Investigating socioeconomic, household and environmental risk factors for Covid-19 in Scotland

This study aims to use linked administrative data for a large cohort of the Scottish population to enhance our understanding of how the occupational, household and environmental circumstances in which people live impact the risk of adverse Covid-19 outcomes.

Research focus

There is growing evidence that a range of social and environmental factors may put some groups at greater risk in the Covid-19 pandemic. Some of these risks may arise from the occupations that individuals do: the extent to which they work in close proximity with others or are unable to work from home, for example. Others may stem from household and housing conditions, notably larger household size and levels of overcrowding, or from environmental factors such as exposure to air pollution. These risk factors may help explain why the impacts of Covid-19 have been so much worse for groups with lower socio-economic status. A better understanding can therefore inform immediate responses to the pandemic but also longer-term efforts to reduce social inequalities as a form of public health intervention.

As part of the Covid-19 Data Intelligence Network and Covid-19 Data Taskforce, a research team from the Scottish Centre for Administrative Data Research (SCADR) has been tasked by Scottish Government to investigate the socioeconomic, household and environmental risk factors for Covid-19 health outcomes. In this study we plan to combine individual-level health records from Public Health Scotland Covid-19 Research Database with:

(i) individual-level demographic and socioeconomic information derived from 2011 Census;

(ii) innovative household-level information derived from Ordnance Survey’s Unique Property Reference Number for each address in Scotland;

(iii) area-level environmental data from a range of publicly available sources.

The assembled linked administrative dataset will be used to analyse the risk of testing positive for SARS-CoV-2, being admitted to hospital with Covid-19 symptoms, receiving critical care and death due to Covid-19 disease. The study will identify how underlying health conditions in both the general population and among those shielding mediate the effects between exposure to socioeconomic and environmental factors and adverse Covid-19 health outcomes.

Data sources

  • Unique Property Reference Number (UPRN)
  • Community Health Index (CHI)
  • 2011 Census
  • Primary care data (GP consultations; GP Out of Hours; NHS 24 calls; Scottish Ambulance Service (SAS); Prescribing information; Shielded Patient List)
  • Secondary care data ( Emergency admissions (A&E); Acute hospital admissions (Scottish Morbidity Record: SMR01); Critical care admissions (Scottish Intensive Care Audit Group: SICSAG); Unscheduled Care Deaths (UCD) )
  • Virology and serology data ( Electronic Communication of Surveillance in Scotland (ECOSS) )
  • Mortality data ( National Records of Scotland (NRS) Deaths)
  • Property data (Scottish assessors dataset; Council tax band data)
  • Environmental data ( Air pollution data; Ultra violet radiation (UVA and UVB) data)
  • HMRC data (Coronavirus Job Retention Scheme (Furlough scheme) data; Self-Employed Income Support Scheme data)

What this will enable researchers to do

By using linked administrative data at individual, household and area-level, we aim to obtain a more accurate estimation of the social (non-health) risk factors associated with Covid-19 outcomes, compared to area-level proxy indicators for socioeconomic position that are often used in epidemiological studies in this area. This will improve our understanding of the consequences of Covid-19 disease for at-risk vulnerable groups in the population, including those advised to shield due to underlying health conditions and those living in households with a shielded individual. The results of this study will help to inform current and future government policy responses, as lockdown measures are lifted and continuing interventions are needed to contain the resurgence of infections among vulnerable groups.

Research Team

Serena Pattaro (Project Lead), Professor Nick BaileyGina Anghelescu and Professor Chris Dibben 

Publications, Outputs and Media Coverage

For more information about this project, please contact us.

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