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The role of the neighbourhood environment in shaping the mental health consequences of Covid-19

The aim of this proposed research is to test to what extent features of the neighbourhood environment moderates the mental health consequences associated with the coronavirus pandemic. While undoubtedly any mental health impact will be partly shaped by individual characteristics, we also posit that there will be differential vulnerability across people due to their neighbourhood environment.


Our starting point is Understanding Society (UKHLS), a survey which collects online data relating to people's mental health. Each individual has a unique identifier meaning that we can track their mental health before, during and after the lockdown, and indeed monitor their mental health on an ongoing long-term basis. Of particular importance for this project is the geographic identifier attached to each individual in the survey. This geographic identifier will allow us to identify the local authority in which each individual lives (391 of these in the UK) and through a special licence application, the lower super output area commonly referred to as the neighbourhood (over 32,000 of these in the UK). Using these identifiers, we will spatially link our longitudinal household survey datasets recording individuals’ mental health with a variety of publically available datasets relating to neighbourhood contextual information (e.g. economic and social deprivation, population density, environmental capital, health services etc.). This will allow us to identify what makes some neighbourhoods produce better outcomes than others. Ultimately, our research will help in identifying those most vulnerable to the coronavirus pandemic and in formulating place based policy interventions aimed at protecting people’s mental health.

Key findings

Main effects

- We find substantive increases in psychological distress for the population overall during the first wave. These impacts were, however, not uniformly distributed.

- The mental health impact for females, younger cohorts, the BAME community, and migrants is much more pronounced.

- Our analysis would suggest that financial worries, health anxiety, social isolation, and crowding stress all played an important role.

Acknowledgments: This work was funded by the Economic and Social Research Council (ESRC), as part of UK Research and Innovation’s rapid response to COVID-19. The underlying data are available upon request, special license data can be acquired from the UK Data Service.

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