Influences of Preclinical Dementia and Impending Death on the Magnitude of Age-Related Cognitive Deficits

Transcription

1 Psychology and Aging Copyright 2002 by the American Psychological Association, Inc. 2002, Vol. 17, No. 3, /02/$5.00 DOI: // Influences of Preclinical Dementia and Impending Death on the Magnitude of Age-Related Cognitive Deficits Lars Bäckman Uppsala University, Stockholm Gerontology Research Center, and Karolinska Institute Erika Jonsson Laukka and Åke Wahlin Stockholm Gerontology Research Center and Karolinska Institute Brent J. Small University of South Florida Laura Fratiglioni Stockholm Gerontology Research Center and Karolinska Institute The authors examined the influence of preclinical dementia and impending death on the cross-sectional relationship between age and performance in tasks assessing episodic memory, visuospatial skill, and verbal fluency. Increasing age was associated with a general decrease in cognitive performance. In addition, those who were to be diagnosed with dementia or had died by a 3-year follow-up, were older, and performed at a lower level than the remaining sample across all cognitive tasks at baseline. Nevertheless, removal of the preclinical dementia and impending death groups from the original sample affected the cross-sectional age cognition relations relatively little. This pattern of findings suggests that the biological aging process exerts negative influences on cognitive functioning beyond those resulting from disease and mortality. Lars Bäckman, Department of Psychology, Uppsala University, Uppsala, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden; and NEUROTEC, Division of Geriatric Epidemiology, Karolinska Institute, Stockholm, Sweden. Erika Jonsson Laukka, Åke Wahlin, and Laura Fratiglioni, Stockholm Gerontology Research Center, and NEUROTEC, Division of Geriatric Epidemiology, Karolinska Institute. Brent J. Small, Department of Gerontology, University of South Florida. This research was supported by grants from the Swedish Council for Research in the Humanities and the Social Sciences, the Swedish Council for Social Research, and the Swedish Medical Research Council. Correspondence concerning this article should be addressed to Lars Bäckman, Stockholm Gerontology Research Center, Box 6401, S Stockholm, Sweden. lars.backman@neurotec.ki.se Although many cognitive functions (e.g., episodic memory, speed of processing, visuospatial skill, verbal fluency) decline across the adult life span, there is considerable variability among normal elderly persons with regard to the size of the age-related cognitive impairment (e.g., Hultsch, Hertzog, Dixon, & Small, 1998; Luszcz, Bryan, & Kent, 1997). Numerous studies indicate that individual differences within demographic (e.g., sex, education), life-style (e.g., activity patterns, substance use), and healthrelated (e.g., vascular factors, vitamin status) domains influence the magnitude of cognitive deficits in old age (for an overview, see Bäckman, Small, Wahlin, & Larsson, 1999). However, perhaps the most powerful individual-difference variable in cognitive aging is dementia. Dementing disorders, such as Alzheimer s disease (AD) and vascular dementia (VaD), have profound effects on cognitive functioning already early on in the pathogenesis (Morris, 1996; Nebes, 1992). In research on normal cognitive aging, clinically demented individuals are not likely to be included because of the screening procedures adopted. However, recent research has demonstrated that there is a long preclinical period in AD during which cognitive deficits are detectable (e.g., Elias et al., 2000; Small, Fratiglioni, Viitanen, Winblad, & Bäckman, 2000). Because the incidence of dementia increases dramatically in late life (e.g., Andersen et al., 1999; Ott, Breteler, van Harskamp, Stijnen, & Hofman, 1998; for an overview, see Fratiglioni et al., 2000), the number of preclinical cases will also increase with advancing age. As a result, there is an age-related increase in the potential for dementia-related impairments to obscure normative age-related deficits in cognitive performance. In an important article, Sliwinski, Lipton, Buschke, and Stewart (1996) demonstrated how the presence of preclinical dementia cases in the study sample may influence our conclusions regarding normative age-related changes in cognitive functioning. These investigators examined a group of year-old adults across a 4-year retest interval. They reported that the inclusion of preclinical dementia cases underestimated the mean and overestimated the variability of cognitive performance in the original sample. However, the key finding was that eliminating persons who had developed dementia at follow-up reduced the size of the agerelated deficit in fluid intelligence and episodic memory at baseline. Sliwinski et al. (1996) hypothesized that the effects of preclinical dementia on the magnitude of the age cognition relationship may be even larger among very old adults, considering the marked increase of new demented cases in late senescence. A forthcoming dementia disease is not the only future event that may be associated with impaired cognitive performance in old age. The phenomenon of terminal decline constitutes an analogous case in point. Terminal decline refers to the fact that there is a relationship between proximity to death and cognitive performance (Kleemeier, 1962). Numerous studies have revealed evidence for terminal decline in cognitive functioning that may reflect the 435

2 436 BÄCKMAN, LAUKKA, WAHLIN, SMALL, AND FRATIGLIONI occurrence of specific diseases that influence central nervous system functioning (CNS) as well as systemic organ failure (for overviews, see Berg, 1996; Small & Bäckman, 1999). As with preclinical dementia, the fact that the probability of dying increases in late life implies that the magnitude of normal age-related differences in cognitive performance may be overestimated because of the influence of impending death. The chief objective of this study was to provide further knowledge concerning the effects of preclinical dementia and impending death on cross-sectional age differences in late-life cognitive performance. Using data from a population-based study on aging and dementia, we examined a group of 75 old persons at baseline and at a 3-year follow-up. It was of particular interest whether removal of those who were diagnosed with dementia or had died at follow-up would alter the size of the baseline relationship between age and performance in tasks assessing episodic memory, visuospatial skill, and verbal fluency. Information pertaining to this issue should be valuable, given that current empirical generalizations on normal cognitive aging are largely derived from crosssectional studies (e.g., Craik & Salthouse, 1992, 1999). Participants Method The sample was selected from all participants in the Kungsholmen Project, a longitudinal population-based study of very old persons (for a detailed description, see Fratiglioni, Viitanen, Bäckman, Sandman, & Winblad, 1992). In an initial screening phase, all inhabitants born in 1912 or earlier in the Kungsholmen parish of Stockholm, Sweden (2,368 individuals), were invited to participate. A cognitive screening test, the Mini- Mental State Examination (MMSE; Folstein, Folstein, & McHugh, 1975), was administered to 1,810 individuals to detect cases with suspected dementia. All participants who scored 23 or below out of a maximum of 30 on the MMSE were considered to have suspected dementia (n 314). These persons were invited back for an extensive clinical examination along with a control sample, matched for age and sex (n 354). In this clinical phase, these 668 persons were assessed by means of social and family interviews, extensive medical, neurological, and psychiatric examinations, laboratory blood analyses, and a comprehensive cognitive battery. The first follow-up took place approximately 3 years (M 2.98, SD 0.46) after the baseline clinical assessment. Diagnosis of dementia and type of dementia in the Kungsholmen Project is made according to Diagnostic and Statistical Manual of Mental Disorders (3rd ed. Rev.; DSM III R; American Psychiatric Association, 1987) criteria and involves several steps. First, the examining physician makes a preliminary diagnosis. Second, a senior physician, who has not examined the participants, makes an independent preliminary diagnosis based on computerized data only. In cases of agreement, this is the final diagnosis; in cases of disagreement, a supervising physician makes the final diagnosis. Because of the lack of possibility to perform morphological examinations of the brain, the differential diagnosis of AD and VaD is based on clinical data. Symptoms and signs of cerebrovascular disorder as well as disease progression and the temporal sequence of relevant events are taken into account. The Hachinski Ischemic Scale (HIS; Hachinski et al., 1975) is used to support the clinical judgment. An HIS score greater than 6 is defined as an indication of VaD, whereas an HIS score below 5 is defined as an indication of AD. The validity of the HIS score in differentiating between AD and VaD is high; sensitivity and specificity estimates of 89% have been reported in pathologically verified cases (Moroney et al., 1997). Note that our AD diagnosis corresponds to probable AD according to the National Institute of Neurological and Communicative Disorders and Stroke (NINCDS) Alzheimer s Disease and Related Disorders Association criteria (McKhann et al., 1984), whereas the VaD diagnosis corresponds to possible VaD according to the National Institute of Neurological Disorders and Stroke (NINDS)-Association Internationale pour la Recherche et l Enseignement en Neuronsciences (AIREN) criteria (Roman et al., 1993). Finally, diagnoses of psychiatric diseases are also made according to DSM III R criteria. The participants in the present study were taken from those who completed the cognitive battery and were examined by the physicians at baseline assessment (n 522). Persons with a diagnosis of dementia (n 123), major depression or dysthymia (n 33), or psychosis (n 1) were excluded. These are all commonly used exclusion criteria in cognitive aging research. In addition, those persons who failed to return for the clinical examination at follow-up for reasons other than death were excluded (n 26) because of lack of information on diagnostic status. We also omitted individuals who received a dementia diagnosis at follow-up but died before they could be tested with the cognitive battery (n 2), because these persons could fit into both the preclinical dementia and impending death subgroups. Hence, a total of 337 persons between 75 and 96 years of age were included in the present study. Of these, 38 persons had MMSE scores of 23 or lower. This original sample was divided into subgroups on the basis of the participants status at follow-up. The preclinical dementia group (n 61) comprised all persons who received a dementia diagnosis at follow-up. Eighteen of these persons had MMSE scores of 23 or lower at baseline. The impending death group (n 69) included all persons who died between baseline and follow-up. Twelve of these persons had baseline MMSE scores of 23 or lower. Finally, the remaining sample (n 207) was defined as those persons who remained after the exclusion of the preclinical dementia and the impending death subgroups from the original sample. Eight persons in this group had baseline MMSE scores of 23 or lower Most research on cognitive functioning in the preclinical phase of dementia has focused on AD, the most common dementia disease, although some studies have treated all preclinical dementia cases as a single group (e.g., Fabrigoule et al., 1998; Grober, Lipton, Hall, & Crystal, 2000; Masur, Sliwinski, Lipton, Blau, & Crystal, 1994). Recently, it has been suggested that AD and VaD, the second most common dementia disease, may share more features than have previously been acknowledged (e.g., Kalaria & Ballard, 1999; Shi, Perry, Smith, & Friedland, 2000). For example, the patterns of cognitive impairment are strikingly similar in AD and VaD (e.g., Almkvist, Fratiglioni, Agüero-Torres, Viitanen, & Bäckman, 1999; Barr, Benedict, Tune, & Brandt, 1992; Villardita, 1993), which may partly reflect that generalized cerebrovascular disease is common in the etiology of VaD (e.g., Erkinjuntti & Hachinski, 1993; Skog, 1994). Given this state of affairs, it is conceivable that cognitive deficits may be present also prior to the diagnosis of VaD. For these reasons, it was decided that all preclinical dementia cases (AD, n 51; VaD, n 7; dementia of unspecified type, n 3) should be considered. However, all analyses were repeated, focusing on preclinical AD cases rather than on preclinical dementia cases. Another major cause of cognitive impairment in old age is stroke (e.g., Bowler, Hadar, & Wade, 1994; Kase et al., 1998). To examine the influence of stroke on the results obtained, we repeated all analyses after the exclusion of persons who had been diagnosed with stroke (n 21). All analyses were also repeated after the exclusion of persons with a low global level of cognitive performance (MMSE 25, n 65; Anthony, LeResche, Niaz, Von Korff, & Folstein, 1982) from the original sample. This was done to determine whether the findings would generalize to a sample likely to be free of other causes of cognitive impairment than those already mentioned. Materials The cognitive battery in the Kungsholmen Project covers a variety of cognitive domains with an emphasis on episodic memory: prospective memory, Trail Making test, free recall and recognition of random words,

3 PRECLINICAL DEMENTIA, DEATH, AND COGNITION 437 free and cued recall of organizable words, face recognition, Digit Span, Poppelreuter s Figures, Block Design, Clock Setting and Clock Reading, category fluency, letter fluency, and optic-spatial and dynamic organization of hand motor functions. Only those tasks that correlated negatively with age (rs.20, ps.01) were considered to be of interest in this study. These tests are described in the following sections. Visuospatial ability. A modified version of the Block Design test from the Wechsler Adult Intelligence Scale Revised or WAIS R (Wechsler, 1981) was used. The modification was done to ensure that severely demented persons could also be assessed. The test consisted of seven designs, each involving four blocks. One design was totally colored red and another was a check of red and white colors. The remaining designs were the first five designs from the WAIS R. Rules for administration and scoring followed WAIS R criteria. Performance time was limited to 60 s for each design. The maximum score was 24. In the Clock Setting test (Christensen, 1984), participants were shown five clockfaces with marks indicating the number locations, although no numbers were displayed. Participants were asked to draw the hands on the clocks to indicate a given time. The times 2 o clock, 5o clock, 3 o clock, ten-forty-five, and seven-fifteen were used. The last two times were both read as written above, not using the word quarter. For correct scoring, a deviation of 2 mm on each side of a given position of the hands of the clock was accepted. The test was self-paced, and the maximum score was 5. Verbal fluency. Three tests measuring verbal fluency were administered (Lezak, 1995). In category fluency, participants were asked to generate as many items as possible that could be found in a grocery store in 60 s. For letter fluency, participants were allowed 60 s to generate as many words as they could think of beginning with the letters N and S, respectively. In the letter fluency tasks, participants were instructed that proper names, numbers, or words with a different suffix were not credited. Because of the strong relationship between the two letter fluency measures (r.78, p.01), a composite letter fluency score was used in the analyses. Episodic memory. In face recognition, participants were presented with photos of famous persons. Half of these persons attained their fame between 1930 and 1950, whereas the other half became famous during the 1980s. During initial presentation, 40 photos were shown at a rate of5sper face. Following presentation of the last face in the series, participants received a self-paced yes no recognition test consisting of 40 dated and 40 contemporary faces presented in random order. The recognition measure used in this study was number of hits minus number of false alarms for dated and contemporary faces, respectively. Because these two measures were highly correlated (r.80, p.01), a composite face recognition score was used in the analyses. Table 1 Baseline Participant Characteristics Across Sample Recall and recognition of words were assessed by means of three different word lists. Each list comprised 12 concrete nouns presented both auditorily and visually. The word lists were comparable with regard to word length, word frequency, and concreteness, as determined by a previous normative study (Molander, 1984). In recall and recognition of random words, one of the lists was presented at a fast rate (2 s/word) and the other at a slow rate (5 s/word). Following presentation, participants were asked to recall as many words as possible in any order. Two minutes were allowed for this task. Immediately after the free recall task, participants were given a self-paced yes no recognition task consisting of the 12 target words randomly intermixed with 12 distractors. The recognition measure used was again the number of hits minus the number of false alarms. Slowly and rapidly presented words were reliably related for both recall (r.57, p.01) and recognition (r.58, p.01), and these measures were aggregated into one recall and one recognition variable. For free and cued recall of organizable words, the word list comprised 12 concrete nouns belonging to 4 taxonomic categories (e.g., furniture, musical instruments). Presentation rate was 5 s per word. After presentation of the last word in the series, participants were given a free recall task. Following completion of this task, a cued recall task was administered, in which the 4 category names were provided as retrieval cues. Two minutes were allowed for free and cued recall of organizable words, respectively. An organized recall composite score was used in the analyses, as the free and cued recall measures were highly correlated (r.79, p.01). Results Baseline participant characteristics for the original and remaining samples as well as for the preclinical dementia and impending death groups are shown in Table 1. One-way analyses of variance contrasting the remaining sample with the preclinical dementia and impending death samples revealed significant group effects on all variables: age, F(2, 334) 15.87, MSE 26.35, p.0001, 2.09; education, F(2, 334) 4.44, MSE 7.03, p.05, 2.03; and MMSE score, F(2, 334) 45.70, MSE 6.62, p.0001, Follow-up t tests showed that the impending death group was older than the other two groups ( ps.01). In addition, the preclinical dementia group was older than the remaining sample ( p.06). The remaining sample had received more education than the other two groups ( ps.05). The main effect for MMSE score reflected that the remaining sample outperformed the other groups ( ps.01) and that the impending death group performed at a higher level than the preclinical dementia group ( p.05). A Sample Original (n 337) Remaining (n 207) Preclinical dementia (n 61) Impending death (n 69) Characteristic M SD M SD M SD M SD Age (M) a Age (Mdn) a Age range a Years of education MMSE score b % women a Age is in years. b MMSE Mini-Mental State Examination (Folstein, Folstein, & McHugh, 1975).

4 438 BÄCKMAN, LAUKKA, WAHLIN, SMALL, AND FRATIGLIONI chi-square analysis showed group differences in sex distribution, 2 (2, N 337) 9.55, p.01, indicating that the preclinical dementia group had a significantly higher proportion of women than the other groups. A 3 (groups) 8 (cognitive variables) multivariate analysis of covariance (MANCOVA), controlling for sex and education, was first conducted on the cognitive data. Because the conclusions from the results of the MANCOVA were identical to those from a multivariate analysis of variance (MANOVA), only the results from the MANOVA are reported. The MANOVA yielded an overall effect of group, Wilks s.63, F(8, 327) 10.73, p Univariate analyses revealed group differences across all cognitive measures: Block Design, F(2, 334) 17.40, MSE 26.71, p.0001, 2.09; Clock Setting, F(2, 334) 15.84, MSE 1.60, p.0001, 2.09; category fluency, F(2, 334) 34.86, MSE 39.26, p.0001, 2.17; letter fluency, F(2, 334) 28.21, MSE 24.58, p.0001, 2.14; face recognition, F(2, 334) 59.19, MSE 16.32, p.0001, 2.26; random recall, F(2, 334) 48.23, MSE 2.19, p.0001, 2.22; organized recall, F(2, 334) 30.72, MSE 3.91, p.0001, 2.16; and word recognition, F(2, 334) 33.23, MSE 4.48, p.0001, The preclinical dementia and impending death groups performed poorer than the remaining sample across all indicators of cognitive performance ( ps.01). In addition, the preclinical dementia group performed at a lower level than the impending death group on random recall and word recognition ( ps.05). Summary data for the cognitive measures across samples are shown in Table 2. Table 2 also indicates that the variability of cognitive performance was generally greater in the original sample compared with the remaining sample. Next, a series of hierarchical regression analyses were conducted in which the amount of variance accounted for by age was compared in the original and remaining samples. In an effort to evaluate the relative contribution of preclinical dementia versus impending death on the age cognition relations, these analyses were followed by analyses in which these two groups were added separately to the remaining sample. In all analyses, sex and education were entered in the first block followed by age in the second block. The results of these regressions are shown in Table 3. Table 3 shows that removal of the preclinical dementia and impending death groups from the original sample had relatively Table 2 Means and Standard Deviations for the Cognitive Variables Across Sample little effect on the age-related cognitive variation. Yet, for three of the cognitive variables category fluency, letter fluency, and word recognition the age-related variation dropped below conventional significance in the remaining sample. Note, however, that the size of the age effect for these variables was relatively small in the original sample. In addition, for face recognition, there was an increase in the age cognition relationship in the remaining sample compared with the original sample. In the remaining four tasks, the difference between the two samples was negligible. These patterns of results were obtained despite that the preclinical dementia and impending death groups were older and had substantially lower scores on all cognitive tests than the remaining sample. Table 3 also indicates that removal of the impending death group rather than the preclinical dementia group resulted in the decrease in the amount of age-related variation for the two fluency measures. For word recognition, the joint effect from removing both of these groups led to the reduction of the age cognition relationship in the remaining sample. To further examine potential differences among samples in the size of the age effect on cognitive performance, we examined the Age Group interaction term for the remaining sample versus the preclinical dementia sample and the remaining sample versus the impending death sample. Of the 16 interaction terms examined, only those terms concerning word recognition for the remaining and preclinical dementia samples were reliable ( p.05). For this measure, the effect of age was nonsignificant in the remaining sample (r.13, p.05), although it was significant in the preclinical dementia sample (r.28, p.05). Thus, the general lack of reliable Age Group interaction effects indicates that the negative effects of age on performance generalized across samples. For all regression analyses presented in Table 3, quadratic and cubic trends were also examined. It was found that the quadratic trend component was reliable in 4 out of a total of 32 possible cases: word recognition in the original sample, the remaining sample, and the remaining and preclinical dementia sample, and category fluency in the remaining and impending death sample ( ps.05). In all instances, the quadratic trend reflected that the age deterioration was more pronounced after age 90 than before age 90. No reliable cubic trends were observed ( ps.10). To assess potential differences in variability between the original and remaining samples, we computed confidence intervals Sample Original Remaining Preclinical dementia Impending death Variable M SD M SD M SD M SD Block Design Clock Setting Category fluency Letter fluency Face recognition Random recall Organized recall Word recognition

5 PRECLINICAL DEMENTIA, DEATH, AND COGNITION 439 Table 3 Results of Hierarchical Regression Analyses for Determining the Influence of Age on Cognitive Performance Across Sample Sample Original Remaining Remaining and preclinical dementia Remaining and impending death Variable R 2 SE R 2 SE R 2 SE R 2 SE Block Design Clock Setting Category fluency * * Letter fluency * * Face recognition Random recall Organized recall Word recognition * Note. All effects are adjusted for sex and education. * p.05. around the standard deviations for the original sample. The issue of interest was whether the standard deviations for the remaining sample were within these confidence intervals. These computations revealed that the standard deviations for the remaining sample were outside the confidence interval for two of the eight measures: face and word recognition. For the remaining measures, the standard deviations in the remaining sample were within the respective confidence intervals for the original sample. All analyses were repeated, eliminating preclinical AD (n 51) rather than preclinical dementia cases. We also repeated all analyses after excluding persons who had previously suffered a stroke (n 21) or had a low level of global cognitive performance (MMSE 25, n 65). All of these additional analyses yielded the same pattern of results as that described above. Discussion The main purpose of this research was to examine the influence of preclinical dementia and impending death on the magnitude of age-related cognitive deficits. Before discussing the data pertaining to this objective, we note that the results concerning crosssectional age differences in cognitive performance as well as those on the effects of preclinical dementia and impending death were in the expected direction. Specifically, in agreement with prior research demonstrating an age-related deterioration in cognitive functioning in late senescence (e.g., Korten et al., 1997; Lindenberger & Baltes, 1997; Zelinski & Burnight, 1997), we found age-related deficits in tasks assessing episodic memory, visuospatial skill, and verbal fluency in this sample of 75 persons. Although the age cognition correlations ranged from low to moderate, the magnitude of the associations is consistent with earlier work, with the age effects appearing stronger for episodic memory and visuospatial skill than for verbal fluency (e.g., Bäckman et al., 1999; Bryan & Luszcz, 2000; Salthouse, 1992). In addition, sizable age cognition relationships may not be expected in this study in view of the fact that (a) the age span was relatively narrow (75 96 years of age) and (b) selective survival effects may be operating among the oldest participants (e.g., Perls, Morris, Ooi, & Lipsitz, 1993). Further, persons who were diagnosed with dementia as well as those who were dead at follow-up showed clear cognitive deficits at baseline. As expected, the degree of impairment was more pronounced in the preclinical dementia group than for those who were to die. Past research indicates that, although the most consistent deficit in preclinical dementia is seen for episodic memory (e.g., Bäckman, Small, & Fratiglioni, 2001; Small, Herlitz, Fratiglioni, Almkvist, & Bäckman, 1997), multiple other cognitive functions (e.g., perceptual speed, attention, verbal ability, visuospatial skill) are typically affected several years prior to the time at which a diagnosis may be rendered (Fabrigoule et al., 1998; Jacobs et al., 1995; Linn et al., 1995). Relatedly, evidence shows terminal decline for numerous cognitive abilities, including memory, speed, verbal skill, and spatial ability (Berg, 1996; Small & Bäckman, 1999). Thus, the present result that preclinical dementia and impending death were associated with deficits across all three cognitive domains assessed is consistent with earlier observations. In addition, although the standard deviations of the remaining sample were outside the confidence interval for the standard deviations of the original sample for two measures only (face and word recognition), there was a trend in the direction of greater variability in the original than in the remaining sample for all measures (Sliwinski et al., 1996). Given these patterns of findings, we can address the question of how preclinical dementia and forthcoming death would alter the size of the baseline relationship between age and cognitive performance. In general, the results indicate that removal of these two groups from the original sample had relatively little effect on the age cognition relations. First, the Age Group interaction effect (i.e., remaining sample vs. preclinical dementia; remaining sample vs. impending death) was found to be nonsignificant in 15 out of 16 possible cases. The single exception to this pattern was word recognition in which the age effect was reliable in the preclinical dementia group but not in the remaining sample. Thus, these analyses indicate that the age performance relationships were similar in these samples. For two of the cognitive variables (Clock Setting and organized recall), there was a slight decrease of the age-related cognitive

6 440 BÄCKMAN, LAUKKA, WAHLIN, SMALL, AND FRATIGLIONI variation in the remaining compared with the original sample. However, for block design, face recognition, and random recall, the opposite pattern was found, with slightly stronger age performance relationships in the remaining than in the original sample. For category fluency, letter fluency, and word recognition, the reliable age effects observed in the original sample were no longer significant in the remaining sample. However, when examining the influence of preclinical AD and impending death separately, it was found that impending death rather than preclinical dementia contributed to the reliable age effect in the original sample for the two fluency tests. This may reflect that, in this population-based sample, those who were to die were on average 4 years older than persons in the remaining sample, whereas the corresponding difference between the preclinical dementia group and the remaining sample was less than 2 years. Thus, the room for influencing the age cognition relationship was larger in the case of impending death than for preclinical dementia. For word recognition, none of the two future events alone altered greatly the size of the age performance relationship, although the age effect dropped below conventional significance when both groups were eliminated from the original sample. It is noteworthy that fluency and word recognition performance yielded the smallest effects of age in the original sample. Toward this end, note also that the decrease of the age effect in the remaining compared with the original sample observed for these three tasks (2% in all cases) was smaller than the corresponding increase of the age effect seen in the remaining sample for face recognition (5%). Thus, the present data suggest that an influence of preclinical dementia and impending death on age cognition relations may be most easily observed for tasks in which the age effect is relatively small already in unselected samples. In general, then, these findings lend little support to the idea that preclinical dementia or impending death affects greatly the magnitude of the age effect in cognitive aging research relying on cross-sectional data. In addition, when such influences are observed, it appears that impending death plays a greater role than preclinical dementia. It is noteworthy that this pattern of results was obtained whether or not (a) participants were screened for stroke, (b) the preclinical dementia sample was confined to AD cases, or (c) only persons with MMSE scores above 24 were included. The fact that the effects of preclinical dementia on the age cognition relations were relatively minor is consistent with the view that the transition from normal aging to dementia is continuous rather than discrete (Bäckman et al., 1999; Brayne, Gill, Paykel, Huppert, & O Connor, 1995). The present results would seem to be at variance with those reported by Sliwinski et al. (1996). Sliwinski et al. found that the age-related deterioration in fluid intelligence observed in their original sample was substantially reduced in the remaining sample. A similar pattern, albeit less pronounced, was seen for episodic memory, whereas the size of the age deficit for crystallized intelligence was similar in the two samples. In the following, we consider potential explanations for the different patterns observed in the two studies. As we have alluded to, the difference in age between the group under examination (e.g., preclinical dementia cases) and the remaining sample obviously influences the likelihood that the age cognition relationship will be different in original and remaining samples. Although the difference in years of age between the remaining sample (M 83.3 years) and the preclinical dementia sample (M 84.7 years) was somewhat smaller than expected in this study, the corresponding difference in the Sliwinski et al. (1996) study was not appreciably different (Ms 78.9 and 80.5 years, respectively). This makes it unlikely that the age difference between the original and remaining samples in the present study was too small to detect alterations in the age cognition relations. Another possibility is that differences in the nature of the cognitive tasks underlie the different patterns observed. Sliwinski et al. (1996) found a large difference in the age cognition relationship between the original and remaining samples for a composite measure of fluid intelligence, a much smaller difference for a marker of episodic memory, and no difference at all for a composite measure of crystallized intelligence. This pattern suggests that the size of age deficit may be most likely to be modified for tasks that are highly age sensitive. We used a different constellation of cognitive tasks than Sliwinski et al. However, it is still possible to compare the differences between the remaining and original samples as a function of the amount of variance accounted for by age in the original samples. This comparison indicates that the pattern was diametrically opposed in the two studies. Specifically, for the three tasks in this study where the age effect was no longer significant in the remaining sample (i.e., category fluency, letter fluency, and word recognition), age exerted the smallest influence in the original sample. For the task that yielded the largest age deficit (face recognition), there was rather an increase in the size of the age effect in the remaining compared with the original sample, and for a marker of fluid intelligence (Block Design) there was also an increase of the age effect in the unexpected direction. Although we cannot rule out the possibility that fluid intelligence is especially sensitive to the effects of preclinical dementia and impending death on age cognition relations, the pattern of findings described above suggests that this possibility is not particularly likely. A more probable reason for the discrepant findings has to do with the nature of the study samples. Whereas Sliwinski et al. (1996) used a volunteer sample, a population-based sample was used in the current study. It is conceivable that a population-based sample involves more individuals with health problems (e.g., circulatory disturbance, depressive symptoms, vitamin deficiency, sensory difficulties) as well as more persons with low cognitive performance independent of health-related factors compared to a volunteer sample. Because of the greater variability caused by these and other factors, the relative impact of preclinical dementia and impending death on the association between age and cognitive performance may be reduced in a population-based sample. In addition, note that although Sliwinski et al. emphasized the effects of preclinical dementia in their writing, they did not separate persons in a preclinical phase of dementia from those who had died or refused participation at follow-up in comparing the original and remaining samples. Thus, the relative importance of preclinical dementia and other future events to the results obtained remains unknown. Although the present findings suggest that the influence of preclinical dementia and death on age cognition relations in the general population may be smaller than perhaps previously thought, it is important to note that the youngest participant in this study was 75 years of age at baseline. To be sure, in cross-sectional samples including also younger and middle-aged individuals, the impact of preclinical dementia and death on the age cognition

7 PRECLINICAL DEMENTIA, DEATH, AND COGNITION 441 relations may be larger. However, a pooled analysis of eight European population-based studies (Fratiglioni et al., 2000) revealed annual incidence rates for all dementias of 0.2%, 0.5%, 1.6%, 3.0%, 4.8%, and 7.0% for the age groups years, years, years, years, years, and 90 years, respectively. Thus, for preclinical dementia to exert an influence on cross-sectional age differences in cognitive performance, a sizable number of old, particularly very old, individuals would need to be included. This is not the case in the typical cognitive aging study. Another concern has to do with the length of the follow-up and retest intervals. In general, the longer time an individual is followed to ascertain a particular outcome (e.g., dementia or death), the more cases will be detected. Given that the cases are older and perform more poorly than those who remain nondemented, a longer follow-up period will increase the likelihood of obtaining differences in the age cognition relationship between original and remaining samples. However, this is not to say that the present findings of relatively small effects of preclinical dementia and forthcoming death on the age cognition relations would not generalize to retest intervals longer than the 3-year interval used in this study. With regard to AD, there is evidence that the size of the preclinical cognitive impairment is similar 6 and 3 years prior to diagnosis (Bäckman et al., 2001; Small et al., 2000). Concerning impending death, some research shows relatively small effects for 6-year retest intervals (Hassing, Small, von Strauss, Fratiglioni, & Bäckman, 2002; Small, Fratiglioni, von Strauss, & Bäckman, 2001), although other research indicates clear terminal decline in cognitive functioning for retest intervals longer than 5 years (Bosworth, Schaie, Willis, & Siegler, 1999; Johansson & Berg, 1989). However, it is important to note that these comparisons concern the size of the cognitive deficit prior to dementia or death. The key issue in this article is whether preclinical dementia and impending death affect the size of the age-related cognitive deficit at baseline. Thus, if anything, a longer retest interval may be expected to yield even smaller differences in the age effects between the original and remaining samples, because those people who are removed from the original sample are less different from those who remain in terms of their cognitive functioning. 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