What are health inequalities?
People experience different combinations of these factors, which has implications for the health inequalities that they are likely to experience. There are also interactions between the factors. For example, groups with particular protected characteristics can experience health inequalities over and above the general and pervasive relationship between socio-economic status and health.
This explainer provides an overview of how health inequalities are experienced in England’s population.
Inequalities in life expectancy
Life expectancy is a key measure of a population’s health status. Inequality in life expectancy is therefore one of the foremost measures of health inequality.
Life expectancy is closely related to people’s socio-economic circumstances. The most common summary measure of these circumstances across a population is deprivation. The index of multiple deprivation is a way of summarising how deprived people are within an area, based on a set of factors that includes their levels of income, employment, education and local levels of crime.
In England, there is a systematic relationship between deprivation and life expectancy, known as the social gradient in health. Males living in the least deprived areas can, at birth, expect to live 9.4 years longer than males in the most deprived areas. For females, this gap is 7.4 years.
Importantly, this social gradient relationship holds true across the whole population – health inequalities are experienced by everyone, not just those at the very bottom and top. Figures 1 and 2 show how life expectancy and disability-free life expectancy, which is discussed in the next section, increase as neighbourhood deprivation falls.
This relationship has become known as ‘the Marmot curve’ because of its prominence in Sir Michael Marmot’s report Fair society, healthy lives. Curves showing the same relationship can also be drawn for other measures of deprivation, such as income or education.
In recent years, in addition to growth in life expectancy stalling in the population as a whole, inequalities in life expectancy by deprivation have widened. Between 2012–14 and 2015–17, the gap in life expectancy at birth increased by 0.3 years for males and 0.5 years for females. Life expectancy for females in the most deprived areas fell by almost 100 days during this period.
There are also geographical inequalities in life expectancy. The north of England has a higher concentration of deprived neighbourhoods than the south of England, and therefore a greater proportion of communities where life expectancy is likely to be lower. But in addition to this, for any given level of deprivation, life expectancy in the north of England is lower than in the south of England.
The maps below illustrate differences in life expectancy at birth in 2015–17 by local authority areas, using data from Public Health England’s Fingertips tool. For females, the gap between the area with the lowest life expectancy (Manchester, at 79.5 years) and the area with the highest (Camden, at 86.5 years) is 7 years. For males, the gap is 8.9 years, between Blackpool (74.2 years) and Hart in Hampshire (83.3 years).
Inequalities in healthy life expectancy
Another key measure of health inequality is how much time people spend in good health over the course of their lives, given how crucial good health is to wider quality of life and people’s ability to do the things that they value.
Two important measures of the amount of time that people spend in good health are ‘healthy life expectancy’ and ‘disability-free life expectancy’. The former estimates time spent in ‘good’ or ‘very good’ health, based on how people perceive their general health. The latter estimates, again based on self-reported assessment, time spent without conditions or illnesses that limit people’s ability to carry out day-to-day activities.
Inequalities in both healthy life expectancy and disability-free life expectancy are even wider than inequalities in life expectancy (illustrated by the steeper curves for disability-free life expectancy in Figures 1 and 2). People in more deprived areas spend, on average, a far greater part of their already far shorter lives in poor health.
The gap in healthy life expectancy at birth is stark. In 2015–17, people in the least deprived areas could expect to live roughly 19 more years in good health than those in the most deprived areas. People in the most deprived areas spend around a third of their lives in poor health, twice the proportion spent by those in the least deprived areas.
Again, geographical inequalities exist in this measure. Healthy life expectancy at birth for males in North-East England is 59.5 years, compared to 66.1 years for males in the South East, a gap of 6.6 years. For females, the gap is 5.8 years.
Figures 5 and 6 show healthy life expectancy at birth for males and females in 2015–17 by local authority area. For females, the area with the lowest healthy life expectancy was Nottingham, at 53.5 years, and the area with the highest was Wokingham, at 71.6 years. For males, the area with the lowest healthy life expectancy was Blackpool, at 54.7 years, and the area with the highest was Rutland, at 69.8 years.
Inequalities in avoidable mortality
Some deaths are avoidable through preventive interventions or timely health care. Differences in rates of avoidable mortality between population groups reflect differences in people getting the help that they need to address life-threatening health risks and illnesses.
The Office for National Statistics analyses deaths that could be averted or delayed through timely, effective health care (‘amenable mortality’) or wider public health interventions (‘preventable mortality’). In 2017, more than 140,000 (almost one in four) deaths were considered avoidable according to these definitions. Cancers were the leading cause, followed by cardiovascular diseases, injuries, respiratory diseases and drug misuse.
In England, in 2017, males in the most deprived areas were 4.5 times more likely to die from an avoidable cause than males in the least deprived areas. Females in the most deprived areas were 3.9 times more likely to die from an avoidable cause than those in the least deprived areas.
Figure 7 shows preventable mortality by local authority area between 2016–18. Darker areas have higher rates of preventable mortality. Blackpool had the highest rate at 318.0 per 100,000, more than two and a half times higher than the lowest area, which was Rutland at 118.9 per 100,000.
Inequalities in long-term health conditions
Long-term conditions are one of the major causes of poor quality of life in England. More than 50 per cent of people with a long-term condition see their health as a barrier to the type or amount of work that they can do, rising to more than 80 per cent when someone has three or more conditions. This means that, on top of their direct impact on health status, long-term conditions also have an indirect impact on health, given the importance of being in good-quality work for an individual’s physical and mental health.
People in lower socio-economic groups are more likely to have long-term health conditions, and these conditions tend to be more severe than those experienced by people in higher socio-economic groups. Deprivation also increases the likelihood of having more than one long-term condition at the same time, and on average people in the most deprived fifth of the population develop multiple long-term conditions 10 years earlier than those in the least deprived fifth.
Inequalities in the prevalence of mental ill-health
Assessing differences in the prevalence of mental illness between social groups is challenging and complex, because rates of recognition, reporting and diagnosis are likely to vary between groups. Existing evidence, although in many cases patchy and inconsistent, suggests a number of important patterns.
Evidence suggests that inequalities in various types of mental ill-health exist across a range of protected characteristics, including sexual orientation, sex and ethnicity. People in the United Kingdom who identify as lesbian, gay, bisexual or transgender (LGBT), for example, experience higher rates of poor mental health, including depression, anxiety and self-harm, than those who do not identify as LGBT.
The 2014 Adult Psychiatric Morbidity Survey found that women were more likely than men to report experiencing a common mental health disorder, with one in five women reporting symptoms compared to one in eight men. The gap between women and men was particularly wide among young people, and young women experienced higher rates of reported self-harm and positive screening for post-traumatic stress disorder (PTSD) than men of the same age. Both alcohol and drug dependence were found to be twice as likely in men as in women.
The Adult Psychiatric Morbidity Survey also showed some disparities in mental ill-health by ethnicity. For example, rates of psychotic disorder experienced by Black men (3.2 per cent) and Asian men (1.3 per cent) were higher than among White men (0.3 per cent), although for women there was no significant difference by ethnicity. Rates of detention under the Mental Health Act among the ‘Black or Black British’ group were more than four times higher than the ‘White’ group, which has been linked in part to higher rates of serious mental illness. There are also differences in pathways into care (through the police, the criminal justice system or general practitioner contact, for example) for psychosis patients from different ethnic groups.
Several socially excluded groups have been shown to experience higher rates of mental ill-health than the general population. For example, more than 80 per cent of people experiencing homelessness report having a mental health difficulty, and people in this group are 14 times more likely than those in the general population to die by suicide. Asylum seekers and refugees are also at increased risk of experiencing depression, PTSD and other anxiety disorders.
Inequalities in access to and experience of health services
Access to health services refers to the availability of services that are timely, appropriate, sensitive and easy to use. Inequitable access can result in particular groups receiving less care relative to their needs, or more inappropriate or sub-optimal care, than others, which often leads to poorer experiences, outcomes and health status. Access to the full range of services that can have an impact on health includes access to preventive interventions and social services, as well as primary and secondary health care.
Inequitable access might mean that a group faces particular barriers to getting the services that they need, such as real or anticipated discrimination or challenges around language. These issues are often reported for asylum seekers and refugees and Gypsy, Roma and Traveller communities. It can mean that information is not communicated in an easily understandable or culturally sensitive way.
We can also measure access in terms of service availability and uptake. More deprived areas tend to have fewer GPs per head and lower rates of admission to elective care than less deprived areas, despite having a higher disease burden.
Different social groups might also have systematically different experiences within the services that they use, including in terms of the quality of care they receive and whether they are treated with dignity and respect. One way of measuring this is in terms of patient satisfaction rates. The 2017 British Social Attitudes survey, for example, found that respondents who identified as Black reported lower levels of satisfaction with the NHS (44 per cent said they were satisfied) than respondents who identified as White (58 per cent). In a recent study by Stonewall, 13 per cent of LGBT respondents reported experiencing unequal treatment from health care staff because they were LGBT, with this number rising to 32 per cent for people who are transgender and 19 per cent for Black, Asian and minority ethnic LGBT people.
Pathways to health inequalities
The examples above show systematic differences across various measures of health for different population groups in England. This section explores differences in the likelihood of engaging in healthy or unhealthy behaviours and differences in the wider determinants of health, which are important causes of health inequalities arising and persisting over time. Both involve differences in the health risks that people are exposed to and in the opportunities that they have to lead healthy lives.
Inequalities in behavioural risk factors
People’s behaviour is a major determinant of how healthy they are. Public Health England’s 2020–25 strategy identifies smoking, poor diet, physical inactivity and high alcohol consumption as the four principal behavioural risks to people’s health in England today. Behavioural risks to health are more common in some parts of the population than in others. The distribution is patterned by measures of deprivation, income, gender and ethnicity, and risks are concentrated in the most disadvantaged groups. For example, smoking prevalence in the most deprived fifth of the population is 28 per cent, compared to 10 per cent in the least deprived fifth.
Risky health behaviours also tend to cluster together in certain population groups, with individuals in disadvantaged groups more likely to engage in more than one risky behaviour. The prevalence of multiple risky behaviours varies significantly by deprivation. In 2017, the proportion of adults with three or more behavioural risk factors was 27 per cent in the most deprived fifth, compared with 14 per cent in the least deprived fifth.
Health-related behaviours are shaped by cultural, social and material circumstances. For example, recent estimates suggest that households in the bottom fifth of income distribution may need to spend 42 per cent of their income, after housing costs, on food in order to follow Public Health England’s recommended diet.
Furthermore, evidence suggests that some people’s circumstances make it harder for them to move away from unhealthy behaviours, particularly if they are worse off in terms of a range of wider socio-economic factors such as debt, housing or poverty. This is compounded by differences in the environments in which people live, with deprived areas much more likely to have fast food outlets than less deprived areas (Blackpool, for example, has more than five times as many fast food outlets per head than Sevenoaks).
Interventions and services aimed at helping to change behaviours need to be able to adapt to the reality of people’s lives, address the wider circumstances in which behaviours take place, and recognise the difficulty of achieving and maintaining behavioural change under conditions of stress.
The wider determinants of health
It is widely recognised that, taken together, these factors are the principal drivers of how healthy people are, and that inequalities in these factors are a fundamental cause of health inequalities. Addressing these wider socio-economic inequalities is therefore a crucial part of reducing health inequalities.
Table 1 provides some examples of health impacts relating to a range of wider determinants. The examples focus on individual determinants, but these determinants are often experienced together and cumulatively over time. Particular groups can be disadvantaged across a number of factors, and these disadvantages can be mutually reinforcing. Deprived areas have, for example, on average nine times less access to green space, higher concentrations of fast food outlets and more limited availability of affordable healthy food.
Table 1 Selected impacts of wider determinants on our health
|Income||Income determines people’s ability to buy health-improving goods, from food to gym memberships. Managing on a low income is a source of stress, and emerging neurological evidence suggests that being on a low income affects the way people make choices concerning health-affecting behaviours.|
Children from households in the bottom fifth of income distribution are over four times more likely to experience severe mental health problems that those in the highest fifth.
|Housing||Poor-quality and overcrowded housing conditions are associated with increased risk of cardiovascular diseases, respiratory diseases, depression and anxiety. As external temperature falls, death rates rise much faster for those in the coldest homes.|
Households from minority ethnic groups are more likely than White households to live in overcrowded homes and to experience fuel poverty.
|Environment||Access to good-quality green space is linked to improvements in physical and mental health, and lower levels of obesity. Levels of access are likely to be worse for people in deprived areas, and for areas with higher proportions of minority ethnic groups.|
Exposure to air pollutants is estimated to cut short 28–36,000 lives a year in the United Kingdom. Exposure has been linked to both deprivation and ethnicity. For example, within the most deprived areas of London, people from non-White groups have been found to be more exposed to high concentrations of nitrogen dioxide, one of the main pollutants associated with traffic fumes.
|Transport||Those living in the most deprived areas have a 50 per cent greater risk of dying in a road accident compared with those in the least deprived areas. Children in deprived areas are four times more likely to be killed or injured on the road than those in wealthier areas.|
|Education||On average among 26 OECD countries, people with a university degree or an equivalent level of education at age 30 can expect to live more than five years longer than people with lower levels of education.|
|Work||Unemployment is associated with lower life expectancy and poorer physical and mental health, both for individuals who are unemployed and for their households. The quality of work, including exposure to hazards, job security and whether it promotes a sense of belonging, affects the impact it has on both physical and mental health. Non-White groups experience higher levels of work stress, controlling for other demographic factors.|
Interactions between the factors driving health inequalities
Our health is shaped by a complex interaction between many factors. These include the quality of health and care services, individual behaviours, the places and communities in which people live and wider determinants such as education, housing and access to green space. Health inequalities arise as a result of systematic variations in these factors across a population.
Inequalities in these factors are inter-related: disadvantages are concentrated in particular parts of the population and can be mutually reinforcing. Lower socio-economic groups, for example, tend to have a higher prevalence of risky health behaviours, worse access to care and less opportunity to lead healthy lives.
The interactions between different kinds of inequality, and the factors that drive them, is often complex and multidirectional. People can find it more difficult to move away from unhealthy behaviours if they are worse off in terms of a range of wider determinants of health. Access to green space, on the other hand, seems to weaken the relationship between income and health status in a complex way.
Based on factors often outside their direct control, people in England experience systematic, unfair and avoidable differences in their health, the care they receive and the opportunities they have to lead healthy lives.
Interventions to tackle health inequalities need to reflect the complexity of how health inequalities are created and perpetuated, otherwise they could be ineffective or even counterproductive. For example, efforts to tackle inequalities of health status associated with behavioural risks (such as poor diets) should address the wider network of factors that influence these behaviours (such as access to affordable healthy food, marketing and advertising regulations) and the impact that these behaviours have on health outcomes (such as access to clinical services).
Health inequalities are not inevitable and the gaps are not fixed. Evidence shows that a comprehensive approach to tackling them can make a difference. Concerted, systematic action is needed across multiple fronts to address the causes of health inequalities. This includes, but goes well beyond, the health and care system. We will set out more on this in our position on health inequalities in the near future.
Long-term health condition can effect a patient day to day life activities do to lack of physical disability like going out, that is if their mobility is bed or shorting down.
I think that patients has the right to choose the nature and type of care that they want. But it is the of the responsibility of the support workers to help and assist in the area of making the right choice. Health inequality differs a responsibility and can be measured in divers range. For instance a homelessness may find it difficult to make the right decision he needs. Bearing in mind that their wellbeing remain pour priority. Assisting in getting shelter , like the assistance for getting asses to good healthcare, the notification of the red army, regardless of the sociological believe or the colour of skin.
As such, the challenge of facing social difficulties has be removed on gradual basis as that can affect their mental illness. Thus, bearing in mind that every patients count. And together we shall safeguard patients.
The gap in health status can only be bridged and reduced through a systematic long-term process. One quick solution cannot fix this as evidenced by the limited success of health-care intervention only. This process must put into consideration, factors such as: Gender equality, racism, ethnicity, wider-determinant of health, economy, and so on.
The demonstrations of geographic variation in LE and disability-tree LE are striking. Two major issues are largely absent from this otherwise excellent piece - and from many other similar presentations. The first is Smoking, mentioned only briefly as an 'example', contrasting prevalence in deprived vs wealthy demographics. The truth is that smoking accounts by itself for over half the excess mortality in deprived populations, is a uniquely preventable risk factor, and one where prevention is uniquely cost-effective, The second is a specific smoking related disease, now the commonest cause of premature death (not just cancer death) in urban populations, which remains largely under the radar, despite being uniquely preventable, increasingly predictable, and eminently curable if caught early. This almost completely preventable mass killer is Lung Cancer. When looking at practical steps which can be taken to reduce health inequalities, and in doing so save hundreds of thousands of lives, a determined assault on smoking, and on the early detection and treatment of lung cancer, should be paramount. As things stand, they are almost entirely neglected, and the NHS has actually disinvested in smoking cessation, leaving it in the hands of cash-strapped local authorities who are in no position to deliver an effective service. The benefits of tobacco control fall biggest and earliest to the NHS, and that link needs to be restored by empowering our healthcare institutions to take direct advantage of it. Cui Bono? is a good principle, and one which needs to be deployed in this area, to create a 'virtuous cycle' of health and cost benefit.
I also like the document, and the comments from the respondents. With a grandson with autism spectrum I can attest to him having no contact with anyone official regarding his well being apart from his family for the whole of the 6 years since he was diagnosed. His school off-rolled him within months of him being diagnosed.
From a thyroid treatment point of view NICE block the pathway to effective treatments, condemning those who cannot be made well by the standard treatment to a life of campaigning for better treatment. And guess what, the treatment is there, just a lack of willingness by Gov.uk to make it available, and by endocrinologists stuck in a mindset and quashed by both CCGs and GMC in being allowed to prescribe as they would wish.
Related to Mathew Barker's comment, patients have a right to choose the provider of the care at the point of referral from a GP for all elective consultant led services and in mental health, for all health care professional led services. I wonder if any work has been done to show whether greater promotion of patient choice, enabling patients to access services, irrespective of where they live, can improve some health inequalities?
On a separate track on inequalities, I'm rare of a rare disease group, who, through the lack of a diagnostic and treatment pathway have a major inequality in care in the UK. With some hospitals, mainly in London, there is a better, but not huge range of medication options, and informed consultants, whereas in other places the medication choice is limited to one drug which can have bad side effects or limited use. This inequality can be seen even within a particular hospital which makes it impossible to complain or campaign for better treatment, in case overall treatment is reduced. NICE appear to be a block in the road towards better care, plus change is slow because we are not a "popular" illness to campaign for, and I am uncertain if these inequalities will ever change in my lifetime.
The comments on learning disabilities echoes my thoughts exactly. I accessed this article to look for some hard evidence of the inequality that I see in my work and was very surprised there was no specific mention of the well known and evidenced inequalities in health and health service provision encountered in this area
Most helpful and informative document - thank you; however, a mention of health inequalities In relation to People with Learning difficulties /conditions such as - Dyspraxia, ADHD, Autistic Spectrum disorders would perhaps add to the contents.
I echo Ian Bell’s comment. Disability is mentioned in passing and not explored in detail. The shocking gap in life expectancy in people with learning disability evident from LeDeR reviews, “Death by Indifference” and CIPOLD reports demands attention and action. Why is this group particularly invisible? It is not a case of a population that is “difficult to reach”, perhaps It is a population that is “easy to ignore”?