Modelling mental health inequalities within an intersectional framework

Photo by Benjamin Elliott on Unsplash

By Kieran Balloo and Anesa Hosein

One of the unique angles of the #StudentWellLives Project is that we are using an intersectional approach to investigate mental health inequalities. Lawyer and scholar, Kimberlé Crenshaw, was the first person to come up with the term intersectionality. She wanted to show how discrimination in employment occurred for Black women – and that the discrimination did not occur because they were Black or because that they were women, but because they were Black women.

We, therefore, expect that when it comes to mental health, the inequalities may be occurring because of what Leslie McCall calls intercategorical complexity – i.e. depending on the multiple social categories that a young person may hold because of, for example, their sex, ethnicity, sexuality, socio-economic class (SEC), and education background. We aim to look at interactions between multiple social categories (e.g. comparing Black male student experiences with white female non-student experiences).

However, in doing this we face a challenge; a large part of the literature on intersectionality is based on qualitative research, much of which subscribes to the anticategorical approach in which McCall explains that social life is seen as being too complicated to be boxed into discrete categories. Whilst we broadly agree with this argument, and that everyone is an individual, in large-scale quantitative datasets such as the Next Steps Study that we are using, patterns are sought about the population to inform policy. Thus, an intercategorical approach is the methodological compromise we need to make. We are also considering these categories in a similar way to Rita Dhamoon and Olena Hankivsky, who contend that these the social categories are really just proxies for systemic privilege and oppression, such as sexism, racism, homophobia, and classism. Hence, through the intercategorical approach we aim to show that social inequalities are a result of structural power hierarchies that shape individuals’ experiences, and intersectionality captures the “numerous interlocking systems of privilege and oppression”, as suggested by Clare Evans and colleagues.

Traditionally, the intercategorical approach would involve an examination of the main effects (i.e. the social categories) and their interactions (i.e. the intersectionalities). We do, however, face some challenges if we use this approach. Firstly, we need to make sure that there are reasonable sample sizes in all of the combinations of social categories. Secondly, this can create some difficulties with interpretation because of the large number of interactions.

However, we may have found an alternative that can get around these challenges. Evans and colleagues recently published a very influential methodological paper about the use of the intercategorical approach in quantitative analyses. In their paper, they propose using multilevel modelling (also known as hierarchical linear modelling) to reflect the power hierarchies embedded in the social categories. The advantages of this approach are that the sample size becomes less of an issue, and the interpretation of the data across social categories can be more easily understood through the use of graphs.

We are still exploring this approach by Evans and colleagues, but we would be interested to hear from other researchers who have adopted a quantitative approach to intersectionality analyses, or those who might be interested in using this novel multilevel approach. Please leave a comment below or connect with us on Twitter: @uniwelllives #StudentWellLives.

Relevant Readings:

  • Crenshaw, K. (1989). Demarginalizing the intersection of race and sex: A black feminist critique of antidiscrimination doctrine, feminist theory and antiracist politics. University of Chicago Legal Forum, 1, 139-167.
  • Dhamoon, R. K., & Hankivsky, O. (2011). Why the theory and practice of intersectionality matter to health research and policy. In O. Hankivsky (Ed.), Health inequities in Canada: Intersectional frameworks and practices (pp. 16–50). UBC Press.
  • Evans, C. R., Williams, D. R., Onnela, J. P., & Subramanian, S. V. (2018). A multilevel approach to modeling health inequalities at the intersection of multiple social identities. Social Science & Medicine203, 64-73.
  • McCall, L. (2005). The complexity of intersectionality. Signs: Journal of women in culture and society30(3), 1771-1800.

Differentiating between mental health and wellbeing


By Kieran Balloo

Currently, in the #StudentWellLives project we are grappling with how to define mental health and wellbeing. Often, the terms mental health and wellbeing are used interchangeably, but research suggests they should be viewed as being connected, but conceptually distinct (Keller, 2020). It might be useful to think of wellbeing as a broader concept that encompasses a range of factors experienced at an individual, community and national level.

Simply put, [wellbeing is] about ‘how we’re doing’ as individuals, communities and as a nation, and how sustainable that is for the future. It is sometimes referred to as social welfare or social value.

What Works Wellbeing (

Mental health refers to a full spectrum of experience ranging from good mental health to mental illness…. Good mental health means more than the absence of illness. It [is] a dynamic state of internal equilibrium in which an individual experiences regular enduring positive feelings, thoughts and behaviours, can respond appropriately to normal negative emotions and situations and is able to make a positive contribution to their community…. Mental illness [is] taken to mean a condition and experience, involving thoughts, feelings, symptoms and/or behaviours, that causes distress and reduces functioning, impacting negatively on an individual’s day to day experience, and which may receive or be eligible to receive a clinical diagnosis.

The University Mental Health Charter (

In the #StudentWellLives project, we believe the distinction is helpful because we will be analysing aspects of both wellbeing and mental health as separate constructs. The Office for National Statistics’ (ONS) Measuring National Well-being programme defines individual wellbeing as representing how people feel about:

  • personal wellbeing
  • health
  • relationships
  • education and skills
  • what they do
  • where they live
  • personal finances
  • the economy
  • governance
  • the environment

Using this conceptualisation, aspects of mental health, such as anxiety and depression, could fall under ‘personal wellbeing’ and ‘health’. ‘Personal wellbeing’ also includes life satisfaction, life worthwhileness, and emotions. Other aspects of wellbeing that are likely to be relevant to our project include: ‘relationships’, which covers personal relationships and feelings of loneliness; ‘education and skills’, which covers educational achievement and human capital; and ‘what they do’, which includes work and leisure activities.

In the Next Steps data we are utilising, there are measures of life satisfaction, health, and relationships with others. There are also measures related to young people’s education and employment outcomes (e.g. job satisfaction), which can be seen as aspects of their wellbeing under the ONS definition. Instead of conflating the two terms, we will be able to see how different aspects of mental health and wellbeing are interrelated, which might be valuable when using the findings to identify how best to support differing student needs. For example, supporting students with their feelings of loneliness when they start university might not mean automatically sending them to student counselling, which might be better for dealing with more profound mental health issues, such as anxiety and depression.

We would be interested to hear about other benefits or disadvantages to separating the two concepts, so please leave a comment below or connect with us on Twitter: @uniwelllives #StudentWellLives.

What environmental data should universities collect for student mental health and wellbeing?

Photo by Pixabay on

By Anesa Hosein

Over the last two months, we have been delving into the UK Higher Education Statistical Agency (HESA) publicly available datasets. And when I say, “we”, I mean Kieran. It is mind blowing how much data is available for each university. And it is such a rich dataset which researchers can use for any amount of secondary data analysis research.

In a recent research bid I was putting together for an Irish Higher Education context, I recognised the lack of data that is available for Higher Education Institutions (HEIs) in other countries in comparison to the UK. If we are to understand the university environment in different international contexts and how they impact on student wellbeing then we need governments to implement plans to collect sufficient and the right data for higher education.

What constitutes the appropriate/right data that HEIs and governments need to collect to understand student mental health and wellbeing is something that our project hopefully might be able to contribute to. We recognise that collecting this type of data requires a huge resource and infrastructure investment and hence we hope to provide clear guidelines in the future about what may be the best data to collect to understand how the university environment affects student mental health and wellbeing.

At the moment we are exploring from the HESA dataset, various cultural, social and built environment variables that contribute to the university environment, including investment in arts, proportion of Black, Asian and minority ethnic (BAME) students, and the size of green spaces and sport fields. We know from the work of WhatWorksWellbeing that the arts, a sense of belonging, and taking part in sports affect mental health and wellbeing. Hence we’re checking the extent to which these variables contribute to a university environment that supports mental health and wellbeing.

So, watch this space and if you can think of any variables that HESA should have for measuring mental health and wellbeing – let us know.

Project launch and start of phase 1

By Kieran Balloo

The Student Wellbeing & Life Outcomes Project launched at the beginning of July and we have got straight to work on the first phase of our four-phase project. As a secondary data analysis project, our main job at the moment involves preparing various data for analysis. During phase 1, which will last for the next few months, we will focus on preparing data to address the following research question:

  • What type of university environment works for having better life outcomes (particularly mental health and wellbeing) for graduates with different social characteristics?

Respondents’ university data from the Next Steps Study will be linked with university data held by the Higher Education Statistical Agency (HESA) and the Office for Students (OfS), and with National Student Survey (NSS) results. Some of the university data will be used to classify universities based on their environment. For example, universities will be clustered based on their financial investment in, and access to, sports facilities, and their perceived levels of academic and personal support.

We will also be meeting with members of our advisory board during this phase to discuss our project plans and ensure our research will be relevant to our beneficiaries.