research papers on health inequalities

• Open access
• Published: 10 March 2021

Measuring health inequalities: a systematic review of widely used indicators and topics

• Sergi Albert-Ballestar 1 , 2 &
• Anna García-Altés   ORCID: orcid.org/0000-0003-3889-5375 1 , 2 , 3  

International Journal for Equity in Health volume  20 , Article number:  73 ( 2021 ) Cite this article

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According to many conceptual frameworks, the first step in the monitoring cycle of health inequalities is the selection of relevant topics and indicators. However, some difficulties may arise during this selection process due to a high variety of contextual factors that may influence this step. In order to help accomplish this task successfully, a comprehensive review of the most common topics and indicators for measuring and monitoring health inequalities in countries/regions with similar socioeconomic and political status as Catalonia was performed.

We describe the processes and criteria used for selecting health indicators from reports, studies, and databases focusing on health inequalities. We also describe how they were grouped into well-known health topics. The topics were filtered and ranked by the number of indicators they accounted for.

We found 691 indicators used in the study of health inequalities. The indicators were grouped into 120 topics, 34 of which were selected for having five indicators or more. Most commonly found topics in the list include “Life expectancy”, “Infant mortality”, “Obesity and overweight (BMI)”, “Mortality rate”, “Regular smokers/tobacco consumption”, “Self-perceived health”, “Unemployment”, “Mental well-being”, “Cardiovascular disease/hypertension”, “Socioeconomic status (SES)/material deprivation”.

Conclusions

A wide variety of indicators and topics for the study of health inequalities exist across different countries and organisations, although there are some clear commonalities. Reviewing the use of health indicators is a key step to know the current state of the study of health inequalities and may show how to lead the way in understanding how to overcome them.

Introduction

Strong efforts to tackle health inequalities can be seen at international and national level since the 1980s. In early 2008, the World Health Organization’s (WHO) Global Commission on Social Determinants of Health called for action on the social determinants of health, the conditions in which persons are born, grow, work, live, and age, to “close the gap in a generation” [ 1 ]. In late 2008, the Spanish Public Health General Direction ( Dirección General de Salud Pública) and the Foreign Health of Health Ministry and Social Policy ( Sanidad Exterior del Ministerio de Sanidad y Política Social ) requested the constitution of the Commission for the Reduction of Social and Health Inequalities ( Comisión para Reducir las Desigualdades Sociales en Salud en España (CRDSS-E) [ 2 ]. The mission of CRDSS-E was to elaborate on a proposal of intervention measures to reduce health inequalities. The CRDSS-E published two documents: one analysing health inequalities in the Spanish context [ 3 ], and another describing some policy proposals to tackle them [ 4 ]. In 2011, a total of 125 countries, Spain being one of them, developed and signed the Rio Political Declaration on Social Determinants of Health [ 5 ]. The declaration recommended interventions from governments and international organisations [ 6 ].

At a regional level in Catalonia, tackling health inequalities is one of the main goals of both the Catalan Health Plan 2016–2020 (led by the Health Department of the Catalan Government) [ 7 ] and the Interdepartmental and Intersectorial Public Health Plan 2017–2020 (PINSAP) [ 8 , 9 ]. During the past years, various reports and peer-reviewed papers about the health effects of the economic crisis on the population of Catalonia were published by the Catalan Health System Observatory [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ].

Overall, much effort has been devoted to monitoring and tackling health inequalities at regional, national, and international levels. Even so, OECD countries continue to present large disparities in health, including, for example, significant differences in life expectancy between people with the highest and lowest levels of education [ 18 ]. The selection of topics represents the first step in monitoring health inequalities according to many conceptual frameworks and is highly relevant, as these topics will potentially limit the detection of health inequalities within the population, hence playing a key role in providing evidence for posterior decision-making [ 19 , 20 ]. Yet some difficulties may arise during the selection of relevant topics, as well as their health indicators. A wide diversity of indicators for monitoring health inequalities have been used across different countries and organisations; this is due to the high variety of contextual factors that may have an influence on it, such as the study goals or the information resources available.

In order to help accomplish this task successfully, the objective of this study is to perform a systematic review of the most common topics and indicators used for measuring and monitoring health inequalities in the reports, projects, and databases of international, national, and regional governmental organizations.

The main purpose of this study is to provide a broad overview of health inequalities topics considered relevant by different public health organizations. Nevertheless, the focus of this review is on countries/regions with similar socioeconomic and political status to Catalonia. It may also be useful for other organizations who decide to study or monitor health inequalities to accomplish its very first step: topic selection. In addition, gaining some insights about which health issues are being prioritized, as well as which indicators were used, are considered secondary goals.

Material and methods

First, a bibliographic search was performed using PubMed, Google Scholar, and Google search engine with the terms “ health inequalities ”, “ health observatories ” and “ health inequalities indicators ”. Occasionally, names of concrete regions, countries, or organisations were added to these terms (i.e., “ Andalucía health observatory ” or “ Canada health inequalities ”). The search was performed from March to June of 2019. Once finished, a set of inclusion criteria was applied; studies included in the review had to:

Include health inequalities indicators : All the reports that contained no health indicators were automatically discarded (i.e., policy frameworks [ 21 ]).

Have been carried out by a governmental organisation or a related entity, whether at an international, national, or regional level : the reports not published by governmental (or government-related) organisations were discarded.

Have a socioeconomic and political status similar (or highly related) to Catalonia : some reports were discarded due to significant differences in the socioeconomic profile of the countries they were studying in comparison to Catalonia or Spain.

Once the reports were selected, the authors performed a quality control check of the indicators shown in the reports and databases. The indicators had to match the basic anatomy of an indicator as a minimum requirement to be considered an indicator. This basic anatomy consists of containing data, i.e. the numerical data input; and containing good metadata, like a title and an explanation of how an indicator is defined and calculated [ 22 ]. In addition, the different reports found were classified according to the geo-political region they were studying: 1. international, 2. national, and 3. regional (Table  1 ).

After this selection process, the indicators were grouped into topics by semantic matching of their definition as well as by the area of knowledge there are intended to measure. Most of the topics were supported by references of relevant organisations like the WHO or the United Nations (UN) (see Table  2 ). Each topic was uniquely named in accordance with the area of knowledge that instruments were intended to measure. Indicators from different sources were often merged due to high similarities between them (most commonly, the only differences were stratifiers such as age, gender or region). Every topic had to be formed by at least five indicators in order to be considered relevant enough; the topics with less than five indicators were discarded.

The search was performed by the two researchers, and the results shared in order to agree on any discrepancies. All the data was organised in spreadsheets to identify common indicators, and then sorted by the amount of indicators they included. The names of the indicators in the spreadsheets were those given in the original reports or their metadata information.

In total, 21 reports, projects, and databases were identified and classified into three categories: 1. international [ 8 ], 2. national [ 10 ], and 3. regional [ 3 ]. In the first category, international, all the projects selected were carried out or funded by the European Commission [ 23 , 24 , 25 , 26 , 27 ], the WHO [ 28 , 29 ] or the World Bank [ 30 ]. In the following category, national, studies were conducted by health agencies or governments of countries such as Andorra [ 31 ], Australia [ 32 ], Canada [ 33 , 34 ], England [ 35 , 36 ], Scotland [ 37 ], Slovenia [ 38 ], Spain [ 39 ] or Portugal [ 40 ]. In the last category, regional, some reports published by Spanish regions were included (Andalucía [ 41 ], Barcelona [ 42 ], Valencia [ 43 ]). A total of 691 health indicators were identified (Table 1 ).

Following an iterative process of evaluation, we identified a core set of 120 candidate topics, of which 34 were finally selected (Fig.  1 ). Table 2 describes a complete list of 34 topics with the corresponding definition of each topic. The ten most commonly used were: “Life expectancy”, “Infant mortality”, “Obesity and overweight (BMI)”, “Mortality rate”, “Regular smokers/tobacco consumption”, “Self-perceived health”, “Unemployment”, “Mental well-being”, “Cardiovascular disease/hypertension”, “Socioeconomic status (SES)/material deprivation”. However, some topics that ranked below these were closely related with some of the most common topics; for example, “Perinatal, neonatal and stillbirths mortality” might be considered as a subtype of “Infant mortality”; and “Perceived mental health” is similar to both “Mental well-being” and “Self-perceived health”. Furthermore, some indicators may represent antithetically the same area of knowledge; that is the case for the indicators in the topic “Long-term limitations/chronic illnesses” and the indicator “Healthy Life Years (HLY)” [within the topic “Life expectancy”], where the former (long-term limitations or chronic illnesses) is used to determine the latter (the end of a healthy life condition). Nevertheless, the metadata of the health indicators within each topic was highly homogeneous: they all had similar definitions and methodology.

Flowchart of the processes undertaken to review the most common topics in the study of health inequalities

In general, the indicators within each topic were very similar. In fact, often the differences among them were related to the different stratifiers (such as sex, age or region) used for their calculation. For example, in the first topic “Life expectancy”, indicators have different variations: “Life expectancy at birth” [ 23 , 24 , 25 , 27 , 28 , 29 , 32 , 33 , 37 , 40 , 41 , 42 ], “Life expectancy at birth by sex” [ 22 , 24 , 25 , 26 , 27 , 33 , 34 ], “Life expectancy at a certain age” [ 25 , 33 , 35 , 40 ], “Life expectancy by educational attainment level” [ 25 ], and “Life expectancy at birth by socioeconomic status” [ 25 ]. Complex measures of inequality, such as “Slope index of inequality (SII) for male and female life expectancy” [ 34 ] may be considered another (more advanced) variation.

Furthermore, in the case of a health outcomes or diagnostics (such as mortality or cancer) the concrete disease or cause may also play an important role in the heterogeneity found among the health indicators. Indicators are focused on different aspects, such as prevalence and incidence, mortality, preventive measures, or treatments. For example, for the topic “HIV”: “HIV incidence” [ 23 , 26 , 28 , 33 , 40 ], “Prevalence of HIV, male/female, by ages” [ 29 , 39 ] and “AIDS-related mortality rate” [ 28 , 39 ] are the most common, yet “Antiretroviral therapy (ART) coverage” [ 28 ] and “HIV test results for TB patients (positive results)” [ 28 ] can also be relevant.

The results of the study show that the most common topics are related to:

Mortality/life expectancy: “Life expectancy” [ 44 , 45 ], “Infant mortality” [ 46 ] or “Mortality rate” [ 47 ] are widely used to study health inequalities.

Incidence/mortality rates of specific diseases: “Cardiovascular disease/hypertension”, “Cancer (incidence or mortality)” [ 48 ], “Diabetes/insulin resistance” [ 49 ], “HIV” [ 50 ], “Tuberculosis (TB)” [ 51 ] or “Respiratory diseases”.

Social determinants of health [ 52 ]:

◦ “Living and working conditions” where this could be studied at an individual level, was highly ranked: “Unemployment” [ 53 ] and “Primary studies/illiteracy”. Otherwise, these indicators were at the bottom of the list.

◦ This was similar for “Individual lifestyle factors and social and community networks” topics, which can also be studied at an individual level: “Obesity and overweight (BMI)” [ 54 , 55 ], “Regular smokers/tobacco consumption” [ 56 ], “Alcohol consumption” [ 57 ], “Hazardous alcohol consumption”, “Physical activity” [ 58 ], and “Food consumption (vegetables, fruit, salt)”.

◦ Socioeconomic level: “Socioeconomic status (SES)/material deprivation” [ 59 , 60 ].

◦ Healthcare system: “Healthcare resources” and “Policy and Legislation”.

Main results of the study

The results of the study showed that the most common topics were related to mortality/life expectancy, incidence/mortality rates of specific diseases (i.e., TB or HIV), and social determinants of health, such as living and working conditions, and individual lifestyle factors and social and community networks, according to Dahlgren and Whitehead’s model of the social determinants of health [ 52 ]. The indicators that can be studied at an individual level tended to be highly ranked, in comparison to those that are studied at different levels (such as hospital or region), which tended to be at the bottom. Many methodological differences between indicators were due to stratifiers in their calculation.

Study selection criteria

To include health inequalities indicators was a fundamental requirement for any report in order to be included in the review. Hence, although some reports provided in-depth insights about tackling health inequalities (i.e., [ 21 , 61 ]) they were not selected due to lack of health indicators monitoring.

In addition, to be carried out by a governmental or a government-related organisation was also an important requirement, as many academic and/or private institutions carry out studies and reviews of health inequalities, but their policy-making influence is limited. Their reports tend to be focused on concrete knowledge fields, such as gender influence [ 62 ], the effects of economic crises [ 63 ], or access to healthcare [ 64 ]; which are also relevant for the study of health inequalities but whose authorship does not fit the selection criteria, as the main interest of this paper is identifying the health inequalities indicators used by health agencies or similar government-related entities. The reports not produced by this kind of organisation were rejected.

Lastly, to have a socioeconomic and politic status similar or highly related to Catalonia criteria was intended to exclude reports whose health indicators were adapted to least developed/developing countries where, for example, access to treatments of diarrhea for infants may still be an issue [ 65 ]. Hence, some reports were discarded due to significant differences in the socioeconomic profile of the countries they are studying in comparison to Catalonia or Spain.

These criteria were applied to all the reports and studies found after an extensive search. The addition of country/region names in the search responded to the need of knowing how particular regions of interest were dealing with health inequalities. Interest in regions was mainly based on previous knowledge of concrete public health organizations studying those regions, as well as interest in looking for other organizations in charge of tackling health inequalities in regions similar to Catalonia. Nevertheless, as in any review, it is not possible to ensure that absolutely all the reports suitable for this study were found during the search, nor that they were selected after applying the selection criteria.

Grouping health indicators into topics

As stated above, the most frequent health indicators were grouped into topics according to the health domain they were measuring (with each indicator related to only one topic). For example, although “ Percentage of 15-year-olds who were overweight in 2009–10, EU Member States by sex ” [ 25 ] and “ Obesity rate by body mass index (BMI) (sdg_02_10) ” [ 23 , 66 ] are different indicators per se, they are both intended to measure the same health issue and, hence, were grouped under the same topic “Obesity and overweight (BMI)” under the indicator name “Obesity and/or overweight (total, by sex, age, or educational level)”.

Most of the selected health indicators were taken from the official statistics of different countries or international organisations, whose development and methodology has been closely consolidated over many years and respond to international standards. In addition, most of these indicators are related to relevant knowledge areas for the study of health inequalities, such as lifestyle habits, deprivation, and mortality .

To prioritise the most relevant topics, all the groups with less than five health indicators were deleted. This meant that, unfortunately, interesting topics such as the “Years of potential life lost” [ 34 , 36 , 42 ], “Unmet health needs” [ 23 , 26 , 39 ] and “Passive smokers” [ 33 , 34 ] were not taken into consideration. Nevertheless, this selection does not imply per se a periodic monitoring of the selected health indicators, as specific topics not present in this list may be studied according to ultimate needs.

Relevance of the most common topics

All the topics aim to measure and study the relation between determinants of health and health outcomes. Interestingly, three of the top five topics in the list (see Table 2 ) are related to mortality: life expectancy, infant mortality, and mortality rate. Life expectancy at birth is an indicator of mortality conditions and, by proxy, of health conditions [ 44 ]. Hence, life expectancy as well as other mortality-related topics are widely used in the study of health inequalities.

Living and working conditions, such as BMI or smoking, are also key factors in the study of health inequalities as both share a strong socioeconomic gradient [ 54 , 56 ]. Therefore, as may be expected, they appeared among the top 10 positions in the list of topics (see Table 2 ). According to our review, the most common way to measure socioeconomic status is to analyse the unemployment rates and material deprivation level of the population.

In Spain, some regions use less common health indicators for studying health inequalities that may be interesting for particular knowledge areas. For example, the Valencian Observatory of Health uses the “Caregiver profile”, which they report to be mostly women, without primary studies, 57-years-old on average, and reporting bad self-perceived health. In addition, they also use “Reasons why contraceptive methods are not used by age and nationality of women” as well as a “Sexual-health information resources (school, parents, friends, etc.)”, which may help to understand possible sexual health inequalities [ 43 ]. In the Andalusian School of Public Health, the indicator “Psychosis and mental illnesses due to drugs or alcohol abuse” may be helpful to estimate various negative health outcomes of alcohol and substance abuse that the healthcare system will need to address [ 41 ]. Even so, more than a half of topics in Table 2 appear in their reports.

As may be expected, the health indicators used in other reports produced by the Catalan Health System Observatory, such as the “Community Health Indicators”, match the implicit measurement concept behind many of the topics: obesity and overweight, mortality by age (including infant), self-perceived health, and population with primary studies are some of them [ 67 ].

• Health indicators

As can be seen in Table  3 , health indicators were combined within each topic if stratifiers such as population sex, age, or region were the only difference in their calculation methodologies. Some indicators were also merged if they were formerly different in the way they expressed the same data (i.e., raw number, rate per 1000 or 100,000).

The health indicators within each topic often cover a different aspect relevant to health inequalities. For example, in the topic “Tuberculosis” [ 23 , 29 , 33 , 34 , 40 , 42 , 43 ] indicators about incidence, prevalence, or mortality can be observed. In addition, health indicators about treatment coverage or vaccination are also included in this topic. Overall, in most topics, indicators try to measure every relevant (and measurable) aspect of the topic.

Common stratifiers are sex, age, and studied region, something that is coherent with the determinants of health perspective and the focus on inequalities. However, the stratifiers found are highly heterogeneous and may also include socioeconomic status, educational level, or nationality/country of origin, among many others.

Research fitted to monitor health inequalities

This comprehensive review was carried out to help accomplish the first step in the process for tackling and monitoring health inequalities: selecting high-impact issues and health indicators [ 19 , 20 ]. The next steps in the analysis will be to carefully take into account stratifiers such as area of residence, gender, age, and nationality. Lastly, after the identification of key health inequalities, decision-making stakeholders will need to play a role during the last steps: determining priorities of action and implementing changes. The time variable will play a key role in the monitoring, as it will indicate the possible health consequences of policy-making decisions [ 19 , 20 ].

Reviewing the most common health indicators and topics used in the study of health inequalities may help research teams in different ways. First, having an overview of what is being done by their neighbouring countries or regions may highlight issues that should not be missed when selecting relevant health topics to study. Second, even if some topics might not ultimately be chosen as a priority of action, having a complete list of key issues will provide an overview of what is relevant in the study of health inequalities, as well as some interesting insights. Lastly, knowing what other research institutions are working on will promote potential collaborations between organizations, creating synergies and bonds that may lead to better understanding and monitoring of health inequalities.

At a regional level, these results are highly valuable for the first stages of health inequalities monitoring cycles in Catalonia. This study provided the basis for choosing health topics to study as well as helped gain insights about which indicators should be used. In addition, regions with similar socioeconomic status and goals in tackling health inequalities may benefit from this research. Similarly, at a national and international level these results may help organizations shift the focus towards undermined health inequalities topics or explore new areas of knowledge (yet unstudied or with a different perspective).

Availability of data and materials

No analysis of quantitative data was performed. Hence, data availability declaration is not applicable.

Abbreviations

Acquired immune deficiency syndrome

Acute myocardial infarction

Bacillus Calmette-Guérin

Body mass index

Chronic obstructive pulmonary disease

Comisión para Reducir las Desigualdades Sociales en Salud en España

Cardiovascular disease

European Core Health Indicators

12-Item General Health Questionnaire

General practitioner

Human Immunodeficiency Virus

Healthy Life Years

International Classification of Diseases, Clinical Modification

International Health Regulations

National Health Service

Portable document format

Public Health Agency of Canada

Interdepartmental and Intersectorial Public Health Plan

Percutaneous transluminal coronary angioplasty

Sustainable Development Goals

Socioeconomic status

Slope index of inequality

Tuberculosis

Uniform resource locator

United Nations

World Health Organization

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Acknowledgements

We thank Neus Carrilero-Carrió (Agència de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS), Barcelona, Spain) for support in reviewing drafts and assistance with writing.

All the activities performed were funded by the Agència de Qualitat i Avaluació Sanitàries de Catalunya (AQuAS) and CIBER de Epidemiología y Salud Pública (CIBERESP).

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SA performed the main bibliographic review as well as the selection and organisation of health indicators and topics. AGA supervised the whole process, contributed to the conceptualisation of the paper and provided extensive comments and improvements to the drafts. The author(s) read and approved the final manuscript.

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Albert-Ballestar, S., García-Altés, A. Measuring health inequalities: a systematic review of widely used indicators and topics. Int J Equity Health 20 , 73 (2021). https://doi.org/10.1186/s12939-021-01397-3

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Transforming health systems to reduce health inequalities

Sarah sowden, jasmine olivera, clare bambra, alex gimson, rob aldridge, carol brayne.

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Address for correspondence: Dr John Ford, Forvie Site, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK. Email: [email protected] Twitter: @johnford1849

Never before in history have we had the data to track such a rapid increase in inequalities. With changes imminent in healthcare and public health organisational landscape in England and health inequalities high on the policy agenda, we have an opportunity to redouble efforts to reduce inequalities.

In this article, we argue that health inequalities need re-framing to encompass the breadth of disadvantage and difference between healthcare and health outcome inequalities. Second, there needs to be a focus on long-term organisational change to ensure equity is considered in all decisions. Third, actions need to prioritise the fundamental redistribution of resources, funding, workforce, services and power.

Reducing inequalities can involve unpopular and difficult decisions. Physicians have a particular role in society and can support evidenced-based change across practice and the system at large. If we do not act now, then when?

KEYWORDS: health inequalities, equity, health systems, healthcare organisations

Introduction

For the first time in history we have the empirical data to witness a rapid compounding of existing inequalities due to the COVID-19 pandemic, particularly for lower socio-economic and minority ethnic groups. 1,2 In the UK, deaths in the most deprived areas are double those in the least deprived (age–sex standardised rate in the least deprived areas are 350 deaths per 100,000 compared with 669 in the most). 3 In the USA and UK, deaths are up to three times higher in minority ethnic groups. 4 The current crisis represents a syndemic pandemic; the intertwined, interactive and cumulative effects on health and wellbeing of the COVID-19 pandemic combined with substantial existing socio-economic inequalities across life courses and in communities. 2

Despite the policy prominence and various frameworks focusing on health inequalities, healthcare leaders still do not feel they have the skills and knowledge to reduce health inequalities. 5–9 The underlying reasons for this may include a failure of researchers to provide accessible evidence on how to translate evidence into practice as well as a lack of a systematic and logical approach to inequalities for healthcare systems. 10–12 Physicians have a particular role in society and can support evidence-based change across practice and the system at large. Here, we first discuss the current policy and research context, then argue it is time for a re-framing of inequalities within healthcare systems, with a concerted effort to build a long-term organisational change to tackle inequalities head on, along with a wider redistribution of resources, funding, workforce, services and power across healthcare and wider society.

Policy, research and legislative context of health systems in the UK

In England, for the first time, key national and local NHS decision-making bodies were required by law to address inequalities in access and outcomes under the Health and Social Care Act 2012. 13 This was the result of a growing body of literature showing sustained stark health outcome inequalities, dating back to the Black report, with inequalities in waiting times, patient experience and hospital admissions. 14–17 The Health and Social Care Act also shifted power from ministerial departments to NHS England with a decentralisation of decision making to local health systems. Despite the statutory responsibility, the years after the enactment of the Health and Social Care Act were dominated by reorganisation with considerable fragmentation of previously aligned services. Reforms were undertaken in the name of efficiency with poor evidence of their impact, rising costs to the health system and little progress on health inequalities, despite the clear negative health and wellbeing impacts of austerity and welfare reform. 18,19 Public health professionals classified the risk of this reorganisation to widen health inequalities as ‘extreme’. 20

In 2019, the NHS in England was asked to develop its own plans for a £20 billion funding injection. High-level policy objectives and initiatives were outlined in The NHS Long Term Plan and, in turn, local healthcare systems were asked to develop their own local response plans. 21 Health inequalities were a prominent feature of the national The NHS Long Term Plan among other priorities, such as primary care workforce, integration, prevention, cardiovascular disease and cancer. The plan set out to establish a ‘more concerted and systematic approach to reducing health inequalities’ alongside a number of specific inequalities initiatives such as supporting minority ethnic groups. However, the plan and its subsequent supporting documents failed to outline how local and national systems could systematically approach health inequalities with an expectation that local healthcare systems would each develop their own approaches. Our own previous research has highlighted that this is challenging for local systems, resulting in local plans being vague and lacking a systematic or joined-up approach. 12 Furthermore, the lack of a national health inequalities strategy (like that successfully pursued between 2000 and 2010) makes it harder to effect change across local health systems. 22,23

In response to COVID-19 inequalities data, NHS England and NHS Improvement (NHSE/I) published eight urgent actions to address health inequalities, including directives protecting the most vulnerable, improving recording, strengthening leadership and increasing preventative measures. 24

The structure of the NHS has moved substantially from its inception, through many re-disorganisations and, lately, the statutory bodies established under the Health and Social Care Act 2012. More recently, integrated care systems have been established, which are likely to merge with clinical commissioning groups. 25 It is likely that further health and social care legislation, under the advice of NHSE/I, will be passed in the near future to catch up with the organisational evolution. 26

Only 7 years after its formation, Public Health England (PHE) is already being disestablished. PHE was set up to protect and improve the nation's health and reduce health inequalities. 27 One action of the Health and Social Care Act was the extraction of public health skills from leadership roles within the NHS, something that was an obvious gap immediately after revealing a lack of understanding of the key role of public health leadership and skills in health and social care systems. This has become critical during the COVID-19 pandemic, as more public health leadership in the health and social care system may have improved the response.

Health inequalities have been a common thread across PHE activities. While trying work across organisational boundaries, these have included the provision of data on health inequalities, guidance, evidence-based tools for local health systems, advice to national government and focused action on inequalities in screening and immunisations. 5 , 28–31 PHE have particularly promoted a place-based approach to inequalities. 5 Under current plans PHE's health protection functions will be taken over by the National Institute for Health Protection, but the future location of the other PHE functions is still under discussion.

The research community has been driving forward the inequalities' agenda. The Academy of Medical Sciences published their report Improving the health of the public by 2040 promoting a health of the public research approach with a strong emphasis on health equity. 32 In response to this, the Strategic Coordination of the Health of the Public Research committee (SCHOPR) was established and has set out its guiding principles on population research, including a priority of focused investigation into how interdisciplinary research can reduce inequalities. 33 Furthermore, the Academy of Medical Sciences has recently written to the secretary of state outlining the need to prioritise prevention and improvement to reduce inequalities. 34

More recently, the Royal College of Physicians have convened a coalition of over 140 organisations to campaign for a cross-government strategy to reduce inequalities, the commencement of the socio-economic duty in the Equality Act and prioritising child health in public policy. 35

With the healthcare and public health reform afoot, inequalities highlighted due to the pandemic are thus high on the policy agenda, and a mobilised research community, it is time to rethink our approach to inequalities within and beyond the healthcare system. Without clarity, sufficient prioritisation and leadership any actions are at risk of only ever having a marginal impact.

Framing inequalities to ensure a systematic and logical approach in health systems

Framing is a way of structuring or presenting a problem and can be helpful, potentially vitally so, to ensuring action. 36 How we discuss and present inequalities must be developed with and for any audience it is hoped might contribute to effective changes; for example, NHS staff are more likely to engage if inequalities are framed around healthcare and the specific services for which they are responsible, such as inequalities in chronic disease management or non-elective admissions alongside concrete actions, rather than high-level more abstract health outcome inequalities, such as differences in life expectancy. 37 A lack of adequate framing brings risks. Focusing only on high level inequalities with healthcare staff, such as life expectancy, may lead to a sense of fatalism because these inequalities are primarily driven by geo-political factors outwith the influence of local health systems and their leaders; or a belief that downstream individual actions targeted at the social determinants of health will reduce inequalities. 38–40 In turn, these may lead to a health inequalities fatigue where motivation for action on inequalities wains due to short-termism and a perceived lack of progress.

A broad framing of inequalities highlighting how multiple different aspects of disadvantage lead to substantial differences in healthcare and health outcomes is needed to allow decision-makers to develop their own systematic and logical approach to doing what is within their power and advocacy to reduce inequalities. Without this systematic approach, there is a risk of an unequal focus on certain groups at the expense of others, such as focusing on the so-called ‘deserving poor’ at the expense of the ‘undeserving poor’. 41 Our review of local NHS plans revealed that systems focused more on people with learning difficulties and autism, but less so on undocumented migrants, people who are transgender or those with justice service involvement. 12 This creates inequalities within inequalities.

Inequalities must be framed and measured to include both healthcare (eg risk factor management, access, diagnosis, treatment and experience) and health outcome (eg morbidity and mortality) inequalities (Fig 1 ). Key components across the spectrum of health and care include the distribution of health system resources (namely funding, workforce and research distribution, and training), access to and quality of healthcare, major drivers of mortality and morbidity (eg cardiovascular disease, respiratory disease, cancer, mental health and musculoskeletal conditions) and conditions which are intrinsically associated with inequalities (such as drug and alcohol abuse).

Unpacking health inequalities.

Framing should avoid language which is stigmatising or shaming. Smith and colleagues describe a paradox where people recognise that health is determined by social factors and acknowledged socio-economic inequalities in society, but are reluctant to acknowledge the resulting health inequalities. 42 The authors suggest this paradox arises because individuals do not want the place in which they live to be stigmatised, shamed, or have negative or derogatory connotations, which may have negative impacts on their employment opportunities or family. 43 Other studies have found that the idea of socio-economic health inequalities can be a source of stress for residents. 44,45

Building the long-term organisational change

Many health inequalities have arisen over decades and even centuries, operating across generations and communities, due to long-standing imbalances in the social determinants of health. It is noteworthy that the north-south pattern of deaths from the Spanish flu pandemic of 1918, almost exactly mirrors the distributions of COVID-19 deaths over a century later. 46 New manifestations of inequalities emerge over time, often with the promise of solutions and enthusiasms from new technologies. Previously this was the offer of screening, known to be taken up preferentially by more advantaged in society, and more recently in access to digital healthcare services with clear differential access. 47 In light of the plethora of existing and emerging inequalities, many feel a moral duty to ‘do something’, including investments in actions that lack a strong evidence base or sustainability (such as social prescribing or hospitals acting as anchor institutions). 48 It is important, therefore, for the NHS to resist the temptation to reach for such short-term actions at the expense of focusing on the long-term organisational change required for sustained and evidenced-based action. With the formation of integrated care systems in the NHS in England we have the opportunity to ensure an equity perspective is adopted from the start, maximising the opportunities of integrated working across health and social care. However, we need inequalities actions at all levels of healthcare, including national, system, organisational and individual (Fig 2 ).

Levels of health inequalities actions.

Much health data, particularly within hospitals, is not presented by socio-economic group, geographical disadvantage or ethnicity. The NHS eight urgent actions to address inequalities aims to improve ethnicity recording. 24 More upskilling is needed to help healthcare analysts undertake equity analyses to explore the difference between groups, adjusting for age and gender where appropriate. Equity perspectives are still rarely considered in healthcare quality improvement programmes, clinical audits, service evaluation or adverse events investigation; for example, hospital-based quality improvement programmes should consider if the services changes improve quality of care across socio-economic groups and ethnicity equally. Adverse event investigations should include an exploration how healthcare supported (or not) patients who are disadvantaged, for example due to poor health literacy or social support, interacted with services.

Previous research suggests that equity-focused processes can support healthcare organisations, their teams and individuals within these to address inequalities. 49 Health inequalities impact assessment is a process of exploring and mitigating the impacts of decisions on inequalities during decision making. Sadare and colleagues found that health inequalities impact assessment, if undertaken a meaningful way, can be a catalyst for equity-focused organisational change. 49 These could be used by clinical directors and hospital leaders to ensure that secondary care services do not increase inequalities.

Applied research has an vital role to play in exploring the distributional effects of interventions across disadvantaged groups and generating evidence of what works to reduce inequalities. 50,51 The evidence produced by current research poorly represents those who are most disadvantaged. The SCHOPR principles call for co-produced, transdisciplinary research to create and deliver targeted national and local solutions to reduce inequalities. 33 More research is needed to develop and understand the implementation of evidence-based solutions drawing upon disciplines such as geography, anthropology, sociology, economics and history. Research capacity and skills must be embedded in the organisations which emerge from the latest restructure to help them become learning systems.

Redistributing resources and power to prevent illness and promote health

Inequalities are caused by the unequal distribution of social determinants of health, public and private investment, public sector workforce, services and power (the ability of one section of society to control another). 52 Without a fundamental change to how society can organise itself to address these, inequalities in health outcomes will persist. However, even within the way we organise ourselves currently and contrary to the sense that nothing can be done, there is evidence that the NHS can reduce inequalities. One example is an analysis of the increase of NHS resources to more deprived areas between 2001 and 2011, revealing a reduction in inequalities from causes amenable to healthcare. 53 This complements the principle of proportionate universalism, which states services should be accessible to all, but the intensity of the service should be proportionate to need with the most disadvantaged receiving more resources (Fig 3 ). 14 While existing national NHS allocation formulae are weighted for deprivation, evidence suggests they do not go far enough; and, in England, the weighting was reduced after the 2011 Act. 54

Distributing resources proportionate to need.

Beyond specific healthcare system evidence, there is also good evidence that cross government action can reduce inequalities. 22,23 Over the last couple of decades, there has been a natural experiment at a national scale. The UK government implemented a cross-government health inequalities programme and strategy from 2000 to 2010. Prior to the start of the programme, the difference in life expectancy between the most deprived areas and the rest of England was increasing by 0.57 months per year for males and 0.30 months per year for females. 22 The strategy reversed these trends with the gap in life expectancy reducing by 0.91 months per year for men and 0.50 months per year for women. Inequalities in the infant mortality rate (IMR) also decreased. 23 However, since the end of the strategy and the implementation of austerity, the inequality gap widened again by a similar amount as before and there is now evidence of increasing inequalities in IMR associated with rising rates of child poverty. 23 Key to the programme was a redistribution of funding, services and power to poorer areas, with regeneration initiatives, Sure Start centres to support early years childcare, increased NHS funding allocations, introduction of national minimum wage, more generous tax and benefit changes targeted at child poverty and targeted services in the most deprived local authorities. Unfortunately, detailed independent evaluation was not embedded or undertaken, and therefore the specific factors, either individually or collectively, which contributed to the observed narrowing inequalities gap remain unknown.

The importance of prevention and health promotion has been highlighted in several key documents. 24,34 The irony is that the under the Health and Social Care Act, public health was taken out of the NHS, but the current The NHS Long Term Plan prioritises prevention. Greater clarity is needed to ensure that the manner in which this emphasis is implemented does not unintentionally widen the gap. 55,56 For example, those with the resources and capabilities to benefit from an untargeted physical activity campaign have been and already are the more affluent groups with financial resources, health literacy and employment flexibility. This is also replicated within our research programmes and recruitment, which in many clinical research spheres do not represent diverse and disadvantaged communities. Policy makers should avoid the temptation to think that unhealthy lifestyles in people living in poorer areas arise because of a lack of knowledge or motivation and that the solution is information campaigns. 52,57 Decades of research reaching has demonstrated again and again that people, whether from poor or rich backgrounds, understand the determinants of health and have logical reasons for unhealthy choices. 57 For example, Graham found that pregnant women on low incomes still found money to buy cigarettes because smoking was the one opportunity in the day to do something for themselves in the context of very challenging life circumstances. 58 More recently, Thirlway found that smoking cessation was shaped by (lack of) social mobility. 59 To prevent illness and promote health we must break down the power hierarchies which suggest that one part of society knows what is best for another and get alongside people to understand why they act the way they do, treating them as experts in their lived experience, co-designing solutions as equal partners and advocating for the wider societal changes needed to address the social and economic context of inequality. 60

We all have an ethical and moral imperative to respond to the rapid proliferation of existing inequalities. Simultaneously, healthcare and public health organisations are being re-structured in England. We argue that the concept of health inequalities needs to be reframed to acknowledge the breadth of health and care inequalities with non-stigmatising language to ensure a systematic approach to the problem. A focus on building long-term equity-orientated organisational change in the NHS is urgently needed. At the core of any action should be the fundamental redistributions of resources, funding, workforce, services and power. If we do not act now in light of these stark inequalities, then when?

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Systematic review of the effectiveness of the health inequalities strategy in England between 1999 and 2010

Ian holdroyd, alice vodden, akash srinivasan, clare bambra, john alexander ford.

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Correspondence to Dr John Alexander Ford; [email protected]

Corresponding author.

Series information

Original research

Received 2022 Mar 22; Accepted 2022 Aug 12; Collection date 2022.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

The purpose of this systematic review is to explore the effectiveness of the National Health Inequality Strategy, which was conducted in England between 1999 and 2010.

Three databases (Ovid Medline, Embase and PsycINFO) and grey literature were searched for articles published that reported on changes in inequalities in health outcomes in England over the implementation period. Articles published between January 1999 and November 2021 were included. Title and abstracts were screened according to an eligibility criteria. Data were extracted from eligible studies, and risk of bias was assessed using the Risk of Bias in Non-randomized Studies of Interventions tool.

The search strategy identified 10 311 unique studies, which were screened. 42 were reviewed in full text and 11 were included in the final review. Six studies contained data on inequalities of life expectancy or mortality, four on disease-specific mortality, three on infant mortality and three on morbidities. Early government reports suggested that inequalities in life expectancy and infant mortality had increased. However, later publications using more accurate data and more appropriate measures found that absolute and relative inequalities had decreased throughout the strategy period for both measures. Three of four studies found a narrowing of inequalities in all-cause mortality. Absolute inequalities in mortality due to cancer and cardiovascular disease decreased, but relative inequalities increased. There was a lack of change, or widening of inequalities in mental health, self-reported health, health-related quality of life and long-term conditions.

Conclusions

With respect to its aims, the strategy was broadly successful. Policymakers should take courage that progress on health inequalities is achievable with long-term, multiagency, cross-government action.

Trial registration number

This study was registered in PROSPERO (CRD42021285770).

Keywords: public health, health policy, quality in health care

Strengths and limitations of this study.

This is the first study to synthesise all published studies and grey literature on the health inequalities strategy conducted in England from 1999 to 2010.

This study used a broad search strategy of peer-reviewed and grey literature.

The retrospective nature of studies and lack of counterfactual means that causal claims as to the effect of the strategy cannot easily be made. This resulted in an increased risk of bias of studies.

Introduction

The pandemic has exacerbated societal health inequalities, with higher numbers of COVID-19 related cases and deaths in areas of higher socioeconomic disadvantage and among minority ethnic groups. 1 2 In England, the COVID-19 mortality rate for those under 65 was 3.7× greater in the most deprived 10% of local areas compared with the least deprived. Age-standardised COVID-19 mortality rates were more than twice as high in the most deprived 10% of areas compared with the least. 2

Knowledge of the existence of health inequalities is not new. The first major UK publication describing health inequalities was the Black report in 1980, although health inequalities had been described and debated in the academic literature for decades before that. It was not until 1997, with a newly elected government, that health inequalities became a policy priority. The government commissioned a health inequalities review, subsequently published in 1998 as the Acheson report, and committed itself to implement the evidence-based policy recommendations. 3 Subsequently, a wide-ranging national health inequalities strategy was implemented, with various strategies and aims updated over time. This was the first and most extensive international attempt to address health inequalities through a widespread programme of cross-government action.

Two national documents set out the health inequalities strategy. First, ‘Reducing health inequalities: an action report’ was published in 1999 in response to the Acheson report. It described a wide variety of policies designed to reduce health inequalities: both more ‘downstream’ initiatives, such as increased National Health Service (NHS) funding or the establishment of a National Institute for Clinical Excellence, and more ‘upstream’ policies, such as a national minimum wage, the new deal for employment and increased funding for schools, housing and transport. 4 Second, ‘Tackling health inequalities: a Program for Action’ was published in 2003. 5 It set out 82 cross-departmental commitments, along with 12 headline indicators of the key areas to be monitored. Again, these commitments included a range of ‘upstream’ and ‘downstream’ policies. Other studies have previously summarised the strategy. 6–8 The strategy involved a wide range of policy actions across different sectors. These included large increases in levels of public spending on a range of social programmes (such as the introduction of the Child Tax Credit; SureStart Children’s Centres), the introduction of the national minimum wage, area-based interventions such as the Health Action Zones and Neighbourhood Renewal funds and a substantial increase in expenditure on the NHS. The latter was targeted at more deprived neighbourhoods when, after 2001, a ‘health inequalities weighting’ was added to the way in which NHS funds were geographically distributed, so that areas of higher deprivation received more funds per head to reflect higher health need. 9

The programme for action included two national targets: (1) by 2010, to reduce by at least 10% the gap in infant mortality between routine and manual groups and the population as a whole and (2) by 2010, to reduce by at least 10% the gap between the fifth of areas with the lowest life expectancy at birth and the population as a whole. The ‘areas with the lowest life expectancy at birth and the population as a whole’ were defined by later documents as the ‘Spearhead areas’. 10–12 These 70 local authority areas were identified as being the worst performing local authorities associated with three or more of: male and female life expectancy at birth, cancer and cardiovascular disease mortality rates for the under 75s and Index of Multiple Deprivation (IMD) 2004 scores. These targets were based on relative, rather than absolute, inequalities. 12 13 This is important as debate exists as to which of these is the most appropriate measure of inequality. 3 14 15 Absolute inequalities measure the numerical gap between groups, while relative inequalities measure the percentage difference between groups.

One major criticism of health inequalities research and policy is that there has been too much effort put into describing the problem, rather than finding solutions. The National Health Inequalities Strategy in England 1999–2010 provides a key international example of the latter. It is a high-profile international case study of long term multifaceted government action. Discussions to date of the effects of the strategy have been polarised, with some prominent commentators arguing that it failed, 8 while others have asserted that it was effective. 16 17 This is partly because early evaluations of this health inequalities strategy suggested that it had failed to reach its targets and that inequalities may have increased during this period. 8 10 16 18 However, subsequent research found that this period was associated with a reduction in health inequalities. 6 9 19–21 As governments around the world consider how to respond to inequalities compounded by the pandemic, here we present a systematic review of the studies assessing the effectiveness of this health inequalities strategy.

This systematic review was conducted in accordance with established methodology 22 and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. 23 This systematic review was registered with PROSPERO (CRD42021285770).

Search strategy and selection criteria

Three electronic databases (Ovid Medline, Ovid Embase and Ebsco PsycINFO) were systematically searched from January 1999 to November 2021. The search terms were based in part on previous literature, which identified key search terms to identify studies investigating inequality and inequity 24 and the UK. 25 Online supplemental table 1 presents the search terms. After removing duplicate records, abstracts and titles were screened according to the eligibility criteria by two researchers (IH and AS) using the software Rayyan by December 2021. Discrepancies were resolved by a third researcher (JAF). Each researcher cross screened 20% of the abstracts and titles of the other to ensure accuracy. Three conflicts arose, which were resolved after discussion. A detailed grey literature search of the UK Government Web Archives, specific websites (such as the King’s Fund) and a broad search using an internet search engine (Google) was used. Relevant citations of included studies were also screened.

bmjopen-2022-063137supp001.pdf (144.9KB, pdf)

Inclusion criteria were:

Studies assessing the impact of the health inequalities strategy in England between 1999 and 2010 on inequality in health outcomes in England.

Any form of quantitative study.

Studies reporting primary research.

Studies in any language.

Exclusion criteria were:

Studies whose methodology make it impossible to draw conclusions about the impact of the strategy.

Studies that reported non-health inequalities.

Earlier editions of included reports.

The full text of all articles screened as meeting the eligibility criteria or possibly meeting the criteria were reviewed. The following information was independently extracted from each study by two authors (IH and AV): first author, year of publication, aim, design, data sources, time period of analysis, population, health inequalities measured, main findings and risk of bias. The main outcomes of interest were absolute or relative changes in socioeconomic inequalities in life expectancy and infant mortality in the population of England between 1999 and 2010 to reflect the aims of the strategy. All results compatible with each outcome domain were sought from each study. Secondary outcomes included changes to socioeconomic inequalities in mortality, comorbidities or self-reported health.

Quality assessment

Risk of bias was assessed at a study level using the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tool, which assesses the risk of bias across seven domains. One author (IH) undertook the risk of bias assessment, and this was double checked by a second author (AS or AV) with disagreements resolved by a third (JAF).

Patient and public involvement

Patients were not involved in the design or execution of this study. Nor were members of the public.

Due to the small number of studies with a large amount of data heterogeneity, it was deemed inappropriate to perform a meta-analysis. Instead, studies were synthesised narratively.

After removal of duplicates, the search identified 10 311 unique records. Forty-two were reviewed in full text, and 11 were included in the final review. A flow diagram of the screening and selection process can be found in figure 1 . Six studies contained data on inequalities of life expectancy or mortality, 6 7 9 10 12 19 three on disease-specific mortality, 10 12 26 three on infant mortality 10 13 21 and three on morbidities. 7 20 27 Six studies investigated geographical health inequalities, four investigated health inequalities at an individual level and one had statistics from both measures. Measures of socioeconomic status included income, living in a spearhead area, deprivation, occupation, social class and education. Data were collected between 1983 and 2017 ( table 1 ). Results from these papers are summarised in table 2 . Table 3 shows the risk of bias of each study across seven domains.

Study selection process.

Study characteristics

ONS, Office for National Statistics.

Study findings

Risk of bias – ROBINS-I tool

NI, No Information; ROBINS-I, Risk of Bias in Non-randomized Studies of Interventions.

Life expectancy, all-cause mortality and disease-specific mortality

Six studies reported data on life expectancy or mortality. Two earlier studies reported a widening of inequalities in life expectancy with one showing narrowing of mortality inequalities. The four more recent studies showed a narrowing of inequalities.

Two early government reports showed widening of life expectancy inequalities and mixed results for mortality inequalities. ‘Tackling Health Inequalities: 2007 Status Report on the Programme for Action’ used Office for National Statistics (ONS) data based on life estimates made using the 2006 census. It compared life expectancy in spearhead areas and the rest of the country. While life expectancy had increased for both spearhead and non-spearhead areas, absolute and relative inequalities between them had increased between 1995–1997 and 2004–2006. 10 The second reported ONS data up to and including 2010. 12 Compared with the 1995–1997 baseline, the absolute and relative gap in life expectancy between spearhead areas and England as a whole increased by 2008–2010.

Four later published studies found that inequalities had narrowed. The first study by Barr and colleagues 9 compared individuals living in the fifth most deprived areas to those living in the fifth least deprived areas. The authors found that inequalities of healthcare amenable mortality, defined as mortality from causes that would be prevented provided appropriate access to high-quality healthcare, narrowed between 2001 and 2011. Absolute inequalities for men and women fell with 85% of the change explained by redistributive resource allocation changes between areas. The relative gap narrowed for males and females. However, the authors found that absolute or relative inequalities of mortality not amenable to healthcare failed to change noticeably between 2001 and 2011. 9

The second study by Barr and colleagues 6 investigated geographical inequalities between 1983 and 2015 using ONS data based on the 2011 census, rather than 2006, which informed earlier government publications. They analysed trends in the absolute difference of life expectancy and mortality in the 20% most deprived local authorities compared with the rest of England. Supplementary analysis compared life expectancy in spearhead and non-spearhead areas. The authors identified breakpoints to account for the lag between implementation and outcomes. Both socioeconomic inequalities and inequalities between spearhead and non-spearhead areas in life expectancy for men and women statistically significantly increased year-on-year before the strategy and decreased during the time of the strategy, with no evidence that this decrease continued after the strategy. Relative socioeconomic inequalities in mortality fell year-on-year throughout the strategy for both men and women and increased before and after the strategy for men. Further analysis showed that the gap in life expectancy between spearhead areas and the rest of the country did not decrease until after 2005. Relative socioeconomic inequalities in life expectancy widened before and after the strategy period and narrowed during it. The authors found that using population estimates using the 2006 census caused an artificial increase in life expectancy inequalities compared with 2011 estimates.

Hu and colleagues 7 compared data from the health survey for England to similar surveys done in other European countries. They investigated trends in inequalities of all-cause mortality between those with high (tertiary) education and the rest of the country. The gap narrowed more significantly in 2000–2010 compared with 1990–2000 in England.

While aforementioned studies, analysing differences between the most and least deprived areas, are important concerning the strategies aims, they fail to describe the change in the social gradient across the whole of the population. Buck and Maguire 19 examined the relationship between area-based income deprivation and life expectancy, comparing data from 1999 to 2003 to 2006–2010. The authors found improved life expectancy for all levels of deprivation but a greater improvement in more deprived areas. It was noted that both unemployment and older people’s deprivation played a particularly important role in determining differences in life expectancy between areas.

Three studies reported changes in inequalities in disease-specific mortality. Two government documents examined inequalities in mortality due to cancer between spearhead areas and England as a whole from 1995 to 1997 to 2006–2008 and 2008–2010 using ONS data. By 2006–2008, absolute inequalities fell, without a change in relative inequalities. 10 By 2010, the absolute gap had fallen further, with an increase in the relative gap. 12 Absolute inequalities in mortality due to circulatory disease decreased by 2006–2008, but relative inequalities widened. By 2008–2010, there was a further decrease in absolute but an increase in relative inequalities. Exarchakou and colleagues 26 reported inequalities of 1-year survival rate following a diagnosis of one of the 24 most common cancers between 1996 and 2013. They investigated the absolute difference between individuals living in the fifth most and fifth least deprived areas. The gap narrowed in only 6 of 20 cancers in men and 2 of 21 cancers in women and widened for three cancers (two in women and one in men). One final study examined inequalities in road accident causality in the fifth most deprived local authority districts areas compared with England as a whole. 10 The absolute gap decreased between 1998 and 2006.

Infant mortality

Three studies reported changes in the infant mortality rate. Initial reporting using ONS data from 2004 to 2006 found that inequalities had widened between routine plus manual groups and the population as a whole compared with the 1997–1999 baseline. 10 A later report found that by 2008–2010, inequalities had narrowed compared with the baseline. 13 Robinson and colleagues 21 calculated the infant mortality rate in 323 lower tier local authorities between 1983 and 2017 to investigate changes in inequalities between the 20% most deprived areas and the rest of the country. Absolute inequality increased year on year before the strategy and decreased during it. A non-significant increase was seen after the strategy ended. Relative inequalities marginally decreased during the time of the strategy, in contrast to an increase that was seen before and after the strategy period.

Morbidities

Three studies reported on morbidities using Health Survey of England data. Specifically, these studies investigated self-assessed health, health-related quality of life, mental health and long-term health. The Health Survey of England contains data collected from a nationally representative sample of those residing at private residential addresses and has been carried out since 1991. 28 Around 8000 adults and 2000 children take part in the survey each year.

Mixed results were found concerning self-reported health. Between 1996 and 2009, the probability of reporting bad or very bad health remained relatively constant for those in the highest social class but increased for those in lower social classes. 27 When comparing those with high and low education, there was no significant difference in inequality trends between 2000 and 2010 compared with 1990–2000. Additionally, there was no significant difference in the change of these trends between these periods compared with three European countries. 7 Costa Font and colleagues 20 measured inequalities in self-reported health using concentration indices, whereby a high result indicates more inequality. Equalised household income was used to measure inequality across the whole population. In contrast to the two aforementioned studies, they reported a fall in the concentration index between 1997 and 2007, indicating a reduction in inequality.

Health-related quality of life did not change between social classes from 1996 to 2008. 27 When assessed by a concentration index comparing different household incomes, inequalities of long-term health problems increased between 1997 and 2007. 20 There was no significant change in the trend of inequalities of long-term health problems by education in 2000–2010 compared with 1990–2000. Nor was there a significant difference in the change in trend in England compared with three European countries. 7 While mental health improved in all social classes between 1997 and 2009, it did so more for individuals in higher social classes. 27

Principle findings

There is evidence that the strategy met the infant mortality target, while the life expectancy target was reached for men but not women. Absolute health inequalities in life expectancy, mortality, infant mortality and multiple major causes of death reduced. Less evidence is available concerning relative inequalities. More recent data suggest that relative socioeconomic inequalities in life expectancy and infant mortality narrowed. Relative inequalities of mortality narrowed between the fifth most deprived areas and the country as a whole, but not between the fifth most and fifth least deprived areas. The only data available on disease-specific conditions suggest an increase in relative inequalities. This may be due to a lack of newly published studies, using more recent census data and sampling from the later years of the strategy being available as it is for life expectancy and infant mortality. The difference may also be due to the statistical relationship whereby relative inequalities may increase as a result of a fall in absolute inequalities. 29 30 There was a lack of change or worsening of change for inequalities in mental health, health-related quality of life and long-term conditions. This lack of change or increased inequality for self-reported health measures may be due to multiple reasons. As all studies used the same survey, with data collected shortly after the 2008 financial crash, perceptions of economic security may have altered results. It may be that self-reported measures are more resilient to change. Alternatively, small changes in categorically assessed self-assessed measures may be less easily observed compared with life expectancy and infant mortality that are continuous measures. Health inequalities were found to have narrowed more consistently when measured between geographical areas rather than between individuals. This may be due to longer follow-up periods in many of the studies that were measured at a geographical level, extending beyond the immediate aftermath of the banking crises. Alternatively, it could have been caused by the redistributive resource allocation changes that occurred between areas. 9

Strengths and limitations

This is the first study to collate and synthesise all evidence of the first international attempt at a cross-government strategy to address health inequalities. We used an extensive search strategy with robust screening, data extraction and quality assessment processes. We included peer-reviewed articles and grey literature, including documents published at the time and identified through the UK government archives.

The main limitation is that the studies included are retrospective using either time-trend or before and after methods. All of the studies have a high risk of bias due to deviations from intended interventions. This was predominantly because of the lack of a robust counterfactual that makes it difficult to unpick the impact of the strategy against the impact of other factors, such as broad economic growth before the financial crash in 2008. These limitations are common to any attempt to assess the impact of national policy; however, considering the breadth and ambition of the strategy it is disappointing that more comprehensive evaluations or data are not available. The strategy’s wide-ranging nature does however allow many of these factors to be considered a part of it rather than as a confounding factor. For example, the large decrease in poverty rates, especially in children 31 and pensioners, 32 may both have contributed. Additionally, not every abstract was double screened. However, 40% of abstracts were cross checked to ensure consistency, and only three discrepancies arose, none of which were included in the review.

The included articles use different measures that make direct comparisons impossible, for example, comparing the most deprived areas to either the least deprived areas or the rest of the population and using individual-level measures of socio-economic status (eg, occupation) or area-based measures (eg, IMD). Morbidity data are based on self-reported measures within a nationally representative survey, rather than chronic disease registers.

As indicated by guidance, absolute and relative inequalities were included. 14 33 This aligns with existing guidance and debate both from those who argue that absolute inequalities are the more important measure for policymakers 3 and others who support the idea that relative inequalities are also of significant importance. 34

What this research means

A lack of progress on health inequalities, despite policy priority, can lead to a sense of fatalism and powerlessness to effect change. These findings are therefore important because they show that with sustained cross-government action, progress on health inequalities is possible. It is particularly encouraging that improvements were made in both of the areas that the strategy predominantly set out to improve: inequalities in life expectancy and infant mortality.

These results are even more encouraging when considering that they came from a strategy that was far from perfect. Critics have noted various points about the strategy, for example, that it was insufficiently based on reliable evidence, 8 18 35 36 flawed in delivery, 8 16 18 insufficiently focused on the wider determinants of health 16 34 37 and that efforts may not have been large enough. 8 34 38

Earlier findings consistently showed no improvement in life expectancy inequalities, yet later results were more positive. This may be due to a lag period between the implementation of the strategy of interventions and changes in health outcomes. Certain initiatives would take considerably longer to impact inequalities in life expectancy, such as reducing childhood poverty, compared with more downstream factors, such as blood pressure control. Alternatively, it may be due to more accurate and up-to-date data, such as the 2011 census. Importantly, this shows that sufficient time is needed between implementation and measuring outcomes.

Implications for policy and research

Governments around the world are taking steps to address health inequalities, particularly in light of the growing evidence of an unequal pandemic. 39 For example, the UK government has committed to a programme of ‘levelling up’ regional inequalities and setting out new legislation to address health inequalities. This review suggests that it is possible to reduce health inequalities through long-term cross-government action, which was wide reaching both in terms of government departments and across the life course. Most encouragingly with respect to current government aims, geographical health inequalities especially narrowed. The strategy was supported by significant increases in both funding and reform of public services, of which only one has continued. Since the end of the strategy period, public services internationally, but particularly in the UK, have experienced reduced funding as a result of austerity policies from 2010 onwards. In the UK, this has particularly impacted on local authorities, social security, children’s services and, until the pandemic, to the NHS. Indeed, there is evidence that from 2010 onwards (and before the unequal impact of the pandemic) the improvements in health inequalities under the English strategy have reversed with, for example, increasing inequalities in infant mortality rates 40 and falling life expectancy in the most deprived areas. 41 Considerable investments in these services would be necessary to recreate a proactive attempt to tackle the social determinants of health inequalities.

The strategy used relative measures of inequality. Absolute measures are easier to change, making them appealing to policymakers as progress can be more easily proven. The goals were based on long-term changes in life expectancy and infant mortality rather than shorter term changes in measures such as blood pressure and heart rate. These were appropriate for the strategy given the wide-ranging, cross-departmental approach that aimed to target determinants of ill health. The fact that long-term, ambitious health inequalities targets require a cross-departmental approach can be of benefit to policy makers. They can provide rationale and strengthen the argument for a wide range of potentially transformative policies that may otherwise fail to be enacted due to a lack of political support. Goals were based on changes between the most and least deprived areas, rather than changes in the societal gradient in health. This again would be an easier target for policymakers to achieve. The government’s current targets, through the ‘levelling up’ programme are less ambitious than the strategy’s. 42 Only an absolute narrowing in life expectancy and well-being is aimed for, rather than the 10% change targeted by the strategy. Additionally, the absolute gap in life expectancy by area is measured between the top and bottom 10% rather than 20%.

Arguably more policy priority should have been given to reducing the gap in morbidities as the data fail to show a convincing narrowing of inequalities of self-reported health, mental health, health-related quality of life and long-term conditions.

More research is needed to unpick the active ingredients and exact initiatives that were most effective during the strategy. This should start with a more detailed understanding of which diseases drove the reduction in life expectancy and a broader understanding of how the wider determinants of health such as housing, income and education may have impacted changes in infant mortality, mortality and life expectancy.

In summary, this review found some evidence that the 1999–2010 cross-government health inequalities strategy led to a reduction in the absolute inequalities in life expectancy, mortality, infant mortality and major causes of death. While the impact on relative inequalities is less clear, there seemed to be a narrowing of relative inequalities in at least life expectancy and infant mortality. The national targets relating to life expectancy were met for men, but not women, and were achieved for infant mortality. Policymakers should take courage that progress on health inequalities is achievable with long-term, multiagency, cross-government action. These findings are especially pertinent at present times whereby many governments are aiming to use postpandemic recovery as an opportunity to build back better.

Supplementary Material

Twitter: @ilk21

Contributors: JAF conceptualised the study. JAF and IH drafted the protocol, and IK and AV provided comments. IK developed the searches with the support of IH and JAF. IH and AS screened the titles and abstract and were supported by JAF. IH and JF screened the full text articles. IH, AS and AV extracted and checked the extraction. IH wrote the first draft of the manuscript. JAF, IK, CB, AS and AV redrafted. All authors approved the final version. JAF is the guarantor.

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: None declared.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review: Not commissioned; externally peer reviewed.

Supplemental material: This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Data availability statement

Data sharing not applicable as no datasets generated and/or analysed for this study.

Ethics statements

Patient consent for publication.

Not applicable.

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Health Inequities and Disparities Research

PLOS ONE is proud to publish the Health Inequities and Disparities Collection. Launched in September 2019, this Call for Papers welcomed articles on all relevant disciplines in the field of public health tackling health inequities and disparities. The resulting collection, in the words of one of our Guest Editors, Professor Diana Burgess, "features cutting-edge papers that tackle health inequities and disparities by researchers from a variety of disciplinary perspectives. The collection is truly international in scope and addresses a broad range of health inequities, rooted in historic and contemporary laws, policies, and practices, which disadvantage certain groups. These papers include health equities due to race/ethnicity, socio-economic status, sexual or gender minority identification, immigrant status (including undocumented immigrants), incarceration, socio-economic status, and country of residence. This thought-provoking collection is an important contribution to the field of health inequities and disparities and will expand our understanding of how we define and study these topics."

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