Commentary:
Although numerous studies have described socioeconomic and ethnic
disparities in maternal mortality in the UK, MBRRACE-UK reports of
Confidential Enquiries into Maternal Deaths and Morbidity have continued
to highlight that these inequities persist. The latest report underlines
the importance of “not los1 sight” of the actions
required to address the systemic biases acting to produce ethnic and
socioeconomic gradients in maternal mortality, and refers to the need
for widespread action across the health and social care system to
address these biases2. Importantly, the report
features an evocative image: a “constellation of systemic biases”
representing intersecting biological, psychological and social factors
leading to maternal mortality2.
How a problem is conceptualised is key to how it is investigated and
addressed. As such, the conceptualisation of multiple intersecting
factors leading to an increased risk of maternal mortality is clearly
relevant in determining if and how we unpack and address them. In her
essay “Epidemiology and the web of causation: has anyone seen the
spider? ”, Prof Nancy Krieger elucidates the power of visual metaphors
to direct the purpose and approach of studies of disease
distribution3. The web of causation, she argues, led
researchers to prioritise identification of individual components or
“strands” of the web which could be “cut” to prevent disease.
Researchers did not question the origin of the web itself, and thereby
deemed the causal mechanisms by which disease distributions arose
unworthy of investigation. Considering the impact the “web of
causation” has had in directing epidemiological enquiry, it may be
helpful to consider the implications of the constellation featured in
the MBRRACE-UK report for research and clinical practice.
Biomedical complexity is challenging in itself to address within our
healthcare system, with multidisciplinary medical care for pregnant
women with complex medical needs proving difficult to
facilitate2. Thus, when healthcare professionals are
faced with a constellation of biological, social and psychological
factors affecting the outcomes of pregnant women and their babies which
are outside their realm of control, they may be overwhelmed, pessimistic
or even nihilistic. The term “clinical nihilism”, originally coined by
Dr Paul Farmer to describe the attitude of the global health community
towards providing high-quality healthcare for those living in poverty
across the world4, is apt in this situation. Do we
consider how the constellation came to exist? It is probably impossible
to deduce. Can we alter the configuration of the constellation? It is
too complex – where would we start? It is tempting to continue defining
the existing constellation, by repeatedly describing existing health
disparities without substantive efforts to unpick or address them. In
view of the current strain on the NHS, it would be all too easy to
“lose sight” of the systemic biases leading to disproportionate
maternal mortality in marginalised populations.
Is it possible instead to conceptualise the multiple factors leading to
an increased risk of maternal mortality in a version of the Swiss cheese
model (Figure 1)? We could construe the systemic biases highlighted by
the MBRRACE-UK report not as errors embedded within systems, but as
disadvantages manifesting themselves repeatedly during interactions with
health and social care workers throughout the pregnancy and the
life-course more generally (Figure 1). As with other “never events”
within healthcare systems, his model highlights the fact that there are
multiple potential opportunities for intervention by individuals within
health and social care systems, which may help to mitigate clinical
nihilism.
Acknowledging the importance of intersectionality is essential when
investigating the systemic biases leading to an increased risk of
maternal mortality. Intersectionality is a term introduced by Prof
Kimberle Crenshaw to describe the oppressions that Black women faced due
to the intersecting effects of racism and sexism5. A
key message is that “racism and sexism factors into Black women’s lives
in ways that cannot be captured wholly by looking at the race or gender
dimensions of those experiences separately” – intersecting oppressions
lead to a result not only greater than but also different from the sum
of their parts. The concept of intersectionality is evidently pertinent
to the study of systemic biases in maternal healthcare – in fact, the
MBRRACE-UK report of Confidential Enquiries into Maternal Deaths and
Morbidity 2015-17 specifically highlights the overrepresentation of
mothers with severe and multiple disadvantages amongst those who
died6. However, commonly used quantitative methods are
limited in their ability to encompass intersectionality. For example,
adjusting for confounders such as race, mental illness and socioeconomic
status, without full consideration of the causal pathways along which
these factors exert their effects, only accounts for the co-occurrence
of these factors and does not capture their interactions.
Luckily, intersectional methodological approaches to describing and
analysing health inequities have already been described in the social
science literature. Trans-disciplinary collaborations with our social
science colleagues would empower us with the tools to interrogate the
complexity depicted in the constellation. One such tool is the index of
concentration at extremes, a measure of inequity which simultaneously
captures concentrations of affluence and deprivation7(Figure 2). This metric has already been used to delineate the
intersectional impact of race and economic deprivation on the risk of
preterm birth in the United States7. Another tool is
the directed acyclic graph (DAG) – in these graphs, arcs are used
depict assumptions regarding the causal relationships between
variables8. DAGs could be used in studies of risk
factors for maternal morbidity and mortality to encourage researchers
and readers to methodically consider how these risk factors intersect,
and the result of such intersections9. In turn,
studies explaining the nature and consequences of the intersecting risk
factors could help to refine the Swiss cheese model of maternal health
inequity through an iterative, translational process (Figure 1).
As the COVID-19 pandemic continues to expose and exacerbate
socioeconomic and health inequities, it is imperative that we avoid
nihilism regarding maternal health disparities in both research and
clinical practice. Mothers from marginalised groups have been dying
disproportionately for too long, and it is time to translate awareness
into action.