The Marmot Review in a Hertfordshire Context
Executive Summary
Key Messages
Generally, Hertfordshire has good outcomes for health and wellbeing in comparison to England. However, large inequalities exist between areas of high and low deprivation levels, and between specific groups within the population. For some of these groups, Hertfordshire has worse outcomes than England.
Reducing inequalities will require interventions, policies, and programmes to be tailored to the needs of population groups. There is evidence that for some services the offer of support is made universally, such as free NHS health checks, but that uptake is lower in deprived groups.
The six policy objectives of the original Marmot Review are still applicable to address health inequalities:
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give every child the best start in life
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enable all children, young people, and adults to maximise their capabilities and have control over their lives
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create fair employment and good work for all
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ensure healthy standard of living for all
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create and develop healthy and sustainable places and communities
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strengthen the role and impact of all ill health prevention
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This review demonstrates the importance of measuring inequalities within Hertfordshire, rather than simply comparing to national averages or using unmodified national definitions of deprivation.
Introduction
Fair Society Healthy Lives, the Marmot Review (2010) demonstrated that those in more deprived areas have substantially worse health outcomes than those living in less deprived areas [1]. These differences arise due to inequalities in the wider determinants of health. Factors such as employment, education, and the environment play a determining role in health and wellbeing, accounting for up to 85% of ‘health’. Addressing health inequality therefore necessitates addressing other inequalities across society. A decade on from the original Marmot Review, follow up reviews were undertaken exploring both if and how inequalities have changed, and how these have been affected by the COVID-19 pandemic [2, 3]. This report assesses how Hertfordshire has fared in relation to the findings of the Marmot Reviews.
Fig 1. Social determinants of health model
The Marmot Review established that across England, life expectancy is strongly correlated with deprivation, and that the steady increase in life expectancy since 2001 had begun to slow. Hertfordshire has a generally higher life expectancy and lower levels of deprivation than England. However, there is substantial inequality within Hertfordshire, with those in deprived areas of the county living three to four years shorter and spending up to 18 years fewer in a state of good health than those in the least deprived parts of the county.
Data on the social determinants of health shows a similar picture. Hertfordshire generally has better outcomes than England across a range of different indicators, including infant mortality rate, and educational attainment at age 15. However, within Hertfordshire there is evidence of inequality between groups, with more deprived areas having less access to green spaces, higher levels of overcrowding in households, and poorer health outcomes. On a number of metrics, the outcomes for some population groups are significantly worse than England, despite Hertfordshire overall performing better. For example, children in care have a third of the educational attainment scores of the Hertfordshire average at age 15. Addressing these inequalities will have a significant impact of the lives of people in Hertfordshire.
COVID-19 has further highlighted the inequalities that exist in the county. During Winter 2020, the case rate in the most deprived areas was almost 50% higher than the rate in the least deprived areas, and the peak of deaths was 35% higher. Since the vaccine roll out in December 2020, those in the most deprived areas have a lower uptake than those within the least deprived areas. As vaccinations begin to lower the impact COVID-19 has, areas and groups with lower uptake may be slower to recover, potentially exacerbating existent inequalities.
Guidance
The Marmot Review in a Hertfordshire Context consists of various sections which users are able to navigate to by using the menu on the left. All graphs and maps in this report are interactive, and users can zoom in and out, select, and deselect categories in the legend, and more. Some sections have tabs showing a number of different indicators.
Confidence Intervals
Confidence intervals (CIs) are a measure of the statistical precision of a value and show the range of uncertainty (caused by sample size and random variation) around the value. Calculations based on smaller sample sizes tend to result in wider CIs. The wider the CI the greater the uncertainty in the value. In public health, the conventional practice is to use 95% CIs. This represents the probability that the interval is 95% likely to include the true value. CIs are important to consider when interpreting data and comparing areas to assess whether differences are ‘real’ or statistically significant. If the CIs around a value do not overlap with the interval around another then we can be certain that there is a statistically significant difference between the data points. If the CI around a value overlaps with the interval around another, we cannot say with certainty that there is more than a chance difference between the two values.
Measuring Deprivation
There are many ways to measure deprivation and inequality. The English Index of Multiple Deprivation (IMD) is the official measure of relative deprivation for lower super output areas (LSOAs) in England, using data from agencies including the Office for National Statistics, the Department for Work and Pensions, and the Department for Education. This value depends on seven discrete domains by different amounts: income (22.5%), employment (22.5%), education (13.5%), health (13.5%), crime (9.3%), barriers to housing and services (9.3%), and living environment (9.3%). Data from each of these domains is combined to create an overall rank for IMD [4].
LSOAs are small areas with an average of approximately 1,500 residents or 650 households produced by the Office of National Statistics. IMD scores are calculated for LSOAs and can be split into even groups (e.g., quintiles or deciles). Figure 2 shows the percentage of LSOAs assigned to each quintile by district to demonstrate the level of deprivation in Hertfordshire, based on national grouping of IMD scores. IMD measures how deprived an area is in comparison to other areas but does not measure to what extend they differ. Whilst providing an accurate measurement of how deprived the whole area is, it cannot be used to identify deprived people, or measure the affluence of an area. IMD is also available at Middle Super Output Area (MSOAs), areas with an average of 7,500 residents or 4,000 households.
Fig 2. Index of Multiple Deprivation
In Hertfordshire, Broxbourne has the highest percentage of LSOAs in the most deprived IMD quintile, while St Albans has the highest percentage of LSOAs in the least deprived quintile.
IMD variation within Hertfordshire
Overall, Hertfordshire has a relatively low deprivation level, and is in the 9th deprivation decile nationally. However, there are variations within Hertfordshire which are illustrated in the map below. This review uses local Hertfordshire IMD ranks/quintiles, where the 690 LSOAs are ranked according to their deprivation score. Compared to using national deprivation quntiles, this better highlights inequalities within Hertfordshire. IMD quintile 1 refers to the most deprived, and 5 refers to the least deprived areas. (See here for more information regarding IMD and other measures of deprivation in Hertfordshire).
Fig 3. IMD in Hertfordshire by LSOA (Map)
Figure 3 illustrates the differences in national IMD quintiles and Hertfordshire IMD quintiles by mapping Hertfordshire LSOAs using the two separate IMD quintile methods.
Life Expectancy and Health Inequalities
Life expectancy and Deprivation
Life expectancy at birth is a summary measure that captures the average number of years a person is expected to live based on mortality rates. When assessed with other indicators, it enables the identification of the driving factors of life expectancy, as well as the effectiveness of population health interventions and treatments. When disaggregated into different population groups, such as by gender, social class and ethnicity, life expectancy can also reflect health inequalities.
Fig 4. Life Expectancy and IMD (England)
Figure 4 shows the relationship between life expectancy at birth and IMD rank for all MSOAs in England between 2015-2019. It can be observed that populations living in areas of higher IMD rank (lower levels of deprivation) report higher life expectancies compared to populations living in areas with a lower IMD rank.
Hertfordshire MSOAs are highlighted in dark blue on Figure 4. While Hertfordshire MSOAs have a generally higher rank, there is a large gap between life expectancies with someone in the least deprived areas of Hertfordshire expected to live almost 16 years longer than someone in the most deprived areas.
Fig 5. Life Expectancy and IMD (Hertfordshire)
Figure 5 shows life expectancy of males and females between 2015-2019 grouped by Hertfordshire’s local IMD quintiles. Grouping life expectancy by quintile illustrated a social gradient of increasing life expectancy with decreasing level of deprivation in both males and females.
Fig 6. Life Expectancy Inequalities
Figure 6 illustrates inequalities in life expectancy between the most and least deprived LSOAs in each area. In 2018-20, there was a 7.6 year gap and a 6 year gap for male and female life expectancy respectively, with significant variation between Hertfordshire districts. Although for female, the trend has stayed similar throughout the period between 2011-13 and 2018-20, male life expectancy showed a gradual increasing trend.
Good Health and Deprivation
Fig 7. Life Expectancy and Healthy Life Expectancy
Whilst addressing inequality in life expectancy is important, giving ‘life to years’ should hold the same level of significance as ‘adding years to life’ [1]. Measuring the gap between life expectancy and life expectancy without significant limiting illness (disability) provides a way to measure this. This is shown in Figure 7, where a wider gap is observed between healthy life expectancy and life expectancy in areas where level of deprivation is higher, meaning that those in deprived areas both live shorter lives, and spend longer in a state of ill-health.
Mortality
Life expectancy at birth is determined by mortality rates. Examining the causes that contribute to mortality at various stages enable us to understand how health can be improved in the Hertfordshire population.
Avoidable mortality
Fig 8. Avoidable mortality rate
Figure 8 shows the avoidable mortality rate of all persons in Hertfordshire districts. Avoidable mortality is defined as any deaths occurring in which the causes are either preventable or treatable. (See here for the list of avoidable death causes included in the definition). Please note that avoidable mortality rate is not available at Hertfordshire level and therefore the most and least deprived districts are shown.
In general, the avoidable mortality rates in all districts have decreased year-on-year over the observed period. Although recently, rises have been seen in some areas, coinciding with the decreasing growth in life expectancy. Most Hertfordshire districts had mortality rates similar to or lower than the English figure, except for Stevenage whose avoidable mortality were on average higher although not statistically significantly than England. Stevenage is also a district with higher level of deprivation. Generally, across Hertfordshire, the avoidable mortality rate is higher in males compared to females.
Causes of Deaths
To understand the underlying contributors to differences in mortality and life expectancy data, differences in causes of deaths between the least and most deprived quintile can be examined [5].
Fig 9. Death causes’ contribution to life expectancy gap
Figure 9 illustrates the percentage difference in death causes’ contribution to life expectancy gap between the most and least deprived quintile between 2015 and 2017.
For females in Hertfordshire, the causes that account for the largest differences in life expectancies between the most and least deprived areas are respiratory (25.2%) and circulatory (22.5%) diseases, and cancer (17.7%).
For males in Hertfordshire, the causes that account for the largest differences in life expectancies between the most and least deprived areas are cancer (27.5%), circulatory (26.8%) and respiratory (14.5%) diseases.
Respiratory Diseases
Respiratory diseases account for a 0.95 year gap (14.5%) between the most and least deprived areas of Hertfordshire for males, and a 1.17 year gap (25.2%) for females. People living in more deprived areas are more vulnerable to respiratory diseases for various reasons, including lifestyle behaviours such as smoking. More deprived population also have a general heightened risk from exposure to pollution and dangerous substances, such as asbestos from both living and working environments [6].
Circulatory Diseases
Circulatory diseases account for a 1.75 year gap (26.8%) between the most and least deprived areas of Hertfordshire for males, and a 1.05 year gap (22.5%) for females. Behavioural risk factors, for example, smoking, physical inactivity and poor diet, are key drivers for circulatory diseases and these factors are in turn correlated with socioeconomic factors such as income, education and work [7].
Cancer
Cancer accounts for a 1.79 year gap (27.5%) between the most and least deprived areas of Hertfordshire for males, and a 0.83 year gap (17.7%) for females. A third of all cancer deaths are attributed to modifiable behaviours such as smoking and poor diet which are more common in deprived populations [6]. Early diagnosis can reduce the probability of cancer mortality, however uptake of screening services is lower in deprived populations [8]. Whether this is due to transportation, or costs of time taken away from work; delayed treatment reduces the chance of survival in patients, resulting in higher rates of cancer mortalities.
Infant Mortality
Infant mortality is a common measure of healthcare and maternity care quality, and is influenced by social, economic, and environmental factors. Nationally, the most deprived areas of England have almost twice the infant mortality rate of the least deprived areas.
Fig 10. Infant mortality
Figure 10 shows infant mortality rates across England and Hertfordshire have decreased since 2001-03. The infant mortality rate in Hertfordshire had been consistently below the rate within England over the past 20 years. However, Hertfordshire has shown fluctuations and has been increasing since 2013-15. Amongst the districts, Watford and Stevenage, the more deprived areas have the highest infant mortality rate, higher than the England average, while North Hertfordshire has the lowest infant mortality rates in the latest period (2017-2019).
Suicide
The Marmot Review has highlighted suicide as an important cause of avoidable mortality that is highly associated with deprivation and socioeconomic disadvantages.
Fig 11. Suicide by IMD
Figure 11 shows the percentage of deaths in Hertfordshire given a coroner’s conclusion of suicide at inquests held between 2017 and 2019 in each Hertfordshire IMD quintile based on their postcode address. A higher percentage of suicides were observed in more deprived areas of Hertfordshire, particularly in the second most deprived quintile.
The Hertfordshire Suicide Audit states that mental health issues are the most reported risk factor for suicide. Other risk factors were also explored, many relate to deprivation and other known health inequalities. For instance, as shown in Figure 12, 19% of suicides audited were retired and 18% were unemployed, despite these groups comprising 12% and 3.5% of the Hertfordshire population.
Within the county, among all deaths with a coroner inquest conclusion of suicide between 2017 and 2019, 67.4% had a mental health issue or condition recorded by their GP practice. A report published by The Samaritans explores how inequalities place socio-economically disadvantaged individuals at higher risks of suicidal behaviours [9]. At an individual level, stressful negative life events, such as childhood adversity, financial crises, bereavement, and relationship breakdown are risk factors for suicidal behaviours. At a community level, contextual factors such as the lack of non-precarious job opportunities, absence of local support networks, and exposure to other individuals’ suicidal behaviours, increase the risk of suicide. Notably, 69% of those who died by suicide had a mental health condition listed on their health record, but only 28% were known to mental health services at the time of their death.
Fig 12. Suicide by Employment
Figure 11 shows the percentage of deaths in Hertfordshire given a coroner’s conclusion of suicide at inquests held between 2017 and 2019 in each Hertfordshire IMD quintile based on their postcode address. A higher percentage of suicides were observed in more deprived areas of Hertfordshire, particularly in the second most deprived quintile.
The Hertfordshire Suicide Audit states that mental health issues is the most reported risk factor for suicide. Other risk factors were also explored, many relate to deprivation and other known health inequalities. For instance, as shown in Figure 12, 19% of suicides audited were retired and 18% were unemployed, despite these groups comprising 12% and 3.5% of the Hertfordshire population.
Within the county, among all deaths with a coroner inquest conclusion of suicide between 2017 and 2019, 67.4% had a mental health issue or condition recorded by their GP practice. A report published by The Samaritans explores how inequalities place socio-economically disadvantaged individuals at higher risks of suicidal behaviours [9]. At an individual level, stressful negative life events, such as childhood adversity, financial crises, bereavement and relationship breakdown are risk factors for suicidal behaviours. At a community level; contextual factors such as the lack of non-precarious job opportunities, absence of local support networks, and exposure to other individuals’ suicidal behaviours, increase the risk of suicide. Notably, 69% of those who died by suicide had a mental health condition listed on their health record, but only 28% where known to mental health services at the time of their death.
Fig 13. Suicide rate
As suicide rates at local authority are based on small numbers, the change in trends are often results of random fluctuations. Sex breakdown are only presented at county and country level.
Hertfordshire’s suicide rate for all persons is lower than England and historically the rate has been significantly lower. However, since 2011-2013 the rate has started to increase and reached a high of 9.19 per 100,000 in 2018-2020. Male suicide rates are significantly higher than those of females, with the rate being three times higher in the latest time period. The difference between the sexes is statistically significant and in line with national figures which found men accounting for three-quarters of suicides, a consistent trend since the mid-1990s [10]. The disparity in suicide rates between males and females is long rooted. The reasons for higher suicide rates in males is multifaceted, and includes factors such as social constructions and expectations of masculinity, greater loss of social support post-relationship breakdown, and the lack of ability and willingness to recognise, talk and cope with their distress [11].
Healthcare Access Inequalities
Easy and early access to services is one way to address inequalities in mortality by finding, treating, and managing conditions more proactively. However, access to services is affected by deprivation, with those in the most deprived areas sometimes being less likely to access preventative care.
NHS Health Check
NHS Health Check is a free health check-up for adults aged between 40 and 74 in England who do not have existing morbidities. It is aimed to identify early signs of a range of non-communicable diseases such as stroke, kidney disease, heart disease, type 2 diabetes and dementia [12].
Fig 14. NHS Health Check Uptake
Figure 14 shows the proportion of people in Hertfordshire being offered and receiving an NHS Health Check in 2019/20. Whilst the proportion of the population being offered a check is similar across deprivation levels, the proportion subsequently taking up the offer is substantially lower in the most deprived quintile compared to the least deprived quintile.
GP Experience
Fig 15. GP Access & Mortality
Figure 15 illustrates the relationship between the percentage of patients having a positive experience of their GP practice and potential years of life lost (PYLL) in 2020 by Primary Care Network (PCN) in Hertfordshire. The most and least deprived PCNs are highlighted in light and dark blue respectively. PYLL is a measure of the number of years a person who died would have been expected to live if they died earlier than would be expected from a given cause of deaths. There is a clear relationship between deprivation, PYLL and satisfaction with access to GP practices with patients in more deprived areas both having less satisfaction and more years of life lost.
As addressed in Figure 9, many of the leading causes of inequality in mortality are not simply an issue of heightened risk of diseases, but also timely, efficient diagnosis and delivery of health services to manage the conditions. Population from more deprived areas experience greater barriers to timely and appropriate care. These barriers can be structural, economic, and cultural. Lang et al demonstrated that more deprived populations have a lower uptake for screening programmes for cardiovascular disease, cervical cancer, and diabetic retinopathy, despite them having a higher need for such services due to the high prevalence of these conditions in more deprived areas [13]. Even if individuals are aware of the need to be screened, they may face economic barriers to do so. Indirect costs such as transportation and lost opportunity cost for missing work are likely to drive low utilisation of health care services within some groups. Cultural barriers also play an important factor to access to care, for instance the availability of information in different languages and differences in health beliefs [14].
COVID-19 and Inequalities
The COVID-19 Marmot Review found that the UK entered the pandemic with large and growing health inequalities and that over time the impacts of the virus have exposed and amplified these pre-existing issues [3]. The section explores how COVID-19 has impacted health inequalities within Hertfordshire.
Infection and Mortality Rates
Fig 28. Case rate
Figure 28 shows COVID-19 case rates by Hertfordshire deprivation quintiles. It can be observed that populations in the most deprived Hertfordshire quintile have generally had higher case rates than the least deprived areas.
Fig 29. COVID-19 Mortality
Figure 29 illustrates deaths attributed to COVID-19 in Hertfordshire by levels of deprivation. Similar rates were observed between the start of the pandemic in March 2020 and September 2020. However, starting from September 2020, the difference in death rates between the most and least deprived started to diverge, with higher deaths rate being observed in the most deprived quintile.
Bambra et al labelled the COVID-19 pandemic as a syndemic, as a common set of social underpinnings, many of which have been highlighted earlier in this report, which have interactively and cumulatively exacerbated the disease burden of a population [39]. These include;
Pre-Existing Conditions
According to a systematic review conducted by Ssentongo and colleagues, cases with pre-existing diseases such as cardiovascular disease, chronic kidney disease and cancer had a significantly higher risk of COVID-19 mortality [40].
Occupation
It is also evident that more severe COVID-19 outcomes are experienced in patients in certain workplaces compared to others. Analysis from COVID-19 deaths through Reporting of Injuries Diseases and Dangerous Regulations illustrated higher risks in occupations including, but not exclusive to social care, nursing, drivers, food processing and retail [41]. These are often jobs which working from home is not supported and social distancing is limited.
Deprivation and Overcrowding
Other than health status and occupations, more deprived populations are also exposed to higher COVID-19 risks, including overcrowded households. As discussed in the Social Determinants of Health section, overcrowded households are more common in more deprived areas. Overcrowded household are more likely to have poor ventilation may be a cause for higher mortality rates in more deprived areas [42].
Ethnicity
In the COVID-19 Marmot Review, BAME populations were found to have higher COVID-19 mortality [24]. The BAME workforce often has higher exposure to disadvantaged social and economic conditions. This includes having jobs that do not facilitate working from home and overcrowded households, as well as poorer access to healthcare.
Vaccine Equity
The vaccine rollout in the UK started on 8th December 2020. The Joint Committee on Vaccine and Immunisation advised the prioritisation for the vaccination programme should be primarily based on age, as risk of mortality from COVID-19 increases with age [43]. The order of priority for the first nine priority groups used UK data from March to June 2020, corresponding with the number of individuals who need to be vaccinated to prevent one death. These nine priority groups are estimated together to account for around 99% of preventable mortality from COVID-19 [44].
Fig 30. Vaccine by Deprivation
Figure 30 shows vaccine uptake in Hertfordshire by IMD, with those in the more deprived quintiles having a lower percentage of vaccine uptake across age groups than those in less deprived quintiles. Using the survey on vaccine hesitancy conducted by the ONS, vaccine uptake mirrors that of vaccine hesitancy, where adults in more deprived areas report higher levels of hesitancy (16%) compared to the least deprived (7%) [44].
Fig 31. Vaccine by Ethnicity
Figure 31 shows percentage of double-vaccinated adults in Hertfordshire and West Essex ICS who are eligible for vaccinations across ethnic groups. Uptake of vaccination in the White ethnic group was significantly higher than in any other ethnic group. The highest vaccination rate for a non-White ethnic group was found in the Asian or Asian British group, with a rate of 72.1%. The lowest rates were found in the Mixed, and Black or Black British group, at 46.5% and 60.1% respectively. This is similarly reflected in ONS’ survey on vaccine hesitancy, where Black or Black British had a particularly high level of vaccine hesitancy (44%), followed by Mixed ethnic group (17%), compared to that of people from a White ethnicity (8%) [45].
The World Health Organisation highlighted vaccine hesitancy as a leading threat to global health [46]. A qualitative study on UK healthcare staff’s attitudes towards vaccination found high levels of suspicion and mistrust towards vaccine development process in Black ethnicities being a factor contributing to hesitancy. This is partly due to Black and Asian ethnic groups being underrepresented in trials, but is also driven by higher levels of misinformation, less effective official communications, and language and cultural barriers [45,47]. As vaccinations begin to lower the impact COVID-19 has, areas and groups with lower uptake may be slower to recover.
While vaccination have been often labelled as a major factor in getting society “back to normal”, the 2020 Marmot Report commented that pre-pandemic state of health is not “normal” with wide and growing disparity in some areas. The COVID-19 pandemic has exposed and amplified these inequalities and provides an opportunity to build back fairer.
Conclusion
Whilst Hertfordshire has generally good outcomes for health and wellbeing compared to England as a whole there are large inequalities within Hertfordshire both within deprived areas and specific segments of the population. Reducing inequalities will require interventions, policies, and programmes to be tailored to the needs of specific groups of the population. There is evidence that for at least some services the offer of support is made universally but that uptake is less in deprived groups.
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Coronavirus and BAME people, Housing: https://publications.parliament.uk/pa/cm5801/cmselect/cmwomeq/384/38408.htmONS, Claimant count QMI: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/methodologies/claimantcountqmiBambra et al., The COVID-19 pandemic and health inequalities, 13 June 2020: https://jech.bmj.com/content/jech/early/2020/06/13/jech-2020-214401.full.pdfSsentonogo et al., Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis, 26 August 2021: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238215Gov.UK, Industrial Injuries Advisory Council, COVID-19 and occupation: position paper 48, 25 March 2021 https://www.gov.uk/government/publications/covid-19-and-occupation-iiac-position-paper-48/covid-19-and-occupation-position-paper-48Aggarwal et al., High Viral Load and Poor Ventilation: Cause of High Mortality From COVID-19, 25 July 2020: https://journals.sagepub.com/doi/full/10.1177/1010539520944725Gov.UK, Joint Committee on Vaccination and Immunisation: advice on priority groups for COVID-19 vaccination, 30 December 2020: https://www.gov.uk/government/publications/priority-groups-for-coronavirus-covid-19-vaccination-advice-from-the-jcvi-30-december-2020/joint-committee-on-vaccination-and-immunisation-advice-on-priority-groups-for-covid-19-vaccination-30-december-2020#vaccine-priority-groups-advice-on-30-december-2020Office for National Statistics, Coronavirus and vaccine hesitancy, Great Britain: 13 January to 7 February 2021, 8 March 2021: https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/healthandwellbeing/bulletins/coronavirusandvaccinehesitancygreatbritain/13januaryto7february2021Robertson et al., Predictors of COVID-19 vaccine hesitancy in the UK household longitudinal study, 6 March 2021: https://www.sciencedirect.com/science/article/pii/S0889159121001100#s0035British Medical Journal, Cultural competence in covid-19 vaccine rollout, 18 December 2020: https://www.bmj.com/content/371/bmj.m4845Woodhead et al., Race, ethnicity and COVID-19 vaccination: a qualitative study of UK healthcare staff, 06 June 2021: https://www.tandfonline.com/doi/full/10.1080/13557858.2021.1936464
Social Determinants of Health
Education
Education is strongly linked to health, with those obtaining higher levels of education being more likely to live longer and have lower morbidity, as well as having higher living standards [15].
Children achieving a good level of development at the end of Reception
Children attaining a good level of development have achieved the expected level in early learning goals in key skills needed to make a good start in their next educational stage [16]. Some children qualify for free school meals (FSM) status if their parent(s) or guardian(s) are in receipt of certain benefits, including Income Support and Jobseeker’s Allowance [17]. By looking at how attainment differs between those eligible for FSM and the total population, an understanding of the relationship between educational attainment, and parental income can be reached.
Fig 16. All and FSM students
In comparison to the overall attainment rate, children eligible for FSM have lower rates of attainment at the end of secondary school, lower rates of employment in the future, and are more likely to receive benefits when they are older [18]. Figure 16 shows that in both England and Hertfordshire there is a significant gap between the attainment of children depending on their FSM eligibility, with those eligible having significantly lower achievement. In Hertfordshire, this inequality is even more pronounced at almost 22%. While the percentage of children achieving a good level of development at the end of reception is significantly better in Hertfordshire than England overall, when assessing those eligible for free school meals, Hertfordshire performs significantly worse than England and the gap has widened since 2016/17. Reducing this gap in attainment at a young age is essential for reducing health inequalities and removing the poverty gap between these two groups.
Due to COVID-19, data for this measure has not been collected since 2018/19.
Attainment 8 Score
The Attainment 8 score refers to a student’s average grade across eight subjects at GCSE, including Maths and English, three qualifications that count towards the English Baccalaureate including the Sciences and the Humanities, and any other remaining GCSEs [19]. Since 2016/17, there has been a change in the GCSE grading system which may have contributed to the decrease in Attainment 8 score [19].
In 2019/20, due to the COVID-19 pandemic, GCSE exams and coursework were not assessed by exam boards. Instead, GCSE grades were awarded based on teachers’ assessments, which may account for the large increase in Attainment 8 score between 2018/19 and 2019/20 seen across many areas [19].
Fig 17. Attainment at 15
Fig 18. Attainment at 15 in care
Fig 19. Attainment at 15 by Ethnicity
Figure 17 shows that the Average Attainment 8 score is higher in Hertfordshire than in England. Within Hertfordshire districts, St Albans, the second least deprived district, has the highest Attainment 8 score across all years the data is available, and Stevenage, the most deprived district, has the lowest Attainment 8 score.
For children in care, shown in Figure 18, the average Attainment 8 score is less than half for both Hertfordshire and England students.
Figure 19 shows Average Attainment 8 score by ethnicity within Hertfordshire. Both boys and girls in the Chinese and Asian ethnic groups have a higher Attainment 8 score than any of their other counterparts. Girls in the Black ethnic group had lower attainment than other groups with a downwards trajectory. For boys, Black, Mixed, and White ethnic groups had consistent lower attainment.
Adverse Childhood Experiences
Adverse childhood experiences (ACEs) are situations where young people are exposed to experiences including: abuse or neglect; living in households where domestic violence, drug, or alcohol abuse occurs; if mental ill health, criminality, or separation is present; or living in care [20]. These situations can be experienced simultaneously, and increase the likelihood of children and young people facing damaging impacts on health, and other social outcomes throughout their lives [20].
A report by the Institute of Health Equality found that children who are exposed to ACEs are more likely to die at a younger age than those who are not exposed, as well as being more likely to experience some long-term health conditions, such as diabetes. They also have an increased risk of mental ill health in adulthood [20].
Fig 20. ACEs by districts
Figure 20 shows the results of a 2017 study into the prevalence of ACEs, which found that in every Hertfordshire district, except Watford, had at least 40% of respondents reporting that they had experienced at least one ACE [21]. About 25% had experienced two ACEs, and 8% experiencing three or more ACEs [21].
The Built & Natural Environment
Environment
The Access to Health Assets and Hazards provides a measure of how “healthy” neighbourhoods are [22]. This is measured by four domains of accessibility: retail environments, health services, physical environment (such as blue space and green space including parks, rivers, playgrounds, and allotments), and air quality [22]. These factors influence physical activity levels, community strength, and mental health.
Fig 21. Nitrogen dioxide levels
There is clear evidence that poor air quality contributes to mortality and ill health [23]. Figure 21 shows that within Hertfordshire, the most deprived LSOAs are exposed to a significantly higher concentration of nitrogen dioxide in comparison to the least deprived LSOAs. As the level of deprivation decreases, the concentration of nitrogen dioxide decreases, suggesting that people in the least deprived areas may be less likely to experience health problems associated with poor air quality, such as respiratory issues, and longer-term issues such as low birth weights, in comparison to those in the most deprived areas [23, 24]. In 2019, 5.7% of mortality within Hertfordshire was attributable to particulate air, compared 5.1% of overall mortality in England [25].
Fig 22. Distance to fast food outlets
Obesity is a major health problem within the UK and is associated with an increased risk of diseases including cardiovascular disease, type 2 diabetes, and at least 12 types of cancer [26]. The prevalence of obesity shows a link with IMD, with 39.5% of women and 30.2% of men living in the most deprived areas suffering from obesity, compared to 22.4% of women and 21.9% of men living in the least deprived areas [26]. There is growing evidence that associates the density and closeness of fast-food outlets with obesity [27]. In Hertfordshire, the most deprived areas have a statistically significantly shorter distance to fast food outlets, in comparison to the least deprived areas. The distance to fast food outlets generally increases as deprivation decreases.
Obesity puts considerable pressure on our health service, with overweight and obesity related conditions costing the NHS £6.1 billion each year, with 900,000 obesity related hospital admissions in 2018-19. By reducing the number of overweight and obese people, doctors and nurses would have more time to focus on other sick and vulnerable patients [28].
Fig 23. Distance to green spaces
There is a positive association between access to green space, and physical activity levels [29]. High levels of physical inactivity contribute to the development of many major health problems, including cancer, obesity, and cardiovascular disease, which have been shown to have higher prevalence in more deprived areas [30]. In Hertfordshire, the nearest green spaces are on average 1.25km away for population in the most deprived LSOA’s, whilst in the least deprived LSOA’s the distance is only 400m. This increases the barriers for those living in more deprived areas to participate in healthy activities.
The above data gives suggestions of why health inequalities may exist between areas of different deprivation, with areas of higher deprivation having larger exposure to nitrogen dioxide, shorter distances to fast food outlets, and longer distances to green spaces. These environmental factors need to be addressed in order to reduce health inequalities between areas.
Rough Sleeping
Rough sleepers are one of the most disadvantaged groups in society, due to the lack of secure accommodation, as well as often having co-existing health issues and vulnerabilities. In a recent report by the Ministry of Housing, Communities, and Local Government, 82% of rough sleepers were found to have a mental health vulnerability, 83% a physical health need, and 60% a substance misuse need [31]. Rough sleeping is estimated by a “snapshot” counting on a single date between 1st October and 30th November of each year, so may not include everyone in an area with a history of sleeping rough during those two months.
Fig 24. Rough sleeping by gender
In Hertfordshire, the estimated number of rough sleepers fluctuates between years and districts. There is a considerably higher number of men than women across all years and areas. The area with the lowest number of rough sleepers across all years is Broxbourne, whilst Watford, Stevenage, and St Albans have the highest numbers.
Across all districts, the number of male rough sleepers is higher than female, with 5 or less females recorded for every district. The highest number of female rough sleepers was in 2017 in Welwyn Hatfield with 5, whilst the highest number of male rough sleepers was in Watford in 2019 with 15.
Rough sleeping has a significant impact on someone’s physical and mental health and increases the risk of developing additional mental and physical health needs, substance abuse issues, and having contact with the criminal justice system. People who are rough sleepers are almost 17 times more likely to have been victims of violence, with more than one in three having experienced violence such as hitting or kicking whilst homeless. The average age of death for rough sleepers is 45 for men and 43 for women, and homeless people are over nine times more likely to die by suicide than the general population [32]. By reducing homelessness and rough sleepers, there will be a reduction in health inequalities and improvement in health outcomes [33].
Levels of overcrowding
A household is considered overcrowded if it has fewer rooms available than recommended, or under-occupied if it has more [34]. The room standard allocates a separate room to each adult couple, any remaining adult over 21, each same sex pair aged 10 to 20, and each pair of children under 10. Living room and bedrooms count as rooms, as do kitchens if they are large enough to accommodate a bed [34]. Fewer rooms than people means the home is classified as overcrowded, with equal rooms to people or more classified as have a sufficient number of rooms. Overcrowding can affect health, including increased risk of intestinal and respiratory infection, as well as risk to mental health from frequent sleep disturbance when adults share beds or bedrooms with children [35].
Overcrowding may occur due to multi-generational families residing in one home or family tradition, sharing costs, and allowing family members to help with care is common in some ethnic minority households. For example, almost 38% of Bangladeshi households are classed as overcrowded. More deprived areas have a higher level of overcrowding than areas in the least deprived [36].
Fig 25. Overcrowding by IMD
Figure 25 shows the percentage of households with some level of overcrowding or where the number of people equals the number of rooms. As deprivation decreases, the percentage of households being overcrowded decreases, with households in the most deprived areas being over four times more likely to be overcrowded and more than twice more likely to have a rating of equal rooms to people than the least deprived areas.
Fig 26. Overcrowding by ethnicity
Figure 26 shows overcrowding analysed by ethnicity; Bangladeshi, Other Asian, and Gypsy or Irish Traveller ethnic groups have the highest percentage of overcrowding. Bangladeshi, Indian, and Chinese households are particularly likely to have people aged over 65 living with children under the age of 16 [37]. The lowest levels of overcrowding are seen in White British and White Irish. Similarly, White Irish were more likely to have two or more spare rooms, followed by White British, whilst Bangladeshi and Gypsy or Irish Traveller were least likely to have two or more spare rooms.
Income
Claimant Count
The Claimant Count is the total number of people claiming unemployment-related benefits, principally for the reason of being unemployed, collected by the Department for Work and Pensions (DWP) [38]. Whilst it does not include everyone who is unemployed, it represents a large proportion of those unemployed, and is less volatile for smaller areas.
Employment rates are used as a primary indicator to measure the economic health of an area, which affects income, interest rates, and inflation. Areas with a low employment rate can have an increased risk of social problems, such as higher crime rates, and increased poverty.
Fig 27. Unemployment benefit claimants
The percentage of people claiming unemployment related benefits is higher for those living in the most deprived areas, with 5.3% of those eligible claiming unemployment benefits, four times more than those in the least deprived area. Claimant count appears to be linked with deprivation levels; as deprivation levels decrease, the percentage of claimants also decreases.