Notebook

Health inequalities in England: A complex case of sticking plasters and category errors

By Jonathan Wistow

In this blog post I will briefly develop three interrelated strands of analysis – political economy, policy, and methodology – that I argue are central to understanding and reducing health inequalities. Focusing on England, it will be argued that within each of these strands the dominant approaches to framing and responding to health inequalities are, more or less, complementary and provide a relatively ‘neat’ and unified understanding and response to this social problem. In short, political economy, policy, and methodological components complement each other with their tendency towards individualism, treatment and behaviour, and linearity respectively. Unfortunately the ontological and epistemological coherence that cuts across these is negatively reinforcing and goes a long way towards explaining the persistence of health inequalities in England. The purpose of this blog post is to make the case for challenging and redefining each of these strands and I do so through making three propositions at the end of each section below.

Political Economy

The economic recession of the mid-to-late 1970s in the UK led to a crisis in Keynesianism and enabled a shift to neoliberal ideology, as the then Labour government submitted to budgetary restraint and austerity mandated by the International Monetary Fund (Crouch, 2011 and Harvey, 2005). Successive governments, commencing with Thatcher’s tenure as Prime Minster in 1979, have viewed the market as the optimal or default form of economic organisation (Sayer, 2016), while key instruments of the welfare state, including local government, were seen as placing constraints on the central state’s marketization project (Crouch, 2011).

These changes also marked (and arguably responded to) a shift from collectivism to individualism in society. One consequence of this was that inequality was no longer seen as necessarily problematic, which allowed for less progressive taxation, privatisation of public assets and runaway salaries at the top of the labour market. As a result the UK witnessed rising income inequality from the late 1970s onwards. Since then health inequalities have remained remarkably persistent and, as Scambler and Scambler (2015: 343) note, there have been, ‘endlessly repeated statistical associations linking socio-economic classification to health’. Much less common, but still important within the academic literature, are calls to question the structural and class forces that are key causal factors in producing health inequalities (see, for example, Coburn, 2009; Lynch, 2017; Scambler and Scambler, 2015; Schrecker, 2017; Wistow et al., 2015).

The apparent disconnect between the understanding of the pattern and distribution of health inequalities and the reluctance amongst some in academia to ask the deeply sociological questions (essentially the next logical step) about the structural forces producing these is our first hint at how political economy, macro-economic policy arising from this, and methodology are aligning to undermine the potential to tackle health inequalities.  

Without addressing and understanding the causal processes produced through the political economy; policy designed to tackle health inequalities is likely to be no more than a ‘sticking plaster’ for the deep cut that these represent within society.

Policy

The extent to which the state is seen to have a role in modifying the inequalities that are (re)produced across society should be a key debate within social and economic policy. However, and as we have seen, this has too long been either neglected, or more conspiratorially, intentionally marginalised in mainstream debates about the political economy. Within the more focused domain of health and health-related policy it is important to question the extent to which governance structures enable the social determinants of health to be effectively identified and addressed.

Gerald Wistow (in Wistow et al., 2015), described the NHS as being based on a ‘category error’ that tended to mirror the medical model’s concern to treat symptoms more than causes of ill health. The relative power of medicine within the NHS remains largely secure, despite prominent challenges from McKeown in 1976 and the development of a longstanding evidence-base about health inequalities dating back to the Black Report in 1980 that was subsequently revisited and refreshed through the 1998 Acheson Report and the 2010 Marmot Review (2010). In short, each of these pointed to the material and structural causes of health inequalities and what should be interpreted as the complex causal relationships that intersect with social standing (class) and place, in particular.

The fact that only four per cent of NHS spending in the first decade of the 21st century was on health promotion and preventing illness (NAO: 2013)​ demonstrates just how skewed resourcing is towards the treatment of the symptoms rather than the underlying causes of health. It is also significant that this distribution of resourcing occurred at the same time as New Labour’s Tackling Health Inequalities policy agenda.  

Even within the field of health promotion and prevention the balance is wrong. A recent speech by the Secretary of State for Health and Social Care, Matt Hancock, on prevention nicely illustrates this point. He started by saying, ‘I want to talk about how preventing ill health can transform lives, and transform society for the better too.  That might sound radical. It is intended to.’ To many this is far from radical but, nonetheless, revealing in that Hancock both thinks it is and has gone as far as to emphasise this point.  

Hancock’s focus moves on to consider the significance of peoples’ behaviours for their health. The argument here is not that behaviours are unimportant; they are extremely significant for health outcomes, but that they are complex and nested in a wider social structure within a neoliberal political economy.  Hancock’s response, in this respect, is both predictable and disappointing: ‘I want to see people take greater responsibility for managing their own health…how can we empower people to take more care of their own health?  By giving people the knowledge, skills and confidence.’ He does not, however, consider the nature of the political economy, nor the social determinants arising from this in his analysis and instead essentially isolates behaviours within debates about individual agency without due consideration of social and structural contexts these are situated in.  

The NHS compounds the category error at the level of the political economy of using a sticking plasters when stitches are required and, to extend the metaphor, does so by producing a plaster that is both too small and the wrong shape for the cut, with little hope of covering it, let alone stemming the flow. Under these circumstances methodology should help us to understand and frame the problem better but as we will see the dominant approaches here are lacking.

Methodology

Back in 1979 Lesley Doyal with Imogen Pennell wrote, The political economy of health, and argued that the, ‘emphasis on the individual origin of disease is of considerable social significance, since it effectively obscures the social and economic causes of ill health.’  They continue that the medical emphasis on individual causation is one means of defusing the political significance of the ‘destruction of health’. 

As we have already seen the evidence-base linking social and economic inequalities to health inequalities has developed considerably since Doyal and Pennell were writing. However, despite public health researchers and professionals generally understanding that the causes of ill health are complex and structural Salway and Green (2017: 523) conclude that both health promotion campaigns and journal evidence, ‘suggest we remain deeply wedded to linear models and individualistic interventions.’ Here the dominance of Randomised Control Trials (RCTs) and, to a lesser extent, epidemiology have significant limitations for understanding an inherently social problem such as health inequalities.

RCTs are often considered to be the gold standard in medical research and are increasingly having an influence over public health and social sciences research.  For example, the National Institute for Health Research has recently funded a £1.5million evaluation (in the form of an RCT) of ‘Strengthening Families, Strengthening Communities’, which is an evidence-based parenting programme, designed to promote protective factors associated with good parenting and better outcomes for children. However, questions have to be asked about the extent to which an RCT is capable of understanding the dynamic and relational factors that operate at levels above and beyond individuals (see, for example, Kelly, 2010) in a research problem such as this.  Instead RCTs fit very well with the reductionist approach of medicine to simplifying and dividing problems into sub-components, thereby, losing sight of the embeddedness of entities in their interconnections (Chapman, 2004).

The effect of epidemiology over public health policy can be seen through the example of Hancock’s speech about prevention. Here public health policy is reduced to identifying factors and markers for disease and using knowledge and empowerment to encourage people to take responsibility for this. The political significance of health is lost and questions are not asked about the ‘causes of the causes’ of ill health with implications for how the state through public servants is likely to encourage individual responsibility for health across social classes. For example, is someone who works as a professional and lives in a healthy area more or less likely to be receptive to being empowered through knowledge than someone who lives in an unhealthy neighbourhood and whose experience and interactions with the state are largely negative through the excessive monitoring and surveillance that comes with living on (or potentially previously living on but no longer doing so due to changes in allocation criteria) incapacity benefits? The point here is not that epidemiological data is not useful but it should be part of inquiry.  

Complexity theory helps to respond to these limitations. Firstly, through framing complex problems like health inequalities and secondly through advocating mixed methods and perspectives. Let’s focus on premature mortality rates resulting from cancer as an example of health inequalities. Many of the causes of cancers for individuals (as ‘cases’) relate to a complex combination of lifestyle behaviours such as smoking, diet, exercise, bodyweight, and exposure to sunlight. However, it is very difficult to isolate these behaviours and attribute causation to these as individual variables. Indeed we can question whether this is a desirable strategy given that in practice people do not live their lives in neat and separate component parts: diet, frequency of exercise, social and work activities, alcohol and nicotine consumption, are all parts of the complex whole that make up individuals’ lifestyle. But this is not the whole picture (and an example of where Hancock’s analysis is fundamentally flawed) because lifestyle, in turn, relates to (but is not wholly determined by) the contexts in which people live their lives. Different people react to these different contexts differently.  The social gradient linking health status to social status is an important factor here and cuts across a multi-scalar approach to context that includes family, workplace, neighbourhood settings, towns, cities and regions – all important contextual characteristics within which people lead their lives. Here we are talking about multiple and non-linear causation in which individuals are embedded and the importance of interactions between these multiple causes. In responding to these issues Castellani (2014) argues that for complex systems both social reality and data are best seen as ‘self-organising, emergent, non-linear, evolving, dynamic, network-based, interdependent, qualitative and non-reductive.’  It follows, therefore that no one method (especially statistics), ‘can effectively identify, model, capture, control, manage or explain them’.

Health inequalities are complex and no one methodological approach should take precedence in understanding these.  By opening up the methodological toolbox and using a variety of methods we can develop a much fuller understanding of how these exist within complex systems, which, in turn, directs our attention much more fully to the constraints in the political economy and the limitations of policy as presently configured.

Jonathan Wistow is an Assistant Professor in the Department of Sociology at Durham University. The blog is based on research for chapter in a forthcoming book commissioned by Policy Press called Social policy, political economy and the social contract, which is due for publication in 2020.  

References

Chapman, J. (2004) System failure: Why governments must learn to think differently, London: Demos.
Coburn, D. (2009) Income inequality and health. In Panitch, L. and Leys, C. (eds) Morbid Symptoms: Health under capitalism. Pontypool: The Merlin Press.
Crouch, C. (2011) The strange non-death of neoliberalism, Cambridge: Polity.
Department of Health (1998) Independent Inquiry into Inequalities in Health – Report. London: HMSO.
Doyal, L., with Pennell, I. (1979) The political economy of health, London, Pluto Press Limited.
Harvey, D. (2005) A brief history of neoliberalism, Oxford: Oxford University Press.
Kelly, M. (2010) The axes of social differentiation and the evidence base on health equity, Journal of the Royal Society of Medicine, 103(7), 266-272.
Lynch, J. (2017) Reframing inequality? The health inequalities turn as a dangerous frame shift, Journal of Public Health, 39: 4, 653-660.
Marmot Review (2010) Fair Society, Healthy Lives: Strategic review of health inequalities in England post-2010, London: The Marmot Review.
McKeown, T. (1976) The role of medicine: Dream, mirage or nemesis? London: Nuffield Provincial Hospitals Trust.
NAO (2013) Early action: Landscape review: https://www.nao.org.uk/report/early-action-landscape-review/​
Salway and Green (2017) Towards a critical complex systems approach to public health, Critical Public Heealth, 27:5, 523-524.
Sayer, A. (2016) Why we can’t afford the rich, Bristol: Policy Press.
Scambler and Scambler (2015) Theorizing health inequalities: The untapped potential of dialectical critical realism, Social Theory and Health, pp 340-354, 13: 3/4
Schrecker, T. (2017) Was Mackenbach right? Towards a practical political science of redistribution and health inequalities, Health and Place, 46, 293-299.
Wistow, J., with, Blackman, T., Byrne, D., and Wistow, G. Studying health inequalities: An applied approach, Bristol: Policy Press
Notebook

Democratisation vs big data? A dialogue between our editors Ros Edwards and Malcom Williams

Ros Edwards

Democratisation and big data have established themselves as key developments in social research processes. But I’m wondering, are they pulling in opposite directions?  Democratised methodologies immerse researchers within communities, undertaking relational work up close. Big data, on the other hand, has been described as a gaze from 30,000 feet.

Voices advocating radical challenges to traditional research practice through democratisation have questioned the model of research that positions the people who are the focus of study as subjects, and those who research them as experts who can analyse and evaluate.  Under the democratisation paradigm, research seeks to serve the needs of those who’ve traditionally been excluded from positions of power, to highlight the voices of those who are disenfranchised on the basis of their gender, race/ethnicity, disability or other characteristics, and to further human rights.  Democratised methodologies are concerned with ensuring that people who experience marginalisation influence research at every level of the process, to identify what it is that’s important to research, and how the community may benefit from involvement.  

The other development, the increasing availability and use of big data, potentially creates critical tensions for democratising research methodologies and knowledge production.  The potential (and seduction) of big data is the scale and availability of large sets of data that may be analysed; it promises easy access to massive amounts of data.

On the one hand, this may make access to data more democratic, with marginalised groups able to obtain material relevant to topics they have identified as important to them, and to engage in analyses with transformative potential.

On the other hand, while big data gives the illusion of providing unmediated and direct access to people’s beliefs and experiences, in fact it’s just as socially mediated and constrained as any other form of data. Indeed, the background frameworks structuring what knowledge gets collected in the form of big data and how it’s analysed may hide the transparent interpretation of human experience that’s central to democratising methodologies.  

But can and how might democratisation of the research process and big data fit together? As big data enables new methods in knowing and defining social life, these new ways of knowing need to be critiqued for their limitations as they emerge. Perhaps it’s here that democratising methodology can step in and enable marginalised groups to have an input and make a difference.

Malcolm Williams

I’m not sure that I would entirely agree with you because I would pose a different question – who is research for?

I don’t think democratising methodology is a one size fits all. At the level of community research, action research etc. where the methods and choice of methods is relatively accessible, then I would agree with you. But when we get to complicated, highly technical statistically sophisticated methods/methodology then this is a bit like democratising high energy physics.

But it is at the level of what we ask and for who we are asking it, some level of democracy is appropriate. What do we research and why? Can the results be made more open and accessible? Even then, I worry that democracy can itself be destructive of well being when people vote or choose in a knowledge vacuum.  I think we have a home grown example in Brexit.

The problem with big data is not method or methodology (well it might at a technical level), but who owns it, who interrogates it and who gets to choose the questions.

Ros Edwards

I can see the strength of the points that you are making, and I wouldn’t disagree with all of them all of the time! I agree that the research questions asked of big data and who chooses them are central issues, but most democratising approaches wouldn’t draw a distinction between that and methodology – where methodology is an understanding of how we can go about gaining knowledge about how the world works, and thus how research should be carried out.

I also want to stress that the background to this is inequality and power and how it relates to methodology. There’s a long history of marginalised communities who have been problematised and stigmatised through the damaging assumptions embedded in the methodological approach and the methods used by social researchers. There is the potential that democratised research (just like democracy generally) may produce knowledge that’s problematic or skewed, although probably in different ways to traditional approaches, and that knowledge is open to challenge. But there’s just as much, maybe more, potential that it produces greater illumination.

There’s a tendency to see uses of ‘big data’ in social research as somehow antithetical to democratised research but I’m asking whether and how the two may be brought together. Attention to methodology seems to me to be an entry point.

Malcolm Williams

I absolutely agree with your second point, but how to get there? Firstly, I’d reiterate we are at one in respect of participatory research, action research etc. Methods and methodology, should and can be democratised. ‘Big data’ and (say) complex administrative datasets do present a bigger challenge. In respect of the former, a current methodological question might be is the general linear model still an appropriate methodological framework? The debate on this is technical and statistical and one I find challenging, but it makes a profound political difference to what is asked and how it is asked. So, how can we improve the links of accountability and decision making between that data scientists and the public, in order to avoid dangerous assumptions/ stigmatisation etc?

The answer, for me, is threefold: firstly we can and should democratise data in society, through more informed critical reflection in the media and promote a better understanding of data in government and the third sector. School students must study English (or French, Spanish, Chinese, etc) and mathematics, but they also should study data in society to enable them to have a critical understanding of how data are used to persuade or govern.

Secondly and inevitably, at the technical and operational level methodological and methods choices must be made by a trained cadre of professionals. To deny this begs the question of why do we have social science degrees, PhDs etc? However, we should resist any shift to wholly methods and methodological training in social science at the expense of scholarship and critical reflection. It seems obvious, but all social scientists should have a critical understanding of the ideological and political context of data, methods and methodology. In the UK, at least, the danger is that universities and the ESRC are often dangerously focussed on measuring impact within a very narrow normative ideological agenda. So what we do and how we do it is so often decided by those who fund it!

Finally we should resist the colonisation of the analysis of big data by those without a social science background, for at best their questions may be trivial, but at worst informed by whatever is the current ideological fashion or project of government or big business.

Calls

Call for Reviewer College Members

The International Journal of Social Research Methodology set up its Reviewer College in 2014. The journal is committed to supporting social researchers and methodologists who have recently entered the profession and indeed values the new ideas and approaches they bring.  

The College has been seen as a positive career experience by its members and several College members have become full board members. Membership of the College is open to social scientists in the early years of their career. They may be currently PhD students, recently graduated PhD students or early career researchers/ academics. Members may work in academic institutions, the private, public or third sector. They may be resident in any country. IJSRM publishes articles that cover the entire breadth of quantitative and qualitative approaches. We are always interested in those with expertise in areas where there are skills shortages, and at present we particularly welcome members who have experience in the following areas: experimental methods and complex interventions, sampling, evaluation methods, data visualisation, indigenous methods, co-production and participatory methods.

College Members receive a discount voucher for Taylor and Francis products for each review they undertake.  They will be expected to review up to three papers per year.

If you would like to apply please send a CV and supporting email to Malcolm Williams WilliamsMD4@cardiff.ac.uk

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Announcements, Competitions

Early Career Researcher Journal Prize

The International Journal of Social Research Methodology is the leading European journal in social research methods and methodology with a five-year impact factor of 1.657.

We are pleased to announce the 2018 competition for papers written by early career researchers (ECRs), who are either current doctoral students, or in their first three years of post-doctoral employment since the date of their doctoral graduation day.  A prize of £500 will be awarded to the best paper and this and runners up will be published in the Journal

The journal aims to encourage high quality rigorous papers that provide an original contribution to current and emerging methodological debates and methodological practice across a range of approaches qualitative, quantitative, hybrid and mixed methods. The prize has been established to encourage and recognise research and contributions from new scholars in these debates and practices.

Potential contributors should carefully read the Aims and Scope of the Journal at http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=tsrm20  and Instructions for Authors at  http://www.tandfonline.com/action/authorSubmission?journalCode=tsrm20&page=instructions.

Papers submitted between  April 30th to June 30th 2018 will be considered as entries in the competition.

All papers will be subject to the journal’s normal refereeing process and the best paper will be selected by the editors and representatives of the editorial board. Papers will be expected to reach the normal publishing standard of the journal and in the unlikely event that none do, the journal reserves the right to publish none and not award the prize.

Questions concerning the competition should be sent to Malcolm Williams WilliamsMD4@cardiff.ac.uk and papers for consideration to tsrm-editor@tandf.co.uk . Your covering letter should indicate that you would like your paper to be considered for the competition and a statement of eligibility as an ECR.