Biological Inequities Index

The Biological inequities Index is a composite dataset aimed at illustrating how some urbanised environments pose a health risk to their inhabitants as a result of the policies and regulations that govern its built environment, activity, and services.

It was created to advance the conversation and communicate a biological framing of data led analysis of the built environment. 

Biological inequity refers to “systematic, unfair, and avoidable stress-related biological differences which increase risk of disease, observed between social groups of a population”. The term aims to unify societal factors with the biological underpinnings of health inequities – the unfair and avoidable differences in health status and risks between social groups of a population - such that these inequalities can be investigated in a holistic manner.

Biological inequity posits that health inequity in urban populations is a result of processes and policies related to the built environment. It uses an ecological framing of health to address the habitat people inhabit (often due to wider forces and not choices) rather than personal behaviours. Through this, primarily, racialised and marginalised groups experience prolonged exposure to physical (e.g. air pollution) and psychosocial (e.g. discrimination) stressors resulting in exposure to chronic stress related events. Chronic stress increases the individual's allostatic load level – which refers to the wear and tear of stress-related biological systems e.g., neuroendocrine, metabolic, immune systems. In turn, these stress-related biological differences increase the risk of disease and poorer health outcomes. The main neuroscientific approach which can begin to explain how urban environments interact with the human biological system is by looking at the stress response, which is one of the key pathways linking the internal human biological environment with the external environment. In this case, the interest is in how the biological system adapts to urban pollutants such as air, noise, thermal, and light.

Stress Response    

The stress response is mitigated by the hypothalamic-pituitary-adrenal axis (HPA-Axis) which is a series of hormonal responses that help the body adapt to stressors. The system engages regardless of whether it is a psychological stressor such as losing a job, financial insecurity, witnessing a crime, or a physical stressor such as illness, environmental changes or external pollutants. The HPA-Axis activation starts in the brain when the stressor — in this case a pollutant — triggers the hypothalamic production of corticotropin-releasing hormone (CRH). This trigger signals to the pituitary gland, which is also located in the brain, to synthesise the adrenal-corticotropin releasing hormone (ACTH). ACTH is then released into the circulation system where it reaches the adrenal glands, which are located above the kidneys. Once it reaches the adrenal glands ACTH stimulates the release of cortisol, which is another regulatory hormone. Finally, cortisol circulates back to the brain through the circulation system, creating a negative feedback loop that repeats until the body comes to homeostasis or equilibrium.

Chronic Stress

Despite the role the HPA-Axis plays in providing the biological system with the means to adapt to stressors by mobilising energy reserves and regulating necessary immune responses, the majority of stressors we experience in urban environments are chronic in nature and overly engage this system. A continual activation of the HPA-Axis can result in its dysregulation and a subsequent cascade of damage to human bodily systems through a process known as ‘allostatic load’ predisposing people to a range of health complications. The dysregulation of the HPA-Axis is a feature of many disease processes associated with chronic stress, such as diabetes, obesity, depression, PTSD, and anxiety.

Environmental Factors of Chronic Stress

The average citizen does not often have the ability to actively investigate the role their environment has in contributing to their health. This is especially true of factors they have no personal control over or are not directly related to their personal activities. Environmental risk factors are often a result of larger infrastructure and activity, such as construction, traffic activity, population density, and presence of green and blue space. A goal of urban health and environmental justice must be to make these factors easier for the average citizen to understand and navigate.

One example of where this information can be useful is visiting the doctor. If someone was able to accurately give insight into the types of environments they are exposed to, it would help a practitioner understand further factors potentially involved in the patient’s health outcomes.

We are an independent health justice research lab prototyping ways to use health-based scientific evidence to support justice movements, surface and socialise non-western epistemologies and create language to articulate the health injustices felt by many racialised and marginalised communities. The Biological inequities Index was the result of a need to communicate this experience through a data led lens. This allows for people to grasp broad concepts and contextualise them in relation to where they live and how they make sense of the world around them. As a lab led by racialised, minoritised, and marginalised people we had an acute focus on communicating what is taking place in the neighbourhoods our Peoples have been forced to live in and its relation to our health demise. It builds on the long standing work of WEB Du Bois, Dr. Carter Goodwin, The Black Panther Party, and Professor Robert Bullard, the “father of environmental justice”.

Lastly, we produced this to show that health outcomes are not the result of poor choice behaviours but are biologically influenced by structural decision making.

The data was produced by CGG, a global geoscience company supporting Centric Lab pro-bono for the advancement and public engagement in geographic data.

• To advance knowledge on the structural determinants of health that result from political, commercial and economic interests.

• To support grassroots organisations see trends in their local areas and advance their organising and mobilising with health relevant data sets.

• To allow decision makers to make decisions that are centred on health reparations rather than economic ones alone when looking to address human health outcomes in urban areas.

The index is weighted 50/50 between two sub-sects of data (indexes in their own right).

• 50% is represented by the Stress Risk Score. This acts as a proxy to determine the physiological influences and impacts on the stress response system.

• 50% is represented by the Index of Multiple Deprivation. This acts as a proxy to determine the psychosocial influences and impacts on the stress response system.

The Stress Risk Score (SRS) is a scale used to measure and present the environmental stress risk factors based on proxies for noise, air, light, and thermal pollution. These measures were established using a meta-analysis of how each stressor engages with the stress response system, specifically allostatic load. The SRS is not an acute diagnostic tool but a tool for understanding the general risk of an environment in a way that can lead to further action and investigation.

While each pollutant presents its own health risks — for example, light pollution has the potential to disrupt melatonin production, linking it to sleep disorders and depression — it is the composite exposure to these pollutants which needs to be addressed, especially as research is indicating that when found together they become more acute and present a higher risk to human biological systems.

Index (Indices) of Multiple Deprivation are a unique measure of relative deprivation at a small local area level (Lower-layer Super Output Areas) across England and have been produced by the Ministry of Housing, Communities and Local Government. The Indices provide a set of relative measures of deprivation for small across England, based on seven different domains, or facets, of deprivation: Income Deprivation; Employment Deprivation; Education, Skills and Training Deprivation; Health Deprivation and Disability; Crime; Barriers to Housing and Services; Living Environment Deprivation Deprivation is measured in a broad way to encompass a wide range of aspects of an individual’s living conditions. Each of the domains above are constructed from a basket of different data datasets, or indicators. As far as is possible, each indicator is based on data from the most recent time point available. It is a uniform, national dataset that can work as a proxy to weight the relative levels of psychological stress a person may experience as a result of inhabiting this/these environment(s). Psychological or psychosocial stress arises as a result of the feeling of not being able to remove oneself from a structural problem, such as housing insecurity, financial insecurity, or harassment.

Geographic Information System scientists from CGG worked with Centric Lab to analyse air, noise, light, and thermal datasets from trusted sources to create the index. Values were assigned and 10 “bins” were created in accordance with the scale. This creates a relative scale of 1 = low and 10 = high. This was combined with the IMD Decile ranking (inverted to work with the SRS data) to create a value out of 20. Therefore, as mentioned, it is not an accurate diagnostic or determinist tool but a way of identifying trends and hotspots.

It cannot be used to confer an outcome. For example, it cannot be used to determine that geography alone is the causal relationship to why a specific group of people are unhealthy. It provides a lens to explain part of the outcome. This is because people often dwell in multiple environments which can be influential to their health. The point is that no area should be a determinant of someone’s ill health through exposure to stressors. This means that stakeholders responsible for an area can critique the geography, services, and policy dynamics of their area in order to reduce their own culpability in determining health outcomes.

It can be used to draw out insights that can lead to identifying trends and ‘hot-spotting’ areas. For example, aligning it with data on the numbers of libraries can show the relationship between structural unhealthy areas and low access to community oriented resources and social infrastructure.

It can be used in conjunction with demographic data, but only for the purposes identifying risks with an intention to apply a justice led approach in resolving matters.

Private gain and self-interest.

Profit.

Prejudice and discriminatory activities such as choosing to limit a person’s access to health services because they live in a high risk area.

Sadly no. Due to the complexity of the data and to ensure its application meets its goals we need to be involved.

• For grassroots community groups we offer to work pro-bono.

• For non-profits, social enterprises, and organisers we will do what we can to support and would prefer to look at its use as mutually beneficial and in collaboration.

• For companies and for-profit organisations Centric Lab time needs to be paid for, with the funds being re-directed to fund our capability in helping non-profits.