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Addressing Disparities: Advancing Mental Health Care for All Americans

By Joshua Gordon

January 29, 2020

As I sit down to write this message, I’m thinking of two former patients. One of them, a Hispanic man, I met in the emergency room at New York-Presbyterian Hospital when I was a resident in the early 2000s. Floridly psychotic, disheveled, and homeless, he was shouting at the emergency room nurse when I first saw him, demanding medications that he said were stolen from a locker in the homeless shelter across the street. The second patient, a White woman, was referred to my private practice in Midtown Manhattan a few years later. Composed and controlled, she asked compelling questions about her illness and its management, bringing with her dozens of pages of medical records. Both patients were young adults. Both had severe bipolar disorder . Both had survived a suicide attempt. Their medication lists were the same. Their lives were not.

Differences in health outcomes like these can reflect a number of underlying factors, including biological factors or environmental exposures; social, economic, and cultural contexts; and access to quality health care. When these differences adversely affect disadvantaged populations, they are known as health disparities .

Disparities in mental health are significant and easily documented. Deaths by suicide, for example, are much more common in American Indians and Alaska Natives  compared to the general population. The rate of deaths by suicide is also higher in rural areas  . Another example: Black and Hispanic children may be diagnosed with autism at a later age  compared to White children. That is an important factor because the earlier the diagnosis, the earlier treatment can start, and the earlier treatment starts, the better these children will do. These and other mental health disparities further disadvantage members of minority groups and increase the burden of mental illnesses on individuals, families, and communities.

Accordingly, the National Institute of Mental Health (NIMH) supports a research agenda aimed at understanding and reducing mental health disparities. One early success comes from research led by  Emily Haroz, Ph.D.   , a promising early-career investigator at the Johns Hopkins Bloomberg School of Public Health. Using an approach that has worked for the U.S. Army, the U.S. Department of Veterans Affairs, and a group of health management organizations (HMOs), Haroz and colleagues built an algorithm that uses electronic health record data to identify individuals in the White Mountain Apache Tribe in Arizona who are at increased risk of suicide. Such a predictor could be used by health professionals to refer these individuals to appropriate mental health care. Meanwhile, NIMH continues to support  three hubs for collaborative research focused on suicide prevention in Native American communities. These hubs are busy establishing common protocols for novel interventions and testing the efficacy of these interventions. This research holds the promise of making a real difference in the near term, helping health professionals and community leaders understand how to reduce deaths by suicide in their communities.

Similar efforts are underway in other communities to help families with children who may have autism. The Autism Spectrum Disorder Pediatric, Early Detection, Engagement and Services Network (ASD PEDS)  is an NIMH-funded network of investigators studying a diverse array of strategies and interventions aimed at identifying and treating children with autism as early as possible. This collaborative group is committed to eliminating disparities by reducing the age at which children from underserved populations are diagnosed and has several projects that are nearing completion. For example, Alice Carter, Ph.D.   , at the University of Massachusetts Boston, is finishing a study designed to test whether a system-level intervention can reduce these disparities. The intervention involves outreach to primary care pediatricians, a comprehensive multi-stage screening process, and motivational interviewing with parents and other caregivers. Wendy Stone, Ph.D.   , at the University of Washington, is testing a complementary intervention that aims to reduce disparities by improving screening and referral procedures in primary care pediatric practices. Stone and colleagues will examine the acceptability and efficacy of the intervention in four diverse communities.

While we at NIMH are justifiably proud of these and other investments in research on mental health disparities, I can’t help but ask whether similar projects would remedy the disparate situations faced by my former patients. Would early intervention have saved my first patient from homelessness? Are there treatment approaches for bipolar disorder that work better for individuals from disadvantaged backgrounds? How can we promote better access to and engagement in community-based mental health care? These are the sorts of questions we need to answer to ensure that improved mental health care meets the needs of all Americans.

Allen. J., Rasmus, S. M., Fok, C. C. T., Charles, B., Henry, D., & Qungasvik Team. (2018). Multi-level cultural intervention for the prevention of suicide and alcohol use risk with Alaska Native youth: A nonrandomized comparison of treatment intensity. Prevention Science, 19 (2), 174-185. doi:10.1007/s11121-017-0798-9

Daniels, A. M., & Mandell, D. S. (2014). Explaining differences in age at autism spectrum disorder diagnosis: a critical review. Autism, 18 (5), 583-597. doi: 0.1177/136236131348027

Haroz, E. E., Walsh, C. G., Goklish, N., Cwik, M. F., O'Keefe, V., & Barlow, A. (2019). Reaching those at highest risk for suicide: Development of a model using machine learning methods for use with Native American communities. Suicide and Life-Threatening Behavior . doi:10.1111/sltb.12598

Ibañez, L. V., Stoep, A. V., Myers, K., Zhou, C., Dorsey, S., Steinman, K. J., Stone, W. L. (2019). Promoting early autism detection and intervention in underserved communities: Study protocol for a pragmatic trial using a stepped-wedge design. BMC Psychiatry, 19 , 169. doi:10.1186/s12888-019-2150-3

Ivey-Stephenson, A. Z., Crosby, A. E., Jack, S. P., Haileyesus, T., & Kresnow-Sedacca, M. (2017). Suicide trends among and within urbanization levels by sex, race/ethnicity, age group, and mechanism of death — United States, 2001–2015. MMWR Surveillance Summary , 66 (No. SS-18), 1–16. doi:10.15585/mmwr.ss6618a1

O'Keefe, V. M., Haroz, E. E., Goklish, N., Ivanich, J., The Celebrating Life Team, Cwik, M. F., & Barlow, A. (2019). Employing a sequential multiple assignment randomized trial (SMART) to evaluate the impact of brief risk and protective factor prevention interventions for American Indian youth suicide. BMC Public Health, 19 , 1675. doi:10.1186/s12889-019-7996-2.

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• Volume 26, Issue 1
• Understanding and responding to the drivers of inequalities in mental health
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• http://orcid.org/0000-0002-9205-2144 Kamaldeep Bhui ,
• http://orcid.org/0000-0001-5179-8321 Andrea Cipriani
• Department of Psychiatry , University of Oxford , Oxford , UK
• Correspondence to Professor Kamaldeep Bhui, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; kam.bhui{at}psych.ox.ac.uk

https://doi.org/10.1136/bmjment-2023-300921

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• adult psychiatry
• depression & mood disorders
• Schizophrenia & psychotic disorders

BMJ Mental Health is delighted to announce a new section called Experience, Ethics, Equity that seeks submissions of primary research, systematic reviews, and perspectives and commentaries. We set out the case for such a section, and then give some guidance on article types and priority areas for research, practice and policy. Ethnic minorities and racialised groups are less likely to be represented in research and, with some exceptions, less commonly occupy higher management positions or have opportunities to influence policy and practice. 1–4 There are ethnic and gender disparities in academic research environments including in publishing. Much is being done to respond to these inequalities, including guidance on delivering inclusive research, commissioning research and on fair publication processes. Lived experience is central to such work. We hope this new section inspires all to contribute to progressive approaches to tackle inequalities.

Causal complexity

Mental illness affects the most vulnerable, those who have experienced multiple adversities from an early age, throughout their lives, where supports and coping styles no longer help. 5 6 Some people are exposed to a greater number of adversities, risk factors for mental illness, including poverty and deprivation and violence, while others are vulnerable given disadvantaged early childhood and family environments and adverse childhood experiences. 7–9 Poor mental health, and the lack to support and resource can be risk factors contributing to drifting into unemployment, poverty or housing crises. Indeed, given growing levels of global migration, natural disasters and conflict, it is likely there are many complex identities and contextual influences that come into play in the generation of inequalities globally and regionally.

Culture, identity and place

Innovation in paradigms of research.

Understanding and responding to the drivers of inequalities require thoughtful engagement with progressive paradigms of research. These must capture multiple drivers of illness from individual to social to geographical and ecosocial influences, including the social and cultural determinants operating in society. 21 22 The interactions with health and social care and pathways to care warrant greater attention, as do filters that exclude some from effective care while engaging others in coercive care escalators .

There is now significant effort to tackle these inequalities, and more so since the COVID-19 pandemic and Black Lives Matter movement which exposed an interplay between structural, institutional and interpersonal types of racism. 23 24 These account for differential experiences and trajectories of mental illness outcomes and premature mortality by racialised groups.

Structural barriers in the past have undermined efforts to improve care; for example, due to cultural competency or clinical skills to tackle ethnic inequalities in the experience and outcome of mental illnesses, inckuding compulsory admission and treatment under the powers of mental health legislation. The production of knowledge, a process of generating evidence for implementation, must be cognisant of these structural and historical barriers, and promote more inclusive research practice. We must guard against an inverse research law mirroring the inverse care law in order to ensure sufficient representation in research of those most affected by poor health. We must develop better culturally optimised and adapted interventions, which are accessible, attractive, safe, empowering and effective even on narrow measures of symptoms as well as on quality of life and well-being. Researchers, ethicists, commissioners, authors, editors, policymakers and legislators will all have to revisit their ethical values and practices. In contemporary research practices, in the UK and high-income countries, we can learn from the Global South, and lived experience testimonies in order to evolve better ways of engaging and involving the most marginalised groups. We should do this being mindful to not retraumatise and remaining cognisant of difficulty in verbalising and sharing stories of pain. A trauma-informed approach is also important for research teams including peer researchers to combat the risks of vicarious and secondary trauma. Lived experience data are central to new paradigms of research, revealing authentic biographical and care experiences. These real-world data are rich in complexities and nuances—new knowledge and clues about how we can prevent mental illness and improve care experiences. We do not exclude neurobiological, inflammatory or genetic pathways, as studies at the biosocial interface can explain how our environment and lived experience become embodied and represented. 22 25

We welcome submissions for this new section, and despite laying out priority areas, we will consider all submissions carefully, as tackling inequalities is a challenging, contested and often undertheorised topic. We wish to see ambitious, well-designed studies, and thoughtful accessible writing suited to interdisciplinary and cross-sector audiences. We are especially interested in intersectional approaches, but will also consider progressive studies that reveal new mechanisms. In particular, we expect significant representation of lived experience in the research process and in the writing of the papers, as well as the foregrounding of lived experience to expose dilemmas of ethics and equity. We anticipate attention to labels and categories deployed, so we will ask all authors to justify the classifications they use, and why they are necessary for the specific hypotheses they are investigating. Similarly, models of lived experience and patient and public involvement require further iteration and testing and improvement, alongside models of inclusive research practice. We anticipate articles will expose new ways of understanding lived experience and related ethical perspectives when trying to address inequalities. We welcome interdisciplinary teams with a balance of senior and early career researchers and practitioners, as well as experiential experts and public representatives. We ask authors to make explicit the particular theoretical and ethical frameworks for understanding inequalities and that the methods and findings are presented in an accessible way to motivate actions and debate beyond mental health setting; we must influence the total system, including public policy, public health, prevention, primary care, the charity sector, as well as formalised specialist health and social care. Discursive handling of reflexivity and subjectivity is welcomed in the methods and discussion sections. The format for articles otherwise matches that for BMJ Mental Health in general; however, we welcome suggestions for new and creative formats where they aid in the effective communication of experiences and data (please contact the Section Editor; [email protected] if further advice or guidance is needed, and with proposals if you are uncertain of scope and style). As a gold open-access journal, BMJ Mental Health makes all its published content accessible to all and free to access under a CC-BY-NC licence. BMJ offers waivers for the full Article Processing Charge (APC) (100% discount of the APC) where all authors are based in low-income countries. Please see the journal’s Instructions for Authors for more information.

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Patient consent for publication.

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Twitter @And_Cipriani

Contributors KB prepared drafts of the manuscript with feedback from AC and the editorial team.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests AC is Editor in Chief of BMJ Mental Health , but played no role in the decision. KB is a new section lead but did not play a part in the decision.

Provenance and peer review Not commissioned; externally peer reviewed.

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• Open access
• Published: 26 May 2020

Advancing mental health equality: a mapping review of interventions, economic evaluations and barriers and facilitators

• Laura-Louise Arundell 1 , 2 ,
• Helen Greenwood 2 ,
• Helen Baldwin 2 ,
• Eleanor Kotas 3 ,
• Shubulade Smith 2 , 4 ,
• Kasia Trojanowska 2 &
• Chris Cooper 1 , 5  

Systematic Reviews volume  9 , Article number:  115 ( 2020 ) Cite this article

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This work aimed to identify studies of interventions seeking to address mental health inequalities, studies assessing the economic impact of such interventions and factors which act as barriers and those that can facilitate interventions to address inequalities in mental health care.

A systematic mapping method was chosen. Studies were included if they: (1) focused on a population with: (a) mental health disorders, (b) protected or other characteristics putting them at risk of experiencing mental health inequalities; (2) addressed an intervention focused on addressing mental health inequalities; and (3) met criteria for one or more of three research questions: (i) primary research studies (any study design) or systematic reviews reporting effectiveness findings for an intervention or interventions, (ii) studies reporting economic evaluation findings, (iii) primary research studies (any study design) or systematic reviews identifying or describing, potential barriers or facilitators to interventions.

A bibliographic search of MEDLINE, HMIC, ASSIA, Social Policy & Practice, Sociological Abstracts, Social Services Abstracts and PsycINFO spanned January 2008 to December 2018.

Study selection was performed according to inclusion criteria. Data were extracted and tabulated to map studies and summarise published research on mental health inequalities. A visual representation of the mapping review (a mapping diagram) is included.

Overall, 128 studies met inclusion criteria: 115 primary studies and 13 systematic reviews. Of those, 94 looked at interventions, 6 at cost-effectiveness and 36 at barriers and facilitators. An existing taxonomy of disparities interventions was used and modified to categorise interventions by type and strategy. Most of the identified interventions focused on addressing socioeconomic factors, race disparities and age-related issues. The most frequently used intervention strategy was providing psychological support. Barriers and associated facilitators were categorised into groups including (not limited to) access to care, communication issues and financial constraints.

Conclusions

The mapping review was useful in assessing the spread of literature and identifying highly researched areas versus prominent gaps. The findings are useful for clinicians, commissioners and service providers seeking to understand strategies to support the advancement of mental health equality for different populations and could be used to inform further research and support local decision-making.

Systematic review registration

Not applicable.

Peer Review reports

Profound inequalities exist in the access to, experience and outcomes of mental health support for many marginalised or minority communities in the UK [ 1 , 2 ]. While a number of these characteristics are legally protected by the Equality Act 2010 (race, gender and sexual orientation) [ 3 ], and despite National Health Service (NHS) commissioners being statutorily bound by the Health and Social Care Act 2012 [ 4 ] to reduce health inequalities, inequities persist, particularly within mental health care where individuals may face an additional level of stigmatisation or discrimination [ 5 ]. Accumulating evidence has also established unsatisfactory experiences and outcomes of mental health care in individuals affected by social determinants of poorer health [ 6 , 7 ] including, but not limited to, socioeconomic deprivation, homelessness and transitional housing and asylum seeker or refugee status [ 2 , 8 , 9 ]. Furthermore, individuals with more than one of these features or protected characteristics are likely to be at further disadvantage, in line with the theory of intersectionality [ 10 ].

To reduce the disadvantage associated with these inequalities, meaningful and effective strategies need to be developed. Furthermore, tackling inequalities in mental health care can significantly benefit the wider economy. Consistent evidence suggests that improving access to, and experience of, mental health care can reduce the economic burden of illness and bring long-term cost savings associated with enhanced employability, fewer lost work hours and reduced utilisation of costly health services [ 11 ]. To truly bring about effective change and improve outcomes, innovative practice is required at all layers of care to promote cultural, structural and attitudinal shifts.

The NHS has committed to prioritising the reduction of health inequalities in both the Five Year Forward View for Mental Health [ 12 ] and, more recently, the NHS Long Term Plan [ 13 ]. Contemporary models of mental health care in high-income countries are primarily based on concepts of mental health and well-being derived from Western culture, and as such, do not necessarily consider cultural and social diversity [ 14 ]. Therefore, one way to advance mental health equality may be to commission, or improve uptake of, evidence-based interventions specifically targeted at communities that face inequalities. There is a growing literature base of ‘disparity interventions’ which aim to adapt existing interventions in such communities or develop new interventions tailored to the community of interest. To bring about change, it is important to understand what interventions have been attempted, their effects and overall costs, as well as barriers and facilitators to uptake and success.

This review is part of a larger piece of work—Advancing Mental Health Equality (AMHE) [ 15 ], which was commissioned by NHS England as part of the Mental Health Care Pathways programme. The review aims to map the existing literature on disparity interventions in order to inform the delivery of more effective and culturally appropriate care and, ultimately, advance mental health equality.

Study design: systematic map

Systematic mapping reviews aim to draw together existing studies in a specific topic area and develop an understanding of the available data as well as any potential gaps [ 16 , 17 , 18 , 19 , 20 ]. There is no authoritative methodological guidance on how to conduct a systematic mapping review, such as exists for instance for a systematic review [ 20 ]. Researchers have gravitated towards a systematic process of study identification, screening and data extraction [ 20 , 21 ], so that it is clear how the maps have been created. However, research questions are commonly broader in mapping reviews than in systematic reviews [ 22 ], study quality is not appraised or graded, and data are presented in a tabular or visual format rather than analysed or fully synthesised [ 16 , 17 , 20 , 21 ].

Systematic mapping was chosen as the method for this work since we aimed to understand the studies and data available with a view to establishing further research priorities. The maps are used to consolidate studies in the broad research area of interventions to address mental health inequalities experienced by marginalised or minority communities.

Research questions and objectives

The research questions were as follows:

What studies are there on interventions to address or reduce mental health inequalities?

The objective of this research question was to identify the existing interventions which seek to address mental health inequalities.

What are the data from economic evaluations for interventions to address or reduce inequalities in mental health care?

The objective here was to identify studies that assess the economic impact of interventions to address inequalities in mental health care.

What are the barriers and facilitators to interventions to address or reduce mental health inequalities?

The objective of the third question was to identify factors which act as barriers and those that can facilitate interventions which seek to address mental health inequalities.

To develop the research questions, we worked with stakeholders and methodologists [ 16 ], scoped the literature and informally reviewed the evidence base to identify relevant studies [ 23 ]. The purpose was to determine suitable research questions and use these to develop the approach to study identification, as well as pilot inclusion criteria and data extraction for the mapping review [ 23 , 24 ]. We convened a group of stakeholders to inform the development of this review as part of the AMHE resource [ 15 ] developed at the National Collaborating Centre for Mental Health (NCCMH). Stakeholders included people with lived experience of mental health problems, informal carers and people with one or more of the characteristics outlined in Table 1 . We also consulted experts in the field of mental health and equalities research; mental health care professionals, including psychiatrists, mental health nurses, approved mental health professionals (AMHPs); and staff working in equality lead roles in the NHS. They contributed to the development of the research questions through a series of focus groups and workshops [ 15 ]. They were also integral to the work on the categorisation of barriers. Stakeholders were informed of the progress of the review and had an opportunity to advise further in subsequent meetings and via email.

Definitions

Mental health inequalities and inequities.

‘Mental health inequalities’ are defined in this work as differences between population groups in their mental health status and outcomes, including the following:

the prevention of mental ill health;

access to and experience of mental health care; and

outcomes associated with mental ill health.

‘Mental health inequities’ are avoidable inequalities between population groups. They arise from social and material inequalities within society, such as discrimination, stigma and distribution of wealth and resources [ 25 ]. This study considers interventions addressing mental health inequities; however, because there is a lack of clear differentiation between definitions of inequity and inequality within the literature, the term ‘mental health inequality’ is used.

The population, intervention, outcomes and study designs

In this work, the targeted population is defined as people who meet at least one criterion from each of the two types of criteria pertaining to: (a) disorder/problem type AND (b) having one or more specific characteristics.

Population: Disorder/problem type

People who have a diagnosis, or who are at risk, of any of the following mental health conditions/disorders or problems:

bipolar disorder

antisocial behaviour and conduct disorders (in children and young people)

eating disorders

mental health problems in the pregnancy and postnatal period

personality disorders

psychosis and schizophrenia

This list is derived from the National institute for Health and Care Excellence’s (NICE) categorisation of guidance and pathways for the above specified conditions [ 26 ]. We have cross-referenced the list with the International Classification of Diseases’ (ICD-10) [ 27 ] classification of mental health disorders for conditions that fall under the categories of:

F20-29: Schizophrenia, schizotypal and delusional disorders

F30-39: Mood (affective) disorders

F40-48: Neurotic, stress-related and somatoform disorders

F60-69: Disorders of personality and behaviour in adult persons

F91: Conduct disorders (in: Behavioural and emotional disorders with onset usually occurring in childhood and adolescence)

Population: Having specific characteristics

People who have one or more of the characteristics outlined in equality impact assessments used by NICE in the development of guidelines. These characteristics served as a basis; we broke them down to identify the specific areas that we wished to focus on (see Table 1 ).

Intervention

In this work, an ‘intervention’ refers to any type of purposeful act, programme, system or deliverable that has been put in place with the intention of addressing or reducing mental health inequality or that is targeted at a specific group at risk of experiencing mental health inequality. These can include treatment interventions, targeted adaptations of existing treatments, policies, intentional organisational or structural changes.

This relates to the research questions, such that for research question 1, the outcomes relate to the effectiveness of interventions measured, for example, using relevant clinician- or patient-rated scales (such as symptom severity scales or quality of life measures) or access rates; for research question 2, the outcome is economic in nature, such as a cost-benefit; and for research question 3, the outcome is any actual or perceived barrier or facilitator to intervention uptake and/or success for which themes were extracted.

Study design

By research question:

Research question 1: any primary study evaluating effectiveness

Research question 2: any economic evaluation

Research question 3: any primary study evaluating barriers and/or facilitators to intervention uptake.

Systematic reviews were included but they are reported separately to studies identified above and in their own table (see Additional file 3 ). Editorials, commentaries and letters were not included.

Search strategy

Study identification (literature search) was undertaken by a qualified information specialist. The following bibliographic databases were systematically searched:

MEDLINE and MEDLINE In-Process via Ovid

Health Management Information Consortium (HMIC) via Ovid

Applied Social Sciences Index Abstracts (ASSIA) via ProQuest

Social Policy & Practice via Ovid

Sociological Abstracts via ProQuest

Social Services Abstracts via ProQuest

PsycINFO via Ovid.

The full search strategy can be found in Additional file 1 and takes the following form: (terms for mental health) and (terms for inequalities and reduce) and (terms for economics, meta-analysis, systematic reviews, observational studies, randomised controlled trials (RCTs) and barriers and facilitators) . The searches were not limited by language and spanned the period from January 2008 to December 2018, a timeframe the authors considered to be within resource limits [ 28 ] and agreed with select stakeholders. The search strategies were reviewed by the research team using the PRESS checklist [ 29 ]. Resources did not permit the inclusion of the Embase database.

Study selection

Studies were double-screened according to the pre-determined inclusion criteria. Title/abstract screening was undertaken using the desktop Rayyan application [ 30 ] and resulted in 97.1% agreement. Disagreements were resolved by discussion with the wider review team.

Inclusion criteria

For all research questions, to be included in the review the studies had to:

Focus on a population with:

Mental health disorders, conditions or problems that meet the definition for population in this review, and

Focus on a population group with protected or other characteristics identified as at risk of experiencing mental health inequalities (see Table 1 ), and

Address an intervention, as defined by this review, focused on addressing or reducing mental health inequalities, and

Meet the following criteria for one or more of the research questions:

Research question 1: be a primary research study (any study design) or systematic review reporting effectiveness findings for an intervention or interventions

Research question 2: report the findings of an economic evaluation; include sufficient detail regarding methods and results; the study’s data and results to be extractable (full economic evaluations that compare two or more relevant options and considered both costs and consequences; costing analyses that compared only costs between two or more interventions; and non-comparative studies were all included)

Research question 3: be a primary research study (any study design) or systematic review identifying and categorising, describing or explaining, potential barriers or facilitators to intervention uptake or success.

Data extraction

Where possible, data were extracted from title/abstract, which is consistent with methods of the other mapping reviews [ 20 ]. Where study abstracts were insufficient in providing the data required for extraction, lacked clarity or there was any doubt, full texts were retrieved and the relevant data extracted. For primary studies, we extracted study aims, study design, population (sample), population characteristic(s) associated with inequality, intervention details, intervention types and strategies (as applicable), comparator (as applicable) and outcomes. We also extracted currency for primary studies answering research question 2 and outcomes and/or themes for those answering research question 3. For systematic reviews we extracted study aims, included studies, population characteristic(s) associated with inequality, intervention details, intervention types and strategies, comparator(s) (as applicable) and outcomes. For systematic reviews to answer research question 3, we extracted themes pertaining to barriers and facilitators. Data extracted by one researcher were always double-checked by another. The data extraction tables are set out in Additional files 2 & 3 .

Study quality (risk of bias)

Study quality was not appraised.

The overarching findings from the study identification and screening processes are reported to PRISMA reporting guidance; a PRISMA flow chart [ 31 ] is included (Fig. 1 ).

PRISMA flow diagram of research studies search

The inclusion criteria were met by 128 studies; 115 were primary studies [ 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 ] and 13 were systematic reviews [ 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , 158 , 159 ]. Relevant data were extracted and tabulated to map the studies (additional file 2 ); separate tables summarised relevant systematic reviews (see Table 2 and additional file 3 ). Maps were used to consolidate primary studies that addressed the broad research area of mental health inequalities. Using Adobe Illustrator [ 160 ], we also developed a visual representation of the mapping review in the form of a mapping diagram (Fig. 2 ).

Mapping diagram of primary studies. *Studies examining these characteristics were only included if they also looked at other characteristics. **Specific populations are those who may have a specific set of characteristics and experiences placing them at risk of experiencing mental health inequalities and therefore may already be defined by multiple characteristics (e.g. refugees). Circle size area is asscociated with the number of primary studies that consider a population characteristic. The lines between the circles indicate where characteristics were considered together, while the thickness of the lines indicates the frequency of the association. 49 studies examined 2 population characteristics; the most frequent association was between age and socioeconomic factors. 24 studies examined 3 characteristics, of which age, race and socioeconomic factors were the most frequent associations. 8 studies examined 4 characteristics. 3 studies examined 5 characteristics. 3 studies examined 6 characteristics

We identified 94 studies that addressed research question 1, 6 that addressed research question 2 and 36 that addressed research question 3; some studies were relevant to more than one question. An existing taxonomy of disparities interventions [ 161 ] was used and modified by way of expansion (Table 3 ), to categorise interventions by type (access, early intervention, intervention, prevention) and strategy (Table 4 ). Target populations in primary studies were categorised by a range of characteristics and characteristic sub-types (Table 5 ). It should be noted that characteristic sub-types may or may not be mutually exclusive; therefore, the ‘Number of studies by characteristic’ column in Table 5 does not offer a summative count. The mapping diagram (Fig. 2 ) presents the findings of the mapping review with reference to the number of primary studies that consider different population characteristics and the frequency with which multiple characteristics are considered together across studies.

For research question 1, we identified 94 studies of interventions that aimed to address mental health inequalities: 85 primary studies and 9 systematic reviews. A total of 74 unique interventions were identified across primary studies.

We categorised primary study target populations according to the following characteristics: socioeconomic factors ( n = 65), age ( n = 46), race/ethnicity ( n = 29), location ( n = 17), pregnancy and maternity ( n = 14), sex ( n = 10), ‘specific intersectional groups’ (homeless people, youth offenders and refugees; n = 6), ‘other’ ( n = 6), disability ( n = 3), sexual orientation and gender identity (lesbian, gay, bisexual, transgender, queer and others (LGBTQ+); n = 2) and religion ( n = 2) (see Table 5 ). The mapping diagram (Fig. 2 ) presents the number of primary studies that consider different population characteristics using circle area, e.g. the circle for socioeconomic factors is largest, while the circle for religion is smallest. The lines connecting the circles indicate characteristics considered together, with thickness of the connecting lines showing frequency of that association. Forty-nine studies examined 2 population characteristics; the most frequent association was between age and socioeconomic factors. Twenty-four studies examined 3 characteristics, of which age, race and socioeconomic factors were the most frequent associations.

Countries in which primary studies were conducted were also recorded (Table 6 ), with the majority conducted in the USA ( n = 34) and the UK ( n = 17).

Intervention strategies used most frequently in primary studies were providing psychological support ( n = 45), delivering education and training ( n = 29), engaging the community ( n = 26) and other—culturally adapted interventions ( n = 26) (Table 4 ). The most frequently reported intervention strategy in systematic reviews was other—culturally adapted interventions ( n = 5) followed by providing psychological support ( n = 4). As with the primary studies, most of the reviews focused on targeting populations based on socioeconomic factors ( n = 6). The systematic reviews we identified, including information on intervention types, strategies and target populations, are summarised in Table 2 .

For research question 2, only 6 economic evaluations were included (Table 7 ); these were cost-effectiveness studies of which 3 were also identified in research question 1 [ 100 , 119 , 152 ]. Five studies examined population variables related to socioeconomic factors: 3 studies were of children [ 100 , 108 , 152 ], 1 looked at pregnant women [ 79 ] and another at adults eligible for Medicaid in the USA [ 119 ]. The last study examined the cost-effectiveness of a health-check intervention for people with learning disabilities [ 121 ]. All three cost-effectiveness studies of children with low socioeconomic factors examined the Incredible Years parenting programme . All cost-effectiveness studies were conducted in either the USA or Europe.

For research question 3, we identified barriers and facilitators to interventions aimed at addressing mental health inequalities, including the populations with whom certain interventions are used (Table 8 ).

Using the input from the lived experience members of the stakeholder group, we categorised the types of barriers reported in the literature (36 studies) into 8 groups: (1) limited treatment options and service limitations, (2) perceived or real discrimination, (3) access to care, (4) financial constraints, (5) communication issues, (6) awareness of available services, (7) trust in services or ‘the system’, (8) appropriateness of available services. Of the 36 included studies, 34 reported information on barriers in their findings, while only 20 reported on facilitators (Table 8 ).

Research question 1: What studies are there on interventions to address or reduce mental health inequalities?

The majority (80%) of primary studies focused on targeting populations based on socioeconomic factors ( n = 65), age (children and young people as well as older adults; n = 46) and race/ethnicity (ethnic minorities and indigenous/aboriginal populations; n = 29), indicating that these populations are most frequently targeted in interventions to address mental health inequalities in the published literature. However, it should also be noted that the majority of the included studies were conducted in the USA or the UK, limiting the ability to generalise these findings to other countries. We identified very few primary studies targeting populations on the basis of religious affiliation ( n = 2), sexual or gender identity and sexual orientation (LGBTQ+; n = 2) and disability ( n = 3), and none of the systematic reviews targeted these populations. These findings warrant further investigation as we are unable to conclude, through use of a mapping review, the reasons for these observations. It is likely that these findings might be indicative of the current state of the literature on availability of interventions for these populations. Further and more focused research on interventions designed for these specific populations is needed.

Identification of intervention strategies used to address inequalities across studies, by frequency, is an interesting finding of this mapping review. However, on its own this finding is of limited use and would be more informative when analysed in conjunction with other research on the effectiveness of these strategies with different populations, to better understand what works for different at-risk groups.

Research question 2: What are the data from economic evaluations for interventions to address or reduce inequalities in mental health care?

Only 6 economic evaluation studies were identified, limiting our ability to adequately address this research question and form a representative picture of the state of the cost-effectiveness literature regarding interventions aimed at addressing mental health inequalities. Half of the included studies were also analysed in research question 1, where the authors had performed a cost-effectiveness analysis as part of the study.

Research question 3: What are the barriers and facilitators to interventions to address or reduce mental health inequalities?

The identification of 8 types of barriers in the literature suggests that addressing inequalities in mental health care may be hindered by several factors, other than those that tend to be most commonly discussed, such as access to care [ 147 , 162 , 163 , 164 , 165 ] and service integration [ 166 ]. The identification and categorisation of barriers and associated facilitators to interventions aimed at tackling inequalities is, therefore, a useful outcome of this mapping review. An understanding of barriers and facilitators can inform future intervention design, clinical practice, service organisation and methods of care delivery. We were able to identify where interventions are likely to encounter challenges in meeting their aims, while also summarising solutions and potentially helpful guidance around what could work. We were also able to identify the population groups that appear at risk of experiencing barriers. Future research should look more deeply at the effectiveness of facilitating factors in improving equality for people from at-risk population groups.

Strengths and limitations

This review demonstrates a number of important strengths. First, the protocol was informed by expert opinion with sustained input from expert stakeholders, including those with lived experience of mental health problems and related inequalities. This approach ensured that the direction of the research was both person-centred and reflected the priorities of the target populations. The input from clinicians also ensured the research held practical applicability and could be translated to clinical practice. In addition, the search strategy was broad, incorporating a range of pervasive cultural, social and intersectional inequalities. Similarly, the articles covered a wide geographical range across several continents and were not excluded on the basis of language. This approach is particularly pertinent for health equity research and ensures that geographical inequalities are also represented within the literature base.

We should also acknowledge the caveats. First, while a systematic approach was taken, it is not comparable with a full systematic review as only select databases were chosen; we did not search Embase and we were unable to search grey literature. To address research question 3, the search approach taken used a pragmatic cluster of search terms to focus the study identification on the barriers and facilitators to advancing mental health equality. The aim was to identify relevant studies within a manageable volume of studies to screen. It is possible that some studies have been overlooked by this approach and future work may look at the use of different terms. The timeframe for our literature search was narrowed to 2008–2018. We decided on a decade span between the authors and with input from stakeholders, as it was considered to be within resource limits, following guidance in the Cochrane Handbook [ 28 ]. As a result of this approach, it is possible that a relevant body of literature has been missed. In particular, considering the lack of literature pertaining to research question 2, it would be beneficial to conduct a full and focused systematic review in the future, to both provide a more encompassing review of the literature and gain a greater insight into the economic effectiveness of these interventions. Furthermore, as this is a mapping review, we did not assess the quality of each study, nor did we determine the effectiveness of the interventions. As such, the findings report the breadth of the data available, but it would be inappropriate to make any firm recommendations. Data were extracted from title/abstract where possible, with extraction from full text only performed when abstracts either lacked the data required or were unclear. While this method of extraction is both efficient and consistent with other mapping reviews [ 20 ], it does carry a risk of potentially relevant information being missed.

A further limitation arises from the problematic nature of categorising communities in the literature. The LGBTQ+ movement represents a diverse range of communities, each with unique needs and social perceptions; for example, the transgender community may face entirely different social issues and experiences of care compared with the lesbian community, and so on. Within the literature, however, these distinct groups were often amalgamated under one overarching label and, as such, it was difficult to separate the findings for lesbian, gay, bisexual, transgender and queer communities. Similarly, the Black, Asian and minority ethnic (BAME) label amalgamates a number of distinct cultures and ethnicities with heterogeneous experiences. Much of the literature did not make any further distinctions, once again limiting our ability to draw distinct conclusions for each component group. This approach limits the practical applicability of academic research concerning these communities and highlights a further pervasive inequality to which they are subjected. Ultimately, this requires a more nuanced, accurate reporting within future academic research involving these communities to ensure care can be tailored to their unique needs.

The stipulation applied to our inclusion criteria regarding population characteristics for age, sex and pregnancy and maternity is potentially problematic. This is because, to be considered eligible for inclusion in the review, studies of these populations needed to include people who have another characteristic or need that puts them at risk of experiencing inequalities. Our reasoning for this decision was to avoid including studies of participants from these groups who did not have an identifiable inequality. For example, studies of children and young people as such may not focus on addressing inequalities but might have been included inappropriately had it not been for the caveat applied here. Still, even though necessary, it is possible that the caveat meant that some potentially relevant studies were excluded.

Based on these limitations, we recommend a full systematic review for each of the characteristic sub-types to gain greater insights into the effectiveness of interventions to tackle mental health inequalities and inform national delivery of care for different population groups.

The mapping review indicated that the majority of mental health inequality interventions identified in this study focus on addressing socioeconomic factors, race disparities and age-related issues (most of which pertain to children and/or young people). The majority of interventions tend to use providing psychological support and delivering education and training as strategies. The review also identified population groups who may be at risk of experiencing barriers to interventions aimed at addressing inequalities. This knowledge is useful for commissioners and service providers seeking to understand what can be done to support the advancement of mental health equality for different populations. The information gained from the mapping review should be used to inform the direction of further research that could influence local commissioning and service provision.

The mapping review was useful in assessing the spread of literature across sub-topics and identifying the highly researched areas (which include interventions aimed at minority races; addressing socioeconomic factors; and age-related inequality issues) versus the prominent gaps (including interventions aimed at marginalised religious groups; the differing and unique needs of groups within the LGBTQ+ community; and people with disabilities). This map supports the identification of these potential gaps in existing research and assists in setting out future research priorities.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the study. Information relevant to this study can be accessed in the additional files.

Abbreviations

Advancing Mental Health Equality

Approved mental health professional

Black, Asian and minority ethnic

Children and young people

Delivering education and training

Engaging the community

Enhancing language, literacy and communication

Improving access to psychological therapies

Improving access to support, care and treatment for mental health problems

Improving access to testing and screening

International Classification of Diseases

Lesbian, gay, bisexual, transgender, queer and others

National Institute for Health and Care Excellence

Not otherwise specified

Other—culturally adapted interventions

Other—community revitalisation

Other—home-based care

Other—not otherwise specified

Other—technology

Providing financial incentives or removing financial barriers

Providing psychological support

Providing reminders and feedback

Socioeconomic status

Randomised controlled trial

Restructuring the care team

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Acknowledgements

The authors would like to thank Sarah Dawson for her contributions to the development of the research questions and search strategy. They would also like to thank Dominique Gardner for her support in project managing this piece of work as part of the Advancing Mental Health Equality (AMHE) resource at the NCCMH. The authors also wish to acknowledge and thank all of the stakeholders involved in the development of the AMHE resource.

This review was funded by NHS England and commissioned by the National Institute for Health and Care Excellence (NICE) as part of the Advancing Mental Health Equality resource, which was developed under the Mental Health Care Pathways programme at the National Collaborating Centre for Mental Health (NCCMH). The publication charge for this article was paid for by the NCCMH.

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LLA contributed to research question design, screening and data extraction and led on the overall development and writing of this review. HG contributed to the writing of this review, particularly the development of definitions and criteria for inclusion, and created the mapping diagram. HB contributed to the screening and data extraction as well as the writing of this review. EK finalised the search strategy and performed the database searches. KT contributed to the writing of this review. SS provided oversight over the development of the review and contributed to definitions and inclusion criteria. CC contributed to the development of the review, particularly with regard to designing the research questions and the methods. All authors have read and approved the final manuscript.

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Tabulated study characteristics for included primary studies.

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Tabulated study characteristics for included systematic reviews.

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Arundell, LL., Greenwood, H., Baldwin, H. et al. Advancing mental health equality: a mapping review of interventions, economic evaluations and barriers and facilitators. Syst Rev 9 , 115 (2020). https://doi.org/10.1186/s13643-020-01333-6

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Mapping mental health inequalities: The intersecting effects of gender, race, class, and ethnicity on ADHD diagnosis

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• 1 Department of Sociology and Criminology, Villanova University, Villanova, Pennsylvania, USA.
• 2 RTI International, Center for the Health of Populations, Waltham, Massachusetts, USA.
• 3 Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
• 4 Department of Health Policy and Management, School of Public Health, State University of New York (SUNY) Downstate Health Sciences University, Brooklyn, New York, USA.
• PMID: 35147240
• DOI: 10.1111/1467-9566.13443

While the effects of social stratification by gender, race, class, and ethnicity on health inequalities are well-documented, our understanding of the intersecting consequences of these social dimensions on diagnosis remains limited. This is particularly the case in studies of mental health, where "paradoxical" patterns of stratification have been identified. Using a Bayesian multi-level random-effects Poisson model and a nationally representative random sample of 138,009 households from the National Survey of Children's Health, this study updates and extends the literature on mental health inequalities through an intersectional investigation of one of the most commonly diagnosed psychiatric conditions of childhood/adolescence: attention-deficit hyperactivity disorder (ADHD). Findings indicate that gender, race, class, and ethnicity combine in mutually constitutive ways to explain between-group variation in ADHD diagnosis. Observed effects underscore the importance and feasibility of an intersectional, multi-level modelling approach and data mapping technique to advance our understanding of social subgroups more/less likely to be diagnosed with mental health conditions.

Keywords: attention-deficit hyperactivity disorder; intersectionality; mental health; multi-level modelling; social constructionism.

© 2022 Foundation for the Sociology of Health & Illness.

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What has economics got to do with it? The impact of socioeconomic factors on mental health and the case for collective action

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• Briana Gonçalves 3 &
• Neil Quinn 1  

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A clear link exists between social and economic inequality and poor mental health. There is a social gradient in mental health, and higher levels of income inequality are linked to higher prevalence of mental illness. Despite this, in the late 20th and early 21st century, psychiatric and psychological perspectives have dominated mental health research and policy, obscuring root socioeconomic contributors. Drawing on contemporary research on the social determinants of mental health, with particular reference to Europe and the U.S., this paper argues that a sharper focus on socioeconomic factors is required in research and policy to address inequalities in mental health. Current attempts to move this direction include: evaluation of the impact of economic policies on mental health, community-based partnerships, increased professional awareness and advocacy on socioeconomic factors. This necessitates greater understanding of the barriers to such actions. This paper argues that advancing ‘upstream’ approaches to population mental health requires an interdisciplinary research vision that supports greater understanding of the role of socioeconomic factors. It also demands collective cross-sectoral action through changes in social and economic policy, as well as economic frameworks that move beyond an exclusive focus on economic growth to embrace collective and societal wellbeing.

The importance of socioeconomic factors for mental health

'Economics is the mother tongue of public policy, the language of public life, and the mindset that shapes society' (Raworth, 2017 , p. 6)

Growing evidence connects economic inequality and poor mental health (Friedli, 2009 ; Pickett and Wilkinson, 2010 ; Platt et al., 2017 ). Experience of socioeconomic disadvantage, including unemployment, low income, poverty, debt and poor housing, is consistently associated with poorer mental health (Silva et al., 2016 ; Elliott, 2016 ; Platt et al., 2017 ; Friedli, 2009 , Rogers and Pilgrim, 2010 ). Mental health problems are particularly prominent amongst marginalised groups experiencing social exclusion, discrimination and trauma, leading to compound vulnerability (Rafferty et al., 2015 ). Greater inequality within societies is associated with greater prevalence of mental illness (Wilkinson and Pickett, 2009 ; Pickett and Wilkinson, 2010 ), and economic recessions have had devastating impacts on population mental health (Platt et al., 2017 ; Wahlbeck and McDaid, 2012 ). At a global level, mental health and substance use disorders account for between one fifth and almost one third of Years Lived with Disability (Whiteford et al., 2013 ; Vigo et al., 2016 ). At the same time there is increasing interest in how to promote positive mental health at a societal level (Friedli, 2009 ; Rogers and Pilgrim, 2010 ; Hanlon and Carlisle, 2013 ).

However, the dominance of medical, psychiatric and psychological perspectives on mental health from the 1970s onwards has distracted from socioeconomic factors (Smith, 2016b ; Shim et al., 2014 ). Drawing on contemporary research on the social determinants of mental health, with particular reference to Europe and the U.S., this paper argues that a sharper focus on socioeconomic factors is required in research and policy to address inequalities in mental health.

Contemporary research on socioeconomic determinants of mental health

'Today, in the wake of the global economic slowdown, rising rates of mental illness and disaffection with psychopharmacology, the idea that there are social determinants of mental health is taking root once more'. (Smith, 2016b , p. 9)

There is growing interest across disciplines in understanding and addressing the social determinants of mental health (Friedli, 2009 ; Fisher and Baum, 2010 ; Bowen and Walton, 2015 ; Kinderman, 2016 ; Compton and Shim, 2015 ; Smith, 2016b ; Silva et al., 2016 ). This sits alongside increased attention to public mental health, and the promotion of positive societal well-being (Wahlbeck, 2015 ; Rogers and Pilgrim, 2010 ; Hanlon and Carlisle, 2013 ). The role of psychosocial factors and chronic stress has also been emphasised in understanding health inequalities (Fisher and Baum, 2010 ; Wilkinson and Pickett, 2017 ). Furthermore, stigma (a ubiquitous component of mental health difficulties), has been recognised as a fundamental cause of health inequalities (Hatzenbuehler et al., 2013 ).

However, within the broad literature on the social determinants of mental health, to what extent are socio-economic factors considered? There is consistent evidence supporting the link between socioeconomic inequality in terms of income, employment, and neighbourhood environments and poorer mental health outcomes (Silva et al., 2016 ). At an ecological level, a significant relationship has been shown between higher income inequality (as measured by the Gini coefficient) and higher incidence rates of schizophrenia (Burns et al., 2014 ). In addition, the connection between experience of socioeconomic disadvantage and increased risk of suicidal behaviour has also been established (Platt et al., 2017 ). Furthermore, the association between educational inequalities and mental health outcomes may be attenuated by controlling for employment status, indicating the importance of employment for mental health (Katikireddi et al., 2016 ). At a community level, low socioeconomic status may lead to greater concerns about neighbourhood safety, and decrease the amount of physical activity in the community, with consequent impacts on mental health (Meyer et al., 2014 ). A focus on socioeconomic factors may also link with ideas of social capital or community efficacy, measures of trust and commitment by residents to a neighbourhood (Platt et al., 2017 ), which have been linked to rates of depression, suicide, and internalising behaviours (Schmidt et al., 2014 ).

Many argue for a renewed focus on social justice, advocating for the significance of socioeconomic factors for mental health (Friedli, 2009 ; Rogers and Pilgrim, 2010 ). The impact of material and economic conditions and consumerism on population wellbeing is also recognised (Rogers and Pilgrim, 2010 ; Friedli, 2009 ). From a U.S. perspective, Jones et al. ( 2009 ) offer a theoretical framework to identify the social determinants of inequity shaped by systems of power and the distribution of resources, including an economic system that creates class structures and dimensions of opportunity (Jones et al., 2009 ). In addition, disparities in education and income play a major role in understanding racial difference in health and mental health (Williams et al., 1997 ). Krieger et al. ( 1997 ) argue that social class, at the household and community level, predicts inequalities in health (Krieger et al., 1997 ), and the role of economic inequality, poverty, and deprivation is implicated in poor mental health in the United States (Compton and Shim, 2015 ; Manseau, 2015 ).

Despite this, in comparison with biomedical, neuropsychiatric and psychological literature, the social determinants of mental health are strikingly understudied (Shim et al., 2014 ). In Europe, research on the prevention of poor mental health has received a comparatively low level of investment (Wykes et al., 2015 ). In the United States, funding of prevention constitutes a notoriously small percentage of overall healthcare expenditures (Miller et al., 2012 ). Yet the economic cost of treatment and lost productivity related to mental health and substance use disorder is well documented. While the National Institute for Mental Health named prevention as a core objective in its strategic plan for research (National Institute for Mental Health, 2015 ), there is not a clear picture of the scope and scale of investment in mental health prevention across government and philanthropy. It is likely there has been even less investment in research on the social determinants of mental health, and socioeconomic factors in particular. Thus, there is a need for greater research capacity (Wahlbeck and McDaid, 2012 ).

Moving from evidence to action: policy, communities and practice

'levels of mental distress among communities need to be understood less in terms of individual pathology and more as a response to relative deprivation and social injustice' (Friedli, 2009 , p.III)

However, it is not only further evidence on the link between economic inequality and mental health that is required, but also action to address it (Smith, 2016b ). This may require a shift from addressing individuals’ psychological states to a focus on social justice and broader economic conditions. Current attempts to move this direction include action in policy, communities and service provision.

In policy, this agenda was advanced by a World Health Organisation report in 2014, which highlighted the social determinants of mental health at an international level (World Health Organization, 2014 ). In Europe, the Joint Action on Mental Health has championed a focus on ‘Mental Health in All Policies’, which promotes action in non-health policy areas including employment and welfare (EU Directorate General for Health and Food Safety, 2015 ). Evidence is beginning to accumulate on relevant policy actions, including labour market regulation (Katikireddi et al., 2016 ) and part-time sickness absence (EU Directorate General for Health and Food Safety, 2015 ), investment in social protection (Niedzwiedz et al., 2016 ), and protective employment policies (Platt et al., 2017 ). In the United States, better population health outcomes have also been found in states with more progressive policies such as minimum wage and corporate tax rates (Rigby and Hatch, 2016 ). It has also been raised that a Universal Basic Income might positively impact on population mental health (Smith, 2016b ). Whilst there is evidence for interventions which can lessen the impact of poverty and inequality on mental health, including interventions aimed at the individual or family level (e.g., parenting interventions), evidence is more limited on community interventions or on cross-sectoral action on policies (Wahlbeck et al., 2017 ).

At a community level, the expansion of the Community Schools model in the U.S., which provides children in socioeconomically disadvantaged areas, with access to health services (medical, dental, vision and counselling services), brings more holistic attention to the education and healthy development of children (Oakes and Daniel, 2017 ). Education policies that recognise structural inequalities show promise to close the economic and achievement gap. Additionally, New York City has launched Thrive NYC, a comprehensive city-based mental health plan to reduce stigma, intervene early, and improve access to services (NYC Thrive, 2016 ). Encouraging partnership and reducing silos, a major component of the initiative, has linked community based organisations serving the most socially and economically disadvantaged populations with mental health providers to increase access to mental health and substance use services (Chapman et al., 2017 ). Furthermore, efforts at a community level which promote social capital are promoted as a buffer against the impact of socioeconomic factors (Wahlbeck and McDaid, 2012 ).

At the level of service provision, there are moves to increase professional awareness and advocacy on the social determinants of mental health (Compton and Shim, 2015 , Shim et al., 2014 ). This may include a focus on social justice and socioeconomic factors in therapeutic work. Kinderman argues 'practical help to resolve real-world issues such as debt, employment issues, housing problems and domestic violence' may be important roles for clinicians (Kinderman, 2016 , p. 4). Shim et al. ( 2014 ) also suggest that mental health professionals have an advocacy role to influence public policies that impact on mental health (Shim et al., 2014 ). Bowen and Walton argue that there is a role for social workers in addressing racial and ethnic disparities in mental health (Bowen and Walton, 2015 ). One relevant example from the U.K. is the work of Psychologists Against Austerity, who have campaigned on the mental health impact of welfare policies (McGrath et al., 2016 ).

Trying to focus ‘upstream’: barriers to action on socioeconomic factors

'We are failing on health equity because we are failing on equity' (Braveman, 2012 , p. 515)

A distinction is often made between 'upstream societal influences' (which can include living and working conditions and wider societal structures) and 'downstream risk factors' (which include behaviours such as smoking or drinking as well as biological risk factors) (Graham, 2009 , p. 472). To effectively take action on socioeconomic factors and mental health, there is a need for awareness of what might pull research and policy ‘downstream’ (Douglas, 2016 ; Graham, 2009 ). These barriers might include the dominance of the current economic paradigm, a focus on psychological or community resilience, ignoring factors like structural racism, or the challenges of mental health care provision.

In health inequalities research it is argued that an exclusive focus on health may over-medicalise the issue, veiling the fundamental problem of social inequality (Lynch, 2017 ; Douglas, 2016 ). It is stated that efforts should include awareness of the socioeconomic and political contexts which generate health inequalities, particularly the influence of neoliberalism (Smith et al., 2016a ; Collins et al., 2016 ) Such arguments are equally salient to mental health. However, focusing ‘upstream’ presents challenges given that the dominant neoliberal paradigm 'actively embraces inequality' (Collins et al., 2016 , p. 129). This may point to confronting the current inequitable economic paradigm and considering alternatives to economic growth that incorporate broader social and environmental concerns (Fioramonti, 2016 ; Raworth, 2017 ). A sharper focus on fundamental inequalities, and the economic system which underpins them, may be critical to addressing the ‘upstream’ influences on mental health.

It has also been argued that it may be problematic to focus on psychological or community assets and strengths, and social capital, as this may mask a focus on socioeconomic factors, which are fundamental causes of distress (Friedli, 2016; Rogers and Pilgrim, 2010 ; Knifton, 2015 ). Indeed, Friedli argues: 'Choosing psycho -analysis over economic analysis has serious consequences for how public health explains and responds to issues of social justice' (Friedli, 2016 , p. 216, original emphasis). This argument may be particularly relevant for mental health, where psychological conceptualisations may predominate. Within a neoliberal policy framework, there is the danger of endorsing individualistic conceptualisations of complex social and economic problems, where the predominant biomedical model has often resulted in a systematic neglect of the impact of social and structural barriers experienced by people with poor mental health (Bayetti et al., 2016 ; Friedli, 2016 ). Thus, whilst the relevance of psychosocial factors is recognised, it is important to increase the salience of social and economic inequalities which generate inequalities in mental health at a population level.

Furthermore, it is critical to consider race and ethnicity (Lynch and Perera, 2017 ). While racism has been identified as a social determinant of health, there is a significant lack of research or policy to address it (Bailey et al., 2017 ; Rafferty et al., 2015 ). Advancing policies to tackle structural racism may have significant implications for population mental health. Despite having distinct healthcare systems and ideologies on healthcare access, both the U.S. and U.K. have significant health inequalities by race and ethnicity (Bailey et al., 2017 ; Department of Health, 2009 ). Research on mental health and racial discrimination has largely considered interpersonal discrimination, not structural racism and the link to inequalities (Bailey et al., 2017 ). While increased funding and resources for mental health services and prevention is needed, greater attention must be given to addressing structural racism that leads to inequalities in education, employment, and mental health.

Finally, the need to ensure adequate mental health care provision is a pressing concern in both Europe and the U.S. Indeed, many OECD countries face ongoing challenges regarding adequate levels of resourcing for mental health services (Wahlbeck and McDaid, 2012 ). Current healthcare policy debates in the U.S. threaten progress in increasing the number of insured individuals as well as what services they can receive. Current debate, focused on insurance access and eligibility, is troublingly void of a focus on prevention or addressing social determinants and structural racism. In fact, while mental health care access improved following implementation of the Affordable Care Act, there was no progress in reducing racial and ethnic disparities (Creedon and Le Cook, 2016 ). While advocates and researchers are pulled toward policy and legislative fights over healthcare provision, larger macro issues impacting health and mental health, i.e. social determinants, are lost. Negotiating space for dialogue on the importance of prevention, alongside service provision, will be crucial.

Conclusions: taking collective action

Smith ( 2016b ) argues that a focus on socioeconomic factors and mental health is not new, but had previously gained ground in the early 20th century (Smith, 2016b ). As a renewed interest emerges in the current context, there are increasing calls for collective actions (Kinderman, 2016 ) and inter-disciplinary and inter-sectoral approaches, which re-invigorate a focus on fundamental socioeconomic inequalities and social justice (Friedli, 2009 ; Braveman, 2012 ).

Encouragingly, the growing body of research on socioeconomic factors and social determinants of health is narrowing in on mental health. Diagnosing problems, however, is not enough. Evidence on policy actions and a collective appreciation of issues that prevent upstream approaches is also needed: structural barriers including racism and discrimination, the medicalising of population mental health, access and quality of services, and ultimately the economic system itself.

To advance upstream approaches will require an inter-disciplinary research vision which extends beyond biomedical, neuropsychiatric and psychological models of mental health, and which supports greater understanding of the role of socioeconomic factors and economics. It will necessitate bold cross-sectoral policy action including changes to wider social and economic policies such as social protection, taxation, employment and housing policy, as well as health policy. Given the ubiquity and influence of economics, this agenda should be supported by the advancement of paradigms that move beyond an exclusive focus on economic growth (Raworth, 2017 ; Fioramonti, 2016 ), and which appreciate the importance of collective and societal wellbeing (Knifton, 2015 ).

Population mental health is intimately connected to societal economic conditions. The (poor) mental health of modern societies offers a stark indication of the consequences of not taking action: 'economic growth at the cost of social recession' (Friedli, 2009 , p. IV). Socioeconomic inequality may be 'the enemy between us' (Wilkinson and Pickett, 2017 , p. 11), increasing status competition, undermining the quality of social relations, increasing stress and impacting on health, mental health, and wellbeing. In response to this, there is a need to build an economic system that tackles these inequalities in mental health.

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Acknowledgements

The collaboration for this paper was made possible by a European Union funded Horizon 2020 RISE project ‘Citizenship, Recovery and Inclusive Society Partnership’ ( www.crisppartnership.eu) . This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement, No 690954. The views in this publication are solely the responsibility of the authors. The Commission is not responsible for any use that may be made of the information it contains.

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Macintyre, A., Ferris, D., Gonçalves, B. et al. What has economics got to do with it? The impact of socioeconomic factors on mental health and the case for collective action. Palgrave Commun 4 , 10 (2018). https://doi.org/10.1057/s41599-018-0063-2

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Understanding inequalities in access to adult mental health services in the UK: a systematic mapping review

• Hayley J. Lowther-Payne 1 ,
• Anastasia Ushakova 1 ,
• Adelaide Beckwith 2 ,
• Catherine Liberty 3 ,
• Rhiannon Edge 1 &
• Fiona Lobban 3  

BMC Health Services Research volume  23 , Article number:  1042 ( 2023 ) Cite this article

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Population groups experience differential access to timely and high-quality mental healthcare. Despite efforts of recent UK policies to improve the accessibility of mental health services, there remains a lack of comprehensive understanding of inequalities in access to services needed to do this. This systematic mapping review aimed to address this gap by identifying which population groups continue to be poorly served by access to adult mental health services in the UK, how access has been measured, and what research methods have been applied.

Seven electronic databases were searched from January 2014 up to May 2022. Primary research studies of any design were included if they examined access to adult NHS mental health services in the UK by population groups at risk of experiencing inequalities. Study characteristics, measures of access, inequalities studied, and key findings were extracted. A best-fit framework approach was used, applying Levesque’s Conceptual Framework for Healthcare Access to synthesise measures of access, and applying a template derived from Cochrane Progress-Plus and NHS Long Term Plan equality characteristics to synthesise key findings associated with inequalities.

Of 1,929 publications retrieved, 152 studies of various types were included. The most frequently considered dimensions of inequality were gender, age, and ethnicity, whilst social capital, religion, and sexual orientation were least frequently considered. Most studies researched access by measuring “healthcare utilisation”, followed by studies that measured “healthcare seeking”. Key barriers to access were associated with individuals’ “ability to seek” (e.g. stigma and discrimination) and “ability to reach” (e.g. availability of services). Almost half of the studies used routinely collected patient data, and only 16% of studies reported patient and public involvement.

Conclusions

Little appears to have changed in the nature and extent of inequalities, suggesting that mental health services have not become more accessible. Actions to reduce inequalities should address barriers to population groups’ abilities to seek and reach services such as stigma-reducing interventions, and re-designing services and pathways. Significant benefits exist in using routinely collected patient data, but its limitations should not be ignored. More theoretically informed research, using a holistic measurement of access, is needed in this area.

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https://doi.org/10.17605/OSF.IO/RQ5U7 .

Peer Review reports

Mental ill health, such as depression, anxiety, and psychosis, is one of the top ten leading causes of global disease burden [ 1 ]. The World Health Organisation (WHO) 2022 report on “transforming mental health for all” called for action to strengthen global mental healthcare to address this need as services continue to be under-funded and under-resourced [ 2 ]. In 2016, it was estimated that only one in three people who experience a mental health condition in England could access the mental health support they need [ 3 ]. By 2021, an estimated 8 million people with mental health needs were not in contact with mental health services [ 4 ]. On the whole, individuals face high thresholds for being eligible to receive mental healthcare and if deemed eligible, long waiting times before receiving care [ 5 ]. Evidence suggests that population groups who have been exposed to social and economic disadvantage experience differential access to timely and high-quality mental healthcare in the UK [ 5 ].

Healthcare access however, is a complex concept to define and measure. Many theoretical frameworks have been developed to conceptualise access, adopting a range of ways to not only define what access is but also understand what may influence access. One of the most recent frameworks is Levesque’s Conceptual Framework for Healthcare Access [ 6 ], which views access as a multi-dimensional concept associated with dimensions of healthcare systems (e.g. their approachability), and individuals’ abilities to access healthcare (e.g. ability to seek). The application of theoretical frameworks is somewhat limited in mental health service research. The stigma people with mental health conditions experience and the existence of involuntary mental healthcare adds further complexity to understanding access to mental health services specifically. Given these unique challenges, there is a need to understand how existing research has conceptualised access in relation to mental healthcare.

In recent years, the UK Government have committed to improving the accessibility of publicly funded mental health services [ 7 , 8 , 9 ]. A recent report reviewing the progress of these commitments based on audits, suggests that whilst more people are now in contact with mental health services than in 2016, targets to improve access and address inequalities have been missed [ 4 ]. A comprehensive understanding of inequalities is required to review and improve access to mental health services for different population groups. The NHS Advancing Mental Health Equalities Strategy summarised differential access to mental health services across population group characteristics (e.g. age, ethnicity, deprivation, sexual orientation) [ 10 ]. Evidence drawn upon in this report however, was largely from the grey literature (e.g. third sector organisation reports). Reviewing the academic literature could develop a more empirical foundation to inform policy decision making and actions to address inequalities. Asthana et al. [ 11 ] conducted an evidence review, now 8 years old, of quantitative variations in access to NHS mental health services in England, and reported differences associated with age, gender, ethnicity, socioeconomic status, and geographical area. The review however, omitted other dimensions (e.g. sexual orientation, gender identity, refugee and asylum seeker status), did not review the intersectionality of these groups, and did not include qualitative evidence. Therefore, it is necessary to update these findings to not only consider more recent research (e.g. impact of COVID-19, effect of mental health policies), but also to consider other dimensions of inequalities and qualitative evidence that may be able to contextualise quantitative variations in access to mental health services between groups.

This systematic mapping review collated existing evidence to identify which population groups are poorly served by access to adult mental health services in the UK. The review explored how access was measured and which, if any, theoretical frameworks have been applied. Due to the complexity of mental health services across different countries and the unique challenges posed for insurance-based and universal healthcare systems, this review focused only on the UK context. The NHS Advancing Mental Health Strategy outlined the need to use data to drive insight and decision making to improve accessibility of services [ 10 ], so this review also assessed how routinely collected patient data has been used to quantify inequalities in access. Specifically, this systematic mapping review aimed to address the following research questions:

How has access been measured in research exploring inequalities in access to adult mental health services in the UK?

What research methods and theoretical frameworks have been applied in this research?

What evidence exists regarding the differences in access between population groups, and how does this evidence offer insights into inequalities in access to adult mental health services in the UK?

How has the analysis of routinely collected patient data from mental health services been used to understand inequalities in access?

A systematic mapping review aims to map out and categorise existing evidence on a broader topic than would be studied in a typical systematic review, to develop an understanding of the literature and identify gaps that could be explored with further research [ 12 ]. Due to the breadth of evidence available in this area, the heterogeneity of studies, and the broad research questions, a systematic mapping review was deemed a suitable way of synthesising evidence from relevant studies. This review was conducted based on existing guidance for scoping reviews [ 13 ], and reported based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist [ 14 ] (see Table S1 in Additional file 1 for reporting checklist), as one does not specifically exist for systematic mapping reviews.

Search strategy

Studies were identified through searching the titles, abstracts, and keywords of records across seven electronic databases (Academic Search Ultimate via EBSCOhost, CINAHL via EBSCOhost, EMBASE via Ovid, MEDLINE Complete via EBSCOhost, PsycINFO via EBSCOhost, Scopus via Scopus, and Web of Science via Clarivate) from January 2014, in line with the release of the NHS Five Year Forward report [ 8 ] and to extend previous review findings [ 11 ], up to 25th May 2022. A search strategy using a combination of Subject Headings and keywords related to main concepts of the research questions was developed and finalised with the assistance of a Faculty Librarian from Lancaster University. Search terms used across all searches are presented in Table 1 . Table S2 presents the search strategies used across the seven databases, the date the search was conducted, and the corresponding number of results identified (Additional file 2 ). Additional studies were identified through screening reference lists and citations of included studies and relevant review articles.

Eligibility criteria

Preliminary searches were used to develop the eligibility criteria. Primary research studies of any design (quantitative, qualitative, mixed methods) which examined access to adult mental health services in the UK and focused on population groups noted to be at risk of experiencing inequalities according to the NHS Long Term Plan [ 7 ] and Cochrane Progress-Plus framework [ 15 ] were eligible for inclusion. Studies were limited to those published in English. As grey literature (e.g. charity reports, policy documents) had already been summarised in a recent NHS policy document [ 10 ], these types of documents were not considered for inclusion. The eligibility criteria is outlined in Table 2 .

Data selection

All retrieved citations from the searches were collated in EndNote [ 16 ] and duplicates were removed. The remaining citations were imported into Rayyan [ 17 ]. One reviewer (HL) screened titles and abstracts of retrieved citations against the eligibility criteria in Rayyan. Full texts of studies thought potentially relevant were obtained and assessed by HL. Twenty percent of the titles and abstracts, and 15% of full text articles were screened by a second reviewer (AB/CL) to check consistency and accuracy in applying eligibility criteria. Uncertainty or disagreements at any stage were resolved through discussion, and if consensus could not be reached, the wider review group was consulted. Reasons for exclusion at the full text screening stage were documented.

Data charting and synthesis

A bespoke data extraction form was developed and piloted to collect relevant information from included studies. Data extracted included author(s), year of publication, study aim(s), setting, design, population, theoretical framework (if applicable), measure of access, measure of inequality, and key findings. Data extraction was performed by HL and a 5% sample of this was checked by a second reviewer (AB/CL) to verify completeness and accuracy. Any discrepancies were resolved through discussion or consultation with a third reviewer, and where necessary the wider review team. Quality assessment was not conducted in this review as studies were not going to be excluded on this basis.

Study characteristics (e.g. design, setting) were tabulated and synthesised narratively to describe the type of evidence available. A best-fit framework approach [ 18 , 19 ] was used to analyse the data. Levesque’s Conceptual Framework for Healthcare Access [ 6 ] was used as the a priori framework to code how each study had measured access, applying the five stages of access as key concepts: perception of needs and desire for care, healthcare seeking, healthcare reaching, healthcare utilisation, and healthcare consequences. This framework offered a useful conceptualisation of access to healthcare as a multi-dimensional concept, and has not been used in this way in reviewing mental health service research.

A further framework was developed by combining equality characteristics in the NHS Long Term Plan [ 7 ], and the Cochrane Progress-Plus framework [ 15 ]: age, disability, education, gender and sex (including gender identity), occupation, place of residence, pregnancy/maternity, ethnicity, religion, sexual orientation, social capital, socioeconomic status, and other. This template was used as the a priori framework to identify which dimensions of inequality had been studied and to code key findings from the studies. Key findings for each dimension of the template framework were grouped together in the synthesis: differences in levels of access, differences in pathways to access, and barriers to accessing mental health services. For data related to barriers to access, the abilities of individuals to access healthcare according to Levesque’s framework [ 6 ], were used to code factors identified by studies that had influenced access: ability to perceive, ability to seek, ability to reach, ability to pay, ability to engage. Tables and figures have been used to characterise the evidence base identified. HL performed the data synthesis and the wider review team were consulted during the process to review and feedback on the presentation and interpretation of the results.

Stakeholder involvement

The proposed research questions were reviewed by a service user group and a public adviser from a marginalised group with lived experience of accessing mental health services. Their involvement led to the inclusion of a theoretical framework [ 6 ] as a lens to further understand how studies have measured access. Three co-authors (AB/CL/FL) have experience and expertise in delivering mental health services to adults experiencing mental health conditions. Finally, the authors received feedback on the review findings and their interpretation from experts-by-experience and domain-experts.

After the removal of duplicates, the search strategy identified a total of 1,929 citations. Based on screening titles and abstracts, 1,653 citations were excluded. A total of 276 full texts were assessed for eligibility, of which 138 papers were included in the review (Fig.  1 ). An additional 14 papers were also identified through citation checking.

Flow chart of the study selection process

Study characteristics

An overview of the study characteristics is presented in Table 3 , split by study type. The size of the literature on access to mental health services has grown gradually over time, seeing a larger increase in qualitative studies in more recent years. Over a third of studies were conducted in secondary care settings (e.g. community mental health teams, early intervention in psychosis services), and another third were conducted in other settings (e.g. population-based surveys, educational). The remaining studies were conducted across Improving Access to Psychological Therapies (IAPT) services, tertiary care (e.g. forensic services, veteran services), and primary care (e.g. GP) settings. Eighty percent of the studies were conducted in England, with fewer studies covering other nations in the UK (Wales ( n  = 6), Scotland ( n  = 4), Northern Ireland ( n  = 2), UK-wide ( n  = 24)). Of those conducted in England, nearly half of the studies were conducted in London ( n  = 50). Almost half of the studies used routinely collected patient data, 62 of which were quantitative. Only 25 studies reported any patient and public involvement, 15 of which were qualitative. Larger sample sizes were seen in quantitative studies.

Measures of access

The five stages of access in Levesque’s framework [ 6 ] were used to note how each study measured access to mental health services. The superscript numbers used in this section refer to the references used in Additional file 3 , which presents a table of included studies categorised by measure of access (Table S3).

Perception of needs and desire for care

Two studies 1−2 explored illness perceptions and help-seeking attitudes of population groups and their influence on accessing mental health services. One study 1 explored how illness attributions differed by ethnicity using a questionnaire, and another study 2 interviewed service users about their perceptions of eligibility for mental healthcare during the COVID-19 pandemic.

Healthcare seeking

Healthcare seeking as a measure of access was used by 48 studies 3−50 . These were most notably qualitative studies 3−8,13,17,18,20–22,24,26–44,46,47,49,50 which explored barriers to seeking mental healthcare from the perspectives of service users, carers, and professionals. Some quantitative studies which used routinely collected data 12,23 or self-report surveys 9−11,14–16,19,25,45,48 about being referred to mental health services were also included here as this suggested seeking mental healthcare but not necessarily reaching or utilising it. Most studies measuring healthcare seeking focused on a specific dimension of inequality, such as ethnicity 4−6,19,21,22,27,29,32,34–36,41,43,46,50 , and occupation 8,13,16,23,26,31,37,44,45,48,49 .

Healthcare reaching

Ten studies 51−60 ascertained from service users or professionals, using mainly interviews, the barriers to reaching mental healthcare. Four studies 52−54,57 were focused specifically on the dimension of disability and the availability and accommodation of mental health services (e.g. location, transport, mobility). Inadequate transitions from child and adolescent mental health services to adult mental health services were the focus of two studies 51,58 measuring healthcare reaching.

Healthcare utilisation

Ninety studies 61−150 measured healthcare utilisation, of which were mostly quantitative and observational. These studies either used routinely collected data or survey responses self-reporting use of mental health services to understand differences in rates of utilisation or receipt of care between population groups. Studies were predominantly conducted in secondary care or IAPT settings, most likely due to the routinely collected patient data that is available from these service providers. Twenty-eight 62,66,67,69,72–75,80,81,83,88,89,100,109,111,112,119,123,128,132,133,137,138,143,146,147 studies measuring healthcare utilisation did not focus on a specific dimension of inequality and were mainly exploratory by looking at the characteristics of those accessing services, whilst 20 studies 61,63,65,68,77,85,88,94,99,103,104,113,114,120–122,124,135,136,150 specifically focused on rates of utilisation by ethnicity.

Healthcare consequences

Two studies 151−152 explored the consequences of accessing inappropriate mental healthcare. One study 151 investigated the experiences of people with mental health conditions accessing remote mental healthcare during the COVID-19 pandemic, and another study 152 examined unmet psychological care needs of people living with HIV and associated health outcomes.

Research methods and theoretical frameworks

Quantitative studies ( n  = 92) were mostly observational using routinely collected patient data ( n  = 55), or surveys collecting quantitative data ( n  = 20), often using established scales (e.g. Barriers to Care, Stigma Scale), to examine differences between population groups. These studies had larger sample sizes and used sampling methods that were more representative, but were less likely to demonstrate evidence of patient and public involvement. Some quantitative studies combined minority groups due to small sample sizes (e.g. Black and minority ethnic, sexual minorities) assuming a shared experience. Descriptive statistics, statistical tests, such as Chi-square, and regression analyses were used to analyse differences between population groups. Qualitative studies ( n  = 45) were mainly interviews ( n  = 34) or focus groups ( n  = 7) conducted with service users, carers, or professionals about their experiences or perspectives on access to mental health services. Participants were recruited purposively, typically belonging to a particular minority group or professional role. Studies often used thematic analysis to synthesise the data, and were more likely to demonstrate evidence of patient and public involvement. Surveys collecting both quantitative and qualitative data were used in mixed methods studies ( n  = 10), but few studies referred to the integration of findings as would be seen in a typical mixed methods design. Only 17 studies discussed the application or production of a theoretical framework to understand access or inequality, and this was mostly frequently used to analyse qualitative data. Dixon-Woods’ Candidacy Framework [ 20 ], Andersen’s Model of Health Services Use [ 21 ], and Kleinman’s Healthcare Model [ 22 ], featured in multiple studies.

Key findings on inequalities in access

To understand inequalities, data was most frequently collected by studies for gender ( n  = 125), age ( n  = 117), and ethnicity ( n  = 114). Social capital ( n  = 6), religion ( n  = 12), and sexual orientation ( n  = 15) were the least frequently considered. Figure  2 presents the percentage of studies that collected data for each dimension of inequality by study type. 113 studies focused on a specific dimension of inequality, these tended to use qualitative methods. Whilst the remaining studies ( n  = 39) were more exploratory or studied multiple dimensions of inequality, these tended to be quantitative. Figure  3 presents the percentage of studies that focused on a specific dimension of inequality by study type. Some studies only included specific groups in their study population, such as ethnic minorities ( n  = 17), young people ( n  = 11), and women in the pre-natal or post-natal period ( n  = 6).

Percentage of studies that collected data for each dimension of inequality by study type

Main dimensions of inequality examined by the included studies by study type

The superscript numbers used in this section refer to the references used in Additional file 4 , which presents a table of the key findings on inequalities in access by dimension of inequality (Table S4).

Differences in levels of access to mental health services

Forty-one studies found no differences in access between age groups 1−6 , disabilities 4,26,52,53 , educational qualifications 13,39 , gender and sex 1,3,4,6,13–15,20,23,24,26,30,32,33,35,38,66–68 , employment status 13,35,75 , place of residence 6,12,18,33,35 , ethnicity 1−3,6,11,14,30,33,38,53,76,92,97–100 , religion 3 , social capital 11,12 , socioeconomic status 16,18,26,35,75,76,128,135 , or relationship status 6,13,23,35 . Referral rates to secondary mental health services were found to be higher for young people 14 , people with long-term conditions 15 , females 16 , and lower for homeless people 53 , and those living in more deprived areas 136,137 . Access measured by mental health service contacts, admissions, and caseloads, highlighted a mixed picture of differences in access by age group, educational qualification, gender and sex, employment status, sexual orientation, and deprivation. Consistent findings for studies measuring access in this way were higher access for females 16,26,27,44,62,63,69,70 , unemployed people 29,44,49,62,76,77,78 , and prisoners 60,70,73 , and lower access for homeless people 53 , and ethnic minorities 13,24,26,27,44,62,64,77,102–107 . Working age adults 11 , people with long-term conditions 11 , those with higher educational qualifications 11−12 , females 10,11,61 , unemployed people 11 , those living alone 12 , people with a sense of belonging and social support 10 , those on lower incomes 11 , and single people 11 , were more likely to report formal mental health help-seeking (e.g. from a mental health professional). Higher mental health service costs were associated with younger and older adults 7−9 , people with long-term conditions 7,8 , males 8 , those living alone 7 , ethnic minorities 7 , and those living in more deprived areas 7−8 . Risk of disengagement with mental health treatment was found in younger adults 30 , people with learning disabilities 52 , unemployed people 30 , homeless people 53 , ethnic minority males 75 , Muslim males 75 , sexual minority males 75 , and males living in more deprived areas 75 . Unmet mental health needs were reported for people with disabilities 54 , people living with HIV 55 , males 70,72 , ethnic minorities 24,64 , and prisoners 64,72 .

Differences in pathways to access mental health services

Referral sources and destinations were explored by some studies to understand pathways into care. For IAPT services, GP-referred patients were more likely to be younger 29 , male 29 , unemployed 29 and White 29 . There were little variation in IAPT access via self-referral routes. Black people 32,68,79,110–112 and males 68 had higher rates of criminal justice system involvement in their referral source to secondary mental health services. Despite presenting to primary care with psychological care needs, refugees and asylum seekers 145 , and migrants 62 were unlikely to be referred to mental health services. Compulsory mental health treatment (e.g. being subject to a Mental Health Act section) was more likely for unemployed people 81 , those living alone 81 or in supported accommodation 32 , ethnic minorities, particularly those from a Black ethnic background 34,79,81,105,110–113 , people from more deprived areas 34 , and single people 33 . Waiting times also differed amongst some groups with people from less deprived areas 6 , ethnic minorities 35 , and older people 28,31,35 waiting less time for treatment.

Barriers to accessing mental health services

Barriers to accessing mental health services were most frequently associated with individuals’ “ability to reach” services, followed by individuals’ “ability to seek” services. Experiences of or anticipating experiences of stigma and discrimination was a key barrier to seeking mental health services across 43 studies, for age 39−42,44 , disability 55,56,58 , education 44,65 , gender and sex 61,65,69 , occupation 44,69,83–91 , pregnancy/maternity 95,96 , ethnicity 44,65,96,97,109,114–117,119–124,126–131 , sexual orientation 44,63,67,134 , contact with criminal justice system 97 , and refugee and asylum seeker status 146 . The majority of studies referred to stigma and discrimination related to having a mental health condition and/or accessing mental health services. However, for studies which looked specifically at ethnicity or sexual orientation, this barrier was also sometimes discussed in terms of individuals’ previous experiences of or anticipating future experiences of stigma and discrimination based on their identity as an ethnic minority 44,114–115,119,124,126–127,129 or sexual minority 44,67,134 . Previous or anticipated experiences of racism or homophobia when accessing mental health services acted as barrier to seeking mental healthcare for these groups specifically. Thirty-two studies identified a key barrier to engaging with mental health services was the appropriateness of services to meet the needs of different population groups, for age 36,37,41 , disability 56,57 , gender and sex 71,74 , occupation 83,88,89 , place of residence 93 , pregnancy/maternity 94,95 , ethnicity 60,96,117,119,121,125,127,129,130,133 , sexual orientation 67,94,134 , socioeconomic status 141,143 , contact with criminal justice system 72,144 , trafficked people 147,149 , and street sex workers 148 . The availability of services was reported a barrier to reaching mental health services across 23 studies, for age 43,45,46 , disability 58,59 , occupation 83,85,87–89 , ethnicity 115,119,121,128,132,133 , socioeconomic status 141 , contact with criminal justice system 72,97,144 , refugees and asylum seekers 132 , trafficked people 147,149 , and street sex workers 148 . Difficulties in recognising mental health symptoms ( n  = 18) and trust in mental health professionals ( n  = 18) were barriers to perceiving mental health needs associated with age 39,49,43 , gender and sex 69,74 , occupation 69,83–90 , pregnancy/maternity 95 , ethnicity 114−120,122,124–128 , contact with criminal justice system 97 , and trafficked people 148 . No studies referred to barriers associated with individuals’ “ability to pay” for services, this is likely due to the provision of universal healthcare in the UK.

Routinely collected patient data

Sixty-nine studies used routinely collected patient data, such as referrals, contacts, attendances, and admissions to mental health services, to explore differential rates of access between population groups. This frequently involved comparing access according to the patient demographic data available (e.g. age, gender, ethnicity, deprivation), and using descriptive statistics, statistical tests, and regression modelling to make inferences about how groups differ in rates of access. A few studies also analysed data such as referral source, referral destination, whether a contact was attended, and whether admission was voluntary, to understand pathways to care as a measure of access. Other data sources such as the UK Census or Office for National Statistics (ONS) data were used by some studies to examine whether access rates were proportionate with population estimates. However, the Census or ONS data tended to be out of date compared with the mental health service data. Other studies linked mental health service data with other health data, such as primary care data or community health survey data, to understand “potential access” (e.g. self-reporting a mental health need in a community health survey, GP appointment for mental health condition) and “realised access” (e.g. contact with a mental health service). A large proportion of studies that analysed routinely collected patient data, had used the Clinical Record Interactive Search (CRIS) system at South London and Maudsley NHS Foundation Trust (SLaM), a large mental health service provider, or had extracted data from NHS Digital, such as the IAPT service evaluation database. Almost all of the studies that used routinely collected patient data were coded as “healthcare utilisation”, as it was a direct quantification of individuals using mental health services. All studies discussed the usefulness of analysing routinely collected patient data to understand differences in access to mental health services, but also reflected on the challenges it poses when being used for research purposes. Its accuracy and completeness, particularly in relation to demographic data such as ethnicity and sexual orientation, incompleteness of which can limit understanding of inequalities, was the main challenge noted by study authors ( n  = 22).

This systematic mapping review synthesised research on inequalities in access to adult mental health services in the UK, and the measures of access, research methods, and key findings of relevant studies. It was important to update previous review findings [ 11 ], following the COVID-19 pandemic [ 23 ] and recent changes to UK policies [ 7 , 8 , 9 ]. Although there was significant heterogeneity amongst studies, this review has provided a broad overview of the evidence base through categorising studies by their approach to measuring access, and the dimensions of inequality that have been studied.

Measures of access and research methods

Whilst this review found studies across the continuum of access as defined by Levesque’s framework [ 6 ], most were positioned in exploring healthcare utilisation. This is similar to findings from reviewing studies of other types of healthcare access [ 24 ]. Healthcare utilisation is determined by the need for care and whether healthcare can be accessed. However, this review found that accounting for differences in need was not routinely considered, and represents a deficiency in current ability to accurately understand inequalities in access to mental health services. This is a conclusion that was shared by Asthana et al. [ 11 ]. Levesque et al. [ 6 ] suggested that to understand the complexity of access, mixed methods research in different contexts is needed to ameliorate factors that influence access and develop strategies to improve access. This review has highlighted that there continues to be a paucity of theoretically informed evidence in this area, and studies tend to rely on a simple conceptualisation of access. Despite the valuable perspective that patients, carers, and the public can bring to research [ 25 ], their involvement was largely absent from this evidence base. There is a need to address challenges associated with involving patients, carers, and the public, and identify ways in which this can be reported effectively in the future [ 26 ].

Inequalities in access to adult mental health services in the UK

This review reiterates findings from the previous review [ 11 ], suggesting that the evidence base of variations in access to mental health services remains complex and somewhat contradictory. Despite the implementation of policy changes, this review has highlighted that inequalities in access may persist for some population groups, such as ethnic minorities and older people. Studies published since 2014 did not indicate a consistent pattern of differences in access, finding over-representation of groups in some contexts (e.g. ethnic minorities and males in compulsory mental health treatment) and less access in others (e.g. ethnic minorities and males in IAPT services). These mixed findings could reflect the differences in which these services are accessed and the stages at which they are accessed. For example, a lack of access to lower intensity therapies such as those delivered by IAPT services could be associated with later presentation to compulsory mental health treatment if mental health conditions have deteriorated. These mixed findings could also highlight the importance of intersectionality in the context of inequalities [ 27 ]. For example, Smyth et al. [ 28 ] explored males accessing IAPT services, and reported differential access within the study population across other dimensions, such as ethnicity and sexual orientation. Differences in access may be obscured if studies do not consider variation within population groups. Despite considering additional dimensions of inequality beyond the scope of Asthana et al. [ 11 ], this review found that studies continued to focus on differences based on age, gender, and ethnicity. This is likely due to the data available from healthcare services for these characteristics. The absence of evidence of inequalities across dimensions such as religion, sexual orientation, and social capital, does not indicate that inequalities do not exist; and highlights a poor understanding of the extent of inequalities in access to mental health services in the UK for these population groups.

Unlike the previous review [ 11 ], qualitative data was analysed to identify key barriers to accessing mental health services across dimensions of inequalities. These findings have added some context to the factors that may influence access to mental health services for different population groups. Stigma and discrimination, appropriateness of services, availability of services, difficulties associated with recognising mental health problems, and trust, were frequently cited by studies; all of which are reflected in the wider literature on barriers to healthcare access [ 29 , 30 , 31 ]. The Health Stigma and Discrimination framework [ 32 ] theorises the mechanisms through which mental health-related stigma and discrimination influence access to healthcare services and how individuals with intersecting stigma, such as minority groups, can lead to a double burden. Action to reduce inequalities should consider how to address the barriers identified. Stigma-reducing interventions may be effective for specific population groups (e.g. ethnic minorities, LGBTQ + groups), such as individual support to overcome internalised stigma, or community support to change harmful attitudes towards mental ill health [ 32 ]. Re-designing services and pathways, in collaboration with population groups experiencing inequalities [ 25 ], could improve the accessibility and appropriateness of mental healthcare to meet the needs of different groups. Mental health awareness campaigns and community outreach programmes, particularly targeted at groups who have difficulties in recognising mental health need and trusting mental health professionals (e.g. veterans, ethnic minorities, LGBTQ + groups), could remove barriers to seeking mental healthcare [ 31 ].

There are significant benefits to using routinely collected patient data to understand inequalities in access to mental health services. Primarily the data, particularly from secondary care services, has been used to examine differences in mental healthcare utilisation between population groups. Other studies had used data to identify variations in pathways into mental healthcare, or risk of disengaging from mental health treatment. Increases in the availability and accessibility of healthcare data have dramatically changed the landscape of population health research [ 33 ], presenting opportunities to conduct studies which require much less resource than primary data collection, and have real-world generalisability, often with large sample sizes [ 34 ]. There are challenges to overcome in using this data for research purposes, many of which study authors alluded to. Low quality or missingness of data on patient characteristics can influence our understanding of variations in access for population groups and limits what conclusions can be reached. As such, there may be hidden inequalities as a result of poor data collection and quality. Recent NHS Digital guidance [ 35 ] has set out to improve data quality for many of the dimensions of inequalities identified in this review, through enabling patient self-reporting, embedding inclusive ways of working and reducing staff assumptions, and sharing feedback on data quality. These planned improvements will enhance the use of this data to generate more reliable evidence of inequalities in access to mental health services and may clarify inconsistent findings.

Strengths and limitations of the review

This systematic mapping review was conducted in line with existing guidelines for reviews [ 13 ], applied a well-established framework in the analysis [ 6 ], and included stakeholder involvement. Comprehensive searches were undertaken across seven electronic databases and eligibility criteria was kept intentionally broad to ensure relevant studies were included. Grey literature was not considered for inclusion in this review as it has been summarised elsewhere [ 10 ]. Whilst this review aimed to identify studies primarily focused on examining access, evidence from studies where this was not the primary focus and inadvertently found inequalities in access may have been missed. As this review captured a breadth of evidence rather than a specific standard of evidence, issues associated with quality appraisal were not addressed. This may have led to an oversimplification of concepts and could limit conclusions about the reliability of findings. There may also have been a publication bias in that studies where no differences or inequalities were found may be less likely to have been published than those that did. This review was unable to draw on the influence of mental health conditions and sometimes the service due to poor description available in the studies; this is important to assess in future studies as access and inequalities are likely to differ based on the condition experienced and the service accessed. This review was limited to studies conducted with adult populations accessing mental health services in the UK; additional insight of other contexts and for children and young people may be beneficial. The majority of the studies identified were conducted in England, particularly London, and so there is a potential limitation to the review findings being generalisable to other regions in England and in the UK. Further exploration to understand inequalities in access to mental health services within these contexts is needed.

This systematic mapping review successfully applied an established framework to synthesise a large heterogenous body of research on inequalities in access to adult mental health services in the UK. The findings indicate that attempts to understand inequalities in access to mental health services require a much more holistic measurement of access than being used in current research. Little has changed in the nature and extent of inequalities, suggesting mental health services have not become more accessible as was planned in policy. Whilst using routinely collected data to measure mental healthcare utilisation provides a useful contribution to understanding inequalities, relying solely on quantifying if someone uses a mental health service does not present an opportunity to fully understand the complexities of access. Policy on addressing inequalities in access to mental health services could be better informed by mixed methods research which attempts to contextualise access in a holistic way, such as considering mental health need, help-seeking behaviour, and healthcare utilisation.

Availability of data and materials

All data generated or analysed as part of this review are included in this publication and its supplementary information files.

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Acknowledgements

The authors would like to thank members of the ARC NWC Public Adviser Forum and the Lancashire and South Cumbria NHS Foundation Trust Service User Research Group, for their feedback on the review, and Louise Speakman, Faculty Librarian for Health and Medicine at Lancaster University, for support in refining the search strategy.

This research was funded by the National Institute for Health and Care Research (NIHR) Applied Research Collaboration North West Coast (ARC NWC). The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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Additional file 1: table s1..

Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist.

Additional file 2: Table S2.

Search strategies.

Additional file 3: Table S3.

Summary of included studies.

Additional file 4: 

Table S4. Summary of key findings associated with dimensions of inequality

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Lowther-Payne, H.J., Ushakova, A., Beckwith, A. et al. Understanding inequalities in access to adult mental health services in the UK: a systematic mapping review. BMC Health Serv Res 23 , 1042 (2023). https://doi.org/10.1186/s12913-023-10030-8

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Header menu - drawer | united kingdom, tackling social inequalities to reduce mental health problems.

We all have mental health and we all can experience mental health problems, whatever our background or walk of life. But the risks of mental ill-health are not equally distributed.

The likelihood of our developing a mental health problem is influenced by our biological makeup, and by the circumstances in which we are born, grow, live and age. Those who face the greatest disadvantages in life also face the greatest risks to their mental health. This unequal distribution of risk to our mental health is what we call mental health inequalities.

This report describes the extent of inequalities that contribute to poor mental health in the UK today. It explains how certain circumstances interact with our individual risk and discusses communities that are facing vulnerabilities. It makes a clearly evidenced case for why addressing inequalities can help to reduce the prevalence of mental health problems and makes a strong call for cross-sectoral action on mental health. The report concludes with proposed actions to address mental health inequalities.

For centuries, mental ill-health has been overlooked, misunderstood, stigmatised and, for a long time, inappropriately treated. Much of this is now changing, although misunderstanding and stigma are not yet things of the past. As a society, we have some way to go before the extent of mental health problems and their damage to our individual and collective wellbeing is fully recognised and comprehensively responded to. Reducing mental health problems and their effects warrants the most urgent and committed public health effort of our generation. As this paper will show, addressing social, economic, cultural and environmental inequalities will take us a long way towards achieving this goal.

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Health matters: reducing health inequalities in mental illness

Published 18 December 2018

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People with severe and enduring mental illness are at greater risk of poor physical health and reduced life expectancy compared to the general population.

This edition of Health matters sets out the scale of the problem and presents actions that local areas can take to reduce health inequalities, improve physical health and life chances of people living with mental illness.

Although the focus is on adults with more severe and enduring mental illness, many of the actions will be of benefit to all people experiencing mental illness.

Scale of the problem

Mental health problems can affect anyone and have a significant effect on the lives of individuals, their families, communities and wider society. Together with substance misuse, mental illness accounts for 21.3% of the total morbidity burden in England.

One in six of adults have had a common mental health disorder, such as anxiety, in the last week, according to survey data. Three quarters of mental health problems are established by the age of 24. Recent data indicates that there are close to 551,000 people in England with more severe mental illness ( SMI ) such as schizophrenia or bipolar disorder. This is likely to be an underestimate as figures only include those who are diagnosed and recorded on GP registers.

Mental illness is closely associated with many forms of inequalities. Health inequalities are avoidable and unfair differences in health status and determinants between groups of people due to demographic, socioeconomic, geographical and other factors.

These differences can be in relation to prevalence, access to, experience and quality of care and support, as well as opportunities and outcomes. Health inequalities can mean reduced quality of life, poorer health outcomes and early death for many people.

People living with SMI experience some of the worst inequalities, with a life expectancy of up to 20 years less than the general population. This is the same life expectancy that the general population experienced in the 1950s, and evidence suggests that the mortality gap is widening.

Economic cost to society

Poor mental health is estimated to carry an economic and social cost of £105 billion a year in England. This includes indirect costs of lost employment, as well as direct costs relating to health and care provision and the human costs of reduced quality of life.

The long-term costs of perinatal depression, anxiety and psychosis collectively are estimated to be around £8.1 billion for the total number of babies born in a year. Most of this cost relates to adverse impacts on the child rather than the mother.

Inequalities experienced by people with mental illness

What drives inequalities in health.

Inequalities in health are largely due to inequalities in society, meaning the conditions in which people are born, grow, live, work and age. It is the unequal distribution of the social determinants of health, such as education, housing and employment, which drives inequalities in physical and mental health, although the mechanisms by which this happens can be complex and inter-related.

Psychosocial pathways

Disadvantage can start even before a child is born, and can accumulate over time and impact on future generations.

Factors include:

• adverse childhood events such as being a victim of abuse
• poor housing
• traumatic events
• poor working conditions

Children facing multiple risks have a heightened risk of multiple and sustained childhood mental health difficulties.

Protective factors such as social support and good quality of work and employment conditions can help buffer the impact of adverse conditions on poor health.

Social inequalities

People with mental illness are more likely to have higher rates of:

• homelessness
• incarceration
• social isolation
• unemployment

As an example, psychosis is up to 15 times higher among people who are homeless compared to the general population.

Levels of psychotic disorders are 9 times higher in people in the lowest fifth (quintile) of household income compared to the highest.

People with severe mental illness are also more likely to live in less safe neighbourhoods, have less access to healthy foods and fewer opportunities to be involved in healthy activities.

Stable, good quality and rewarding employment is protective for health and can be a vital element of recovery from mental health problems. Yet challenges remain for people with mental health problems in gaining and maintaining employment; sometimes because of negative attitudes and stigma. They are also often over-represented in low-pay and temporary work.

Many people want to work but are not always offered opportunities to do so or the most effective help when they do ask for it. The 2018 National Clinical Audit of Psychosis identified that less than half (46%) of patients who were unemployed and seeking work were receiving some form of support towards this goal.

Improving lives: the future of work, health and disability sets out the government’s plans to transform employment prospects for disabled people and those with long-term health conditions over the next 10 years. This includes an NHS England ambition to double national access to Individual Placement and Support ( IPS ) services by 2020 to 2021, allowing more people who experience SMI to find and retain employment.

Stable and appropriate housing is another important part of the recovery pathway and can reduce the need for inpatient care. People with mental health problems can experience significant barriers to accessing appropriate accommodation including stigma, discrimination, poverty as well as limited supply. Just over half (54%) of working-age adults in contact with secondary mental health services on the Care Programme Approach are living independently, with or without support.

Citizens Advice report that a growing number of people with mental health problems are turning to them for advice for social issues and that their needs tend to be more complex and urgent.

The main advice areas include finances and debt, essential services, housing, employment and the welfare system.

Having a practical problem can impact on a person’s ability to manage their health and lead to worsening mental health. The report calls for essential service providers, local authorities, landlords and employers to do more to support people with mental health problems effectively.

Physical health inequalities

Compared to the general population, people with mental illness experience a greater burden of physical health conditions. It is estimated that for people with SMI , 2 in 3 deaths are due to physical illnesses such as cardiovascular disease ( CVD ) and can be prevented.

This increased burden of physical health problems affects all ages. Recent analysis by PHE found that younger adults with SMI are 5 times more likely to have 3 or more physical health conditions compared to younger adults overall.

Those living in more deprived areas are likely to have a higher prevalence of physical health conditions.

Excess premature mortality rates are more than 3 times higher amongst people with mental illness in England compared to the general population.

Although CVD accounts for the majority of premature deaths among people with SMI , health disparities are greatest for liver disease and respiratory disease and there has been little improvement over time.

The reasons for this increased burden of physical ill-health and reduced life expectancy are due to complex and interrelated factors.

These include:

• wider social factors such as unemployment and poverty
• increased behaviours that pose a risk to health such as smoking and poor diet
• lack of support to access care and support
• effects of medication which include weight gain
• stigma, discrimination, isolation and exclusion preventing people from seeking help
• diagnostic overshadowing, which is the misattribution of physical health symptoms to part of an existing mental health diagnosis, rather than a genuine physical health problem requiring treatment

Suicide is also a significant cause of death amongst people with mental illness. The 2018 National Confidential Inquiry reports that 28% of all suicides were in people who had contact with mental health services in the 12 months prior to death.

Older people may experience inequalities in access to care and treatment. A report from the Royal College of Psychiatrists highlights that older people who self-harm or have depression are much less likely to be referred to specialist mental health services than younger adults.

Perinatal mental illness can have a significant and long lasting effect on women, their babies and families if not identified early enough and managed effectively. Some groups may be more vulnerable to perinatal mental health problems such as women with a pre-existing psychiatric diagnosis. The Confidential Enquiry into Maternal Deaths and Morbidity shows that suicide remains one of the leading causes of maternal mortality in the UK.

People from minority ethnic backgrounds experience further disadvantage. For example, black people are more likely to be detained under the Mental Health Act, and have lower rates of recovery.

Black people with SMI are more likely than other groups to come into contact with secondary care services through non-health agencies, in particular, the police. Adverse experiences of hospital mental health services among minority ethnic groups continue to be a cause of concern. These issues can lead to a mistrust of services and delays in seeking care.

The commitments being taken forward by national organisations in response to the Five Year Forward View for Mental Health ( FYFVMH ) are underpinned by a need to achieve equality in mental health, particularly for BAME groups.

Behavioural health risk factors

People living with mental illness also have higher rates of health risk factors. Wider social factors and stressors can impact people’s psychological wellbeing and their health behaviours. These connections are complex but many health behaviours are perceived as immediate coping and survival mechanisms despite their impact being damaging to health.

Smoking remains the largest single cause of preventable death in England. Whilst smoking prevalence in the general population is at an all-time low at 14.9%, amongst people with SMI registered with a GP , it is almost 3 times that at 40.5%.

The Tobacco Control Plan for England recognises the need for urgent action in inpatient and community mental health settings to reduce the stark difference in smoking rates, and ensure people with a mental health condition are not left behind as we move towards a smokefree generation.

Alcohol and drug misuse are also very common among people with mental illness, and vice versa. Research shows that mental health problems are experienced by the majority of drug (75%) and alcohol (85%) users in community substance misuse services.

Death by suicide is also a major risk, with a history of alcohol or drug use being recorded in 54% of all suicides in people experiencing mental health problems in England.

Preventative care and support

People with SMI experience more risks to remaining well but are not always offered timely and appropriate health assessments for early detection of physical health problems. They may be less likely to receive preventative care or health promotion interventions.

The National Clinical Audit of Psychosis 2018 found that physical health monitoring is gradually improving, with 42% of patients having 5 major physical health risk factors monitored annually compared to 27% 6 years ago in the first audit.

National screening programmes save lives, improve health and enable choice.

However screening services are not always as accessible as they should be, and groups such as those with mental health problems face significant barriers in making an informed personal choice about screening and accessing services. These barriers include:

• lack of registration with a GP
• lack of knowledge and confidence about screening amongst health staff in some health care settings

PHE ’s screening inequalities strategy sets out the case for change and identifies key actions that PHE will take to support the health system to reduce inequalities in national screening programmes.

Amongst these actions is a commitment to better understand and support the system to address the barriers faced by people with severe mental illness, for example, by putting in place mechanisms to ensure that people receiving long term hospital care, with or without a GP , receive an invitation for screening.

Screening providers need to be aware of all local mental healthcare settings in their catchment area and work collaboratively to make sure all eligible patients are supported to make an informed decision about screening, for example through the provision of appropriate and accessible information materials.

NHS England guidance, Improving physical healthcare for people living with severe mental illness in primary care sets out what good quality physical healthcare provision in primary care must include. A Kings Fund report Bringing together physical and mental health sets out what an integrated approach to physical and mental health would look like for people with mental illness.

People in contact with the criminal justice system living with mental illness

People in contact with criminal justice are more likely to experience mental ill-health than people in the general population. These mental health needs are often compounded by coexisting social disadvantage, such as substance misuse, poor physical health, homelessness or insecure accommodation, offending behaviour, unemployment, persistent poverty and debt.

Prevalence of self-inflicted deaths and self-harm in prisons remain higher than in the general population. In 2017, the likelihood of self-inflicted death in prisons was 5.1 times greater than the risk in the community. Current research shows that effective strategies should focus on 2 main interventions: targeted individual support and population or environmental approaches such as improving the safety of the prison environment and linking to wider community programmes post release.

However, this population is often described as being ‘underserved’, with services provided that are not appropriate or accessible to this population. This can be due to personal and structural barriers such as stigma, low levels of help seeking behaviour, complex commissioning arrangements leading to fragmented pathways as well as challenging personal and social circumstances.

This can restrict the opportunities for early detection, monitoring and treatment of health and social problems resulting in the health needs of this population going unmet and often escalating levels of conflict with law enforcement.

Local actions to reduce inequalities in mental illness

Good health and wellbeing demands a broader focus than just health care services. Prevention is better than cure sets out the government’s plans to rebalance healthcare with greater emphasis on prevention. Creating the right conditions for good health and wellbeing will require taking a whole person approach, addressing the root causes of poor health amongst people with mental illness, and empowering people to make informed choices. This will need system wide action at both a local and national level with targeted action for those most at risk.

This section highlights a range of preventative actions that local areas can take to reduce inequalities and improve health outcomes and the lives of people with mental illness.

Examples of PHE tools and resources that can support are also highlighted.

1. Understand local population need

Understanding the mental health needs of the local population is vital for good service planning and commissioning. All local areas should have a mental health and wellbeing Joint Strategic Needs Assessment ( JSNA ) in place to build a picture of local needs, including an understanding of variations in prevalence, risk and protective factors for people with or at risk of mental illness and amongst different populations, for example BAME .

PHE provides a range of data tools and resources to support the JSNA development process and inform local decision making:

• PHE ’s Mental Health and Wellbeing JSNA knowledge guide provides an overview of the areas to consider when thinking about the mental health needs in a local area, with a focus on understanding place factors and population groups across the life course. This is accompanied by a Mental Health and Wellbeing JSNA data profile and updated PHE ’s Health profiles for England . A report on key features of a good Mental Health JSNA is also available.

• PHE Fingertips Mental Health Profiles support local areas to focus on specific themes, such as severe mental illness and co-occurring substance misuse and mental health . Data can be filtered at different levels such as by local authority and sustainability and transformation partnerships ( STPs ).
• PHE Alcohol, drugs and tobacco: commissioning support pack has been developed to help commissioners and local authorities develop joint strategic needs assessment and health and wellbeing strategies to reduce the harm caused by smoking, drinking, substance use and misuse in both adults and children.
• The Prevention concordat for better mental health is helping galvanise adoption of effective place based arrangements to promote good mental health and prevent onset, development and deterioration of mental health problems. PHE has produced resources to support prevention focused planning and leadership, secure cross sector action, and deliver an increase in health equity.
• Guidance on local suicide prevention planning is available. There is also a PHE Fingertips suicide prevention profile to support local areas to ensure prevention plans are based on local need.The National Confidential Inquiry into Suicide and Safety in Mental Health have published a self-assessment toolkit for mental health services and primary care to help reduce suicide rates and improve safety for all mental health patients.
• PHE ’s report on understanding and reducing ethnic inequalities provides material on ethnicity and health for use in local JSNAs and local health and wellbeing strategies.

In addition, local areas should explore and analyse their own service level data to identify and reduce health inequalities, where local agreements for access exist.

2. Address the social determinants of poor health

Addressing social factors and improving the conditions in which people live and work can help reduce the stressors faced by the population, improve physical and mental health and reduce health inequalities. Efforts to improve outcomes should include action to reach and support specific groups who face particular disadvantage and exclusion. Commissioners and providers should collaborate and work with their system partners and people with lived experience to address social factors and reduce inequalities.

Local areas can use the ‘understanding place’ section of the PHE JSNA toolkit to help understand the social and contextual factors that impact mental health in their local area and to inform interventions to improve health. A Wider Determinants of Health Profile is also available. Emphasis should be placed on enhancing the protective factors for health and factors that promote health alongside reducing risk factors.

Interventions to improve employment opportunities and employment retention of people with mental illness are likely to contribute towards reducing health inequalities. PHE has produced local data packs on work, worklessness and health for each county and unitary authority in England. The pack includes data on the mental health employment gap for each local area and further information to inform local conversations and action.

Examples of local interventions can be found in the PHE and the Institute of Health Equity’s evidence review on increasing employment opportunities and improving workplace health . They include using a regional trainer approach to accelerate implementation of IPS across mental health services. In line with this, NHS England and the Joint Work and Health Unit have jointly funded a national support programme, designed to drive consistent delivery of high-quality IPS services among existing and new services within secondary mental health care.

Case study: Mental health: improving employment and health outcomes

Further PHE resources are available to help local areas make plans to reduce health inequalities and improve health and wellbeing through the places people live such as creating healthy communities and neighbourhoods, preventing homelessness and improving access to green spaces.

Increasing the use of good quality green space for all social groups is likely to improve mental health outcomes and reduce health inequalities, as well as bring other benefits such as greater community cohesion and less social isolation. Research shows there is a positive association between living near green space and higher levels of physical activity.

3. Build stronger communities and social connections

Addressing loneliness, social isolation, building a sense of belonging and participation in a local area and creating good social networks and social support are important outcomes for reducing inequalities in mental illness.

Community-centred approaches can also be an effective way of engaging marginalised groups and vulnerable individuals, therefore helping to reduce health inequalities within a local area. These types of approaches are about mobilising the assets within communities, fostering social connectedness, community resilience, promoting equity and increasing people’s control over their health and lives.

Local areas should consider how community-centred approaches that build on individual and community assets can become an essential part of local mental health plans and strategies.This should include co-production and involving those experiencing or at risk of mental illness in designing and delivering solutions that address inequalities in health.

The Health Matters edition on community assets gives more information on the important roles for NHS, local government and their partners in commissioning and delivering community-centred mental health approaches. E-learning modules are available to support implementation of the guide

4. Early detection and intervention for physical health risks

The FYFVMH emphasises the need to better meet the physical health needs of people with mental illness. This includes ensuring access to prevention and screening programmes and early recognition of health risks and appropriate intervention.

Equally Well UK is a new initiative, led by Centre for Mental Health, which seeks to promote and support collaborative action to improve physical health among people with a mental illness and reduce inequalities and offers a range of useful resources.

Physical health checks for people with severe mental illness

Via the FYFVMH , NHS England has committed to ensuring that by 2020 to 2021, at least 280,000 people living with SMI have their physical health needs met. Commissioning guidance for CCGs has been published to support this, and includes ensuring that people receive the full list of recommended physical health assessments as part of a routine check at least annually. The Improving physical healthcare to reduce premature mortality in people with serious mental illness CQUIN 2017 to 2019 provides a financial incentive to drive further integration to improve physical health care for people with SMI and also includes a focus on interoperability between primary and secondary care.

The NHS Health Check is a national programme offering a health check-up for adults in England aged 40 to 74. The programme features 3 components: risk assessment, risk awareness and risk management. The NHS Health Check is designed to help prevent and detect early signs of heart disease, kidney disease, Type 2 diabetes and dementia, although its impact is likely to benefit a number of non-communicable diseases, given a number of shared risk factors. To maximise the impact of the NHS Health Check programme and to ensure it is contributing to reducing health inequalities and increasing healthy life expectancy, local areas need to ensure not only equity of access, but also equity of outcomes from checks. The NHS Health Check Programme Health Equity Audit (HEA) guidance, produced collaboratively by PHE and local authorities, can be used to help identify the extent of inequalities in access, uptake and outcomes between different groups and areas, including those with mental health problems, and inform where to focus efforts.

The recommended physical health assessment for people with SMI aligns to the NHS Health Check but is more comprehensive. It is offered annually, to all ages and includes additional checks, personalised care planning and psychosocial support. Local areas may want to consider streamlining the delivery arrangements for the two processes where possible for those eligible.

Routinely screen and intervene for smoking and harmful alcohol use

Implementing the national Preventing Ill Health by Risky Behaviours – Alcohol and Tobacco CQUIN has the potential to reduce the risk of a physical health conditions such as heart disease as well as reduce future hospital admissions. Tools to support implementation include an e-Learning module for smoking and alcohol interventions guidance page and Knowledge Hub to share learning.

Data from the CQUIN ’s first year of operation shows some improvements in the proportion of patients with mental health problems who are being routinely screened and offered support for these health risks but there is wide variation across Mental Health Trusts.

Case study: South London and Maudsley NHS Foundation Trust refocus on alcohol screening and interventions

Smoking cessation

People with a mental health condition are just as likely to want to stop smoking as other smokers and must be offered the support they need to quit. PHE ’s Health Matters: Stop smoking – what works? presents the range of smoking quitting routes that are available and the evidence for their effectiveness. Guidance for conversations with patients and for frontline staff in mental health settings on how to deliver Very Brief Advice ( VBA ) to patients who smoke are also available.

Further resources for commissioners and providers to help people to stop smoking and to support implementation of NICE smoking and mental health guidance PH48 and PH45, include:

• Smoking cessation implementation guidance
• Good Practice for mental health services
• Guidance on using the mental health deep dive self-assessment tool on NICE smokefree compliance as well as local case studies

Case study: Smoke-free implementation in the Sheffield NHS trust

Make every contact count

All staff should Make every contact count and use every opportunity to have brief conversations with patients about making positive changes to their health and wellbeing.

Practical resources are available to support local implementation. The Prescribing Movement toolkit provides a range of information to support 1 minute, 5 minute and even more minute conversations on physical activity for people with different conditions including depression.

‘If a contact is to truly count, the focus should be on the individual and their needs. This may involve lifestyle areas …. It may also involve ensuring individuals can access services to support the wider determinants of health, such as housing or financial support, which may be barriers to making a healthy lifestyle choice.’ NHS England.

Optimal preconception, pregnancy and postnatal care

Whilst significant improvements have been made, continued action is needed to ensure optimal preconception and contraception support for women to improve health outcomes, as outlined in the NHS England perinatal mental health pathway . Targeted action is needed to support the needs of more vulnerable groups such as women with SMI .

The PHE JSNA toolkit provides an overview of perinatal mental health issues with examples of useful resources and information.

Additional resources include early years high impact areas which includes maternal mental health and PHE preconception care resource to support coordinated, collaborative service provision within local maternity systems, across primary care and broader health and prevention services.

The charity Tommy’s has a digital preconception tool which gives women information on achieving a healthy pregnancy including their mental health.

System wide action to meet the health needs of people in contact with the criminal justice system

PHE has co-produced the publication Rebalancing Act for Directors of Public Health, Police and Crime Commissioners ( PCC ) and other system leaders. It provides national evidence on the needs of people in contact with the criminal justice system. Its aims are to stimulate conversations and action between local health, social care, criminal justice and other partners, to address the health inequalities experienced by people in contact with criminal justice and reduce offending behaviour. It also provides a reference for developing local needs assessments as part of the JSNA . PHE has also published a Health Needs Assessment template which provides a description of a standard report for an adult (18 years and over) prison health needs assessment ( HNA ) which are commissioned by NHSE every 3 years or when a new service provider is commissioned. A specific guide on older people in prison has also been published.

5. No wrong door: support available through every contact point

5.1 Improved access to services for people with co-occurring conditions

Despite the increased risk, evidence from Care Quality Commission ( CQC ) service user and provider surveys suggests that people with co-occurring conditions are often unable to access the care that they need from both mental health services and addiction services, and are often excluded from both services.

Providers in alcohol and drug, mental health and other services should aim to have an open door policy for individuals with co-occurring conditions, and make every contact count. Meeting the needs of those with co-occurring conditions needs to become recognised as everyone’s job and treatment for co-occurring conditions should be available through every contact point.

Better care for people with co-occurring mental health and alcohol and drug use conditions sets out how commissioners and providers can and should work together to improve access to services which can reduce harm, improve health and enhance recovery, so that services respond effectively and flexibly to presenting needs and prevent exclusion.

This guidance highlights the importance of joint commissioning across mental health and alcohol and drug services, integrated and coordinated care for individuals with co-occurring conditions and access to recovery support and wrap around services. It points out the need for crisis mental health care to be available round the clock and to be responsive to the needs of those with co-occurring conditions, including when people are intoxicated when they present to services.

5.2 Drug related deaths

PHE is working with drug treatment providers to support improvements in their identification of, and clinical responses to, those most at risk of a drug related death. It is also working to encourage local authorities and their commissioned services to expand the availability of naloxone, the ‘antidote’ to heroin overdose.

With the publication of drug death figures for 2017 , we may now be seeing the first signs that this work is helping to reverse the upward trend in drug misuse deaths, but the numbers are still too high. This was the first decrease in drug misuse deaths in England since 2012 and follows annual increases totalling 60% from 2012 to 2016. PHE is updating 2011 guidance on local drug death review processes and helping local areas to audit their understanding of, and responses to, drug and alcohol deaths.

6. Build a confident, competent and committed public mental health workforce

Local partners responsible for leadership and workforce development should incorporate within their workforce development plans the 6 ambitions from the PHE Public mental health leadership and workforce development framework within their workforce development plans and take action on the priorities.This includes supporting the development of a workforce that is confident, competent and committed to improving the quality of life and healthy life expectancy of people living with mental illness and tackling inequalities.

Primary care staff and others working in non-mental health roles need to be able to meet the needs of people with a mental illness and ensure equitable access to services. Skills for Health, Health Education England, and Skills for Care have produced the Mental Health Core Skills Education and Training Framework for the general workforce who come into contact with people with mental illness.

Physical health and prevention should also be within the skill set of mental health service professionals so they can identify and meet physical health needs and have seamless referral pathways to other services. Training mental health staff in Making Every Contact Count will give them the confidence to have brief conversations with patients about how to improve their overall health and wellbeing.

Every local authority is encouraged to have an elected member mental health champion as part of their leadership responsibilities.

Additional information resources for health care professionals include:

• Improve the physical health of people with mental health problems: Actions for mental Health Nurses . This sets out actions in 8 key areas that are associated with particular risk factors for physical ill-health.
• PHE All our Health: mental health and wellbeing is part of a series of resources to help all healthcare professionals prevent illness, protect health and promote wellbeing
• The Charlie Waller Memorial Trust provides train the trainer programmes in mental health and wellbeing for practice and community nurses.

Read the PHE public mental health collection

Download supporting references .

Download the Health matters infographics

Read the Health matters blog .

Read case study: Mental health: improving employment and health outcomes

Read case study: Smoke-free implementation in the Sheffield NHS trust

Read case study: South London and Maudsley NHS Foundation Trust refocus on alcohol screening and interventions

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2 Social inequalities and mental health

• Published: September 2018
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This chapter discusses evidence linking social inequalities, across social, economic, and environmental dimensions to inequalities in mental health. A framework for thinking about the lifetime causes of inequalities in mental health is presented and used to discuss how experiences and conditions affect mental health across the life course. The chapter focuses particularly on factors that affect child development because of the importance of child developmental outcomes for future mental and physical health, and on life chances. Finally, the need for more attention to be focused on addressing the causes of social inequalities in mental health through multiple types of policies and interventions is discussed.

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• Systematic review
• Open access
• Published: 06 December 2018

How do macro-level structural determinants affect inequalities in mental health? – a systematic review of the literature

• A. McAllister   ORCID: orcid.org/0000-0003-1857-8882 1 ,
• S. Fritzell 1 , 2 ,
• M. Almroth 1 ,
• L. Harber-Aschan 1 ,
• S. Larsson 1 &
• B. Burström 1  

International Journal for Equity in Health volume  17 , Article number:  180 ( 2018 ) Cite this article

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In Europe and elsewhere there is rising concern about inequality in health and increased prevalence of mental ill-health. Structural determinants such as welfare state arrangements may impact on levels of mental health and social inequalities. This systematic review aims to assess the current evidence on whether structural determinants are associated with inequalities in mental health outcomes.

We conducted a systematic review of quantitative studies published between 1996 and 2017 based on search results from the following databases Medline, Embase, PsychInfo, Web of Science, Sociological Abstracts and Eric. Studies were included if they focused on inequalities (measured by socio-economic position and gender), structural determinants (i.e. public policies affecting the whole population) and showed a change or comparison in mental health status in one (or more) of the Organisation for Economic Cooperation and Development (OECD) countries. All studies were assessed for inclusion and study quality by two independent reviewers. Data were extracted and synthesised using narrative analysis.

Twenty-one articles (17 studies) met the inclusion criteria. Studies were heterogeneous with regards to methodology, mental health outcomes and policy settings. More comprehensive and gender inclusive welfare states (e.g. Nordic welfare states) had better mental health outcomes, especially for women, and less gender-related inequality. Nordic welfare regimes may also decrease inequalities between lone and couple mothers. A strong welfare state does not buffer against socio-economic inequalities in mental health outcomes. Austerity measures tended to worsen mental health and increase inequalities. Area-based initiatives and educational policy are understudied.

Although the literature on structural determinants and inequalities in mental health is limited, our review shows some evidence supporting the causal effects of structural determinants on mental health inequalities. The lack of evidence should not be interpreted as lack of effect. Future studies should apply innovative methods to overcome the inherent methodological challenges in this area, as structural determinants potentially affect both levels of mental health and social inequalities.

Introduction

The burden and prevalence of mental ill-health and mental illnesses are increasing [ 1 ]. Research shows that there are many explanations for this such as better awareness and diagnosis, environmental factors, structural factors and changes in public policy [ 2 ]. In this review, we focus on the structural, defining structural determinants as public policies affecting the whole population [ 3 ], we propose six main domains of welfare states, family policy, employment policy, income support and social insurance policy, area-based initiatives and education policy (see further explanation below). The Swedish Government commissioned The Public Health Agency of Sweden to increase the knowledge on mental health inequalities and their underlying determinants, this study is part of this larger project. Against this background, the main focus of the review was on studies of structural determinants and policies in Western welfare states. We define mental health broadly including positive mental health, mental ill-health and diagnoses of mental illnesses. Overall, we aim to investigate whether structural determinants are associated with mental health outcomes and if these determinants differentially impact on mental health outcomes by socio-economic status (SES) and gender.

The following provides a further explanation of inequalities in mental health and structural determinants of mental health.

What are inequalities in mental health?

The burden of mental illness is not equally distributed in the population. Epidemiological evidence consistently demonstrates an inverse association between SES and psychiatric morbidity, such that more disadvantaged groups are affected by mental illness to a greater extent [ 4 ]. Also, demographic factors such as gender and ethnicity (although not in themselves modifiable) may further modify the risk of mental disorder, depending in turn on how wealth, power and resources are distributed by gender and ethnicity (see for example [ 5 , 6 ]). This further suggests that distributions of mental illness are systematically shaped by social, economic as well as physical environments throughout the life-course [ 7 ], putting more disadvantaged population sub-groups at greater risk for mental illnesses through exposure to unfavourable social and economic circumstances.

How are structural determinants related to mental health?

We propose that structural determinants affect the distribution of resources and have the potential to influence mental health inequalities. Previous research shows that welfare state arrangements, social and economic policy may influence the distribution of health between social groups [ 3 , 8 , 9 , 10 , 11 , 12 ]. We used this literature to deconstruct structural determinants into six public policy domains: welfare states, family policy, employment policy, income support and social insurance policy, area-based initiatives and education policy (see Table  1 ). Borrell , et al. [ 3 ] suggest that such policy domains are drivers of the social structure and power relations that ultimately generate social inequalities in health. We suggest that these policy domains may mitigate or reduce the risk of poor mental health that provides the conditions for everyday life and influence the opportunities available to people across the life course. We also acknowledge the importance of healthcare policies in shaping access to services, and that these are likely to contribute to mental health inequalities. However, we do not asses these in this review as we conceptualise these as downstream factors influencing the treatment of mental illnesses, as opposed to broader structural determinants of mental illness.

We included all welfare typologies in our review. We propose, that regardless of the typology, examining welfare regimes provides insight into the values and norms that influence structural determinants. To illustrate, we use Korpi’s [ 13 ] family model regime typology. The dual-earner/carer models (e.g. Denmark, Sweden, Norway, Finland) are characterised by providing universalistic public policies to encourage labour force participation and gender equality. In contrast, the market-oriented model (e.g. Australia, the United Kingdom and the United States) provides limited social protection mostly towards those considered ‘deserving’ through means-tested benefits. In this welfare regime, the market, rather than public policy determines gender roles. In traditional family models, (e.g. Belgium, the Netherlands, Spain), policies are organised around the family with men often viewed as the ‘breadwinner’. Unpaid labour is seen as a responsibility of the family rather than the state which leads to low support for female labour force participation.

While social determinants of mental illness have long been recognised [ 7 , 14 ], only recently have they received more attention, especially in the wake of the recent economic crisis [ 15 ]. However, most empirical research focuses on proximal, “down-stream” determinants and few focus on broader, “upstream”, what we define as structural determinants and how these might affect social distributions of mental illness. To the best of our knowledge, no systematic review of the literature exists on structural determinants and their impact on mental health outcomes. We specifically sought to answer the following:

Which structural determinants (i.e. public policies) are associated with inequalities in mental health outcomes?

In what context have these policies been implemented?

What social differentials (across socio-economic groups and between men and women) exist regarding mental health outcomes?

This review was structured in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [ 16 ], with additional focus on equity using the PRISMA-E 2012 [ 17 ].

Information sources and search strategy

We searched for eligible articles in the following databases: Medline (Ovid), Embase ( Embase.com ), PsycINFO (Ovid), Web of Science, Sociological Abstracts (ProQuest) and ERIC (ProQuest). The Karolinska Institutet Library completed the initial search on 16 March 2017 and an updated search on 7 November 2017.

We also reviewed publications of recognised experts in this area as well as other relevant studies and projects such as Evaluating the Impact of Structural Policies on Health Inequalities (SOPHIE) [ 18 ]. Two reviewers also screened the bibliographies of all relevant reviews. See Additional file 1 for a detailed search strategy. Ethical approval was not required as results are based on previously published papers.

Eligibility criteria

Articles were considered eligible if they were (1) Original, peer-reviewed, written in English and published between 1996 and 2017. (2) Quantitative studies showing a change or comparison in mental health status (i.e. mental disorder diagnosis, positive (self-rated) mental health, suicide rate) using a validated mental health measure, and (3) Examined one of the policy domains (Table 1 ) in at least one of the Organisation for Economic Cooperation and Development (OECD) countries. See Additional file 2 for more information about the inclusion and exclusion criteria used in the selection process.

Study selection

We employed two levels of screening to identify relevant studies. All screening tools were pilot tested before each level of screening. In the following section, we briefly describe each level:

Level 1 – Title and abstract screening

Most articles were excluded at this level because the title and abstract did not focus on mental health and/or one of the policy domains. This was primarily conducted by SL. Another reviewer (AM) independently applied the criteria for inclusion and exclusion to 14% of the title and abstracts (350 references). Any disagreements between SL and AM were resolved after discussions.

Level 2 – Full-text screening

The selection criteria were clarified and rewritten for the Level 2 – Full-text screening. Four reviewers participated in Level 2 screening. All articles were reviewed by at least two reviewers. The review team discussed articles where there were disagreements on final decisions (30%). If the team could not agree, then the article was reviewed by a third member of the review team. AM was responsible for making all final decisions.

Study quality assessment and risk of bias

All included articles were assessed using the “Health Evidence Bulletin, Wales: Questions to assist with the critical appraisal of an observational study” (hereto referred to as HEB – Wales Tool) [ 19 ]. The HEB – Wales Tool is one of the few quality assessment tools that is designed to fairly assess different study designs. The tool has been endorsed by Sanderson , et al. [ 20 ] for its ability to be used to assess cohort, case-control and cross-sectional study designs; transparency regarding development; applicability for future use; and use of a checklist system which we used to develop a rating scale. We adapted the tool so that questions were most relevant to our study aims (see Additional file 3 ).

While the HEB – Wales Tool was designed as a checklist rather than a scoring tool, we agreed on a scoring system (a priori) where the study was given a score of two if the criteria for the item was met. If it was unclear then a score of one was given, and if it clearly did not meet the criteria then a score of zero was given. Each study was given a total score out of 30 possible points. If a study had a score of more than 23 points (the authors met at least 80% of the items), then it was classified as high quality. Medium quality studies had a cut-off score between 18 to 23 points and low-quality studies scored 17 points or less (the authors only met 60% of the items). All articles were quality appraised by two reviewers. The final score is an average of the two reviewers’ scores (see Additional file 4 for a summary of the scores).

We assessed the risk of bias in individual studies using Part B of the HEB – Wales Tool entitled “Do I trust it?” In this section, we assessed whether the study design and study population was appropriate, confounding and bias were considered in the study, and there was a long enough follow-up time. Most of the risk of bias was assessed at the design rather than outcome level.

Data extraction strategy

A data extraction template was created and piloted by SF and AM. Using this template, we extracted data from all articles that were marked as ‘included’ in Level 2 screening. Four reviewers completed this phase, with two reviewers assigned to each article to extract data. AM then compared the results and completed a summary table. Any discrepancies were resolved through discussion between the two reviewers.

Table  2 summarises the data items extracted from each article.

Data synthesis

We used narrative analysis to synthesise the data. Categorising the policy domains and focusing on the two specific types of inequalities (gender and SES), were deliberate strategies intended to make the data synthesis clearer. Furthermore, other data items extracted such as study design, population, and setting were intentional measures to assist with comparing heterogeneity in the studies. The implementation of the HEB-Wales Tool also made it possible to systematically compare the quality of the studies.

The search strategy and other sources produced 3394 papers which were assessed for inclusion in the review. Data were extracted from 21 papers that met our eligibility criteria. Figure  1 shows a PRISMA flow diagram of the selection process.

PRISMA Flow Diagram [ 15 ]

Study characteristics

The 21 selected articles were representative of 17 different studies or data sources. The majority investigated European countries, including 10 articles involving Sweden. Five articles, however, included data from Australia, Canada, the USA and Japan. Twelve of the studies compared two or more countries, while the remaining nine focused on a single country. One study focused on adolescents and the remaining 20 involved a working age population Footnote 1 .

Thirteen articles used cross-sectional methods and 10 used longitudinal methods, two of which used a natural policy experiment design.

The articles measured constructs of positive mental health, mental ill-health and diagnoses of mental illnesses. Positive mental health constructs were represented in 11 articles and included mental health functioning, mental well-being and social-emotional development. Mental distress, poor mental health, depression, suicide rates, psychiatric diagnosis and anti-depressant prescription represent the negative aspects of mental health and diagnoses of mental illnesses measured in 10 of the studies. Several validated mental health measures were used including the World Health Organization Well-Being Index (WHO-5), the Global Health Questionnaire (GHQ-12), the Short Form Health Survey (SF36 and SF12), the Centre for Epidemiological Studies Depression Scale (CES-D8), Mental Health Inventory (MHI-5), Ages and Stages Questionnaire (ASQ-SE), Health Behaviour in School Age Children (HBSC), Self-Reported Health in the Quarterly Labour Force Survey, suicide statistics and register data for psychiatric diagnoses.

Five articles focused only on gender inequalities in mental health, and 12 articles measured only SES inequalities, with four investigating both types of inequalities. Table  3 summarizes the results from the 21 included articles.

As results showed that the type of welfare regime strongly influenced the direction of some policy domains, the dimensions of employment policies, family policies and income support and social insurance policies, were added as sub-domains to the welfare state domain. The following section outlines the results by each policy domain or sub-domain.

Welfare states

Nine articles focused on the policy domain of overall welfare states [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 ], meaning that comparisons were made by categorising European countries into welfare regime types, such as the Nordic dual earner/carer model, family oriented, and market-oriented models. Four of the nine articles addressed gender inequalities, three addressed SES inequalities and two addressed gender and SES. Two articles, (Sekine , et al. [ 26 ] and Sekine , et al. [ 27 ]) were based on the same study, but the former focused on SES inequalities while the latter focused on gender inequalities. Only one study focused on social expenditures [ 29 ] and the other eight focused on employment or work characteristics within different welfare regimes.

A dual-earner model where both partners contribute to wage earning and care responsibilities (typically in the Nordic countries) seems to be associated with better mental health outcomes for women while the market-oriented model (e.g. the UK) was associated with worse mental health outcomes for women [ 21 , 22 , 23 , 27 , 28 ]. There also appears to be less of a gap between men and women when it comes to mental health functioning in the dual-earner model [ 23 ]. Furthermore, greater investment in social spending and family focused welfare models were associated with better mental health outcomes for women [ 29 ].

Family policy

Four articles focused on the policy sub-domain of family [ 30 , 31 , 32 , 33 ]. One of these focused-on gender inequality while the other three focused on SES inequality. Findings from Huang , et al. [ 32 ] and Rathmann , et al. [ 33 ] had opposing conclusions in that Huang , et al. [ 32 ] found that cash benefits reduced mental health inequalities between children of lone and couple mothers, and Rathmann , et al. [ 33 ] concluded that an increase in family benefits actually led to a greater gap in SES inequality in mental health outcomes. The limited evidence generally suggests that investment in family benefits leads to overall better mental health outcomes but may not reduce the gap in inequalities in mental health outcomes.

Employment policy

Only one article focused on the policy sub-domain of employment and addressed gender and SES inequality [ 34 ]. As such, we cannot conclude about inequalities in mental health outcomes related to this domain. However, given the quality of the study design and the large sample size, we should consider that in this case, austerity measures contributed to worse mental health outcomes among lower SES groups [ 34 ].

Income support and social insurance

Four studies focused on the policy sub-domain of income support, all of which analysed SES inequalities rather than gender inequalities [ 35 , 36 , 37 , 38 ]. Three of these articles focused on austerity measures and found that mental health inequalities increased, and particularly vulnerable groups experienced greater mental health problems. Van der Wel , et al. [ 38 ] found that mental health inequalities were smaller in countries with more generous sickness benefits. It is unclear if these effects are a direct result of the policies or if they work through other mechanisms. For example, Barr , et al. [ 36 ] suggest that austerity measures may have contributed to increased suicide rates and other mental health problems while Blomqvist , et al. [ 37 ] conclude that inequalities in mental health among women could be due to stricter eligibility criteria and decrease in benefit levels but there is no definitive evidence that policy change (i.e. tightening eligibility criteria and reduced benefit levels) leads to mental distress. The limited evidence shows that more generous welfare benefits are associated with better mental health outcomes and austerity measures are associated with poorer mental health outcomes including increased suicide rates. Additionally, austerity measures seem to contribute to widening the social inequalities gap.

Area-based initiatives

Three articles focused on the policy domain of area-based initiatives, or interventions in a specific geographical location [ 39 , 40 , 41 ]. Two studies focused on the New Deal for Communities initiative in England [ 40 , 41 ] with both focusing on SES inequality. Mohan, et al. [ 39 ] studied a different area-based initiative and focused on gender and SES inequality. Limited results regarding area-based initiatives show that these interventions can prevent or reduce the gap in social inequalities of mental health, or at least prevent the widening of this gap in the targeted areas, and that neighbourhood renewals in more disadvantaged areas provide some improvement to women’s mental well-being.

We did not find any articles focused on the policy domain of education which met our criteria. We therefore cannot draw any conclusions related to educational policy and mental health inequalities.

We synthesised the literature examining the impact of structural determinants on mental health inequalities, specifically focusing on economic and social policies underpinning the welfare state, and prevailing societal norms (see Table  4 ). Of the 21 research articles identified, most were observational studies, and only two studies used a natural policy experiment study design. Of the policy domains examined, welfare states were the most comprehensively researched. We should note that most included studies focusing on welfare states used a regime approach (e.g. Korpi’s [ 13 ]) but as Bergqvist , et al. [ 42 ] argue there are other ways to examine welfare states such as through an institutional or expenditure approach. Other approaches may provide alternative perspectives on our research question.

This review indicates that more comprehensive and gender inclusive welfare states lead to better mental health outcomes especially for women, but there is little evidence that this reduces socio-economic inequalities. We discuss these issues separately below.

Gender inequalities and mental health

Evidence from the welfare state domain indicated that dual-earner models (typically found in the Nordic countries) were associated with better mental health outcomes and less prominent mental health inequalities by gender, compared to other welfare regimes especially basic-security/market welfare states [ 21 , 23 , 26 , 27 , 28 ]. These findings align with findings of Borrell , et al. [ 3 ] that in dual-earner models, public policies support women’s employment while imposing more equitable sharing of domestic work leading to better health outcomes.

Three studies examined the intersection between gender and relationship status [ 28 , 30 , 32 ], highlighting a socially and economically vulnerable group of women; lone mothers. Van de Velde , et al. [ 28 ] found that, in general, lone mothers’ mental health seems to be worse than cohabitating mothers, aligning with other studies (see for example [ 43 , 44 , 45 , 46 ]. Included studies looked at welfare state arrangements and tested specific measures to lessen financial strain. Van de Velde , et al. [ 28 ] conclude that welfare regimes may moderate inequalities in mental health between lone and cohabitating mothers, finding smaller inequalities in Sweden (i.e. Nordic welfare regime) than Britain (i.e. Market-oriented welfare regime). Huang , et al. [ 32 ] suggests that cash benefits to lone mothers are one way to reduce the gap in mental health between children of lone and cohabitating mothers. However, Bergqvist , et al. [ 42 ] notes that reducing inequalities takes a combination of generous family benefits and supporting women in the labour market. On the other hand, Whitehead , et al. [ 44 ] found that the pressure for lone mothers to work in Sweden could contribute to worse health outcomes. Many studies show that family policies facilitate the work-family balance and decrease financial strain, both factors are associated with better health among lone mothers (see for example [ 44 , 45 , 46 ], however, many of these studies mostly focus on mothers’ general health, rather than mental health outcomes.

While outside the scope of our article, some included studies [ 23 , 26 , 27 ] emphasised the role that job quality plays in gender differences. For example, De Moortel , et al. [ 23 ] purposes that differential exposure to bad quality employment (e.g. non-permanent contracts, low wage, lack of union representation) is partly explained by welfare regimes.

Socio-economic inequalities and mental health

While the Nordic countries seem to produce better mental health outcomes for women, our results do not support that this approach reduces socio-economic inequalities in mental health outcomes. Rather, our results support Mackenbach’s [ 47 ] conclusions that strong welfare states such as in Sweden do not buffer against socio-economic inequalities in health.

We found that the evidence on welfare states and socio-economic inequalities was inconsistent. On the one hand, Niedzwiedz , et al. [ 24 ] suggests that higher spending on active labour market programmes reduced inequalities, specifically by improving mental health outcomes among those with the lowest education. However, Rathmann , et al. [ 33 ] found that higher spending on social protection, especially during the recent recession, is not enough to reduce the socio-economic inequalities in the mental health of adolescents. Rather, the authors suggest that a combination of social spending and programs directly targeting adolescents could be more effective [ 33 ]. Hewitt , et al. [ 31 ] also found that increased spending on paid parental leave, improved overall maternal mental health but did not decrease the gap between mothers with low SES and high SES.

Contrasting these studies, Nordenmark , et al. [ 25 ] note that socio-economic inequalities could be wider in Sweden than the UK because of a ‘levelling down’ process that happens with those in higher SES in the UK. The authors explain that persons with higher SES experience greater economic strain receiving flat-rate benefits (i.e. the UK) as their drop in income is larger, compared to countries with income replacement (i.e. Sweden), leading to poorer mental health outcomes on flat-rate benefits than persons with lower SES [ 25 ].

Austerity measures associated with poor mental health outcomes

Four of the included studies [ 34 , 35 , 36 , 37 ] showed an association between poor mental health outcomes and austerity measures – reducing government spending, e.g. by cutting programs and reducing benefit levels. A growing body of literature on the direct and indirect health effects of austerity measures support our findings (see for example [ 15 , 48 ]). More generous public policies like those in Nordic welfare states are associated with better overall mental health outcomes, even if they do not reduce socio-economic inequalities.

Why so little on education policy?

We propose that the absence of studies focused on education policy is in part because most school policy and school intervention research focus on academic outcomes rather than mental health outcomes. Academic outcomes are more accessible to researchers given that children are already assessed based on their school performances. Academic achievement is closely related to mental health, and the two are associated throughout the life course [ 49 ], however, more research is warranted to disentangle some of these mechanisms. Furthermore, school is often seen as a neutral environment that is supposed to ‘level the playing field’ to some extent. The focus of inequality is often based on students’ background characteristics rather than what actually happens at school, or how these factors interact [ 50 ]. Other studies examine much older policy changes and do not explicitly focus on mental health outcomes (see for example [ 51 ]). Further research on school-level determinants of mental health outcomes and investigation of school systems which have undergone changes in educational policy may help elucidate some of these questions.

Limitations

Readers should interpret results from this review with caution, given the heterogeneity of the literature with regards to methodology, mental health outcomes and policy settings. Other methodological limitations included inconsistencies in choice of comparison groups, and datasets often lacking sufficient information to comprehensively adjust for confounding factors, both at the individual and area-level.

The generalizability of our study is also somewhat limited by the definitions used. Our mental health definition included all aspects of mental health meaning that our analysis did not capture the nuanced differences, for example, between different mental illnesses or psychiatric comorbidity as opposed to mental well-being [ 52 ]. Our definition of structural determinants was also broad encompassing many policies, making policy conclusions challenging. Whitehead , et al. [ 44 ] suggest that a better approach is to focus on specific groups in the population and particular policies. We deliberately took a broad approach to get an overview, given that no systematic review has examined structural determinants and inequalities of mental health before.

Health inequalities is a growing field of research. Given the potential importance of structural determinants of mental illness, it is surprising that we did not find more research articles assessing this research question. There are clearly methodological challenges in designing studies in this area. We must also note that important variations in study context mean that other factors, such as economic trends, migration trends, and the political climate may have played a role. Furthermore, it is important to acknowledge the time lag from policy implementation to observing any associated effects on mental health [ 53 ].

Implications

To the best of our knowledge, this is the first review to examine structural determinants in inequalities in mental health. Additionally, our study is one of the few that focuses specifically on mental health outcomes rather than inequalities focused on self-rated health outcomes. Our study provides an overview of what limited evidence is available in this field and identifies areas of future research and policy directions.

In this review, we identified important gaps in the literature for future research. Area-based initiatives and educational policy for example are understudied. Studies should specifically research inequalities, if we are to increase knowledge in this area. Methodologically, we need more natural policy experiments and more studies utilising historical cohort data to examine effects of structural determinants over a longer time frame. Studies drawing on the life-course approach would also strengthen this area of research, given that the risk of mental illnesses may start as early as in childhood and may accumulate over time. Finally, we must acknowledge that the health care system may be a possible mediator. However, given that most mental health policy research focuses on health care access we intentionally excluded the health care domain from this review to focus on other important policy domains. Future research should integrate the health policy domain.

Research comparing welfare states is important, but we must also compare within welfare states (e.g. [ 43 ]) and follow change over time. For example, although the Nordic countries share an overall ethos of equality and a strong focus on gender equality, there are differences between policy designs in each country [ 46 ]. As such, more case study research on the different policy designs of Nordic countries are needed before we can conclude that all Nordic countries promote better mental health outcomes for women.

The findings from this review bear some relevance to policy. For instance, our results indicate that austerity measures are associated with poor mental health outcomes and possibly increased suicides [ 29 , 36 ]. Our findings should be a cautionary tale for governments wanting to shrink welfare states.

Our review also indicates that improving mental health outcomes may present policy-makers with a trade-off between reducing socio-economic inequalities or improving overall mental health outcomes. We need more innovative policy solutions that reduce the risk of this trade-off.

In Europe and elsewhere, rising concern about inequality in health and increased prevalence of mental ill-health, means that ignoring the structural policies that may contribute to inequalities in mental health is no longer an option. This review provides knowledge to policy-makers and researchers when considering reforming policies to reduce inequalities in mental health outcomes. While, this review shows limited evidence supporting the causal effects of structural determinants on socio-economic inequalities in mental health, we found some evidence that policy may affect gender inequalities. The lack of evidence should not be interpreted as lack of effect. To strengthen the evidence base within the structural determinants of mental health inequalities research field and inform policies to reduce inequalities in mental health, future studies should seek to apply innovative methods to overcome the inherent methodological challenges in this area.

The study by Huang et al. 2017 included mothers as participants but measured mental health on the child level. Thus the exposure was on the adult level and the outcome was on the child level.

Abbreviations

Active Labour Market Policies

Ages and Stages Questionnaire

Child Development Accounts

Centre for Epidemiological Studies Depression Scale

Global Health Questionnaire

Health Behaviour in School-Age Children

Health Evidence Bulletin, Wales

Mental Health Component Score

Mental Health

Mental Health Inventory

Mental Well-Being

New Deal for Communities

Neo-Marxian Social Class

Organization for Economic Co-operation and Development

Paid Parental Leave

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

Socio-Economic Status

Short Form Health Survey

Short Form Health Survey (36 items)

Evaluating the Impact of Structural Policies on Health Inequalities

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McAllister, A., Fritzell, S., Almroth, M. et al. How do macro-level structural determinants affect inequalities in mental health? – a systematic review of the literature. Int J Equity Health 17 , 180 (2018). https://doi.org/10.1186/s12939-018-0879-9

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Poverty, social inequality and mental health.

Published online by Cambridge University Press:  02 January 2018

The World Health Organization has described poverty as the greatest cause of suffering on earth. This article considers the direct and indirect effects of relative poverty on the development of emotional, behavioural and psychiatric problems, in the context of the growing inequality between rich and poor. The problems of children in particular are reviewed. Targets to reduce inequality have been set both nationally and internationally.

In Bridging the Gaps , the World Health Organization (1995) states, ‘The world's most ruthless killer and the greatest cause of suffering on earth is extreme poverty.’ This statement emphasises the importance of poverty as a variable adversely influencing health. Poverty is a multidimensional phenomenon, encompassing inability to satisfy basic needs, lack of control over resources, lack of education and poor health. Poverty can be intrinsically alienating and distressing, and of particular concern are the direct and indirect effects of poverty on the development and maintenance of emotional, behavioural and psychiatric problems.

The measurement of poverty is based on incomes or consumption levels, and people are considered poor if their consumption or income levels fall below the ‘poverty line’, which is the minimum level necessary to meet basic needs. It should be emphasised that for the analysis of poverty in a particular country, the World Bank bases the poverty line on the norms for that society.

It is a well-recognised fact that poverty has important implications for both physical and mental health. In this article we discuss the impact of poverty on mental health, and explore possible explanations for the relationship between the two. It is vital to distinguish between absolute and relative poverty; even in countries where families generally have access to sufficient resources to maintain life, many are living in disadvantageous circumstances with poor housing, diet and amenities that do not live up to the expectations of society in general ( Reference Townsend Townsend, 1979 ).

Poverty and social inequality

The gulf between the poor and rich of the world is widening. Within the UK, the financial gap between the wealthy and the poor is not narrowing and differences in health between social classes I and V are becoming greater ( Reference Smith, Bartly and Blane Smith et al , 1990 ). Poverty and social inequality have direct and indirect effects on the social, mental and physical well-being of an individual. It is important to note that poverty and inequality are closely linked. Reference Wilkinson Wilkinson (1997) believed that income inequality produces psychosocial stress, which leads to deteriorating health and higher mortality over time. However, the association between income inequality and life expectancy is slowly disappearing and is no longer widely accepted. Those who live in deprived communities, where there is under-investment in the social and physical infrastructure, experience poor health, resulting in higher mortality for those of lower socio-economic class. The effects of income inequality also spill over into society, causing stress, frustration and family disruption, which then increase the rates of crime, homicide and violence ( Reference Wilkinson Wilkinson, 1996 ).

There are several obstacles, deficits and threats to health inherent in poverty. It is the poor who are exposed to dangerous environments, who (if employed) often have stressful, unrewarding and depersonalising work, who lack the necessities and amenities of life and who, because they are not part of the mainstream of society, are isolated from information and support. The inverse association between socio-economic level and risk of disease is one of the most pervasive and enduring observations in public health ( Reference Kaplan, Haan, Syme, Amler and Dull Kaplan et al , 1987 ). It has been known for a long time that the lowest-income groups are more likely to suffer negative effects of ‘risky’ health behaviours than their less poor counterparts. These ‘maladaptive’ behaviours are not necessarily undertaken with a harmful intent, but may be regarded as coping behaviours to provide comfort or relief from stressful lives. Moreover, people in lower socio-economic classes by virtue of their life circumstances are exposed to more stressors, and with fewer resources to manage them and greater vulnerability to stressors, they are doubly victimised. Poverty is associated with many long-term problems, such as poor health and increased mortality, school failure, crime and substance misuse. The relationship between occupational class and mortality is evident from a survey in the 1970s, which showed that the mortality rate among men aged 20–64 years was almost twice as high for those in class V as for those in class I, and by the early 1990s it was almost three times as high ( Reference Drever, Bunting, Drever and Whitehead Drever & Bunting, 1997 ) ( Table 1 ).

Table 1 Standardised mortality rates per 100 000 for men aged 20–64 years in England and Wales: comparison of years 1970–72 and 1991–93

Poverty and psychiatric disorders

It is not just infectious diseases that demonstrate the powerful social-epidemiological correlation; it is also psychiatric conditions, which not only occur at higher rates in the poorest areas, but also cluster together, usually in disintegrating inner-city communities. Money is not a guarantor of mental health, nor does its absence necessarily lead to mental illness. However, it is generally conceded that poverty can be both a determinant and a consequence of poor mental health ( Reference Langner and Michael Langner & Michael, 1963 ).

The relationship between low economic status and elevated incidence and prevalence of mental illness has become increasingly apparent. The New Haven study in 1958 ( Reference Hollingshead and Redlich Hollingshead & Redlich, 1958 ) and the Midtown Manhattan Study conducted a few years later ( Reference Langner and Michael Langner & Michael, 1963 ) indicated that there was a direct relationship between the experience of poverty and a high rate of emotional disturbance, as well as differential availability and use of treatment modes and facilities by different social classes. Many assume that the socio-economic class gradient with respect to disease can mostly be explained by differences in health care access.

The complexity and interrelatedness of factors such as poverty, health and employment make it interesting to look at the relationship that prevails between them. Relationships between social status and various aspects of mental disorder have long been of interest to both clinicians and researchers, and a large body of research exists showing the importance of social status in understanding psychiatric illness and disability. Epidemiological studies throughout the world have demonstrated an inverse relationship between mental illness and social class. Psychiatric disorders have been consistently shown to be more common among people in lower social classes. The prevalence of psychiatric disorders, including neurotic disorders, functional psychoses and alcohol and drug dependence, was investigated in the 1995 survey published by the Office of Population Censuses and Surveys ( Reference Meltzer, Gill and Petticrew Meltzer et al , 1995 ). Employment status was a major factor in explaining the differences in prevalence rates of all psychiatric disorders in adults. Unemployment significantly increased the odds ratio of psychiatric disorders compared with the reference group. It almost quadrupled the odds of drug dependence after controlling for other socio-demographic variables. Unemployment also approximately trebled the odds of phobia and functional psychosis. It more than doubled the odds of depressive episode, generalised anxiety disorder and obsessive–compulsive disorder, and increased the odds of mixed anxiety and depressive disorder by more than two-thirds ( Table 2 ).

Table 2 Prevalence (%) of psychiatric disorders according to social class, with odds ratio of employment status

It is well recognised that psychoses show a relationship with social class, with the highest prevalence of psychosis in both men and women found in social class V ( Reference Argyle Argyle, 1994 ). However, there are controversies over whether the poor social performance and lower social class of patients with schizophrenia are consequences of the illness, consequences of changes in individuals predisposed to develop schizophrenia, or due to the adverse social conditions that lead to schizophrenia. The relationship between poverty and psychosis is complex, and two explanatory hypotheses have been put forward: social causation (‘breeder’) and social selection (‘drift’). According to the social causation theory, the greater socio-economic adversity characteristic of lower-class living conditions precipitates psychosis in vulnerable individuals. However, this theory was challenged by Reference Goldberg and Morrison Goldberg & Morrison (1963) in a study showing that the social class distribution of the fathers of patients with schizophrenia did not deviate from that of the general population. The excess of low socio-economic status among people with schizophrenia was mainly attributable to individuals who had drifted down the occupational and social scale prior to the onset of psychosis.

It is possible that the relationship between class and schizophrenia exists because the conditions of life experienced by people of lower social class foster conceptions of social reality that are so limited and rigid as to impair their ability to deal resourcefully with problematic and stressful situations. Although such impairment does not in itself result in schizophrenia, in conjunction with genetic vulnerability and great stress it could be disabling.

The association between social inequality at birth and subsequent risk of schizophrenia is uncertain. Reference Mulvany, O'Callaghan and Takei Mulvany et al (2001) concluded that low social class at birth was not associated with increased risk of schizophrenia, but views remain divided on the association between social inequality and psychoses and no definite conclusion has been reached.

Reference Brown, Susser and Jandorf Brown et al (2000) studied the relationship between social class of origin and cardinal symptoms of schizophrenic disorders over the course of early illness. Patients whose origin was upper or middle social class, compared with those from the lower social class, had lower symptom levels of hallucinations and delusions. Patients from the lower social class were older at first contact with psychiatric services than those from the higher social classes; this could be explained by the fact that people from the lower social class find it more difficult to access services. Alternatively, people belonging to the higher social class might be better informed about mental illness and seek treatment early. It is also possible that the beliefs and values of people in lower socio-economic groups, such as their tolerance and acceptance of the behavioural and social aspects of the disorder, explain the observed socio-economic inequalities.

Mood disorder

Many studies have reported that low socio-economic status is associated with high prevalence of mood disorders ( Reference Dohrenwend, Levav and Shrout Dohrenwend et al , 1992 ). In addition, longitudinal research in Stirling County ( Reference Murphy, Oliver and Monson Murphy et al , 1991 ) indicated that during the 1950s and 1960s the prevalence of depression was significantly and persistently higher in the low socio-economic status population than at other socio-economic status levels. Incidence of depression after the study began was also higher among those who were initially in the low socio-economic status group, supporting the view that the stress of poverty may be causally related to depression. There was also a trend for prior depression to be associated with subsequent downward social mobility, supporting the view that the concentration of people with depression at the lower end of the social hierarchy may result from disabling aspects of the illness.

A positive relationship has been found between socio-economic status and vulnerability to mood disorder, with higher rates of vulnerability found among individuals with lower educational and social achievement levels. The social causation hypothesis suggests that the stress associated with low social position, such as exposure to social adversity and lack of resources to cope with difficulty, might contribute to the development of mood disorder, whereas the social selection hypothesis argues that genetically predisposed individuals drift down to – or fail to rise out of – such a position ( Reference Jarvis Jarvis, 1971 ). Patients with major depressive disorder or bipolar depression were more ‘downwardly mobile’ than people with neurotic depression ( Reference Eisemann Eisemann, 1986 ).

The work of Reference Brown and Harris Brown & Harris (1978) points strongly to the importance of supportive relationships in protecting vulnerable women from developing depression. The effect of poverty is substantially reduced when the degree of isolation from friends and family is controlled for, suggesting that social isolation mediates some of the relationships between economic status and mood disorders ( Reference Bruce and Hoff Bruce & Hoff, 1994 ).

It has also been suggested that social class might have an influence on the psychopathological pattern of depressive symptoms. Patients who presented with somatisation and anxiety symptoms were more frequently from the lower social classes, whereas cognitive symptoms were more common among the upper classes. The amount of depression associated with economic hardship among adults may depend on age: Reference Mirowsky and Ross Mirowsky & Ross (2001) found that the amount of depression associated with economic hardship decreases with greater age. Economic deprivation and poor marital relationships were important risk factors for the occurrence and chronicity of depression ( Reference Patel, Rodrigues and DeSouza Patel et al , 2002 ). Both depression and poverty tend to be chronic, and warrant the attention of caregivers and policy-makers.

The National Confidential Inquiry into Suicide and Homicide by People with Mental Illness, along with many other studies, reported that the majority of people who completed suicide were either unemployed or had a long-term illness ( Department of Health, 1999 a ). Compared with the general population, people who attempt suicide belong more often to the social categories associated with social destabilisation and poverty.

Reference Gunnell, Peters and Kammerling Gunnell et al (1995) examined the relations between suicide, parasuicide and socio-economic deprivation. A strong association was found between suicide and parasuicide, with socio-economic deprivation accounting for much of this relationship. Furthermore, homicide and suicide occur more frequently in highly populated, deprived areas ( Reference Kennedy, Iveson and Hill Kennedy et al , 1999 ). This finding is also supported by Reference Crawford and Prince Crawford & Prince (1999) , who noted increasing rates of suicide in young unemployed men living in conditions of extreme social deprivation. It is also true that the mortality rates of overdoses involving cocaine and opiates are significantly associated with poverty status ( Reference Marzuk, Tardiff and Leon Marzuk et al , 1997 ).

Alcohol and substance misuse

Alcohol and drug dependence fit in with the general pattern, with high rates found among those in social class V. Among men and women, alcohol and drug dependence are both much higher among the unemployed group. Social class is a risk factor for alcohol-related mortality, which is also linked to social structural factors such as poverty, disadvantage and social class ( Reference Harrison and Gardiner Harrison & Gardiner, 1999 ). Alcohol-related mortality rates are higher for men in the manual occupations than in the non-manual occupations, but the relative magnitude depends on age. Men aged 25–39 years in the unskilled manual class are 10–20 times more likely to die from alcohol-related causes than those in the professional class, whereas men aged 55–64 years in the unskilled manual class are only about 2.5–4 times more likely to die than their professional counterparts.

For women, younger women in the manual classes are more likely to die from alcohol-related causes, but among older women it is those in the professional class who have the greater mortality. Reference Hans Hans (1999) studied the demographic and psychosocial characteristics of substance-misusing pregnant women, and found that demographic features were related only to type of substance used, with Black women and poorer women more likely to use illicit substances, particularly cocaine, and White women and better-educated women more likely to use alcohol.

Personality disorders

The relationship between low socio-economic status and personality disorders has not been extensively studied. However, there is some evidence that personality disorders are more frequent among single individuals from lower socio-economic classes in inner cities. Studies focusing on antisocial personality disorder have shown that it too is found more commonly in people belonging to lower socio-economic classes.

Low family income and poor housing predict official and self-reported juvenile and adult offending. However, the relationship between poverty and criminality is complex and continuous. The interaction between impulsivity and neighbourhood on criminal activities indicates that the effects of impulsivity are stronger in poorer neighbourhoods than in better-off ones ( Reference Lynam, Caspi and Moffitt Lynam et al , 2000 ). In severely disadvantaged settings, even quite young children may be directly exposed to community violence ( Reference Osofsky Osofsky, 1995 ).

In the Cambridge Study in Delinquent Development, an unstable job record at the age of 18 years was an important independent predictor of young men's convictions between the ages of 21 and 25 ( Reference Farrington Farrington, 1995 ). In addition, having an unskilled manual job at the age of 18 was an independent predictor of adult social dysfunction and antisocial personality at the age of 32. Between the ages of 15 and 18, young males in this study were convicted at a higher rate when they were unemployed than when they were employed, suggesting that unemployment is associated with crime. It seems likely that financial need is an important link in the causal chain between unemployment and crime.

Personality disorder or criminality?

It is interesting to note that the major criticism of the DSM–III–R criteria for antisocial personality disorder ( American Psychiatric Association, 1987 ) was that personality traits or symptoms of psychopathy were neglected and that the disorder was conceptualised as synonymous with criminality. However, the criteria for the disorder in DSM–IV ( American Psychiatric Association, 1994 ), and also in ICD–10 ( World Health Organization, 1992 ), reflect personality traits more than overt criminal behaviour.

Effect of poverty on children

Psychiatric disorders of childhood result from the interplay between genetic and environmental factors. The link between adverse experiences and childhood disorder is complex and involves reciprocal effects from children, as they are not just passive recipients of experience. There is a growing body of research relating to poverty and health indicating that low income combined with disruptive demographic factors and poor external support generate the stress and life crises that put children at risk, and may precipitate psychiatric disorders in childhood.

Children in the poorest households are three times more likely to have a mental illness than children in the best-off households ( Department of Health, 1999 b ). Poverty and social disadvantage are most strongly associated with deficits in children's cognitive skills and educational achievements ( Reference Duncan and Brooks-Gunn Duncan & Brooks-Gunn, 1997 ). In the behavioural domain, conduct disorder and attention-deficit hyperactivity disorder show links with family poverty, and this is most marked for children in families facing persistent economic stress. The relationship between poverty and childhood disorder appears to be more marked for boys than for girls, and seems to be stronger in childhood than in adolescence. Rates of childhood disorder vary in different neighbourhoods and communities. Early studies in the UK suggested that risks of disorder in inner-city areas were twice those in small towns ( Reference Rutter, Yule and Quinton Rutter et al , 1975 ).

It is well recognised that conduct disorder is three to four times more common in children who live in socio-economically deprived families with low income, or who live in a poor neighbourhood. The mechanisms that place poor children at increased risk of psychiatric disorder may have to do primarily with increased rates of parental and family characteristics associated with child psychiatric disorder, rather than the economic disadvantage itself. With regard to economic disadvantage, persistent poverty should be distinguished from current poverty: persistent poverty significantly predicts internalising symptoms such as childhood depression, whereas just current poverty predicts externalising symptoms such as childhood behavioural disorders. It is likely that poverty imposes stress on parents and that this inhibits family processes of informal social control, in turn increasing the risks of harsh parenting and reducing parents’ emotional availability to meet their children's needs.

Reference Kaplan, Turrell and Lynch Kaplan et al (2001) looked at childhood socio-economic position and cognitive function in adulthood and concluded that higher socio-economic position during childhood and greater educational attainment are both associated with cognitive function in adulthood, with mothers and fathers each contributing to their offspring's formative cognitive development and later-life cognitive ability. Improvements in both parental socio-economic circumstances and the educational attainment of their offspring could possibly enhance cognitive function and decrease the risk of dementia later in life.

Erratic, threatening and harsh discipline, lack of supervision and weak parent–child attachments mediate the effects of poverty and other structural factors on delinquency. In the Cambridge Study in Delinquent Development, one of the most important childhood predictors of delinquency was poverty ( Reference Farrington Farrington, 1995 ). Poverty was also found to have an effect on both academic failure and extreme delinquency when maternal education and early childhood behaviour were controlled for ( Reference Pagani, Boulerice and Vitaro Pagani et al , 1999 ). Reference Eyler and Behnke Eyler & Behnke (1999) studied the outcome during the first 2 years in children prenatally exposed to the most commonly used drugs of misuse, and concluded that the effects of drugs appear to be exacerbated in children living in poverty.

Health inequalities – explanatory models

We have argued that economic distress has significant effects on health indicators. How might such effects be mediated? The Black Report ( Reference Townsend, Davidson and Whithead Townsend et al , 1992 ) highlights various explanations for the existing health inequalities, dividing them into four categories: artefact explanations; theories of natural or social selection; materialist or structuralist explanations; and cultural and behavioural explanations.

Artefact theory

The artefact theory suggests that both class and health are artificial variables, and that the relationship between them may itself be an artefact. It is believed that the failure to reduce the gap between classes has been counterbalanced by the shrinkage in the relative size of the lower socio-economic classes themselves.

Natural selection

Theories of natural or social selection relegate occupational class to the status of dependent variable, and health acquires the greater degree of causal significance. This explanation suggests that social class I has the lowest rate of premature mortality because it is made up of the strongest and most robust men and women in the population, and that class V has the weakest people. It puts forward the idea that poor health carries low social worth as well as low economic reward, but that these factors do not do not cause the high mortality.

Materialist theories

Materialist or structuralist explanations emphasise the role of economic and associated socio-structural factors in the distribution of health. It is difficult to ascribe the premature mortality in the lower socio-economic class to subsistence poverty. Social class and the characteristics associated with belonging to that class have health implications. As poverty is a relative concept, people belonging to a low socio-economic class may be relatively disadvantaged in relation to the risks of illness or accident, or to the factors that promote a healthy lifestyle.

Behavioural theories

The cultural or behavioural explanations of the distribution of health suggest that its unequal distribution in modern industrial society is the result of incautious lifestyles, wherein people harm themselves or their children by their excessive consumption of harmful commodities and refined foods, and by their underutilisation of preventive health care and contraception. It is implied that there are subcultural lifestyles, rooted in personal characteristics and level of education, which govern behaviour. According to the ‘culture of poverty’ view of Oscar Reference Lewis Lewis (1967) , human existence in any given environment involves a process of biological and social adaptation which gives rise to the elaboration of a structure of norms, ideas and behaviours. This ‘culture of poverty’ over time seems to help individuals to cope with their environment. This view firmly ascribes poor health to the behaviour of people themselves, and by implication makes them fully responsible for the untoward outcomes. The implication that the poor are in some respects a homogeneous group has caused this view to be widely criticised by British social scientists ( Reference Rutter and Madge Rutter & Madge, 1976 ; Reference Holman Holman, 1978 ; Reference Townsend Townsend, 1979 ).

Social inequality and poverty have demonstrable adverse effects on health. These effects are, in our view, amenable to remediation. In the UK, the National Health Service has several interlinked responsibilities in relation to health inequalities, which include the provision of equity of access to effective health care. One of the recommendations of the Independent Inquiry into Inequalities in Health ( Reference Acheson Acheson, 1998 ) was that as part of health impact assessment, all policies likely to have a direct or indirect effect on health should be evaluated in terms of their impact on health inequalities. These policies should be formulated in such a way that by favouring those who are less well-off, they should ultimately reduce such inequalities. In the consultation document Tackling Health Inequalities ( Department of Health, 2001 ), the Government has set nationa targets for doing this ( Box 1 ).

Box 1 National targets for reducing health inequalities ( Department of Health, 2001 )

Infant mortality Starting with children under 1 year old, by 2010 to reduce by at least 10% the gap in mortality between manual groups and the population as a whole

Life expectancy Starting with health authorities, by 2010 to reduce by at least 10% the gap between the fifth of areas with lowest life expectancy at birth and the population as a whole

Child poverty To work towards the eradication of child poverty by reducing the number of children living in poverty by a quarter by 2004

Smoking To reduce smoking rates among manual groups from 32% in 1998 to 26% by 2010, so that we can narrow the gap between manual and non-manual groups

Teenage pregnancy By achieving agreed local conception reduction targets, to reduce the national under-18 conception rate by 15% by 2004 and 50% by 2010

On a global level, the Development Assistance Committee of the Organisation for Economic Co-operation and Development has called for a global partnership to pursue a new development strategy focused on poverty and social goals ( Development Assistance Committee, 1996 ), and the World Bank suggests various ways of responding to poverty ( Box 2 ). The poverty goal is to halve the proportion of people in extreme poverty by 2015. This is expected to be achieved by accelerating economic growth and by improving the distribution of income and wealth. The social goals include reducing infant mortality by two-thirds by 2015, achieving universal primary education in all countries, providing access to reproductive health services for all by 2015, and making progress towards gender equality by 2005. To achieve these goals, international agencies must support countries that show interest and determination to take up the challenges of the goals for the 21st century, and must strengthen their capacity to monitor progress. In order to build a successful economy, new challenges have to be met with resilence, fresh thinking and courage. This will enable us to make long-term decisions and progress towards a better world.

Box 2 Responding to poverty ( World Bank Group, 2004 )

Poverty can be fought by:

• improving the distribution of income and wealth and, more importantly, learning about the impact of policies on income distribution;

• accelerating social development, which includes education of girls and women, provision of safe water and sanitation, child immunisation, and the provision of safety nets to protect the most vulnerable;

• international agencies that support countries showing a determination to take up the challenges of the goals for the 21st century

• international agencies that work with developing countries to strengthen each country's capacity to monitor progress on outcomes;

• accelerating economic growth, which will require policies that encourage macroeconomic stability, shift resources to more efficient sectors, and integrate with the global economy.

Multiple choice questions

a the poverty line is the minimum income level necessary to meet basic needs

b the World Bank uses poverty lines based on the norms defined for each society

c poverty and social inequality are closely linked

d poverty affects mental and social well-being

e the gap between the poor and rich of the world is narrowing.

2 Poverty and psychiatric disorders:

a the effect of poverty is substantially reduced when the degree of isolation from friends and family is controlled for

b employment status is a major factor in understanding the differences in prevalence rates of all psychiatric disorders in adults

c according to the social causation theory, the excess of low socio-economic status among patients with schizophrenia is mainly attributable to individuals who drift down the occupational and social scale before the onset of psychosis

d homicide and suicide are less frequent in highly populated deprived areas

e alcohol-related mortality rates are higher for men in the manual occupations than in non-manual occupations.

3 Poverty and childhood psychiatric disorder:

a poverty is strongly associated with deficits in children's cognitive skills and educational achievements

b disruptive behaviours are most marked in children of families facing persistent economic stress

c inner-city areas have double the risks of childhood psychiatric disorder compared with small towns

d the relationship between poverty and childhood disorder seems to be more marked for boys than for girls

e children in the poorest households are three times more likely to have mental illness than children in the richest households.

4 Poverty and delinquency:

a the effects of impulsivity are stronger in poorer neighbourhoods than in better-off neighbourhoods

b boys were found to be convicted at a lower rate when they were unemployed than when they were employed

c one of the most important childhood predictors of delinquency is poverty

d erratic, threatening and harsh discipline, low supervision and weak parent–child attachments mediate the effects of poverty and other structural factors on delinquency

e in the Cambridge Study, an unstable job record of a young man at the age of 18 years was an important predictor of his later convictions.

MCQ answers

This is the fourth in a series of papers on the mental health of marginal groups. Previous papers have considered the effects of asylum-seeking and refugee status on mental health ( Reference Tribe Tribe, 2002 ), the implications for UK psychiatric services of young refugees who have fled from chronic civilian strife ( Reference Hodes Hodes, 2002 ) and the mental health of nurses in the UK ( Reference Nolan and Smojkis Nolan & Smojkis, 2003 ).

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• Volume 10, Issue 3
• Vijaya Murali and Femi Oyebode
• DOI: https://doi.org/10.1192/apt.10.3.216

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Towards Improved Specificity in Mental Health Syndromes: Projection-Based Clustering of Depressive Phenotypes

25 Pages Posted: 13 Sep 2024

Alexander Tashevski

The University of Sydney

Mathew Varidel

Jacob crouse, caroline hunt, maree j. abbott, frank iorfino.

Background: Mental health syndromes show significant heterogeneity, affecting the specificity of treatments and research. Past attempts to improve specificity using clustering or Latent Class Analysis (LCA) typically produce large heterogenous clusters. Concurrently, attempts to mechanistically understand disorders, such as the Research Domain Criteria (RDoC), have few tools to connect underlying causes to emergent patterns in patients’ symptom presentations, and vice versa for dimensional models such as The Hierarchical Taxonomy Of Psychopathology (HiTOP). Using depression, we examine statistical phenomena underlying past difficulties in identifying data-driven subtypes. Then, we apply a projection-based clustering methodology to identify new homogenous syndrome subtypes.  Methods: This cross-sectional, observational study recruited 2820 participants aged 12-to-25 years, from primary-healthcare services in Australia, between November 2018 and July 2023. Participants completed self-reported measures of depression, anxiety and mania-like experiences. 1843 participants completed relevant items and were included for analysis. Principle Component Analysis (PCA) examined sources of within-syndrome variance. Density-based disorder subtypes were compared to traditional quantitative phenotyping approaches: clustering paradigms (Model-Based, Centre-Based Partition, Hierarchical), LCA, and Exploratory Factor Analysis (FA).   Findings: A power-law distribution was identified in the variance underlying the syndrome. This affected standard LCA and clustering methods, producing heterogeneous subtypes identified in prior research. Whilst present in FA, the distribution didn’t adversely affect HiTOP results. However, a projection-based clustering procedure was shown to produce better specified phenotypes of the depressive syndrome. This identified 14 clusters organisable in six novel syndrome profiles: sleep, mania, anxiety, weight/appetite gain, weight/appetite loss, and an undifferentiated type.  Interpretation: Past difficulties identifying well-specified data-driven phenotypes may be attributed to the power-law distribution of variances. Projection-Based Clustering showed improved specificity and qualitative distinctions between phenotypes. Additionally, identified clusters may reflect key attractor states within the depressive syndrome, whilst profiles reflect major trends in symptom expression.   Funding: National Health and Medical Research Council, Australia. Declaration of Interest: IBH is the Co-Director, Health and Policy at the Brain and Mind Centre (BMC) University of Sydney, Australia. The BMC operates an early-intervention youth services at Camperdown under contract to headspace. Professor Hickie has previously led community-based and pharmaceutical industry-supported (Wyeth, Eli Lily, Servier, Pfizer, AstraZeneca, Janssen Cilag) projects focused on the identification and better management of anxiety and depression. He is the Chief Scientific Advisor to, and a 3.2% equity shareholder in, InnoWell Pty Ltd which aims to transform mental health services through the use of innovative technologies. Ethical Approval: The Northern Sydney Local Health District Human Research Ethics Committees approved this study (HREC/17/HAWKE/480), and all participants gave online informed consent (via an opt out process).

Keywords: Clustering, Subtypes, Variance, Depression, MDD, Power Law, Phenotype, LCA, HiTOP, Target, High, Dimensional

Suggested Citation: Suggested Citation

Alexander Tashevski (Contact Author)

The university of sydney ( email ).

University of Sydney Sydney, 2006 Australia

University of Sydney Sydney, NSW 2006 Australia

University of Sydney Sydney, NSW 2006 Australia 61 2 9114 4342 (Phone)

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• DOI: 10.35631/ijepc.954032
• Corpus ID: 271260659

REVIEWING THE INFLUENCE OF MENTAL HEALTH AND COPING STRATEGIES ON ACADEMIC PERFORMANCE

• Noraida Saidi , Nik Zam Nik Wan , +4 authors Normaizatul Akma Saidi
• Published in International Journal of… 30 June 2024
• Psychology, Education

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National Academy of Medicine; Alexander C, Murry VMB, Bogard K, editors. Perspectives on Health Equity and Social Determinants of Health. Washington (DC): National Academies Press (US); 2017.

Perspectives on Health Equity and Social Determinants of Health.

• Hardcopy Version at National Academies Press

1 HEALTH INEQUITIES, SOCIAL DETERMINANTS, AND INTERSECTIONALITY

Editors: NANCY LÓPEZ , PHD and VIVIAN L. GADSDEN , EDD.

In this essay, we focus on the potential and promise that intersectionality holds as a lens for studying the social determinants of health, reducing health disparities, and promoting health equity and social justice. Research that engages intersectionality as a guiding conceptual, methodological, and praxis-oriented framework is focused on power dynamics, specifically the relationships between oppression and privilege that are intrinsic to societal practices. Intersectional knowledge projects aimed at studying this interplay within and across systems challenge the status quo. Whether reframing existing conceptualizations of power, implementing empirical research studies, or working with community organizations and global social movements, intersectional inquiry and praxis are designed to excavate the ways a person's multiple identities and social positions are embedded within systems of inequality. Intersectionality also is attentive to the need to link individual, institutional, and structural levels of power in a given sociohistorical context for advancing health equity and social justice.

• HEALTH DISPARITIES, INEQUITY, AND SOCIAL DETERMINANTS: A BRIEF CONTEXT

The urgency to promote health, reduce health disparities, and address the social determinants of health is highlighted in countless reports ( Hankivsky and Christoffersen, 2008 ; World Health Organization, 2006 , 2015 ). In short, problems in health disrupt the human developmental process. They undermine the quality of life and opportunities for children, youth, and families, particularly those exposed to vulnerable circumstances. Despite incremental change within and across health-serving agencies and increased health education and scrutiny of patient care, we continue to see significant disparities in the quality of health and life options that children in racial and ethnic minority, low-income homes and neighborhoods experience ( Bloche, 2001 ). Research has uncovered several interconnections between health and environmental and social factors ( Chapman and Berggren, 2005 ; Thorpe and Kelley-Moore, 2013 ) but has not always shifted paradigms sufficiently to either disentangle intersecting inequalities or tease apart the ways social factors and structural barriers at once interlock to prevent meaningful and sustainable change.

In this essay, we focus on the potential and promise that intersectionality holds as a lens for studying the social determinants of health, reducing health disparities, and promoting health equity and social justice. Collins and Bilge (2016) describe intersectionality as follows:

A way of understanding and analyzing complexity in the word, in people, and in human experiences. The events and conditions of social and political life and the self can seldom be understood as shaped by one factor. They are shaped by many factors in diverse and mutually influencing ways. When it comes to social inequality, people's lives and the organization of power in a given society are better understood as being shaped not by a single axis of social division, be it race or gender or class, but by many axes that work together and influence each other. Intersectionality as an analytic tool gives people better access to the complexity of the world and of themselves . . . People use intersectionality as an analytic tool to solve problems that they or others around them face. (p. 2)

We ask: How do we engage in inquiry and praxis (action and reflection) that departs from the understanding that intersecting systems of oppression, including race/structural racism, class/capitalism, ethnicity/ethnocentrism, color/colorism, sex and gender/patriarchy, and sexual orientation/heterosexism, nationality and citizenship/nativism, disability/ableism, and other systemic oppressions intersect and interact to produce major differences in embodied, lived race-gender that shape the social determinants of health? How can we as scholars, researchers, and practitioners concerned with child and family well-being take seriously the reality of how intersecting systems of power produce lived race-gender-class and other social locations of disadvantage and develop an intersectionality health equity lens for advancing health equity inquiry, knowledge projects, and praxis?

We argue that the potential power of intersectionality as a transformational paradigm lies in two domains relevant to understanding social determinants. First, it is a critical knowledge project that questions the status quo and raises questions about the meaning and relationship between different social categories and intersecting systems of privilege and oppression ( Bowleg, 2008 ; Collins, 2008 , 2015 ; Collins and Bilge, 2016 ; Hancock, 2016 ; McCall, 2001 ; Yuval-Davis, 2011 ). It also pushes against the idea of “blaming the victim”—the simplicity of explaining health or educational outcomes by attributing problems to individuals' genetics or cultural and social behaviors alone. Second, by focusing on power relations at the individual, institutional, and global levels and the convergence of experiences in a given sociohistorical context and situational landscape, it serves as an anchor to advance equity and social justice aims for marginalized communities that have experienced and continue to experience structural inequalities ( Collins, 2008 , 2009 , 2015 ; Crenshaw, 1993 ; Weber, 2010 ). In both instances, researchers and practitioners cross traditional academic, sectoral, and disciplinary boundaries to reconceptualize a problem and combine methods from different disciplines (e.g., in interdisciplinary research), or they apply conceptualizations and methods from one discipline to closely examine issues in another (e.g., in transdisciplinary research, epistemologies, and methodologies).

There is growing evidence and professional wisdom to suggest that health disparities do not exist in isolation, but are part of a reciprocal and complex web of problems associated with inequality and inequity in education, housing, and employment ( LaVeist and Isaac, 2013 ; Schultz and Mullings, 2006 ; Weber, 2010 ; Williams and Mohammed, 2013 ). These disparities affect the unborn child through social-emotional challenges such as maternal stress and diagnosed and undiagnosed medical problems, including higher prevalence of gestational and preexisting diabetes in some pregnant populations. In other cases, they are observable at birth, particularly pronounced when prenatal care is unavailable, when the importance of care is not understood fully, and when young children are not exposed to the cognitive and social-emotional stimulation needed to thrive. These and other problems are manifested in parental stress, for example, in mother-headed and two-parent, low-income, and immigrant households alike. Parent and family adversity may reduce the number and quality of resources available and life experiences for children and families in the early years and throughout the life course. Such adversity is exacerbated by structural barriers that limit employment opportunities, increase housing instability, and contribute to homelessness, and that constrain efforts by families to effect positive change.

Over the past 20 years, two major shifts in discussions of health disparities and inequity have spurred interest and research. One shift is the growth in and opportunities presented by interdisciplinary and transdisciplinary research (e.g., work extending from sociology and psychology to economics, among other fields) and cross-domain practice (e.g., medicine, education, and social work) (see Gadsden et al., 2015b ; LaVeist and Isaac, 2013 ). The reach of interests in these issues can be found not only in the social and medical sciences but also in contemporary ethical, moral, and political philosophy, such as Sen et al.'s (2009) linking of health equity and agency, and their commentaries on the implications for social justice. A second shift has been the heightened attention to health determinants, more frequently called social determinants of health, instead of a biomedical model that solely focuses on the individual-level makeup and behaviors of patients as the source of health disparity. The report of the Commission on the Social Determinants of Health ( CSDH, 2008 ) points to the importance of being attentive to the overlapping effects and simultaneity of intersecting inequalities and their implications for social determinants:

The poor health of the poor, the social gradient in health within countries, and the marked health inequities between countries are caused by the unequal distribution of power, income, goods, and services, globally and nationally, the consequent unfairness in the immediate, visible circumstances of people's lives—their access to health care, schools, and education, their conditions of work and leisure, their homes, communities, towns, or cities—and their chances of leading a flourishing life. This unequal distribution of health-damaging experiences is not in any sense a “natural” phenomenon, but is the result of a toxic combination of poor social policies and programmes, unfair economic arrangements, and bad politics. Together, the structural determinants and conditions of daily life constitute the social determinants of health and are responsible for a major part of health inequities between and within countries. (p. 1)

In emerging conceptualizations of these social determinants, racism and discrimination are overwhelmingly significant factors, but are not the only critical dimensions related to identity to be considered ( Williams and Mohammed, 2013 ). They are tied inextricably to multiple identities and social locations that children, youth, and adults assume, and define a context for health (Bauer et al., 2016; Brown et al., 2016 ). One might argue that there is no issue more important than ensuring health. How a person understands this point and is able to act upon it is determined by more than her or his cognitive ability to engage the idea. It is influenced as well by a range of dynamic and situational identities and social positions that are biological, cultural, and epigenetic; by social determinants (i.e., where people are born, grow up, work, and age, and interact with their changing environments); and by a person's social experiences and encounters, rather than solely her or his self-agency across a variety of social settings. Even individuals with the strongest work ethic and sense of agency, when faced with daily problems associated with intersectionality across any combination of racial, class, gender, sexual orientation, language, or disability systemic oppressions and discrimination, may find fighting against these inequalities daunting.

Several researchers have advocated for a new way of combining the insights and perspectives used in intersectional knowledge projects in order to move away from decontextualized, biomedical frameworks that often fetishize “cultural competence” as the panacea for structural intersecting inequalities ( Viruell-Fuentes et al., 2012 ). Instead of getting distracted by the alleged “deficits” or “individual behaviors” of marginalized communities, they call for what Chapman and Berggren (2005) refer to as a “radical contextualization of the social determinants of health perspectives.” Sen and colleagues (2009) acknowledge this shift:

In addition to the obvious benefit of deepening our insights into social inequalities and how they interact, the study of intersectionality . . . has the potential to provide critical guidance for policies and programmes. By giving precise insights into who is affected and how, in different settings, it provides a scalpel for policies rather than the current hatchet. It enables policies and programmes to identify whom to focus on, whom to protect, what exactly to promote and why. It also provides a simple way to monitor and evaluate the impact of policies and programmes on different subgroups from the most disadvantaged through the middle layers to those with particular advantages. (p. 412)

Our objective in the remainder of this essay is to provide a discussion of the possibilities for innovation in conceptualization, methodologies, and practices that can promote human development and health equity through an “intersectionality health equity lens.” We employ Jones's (2016) definition of health equity. Jones defines health equity as “the [active] assurance of optimal conditions for all people.” Jones explains that we can get there by “valuing everyone equally, rectifying historic inequities and distributing resources according to need.” Jones invites us to think deeply and critically about equity as a never-ending process that requires constant and ongoing vigilance and not just an outcome that once accomplished can be forgotten. Building on Jones's (2016) and Collins and Bilge's (2016) ideas about equity and intersectionality we define an intersectionality health equity lens as ongoing critical knowledge projects, inquiry, and praxis that can include research, teaching, and practice approaches that are attentive to the ways systems of inequality interlock to create conditions for either health equity or health inequities ( Collins, 2008 , 2015 ; Collins and Bilge, 2016 ; Crenshaw, 1993 ).

We also embrace Collins and Bilge's (2016) core ideas of intersectionality, namely a focus on inequality, relationality and connectedness, power, social context, complexity, and social justice. They use the analogy of “domains of power” to paint a picture of the way that power is visible at the “interpersonal” or individual level in terms of who is advantaged or disadvantaged at the level of social interactions. For example, individuals may experience privilege or disadvantages when searching for a job, housing, interacting with law enforcement, or even when accessing a voting booth. Collins and Bilge (2016) assert

Using intersectionality as an analytic lens highlights the multiple nature of individual identities and how varying combinations of class, gender, race, sexuality, and citizenship categories differentially position every individual. (p. 8)

Collins and Bilge (2016) also underscore that we must always be attentive to the “disciplinary” level as a domain of power that organizes and regulates the lives of people in ways that echo our distinct social positions with regard to systems of oppression. For example, rules about who will or will not be seen at a medical office because of the ability to pay a copay, who will or will not be admitted to a domestic violence shelter based on their English proficiency, and who has access to a gifted classroom, based on IQ test scores that are rooted in eugenicist origins, will inevitably impact the conditions for the advancement of health equity (see also Crenshaw, 1993 ; Zuberi, 2001 ).

Collins and Bilge also invite us to reflect on how power is visible at the “cultural” level or in the realm of ideas, norms, and narratives. For Collins and Bilge (2016) , ideas matter and how messages are manufactured creates explanations, justifications, or challenges to the status quo vis-à-vis inequalities. For instance, if the idea that racialized health inequalities are simply a matter of individual behavior, food ways, and choice, and that we live in a meritocracy, where your station in life is simply a matter of individual effort, then we are subscribing to what Bonilla-Silva refers to as “colorblind” racism or the belief that present-day realities of race gaps in health only mirror individual deficits of individuals or defective cultures.

The last arena where Collins and Bilge interrogate the dynamic of power includes the “structural” level or at the level of institutional arrangements, which interrogates how intersecting systems of institutionalized power, whether in the economy and labor market in terms of whose labor is valued and who is exploited, or at the political level in who is granted substantive citizenship rights and privileges and who is not, as well as at the level of who has access to structures of political power and influence, shapes the institutionalization of the conditions for health equity. For example, the struggle for sovereignty of indigenous people, as evidenced in the Standing Rock movement to protect indigenous land and water for generations in South Dakota provides a snapshot of the structural location of indigenous nations and capitalist neoliberal actors that are in a struggle to define the environmental context for current and future generations, which will have grave consequences for health justice for marginalized indigenous communities.

While an intersectionality health equity lens may inform or drive interdisciplinary or transdisciplinary research, it must also be considered as part of both the process of conceptualizing the problem and the product of research on the problem. Throughout this essay, readers should consider the potential applications of an intersectionality health equity lens, how its use enhances (or disrupts) our understanding of salient and longstanding issues, what might be learned from its use that will inform and deepen research and practice with children and families who are among the marginalized in society, and what types of intersectionality-focused approaches might lead to health access and equity. In the next section, we focus on the contributions of an intersectionality health equity lens for research and for promoting health equity.

AN “INTERSECTIONALITY HEALTH EQUITY LENS” FOR SOCIAL JUSTICE

When developing or applying an intersectionality health equity lens, the researcher engages in deep self-reflection that contextualizes and recognizes the ways race, gender, class, sexual orientation, disability, and other axes of inequality constitute intersecting systems of oppression. Such systems produce very different lived experiences for entire categories of people who are embedded within complex webs and social networks at different levels (e.g., family, neighborhood, and community as well as institutional and structural). These lived experiences can either enhance or challenge the developmental pathways of children through adulthood and the ability of parents and families to ensure a positive trajectory for their children. They affect both the individual child and the networks and communities in which children live and grow and that define their access to resources.

An intersectionality health equity lens for the purposes of our discussion takes on the broader, philosophical meaning attached to praxis as a process involving health, educational, and social service researchers and practitioners in not only self-reflection but also action. Critical self-reflection allows researchers and practitioners to continually and closely examine their own race, gender, class, sexual orientation, disability, language, nativity/citizenship and social position, and their relationship to systems of inequality as part of intersecting systems of oppression and privilege. It argues for researchers and practitioners to draw upon their own experiences with health inequities and discrimination, and to understand and respond to new or subtle forms of inequities and discrimination. These subtle forms of inequity and discrimination are sometimes so deeply embedded in and accepted as societal practices that they may be difficult to uncover, yet render many children and families hopeless. The interplay between and among relevant systems and the statuses accompanying power attributed to different ethnic, racial, cultural, and socioeconomic groups affect both individuals and their social networks (e.g., family, neighborhood, and community). They are tied directly to and within institutional and structural hierarchies.

Crenshaw (1993) points to the entrenched nature of inequity, underscoring the need for a useful paradigm in which to locate the issues faced by African American women and other racially stigmatized, visible minority women of color. Credited with creating a systematic analysis of the concept of intersectionality, Crenshaw (1993) urged readers to “map the margins” by focusing on those social locations that remain invisible. She argues that such invisibility results from a reliance on a mythical, universal “black experience” (e.g., when we assume that the default category is the “black male experience” and by the same token when we speak about “‘women's experiences” and assume that all women's experiences are represented in white women's experience). In each of these dominant conceptualizations of the black [male] and [white] woman's experience, heteronormativity is the invisible structure.

Crenshaw (1993) also illustrates how language, and potentially nativity and citizenship status, can serve as other axes of stratification that have received less attention than race and class. To illustrate her point, Crenshaw flexes her intersectional lens to bring into sharp relief the effects of “good intentions” on the real lives of women. She demonstrates that, despite their good intentions, some domestic violence shelters may operate in ways that ignore the plight of immigrant women with children who may not speak English and are unable to access domestic violence shelters. It goes without saying that this would structurally exclude immigrant (both documented and undocumented) women and their children who do not speak English. “Nativism, English Only” categories are the invisible, yet real, structural barriers to addressing domestic violence in the aforementioned situation. By the same token, members of lesbian, gay, bisexual, transgender, queer, and in-transition (LGBTQI) communities may not face explicit rules about being barred from these services because of their gender identity, but if counselors and other providers assume that their clients are in heterosexual, gender-conforming relationships, heteronormativity can operate as another type of an informal barrier.

One might well ask, given the complex relationships in addressing identity, whether it is possible to create intersectionality-grounded projects that integrate the issues of race, class, gender, disability, and other identities, statuses, and social locations in research on health and well-being for the range of issues facing marginalized children, youth, and families. Although we do not have a simple response, we highlight the need to address the real or perceived complexity of creating such projects and allowing time and resources for them to be developed well and to be refined ( Cacari-Stone et al., 2017 ; López et al., 2017a , 2018 ; Van Hattum et al., 2017 ). We similarly understand the limitations of relying on one-dimensional categories that are, at best, additive, for example, first race, then maybe class, then maybe gender, depending on the focus of the research. As the World Health Organization (2015) and several health researchers before (e.g., LaVeist and Isaac, 2013 ; Williams and Mohammed, 2013 ) suggest, understanding the social determinants of health requires a broad reach to identify, and respond to, the embedded and entrenched inequities of policies that are situated in place and context.

Intersectionality health equity lenses help us understand that every person's experience is fundamentally different than the experience of others, based on their unique identity and structural positions within systems of inequality and structural impediments ( Feagin and Sikes, 1994 ; López, 2003 , Nakano Glenn, 2002 , 2015 ; Weber, 2010 ). More than just a theory or framework to be used selectively, it is a commitment to developing a relentlessly critical and self-reflective lens that begins with the premise that race, class, gender, and other axes of social identities are intertwined and mutually constitutive, and that such a lens can help advance health disparities research, practice, and leadership by making the invisible visible ( López et al., 2017b ; López, 2018 ).

• INTEGRATING RACE, GENDER, CLASS, AND SEXUALITY AS LIVED EXPERIENCES: A CASE EXAMPLE

In considering intersectionality projects, we must be aware of the overwhelming inequities associated with longstanding problems of race and gender and the added problems of poverty and class—problems that have narrowed in some cases over time but where inequality persists. It should come as no surprise that an intersectionality-focused project might appear opaque or obscure initially, despite its potential to uncover the breadth of issues faced in ensuring health and well-being.

Imagine the year 2050, and all institutional data are derived from the critical insight offered by Bowleg (2008) :

It is the analysis and interpretation of research findings within the sociohistorical context of structural inequality for groups positioned in social hierarchies of unequal power . . . . that best defines intersectionality research. (p. 323)

López (2013) proposes the “racialized-gendered social determinant of health” as a heuristic device or framework for centering the lives of marginalized communities. This framework consists of two major concepts: (1) “lived race-gender” and (2) “racialized-gendered pathways of embodiment.” López (2003) offers an example of the enactment of these concepts in the minds and experiences of both the observer and the observed. For example, she makes explicit the ways race-gender disparities are enacted and experienced in school and society by young Dominican and Caribbean men and women in what she calls “New York Immigration and Racialization.” Consider Orfelia's narrative on the public's perceptions of blacks, Hispanics, and whites and the differential result of their identities on these perceptions:

If you put on the news, anyone who does anything bad, if he's not Black, he's Hispanic . . . . You watch the news and you see that when any white guy does something, you won't see their face. They might just say it, and that's all. But if it's a Dominican, a Hispanic, a Black, they put him on for about two minutes, so that you can know him. (p. 23)

Orfelia points to the ways she has internalized race and gender stigma as dominant identity markers and their intersections with place (Queens in New York) and other intersectional identities such as immigrant and Spanish speaker. The mental health costs of feeling racially stigmatized may become embodied by many youth who also feel what sociologist W. E. B. DuBois coined in 1903 as the “double consciousness” experienced by blacks in the U.S. context or the sense of always being seen with contempt, pity, or disdain because of one's stigmatized status ( DuBois, 1999 ; Vidal-Ortiz, 2005 ). 1

López also underscores the dominance of race and gender identities, along with other identities (e.g., social class, sexual orientation, age, ethnicity and nativity, and legal status) that form the basis for education and health frameworks. She draws upon a personal example to demonstrate connections among race, gender, sexuality, and social class and the significance attached to heteronormativity ( Box 1-1 ).

BOX 1–1

Contextualizing Lived Race-Gender and the Racialized-Gendered Social Determinants of Health.

While race, gender, and class were overriding identities in the short narrative in Box 1-1 , heteronormativity was the silent but overpowering lens for López and her cousin. 3 As López notes, the nature and type of her cousin's experiences in and out of school, within family and community contexts, and with stressors that were unnamed distinguished the two cousins. As she suggests through this anecdote, sexuality played only a small though apparently significant part in the everyday encounters that her cousin faced. What remains unanswered are questions about the ways race and gender (male and Dominican) played in her cousin's schooling, and the ways that gender nonconformance (what we now refer to as transgender identity) produced barriers to health access, care, prevention, and maintenance; to employment; to housing; and to the daily acceptances that allow individuals to maintain not just a healthy personal racial, gendered, class, ethnic, or sexual identity but also an identity that can be embraced in full in all social domains and situations that López's cousin traversed throughout their short life.

Focusing on López's cousin's experiences from a health equity perspective, several additional questions are raised: Did the health system fail her cousin, or was it the larger social system that did not accept their intersectional identities? To what degree do our current systems of data collection make her cousin's intersecting lived oppressions vis-à-vis race, national origin, class, sexuality, gender identity, and nativity invisible? If we collect data only on gender identity and not class, nativity, citizenship, ethnicity, language, and/or national origin, do we make some social locations invisible? Do we ignore the temporal element of identities across the life course? How would López's cousin's life experiences have been different if her cousin had been from an LGBTQI middle class, Dominican immigrant family that was light skinned, white-looking Latinx and not a visible minority? All of these data challenges are opportunities for establishing communities of practice committed to intersectionality praxis (action and reflection). 4 Bowleg (2008) provides us with critical epistemological, ontological, and methodological insights on advancing intersectional inquiry and praxis:

I argue that a key dilemma for intersectionality researchers is that the additive (e.g., Black + Lesbian + Woman) versus intersectional (e.g., Black Lesbian Woman) assumption inherent in measurement and qualitative and quantitative data analyses contradicts the central tenet of intersectionality: social identities and inequality are interdependent for groups such as Black lesbians, not mutually exclusive. In light of this, interpretation becomes one of the most substantial tools in the intersectionality researcher's methodological toolbox. (p. 312)

In studying these and other questions related to health access and equity, drawing upon broad conceptualizations and nuanced analyses is important as is drawing upon conceptually complementary methodological approaches. The efficacy of rigorous quasi-experimental studies and of large, integrated datasets, including administrative data, in identifying and addressing multiple problems facing differing communities is clear. For example, Brown and colleagues (2016) examine the influence of the intersecting consequences of race-ethnicity, gender, socioeconomics status (SES), and age on health inequality with almost 13,000 ( n = 12,976) whites, blacks, and Mexican Americans, based on panel data from the Health and Retirement Study. Drawing upon multiple-hierarchy stratification and life-course perspectives, they focus on (1) the variation of racial/ethnic stratification of health by gender and/or SES and (2) the decrease, stability, or increase of combined inequality in health between middle and late life. Analyses of the data indicated that the effects of racial/ethnic, gender, and SES stratification were interactive, resulting in the greatest racial/ethnic inequalities in health among women and those with higher SES.

Although improving our quantitative data infrastructure is of paramount importance, Chapman and Berggren (2005) also call upon health disparities researchers to take advantage of the benefits of qualitative data methods that “radically contextualize” the sociohistoric contexts that fuel the social determinants of health. They argue that qualitative methodologies such as participant observation, ethnography, and interviews can serve to demystify the link between structural, institutional, community, and individual processes that contribute to health inequities by shedding light on the social practices, interactions, policies, mechanisms, and processes that undergird manufactured health inequities. Rather than committing to one or the other, this focus on intersectionality will require the use of multiple methods, strategically layered to identify the problem and provide responsive interventions and equitable policies ( Minkler and Wallerstein, 2011 ).

An intersectional paradigm or conceptual universe takes identity categories embedded within systems of inequality as a starting point to understanding the interactions between individuals and systems and among individual identities, systems, and social locations across the life course. The categories are fluid and must be examined in combination with each other. Metzl and Hansen's (2014) concept of “structural competency” offers a useful example. It begins with the assumption that “inequalities in health [education, employment, housing, voting, law enforcement, nativity, etc.] must be conceptualized in relation to the institutions and social conditions that determine . . . resources” (p. 127). Discussions of intersectionality address Metzl and Hansen's concerns, described earlier, and emphasize the importance of examining the simultaneity of racism, sexism, heterosexism, classicism, and other axes of inequality for mapping and interrupting the sedimentation of health inequities in health care access and the social determinants of health. This perspective is moving slowly into mainstream health disparities research, as health focuses more directly on the social bases for health determinants ( WHO, 2015 ). Intersectionality considers the multiplicity of policies and practices constructed for different groups. At the same time, it acknowledges the ways these historically situated policies and practices reinscribe positions of power, dominance, and oppression that contribute to the social determinants of health, education, and well-being.

• DEVELOPING AN INTERSECTIONALITY HEALTH EQUITY LENS: CHANGING THE NARRATIVE FOR SOCIAL JUSTICE

What happens when health research takes an intersectional stance in producing and using knowledge to effect positive practice and social change and advance equity? In what ways do our personal and professional positionalities contribute to this intersectional stance, our research, and the opportunities afforded by our ways of seeing and knowing the world? How do we address the health inequalities and inequities that reduce these opportunities for children, youth, and families and redirect them to promote social justice?

We are aware that the answers to these questions require time, depth of inquiry, and breadth of analysis, and that they contribute to, rather than outline, a social justice framework. Throughout this essay, we argue that a critical, self-reflexive intersectionality health equity lens and praxis depend upon a visceral commitment to uncovering the workings of the multiple systems of inequality in unpacking the social determinants of health. Such a lens might be expanded to become an “intersectionality equity” lens that questions further how our research, teaching, and practice can enact Crenshaw's (1993) idea of “mapping the margins.” To achieve this, Crenshaw argues, we must center the lives of groups that remain often invisible when we talk about the generic working class “women” or “men” or “Latinos” or “LGBTQ” communities.

In moving forward, we also must be committed to enlarging and diversifying the pool of research scientists who study the issues. By diversity within an intersectionality health equity lens, we are referring to research scientists whose own awareness of their intersectional identities—that is, ethnicity, race, gender, class, sexuality, nativity, and disability—pushes them to design research that produces greater knowledge and clarity about the conceptualization of sound intersectionality-grounded studies and the range of methods to ensure new knowledge, better applications of knowledge, and effective uses of knowledge to guide our understanding of human development and health.

Initiatives focused on advancing social cohesion through intentional efforts to increase the diversity and number of research scientists with lived experiences that reflect multiple intersecting systems of oppression may take different forms. For example, in April 2011, the Institute for the Study of “Race” and Social Justice at the University of New Mexico, with support from a National Institutes of Health workshop grant, convened a group of scholars from the health and biological sciences and social sciences who embodied the intersecting race, gender, sexual orientation, class, age, disability status, religious, ethnic, citizenship, and national origin backgrounds that form the rich tapestry of our diverse union ( Figure 1-1 ).

FIGURE 1–1 |

National Institutes of Health (NIH) R21 Workshop. This gathering convened diverse multidisciplinary scholars for a workshop entitled, “Mapping ‘Race’ & Inequality: Best Practices for Conceptualizing and Operationalizing (more...)

Other activities may include opportunities for interdisciplinary conferences and collaborative research, teaching, and writing. For example, at the University of Pennsylvania, one health disparities course is cofacilitated with tenure-track and clinical faculty within education and across the social sciences, medicine, and nursing. Bringing together all of the insights from health sciences, psychology, anthropology, art history, American studies, and law can actually generate new knowledge and new ways of doing research and developing equity-based policy. It is tremendously powerful to build on interdisciplinary knowledge. It is not the case that any one discipline has all the answers. We need all of us working together, harmoniously, to continue to make advancements and these insights should be reflected in what is considered required coursework for all disciplines interested in health equity.

An intersectionality health equity lens offers enormous possibilities for research projects that take seriously the multiple identities of children, youth, and families in the study of health and human development. One might argue that a relationship exists between social-ecological models of human development and health that highlight the intersections and interactions between and across contexts and discussions of intersectionality that consider social statuses.

In supporting an “intersectionality health equity lens” for research, we accept the limitations of implementation and of ways of looking at problems that children, youth, and families face. In our examples, drawn from our personal and research experiences, we suggest that there is little to no likelihood that a clean, one-size-fits-all approach exists to uncover the multiple intersectional identities in a given situation or sociopolitical and historical context. We also argue that to reveal the full expanse of complex intersecting factors that create social determinants of health and well-being, the discomforts associated with linking the different identities, the tendency to focus on one over another, and the difficulty of determining and building appropriate methodologies will have to be addressed (see Gadsden et al., 2014 , 2015a ). Palència and colleagues (2014) , referring to their research and practice in Barcelona, remind us that “the development of research designs and methods that capture effectively all of the tenets of intersectionality theory remains underexplored” (p. 8). While intersectional analyses have relied heavily on ethnographic approaches, the authors note that “quantitative researchers have acknowledged the tensions between conventional research designs, intended to test for independent effects, and intersectionality principles” (p. 8).

The social sciences and health sciences are making progress toward considering the range of factors outside of simple genetics and social environments that affect health and health interventions. Intersectionality knowledge projects draw upon and have the potential to create innovative research and policy paradigms that can lead to practical measures and solutions for advancing health equity. Such measures map and interrupt inequality among racially stigmatized and other marginalized communities in local, municipal, state, and national contexts. At a minimum, they suggest a revisioning of policies that cut across relevant areas of health, education, social services, and law.

In developing our focus on intersectionality and social determinants of health, we attach our analysis to the goals of advancing social justice, where commitments to equality and equity reside and power is shared. A list of resources focused on intersectionality appears in Box 1-2 and demonstrates the range of efforts. As these efforts suggest, for all health and health policy researchers, scholars, practitioners, and community leaders who embrace a social justice framework, an intersectionality health equity lens could help to illuminate the often stifled issues that affect the health, development, and well-being of children and families in marginalized communities. This would mean that they would take seriously the ways institutional rights and duties allow people to participate and receive resources such as health, education, and social services in ways that are fundamentally shaped by intersecting inequalities. That would also mean promoting equal access to the fair distribution of wealth, equal opportunity, and equality of outcome by making the invisible visible through interrogating how race and class systems of oppression work together in shaping the social determinants of health.

Partial List of Intersectionality-Focused Resources.

Organizations such as the NAM can serve as convergence spaces where intersectionality knowledge projects centering on the lives of multiple and diverse marginalized groups in a given sociohistorical context can be incubated and developed to advance health justice. How specialists see, treat, and understand the human experiences of children and families and the potential for their well-being will be revised. As a result, we begin to address the multiplicity of identities, social positions, and systems of intersecting inequalities that contribute to the social determinants of health for diverse populations of children, youth, and families and move closer to effecting sustainable change and equity.

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See also Gravlee (2009) on when race becomes embodied.

“They” or “their” is used to denote the gender history of the transgender person.

For more information on providing equitable health care services for diverse LGBTQI communities, see Vidal-Ortiz (2005) , NBER (2012) , and Johnson et al. (2017) . For information on the difference between ethical accuracy for civil rights and aesthetic accuracy for compliance only and the value added for having a separate question on Hispanic origin and race for the 2020 Consensus, please see Johnson et al. (2017) .

For more on the AfroLatin@ experience in the United States, see Román and Flores (2010) ; for more information on providing equitable health care services for diverse LGBTQI communities, see Ortiz et al. (2015) ; for more on segregation, see Vidal-Ortiz (2004) , NBER (2012) , and Saenz and Morales (2015) .

• Cite this Page LÓPEZ NANCY, GADSDEN VIVIANL, editors. HEALTH INEQUITIES, SOCIAL DETERMINANTS, AND INTERSECTIONALITY. In: National Academy of Medicine; Alexander C, Murry VMB, Bogard K, editors. Perspectives on Health Equity and Social Determinants of Health. Washington (DC): National Academies Press (US); 2017. 1.
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‘The challenges facing nurse education must be tackled’

STEVE FORD, EDITOR

• You are here: Mental health

Nursing staff raise alarm over mental health care inequality

10 October, 2023 By Ella Devereux

Source:  Alamy

Just one in 10 nursing staff across the UK think governments are achieving equality between mental and physical health care, it has been revealed.

To mark World Mental Health Day, the Royal College of Nursing (RCN) has published results from a survey of 4,424 nursing staff about the challenges that remain in achieving parity between mental and physical health.

The RCN has called on governments across the UK to support mental health care by increasing funding, improving access to services and ensuring there are safe levels of staffing.

"Governments across the UK are failing to provide the funding and resources that mental health care services need" Nicola Ranger

In 2013, the NHS Constitution in England changed with the aim of ensuring physical and mental health care would be treated equally, after legislation on the issue.

Yet a decade later, nursing staff have told the RCN that disparities remain between mental health and physical health care.

The RCN conducted its last survey on this topic in 2018, and has now expanded its remit to include all health and care settings where RCN members work.

In the latest survey, published today, 95% of nursing staff said they believe there is inequality between mental and physical health care in the UK.

In addition, half of respondents (50%) said that efforts to achieve mental health equality had got worse since the pandemic, compared to 15% who said it had got better.

Respondents noted that having enough funding, patient access to services and safe staffing were the greatest areas where inequalities existed between the two.

Notably, these were exactly the same areas identified in the 2018 survey, which the RCN said reflected “little shift in thinking around where priorities should lie”.

The survey revealed that over two thirds of respondents (68%) thought that their country of work had been unsuccessful in ensuring mental health gets equal attention to physical health.

Just one in ten (10%) reported that they thought their country had been successful in achieving this.

Similarly, 60% of respondents said that their local NHS service had been unsuccessful in ensuring that mental health gets equal attention to physical health, while 12% said their local NHS service had been successful.

In its report of the findings, the RCN said that nursing staff thought mental health services were “often reactive and short term instead of proactive and long term”.

In addition, respondents said staffing was a major barrier to equality, “with many feeling that there are insufficient resources to provide adequate care”.

One respondent said: “There is a will to give mental health an equal footing but not the budget to allow the investment to match that aspiration.”

Another said: “I think local NHS services are trying their best with what they have got but long-term poor planning has impacted services.”

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For those working in a predominantly physical health setting, almost half (49%) said it was ill-equipped to support the mental health needs of patients, while 26% said their setting was equipped to deal with it.

There was a common feeling among respondents that mental and physical health services were often treated as separate entities, leading to a lack of consistency in the level of support provided for mental health needs.

One respondent said: “Despite working in a hospital that has a mental health unit on the same site, referrals are difficult to make.”

Another said: “I work in an A&E department. Physical and mental health are still very much treated as separate conditions.”

Meanwhile, for those working in a predominantly mental health setting, over 40% of respondents said it was equipped to deal with the physical health needs of patients, while 34% said it was ill-equipped.

Respondents cited efforts to deliver “robust physical health care skills” for those receiving care in mental health settings, however responses showed an “inconsistent and patchy picture across services”.

“Unfortunately, many areas do not have fully functioning equipment for monitoring physical health,” said one respondent.

However, another said: “On our mental health wards, we have physical health nurses attached to each ward.

“We also have physical health nurse contacts for community mental health settings.”

Nursing staff working across mental health and physical health settings agreed that further training and the ability to work with other local services would help to achieve equality in the delivery of care.

Commenting on the survey, the RCN’s chief nurse, Professor Nicola Ranger, said: “Despite many years of promises and commitments for equal treatment of physical and mental health care, nursing staff are seeing things heading in the wrong direction.

"Governments across the UK are failing to provide the funding and resources that mental health care services need, with serious care consequences for patients and service users.

Nicola Ranger

“People are waiting far too long, traveling huge distances, or even feeling forced to pay privately to get treatment.

“This World Mental Health Day, we’re reminding governments why parity matters and to provide the funding, resources and joined-up care between mental and physical health care that people desperately need.”

Responding to the survey, the deputy chief executive of NHS Providers, Saffron Cordery, said: "It appears that achieving equity for mental health services is no longer a priority.

"Mental health care needs more long-term investment, including for staff, for capital to transform dated facilities and for early intervention and prevention, to give patients the high-quality, 21st century treatment they need."

When asked to comment, the Department of Health and Social Care directed Nursing Times to a blog on how the government is supporting mental health services in England.

The blog noted that funding for mental health was “expected to increase to 8.92% of NHS funding in this financial year”.

In addition, it highlighted that the government was investing at least £2.3bn of additional funding a year by March 2024 “to expand and transform mental NHS health services, so an extra two million people can get mental health support”.

Meanwhile, a Welsh Government spokesperson said: “We recognise the important role mental health nurses play, which is why we've increased training places by 29.2% in the last year.

"We are also investing £6m in the Mental Health Workforce Plan for Wales.

“Later this year we [will] also be consulting on our successor strategy to Together for Mental Health.

“Ensuring people can access effective mental health support is a priority.”

Also responding, a Scottish Government spokesperson said: “Mental health spending by NHS Boards has doubled in cash terms - from £651 million in 2006-07 to £1.3bn in 2021-22 - and we have record numbers of staff providing support to a larger number of people than ever before.”

They added that, in the coming weeks, the government will be publishing a strategy delivery plan and accompanying mental health and wellbeing workforce action plan.

The spokesperson said: “As part of this work, we will commission a Scottish mental health nursing review.

“This will provide a specific focus on the unique challenges faced in mental health nursing and allow us to consider what more needs to be done to attract, grow, support, and develop the mental health nursing workforce and leadership.”

The Department of Health in Northern Ireland was contacted for comment.

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We must tackle the model-minority myth with self-advocacy and personal storytelling

3-minute read.

When we were both 14-year-old high school students in Scarsdale, my friend Emma (a pseudonym) confided in me that she had thought about suicide. Normally, an admission like this would have been shocking. But I understood where Emma was coming from.

My conversations with Emma inspired my advocacy work. I share her story with her blessing.

Emma and I grew up in Chinese-American families with deeply held cultural beliefs emphasizing the value of hard work and perseverance while minimizing discussion of mental health. Emma felt her parents saw her as a high-achieving high school standout and feared they would not take her mental health challenges seriously. In our families, "saving face" often took priority over well-being.

Our emotion-suppressing culture was born from intergenerational and immigration-related traumas and shaped, in part, by the “model minority myth.” This is the societal perception, rooted in racism, that Asian-Americans and Pacific Islanders (AAPIs) are a “problem-free” group – setting the expectations of perfection and preventing help seeking.

Research released by  The Jed Foundation (JED) , a leading nonprofit that protects emotional health and prevents suicide, found that AAPI teenagers are more likely than others to believe their problems are not serious enough to discuss with someone else. Another  study  found that only 36% of AAPI people with a mental health condition received treatment in the previous year — 15 percentage points lower than the national average.

These factors contribute to suicide being the  leading  cause of death among AAPI teens and young adults. It is essential we bridge the chasm between cultural assumptions and the urgent need for mental health support. We must equip people to know the signs of distress and how to act. Identifying those at risk quickly is critical in linking people to necessary support, and these efforts are most effective when employed as part of a comprehensive suicide prevention program.

We must also work to change perceptions and expectations of AAPI youth. While this burden cannot rest just on young people’s shoulders, self-advocacy and storytelling play crucial roles in confronting these challenges.

Self-advocacy can take many forms, including confiding in a trusted friend or adult, starting a mental health club at school, or visiting a counselor. And for those comfortable doing so, it may include speaking about our experiences.

Sharing our stories is vital in dismantling the model minority myth, which reduces a diverse population to a simplistic stereotype and imposes unrealistic expectations on AAPI youth.  We cannot, should not, be forced into a singular narrative.

Emma was not yet ready to seek professional help, but her admission sparked something in me. I resolved to do something to help my friend, along with my AAPI peers struggling with cultural pressures. 

That’s when I founded SchoolSight: A Comprehensive Mental Health Vision, which is dedicated to raising awareness about mental health issues and reducing the cultural stigma within my Westchester County community. Through fundraisers, speakers, and wellness spaces for students to share their experiences, we work to shatter the silence Emma and so many others face. Instead of waiting for adults to prepare psychoeducation for us students, we students developed presentations for parents in the community, outlining mental health challenges AAPI youth face.

Two years ago, I gave a talk at a national mental health convention to discuss Emma’s journey. Since then, I’ve shared our story at numerous events, allowing me to advocate for the mental health needs of AAPI youth.

Today, I am pleased to share that Emma is thriving. With access to  culturally competent mental health care , she found the support she needed. She also began her own journey of  self-advocacy  to help communities invest in their most valuable, yet traditionally overlooked stakeholders: those with firsthand experience.

While self-advocacy and storytelling are vital, they alone won’t bring meaningful change. Nor is it our responsibility as youth to create the conditions in which our mental health is taken seriously and treated effectively. Everyone who cares about our well-being, including schools and the mental-health establishment, must work to ensure AAPI youth — and all young people — have access to culturally competent mental health care, safe spaces online and offline to connect with and support each other, better training in coping mechanisms and managing stress, and more. Publicizing our stories is an important step in moving in that direction.

By speaking out, we forge pathways to a more inclusive and empathetic understanding of mental health. It is equally important to seek help when needed. Whether it is reaching out to a trusted friend, family member, or mental health professional, taking that first step can make a difference. By advocating for ourselves and seeking support, we pave the way for future generations to inherit a society that recognizes and respects the full spectrum of mental health needs across racial and cultural lines.

Rick Yang, a native of Scarsdale, is a first-year student at Harvard University.

ANT 251 Global Health Inequalities

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