Life space and mental health: a study of older

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ter psychological health will display greater spatial mobil- .... can be found at http://www.dlg.nsw.gov.au/dlg/dlghome/dlg_regions.asp (accessed 7 June 2013).
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Life space and mental health: a study of older community-dwelling persons in Australia a

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Julie E. Byles , Lucy Leigh , Kha Vo , Peta Forder & Cassie Curryer a

Research Centre for Gender, Health and Ageing, Faculty of Health and Medicine, The University of Newcastle, Callaghan, Australia Published online: 06 Jun 2014.

To cite this article: Julie E. Byles, Lucy Leigh, Kha Vo, Peta Forder & Cassie Curryer (2014): Life space and mental health: a study of older community-dwelling persons in Australia, Aging & Mental Health, DOI: 10.1080/13607863.2014.917607 To link to this article: http://dx.doi.org/10.1080/13607863.2014.917607

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Aging & Mental Health, 2014 http://dx.doi.org/10.1080/13607863.2014.917607

Life space and mental health: a study of older community-dwelling persons in Australia Julie E. Byles*, Lucy Leigh, Kha Vo, Peta Forder and Cassie Curryer Research Centre for Gender, Health and Ageing, Faculty of Health and Medicine, The University of Newcastle, Callaghan, Australia

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(Received 4 December 2013; accepted 16 April 2014) Objectives: The ability of older people to mobilise within and outside their community is dependent on a number of factors. This study explored the relationship between spatial mobility and psychological health among older adults living in Australia. Methods: The survey sample consisted of 260 community-dwelling men and women aged 7580 years, who returned a postal survey measuring spatial mobility (using the Life Space Questionnaire) and psychological health (using the SF36 Health Related Quality of Life Profile). From the Life Space Questionnaire, participants were given a life-space score and multinomial regression was used to explore the potential effect of mental health on life-space score. Results: The study found a significant association between mental health and life space. However, gender, physical functioning, and ability to drive were most strongly associated with the extent of life space and spatial mobility. Compared to men, older women are more likely to experience less spatial mobility and restricted life space, and hence are more vulnerable to social isolation. Conclusion: Mental health and life space were associated for the older people in this study. These findings have important implications for health policy and highlight the need to support older persons to maintain independence and social networks, and to successfully age in place within their community. This study also highlights the utility of the Life Space Questionnaire in terms of identifying older persons at risk of poorer mental health. Keywords: psychological health; physical functioning; gender; spatial mobility

Introduction Healthy ageing includes active participation in life and comprises physical, psychological, and emotional health (Australian Institute of Health and Welfare, 2012). Social participation has been shown to be an important factor in the promotion of healthy ageing (Andrews, 2001; Australian Institute of Health and Welfare, 2012; Clarke & Nieuwenhuijsen, 2009; Kalachea & Kickbusch, 1997; MacKellar, 2009; Prilleltensky, 2005). Moreover, older people provide valuable economic, political, social, and cultural contributions to their communities, and are the ‘social glue’ that binds generations and communities (Andrews, 2001; Hodgkin, 2012; Ju-hyun Kim, 2013; Warburton & Chambers, 2007; WRVS, 2011). However, the extent of an individual’s social participation may be limited as a result of psychological distress such as depression (Clarke & Nieuwenhuijsen, 2009), and by the lack of a supportive environment. The role of supportive neighbourhoods and communities in enabling older persons to successfully age in place and maintain social connections and identity has been well established (Bowling, 2011; Gardner, 2011; Gidlow, Cochrane, Davey, Smith, & Fairburn, 2010; World Health Organization [WHO], 2007; Yen & Anderson, 2012). Furthermore, social networks have been shown to be important for maintaining social and physical activity, and hence psychological health and well-being (Litwin, 2012). For older people particularly, the ability to access the benefits of a supportive community is dependent on

*Corresponding author. Email: [email protected] Ó 2014 Taylor & Francis

the ability to successfully navigate and mobilise within and outside of the community. This ability can be influenced by a number of factors, including psychological health and cognitive status, physical health, environment (weather, neighbourhood crime, location of services), resources (availability and affordability of public and private transport, and infrastructure such as public toilets), and intrapersonal factors including social roles and obligations such as caring (Andrews, 2001; Baker, Bodner, & Allman, 2003; Bowling, 2011; Darlington & Carnovale, 2011; Murata, Kondo, Tamakoshi, Yatsuya, & Toyoshima, 2006; Peel et al., 2005; Stalvey, Owsley, Sloane, & Ball, 1999; Webber, Porter, & Menec, 2010; WHO, 2007; Xue, Fried, Glass, Laffan, & Chaves, 2008). Consequently, the experience of ageing, and the ability to participate in the social life of communities, can vary greatly being dependent on these many physical, personal, and social factors. Life space is a multidimensional and dynamic construct that reflects the extent of a person’s physical and social mobility. Life space is influenced by cognitive, psychosocial, physical, environmental, and financial domains, as well as gender, culture, and biographical influences (Boyle, Buchman, Barnes, James, & Bennett, 2010; Stalvey et al., 1999; Webber et al., 2010). Cognitive determinants include mental status, speed of cognitive processing (which is important for maintaining ability to drive), and memory. For example, dementia may inhibit life space and mobility outside the home due to personal

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fears or the influence of others (such as family or friends) and concerns that the individual may forget the way home or become lost (Darlington & Carnovale, 2011; Webber et al., 2010). Psychosocial determinants of life space include self-efficacy, coping and compensatory behaviours, motivation, psychological well-being such as the existence or absence of depression, emotional health, social support networks, social and work roles, and interpersonal relationships. For example, older people with low-efficacy beliefs may restrict their travels beyond the home, regardless of actual driving or walking ability (Webber et al., 2010). Previous studies have shown that smaller life space (and hence a smaller range of spatial mobility) is associated with depression (Peel et al., 2005; Snih et al., 2012; Stalvey et al., 1999; Xue et al., 2008), and higher levels of functional and sensory limitations, such as poor eyesight or inability to walk unaided, poor self-rated health (Stalvey et al., 1999); older age, being female, having a high BMI  35 kg/m2, and having ever had a stroke (Peel et al., 2005; Snih et al., 2012); and frailty (Xue et al., 2008). Constricted life space has been associated with negative health and psychological outcomes such as poor mental well-being or depression, disability, reduced social interaction (Lampinen, Heikkinen, Kauppinen, & Heikkinen, 2006; Webber et al., 2010; Xue et al., 2008), increased risk of frailty (Xue et al., 2008), and increased risk of mortality (Boyle et al., 2010; Xue et al., 2008). A study by Boyle et al. (2010) found that people confined to the immediate home environment (having a constricted life space) were 1.6 times as likely to die early when compared to people whose life spaces were more extensive and included travel out of town. This association persisted, even allowing for potential confounders such as physical activity and physical function, disability, depression, social networks, and a number of chronic medical conditions (Boyle et al., 2010). Constricted life space is also associated with increased risk of cognitive decline (Crowe et al., 2008), and Alzheimer’s disease (James, Boyle, Buchman, Barnes, & Bennett, 2011). James et al. (2011) found that those persons who had not been to an area beyond their home environment in the previous week were almost twice as likely to develop Alzheimer’s than those persons who had travelled outside of town. While Choi and McDougall (2007) have found that homebound older adults are at greater risk of depressive symptoms than older adults who attend senior centres, only limited research exists on the relationship between mental health and spatial mobility within the home and immediate neighbourhood and beyond  the life space, of older persons dwelling in the community. This study explored the relationship between psychological health and spatial movement among a sample of 260 community-dwelling men and women aged 7580 years, and living in the greater Sydney metropolitan area of New South Wales, Australia. This study proposed that those with better psychological health will display greater spatial mobility and hence experience greater participation, social interaction, and support within their community. Since interpersonal factors, such as social interaction, and

environmental factors, such as transport, can also affect life space, we explored these associations. Life space  a conceptual framework for measuring mobility Life space is a conceptual measure of the extent of spatial mobility or travel that an individual moves in the course of everyday life within a given period of time (for example, within a day or week), through successive zones such as the bedroom, other rooms of the home, the immediate areas surrounding the home such as the front porch or yard, across the street, the local community (for example, parks, shops, businesses, and health services), and beyond (May, Nayak, & Isaacs, 1985; Stalvey et al., 1999). Lifespace mobility encompasses multiple modes of travel, including walking, using a mobility scooter, being a passenger in or driving a motor vehicle, and travel by public transport. Travel is scored according to how far the individual travels within the given zones, with a higher score indicating a larger life space, and so more extensive mobility or travel (May et al., 1985; Stalvey et al., 1999). Life space is a useful measurement for determining the impact of physical and mental health and disabilities beyond that of activities of daily living (ADL) and instrumental activities of daily living (IADL) measurements, which measure mobility at one specific point in time (Peel et al., 2005). By comparison, life space allows the researcher to more fully understand the spatial movements of the individual, taking into account environmental, personal, and intrapersonal resources (such as functional and psychological health, cognitive status, social roles or commitments, and coping or compensatory strategies) (Stalvey et al., 1999). Moreover, life space is a useful construct when evaluating changes in mobility due to sensory or motor deficits, depression or disengagement (Peel et al., 2005; Stalvey et al., 1999). Life space is also an indicator of health, social, and psychological well-being (Boyle et al., 2010), and can provide important prognostic indicators for the risk of mortality at older ages (Boyle et al., 2010). Social isolation has been associated with lesser physical engagement (Litwin, 2012) and with depression (Choi & McDougall, 2007). As such, life space as a measurement tool can be used to identify older adults most at risk of social isolation, thus enabling strategies and support services to be put in place to help reduce the risk of depression. The Life Space Questionnaire The Life Space Questionnaire covers a broad range of environmental regions as a means to characterise an older person’s mobility within their immediate (home) and extended (neighbourhood, community, interstate) environment (Peel et al., 2005; Stalvey et al., 1999). The Life Space Questionnaire has been shown to have good construct and criterion validity in previous studies for measuring the spatial extent of mobility in older communitydwelling adults (Baker et al., 2003; Stalvey et al., 1999; Xue et al., 2008). Stalvey et al. (1999) found that the Life Space Questionnaire provided good testretest reliability

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Table 1. Demographic details for the selected LGAs.

LGA

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Inner Sydneyb Woollahra Hunters Hill Mosman Outer Sydneyb Ku-ring-gai Sutherland Bankstown Sydney surroundsb Wyong

Population a (’000) a

% aged 75 years or older

Area (km2) a

Median household income (A$) a

Relative position to Sydney CBD

52 9 29

8.0 11.2 8.0

12 6 9

2398 2178 2465

5 km E 7 km NW 6 km N

107 214 183

9.1 7.2 7.1

85 335 77

2508 1678 1091

16 km N 26 km S 23 km SW

144

9.1

820

934

93 km N

Notes: a2011 data obtained from the ABS ‘Quick Stats’ search page (accessed 12 June 2013, http://www.abs.gov.au/websitedbs/censushome.nsf/home/ quickstats?opendocument&navpos ¼ 220). b Map of the LGAs can be found at http://www.dlg.nsw.gov.au/dlg/dlghome/dlg_regions.asp (accessed 7 June 2013).

(Kappa coefficient 0.80), good criterion validity (when tested for association between life space and other common measures of mobility such as IADL and driving behaviour), and good construct validity (by examining to what extent Life Space Questionnaire score was associated with intrapersonal factors in older persons such as vision, depression, and general health). Likewise, Baker et al. (2003) reported good validity for correlations between baseline life space and physical and mental health, and short-term testretest reliability.

Ethics approval This research was approved by the University of Newcastle Human Research Ethics Committee (H-2009-0209).

Methods The Housing and Independent Living (HAIL) study The HAIL study sought to identify people’s health and well-being within the context of home and neighbourhood environments and the study design has been discussed in detail elsewhere (Byles et al., 2012). The HAIL study involved 260 men and women aged 7580 years, who were living in the greater Sydney region of New South Wales, Australia, and who returned a postal survey (in 2010) regarding their health, homes, and neighbourhoods, and who had been recruited into the larger 45 and Up Study (during 20062009) (45 and Up Study Collaborators, 2008) (https://www.saxinstitute.org.au/our-work/45up-study/). A total of 400 men and women were randomly drawn from seven socioeconomically and geographically diverse local government areas (LGAs) from the greater Sydney area, identified as having the greatest proportion of older residents aged 75 years and older. The LGAs of Woollahra, Hunters Hill, and Mosman were selected from the inner Sydney area, while the outer Sydney area was represented by the LGAs of Ku-ring-gai, Sutherland, and Bankstown. The Wyong LGA was selected from the Sydney Surrounds area (http://profile.id.com.au/sydney).

Further details concerning these seven LGAs are presented in Table 1, showing the diversity in population density and median household incomes. Survey content The HAIL survey content included questions on date of birth, gender, work status, living arrangement, retirement status, housing description (home cooling, home heating, design of home, etc.), transport, mental and physical health, and life space. Survey measures Survey measures included the Life Space Questionnaire (Stalvey et al., 1999), and the SF36 Health Related Quality of Life Profile (Ware, Kosinski, & Keller, 1994). To determine maximum life space (MLS), participants were asked: ‘During the past 3 days, have you been to: a) Other rooms of your home besides the room where you sleep?, b) An area immediately outside your home such as your porch, deck or patio, hallway of an apartment building, or garage?, c) An area outside your home such as a yard, courtyard, driveway or parking lot?, d) Places in your immediate neighbourhood, but beyond your own property or apartment building?, e) Places outside your immediate neighbourhood, but within your town or community?, f) Places outside your immediate suburb?, g) Places outside your metropolitan area?, h) Places outside New South Wales (state)?, i) Places outside Australia?’ Responses were scored as either 1 (yes) or 0 (no). The summed scores provided the final life-space score and ranged from 0 to 9, such that a score of 0 indicated the person had not left their bedroom, a score of 5 indicated the person had left their neighbourhood, but not left town, a score of 8 indicated that the person had left the state, but not the country, and a score of 9 indicated that the person had left the country. The life-space score was the focal outcome variable for our study and was categorised into three groups: low (scores of 05), mid (score of 6), and high (scores of 79).

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J.E. Byles et al. low-score category (scores 05) was chosen as the reference group for the outcome, in keeping with the research question, in order to examine effects on having a better life-space score (high score and mid score) over a poor life-space score (low score). Neighbourhood satisfaction and safety scales were dichotomised at lowest quartile in order to identify participants least likely to perceive supports from surrounding neighbourhood (Byles et al., 2012). The association between MLS scores and SF36 social functioning was measured by the Spearman correlation. The association between MLS score and means of transport (self-driving versus other) was assessed using a Wilcoxon two-sample test and visualised by box plots. SAS 9.3 (SAS Institute Inc., 2011) was used for analyses.

Mental health was the main variable of interest measured by The Medical Outcomes Study Short Form 36 (SF36) mental health sub-scale (Ware et al., 1994). This sub-scale was derived from five questions asking if the participant had been ‘nervous’, ‘down in dumps’, ‘calm and peaceful’, ‘felt down’, and ‘happy person’ in the past four weeks. The answer options for each question included ‘all of the time’, ‘most of the time’, ‘some of the time’, ‘a little of the time’, and ‘none of the time’ scoring from 1 to 5 for question about being ‘nervous’, ‘down in dumps’, and ‘felt down’, while scoring from 5 to 1 for question about being ‘calm and peaceful’, and ‘happy person’. The scores from five questions were added up and the total score was scaled to have range from 0 to 100. Mental health is strongly correlated with other measures of depression (Berwick et al., 1991). Other covariates included age, gender, living arrangement, retirement status, neighbourhood satisfaction, and safety scales (Young, Russell, & Powers, 2004), main means of transport (self-drive/other), and the SF36 physical functioning and social functioning items (Ware et al., 1994). The neighbourhood satisfaction and safety scales ranged from one to four and were derived from questions asking opinion about neighbourhood surroundings, social interaction and sense of belonging, safety, traffic at day and night, walking distance, etc. A better sense of neighbourhood is associated with better physical and mental health, social support, and being physically active (Young et al., 2004).

Results A total of 260 people (128 men, 131 women, 1 missing) (66.5% response rate) returned the survey. The mean age of respondents was 77 years. Men were more likely to be married than women (84% of men; 52% of women). Women were more likely to be living alone (11% of men; 37% of women). Most participants were completely retired; 17% of men and women were not retired and 6% of men were partly retired. Most men (94%) had access to a car and 87% drove themselves as their main means of transport. In contrast, 84% of women had access to a car and 65% drove themselves as their main means of transport.

Data management and analyses Multinomial regression was used to explore the potential effect of mental health on MLS score. This analysis was first conducted without considering other covariates and then subsequently adjusted for age, gender, living arrangement, retirement status, neighbourhood satisfaction and safety scales, and SF36 physical functioning scores. The

The distribution of maximum life-space (MLS) score Fourteen participants did not answer the questions on MLS, and were excluded from analysis. MLS scores for the remaining 246 participants are shown in Table 2. Few people had not left their homes or neighbourhoods (15.9%

Table 2. Distribution of maximum life-space score. In past three days, have you been to?

Corresponding maximum life-space score

N

Not outside bedroom

0

0

Other room of your home besides bedroom Area immediately outside the house (porch, deck, garage, etc.) Area outside the house (yard, courtyard, driveway, parking lot) Immediate neighbourhood, beyond property or apartment building Outside immediate neighbourhood but within suburb Outside immediate suburb Outside metropolitan area Outside NSW Outside Australia

1 2

1 1

3

5

4

5

5 6 7 8 9

27 118 81 6 2

Note: N ¼ 246, excluding 14 participants who did not answer the question.

Outcome for analysis Low score N ¼ 39 (15.9%) (Reference group)

Mid score N ¼ 118 (48.0%) High score N ¼ 89 (36.1%)

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Table 3. Odds ratio (95% CI) of having high and mid life-space score by SF36-mental health. Mid score versus low score

Covariates SF36-mental health Age Gender Living arrangement

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Retirement status Neighbourhood satisfaction score Neighbourhood safety score

High score versus low score

Unadjusted model N ¼ 238

Adjusted model N ¼ 230

Unadjusted model N ¼ 238

Adjusted model N ¼ 230

1.02 (0.99; 1.04)

1.00 (0.98; 1.03)

1.03 (1.00; 1.05)

1.01 (0.98; 1.04)

1.21 (0.90; 1.63) Ref 2.44 (1.05; 5.72) Ref

0.97 (0.72; 1.32) Ref 2.06 (0.85; 4.99) Ref

With spouse/ partner/other family members Not retired

0.45 (0.15; 1.32)

0.47 (0.15; 1.45)

Ref

Ref

Retired Other

0.48 (0.10; 2.32) Ref

0.79 (0.15; 4.18) Ref

Lowest quartile Other

0.56 (0.24; 1.29) Ref

0.56 (0.23; 1.34) Ref

Lowest quartile

0.70 (0.30; 1.62) 1.01 (1.00; 1.03)

0.76 (0.32; 1.81) 1.02 (1.00; 1.04)

Women Men Alone

SF36-physical functioning Note: ORs in bold indicate p < 0.05.

scored 05), most people (48% scored 6) had been outside their immediate suburb but not left the metropolitan area, and around one-third of the participants (36.1%) had been outside the metropolitan area, state, or country (scored 79). (See Table 2).

Mental health and life space Table 3 presents the effect of SF36 mental health on the odds of having MLS score in the mid score (6) or high score (79) when contrasted with having a low score (05). In the unadjusted analyses, SF36 mental health was statistically significant when contrasting high-score with low-score group (OR ¼ 1.03; 95% CI ¼ 1.001.05, p ¼ 0.0410), but was not significant when contrasting mid-score and low-score group (OR ¼ 1.02; 95% CI ¼ 0.991.04, p ¼ 0.21). Each 10 unit increase in SF36 mental health score was associated with being 30% more likely to have a high MLS score (OR ¼ 1.30; 95% CI ¼ 1.011.66). After adjusting for the effects of age, gender, living arrangement, work status, neighbourhood satisfaction and safety, and SF36 physical functioning, the effect of SF36 mental health was diminished. There were different significant factors affecting MLS score. Gender was a significant factor in analysis contrasting mid score with low score (p ¼ 0.0394), while SF36 physical functioning was significant in analysis contrasting high score with low score (p ¼ 0.0462). There was no significant association

between MLS score and age, living arrangement, work status, neighbourhood satisfaction and safety in these analyses. (See Table 3).

Social interaction There was weak positive association between MLS score and SF36 social functioning (Spearman correlation coefficient ¼ 0.17, p ¼ 0.0064).

Transport Participants who mostly drove themselves had a higher MLS score than those who did not. While the CIs in Figure 1 overlap, p value from the Wilcoxon test is p < 0.0001, indicating a statistically significant difference.

Discussion This study examined the association between MLS scores and the SF36 Mental Health profile scores among community-dwelling men and women aged 7580 years, and who were participants in the HAIL study in Australia. The study found a significant association between mental health and life space in the unadjusted model, and reflects previous studies which found that poor psychological health was associated with increased social isolation (Boardman, 2011; Gracia & Herrero, 2004; Murata et al., 2006). However, the effect of mental health on life space

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Figure 1. Maximum life-space scores by means of transport.

was not significant when adjusted for other covariates (demographic factors and physical functioning). In this study, gender and physical functioning appeared to be the strong factors affecting life space. This pattern of results is consistent with previous work such as Barnes et al. (2007), Hjorthol (2013), Peel et al. (2005), and Stalvey et al. (1999). Hjorthol’s (2013) study found that compared to men, older women experience greater mobility limitations due to women’s longer life expectancy and greater levels of disability such as arthritis; Peel et al. (2005) similarly found that being female was associated with lower life-space scores. In keeping with Stalvey et al. (1999), this study found that poor physical functioning was associated with smaller life space and spatial mobility. Moreover, this study concurs with previous findings that transport type and in particular, ability to drive oneself, impacts upon older people’s mobility (Hjorthol, 2013; Stalvey et al., 1999), and hence life-space score. Gendered social roles and obligations (such as caring for a spouse), and socioeconomic factors such as women’s lower incomes across the life course may preclude women from owning and maintaining a car or learning to drive (Hjorthol, 2013). Driving ability is seen as a key factor in maintaining independence and social connections among

older persons dwelling in the community (Hjorthol, 2013; Webber et al., 2010), and so maintaining driving ability can play an important role in preventing social isolation. For those unwilling or unable to drive, public transport is an extremely important aspect of active ageing (Day, 2008). Not only important for increasing mobility, public transport is also viewed by older people as a valuable social opportunity (Michael, Green, & Farquhar, 2006). The loss of a spouse can suddenly and substantially impact upon an older woman’s spatial mobility (Hjorthol, 2013; Webber et al., 2010), for example, if the surviving partner cannot drive themselves, can no longer afford the cost of public transport (Hjorthol, 2013), or lacks confidence, knowledge, or experience in using public transport (Darlington & Carnovale, 2011). There may also be fears about crime in the community and travelling on one’s own (Rantakokko et al., 2009). This study found that older women were more vulnerable than men in terms of spatial movement, and thus, older women require increased social support to ensure they do not become socially isolated. Social functioning was also found to be correlated with life space. This study found that those persons with a higher social functioning score (being able to perform normal social activities without interference or limitation

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Aging & Mental Health due to psychological, emotional, or physical problems) experienced greater mobility and life space, and these findings are consistent with previous studies (Barnes et al., 2007). In this study, most participants scored either in the mid (outside immediate suburb) or high (outside metropolitan area and beyond) ranges for MLS score, reflecting high levels of spatial mobility. Boyle et al. (2010) similarly found that most participants were relatively mobile, with 66% travelling outside of town, and only a small proportion being homebound (having a severely restricted life space) (2%). Comparisons with previous studies are difficult, however, as most participants in this study were of good health, whereas other studies, for example Xue et al. (2008) and Snih et al. (2012) have sampled disabled persons only. Moreover, considerable variability in measurements was found (for example, mental and physical health, social functioning, self-report versus performancebased measures, timeframe) and scoring and interpretation of the Life Space Questionnaire. For example, Boyle et al.’s study used a reversed system of scoring whereby the lowest score (zero) indicated travel outside of town and a score of 5 indicated being homebound, and presence of depressive symptoms was assessed using the 10-item Centre for Epidemiologic Studies Depression scale (Boyle et al., 2010). The use of consistent, standardised measures for life-space research in the future would enable more accurate comparisons to be made. This study has provided a useful overview of the lifespace concept as applied to the studies of older persons living in the community. This study extends current research and knowledge about the relationship between psychological health and spatial mobility of older persons dwelling in the community. Moreover, these findings have important implications for future research (such as the need for standard of measures), and for policy and practice, such as increased support for older women who are socially isolated.

Limitations The results of this study may be limited by the relatively short timeframe, which focused on the previous three days only. This could be an important consideration for future research. Moreover, it is conceivable that some participants may have edited their responses rather than admit, for example, they had stayed indoors for three days, or to reflect what they thought were more valid responses. Also, the participants in this study were in relatively good health based on Australian Bureau of Statistics benchmarks (Australian Bureau of Statistics, 1997), reflecting the health status of most of the population in this age group, and so may experience a greater extent of mobility than a disabled sample (Australian Bureau of Statistics, 1997). For example, those with better health may be more likely to undertake travel interstate or outside of the country than those with poor physical or psychological health.

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The geographical diversity of the LGAs in this study may also influence these findings. Those participants who live in smaller LGAs and closer to their place of work (if working), shopping, medical or other facilities, and close to their relatives, and friends may report consistently smaller or larger life-space scores depending on their location. Similarly, a journey of only a few kilometres may see them reaching a destination in the next or neighbouring suburb, something that in a geographically large government or local area such as Wyong may not be so easily achieved. However, many residents commute over considerable distances to the Sydney central business district (CBD) for work, medical, or specialist appointments or entertainment/social activities. Persons living in more dispersed LGAs on the outer metropolitan areas (for example, Wyong) may commute to the centre of Sydney by car or train which can take up to two hours each way (West, 29 May 2010), a distance of 200 kilometres. The suburbs selected for this study are not typical of all neighbourhoods in New South Wales, but were particularly selected for having a high proportion of older people. These suburbs would be expected to be more age friendly than areas with more diverse age ranges, and comprise older, more established homes, and neighbourhoods. These results therefore, must be interpreted in light of this, and may not be representative of other areas such as those in rural and remote areas. Also, the level of available infrastructure (for example, transport and adequate footpaths) may influence the distance that persons may be able to travel, as a lack of public transport will impact on the ability to travel any distance. Moreover, the variability between LGAs in terms of socioeconomic status may also influence these results, as those persons living in higher socioeconomic areas may have more resources (such as being able to own and drive a car) to enable them to travel further distances more frequently. At an international level, the extent of representativeness of this Australian study to other contexts is dependent on a number of factors such as transport infrastructure, geographic location, and whether the environment can be considered age friendly in terms of mobility (WHO, 2007). For example, urban environments in developed countries with high income may have better transport and other infrastructure. However, these limitations are outweighed by the representativeness of the sample to the general population. Moreover, the geographical and socioeconomic diversity of the seven LGAs reduce the likelihood of oversampling in those areas more predictive of either greater or lower life-space scores.

Conclusion Mental health and life space are intricately related for older people, and are relevant to policy initiatives aimed at improving independence and well-being in older age. As suggested by the World Health Organization’s Global Age Friendly Cities project (WHO, 2007), community features, and infrastructure such as transport and other

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services, can enable older people to have greater mobility and participation in their communities. This study highlights the need to improve health policy to enhance the life space of older people. This study also emphasises the importance of transport for enabling older people’s access to a wider geographical area and enabling opportunities for social participation. Policy initiatives aimed at maintaining driving ability, such as driver training and increased safety design of transport and road infrastructures, may provide benefits for people as they age. One possible response to the needs of older people is the use of ‘Senior Impact Statements’, such as advocated by seniors organisations for example, Council on the Ageing New South Wales, 2012. These may assist government, non-government, and corporate sector agencies to make decisions that are cognisant of the potential impact on older people, and help agencies to develop age friendly, positive, policy reforms that enable greater life space and more social engagement among older people. Additionally, as older women are particularly vulnerable to having lower life-space scores, increased attention to promoting and supporting community participation among older women is indicated, and may be helpful in reducing social isolation in this vulnerable sub-population. Finally, the study has also demonstrated the overall utility of lifespace measurement as an indicator of older persons in the community who may benefit from the implementation of additional strategies and support services to reduce the risk of psychological distress and social isolation.

Acknowledgements This paper draws on findings from the Housing and Independent Living (HAIL) project undertaken by researchers at the University of Newcastle, the University of Sydney, and the Sax Institute. The 45 and Up Study is managed by the Sax Institute in collaboration with the major partner Cancer Council New South Wales; and partners: the National Heart Foundation of Australia (NSW Division); the New South Wales (NSW) Ministry of Health; beyondblue: the national depression initiative; Ageing, Disability and Home Care, NSW Family and Community Services; Australian Red Cross Blood Service; and Uniting Care Ageing. We sincerely thank the men and women of the 45 and Up Study who consented to participate in the HAIL project and who allowed assessors to visit them in their home, and for their graciousness and willingness to provide information relevant to the HAIL project. Further information is available from http:// www.45andup.org.au. All researchers in the Faculty of Health and Medicine at the University of Newcastle are members of the Hunter Medical Research Institute (HMRI). We thank Louise Thomas from the Research Centre for Gender, Health and Ageing, the University of Newcastle, for assistance with manuscript preparation.

Funding The HAIL study was funded by the Ageing Disability and Home Care, NSW Family and Community Services [grant number G0190151].

References Andrews, K. (2001). National strategy for an ageing Australia: An older Australia, challenges and opportunities for all. Canberra: Department of Health and Ageing. Retrieved from http://www.health.gov.au/internet/main/publishing.nsf/ Content/88E4FA447207F25DCA257BF000217932/$File/natstrat-for-ageing-aust.pdf. Australian Bureau of Statistics. (1997). National health survey: SF36 population norms, Australia, Cat No. 4399.0. Canberra: ABS. Retrieved from http://www.abs.gov.au/AUSSTATS/[email protected]/ Lookup/4399.0Main+Features11995?OpenDocument Australian Institute of Health and Welfare. (2012). Australia’s health 2012: Australia’s health No. 13, Cat. No. AUS 156. Canberra: AIHW. Retrieved from http://www.aihw.gov.au/ publication-detail/?id=10737422172 Baker, P.S., Bodner, E.V., & Allman, R.M. (2003). Measuring life-space mobility in community-dwelling older adults. Journal of the American Geriatrics Society, 51(11), 16101614. doi:10.1046/j.1532-5415.2003.51512.x Barnes, L.L., Wilson, R.S., Bienias, J.L., Mendes de Leon, C.F., Kim, H.-J.N., Buchman, A.S., & Bennett, D.A. (2007). Correlates of life space in a volunteer cohort of older adults. Experimental Aging Research, 33(1), 7793. doi:10.1080/ 03610730601006420 Berwick, D.M., Murphy, J.M., Goldman, P.A., Ware Jr, J.E., Barsky, A.J., & Weinstein, M.C. (1991). Performance of a five-item mental health screening test. Medical Care, 29(2), 169176. Boardman, J. (2011). Social exclusion and mental health  how people with mental health problems are disadvantaged: An overview. Mental Health and Social Inclusion, 15(3), 112121. Bowling, A. (2011). Effects of neighbourhood environment on social and physical functioning in older age. In J.O. Nriagu (Ed.), Encyclopedia of environmental health (pp. 254258). Burlington: Elsevier. Boyle, P.A., Buchman, A.S., Barnes, L.L., James, B.D., & Bennett, D.A. (2010). Association between life space and risk of mortality in advanced age. JAGS, 58, 19251930. Byles, J.E., Mackenzie, L., Redman, S., Parkinson, L., Leigh, L., & Curryer, C. (2012). Supporting housing and neighbourhoods for healthy ageing: Findings from the Housing and Independent Living Study (HAIL). Australasian Journal on Ageing, doi:10.1111/j.1741-6612.2012.00646.x Choi, N.G., & McDougall, G.J. (2007). Comparison of depressive symptoms between homebound older adults and ambulatory older adults. Aging & Mental Health, 11(3), 310322. doi:10.1080/13607860600844614 Clarke, P., & Nieuwenhuijsen, E.R. (2009). Environments for healthy ageing: A critical review. Maturitas, 64(1), 1419. Council on the Ageing New South Wales. (2012). Seniors impact statement. Sydney: COTA NSW. Retrieved from http://cotansw.com.au/wp-content/uploads/2012/02/Seniors _Impact_Statement_Checklist_Handout_-_Copy.pdf Crowe, M., Andel, R., Wadley, V.G., Okonkwo, O.C., Sawyer, P., & Allman, R.M. (2008). Life-space and cognitive decline in a community-based sample of African American and Caucasian older adults. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 63(11), 12411245. Darlington, K., & Carnovale, A. (2011). Older women and social connectedness: A snapshot of the ACT. Canberra: Women’s Centre for Health Matters Inc. Retrieved from http://www. wchm.org.au/_literature_102910/Older_Women_and_Social_ Connectedness Day, R. (2008). Local environments and older people’s health: Dimensions from a comparative qualitative study in Scotland. Health & Place, 14, 299312. 45 and Up Study Collaborators. (2008). Cohort profile: The 45 and Up Study. International Journal of Epidemiology, 37, 941947.

Downloaded by [University of Newcastle (Australia)] at 16:00 10 June 2014

Aging & Mental Health Gardner, P.J. (2011). Natural neighborhood networks  Important social networks in the lives of older adults aging in place. Journal of Aging Studies, 25(3), 263271. Gidlow, C., Cochrane, T., Davey, R.C., Smith, G., & Fairburn, J. (2010). Relative importance of physical and social aspects of perceived neighbourhood environment for self-reported health. Preventative Medicine, 51, 157163. Gracia, E., & Herrero, J. (2004). Determinants of social integration in the community: An exploratory analysis of personal, interpersonal and situational variables. Journal of Community & Applied Social Psychology, 14(1), 115. doi:10.1002/casp.746 Hjorthol, R. (2013). Transport resources, mobility and unmet transport needs in old age. Ageing & Society, 33(7), 11901211. doi:10.1017/S014468612000517 Hodgkin, S. (2012). ‘I’m older and more interested in my community’: Older people’s contributions to social capital. Australasian Journal on Ageing, 31(1), 3439. doi:10.1111/ j.1741-6612.2011.00528.x James, B.D., Boyle, P.A., Buchman, A.S., Barnes, L.L., & Bennett, D.A. (2011). Life space and risk of Alzheimer disease, mild cognitive impairment, and cognitive decline in old age. American Journal Geriatric Psychiatry, 19(11), 961969. doi: 10.1097/JGP.0b013e318211c219 Ju-hyun, Kim. (2013). Productive activity and life satisfaction in Korean elderly women. Journal of Women and Aging, 25(1), 8096. Kalachea, A., & Kickbusch, I. (1997). A global strategy for healthy ageing. World Health, 50(4), 45. Lampinen, P., Heikkinen, R.-L., Kauppinen, M., & Heikkinen, E. (2006). Activity as a predictor of mental well-being among older adults. Aging & Mental Health, 10(5), 454466. Litwin, H. (2012). Physical activity, social network type, and depressive symptoms in late life: An analysis of data from the National Social Life, Health and Aging Project. Aging & Mental Health, 16(5), 608616. doi:10.1080/ 13607863.2011.644264 MacKellar, T. (2009). Using the SPECS model to explore new paradigms in health psychology. The Australian Community Psychologist, 21(1), 102107. May, D., Nayak, U.S., & Isaacs, B. (1985). The life-space diary: A measure of mobility in old people at home. International Rehabilitation Medicine, 7, 182186. Michael, Y.L., Green, M.K., & Farquhar, S.A. (2006). Neighbourhood design and active aging. Health & Place, 12, 734740. Murata, C., Kondo, T., Tamakoshi, K., Yatsuya, H., & Toyoshima, H. (2006). Factors associated with life space among community-living rural elders in Japan. Public Health Nursing, 23(4), 324331. doi:10.1111/j.1525-1446.2006.00568.x Peel, C., Baker, P.S., Roth, D.L., Brown, C.J., Bodner, E.V., & Allman, R.M. (2005). Assessing mobility in older adults:

9

The UAB study of aging life-space assessment. Physical Therapy, 85(10), 10081019. Prilleltensky, I. (2005). Promoting well-being: Time for a paradigm shift in health and human services. Scandinavian Journal of Public Health, 33(66), 5360. doi:10.1080/ 14034950510033381 Rantakokko, M., M€anty, M., Iwarsson, S., T€ orm€akangas, T., Leinonen, R., Heikkinen, E., & Rantanen, T. (2009). Fear of moving outdoors and development of outdoor walking difficulty in older people. Journal of the American Geriatrics Society, 57 (4), 634640. doi:10.1111/j.1532-5415.2009.02180.x SAS Institute Inc. (2011). SAS statistical software (Version 9.3) [Computer software]. Cary, NC: Author. Snih, S.A., Peek, K.M., Sawyer, P., Markides, K.S., Allman, R. M., & Ottenbacher, K.J. (2012). Life-space mobility in Mexican Americans aged 75 and older. JAGS, 60, 532537. Stalvey, B.T., Owsley, C., Sloane, M.E., & Ball, K. (1999). The Life Space Questionnaire: A measure of the extent of mobility of older adults. Journal of Applied Gerontology, 18(4), 460478. doi: 10.1177/073346489901800404 Warburton, J., & Chambers, B. (2007). Older indigenous Australians: Their integral role in culture and community. Australasian Journal on Ageing, 26(1), 37. Ware, J., Kosinski, M., & Keller, S. (1994). SF-36 physical and mental health summary scales: A user’s manual. Boston, MA: The Health Institute, New England Medical Centre. Webber, S.C., Porter, M.M., & Menec, V.H. (2010). Mobility in older adults: A comprehensive framework. The Gerontologist, 50(4), 443450. doi:10.1093/geront/gnq013 West, A. (2010, May 29). Time travel as daily routine. Sydney Morning Herald. Retrieved from http://www.smh.com.au/ nsw/time-travel-as-a-daily-routine-20100528-wldl.html World Health Organization. (2007). Global age-friendly cities: A guide. Geneva: Author. Retrieved from http://www.who .int/ageing/publications/Global_age_friendly_cities_Guide_ English.pdf WRVS. (2011). Gold age pensioners: Valuing the socio-economic contribution of older people in the UK. Cardiff: Author. Retrieved from http://www.royalvoluntaryservice.org.uk/ Uploads/Documents/gold_age_report_2011.pdf Xue, Q.-L., Fried, L.P., Glass, T.A., Laffan, A., & Chaves, P.H. M. (2008). Life-space constriction, development of frailty, and the competing risk of mortality. American Journal of Epidemiology, 167(2), 240248. doi:10.1093/aje/kwm270 Yen, I.H., & Anderson, L.A. (2012). Built environment and mobility of older adults: Important policy and practice efforts. Journal of the American Geriatrics Society, 60(5), 951956. doi:10.1111/j.1532-5415.2012.03949.x Young, A., Russell, A., & Powers, J. (2004). The sense of belonging to a neighbourhood: Can it be measured and is it related to health and well-being in older women? Social Science & Medicine, 59, 26272637.