Resetting the relationship between local and national government. Read our Local Government White Paper

Health inequalities: Ethnicity and COVID-19

It became clear early in the pandemic that ethnicity was a factor in both the impact and outcome of the disease.

Health inequalities banner

This forms part of the LGA’s A Perfect Storm report, published April 2021.

In July 2020, Public Health England (PHE) examined the extent of that impact and found that people of Black, Asian and other minority ethnic (BAME) groups were more exposed to COVID-19, more likely to be diagnosed with it and more likely to die from it than those of white ethnicity (COVID-19: Review of disparities in risks and outcomes). 

The reasons for this are multi-layered. Deprivation, low income, minority ethnicity, and poor housing are often interlinked and have all been found to be associated with an increased risk of COVID-19, demonstrating that existing health inequalities mean an inequitable starting point for how well people survive the pandemic.

The complexity of these interconnecting factors means that there is no simple one size fits all solution to reduce health inequalities amongst those in our black, minority and ethnic communities. In addition, BAME is not one homogenous group and the impact of COVID-19 is different for different ethnic populations.  

Tackling London’s ongoing COVID-19 health inequalities, a blog by PHE’s regional director of public health for London, Kevin Fenton, revealed that ethnicity continued to feature alongside deprivation as a major factor in the health outcomes of communities in the city during the second wave of the pandemic.

Case rate and mortality data showed London’s Asian populations were worst affected during the second wave to early February, followed by Black communities, with both communities experiencing significantly higher case rates and deaths than their White counterparts. In England overall, it was Pakistani and Bangladeshi men who fared worst during the second wave.

There are underlying factors influencing health outcomes that affect minority communities in particular – demographics, existing conditions, health behaviours and family structures are all contributors that have been identified in national literature.

People in BAME populations are more likely to be in occupations that mean they cannot work from home so must travel to work, very often on public transport - indeed their job may involve working on public transport, coming into contact with other people on a daily basis. Many of our ethnic minorities work in health and social care, directly exposing them to the virus.

Conclusion

It is clear that ethnicity alone is the main driver for the impact of COVID-19 amongst minority ethnic communities, but rather the combination of other factors that are prevalent within ethnic groups. 

Deprivation has been shown to be a key driver for high transmission and impact of the virus. BAME communities are more likely to live in densely populated areas with overcrowded housing. This makes household isolation much more challenging and increases the risk of intra-household transmission.  Moreover, those from BAME communities are also more likely to live in a multigenerational house where grandparents, parents and children all live together. This may contribute to explaining higher death rates in BAME populations where vulnerable older adults or those in shield categories may find it harder to isolate. 

Underlying health conditions such as diabetes, obesity, cardiovascular disease and chronic kidney disease which have been shown to be associated with higher mortality rates are all more prevalent in BAME communities. 

Finally, occupational risk has been shown to have played a key part in driving infection, particularly in the first lockdown period. Occupations classed as critical which continued during lockdowns were often staffed by a higher proportion of those of BAME background such as healthcare workers, taxi drivers and security guards. 

While it is difficult for councils to know what interventions to implement, it is clear that structural change is necessary. Reduce deprivation and much of the associated problems dissipate to an extent. This means greater support for education and employment in order to aid recovery and make progress against health inequalities.

Case studies