Transport-related social exclusion amongst older people in rural Southwest England and Wales
Highlights
► Social exclusion due to transport reasons is assessed for older citizens in six rural areas in the UK. ► Rurality is found to have a small, statistically significant effect on overall exclusion. ► Car availability had greater influence than age on difficulty in accessing essential services. ► The growing number of older old suggests a growing accessibility deficit particularly in rural areas. ► Policy should consider active travel and organised lift-sharing alongside public transport solutions.
Section snippets
Introduction: the relationship between transport and social exclusion
The focus of this paper is the susceptibility to transport-related exclusion of older people (defined as those over the age of 60) living in six rural areas of the UK, a state fairly typical of developed, industrialised nations in terms of its demography and socioeconomic characteristics. The paper begins by exploring the relationship between mobility, accessibility and exclusion, with a focus on older people. It then moves on to examine why this is a particular (and developing) issue for this
Ageing and accessibility in a rural context
The focus of this study on older people in rural areas (and their potential for exclusion), is increasingly important, as rural populations are ageing. In more developed countries, such as the UK, the over-60s already make up one-fifth of the population, and by 2050 this may be one-third (UN, 2009). In Europe specifically, the forecast is for older people (those 60 and over) to be 35% of the population in 2050. The proportion of older people in rural areas in these states has also been growing
Methodology
The data underpinning the analyses reported in this paper are drawn from quantitative and qualitative data collection carried out in Southwest England and Wales in 2009–2010. Nine hundred and twenty people over the age of 60 completed a quantitative survey in six different rural locations, with 38 of them then taking part in semi-structured interviews lasting about an hour. The data collection was carried out to help understand community connectivity, including satisfaction with community
Incidence of self-reported exclusion
For participants of the quantitative survey ‘community’ was simply identified as ‘the community in which you live’ and was not further defined. It is assumed that for most respondents that this was interpreted as meaning the immediate spatial community based on the nearest village or rural town. In response to the statement ‘I often feel excluded within my community’, a simple majority ‘disagreed’, but 51 older people (6%) did agree that they were excluded, and another 53 people responded that
Rural mobility exclusion revisited
The empirical findings and analyses have confirmed the importance of mobility as a facilitating factor in social exclusion. In respect of self-identification of overall exclusion within the community, those affected are confirmed as a small minority of around one in 20. For this broad measure, encapsulating all dimensions identified in Section 2, degree of rurality did emerge as a contributory factor. However, considering the role of accessibility within exclusion, the effect of degree of
Conclusions
Despite policy concerns about the quality of accessibility in rural areas, and the multiple risks that older rural citizens face, exacerbated in some cases by declining health and economic resources, a relatively low incidence of self-reported social exclusion was found amongst older citizens in the six rural areas. The multi-faceted nature of social exclusion is supported by the fact that the overwhelming majority of those that described themselves as ‘often excluded’ had access to a car –
Acknowledgements
The research for this paper was supported as part of the Grey and Pleasant Land? project by the UK Research Councils involved in the New Dynamics of Ageing Programme (grant number RES-353-25-0011). The authors acknowledge the insightful discussions with colleagues in the wider project and are grateful in particular to the Workpackage 1 team led by Prof. Nigel Curry for coordinating the quantitative data collection. We are also grateful for advice on statistical analysis given by Dr Eran
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