Mortality insights from GAD – July 2022

Mortality insights from GAD – July 2022

The effect of socioeconomic differences on life expectancy

Welcome to Mortality Insights. In this edition, and in light of the Queen’s recent important celebrations, we explore mortality patterns across various social and economic groups.

We consider differences in life expectancy across local regions in the UK, and how the pandemic has disproportionately affected people of different socioeconomic backgrounds.

Please note, throughout this article we use life expectancy. This means that it does not take into account expected future changes in mortality rates. Please see this ONS article for more information on the difference between time period and group life expectancy.

Platinum Jubilee

This year, Her Majesty the Queen celebrated her Platinum Jubilee, marking the 70th anniversary of her accession to the throne of the United Kingdom. When the Queen was born in 1926, the average life expectancy at birth for females in England and Wales was 62 years. The Queen exceeded this by more than 34 years.

The International Center for Longevity currently estimates that only about 0.15% of the UK population is the same age or older as the Queen. Many members of the royal family also enjoyed long lives; Recently, Prince Philip turned 99 and the Queen Mother was 102 at the time of her death.

The life expectancy of a woman born in England in 2022 is currently expected to be 83 years, a 21-year increase in life expectancy since the birth of the Queen.

While life expectancy has greatly improved, each individual’s chance of reaching that age can vary greatly. With that in mind, we consider studies of how life expectancy varies between groups of people in the UK from different socioeconomic backgrounds. We also look at how COVID-19 has exacerbated these differences.

Finally, we examine how the task of narrowing the gap in healthy life expectancy, as laid out in the recent white paper on scaling up government, can be accomplished.

Life expectancy and deprivation groups

Life expectancy depends on many factors, including but not limited to genes, access to health care, housing, nutrition, wealth and education.

Research has shown that those who live in affluent areas are likely to live much longer than those who live in more deprived areas.

The Multiple Deprivation Index (IMD) is a measure of relative deprivation in England. IMD ranks every small area in England from most to least deprived, based on characteristics including income, employment, education, health and crime.

There are other similar measures in the rest of the UK. These ranks are grouped into decimal categories so that:

  • Ten 1 represents the most deprived small area in England
  • The 10 represents the least deprived 10% of small spaces in England

From 2017 to 2019, males and females in the most deprived areas were expected to live nearly a decade less than those in the least deprived areas. This gap is wider for males (9.4 years) than for females (7.7 years), as shown in Figure 1 below.

shape 1: Life expectancy, England, 2017 to 2019

Source: Office of National Statistics (ONS)

Figure 2 shows the disparity in mortality rates between 2015 and 2019 among the leading causes of death.

It shows how mortality rates, after taking into account differences in the age profiles of different groups, are significantly higher in all-cause disadvantaged areas. In the case of respiratory diseases, the mortality rate is more than double in the most deprived regions compared to the least deprived regions.

Figure 2: Mortality rates from major causes in most and least deprived regions, England, 2015 to 2019

death rate

Source: Public Health England (PHE) based on ONS . data

Lifestyle factors that are known to contribute to reduced life expectancy include:

  • Smoking (in 2019, the prevalence of smoking in the most deprived areas was almost twice as high as in the least deprived areas)

  • Malnutrition and obesity
  • Excessive alcohol and drug abuse
  • poor quality housing
  • Less access to green spaces

All of these factors tend to be more common in underserved areas. They contribute to ill health and are risk factors for leading causes of death.

Differences and changes

Using IMD, ONS analyzes life expectancy at birth in the most and least deprived areas.

Figure 3 shows the change in life expectancy at birth for males and females across two deprivations over the period from 2015 to 2017 and 2018 to 2020.

The baseline data for Figure 3 also showed the increase in deaths in 2020 resulting from the COVID-19 pandemic.

Figure 3: Change in life expectancy at birth by sex and deprivation decile categories, 2015–2017 and 2018–2020

Change in life expectancy at birth

Source: Office of National Statistics (ONS)

Over a typical time period, we would expect life expectancy to continue to increase, as it has over the past century. However, the life expectancy of those living in the most disadvantaged areas has seen a negative change, decreasing by up to 6 months.

In contrast, life expectancy in the richer regions saw no change (eg decile 5 and 8) or a relatively small decrease for males and an increase for females. This is illustrated in Figure 3. This indicates that the gap in life expectancy between the most and least disadvantaged groups in England has widened during recent years.

COVID-19

Figure 2 indicates that individuals living in disadvantaged areas were already experiencing higher mortality rates than underlying health conditions, even before the pandemic. It is possible that these conditions and other risk factors may have increased the severity of COVID-19, and increased mortality rates.

Research indicates a high prevalence of overcrowded housing and jobs that cannot be done from home in low-income areas, resulting in high death rates from COVID-19.

Office for National Statistics data shows that the death rate from COVID-19 at the start of the pandemic was twice as high in the most deprived areas. This is compared to richer regions, based on data released in August 2020. This is evidence that the pandemic has exacerbated the inequality that the most disadvantaged communities face.

Will the gap continue to widen?

Life expectancy is related to healthy life expectancy, which refers to the period during which individuals can expect to live in good health.

Analysis by the Office for National Statistics indicates that those who live in the most affluent areas also have a higher healthy life expectancy, compared to those who live in the most deprived areas. This means that they are likely to spend a higher percentage of their lives in good health. With males in the most deprived areas expected to live less than 75% of their lives in good health, while those in the least deprived areas spend nearly 85% of their lives in good health.

The latest settlement white paper sets a mission to narrow the gap in healthy life expectancy between local areas by 2030. It also sets a goal to increase life expectancy overall by 2035.

The white paper outlines how the overarching ambition to improve overall well-being in the UK will be realized. These include improving the health of the most disadvantaged communities by:

  • Piloting a healthy eating initiative and school cooking revolutions
  • Introducing a new tobacco control plan
  • Establishing community diagnostic centers

These are expected to narrow the gap in healthy life expectancy between regions where it is highest and lowest. Improvement in healthy life expectancy is expected to increase overall life expectancy in the target groups.

last thoughts

Differences in age between some members of the royal family and the public, and those between subgroups within the public, can be largely attributed to the same causes.

No one knows how life expectancy will improve in the future because there are many uncertainties, including the unknown long-term effects of the pandemic.

However, focusing on trying to reduce the differences in life expectancy between different socioeconomic groups will contribute to an overall increase in life expectancy.

disclaimer

The information in this newsletter is not intended to provide specific advice. Please see full disclaimer for details.

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