For high-grade participants this association was reversed, with those living in the most deprived areas rating themselves as slightly higher on the ladder. For each 1 SD increase in Townsend deprivation, high-grade participants placed themselves 0.
These relationships showed the same patterns for male and female civil servants. Heterogeneity within the neighbourhood and the possibility that, for a given ward, high-grade participants live in better parts of wards than low-grade participants was investigated using data for enumeration districts.
There is an average of 12 enumeration districts within a ward. Table 4 shows levels of owner-occupancy, public housing renting, and male unemployment for high-grade and low-grade participants living in the most deprived wards columns 2 and 3 and low-grade and high-grade participants living in the least deprived wards columns 4 and 5.
In the most deprived wards here taken to be the top quartile of Townsend deprivation , high-grade participants were more likely to be living in enumeration districts which had below average deprivation for the ward compared with low-grade participants. For example, Those in the high grades were more likely to be living in parts of the ward with below-average public housing and unemployment. This supports the suggestion that high-grade participants in the most deprived wards tend to live in the better parts of the ward.
It was less clear whether low-grade participants living in the least-deprived wards the bottom quartile of Townsend deprivation were in less-desirable parts of the ward.
In the least-deprived wards, Nevertheless, for high-grade participants living in the most deprived wards, levels of owner-occupancy in the more immediate vicinity the enumeration district were lower than the overall average Whether electoral wards larger areas or enumeration districts smaller areas were considered, it was possible to identify some high-grade participants living in more deprived residential conditions and some low-grade participants living in less-deprived conditions.
Table 3 last 3 columns shows physical and mental health by individual and neighbourhood SES, after controlling for neighbourhood problems estimated at the level of no neighbourhood problems , age and sex.
Whilst those in the lower grades continued to have a greater risk of poor self-rated and mental health, the differences between high and low grades were more similar across different levels of neighbourhood deprivation once neighbourhood problems are included in the model. These figures were This indicates that problems in the neighbourhood account for much of the higher prevalence of poor general self-rated and mental health among poorer individuals living in poorer areas.
Health differences between high- and low-grade civil servants may be larger in more deprived areas, although interaction tests were not statistically significant. Larger studies would be useful for investigating whether those in higher socioeconomic positions are protected from the health-damaging aspects of deprived neighbourhoods.
These analyses can be considered as a test of one component of the relative deprivation hypothesis. If people in the same residential area are a relevant comparison group, we would expect poorer people living in more wealthy areas to have poorer health, greater financial stress, or a lower perception of themselves on the ladder.
Our findings do not support this hypothesis at the neighbourhood level; low grades living in less-deprived areas rated themselves higher up the ladder than low grades in more deprived areas.
However, at the opposite end of the socioeconomic spectrum we found that perceived position in the ladder of society increased with increasing area deprivation for high-grade participants.
Relevant comparison groups may also be different for those in high versus low socioeconomic positions. It was not possible to use these data to investigate whether the tendency to draw influence from social contact in the neighbourhood varied by employment grade.
Our findings are consistent with a collective resources model. Neighbourhood deprivation was associated with all three health outcomes over and above individual socioeconomic position. Neighbourhood problems mediated these associations. The large difference in health status between low-grade participants living in high- and low-deprivation neighbourhoods was substantially reduced when information on neighbourhood problems was added to the regression model, indicating that collective resources are poorer in more-deprived neighbourhoods and are on the pathway linking neighbourhood deprivation to health.
For a given level of area deprivation, those in high grades reported fewer problems with the neighbourhood than those in lower grades. Assuming homogeneity within the neighbourhood, this suggests that the impact of neighbourhood deprivation is greater for those in lower socioeconomic positions although we do note that interactions were not formally significant.
Another study in London neighbourhoods found that neighbourhood problems increased with neighbourhood deprivation, especially for lower-status individuals.
A differential vulnerability to living in a deprived area may be due to greater exposure to the local area. For example, poorer people in Glasgow were found to walk around their neighbourhood more than richer people. Individual resources held by richer individuals may protect them from the neighbourhood stressors in a deprived area.
Additionally, living in a deprived area may exacerbate the effect of stressors at the individual level or resources at the individual level may be rendered less beneficial in the context of a deprived area. Results from a study in Nevada suggested that financial strain had a larger impact on health in lower-status neighbourhoods and that the protective effect of frequent social interaction was present in high-status neighbourhoods but not in low-status ones.
Another explanation for the more-frequent reporting of neighbourhood problems by poorer people is heterogeneity within the neighbourhood, here defined by electoral ward boundaries.
Inspection of smaller spatial units showed that high-grade participants tend to live in the less-deprived parts of those deprived wards. This is likely to go some way towards explaining why, for a given level of Townsend deprivation, they report fewer neighbourhood problems than those in the lower grades.
The value of investigating neighbourhood characteristics when neighbourhoods are diverse has been questioned. Increasingly, people are spatially segregated along socioeconomic lines 41 so those of high SES living in more-deprived places and those of low SES living in less-deprived places are atypical.
Area of residence may provide additional information on social position, connoting an aspect of status that is not captured by traditional occupation-based socioeconomic measures. Supplementary data on socioeconomic position, such as level of assets and educational attainment, were available. There are some methodological limitations with this work. Market forces dictate that poor people are less able to afford to live in affluent areas. This reduces the power to detect a statistically significant interaction between individual and area deprivation on health because of the small number of poor people in affluent areas and rich people in poor areas.
On the other hand, the Townsend index was based on data from the census, some 6—8 years prior to the measurement of health status. More up-to-date data on neighbourhood deprivation may be expected to show a stronger relationship with perceived health. These data are cross-sectional so we cannot exclude the possibility that poor health leads people to move to more-deprived areas. However, when the analysis was limited to participants who had not moved since the previous phase about 5 years earlier , there was negligible change in the estimates.
This suggests that the movement of less-healthy participants to more-deprived areas is not driving the associations presented here. Finally, these models have been laid out as competing but it is possible that elements of both are present. If the health-enhancing effect of living in a rich neighbourhood were present but smaller for poorer individuals then it could be that collective resources are good for health and, at the same time, living among relatively wealthy neighbours is detrimental to health.
The effects on general and mental health of living in a deprived area appear to be larger for lower-status individuals. Additionally, low-status individuals living in deprived areas report more neighbourhood problems than high-status people living in similar areas.
At the other end of the socioeconomic spectrum, high-status people living in deprived areas rated themselves as higher up the ladder of society than high-status people living in less-deprived areas. Both these mechanisms could explain larger health differences between rich and poor individuals in deprived areas.
Few studies have investigated whether the health effects of neighbourhood deprivation are the same for individuals occupying low and high socioeconomic positions.
We find that collective resources in the neighbourhood indicated by lower neighbourhood deprivation are associated with better health. The effect may be larger for poorer people. Poorer people living in more affluent neighbourhoods do not report more financial problems, less satisfaction with their standard of living or perceive themselves to be lower down the ladder of society—being less well-off than your neighbours does not appear to have negative health implications.
Richer people living in more deprived neighbourhoods perceived themselves to be higher up the ladder of society than those living in more affluent neighbourhoods. General and mental health of participants at Phase 5 of the Whitehall Study by individual employment grade and neighbourhood deprivation, adjusted for age and sex.
Multiplicative effects of individual employment grade and neighbourhood deprivation at Phase 5 of the Whitehall Study. Neighbourhood problems by area deprivation and individual socioeconomic position reported by participants in the Whitehall II study. Financial problems by area deprivation and individual socioeconomic position reported by participants in the Whitehall II study. Dissatisfaction with standard of living by area deprivation and individual socioeconomic position reported by participants in the Whitehall II study.
Self-reported position on ladder by area deprivation and individual socioeconomic position reported by participants in the Whitehall II study.
MS is supported by the Health Development Agency. Thanks to Paola Primatesta for comments on an earlier draft, all participating civil service departments and their welfare, personnel, and establishment officers; the Occupational Health and Safety Agency; the Council of Civil Service Unions; and all participating civil servants in the Whitehall II study and members of the Whitehall II study team. Thanks also to the referees for their helpful and constructive comments on an earlier version.
Poverty and health: Prospective evidence from the Alameda County study. Am J Epidemiol ; : — Shaper AG, Elford J. Place of birth and adult cardiovascular disease: the British Regional Heart Study. 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.
In , more than , 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 , males in the most deprived areas were 4. Females in the most deprived areas were 3. Figure 7 shows preventable mortality by local authority area between — Darker areas have higher rates of preventable mortality. Blackpool had the highest rate at 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. 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. 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 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. 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.
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 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. 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.
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 , 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. The report also shows that early death and illnesses associated with mental wellbeing, diet, drug use, tobacco and alcohol dependency, are more common in poorer areas than in richer areas.
The leading causes of ill health or early death are drug use disorders, heart disease, depression, lung cancer and Chronic Obstructive Pulmonary Disease COPD. Most of the conditions that cause a high proportion of the early death or ill health are related to modifiable factors that affect health. In England, a weighted capitation formula is used to allocate health care resources to authorities in local areas.
In addition to weighting for age and gender and utilization-based estimates of need, the formula currently includes an additional weighting for DFLE. The present results provide empirical support for this approach, but also provide evidence of greater costs for health service users in deprived areas, through generally greater levels of multiple morbidity, as well as more frequent depression as an important driver of costs.
Predictive risk modelling would be likely to pick up these drivers of resource use to inform better allocation decisions. In considering the tasks of the new local commissioners of services, a number of studies have demonstrated that employing effective treatments not only helps patients across the socioeconomic spectrum but can also reduce socioeconomic inequalities in outcomes. For example, increased uptake of specific medical technologies to prevent heart failure was found to reduce absolute differences in heart failure rates by socioeconomic status among patients in the English General Practice Research Database GPRD from to This study provides new evidence of the impact of deprivation on the occurrence of multiple morbidity.
People living in social and material deprivation are channelled, through the higher incidence of disease, into higher categories of multiple morbidity. People living in deprived circumstances live longer with multiple morbidity, and more of those who die have multiple morbidity.
Depression is associated with morbidity, but deprivation is associated with a higher prevalence of depression at any level of morbidity. In multiple morbidity, the costs of health care use tend to be more strongly determined by the level of morbidity than the deprivation level.
The data emphasize the importance of disease prevention and health promotion to reduce inequalities in health. The findings demonstrate the impact of deprivation on needs for services for patients with multiple morbidity. These needs include not only disease management pathways but also needs for mental health care, social care for attendant disabilities and end-of-life care. However, the interpretation and conclusions contained in this study are those of the authors alone.
National Center for Biotechnology Information , U. J Health Serv Res Policy. Author information Copyright and License information Disclaimer. Email: ku. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article has been cited by other articles in PMC. Abstract Objective This study aimed to estimate the impact of deprivation on the occurrence, health outcomes and health care costs of people with multiple morbidity in England. Conclusions The higher incidence of disease, associated with deprivation, channels deprived populations into categories of multiple morbidity with a greater prevalence of depression, higher mortality and higher costs.
Keywords: comorbidity, coronary heart disease, depression, deprivation, diabetes, equity, health care costs, health care utilization, primary care, socioeconomic inequalities, stroke. Introduction Socioeconomic inequalities in health status are observed in all countries. Disease states The research included four conditions known to be associated with lifestyle risks: diabetes mellitus, coronary heart disease CHD , stroke and colorectal cancer.
Statistical analysis Person years, incident events and deaths were tabulated by deprivation quintile and number of conditions. Table 1. Open in a separate window. Table 2. Table 3. Table 4. GLM: general linear model.
Table 5. Discussion What this paper shows This epidemiological study evaluated the impact of deprivation on incidence, mortality, prevalence of depression and health care costs associated with multiple morbidity in a large population. Strengths and limitations of this paper The paper was based on analysis of a very large sample of nearly , participants drawn from primary care registers in the UK.
What other research shows The association of deprivation with greater morbidity and mortality and higher health care costs is well recognized. Policy implications The findings of this study have implications both for resource allocation and for intervention strategies to attenuate morbidity differences related to socioeconomic status.
Conclusions This study provides new evidence of the impact of deprivation on the occurrence of multiple morbidity. References 1. Commission on Social Determinants of Health Closing the gap in a generation. Socioeconomic differences in the prevalence of common chronic diseases: an overview of eight European countries. Area-based socioeconomic status, type 2 diabetes and cardiovascular mortality in Scotland.
Diabetes prevalence and socioeconomic status: a population based study showing increased prevalence of type 2 diabetes mellitus in deprived areas. Wildman J.
Income related inequalities in mental health in Great Britain: analysing the causes of health inequality over time. Mental health inequalities in Wales, UK: multi-level investigation of the effect of area deprivation.
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