What accounts for ‘England’s green and pleasant land’? A panel data analysis of mental health and land cover types in rural England
This study was published here in Landscape and Urban Planning.
The point of this piece of work was to investigate links between health and the natural environment in rural areas. Since rural areas are dominated by ‘greenspace’ (in terms of quantity) the sorts of measures used in other studies (including our own), such as ‘% area that is greenspace’, are not necessarily very good at representing the type of environments that rural residents live in. To investigate this, we used data from the British Household Panel Survey (BHPS). The BHPS followed around 10,000 people every year for 18 years from 1991, we’ve published work on urban residents using this data previously, e.g. this study. We then linked small area data on land cover types (from the UK Land Cover Map) to the areas in which BHPS participants lived each year, and related this to measures of mental health.
One of the key challenges with this type of analysis is that we lack environmental data that has been collected consistently over time to link with the survey data. In this case we just used land cover data for 2007, and presumed this to be constant across the study period (1991-2008). This no doubt introduces some error, but it’s the best we can do at the moment.
The findings were somewhat mixed, but did suggest that when we look at the health of people people moving home between rural areas with different environmental characteristics, certain land cover types appeared to be more beneficial for mental health. These included broadleaf woodland, coastal areas and grassland, this is to some extent in accord with findings from our study using data from the Census (described here).
This type of analysis is very powerful, because it follows people over time, and therefore overcomes some of the key limitations of studies such as our ‘snapshot’ analysis of the Census. Future research of this type could help to add further weight to the evidence base, and would benefit from larger, longitudinal population data in conjunction with longitudinal environmental data to thoroughly investigate changes over time and space.
We reflect on what these studies mean in a post here.