Page reviewed June 2020

Risk of dying from Covid-19 is higher for BAME people: Government review summarised

Why do BAME people have a higher risk of COVID?

After public & institutional pressure, the UK government yesterday released the much-awaited report reviewing the risk of Covid-19 for different groups of people. Widely referred to as the “BAME review”, the analysis looked at how various demographic factors and inequalities affect the risk of contracting Covid-19 and getting severely ill or dying from it.

The HSJ reported yesterday that the government removed a key section from the report before publishing it, noting that an earlier draft of the review was circulated within the government last week which contained a section with responses and evidence from over 1,000 organisations. These responses suggested that social inequalities, including discrimination and poorer life chances, contributed to the increased risk BAME people face from Covid-19.

Notwithstanding the omission, we’ve summarised the published report below. You can access it in full here.

Summary of findings

  • This review investigates the disparities in the risk and outcomes from Covid-19 on different groups of people
  • The findings confirm that the impact of Covid-19 has replicated existing health inequalities, and in some cases, exacerbated them
  • People who were aged 80 and older were found to have the highest risk of death
  • Risk of dying was higher in males than females
  • Highest rates of diagnoses and death were in urban areas
  • Risk of dying was higher for those living in more deprived areas
  • Risk of dying was higher for those in BAME groups than White groups, and for those born outside the UK and Ireland
  • Limited data on rough sleepers — 67 recorded diagnoses of Covid-19 among people with ‘no fixed abode’, representing 1.6% of the population who sleeps rough
  • Risk of dying was higher for those in occupations that involve close contact with others, including caring occupations, taxi drivers and chauffeurs, and security guards
  • The analysis takes into account age, sex, deprivation, region, and ethnicity, but not the impact of existing health conditions which may increase the risk of Covid-19 — it only notes where other conditions were mentioned on a death certificate that also mentioned Covid-19

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How was this data collected?

Data for this analysis was taken from an application called Respiratory Datamart and the Second Generation Surveillance System (SGSS), which stores and manages laboratory data. This data contains information about all samples tested and whether they were positive or negative for Covid-19.

When this data was analysed, most tests to confirm Covid-19 were being offered to those in hospital, which means that the number of confirmed cases represents those in hospital with severe disease. Differences in diagnosis rates may then reflect differences in risk of getting the infection, but could also describe whether or not someone presented to hospital, or differences in who is more likely to be tested.

Analysis of ethnicity did not include the effect of occupation, which the review notes is a key shortcoming, as some occupations have a higher proportion of workers from BAME groups. The ethnicity analysis used deaths reported by the ONS to compare inequalities in death rates, comparing death certificates mentioning Covid-19 with all cause death rates for previous years (the ‘baseline all cause’ figure).

Data breakdown

Age and sex

Covid-19 diagnosis rates generally increased with age for both men and women, however were higher among women under 60 and higher among men over 60. Men make up 46% of diagnosed cases yet account for almost 60% of deaths and 70% of ICU admissions due to Covid-19.

Working-age men diagnosed with Covid-19 were found to be twice as likely to die than women. This supports other findings from other countries and institutions: data from the Intensive Care National Audit and Research Centre (ICNARC) has reported that men make up 71% of admissions to the ICU due to Covid-19.

It is not yet fully clear why these differences occur, however trials are underway in the UK and US investigating the role biology and hormones may play

Covid-19 mortality rates increase with age for both men and women, with men aged 35-39 and above and women aged 40-44 and above seeing the most significant risk. Among those who tested positive, people who were aged 80 or older were seventy times more likely to die than those aged under 40. This was found to be true even when taking ethnicity, deprivation, and region into account.

As of May 13, there had been 17,598 deaths in confirmed cases among males (59.3%) and 12,075 in females (40.7%), while 56.3% of deaths were among people aged 80 and older.

It is not yet fully clear why these sex differences occur, however trials are underway in the UK and US investigating the role biology and hormones may play.

Geography

Interestingly, men and women experienced different diagnosis rates in different parts of the country. For men, London had the highest rates of diagnoses and death, while women had higher diagnosis rates in the North East and West Midlands but a higher death rate in London.

Here, more context is required: are ethnically-diverse populations in themselves more at risk, or is the risk created by the social inequality that they experience?

People living in urban versus rural areas were found to have increased odds of testing positive for Covid-19 — a finding that has been replicated by other studies. It is also fairly commonsense: when people are living closer together, they are more likely to come into contact and therefore be exposed to the infection. The review also suggests that deprivation and ethnically-diverse populations within urban areas could also be associated with higher mortality rates from Covid-19.

Here, more context is required: are ethnically-diverse populations in themselves more at risk, or is the risk created by the social inequality that they experience?

Death rates in London from Covid-19 were over three times higher than in the region with the lowest rates, the South West. This is a greater difference in death rates between regions than from deaths from all causes (known as “all cause mortality”).

Deprivation

Mortality rates from Covid-19 in the most deprived areas of England were more than double than those in the least deprived areas, for both men and women. As above, Covid-19 represents a greater difference in death rates than from deaths observed from all causes within these regions between 2014-2018.

High diagnosis rates may be due to geographic proximity to infections — for example, in a council estate in the middle of London — or having an occupation where exposure to the virus is more likely.

The diagnosis rate in the most deprived quintile was 1.9 times the rate in the least deprived quintile for men and 1.7 times among women. A quintile is a data set that represents 20% of a given population.

A more thorough inquiry into how these social inequalities — including racism — affect BAME people’s day-to-day lives and how they can be addressed through policy and service design is needed

Survival among those with confirmed Covid-19 was lower in the most deprived areas, particularly among those of working age. The death rate in the most deprived quintile was 2.3 times that in the least deprived quintile for men and 2.4 times among women — however, male death rates were significantly higher than female rates across all quintiles. Poor outcomes for those in the most deprived areas remained after adjusting for ethnicity.

The review doesn’t suggest why this may be the case, but the impacts of poverty and deprivation on poor health outcomes are clear and well-established. In the context of this pandemic, lower-paid workers may not be able to afford to stay home, may live in households with a higher amount of people and so be unable to isolate, and may face additional barriers to accessing care.

What do you mean by ‘deprivation’?
Deprivation is classified using the Index of Multiple Deprivation, which encompasses a wide range of someone’s living conditions, including income, employment, education, health, crime, housing, and living environment. The review notes that deprived areas can be found both in urban and rural areas of England.

Ethnicity

Black people had the highest rates of Covid-19 diagnoses, and along with Asian ethnic groups, had higher death rates than White people. Diagnosis rates were also lower among White people.

While diagnosis rates were lower in women across all ethnic groups, women in Black, Asian, and Mixed Ethnic groups had higher diagnosis rates than both White men and White women.

After accounting for the effect of sex, age, deprivation, and region, Bangladeshi people had around twice the risk of death than White British people. People of Chinese, Indian, Pakistani, other Asian, Caribbean, and other Black ethnicity had between a 10-50% higher risk of death when compared to White British people.

Racial discrimination plays a role in preventing access to care and making social mobility more difficult

When compared to previous years, all cause mortality was almost 4 times higher than expected among Black men during this Covid-19 period, almost 3 times higher in Asian males, and almost 2 times higher in White males. Deaths among Black, Mixed, and Other females were almost 3 times higher, and 2.4 times higher in Asian females, compared with 1.6 times higher for White women.

Why are BAME people more at risk?
The review says that a combination of factors are likely at play. For one, BAME people are more likely to live in urban areas, in overcrowded households, in deprived areas, and have jobs that expose them to higher risk. The review also acknowledges language and cultural barriers in accessing care services in the UK, and develops on the additional risks introduced by occupation in the Occupation analysis (summarised below). We would add that racial discrimination plays a role in preventing access to care and making social mobility more difficult.

As well as the risk of infection, BAME groups are more likely to have poorer outcomes once they have Covid-19. The review notes that co-morbidities more common among certain ethnic groups can play a role here, for example, that people of Bangladeshi and Pakistani background have higher rates of cardiovascular disease than people of White British ethnicity, while Black Caribbean and Black African people have higher rates of hypertension compared to other groups.

The review doesn’t offer any deeper analysis here, but it has been well-established that social inequalities exacerbate health inequalities.1 A more thorough inquiry into how these social inequalities — including racism — affect BAME people’s day-to-day lives and how they can be addressed through policy and service design is needed. It’s important that BAME people are also included in the design and implementation of these changes.

Occupation

Occupations where workers were more likely to be exposed to the virus, due to close or frequent contact with other people, lead to an increased risk in Covid-19 infection. Healthcare workers (HCPs) were particularly at risk, with others in retail, hospitality, transport, emergency services, and security also at risk. Data from European countries suggests that HCPs may account for 9-26% of those infected.

Among workers that are more likely to be in frequent contact with people and exposed to disease, three in four are women and one in five are from BAME groups

Among workers that are more likely to be in frequent contact with people and exposed to disease, three in four are women and one in five are from BAME groups. An analysis of 119 deaths from NHS workers showed that a disproportionate amount of BAME staff had died.

The ONS has reported that men working in ‘low-skilled’ occupations had the highest rate of death due to Covid-19 up to April 20, 2020. Men and women working in social care also had significantly higher rates of death from Covid-19.

People born outside the UK & rough sleepers

This section of the review looks at two groups that experience social exclusion: migrants and homeless people. These groups generally have poor health outcomes, in part due to the multiple and overlapping barriers that prevent them from accessing adequate care. To boot, these people are not consistently recorded in electronic records, which effectively makes them invisible to those in service and policy planning.

A recent modelling exercise estimated that if no action were to be taken (a “do nothing” scenario), 34% of people living in hostels and sleeping rough would be infected with Covid-19, leading to over four thousand hospital admissions. Of those with “no fixed abode”, 54 men and 13 women were diagnosed with Covid-19, which is estimated to represent 2% and 1.5% of the known women and men respectively who experienced rough sleeping in 2019.

This information doesn’t really give us enough insight to understand what would be causing these disparities and more importantly, how we can make policy and procedure changes to action them

The biggest relative increase in deaths for those born outside the UK was from people born in Central and West Africa (including Nigeria, Ghana, and Somalia). For people born in four other groups of countries, deaths in 2020 were more than 3 times higher than the equivalent period in 2014-2018: the Caribbean, South East Asia (including Malaysia, the Philippines, and Vietnam), the Middle East, and South and Eastern Africa (including South Africa, Zimbabwe, and Kenya).

This information is indicative but quite general, and doesn’t really give us enough insight to understand what would be causing these disparities and more importantly, how we can make policy and procedure changes to action them. The review does point towards factors that prevent these groups from accessing care but does not commit to specifically calling anything out.

Deaths in care homes

By April 10 2020, deaths in care homes accounted for 10% of all deaths from Covid-19 in England. This percentage has increased over time, sitting at 43% by May 8, compared with 50% for hospitals.

The review estimates that 38% of care homes in England experienced an outbreak, while deaths in care homes were around 2.3 times higher than expected between March 20 and May 7.

Comorbidities

While the review didn’t focus as heavily on this, it does include some findings relating to existing conditions that have been associated with a higher risk of Covid-19. Data for this section was collected by looking at other conditions mentioned on death certificates that also mentioned Covid-19.

Diabetes was mentioned on 21% of death certificates where Covid-19 was also mentioned. This proportion was higher in all BAME groups (43% in the Asian group and 45% in the Black group) when compared to White ethnic groups. The same disparities were seen for hypertensive disease, which refers to heart conditions caused by high blood pressure.

A higher percentage of death certificates that mentioned Covid-19 also mentioned diabetes, hypertensive diseases, chronic kidney disease, chronic obstructive pulmonary disease, and dementia, than all cause death certificates.

What should I make of these findings?

The information within this review describes correlations between various demographic factors and Covid-19 outcomes. That means that it establishes a connection between these factors, but does not prove that one factor causes the other. Finding correlations between groups of people and health outcomes can be very useful in identifying inequalities, and pointing us in the direction for what we need to investigate if we want to figure out what is really causing those inequalities.

This review has been criticised for simply reiterating existing findings and failing to provide practical guidance or recommendations

A limitation of this is that sometimes, labels that we use when measuring demographics can invite generalisation, which can carry through to oversimplification or even ignorance when considering how factors correlate.

If labels are too broad, for example, ‘People in West Africa and Central Africa’, then our findings may lead to generalisations about the huge amounts of people that live in this area, including the different countries within it. Accepting generalisations may also prevent us from going deeper and really trying to understand the experiences of a given group.

This review has been criticised for simply reiterating existing findings and failing to provide practical guidance or recommendations. The British Medical Association (BMA), a professional body for doctors in the UK, called it a “missed opportunity” to make important change.

The next, and most important, step following this review is to dive deeper into understanding why the inequalities this report has identified occur and how they can be addressed through policy and service change. Sadiq Khan is among those who has called for a public inquiry into the higher death rate among BAME people.

Featured image is an outline illustration of a woman wearing a face mask. She is outlined in white against a black background

Page last updated June 2020

Monica Karpinski

Founder & Editor, The Femedic

Monica is the Founder and Editor of The Femedic. Against a journalism background and after years of leading content marketing projects in the healthcare space, it became clear that health information out there for women simply wasn’t good enough. No-one had bothered to look deeper into the ways women were searching for information, or consider the depth of what they actually needed to know. Instead of waiting for the perfect publication to approach her, she created The Femedic.

Monica has been named one of The Drum’s 50 under 30 for influential women in digital 2018 and was shortlisted for Female Entrepreneur of the Year in the 2018 British Business awards. She speaks and writes widely on gender and health inequality.

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References

  1. National Research Council (US) Committee on Future Directions for Behavioral and Social Sciences Research at the National Institutes of Health, ‘The Influence of Inequality on Health Outcomes,’ in Singer, B.H., and Ryff, C.D (ed.), New Horizons in Health: an Integrative Approach, Washington DC, National Academies Press, US, 2001 [online] (accessed 3 June 2020)