Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2010 Dec 1.
Published in final edited form as: J Adult Dev. 2009 Dec;16(4):199–208. doi: 10.1007/s10804-009-9066-y

Engaged Lifestyle, Personality, and Mental Status Among Centenarians

Peter Martin 1,, Joan Baenziger 2, Maurice MacDonald 3, Ilene C Siegler 4, Leonard W Poon 5
PMCID: PMC2995529  NIHMSID: NIHMS247650  PMID: 21132076

Abstract

This study assessed engaged lifestyle activities (e.g., volunteering, traveling, and public speaking) for centenarians of the Georgia Centenarian Study. A total of 285 centenarians and near-centenarians (i.e., 98 years and older) and their proxy informants participated in this study. The Mini-Mental Status Examination (MMSE) was assessed for all centenarians, and proxy informants reported on lifestyle activities and personality traits of the centenarians. Results suggested that participants who had volunteered, traveled, and those who had given public talks and balanced their checkbooks were more likely to show relatively high mental status scores (i.e., MMSE > 17). Personality traits were found to be moderators in the relationship between engaged lifestyle and mental status: Participants with high levels of Emotional Stability, Extraversion, Openness, and Conscientiousness and with high levels of engaged lifestyle were more likely to show relatively high mental status scores (i.e., MMSE > 17), whereas participants with low levels of Emotional Stability, Extraversion, Openness, Agreeableness, and Conscientiousness and with low levels of engaged lifestyle were more likely to show relatively low mental status scores (i.e., MMSE < 18). The results suggest that engaged lifestyle, particularly in combination with personality traits, plays an important role in the level of cognitive functioning among oldest old adults.

Keywords: Activities, Centenarians, MMSE, Personality, Lifestyle

Introduction

There is no doubt that reaching 100 years of age signifies an extraordinary accomplishment. Even though the 100th birthday is an extraordinary event for individuals and their families, some have questioned the quality of life in very old age (Andersen-Ranberg et al. 2001; Baltes and Baltes 1990). We have pointed out four critical areas that centenarians have to come to terms with in very late life: physical health, functional health, mental health, and economic dependency (Martin et al. 2006). For these four areas of functioning, we wonder why some centenarians continue to do relatively well, whereas others seem to be more functionally impaired. The purpose of this article was to assess the role of a past engaged lifestyle in predicting mental status among centenarians, and to test whether personality traits serve as moderators in the past engaged lifestyle–mental status relationship. In the following sections, we review evidence concerning the mental status of centenarians, the role of engaged lifestyle over the life span, and personality as an important individual difference variable.

Mental Status in Very Late Life

There is conflicting evidence about the prevalence rates of cognitive impairment among the oldest old. Ritchie and Kildea (1995) in their meta-analysis reported dementia prevalence rates of about 40% for older adults at age 95. Jeune and Andersen-Ranberg (2000), Bauco et al. (1998), and Jorm et al. (1987), on the other hand, noted a prevalence rate as high as 62% by the age of 95. Recent research on centenarians and mental status in the Heidelberg Centenarian Study found that about half of centenarians showed moderate to severe cognitive impairment but that one quarter was found to be cognitively intact (Kliegel et al. 2004). Results of the Heidelberg study further showed that cognitive decline was slightly but significantly accelerated in the last 6 months prior to death. Finally, a recent Japanese study reported that 24.3% of their centenarian sample had no dementia, 13.8% were classified as showing probably no dementia, and 61.8% were classified as mildly to severely demented. The authors also reported a significant main effect for gender indicating that men were generally more cognitively intact than women (Gondo et al. 2006).

The Role of Engaged Lifestyle

Whether older adults decline in cognitive performance may have different reasons, including genetic disposition, educational experience, and cognitive activity patterns. “The disuse” perspective on cognitive aging (Hultsch et al. 1999; Salthouse 1991) characterizes the impact of changes in lifelong activity patterns resulting in disuse and consequently deterioration of cognitive skills. If disuse of cognitive skills exacerbates age-related cognitive decline, then deliberate practice of such skills would at least result in stable performance by maintenance or enhancement of the original skills (Ericsson and Charness 1994).

Other researchers have proposed that through a variety of potential compensatory mechanisms cognitive skills could improve (Dixon and Backman 1995). In addition, further extrapolation would lead to the possibility that practice by individuals of “rusty” skills would lead to a reversal in age-related declines (Schaie and Willis 1986). Baltes and Baltes (1990) demonstrated that older adults possess considerable reserve capacity that permits them to benefit from exposure to performance-enhancing environments. Several studies have also shown that older adults have a large amount of plasticity in their performance, but that their reserve capacity does decline with age (Schaie and Willis 1986; Verhaeghen 1993).

Whether specific past positive achievements could slow down or attenuate cognitive decline in late life was examined by Pushkar et al. (1995). They reported a significant but small effect of engaged lifestyle on the maintenance of verbal intellectual function in late life. Another study found that factors such as education and maintenance of cognitive stimulation may slow the rate of cognitive decline (Wilson et al. 2002). Finally, Ghisletta et al. (2006) recently reported that activity engagement lessened the decline in perceived speed, but not in verbal fluency or performance.

Hultsch et al. (1999) posed the question, “Does stimulation provided by typical everyday activities facilitate the maintenance and improvement of general cognitive skills in a manner that is analogous to exposure to cognitive training?” (pp. 245–246). Hultsch et al.'s (1999) study provides evidence that specific engaging activities were related to working memory and other cognitive measures. Individuals who participated in intellectually challenging activities were less likely to show cognitive decline, and those individuals who maintained their participation in such activities were also less likely to show cognitive change over time. As Hultsch et al. pointed out, their results could alternatively be explained in that high-ability adults lead intellectually active lives. Kliegel et al. (2004) also noted that lifelong intellectual activities were important predictors of cognitive impairment in centenarians.

The approach of this study is consistent with the environmental complexity hypothesis (Schooler 1987) stating that complex environments characterized by diverse stimuli allow individuals who engage in activities that make significant demands on their cognitive skills show greater maintenance or improvement of their abilities than individuals who are exposed to less complex environments with more minimal cognitive demands (Hultsch et al. 1999; Schooler 1987).

Personality as Individual Difference Characteristics

The evidence reviewed suggests that active, engaged lifestyle is related to the maintenance of cognitive performance in older adults. However, the relationship between lifestyle and cognitive performance may also be influenced by individual difference characteristics. Personality traits may be considered as individual difference variables that moderate between active lifestyle and cognitive performance (Hultsch et al. 1999).

Higher cognitive functioning is often associated with Openness to Experience (Ackerman and Heggestad 1997; Austin et al. 2002), Conscientiousness (Ducheck et al. 2007; Moutafi et al. 2004), and Extraversion (Ackerman and Heggestad 1997; Moutafi et al. 2005), but negatively correlated with Neuroticism (Ackerman and Heggestad 1997; Ducheck et al. 2007; Gow et al. 2005). Wilson et al. (2005) noted that higher levels of Neuroticism were associated with an increased risk of Alzheimer's disease incidence. In their prospective study, the odds of developing Alzheimer's disease were more than doubled in individuals with high scores in Neuroticism when compared to those with relatively low scores, even though the effect was stronger in Whites compared to African Americans. Chamorro-Premuzic and Furnham (2004) also noted that an increasing number of studies acknowledge the interface of personality and cognition. Their model includes an interaction of personality with measures of intelligence.

One way to assess individual differences in engaged lifestyle patterns is by using a typology approach. The approach taken is the “type as distinctive form” perspective (Block and Ozer 1982) based on the notion that a discrete structure of individual differences exists underlying an observed variation on quantitative measures. As Meehl (1992) aptly pointed out, the question whether a particular phenomenon is viewed as dimensional, taxonic, or some mix thereof is largely an empirical question. Taxometric methods include techniques such as cluster analysis, mixture models, latent class analyses, and configural frequency analysis (CFA) (MacCallum et al. 2002).

The Present Study

The purpose of the current study was to assess the relationship between specific engagement tasks and cognitive mental status among centenarians. A secondary goal was to assess the role of the five personality traits Extraversion, Neuroticism, Conscientiousness, Agreeableness, and Openness to Experience in the relationship between engaged lifestyle and mental status. Based on the literature, we predicted that cognitive engagement tasks would be positively associated with mental status and that Extra-version, Emotional Stability, Conscientiousness, Agreeableness, and Openness to Experience would enhance the association of cognitive engagement with mental status functioning, whereas Introversion, Neuroticism, and low levels of Conscientiousness, Agreeableness, and Openness to Experience would diminish the association of engaged lifestyle with mental status functioning.

Method

Participants and Procedure

This study used population-based data from the second Georgia Centenarian Study (Poon et al. 2007), including a sample of centenarians and near-centenarians (98 year and older) from northern Georgia. The overall purpose of the study was to investigate factors related to survival and optimal functioning of centenarians.

A total of 285 centenarians participated in the study. The average age was M = 100.33 years. As would be expected, 82.1% older adults in this sample were women (n = 234) and the majority (77.5%) was Caucasian. With regard to marital status, 85.9% were widowed. The average Mini-Mental Status Examination (MMSE) score for the centenarians was M = 16.92. A total of 48.2% were severely cognitively impaired (MMSE < 18), whereas 32.4% showed little or no cognitive impairment (MMSE > 17). A summary of demographic characteristics in this study is presented in Table 1.

Table 1.

Summary of demographic characteristics

Demographic characteristics n %
Gender
    Female 234 82.1
    Male 51 17.9
Ethnicity
    White/Caucasian 221 77.5
    Black/African American 64 22.5
Education
    0–4 years 12 5.2
    5–8 years 55 23.9
    Some high school 26 11.3
    High school diploma 44 19.1
    Trade school or vocational degree 30 13.0
    Some college 22 9.6
    College Degree 19 8.3
    Graduate Degree 22 9.6
Marital status
    Never married 13 4.6
    Married 16 5.7
    Widowed 243 85.9
    Divorced/separated 11 3.9
Cognitive functioning
    Severe impairment (MMSE 0-17) 137 48.2
    Mild cognitive impairment (MMSE, 18-22) 55 19.4
    No cognitive impairment (MMSE, 23-30) 92 32.4

The names of the participants were obtained from the voter registration rolls from the State of Georgia and from calls to a random subset of nursing home facilities. The sampling frame included 44 counties in Northeast Georgia within a 2-h drive from Athens. Participants were first recruited by telephone and mail, and subsequent face-to-face interviews were conducted.

The Georgia Centenarian Study collected data from centenarians and proxy informants. Informants included 240 proxies who provided additional information on our centenarian participants. The majority of the proxies were their adult children (61.1%). Additional proxies included nieces and nephews (13.9%), granddaughters (9.9%), and miscellaneous informants, such as spouses, siblings, or friends (15.1%).

Measures

Engaged Lifestyle

Past engaged lifestyle activities were defined by educational attainment and by a series of cognitive engagement tasks (Hultsch et al. 1999), and were assessed from surveys with proxy informants. Education was a dichotomized variable defined as relatively low level of education (up to high school completion) or relatively high level of education (post-high school education). Questions pertaining to cognitive engagement tasks included, “Did he/she ever learn a foreign language,” “Did he/she ever go back to school for more education,” “Did he/she ever do volunteer work for an organization such as a hospital, church, school, or political party,” “Did he/she ever travel within his/her country,” “Did he/she ever travel to a foreign country,” “Did he/she typically prepare his/her own taxes,” “Did he/she ever give a public talk or lecture (to a club, service organization, etc.),” and “Did he/she typically balance his/her checkbook (take care of finances).” Participants answered “yes” or “no” to these questions. These items were used separately in the first part of the analysis and combined to a summary score in the second part. The eight cognitive engagement items had an internal consistency of alpha = .68. Because it is unclear to what extent centenarians and proxies agree on the occurrence of lifestyle tasks and personality, inter-rater agreement (self-ratings and proxy ratings) were computed for those centenarians who were able to report about their activities and personality. Inter-rater agreement of whether a task had occurred or not ranged from 70. 4% for “going back to school” to 96.0% for “traveling within his/her country.” Average agreement for all items was 81.6%.

Personality

The NEO Personality Inventory (NEO PI-R) was used to obtain personality assessments by caregiver proxies (Costa and McCrae 1992). This measure includes 240 items. We used this measure with proxies in order to assess centenarians’ personalities. The NEO PI-R uses a 5-point scale that ranges from SD = strongly disagree (= –2), D = disagree (= –1), N = neutral (= 0), A = agree (= 1), and SA = strongly agree (= 2). Higher scores indicate higher levels of the personality trait assessed. Some of the questions asked were “she/he really likes most people she/he meets” (Extraversion), “sometimes she/he feels completely worthless” (Neuroticism), and “she/he is known for his/her prudence and common sense” (Conscientiousness). In this study, the reliability for Neuroticism was α = .85, .77 for Extraversion, .69 for Openness, .88 for Agreeableness, and .90 for Conscientiousness. For Neuroticism, the opposite end of the scale (i.e., Emotional Stability) is used for ease of interpretation.

Again, it is unclear to what extent centenarian self-ratings corresponded with proxy ratings for personality. Other studies have reported that personality rating agreements between older adults and proxy informants are quite good (Duchek et al. 2007; Rankin et al. 2005). In this study, centenarians only responded to a few traits and facets of the NEO. Paired t-tests were therefore computed for Neuroticism, Extraversion, Ideas (a facet of Openness), Competence (a facet of Conscientiousness), and Trust (a facet of Agreeableness). No mean differences were obtained for Extraversion, t(103) = 0.15, p > .05 and Ideas, t(82) = 0.82, p > .05. Significant differences were obtained for Neuroticism, t(111) = 4.26, p < .001, Competence, t(91) = 4.50, p < .001, and Trust, t(104) = 5.23, p < .001, indicating that centenarians rated themselves lower in Neuroticism, but higher in Competence and Trust when compared to their proxies.

Mental Status

Cognitive performance was assessed with the MMSE (Folstein et al. 1975). A high score on the MMSE indicates higher cognitive performance. There is continued debate about the appropriate cutoff score for cognitive impairment when using the MMSE. After their extensive review of the literature, Tombaugh and McIntyre (1992) suggested that a score <18 be used for severe cognitive impairment, whereas a score ≥18 would indicate mild cognitive impairment or no cognitive impairment. The authors point out that lower educational levels and ethnicity may yield lower scores than would be expected in highly educated or majority populations. In very old populations, vision impairment may also account for lower MMSE scores (Holtsberg et al. 1995). For the purposes of this study, the MMSE was dichotomized into high and low status by dividing the sample with a score of ≥18 in the relatively high mental status category and a score of ≤17 in the relatively low mental status category.

Design and Analyses

The general analytic strategy of this article was to assess underlying categories (“types”) of centenarians that fall in relatively high or low categories of mental status functioning. CFA is used in this study. CFA is a multivariate statistical method that identifies discrete and uniquely constituted groups of individuals (von Eye 1990) by comparing observed to expected frequencies in a cross tabulation. Significant differences suggest the presence of groups (configurations) that include either more or less individuals than would be expected under an assumption of complete independence. The significant configurations are referred to as types and antitypes (von Eye 1990). Any configuration with a probability value <.05 could be considered a significant type or antitype. Because each configuration is tested for significance, Bonferroni adjustments for number of tests are applied. The program also computes relative risk values. The relative risk of a configuration indicates the relative frequency of the occurrence of a configuration, given the expectation from the base model. A score of RR = 2, for example, suggests that twice as many cases were observed as expected from the base model (von Eye 2000).

CFAs were computed using education, the cognitive engagement variables, personality, and mental status as cross-configuration variables. First, education and each cognitive engagement variable were related to mental status alone, and then the summary variable of cognitive engagement was related to each personality trait and mental status. For the configural frequency analyses, personality traits were dichotomized at the median level. Scores for all scales could range from –96 to 96 with zero as the scale midpoint. For Neuroticism, the median split occurred at –26, for Extraversion at 9, for Openness at –4, for Agreeabless at 29, and for Conscientiousness at 30.

Results

General descriptive results separated by mental status are provided in Table 2. In general, traveling in the United States and balancing one's checkbook were the most frequent engaged lifestyle activities used by centenarians, whereas preparing a tax return and learning a foreign language were the least frequent lifestyle activities. Significant differences were obtained for all engaged lifestyle tasks favoring the higher MMSE group. For example, 63.2% of the high MMSE group but only 32.7% of the low MMSE group had ever visited a foreign country. Similarly, 84.3% of the high MMSE group but only 56.5% of the low MMSE group had ever volunteered.

Table 2.

Frequencies and means of engaged lifestyle tasks and personality traits

Lifestyle task Total Low MMSE (<18)
High MMSE (>17)
χ 2
Yes, n No, n Yes, n No, n
Return to school 225 15 94 35 81 8.76**
Travel U.S. 227 100 10 114 3 4.57*
Balance checkbook 222 79 28 101 14 7.08**
Volunteer work 223 61 47 97 18 20.94***
Foreign travel 227 36 74 74 43 21.15***
Public lecture 219 37 68 70 44 14.98**
Tax return 217 18 88 39 72 9.23**
Foreign language 216 10 91 33 82 11.91***
M SD M SD F
Neuroticism –16.87 19.36 –29.16 21.45 15.65***
Extraversion 5.59 18.50 13.12 19.95 6.63*
Openness to experience –8.22 13.58 –2.16 16.95 6.22*
Agreeableness 26.26 21.15 28.62 23.54 .50
Conscientiousness 24.72 21.93 32.02 21.96 4.68*

Centenarians had low scores on Neuroticism and Openness but relatively high scores on Extraversion, Agreeableness, and Conscientiousness. Personality differences by mental status were obtained for Neuroticism, Extraversion, and Openness. Centenarians with high levels of cognitive functioning were less likely to be neurotic, but more extraverted, open to experience, and conscientious. No differences were obtained for Agreeableness.

Bivariate correlations for high and low functioning centenarians are summarized in Table 3. For centenarians with low cognitive functioning scores, engaged lifestyle was significantly related to Extraversion, Conscientiousness, and cognitive functioning, indicating that centenarians with high levels of engaged lifestyle were more likely to be extraverted, conscientious, and cognitive functioning. Conscientiousness was also positively related to the engaged lifestyle for high functioning centenarians, but Extraversion and cognitive functioning were not related to the engaged lifestyle. In contrast to centenarians with low scores in cognitive functioning, highly functioning centenarians showed a significant correlation between Openness and engaged lifestyle.

Table 3.

Bivariate correlations

1 2 3 4 5 6 7
1. Engaged lifestyle 1.00 –.13 .10 .24* .01 .26* .16
2. Neuroticism –.06 1.00 –.39** –.33** –.54** –.63** .05
3. Extraversion .27* –.46** 1.00 .48** .11 .40* .04
4. Openness to experience .09 .05 .46** 1.00 .23* .35** .13
5. Agreeableness –.11 –.48** .23* .19 1.00 .39** .06
6. Conscientiousness .30* –.57** .47** .22 .35** 1.00 .17
7. Cognitive functioning .29** .00 .31* .14 .16 .02 1.00

Note: Values below the diagonal are for low cognitive functioning (MMSE < 18), whereas above the diagonal are for high cognitive functioning (MMSE > 17)

*

p < .05

**

p < .01

The results of the configural frequency analyses are summarized in Table 4. Our hypothesis suggested that more participants should be found in the High Engagement and High Mental Status groups as well as in the Low Engagement in Low Mental Status Group. These groups should show up as significant types. In contrast, few participants would be expected in the Low Engagement High Mental Status and in the High Engagement–Low Mental Status group (antitypes).

Table 4.

Configural frequency analysis of engaged lifestyle and mental status

Engagement Configuration FO FE p Type/antitype RR
Education Low–Low 80 57.00 .000 Type 1.40
Low–High 56 57.00 .475 1.98
High–Low 28 57.00 .000 Antitype .49
High–High 64 57.00 .160 1.12
Foreign language Low–Low 91 54.00 .000 Type 1.68
Low–High 82 54.00 .000 Type 1.52
High–Low 10 54.00 .000 Antitype .19
High–High 33 54.00 .000 Antitype .61
Return to school Low–Low 94 56.25 .000 Type 1.67
Low–High 81 56.25 .000 Type 1.44
High–Low 15 56.25 .000 Antitype .27
High–High 35 56.25 .000 Antitype .62
Volunteer work Low–Low 47 55.75 .100 .84
Low–High 18 55.75 .000 Antitype .32
High–Low 61 55.75 .230 1.09
High–High 97 55.75 .000 Type 1.74
Travel U.S. Low–Low 10 56.75 .000 Antitype .18
Low–High 3 56.75 .000 Antitype .05
High–Low 100 56.75 .000 Type 1.76
High–High 114 56.75 .000 Type 2.01
Foreign travel Low–Low 74 56.75 .006 Type 1.30
Low–High 43 56.75 .019 .76
High–Low 36 56.75 .001 Antitype .63
High–High 74 56.75 .006 Type 1.30
Tax return Low–Low 88 54.25 .000 Type 1.62
Low–High 72 54.25 .004 Type 1.33
High–Low 18 54.25 .000 Antitype .30
High–High 39 54.25 .009 Antitype .72
Public talk Low–Low 68 54.75 .030 1.24
Low–High 44 54.75 .050 .80
High–Low 37 54.75 .003 Antitype .68
High–High 70 54.75 .012 Type 1.28
Balance checkbook Low–Low 28 55.50 .000 Antitype .51
Low–High 14 55.50 .000 Antitype .25
High–Low 79 55.50 .000 Type 1.42
High–High 101 55.50 .000 Type 1.82

The first column of each configuration refers to level of engaged life style (yes/no), the second column of each configuration refers to level of mental status (high/low)

Note: FO observed frequencies, FE expected frequencies, RR relative risk

Our hypotheses were partially supported. More participants fell in the group of High Engagement–High Mental Status (type) for the following activities: Volunteer work, traveling within the United States, foreign travel, giving a public talk, and balancing one's checkbook. The opposite configuration (low engagement, low mental status) was obtained for education, learning a foreign language, returning to school for more education, foreign travel, and preparing a tax return.

Unexpected types were obtained for learning a foreign language (low engagement and high mental status), returning to school (low engagement and high mental status), traveling within the United States (high engagement–low mental status), preparing a tax return (low engagement, high mental status), and balancing a checkbook (high engagement–low mental status). These results are perhaps best explained by the relatively low number of participants who had ever learned a foreign language, returned to school, and who had ever prepared a tax return, whereas an extremely large number of participants had traveled within the United States and balanced a checkbook.

Finally, configural frequencies analyses were computed by including personality traits. Tables 5, 6, 7, 8, and 9 depict frequencies for eight configurations relative to specific personality traits. For all personality traits, low trait levels combined with low levels of engaged lifestyle, and low levels of mental status were obtained more often than would be expected by chance. Conversely, the configuration of high engaged lifestyle, high personality trait (except for Agreeableness), and high mental status also occurred more often than would be expected by chance.

Table 5.

Configurations of engaged lifestyle, extraversion, and mental status

Configuration FO FE p Type/antitype RR
Low ELS, Low E, Low MS 38 19.63 .013 Type 1.94
Low ELS, Low E, High MS 18 19.63 .000 .92
Low ELS, High E, Low MS 18 19.63 .320 .92
Low ELS, High E, High MS 17 19.63 .000 .87
High ELS, Low E, Low MS 8 19.63 .179 Antitype .41
High ELS, Low E, High MS 15 19.63 .166 .76
High ELS, High E, Low MS 9 19.63 .036 Antitype .46
High ELS, High E, High MS 34 19.63 .057 Type 1.73

Bonferroni-adjusted alpha = .0062500

Note: ELS engaged lifestyle, E extraversion, MS mental status, RR relative risk

Table 6.

Configurations of engaged lifestyle, emotional stability, and mental status

Configuration FO FE p Type/antitype RR
Low ELS, Low ES, Low MS 32 19.13 .002 Type 1.67
Low ELS, Low ES, High MS 14 19.13 .127 .73
Low ELS, High ES, Low MS 18 19.13 .451 .94
Low ELS, High ES, High MS 21 19.13 .358 1.10
High ELS, Low ES, Low MS 11 19.13 .025 .58
High ELS, Low ES, High MS 20 19.13 .451 1.05
High ELS, High ES, Low MS 6 19.13 .000 Antitype .31
High ELS, High ES, High MS 31 19.13 .004 Type 1.62

Bonferroni-adjusted alpha = .0062500

Note: ELS engaged lifestyle, ES emotional stability, MS mental status, RR relative risk

Table 7.

Configurations of engaged lifestyle, agreeableness, and mental Status

Configuration FO FE p Type/antitype RR
Low ELS, Low A, Low MS 34 19.63 .001 Type 1.73
Low ELS, Low A, High MS 13 19.63 .064 .66
Low ELS, High A, Low MS 19 19.63 .500 .97
Low ELS, High A, High MS 23 19.63 .239 1.17
High ELS, Low A, Low MS 11 19.63 .019 .56
High ELS, Low A, High MS 23 19.63 .239 1.17
High ELS, High A, Low MS 6 19.63 .000 Antitype .31
High ELS, High A, High MS 28 19.63 .033 1.43

Bonferroni-adjusted alpha = .0062500

Note: ELS engaged lifestyle, A Agreeableness, MS mental status, RR relative risk

Table 8.

Configurations of engaged lifestyle, openness, and mental status

Configuration FO FE p Type/antitype RR
Low ELS, Low O, Low MS 31 18.25 .002 Type 1.70
Low ELS, Low O, High MS 18 18.25 .537 .99
Low ELS, High O, Low MS 16 18.25 .340 .88
Low ELS, High O, High MS 17 18.25 .437 .93
High ELS, Low O, Low MS 7 18.25 .002 Antitype .38
High ELS, Low O, High MS 18 18.25 .537 .99
High ELS, High O, Low MS 8 18.25 .004 Antitype .44
High ELS, High O, High MS 31 18.25 .002 Type 1.70

Bonferroni-adjusted alpha = .0062500

Note: ELS engaged lifestyle, O openness, MS mental status, RR relative risk

Table 9.

Configurations of engaged lifestyle, conscientiousness, and mental status

Configuration FO FE p Type/antitype RR
Low ELS, Low C, Low MS 33 18.75 .001 Type 1.76
Low ELS, Low C, High MS 18 18.75 .488 .96
Low ELS, High C, Low MS 16 18.75 .297 .85
Low ELS, High C, High MS 15 18.75 .214 .80
High ELS, Low C, Low MS 7 18.75 .001 Antitype .37
High ELS, Low C, High MS 20 18.75 .415 1.07
High ELS, High C, Low MS 10 18.75 .015 .53
High ELS, High C, High MS 31 18.75 .003 Type 1.65

Bonferroni-adjusted alpha = .0062500

Note: ELS engaged lifestyle, C conscientiousness, MS mental status, RR relative risk

Discussion

The purpose of this study was to assess the relationship between engaged lifestyles and mental status in very late life. We hypothesized that a number of lifetime activities (e.g., traveling, volunteering, or balancing a checkbook) would be protective markers of relatively high mental status. Three major findings emerged from our analyses: descriptive analyses showed that traveling, volunteering, and balancing a checkbook were frequent activities, whereas learning a foreign language and preparing a tax return were relatively infrequent activities. Second, a number of activities were protective markers of late life mental status. Third, personality traits moderated the effect of activities on mental status: Emotional Stability, Extraversion, Openness, and Conscientiousness each in combination with high activity levels were associated with higher mental status scores.

It comes as no surprise that some activities are more likely to be reported than others. Traveling within the United States, for example, requires fewer resources than traveling abroad, and volunteer opportunities exist in most communities of the United States. Foreign language learning, on the other side, was not particularly frequent when centenarians attended school more than 80 years ago. If only a small number of participants report an activity, then it becomes likely that an “antitype” configuration is obtained.

The analysis of statistical configurations, however, did demonstrate that for almost all individual activities high engaged activity was associated with high mental status: for volunteering, traveling, public speaking, and balancing a checkbook, a larger number of participants was obtained in the higher mental status group than would be expected by chance. It is important to note, however, that participants who had not engaged in these activities were not more likely to show low mental status scores, except for foreign travel. Not a single pattern of high activity–high mental status along with low activity–low mental status emerged, although for public speaking a statistical trend for both configurations was obtained.

The results confirm earlier research indicating that engaged activities are important. Pushkar et al. (1995), for example, noted that past positive achievements could slow down or attenuate cognitive decline in late life. Hultsch et al. (1999) also noted that intellectually engaging activities served to buffer individuals against potential decline. Another centenarian study by Kliegel et al. (2004) had also reported that lifelong intellectual activities were important predictors of cognitive functioning in very late life. The results partially confirm the “disuse perspective” of cognitive aging (Hultsch et al. 1999), because the lack of engagement was not as strongly and consistently associated with lower cognitive functioning scores, but it is possible that lifetime engagement in specific activities builds “reserve capacities” (Baltes and Baltes 1990) that serve as protective factors in very late life.

The third major finding of this study relates to the role that personality might play as a moderator in the relationship between engaged lifestyle and mental status. Of the five major personality traits described by the Big-5 typology, low levels of all traits together with low levels of engaged activities were associated with low levels of mental status, whereas high trait levels together with engaged lifestyle activity were associated with high levels of mental status. These results suggest that it is not engaged lifestyle alone that contributes to higher or lower mental status. Rather, the relationship between engaged lifestyle and mental status is dependent on personality traits of participants. Only if centenarians exhibited high levels of emotional stability, extraversion, openness, and conscientiousness was engaged lifestyle associated with higher mental status functioning. The role of personality traits for survivorship has been pointed out in other research (Friedman et al. 1993; Martin et al. 2006).

As is true for all research, this study has a number of limitations. First, participants of this study were only recruited from one geographic area of the United States. Results can therefore not be generalized to other regions of the United States. Second, this study was conducted only with centenarians, a highly selective group of survivors. Results therefore cannot be generalized to other age groups or cohorts. Another limitation is that only a few selected dimensions of engaged lifestyle were part of this study. Surely there are many other activities that may play an important role and that should be investigated in the future. We also focused only on the question whether participants had ever engaged in these activities. To assess the last time or the frequency by which these activities were pursued would also be important to consider. Finally, all assessments (except for mental status) in this study were reported by proxies who may more or less accurately recall the activities of their centenarian family member. Other studies, however, have demonstrated that proxy reports can provide useful information in special populations (Sloane et al. 2005). It should be cautioned, however, that proxy reports can be biased because cognitively functioning centenarians (when compared with their cognitively impaired peers) could remind their close relatives or caregivers of their previous activities. As a result, informants of cognitively intact centenarians (when compared to their cognitively impaired peers) would have that information more readily available when being asked, thereby resulting in reporting of more activities in cognitively fit centenarians (when compared with their cognitively impaired peers).

In spite of these limitations, results of this study confirm that engaging in a number of challenging activities may have a lifelong protective effect on mental status. Furthermore, personality traits in combination with the lack of engaged lifestyle may point to risk factors of mental status in very late life. If these results can be confirmed in others studies, then centenarians may well point to specific pathways of optimal cognitive aging.

Acknowledgments

The Georgia Centenarian Study (Leonard W. Poon, PI) is funded by 1P01-AG17553 from the National Institute on Aging, a collaboration among The University of Georgia, Tulane University, Boston University, University of Kentucky, Emory University, Duke University, Wayne State University, Iowa State University, and University of Michigan. Authors acknowledge the valuable recruitment and data acquisition effort from M. Burgess, K. Grier, E. Jackson, E. McCarthy, K. Shaw, L. Strong, and S. Reynolds, data acquisition team manager; S. Anderson, E. Cassidy, M. Janke, and T. Savla, data management; M. Poon for project fiscal management.

Footnotes

“This study is conducted for the Georgia Centenarian Study.”

Additional authors for the “Georgia Centenarian Study” include S. M. Jazwinski, R. C. Green, M. Gearing, W. R. Markesbery, J. L. Woodard, M. A. Johnson, J. S. Tenover, W. L. Rodgers, D. B. Hausman, C. Rott, A. Davey, and J. Arnold.

Contributor Information

Peter Martin, Gerontology Program, Iowa State University, 1096 LeBaron Hall, Ames, IA 50011, USA pxmartin@iastate.edu.

Joan Baenziger, Gerontology Program, Iowa State University, 1096 LeBaron Hall, Ames, IA 50011, USA.

Maurice MacDonald, Gerontology Program, Iowa State University, 1096 LeBaron Hall, Ames, IA 50011, USA.

Ilene C. Siegler, Duke Behavioral Medicine Research Center, Durham, NC, USA

Leonard W. Poon, University of Georgia, Athens, GA, USA

References

  1. Ackerman PL, Heggestad ED. Intelligence, personality, and interests: Evidence for overlapping traits. Psychological Bulletin. 1997;121:219–245. doi: 10.1037/0033-2909.121.2.219. [DOI] [PubMed] [Google Scholar]
  2. Andersen-Ranberg K, Vasegaard L, Jeune B. Dementia is not inevitable: A population study of Danish centenarians. Journal of Gerontology: Psychological Sciences. 2001;56:P152–P159. doi: 10.1093/geronb/56.3.p152. [DOI] [PubMed] [Google Scholar]
  3. Austin AJ, Deary IJ, Whiteman MC, Fowkes FGR, Padersen NL, Rabbitt P, et al. Relationship between ability and personality: Does intelligence contribute positively to personal and social adjustment? Personality and Individual Differences. 2002;32:1391–1411. [Google Scholar]
  4. Baltes PB, Baltes MM. Psychological perspectives on successful aging: The model of selective optimization with compensation. In: Baltes PB, Baltes MM, editors. Successful aging: Perspectives from the behavioral sciences. Cambridge University Press; Cambridge, UK: 1990. pp. 1–34. [Google Scholar]
  5. Bauco C, Borriello C, Cinti AM, Martella S, Zannino G, Rossetti C, et al. Correlation between MMSE performance, age and education in centenarians. Archives of Gerontology and Geriatrics. 1998;26(Suppl. 6):23–26. [Google Scholar]
  6. Block J, Ozer DJ. Two types of psychologists: Remarks on the Mendelsohn, Weiss, and Feimer contribution. Journal of Personality and Social Psychology. 1982;42:1171–1181. [Google Scholar]
  7. Chamorro-Premuzic T, Furnham A. A possible model for understanding the personality-intelligence interface. British Journal of Psychology. 2004;95:249–264. doi: 10.1348/000712604773952458. [DOI] [PubMed] [Google Scholar]
  8. Costa PT, Jr., McCrae RR. The NEO personality inventory manual. Psychological Assessment Resources; Odessa, FL: 1992. [Google Scholar]
  9. Dixon RA, Backman L. Compensating for psychological deficits and declines: Manage losses and promoting gains. Erlbaum; Hillsdale, NJ: 1995. [Google Scholar]
  10. Duchek JM, Balota DA, Storandt M, Larsen R. The power of personality in discriminating between healthy and early-stage Alzheimer's disease. Journal of Gerontology: Psychological Sciences. 2007;62B:P353–P361. doi: 10.1093/geronb/62.6.p353. [DOI] [PubMed] [Google Scholar]
  11. Ericsson KA, Charness N. Expert performance: Its structure and acquisition. American Psychologist. 1994;49:725–747. [Google Scholar]
  12. Folstein MF, Folstein SE, McHugh PR. Mini-Mental State: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research. 1975;12:189–198. doi: 10.1016/0022-3956(75)90026-6. [DOI] [PubMed] [Google Scholar]
  13. Friedman HS, Tucker JS, Tomlinson-Keasey C, Schwartz JE, Wingard DL, Criqui MH. Does childhood personality predict longevity? Journal of Personality and Social Psychology. 1993;65:176–185. doi: 10.1037//0022-3514.65.1.176. [DOI] [PubMed] [Google Scholar]
  14. Ghisletta P, Bickel JF, Lördén M. Does activity engagement protect against cognitive decline in old age? Methodological and analytical considerations. Journal of Ger-ontology: Psychological Sciences. 2006;61B:P253–P261. doi: 10.1093/geronb/61.5.p253. [DOI] [PubMed] [Google Scholar]
  15. Gondo Y, Hirose N, Arai Y, Inagaki H, Masui Y, Yamamura K, et al. Functional status of centenarians in Tokyo, Japan: Developing better phenotypes of exceptional longevity. Journal of Gerontology: Biological Sciences. 2006;61:305–310. doi: 10.1093/gerona/61.3.305. [DOI] [PubMed] [Google Scholar]
  16. Gow AJ, Whiteman MC, Pattie A, Deary IJ. The personality-intelligence interface: Insights from an ageing cohort. Personality and Individual Differences. 2005;39:751–761. [Google Scholar]
  17. Holtsberg PA, Poon LW, Noble CA, Martin P. Mini-Mental State Exam Status of community dwelling, cognitively intact centenarians. International Psychogeriatrics. 1995;7:417–427. doi: 10.1017/s104161029500216x. [DOI] [PubMed] [Google Scholar]
  18. Hultsch DF, Hertzog C, Small BJ, Dixon RA. Use it or lose it: Engaged lifestyle as a buffer of cognitive decline in aging? Psychology and Aging. 1999;14:245–263. doi: 10.1037//0882-7974.14.2.245. [DOI] [PubMed] [Google Scholar]
  19. Jeune B, Andersen-Ranberg K. What can we learn from centenarians? In: Martin P, Rott C, Hagberg B, Morgan K, editors. Autonomy versus dependence in the oldest old. Serdi; Paris: 2000. pp. 9–24. [Google Scholar]
  20. Jorm AF, Korten AE, Hendersen AS. The prevalence of dementia: A quantitative integration of the literature. Acta Psychiatrica Scandinavia. 1987;76:465–479. doi: 10.1111/j.1600-0447.1987.tb02906.x. [DOI] [PubMed] [Google Scholar]
  21. Kliegel M, Moor C, Rott C. Cognitive status and development in the oldest old: A longitudinal analysis from the Heidelberg Centenarian Study. Archives of Gerontology and Geriatrics. 2004a;39:143–156. doi: 10.1016/j.archger.2004.02.004. [DOI] [PubMed] [Google Scholar]
  22. Kliegel M, Zimprich D, Rott C. Life-long intellectual activities medicate the predictive effect of early education non cognitive impairment in centenarians: A retrospective study. Aging & Mental Health. 2004b;8:430–437. doi: 10.1080/13607860410001725072. [DOI] [PubMed] [Google Scholar]
  23. MacCallum RC, Zhang S, Preacher KJ, Rucker DD. On the practice of dichotomization of quantitative variables. Psychological Methods. 2002;7:19–40. doi: 10.1037/1082-989x.7.1.19. [DOI] [PubMed] [Google Scholar]
  24. Martin P, da Rosa G, Siegler I, Davey A, MacDonald M, Poon LW, et al. Personality and longevity: Findings from the Georgia Centenarian Study. Age. 2006;28:343–352. doi: 10.1007/s11357-006-9022-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Meehl PE. Factors and taxa, traits and types, differences of degree and differences in kind. Journal of Personality. 1992;60:117–174. [Google Scholar]
  26. Moutafi J, Furnham A, Paltiel L. Why is conscientiousness negatively correlated with intelligence? Personality and Individual Differences. 2004;37:1013–1022. [Google Scholar]
  27. Moutafi J, Furnham A, Paltiel L. Can personality and demographic factors predict intelligence? Personality and Individual Differences. 2005;38:1021–1033. [Google Scholar]
  28. Poon LW, Jazwinski SM, Green RC, Woodard JL, Martin P, Rodgers WL, et al. Annual review of gerontology and geriatrics, vol. 27: Biopsychosocial approaches to longevity. Springer; New York: 2007. pp. 231–264. [PMC free article] [PubMed] [Google Scholar]
  29. Pushkar G, Reis D, Feldman M, Markiewicz D, Andres D. When home caregiving ends: A longitudinal study of outcomes for caregivers of relatives with dementia. Journal of the American Geriatrics Society. 1995;43:10–16. doi: 10.1111/j.1532-5415.1995.tb06235.x. [DOI] [PubMed] [Google Scholar]
  30. Rankin KP, Baldwin E, Pace-Savitsky C, Kramer JH, Miller BL. Self awareness and personality change in dementia. Journal of Neurology, Neurosurgery, & Psychiatry. 2005;76:632–639. doi: 10.1136/jnnp.2004.042879. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Ritchie K, Kildea D. Is senile dementia age-related or ageing-related? Evidence from meta-analysis of dementia prevalence in the oldest old. Lancet. 1995;346:931–934. doi: 10.1016/s0140-6736(95)91556-7. [DOI] [PubMed] [Google Scholar]
  32. Salthouse TA. Theoretical perspectives on cognitive aging. Erlbaum; Hillsdale, NJ: 1991. [Google Scholar]
  33. Schaie KW, Willis SL. Can decline in adult intellectual functioning be reversed? Developmental Psychology. 1986;22:223–232. [Google Scholar]
  34. Schooler C. Psychological effects of complex environments during the life span. A review and theory. In: Schooler C, Schaie KW, editors. Cognitive functioning and social structure over the life course. Ablex; Norwood, NJ: 1987. pp. 24–49. [Google Scholar]
  35. Sloane PD, Zimmerman S, Williams CS, Reed PS, Gill KS, Preisser JS. Evaluating the quality of life of long-term care residents with dementia. The Gerontologist. 2005;45:37–49. doi: 10.1093/geront/45.suppl_1.37. [DOI] [PubMed] [Google Scholar]
  36. Tombaugh TN, McIntyre NJ. The Mini-Mental Status Examination: A comprehensive review. Journal of the American Geriatrics Society. 1992;40:922–935. doi: 10.1111/j.1532-5415.1992.tb01992.x. [DOI] [PubMed] [Google Scholar]
  37. Verhaeghen P. Teaching old dogs new tricks: Plasticity in episodic memory performance in old age. Catholic University of Leuven; Leuven, Belgium: 1993. [Google Scholar]
  38. Von Eye A. Introduction to configural frequency analysis. Cambridge University Press; New York: 1990. [Google Scholar]
  39. Von Eye A. Configural frequency analysis—A program for 32 Bit Windows operating system. Manual for Program Version 2000. Michigan State University; Lansing, MI: 2000. [Google Scholar]
  40. Wilson RS, Barnes LL, Bennett DA, Li Y, Bienias JL, Mendes de Leon CF, et al. Proneness to psychological distress and risk of Alzheimer disease in a biracial community. Neurology. 2005;64:380–382. doi: 10.1212/01.WNL.0000149525.53525.E7. [DOI] [PubMed] [Google Scholar]
  41. Wilson RS, Beckett LA, Barnes LL, Schneider JA, Bach J, Evans DA, et al. Individual differences in rates of change in cognitive abilities of older persons. Psychology and Aging. 2002;17:179–193. [PubMed] [Google Scholar]

RESOURCES