C International Psychogeriatric Association 2014 International Psychogeriatrics (2014), 26:9, 1417–1430 doi:10.1017/S1041610214000301
Life course influences of physical and cognitive function and personality on attitudes to aging in the Lothian Birth Cohort 1936 ...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Susan D. Shenkin,1,2 Ken Laidlaw,3 Mike Allerhand,2,4 Gillian E. Mead,1 John M. Starr1,2,5 and Ian J. Deary2,4 1
Department of Geriatric Medicine, University of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SB, UK Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK 3 Clinical Psychology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK 4 Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK 5 Alzheimer Scotland Dementia Research Centre, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK 2
ABSTRACT
Background: Reports of attitudes to aging from older people themselves are scarce. Which life course factors predict differences in these attitudes is unknown. Methods: We investigated life course influences on attitudes to aging in healthy, community-dwelling people in the UK. Participants in the Lothian Birth Cohort 1936 completed a self-report questionnaire (Attitudes to Aging Questionnaire, AAQ) at around age 75 (n = 792, 51.4% male). Demographic, social, physical, cognitive, and personality/mood predictors were assessed, around age 70. Cognitive ability data were available at age 11. Results: Generally positive attitudes were reported in all three domains: low Psychosocial Loss, high Physical Change, and high Psychological Growth. Hierarchical multiple regression found that demographic, cognitive, and physical variables each explained a relatively small proportion of the variance in attitudes to aging, with the addition of personality/mood variables contributing most significantly. Predictors of attitudes to Psychosocial Loss were high neuroticism; low extraversion, openness, agreeableness, and conscientiousness; high anxiety and depression; and more physical disability. Predictors of attitudes to Physical Change were: high extraversion, openness, agreeableness, and conscientiousness; female sex; social class; and less physical disability. Personality predictors of attitudes to Psychological Growth were similar. In contrast, less affluent environment, living alone, lower vocabulary scores, and slower walking speed predicted more positive attitudes in this domain. Conclusions: Older people’s attitudes to aging are generally positive. The main predictors of attitude are personality traits. Influencing social circumstances, physical well-being, or mood may result in more positive attitudes. Alternatively, interventions to influence attitudes may have a positive impact on associated physical and affective changes. Key words: attitudes to aging, aging, personality, cognitive assessment, physical performance
Introduction Increases in longevity have led to widespread concern about the negative impact this may have on health and social care, and more widely on society. Some predictions of disproportionate Correspondence should be addressed to: Dr Susan D Shenkin, Geriatric Medicine, Room S1642, Department of Clinical and Surgical Sciences, The University of Edinburgh, Royal Infirmary of Edinburgh, 51 Little France Crescent, Edinburgh EH16 4SB, UK. Phone: +44-(0)131-242-6481; Fax: +44-(0)131242-6370. Email:
[email protected]. Received 25 Jun 2013; revision requested 29 Jul 2013; revised version received 14 Jan 2014; accepted 10 Feb 2014. First published online 13 March 2014.
burdens are so extreme as to have been termed “apocalyptic demography” (Martin et al., 2009), and are associated with a generally negative view of aging. Apocalyptic demography ignores the contributions that older people make to society and focuses on negative factors and stereotypes emphasizing decrepitude, decay, and the demand on resources. However, rates of disability are declining in comparison to previous cohorts of older people (Kinsella and Wan, 2009), and older people report high levels of life satisfaction and emotional well-being (Charles and Carstensen, 2009).
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Models for understanding the experience of aging Aging is a process rather than a state, and there is a great deal of heterogeneity in how people experience aging. Many studies of attitudes to aging do not seek the views of older people themselves; instead, they investigate perceptions of aging in the media or attitudes of younger people to aging (Abrams et al., 2009; Levy, 2009). Asking older people themselves about aging is important for understanding the experience of aging in a more accurate and nuanced way. The mechanisms by which individuals develop perceptions of themselves as older people are complex. Diehl and Werner-Wahl (2010) propose that the subjective nature of an individual’s experience of aging can be understood by reference to the concept of awareness of age related change (AARC; Diehl and Werner-Wahl, 2010). That is that a person only becomes subjectively aware of their personal experience of aging by perceiving that life has changed due to some consequence of aging. These changes attributed to age are perceived as either positive or negative (expressly not neutral). The subjective awareness of age-related changes may not necessarily align with objective change or chronological age. Levy (2003) suggests that agist societal attitudes internalized from a very young age and reinforced throughout adulthood can become negative age-stereotypes reinforced by an attentional bias towards negative information about aging. Stereotypes internalized during childhood and then reinforced during adulthood become selfstereotypes and this acts as a predisposing vulnerability for development of negative attitudes to aging. Consistent with AARC, Levy (2009) suggests that becoming aware of being “old” at the individual level is less to do with chronological age and is more likely a transitional process signaling a change from this being an external state to an attribute of the individual. Hence, the subjective view of the individual determines whether and when they see themselves as “old”. Stereotypes become embodied when the individual takes on the attributes associated with the stereotype as embedded within their self-view. Thus, aging, and the awareness of it, is a more complex, personal, and psychological process than was at first conceived. Attitudes to aging The assessment of attitudes to aging has been under-developed for many years, with the most frequently used measure being the “attitudes towards own aging” subscale of the Philadelphia
Geriatric Morale Scale (Lawton, 1975). This measure contains five items in total, which are unlikely to be able to give a comprehensive and upto-date account of a complex issue such as attitudes to aging. As gerontological models of aging suggest understanding this experience is more complex and multidimensional than previously thought there is a need for a more sensitive measure. The “Attitudes to Aging Questionnaire” (AAQ; Laidlaw et al., 2007) was developed as part of a large international project on the development of Quality of Life (QoL) tools for use with older adults in collaboration with the World Health Organization (WHO) to provide a standardized cross-cultural measure of an individual’s experience and attitudes to aging. Personality in later life Understanding aging as a personal experience, the character of an individual may have an important bearing on the way that people adapt to the negative and positive experiences associated with aging. Therefore, assessment of personality dimensions is an important consideration when understanding one’s attitude to aging. Within personality research, there is a consensus that much personality variation can be captured by five domains: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness (Costa and McCrae, 1992). Longitudinal follow-up evidence suggests mean levels of personality dimensions remain relatively stable over the life course (e.g. Roberts and DelVecchio, 2000), nevertheless there are still the opportunities for growth, change, and development across the lifespan (e.g. Mottus et al., 2012). However, there may be specific occasions when personality traits act as less stable descriptors, such as when a person’s mood is disturbed, as mood congruent biases may impair self-judgments. Thus, when assessing an individual’s attitudes to their own aging, one ought to take account of personality disposition (e.g. neuroticism and extraversion) and mood/affective state. Study aims and hypotheses We investigated life course associations with attitudes to aging in a large, well-characterized cohort of older people in the UK: the Lothian Birth Cohort of 1936 (LBC1936; Deary et al., 2007). These individuals have detailed information on cognition and health measured twice in later life (aged around 70 years and around 73 years). In addition, these individuals had general cognitive ability measured at age 11 years, providing the rarely available phenotype of life-time cognitive change. The availability of mental ability scores
Life course influences on attitudes to aging
many decades prior to the collection of the AAQ allows questions regarding life course predictors of outcomes in older age to be answered. The general aim of this study is to explore life course predictors of attitudes to aging. The objectives are: (a) to describe attitudes to aging in a community-dwelling sample of UK residents aged around 75 years; (b) to determine the relationship between attitudes to aging and their cognitive ability (measured aged around 70 and 11 years); (c) to determine the relationship between attitudes to aging and physical functional ability (measured aged around 70 years); and (d) to determine the relationship between attitudes to aging and other influences such as personality and mood.
Method Participants and general method The study sample was collected to follow up surviving members of the Scottish Mental Survey of 1947 (SMS1947; Deary et al., 2009) who reside in the Edinburgh area (Lothian) of Scotland. The SMS1947 applied a test of general intelligence to almost all children born in 1936 and attending Scottish schools on June 4th, 1947. The LBC1936 comprises 1,091 participants who were part of the original SMS1947 cohort, with participants generally in good health and living independently in the community (Deary, 2007). They are participating in a longitudinal study of cognitive aging, particularly exploring the importance of early life intelligence on later health (cognitive epidemiology). The present study used this cohort to investigate the influence of cognitive, physical, personality, and other factors across the life course on attitudes to aging in old age. Ethical approval for the LBC1936 was obtained from the Multi-Centre Ethics Committee for Scotland (MREC/01/0/56) and Lothian Research Ethics Committee (LREC/2003/2/29). The research was conducted in compliance with the Helsinki declaration. All participants gave written, informed consent.
Measures “Attitudes to ageing questionnaire” (AAQ) Development of the AAQ followed a coherent, logical, and empirical process taking full account of contemporary gerontological theory and both modern and classical psychometric analytical methods. Factor analysis and structural equation modeling were used in determining three distinct subscales for the AAQ: (1) Psychosocial Loss; (2) Physical Change; and (3) Psychological
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Growth. Each domain includes eight items. The Psychosocial Loss subscale measures the perceived negative experiences of aging and functions as a proxy for negative attitudes to aging where old age is seen primarily as a negative experience involving psychological and social loss. Physical Change focuses on items primarily related to health and the experience of aging itself, therefore a subjective individualized psychological perspective on health is assessed. Psychological Growth is explicitly positive and could be summarized as “Personal Wisdom” as it recognizes a lifespan development perspective on aging as viewed by the individual. Thus, the three-domain structure of the AAQ reflects both positive and negative aspects of aging, and asks questions relating to two aspects of aging: (i) that of a more general attitude component (i.e. attitudes to aging or being old in general); and (ii) a more personal experiential component (i.e. attitudes to the individual’s own experience of aging) from the perspective of the older people themselves (LucasCarrasco et al., 2013). This questionnaire, and the factor-analytic derived subscale structure, have been validated in Canadian and Norwegian samples of older people (Kalfoss et al., 2010). The 24 items of the AAQ scale are scored on a five-point Likert scale (1 = strongly disagree, 5 = strongly agree). All questions within each domain were asked in the same “direction”; i.e. all questions for Psychosocial Loss were in a “negative” direction (e.g. “Old age is a time of loneliness”), all questions for Physical Change in a “positive” direction (e.g. “I don’t feel old”), and all questions for Psychological Growth in a “positive” direction (e.g. “Wisdom comes with age”). Each factor has eight questions and is unit weighted. Therefore, the minimum score is eight (strongly disagree with all questions) and maximum score is 40 (strongly agree with all questions), with a total score of 24 indicating, on average, a neutral response over all questions, though this score could be achieved in other ways. General fluid-type cognitive ability (g) at age 70. A full description of the battery of cognitive tests and administration procedures is given in Deary et al. (2007). In this study, we used a composite cognitive score derived from principal components analysis (PCA) to represent general (fluid) cognitive ability. This was derived from a PCA of scores on six Wechsler Adult Intelligence Scale-IIIUK subtests (Wechsler, 1998): letter-number sequencing and digit span backwards (working memory), matrix reasoning (non-verbal reasoning), block design (constructional ability), digit symbol coding and symbol search (speed of information processing). The scree plot and eigenvalues suggested a single component could be extracted. The first unrotated component explained
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53% of the variance. All subtests had high loadings. Regression scores were calculated for the first unrotated principal component of the tests. We have used this method rather than individual test scores due to very small bivariate associations with individual tests scores and outcome variables, the large proportion of shared variance between cognitive tests, and that associations with cognition in an aging context are most often with this general component. Associations between individual test scores or cognitive domains and AAQ domains are available from the authors. Mini-Mental State Examination (MMSE; Folstein et al., 1975) is test of global cognitive function in wide clinical use that is simple to administer and takes about 10 minutes to complete. Scores above 27 (out of a possible 30) are considered “normal”. A score of = 24 who completed the AAQ. Descriptive statistics for demographic, cognitive, physical, and AAQ data are shown in Table 1. Characteristics of non-responders There were no statistically significant differences in sex, age, social class, education, cognitive, or physical variables between participants who participated in wave 2, but did not fully complete the AAQ (n = 23), and those who did (data not shown). Those who did not participate in wave 2 were more likely to be female and have a lower age 11 and 70 IQ, and lower grip strength (Deary et al., 2012). Attitudes to aging Cronbach’s α scores showed acceptable internal consistency within the subscales (Psychosocial Loss α = 0.80; Physical Change α = 0.77; Psychological Growth α = 0.75). Scores on all subscales are intercorrelated: Psychosocial Loss and Physical Change r = –0.45; Psychosocial Loss and Psychological Growth r = –0.36; Physical Change and Psychological Growth r = 0.46; ps: all < 0.001. There was a range of attitudes to aging reported, but in general attitudes in this cohort were in a positive direction. Note that items were scored on a Likert scale, with 1 = strongly disagree, 5 = strongly agree. A median score of 24 (neutral = 3, on each of eight items) would indicate a neutral attitude, consistent with Bryant et al. (2012). The Psychosocial Loss scale was positively skewed, with a median of 14 (I-Q range 12–18), indicating that most people disagree with statements such as “I
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Table 1. Descriptive statistics of demographics, cognitive, and physical tests at wave 1 testing of those who later completed the AAQ na
MEAN
SD
............................................................................................................................................................................................................................................................................................................................
Age (years) Age 11 IQ Age 70 IQ General cognitive factor (g) Crystallized intelligence (NART) 6-m walk time (sec) Grip strength right hand (kg) Attitudes to Aging Psychosocial Loss† Physical Change†† Psychological Growth†††
792 752 789 781 792 790 788
69.5 100.9 101.5 0.11 34.8 3.8 27.7
0.83 15.2 13.7 0.95 8.0 1.0 9.8
792 792 792
15.2 28.0 28.3
4.8 5.1 4.3
Years of education MMSE Townsend disability Anxiety (HADS-A) Depression (HADS-D) Childhood deprivation score Adult deprivation (SIMD)
792 792 792 791 789 791 785
Sex: male Adult SC: I II III-N III-M IV V Retired Living alone Own home HADS-A >= 8 HADS-D >= 8 Townsend >= 1
Total n 792 778
792 792 792 791 789 789
Median 10 29 0 5 2 −0.16 5,550
Inter-quartile range 10, 12 28, 29 0, 1 2, 7 1, 4 −0.38, 0.15 3,279, 6,270
n 407
% 51.4
150 295 174 132 22 5 763 191 732 137 31 270
18.9 37.2 22.0 16.7 2.8 0.6 96.3 24.1 92.4 17.3 3.7 34.2
SMS = Scottish Mental Survey; Adult SC = adult social class (I = Professional, II = intermediate, III-N = skilled non-manual, III-M = skilled manual, IV = semi-skilled manual, V = unskilled); NART (National Adult Reading Test) score = number correct; MMSE = Mini-Mental State Examination; HADS-A = Hospital Anxiety and Depression Score–Anxiety; HADS-D = Hospital Anxiety and Depression Score–Depression; g = general cognitive factors (see text); SIMD = Scottish Index of Multiple Deprivation (adult deprivation score: see text); SD = standard deviation. a Results: n = 792 except for some cognitive and physical tests (see table; non-completion of tests), and social class (n = 778) (missing data for people who had more than one substantive job in different social class categories). †Median = 14; †† Median = 28; ††† Median = 29.
see old age mainly as a time of loss”. Physical Change and Psychological Growth were more normally distributed, around medians of 28 and 29 respectively. This indicates that most people have a positive attitude to aging (agreeing with statements such as “My health is better than I expected for my age” and “I want to give a good example to younger people”). It should be noted that these summary group-level statistics do not reflect the full details of individual processes. There were statistically significant differences between men and women in scores on AAQ for Physical Change, Mann–Whitney U (df 792) =
85,092, z = 2.1, p = 0.036, with women having a more positive attitude to Physical Change (e.g. agreeing with “Growing older has been easier than I thought”). There were no sex differences in Psychosocial Loss, U (df 792) = 73,128.5, z = –1.6, p = 0.10, or Psychological Growth, U (df 792) = 78,143.5, z = –0.06, p = 0.95. Relationship between AAQ and cognitive ability: univariate analyses (Table 2) The univariate correlations (Table 2) show that there is a small to moderate, statistically significant
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Table 2. Univariate associations (Pearson’s r) between attitudes to aging and physical, cognitive, and social parameters PSYCHOSOCIAL LOSS PHYSICAL CHANGE PSYCHOLOGICAL GROWTH ............................................................................................................................................................................................................................................................................................................................
Age (years) g cognition NART 6-m walk time Grip strength Years of education Townsend’s disability Scale HADS anxiety score HADS depression score Childhood deprivation score Social class age (70 years) SIMD deprivation index age (70 years) NEO-FFI neuroticism NEO-FFI extraversion NEO-FFI openness NEO-FFI agreeableness NEO-FFI conscientiousness
0.014 − 0.130∗∗∗ − 0.060 0.180∗∗∗ 0.010 − 0.062 0.229∗∗∗ 0.292∗∗ 0.478∗∗∗ 0.051 0.059 − 0.036 0.382∗∗∗ − 0.329∗∗∗ − 0.125∗∗ − 0.272∗∗∗ − 0.294∗∗∗
− 0.062 0.127∗∗∗ 0.052 − 0.233∗∗∗ 0.007 0.070 − 0.284∗∗∗ − 0.169∗∗ − 0.337∗∗∗ − 0.097∗∗ − 0.069 0.016 − 0.228∗∗∗ 0.297∗∗∗ 0.176∗∗∗ 0.183∗∗∗ 0.250∗∗∗
− 0.004 − 0.065 − 0.175∗∗ 0.017 0.014 − 0.081 − 0.008 − 0.048 − 0.211∗∗∗ − 0.038 0.095∗∗ − 0.100∗∗ − 0.161∗∗∗ 0.318∗∗∗ 0.049 0.236∗∗∗ 0.315∗∗∗
∗∗ p
< 0.01; ∗∗∗ p < 0.001. For n see Table 1. NART (National Adult Reading Test) score = number correct; HADS-A = Hospital Anxiety and Depression Score–Anxiety. HADS-D = Hospital Anxiety and Depression Score–Depression; g = general cognitive factors (see text); SIMD = Scottish Index of Multiple Deprivation adult deprivation score (higher score equates to less deprivation: see text); NEO-FFI (Neuroticism-Extraversion-Openness-Five Factor Inventory). Direction of association: significant positive correlations with Psychosocial Loss indicate variables which are associated with agreement to statements regarding older age as a time of loss (i.e. in a negative direction); conversely, significant positive correlations with Physical Change and Psychological Growth indicate variables which are associated with agreement to statements regarding older age as a time of health or growth (i.e. in a positive direction).
correlation between higher scores on Psychosocial Loss (e.g. “Old age is a depressing time of life”) and lower g at age 70, but not NART. Physical Change (e.g. “I keep as fit and active as possible by exercising”) is significantly negatively associated with similar variables; i.e. in the opposite direction as this domain is worded in a positive direction, compared with Psychosocial Loss which is in a negative direction (Table 2). Participants scoring higher on the AAQ Physical Change domain have higher age 70 g. Correlations with Psychological Growth (e.g. “It is a privilege to grow old”) are slightly different compared with the other two AAQ dimensions. It is associated with lower NART, and not statistically significantly associated with age 70 g. Relationship between AAQ and physical ability: univariate analyses (Table 2) Psychosocial Loss is associated with slower 6-m walk time, functional limitation (i.e. more disability: score of one or more, rather than zero on the Townsend scale). Higher scores on Physical Change are associated with quicker 6-m walk time and the absence of functional limitation (score of zero, rather than one or more on the Townsend scale).
Scores on Psychological Growth are not associated with physical disability. Relationship between AAQ and other factors – (i) personality and mood; (ii) socioeconomic environment: univariate analyses (Table 2) Psychosocial Loss is significantly (p < 0.001) associated with higher anxiety and depression scores as measured by the HADS scale, and NEOFFI personality traits (higher neuroticism, and lower extraversion, openness, agreeableness and conscientiousness), but not with current or prior socioeconomic environment. Higher Physical Change scores were correlated with lower anxiety and depression scores (HADS), and personality (lower neuroticism, higher extraversion, openness, agreeableness and conscientiousness). Physical Change was associated with less childhood deprivation, but not with current socioeconomic environment. Higher scores on Psychological Growth are associated with lower depression scores and personality (lower neuroticism, and higher extraversion, openness, agreeableness and conscientiousness. Psychological Growth is not associated with childhood deprivation, or anxiety scores. Unlike other domains, Psychological Growth is associated
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Table 3. Results of hierarchical multiple regression analyses predicting attitudes to aging PSYCHOSOCIAL LOSS
n
p
R2
PHYSICAL CHANGE
n
p
R2
PSYCHOLOGICAL GROWTH
n
p
R2
.........................................................................................................................................................................................................................................................................................................................
Model 1 Model 2 Model 3 Model 4
770 759 752 655
0.044
