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Overview

This report is a comprehensive review of health in the East Midlands and builds on the findings of the Health Profile for England.

This report includes a set of important health-related topics based on the Health Profile of England. It highlights the universal impact of COVID-19 as well as presenting inequalities between the least and most deprived areas, and variation in health behaviours seen in each region in England. As we move into the post pandemic and recovery phase there are emerging opportunities to sustainably tackle the historical and emerging challenges through the Levelling Up1 and soon to be published Disparities White Papers. Action will be supported via greater integration between the NHS and social care enabled by the development of Integrated Care Systems.

The data in this report provides evidence of the impact of COVID-19 on life expectancy, increasing risk factors in our population and the impact on the determinants of health which will have an enduring and long-term impact on the health of our population.

Healthy life expectancy at birth had started to decrease or level off in most regions before the pandemic. This represents an increasing number of years lived in poor health, resulting in a reduced ability to work, a reduced sense of wellbeing and an increased need to access services.

In all regions obesity was the largest contributor to morbidity. Smoking and diabetes were the second and third largest contributors although their placing varied in different regions.

In many areas we have seen a widening of inequalities between the most and least deprived areas. The harms to health are not uniform, data in this report tells a compelling story about widening health inequalities and variations in health behaviours.

There are also areas of improvement, the proportion of mothers smoking at the time of delivery continues to decline and antibiotic prescribing continues to decrease.

Taken together, these data confirm that we are now observing the direct and indirect impacts of the COVID-19 pandemic on all parts of society, with many chronic health conditions worsening and most historically disadvantaged areas being further so. This has resulted in greater health need and widening health inequalities in all parts of the nation. The findings reinforce the need for targeted increases of clinical and preventive services recovery programmes with a resolute focus on secondary prevention called for in the NHS Core20Plus5 initiative. As we have learned throughout the pandemic the nature and scale of the challenges cannot be met by any single agency. We must harness the full potential of our newly transformed public health and health care systems, guided by the new national strategies and frameworks, working closely with our partners in place, and engaging and mobilising local communities. Ultimately, these data confirm areas for system-wide prioritisation, mobilisation and action.


Introduction

The Regional Health Profile for England 2021: East Midlands report provides a comprehensive look at the state of the region’s health. It presents a range of population health data, such as smoking and obesity as well as providing an early summary of the impact of the COVID-19 pandemic on many aspects of health and health inequalities. The report provides a regional view of health and indicators presented in the Health Profile for England 2021, first produced by Public Health England (PHE) in 2017.The purpose of this regional report is to provide an overarching summary of the health of the population of the East Midlands for key public health stakeholders. The key stakeholders for this report are the Office for Health Improvement and Disparities, UK Health Security Agency and NHS England and Improvement. The report will also be of interest and importance to the wider public health system. The report gives a clear and consistent description of the health challenges facing the population and is a useful background document to support public health organisations working together to improve population health. It will be used to support and inform regional public health strategy and priority setting.

As the first edition of the Health Profile for the East Midlands region, the report includes public health intelligence about prevalence, regional trends, local authority comparisons, and health inequalities. The interactive charts and interpretation are grouped by these key themes:

The East Midlands edition is part of a set of nine new regional profiles that have been produced following the content, format, and methods and definitions published in the Health Profile for England. Content differs from the national report and between regions depending on the availability of regional level data and indicators. For example, the regional reports provide local authority comparisons benchmarked mostly against regional averages, whereas the Health Profile for England provides a wider view from international to regional comparisons. The regional editions do not include all the inequality breakdowns available in the England report, as some of the sub-national breakdowns are not available. Some references to the national level inequalities data, however, have been presented here for important context about how health outcomes and risks vary by ethnicity, age, sex and socioeconomic status and area deprivation.


Note on the format of the report

Charts in this report follow a standard format, with three sections for each topic area where data is available:

Headline - overall data for the key indicator used in the East Midlands, usually as a trend over several years. Regions are defined as government regions. Where this is not possible, other geographical region definitions are used as indicated in the supporting information.

Inequalities - how the indicator varies between different groups in the East Midlands, by protected characteristics such as age, sex and ethnicity or categories of socioeconomic deprivation where possible. Some inequalities information presented at national level in the Health Profile for England 2021 is not available at regional and sub-regional levels.

Sub-regional comparison - headline information on the indicator variation is presented at the Upper Tier Local Authority (UTLA) level - referred to as ‘local authorities’ in the narrative. UTLAs affiliated with the government region are shown unless stated otherwise. UTLA codes and boundaries are subject to change pending the data released. It is not always possible to use the same indicator for the headline, inequalities and sub-regional comparisons within each topic area.

Note on date formats - where more than one calendar year is used to calculate a measure, then a hyphen is used to show which years are included i.e. 2019-2020 for a two-year average. Where the data used covers a financial year or an academic year, a slash is used to indicate which years are covered i.e. 2019/20 indicates that the data covers April 1 2019 to March 31 2020. When describing change over time, the preposition ‘to’ is used.

Note on statistical significance - point estimates for lower geographies are compared to a national, regional or benchmark value. Where confidence intervals do not overlap with the reference point estimate, the difference is statistically significantly different. This is described as significantly higher or lower in the narrative. Where confidence intervals do overlap, the point estimates are described as similar. Where two time points or categories are compared for the same geographical area, statistical significance is based on overlapping confidence intervals around each point estimate and described in the same way as above.

Further information is available from the Health Profile for England data methods and definitions but please note that not all England level indicators have been used in this report.


Key findings

The East Midlands is home to a diverse population. When compared to England, deprivation appears to be lower in the region overall, but this masks the wide inequalities within the region. Inequalities exist in all places across the East Midlands whether they are urban, industrial, rural, or coastal communities. The city areas of Leicester, Nottingham and Derby are significantly more deprived than average with 1 in 5 people living in an area classed as income deprived and more than 1 in 4 children living in poverty.

Through mechanisms related to this socioeconomic deprivation, these populations experience poorer housing and working conditions, fuel poverty and reduced access to goods and services that improve health. In the industrial towns of the counties there has been a decline in the local jobs market also leading to socioeconomic disadvantage. Intersectionality describes how these multiple forms of disadvantage interact with individual characteristics such as gender, ethnicity, and age, resulting in the health inequalities presented throughout this report.

Many other factors impact on population health and wellbeing, such as age, sex and ethnicity. It is important to note that Leicester, Nottingham and Derby have significant proportions of their populations from ethnic minority groups.

Nationally, the evidence shows that the COVID-19 pandemic has exacerbated existing inequalities in both risk factors and outcomes. During the first year of the pandemic, the employment rate decreased in the region overall, worsening the socioeconomic drivers of health outcomes already experienced by the most deprived areas.

Across the East Midlands, there has been an increase in risk factors for ill health. This is particularly evident in the measures of self-reported wellbeing which show concerning trends over the pandemic, with significant percentage point increases in self-reported anxiety, low happiness, and satisfaction among the region’s population. The East Midlands has significantly higher rates of hypertension, obesity and smoking than the England average. Trends in obesity rates in the East Midlands show that this has been increasing in recent years in both adults and children. The impact of the pandemic on adult obesity levels is not known but given the changes in other risk factors presented (diet, physical activity and alcohol), it is possible we will see an increase in prevalence and a widening of inequalities. Smoking remains the risk factor most associated with lower life expectancy and healthy life expectancy. Overall smoking prevalence in the East Midlands continues to decline but remains higher than the England average. Inequalities in smoking prevalence among those in routine and manual occupations and those with a long-term mental health condition persist. There has also been an increase in the rate of deaths from alcohol-specific conditions, which were particularly high in 2020.

Added to these increasing risk factors for ill health is the impact of the pandemic on the use of health services. This may have influenced health outcomes across the life course. There were significant reductions in outpatient and inpatient admissions to hospital during the pandemic. Whilst emergency hospital admissions have returned to pre-pandemic levels, outpatients and elective admissions are still below average levels. Of particular concern is a reduction in new cancer patients entering treatment, over 8,000 lower for the Midlands (East and West combined) during the time period analysed compared to pre-pandemic levels. It will not be known for some time how this will affect health outcomes.

The direct and indirect impact of COVID-19 has resulted in a decline in overall life expectancy across the region. There were over 13,000 deaths registered with COVID-19 mentioned on the death certificate by the end of 2021. Because of this, COVID-19 became the leading cause of death for men in the region and the second largest cause of death among females after dementia and Alzheimer’s disease.

The impact on existing inequalities in mortality and life expectancy is evident. The difference in life expectancy between the most and least deprived areas in the region increased for both males (by 1.2 years to 9.7 years difference) and females (0.9 years to 8.5 years difference).

Healthy life expectancy is decreasing in the East Midlands for both males and females, and in 2017-2019 was 62.2 years for males and 61.9 years for females. Healthy life expectancy is a key metric for understanding overall health, but we cannot yet see the impact of the Covid pandemic on this metric. It is important to note that healthy life expectancy was declining prior to the pandemic, with women expecting to live for 21 years with poor health and men 17.4 years. The increase in the number of years that people will live with poor health reduces their ability to work, reduces their sense of wellbeing, and increases their need to access services.


Introduction to the East Midlands

The East Midlands is made up of ten local authorities: Derby, Derbyshire, Leicester, Leicestershire, Lincolnshire, North Northamptonshire, West Northamptonshire, Nottingham, Nottinghamshire, and Rutland. In April 2021, North Northamptonshire and West Northamptonshire were formed when Northamptonshire County Council split was transformed into two new unitary authorities. Because this change is comparatively recent, there are sections throughout the report where data is presented at the Northamptonshire level as opposed to North and West Northamptonshire separately.

Based on population estimates from mid-2020, the East Midlands has a population of 4.9 million people, equating to 9% of the England population. The population of the East Midlands continues to grow and is expected to increase to 5.5 million people by 2043, an increase of 11% from 2022. However, the East Midlands population is ageing. In 2022, it was estimated that 992,583 people (20%) in the East Midlands were aged 65 and over. By 2043, this is projected to increase to just under 1.4 million people, resulting in 25% of the population being aged 65 and over.

In the East Midlands, 34% of the population live in rural areas, whereas 66% live in urban areas, and 18% of the East Midlands population live in the most deprived quintile. In 2019/20, 18% of children lived in relative low income families. In the 2021 Annual Population Survey (APS), 420,200 people in the East Midlands were from ethnic minorities, equating to 11% of the East Midlands population.

The city areas have higher than average proportions of the population that are from ethnic minorities; Leicester (49%), Nottingham (24%) and Derby (17%). These areas are also the most deprived local authorities in the region, with around 20% of people living in an area classed as income deprived. In 2019/20, the proportion of children living in relative low income in these areas was as high as 31% in Leicester, 27% in Nottingham and 24% in Derby. There are also other pockets of deprivation in the industrial towns of the county areas and coastal Lincolnshire. These inequalities in wider determinants are reflected in the inequalities in health outcomes seen across the region.


COVID-19

Introduction

This section examines the direct impact of the COVID-19 pandemic on health with analysis of COVID-19 cases, death rates involving COVID-19, excess deaths, and vaccination rates during the pandemic up until 31 December 2021.


England had experienced 2 main waves of cases by the end of June 2021. The first wave took place in spring 2020 and the second from autumn 2020 to spring 2021. The timing of the second wave varied throughout the country and cases in regions in the north of England were relatively high in October and November 2020, while in regions in the south of England case rates increased later in December 2020 and January 2021.


COVID-19 cases

The data in figure 1 shows that:

  • at the end of December 2021, 1,020,990 confirmed cases of COVID-19 had been reported in the East Midlands
  • the region’s highest 7-day average case rate occurred in the week ending on 31 December 2021 at 14,696 cases per 100,000 population that week

Cumulative case rates presented may be lower than actual case rates due to the limited community testing in the earlier phases of the pandemic. COVID-19 has impacted some groups more than others and the cumulative confirmed case rates in the region were:

  • by sex, higher in females than males at 21,308 and 19,315 per 100,000 population respectively
  • by age, highest in people aged 25 to 49 at 25,671 per 100,000 population
  • by deprivation, highest in deprivation decile 9 at 21,210 per 100,000 population
  • by ethnicity, highest in the black/black British ethnic group at 23,058 per 100,000 population
  • by population density, highest in the 5th density decile at 21,330 per 100,000 population
  • by local authority, highest in Leicester at 23,702 per 100,000 population. At the end of December 2021, Derbyshire had the highest 7-day rolling rate at 2,059 per 100,000 population


Figure 1 - COVID-19 cases

Figure 1a - Trends

Source: UKHSA COVID-19 dashboard Date accessed: 02/03/2022 Note: Source data are updated daily and historic data may be revised. Download data

Figure 1b - Inequalities

Source: OHID COVID-19 Health Inequalities Monitoring for England (CHIME) tool Date accessed: 23/02/2022 Note: Source data are updated monthly and historic data may be revised. Download data

Figure 1c - Local Authority

Source: UKHSA COVID-19 dashboard Date accessed: 23/02/2022 Note: Source data are updated daily and historic data may be revised. Download data

Deaths involving COVID-19

The data in figure 2 shows that:

  • at the end of December 2021, there were 13,674 deaths registered with COVID-19 mentioned on the death certificate in the East Midlands region
  • the region’s highest 7-day age-standardised mortality rate occurred in the week ending 16 January 2021 at 99 deaths per 100,000 population

There are wide inequalities in death rates involving COVID-19 and the cumulative age-standardised mortality rates in the region were:

  • by sex, higher in males than females at 366 and 222 per 100,000 population respectively
  • by age, highest in those aged 85 and over at 4,615 per 100,000 population
  • by deprivation, highest in deprivation decile 1 (most deprived) at 460 per 100,000 population
  • by ethnicity, highest in the any other ethnic group at 601 per 100,000 population
  • by population density, highest in the most densely populated decile at 458 per 100,000 population
  • by local authority, highest in Leicester at 438 per 100,000 population


Inequalities in death rates from COVID-19 largely reflect inequalities in COVID-19 case rates. However, they are also influenced by differences in survival following COVID-19 infection. During the first wave of the pandemic in England, people aged over 80 years were 70 times more likely to die from COVID-19 once infected, compared with those aged under 40 years2, Survival was higher in females than males, and after controlling for age, deprivation and pre-existing health conditions, survival among many ethnic minority groups remained lower than the white group. The Bangladeshi ethnic group had the poorest survival and had 1.88 times the odds of dying once diagnosed than the white ethnic group. The Pakistani, Chinese, and black other ethnic groups had 1.35 to 1.45 times the odds of dying once diagnosed and the Indian group 1.163. The possible reasons for these differences and further interpretation of ethnic inequalities in COVID-19 mortality rates are discussed in depth in other reports4 5.


Figure 2 – COVID-19 deaths

Figure 2a - Trends

Source: UKHSA COVID-19 dashboard Date accessed: 02/03/2022 Note: Source data are updated daily and historic data may be revised. Download data

Figure 2b - Inequalities

Source: OHID COVID-19 Health Inequalities Monitoring for England (CHIME) tool Date accessed: 23/02/2022 Note: Source data are updated monthly and historic data may be revised. Download data

Figure 2c - Local Authority

Source: OHID COVID-19 Health Inequalities Monitoring for England (CHIME) tool Date accessed: 23/02/2022 Note: Source data are updated monthly and historic data may be revised. Download data

COVID-19: excess mortality

Excess mortality is a measure of how much higher all-cause mortality was in the pandemic period than what would have been expected, based on previous years, had the pandemic not occurred. These figures account for inequalities prior to the pandemic and therefore reflect the disproportionate direct and indirect impact of the pandemic on black and Asian groups and deprived areas. Between 27 March 2020 and 31 December 2021, the excess cumulative all-cause deaths as presented in figure 3 were:

  • 1.13 times higher than expected in the region as a whole
  • by sex, 1.15 times higher in males and 1.12 times higher in females
  • by age, higher than expected in age groups over 25, with the highest excess deaths in the 25 to 49 age group for both males (1.23) and females (1.18) respectively
  • by deprivation, excess mortality was highest in deprivation quintile 3 at 1.17 times higher than expected in males and 1.16 times higher than expected in females, compared to 1.13 and 1.09 times higher in males and females in the least deprived quintile
  • by ethnicity, excess mortality was highest in the mixed ethnic minority group for males at 1.48 times higher than expected, and in the other ethnic minority group for females at 1.47. The lowest excess mortality was in the white ethnic group for males at 1.14 times higher than expected, and in the black ethnic minority group for females at 1.07
  • by place of death, the highest excess mortality was for deaths in the home which were 1.30 times higher than expected. Deaths in care homes, hospitals and other places were also higher than expected. However, deaths occurring in a hospice were 14% lower than baseline
  • by local authority, highest in Leicester at 1.24 times higher than expected


Nationally, there was an association between deprivation and excess mortality, with a ratio of 1.17 in the most deprived areas and 1.13 in the least deprived areas. As with the regional figures, this takes existing inequality in mortality by deprivation into account, so this greater excess mortality in deprived areas is an indication that COVID-19 has exacerbated existing inequalities by deprivation. Further analysis has shown that among black and Asian groups excess mortality in those aged under 75 did not vary by deprivation and was high across all deprivation groups. This indicates that the excess mortality in those aged under 75 in the black and Asian groups cannot be explained by deprivation alone and that other factors might play a role6.


Figure 3 – Excess deaths

Figure 3a - Trends

Source: OHID Excess mortality in England dashboard Date accessed: 07/02/2022 Download data

Figure 3b - Inequalities & UTLA

Source: OHID Excess mortality in English regions dashboard Date accessed: 07/02/2022 Download data

COVID-19 vaccinations

In the East Midlands, by the end of December 2021, 3,710,021 people had only received one dose, 3,443,374 had only received two doses and 2,566,498 had received three doses. However, there has been variation in uptake as presented in figure 4 (for two COVID-19 vaccinations):

  • by country of birth, 89.2% for those born in the UK compared to 77.8% for those born outside the UK
  • by English language proficiency, 89% for those whose main language is English compared to 72.4% for those whose is not
  • by sex, 86.4% in males compared to 89.6% in females
  • by disability, those who report having some level of disability had higher vaccination coverage
  • by deprivation, 92.7% in the least deprived areas compared to 79.6% in the most deprived areas
  • by ethnicity, lowest in those from the black Caribbean ethnic group at 63.1%
  • by housing tenure, lowest in those classed as social rented at 77.3%
  • by religion, lowest in those of Muslim faith at 73%
  • by rural-urban classification, 86.5% among urban populations compared to 91.9% among rural populations
  • by socio-economic class, lowest in those classed as never worked and long-term unemployed at 69.8%
  • by local authority, Nottingham had the lowest uptake for the first dose (68.1%), second dose (61.3%), and third dose (35.3%)


Figure 4 – COVID-19 Vaccinations

Figure 4a - Trends

Source: UKHSA COVID-19 dashboard Date accessed: 02/03/2022 Note: Source data are updated daily and historic data may be revised. Download data

Figure 4b - Inequalities

Source: OHID COVID-19 Health Inequalities Monitoring for England (CHIME) tool Date accessed: 23/02/2022 Note: Source data are updated monthly and historic data may be revised. Download data

Figure 4c - Local Authority

Source: UKHSA COVID-19 dashboard Date accessed: 02/03/2022 Note: Source data are updated daily and historic data may be revised. Download data

Life expectancy and mortality

Introduction

This section examines trends and inequalities in all-cause mortality, mortality from leading causes of death and life expectancy. It presents data for the pre-pandemic period, and 2020 data where it is available.


Life expectancy

Trends in life expectancy at birth from 2001 to 2020 have increased for both males and females in the East Midlands region. However, compared to 2019, life expectancy fell in 2020 by 1.2 years for males to 78.5 years and 0.8 years for females to 82.3 years. Out of the nine regions in England, the East Midlands region had the fifth largest fall in life expectancy for males and the sixth largest fall for females. The fall in life expectancy represents widening inequalities in health outcomes. Figure 5 shows that:

  • by deprivation, the largest fall in life expectancy was in the most deprived decile for males at 2.2 years, down to 72.6 years. For females, the largest fall was also in the most deprived decile at 1.7 years, down to 77.4 years
  • by local authority, life expectancy for males was significantly lower in 2020 in Derby (76.4 years), Nottingham (75.6 years) and Leicester (75.0 years), compared to the East Midlands average. Life expectancy for females was significantly lower in Derby (81.3 years), Nottingham (80.7 years) and Leicester (80.4 years). The city areas saw the largest decreases in life expectancy during the pandemic

The slope index of inequality (SII) is a measure of the social gradient in an indicator and shows how much a health outcome varies with deprivation. It takes account of inequalities across the whole range of deprivation within England and summarises this into a single number. The measure assumes a linear relationship between the indicator and deprivation7. The higher the value of the SII, the greater the inequality within an area. Within the East Midlands region in 2020 there was a difference of:

  • 9.9 years between the most and least deprived males in the region, an increase of 1.1 years compared to 2019
  • 8.6 years between the most and least deprived females in the region, an increase of 1.5 years compared to 2019


Figure 5 – Life expectancy

Figure 5a - Trends

Source: OHID Public Health Outcomes Framework Date accessed: 10/06/2022 Download data

Figure 5b - Inequalities

Source: OHID COVID-19 Health Inequalities Monitoring for England (CHIME) tool Date accessed: 02/03/2022 Note: SII = Slope Index of Inequality. See data and definitions document for more details. Download data

Figure 5c - Local Authority

Source: OHID public health profiles Date accessed: 02/03/2022 Download data

Life expectancy, mortality and Covid-19

The mortality data and life expectancy data presented in this report demonstrate the significant detrimental impact that the pandemic had in 2020 on health outcomes in the East Midlands. However, the direct impacts of Covid will reduce as the population adapts to living with Covid.

Throughout this report, data is presented that starts to explore the wider impacts of Covid on the health of the population. The wider impacts range from increases in wider determinants such as employment rates which will drive health inequalities, increases in risk factors for ill health and a reduction in access to services, particularly in access to cancer services.

It is important to recognise that the wider impacts of the pandemic on the health of the East Midlands will extend beyond the direct impacts on mortality and life expectancy.


Figure 8 – Leading causes of death

Figure 8a
Females
Males

Source: Office for National Statistics Nomis Note: Age groups should be compared with caution as there are many more deaths in older age groups than in younger age groups. Download data

Figure 8b - Inequalities

Source: OHID Wider Impacts of COVID-19 on Health (WICH) tool Date accessed: 07/02/2022 Download data

Figure 8c - Local Authority

Source: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Date accessed: 18/08/2022 Download data

Child health

Introduction

Every child having a good start in life is the foundation for the future health and wellbeing of England’s population. This section presents some key indicators of child health: birthweight, infant mortality, early child development and childhood obesity. The data includes the pre-pandemic period and up to the end of March 2021, where available.


Low birthweight

Low birthweight is a measure of the proportion of full-term babies weighing less than 2,500 grams and is expressed as a proportion of all full-term live births (excludes still births).


In England the last two decades have seen overall improvements in babies born with a low birthweight, infant deaths and child development. However, in the years leading up to the coronavirus pandemic, improvements had slowed down.

Low birthweight increases the risk of childhood mortality and of developmental problems for the child and is associated with poorer health in later life. At a population level, there are inequalities in low birthweight and a high proportion of low birthweight births could indicate lifestyle issues of the mothers and/or issues with maternity services. There are well-established inequalities by ethnic group in low birthweight10. The Health Profile for England found that low birthweight in the most deprived areas was more than double the proportion in the least deprived areas, as measured by the Relative Index of Inequality (RII).


Figure 9 shows that in the East Midlands:

  • prior to the pandemic the proportion of babies born at full term with a low birthweight decreased between 2006 and 2019, from 3.1% to 2.8%
  • in the first year of the pandemic, 2020, the proportion fell again to 2.6%, however, this is not a significant trend
  • in 2020, the proportion was significantly lower than the England average of 2.9%
  • by local authority, in 2020, both Leicester (4.9%) and Nottingham (3.8%) had significantly higher proportions of babies with low birthweight compared to the regional average


Figure 9 – Low birthweight

Figure 9a - Trends

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Figure 9b - Local Authority

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Infant mortality

Infant mortality covers all deaths within the first year of life. The majority of these are neonatal deaths which occur during the first month and the main cause is related to prematurity and preterm birth, followed closely by congenital anomalies11.

The full impact of the pandemic on the infant mortality rate is not yet known, however the latest data suggest that there has been little change. Figure 10 shows that:

  • in the East Midlands region, the rate of mortality fell from 5.5 per 1,000 live births in 2001-2003 to 4.2 in 2018-2020 (figure 10a). The region was similar to the national average of 3.9 per 1,000 in 2018-2020
  • by local authority, both Nottingham (6.1) and Leicester (5.8) had significantly higher rates of infant mortality than the regional average. Lincolnshire (2.6) and Leicestershire (3.3) had a significantly lower rate than the regional average


Figure 10 – Infant mortality

Figure 10a - Trends

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Figure 10b - Local Authority

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Child development

Starting primary school is a significant milestone in a child’s educational journey. Language and communication skills are fundamental to young people’s potential development and achievements later in life12. Being able to express themselves, interact with peers and make themselves understood helps to build a child’s confidence and boost their self-esteem13. Inadequate communication skills can lead to poorer adult outcomes in literacy, mental health and employment14. Data is not available for the Northamptonshire area in the figure below. Figure 11 shows that:

  • in the East Midlands, in the academic year 2018/19, 70.3% of children achieved a good level of development at the end of Reception year, significantly lower than the England average of 71.8%. Although an annual improvement has been observed since 2012, the rate of progress has slowed since 2015/16 (figure 11a)
  • fewer boys than girls achieved a good level of development in the region in 2018/19 at 63.9% compared to 77.0%, respectively
  • by local authority, Nottingham (66.9%) and Leicester (67.7%) had significantly lower rates of children achieving a good level of development at the end of Reception year. Rutland (77.8%) and Leicestershire (72.1%) had rates that were significantly higher than the regional average
  • among children receiving free school meals, 62.8% of females and 46.8% of males achieved a good level of development, lower than for all children and the national average
  • by local authority, for children receiving free school meals, more deprived areas have significantly higher proportions of children in this group achieving a good level of development; Leicester 60.8% and Derby 60.0% compared to the regional average of 54.5%. Nottinghamshire (50.5%) and Leicestershire (48.7%) had significantly lower proportions


Due to the pandemic, data on child development at the end of Reception year was not reported for the academic year September 2019 to July 2020. In March 2020, Early Years settings were closed to most children, with only children from key workers and vulnerable families continuing to attend (around 7% of children aged 2 to 4)15. Outside formal Early Years settings, young children may also have experienced a lack of social activities and interactions that would normally have helped to prepare them for the start of school, such as with grandparents and via play dates.

Although the full impact of the pandemic on early years development will not be known for some time, a study carried out by the Education Endowment Foundation (EEF) found that out of the schools in England surveyed, 76% reported that children who started school in the Autumn 2020 term needed more support than children in previous cohorts. Almost all surveyed schools indicated that they were concerned about pupils’ communication and language development (96%), personal, social, and emotional development (91%) and levels of literacy (89%)16.


Figure 11 – Child development

Figure 11a - Trends

Source: OHID Child and Maternal Health Profile Date accessed: 31/03/2022 Download data

Figure 11b - Local Authority

Source: OHID Child and Maternal Health Profile Date accessed: 31/03/2022 Download data

Childhood obesity

Prevention and treatment of childhood obesity presents a significant public health challenge. Obesity in childhood can result in the early onset of cardio-metabolic, respiratory and musculoskeletal conditions, as well as adverse psycho-social outcomes and an increased risk of living with obesity and its associated morbidity and mortality later in life17. Figure 12 shows that:

  • in the East Midlands, in the academic year 2019/20, data from the National Child Measurement Programme (NCMP) showed that 9.4% of males and 9.0% of females aged 4 to 5 (Reception year) were obese. Trends show that for males there has been little change in prevalence since 2007/08. However, for females, the trend appears to be increasing in recent years
  • among pupils aged 10-11 years (Year 6) in the region, 23.3% of males and 18.2% of females were obese. Trends show that this has been increasing, particularly in recent years, for both males and females
  • by local authority, in 2019/20, Nottingham (12.2%) and Lincolnshire (10.5%) had the highest prevalence of obesity in Reception aged children, significantly higher than the regional average of 9.2%
  • obesity among Year 6 children is significantly higher than the regional average of 21.0% in Nottingham (26.0%), Derby (23.9%), Leicester (23.8%) and Lincolnshire (22.2%)


The latest findings from the NCMP suggest that obesity has increased across all regions in both reception age children and children in year 6. A link between weight gain and out of school time in the school holidays has previously been demonstrated18. Closure of schools, sporting and leisure facilities, park facilities and recreational areas, together with an increase in screen time over the pandemic period have led to a reduction in physical activity in children and young people19. Recent evidence suggest that in England, there has also been a reduction in physical activity in boys, and increase in girls during the pandemic in England. Whereas the differences by deprivation have widened.


Figure 12 – Child obesity

Figure 12a - Trends

Source: OHID Child and Maternal Health Profile Date accessed: 31/03/2022 Download data

Figure 12b - Local Authority

Source: OHID Child and Maternal Health Profile Date accessed: 31/03/2022 Download data

Other indicators of child health

One national survey comparing aspects of mental health found that in 2020, one in six (16.0%) of children aged 5 to 16 years were identified as having a probable mental disorder, increasing from one in nine (10.8%) in 2017. When compared with those unlikely to have a mental disorder, children and young people with a probable mental disorder were more likely to say that lockdown had made their life worse, with 54.1% of 11 to 16 year olds and 59.0% of 17 to 22 year olds stating this, compared with 39.2% and 37.3% respectively20.

Trends in the proportion of school pupils with social, emotional and mental health needs suggest that in recent years this need was increasing in the East Midlands from 2.1% in 2016 to 2.7% in 2021. This equates to 19,175 pupils in the first year of the pandemic.

During the pandemic, England level data shows that hospital admissions of children and young people under 25 (unless otherwise stated) due to asthma, diabetes, epilepsy, gastroenteritis (0 to 4 years), lower respiratory tract infections (0 to 4 years) and accidents were generally below the average for 2018 and 201921. Figure 13 shows that:

  • in 2020/21 in the East Midlands, the rate of admissions to hospital for unintentional and deliberate injuries in children aged 0 to14 years was 56.4 admissions per 10,000 population, a decrease from 103.6 admissions per 10,000 population in 2010/11. Throughout this period the rates of admissions remained significantly lower than the England average
  • by local authority, in 2020/21, Lincolnshire (75.8), Derbyshire (70.5), and Nottinghamshire (60.6) reported hospital admission rates that were significantly higher than the regional average


Figure 13 – Injured resulting in hospitalisation

Figure 13a - Trends

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Figure 13b - Local Authority

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Reports published prior to the pandemic demonstrated inequalities in many other aspects of children’s health22, including during pregnancy. You can find out more about Child and Maternal Health from OHID Fingertips Public Health profiles. Data on maternal smoking in figure 14 shows that:

  • in the region, the proportion of mothers smoking at the time of delivery decreased from 15.8% in 2010/11, to 12.6% in 2020/21. The regional rate remained significantly higher than the national average of 9.6%
  • by local authority, three areas were significantly higher than the regional average, including Lincolnshire (15.8%), Nottingham (13.9%), and Nottinghamshire (13.8%)


The pandemic has had a profound effect on the life of young people, through isolation and interruptions to education. Some of these effects will be longer-term and data are not available to measure them yet.

Prior to the pandemic, in England smoking among teenagers had been reducing, while drug use had increased. The proportion of 15-year-olds who reported they were regular smokers decreased from 12% to 5% between 2010 and 201823.


Figure 14 – Smoking in pregnancy

Figure 14a - Trends

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Figure 14b - Local Authority

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Health in adults

Introduction

Good health is vital to maintaining quality of life in adults. The benefits are wide ranging, from remaining in employment, to maintaining relationships and being involved in activities that provide meaning and purpose24. Helping people to be healthy for as many years as possible is not only important at an individual level but is also vital to the sustainability of the health and care system and the economy25.

This section examines trends in the health of adults prior to the pandemic, and where available, includes data that describes what has happened during the pandemic.


Healthy life expectancy

As well as life expectancy (how long the population could expect to live), it is also important to consider the quality of life or length of time spent in good health. This is referred to as healthy life expectancy. Healthy life expectancy is not available for the years covering the pandemic yet. Healthy life expectancy in the East Midlands (figure 15a):

  • for males in 2017-2019 was 62.2 years. This has decreased by 0.8 years since 2010-2012, increasing the average years of life lived in poor health to 17.4 years in 2017-2019 compared to 16 years in 2010-2012
  • for females in 2017-2019 was 61.9 years. This has decreased by 1.5 years since 2010-2012, increasing the average years of life lived in poor health to 21.1 years in 2017-2019 compared to 19.4 years in 2010-2012


Figure 15 – Healthy life expectancy

Figure 15a - Trends

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Leading causes of morbidity

The Global Burden of Disease uses years lived with disability (YLDs) to attribute the burden of morbidity. YLDs is a measure of morbidity that combines the prevalence of each disease with a rating of the severity of its symptoms (excluding death itself), to give an overall measure of the loss of quality of life. Figure 16a identifies the most common causes of morbidity in 2019 according to GBD, as measured by age-standardised YLDs per 100,000 population. It also shows the change in YLDs since 1990. Change over time needs to be interpreted with caution as this may reflect changes in methodology and categorisation. Overall, the top 3 leading causes of morbidity in the region in 2019 were low back pain, depressive disorders, and headache disorders. However, for:

  • males, the top 3 were low back pain at 990.4 years lived in disability per 100,000 population, diabetes mellitus at 667.1 years, and depressive disorders at 613.8 years. Diabetes mellitus showed the largest change over time with an increase of 375.7 years lived in disability per 100,000 population since 1990
  • females, the top 3 were low back pain at 1303.7 years lived in disability per 100,000 population, headache disorders at 934.4 years, and depressive disorders at 829.5 years. Diabetes mellitus showed the largest change over time at 489.9 years lived in disability per 100,000 population, an increase of 268.9 years since 1990
  • in 2019, the total YLDs per 100,000 population were highest in Derbyshire and Northamptonshire


Figure 16 – Leading causes of morbidity

Figure 16a

Source: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Download data

Figure 16b - Local Authority

Source: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Download data

Mental health and wellbeing

According to the Global Burden of Disease, in 2019, mental health conditions such as depression and anxiety accounted for 14.5% of total morbidity in the East Midlands region.

Figure 17a shows trends in wellbeing up to the end of March 2020, measured by four indicators; anxiety, low happiness, low life satisfaction and low worthwhile feelings. In the East Midlands region:

  • 22.2% of the population reported feeling high anxiety in 2019/20, increasing to 24.1% in 2020/21
  • 9.0% of the population reported feeling low happiness in 2019/20, decreasing to 8.5% in 2020/21
  • 4.3% of the population reported feeling low satisfaction in 2019/20, increasing to 5.9% in 2020/21
  • 3.6% of the population reported feeling low worthwhile feelings in 2019/20, increasing to 3.7% in 2020/21

Figure 17b shows wellbeing trends at local authority level. However, there is no data available for North Northamptonshire and West Northamptonshire. There are some values missing for other local authorities with the exception of Nottingham; this is due to the areas having small sample sizes. Figure 17b shows that there is some variation:

  • anxiety scores were similar to the regional average of 24.1% across all local authorities and ranged from 27.3% in Leicester to 19.5% in Rutland
  • low satisfaction scores were significantly higher in Nottingham at 9.2% compared to the regional average (5.9%)
  • low happiness scores were also significantly higher in Nottingham at 12.8% compared to the regional average (8.5%)
  • there was only enough data to report a low worthwhile feeling score in Nottingham at 4.5%, similar to the regional average of 3.7%


Figure 17 – Mental health and wellbeing

Figure 17a - Trends
<b>Source:</b> <a href = 'https://fingertips.phe.org.uk/public-health-outcomes-framework#page/0/gid/1000042/pat/15/par/E92000001/ati/6/are/E12000004/yrr/1/cid/4/tbm/1' target = '_blank'> OHID Public Health Outcomes Framework </a> <b>Date accessed:</b> 31/03/2022 <a href = 'https://fingertips.phe.org.uk/static-reports/health-profile-for-england/Data/East_Midlands_017a_mental_health_and_wellbeing.csv' target = '_blank'><b>Download data</b></a>

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Figure 17b - Local Authority
<b>Source:</b> <a href = 'https://fingertips.phe.org.uk/public-health-outcomes-framework#page/0/gid/1000042/pat/15/par/E92000001/ati/6/are/E12000004/yrr/1/cid/4/tbm/1' target = '_blank'> OHID Public Health Outcomes Framework </a> <b>Date accessed:</b> 31/03/2022 <a href = 'https://fingertips.phe.org.uk/static-reports/health-profile-for-england/Data/East_Midlands_017b_mental_health_and_wellbeing.csv' target = '_blank'><b>Download data</b></a>

Source: OHID Public Health Outcomes Framework Date accessed: 31/03/2022 Download data

Figure 18 demonstrates trends in self-harm and suicides. It shows that:

  • trends in admissions for self-harm ranged from 224.3 per 100,000 in 2010/11 to 189.6 in 2020/21 in the East Midlands. Since 2016/17, admission rates have been significantly higher than the national average
  • trends for suicide have shown an upward trend in recent years, increasing from 8.9 per 100,000 in 2010-2012 to 9.9 in 2018-2020 in the East Midlands. The region was similar to the national average of 10.4 per 100,000 in 2018-2020
  • at local authority level, West Northamptonshire had the highest person rate for self-harm at 296.8 per 100,000. Lincolnshire had the highest person rate of suicide at 12.6 per 100,000

Severe mental illness (SMI) refers to those people with psychological problems that are so debilitating that they impact on all aspects of life. SMI includes conditions such as schizophrenia and bipolar disorder, as well as personality disorder, eating disorder and severe depression. SMI affects close to an estimated 551,000 people in England26.

Many people with SMI also experience poor physical health and have higher premature mortality27. PHE analysis of primary care data has shown that people with SMI had higher rates of obesity, asthma, diabetes, chronic obstructive pulmonary disease, coronary heart disease, stroke, and heart failure\(^{27}\). Data for deaths among those with SMI shows that:

  • premature mortality in adults whose death was registered in 2018-2020, and who were in touch with secondary mental health services in the 5 years before death, was significantly higher in the East Midlands region than compared to the national average at 114.1 per 100,000 population compared to 103.6 nationally
  • at local authority level, the rate of premature death among those in contact with services is significantly higher than the national average in areas with higher levels of deprivation, including Nottingham (170.7), Leicester (164.4), Derby (148.4), Lincolnshire (110.6)
  • in the East Midlands, for people whose death was registered in the years 2018-2020, those in contact with secondary mental health services in the 5 years before death had a risk of dying young that was 4.1 times higher than their peers who were not in touch with services
  • at local authority level, areas like Leicestershire (4.9 times higher) have a much larger excess premature mortality among those who were in touch with services in the 5 years before death, compared to those who were not. This is thought to be because in areas with lower deprivation most of the population experiences high life expectancy, so the difference between those in touch with services and those who were not is much more pronounced than in an area with higher deprivation and generally higher premature mortality, such as Leicester (3.2 times higher).


Figure 18 – Suicide and Self-harm

Figure 18a - Trends
<b>Source:</b> <a href = 'https://fingertips.phe.org.uk/search/21001#page/4/gid/1/pat/15/ati/6/are/E12000004/iid/20101/age/235/sex/4/cat/-1/ctp/-1/yrr/1/cid/4/tbm/1' target = '_blank'> OHID Public health profiles </a>, <a href = 'https://fingertips.phe.org.uk/search/41001#page/4/gid/1/pat/15/ati/6/are/E12000004/iid/20101/age/235/sex/4/cat/-1/ctp/-1/yrr/1/cid/4/tbm/1' target = '_blank'> Suicide Prevention Profile </a> <b>Date accessed:</b> 31/03/2022 <a href = 'https://fingertips.phe.org.uk/static-reports/health-profile-for-england/Data/East_Midlands_018a_suicide_and_self_harm.csv' target = '_blank'><b>Download data</b></a>

Source: OHID Public health profiles , Suicide Prevention Profile Date accessed: 31/03/2022 Download data

Figure 18b - Local Authority

Source: OHID Public health profiles , Suicide Prevention Profile Date accessed: 31/03/2022 Download data

Dementia and Alzheimer’s disease

As discussed earlier in the report, dementia and Alzheimer’s disease is a leading cause of death, and despite not featuring in the leading YLDs, dementia is a significant cause of ill health in the East Midlands region. The directly standardised rate of mortality for people aged 65 and over with dementia:

  • in 2019 was 923 per 100,000 in the East Midlands and is significantly higher than the England average
  • at local authority level, the highest rate was in Leicester at 1,159 deaths per 100,000, with the lowest rate in Rutland at 747 deaths per 100,000 population

A particular commitment of the NHS in the 2014-15 mandate was to increase the number of people living with dementia who have a formal diagnosis, so their carers and healthcare staff can provide timely interventions and improve outcomes. As not all people with dementia have a formal diagnosis, the indicator ‘estimated dementia diagnosis rate (aged 65 and over)’ was created to compare the number of people estimated to have dementia with the number of people diagnosed with dementia (aged 65 and over). The target was to increase the estimated dementia diagnosis rate to 66.7%. Data shows that:

  • in the East Midlands region, over the pandemic, there was a 7.5% decline in the estimated dementia diagnosis rate, from 72.3% in 2019 to 64.8% in 2021. This equates to a fall of 3,778 in the estimated number of people in the population with a dementia diagnosis
  • the recorded prevalence of dementia in the East Midlands region decreased by 0.4% from 4.5% in 2019 to 4.1% in 2020. This equates to a reduction of 3,356 recorded diagnoses and may reflect the deaths from COVID-19 that occurred in the older population, but also the lower diagnoses over the pandemic

Care plan reviews are an important aspect of dementia care and the Quality and Outcomes Framework (QOF) target is that 75% of people with a dementia care plan get a review in the preceding 12 months.

Over the pandemic, across the East Midlands in general, there has been a reduction in the proportion of those with dementia receiving a care plan review, with 19,834 fewer care plans reviewed in the previous 12 months. In several local authorities in the region, this now falls short of the 75% QOF target.


Cancer

Cancers do not feature as leading causes of YLDs in the GBD data presented earlier in this report but are a significant cause of ill health and mortality in the East Midlands region.

Figure 19 shows that, since January 2018, the trend for new cancer diagnoses for the four major sites (breast, colorectal, prostate, and lung), and for all sites combined, was steady until the first COVID-19 restrictions in March 2020. During the spring and summer of 2020, new cancer diagnoses for all sites combined were at an unprecedented low. However, the number of new diagnoses had returned to historic levels by December 2020, with minor fluctuations. Similar trends were observed for the four major cancers.

Data that measured the number of first treatments for cancer over the pandemic shows that at a Midlands level, there was a deficit of 8,551 new treatments between March 2019 and September 2021 compared to baseline activity in the previous 2 years. There is a significant trend across deprivation groups, with a smaller deficit among the least deprived at 91% of baseline compared to 89% among the most deprived group.


Figure 19 – Cancer incidence

Figure 19a - Trends

Source: National Cancer Registration & Analysis Service Date accessed: 07/02/2022 Note: Data based on Cancer Alliance 2020 geographies. See data and definitions document for more details on mapping alliances to Government Office Regions. Download data

Health service contact during the pandemic

Data on admissions to hospital during the pandemic for causes other than COVID-19 can help to understand the potential broader impacts of the pandemic on future health. The Health Profile for England report provides a national interpretation of a variety of metrics describing trends in health service contact over the pandemic. The reduced admissions, GP consultations, A&E attendances and health seeking behaviour observed during this period may be a factor in the increase in deaths at home presented earlier. They may also represent missed opportunities to provide secondary prevention treatment to patients, such as blood pressure and cholesterol control, and may also result in an increase in long-term health complications.

Data on hospital activity during the pandemic for causes other than COVID-19 can help to understand the potential broader impacts of the pandemic on future health. This shows that:

  • in the East Midlands the emergency hospital admissions for all causes decreased by 24.1% in the first quarter of 2020-21, compared to a baseline of 2018-19. While this reduction in emergency admissions began to return to normal over the pandemic, there was still a slight reduction in 2021-22 in Q1, at 0.3% below baseline
  • in the East Midlands the elective hospital admissions for all causes decreased by 64.0% in the first quarter of 2020-21, compared to a baseline of 2018-19. While this reduction began to return to normal, there was still a reduction in 2021-22 in Q1, at 14.7% below baseline
  • outpatient attendances in the first quarter of 2020-21 reduced by 36.7% and were still below the baseline by 3.3% a year later in the first quarter of 2021-22


Risk factors associated with ill health

Introduction

Risk factors play an important role in determining whether a person becomes ill, at what age, and the associated effect on quality of life. The Global Burden of Disease (GBD) divides risk factors into 3 main groups: behavioural, metabolic, and environmental and occupational. These are underpinned by the broader social and economic risk, and by protective factors that shape people’s lives, such as education, income, work and social capital. These wider determinants are discussed in the next section of this report. At the time of writing, GBD 2019 results for regions and local authorities were available but an update is due in 2022.

This section focuses on behavioural and metabolic risk factors in adults. It examines the contribution that these risk factors make to morbidity and mortality, using GBD data. Trends and inequalities in some of the risk factors making the largest contribution are examined.


Inequalities in risk factor prevalence contribute to inequalities in ill health and mortality. For example, inequality in smoking prevalence by deprivation is a large determinant of the inequalities in mortality and life expectancy. In 2019, national smoking prevalence remained much higher than average in some groups, for example, people in manual occupations (23.2%), people with a long-term mental health condition (25.8%), deprived areas (16.9%), and the mixed ethnic group (19.5%). The national prevalence of ‘increasing or higher risk’ drinking was greatest in the highest household income group at 34.8%. The national prevalence of obesity in adults was higher in the most deprived than least deprived areas, and there were wide inequalities in the proportion of adults meeting recommended level of physical activity and fruit and vegetable consumption. Health Survey for England evidence suggests that the prevalence of multiple risk factors is higher in men, the white ethnic group, lowest income households, most deprived areas, and people with long term health conditions28.


Leading risk factors

Figures 20a and 20b show the 15 most common risk factors associated with morbidity and mortality respectively in the East Midlands, using data from GBD 2019. Please note that the disease burdens attributable to specific risks are independently calculated for each risk factor. Risk factors attributed to YLDs or deaths cannot be summed together. In addition, these risk factors are connected, and individuals often have more than one risk factor. Figure 20 shows that:

  • the risk factors making the biggest contribution to mortality in the East Midlands were tobacco, high systolic blood pressure, diet and high fasting plasma glucose
  • these risk factors also made a significant contribution to morbidity, along with high body mass index (or obesity), alcohol, drug use and occupational risks


The Health Profile for England 2021 reported that the prevalence of ‘increasing and higher risk’ drinking increased in April 2020 and remained above pre-pandemic levels until June 2021. There has also been a reduction in physical activity levels, particularly in black and Asian groups and lower socioeconomic groups. The number of people trying to quit smoking during the pandemic increased, with over a third of smokers attempting to quit in the 3 months up to June 2021. Data on the impact of the pandemic on adult obesity is not yet available.


Figure 20 – Leading risk factors

Figure 20a - Morbidity

Source: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Download data

Figure 20b - Mortality

Source: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Download data


Figure 21a shows trends in smoking prevalence, obesity and hypertension (high blood pressure). Figure 21b shows variation across local authorities in these risk factors.

Figure 21 – Risk factors

Figure 21a - Trends
Figure 21b - Local Authority
<b>Source:</b> <a href = 'https://fingertips.phe.org.uk/covid19#page/1/gid/1938133364/pat/15/par/E92000001/ati/6/are/E12000004/yrr/1/cid/4/tbm/1/page-options/car-do-0' target = '_blank'> Wider Impacts of COVID-19 on Health: Wellbeing and behavioural risk factors </a>, <a href = 'https://fingertips.phe.org.uk/covid19#page/3/gid/1938133361/pat/15/ati/6/are/E12000004/iid/219/age/1/sex/4/cat/-1/ctp/-1/yrr/1/cid/4/tbm/1/page-options/car-do-0' target = '_blank'> Wider Impacts of COVID-19 on Health: Hypertension QOF </a> <b>Date accessed:</b> 31/03/2022 <a href = 'https://fingertips.phe.org.uk/static-reports/health-profile-for-england/Data/East_Midlands_021b_risk_factors.csv' target = '_blank'><b>Download data</b></a>

Source: Wider Impacts of COVID-19 on Health: Wellbeing and behavioural risk factors , Wider Impacts of COVID-19 on Health: Hypertension QOF Date accessed: 31/03/2022 Download data

Smoking

There is evidence of an increase in the rates of people attempting to quit smoking during the pandemic at national level. Although the rates have fluctuated, quit rates remained consistently higher than in 2019.

Recent methodological changes mean that current 2020 prevalence from the Annual Population Survey (APS) cannot be reliably compared to previous years. In order to present the trend in smoking prevalence, data in figure 21 uses the superseded methodology. This data shows that:

  • the smoking prevalence in 2019 among adults was 14.8% in the region, higher than the national average of 13.9% (figure 21a)
  • by local authority, in 2019, smoking prevalence was highest in Nottingham at 20.9%, and lowest in Rutland at 10.2% (figure 21b)

Smoking prevalence remained much higher than average in different groups:

  • among people in manual occupations, 25.5% were estimated to be smokers in 2019, significantly higher than the national average for this group (23.2%)
  • prevalence is also higher in those with a long term mental health condition. In 2019/20 the prevalence in the East Midlands was 24.2%, more than twice as high than in the general population

Obesity

As with other risk factors, there are inequalities in adult obesity prevalence by age, sex and deprivation. The Health Profile for England reported that in 2019, the prevalence of obesity was lowest in those aged under 25, with a gradual increase by age group up to those aged 65 to 75 after which the prevalence decreased. This pattern was seen for both males and females. Obesity prevalence was lowest in the least deprived areas and highest in the most deprived, with a clearer gradient for females than males.

The impact of the pandemic on adult obesity levels is not known but given the changes in other risk factors presented (diet, physical activity and alcohol), it is possible we will see an increase in prevalence and a widening of inequalities.

Long-term trends show an increase in adult obesity in England, although with some fluctuation year to year. Data in figure 21 shows that:

  • in the East Midlands region, the prevalence of overweight and obesity increased from 64.1% in 2015/16 to 66.6% in 2020/21, significantly higher than the England average of 63.5%

  • there was some variation by local authority with the highest prevalence of overweight and obesity reported in North Northamptonshire (69.6%), significantly higher than the regional average. Derbyshire also had a significantly higher prevalence at 69.2%


Physical activity

Those who are classed as physically active are those who undertake at least the recommended level of 150 minutes of moderate intensity physical activity or equivalent per week. Data shows that:

  • in 2019/20, 65.9% of adults were physically active in the East Midlands region, similar to the England average of 66.4%
  • there is variation by local authority, with the highest level of physical activity in Derbyshire at 70.6%. This is the only local authority that was significantly higher than the national and regional values. Leicester has the lowest physical activity level at 61.1%, and is significantly lower than England and the East Midlands region


As with children, England level findings in 2020-21 from Sport England uncovers wide inequalities in physical activity in adults. The proportion was lower for people who are in routine/semi routine jobs and those who are long-term unemployed or have never worked (52%); those living with a disability or long term health condition (45%); and Asian (48%) and black (52%) ethnic groups.


Diet

In 2019/20, the proportion of the population meeting the recommended ‘5-a-day’ on a ‘usual day’ was 55% in the East Midlands, similar to the England average of 55.4%.

There is some variation by local authority, with the highest percentage of the population eating the recommended 5 a day in Rutland at 64.9%. The lowest was in Nottingham at 50.1%, significantly lower than the England and East Midlands averages.


The Health Profile for England 2021 reported wide inequalities at the England level: the recommended 5-a-day is lower for people who were unemployed (45.2%), living with a disability (52.1%), working in routine and manual occupations (45.8%), Asian (47.2%), black (45.7%), or living in the most deprived areas (45.7%)29.


Blood glucose

Increased blood glucose levels may lead to diabetes and can increase the risk of heart disease and stroke, kidney disease, vision and nerve problems. A blood glucose level that is above normal but not in the diabetic range is referred to as non-diabetic hyperglycaemia (NDH). While we do not have regional data, it is estimated that approximately 5 million people in England have NDH and only 23.8% are diagnosed and recorded, but this proportion has increased steadily since the establishment of the Diabetes Prevention Programme30 31.


High blood pressure

Figure 21a shows that there was little change in the trends in QOF prevalence of high blood pressure (hypertension) between 2015 and 2020. There may have been some decrease in the diagnosis of hypertension due to limited GP appointments during the pandemic. Data shows that:

  • the registered prevalence of high blood pressure in the East Midlands in 2020/21 was 14.9%. Although this is similar to previous years, the number of diagnoses was much lower at 638,133 in 2020 compared to 757,507 in 2019
  • there is some variation by local authority, with the highest QOF prevalence of high blood pressure in Rutland at 17.3% and lowest in Nottingham at 10.4%


Alcohol

Increasing and higher risk drinking is defined as drinking more than 14 units per week and up to 35 units for women and 50 units for men. In 2019, the Health Survey for England showed that:

  • the prevalence of ‘increasing risk drinkers’ - in the East Midlands was 16% and of ‘higher risk drinkers’ (more than 35 or 50 units per week) was 4%
  • the prevalence of ‘increasing risk drinkers’ in the East Midlands was approximately 12% for women and 20% for men
  • the prevalence of ‘higher risk drinkers’ (more than 35/50 units per week) was 2% for women and 5% for men

Nationally, alcohol-specific mortality increased by around 20% between 2019 and 2020, driven chiefly by increases in mortality from alcoholic liver disease32. Alcohol-specific mortality rates had been increasing prior to the pandemic, but this represented a significant acceleration in the upward trend. The increase in alcoholic liver disease mortality during 2020 has been linked to increased alcohol consumption among heavy drinkers who were already at risk of liver failure\(^{32}\). Alcohol mortality data from Fingertips shows that:

  • the number of deaths related to alcohol in the region was 1,832 in 2020, representing a rate of 38.1 per 100,000 population, similar to the England average of 37.8
  • the trend in the age standardised rate of deaths from alcohol-specific conditions shows that rates are increasing and getting worse in the region. In 2020, there was a significant increase in the rate in the region from 11.1 per 100,000 in 2019 to 12.9 per 100,000, equating to an increase of 17%, or 89 deaths


The Health Profile for England 2021 reported differences in drinking patterns by age and income. ‘Increasing or higher risk’ drinking was highest in the 55 to 64 age group, with the lowest rates among the younger age groups (under 25s), as well as those aged 75 or over. Consistent with wider evidence, in 2018-19 the prevalence of ‘increasing or higher risk’ drinking was greatest in the highest household income group, but greater harm, such as hospital admissions for alcohol-related conditions were more than double that in the least deprived areas. This gap has only slightly narrowed since 2010-1133. This inverse relationship between consumption and harm is often referred to as the ‘alcohol harm paradox’. Attempts to understand this have suggested interactions with other behaviours such as smoking, poor diet and exercise, among the reasons why alcohol-related harms are greater in more deprived areas34.


Drug use

Pre-pandemic survey-based estimates for recent drug use in England vary year-on-year. 9.4% of people aged 16 to 59 reported using any drug in the last year in 2019-20. Rates of deaths due to drug misuse continue to be highest among those born in the 1970s. Regional differences are significant; in 2018-2020, the North East had the highest rate of deaths due to drug misuse, whereas London had the lowest (9.9 and 3.5 deaths per 100,000 respectively). Data shows that:

  • in the East Midlands region, the rate of deaths due to drug misuse was 4.0 per 100,000, significantly lower than the England average of 5.0 per 100,000, although this has been increasing in recent years
  • by local authority, in 2018-2020, the rate of deaths due to drug misuse ranged from 2.8 per 100,000 in Nottinghamshire to 6.2 in Derby


Wider determinants of health

Introduction

The wider determinants of health are a diverse range of social, economic and environmental factors which influence people’s mental and physical health across the life course35. This section presents some key indicators for a range of wider determinants of health including the built and natural environment, education, employment and income, and communities and social capital.

Here, the wider determinants of health are presented individually. However, Marmot et al36. describe how “intersections between socioeconomic status, ethnicity and racism intensify inequalities in health for ethnic groups”, and that “the cumulative experiences of multiple forms of disadvantage interact with and are exacerbated by features of the communities in which people live”. The complexity of these interactions, referred to as intersectionality, are an important driver of the inequalities in risk factors and health outcomes presented throughout this report.


Employment

Good employment improves health and wellbeing across people’s lives, boosting quality of life and protecting against social exclusion.

Figure 22 shows that, for the East Midlands, employment had been increasing up to 2019-20 to 76.8%. However, within the first year of the pandemic, employment had shown a downturn to 74.7% in 2020/21. Compared to England (75.1%), the East Midlands had similar employment rates. However, there are differences between males and females in the region:

  • employment rates have historically been lower for females compared to males, ranging from 65.6% in 2011/12 to 73% in 2019-20. During the pandemic the female employment rate decreased to 71.3% in 2020/21
  • for males, employment rates increased from 76.8% in 2011/12 to 80.6% in 2019-20. During the pandemic, the employment rate decreased to 78.2% in 2020/21

Although many local authorities in the East Midlands had similar employment rates to the regional average, there was inequality in employment rates observed in local authorities across the region:

  • Leicester had the lowest levels of employment at 69.9%, significantly lower than the regional average
  • North Northamptonshire had the highest levels of employment at 79.6%, significantly higher than the regional average


The COVID-19 pandemic has had a substantial impact on employment patterns and opportunities. The proportion of adults claiming unemployment benefits more than doubled between March 2020 and May 2020 and remained high into 2021. There is evidence that the economic impacts of the pandemic affected young people disproportionately. At the end of January 2021, the take up rate of eligible employees that made a claim to HMRC under the furlough scheme was highest in those aged under 18 (34.5%) and those aged 18 to 24 (21.1%). There has also been a decline in the number of 16 and 17 year olds in employment, from 22.5% in the 3 month period March to May 2020, to 13.9% in the comparable period in 2021. In November 2020, the arts, entertainment and recreation industry and the accommodation and food service industry had the highest percentage of employees on furlough leave at 33.6% and 21.9% respectively. These are industries with a high proportion of the workforce who are relatively young\(^{21}\).


Figure 22 – Employment

Figure 22a - Trends

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Figure 22b - UTLA

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Income

The Minimum Income Standard (MIS) is defined as not having enough income to afford a ‘minimum acceptable standard of living’, based on what members of the public think is enough money to live on37. Figure 23 shows that:

  • in 2018/19, 26.7% of the population of the East Midlands did not reach the MIS, lower than the national average of 29.8%. For the same period, 34.8% of children in the East Midlands were living in households that did not meet the MIS, which was also lower than the national average of 42.3%
  • district level data estimating the rate of child poverty in 2019/20 showed that there was large variation across the region. The lowest rate was in South Northamptonshire and Rushcliffe at 15%, and the highest in Leicester at 38%


Many physical and mental health outcomes improve incrementally as income rises38 39. Income is related to life expectancy, disability free life\(^{39}\), and self-reported health40. The relationship operates through a variety of mechanisms. Financial resources determine the extent to which a person can both invest in goods and services which improve health and purchase goods and services which are bad for health. Low income can also prevent active participation in social life and day to day activities, affecting feelings of self-worth and status41. It can also influence health through feelings of shame, low self-worth and exclusion42.


Figure 23 – Minimum income standard

Figure 23a - Trends

Source: Joseph Rowntree Foundation Households below a Minimum Income Standard: 2008/09 - 2018/19 Date accessed: 31/03/2022 Download data

Figure 23b - Local Authority

Source: After housing cost childer poverty rate estimates, Loughborough University 2019-20 Date accessed: 31/03/2022 Download data

The built and natural environment

The quality of the built and natural environment such as air quality, quality of and access to green spaces, and housing quality all affect health. Poor housing has a negative effect on our physical and mental health, particularly for older people, children, disabled people and individuals with long-term illnesses. Homelessness and the use of temporary accommodation remain at high levels in England43. Data shows that:

Fuel poverty is now measured by the new Low Income Low Energy Efficiency (LILEE) statistic44. A household is defined as fuel poor if it has income below a certain level after accounting for fuel costs, and a low energy efficient home. Data shows that:

  • in the East Midlands region, 13.9% of households were living in fuel poverty in 2019, similar to the England average of 13.4%

Living in a greener environment can promote and protect good health, aid recovery from illness and help with managing poor health. Green space can help to bind communities together, reduce loneliness, and mitigate the negative effects of air pollution, excessive noise, heat, and flooding45. The Monitor of Engagement with the Natural Environment (MENE) survey collected information on the utilisation of outdoor space for exercise/health reasons between 2009-19. Regional level data is available for this for the year 2015-16, showing that:

  • in the East Midlands, 18.5% of residents visited the natural environment for health or exercise purposes over the previous seven days, similar to the national average of 17.9%


Education

Educational attainment is strongly linked with health behaviours and outcomes. Better-educated individuals are less likely to suffer from long-term diseases, to report themselves in poor health, or to suffer from mental health conditions such as depression or anxiety46. Education provides knowledge and capabilities that contribute to mental, physical, and social wellbeing. Educational qualifications are also a determinant of an individual’s labour market position, which in turn influences income, housing and other material resources associated with health. Data on child development measures are referred to under the child development section of the child health chapter, earlier in this report. It indicates that, compared to the national average, fewer children in the region are reaching a good level of development at the end of Reception. In 2020, for older children, the percentage of 16 to 17 year olds who are not in education, employment or training (NEETs) for the East Midlands region was 6.2%, significantly higher than the national average of 5.5%. The percentage was significantly higher than the national average in Nottingham (6.3%), Leicester (7.4%), Derby (7,4%) and Nottinghamshire (13.8%), and had increased when compared to 2019.


Health protection

Introduction

Health protection issues include the prevention and control of all types of infectious diseases, and chemical and environmental threats to the health of the population.

Over the past century, there has been a considerable reduction in the number of deaths from infectious diseases. However, the COVID-19 pandemic has demonstrated how threats from new infectious diseases can emerge and will continue to do so as a result of a whole range of global factors.

Environmental threats include factors such as air pollution, climate change and flooding. Climate change is a risk to health both nationally and globally. It affects all aspects of our everyday life and our environment, including the places we live and the air we breathe, as well as our access to food and water47.

It is not possible to cover all health protection issues in this report. This section presents specific information on air pollution, sexually transmitted infections, tuberculosis (TB), vaccinations and vaccine preventable infections, and anti-microbial resistance (AMR).


Air pollution

Air pollution can contribute to cardiovascular and respiratory conditions and shortens lives. It is estimated that long-term exposure to the air pollution mixture in the UK has an annual effect equivalent to 28,000 to 36,000 deaths48.


Social restrictions implemented during the pandemic meant that there were fewer vehicles on the roads, as people were asked to stay at home, which had a favourable impact on air pollution levels. Motor vehicle use fell dramatically during the first (March 2020) and third (January 2021) national lockdowns in England, but by the end of July 2021 were similar to previous years\(^{21}\).


Figure 24 presents the annual concentration of human-made fine particulate matter, adjusted to account for population exposure. Fine particulate matter is also known as PM2.5 and has a metric of micrograms per cubic metre (\(\mu\)g/\(m^{3}\)). Data is not available for the Northamptonshire area in the figure below. Figure 24 shows that:

  • the regional trend between 2011 and 2019 was around 9 \(\mu\)g/\(m^{3}\) for each year and was generally higher than the national average
  • during the first year of the pandemic, 2020, the man-made fine particulate matter level of air pollution fell to 6.5 \(\mu\)g/\(m^{3}\) in the region
  • there was some regional variation in fine particulate matter air pollution in 2020. The highest exposures were generally in the cities of Leicester, Nottingham and Derby at over 7 \(\mu\)g/\(m^{3}\). These are areas with high levels of deprivation; therefore, air pollution will be contributing to the health inequalities presented in this report


Figure 24 – Air quality

Figure 24a - Trends

Source: OHID Wider Determinants of Health Date accessed: 31/03/2022 Download data

Figure 24b - UTLA

Source: OHID Wider Determinants of Health Date accessed: 31/03/2022 Download data

Sexually transmitted infections

The epidemiology of sexually transmitted infections (STIs) has changed markedly over the last two decades, reflecting changes in demographics, individual behaviours, surveillance techniques, diagnostics and treatments. There has been a continued decline in the rate of new HIV diagnoses49 due to a combination of testing, pre-exposure prophylaxis, rapid linkage to treatment and support for those diagnosed with HIV to attain viral suppression. There has also been a decline in the rate of genital warts following the introduction of the HPV vaccination programme (Figure 25a). Trend data shows that:

  • the diagnostic rates per 100,000 for chlamydia (aged 25+), gonorrhoea and syphilis increased in the East Midlands region between 2012-19. The diagnostic rate per 100,000 for genital warts decreased since 2012. 2020 saw a decline in the detection rates of all STIs

  • diagnostic rates per 100,000 in the East Midlands region in 2020 were:

    • 115 per 100,000 for chlamydia (aged 25+), significantly lower than the national average of 171
    • 66 per 100,000 for gonorrhoea, significantly lower than the national average of 101
    • 38 per 100,000 for genital warts, significantly lower than the national average of 49
    • 5 per 100,000 for syphilis, significantly lower than the national average of 12

  • at local authority level, the incidence of these infections followed similar trends. However, there was wide variation across the region in 2020:

    • Nottingham had significantly higher rates than the regional average for all four infection types: for chlamydia (285 per 100,000), gonorrhoea (190 per 100,000), genital warts (72.1 per 100,000), and syphilis (11.9 per 100,000)
    • compared to the regional average, Derby had significantly higher rates for gonorrhoea (127 per 100,000) and chlamydia (194 per 100,000)
    • Leicester had significantly higher rates for gonorrhoea (149 per 100,000) and chlamydia (169 per 100,000) compared to the regional average


The measures taken to control the COVID-19 pandemic resulted in a drop in the number of people accessing services. Reduced demand for these services during this time may have been influenced by compliance with social distancing measures and changes in risk perception and behaviour but may also indicate undetected infections. The full impact on infection transmission and long-term health outcomes will take time to emerge and evaluate50.


Figure 25 – Sexually transmitted infections

Figure 25a - Trends

Source: Sexual and Reproductive Health Profiles Date accessed: 31/03/2022 Download data

Figure 25b - Local Authority

Source: Sexual and Reproductive Health Profiles Date accessed: 31/03/2022 Download data

Tuberculosis

The number of new cases of tuberculosis (TB) have fallen dramatically in England over the last century51. Over the last 10 years, there has been a steady decline in the incidence rate (new cases per 100,000 population) but then a levelling off in more recent years Figure 26 shows:

  • by 2020, the incidence rate of TB per 100,000 was 6.4 in the region, significantly lower than the national average of 7.3
  • all local authorities have followed a similar trend to that seen regionally. In 2018-2020, Leicester had the second highest rate TB incidence rate nationally at 39.5 per 100,000. Derby and Nottingham also had significantly higher rates of TB than the national average in 2018-2020


Rates of TB are higher in people born outside the UK, particularly in those of Indian, Pakistani or black African ethnicity. It was also higher in the most deprived areas and more than a fifth of UK born cases have a known social risk factor such as homelessness or drug use.


Figure 26 – Tuberculosis

Figure 26a - Trends

Source: OHID TB Strategy Monitoring Indicators Date accessed: 31/03/2022 Download data

Vaccines and vaccine preventable infections

As a result of effective vaccination programmes the incidence of many diseases has reduced significantly over time and the importance of vaccination in controlling infectious diseases is highlighted by the COVID-19 pandemic as discussed earlier. Data shows that:


Across the country, uptake rates for influenza vaccination in winter 2020 to 2021 were higher than they had been in previous years due to increased efforts to reach as many people as possible and increased awareness due to the COVID-19 pandemic. As a consequence of this and the social distancing measures introduced for the COVID-19 pandemic influenza-like illness was much lower in winter 2020 to 2021 than in other seasons52.


Advice from the Joint Committee on Vaccination and Immunisation (JCVI) on routine childhood immunisations stated that children should continue to receive vaccinations according to the national schedule during the COVID-19 pandemic53. Measles is a highly infectious disease which can only be controlled by vaccination. People who have not received 2 doses of the MMR (measles, mumps and rubella) vaccine are at risk of developing measles. Data shows that:

  • population vaccination coverage for one dose of MMR by age 2 in the East Midlands region had been following a downward trend until 2018/19, falling to 92.0%. This had increased slightly to 92.4% in 2020/21
  • population vaccination coverage for 2 doses by age 5 had also fallen to around 88% from 2016/17 to 2019/20 but increased to 89% in 2020/21. This remains lower than the target of 95%
  • at local authority level, in 2020/21, both Leicestershire (96.1%) and Derbyshire (95.2%) had achieved the goal of 95% coverage of 1 dose by age 2. However, Leicester (89.8%), Derby (89.2%) and Nottingham (87.3%) had not achieved 90% coverage
  • in 2020/21, Leicestershire had achieved the goal of 95% coverage for two doses by age 5. However, Leicester (87.1%), Lincolnshire (85.4%), Derby (81.7%) and Nottingham (81.3%) achieved less than 90% coverage


Antimicrobial resistance

Antibiotic-resistant bloodstream infections rose by an estimated 32% between 2015 and 2019 in England54. Figure 27a shows the trend in the rate of antibiotic prescribing in primary care in England and the East Midlands between 2015 and 2020. Antibiotic prescribing in primary care is often measured in STAR-PU, which are weighted units to allow comparisons adjusting for the age and sex of the population. It shows that:

  • the rate of antibiotic prescribing in primary care in England and the East Midlands has fallen every year, with the largest drop between 2019 and 2020. In the region, this fell from 1.0 items per STAR-PU in 2019, to 0.7 in 2020 - lower than the target of the mean England prescribing in 2013/14 (1.161 items per STAR-PU)
  • at local authority level, all areas had fallen below the 2013/14 England mean target for prescribing. However, there is still some regional variation, with Derbyshire, Leicestershire, Lincolnshire, and Rutland significantly higher than the regional average

Figure 27 – Antibiotic prescribing

Figure 27a - Trends

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Figure 27b - Local Authority

Source: OHID Public health profiles Date accessed: 31/03/2022 Download data

Acknowledgements

Members of the Local Knowledge and Intelligence Service (LKIS) Midlands:

Janine Dellar, Rebecca Elleray, Karandeep Kaur, Dorcas Ogunsumi, Paul Lester, George Fowajuh, Anam Khan, Matthew Francis, Robyn Bates

Other contributing members from LKIS:

Emily Baldwin and James Brett


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