This Is How Seriously a Patient’s Skin Colour Can Affect the Quality of Medical Care They Receive
Why Read This
What Makes This Article Worth Your Time
Summary
What This Article Is About
Professor Devi Sridhar, Chair of Global Public Health at the University of Edinburgh, uses new Guardian reporting to make an evidence-based case that race and ethnicity are directly linked to the quality of healthcare people receive. She introduces the concept of the “ethnicity pain gap” — the documented pattern in which patients from Black, Asian, and mixed ethnic backgrounds are offered fewer and lower doses of pain-relieving medication than white patients, even when age, cancer type, deprivation, and other variables are controlled for. In maternal care, Black women are stereotyped as having a higher pain tolerance while Asian women are dismissed as over-demanding, and both groups are less likely to receive an epidural during childbirth despite requesting one.
Sridhar argues that acknowledging this data is only a first step, and goes on to outline four evidence-based interventions: routine collection of racial and ethnic disparity data; awareness-raising about unconscious bias among all healthcare staff; standardised clinical pathways and checklists that reduce individual bias at key decision points; and committed leadership that makes the ethnicity pain gap an organisational priority. She concludes with a personal note — as a woman of South Asian heritage who has lived across multiple countries — that skin colour is a superficial biological trait reflecting melanin adaptation, and that the genetic similarities between all humans far outweigh the differences.
Key Points
Main Takeaways
The Ethnicity Pain Gap Is Real
Multiple studies confirm that patients from Black, Asian, and mixed ethnic backgrounds consistently receive fewer and lower doses of pain relief than white patients, across all healthcare settings.
Stereotypes Drive the Gap
Black women are falsely assumed to have higher pain tolerance; Asian women are dismissed as over-demanding. Both harmful stereotypes lead to women being ignored when they request pain relief during childbirth.
Data Collection Is the First Fix
What gets measured gets improved. Healthcare organisations must routinely collect, share, and act on racial and ethnic disparity data with clear accountability — just as they do for infection rates and waiting times.
Standardised Pathways Reduce Bias
Checklists, clinical protocols, and objective criteria at key decision points — such as epidural access during labour — reduce the role of unconscious or conscious bias in individual medical decisions.
Leadership Sets the Culture
Unless organisational leaders explicitly prioritise the ethnicity pain gap, it disappears from view. Cultural change — not just individual training — is essential to achieving equitable healthcare outcomes.
Skin Colour Is Biologically Superficial
Skin pigmentation reflects ancestral melanin adaptation to sunlight and UV exposure — a minor biological variation. The genetic similarities between all human populations vastly outweigh ethnic differences.
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Article Analysis
Breaking Down the Elements
Main Idea
Race Shapes Medical Care — and Evidence Can Fix It
Sridhar’s central argument is that the ethnicity pain gap is not conjecture but a well-documented, evidence-based phenomenon affecting pain relief in childbirth and cancer care alike. Beyond diagnosis, she pivots to four concrete, systems-level interventions — making this as much a policy prescription as a problem statement.
Purpose
To Persuade and Prescribe
Sridhar writes to persuade a potentially sceptical, politically mixed readership that racial health disparities are a matter of evidence rather than ideology — and then to prescribe actionable remedies. By deliberately sidelining the accusatory framing of “racism” in favour of data and systems thinking, she aims to build consensus across political lines and pre-empt defensive resistance from healthcare practitioners.
Structure
Political Context → Evidence → Solutions → Personal Close
The article opens by situating itself within the current political backlash against DEI, then pivots to evidence (maternal care, cancer care), introduces the ethnicity pain gap concept, transitions to a solutions framework (four numbered interventions), and closes with a personal biographical reflection. Contextual → Expository → Prescriptive → Personal.
Tone
Measured, Authoritative & Quietly Urgent
Sridhar deliberately moderates her tone to avoid inflammatory language, foregrounding data over outrage. Yet the piece carries a quiet moral urgency — particularly in the personal closing paragraphs — that gives it emotional weight without sacrificing the credibility she needs to reach a politically diverse audience. Evidence-driven, yet humanised throughout.
Key Terms
Vocabulary from the Article
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Tough Words
Challenging Vocabulary
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A strong negative reaction by a large number of people against a social or political development, often seeking to reverse recent progress.
“We are now seeing a backlash from certain political groups against diversity initiatives.”
Subjected to widely held but oversimplified and fixed assumptions about a particular group of people, applied to an individual without regard for their actual characteristics.
“Black women are stereotyped as having ‘thick skin’ and being able to tolerate pain.”
In research methodology, statistically accounting for the potential influence of a variable so it does not distort the relationship being studied between two other factors.
“…even after controlling for patient age, cancer type, health condition, deprivation and other variables.”
To make a belief, feeling, or impression disappear or be dismissed by proving it to be false or unfounded through evidence or reasoning.
“…training for medical professionals to dispel myths such as that Black patients have a higher pain tolerance.”
Existing only at the surface level; lacking depth or significance. Sridhar uses it to argue that skin colour reflects a minor biological variation with no deeper implications for how a person should be treated.
“I think my skin colour is the most superficial thing about me, and about others.”
A tendency to respond to criticism or perceived threats with protective resistance rather than open engagement, making constructive change less likely.
“I don’t think calling people racist generally helps… it can lead to defensiveness and reluctance to change.”
Reading Comprehension
Test Your Understanding
5 questions covering different RC question types
1According to the article, Black and Asian women receive fewer epidurals during childbirth primarily because they request pain relief less often than white women.
2Why does Sridhar recommend framing the ethnicity pain gap as a data problem rather than accusing individuals of racism?
3Which sentence best explains why Sridhar believes the biological differences used to justify racial distinctions in medicine are unfounded?
4Evaluate these three statements about Sridhar’s four proposed interventions.
Sridhar recommends that racial and ethnic disparity data should be collected routinely and shared transparently, with clear accountability for what the data reveals.
Standardised clinical pathways are intended to reduce the impact of both unconscious and conscious bias at key medical decision points.
Sridhar argues that individual clinical judgment should be eliminated entirely and replaced by rigid, protocol-driven care in all situations.
Select True or False for all three statements, then click “Check Answers”
5What can be inferred about Sridhar’s intended audience from the way she opens the article and references political figures like Kemi Badenoch and Nigel Farage?
FAQ
Frequently Asked Questions
The ethnicity pain gap is the documented pattern in which patients from Black, Asian, and mixed ethnic backgrounds consistently receive fewer and lower doses of pain-relieving medications than white patients. Research shows this disparity exists across healthcare settings — from maternity wards to cancer treatment — and persists even after controlling for age, disease type, deprivation, and other variables that might otherwise explain the difference.
According to the research cited by Sridhar, Black women are falsely stereotyped as having “thick skin” and a higher tolerance for pain, leading healthcare providers to dismiss or ignore their requests for pain relief. Asian women, by contrast, are labelled as “princesses” who over-demand and are judged negatively for being unable to tolerate even minor discomfort. Both stereotypes are racially grounded myths that have measurable consequences for the treatment women receive during childbirth.
Sridhar draws on a well-known principle in public management: organisations tend to improve outcomes they systematically track, because measurement creates accountability and visibility. Healthcare systems already routinely measure waiting times, infection rates, and mortality outcomes — and those areas receive sustained attention and resources. She argues that racial and ethnic disparity data must be added to this list so that the ethnicity pain gap receives the same institutional focus and improvement effort.
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This article is rated Intermediate. The vocabulary is accessible and the argument is clearly organised around evidence and numbered solutions. However, readers need to track the distinction between direct racism and systemic bias, follow a multi-part policy argument, and pick up on rhetorical cues such as why Sridhar deliberately avoids accusatory language. These demands on inference and authorial intent move it beyond Beginner level.
Prof Devi Sridhar is Chair of Global Public Health at the University of Edinburgh and one of the UK’s most prominent public health voices, widely known for her commentary on COVID-19 policy. Her South Asian heritage and experience of migrating between the US and the UK give her personal credibility on questions of race and healthcare. Writing in The Guardian’s opinion section, she brings together epidemiological rigour and lived experience to make a case that speaks to both policymakers and the general public.
The Ultimate Reading Course covers 9 RC question types: Multiple Choice, True/False, Multi-Statement T/F, Text Highlight, Fill in the Blanks, Matching, Sequencing, Error Spotting, and Short Answer. This comprehensive coverage prepares you for any reading comprehension format you might encounter.
