify factors associated with terminal decline and characterize variation across cognitive domains. Finally, assuming a 4% annual mortality rate, >10% of survivors are likely to die in the next 3.5 years. Because it is likely that this subgroup disproportionately contributes to decline among survivors, the current results probably underestimate the size of the terminal decline effect.

In summary, the results suggest that a substantial proportion of old people experience accelerated cognitive decline in the last few years of life, consistent with the terminal decline hypothesis. Because of the heterogeneity in terminal decline, its association with the apolipoprotein E {varepsilon}4 allele, and other observations, we hypothesize that the effect is partly a manifestation of Alzheimer’s disease pathology and perhaps other lesions associated with progressive cognitive decline (i.e., Lewy bodies) and so a common but not inevitable feature of the last years of life. These data underscore the malignant nature of cognitive decline in old age and the importance of identifying means to delay its onset and slow its progression.

We thank the many Illinois residents for participating in the Rush Memory and Aging Project; Traci Colvin, MPH, and Tracy Hagman for coordinating the study; George Dombrowski, MS, and Greg Klein for data management; and Valerie J. Young for preparing the manuscript.


   NOTES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
REFERENCES
 
This research was supported by National Institute on Aging grant R01 AG17917 and the Illinois Department of Public Health.

Received for publication May 12, 2006; revision received October 23, 2006.

DOI:10.1097/PSY.0b013e31803130ae


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 METHODS
 RESULTS
 DISCUSSION
 NOTES
 REFERENCES
 

  1. Kleemeier RW. Intellectual change in the senium. In: Proceedings of the social statistics section of the American statistical association. Washington, DC: American Statistical Association; 1962.
  2. Bosworth HB, Siegler IC. Terminal change in cognitive function: an updated review of longitudinal studies. Exp Aging Res 2002;28:299–315.[CrossRef][Medline]
  3. Wilson RS, Beckett LA, Bienias JL, Evans DA, Bennett DA. Terminal decline in cognitive function. Neurology 2003;60:1782–7.[Abstract/Free Full Text]
  4. Bennett DA, Schneider JA, Buchman AS, Mendes de Leon CF, Bienias JL, Wilson RS. The Rush memory and aging project: study design and baseline characteristics of the study cohort. Neuroepidemiology 2005;25:169–75.[CrossRef]
  5. McKhann G, Drachmann D, Folstein M, Katzman R, Price D, Stadlan E. Clinical diagnosis of Alzheimer's disease. Report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology 1984;34:939–44.[Abstract/Free Full Text]
  6. Wilson RS, Krueger KR, Arnold SE, Schneider JA, Kelly JF, Barnes LL, Tang Y, Bennett DA. Loneliness and risk of Alzheimer's disease. Arch Gen Psychiatry. In press.
  7. Boyle PA, Wilson RS, Aggarwal NT, Tang Y, Bennett DA. Mild cognitive impairment: risk of Alzheimer's disease and rate of cognitive decline. Neurology 2006;67:441–5.[Abstract/Free Full Text]
  8. Bennett DA, Wilson RS, Schneider JA, Evans DA, Beckett LA, Aggarwal NT, Barnes LL, Fox JH, Bach J. Natural history of mild cognitive impairment in older persons. Neurology 2002;59:198–205.[Abstract/Free Full Text]
  9. Welsh KA, Butters N, Mohs RC, Beekly D, Edland S, Fillenbaum G, Heyman A. The consortium to establish a registry for Alzheimer's disease (CERAD). part V. a normative study of the neuropsychological battery. Neurology 1994;44:609–14.[Abstract/Free Full Text]
  10. Albert MS, Smith L, Scherr P, Taylor J, Evans DA, Funkenstein H. Use of brief cognitive tests to identify individuals in the community with clinically diagnosed Alzheimer's disease. Int J Neurosci 1991;57:167–78.[Medline]
  11. Wilson RS, Beckett LA, Barnes LL, Schneider JA, Bach J, Evans DA, Bennett DA. Individual differences in rates of change in cognitive abilities of older persons. Psychol Aging 2002;17:179–93.[CrossRef][Medline]
  12. Wechsler D. Wechsler memory scale-revised manual. San Antonio, TX: Psychological Corp.; 1987.
  13. Kaplan EF, Goodglass H, Weintraub S. The Boston naming test, 2nd Ed. Philadelphia: Lea & Febiger; 1983.
  14. Nelson HE. National adult reading test (NART) test manual. Windsor Berkshire, UK: NFER-Nelson Publishing Company; 1982.
  15. Cooper JA, Sager HJ, Jordan N, Harvey NS, Sullivan EV. Cognitive impairment in early, untreated Parkinson's disease and its relationship to motor disability. Brain 1991;114:2095–122.[Abstract/Free Full Text]
  16. Smith A. Symbol digit modalities test manual-revised. Los Angeles: Western Psychological Services; 1982.
  17. Ekstrom RB, French JW, Harman HH, Kermen D. Manual for kit of factor-referenced cognitive tests. Princeton, NJ: Educational Testing Service; 1976.
  18. Trenerry MR, Crosson B, DeBae J, Leber WR. The Stroop neuropsychological screening test. Odessa, FL: Psychological Assessment Resources; 1989.
  19. Benton AL, Sivan AB, Hamsher K, Varney NR, Spreen O. Contributions to neuropsychological assessment. 2nd ed. New York: Oxford University Press; 1994.
  20. Raven JC, Court JH, Raven J. Manual for Raven's progressive matrices and vocabulary scales. Oxford: Oxford University Press; 1992.
  21. Wilson RS, Arnold SE, Tang Y, Bennett DA. Odor identification and decline in different cognitive systems in old age. Neuroepidemiology 2006;26:61–7.[CrossRef][Medline]
  22. Wilson RS, Barnes LL, Bennett DA. Assessment of lifetime participation in cognitively stimulating activities. J Clin Exp Neuropsychol 2003;25:634–42.[Medline]
  23. Wilson RS, Barnes LL, Krueger KR, Hoganson G, Bienias JL, Bennett DA. Early and late life cognitive activity and cognitive systems in old age. J Int Neuropsychol Soc 2005;11:400–7.[Medline]
  24. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. JAMA 1963;185:914–23.[Abstract/Free Full Text]
  25. Boyle PA, Wilson RS, Aggarwal NT, Arvanitakis Z, Kelly JF, Bienias JL, Bennett DA. Parkinsonian signs in subjects with mild cognitive impairment. Neurology 2005;65:1901–6.[Abstract/Free Full Text]
  26. Laird N, Ware J. Random-effects models for longitudinal data. Biometrics 1982;38:963–74.[CrossRef][Medline]
  27. Hall CB, Lipton RB, Sliwinski M, Stewart WF. A change point model for estimating the onset of cognitive decline in preclinical Alzheimer's disease. Stat Med 2000;19:1555–66.[CrossRef][Medline]
  28. SAS Institute Inc. SAS/STAT User's Guide, Version 8. Cary, NC: SAS Institute Inc; 2000.
  29. Bassuk SS, Wypij D, Berkman LF. Cognitive impairment and mortality in the community-dwelling elderly. Am J Epidemiol 2000;151:676–88.[Abstract/Free Full Text]
  30. Deeg DJH, Hofman A, van Zonneveld RJ. The association between change in cognitive function and longevity in Dutch elderly. Am J Epidemiol 1990;132:973–82.[Abstract/Free Full Text]
  31. Johansson B, Berg S. The robustness of the terminal decline phenomenon: longitudinal data from the digit-span memory test. J Gerontol 1989;44:P184–6.[Abstract]
  32. Johansson B, Hafer SM, Allaire JC, Maldonado-Molina MM, Piccinin AM, Berg S, Pedersen NC, McClearn GE. Change in cognitive capabilities in the oldest old: the effects of proximity to death in genetically related individuals over a 6-year period. Psychol Aging 2004;19:145–56.[CrossRef][Medline]
  33. Bosworth HB, Schaie KW, Willis SL. Cognitive and sociodemographic risk factors for mortality in the Seattle Longitudinal Study. J Gerontol 1999;54B:P273–82.
  34. Anstey KJ, Luszcz MA, Giles LC, Andrews GR. Demographic, health, cognitive, and sensory variables as predictors of mortality in very old adults. Psychol Aging 2001;16:3–11.[CrossRef][Medline]
  35. Colsher P, Wallace R. Longitudinal application of cognitive function measures in a defined population of community-dwelling elders. Ann Epidemiol 1991;1:215–30.[Medline]
  36. Hassing LB, Johansson B, Berg S, Nilsson SE, Pedersen NL, Hofer SM, McClearn G. Terminal decline and markers of cerebro- and cardiovascular disease: findings from a longitudinal study of the oldest old. J Gerontol 2002;57B:P268–76.
  37. Palmore E, Cleveland W. Aging, terminal decline, and terminal drop. J Gerontol 1976;31:76–81.[Abstract/Free Full Text]
  38. Riegel KF, Riegel RM. Development, drop, and death. Dev Psychol 1976;6:306–19.[CrossRef]
  39. Botwinick J, West R, Storandt M. Predicting death from behavioral test performance. J Gerontol 1978;33:755–66.[Abstract/Free Full Text]
  40. Bruce ML, Hoff RA, Jacobs SC, Leaf PJ. The effects of cognitive impairment on 9-year mortality in a community sample. J Gerontol 1995;50B:P289–96.
  41. Hassing LB, Small BJ, von Strauss E, Fratiglioni L, Backman L. Mortality-related differences and change in episodic memory among the oldest old: evidence from a population based sample of nonagenarians. Aging Neuropsychology and Cognition 2002;9:11–20.
  42. Steuer J, LaRue A, Blum JE, Jarvik LF. Critical loss in the eighth and ninth decades. J Gerontol 1981;36:211–3.[Abstract]
  43. Lovden M, Bergman L, Adolfsson R, Lindenberger U, Nilsson L-G. Studying individual aging in an interindividual context: typical paths of age-related, dementia-related, and mortality-related cognitive development in old age. Psychol Aging 2005;20:303–16.[CrossRef][Medline]
  44. Sliwinski MJ, Hofer SM, Hall C, Buschke H, Lipton RB. Modeling memory decline in older adults: the importance of preclinical dementia, attrition, and chronological age. Psychol Aging 2003;18:658–71.[CrossRef][Medline]
  45. Bennett DA, Wilson RS, Schneider JA, Evans DA, Aggarwal NT, Arnold SE, Cochran EJ, Berry-Kravis E, Bienias JL. Apolipoprotein E {varepsilon}4 allele, AD pathology, and the clinical expression of Alzheimer's disease. Neurology 2003;60:246–52.[Abstract/Free Full Text]
  46. Bennett DA, Schneider JA, Wilson RS, Bienias JL, Berry-Kravis E, Arnold SE. Amyloid mediates the association of apolipoprotein E {varepsilon}4 allele to cognitive function in older people. J Neuol Neurosurg Psychiatry 2005;76:1194–9.[CrossRef]
  47. Wolfson C, Wolfson DB, Asgharian M, M'Lan CE, Ostbye T, Rockwood K, Hogan DB, Clinical Progression of Dementia Study Group. A reevaluation of the duration of survival after the onset of dementia. N Engl J Med 2001;344:1111–6.[Abstract/Free Full Text]
  48. Brookmeyer R, Corrada MM, Curriero FC, Kawas C. Survival following a diagnosis of Alzheimer's disease. Arch Neurol 2002;59:1764–7.[Abstract/Free Full Text]
  49. Small BJ, Backman L. Time to death and cognitive performance. Current Directions in Psychological Science 1999;8:168–72.
  50. Small BJ, Fratiglioni L, von Strauss E, Backman L. Terminal decline and cognitive performance in very old age: does cause of death matter? Psychol Aging 2003;18:193–202.[CrossRef][Medline]
  51. Wilson RS, Schneider JA, Barnes LL, Beckett LA, Aggarwal NT, Cochran EJ, Berry-Kravis E, Bach J, Fox JH, Evans DA, Bennett DA. The apolipoprotein E {varepsilon}4 allele and decline in different cognitive systems during a 6-year period. Arch Neurol 2002;59:1154–60.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
 J Gerontol B Psychol Sci Soc SciHome page
E. L. Idler, J. McLaughlin, and S. Kasl
Religion and the Quality of Life in the Last Year of Life
J Gerontol B Psychol Sci Soc Sci, July 1, 2009; 64B(4): 528 - 537.
[Abstract] [Full Text] [PDF]

Home page
 Age AgeingHome page
G. Muniz-Terrera, F. Matthews, T. Dening, F. A. Huppert, C. Brayne, and CC75C Group
Education and trajectories of cognitive decline over 9 years in very old people: methods and risk analysis
Age Ageing, May 1, 2009; 38(3): 277 - 282.
[Abstract] [Full Text] [PDF]

Home page
 NeurologyHome page
R. S. Wilson
Advancing age, impending death, and declining cognition
Neurology, September 16, 2008; 71(12): 874 - 875.
[Full Text] [PDF]

Home page
 Arch Gen PsychiatryHome page
R. S. Wilson, J. A. Schneider, S. E. Arnold, J. L. Bienias, and D. A. Bennett
Conscientiousness and the Incidence of Alzheimer Disease and Mild Cognitive Impairment
Arch Gen Psychiatry, October 1, 2007; 64(10): 1204 - 1212.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrowRequest Permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Wilson, R. S.
Right arrow Articles by Bennett, D. A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Wilson, R. S.
Right arrow Articles by Bennett, D. A.

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS