Questions and answers about coronavirus and the UK economy

Is mental health among ethnic minorities worse affected by the pandemic?

Covid-19 is disproportionately affecting the physical and mental health of black, Asian and minority ethnic people in the UK, exacerbating existing inequalities. Bangladeshi, Indian and Pakistani men have suffered the highest increase in mental distress.

The pandemic appears to be affecting the health of black, Asian and minority ethnic people in a disproportionately damaging way (see, for example, Bentley, 2020; Kirby, 2020). This disadvantage is observed in the general population and among health and care workers (for example, Razaq et al, 2020).

A report from Public Health England, investigating the disparities in the risk and outcomes from Covid-19, reveals that ‘the impact of Covid-19 has replicated existing health inequalities, and in some cases, increased them.’ (Public Health England, 2020). Most studies have focused mainly on physical health – but what about mental health? 

It is important to understand whether, in addition to the higher risks of infection and serious illness from Covid-19 facing black, Asian and minority ethnic people, they also suffer greater deterioration in their mental health. Health and socio-economic inequalities by ethnicity - which have been exacerbated by the pandemic via differential exposure to infection and health risks (including mortality) as well as differential exposure to income losses (Platt and Warwick, 2020) - could be made even worse through greater deterioration of mental health.

Related question: How is coronavirus affecting inequalities across ethnic groups?

What does the evidence from research tell us?

Much has been written about the differential effects of the pandemic by age and gender. The 12-item General Health Questionnaire (GHQ-12) – a screening device for identifying minor psychiatric disorders, with higher scores indicating higher mental distress – can be used to compare mental distress before (2017-19) and after the beginning of the pandemic (April 2020) among individuals interviewed in the UK Household Longitudinal Study (Understanding Society or USoc hereafter).

The data show that the mental distress of the 14,289 individuals interviewed before and after the beginning of the pandemic increased by 11%. Men suffered a 7.5% increase in mental distress, while for women, the increase was larger, at 13.5%.

The much larger reduction in women’s mental health relative to men’s, as measured by the GHQ-12, has been reported elsewhere (Banks and Xu, 2020; Daly et al, 2020; Etheridge and Spantig, 2020). Age and gender seem to be the main explanatory factors behind the GHQ-12 inequality (Davillas and Jones, 2020).

With age, the larger drop in mental health is found among younger individuals (Banks and Xu, 2020; Daly et al, 2020). Gender differences across socio-economic and wellbeing dimensions, including measures of anxiety (General Anxiety Disorder-7), also emerge in an online sample of approximately 1,500 respondents after three months of lockdown (June 2020) in the UK (Oreffice and Quintana-Domeque, 2020). 

Much less is known about how mental health has changed before and after the beginning of the pandemic among ethnic groups. Similar increases in mental health problems are found between white and non-white individuals between 2017-19 and April 2020, after removing the influence of factors such as age, sex, marital status, education, income and vulnerability to the health effects of Covid-19 (Daly et al, 2020). 

But it is important to note that the non-white community is a very heterogeneous group, which raises the question: are there differential effects on mental health deterioration among black, Asian and minority ethnic people? 

Using the same data source, a recent study quantifies the changes in mental distress before (2017-19) and after the pandemic (April 2020) by ethnicity and gender (Proto and Quintana-Domeque, 2020). Black, Asian and minority ethnic people suffered a 12.8% increase in mental distress, from a score of 11.60 to 13.08 (1.48 units), while British white individuals suffered an increase of 10.9%, from a score of 11.05 to 12.26 (1.21 units). As recorded elsewhere (Daly et al, 2020), the differential increase is not statistically significant when respondents are considered all together. 

But the situation changes dramatically when respondents are separated by gender. Figure 1 shows that black, Asian and minority ethnic men report a 14.1% increase in mental distress, from 10.91 to 12.45 (1.54 units), while for British white men, the increase was 6.5%, from 10.32 to 10.99 (0.67 units).

The differential increase is 7.6 percentage points, which is statistically significant and sizeable, similar to the 6 percentage point’s gap in mental health deterioration between men and women. The mental distress for women, regardless of ethnicity, is very similar to that experienced by black, Asian and minority ethnic men. 

The higher increases in mental distress among black, Asian and ethnic minority men might be explained by several factors, including differences in age, geographical locations, income, education, occupational choices, employment status, family structure, presence of co-morbidities, among others.

While all are plausible factors, there is no evidence that the differential increases reported among black, Asian and ethnic minority men are explained by differences in these variables, although these variables are relevant factors in explaining changes in mental health. For example, people living in London and Scotland have suffered a higher increase in mental distress (0.5 units more) compared with individuals living in England (excluding London).

A similar picture emerges for self-employed and retired individuals, whose mental distress has increased 0.5 units more than people who are employed. Within the sample of working individuals, the geographical patterns disappear once adjustment is made for the type of job: those classified as ‘small employers or own account’ have suffered a larger increase in mental distress (1.1 units more) compared with individuals classified as working in ‘management and professional’ occupations. 

Neither marital status nor household size predict changes in mental health. Similarly, both net personal income and being classified as clinically vulnerable to the health effects of Covid-19 are not predictors of mental health deterioration.

Figure 1: Average mental distress (GHQ-12) in 2017-19 and April 2020 among BAME (black, Asian and ethnic minority) and British white individuals by gender

Graph showing average mental distress across ethnicities and genders
Notes: The black lines represent 95% confidence intervals: if the confidence intervals for two groups/periods overlap, the averages are not statistically different at the 5% significance level across the two groups/periods. Authors’ elaboration using USoc data (Proto and Quintana-Domeque, 2020).

Figure 2 reveals that there is substantial heterogeneity across different ethnic groups, although these estimates need to be taken with caution given the smaller sample sizes - the largest non-British white group, with 709 respondents, is Bangladeshi, Indian and Pakistani) and the smallest one, with 25 respondents, is Arab. 

Bangladeshi, Indian and Pakistani respondents experienced an increase in mental distress of 2.11 units – from 11.61 to 13.72. This is a 18.22% increase, higher than that among British white individuals. Arab respondents suffered from a sizeable increase in mental distress, albeit this is not statistically significant due to the very small sample size for this group, which translates into a wide confidence interval.

Figure 2: Average mental distress (GHQ-12) in 2017-19 and April 2020 among British white and other ethnic groups (top panel) and differences in average mental distress from 2017-19 to April 2020 (bottom panel).

Graph comparing changes in mental health across ethnic groups
Notes: BIP stands for Bangladeshi, Indian and Pakistani. The coloured lines represent 95% confidence intervals: if the confidence intervals for two groups/periods overlap, the averages are not statistically different at the 5% significance level across the two groups/periods. Authors’ elaboration using USoc data (Proto and Quintana-Domeque, 2020).

Related question: How might social isolation affect people's wellbeing during the pandemic?

What does this mean for policy? 

The pandemic is disproportionately affecting both the physical and mental health of black, Asian and minority ethnic people, and this could have dramatic consequences for the exacerbation of existing health and socio-economic inequalities. Given the well-established link between productivity and psychological wellbeing (see Proto, 2016, for a review), the greater deterioration in mental health among black, Asian and minority ethnic people could lead to an increase in wealth inequality. 

The differential deterioration in mental wellbeing of British white individuals and black, Asian and minority ethnic people mirrors to some extent the higher risk of infections and severe illness, but there are important differences:

  • First of all, the differential drop in mental wellbeing by ethnicity seems to exist only among Bangladeshi, Indian and Pakistani respondents and perhaps Arab groups, but not among black, Chinese or mixed ethnicities. 
  • Second, the differential drop is found only among men; no differential drop is detected among women. 
  • Third, the differential deterioration in mental health is not explained by differences in age, education, income, place of residence, employment status, type of job or existing co-morbidities increasing the Covid-19-related risks. 

Future work should focus on the biological, social and structural differences between ethnic groups that might explain the differential deterioration of mental wellbeing. This investigation is necessary to design effective policies that address the ethnic divide in the negative consequences of the pandemic.

From an economic point of view, it is important to understand whether (and to what extent) tax and spend policies or greater support for public services might ameliorate the negative consequences of the current (or future) pandemic(s) on the wellbeing and mental health depreciation among black, Asian and minority ethnic individuals. 

With this aim in mind, it will be crucial in the near future to collect more data on ethnic minority groups and vulnerable populations in general (Jackson et al, 2019). The evidence described above, mostly based on USoc, has emphasised some of the limitations of existing data sets, including the small number of black, Asian and minority ethnic people who are surveyed. This echoes the recent calls for monitoring of ethnic differences in all areas of life.

Recent efforts in this direction can be seen in the Covid-19 Social Study run by University College London, which is collecting data during the pandemic. Over 4,500 black, Asian and minority ethnic individuals had taken part in the study by 28 June, and they have had higher levels of depression and anxiety across the pandemic (Fancourt et al, 2020). This and future data collection will be important to understand how (and why) the pandemic is affecting ethnic groups. 

Where can I find out more?

Why are people in some socio-economic groups more vulnerable to coronavirus? Michèle Belot and Otto Lenhart show that Covid-19 infections and mortality have been more prevalent among disadvantaged groups of people in the UK and elsewhere. Differences in vulnerability seem to result from a combination of socio-economic differences in exposure to the disease, health behaviours and health conditions.

Covid-19: understanding the impact on BAME communities: A summary of stakeholder insights into factors affecting the impact of coronavirus (Covid-19) on Black, Asian and minority ethnic (BAME) communities.

At greater risk: why Covid-19 is disproportionately impacting Britain’s ethnic minorities: Lucinda Platt and Ross Warwick investigate recent claims that minority ethnic groups are being worse affected by Covid-19. 

Ethnic differences in effects of Covid-19: household and local context: Alita Nandi and Lucinda Platt examine ethnic differences in the experience of the pandemic focusing on the role of household and neighbourhood characteristics.

Socio-economic determinants of Covid-19 infections and mortality: evidence from England and Wales: Filipa Sá uses data on Covid-19 infections and mortality for small local areas in England and Wales to study the link of Covid-19 with socio-economic factors.

The colour of money: how racial inequalities obstruct a fair and resilient economy: A report by Omar Khan (Runnymede Trust) on economic inequality and racial inequalities in the UK.

Who are experts on this question?

Authors: Eugenio Proto, University of Glasgow, and Climent Quintana-Domeque, University of Exeter

Published on: 15th Aug 2020

Last updated on: 15th Aug 2020

Funded by

UKRI Economic and Social Research Council
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