The Health Profile for England (HPfE) was first produced by Public Health England (PHE) in 2017. It brings together PHE data and knowledge with information from other sources to give a broad picture of the health of people in England today. The report has been updated annually, with content and format altering slightly each year.
The 2021 edition of the HPfE provides a comprehensive snapshot of the nation’s health and updates many indicators presented in previous reports. It also contains a summary of the impact of the coronavirus (COVID-19) pandemic on many aspects of health.
During the pandemic, PHE has been publishing information on its impacts on health in a series of tools and outputs including the COVID-19 dashboard (1), the COVID-19 Health Inequalities Monitoring for England tool (CHIME) (2), the Wider Impacts of COVID-19 on Health (WICH) monitoring tool (3) and the weekly Excess Mortality in England reports (4). The information and insight gained from these tools are used, with other sources, as a basis for discussion of the impact of the pandemic on wider health outcomes and health inequalities.
In addition, the report makes comparisons with health in a selection of other countries (see Box 1 for selection) where possible. Much of the information is presented in a standard chart format (see Box 1) and key points emerging from these charts are discussed.
This report is divided into the following sections:
- mortality and life expectancy
- child health
- adult health
- risk factors associated with ill health
- the wider determinants of health
- health protection issues
Summary points are included at the beginning of each section, followed by detailed analysis and charts.
The data and evidence in the report are provided to support policy makers and practitioners, to inform health improvement activities and support a reduction in health inequalities in their policy areas.
Charts in this report follow a standard format, with 3 sections for each topic area:
Trends – overall headline data for the key indicator used in England, usually as a trend over several years.
Inequalities – how the indicator varies between different groups in England, by protected characteristics such as age, sex and ethnicity or categories of socioeconomic deprivation where possible. Other breakdowns for specific indicators are also included where available and relevant.
International comparison – the closest available indicator for the topic area, for 9 selected countries including the UK. This includes all countries in the Group of Seven (G7) – the USA, Canada, Japan, France, Italy, Germany and the UK – as well as the 2 other European Union (EU) nations with a population greater than 35 million – Spain and Poland. Where possible, a breakdown within the UK is included, but this is not available for many indicators
It is not always possible to use the same indicator for the headline, inequalities and international comparisons within each topic area.
The data behind each chart is available to download here.
Further information on methods, data and definitions is available here
This section examines the direct impact of the COVID-19 pandemic on health. Prior to the COVID-19 pandemic, the 1918 flu pandemic was the most significant and accounted for around 150,000 deaths in England and Wales (5). The 2009 swine flu pandemic was mild by comparison and caused fewer than 700 deaths across the whole of the UK (6).
This section presents data on COVID-19 case and vaccination rates up until the end of June 2021 and death rates involving COVID-19 up until the end of May 2021. It also presents information on excess deaths during the pandemic up until 2 July 2021.
Summary 1 – COVID-19 cases
At the end of June 2021, 4,174,318 confirmed cases of COVID-19 had been reported in England. COVID-19 has impacted some groups more than others and at the end of June 2021, cumulative confirmed case rates in England were higher in females than males, highest in the North West region followed by London and the North East, higher in more deprived than less deprived areas, and highest in the Asian ethnic group. The UK’s highest 7-day average in early January 2021 (881 per million population) was the largest per head of population seen at any time in the countries presented. These differences between groups and countries were influenced by testing availability and policy, particularly early in the pandemic.
Summary 2 – deaths involving COVID-19
At the end of June 2021, 132,053 deaths among England residents had been registered with COVID-19 mentioned on the death certificate. Wide inequalities in death rates involving COVID-19 have been seen. At the end of May 2021, the cumulative age-standardised mortality rate was highest in London followed by the North West region. The rate in the most deprived areas in England was 2.4 times the rate in the least deprived, the rate in males was 1.6 times that of females, the rate in those aged 85 years and over was 3.2 times those aged 75 to 84 years and the rates in Black and Asian groups were more than double the rate in the White group.
Summary 3 – excess mortality
Excess mortality is a measure of how much higher all-cause mortality was in the pandemic period than would have been expected, based on previous years, had the pandemic not occurred. Between 21 March 2020 and 2 July 2021, all-cause deaths in England were 1.14 times higher than expected and this rose to 1.23 times higher in London. They were higher than expected in all age groups over 25. In deprived areas deaths were 1.17 times higher than expected. Deaths in the Black and Asian groups were close to 1.50 times higher than expected, compared with 1.12 times higher in the White group. 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.
Summary 4 – COVID-19 vaccinations
At the end of June 2021, 92.0% of those aged 50 and over had received both doses of the COVID-19 vaccine. There was variation in uptake, from 94.9% in the least deprived areas to 86.8% in the most deprived areas, from more than 90.0% in the White British and Indian ethnic groups to less than 70.0% in the Black African and Black Caribbean groups, from 93.4% in those born in the UK to 81.8% in those born outside of the UK and from over 90.0% in most regions to 84.7% in London. However, among the countries presented, the UK and USA had the highest rates of second dose vaccinations.
Detailed analysis and charts
The first two cases of COVID-19 were detected in England on 30 January 2020 and the first death within 28 days of a positive test occurred on 2 March 2020. At the end of June 2021, 4,174,318 confirmed cases of COVID-19 had been reported in England (1).
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.
Based on the specimen date (the date the sample was taken), Figure 1a shows daily cases peaked in England at 72,510 on 29 December 2020, during the second wave of the pandemic. However, case numbers in the first wave were significantly underestimated by limited testing availability.
In England, inequalities in COVID-19 case rates emerged early on in the pandemic and persisted into the second wave (2, 7). The inequality breakdowns presented in Figure 1b show that, at the end of June 2021, cumulative age-standardised case rates were higher in females than males, highest in the North West region followed by London and the North East, higher in more deprived than less deprived areas, and highest in the Asian ethnic group particularly the Pakistani and Bangladeshi groups.
Although the cumulative case rate at the end of June 2021 was highest for those aged 85 and over, the second highest rate was for those aged 25 to 49 years and the lowest rate was for those aged 65 to 74 years. These age patterns have changed throughout the pandemic as they been influenced by testing policies and capacity as well as vaccination policy and uptake through the second wave. In June 2021 the highest case rates were in the 0 to 24 age group, many of whom were not eligible for vaccination, followed by people aged 25 to 49 who became eligible later in the vaccination rollout program (2).
In terms of international comparisons, Figure 1c shows that the timing of peaks in case rates per million population varied considerably between the countries presented. The data in Figure 1c are based on the date positive cases were reported, not the date the sample was taken, and 7-day averages are used as not all countries report cases every day. Comparisons of case rates between countries should be treated with caution as, although influenced by factors such as differences in population mixing, sociodemographic profiles and measures to control the virus, they are also influenced by differences in testing availability and case definitions between countries.
Nevertheless, the UK’s peak in early January 2021 (a 7-day average of 881 per million population) was the largest per head of population seen at any time in the 9 countries presented. At the end of June 2021, however, the USA had the highest cumulative case rate, followed by France, Spain, Poland, the UK and Italy.
Figure 1 – COVID-19 cases
Cases per day7 day rolling averageDateNumber of new casesNumber of COVID-19 cases per day and 7-day average, England, March 2020 to June 2021Number of new cases
For some individuals COVID-19 related symptoms persist for more than 4 weeks (“long COVID”). Data from the Coronavirus (COVID-19) Infection Survey (CIS), estimate that at 4 July 2021 the prevalence of long COVID in the UK was 1.46% (945,000 people) (8). The REACT-2 study estimated that 37.7% of people who had been infected still reported at least one symptom after 12 weeks (9). Prevalence of self-reported long COVID was greatest in people aged 35 to 69 years, females, people living in the most deprived areas, those working in health or social care, those with another activity-limiting health condition or disability (8) and people who smoked or were obese (9). The impact of this on the long-term health of the population is not yet known.
Deaths involving COVID-19
According to the Office for National Statistics (ONS), by the end of June 2021, 132,053 deaths mentioning COVID-19 on the death certificate had been registered among England residents (10). This is more than the number of deaths occurring within 28 days of a positive test (112,694) (1) as not all of those who died with COVID-19 will have received a positive test, particularly in the first wave of the pandemic where testing was limited, and a small proportion of deaths due to COVID-19 occurred more than 28 days after a positive test.
Unlike the number of confirmed cases which were greater in wave 2 than wave 1, Figure 2a shows that daily deaths (with any mention of COVID-19 on the death certificate) peaked at similar levels in both waves: 1,286 occurred on 8 April 2020 and 1,322 on 19 January 2021. However, it is possible that deaths were under recorded at the start of the pandemic as well as COVID-19 cases.
Inequalities in mortality involving COVID-19 have been widely reported (7, 11, 12). There have been higher COVID-19 mortality rates in older age groups, among men, and in more deprived areas. These patterns were observed in both waves of the pandemic (2). Figure 2b shows that, at the end of May 2021, the cumulative age-standardised mortality rate for the most deprived areas in England was 2.4 times the rate for the least deprived, the rate in males was 1.6 times females and the rate in those aged 85 years and over was 3.2 times those aged 75 to 84 years.
The patterns of COVID-19 death rates by ethnic group and regions of England have varied throughout the pandemic. The regional pattern has been influenced by the geographic patterns in cases, as described above, and the timing of measures to control the spread of the virus. At the end of May 2021, London had the highest overall cumulative COVID-19 mortality rate among English regions and the South West the lowest (Figure 2b). London also had the highest monthly mortality rate at the peak of the first wave (April 2020) and the peak of the second wave (January 2021). However, in October and November 2020, the monthly mortality rates were highest in the North West, North East and Yorkshire and the Humber due to an increase in cases in these regions (2).
At the end of May 2021, Figure 2b shows that the cumulative COVID-19 mortality rates in Black and Asian groups were more than double the rate in the White group (452 and 478 per 100,000 respectively, compared with 224 per 100,000). Within the Black group, the highest cumulative mortality rate at the end of May 2021 was among the Other Black group. Within the Asian group the highest rates were among the Pakistani and Bangladeshi groups
The monthly mortality rate in April 2020 was highest among the Black group, reflecting the high case rate in the Black group at the time, but in January 2021 the highest mortality rate was among the Asian group, and in particular the Bangladeshi group that is predominantly resident in London (2, 13). In October and November 2020, death rates were highest in the Pakistani ethnic group (2), which may also reflect the regional pattern described above.
The inequalities in death rates from COVID-19 presented in Figure 2b largely reflect inequalities in COVID-19 case rates but 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 years (7). 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 1.16 (14). The possible reasons for these differences and further interpretation of ethnic inequalities in COVID-19 mortality rates are discussed in depth elsewhere (15, 16).
Although not presented in Figure 2b, analyses from ONS shows that the highest age-standardised mortality rates involving COVID-19 in the first wave were in urban conurbations, and that those working in occupations that involved being in close proximity to others experienced higher mortality rates (12, 17). Men and women working in social care, and men working in healthcare had significantly higher mortality rates than average.
There is evidence that the COVID-19 pandemic has disproportionately impacted inclusion health groups. Inclusion health is a ‘catch-all’ term used to describe any population group that is socially excluded. This can include people who experience homelessness and rough sleeping, drug and alcohol dependence, vulnerable migrants, Gypsy, Roma and Traveller communities, sex workers, people in contact with the justice system and victims of modern slavery, but can also include other socially excluded groups (18).
There were high rates of COVID-19 infection and mortality among vulnerable migrants in high-income countries (19) and prison populations in England and Wales (20). Measures introduced early in 2020 in England to protect people experiencing homelessness from COVID-19 infection, such as the use of hotel accommodation, are estimated to have prevented hundreds of deaths among homeless people (21). In March 2020, PHE modelling suggested a reasonable worst-case scenario of more than 2000 deaths in prisons across England and Wales (22). However, efforts to protect prisoners have ensured that deaths in prison residents from COVID-19 remained under 150 at end July 2021 (23).
An analysis of deaths possibly or definitely involving COVID-19 among people identified as having learning disabilities showed higher rates than the general population. Between the start of February and 5 June 2020, adults with learning disabilities had between 2.3 and 3.6 times the COVID-19 death rate of the general population (24). Another study found COVID-19 death rates were particularly high among those with a severe to profound learning disability or Down’s syndrome (25).
People with certain underlying pre-existing health conditions and those classed as ‘extremely clinically vulnerable’ or ‘clinically vulnerable’ are also at higher risk from COVID-19 (26). Analysis by ONS showed 91.1% of people who died with COVID-19 between March and June 2020 had other pre-existing conditions mentioned on their death certificates. Dementia was most commonly mentioned and was the main pre-existing condition for 25.6% of all deaths involving COVID-19. Heart disease was the second most common pre-existing condition at 9.9% (27). Excess weight is also associated with an increased risk of death with COVID-19, even after taking into account demographic and socioeconomic factors (28). In addition, people living with obesity may have other underlying conditions which influence their outcomes from COVID-19.
Figure 2c shows international comparisons in COVID-19 death rates. As with case rates, there is variation in the timing of peaks in COVID-19 mortality rates between the 9 countries included in the international comparison. For the UK Figure 2c presents deaths in positive cases, not registered deaths, and definitions will vary across the other countries so these data should be treated with some caution. Throughout January and the first half of February 2021, the UK had the highest 7-day average mortality rate. At the end of June 2021, the UK had the third highest cumulative mortality rates out of the countries examined, behind Italy and Poland.
The rank order of countries in Figure 1c (cases rates) and Figure 2c (death rates) is not entirely consistent. This may reflect differences in definitions, but in addition, these data do not adjust for age and countries with an older population may have a higher mortality rate from COVID-19 for a given case rate.
Figure 2 – COVID-19 deaths
Daily COVID-19 deathsCOVID-19 deaths (7 day average)DateNumber of deathsDaily deaths with COVID-19 on the death certificate and 7-day average, England, March 2020 to June 2021Number of deaths
Excess mortality during the COVID-19 pandemic
Excess mortality in any population group is a measure of the number of deaths, from all causes, over and above what would be expected in that population group, had the pandemic not happened (29, 30). Because excess mortality captures deaths from all causes, not just COVID-19, it provides an understanding of both the direct and indirect impact of COVID-19.
The direct impact is taken to be the deaths from COVID-19 presented in the previous section. The indirect impact covers deaths from other causes. This could be due to a number of factors such as more limited access to healthcare or the impact of measures taken to combat the spread of the virus.
PHE routinely produces a weekly excess mortality report (4), which provides a breakdown of excess mortality by age, region, local authority, deprivation and ethnicity. These reports show that over the course of the pandemic to 2 July 2021, there were almost 91,000 excess deaths registered in England. This is lower than the total number of deaths involving COVID-19 up to this date (132,740) because some of these deaths involving COVID-19 would have been expected had the pandemic not happened (4).
Figure 3a shows the number of excess deaths by week. The first wave of the pandemic saw the highest weekly excess mortality, with an estimated 11,568 excess deaths registered in the week ending 17 April 2020. In this week the ratio of registered to expected deaths was 2.21 (deaths were 2.21 times higher than expected). In many weeks throughout the summer of 2020 there were fewer deaths than would be expected.
However, overall, up to 2 July 2021, the ratio was 1.14 meaning deaths were 1.14 times higher than expected for the whole period since 21 March 2020. The ratio was 1.20 in the 50 to 64 age group, the largest proportional excess of any age group, while the ratio was 0.94 (6% fewer deaths than expected) among those aged under 25 (Figure 3b).
Figure 3b shows large inequalities in excess deaths by ethnic group. Deaths in the Asian and Black ethnic groups were both close to 1.50 times higher than expected, whereas the ratio was 1.12 in the White group. This reflects the disproportionate impact of the pandemic on Black and Asian groups and is consistent with the high case rates and COVID-19 mortality rates presented earlier. This is particularly evident as there is growing evidence that these groups had lower mortality than the White group prior to the pandemic (7, 31).
Figure 3b also shows that London had the highest excess mortality ratio (1.23) followed by the West Midlands (1.17), and the South West the lowest (1.06). This regional pattern is not identical to the rank order for deaths involving COVID-19, because existing regional variation is taken into account when calculating excess mortality. The North West had lower excess mortality than the West Midlands, despite higher mortality from COVID-19 because the expected mortality, based on previous years, was higher in the North West than the West Midlands.
There was an association between deprivation and excess mortality, with the ratio 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 and other factors play a role (32).
Across the period of the pandemic to 2 July 2021, excess mortality in care homes (1.14 times higher) was similar to overall excess mortality. However, at the peak in excess mortality in the week of 17 April 2020, the excess mortality ratio was 3.37 in care homes compared with the overall ratio of 2.21 (4). It should be noted that this refers to deaths occurring in care homes, rather than deaths of care home residents. However, analysis by ONS includes those who lived in a care home but died elsewhere, and shows similar excess for this group (33).
In terms of excess mortality in other settings, up to 2 July 2021, the ratios were 1.31 for deaths at home and 1.10 for deaths in hospitals and 0.80 (20% fewer deaths than expected) in hospices (Figure 3b). This indicates that a higher proportion of deaths occurred at home than in previous years, but fewer in hospices.
Figure 3c shows relative excess mortality in 2020 for the countries where data are available. Relative excess mortality is the absolute change in the age-standardised mortality rate in 2020 compared to the baseline period (2015 to 2019) presented as a percentage of the rate in the baseline period. This differs from the measure of excess mortality shown in Figures 3a and 3b, which presents a ratio for the given period.
The USA and Poland had the highest relative excess mortality in 2020, in both males and females. However, Figure 2c shows that at the end of December 2020, a similar period, cumulative COVID-19 mortality rates were higher in Italy than USA or Poland. However, these measures are not directly comparable as data in Figure 2c are not age-standardised.
Germany had little or no relative excess mortality in 2020 in males and females. Spain and Italy have experienced similar or greater relative excess mortality in 2020 than England, while France saw a lower excess.
These findings are broadly consistent with the impact on life expectancy in 2020 discussed later in this report for the countries where both sets of data are available.
Figure 3 – Excess deaths
Fewer deaths than expectedMore deaths than expectedTime periodNumber of excess deathsWeekly number of excess deaths, England, 27 March 2020 to 2 July 2021Number of excess deaths
The first COVID-19 vaccinations, outside the clinical trial setting, in England took place on 8 December 2020, 6 days after the first vaccine was approved for use. The COVID-19 vaccination policy in England initially required a second dose to be administered within 12 weeks of the first dose. The gap required between doses was revised to 8 weeks in May 2021. As of 30 June 2021, 37.6 million adults had received a first vaccine dose (82.3% of the adult population), and 27.8 million adults had a received a second dose (60.8%)(1).
Figure 4b shows the cumulative percentage of those aged 50 years and over who have received 2 COVID-19 vaccinations between January and June 2021 by several population characteristics. There have been marked differences in rates of vaccination uptake. While 92.0% of those aged 50 and over had received both doses of the vaccine by 30 June, this varied from 94.9% in the least deprived areas to 86.8% in the most deprived areas. Among different ethnic groups, uptake was lower than 70% in the Black African and Black Caribbean groups, and over 90% in the White British and Indian groups. Those born outside the UK had lower uptake than those born in the UK (81.8% compared with 93.4%). The rate of vaccination uptake was lower in London (84.7%) than in other regions (all over 90%).
Due to vaccine prioritisation being mainly determined by age in England, differences between age groups are the most difficult to interpret. However, by June 2021 uptake of both doses was slightly lower among those in their 50s and 60s (87.6% and 92.5%) than among those aged 70 or over (upwards of 95.5%). While this comparison may be distorted because some people towards the younger end of this range may be awaiting their second vaccination, data shows that higher proportions in their 50s and 60s have yet to receive any vaccination, with little change between April and June 2021 (2).
Many inclusion health groups in England have experienced barriers to accessing COVID-19 vaccination (34). However, strategies like co-produced communication campaigns and alternative access points for vaccination (for example walk-in centres or foodbanks) have also been found to improve access and uptake of COVID-19 vaccination in inclusion health groups like vulnerable migrants in England (35).
Figure 4c shows that the UK had the highest vaccination rate for first doses among the 9 countries until early June 2021, when Canada’s rate exceeded the UK’s. The UK and USA had the highest rates of second dose vaccinations as at the end of June 2021. When comparing countries and different population groups, it is important to note that these are rates for the whole population which reflect a combination of access to vaccine supplies, vaccine delivery strategies and population uptake.
Figure 4 – COVID-19 Vaccinations
DateFirst doseNumber of vaccinationsSecond doseNumber of vaccinationsDaily number of COVID-19 vaccinations (by first and second dose), and 7 day average, England, January to June 2021First doseNumber of vaccinationsSecond doseNumber of vaccinations
Mortality and life expectancy
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.
Summary 5 – life expectancy
In the decade prior to the pandemic in England, improvements in life expectancy had slowed down. The very high level of excess deaths due to the pandemic caused life expectancy in England to fall in 2020, by 1.3 years for males and 0.9 years for females. This was the lowest life expectancy since 2011 for males and females. Spain, Italy and Poland experienced similar decreases in 2020, while France had a smaller decrease.
Summary 6 – inequalities in life expectancy
The gap in male life expectancy between the most and least deprived areas in England was 10.3 years in 2020, 1 year larger than in 2019. For females, the gap was 8.3 years in 2020, 0.6 years larger than in 2019. This level of inequality was larger than all previous years we have data for, which is the last 2 decades. This demonstrates that the pandemic has exacerbated existing inequalities in life expectancy by deprivation. COVID-19 was the cause of death that contributed most to the gap in 2020, however, higher mortality from heart disease, lung cancer, and chronic lower respiratory diseases in deprived areas remained important contributors.
Summary 7 – leading causes of death
In 2020, COVID-19 was the leading cause of death among males, replacing heart disease, and the second largest cause of death among females after dementia and Alzheimer’s disease. Between March and June 2020, dementia was also reported as the main pre-existing condition on 25.6% of deaths certificates involving COVID-19 and heart disease on 9.9%. Alcohol-specific mortality increased by around 20% in 2020, which was an acceleration of the increasing trend before then and was driven mainly by increases in liver disease mortality (36). Drug misuse deaths have been on a general increasing trend since 2012.
Detailed analysis and charts
Trends in all-cause mortality
Figure 5a shows trends in age-standardised mortality rates at all ages and aged under 75 for males and females in England from 2001 to 2020. It shows that the all-cause age-standardised mortality rate in England increased by 15% between 2019 and 2020 for males, and by 12% for females. These were the highest rates since 2008 and reflect the direct and indirect impact of the pandemic on mortality at all ages. Age-standardised death rates in those aged under 75 also increased by 13% for males and 9% for females between 2019 and 2020.
Figure 5b shows that age-standardised mortality rates in those age under 75 increased between 2019 and 2020 in all deprivation deciles but increased most in the most deprived areas. For all persons aged under 75, in 2020, the rate in the most deprived decile in 2020 was 3.2 times the rate in the least deprived decile. This compares with 3.0 times in 2019 indicating that the pandemic has widened inequalities. In addition, Figure 5b shows that London had lower than average mortality in 2019, but similar to average in 2020, reflecting the impact of COVID-19 on people aged under 75 in London.
The international comparison in Figure 5c shows age-standardised mortality rates in people under 75 years for 2019 and 2020, for the selected countries. All countries had an increase in mortality between 2019 and 2020 for both males and females. Poland and the USA had the highest male mortality in 2019 and 2020, and the largest absolute increase between the 2 years. For females, USA had the highest mortality followed by Poland and Scotland.
Figure 5 – All cause mortality
Time periodFemaleAge-standardised rate per 100,000MaleAge-standardised rate per 100,000Aged under 75All agesAge-standardised mortality rate per 100,000 population, all ages and aged under 75, England, 2001 to 2020FemaleAge-standardised rate per 100,000Aged under 75All agesMaleAge-standardised rate per 100,000
Figure 6a shows trends in life expectancy at birth for each year from 1981 to 2020. For much of the decade prior to the pandemic, up to 2018, England had been experiencing a slowdown in improvement of life expectancy year on year (37). However, 2019 saw an increase of 0.4 years for both males and females, to 80.0 years for males and 83.6 years for females.
The very high level of excess deaths due to the pandemic caused life expectancy to fall in 2020. It fell to 78.7 years for males and 82.7 years for females. The fall from 2019 was bigger for males (1.3 years) than females (0.9 years), confirming that the impact of the pandemic on mortality has been greater in men than women. These falls exceed previous year-on-year changes seen since 1981.
These estimates of life expectancy at birth are not projections or predictions of how long babies born in a given year can actually expect to live. They are instead the average number of years a baby born in 2020, for example, would live if they experienced the age-specific mortality rates for 2020 throughout their life. As mortality rates will change in the future, the figures are not a forecast of future life expectancy but are an alternative way of summarising mortality rates for a given period.
The biggest fall in life expectancy between 2019 and 2020 was in London for both males (2.5 years) and females (1.6 years). The South West had the smallest fall for males (0.6 years) while for females the smallest fall was in the East of England (0.7 years). Life expectancy fell for all deprivation groups in 2020, with the largest fall seen among the most deprived areas, which is further evidence of widening inequalities (3, 38).
The slope index of inequality (SII) is a measure of the social gradient in an indicator and shows how much the indicator 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 deprivation (39). The higher the value of the SII, the greater the inequality within an area. Figure 6b shows that the inequality in male life expectancy between the most and least deprived in England was 10.3 years in 2020, 1 year larger than in 2019. For females, the gap was 8.3 years in 2020, 0.6 years larger than in 2019. Inequality in life expectancy in 2020 was greater than we have seen for all years that we have data for, which is the last 2 decades (40).
Figure 6c shows international comparisons in overall life expectancy prior to the pandemic. Among the countries examined, the highest life expectancies in 2019 were in Japan and Spain for females, and Japan, Italy and Spain for males. Poland and the USA had the shortest life expectancy which is consistent with the data on under 75 mortality rates presented in Figure 5c.
Not all countries have reported life expectancy data for 2020 yet. Four of the European countries (France, Spain, Italy and Poland) have reported falls in life expectancy in 2020. The data suggest that for both sexes Spain, Italy and Poland have experienced similar or greater decreases in life expectancy in 2020 than England, while France experienced smaller decreases. Of these five countries, Poland had the greatest decrease for males (1.5 years), while Spain had the greatest reduction for females (1.6 years) (41). This is broadly consistent with the excess mortality analysis presented in Figure 3c.
Figure 6 – Life expectancy
Time periodYearsMaleFemaleLife expectancy at birth, by sex, England, 1981 to 2020Years
Breakdown of trends in life expectancy by age or cause of death
This section examines which age groups and causes of death have contributed to the trend in life expectancy or inequalities in life expectancy presented earlier. Figure 7a shows a breakdown of the change in life expectancy by year in England between 2017 and 2020 according to age group or cause of death. A positive value for a cause of death or age group means that reductions in the mortality rate in that group acted to increase life expectancy. A negative value means that an increase in the mortality rate in that group acted to decrease life expectancy.
Between 2018 and 2019, most causes of death show positive values. This means that death rates from these causes reduced, contributing to an increase in life expectancy. Between 2019 and 2020, mortality from COVID-19 was estimated to have reduced life expectancy by 1 year for females and 1.3 years for males. All other causes of death had little impact on the change in life expectancy between 2019 and 2020. .
Between 2018 and 2019 most age groups had a reduction in mortality rates and therefore changes in most age groups led to an increase in life expectancy. Between 2019 and 2020, increases in mortality rates in all age groups over 30 contributed to the decrease in life expectancy, but the largest contribution was from the 70 to 79 and 80 to 89 age groups. Age groups under 30 generally made a small positive contribution to life expectancy between 2019 and 2020 and offset some of the overall decrease in life expectancy.
The inequalities data in Figure 7b show the contribution by age group or cause to the gap in life expectancy between the most deprived and the least deprived areas in England in 2019 and 2020. In 2020, COVID-19 was estimated to contribute 1.2 years to this gap for females and 1.4 years for males. In addition, higher mortality from heart disease, lung cancer, and chronic lower respiratory diseases in deprived areas are important reasons for the gap in life expectancy in both 2019 and 2020. Accidental poisoning also made a large contribution in males. Addressing inequalities in these diseases would have a substantial impact on reducing inequalities in life expectancy.
Figure 7 – Breakdown of trends and inequalities in life expectancy
FemaleMaleContribution to change inlife expectancy (years)Contribution to change inlife expectancy (years)Contribution to change inlife expectancy (years)Age groupBreakdown of change in life expectancy at birth by age, England2017 to 2018Age group2018 to 2019Age group2019 to 2020Age groupBy age▼
Leading causes of death
Figure 8a shows the five leading causes of death in each age group over 20 in 2020, based on the number of deaths by underlying cause, for females and males separately. Deaths in children aged under 20 are not included in this chart as the number of deaths is small and the leading causes vary from year to year, but include suicide, accidents, cancers and congenital anomalies.
Figure 8a refers to deaths registered in 2020. Sudden deaths, those where the cause is unclear and those suspected to be due to certain causes, such as suicide or drug poisonings, can only be registered after referral to a coroner and sometimes an inquest is required which may take months or even years to conclude (42). Although the full impact of the pandemic will not become clear for some time, coroners have reported pressure on the system which may have resulted in lengthier registration delays than previously (43). This may impact on the pattern of leading causes of death presented for 2020.
In 2020, COVID-19 was the leading underlying cause of death among males, replacing heart disease, and the second largest cause of death among females, after dementia and Alzheimer’s disease. As mentioned previously, many of those who died from COVID-19 also had dementia or heart disease mentioned on their death certificate. Between March and June 2020, dementia was the most common main pre-existing condition, for 25.6% of all deaths involving COVID-19 in England and Wales. Heart disease was the second most common at 9.9% (27).
As previous Health Profile for England reports have discussed in depth, prior to the COVID-19 pandemic the age-standardised death rates from dementia and Alzheimer’s disease had been increasing (44). A number of factors have contributed to the long term increase in the death rates from dementia and Alzheimer’s disease including an increase in awareness of dementia and historical NHS policies encouraging GPs to diagnose, leading to increased recording on death certificates (45). This means that, in recent years, deaths may have been classified as dementia that would not have been in the past. The dementia mortality rate increased further in 2020 for females, but was similar to 2019 for males (46).
COVID-19 featured particularly prominently in the leading causes in older age groups, alongside the causes mentioned above. In younger age groups, COVID-19 was among the top five leading causes, but there were more deaths registered from external causes such as suicide or accidental poisoning, as well as cirrhosis and liver disease, heart disease (in males) and breast cancer (in females).
The data in Figure 8b show inequalities in age-standardised mortality rates at all ages for 2015 to 2019 and for 2020, for several cause groups including cardiovascular disease, cancers, respiratory disease and dementia and Alzheimer’s. Inequalities in mortality from these causes of death persisted in 2020 and with the exception of dementia and Alzheimer’s, mortality declined across every deprivation category. However, comparisons by cause over time need to be made with caution. COVID-19 was a new cause of death in 2020 and some who died from it may have died from another cause instead if the pandemic had not occurred. In addition, this ‘mortality displacement’ may not be consistent across deprivation categories as we know that COVID-19 disproportionately impacted deprived areas.
Alcohol-specific mortality increased by around 20% between 2019 and 2020, driven chiefly by increases in mortality from alcoholic liver disease (36). 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 (47).
Drug misuse deaths have been on a general increasing trend since 2012, and in 2020 they were the highest they have ever been (48). One possible explanation for this general increase is an increasing number of long-term heroin users with failing health that are at greater risk. This is supported by the fact that the average age at death from drug misuse has increased since the 1980s. There is also evidence of considerable inequalities in relation to drug misuse death rates. In 2020 the rate was almost 10 times higher in the most deprived areas compared with the least deprived areas (as measured by the relative index of inequality (RII)) (49). This inequality in drug-related mortality is related to prevalence of drug use, particularly use of opioids, which is also associated with deprivation (50).
Figure 8c shows international comparisons of age-standardised years of life lost rates from four leading groups of causes of death using data from the Global Burden of Disease (GBD) 2019. Years of life lost are estimated by multiplying the number of deaths by the maximum global life expectancy for each age and sex, and then summing to get the total number in each country. England, the UK and the USA had high rates of years of life lost from chronic respiratory disease in males and females compared with other countries. Years of life lost from cancers in females were highest in Poland followed by England and the UK while in males the England and UK rates were lower than many other counties. For years of life lost from cardiovascular disease and dementia, England and the UK were not among the highest or lowest countries.
Figure 8 – Leading causes of death
CancersCirculatoryCOVID-19ExternalOtherRespiratoryLeading causes of death by age group, England, 2020Rank (by number of deaths descending)Suicideand injury/poisoning ofundeterminedintentAccidentalpoisoningLiver diseaseCOVID-19Breast cancerBreast cancerLiver diseaseAccidentalpoisoningCOVID-19Suicideand injury/poisoning ofundeterminedintentBreast cancerLung cancerCOVID-19Heart diseaseLiver diseaseCOVID-19Lung cancerHeart diseaseChronic lowerrespiratorydiseasesDementia andAlzheimer’sdiseaseDementia andAlzheimer’sdiseaseCOVID-19Heart diseaseStrokeInfluenza andpneumoniaDementia andAlzheimer’sdiseaseCOVID-19Heart diseaseStrokeChronic lowerrespiratorydiseases
CancersCirculatoryCOVID-19ExternalOtherRespiratoryLeading causes of death by age group, England, 2020Rank (by number of deaths descending)Suicideand injury/poisoning ofundeterminedintentAccidentalpoisoningTransportaccidentsHomicideCOVID-19AccidentalpoisoningSuicideand injury/poisoning ofundeterminedintentHeart diseaseLiver diseaseCOVID-19Heart diseaseCOVID-19Liver diseaseLung cancerColorectal &anal cancerHeart diseaseCOVID-19Lung cancerChronic lowerrespiratorydiseasesDementia andAlzheimer’sdiseaseCOVID-19Dementia andAlzheimer’sdiseaseHeart diseaseStrokeChronic lowerrespiratorydiseasesCOVID-19Heart diseaseDementia andAlzheimer’sdiseaseLung cancerChronic lowerrespiratorydiseases
Every child having a good start in life is the foundation for the future health and wellbeing of England’s population. This section presents indicators on several aspects of child development and health including birthweight, infant mortality, early child development, dental health and child obesity. It presents data for the pre-pandemic period and includes preliminary data for 2020 where it is available.
Summary 8 – trends in child health
Recent decades have seen overall improvements in babies born with a low birthweight, infant deaths, child development and dental health. However, in the years leading up to the coronavirus pandemic improvements in these indicators had slowed. In addition, there has been little change in the prevalence of obesity in children aged 4 to 5 (9.9% in 2019 to 2020) and an increase in children aged 10 to 11 years (from 18.7% in 2009 to 2010 to 21.0% in 2019 to 2020).
Summary 9 – inequalities in child health
Wide inequalities are apparent across all indicators of child health presented. In 2019, in the most deprived areas, the proportion of term babies with a low birthweight, the infant mortality rate and the prevalence of obesity in children aged 4 to 5 and 10 to 11 years was more than double the least deprived. In 2018 to 2019, 23.4% of children aged 5 years had dental decay, and the prevalence was almost 4 times higher in most deprived areas than in the least deprived areas. For those indicators with data available by ethnicity (low birthweight, infant deaths, dental decay, obesity) inequalities by ethnic group are present.
Summary 10 – impact of the pandemic on child health
Preliminary data suggest that the proportion of babies born with low birthweight and the infant mortality rate has not changed significantly since the start of the pandemic. Comparable data on child obesity or child development are not available for the pandemic period, but there is evidence of a reduction in physical activity and that children who started school in Autumn 2020 needed additional developmental support compared with children in previous years. The hospital admission rate for extraction of teeth due to dental decay in children reduced in 2020 and in children up to the age of 5 was half that seen in previous years. This may indicate that more children are living with severe dental decay as a result.
Detailed analysis and charts
There was little change in the proportion of babies born at full term with a low birthweight (less than 2500 grams) between 2006 and 2019, remaining at just under 3% (Figure 9a). During the pandemic period the available indicator measures low birthweight among all live and still births instead of live births at full term. These figures are higher than the main indicator used in England, as low birthweight is more common among still births and premature births. However, the pandemic has not altered the trend in low birthweight. Provisional monthly low birthweight data from April 2020 to March 2021, suggest a very slight reduction in low birthweight rate compared with the average for April 2016 to March 2020 (3).
In 2018 the proportion of babies born at full term with a 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 9b). The relative index of inequality is a summary measure of inequality. It measures the relative difference between the most and least deprived areas and is presented as a ratio. For low birthweight the RII is 2.2, meaning that the level in the most deprived areas is 2.2 times higher than the least deprived. Analysis by deprivation back to 2010 shows that this inequality remained broadly similar (39). The analysis for April 2020 to March 2021 suggests that these inequalities have remained throughout the pandemic (3).
There are well-established inequalities by ethnic group in low birthweight (51). During April 2016 to March 2020 and the pandemic period from April 2020 to March 2021, low birthweight was highest among Asian and Black groups and lowest in the White group (3).
International comparisons of low birthweight in Figure 9c, presented for the latest year available, are measured as a proportion of all live births only (excludes still births). Of the eight countries with recent data, Japan has the highest proportion (over 9% in 2019), while the UK rate is just under 7%.
Figure 9 – Low birthweight
Time periodPercentagePercentage of low birthweight babies at term, England, 2006 to 2019Percentage
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 anomalies (52).
Figure 10a presents trends in infant mortality rates from 2001 to 2003 until 2017 to 2019. They are presented on a three-year rolling average basis to smooth out variation. The rate fell from 5.4 per 1,000 live births in 2001 to 2003 to 3.9 in 2013 to 2015 and it remained at this level up to 2017 to 2019. Therefore, there has been little improvement in recent years. The impact of the pandemic on the infant mortality rate is not yet known, however provisional data suggest that there has been little change (53).
There are substantial inequalities in infant mortality rates (Figure 10b). In 2017 to 2019, the rate in the most deprived areas was more than double that in the least deprived areas, as measured by the RII. Longer-term analysis shows that the inequality in infant mortality rates has remained broadly similar in the past decade (39). In addition to this, in 2018, infant mortality rates were highest in the Black Caribbean (6.5 per 1,000 live births) Black African (6.4) and Pakistani (6.3) groups and lowest in the White British (3.2) and White Other (2.7) groups (52).
Among the 9 countries examined in Figure 10c, the United States and Canada had the highest infant mortality rates in 2018 or 2019, and Japan had the lowest rate. The UK had a relatively high rate among the European countries presented, although rates were similar to France and Poland, and the UK’s position relative to other European countries has worsened over the last 3 decades (54).
Figure 10 – Infant mortality
Time periodRate per 1,000 live birthsInfant mortality rate, England, 2001 to 2003 up to 2017 to 2019Rate per 1,000 live births
Dental decay remains a serious child health issue and is a major cause of hospital admission in children in England, but it is largely preventable (55). If left untreated tooth decay can cause pain, infection, lack of sleep and time off school. Figure 11a shows trends in the percentage of children aged 5 years with experience of obvious dental decay. In the academic year 2018 to 2019, 23.4% of children aged 5 years had experienced obvious dental decay. This was similar to 2017 to 2018, but a decrease from 2007 to 2008, where the figure was 30.9%.
There are also wide inequalities in the prevalence of dental decay by deprivation and ethnic group. Figure 11b shows that, in the academic period 2018 to 2019, children from the most deprived areas were 3.8 times more likely to have experienced dental decay than those from the least deprived areas (as measured by the RII). This inequality is wider than in 2011 to 2012 when the RII was 3.2 (39). In addition, prevalence was highest in the Other ethnic group (44.3%) and the Asian ethnic group (36.9%) and lowest in the White ethnic group (20.6%). Comparable data for other countries are not available for this indicator.
Figure 11 – Dental decay
Time periodPercentagePercentage of 5 year olds with experience of visually obvious dental decay, England, academic years 2007 to 2008,up to 2018 to 2019Percentage
In the period 2017 to 2018 up to 2019 to 2020, 34,771 children aged 5 or younger were admitted to hospital due to dental decay, a rate of 286 per 100,000 (56). Monthly monitoring of admissions during the COVID-19 pandemic saw a significant reduction between February and April 2020. Although admission rates have risen again since, the rate for 2020 was half that seen on average during 2018 and 2019. This reduction reflects the impact of the pandemic on dental and other elective services. Reductions in routine services, which varied across the country, are likely to have been behind this decrease in admissions and may indicate that there are children living with severe dental decay as a result.
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 life (57). Being able to express themselves, interact with peers and make themselves understood helps to build a child’s confidence and boost their self-esteem (58). Inadequate communication skills can lead to poorer adult outcomes in literacy, mental health and employment (59).
In the academic year 2018 to 2019, 82.2% of children achieved at least the expected level of development in communication and language skills at the end of Reception year, and this is an improvement since 2012 (Figure 12a). Fewer boys than girls achieved the expected level of development, 77.2% compared with 87.4%.
Figure 12b shows that a clear gradient can be seen between child development and deprivation with 77.7% children living in the most deprived areas achieving the expected level compared with 87.0% of those living in the least deprived areas. Comparable data for other countries are not available for this indicator.
Figure 12 – Child development
Time periodPercentageMalePersonsFemalePercentage of children achieving at least the expected level of development at the end of reception year (communication and language),England, academic years from 2012 to 2013, to 2018 to 2019Percentage
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) (60). 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 surveyed, 76% reported that children who started school in the Autumn 2020 term needed more support than children in previous cohorts. Almost all schools indicated that they were concerned about pupils’ communication and language development (96%), personal, social and emotional development (91%) and levels of literacy (89%) (61).
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 associated mortality and morbidity later in life (62).
In the academic year 2019 to 2020, data from the National Child Measurement Programme (NCMP) showed that, 9.9% of children aged 4 to 5 (Reception year) were obese and this had seen little change since 2009 to 2010. However, 21% of children aged 10 to 11 years (Year 6) were obese, up from 18.7% in 2009 to 2010 (Figure 13a).
Figure 13b shows wide inequalities in childhood obesity. In both age categories, children in the most deprived areas were more than twice as likely as children in the least deprived to be obese, as measured by the RII. There are also inequalities by ethnic group. The Black African ethnic group had the highest prevalence in children aged 4 to 5 years (15.9%) and the Black African, Black Caribbean and Bangladeshi ethnic groups had the highest prevalence in children aged 10 to 11 years (around 30%).
Figure 13 – Child obesity
Time periodTime periodFemalePercentagePersonsPercentageReceptionYear 6Prevalence of obesity in children aged 4 to 5 years (reception) and 10 to 11 years (Year 6), England,academic years 2019 to 2010, to 2019 to 2020FemalePercentageReceptionYear 6MalePercentageReceptionYear 6PersonsPercentage
The full impact of the COVID-19 pandemic on obesity levels for children is not yet known, however, a link between weight gain and out of school time in the school holidays has previously been demonstrated (63). 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 people (64). Sport England estimate that the impact has been greater on boys than girls and on those from Black and Mixed ethnic groups (65).
Other indicators of child health
Previous Health Profile for England reports, prior to the pandemic, demonstrated inequalities in many other aspects of children’s health (66).
In 2018 to 2019 obesity levels in early pregnancy in deprived areas (28.5%) were almost double the least deprived (15.1%) (67), and smoking in early pregnancy in deprived areas (24.0%) was more than 5 times the least deprived (4.3%) (68). The proportion of mothers smoking at the time of delivery has reduced slightly from 13.6% in 2010 to 2011, to 10.4% in 2019 to 2020, but remained higher in deprived areas (69). In 2018, the teenage conception rate continued to decline, but in the most deprived areas was more than double the least deprived (70).
Prior to the pandemic, 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 2018 (71). Lifetime prevalence of drug use among school pupils aged 11 to 15 increased sharply between 2014 and 2016, even accounting for a methodological change, but then remained level up to 2018 at 24% (72).
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. The impact on education and employment among young people is covered in the wider determinants section of this report.
In 2020, hospital admissions of children and young people (under 25 unless otherwise stated) for asthma, diabetes, epilepsy, gastroenteritis (0 to 4 years), lower respiratory tract infections (0 to 4 years) and following accidents were generally below average for 2018 and 2019. Admissions in this age group for self-harm and assault were reduced in the quarter from April to June 2020, but returned to similar to average for 2018 and 2019 levels in the latter half in 2020, except for the 5 to 14 age group which were above average (3).
One national survey comparing aspects of mental health found that in 2020, one in six (16.0%) 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% respectively (73).
Health in adults
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 purpose (74). 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 economy (75).
This section examines trends in the health of adults prior to the pandemic, but also summarises the information to date on the potential impact of the pandemic.
Summary 11 – healthy life expectancy
Healthy life expectancy measures the number of years spent in good health. In 2017 to 2019, healthy life expectancy was 63.5 for females and 63.2 for males, and this has shown little improvement in recent years. In addition, healthy life expectancy was shorter in the most deprived areas and the gap with the least deprived areas was 19 years for both males and females. In 2018, the UK had the lowest reported healthy life expectancy out of the countries presented for females and the second lowest for males.
Summary 12 – causes of morbidity
In 2019, the top 3 causes of ill health (excluding mortality) for males were low back pain, diabetes mellitus and depression, and for females were low back pain, headache and gynaecological diseases. Out of the countries examined, for males England had the highest rate of ill health from diabetes, depression and alcohol use. For females England had the highest rate for asthma and second highest for diabetes and neck pain.
Summary 13 – impact of the pandemic on health in adults
The pandemic has impacted mental and physical health. The prevalence of high anxiety levels and low happiness around the start of the first national lockdown was more than double previous years. In addition, changes in service provision and patterns of health seeking behaviour has meant that there is a consistent pattern of reduced contact with health services over the pandemic period. New cancer diagnoses between April and December 2020 were 16% lower than in the same months in 2019. Since March 2020, the percentage of people with dementia in receipt of a care plan review declined each month to 39.4% in January 2021, compared with more than 70% in previous years. These reductions in contact may result in missed opportunities to provide preventative treatment and support, long-term health complications or an increase in deaths in the future.
Detailed analysis and charts
Prior to the pandemic, as discussed in previous Health Profile for England reports (44), England’s older population had been increasing. As the number of older people increased, the number of people living with ill health or one or more long-term health conditions also increased.
The latest population estimates from ONS, for 2020, indicated that almost 10.5 million people living in England were aged 65 or over and more than 0.5 million aged 90 or over. This is an increase of nearly 2 million and 0.13 million respectively since 2010. As a proportion of the population, those aged 65 and over increased from 16.3% to 18.5% over the same time period.
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. In 2017 to 2019, healthy life expectancy was 63.2 years for males and 63.5 years for females and has shown little improvement in recent years (Figure 14a). Females could expect to spend around 20 years in poor health, or 24% of their life. As male life expectancy is shorter, but males have similar healthy life expectancy to females, males could expect to spend fewer years in poor health (17 years), or 21% of their life.
In 2017 to 2019, the inequality gap in years spent in good health was even larger than the gap in life expectancy presented earlier. Differences in education, employment and living conditions and variations in social care and health services influence healthy life expectancy (76). The gap in healthy life expectancy between the most and least deprived areas in England (as measured by the SII) was 19 years for both females and males. Therefore, people in deprived areas had shorter life expectancy, spent fewer years in good health and also spent a larger proportion of life in poor health: 35% for females and 29% for males, compared with 18% and 15% in the least deprived decile. (Figure 14b)
Figure 14 – Healthy life expectancy
Time periodTime periodFemaleYearsLife expectancy and healthy life expectancy at birth, England, from 2009 to 2011, to 2017 to 2019FemaleYearsMaleYears64 yearsin good health18.7 yearsin poor health63 yearsin good health15.8 yearsin poor health63.5 yearsin good health19.9 yearsin poor health63.2 yearsin good health16.6 yearsin poor health
Trends in the health of adults can also be measured in other ways. 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. Between 1990 and 2017, the rate of YLDs in every age group over 30 increased very slightly, although as these are modelled estimates there is some degree of uncertainty around them (44).
The Health Survey for England examines trends in self-reported health conditions. In 2017, for every age group over 45, the prevalence of a long-term condition was lower than in 2005, however the rates fluctuated a lot between those years (44).
Data on trends in the prevalence of ill health in the population present a complex picture, but it appears that there has been little change in all these measures over the last decade. This is partly because prevalence is determined by the percentage of people who develop ill health or the condition and how long they live with it. Positive health developments such as better treatment may work to increase prevalence as they may increase survival of those in ill health.
Estimates of healthy life expectancy for 2020 or other measures of the prevalence of ill health are not yet available, so the impact of the pandemic is unknown. As mentioned earlier, there may be long term negative effects on health due to ‘long COVID’, as well as indirect effects arising from, for example, delays in accessing treatment for health problems and changes in behaviours as discussed later in this report. It may take some time for the full impact of the pandemic on health status to be quantified.
The international comparisons of healthy life expectancy presented in Figure 14c also predate the period of the pandemic. The highest reported healthy life expectancies in 2018 for both males and females were in Spain and Italy. The UK had the lowest reported healthy life expectancy out of the countries presented for females and the second lowest for males. In terms of the proportion of life spent in poor health, the UK ranked lowest for both sexes. These international comparisons should be treated with some caution as there may be differences in the measurement and self-reporting of health status between countries.
Leading causes of morbidity
Figure 15a 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. The top 3 causes for males in 2019 were low back pain, diabetes mellitus and depressive disorders, and for females were low back pain, headache disorders and gynaecological diseases. These conditions are different from the 2017 estimates reported in the 2019 Health Profile (66) but these changes largely reflect improvements in the methodology used and changes to the categorisation of conditions rather than changes in the rates of occurrence of the conditions in the population.
Figure 15a shows that the YLD rate for diabetes mellitus increased significantly between 1990 and 2019, for males it was 2.3 times greater and for females it was 2.2 times greater in 2019. The national diabetes audit shows a recent increase in prevalence from less than 5% in 2010 to 2011 to more than 7% in 2019 to 2020 (77). There are also inequalities in diabetes prevalence, with higher rates in Black and Asian groups and low income households (78, 79).
Data from the GP Patient Survey show that the prevalence of any long-term musculoskeletal problem in England was 18.6% in 2020, similar to 2019 (80). The prevalence increased with age and was higher than average in females (20.6%), White ethnic groups (20.6% to 27.3%), the Black Caribbean group (19.9%), most deprived areas (19.4%), and people who are permanently sick or disabled (45.0%) or retired (38.0%).
In 2019, of the 9 countries presented, Figure 15c shows that for both males and females the USA had the highest burden of all cause morbidity followed by England (and the UK), while Japan had the lowest. For males, England had the highest rate of morbidity for diabetes, depression and alcohol use. For females England had the highest rate for asthma and second highest for diabetes and neck pain.
Figure 15 – Leading causes of morbidity
20191990Years lived with disability, per 100,000 populationCauseAge-standardised morbidity rate, leading causes, by sex, England 1990 and 2019CausePersons▼
Mental health and wellbeing
According to the Global Burden of Disease, in 2019, mental health conditions such as depression and anxiety, accounted for 16.9% of total morbidity in the population (81). Data from the latest Adult Psychiatric Morbidity Survey show that in 2014 nearly 1 in 5 adults aged 16 to 64 years in England had at least one common mental health disorder (CMD) such as depression, anxiety, phobias, obsessive compulsive disorder or panic disorders (82). Between 1993 and 2014, the prevalence of a CMD in adults has increased.
There are substantial differences in the mental health of population groups in England. In 2014, the prevalence of a CMD among females was greater than males (20.7% compared with 13.2%). Overall, people of working age were most likely to have symptoms of a CMD although the highest prevalence was among females aged 16 to 24 years. However, unlike most physical health problems, prevalence was lowest among the oldest age groups.
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, bipolar disorder and also personality disorder, eating disorder and severe depression. SMI affects close to an estimated 551,000 people in England (83).
Many people with SMI also experience poor physical health and have higher premature mortality (84). 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 (84). Compared with the general population, in 2016 to 2018, people aged under 75 in contact with mental health services in England had death rates that were 3.7 times higher than the general population. This rose to 5.4 times higher for liver disease and 5.2 times higher for respiratory disease, and was 3.1 times higher for cardiovascular disease and 1.1 times higher for cancer (85).
Figure 16a shows trends in wellbeing up to 2019 to 2020, measured by four indicators, anxiety, low happiness, low life satisfaction and low worthwhile feelings. Generally, there was a decline in the proportion with low life satisfaction and low happiness in the years prior to the pandemic, but there was little change in high anxiety and low worthwhile feelings. In the latest year 2019 to 2020 wellbeing worsened across all indicators.
In 2019 to 2020, low wellbeing scores were more common among people who were economically inactive and in particular unemployed, those living with a disability, people in the Black (low life satisfaction only) and Mixed ethnic group, and people aged between 45 and 64 (Figure 16b).
Figure 16 – Mental health and wellbeing
Time periodTime periodPeople with a high anxiety scorePercentagePeople with a low satisfaction scorePercentageMalePersonsFemaleSelf-reported wellbeing, England, 2011 to 2012, to 2019 to 2020People with a high anxiety scorePercentageMalePersonsFemalePeople with a low happiness scorePercentageMalePersonsFemalePeople with a low satisfaction scorePercentageFemalePersonsMalePeople with a low worthwhile scorePercentage
Self-reported mental health and wellbeing worsened during the pandemic. Adults experienced relatively high anxiety levels and low happiness levels in the week immediately preceding the first national lockdown and the 2 following weeks. Prevalence for both indicators was more than double the average for 2019. Prevalence for both these has since declined but has generally remained above 2019 levels up to the week of the 11 July 2021 (3).
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 England.
Prior to the pandemic, rates of recorded dementia prevalence among those aged 65 and over had been around 4.3% since 2017. Recorded prevalence dropped in March 2020, to around 4% in June 2020, and remained around this level up to June 2021 (3, 86). This indicates there were around 35,000 fewer people aged 65 and over with a diagnosis of dementia (86). This partly reflects reduced access to services where diagnosis takes place, however, as described earlier many people who died from COVID-19 also had a dementia diagnosis.
Early and prompt diagnosis is important in the management and treatment of dementia. Diagnoses of those at early or a mild stage can occur through a GP referral to a Memory Assessment Service. This pathway route accounts for about 50% of new diagnoses. Very few referrals were made between March to May 2020 (first national lockdown), by September 2020 referrals were down by around 25% of those expected (3). It is estimated that there have been 10,000 missed referrals up to March 2021.
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. In 2018 to 2019 78.0% of people with dementia received a care plan review. This fell to 75.0% in 2019 to 2020 (86). Since March 2020, the percentage of people with dementia in receipt of a review declined each month to 39.4% in January 2021 and remained around this level until June 2021 (3).
The impact of individuals needs not being addressed by the health and social care system may result in changes in behaviours. Antipsychotic drugs are used to treat agitation, aggression, and psychosis in dementia when alternative strategies have failed. Since February 2020 there has been a sustained increase in the proportion of people with dementia being prescribed antipsychotic medication (3).
Cancers do not feature as leading causes of YLDs in the GBD data presented above, but are a significant cause of ill health and mortality in England. Prior to the COVID-19 pandemic, the number of cancers diagnosed had been increasing year-on-year. In 2018, more than 320,000 malignant tumours were diagnosed, an increase of 39.6% from just under 230,000 in 2002 (87). After taking account of population size and age, the age-standardised rate of cancer diagnoses was highest in 2013, and fell by 3% between then and 2018.
In 2018 the most common cancer sites for males were prostate, lung and bowel. For females it was breast, lung and bowel. Between 2008 and 2018 thyroid cancer had the greatest percentage increase in age-standardised incidence for both sexes at 59% for females and 77% for males, followed by liver cancer. However, many other cancer sites also showed an increase. Lung cancer incidence decreased in males, but increased in females over this time period (87). This difference in the trend in lung cancer reflects differences in the historical trend in smoking prevalence between the sexes.
The Rapid Cancer Registration Dataset (RCRD) provides a quick, indicative source of cancer data from January 2018 onwards (88). Monthly incidence up to April 2021, following adjustment for the number of working days in each month, is presented in Figure 17a and for the four most common cancers. New cancer diagnoses in April and May 2020 were more than a third lower than those in the same months in 2019. Overall incidence from April to December 2020 was 16% lower than the equivalent period in 2019. There is some variation in the reduction in cancer incidence by tumour site, with prostate cancer, breast cancer and melanoma associated with the greatest reductions in 2020.
Incidence is compared with the same month in the previous year in Figure 17b, for a range of breakdowns and presented as a ratio multiplied by 100. From March 2021, the comparison is to 2019, to avoid comparing months within the period of the pandemic. There were reductions across all referral routes, but those following referral from screening showed the greatest reduction. From April to December 2020 the number of cases diagnosed following screening was less than half that in the equivalent period in 2019. Screening is a vital tool in early diagnosis of cancer, but the availability of screening programmes was reduced during 2020 (89).
Figure 17b shows there were smaller reductions for cancer diagnoses at a later stage than at earlier stages, and there were similar reductions across sex, deprivation and ethnicity groups. However, people aged 0 to 49 had a smaller reduction than other age groups.
This demonstrates that measures to control the spread of COVID-19 in England have had a significant impact on the number of new cancer diagnoses. This may result in more people being diagnosed at later stages, when curative treatments are less likely to be effective. It is possible that we may see the impact of these reductions in new diagnoses through an increase in deaths in future years.
Figure 17 – Cancer incidence
Time periodNew cancer diagnoses (working day adjusted)LungProstateColorectalBreastAll sites combinedMonthly new cancer diagnoses, working day adjusted, England, January 2018 to April 2021New cancer diagnoses (working day adjusted)
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. For a wide range of reasons for admission or diagnoses, data from the WICH tool show there is a generally consistent pattern of reduced admissions from April to December 2020 compared with a baseline showing the average for the equivalent period across 2018 and 2019. Overall emergency and elective admissions were reduced for both males and females, and for all age groups, ethnic groups and deprivation groups. These patterns were also observed for Accident and Emergency (A&E) attendances and outpatient appointments (3).
In older adults aged 65 and over, rates of hospital admissions for falls and hip fractures from April to September 2020 were below or similar to the average rates for 2018 and 2019 for equivalent months. Rates from October to December 2020 were below the 2018 and 2019 levels. This is likely to reflect the fact that fewer people were going out at the start of the second wave of the pandemic (3).
Weekly emergency admissions for acute coronary syndromes (including heart attacks) and stroke were lower during the first national lockdown in the spring of 2020 compared with the same weeks in 2018 and 2019. They were also lower from mid-February to early March 2021. This trend was seen in both males and females and is likely to reflect a reluctance to seek help during the peaks in COVID-19 cases (3).
There were 9 million outpatient attendances (equating to approximately 3.4 million individual patients) for vision in financial year 2019 to 2020, an increase of over 37% compared with a decade ago. However, in 2020, due to the COVID-19 pandemic, there was a 29% reduction in vision outpatient attendances. Cataract surgery was also affected and decreased by over 40% in the year 2020 compared with the previous year. (90).
There is evidence of a reduction in GP consultations, particularly in the first wave of the pandemic, and a shift to undertaking consultations remotely (91). Survey data collected during the period 6 May 2020 to 26 January 2021 show that of those people reporting that they had a worsening health condition in the preceding 7 days, around half reported that they had not sought advice for their condition. The most common reason for not doing so was to avoid putting pressure on the NHS, followed by concerns about catching COVID-19(3).
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.
Risk factors associated with ill health
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 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.
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 in detail where data are available.
Summary 14 – trends in risk factors
Prior to the pandemic, there was an upward trend in obesity in adults to 28.0% in 2019, while the prevalence of smoking in adults declined to 13.9%. The prevalence of ‘increasing or higher risk’ drinking in adults was 22.7% in 2019, a slight reduction on previous years, while there was evidence of an increase in drug use. The proportion of adults meeting recommended level of physical activity and fruit and vegetable consumption had remained fairly constant.
Summary 15 – impact of the pandemic on risk factors
The prevalence of ‘increasing and higher risk’ drinkers 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 There has been an increase in the number of people trying to quit smoking during the pandemic 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 obesity is not yet available.
Summary 16 – inequalities in risk factors
Inequalities in risk factor prevalence contribute to inequalities in ill health and mortality. In 2019, 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 prevalence of ‘increasing or higher risk’ drinking was greatest in the highest household income group at 34.8%. The 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.
Detailed analysis and charts
Leading risk factors
Figures 18a and 18b show the top 15 risk factors associated with morbidity and mortality respectively in England, using data from GBD 2019. The risk factors making the biggest contribution to mortality were tobacco, high blood pressure, diet and high blood glucose. These also make a significant contribution to morbidity along with high body mass index (or obesity), alcohol, drug use and occupational risks. Please note that the disease burden 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. 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 conditions (92).
Figure 18 – Leading risk factors
Low back painDepressive disordersDiabetes mellitusAnxiety disordersFallsAsthmaAge-related and other hearing lossDrug use disordersAlcohol use disordersOsteoarthritisAll other causesPercentage of YLDs (age standardised)Behavioural risksMetabolic risksEnvironmental or occupational risksAge-standardised morbidity attributed to risk factors, broken down by cause of morbidity, England 2019Behavioural risksMetabolic risksEnvironmental or occupational risks
Figure 19a shows trends in the levels of four different risk factors: smoking prevalence, ‘increasing or higher risk’ drinking, obesity and hypertension (high blood pressure). ‘Increasing or higher risk’ drinking is defined as drinking more than 14 units of alcohol per week. Figure 19b shows inequalities in these risk factors. Figure 19c shows international comparisons where data are available.
Figure 19 – Risk factors
Time periodTime periodPrevalence of hypertension (HSE)PercentagePrevalence of increasing or higher risk drinking (HSE)PercentagePrevalence of obesity (HSE)PercentageSmoking Prevalence in adults (18+) – current smokers (APS)PercentageFemalePersonsMaleTrends in prevalence of risk factors, England, 2011 to 2019Prevalence of hypertension (HSE)PercentageFemalePersonsMalePrevalence of increasing or higher risk drinking (HSE)PercentageMalePersonsFemalePrevalence of obesity (HSE)PercentageFemalePersonsMaleSmoking Prevalence in adults (18+) – current smokers (APS)Percentage
Estimated smoking prevalence in adults decreased from 19.8% to 13.9% for adults between 2011 and 2019 (Figure 19a). Males and females have seen a similar decrease over time. However, there are groups of the population where smoking prevalence remained much higher than average.
Among people in manual occupations, 23.2% were estimated to be smokers in 2019, more than double the proportion among those working in other occupations or not working (93). Smoking prevalence among those with a long-term mental health condition was estimated to be 25.8% in 2019 to 2020, also more than double the prevalence in the rest of the population (94). Smoking prevalence in the Mixed ethnic group (19.5%) and the White group (14.4%) were significantly higher than average (93).
In addition, Figure 19b shows that, in 2019, smoking prevalence was highest in Yorkshire and the Humber (15.7%) and lowest in the South East (12.2%), and in the most deprived areas it was 1.9 times higher than in the least deprived areas in 2019. This inequality in smoking prevalence by deprivation is a large determinant of the inequalities in mortality and life expectancy presented earlier in this report.
Figure 19c shows that in 2019 the UK had lower smoking prevalence than the other European countries presented, but higher prevalence than the USA and Canada, for both males and females.
There is early evidence that the pandemic may have had a positive impact on enabling some people to quit or reduce smoking. Data from the UCL smoking tool kit, reported in the WICH tool, shows that over a third of smokers attempted to quit in the 3 months up to June 2021. Over-the-counter nicotine replacement therapy (NRT) and e-cigarettes are still the most commonly used aids for quitting. However, during the pandemic there has been a reduction in their use, which suggests an increase in people trying to quit unaided (3).
The impact of the pandemic on overall smoking prevalence is not fully clear as yet. Data from the ONS Opinions and Lifestyle Survey indicate that the proportion smoking between November 2020 and June 2021 was consistently lower than the average for 2019 (3). However, data from the Smoking Toolkit Study suggests smoking prevalence has remained stable, with some evidence of increases among young adults in the first national lockdown and during 2021 (95).
The prevalence of ‘increasing or higher risk’ drinking is estimated to have reduced slightly over the past decade, from 25.7% of people aged 16 or over in 2011 to 22.7% in 2019 (Figure 19a). This reduction was seen for both males and females. In 2019, ‘increasing or higher risk’ drinking was highest in the 55 to 64 age group (29.5%), with the lowest rates among those aged under 25 or aged 75 or over (Figure 19b). The North East had the highest prevalence (28.7%) followed by the North West (26.9%) and the East Midlands the lowest (18.7%).
The prevalence of ‘increasing or higher risk’ drinking was greatest in the highest household income group, with 34.8% of those in the highest income group drinking at least 14 units a week, compared with 15.2% in the lowest income group (Figure 19b). Despite this, the rate of hospital admissions for alcohol-related conditions in 2018 to 2019 in the most deprived areas was more than double that in the least deprived areas (as measured by the relative index of inequality (RII)), and this gap has only slightly narrowed since 2010 to 2011 (39).
This inverse relationship between consumption and harms has also been seen in other countries and 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 areas (96).
Although pubs, bars and restaurants were often closed during the pandemic, other factors such as isolation and lack of employment may have influenced drinking patterns. Initial data shows there was an increase in the proportion of ‘increasing and higher risk’ drinkers in April 2020. Since then, up until June 2021, the proportion has declined but remains above the level seen in 2019, and this increase was observed for both males and females, and regardless of social class. This increase coincided with increased hospital admissions and mortality during the pandemic as described earlier in this report (47).
Figure 19c shows that, in 2019, the UK had lower alcohol consumption than the other European countries presented except Italy, but greater consumption than the USA, Canada and Japan.
Survey-based estimates of recent drug use in the population vary year-on-year, however 9.4% of people aged 16 to 59 reported using any drug in the last year in 2019 to 2020, which was higher than in 2009 to 2010 (8.6%) (97). Prevalence of opioids and/or crack cocaine use is estimated to have increased from 2012 to 2013 until the latest estimates in 2016 to 2017 (98).
In 2019 to 2020, 66.4% of adults reported undertaking at least the recommended level of 150 minutes of moderate intensity physical activity or equivalent per week (99, 100), but there were wide inequalities. For example, this proportion was lower for people who were unemployed (56.7%), living with a disability (52.6%), working in routine and manual occupations (58.4%), Asian (51.9%), Black (54.5%), or living in the most deprived areas (54.9%) (100).
Analysis from Sport England estimates that the proportion reaching the recommended level of physical activity reduced during the pandemic. The impact varied through the different stages of lockdown, but females saw a more sustained drop and the overall impact was greater in lower socioeconomic groups, and Black and Asian ethnic groups (101).
The proportion of the population meeting the recommended ‘5-a-day’ on a ‘usual day’ was 55.4% in 2019 to 2020 and this has declined slightly from 56.8% in 2015 to 2016. There were wide inequalities, for example this proportion was 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%) (102).
The pandemic has impacted on grocery purchasing and food use behaviours. Since the first lockdown and up to the latest data (week ending 14 February 2021) shoppers made fewer trips but bought more items per trip than in the same period in the previous year Changes in food use behaviours were most visible among the younger age groups, households with children and those who were self-isolating. About half of 16 to 34 year olds changed their food use patterns between April and June 2020 while the habits of most of the older age groups remained consistent. There was a shift towards cooking more from scratch, eating together with the family and eating healthy meals, but also a marked increase in snacking, especially in April and May 2020 (3).
Figure 19a shows the long-term trend in adult obesity. It is estimated to have increased from 24.8% in 2011 to 28.0% in 2019, although there has been some fluctuation from year to year. The proportion is consistently slightly higher in females than males (29.1% compared with 27.0% in 2019).
As with other risk factors, there are inequalities in adult obesity prevalence by age, sex and deprivation (Figure 19b). In 2019 it was lowest in those aged under 25, and then increased by age group up to age 65 to 74. It was lower in those aged over 75 years than in those aged 65 to 74 years. This pattern was seen for both males and females. By deprivation, obesity prevalence was lowest in the least deprived areas and highest in the most deprived, although there was a clearer gradient for females than males in 2019. In addition, obesity prevalence was highest in the North East (34.0%) and lowest in London (23.4%).
Figure 19c shows international comparisons in obesity prevalence in 2019 for the countries where data are available, according to whether it has been measured or self-reported. Among the countries with measured obesity levels, the UK had the second highest prevalence (64.2%), after the USA (73.1%), and Japan had the lowest (27.2).
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 and a widening of inequalities.
High blood pressure
Figure 19a shows there has also been a downward trend in the estimated prevalence of high blood pressure (hypertension) in adults from 29.5% in 2011 to 27.9% in 2019. These figures include adults with blood pressure higher than 140/90 mmHg and also those with blood pressure below this limit who report taking medication to lower their blood pressure.
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). 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 Programme (103, 104).
Wider determinants of health
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 course (105). Inequalities in these factors are an important driver of the inequalities in risk factors and health outcomes presented earlier in this report.
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.
Summary 17 – inequalities in the wider determinants of health
The employment rate in England in 2019 to 2020 was 76.2%, but the rate was higher in males and in the least deprived areas. It was lower in Pakistani or Bangladeshi (56.9%), Other (64.8%), Mixed (68.3%) and Black (68.6%) ethnic groups than the Indian (76.9%) and White (78.1%) groups. In 2018 to 2019, 42.3% of all children and 67.7% of children in lone parent households were living below the minimum income standard for healthy living, compared with 29.1% of working age adults and 18.2% of pensioners . In academic year 2019 to 2020, average educational attainment 8 score at age 16 varied from 54.9 in the least deprived local authorities to 47.4 in the most deprived.
Summary 18 – impact of the pandemic on the wider determinants of health
The COVID-19 pandemic has impacted these determinants in complex ways through school and business closures, and changes in employment patterns. The proportion of adults claiming unemployment benefits more than doubled between March 2020 and May 2020 and remained high into 2021. Young adults were particularly affected by changes in employment and 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%).
Detailed analysis and charts
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 also affect health. The contribution of air quality is discussed in the section on health protection.
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 England (106). While the proportion of homes meeting the Decent Homes Standard has increased in recent years, 17% of dwellings in England in 2019, amounting to 4.1 million homes, still failed to meet the standard (107). The private rented sector had the largest proportion of dwellings not meeting the standard at 23%, compared with 16% of owner-occupied homes and 12% of social rented homes.
Fuel poverty is now measured by the new Low Income Low Energy Efficiency (LILEE) statistic (108). A household is defined as fuel poor if it has income (after accounting for fuel costs) below a certain level and a low energy efficient home. In 2019, there were an estimated 13.4 per cent of households (3.18 million) in fuel poverty in England, down from 15.0 per cent in 2018 (3.52 million). Improvements in energy efficiency are considered the main driver of this reduction (109).
Living in a greener environment can promote and protect good health, aid recovery from illness and help with managing poor health. Greenspace can help to bind communities together, reduce loneliness, and mitigate the negative effects of air pollution, excessive noise, heat and flooding (110). Access to safe, high quality greenspace varies across England and the most deprived areas have less available good quality public greenspace (111). This means those who are at greatest risk of poor health, as described earlier in this report, may have the least access to the benefits of greenspace.
In 2018 to 2019, 65% of adults spent time outdoors in the natural environment every week. This proportion was greater in the least deprived areas (70%) than the most deprived (57%). In addition, around 40% of people from Black and Asian ethnic groups spent time outdoors once a week compared with 69% of the White ethnic groups (112).
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 anxiety (113). 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.
Children are assessed for ‘school readiness’ upon completion of the Reception year in school at around 5 years of age, and as discussed earlier in this report, wide inequalities in development are evident in the early years, but also exist throughout the education system. In the academic year 2019 to 2020, the average attainment 8 score (average grade across 8 subjects) at age 16 was 50.2. It varied from to 47.4 in the most deprived to 54.9 in the least deprived local authorities (114). Children from the Chinese ethnic group had the highest score out of all ethnic groups (67.6) and White Gypsy and Roma pupils had the lowest score (23.3). Children who are eligible for free school meals had a lower average score (38.6) than those who were not, and this was apparent across all ethnic groups (115).
As mentioned earlier, children’s education has been severely disrupted during the pandemic. From 23 March 2020 until June 2020, most schools in England were closed to children other than those with parents who were keyworkers or who were classed as vulnerable. Some school years did return in June 2020, but this varied throughout the country. Many parents were homeschooling their children and exams were cancelled. In addition, COVID-19 cases in schools led to the closure of many school ‘bubbles’ during autumn term in 2020 and winter 2021, especially in areas with high COVID-19 case rates.
The long-term impact of this on education and health is not yet known. However, initial studies conclude that, for most pupils and year groups, learning did suffer to some degree and this was greater for primary and more disadvantaged students. Although the difference in learning loss between regions was small, the North East and Yorkshire and the Humber had the greatest losses (116, 117).
Good employment improves health and wellbeing across people’s lives, boosting quality of life and protecting against social exclusion.
Although the employment rate in England continued to rise up until 2019 to 2020, when it was 76.2% (Figure 20a), there were inequalities by sex (males 80.2%, females 72.3%) and by deprivation (Figure 20b). The employment rate was lower in Pakistani or Bangladeshi (56.9%), Other (64.8%), Mixed (68.3%) and Black (68.6%) ethnic groups than the Indian (76.9%) and White (78.1%) groups. In addition, only 5.6% of people with a learning disability and 9.0% of people in contact with secondary mental health services were in employment in 2019 to 2020 (118).
Figure 20 – Employment
Time periodPercentageFemalePersonsMalePercentage of people aged 16 to 64 years in employment, England, financial year 2011 to 2012, to 2019 to 2020Percentage
The COVID-19 pandemic has had a substantial impact on employment patterns and opportunities. Despite the establishment of the furlough scheme and other mechanisms to support businesses through the pandemic, the redundancy rate more than tripled from the quarter March to May 2020 (4.1 people per 1,000 employees) to September to November 2020 (14.5). Since then, in the quarter March to May 2021, the redundancy rate returned to pre-pandemic levels. Redundancy rates have been slightly higher in males than females throughout the pandemic (3).
The proportion of adults claiming unemployment benefits more than doubled between March 2020 (3.0%) and May 2020 (6.4%) and remained at a similar level until March 2021. The proportion of claimants then decreased to 5.7% in June 2021 (3).
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 years 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 (3).
Many physical and mental health outcomes improve incrementally as income rises (119, 120). Income is related to life expectancy, disability free life expectancy (120), and self-reported health (121). 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 status (122). It can also influence health through feelings of shame, low self-worth and exclusion (123).
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 on (124). In 2018 to 2019 29.8% of individuals were living below the MIS (Figure 21a) and this was even greater in the North East, Yorkshire and Humberside and London regions (33-34%), and was higher among children (42.3%) than working age adults (29.1%) and pensioners (18.2%). In addition, the percentage remains much higher among children of lone parents (67.7%).
Figure 21 – Minimum income standard
Time periodPercentageAll individualsChildrenIndividuals not reaching the minimum income standard, England 2008 to 2019Percentage
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. In addition, antimicrobial resistance (AMR) remains a risk to health. AMR describes the change of an organism which causes infection and therefore makes a previously effective treatment, such as antibiotics, ineffective. One of the main drivers of AMR which we can influence is the inappropriate use of antibiotics.
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, the air we breathe, as well as our access to food and water (130). In the UK we are experiencing a warmer and wetter climate. All of the top ten warmest years on record have occurred since 1990 with 8 of those since 2000 (131).The recent Climate Change Risk Assessment identified high temperatures and flooding as two of the key risks to health associated with climate change in England (132). Extreme weather events such as these already have a significant impact on public health through increased deaths and ill health (132).
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 AMR.
Summary 19 – air pollution
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 deaths. The highest air pollution exposures have been in deprived urban environments therefore contributing to health inequalities. During the pandemic, up to July 2021, there were fewer vehicles on the roads, which had a favourable impact on air pollution levels.
Summary 20 – infectious diseases
Prior to the pandemic the incidence of many infectious diseases such as TB had been declining, but disproportionately impacted more deprived or inclusion health groups. In 2019, the incidence of TB was higher in people born outside of the UK, particularly those of Indian, Pakistani or Black African ethnicity, than in people born inside the UK. It was also higher in the most deprived than the least deprived areas and more than a fifth of UK born cases had a known social risk factor such as homelessness or drug use. Preventable bacterial sexually transmitted infections (STIs) such as chlamydia and gonorrhoea had been increasing prior to the pandemic.
Summary 21 – impact of the pandemic on infectious diseases
The level of testing for or detection of many infectious diseases such as TB and STIs decreased during the pandemic, which may reflect a real decrease in incidence due to social distancing measures or may reflect a reluctance to be tested. In addition, as demonstrated by the reduction in MMR (measles, mumps, rubella) vaccine coverage, childhood vaccinations were also interrupted during the pandemic while flu vaccination coverage was considerably higher than previous years. Flu vaccine uptake in England from 1 September 2020 to 28 February 2021 was 80.9% for patients aged 65 years and over compared with 72.4% in 2019 to 2020.
Detailed analysis and charts
Air pollution can contribute to cardiovascular and respiratory conditions and shorten 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 deaths (133). Figure 22 shows the areas of the country with the highest concentration of human-made fine particulate matter (PM2.5) levels in 2019. The highest exposures were generally in busy, urban environments, often with high levels of deprivation, contributing to the health inequalities presented in this report.
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 (3).
Monitoring of air quality in London, Manchester and Birmingham, showed that there were improvements in some aspects of air quality following the introduction of the initial lockdown in March 2020, mainly reductions in the concentration of nitrogen dioxide (NO2)(3). Data for NO2 up to the end of November 2020 showed that these values were generally lower than the same period in 2019, however, these data do not account for the influence of other factors such as meteorological conditions. More recent data on NO2 emissions are not available.
Figure 22 – Fine particulate matter (PM2.5)
Source: PHE Wider determinants profile
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 diagnoses (134) 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 23a).
However, Figure 23a shows an increase in the rate of new diagnoses of preventable bacterial sexually transmitted infections such as chlamydia and gonorrhoea up to 2019. This figure excludes diagnoses of chlamydia in under 25 year olds, who are targeted via the national chlamydia screening programme. In 2019, the rate of new STI diagnoses in the third most deprived decile was more than double the rate in the least deprived areas (Figure 23b). This pattern by deprivation is influenced by geographic differences as the rate in London was considerably higher than the England average, with the highest rates consistently in several London boroughs (135).
As discussed earlier in the report, the measures taken to control the COVID-19 pandemic resulted in a drop in the number of people accessing services. The number of tests for chlamydia decreased between March and May 2020 compared with the equivalent months in 2019. Chlamydia testing began to increase in June and July 2020, levelled off until September 2020 but remained below the rates seen in 2019. There was a similar pattern in the testing for other STIs and Hepatitis C. 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 evaluate (136).
Figure 23 – Sexually transmitted infections
Time periodDiagnostic rate per 100,000SyphilisGenital wartsGonorrhoeaChlamydia (aged 25+)New sexually transmitted infections (STIs), excluding chlamydia aged under 25 years, England, 2012 to 2019Diagnostic rate per 100,000
The number of new cases of tuberculosis (TB) have fallen dramatically in England over the last century (44). More recently there has been a steady decline in the incidence rate (new cases per 100,000 population) up to 2018, but then a levelling off (Figure 24a).
However, Figure 24b shows there are wide inequalities in the incidence of TB. In 2019 it was higher in people born outside of the UK, particularly those of Indian, Pakistani or Black African ethnicity, than in people born inside the UK. It was also higher in the most deprived than the least deprived areas and more than a fifth of UK born cases have a known social risk factor such as homelessness or drug use. Figure 24c shows that Poland and Japan had the highest TB incidence in 2019 among the 9 countries presented.
Quarterly data covering the pandemic provides some evidence of a drop in new cases through the pandemic period, which may reflect a real drop in incidence, or a change in healthcare-seeking behaviour or access to healthcare (137).
Figure 24 – Tuberculosis
Time periodIncidence per 100,000Tuberculosis (TB) incidence in England, 2000 to 2019Incidence per 100,000
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.
uptake rates 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. Influenza vaccine uptake in GP registered patients from 1 September 2020 to 28 February 2021 in England was 80.9% for patients aged 65 years and over compared with 72.4% in 2019 to 2020, and 53.0% for patients aged 6 months to under 65 years old in one or more clinical risk groups compared with 44.9% in 2019 to 2020 (138). As a consequence of this and the social distancing measures introduced for the COVID-19 pandemic influenza-like illness was much lower in 2020 to 2021 than in other seasons (139).
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 pandemic (140). 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, rubella) vaccine are at risk of developing measles. In 2019 to 2020 only 86.8% of children aged 5 had received the 2 doses, a slight decline from previous years (141).
Monthly monitoring of MMR vaccination coverage shows that the measures implemented to manage the pandemic have impacted vaccination uptake. MMR (first dose) monthly vaccine coverage estimates measured at 18 months of age from 2019 to 2021, show a decrease from April 2020. The largest decreases were seen in data for August to November 2020, reflecting a decline in uptake within the cohort of children who would have been eligible for the vaccine during the March to May 2020 lockdown. In May 2021, 86.4% of infants were vaccinated with MMR (first dose) by 18 months of age. This is a 1.7 and 1.5 percentage point reduction on May 2019 and May 2020 respectively (142).
Antibiotic-resistant bloodstream infections rose by an estimated 32% between 2015 and 2019 in England (143). Figure 25a shows the trend in the rate of antibiotic prescribing in primary care in England 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 has fallen every year, with the largest drop between 2019 and 2020. There is some variation in prescribing rates with higher prescribing levels in the two most deprived areas in 2020 (Figure 25b).
Figure 25 – Antibiotic prescribing
Time periodIndirectly standardised ratio – per STAR-PUAntibiotic prescribing in primary care, England, 2015 to 2020Indirectly standardised ratio – per STAR-PU
The 2021 Health Profile for England has provided a comprehensive snapshot of the nation’s health, updating many indicators presented in previous reports. The report has also provided an early summary of the impact of the COVID-19 pandemic on many aspects of health and health inequalities.
The report has highlighted how the direct impact of COVID-19 pandemic has disproportionally affected people from ethnic minority groups, people living in deprived areas, older people and those with pre-existing health conditions.
There have been substantial indirect effects on children’s education and mental health, and on employment opportunities across the life course, but particularly for younger people working in sectors such as hospitality and entertainment. In addition, it is clear that access and use of a range of health services has been disrupted during the pandemic and the long-term effects of this is not yet realised.
Data on many aspects of health during the pandemic are not yet available but will be added to the Wider Impacts of COVID-19 on Health (WICH) monitoring tool where possible and summarised in future Health Profile for England reports. Continued monitoring of the indirect impacts of the pandemic on the nation’s health and health inequalities will remain a priority.
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