Five years from now: correlates of older people's expectation of future quality of life.

Article

Five Years From Now: Correlates of Older People’s Expectation of Future Quality of Life

Research on Aging 2015, Vol. 37(1) 18–40 ª The Author(s) 2014 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0164027513520329 roa.sagepub.com

Kevin J. McKee1, Johan Kostela2, and Lena Dahlberg1,3

Abstract Few studies have explored older people’s expected future quality of life (QoL), despite evidence that perceptions of one’s future influence healthy aging. Research on this topic should embrace a range of potential influences, including perceptions of one’s neighborhood and region. This study examined expected QoL in a random sample of the population of Dalarna, a Swedish region. A self-completion questionnaire assessed demographic characteristics, current neighborhood and regional evaluations, self-evaluations, expectations for the future, and current and expected QoL. In total, 786 people aged 65 years participated. A sequential multiple regression model explained 44% of the variance in older people’s expected QoL, with selfreported health (sr2 ¼ .03), Expected Regional Opportunity (sr2 ¼ .03), and Perceived Regional Status (sr2 ¼ .02) having the strongest associations with expected QoL. Research on the importance of one’s neighborhood to QoL in older people should encompass people’s perceptions of their region, to better inform social policy for healthy aging.

1

School of Health and Social Studies, Dalarna University, Falun, Sweden Dalacampus, Dalarna University, Falun, Sweden 3 Aging Research Center, Karolinska Institutet/Stockholm University, Stockholm, Sweden 2

Corresponding Author: Kevin J. McKee, School of Health and Social Studies, Dalarna University, 791 88 Falun, Sweden. Email: [email protected]

Downloaded from roa.sagepub.com at UCSF LIBRARY & CKM on March 9, 2015

McKee et al.

19

Keywords older people, quality of life, expected quality of life, social influence, place attachment, neighborhood context With more older people living longer, policy is being directed to providing the social environments and resources to sustain healthy aging in the older population. Research evidence on the determinants of a good quality of life (QoL) in later life is essential for the development of such policy. Research to date has focused on both the fundamental domains or dimensions of QoL and what factors older people see as contributing to their QoL. Less research has examined people’s expectations of what their QoL might be in the future or on what factors might be linked to such expectations. This article explores, in a sample of community-resident older people, the demographic, personal, and social factors linked to expectations of future QoL.

QoL in Later Life There has been a growing emphasis on the need to understand what influences older people’s QoL, as it is argued to be of greater value as an outcome measure in this population than traditional outcome measures, such as health status (Farquhar, 1995). While physical health is widely regarded as important for QoL, other domains theorized as integral to QoL are psychological well-being, social relationships, and the physical environment (The WHOQOL Group, 1998). Research suggests that, in comparison to younger age-groups, older people’s QoL is more closely linked to issues such as health, independence, and mobility, and less to social life and (unsurprisingly) work and work relationships (McKee et al., 2005). Whether these differences are cohort effects, or reflect ontological change, is not well understood. QoL research can be divided into two broad categories: First, research that is concerned with macro-level societal indicators or indexes of QoL in populations (Boarini, Johansson, & Mira d’Ecole, 2006); and second, research concerned with micro- and meso-level indicators of individual QoL. Within this second category, some work focuses on the importance of the physical environment for QoL (Parker et al., 2004), while other work concentrates on the influence of social relationships or factors such as personality or psychological health (Litwin, 2010; Seymour et al., 2008). It is rare to find QoL research that tries to examine a wide range of factors in a single study, encompassing the physical and social environment and personal


20

Research on Aging 37(1)

relationships and activities. The importance of place, and its meaning for the individual, is also relatively neglected in QoL research. Yet neighborhood has been shown to be associated with mental health in old age (Gale, Dennison, Cooper, & Sayer, 2011; Kubzansky et al., 2005; Wight, Ko, & Aneshensel, 2011), and place is of particular importance for an older person’s QoL (Gilleard, Hyde, & Higgs, 2007; Peace, Holland, & Kellaher, 2005). Many older people will have lived for a long period of their lives in the same area (Phillips, Siu, Yeh, & Cheng, 2005), if not in the same house; will spend comparatively more time in the immediate neighborhood than younger people; are more dependent on the social relations in the community for support; and have strong emotional investments in their surrounding community (Buffel, Phillipson, & Scharf, 2013; Cannuscio, Block, & Kawachi, 2003). Social policy reflects the wishes of many older people themselves that they should ‘‘age in place,’’ that is, that they should remain in their own home and community even when faced with increased frailty (Gardner, 2011; Smith, 2009). However, for older people facing the challenges of decreasing physical and mental capacity, a tension exists around the amount of time left for them to remain in their current dwelling before a move to a more supportive environment is required (Caro et al., 2012). To the extent that the association between place and QoL has been studied, focus has been placed on the residential environment and local community rather than the region (Lewicka, 2011). Yet work has shown that people in general and older people in particular can have a strong sense of regional belonging, sometimes greater than their sense of belonging to the town in which they live (Gustafson, 2009; Laczko, 2005). More research is required that engages with locality on a broader level than a person’s immediate neighborhood, to determine the extent to which perceptions of a region are connected to QoL

Expected Future QoL and Healthy Aging Promoting an enhanced perception of QoL in an older person can be seen not only as an objective in itself but also as a potential way to support healthy aging and postpone health declines. This is because a person’s psychological state is known to profoundly influence health, both through physiological or immunological routes (Tsuboi et al., 2005; Uchino, Cacioppo, & KiecoltGlaser, 1996) and through the role played by psychological factors in the maintenance of behaviors that are supportive of health (Zimmerman & Vernberg, 1994).


McKee et al.

21

In so far as people’s expectations have been widely demonstrated to shape current and future affect and behavior (Fishbein & Ajzen, 2010), a person’s expectation of what QoL he or she will experience in the future can be hypothesized to also influence his or her health. Maintaining an expectation of a positive QoL in the future might be challenging in late life, where the changes in health, functioning, and social relationships that may accompany aging can increase the salience of negative outcomes such as one’s functional limitations (Cate & John, 2007). Yet expectation of a poor future QoL could be anticipated to be a barrier for healthy aging, as continuing to generate positive life goals is theorized to be an essential feature of aging successfully (Baltes, Lindenberger, & Staudinger, 1996; Ebner, Freund, & Baltes, 2006; Freund & Baltes, 1998). Empirical work has shown that sustaining goal pursuit in later life has beneficial motivational and broader psychological effects (Frazier, Newman, & Jaccard, 2007). Furthermore, a diverse range of studies point to a positive engagement with the future as being a factor in good health and well-being in older people: Ouwehand, de Ridder, and Bensing (2006) found a future time orientation in older people was important for well-being; Prenda and Lachman (2001) found that planning for the future predicted life satisfaction, with the effect strongest in older adults and mediated by perceived control; and Lawton, Moss, Winter, and Hoffman (2002) showed that the maintenance of personal projects in older people was linked to positive affect. However, not all research evidence indicates that a positive view of one’s future is beneficial in older adults. A recent longitudinal study found that for older people being overly optimistic about one’s future life satisfaction is predictive of a greater risk of disability and mortality, while underestimating one’s future life satisfaction is predictive of positive health outcomes (Lang, Weiss, Gerstorf, & Wagner, 2013). According to socioemotional selectivity theory (Carstensen, 1993; Carstensen, Isaacowitz, & Charles, 1999), as people age their future time perspective diminishes, leading them to selectively focus on goals and activities that are more emotionally meaningful. Prioritizing such goals and activities has been found to be associated with higher levels of social satisfaction and reduced strain with others (Lang & Carstensen, 2002). It may be that older people who are overly pessimistic about their future QoL are the most highly motivated to adapt their goals and activities, leading to unanticipated increases in QoL through, for example, emotionally more meaningful relationships that might arise as a consequence of their adaptation. Pessimism may also work to improve health through increasing the motivation to adopt healthmaintaining behaviors (Lang et al., 2013).


22


The Present Study Expectations in an older person of a poor QoL in the future might be an indicator of an increased use of health and social services over time or a change in housing needs. Knowledge of older people’s expectation of future QoL can thus help managers of social and health care budgets to anticipate future patterns of behavior and health and plan resources accordingly. Furthermore, understanding how expectations of future QoL are linked to perceptions of one’s current social milieu might provide an opportunity to augment or enhance those social resources identified as important, in turn enhancing expectations of future QoL. This article reports a study of community-resident older people in Dalarna, Sweden, in which their perceptions of their current living conditions and social environment were sought, together with their expectations of their future, 5 years ahead. The analyses reported in this article focus on identifying the most important contributors to expectations of future QoL, and our research questions were: Are perceptions of one’s current living conditions and the local and wider social environment significant in a model of expected QoL, after the effect of current QoL is controlled? Do perceptions of one’s neighborhood and region remain significantly associated with expected QoL, after self-evaluations and future expectations are added to the model? Do perceptions of one’s neighborhood or perceptions of one’s region explain most unique variance in expected QoL?

Method Design and Sampling The study design comprised a cross-sectional survey of a stratified random sample of the population of Dalarna. Dalarna is a rural region in the middle of Sweden with a population of approximately 275,000. A third of the population live in towns, but only two of the towns have more than 35,000 inhabitants. The region has 15 municipalities, of which the 2 most populated are situated approximately 140 miles northwest of Stockholm. The population of Dalarna is slightly older than the average for Sweden, with fewer young adults (20–30 years) due to migration. The main industries in the region have traditionally been steel, forest, and mining. There is also a strong manufacturing industry in the region, and the tourist industry is also well represented.


McKee et al.

23

The sample was provided by the National Tax Authority via the County Council. Sampling was stratified by municipality. Only one individual was sampled per household, and only those people living in the community were eligible for the study (i.e., excluding people in long-term care settings). A total sample of N ¼ 3,000 was proposed and with an anticipated response rate of 60%, which indicated a survey of approximately 5,000 inhabitants. Due to the intention to perform analyses on subgroups (e.g., municipalities), there was oversampling to ensure adequate sample size within the smaller municipalities. In total, 2,983 people participated in the survey (aged 18–80 years), representing a response rate of 52.7% of the 5,660 sent a questionnaire. Of the respondents, older people (age 65 years, the group on which the analyses described subsequently were performed) comprised 26.3% (n ¼ 786). The response rate for this age-group was 66.4%, slightly higher among men compared to women, but with little variation across municipalities. The educational level for this group of respondents was a little bit lower than the average in Dalarna, but the age distribution of respondents matched the population distribution well.

Measures A questionnaire was developed by the research team in collaboration with the Regional Development Council of Dalarna County. Due to the uncommon focus of the study, there was a lack of appropriate validated measures in Swedish, and many of the items used in the study were therefore developed by the research team. The requirement to cover a broad range of issues together with the need to maximize the response rate by limiting the length of the questionnaire drove the development of brief measures or single items to assess domains of interest. The items used in the study and relevant to the present article are described in detail subsequently. Where items assessed similar domains and responses were consistently scaled, a process of scale development was undertaken utilizing principle components analysis and reliability (Cronbach’s a) analyses with item trial removal, in order to combine items into a series of scales.1 Demographic characteristics. The questionnaire contained items addressing demographic characteristics such as age (derived from date of birth); gender; place of birth (current municipality, elsewhere in Dalarna, elsewhere in Sweden, elsewhere in Nordic countries, other country specified, the last three categories were combined for analysis), current place of residence (in or near town, in or near village, isolated), years at current residence (categorized as


24


up to 10 years and 10 years or more), household composition (coded for analysis as married or cohabiting, other), gross annual household income (a 5-point scale from less than 200,000 Swedish kronor (SEK) to more than 750,000 SEK, and the last 3 scale points were combined into more than 300,000 SEK for analysis), house size (up to two rooms, three to four rooms, five rooms or more, the first two categories were combined for analysis), and education level (coded for analysis as basic school education, higher school education, and tertiary/university education). Current local and regional evaluations. This section of the questionnaire contained a series of items that required participants to rate the quality of their locality and region across a range of characteristics. The first question asked ‘‘From your place of residence, what are the possibilities for you to access or take part in the following cultural, recreational, and outdoors facilities or activities?’’ Ten facilities/activities were listed, including a cinema, a library, shopping, water features, beautiful town environment, and so on. For each of the facilities/activities, the participant provided a rating on a 5-point scale from very good to very bad. Participants were then asked for the same facilities/activities ‘‘How important is it to you that the following facilities or activities are available in or around your place of residence?’’ with a 5-point rating scale from very important to very unimportant. The 10 items produced two components, labeled Culture Evaluation and Nature Evaluation, on both the availability and importance ratings. The summed products of the availability and importance ratings were then considered as potential subscales: Culture Evaluation, 7 items, a ¼ .91; and Nature Evaluation, 2 items, a ¼ .70. Mean scale values were used in subsequent analyses in order to retain cases. The next question asked ‘‘From your place of residence, what are the possibilities for you to access or utilize the following services or resources?’’ Fourteen services/resources were listed, including a nursery, high school, hospital, police, church, petrol station, and so on. For each of the services/ resources, the participant provided a rating on a 5-point scale from very good to very bad. Participants were then asked for the same services/resources ‘‘How important is it to you that the following services or resources are available in or around your place of residence?’’ with a 5-point rating scale from very important to very unimportant. The 14 items produced two components, labeled Public Services Evaluation and Education Services Evaluation, on both the availability and importance ratings. The summed products of the availability and importance ratings were then considered as potential subscales: Public Services Evaluation, 10 items, a ¼ .89; Education Services


McKee et al.

25

Evaluation, 4 items, a ¼ .95. Mean scale values were used in subsequent analyses in order to retain cases. However, due to the large number of missing cases on Education Services Evaluation, this scale was not carried forward for further analysis. Next, the participants were required to indicate their agreement or disagreement on 5-point scales, from strongly agree to strongly disagree, with four statements about their neighborhood: ‘‘I like the neighbourhood in which I live’’; ‘‘The neighbourhood in which I live is good for children’s development’’; ‘‘Social contact with local people is good’’; and ‘‘I believe the neighbourhood in which I live is secure and safe.’’ The 4 items were combined to form a scale, Neighborhood Evaluation (a ¼ .71). A further question asked participants to indicate their agreement or disagreement on 5-point scales, from completely agree to completely disagree, with eight statements about their municipality and region. Four statements addressed their municipality (e.g., item: My municipality offers good care for older people), while 4 items addressed potential routes for regional development (e.g., item: Increasing equality is good for the development of Dalarna). The 4 items concerning the municipality were combined to form a scale, Municipality Evaluation (a ¼ .79); while the 4 items concerning regional development were combined to form a scale, Regional Development Beliefs (a ¼ .62). Two final items asked for the participant’s perceptions on how other people viewed their region: ‘‘How do you think people in other parts of Sweden view Dalarna?’’ and ‘‘How do you think people in Dalarna view the region?’’ Both items were rated on 5-point scales from very positive to very negative. The 2 items were combined to form a scale, Perceived Regional Status (a ¼ .61). Self-evaluations. Participants were asked ‘‘How is your current general health?’’ ‘‘How is your social life in general?’’ and ‘‘In general, how would you describe your quality of life?’’ all rated on 5-point scales from very good to very bad. A fourth item asked ‘‘What possibilities do you have to influence your community and your everyday life?’’ rated on a 5-point scale from very great to very small. Future expectations. Three items asked the participants to rate their expectations for the future of their region, on 5-point scales from very good to very bad. A general premise asked ‘‘How do you evaluate the future for Dalarna in the next five years with regard to . . . ,’’ with three roots: ‘‘attractive housing?’’ ‘‘access to work and career opportunities?’’ and ‘‘educational


26


development opportunities?’’ The 3 items were combined into a scale, Expected Regional Opportunity (3 items, a ¼ .71). A further item on expected change in housing need asked ‘‘How large a house do you think you will need in five years’ time?’’ with response options ‘‘The same as I have now,’’ ‘‘Larger than I have now,’’ ‘‘Smaller than I have now,’’ and ‘‘Unsure.’’ These response options were recategorized for analysis into ‘‘No change in housing need’’ (original first response option) and ‘‘Possible change in housing need’’ (original last three response options). A final item asked, ‘‘Five years from now, in general how do you see your quality of life?’’ rated on a 5-point scale from very positive to very negative.

Procedure All individuals identified via the random sampling process described earlier were sent a questionnaire for self-completion, with a covering letter enclosed in the same envelope. The letter described the study, provided background information on its origin and purpose, and indicated that each questionnaire was numbered so that the identity of the respondent could be ascertained via a returned questionnaire. The letter also outlined issues related to how the data would be handled, stored, and the potential for publications based on the data collected. In line with standard ethical protocol (Vetenskapsra˚det, 2002), returned completed questionnaires were held to constitute informed consent on the part of the respondent to participate in the study. Two weeks after the initial questionnaire had been distributed, those individuals who had not returned their questionnaire were sent a reminder letter. No further reminders were sent.

Data Analysis Data were analyzed using the Statistical Package for Social Science (SPSS) 20.0 for Windows. All items/scales were recorded where necessary so that high scores were a reflection of high levels or positive evaluations of the measured construct. Descriptive statistics were generated for each variable. Bivariate analysis was performed to identify associations between the dependent variable (DV; expected QoL in 5 years’ time) and independent variables (IVs), and the level of significance set at p < .05. No adjustment to experimental a was made for multiple testing, and so note should be taken of the potential for inflated Type I error rate. Taking into account also the study’s substantial sample size, significance tests should be interpreted cautiously and with reference to the relevant effect size.


McKee et al.

27

Sequential multiple regression was performed to determine the prediction of expected QoL in 5 years’ time (DV) from those IVs having significant bivariate association with the DV. Due to the substantial sample size inflating the potential for Type I error, and in order to promote a parsimonious model, the level of significance for bivariate associations allowing entry to the model was set at p < .01.2 IVs were entered in blocks, order of entry determined by a theoretical framework positing distal (demographic and environmental) variables, and current evaluations would impact less than proximal (self) variables and future evaluations. Evaluation of current QoL was entered as the first IV to determine the level of additional contribution made by other IVs to expected QoL. Order of entry of variables after current QoL was demographic variables, current local and regional evaluations, selfevaluations, and future expectations. Assumptions related to multivariate analysis, including normality, linearity, and homoscedasticity of residuals, multicollinearity, and the influence of multivariate outliers, were examined and found to be met.

Results Descriptive Analyses Participants’ responses to the questionnaire items relating to demographic characteristics are presented in Table 1. Participants’ mean age was 71.35 (standard deviation ¼ 4.50, range 65–80), with the sample consisting of slightly more males (50.5%) than females. Just under two thirds of the sample had been born within Dalarna, with most (56.9%) living in or near a town and the large majority (83.0%) having lived in their current residence for 10 years or more. Just over half (55.0%) of the sample lived in a house with five rooms or more, while just over a third (38.6%) had a gross annual household income of less than 200,000 SEK and just over two thirds (69.0%) had basic school education. Nearly three quarters of the sample (74.2%) was married or cohabiting. With regard to the relationship between the assessed demographic characteristics and expected QoL, there were significant associations between higher expected QoL and lower age, r(764) ¼ .16, p < .001, larger house size, rb(754) ¼ .15, p < .005, being married/cohabiting, rpb(736) ¼ .09, p < .05, greater household income, rs(728) ¼ .16, p < .001, and higher education level, rs(729) ¼ .19, p < .001.3 Gender, place of current residence, place of birth, and duration of local residence were not significantly associated with expected QoL.


28


Table 1. Participants’ Demographic Characteristics. Characteristic

%

Age (n ¼ 786) 65–69 years 70–74 years 75–80 years Gender (n ¼ 786) Female Male Place of birth (n ¼ 775) Current municipality Elsewhere in Dalarna Outside region Current place of residence (n ¼ 691) In or near town In or near village Isolated Years at current residence (n ¼ 704) Up to 10 years 10 years or more Household composition (n ¼ 759) Married or cohabiting Other House size (n ¼ 778) Up to four rooms Five rooms or more Household income (n ¼ 746) Less than 200,000 Swedish kronor Between 200,000 and 300,000 Swedish kronor More than 300,000 Swedish kronor Education level (n ¼ 748) Basic school education Higher school education Tertiary/university education

40.2 31.9 27.9 49.5 50.5 39.2 22.3 38.5 56.9 38.6 4.5 17.0 83.0 74.2 25.8 45.0 55.0 38.6 34.6 26.8 69.0 12.4 18.6

Current local and regional evaluations and self-evaluations. Responses to the items and scales assessing current local and regional evaluations, self-evaluations, and future expectations are presented in Table 2, together with the bivariate associations between the study variables and current and expected QoL. The participant’s responses on the whole indicate a favorable evaluation of their immediate neighborhood and wider region, with most mean values being at or above the respective item and/or scale midpoints. Self-reported


McKee et al.

29

Table 2. Study Variable Means, Standard Deviations, and Correlations With Quality of Life. Quality of life Current Expected Variable

n

Culture Evaluation Nature Evaluation Public Service Evaluation Neighborhood Evaluation Municipality Evaluation Regional Development Beliefs Perceived Regional Status Self-reported health Social life Social influence Expected Regional Opportunity Expected change housing need Quality of life Expected quality of life

676 652 660 775 756 754 765 776 777 765 743 771 775 762

Min Max 1 1 1.67 1 1 1 1 1 1 1 1 1 1 1

25 25 25 5 5 5 5 5 5 5 5 2 5 5

M

SD

13.01 18.56 14.64 4.40 3.72 4.13 4.06 3.92 4.16 2.39 3.52 1.39 4.26 3.60

5.32 5.12 4.26 0.56 0.63 0.62 0.56 0.82 0.72 0.94 0.58 0.49 0.71 0.77

r .20 .22 .13 .41 .26 .20 .20 .59 .62 .23 .26 .20a — .46

.23 .21 .13 .31 .34 .26 .34 .47 .42 .27 .41 .19a — —

Note. M ¼ mean; SD ¼ standard deviation. All tabulated correlations p < .01. a Biserial correlation coefficient; mean scale values computed and presented in order to retain cases.

health and social life were both positively evaluated, whereas the mean value for social influence was only marginally above the scale midpoint. All the assessed variables had significant bivariate associations with expected QoL, the size of the associations ranging from .13 for Public Service Evaluation to .47 for self-reported health. Current QoL was also favorably evaluated, and while expected QoL also received a positive assessment, the mean value for expected QoL was notably lower than that for current QoL, t(755) ¼ 24.06, p < .05. Indeed, only 3.6% (n ¼ 27) of the participants rated their expected QoL higher than their current QoL. We grouped our participants into those whose expected QoL was rated higher than or equal to their current QoL (QoL stable or will improve), and those who rated their expected QoL lower than their current QoL (QoL will get worse) and explored the associations between this categorical variable and the assessed demographic variables. The variable was associated with one demographic characteristic, that is, years at current residence: Participants in the ‘‘QoL stable or will improve’’ group had a higher


30


than expected representation in the group of participants who had lived less than 10 years at their current residence (f ¼ .10, p < .01).4

Multivariate Analyses All IVs with bivariate association with expected QoL at p < .01 were entered into a multiple regression (of those IVs with association with expected QoL at p < .05, only household composition failed to meet this more stringent model entry criterion). Due to listwise deletion of missing values, the final sample for the model was n ¼ 557. Table 3 displays the unstandardized regression coefficients (B), standard error of B, and the standardized regression coefficients (b) after entry of all IVs in the model predicting expected QoL. R was significantly different from zero at the end of each step. After Step 5, with all IVs in the equation, R ¼ .66, F(17, 539) ¼ 24.73, p < .001. After Step 1, with only current QoL included, R2 ¼ .237, Finc(1, 555) ¼ 172.2, p < .001. After Step 2, with demographic variables added, R2 ¼ .263, DR2 ¼ .0026, Finc(5, 551) ¼ 39.3, p < .005. After Step 3, with current local and regional evaluation variables added, R2 ¼ .349, DR2 ¼ .0086, Finc(12, 544) ¼ 24.3, p < .001. After Step 4, with the self-evaluation variables self-reported health, social life, and social influence added, R2 ¼ .407, DR2 ¼ .0057, Finc(15, 541) ¼ 24.7, p < .001. After the final Step 5, with expected change in housing need and Expected Regional Opportunity variables added, R2 ¼ .438, DR2 ¼ .032, Finc(17, 539) ¼ 24.7, p < .001. Thus, there was a significant increment in R2 at each step in the model. Nine IVs were significant in the final model of expected QoL, with the unique variance explained by each of the these IVs in expected QoL (indicated by the semipartial correlation coefficient) as follows: current QoL (sr2 ¼ .01), age (sr2 ¼ .01), education level (sr2 ¼ .01), Regional Development Beliefs (sr2 ¼ .01), Perceived Regional Status (sr2 ¼ .02), self-reported health (sr2 ¼ .03), social influence (sr2 ¼ .01), Expected Regional Opportunity (sr2 ¼ .03), and expected change in housing need (sr2 ¼ .01).

Discussion Main Findings The model developed in the current study successfully predicted older people’s expectations of their future QoL. The final model explained nearly 44% of the variance in expected QoL, with each component of the model explaining a significant amount of variance. Older people’s perception of their


McKee et al.

31

Table 3. Sequential Multiple Regression of Expected Quality of Life in 5 Years’ Time. Variable Quality of life Age House size Household income Education level Culture Evaluation Nature Evaluation Public Services Evaluation Neigborhood Evaluation Municipality Evaluation Regional Development Beliefs Perceived Regional Status Self-reported health Social life Social influence Expected Regional Opportunity Expected change housing need

B

SE B

b

.18 .01 .06 .03 .09 .01 .03 .01 .06 .07 .11 .20 .20 .08 .06 .25 .12

.052 .006 .057 .035 .032 .006 .005 .008 .052 .051 .045 .044 .039 .047 .028 .050 .055

.16* .09* .04 .03 .10* .05 .02 .07 .04 .06 .09* .15* .21* .07 .08* .19* .08*

Note. n ¼ 557. SE ¼ standard error. R2 ¼ .237 for Step 1; DR2 ¼ .0026 for Step 2; DR2 ¼ .0086 for Step 3; DR2 ¼ .0057 for Step 4; and DR2 ¼ .032 for Step 5; (ps < .05). *p < .05.

current QoL explained 23.7% of the variance in expected QoL. Controlling for current QoL, demographic characteristics explained a further 2.6% variance, adding current local and regional evaluations to the model explained 8.6% additional variance, while self-evaluations explained an additional 5.7%. The final component of the model, future expectations, explained 3.2% additional variance in expected QoL. These findings provide positive answers to our first two research questions, in that older people’s perceptions of their current living conditions and their local and wider social environment were indeed significantly associated with expected QoL, even after the effect of current QoL was controlled; and that older people’s perceptions of their neighborhood and region remained significantly associated with expected QoL, after self-evaluations and future expectations are added to our model. Current and future QoL. As researchers on habit and the prediction of behavior will acknowledge, there is a well-established stability to any given individual’s behavior such that having information about that person’s past behavior


32


provides a good insight into that person’s likely future behavior (Triandis, 1977). Researchers exploring attitude change will also testify that attitudes toward ourselves and others can be resistant to change; indeed, built into the concept of an attitude is the notion that it is something enduring (Petty & Cacioppo, 1996). A consistency in how individuals evaluate their QoL is therefore to be expected. Indeed, one of the issues with the measurement of QoL is that as an outcome measure for health interventions and treatments, it is remarkably insensitive: Despite major changes in physical and mental health, an individual’s rating of his or her QoL can vary very little; and when there is variation, over time the rating will often return to the original rating (Hatton, 1998). Research has found that older people’s predictions of their future life satisfaction show more ‘‘temporal realism’’ than do the predictions of young and middle-aged adults, in that the prediction is closer to the actuality (Lachman, Rocke, Rosnick, & Ryff, 2008). Thus, it was to be expected that our participants’ rating of their current QoL would be a strong indicator of their expectations of their future QoL. Only a small minority of our participants (3.6%) had a higher rating for their expected QoL than for their current QoL. This finding is in keeping with other studies that have demonstrated that while young adults have an expectation that life satisfaction will improve, older adults’ expectations decline (Lachman et al., 2008). Age itself was significant in the final model of expected QoL, with greater age associated with expectations of poorer QoL in 5 years’ time. Other work has found that age is the key sociodemographic factor in terms of determining the ratings of life satisfaction over time (Rocke & Lachman, 2008). The fact that our study examines a sample of people in later life might partly explain why so many factors were linked to expectations of future QoL: With aging come physical, mental, and social changes that can be powerfully salient when making judgments about the future, about one’s place in and requirements for that future. For example, self-reported health was a particularly strong predictor of our participants’ ratings of their expected QoL, with poorer self-reported health associated with expectations of poorer future QoL. While subjective well-being, an important part of QoL, remains relatively stable as people age, health constraints have been found to lead to decrements in subjective well-being in a way that aging per se does not (Kunzmann, Little, & Smith, 2000). We also found that older people who indicated a possibility of change in their housing needs in the future scored lower on expected QoL. The changes that come with aging impact on housing need, and factors such as place of residence and the informal and formal support available may influence an older person’s views on whether to


McKee et al.

33

relocate (Tang & Lee, 2011). The perception by an older person that his or her current housing may not fit his or her needs in the near future may be both a strong signifier of personal aging and a negative influence on his or her current well-being and expectations of future well-being. Of interest is the fact that our participants’ rating of their social life was not associated with expected future QoL, whereas perceived social influence was. Social engagement is regarded as a central aspect of healthy aging, although current conceptualization of social engagement is weak, with various overlapping concepts promoted as key contributors to healthy aging (FUTURAGE Group, 2011). Our findings suggest that older people’s expected QoL is linked more to their perceived social power than to their social activities and that this might be an important distinction to make when developing policy to promote healthy aging. Other research has confirmed that exclusion from political participation has an influence on aspects of older people’s well-being, for example, perceptions of safety (De Donder, De Witte, Buffel, Dury, & Verte´, 2012). Finally, our study finding that higher levels of education are associated with higher expected QoL is consistent with other research that has shown education level to be predictive of QoL in older people, even when controlling for current or recent circumstances (Seymour et al., 2008). The pathways by which education exerts its effect on QoL are varied, and our study suggests that education may partly influence QoL through its association with positive expectations of the future, at least in later life. The importance of place for the individual. Much research into QoL reflects an individualistic or relational perspective, with emphasis on psychological and interpersonal factors. It is much rarer for QoL research to attempt to contextualize the individual within a locality or region and relate that wider context to the individual’s QoL. Our findings suggest that this is a limitation of much research, as our participants’ perception of their region, both the current and the future, informed their expectations of their future QoL. In this context, the research on place attachment, involving the attempt to define the concepts of community and neighborhood and their meaning for older people, can be seen to be of great importance (Peace et al., 2005; Peace, Wahl, Mollenkopf, & Oswald, 2007). In our study, older people’s expectation of their future QoL was more positive when they also had more positive expectations for the future of their region, where they thought people both within and outside their region viewed their region positively, and where their beliefs about their region were more socially progressive. Our final research question asked whether it was older people’s perceptions of their


34


neighborhood or their perceptions of their region that explained most unique variance in expected QoL. In our final model, while regional evaluations contributed significantly to participants’ expected QoL, our measures of neighborhood and municipality did not. Thus, while measures that explored participants’ evaluation of culture and nature in their locality, and perceptions of local public services, were related to expected future QoL in bivariate analyses, in the multivariate analyses such measures became nonsignificant. It may be that some factors related to the environment and one’s sense of place have a stronger relationship to current QoL than to expected QoL (compare, e.g., the coefficient for the relationship between Neighborhood Evaluation and current QoL with that between the same variable and expected QoL, as displayed in Table 2) and that in a multivariate model, the former relationship mediates much of the effect of the latter relationship. Work investigating perceptions of the region or regional identity is limited, although such factors do overlap with some of the indicators of social capital that have been used in recent research (cf. De Donder et al., 2012; Elgar et al., 2011). The relative importance to an older person’s QoL of region compared to neighborhood that was found in our study is not found elsewhere. One international study found that, in general, attachment to one’s region is not as great as that to one’s country or neighborhood, although greater than that to one’s town (Laczko, 2005). This was the pattern for the Swedish sample in the study and also the pattern in a separate study carried out in Sweden (Gustafson, 2009). Nevertheless, our findings would suggest that (a) research that demonstrates a relationship between particular aspects of the environment and elements of QoL might overestimate the strength of the relationship if other aspects of the environment are not controlled for in the analyses and (b) research that focuses on older people’s immediate physical and social environment, such as their home and neighborhood, might be overestimating the importance of such local contexts for the well-being of older people if measures of the wider social environment, such as perceptions of the region or regional identity, are also not accounted for.

Study Limitations It is wise to acknowledge that the current data are drawn from one particular region of Sweden and that the finding of the significance of the region for our participants’ QoL might reflect something particular to this milieu and its inhabitants. Furthermore, due to missing data, the sample for our regression model was considerably reduced compared to the original sample. An


McKee et al.

35

analysis of the differences between the retained and lost groups in our sample indicate that, in comparison to the retained group, the group lost is older (d ¼ .42), has a lower income (d ¼ .54), a lower education level (d ¼ .40), a lower current QoL (d ¼ .28), and a lower expected QoL (d ¼ .25).5 Thus, the excellent representative quality of the original sample is somewhat reduced. Nevertheless, the strength of the relationship—even after controlling for a range of other factors—would at the very least indicate a finding worth full consideration and an attempt at replication elsewhere, optimally where models for expected future QoL can be compared between differing regions. The crosssectional nature of the study also brings with it several limitations, the most significant of which is that it precludes any conclusions about direction and causality in the relationships detected. Thus, we have interpreted our findings as suggesting that perceptions of the locality and region affect expected QoL, but equally one’s expectation of future QoL could be anticipated to influence one’s perceptions of one’s neighborhood and region. Similarly, while we have argued earlier for the importance of understanding people’s expectation of the future, still expectations do not necessarily correspond to the eventual actuality. Further work is required, perhaps informed by the present study’s findings, using more robust designs and more highly specified models, enabling the deployment of sophisticated model-testing techniques. As previously mentioned, many of the items and scales used in our study were newly developed, and as such concerns could be raised about their reliability and validity. However, the size and direction of the intercorrelations obtained among the items and scales, and in particular with our measures of QoL, are in general as would be expected if they were true measures of their underlying constructs, providing some evidence of validity; and most of the multi-item scales that were developed demonstrated good internal consistency. Nevertheless, further work is required on the scales to fully complete the validation process, including confirmatory factor analysis utilizing a new sample.

Conclusions There is a substantial amount of research into what factors contribute to older people’s QoL, reflecting the importance of this issue for social policy. However, consideration of what factors influence older people’s expectations of their future QoL is rare, despite evidence that a person’s expectations of his or her future is an important influence on his or her current behavior and that a positive orientation toward the future is important for healthy aging. Our findings have established the significance of an older person’s perception


36


of his or her locality for his or her expected future QoL. Surprisingly, perhaps, it is not perceptions of neighborhood and community that play so important a role, but rather perceptions of the wider region and expectations of the region’s development. So, as well as demonstrating the relevance of education, self-reported health, and social influence for an older person’s expected QoL, our findings indicate that living in a region that is felt to be progressive, viewed positively, and held to have a positive future, is linked to an older person’s expectations of his or her own future QoL. Policies that focus only on individual and relational factors for the promotion of healthy aging are arguably missing a critical link between place and older people’s QoL. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported in part by a grant from The Regional Development Council of Dalarna County.

Notes 1. Full details of these analyses are available from the first author on request. 2. Type I error is inflated due to the large sample, but this presents little concern with regard to the descriptive analyses as the effect sizes for associations between variables are readily apparent, enabling the reader to consider a significant association in the context of its strength. Thus, the conventional significance level of p < .05 is used for the descriptive analyses. With regard to the development of a multivariate model, the Type I error rate is more problematic as entry of an independent variable (IV) to the model is determined solely on the basis of whether its association with the dependent variable (DV) is significant. Thus, there is the potential for IVs with weak associations with the DV having undue influence in the final model, and simultaneously their inclusion negatively influences model parsimony. To counteract this and filter out such IVs, the required level of significance for entry of an IV into the model is raised by a step (i.e., to p < .01). 3. rb ¼ biserial correlation; rpb ¼ point-biserial correlation; rs ¼ Spearman’s r. 4. f ¼ phi coefficient. 5. Cohen’s d as a measure of effect size; conventionally, effects are regarded as small where d .20, medium d .50, and large d .80.


McKee et al.

37

References Baltes, P. B., Lindenberger, U., & Staudinger, U. M. (1996). Life-span theory in developmental psychology. In R. M. Lerner (Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human development (5th ed., pp. 1029–1144). New York, NY: John Wiley. ˚ ., & Mira d’Ecole, M. (2006). Alternative measures of wellBoarini, R., Johansson, A being (OECD Economics Department Working Papers No. 476). doi:10.1787/ 832614168015. Buffel, T., Phillipson, C., & Scharf, T. (2013). Experiences of neighbourhood exclusion and inclusion among older people living in deprived inner-city areas in Belgium and England. Ageing & Society, 33, 88–109. Cannuscio, C., Block, J., & Kawachi, I. (2003). Social capital and successful ageing: The role of senior housing. Annals of Internal Medicine, 139, 395–399. Caro, F. G., Yeee, C., Levien, S., Gottlieb, A. S., Winter, J., McFadden, D. L., & Ho, T. H. (2012). Choosing among residential options: Results of a vignette experiment. Research on Aging, 34, 3–33. Carstensen, L. L. (1993). Motivation for social contact across the life-span—A theory of socioemotional selectivity. Nebraska Symposium on Motivation, 40, 209–254. Carstensen, L. L., Isaacowitz, D. M., & Charles, S. T. (1999). Taking time seriously— A theory of socioemotional selectivity. American Psychologist, 54, 165–181. Cate, R. A., & John, O. P. (2007). Testing models of the structure and development of future time perspective: Maintaining a focus on opportunities in middle age. Psychology and Aging, 22, 186–201. De Donder, L., De Witte, N., Buffel, T., Dury, S., & Verte´, D. (2012). Social capital and feelings of unsafety in later life: A study on the influence of social networks, place attachment, and civic participation on perceived safety in Belgium. Research on Aging, 34, 425–448. Ebner, N. C., Freund, A. M., & Baltes, P. B. (2006). Developmental changes in personal goal orientation from young to late adulthood: From striving for gains to maintenance and prevention of losses. Psychology and Aging, 21, 664–678. Elgar, F. J., Davis, C. G., Wohl, M. J., Trites, S. J., Zelenski, J. M., & Martin, M. S. (2011). Social capital, health and life satisfaction in 50 countries. Health and Place, 17, 1044–1053. Farquhar, M. (1995). Definitions of quality of life: A taxonomy. Journal of Advanced Nursing, 22, 502–508. Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior. A reasoned action approach. New York, NY: Psychology Press. Frazier, L. D., Newman, F. L., & Jaccard, J. (2007). Psychosocial outcomes in later life: A multivariate model. Psychology and Aging, 22, 676–689.


38


Freund, A. M., & Baltes, P. B. (1998). Selection, optimization and compensation as strategies of life management: Correlations with subjective indicators of successful aging. Psychology and Aging, 13, 531–543. FUTURAGE Group. (2011). FUTURAGE. A road map for European ageing research. Sheffield, England: Sociological Studies, University of Sheffield. Gale, C. R., Dennison, E. M., Cooper, C., & Sayer, A. A. (2011). Neighbourhood environment and positive mental health in older people: The Hertfordshire Cohort Study. Health and Place, 17, 867–874. Gardner, P. J. (2011). Natural neighborhood networks. Important social networks in the lives of older adults aging in place. Journal of Aging Studies, 25, 263–271. Gilleard, C., & Hyde, M., & Higgs. (2007). The impact of age, place, aging in place, and attachment to place on the well-being of the over 50s in England. Research on Aging, 29, 590–605. Gustafson, P. (2009). Mobility and territorial belonging. Environment and Behavior, 41, 490–508. Hatton, C. (1998). Whose quality of life is it anyway? Some problems with the emerging quality of life consensus. Mental Retardation, 36, 104–115. Kubzansky, L. D., Subramanian, S. V., Kawachi, I., Fay, M. E., Soobader, M. J., & Berkman, L. F. (2005). Neighborhood contextual influences on depressive symptoms in the elderly. American Journal of Epidemiology, 162, 253–260. Kunzmann, U., Little, T. D., & Smith, J. (2000). Is age-related stability of subjective well-being a paradox? Cross-sectional and longitudinal evidence from the Berlin Aging Study. Psychology and Aging, 15, 511–526. Lachman, M. E., Rocke, C., Rosnick, C., & Ryff, C. D. (2008). Realism and illusion in Americans’ temporal views of their life satisfaction age differences in reconstructing the past and anticipating the future. Psychological Science, 19, 889–897. Laczko, L. S. (2005). National and local attachments in a changing world system: Evidence from an international survey. International Review of Sociology, 15, 517–528. Lang, F. R., & Carstensen, L. L. (2002). Time counts: Future time perspective, goals, and social relationships. Psychology and Aging, 17, 125–139. Lang, F. R., Weiss, D., Gerstorf, D., & Wagner, G. G. (2013). Forecasting life satisfaction across adulthood: Benefits of seeing a dark future? Psychology and Aging, 28, 249–261. Lawton, M. P., Moss, M. S., Winter, L., & Hoffman, C. (2002). Motivation in late life: Personal projects and well-being. Psychology and Aging, 17, 539–547. Lewicka, M. (2011). Place attachment: How far have we come in the last 40 years? Journal of Environmental Psychology, 31, 207–230. Litwin, H. (2010). Social networks and well-being: A comparison of older people in Mediterranean and non-Mediterranean countries. Journals of Gerontology Series B-Psychological Sciences and Social Sciences, 65, 599–608.


McKee et al.

39

McKee, K. J., Parker, S. G., Elvish, J., Clubb, V. J., El Nahas, M., Kendray, D., & Creamer, N. (2005). The quality of life of older and younger people who receive renal replacement therapy. Ageing & Society, 25, 903–923. Ouwehand, C., de Ridder, D. T. D., & Bensing, J. M. (2006). Situational aspects are more important in shaping proactive coping behaviour than individual characteristics: A vignette study among adults preparing for ageing. Psychology & Health, 21, 809–825. Parker, C., Barnes, S., McKee, K. J., Morgan, K., Torrington, J., & Tregenza, P. (2004). Quality of life and building design in residential and nursing homes for older people. Ageing & Society, 24, 941–962. Peace, S. M., Holland, C., & Kellaher, C. (2005). The influence of neighbourhood and community on well-being and identity in later life: An English perspective. In G. D. Rowles & H. Chaudhury (Eds.), Home and identity in later life: International perspectives. (pp. 297–315). New York, NY: Springer. Peace, S., Wahl, H. W., Mollenkopf, H., & Oswald, F. (2007). Environment and ageing. In J. Bond, S. Peace, F. Dittmann-Kohli, & G. J. Westerhof (Eds.), Ageing in society: European perspectives on gerontology (pp. 209–234). London, England: Sage. Petty, R. E., & Cacioppo, J. T. (1996). Attitudes and persuasion: Classic and contemporary approaches. Boulder, CO: Westview Press. Phillips, D. R., Siu, O. L., Yeh, A. G. O., & Cheng, K. H. C. (2005). Ageing and the urban environment. In G. J. Andrews & D. R. Phillips (Eds.), Ageing and place: Perspectives, policy and practice (pp. 147–163). New York, NY: Routledge. Prenda, K. M., & Lachman, M. E. (2001). Planning for the future: A life management strategy for increasing control and life satisfaction in adulthood. Psychology and Aging, 16, 206–216. Rocke, C., & Lachman, M. E. (2008). Perceived trajectories of life satisfaction across past, present, and future: Profiles and correlates of subjective change in young, middle-aged, and older adults. Psychology and Aging, 23, 833–847. Seymour, D. G., Starr, J. M., Fox, H. C., Lemmon, H. A., Deary, I. J., Prescott, G. J., & Whalley, L. J. (2008Quality of life and its correlates in octogenarians. Use of the SEIQoL-DW in Wave 5 of the Aberdeen Birth Cohort 1921 Study (ABC1921). Quality of Life Research, 17, 11–20. Smith, A. E. (2009). Ageing in urban neighbourhoods. Place attachment and social exclusion. Bristol, England: The Policy Press. Tang, F. Y., & Lee, Y. (2011). Social support networks and expectations for aging in place and moving. Research on Aging, 33, 444–464. The WHOQOL Group. (1998). The World Health Organization Quality of Life assessment (WHOQOL): Development and general psychometric properties. Social Science and Medicine, 46, 1569–1585.


40


Triandis, H. C. (1977). Interpersonal behavior. Monterey, CA: Brooks-Cole. Tsuboi, H., Kawamura, N., Hori, R., Kobayashi, F., Iwasaki, Y., Takeuchi, H., & Fukino, O. (2005). Depressive symptoms and life satisfaction in elderly women are associated with natural killer cell number and cytotoxicity. International Journal of Behavioral Medicine, 12, 236–243. Uchino, B. N., Cacioppo, J. T., & Kiecolt-Glaser, J. K. (1996). The relationship between social support and physiological processes: A review with emphasis on underlying mechanisms and implications for health. Psychological Bulletin, 119, 488–531. Vetenskapsra˚det. (2002). Forskningsetiska principer inom humanistisk-samha¨llsvetensaplig forskning. Stockholm, Sweden: Vetenskapsra˚det. Wight, R. G., Ko, M. J., & Aneshensel, C. S. (2011). Urban neighbourhoods and depressive symptoms in late middle age. Research on Aging, 33, 28–50. Zimmerman, R. S., & Vernberg, D. (1994). Models of preventive health behavior: Comparison, critique and meta-analysis. Advances in Medical Sociology, 4, 45–67.

Author Biographies Kevin J. McKee, PhD, is a professor of gerontology in the School of Health and Social Studies, Dalarna University, Falun, Sweden. His research is concerned with transitions in physical and mental health in old age and their impact on older people’s quality of life. Johan Kostela, PhD, is an analyst at Dalacampus, Dalarna University, Falun, Sweden. His research focuses on regional development and demographics. Lena Dahlberg, PhD, is a lecturer in the School of Health and Social Studies, Dalarna University, Falun, Sweden, and guest researcher at the Aging Research Center, Karolinska Institutet/Stockholm University, Stockholm, Sweden. Her research focuses on informal care, social exclusion, and the living conditions of older people.


Thirty years from now: future physics contributions in nuclear medicine.

Predicting Future Years of Life, Health, and Functional Ability: A Healthy Life Calculator for Older Adults.

Assuring the quality of diagnostic testing: The future is now.

Health-related quality of life five years after birth of the first child.

Subjective quality of life of those 65 years and older experiencing dementia.

Does a test impact on a patient's life many years from now?

Life expectation of Italian Renaissance artists.

Our future is now.

Neural correlates of expectation of musical termination structure or cadence.

Correlates of perceived health related quality of life in obese, overweight and normal weight older adults: an observational study.

Looked at life from both sides now.

The future is now.

A survey of older peoples' attitudes towards advance care planning.

[Religiousness and health-related quality of life of older adults].

Quality of life of older adults in Turkey.

Technology's future now.

Quality of life of institutionalized older adults by dementia severity.

Significant predictors of poor quality of life in older asthmatics.

The future of pathology is now.

Five years of translation.

Rapid Positive Influence of Cochlear Implantation on the Quality of Life in Adults 70 Years and Older.

Long-term survival and quality of life after intensive care for patients 80 years of age or older.

Edentulism and quality of life among older Ghanaian adults.

Calibration of quality-adjusted life years for oncology clinical trials.