By Danielle Sinnett, Issy Bray, Harry West and Owain Hanmer
A recent study, using Bristol City Council’s Quality of Life data, has found that neighbourhood satisfaction, wellbeing and life satisfaction are all related to how satisfied residents are with their greenspaces.
Mental health, particularly for urban populations, is a growing public health concern. There is good evidence about the importance of green and blue infrastructure, including parks, street trees, rivers and other water features, for the wellbeing of urban residents. There is also emerging evidence about the benefits of certain ‘grey’ features, such as historic buildings and transport infrastructure, including active travel routes and public transport. Other features, such as proximity to heavily trafficked roads or derelict buildings, are associated with negative impacts. To date, these different forms of infrastructure have tended to be explored individually rather than looking at the complex interactions between them.
It is important to plan and develop towns and cities that maximise population wellbeing, and related health and social outcomes, at the same time as contributing to the sustainability agenda. Our increasingly urban economy has deepened inequalities, which we know to be a driver of poorer physical health, life satisfaction and other social outcomes. We also know that interventions that are accessible to everyone, like green-blue-grey infrastructure, are one of the most effective approaches to reducing inequalities.
Our approach
Our research used Bristol’s Quality of Life data as well as data on the green (e.g. proximity to parks, neighbourhood trees), blue (e.g. proximity to rivers) and grey (e.g. access to bus stops, density of listed buildings) infrastructure in the city to investigate relationships between green-blue-grey infrastructure and a range of health and social outcomes in neighbourhoods across Bristol.
The Bristol City Council Quality of Life survey has been running since 2001 and provides an annual snapshot of the quality of life across Bristol. The survey includes up to 190 indicators of quality of life and wellbeing of residents, and between 3,000 and 5,000 Bristol residents respond each year. Our project analysed anonymised data from 2011-2022 using geographical information systems and logistic regression models to explore the associations between green-blue-grey infrastructure and the following self-reported outcomes:
- Neighbourhood Satisfaction
- Life Satisfaction
- Wellbeing (Short Warwick-Edinburgh Mental Wellbeing Scale)
- General Health (self-reported over 12 months).
We took sociodemographic neighbourhood factors into account in the analysis. Importantly, the Quality of Life Survey also asks residents about their satisfaction with green-blue-grey infrastructure, including local greenspaces, bus services, leisure and cultural facilities. This meant that we could explore people’s perceptions of these features as well as their distance to people’s homes. This is useful as we know that sometimes people can feel that local facilities are not accessible to them even though they might be close to home.
Key findings
Interestingly, none of the measures of proximity to greenspace, rivers, amenities or neighbourhood levels of greenery were significantly related to the health-related outcomes we examined.
However, those who were more satisfied with their greenspaces were more likely to have greater levels of neighbourhood satisfaction, life satisfaction and wellbeing. It is difficult to tell how people interpret satisfaction with greenspace and it is likely that they are thinking about the availability of greenspaces within their neighbourhood, the city as a whole and the quality of those spaces. This is important as many studies only explore proximity and often fail to find a relationship, whereas examining how people perceive their greenspaces might be a better measure.
Similarly, in terms of grey infrastructure, residents who were more satisfied with their local amenities were also more likely to be satisfied with their neighbourhoods and have greater life satisfaction. Specifically, satisfaction with museums was related to both these outcomes and satisfaction with leisure centres, bus services and libraries was related to neighbourhood satisfaction.
Those who felt a greater sense of belonging in their neighbourhood, and those who were more satisfied with the safety and noise levels in their neighbourhood, and neighbourhood noise were also more likely to have greater neighbourhood and life satisfaction. Levels of street litter were also related to neighbourhood satisfaction.
Some unexpected findings were that those who lived further away from outdoor leisure centres were more satisfied with their neighbourhoods, and those in neighbourhoods with less garden coverage had greater life satisfaction and those further from a train station had greater wellbeing. We think this may be due to differences between more urban and suburban neighbourhoods that tend to have worse access to other amenities. Similarly, those who lived closer to a bus stop had lower life satisfaction, which could be due to heavily trafficked nature of the main roads in the city, which tend to also be the major bus routes (i.e. this is actually measuring dissatisfaction with living close to busy roads).
We did not find a relationship between any of the green-blue-grey infrastructure factors we explored and general health, which was very strongly associated with socioeconomic factors.
Summary of findings
Conclusions
Satisfaction with greenspace was the most consistent predictor of the wellbeing outcomes we considered. There was notable variation across the city, for example, neighbourhoods in South Bristol have similar levels of greenspace access and greenery as those in North Bristol, but greenspace satisfaction in these areas is much lower. This emphasises the importance of the quality of greenspace, and other improvements to neighbourhood infrastructure, for example, to enable people to visit their greenspaces.
Further information
We have produced a Story Map where you can explore some of the data: https://arcg.is/08WSir
And an animation: https://youtu.be/4TueNcibsmM