# data[].attributes.attachment_link.description
British Journal of Midwifery (BJM) is the leading clinical journal for midwives, promoting excellence in midwifery and women's health.

# data[].attributes.body
https://www.nature.com/articles/d41591-022-00062-8

# data[].attributes.attachment_link.readable_text
To maximize the benefits of patient-reported outcomes data while protecting patient welfare, a panel of experts set out ethical guidelines for the incorporation of these into clinical research.

In clinical research, patient-reported outcomes (PROs) are used to provide information on the effects of a disease or treatment from the patient's perspective. PRO data can inform healthcare, research and policy, but they give rise to important ethical issues that need to be addressed in order to maximize the benefits while protecting patients' welfare.
doi: https://doi.org/10.1038/d41591-022-00062-8

# data[].attributes.attachment_link.title
Ethically incorporating patient perspectives into research

# data[].attributes.attachment_link.description
To maximize the benefits of patient-reported outcomes data while protecting patient welfare, a panel of experts set out ethical guidelines for the incorporation of these into clinical research. To maximize the benefits of patient-reported outcomes data while protecting patient welfare, a panel of experts set out ethical guidelines for the incorporation of these into clinical research.

# data[].attributes.body
https://www.bbc.com/news/health-61392698

# data[].attributes.attachment_link.readable_text
A government consultation on how to tackle the nation's vitamin D deficiency problem ends on Sunday.

One idea being floated is getting people to eat biofortified foods, such as mushrooms that have been exposed to UV light.

It is a process that makes the food extra-rich in the nutrient.

More than one in 10 adults in the UK is thought to be lacking in the sunshine vitamin, which is needed to keep muscles and bones healthy.

Too much vitamin D can be bad too though - a build-up of of it can cause too much calcium in the body.

That is why there is a debate about what is the best way to improve the nation's intake, since some people already get plenty.

The England-only consultation, led by the Office for Health Improvement and Disparities and the Department of Health and Social Care has asked for individuals or businesses to contribute with suggestions.

The next step will involve a national campaign to improve the vitamin status of the population.

There could also be legislation passed to allow food producers to put more vitamin D in foods that don't naturally contain it, in a process known as fortification, as well as growing produce and breeding meat to be more vitamin D-rich through biofortification.

Margarines used to have to be fortified by law, but the government dropped that requirement in 2013 to reduce the amount of regulations dairy farmers had to follow.

Some people are concerned that if many foods were fortified with various vitamins and nutrients, we might end up consuming too many. However, Dr Stacey Lockyer, from the British Nutrition Foundation, says this is unlikely.

"The safe upper limit for a nutrient, set by health authorities to help ensure that total intakes do not pose risks for public health, would always be carefully considered before the implementation of a food fortification policy," the nutrition scientist tells the BBC.

"Studies conducted across Europe - under the Odin Project - have looked at the inclusion of vitamin D-fortified foods, either singularly, but also in combination, and have concluded that diverse fortification strategies carry little risk of exceeding the safe upper limit for vitamin D and thus could safely increase population intakes."

A national deficiency

People can get some vitamin D from their diet, but also make it in their skin when it is exposed to the sun.

There is no exact figure for how much time should be spent in the sun, but the charity Cancer Research says people should always be careful about skin cancer risk.

For a while now, the government has recommended everyone should consider taking daily vitamin D supplements during the autumn and winter to top up their levels.

Some people are more likely to be deficient - people who don't get outdoors much or who cover their skin, as well as people with naturally darker skin.

During the pandemic, more than 900,000 vitamin D supplements were given to people who were clinically extremely vulnerable and those in care homes to help avoid more deficiencies.

These free supplements were discontinued in February 2021, which clinicians from the Royal Osteoporosis Society (ROS) say is concerning, because it could lead to more people developing osteoporosis.

"Elderly people in particular face a perfect storm if vitamin D supplements are not made readily available, as do vulnerable individuals who cannot get out for UV exposure over a UK summer," they tell the BBC.

Now only eligible pregnant women, new mothers and children under four can get free supplements, which contain folic acid, vitamin C and D as part of the Healthy Start scheme.

"Targeting these groups is helpful but doesn't address the magnitude of the problem that exists from cradle to grave," they add.

Supplements can be purchased from most supermarkets and pharmacies, with a three-month supply costing under £3.

You should be able to get the right amount of vitamin D just by going out in the sun between March and September in the UK.

But during the winter months, the sun will not be enough.

Foods that naturally contain vitamin D include oily fish like salmon, sardines, herring and mackerel, red meat and egg yolks.

Some products, like breakfast cereals, are fortified with vitamin D, meaning it has been added to them. Researchers are also exploring biofortification - for example, rearing animals to produce vitamin-D rich beef, pork, chicken and eggs.

There are two important forms of vitamin D - D2 (ergocalciferol) and D3 (cholecalciferol). D2 generally comes from plants, such as mushrooms, while D3 comes from animal sources, such as eggs and fish, as well as our skin when it is exposed to the sun. Both D2 and D3 can be found in supplements.

Most Vitamin D supplements contain vitamin D3, which is typically produced from a wax called lanolin, extracted from sheep's wool, and so may not be suitable for vegans or those who do not consume dairy.

Dr Lockyer says you can still get the vitamins you need when you're vegan or vegetarian.

"Eggs are a useful source of vitamin D for vegetarians who eat them," she tells the BBC.

"Other food sources of vitamin D that are suitable for vegetarians and vegans are foods fortified with vitamin D such as some plant oil-based polyunsaturated fat spreads, some plant-based dairy alternatives - choose unsweetened versions - and some breakfast cereals - where fortified with a form of vitamin D suitable for vegans."

Dr Lockyer also says vitamin-D enriched mushrooms can be purchased instead of regular ones to help increase intake.

What's needed?

Research from March this year by YouGov found that nearly a third of adults (29%) in the UK can't identify a dietary source of vitamin D, while more than half of UK adults (54%) don't take any vitamin D supplements at all during the year.

The research, which was conducted on behalf of the ROS, also found that despite the pandemic providing more opportunity for many people to spend more time outdoors, adults were actually going outside less.

A total of 30% of UK adults said they were spending less than an hour outside on an average day, while 64% said they were spending two hours or less outside.

ROS chief executive Craig Jones says he is pleased the government is running the consultation, and wants free supplements to be top of the agenda.

"There are still people facing barriers to good bone health, and we're concerned that the rising cost of living might prevent even more people from following the advice to supplement," he says.

"Access to information and supplements should be available to everyone who needs it, and they shouldn't have to choose between their finances and their bone health."

Dr Lockyer has also expressed the British Nutrition Foundation's issues with vitamin D consumption in the UK, and says "multiple strategies" are needed to improve it throughout the population.

"Not getting enough vitamin D can lead to an increased risk of bone deformities such as rickets in children, and bone pain caused by a condition called osteomalacia in adults," she says.

The BBC is not responsible for the content of external sites.

# data[].attributes.attachment_link.title
Vitamin D: Could UV-mushrooms help fix the nation's issue?

# data[].attributes.attachment_link.description
A government consultation on how to tackle the nation's vitamin D deficiency problem ends on Sunday. One idea being floated is getting people to eat biofortified foods, such as mushrooms that have been exposed to UV light. It is a process that makes the food extra-rich in the nutrient.

# data[].attributes.attachment_link.title
Elaine Fong: My mother's final wish -- and the right to die with dignity

# data[].attributes.attachment_link.description
After a terminal cancer diagnosis upended 12 years of remission, all Elaine Fong's mother wanted was a peaceful end of life. What she received instead became a fight for the right to decide when.

# data[].attributes.attachment_link.description
The UK’s largest database of information and research on all aspects of social care and social work.

# data[].attributes.body
British Journal of Nursing.

British Journal of Sociology.

Health and Social Care in the Community.

Journal of Integrated Care.

Journal of Social Policy.

Journal of Social Welfare & Family Law.

# data[].attributes.attachment_link.readable_text
Transforming patients' lives, at the cutting edge of medicine. Meet the world-leading surgeons pushing science - and the human body - to its limits.

Addenbrooke's and Royal Papworth hospitals in Cambridge are renowned for the expertise of their surgical staff. At both centres, surgeons undertake some of the most complex operations in the world, where technical skill is paramount because even the smallest slip of the scalpel would result in catastrophe.

# data[].attributes.attachment_link.description
Surgeons in Cambridge undertake some of the most complex operations in the world.

# data[].attributes.attachment_link.title
Living With Celiac Disease: A Day In The Life | imaware™

# data[].attributes.attachment_link.description
Learn about living with Celiac Disease from a day in the life account of a sufferer of the disease and find out what to expect.

# data[].attributes.attachment_link.description
Whatever your lifestyle, knowing how to stay well with your asthma is critical to reduce your risk of an asthma attack.

# data[].attributes.attachment_link.readable_text
By Anthony Reuben
BBC Reality Check

The Treasury has announced that the Budget and Spending Review will end the freeze on public sector pay that was announced this time last year.

Public-sector employees are generally those paid directly by the state such as teachers and members of the armed forces. All others work in the private sector.

How much their pay will go up from April will depend on the recommendations of the Pay Review Bodies.

The Treasury said that freezing pay in 2020-21 had helped "to ensure fairness between the private and public sector".

There is no question that there is a gap between pay in the public and private sectors, but whether that is fair is a tricky question.

As the Institute for Fiscal Studies (IFS) says, public-sector workers are more likely to be highly educated professionals who command higher wages in the labour market.

So the problem with comparing average earnings for the public and private sector is highly educated professionals would be expected to be earning more.

And this has increasingly been the case as successive governments have paid private-sector companies to carry out lower-paid jobs such as cleaning, security or catering.

The IFS also calculates the percentage gap between public and private sector pay if you take into account characteristics such as a worker's education and experience, which is the red line in the chart below.

Public-sector pay was frozen from 2011-13 and then capped at a 1% annual increase until 2018.

As a result, the difference between public and private-sector pay has narrowed since 2011, such that in 2019-20, there was no gap once you took into account their characteristics.

In 2020-21, the gap increased somewhat, indicating that the public sector had a somewhat better year than the private sector.

And we knew that - employees in the public sector worked very hard during the pandemic but they weren't furloughed and were less likely to lose their jobs than those in the private sector.

How much difference?

The Treasury release said that average earnings in 2020-21 had risen:

4.5% in the public sector

1.8% in the private sector

That's not the figure that the Office for National Statistics (ONS), which calculates the figures, uses.

According to the ONS, average earnings in 2020-21 rose:

5.6% in the public sector

4.6% in the private sector

The reason for the difference is that the Treasury has taken an average of all the monthly figures in 2020-21 and compared them with the same figure for 2019-20, whereas the ONS has compared average pay at the end of 2019-20 with average pay at the end of 2020-21.

So the Treasury figure is taking more account of the dip seen by the private sector during 2020, when employees were furloughed, which meant some of them were receiving only 80% of their normal pay.

You can see that dip very clearly in the blue line in the first chart in this piece.

The Treasury's way of calculating it makes the change in private sector wages look considerably worse than the ONS's headline figures.

There are other caveats about earnings figures at the moment, with the very large changes in things like bonus payments during the pandemic making the figures difficult to analyse.

Nonetheless, it is still fair to say that public sector workers had a better time overall on wages over the pandemic than their private sector counterparts.

Longer view

But if you take a longer term view, many workers in the public sector have had a difficult time.

The IFS says, for example, that pay levels for experienced teachers in 2021 are 8% lower once you adjust for rising prices than they were in 2007.

Average pay for NHS dentists fell by 32% between 2006−07 and 2017−18, and is estimated to have continued to fall since.

What about pensions?

Of course, the attractiveness of a job is not just about the amount you are paid.

This analysis excludes pension provision, which tends to be considerably better in the public sector.

On the other hand, bonuses and overtime payments are much more significant in the private sector.

And one thing that the pandemic has highlighted is the greater job security in the public sector, especially because those in the public sector were more likely to be classified as key workers.

# data[].attributes.attachment_link.title
Is there a gap between public and private sector pay?

# data[].attributes.attachment_link.description
By Anthony Reuben BBC Reality Check The Treasury has announced that the Budget and Spending Review will end the freeze on public sector pay that was announced this time last year. Public-sector employees are generally those paid directly by the state such as teachers and members of the armed forces.

# data[].attributes.attachment_link.readable_text
A California couple gave birth to a stranger's child after being given the wrong embryo by a fertility clinic during in vitro fertilisation (IVF), says a lawsuit.

Daphna and Alexander Cardinale say they gave birth in September 2019 to a girl that looked nothing like them.

After a DNA test, they found the couple that carried their daughter to term, and together decided to swap the girls.

This is not the first alleged mix-up during an IVF procedure.

IVF is a procedure during which a woman's eggs are fertilised by man's sperm in a laboratory before the embryos are implanted into a woman's uterus.

The Cardinales are suing the Los Angeles-based fertility centre, the California Center for Reproductive Health (CCRH), as well as In VitroTech Labs, an embryology lab.

The lawsuit alleges medical malpractice, negligence and fraudulent concealment. Neither company responded to a BBC News request for comment.

In an emotional news conference on Monday, Mrs Cardinale said her family's "heartbreak and confusion can't be understated".

"Our memories of childbirth will always be tainted by the sick reality that our biological child was given to someone else, and the baby that I fought to bring into this world was not mine to keep."

Mrs Cardinale said she was "robbed of the ability to carry my own child".

According to the lawsuit, the couple sought help from the fertility clinic in the summer of 2018.

Mrs Cardinale gave birth the next year to a child they thought was theirs.

In the delivery room, Mr Cardinale had expected "a fair child", like their firstborn, but he was surprised to see the baby girl "came out with much darker skin", says the lawsuit.

"It was so jarring that Alexander actually took several steps away from the birthing table, backing up against the wall," reads the legal action.

Nearly two months later the family decided to take at-home DNA tests, which ultimately determined they were not biologically related to the infant.

"The room shrank and got really dizzy and everything just went numb," Mr Cardinale said, recalling the moment the DNA results came back.

The CCRH then helped them find the California couple who had carried their daughter and had given birth to another healthy girl a week apart. The Cardinales' daughter was around four months old when they first met. After several meetings, the couples agreed to go through the legal process of formally exchanging the babies, which happened in January 2020.

"Instead of breastfeeding my own child, I breastfed and bonded with a child I was later forced to give away," Mrs Cardinale said at the news conference.

She added that the incident has been hardest for the couple's seven-year-old daughter, who has struggled to understand the swap.

"The horror of this situation cannot be understated," says the lawsuit.

Mrs Cardinale, a licensed therapist, and her husband, a singer-songwriter, have since both sought mental-health treatment for "symptoms of anxiety, depression, and PTSD", says the legal action.

Adam B Wolf, a lawyer representing the Cardinales, said the other family in the mix-up also plans to sue, but will remain anonymous.

In 2019, another California family discovered that their child had been born in New York.

They sued the birthmother, who reportedly wanted to keep the child. The judge later ruled in favour of the genetic parents.

More on this story

# data[].attributes.attachment_link.title
California couple sue clinic for alleged IVF swap 'horror'

# data[].attributes.attachment_link.description
A California couple gave birth to a stranger's child after being given the wrong embryo by a fertility clinic during in vitro fertilisation (IVF), says a lawsuit. Daphna and Alexander Cardinale say they gave birth in September 2019 to a girl that looked nothing like them.

# data[].attributes.attachment_link.description
NICE helps practitioners and commissioners get the best care to patients, fast, while ensuring value for the taxpayer.

# data[].attributes.attachment_link.description
AAA screening, see Abdominal aortic aneurysm screening

# data[].attributes.attachment_link.readable_text
Life expectancy is the key metric for assessing population health. Broader than the narrow metric of the infant and child mortality, which focus solely at mortality at a young age, life expectancy captures the mortality along the entire life course. It tells us the average age of death in a population.

Estimates suggest that in a pre-modern, poor world, life expectancy was around 30 years in all regions of the world.

Life expectancy has increased rapidly since the Age of Enlightenment. In the early 19th century, life expectancy started to increase in the early industrialized countries while it stayed low in the rest of the world. This led to a very high inequality in how health was distributed across the world. Good health in the rich countries and persistently bad health in those countries that remained poor. Over the last decades this global inequality decreased. No country in the world has a lower life expectancy than the countries with the highest life expectancy in 1800. Many countries that not long ago were suffering from bad health are catching up rapidly.

Since 1900 the global average life expectancy has more than doubled and is now above 70 years. The inequality of life expectancy is still very large across and within countries. in 2019 the country with the lowest life expectancy is the Central African Republic with 53 years, in Japan life expectancy is 30 years longer.
Related research:
Why do women live longer than men? by Esteban Ortiz-Ospina

Interactive charts on Life Expectancy

Differences in life expectancy across the world

The world map shows the latest data published by the United Nations for life expectancy.

Life expectancy is a measure of premature death and it shows large differences in health across the world.

The population of many of the richest countries in the world have life expectancies of over 80 years. In 2019 the life expectancy in Spain, Switzerland, Italy, and Australia was over 83 years. In Japan it was the highest with close to 85 years.

In the countries with the worst health life expectancy is between 50 and 60 years. The population of the Central African Republic has the lowest life expectancy in 2019 with 53 years.

Use the slider below the map to see the change over time or click on any country to see the changing of life expectancy around the world.

OECD Data: Life Expectancy at birth

UN WPP Data: Life expectancy

How did life expectancy change over time?

Twice as long - life expectancy around the world

The three maps show the global history of life expectancy over the last two centuries.¹

Demographic research suggests that at the beginning of the 19 th century no country in the world had a life expectancy longer than 40 years.² Every country is shown in red. Almost everyone in the world lived in extreme poverty, we had very little medical knowledge, and in all countries our ancestors had to prepare for an early death.

Over the next 150 years some parts of the world achieved substantial health improvements. A global divide opened. In 1950 the life expectancy for newborns was already over 60 years in Europe, North America, Oceania, Japan and parts of South America. But elsewhere a newborn could only expect to live around 30 years. The global inequality in health was enormous in 1950: People in Norway had a life expectancy of 72 years, whilst in Mali this was 26 years. Africa as a whole had an average life expectancy of only 36 years, while people in other world regions could expect to live more than twice as long.

The decline of child mortality was important for the increase of life expectancy, but as we explain in our entry on life expectancy increasing life expectancy was certainly not only about falling child mortality - life expectancy increased at all ages.

Such improvements in life expectancy - despite being exclusive to particular countries - was a landmark sign of progress. It was the first time in human history that we achieved sustained improvements in health for entire populations.³ After millennia of stagnation in terrible health conditions the seal was finally broken.

Now, let's look at the change since 1950. Many of us have not updated our world view. We still tend to think of the world as divided as it was in 1950. But in health - and many other aspects - the world has made rapid progress. Today most people in the world can expect to live as long as those in the very richest countries in 1950. The United Nations estimate a global average life expectancy of 72.6 years for 2019 - the global average today is higher than in any country back in 1950. According to the UN estimates the country with the best health in 1950 was Norway with a life expectancy of 72.3 years.

The three maps summarize the global history of life expectancy over the last two centuries: Back in 1800 a newborn baby could only expect a short life, no matter where in the world it was born. In 1950 newborns had the chance of a longer life if they were lucky enough to be born in the right place. In recent decades all regions of the world made very substantial progress, and it were those regions that were worst-off in 1950 that achieved the biggest progress since then. The divided world of 1950 has been narrowing.

Globally the life expectancy increased from less than 30 years to over 72 years; after two centuries of progress we can expect to live much more than twice as long as our ancestors. And this progress was not achieved in a few places. In every world region people today can expect to live more than twice as long.

The global inequalities in health that we see today also show that we can do much better. The almost unbelievable progress the entire world has achieved over the last two centuries should be encouragement enough for us to realize what is possible.

Life expectancy in 1800, 1950, and 2015⁴

Life expectancy has improved globally

This visualization shows the dramatic increase in life expectancy over the last few centuries as a line chart. For the UK - the country for which we have the longest time-series - we see that before the 19th century there was no trend for life expectancy: life expectancy fluctuated between 30 and 40 years.

Over the last 200 years people in all countries in the world achieved impressive progress in health that lead to increases in life expectancy. In the UK, life expectancy doubled and is now higher than 80 years. In Japan health started to improve later, but the country caught up quickly with the UK and surpassed it in the late 1960s. In South Korea health started to improve later still and the country achieved even faster progress than the UK and Japan; by now life expectancy in South Korea has surpassed life expectancy in the UK.

The chart also shows how low life expectancy was in some countries in the past: A century ago life expectancy in India and South Korea was as low as 23 years. A century later, life expectancy in India has almost tripled and in South Korea it has almost quadrupled.

You can switch to the map view to compare life expectancy across countries. This view shows that there are still huge differences between countries: people in many Sub-Saharan countries have a life expectancy of less than 60 years, while in Japan it exceeds 80.

Rising life expectancy around the world

In the pre-modern, poor world life expectancy was around 30 years in all regions of the world. The estimates by historian James Riley shown here suggest that there was some variation, between different world regions, but in all world regions life expectancy was well below 40 years.⁵

The historical estimates are associated with a considerable uncertainty - it is worth reading the work by Riley to understand the limitations and strengths of the estimates.⁶ But of course these uncertainties are much smaller than the very large increase in life expectancy since then.

Infectious diseases raged in all parts of the world and as we show in our entry on child mortality almost half of all children died before they reached adulthood. And those that survived often died soon after. Without public health measures and without effective medicines diseases were killing most people at a very young age.

This was the reality for humanity until very recently. Life expectancy in each region of the world stayed fairly stable for most of history until humanity started to make progress against poor health just a few generations ago. Epidemiologists refer to this period in which life expectancy began to increase substantially as the "health transition".

This chart shows that the health transition began at different times in different world regions; Oceania began to see increases in life expectancy around 1870, while Africa didn't begin to see increases until around 1920.

Since then life expectancy doubled in all world regions.

In Oceania life expectancy increased from 35 years before the health transition to 79 years in 2019.

In Europe from 34 to 79 years.

In the Americas from 35 to 77 years.

In Asia from 27.5 to 73.6.

And in Africa from 26 years to 63 years.

Globally the life expectancy increased from an average of 29 to 73 years in 2019.

Life expectancy increased in all countries of the world

There is a lot of information in the following - rather unusual - chart. On the x-axis you find the cumulative share of the world population. And all the countries of the world are ordered along the x-axis ascending by the life expectancy of the population. On the y-axis you see the life expectancy of each country.

For 1800 (red line) you see that the countries on the left - India and also South Korea - have a life expectancy around 25. On the very right you see that in 1800 no country had a life expectancy above 40 (Belgium had the highest life expectancy with just 40 years).

In 1950 the life expectancy of all countries was higher than in 1800 and the richer countries in Europe and North America had life expectancies over 60 years - over the course of modernization and industrialization the health of the population improved dramatically. But half of the world's population - look at India and China - made only little progress. Therefore the world in 1950 was highly unequal in living standards - clearly devided between developed countries and developing countries.
This division is ending: Look at the change between 1950 and 2012! Now it is the former developing countries - the countries that were worst off in 1950 - that achieved the fastest progress. While some countries (mostly in Africa) are lacking behind. But many of the former developing countries have caught up and we achieved a dramatic reduction of global health inequality.

The world developed from equally poor health in 1800 to great inequality in 1950 and back to more equality today - but equality on a much higher level.
How to read the following graph: On the x-axis you find the cumulative share of the world population. The countries are ordered along the x-axis ascending by the life expectancy of the population.

Life expectancy of the world population, 1800, 1950 and 2012⁷

Mortality and life expectancy by age

It is not only about child mortality - life expectancy by age

It's often argued that life expectancy across the world has only increased because child mortality has fallen. If this were true, this would mean that we've become much better at preventing young children from dying, but have achieved nothing to improve the survival of older children, adolescents and adults. Once past childhood, people would be expected to enjoy the same length of life as they did centuries ago.

This, as we will see in the data below, is untrue. Life expectancy has increased at all ages. The average person can expect to live a longer life than in the past, irrespective of what age they are.

The visualization shows the life expectancy in England and Wales over the last three centuries.

The red line shows the life expectancy for a newborn. Until the mid-19th century a newborn could expect to live around 40 years. At times, even less.

The rainbow-colored lines show how long a person could expect to live once they had reached that given, older, age. The light green line, for example, represents the life expectancy for children who had reached age 10.

The most striking development we see is the dramatic increase in life expectancy since the mid-19th century. Life expectancy at birth doubled from around 40 years to more than 81 years.⁸ This achievement was not limited to England and Wales; since the late 19th century life expectancy doubled across all regions of the world.

While England and Wales are not the only region that achieved this improvement, the last 150 years are the only time that humanity achieved anything like this. The evidence that we have for population health before modern times suggest that around a quarter of all infants died in the first year of life and almost half died before they reached the end of puberty (see here) and there was no trend for life expectancy before the modern improvement in health: In the centuries preceding this chart, life expectancy fluctuated between 30 and 40 years with no marked increase ever.
Life expectancy increased at all ages

A common criticism of the statement that life expectancy doubled is that this "only happened because child mortality declined". I think that, even if this were true, it would be one of humanity's greatest achievements, but in fact, this assertion is also just plain wrong. Mortality rates declined, and consequently life expectancy increased, for all age groups.

The data shown in this chart makes this clear.

Let's see how life expectancy has improved without taking the massive improvements in child mortality into account. Child mortality is defined as the share of children who die before reaching their 5th birthday. We therefore have to look at the life expectancy of a five-year-old to see how mortality changed without taking child mortality into account. This is shown by the yellow line. In 1841 a five-year-old could expect to live 55 years. Today a five-year-old can expect to live 82 years. An increase of 27 years.

The same is true for any higher age cut-off. A 50-year-old, for example, could once expect to live up to the age of 71. Today, a 50-year-old can expect to live to the age of 83. A gain of 13 years.

This is true for countries around the world. Here is the data for the life expectancy of 15-year-olds around the world.

A second striking feature of this visualization is the big decline of life expectancy in 1918. It was caused by a very large global influenza epidemic, the Spanish flu pandemic. I have studied the impact of this pandemic and especially it's differential impact for different age-groups - the life expectancy of older people barely changed as the chart shows - in a text on the this pandemic here.

Yes, the decline of child mortality matters a lot for life expectancy. But as we've seen, the gains go much further than this. As we have seen here it was not only children that benefited from this progress, but people at all ages.

'Population survival curves' show the share of people who are expected to survive up to a certain age. The chart here plots the survival curves for individuals in England and Wales from 1851 up to 2011.

As we can see, less than half of the people born in the mid-19th century made it past their 50th birthday. In contrast, 97% of the people born in England and Wales today can expect to live longer than 50 years.

Life expectancy estimates only describe averages, these curves therefore provide an important complementary view and help us understand how the inequality of life lengths has changed over time. In the 19th century the inequality was very large, many died at a very young age and a considerable number of people died between the age of 5 and 60. Today the inequality is much lower, the huge majority survives the first 60 or 70 years of their life and the span at which most people die is much more compressed than it was 150 years ago.

Related chart: Deaths by age group in England and Wales

The following visualization shows the estimates and UN-projections of the remaining expected life years for 15-year-olds. The rise - best visible on the Map-view - shows that the increasing life expectancy is not only due to declining child mortality, but that mortality rates at higher ages also declined globally.

In this chart we see the breakdown of deaths by age bracket. Globally fewer and fewer people die at a young age.

In 2017, there were 56.5 million deaths globally; just over half of these were people who were 70 years or older; 26% were between 50 and 69 years old; 13% were between 15 and 49; only 1% were older than 5 and younger than 14; and almost 9% were children under the age of 5.

The age at which people die has changed significantly since 1990. Fewer people die at a young age. In 1990 nearly one-quarter of all deaths were in children younger than 5. In 2019, this had declined to just under 9%. In contrast, the share of deaths in the over-70s age bracket has increased from a third to half of all deaths over this period.

It is possible to change this chart to any other country or region in the world. In countries with good health the share dying at a young age is very low. In Japan more than 85% are 70 years or older.

Inequality of life expectancy

The inequality in years of life between people within the same country can be measured in the same way that we measure, for example, the inequality in the distribution of incomes. The idea is to estimate the extent to which a small share of a country's population concentrates a large 'stock of health', hence living much longer than most of the population in the same country.

The following visualization presents estimates of the inequality of lifetimes as measured by the Gini coefficient. A high Gini coefficient here means a very unequal distribution of years of life - that is, large within-country inequalities of the number of years that people live. These estimates are from Peltzman (2009)⁹, where you can find more details regarding the underlying sources and estimation methodology.

As can be seen in the chart, inequality in health outcomes has fallen strongly within many countries.

In every country the life expectancy of women is higher than the life expectancy of men as this chart shows.

Why this is the case is answered by Esteban Ortiz-Ospina in his text Why do women live longer than men?

The rise of maximum life expectancy

The following graph is an updated version of the graph in the paper ' Broken Limits to Life Expectancy' published in Science by Oeppen and Vaupel in 2002.¹⁰

It shows quite a lot of information:

The colored symbols represent the highest life expectancy of women from 1840 to today - indicating that country with the highest life expectancy at each point in time. For instance, we can see that in the mid-1800s, Norway had the highest life expectancy, but then by 1880 people in non-Maori New Zealand were expected to live the longest lives. The data shows that in the life expectancy in the leading country of the world has increased by three months every single year.

The solid horizontal line represents the results of the linear regression on all these points; remarkably, the maximum life expectancy seems to follow this linear trend very closely. The gray dashed line is the extension of this trend into the future, and the red dashed lines represent 'projections of female life expectancy in Japan published by the UN in 1986, 1999, and 2001.'

The author names listed on the right refer to multiple predictions of the maximum possible life expectancy for humans. The horizontal black lines extending from the publication denote the prediction in each publication of the asserted ceiling on life expectancy attainable by humans and the year in which the study was published. Dublin published a study in 1928 that asserted that the maximum life expectancy possible was less than 65 while at the same time life expectancy in New Zealand was already over 65. The predictions of maximum life expectancy were proven wrong again and again over the course of the last century. On average the predictions have been broken within 5 years after publication.

Record female life expectancy including time trend and asserted ceilings on life expectancy, 1840 to the present¹¹

How has healthy life expectancy changed?

As prior visualizations in this entry have shown, life expectancy has been rising globally. However, this can be broken down further into 'healthy life expectancy' and 'years lived with disability'. This breakdown in shown in this chart.

It is true that there has been an increase for most countries in both aspects. Healthy life expectancy has increased across the world (in some countries, significantly in recent decades). It is also true that improved healthcare and treatments have also increased the number of years, on average, in which people live with a given disease burden or disability. This increase has, in most cases, been slower than the increase of healthy life expectancy.

The map shows the expected years lived with disability across the world. In general, we tend to see that higher-income countries tend to spend more years with disability or disease burden than at lower incomes (around 10-11 years versus 7-9 years at lower incomes).

The scatter plot shows that in countries where the life expectancy is highest the expected years lived with disability or disease tend to be the longest too.

The median age of a country's population is an indicator of demographic makeup of the country and of its the population growth. This chart shows how the world population is aging; the median age is increasing around the world. However, there are considerable differences between world regions - many parts of sub-Saharan Africa are much younger since both birth rates and mortality are higher.

What drives improvements in life expectancy?

Many aspects had to change for life expectancy to double. It is helpful therefore to read our entries on all the many causes of death, from infectious diseases like smallpox and malaria to non-communicable diseases like cancer. Not just specific medical innovations, like vaccinations or antibiotics, were necessary, but also public health interventions - improved public sanitation and publicly funded healthcare - were crucial.

Below we are looking at several aspects, but this section is not yet complete and we will work on it in the future.

One of the most important inputs to health is health care. Here we study cross-country evidence of the link between aggregate healthcare consumption and production, and health outcomes.

One common way of measuring national healthcare consumption and production is to estimate aggregate expenditure on healthcare (typically expressed as a share of national income).

This visualization shows the cross-country relationship between life expectancy at birth and healthcare expenditure per capita.

The chart shows the level of both measures at two points in time, about a generation apart (1995 and 2014 respectively). The arrows connect these two observations, thereby showing the change over time of both measures for all countries in the world. As it can be seen, countries with higher expenditure on healthcare per person tend to have a higher life expectancy. And looking at the change over time, we see that as countries spend more on health, life expectancy of the population increases.

Notice that the relationship in this chart seems to follow a pattern of 'diminishing returns': the increase in life expectancy associated with an increase in healthcare expenditure decreases as expenditure increases. This means the proportional highest gains are achieved in poor countries with low baseline levels of spending. This pattern is similar to that observed between life expectancy and per capita income.

The countries are color-coded by world region, as per the inserted legends. Many of the green countries (Sub-Saharan Africa) achieved remarkable progress over the last 2 decades: health spending often increased substantially and life expectancy in many African countries increased by more than 10 years. The most extreme case is Rwanda, where life expectancy has increased from 32 to 64 years since 1995 - which was one year after the Rwandan genocide. The graph also shows that the African countries that suffered the most under the HIV/AIDS epidemic - Lesotho, Eswatini, and South Africa - experienced a decline of life expectancy from which they have not yet recovered.

The two most populous countries of the world - India and China - are emphasized by larger arrows. It is interesting to see that in 1995 China achieved already relatively good health outcomes at comparatively low levels of health spending.

The association between health spending and increasing life expectancy also holds for rich countries in Europe, Asia, and North America in the upper right corner of the chart. The US is an outlier that achieves only a comparatively short life expectancy considering the fact that the country has by far the highest health expenditure of any country in the world.

Earlier in this entry we explored the breakdown of total life expectancy between 'healthy life expectancy' and 'years lived with disability or disease burden'. In this chart we see the relationship between years lived with disability or disease burden versus average per capita health expenditure. Here we see a positive correlation whereby countries with higher healthcare expenditure tend to live more years with disability or disease burden. This is likely to result from increased healthcare resourcing in general care and treatment (allowing for an extension of life with a given illness or disability).

Better science and better health

David Cutler, Angus Deaton, and Adriana Lleras-Muney¹² write: "Knowledge, science and technology are the keys to any coherent explanation. Mortality in England began to decline in the wake of the Enlightenment, directly through the application to health of new ideas about personal health and public administration, and indirectly through increased productivity that permitted (albeit with some terrible reversals) better levels of living, better nutrition, better housing and better sanitation. Ideas about the germ theory of disease were critical to changing both public health infrastructure and personal behavior. Similarly, knowledge about the health effects of smoking in the middle of the twentieth century has had profound effects on behavior and on health. Most recently, the major life-saving scientific innovations in medical procedures and new pharmaceuticals have had a major effect, particularly on reduced mortality from cardiovascular disease. There have also been important health innovations whose effect has been mainly in poor countries: for example, the development of freeze-dried serums that can be transported without refrigeration, and of oral rehydration therapy for preventing the death of children from diarrhea."

Life expectancy and GDP

This graph displays the correlation between life expectancy and gross domestic product (GDP) per capita. It shows that In general, countries with higher GDP tend to have a higher life expectancy. It is a logarithmic relationship: the difference in life expectancy per difference in GDP per capita is higher for poorer than for richer countries.

The cross-sectional relationship between life expectancy and per capita income is known as the Preston Curve, named after Samuel H. Preston who first described it in a famous paper from 1975.¹³

In the chart we are plotting the cross-sectional relationship for the years 1800, 1950, 1980, and 2012. Interestingly we then find that the life expectancy associated with a given level of real income is rising over time. If economic development was the only determinant of health countries then we would see a steady relationship between the two metrics and the curve would not shift over time. Since this is not the case we can conclude that economic development cannot be the sole determinant of health. A possible explanation for this changing relationship is that scientific understanding and technological progress makes some very efficient public health interventions - such as vaccinations, hygiene measures, oral rehydration therapy, and public health measures - cheaper and brings these more and more into the reach of populations with lower and lower incomes.

The Preston curves below show the correlation between prosperity and life expectancy across countries. How did life expectancy change over time when countries got richer?

The historical research focuses on England as it is the country that first achieved economic growth and also the country for which we have the best long-run data.

The historical data for life expectancy in England shows clearly that life expectancy did not increase for much of the early period of British industrialization. According to the famous research by historian and Nobel laureate Robert Fogel living conditions for most people declined during the early period of industrialization. The debate about how living conditions changed then is still very much alive today,¹⁴ but what is clear however from this research is that rising prosperity itself is not sufficient to improvements in health. This is why our publication is so very broad and why we explain in our mission that "measuring economic growth is not enough" to understand whether we are making progress against the problems we are concerned with.
Related charts:

Life expectancy vs. GDP per capita since 1800¹⁵

"Life expectancy" - what does this actually mean?

Life expectancy has doubled in all world regions. What does this mean exactly?

Despite its importance and prominence in research and policy, it is surprisingly difficult to find a simple yet detailed description of what "life expectancy" actually means. In this section, we try to fill this gap.

The term "life expectancy" refers to the number of years a person can expect to live. By definition, life expectancy is based on an estimate of the average age that members of a particular population group will be when they die.

In practice, however, things are often more complicated:

One important distinction and clarification is the difference between cohort and period life expectancy.

The cohort life expectancy is the average life length of a particular cohort - a group of individuals born in a given year. When we can track a group of people born in a particular year, many decades ago, and observe the exact date in which each one of them died then we can calculate this cohort's life expectancy by simply calculating the average of the ages of all members when they died.

You can think of life expectancy in particular year as the age a person born in that year would expect to live if the average age of death did not change over their lifetime.

It is of course not possible to know this metric before all members of the cohort have died. Because of that statisticians commonly track members of a particular cohort and predict the average age-at-death for them using a combination of observed mortality rates for past years and projections about mortality rates for future years.

An alternative approach consists in estimating the average length of life for a hypothetical cohort assumed to be exposed, from birth through death, to the mortality rates observed at one particular period - commonly a year. This approach leads to what is known as ' period life expectancy ' and it is the much more commonly used life expectancy metric. It is the definition used by most international organizations, including the UN and the World Bank, when reporting 'life expectancy' figures. Period life expectancy estimates do not take into account how mortality rates are changing over time and instead only reflects the mortality pattern at one point in time. Because of this, period life expectancy figures are usually different to cohort life expectancy figures.

Since period life expectancy estimates are ubiquitous in research and public debate, it is helpful to use an example to flesh out the concept. Let's consider the map showing life expectancy-specifically period life expectancy-at birth in 2005. You can hover the mouse over a country to display the corresponding estimate.

For Japan, we can see that life expectancy in 2005 was 82.3 years. This means that a hypothetical cohort of infants living through the age-specific mortality of Japan in 2005 could expect to live 82.3 years, under the assumption that mortality patterns observed in 2005 remain constant throughout their lifetime. But if life expectancies are increasing the reality for a cohort born then is that the cohort life expectancy is higher than that period life expectancy. We see this in the data: if you move the slider below the map forward, you'll see that in 2019 the period life expectancy in Japan was 84.6 years, which means that mortality patterns in Japan did improve in the period 2005-2019.

In general, the commonly-used period life expectancies tend to be lower than the cohort life expectancies, because mortality rates were falling over the course of modern development. Whenever mortality rates are falling then the period life expectancy is lower than the life expectancy of the cohort born then

An important point to bear in mind when interpreting life expectancy estimates is that very few people will die at precisely the age indicated by life expectancy, even if mortality patterns stay constant.

For example, very few of the infants born in South Africa in 2009 will die at 52.2 years of age, as per the figures in the map above. Most will die much earlier or much later, since the risk of death is not uniform across the lifetime. Life expectancy is the average.

In societies with high infant mortality rates many people die in the first few years of life; but once they survive childhood, people often live much longer. Indeed, this is a common source of confusion in the interpretation of life expectancy figures: It is perfectly possible that a given population has a low life expectancy at birth, and yet has a large proportion of old people.

Given that life expectancy at birth is highly sensitive to the rate of death in the first few years of life, it is common to report life expectancy figures at different ages, both under the period and cohort approaches. For example, the UN estimates that the (period) global life expectancy at age 15 in 2005 was 73.6 years. This means that the group of 15-year-old children alive around the world in 2005 could expect to live another 63.6 years (i.e. until the age of 73.6), provided that mortality patterns observed in 2005 remained constant throughout their lifetime.

Finally, another point to bear in mind is that period and cohort life expectancy estimates are statistical measures, and they do not take into account any person-specific factors such as lifestyle choices. Clearly, the length of life for an average person is not very informative about the predicted length of life for a person living a particularly unhealthy lifestyle.

How is life expectancy calculated?

In practical terms, estimating life expectancy entails predicting the probability of surviving successive years of life, based on observed age-specific mortality rates. How is this actually done?

Age-specific mortality rates are usually estimated by counting (or projecting) the number of age-specific deaths in a time interval (e.g. the number of people aged 10-15 who died in the year 2005), and dividing by the total observed (or projected) population alive at a given point within that interval (e.g. the number of people aged 10-15 alive on 1 July 2015).

To ensure that the resulting estimates of the probabilities of death within each age interval are smooth across the lifetime, it is common to use mathematical formulas, to model how the force of mortality changes within and across age intervals. Specifically, it is often assumed that the proportion of people dying in an age interval starting in year and ending in year corresponds to , where is the age-specific mortality rate as measured in the middle of that interval (a term often referred to as the 'central death rate' for the age interval).¹⁶

Once we have estimates of the fraction of people dying across age intervals, it is simple to calculate a 'life table' showing the evolving probabilities of survival and the corresponding life expectancies by age. Here is an example of a life table from the US, and this tutorial from MEASURE Evaluation explains how life tables are constructed, step by step (see Section 3.2 'The Fergany Method').

Period life expectancy figures can be obtained from 'period life tables' (i.e. life tables that rely on age-specific mortality rates observed from deaths among individuals of different age groups at a fixed point in time). And similarly, cohort life expectancy figures can be obtained from 'cohort life tables' (i.e. life tables that rely on age-specific mortality rates observed from tracking and forecasting the death and survival of a group of people as they become older).

For some countries and for some time intervals, it is only possible to reconstruct life tables from either period or cohort mortality data. As a consequence, in some instances-for example in obtaining historical estimates of life expectancy across world regions -it is necessary to combine period and cohort data. In these cases, the resulting life expectancy estimates cannot be simply classified into the 'period' or 'cohort' categories.

What else can we learn from 'life tables'?

Life tables are not just instrumental to the production of life expectancy figures (as noted above), they also provide many other perspectives on the mortality of a population. For example, they allow for the production of 'population survival curves', which show the share of people who are expected to survive various successive ages. This chart provides an example, plotting survival curves for individuals born at different points in time, using cohort life tables from England and Wales.

At any age level in the horizontal axis, the curves in this visualization mark the estimated proportion of individuals who are expected to survive that age. As we can see, less than half of the people born in 1851 in England and Wales made it past their 50th birthday. In contrast, more than 95% of the people born in England and Wales today can expect to live longer than 50 years.

Since life expectancy estimates only describe averages, these indicators are complementary, and help us understand how health is distributed across time and space. In our entry on Life Expectancy you can read more about related complementary indicators, such as the median age of a population.

Long-run data on life expectancy at birth for the time period since 1800 is available from the Clio Infra project.

Long-term data is available at Lifetable.de. Lifetable.de - a project by researchers at the Max Planck Institute in Rostock, the University of Berkeley and the Institut national d'études démographiques in Paris - presents life expectancy estimates drawn from some 700 sources. The estimates along with the sources are presented at lifetable.de.

Gapminder presents estimates for life expectancy since 1800. Here is the corresponding documentation.

# data[].attributes.attachment_link.description
When and why did the average age at which people die increase and how can we make further progress against early death?

# data[].attributes.attachment_link.description
Our reports tell you what we think about the quality of care.

# data[].attributes.attachment_link.title
Nike has made hands-free shoe for people with disabilities

# data[].attributes.attachment_link.description
Big brands are finding ways to make their clothing and footwear more accessible to the 15% of the world population living with a disability.

# data[].attributes.attachment_link.readable_text
Select Your Cookie Preferences

We use cookies and similar tools that are necessary to enable you to make purchases, to enhance your shopping experiences and to provide our services, as detailed in our Cookie Notice. We also use these cookies to understand how customers use our services (for example, by measuring site visits) so we can make improvements.

If you agree, we'll also use cookies to complement your shopping experience across the Amazon stores as described in our Cookie Notice. This includes using first- and third-party cookies, which store or access standard device information such as a unique identifier. Third parties use cookies for their purposes of displaying and measuring personalised ads, generating audience insights, and developing and improving products. Click 'Customise Cookies' to decline these cookies, make more detailed choices, or learn more. You can change your choices at any time by visiting Cookie Preferences, as described in the Cookie Notice. To learn more about how and for what purposes Amazon uses personal information (such as Amazon Store order history), please visit our Privacy Notice.

# data[].attributes.attachment_link.description
Buy My Sister's Keeper by Picoult, Jodi from Amazon's Fiction Books Store. Everyday low prices on a huge range of new releases and classic fiction.

# data[].attributes.attachment_link.readable_text
Responding to the Care Quality Commission's (CQC) annual assessment of health and social care over the past year in England, Andrea Sutcliffe, NMC Chief Executive and Registrar, said:

"Today's report highlights the extraordinary pressures on health and social care services and reflects what we hear from nursing and midwifery professionals across the UK. Their outstanding contribution to the pandemic response has been vital but they are now understandably exhausted.

"The report exposes a tired and depleted workforce facing immense difficulties, many exacerbated by the pandemic - unacceptable inequalities facing people from Black, Asian and minority ethnic backgrounds; increased challenges for people with a learning disability; slow progress in maternity services improvement; and the damaging impact of the crisis in social care on people in the most vulnerable of circumstances, their families and carers.

"Building something better - a health and care system that works for everyone - is the challenge set by the CQC and is a challenge we all need to meet with determination and focus. And we need to do it together."

# data[].attributes.attachment_link.title
Response to CQC's annual assessment of the state of health and social care in England

# data[].attributes.attachment_link.description
Responding to the Care Quality Commission's (CQC) annual assessment of health and social care over the past year in England, Andrea Sutcliffe, NMC Chief Executive and Registrar, said: "Today's report highlights the extraordinary pressures on health and social care services and reflects what we hear from nursing and midwifery professionals across the UK.

# data[].attributes.attachment_link.readable_text
Published on 02 November 2021

Find out more

Following an appeal by the Professional Standards Authority (PSA) to the High Court, the Court has ordered that nurse Melanie Hayes be struck off the NMC's register. The PSA appeal was against an original decision of the NMC's Fitness to Practise Committee, which the PSA considered was insufficient to protect the public. The Court approved a consent order agreed by all the parties.
Andrea Sutcliffe, Chief Executive and Registrar at the NMC, said:

"I'm very sorry that our original decision wasn't the right one, and I know how much concern that caused. I hope people feel reassured that by recognising this and referring our decision to the PSA, we've now reached an appropriate outcome, with the High Court deciding that Ms Hayes should be removed from our register.

"We're absolutely committed to learning from this and making sure that we have suitable guidance and training in place to enable us and our independent Fitness to Practise panels to make the right decisions in cases concerning racism or any other form of discrimination."

Notes
1. The independent fitness to practise panel's decision was to accept the provisional consensual panel determination (CPD) which had been agreed between the NMC and Ms Hayes.

a. A CPD is when the NMC agrees with the registrant that their fitness to practise is impaired, and what the appropriate sanction is. The registrant must admit the factual allegations against them. The agreement is put in writing, and a panel is asked to consider it.

2. Following this decision the NMC asked the PSA to consider exercising its power to refer the case to the High Court.

# data[].attributes.attachment_link.title
Nurse struck off following High Court decision

# data[].attributes.attachment_link.description
Published on 02 November 2021 Find out more Following an appeal by the Professional Standards Authority (PSA) to the High Court, the Court has ordered that nurse Melanie Hayes be struck off the NMC's register. The PSA appeal was against an original decision of the NMC's Fitness to Practise Committee, which the PSA considered was insufficient to protect the public.

# data[].attributes.attachment_link.description
We're the independent regulator for nurses, midwives and nursing associates. We hold a register of nurses and midwives who can practice in the UK, and nursing associates who can practice in England.

# data[].attributes.attachment_link.readable_text
The tragic case of a 23-month-old boy who died after spending more than a year in hospital attracted widespread media attention.

Alfie Evans's parents had been fighting to take the toddler to Rome for further treatment, but a court ruled his life support could be turned off several days ago.

Here is how the story unfolded.

Who was Alfie Evans?

Alfie was born to parents Tom Evans and Kate James, from Bootle in Merseyside, on 9 May 2016.

He was first admitted to Alder Hey Children's Hospital in Liverpool in December 2016 after suffering seizures and has been a patient in the hospital ever since.

Doctors diagnosed a degenerative neurological condition, which they have not been able to identify definitively.

Alfie's parents and the hospital clashed over what should happen to Alfie, who had been in a semi-vegetative state for more than a year.

His parents said they wanted to fly him to a hospital in Italy but this was blocked by Alder Hey, which said continuing treatment was "not in Alfie's best interests".

The Alder Hey Children's Hospital NHS Foundation Trust went to the High Court to seek a declaration that "continued ventilator support is not in Alfie's best interests and in the circumstances it is not lawful that such treatment continue".

Sitting at the High Court in Liverpool, Mr Justice Hayden began overseeing the case on 19 December.

But his parents disagreed and wanted permission to fly him to the Bambino Gesu Hospital in Rome in the hope of prolonging his life.

The Italian hospital, which has links to the Vatican, suggested operations to help Alfie breathe and keep him alive for an "undefined period".

The judge said he would make a decision on what was best for Alfie if an agreement was not reached.

One of the dilemmas Alfie's case raised is whether doctors are the right people to determine if withdrawing life-support treatment is in "the best interests" of a terminally ill child.

One of the key arguments presented by his parents was that they should decide what is best for their son.

The law in the UK falls somewhere in-between. The 1989 Children's Act makes it clear that where a child is at risk of harm the state can and should intervene.

This means that the rights of parents are not absolute and the state has been emboldened to challenge the view of parents where they believe a child's best interests are not being served.

If a public body disagrees with the parents' choices, they must go to court in order to override this parental responsibility.

What did the judges rule?

Mr Evans said he believed his son was still responsive, telling reporters outside court Alfie was "improving".

But Michael Mylonas QC, representing the hospital, said: "One of the problems of this case is they [Alfie's parents] look at him and, barring the paraphernalia of breathing and feeding, he's a sweet, lovely, normal-looking boy who opens his eyes, [and] will smile..."

The hospital asserted that any movements by the child were "spontaneous seizures as a result of touching".

Mr Justice Hayden ruled in favour of hospital bosses and doctors were set to withdraw ventilation on 23 February before his parents embarked on a lengthy legal battle.

How the case unfolded

Alfie's parents refused to give up hope and took the case to the Court of Appeal on 6 March where judges upheld Mr Justice Hayden's decision.

On 20 March, the couple appealed to the Supreme Court where justices refused to give the couple permission to mount another appeal.

Despite this, their lawyers went to the European Court of Human Rights (ECHR) after exhausting all legal avenues in the UK.

But three judges ruled the submission "inadmissible", saying they were unable to find any violation of human rights.

On 11 April, Mr Justice Hayden then endorsed an end-of-life care plan for Alfie, setting a date to switch off life support. This was the first time Alfie's parents were represented by the Christian Legal Centre (CLC) in court.

The CLC is a sister body to Christian Concern and describes itself as an organisation that defends "individuals and churches who have suffered discrimination and challenges because of their desire to live and work according to biblical beliefs".

CLC lawyers began a final legal bid to the parents to take control over the treatment of their son on 16 April, claiming he was being "unlawfully detained".

But this was rejected for a second time by the Court of Appeal and the Supreme Court.

Two days later Mr Evans flew to Rome for a meeting with the Pope, pleading with him to "save our son".

Despite an urgent application to the ECHR on Monday, judges refused to intervene in the case, prompting angry scenes at Alder Hey Children's Hospital.

Within hours, the Italian Ministry of Foreign Affairs granted 23-month-old Alfie Italian citizenship, hoping it would allow an "immediate transfer to Italy".

Pope Francis then tweeted his support for the family: "I renew my appeal that the suffering of his parents may be heard and that their desire to seek new forms of treatment may be granted."

But this last-ditch appeal was dismissed by Mr Justice Hayden who stated that "Alfie is a British citizen" who "falls therefore under the jurisdiction of the High Court".

The Italian Embassy has since clarified it was not trying to challenge any decisions made previously by the British courts.

A spokesman described the granting of citizenship as a "signal" to the judge that should he change his mind, they are ready to facilitate his transfer to the Italian hospital.

A further hearing then took place on Tuesday afternoon in which Mr Hayden said the case had now reached its "final chapter".

He rejected claims by Mr Evans's lawyers that his son was "significantly better" than first thought because he had been breathing unaided for 20 hours after doctors first withdrew life support.

Alfie's parents then launched a further appeal against the order stopping them from taking him to Italy, which was heard on Wednesday afternoon by a panel of three Court of Appeal judges, headed by Sir Andrew McFarlane.

The judges upheld a ruling preventing the 23-month-old from travelling abroad after life support was withdrawn.

What was Alfie's Army?

Throughout its campaign the family has been encouraged by Alfie's Army, a social media campaign whose supporters gathered regularly outside the hospital.

Alfie's parents apologised, saying they did not intend to "harm or cause conflict or upset".

Before their son was granted Italian citizenship, a group of protesters tried to storm the front entrance before police officers formed a line to block the entrance.

A group of about 100 Alfie supporters held a candle-lit vigil outside the hospital overnight on Monday.

On Monday, Alfie's life support was turned off at 21:00 BST after a High Court judge dismissed fresh submissions heard in private from CLC lawyers.

Alfie's father had said his son was continuing to breathe unassisted and his life support should be reinstated.

On Tuesday morning, Ms James posted a picture on Facebook showing him sleeping in her arms.

"No matter what happens, he has already proved these doctors wrong. How amazing is he. How beautiful does he look," she wrote.

Asked on Wednesday if he had given up on taking their son to Italy, Mr Evans said: "No, we haven't. He's proving them wrong."

"It's time to give him some grace and dignity and let him go home or to Italy", he told ITV's This Morning.

Alder Hey Children's Hospital said it would not issue any updates on the toddler's condition "out of respect for the privacy of Alfie and his family".

Speaking outside the hospital on Thursday after a meeting with doctors, Mr Evans praised the staff for how they were treating Alfie.

He also thanked supporters Alfie's Army, but asked them to go home.

The BBC is not responsible for the content of external sites.

# data[].attributes.attachment_link.title
Who was Alfie Evans and what was the row over his treatment?

# data[].attributes.attachment_link.description
The 23-month-old at the centre of repeated legal hearings died in the early hours of 28 April.