by Dr Helena Tunstall, REALITIES researcher

The REALITIES research consortium cuts across give geographic locations in Scotland, each with their own community hubs, where third sector organisations and local council representatives have developed arts, gardens and other creative community projects. Within these REALITIES ‘hubs’ in Clackmannanshire, Easter Ross, North Lanarkshire, Dundee, and Edinburgh, community embedded researchers (CERs) are working with academic researchers to co-research how community projects can support health and wellbeing.

The REALITIES consortium includes quantitative academic researchers working with statistical data describing local community resources. The research collaboration between REALITIES community groups and quantitative researchers has highlighted questions regarding the relationship between community groups’ work, community experiences and community representation in local statistical data:

• How are local statistical measures used in community groups’ work?
• How do statistical measures of communities’ characteristics compare to local perceptions?
• Are both statistical measures and perceptions of local areas related to health and wellbeing in communities?

How REALITIES’ community groups use local statistical data

Much of the REALITIES’ community groups’ work providing services in their communities is shaped by their knowledge of their localities and the people that use their services, developed through their work. However, statistical data are often required at the ‘interface’, with outside organisations in funding and governance tasks. Statistics are used by community groups in funding bids, end of funding reports and trustee reports. Funders may require targeting on particular population groups or neighbourhoods, so community groups often require evidence of local population characteristics and disadvantages.

The Indices of Multiple Deprivation (IMD) are commonly used by community groups (Braggins and Sollazzo, 2017), including those participating in REALITIES. Demographic data, such as statistics from Office for National Statistics and National Records of Scotland, also can be useful for their work. These deprivation and demographic datasets can describe small neighbourhoods and have national coverage, supporting comparisons between different neighbourhoods and regions.

Some types of statistical data capturing aspects of local areas that are important to many community groups’ work are, however, difficult to access.  In particular, data describing social relationships, including informal social networks and, conversely, loneliness. REALITIES community groups also find that it is not always easy to access data describing community services available in their areas, making it difficult to demonstrate gaps in provision.

Comparing ‘subjective’ and ‘objective’ measures of neighbourhoods

Within academia, health and social researchers have assessed ‘subjective’ and ‘objective’ measures of neighbourhoods to compare their roles in shaping health and wellbeing of local populations. In these analyses, ‘subjective’ perceptions of neighbourhoods are often represented by data from surveys that have collected residents’ views of their areas. These have been compared to ‘objective’ neighbourhood data from official administrative sources.  These two kinds of evidence don’t always tell the same story: ‘objective’ data from official sources are often seen as ‘better’, but may not capture aspects of local environments that are important to residents.

Some of the best-known work comparing subjective and objective measures of neighbourhoods has focussed on ‘fear of crime’, assessing both peoples’ perceptions of risk of crime in their local area, and official crime statistics. Researchers have also compared subjective and objective measures of positive resources in communities, including natural spaces. For example, a UK study which assessed the availability and use of local neighbourhood gardens, parks, woodlands and other ‘green space’, found that statistical measures of the quantity of these spaces were not a predictor of how often people visited them (Flowers et al, 2016). Instead, people’s perception of the quality of their local green space predicted their visit frequency.

Evidence suggests that subjective perceptions of local neighbourhoods can be important in their own right as they affect behaviour and wellbeing. Policies to improve physical and social infrastructure may need to draw on both objective statistical measures and subjective perceptions of the characteristics of neighbourhoods to maximise benefits to health and wellbeing.

Within REALITIES, we are currently developing statistical analyses comparing subjective and objective measures of crime, air pollution and social cohesion, and assessing how they relate to health. This analysis uses survey data from the UK Household Longitudinal Survey, ‘Understanding Society’, and compares these survey respondents’ perceptions of their residential neighbourhoods to neighbourhood statistical data, including data from the Indices of Multiple Deprivation. This analysis will assess whether commonly used statistical data sources describing neighbourhood resources predict residents’ perceptions of their neighbourhoods and compare how these subjective and objective measures are related to their wellbeing.

References

Braggins, M. and G. Sollazzo (2017). “Data for the Community: Taking a look at how data assets are being used at a local level.”  WP-2017-07-Data for the community.pdf

Flowers, E. P., Freeman, P., & Gladwell, V. F. (2016). A cross-sectional study examining predictors of visit frequency to local green space and the impact this has on physical activity levels. BMC Public Health, 16, 420. https://doi.org/10.1186/s12889-016-3050-9