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Being a Consumer.

We use material and experiential consumption to enact our personal and collective identities. It is far more than sitting behind the wheel of our new car pretending to be a racing driver. What we eat, wear and the experiences we choose identifies us and our lifestyle. It facilities social differentiation.

Retirement can wipe out an identity that we may have occupied for 40 years. It may be combined with the end of other identities. Children may leave home. Houses may be changed. Friends and family may have died. There is huge pressure to create a replacement identity. Recent studies have shown just how important this can be.

A study by the National Bureau of Economic Research looked at a large US longitudinal data set. The study tracked cognitive ability over time. It also tracked employment history. They found that future cognitive ability was tied to employment. People who stopped work early suffered. Those who stopped work before 65 had a poorer trajectory of cognitive ability. The loss of that “worker” identity had a big effect. “Attitude to ageing” can influence physical and mental health. Having a strong self-identity is part of having a positive attitude towards life and ageing.

The Dimensions of a New Identity

Different individuals build their new identity in different ways. Some go back to the past. To the identities they had before work squeezed out everything else. Whether that was being a musician, a crafts person or involved in some club or society. What may have been suppressed into a “hobby” now returns to center stage. Others truely reinvent themselves and take on a completely new identity.

Some are motivated internally on “self-expression”. On self-discovery or on creating a legacy. On exploring their inner selves. Others focus on affiliation. They may organize family or friends’ events and trips. They create an identity anchored in a particular group of people.

Barriers to a New Identity

Any new identity has an uphill battle against existing societal retirement ideas. Society expects “decline” to be a core aspect of ageing. Society reveres youth and fears dying. Society expects real life loss of physical and mental functionality. The Protestant Work ethic is still strong in Society. It expects productivity even in retirement.

There is a constant gap between these ageist precepts and self-identity. The gap between how others see us (old) and how we feel (young).

The good news is that individuals can still use their consumption to embody their new identities. Since the 1940’s consumption has changed. The variety of products and experiences have exploded. The offers for “retirement” have grown. The real costs have declined. At the same time today’s 65-year-olds have the time and the money to build those new identities.

Barriers to Consumption.

Retirees have the time and the money. They have the motivation to reinvent their identities. They want to be consumers. One thing stands in their way – consumer ageism.

Ageing does mean changes in functional ability. We think nothing of wearing glasses for reading or driving. They represent a loss of visual functionality. Because they mostly “arrive” in our forties we do not associate them with ageing. Loss of other sensory sensitivity comes later. It is progressive. Thresholds rise but idiosyncratically. Loss of high frequency sounds is common. Touch can become less sensitive.

All can be compensated for with good design. Increased lighting helps with vision. As does a larger typeface and high contrast on menus. Background music can be lowered, particularly when the venue gets busy. The keys on the credit card machine can be made larger and spaced further apart. Tables or chairs place further apart to avoid tripping. Most changes will also be viewed positively by non-elder customers. (Especially if they wear glasses !). Most do not cost much to change.

The pressure for productivity on front-line employees is huge. Check out staff in a supermarket are monitored continuously. Self-scanning and automation of all sorts remove people. People who can be part of an identity renaissance. People who can help with the process of co-creating. People who could care.

The Dutch supermarket Jumbo has introduced “chat check-outs”. These are designed to slow down the process and encourage chatting. Not every check out but a few per store. The lanes are specifically introduced to give servers a chance to chat. To reduce customer loneliness. The initial lanes were so popular that they were rolled out across the Netherlands. Jumbo is now introducing “chat corners”. These are areas were customers can grab a coffee and socialize. A deliberate attempt to build care into a productivity driven world.

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It is odd that so many people worldwide say that they feel tired all the time. In most places we have enough food. We have the calories/energy that we need. Our bodies do not seem to be able to make the energy available when we need it. Recent research suggests that this may be a mental not physical problem.

Body Balancing

Our brain is a forecasting engine. We cannot turn energy on like a tap. Instead at any time the brain first checks how much energy is available. It then deducts what it knows it will need to just keep the body functioning. It then anticipates future demand for energy in what we plan to do next. This can be physical activity. It can also be stressful situations. Energy consumption can jump by up to 60% when we are stressed.

The brain makes the best guess at what is likely to happen in the outside world. It keeps an energy reserve for that future event. When the prediction and reality do not match then we need a nap. This explains why being given good news can appear to give us extra energy. The brain has recalculated the energy needed based on a lower stress level. It releases more energy.

It also explains why we get tired when we are sick. The body has to generate extra energy to fight the disease. It draws a bigger share of the available energy for body maintenance. This leaves less for all other normal activities. It also explains why we can wake up tired. Our mind is anticipating a long day at the office full of meetings. Our body is saving energy and not making it available to us. We can feel much less tired when we find that there is a transport strike and the meetings are cancelled!

Mitochondria in the Cells

The power cells of our body are the mitochondria that live within every cell. They convert glucose and oxygen into adenosine triphosphate (ATP). This is the fuel needed to drive the cells. Unfortunately, there is a problem, the food supply can become too much. When this happens, the mitochondria switch from processing to storing. To put excess away for future use in the form of fat. That fat is in the mitochondria. At that point our energy levels can drop. The classic example is the impact of a high sugar diet. Energy production drops. We feel moody and sluggish.

The phrase “body balance” was coined by Prof Lisa Feldman Barratt. She is a neuroscientist and psychologist. She argues for the importance of body balancing to our emotions. How well our mind can forecast the future determines our mood.

Ageing Body Balance

Ageing starts at the cell level. More and more of our cells are damaged. We need energy for repairs. We struggle to keep up. Unfortunately ageing also affects the mitochondria. They gradually lose their ability to produce cellular energy. The production of ATP can drop by up to 40%. At the same time they are increasing the release of damaging free radicals.

Those free radicals can cause mutation of their DNA. Normally the cells will purge such mutations and failing mitochondria. Unfortunately ageing slows down the cleaning process. The consequences are most significant in those organs that require the most energy. This includes the brain, heart, and skeletal muscles. Mitochondrial decline is related to fatigue, cardiovascular disease and muscle loss.

Exercise can help recharge the mitochondria capacity. High intensity training seems to simulate the body to produce new mitochondria. Other exercises can help to stimulate the existing supply. Even aerobic exercise at low levels can do this. Taking a walk at a speed that still allows you to talk can simulate the efficiency of these important energy supplies. So too can weight training which stimulates cells within the muscles.

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Decomposing the TFR

A recent paper proposed that the TFR should be decomposed into two. The Total Maternity Rate (TMR) and the Total Children per Mother (TCM). The Total Maternity Rate is defined as the proportion of women who would become mothers during their child bearing years. Multiplying TMR by CPM gets us back to TFR.

Is worth it? The first thing to say is that it seems that TMR and CPM are independent of each other. The researchers used data from Italy, the UK, the USA and Japan. These countries have good data going back to the 1960’s and they could assemble 158m mothers. They used a very sophisticated set of analyses to look for any relationship. They looked at whether trends in the data were the same. They looked at whether breakpoints in the the two measures occurred at the same time. They used “wavelet coherence” which they describe as looking for “harmonies in a musical duet”. They extended their analysis to another 29 countries and 156m mothers. They still could not find any relationship.

Insights from an Alternative Viewpoint.

Decomposing TFR shows how some things are hidden. The US TFR in 2016 was 1.82 children per female over their childbearing years. This was the identical number in 1980. However the components have changed dramatically. The TMR has gone down from 76.1% in 1980 to 69.4% in 2016. The number of women becoming mothers has dropped significantly. However, those women who become mothers are having more children.

There was a break in the US trend for TMR in 2008 and it started to decline. In fact it has dropped by nearly 20%. However, the CPM has increased from 2.6 to 2.75. That is way above the replacement rate of 2.1. It has been estimated that if the proportion of women becoming mothers in the USA had been maintained there would be no fertility issue in the USA.

Comparing countries has the same issue. The USA and France currently have the same aggregate TFR number of 1.66. One would expect that the policy issues for the two Governments to be the same. However, if we disaggregate the TFR the pictures are very different. The TMR in the USA is 65% but in France it is 72.8%. Many more French women are becoming mothers. However, the French mothers are having only 2.28 children compared to 2.6 in the USA. Where any pro-natalist policies should be targeted is different.

The Scale of the Problem.

There are variations by country in TMR and CPM. However the same countries appear when looking for problems. South Korea tops both lists. It has a total childless rate (TCR) of 52.1%. More than half of Korean women will never become mothers. Those that do will only, on average, have 1.75 children. This alone is a lot less than replacement. It is also less than the aspiration of mothers to have at least two children. Spain has a TCR rate of 42.5% and a CPR of only 1.95. Italy has a TCR rate of 40.5% and each mother averages only 2 children. The UK by comparison has one of the lowest TCR rates of 29.5% and a CPM ratio of 2.23.

Insights into the Cause of these Declines.

The research looked at breakpoints in the trends. This was particularly the case for TMR. The choice of a woman to become a mother. Breakpoints are steep changes in the trends over time. TMR fell sharply in Italy , Japan and the UK around 1974. The US had abrupt drops in 1971 and 2008. The researchers suggest that these were driven by the global oil crisis of 1973-1974 and the global mortgage crisis of 2007-8. In each case there was a bounce afterwards. However the TMR never returned anywhere near to the previous level. Disaggregation of the TFR may offer new insights into the global fertility collapse.

Statistics

In previous Newsletters I have suggested a heathy cynicism when seeing statistics quoted. There is usually nothing wrong with the expert who created a number. Especially if it was created by a government department. The issue is the purpose of the number and how it is subsequently interpreted. Period Life Expectancy is not a forecast of one’s life but a comparator index to compare improvements in health care. There is nothing wrong with TFR when comparing within and across countries. The problems come from the way the numbers are interpreted.

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One in five people report that they are fatigued during the day. This was the finding from a synthesis of 91 different studies. They involved nearly four thousand participants. We know from multiple studies that lack of sleep can have a negative effect.(See Newsletter #240 "Brainwashing") We know that our perceived quality of sleep is one of the top five measures that we use to assess our wellbeing. It seems it can influence our cognitive abilities(See Newsletter #186 "Sleeping on it"). But which sleep? The objectively measured sleep or perceptions of how well we slept?

There have been multiple cross sectional studies comparing our assessment of the quality of sleep and how it differs from objectively measured data. It turns out that there is little connection between the two if measured that way. We are not even aware how often we wake in the night. A study tracked actual sleep over the course of a week with a wrist monitor. At the end of the week, individuals were asked to rate their quality of sleep and its duration. There was no relationship between the objective and subjective measure.

Researchers have pointed out that these results may not be valid. Individual characteristics may be biasing the averages. A very recent study instead looked at longitudinal data of a different kind. They measured objective and subjective sleep data for the same individuals over 8 days. They could then compare the subjective assessment with the objective eight times within person. They did find association with objective measures of how long it took people to go to sleep, how many times they woke and total amount of time asleep. Different people had different sensitivity to their objective sleep.

Inferring Sleep Quality

Subjective sleep quality is not inferred exclusively from the objective data. Instead, we infer sleep quality from the time before and after our sleep. One research team created a simple task. It asked people to report on the quality of their sleep the next day. Not just first thing in the morning. Instead, they asked for the report every two hours for the rest of the day. The reports changed as the day progressed.

On each occasion they were asked to rate their total sleep time. Then their sleep quality assessment. They were also asked for a broad assessment of their mood. Whether they were engaging in physical or social activity at the time of the report. The results confirmed that we infer subjective sleep quality from activities the next day. Ninety one percent of respondents changed their ratings of their sleep experience. The total sleep time stayed remarkably constant, with 80% giving the same score. However, only 8.9% of subjectively assessed sleep quality remained the same.

The pattern showed a steady increase in changed scores as the day progressed. By two o’clock in the afternoon most people had changed their scores. The researchers tried to explain what was causing those, usually upward, re-ratings. Social activity had some effect. The big driver was physical activity of any kind. Exercise made people re-rate the quality of their sleep the previous night.

Does it Make a Difference?

Is it the objective measure or the subjective one that has the impact upon us? Which one affects our cognitive ability? Which one affects our moods and emotions? It turns out that they affect different variables. Researchers measured a suite of cognitive and mood measures. They measured respondents’ ability to inhibit action. They were asked to respond according to the directions in which an arrow pointed. However, if a noise sounded, they were to do nothing. They measured short term memory by seeing how long a string of numbers people could recall. They also measured emotional bias. Using pictures portraying people displaying different positive and negative emotions. Respondents rated the pictures positive or negative. They also measured anxiety and general orientation to be positive or negative.

Cognitive scores were related cross-sectionally to the objectively measured dimensions of sleep. How long they slept. How active they were in the night and how much of the time they were asleep when in bed. All were related to the different cognitive measures.

More importantly the subjectively measured sleep quality did not predict the cognitive scores. Interestingly the subjective measures were good predictors of mood and emotion. The objective scores failed to predict emotions. Emotional bias, positive or negative emotional and anxiety.

Its All in the Mind

What do these studies tell us about the current fascination with quality of sleep? Sleep apps have become more and more popular. They can measure an approximation to our objective quality of sleep. They have become more sophisticated.(See Newsletter #184 "Do We Really Need a Fitness Tracker?") They are still nowhere near the level of the equipment in a sleep laboratory. They can perhaps tells us on which days we should or should not engage in lots of cognitive activity.

A lot of our mood the next day is driven instead by our view of how we slept. That in turn can change during the day. We think we have had a bad night perhaps because our smart watch told us so. It might be just a feeling. What we should not do is stay at home and cocoon ourselves. Better to go for a walk or go to the gym.

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The Grandmother Hypothesis tries to explain an evolutionary quirk of humankind. We do not die when we are no longer capable of reproduction. All other primates have a very limited life after they are no longer useful to evolution. The Hypothesis argues that the older generation can still help. They allow women to increase the rate at which they can have children. The “extra hands” can increase the amount of food hunted and gathered. Researchers analysed many different ancient and primitive societies. They found women whose mother is still alive have more children who survive. See Newsletter #202

In the modern setting grandparents enable women to return to work sooner and for longer. Billions of pounds of unpaid child minding are provided. This underpins the economic benefits of a growing female workforce. Grandparents provide the “emergency backup” to childminders. That allows for the productivity of their female offspring (See Newsletter # 191 £3.5 of Family Childcare).

What’s in it for the Grandparents?

There is evidence of a growing resistance amongst grandparents. They want to cap the number of hours they provide. There are huge emotional rewards that come from the love of a grandchild. Even so grandparents do not want to be “exploited”. A study published this month in the Journal of Psychology and Ageing suggests another benefit. It may help to tip the balance.

The researchers used ELSA. This is a UK longitudinal study of individuals and families over many years. They included some 2887 grandparents in the analysis. The study has measured two key variables. They know when a person becomes a grandparent. They also measure every two years their cognitive ability. The new study relates the two.

The first analysis they did simply compares grandparents and non-grandparents and their cognitive ability. They added some 7395 comparable individuals who were not grandparents. It is not quite that simple. There are many other factors that can impact cognitive ability. Age, education, health etc can all can be important. The researchers therefore had to standardize the two samples. To make them as comparable as possible. The results showed that both grandparents had a higher score. That is when compared groups who were not grandparents. Of course, this is an association and only a clue.

They then looked at effects over time. They tracked cognitive ability before and for many years after becoming a grandparent. The results showed an interesting split. Grandmothers stayed cognitively younger than comparable females. Grandfathers did not. There are various possible explanations. Grandmothers may have a greater emotional attachment to the child. They may help more often and in more ways.

Does It Matter What you do with your Grandchild?

Different grandparents play different roles. Over half of those studied were prepared to offer care throughout the year. Others focused on school holidays and weekends. They also reported how frequently they offered care, measured by the number of days in the week. The researchers could therefore test for the frequency of giving care. Whether it delivered any cognitive benefit.

The ELSA data also includes seven different activities for grandchild and grandparent. For example, picking up or delivering to school or helping with homework. Cooking food or engaging in leisure activities. They could create a “variety score” for each grandparent. Next they looked for relationships. Did the frequency of contact influence staying cognitively younger? Did the variety of activities have an effect. There was no such relationship in the data. Other researchers have suggested one possible reason. There is a diminishing return. After a while, any cognitive benefits decline with familiarity.

This analysis does not explain the difference between grandmothers and grandfathers. The women get a cognitive benefit, but the men do not. The Grandmother Hypothesis found a similar effect. Having a grandmother present improved the success rate of the number of healthy children. Having a grandfather had little effect. One suggestion is that the grandmothers have a deeper emotional bond with their grandchild.

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I came across the “sidewalk ballet” when researching the Newsletter on children leaving the city (Newsletter #264 Where have all the children gone?). It describes the set of interactions, routines and scripts that some streets have. These can build trust across a group of people that are not really related. Or at least related only by proximity and frequency of contact. The “school run pick up” was a classic example. Groups of people regularly in the same place. Parents but also shoppers and shop keepers.

People who plan cities traditionally look at the physical layout of the buildings. They might consider the parks and the benches. They start from the buildings and work their way back to the people. Historically they did not have the tools to look instead at the people. At the patterns of mobility across even a small area, let alone a whole city. Only then would they be able to understand the true nature of a street community.

A powerful illustration of how powerful a people focused approach can be comes from a study on the MIT campus. Not a city but still a large complex environment. They tracked the location of an individual’s office. They tracked their route to the canteen for lunch. They tracked their normal routes in and out of the office. They also tracked the email traffic between individuals as a dependent measure. Physical proximity does make a difference to subsequent email activity. Passing in the corridor did make a difference but only a small one. If corridors are busy there was less impact. This was because there was less interaction. Eating in the same cafeteria generated many more emails. The physical mobility was affecting the electronic world.

New Kinds of Data

Researchers have traditionally used simple counts of the number of pedestrians. They measure these at a particular point over time. Across all the locations they look for patterns. The look for unoffcial paths across lawns to find out what pedestrians are up to. Recently all that is changing as researchers focus on new kinds of data. For example, there is a group at MIT in the USA looking at the millions of pictures of streets in Google maps. They have trained AI to search out people in the pictures. Their interactions with others is coded together with the street. They can created millions of data points.

Other groups are looking for people level data. Many large cities do transportation surveys. Capturing retrospectively travel patterns from large groups of people. Some researchers are using mobile phone data. Data that can track individual movements anonymously. They can track places and the kinds of people that are within them. Others are using drone footage to look at which people use a given street and how they use it. AI is enabling the processing of vast amounts of such data.

Spatial Segregation

When researchers looked at cities the results showed how they can reinforce but also breakdown segregation of all kinds. They looked at five different cities around the world. Each had surveyed at least 25,000 people and their movements. What they found was that different groups used the city in different ways. Because of where they visited and when they travelled, they were segregated.

In the US cities different racial groups moved did not mix during most of their journey. They were effectively travelling in corridors for much of the time. In cities around the world different socio- economic groups travelled in those same corridors. One of the strongest patterns was the typical commute. From the dropping of the children at school, to work and to lunch etc. there was a lock step pattern. The mixing with different socio-demographics was minimal. The commuter families travelled in a pack.

They researchers computed a “mixing index”. This measured the chances in these spatial patterns that an individual had to meet someone “different”. They also looked for locations where the chances of mixing where the highest. There where such locations in any city. Here people at least saw someone who looked different to themselves.

Age Does Bring Mixing.

One of the surprising findings was that retired people mix more, at least in their third age. Retirement brings relief from the commuter pack. Within the five big cities they studied, the retired group had a higher mixing index than many other groups. They had a much bigger exposure to different groups. They had a much bigger chance to see the people for whom they had stereotypes. To question their own stereotypes of (say) teenagers who otherwise they would hardly meet. They themselves would question the stereotypes held by the people around them. To demonstrate that the elders are not “dear but doddery”. That mixing was concentrated in public spaces, shops and retail services.

Mixing is important to older people. Loneliness has been shown to be as big a killer as smoking. In any earlier Newsletter I talked about loneliness. I drew the distinction between psychological loneliness and social isolation (Newsletter #95 Loneliness). You can be lonely even when surrounded by crowds of people. However, for many people those crowds can break down loneliness. The surveys give no insight into whether mixing actually meant interaction. Mobile phone data could show a hotspot of potential interaction in a coffee shop. Did people actual talk or was everybody merely scrolling on social media?

Designing the Elusive Communities.

At the moment researchers are converging on that community “instruction book”. What are the different ingredients of a supportive street community? One that can be familiar and friendly to an older person. One where the street ballet is choreographed to create that invisible web of trust. The recipe can only come from a mixture of analysis and intuition. Perhaps it is closer to a recipe for cooking a meal than an instruction book for assembling a bookshelf.

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The “Knowledge Test” was first introduced in London in 1865. It is known as the most difficult taxi test in the world. The impact on the brains of the drivers was not investigated until the turn of this century. Initial cross- sectional studies used brain scans. They found that London Taxi drivers had a much-enlarged posterior hippocampus. This was compared to a matched non taxi driver group. That part of the brain is dedicated to spatial navigation.

Correlation is not causation. The researchers therefore tracked a group of 79 new drivers. From when they started to learn the knowledge for four years. By that time 39 had passed. They tracked the changes in their brains. Those thirty-nine who had passed already had bigger posterior hippocampi. Those that failed had no or little change. Learning the knowledge was changing their brains.

Neuroplasticity

This study demonstrates just how much adult brains can be rearchitected. We take our brain as something fixed in childhood or adolescence. Older people recruit different parts of their brain to maintain their cognitive ability. These taxi drivers show that we can even change the physical structure much later into life.

Further studies showed that the process continues. This area of the brain grows the more drivers spend their days driving. They also showed that the brain was not generating new neurons. Rather it seemed to be re-purposing the anterior part of the hippocampus. Some studies have shown a corresponding decline in other types of spatial memory. This suggests that stealing neurons for one task may diminish other abilities.

The Dangers of Google Maps

Brain scan studies have been done using simulators of journeys. Respondent had to navigate the journey with or without Google Maps. Having electronic assistance changes the parts of the brain working. We are far more passive than if we are actively navigating ourselves. We are engaging less of our spatial reasoning. This is the same effect as using a laptop in class rather than taking notes on pencil and paper. See Newsletter #257 The Pen is Mighter than the Keyborad).

In the real world, studies of taxi drivers in different cities have shown a negative impact of using satnavs. Unaided navigation ability declines the more that the satnav is used. It seems that spatial reasoning and memory suffer from “Use it or Lose it”. The satnav is doing the spatial reasoning for us.

To mitigate the impact researchers, suggest a number of strategies. The first is to turn the satnav off regularly and go back to reasoning the route out for yourself. Alternatively look at the full map of the journey on the satnav. Then try to minimize the use of the audio directions. Similarly turn off Google Maps for sections of journey where it adds little value. Use it for navigating city streets not major roads.

Its Not Just About Driving

We use the same reasoning skills far away from driving. If we enter a dark room, we use our skills and memory to cross it successfully. Spatial memory is also our object location memory. It allows us to memorize where we put the car keys! Spatial reasoning is part of our cognitive tool kit, and we process situations using it. Google Maps may interfere with all of these.

Researchers are also looking at the link between Alzheimer’s and spatial reasoning. One of the first places that Alzheimer’s is visible is in the hippocampus. People are questioning whether taking the “knowledge” helps. Do London Taxi drivers have less chance of getting Alzheimer’s? Does losing spatial reasoning have other implications?

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Five years ago today I started to publish the ConsumerAgeism Substack. I have managed to not miss a week. It was close and I even published one Newsletter from a British Airways flight over the Andes! I give this birthday cake to you, my loyal readers. To those who have been with me from the beginning thank you for your support. To those who have just started reading – welcome. It would not be in same if you were not there! Keep your comments and thoughts coming.

The Demographic Pyramid

A Demographic Pyramid charts the age profile of a country. It shows the number or percentage of the population in age bands. It charts men and women separately. They are placed side by side to make the famous pyramid. We are used to the idea of a broad base of children narrowing to a spike of old people. The shape came from a combination of forces. When the charts were first created fertility was high. Child mortality was over twenty percent. Many children died before becoming a teenager. Life expectancy was lower. All that has changed and the country pyramids are become columns.

City charts are however different. This is a recent plot of the city of Manchester. It shows a completely different “Christmas Tree” pattern. There are many fewer children. The population explodes when young people arrive in the city to work or study. However, when they start to have children, the population falls. They leave the city taking the children with them.

A Global City Phenomenon.

All over the world the pattern is the same in the cities. The number of children is declining. Primary School registrations are a good marker. They are down by a quarter in Paris in the past decade. In New York they were down 18% and in San Francisco the pre-school intake has fallen from 56,000 to 49,000.

The London population has increased by 543,000 in the past decade. The population of under nines has decreased by 107,000. There has been a drop in the number of babies born in the UK in that period. In 2012 there were 729,000 babies born in England and Wales. Ten years later that had dropped to 591,000. Fertility decline is real.

The cities are however compounding this with other factors. Affordable family homes are in short supply. Only half of London’s homes have three or more bedrooms. Government schemes for affordable housing tend to deliver one- and two-bedroom homes. Houses are divided for rental or Airbnb. Childcare is more difficult.

The Schools are Closing.

Economically there is a benefit in the decline in the number of children. The cost of education can go down. In cities especially that means the closure of schools, particularly inner-city schools.

In London there was a cohort of children that started primary school in 2017. By the time they moved to “big school” in 2024, 20% had moved away. Schools are built for large scale education. Their physical structure cannot shrink. Buildings and whole schools have to be closed. Today it is the primary schools but soon it will be the secondary schools. Logistically is in a nightmare for their managers. Last year a School in Hackney for 500 children closed. They all had to start a new School, many a mile away. Governments are worried. If the decline is not carefully managed there will be no savings and time is running out.

Schools as the Engine of Safe Streets.

Schools and the “school run” are the foundation of the community. Relationships are built and people recognized. They are part of what an American author called a “sidewalk ballet”. The trust in a city street is built up from many little public sidewalk/pavement contacts. The “pre school” but especially the “after-school” run is part of that ballet. It builds a network of shopkeepers, neighbours and parents. They provide a safety net of informal supervision. It is that same implicit safety that older people seek. This is what drives the wish to remain at home in their neighbourhood. Without the local School, will the safety net erode as people become strangers?

Fewer children have a knock-on effect in other community facilities. If the children go to School a mile away what happens to the community and church halls? What happens to the after-school activities? Do they migrate as well. Certainly, the School run is more likely not to be a walk. If the usage falls, will they close and with them the elder activities?

The Catchment Area Game

Not all schools are the same. Some have better reputations. Demand for them is higher. Rationing of places is often based on the “catchment area”. Schools favour children in their locality. The result is that house prices in those areas go up as schools create demand. When the world was stable all a parent had to worry about was whether the school could maintain its standards. What happens when schools might close?

Age Based Ghettos

Ageism can be beaten. One of the easiest ways is to challenge the “stereotypes” is with contact. It is much more difficult to maintain a prejudiced view of a “gang of sixteen-year-olds” if you meet them. If they are polite and helpful. It is much more difficult to maintain a view of a old person as slow and frail when you talk to them. Children are leaving the cities together with their parents. The old are migrating to the country and the coast. Are we creating age-based ghettos?

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Defining Desire

The gap between desired number of children and the actual has been well documented. Many of the studies measure a stated desire from young adults. Many years later they compare this with their subsequent families. This ignores the fact that during our lifetimes we may have perfectly good reasons to change our minds. Instead, a recent study looked at women who had just reached an age when they can no longer have children. It asked them retrospectively whether they had the children they desire.

Cross National Comparisons

This questions were included in a recent large international study. It turns out that the gap between desired and actual exists. Moreover it is reasonably constant across countries. The countries include more devloped nations such as Austria, the UK, Demark. They also include Estonia, Moldova, Argentia and Uruguay. Perhaps surprisingly the society and the medical infrastructures do not seem to have an effect. For women the ideal across countries averages just below 2.5. The resulting families have less than 2.

The Impact of Infertility

The age at women have their first child is increasing all over the world. A women born in theUK in 1978 is now passing childbearing age. They had on average one child per woman by age 31 years. Their mothers’ generation (born in 1951), had one child by age 26 years. Women born in 2007 can be considered to be the daughters of those born in 1978. They are projected to have an average of one child per woman by 35. For those born in 2025, this is forecast to occur by age 36. Fertility declines with age. Is infertility becoming an increasing issue in the gap between desired an actual family?

The vast majority of disappointment comes from women who were childless or only had one child. Disappointment was only as third as high for women with two or more children. The survey also asked these women whether they had an issue with fertility. 64% of women who were childless and did not have fertility issues were disappointed. For those with fertility issues, 93% were disppointed.

The Assisted Reproductive Technoloy (ART) Data

The first IVF in the world took place in 1978. Today there are estimated to be 8m people in the world born by IVF. This is a procedure that is highly regulated and documented around the world. The UK Regulator says that in 2023, 20,700 babies were born with IVF. They accounted for only 3% of all babies born. This compares with Denmark where 11% of all births involved ART. In Europe the next highest was Belgium at 5%

The percentage of babies born with ART varies by age. For women under 35 less that 2% of UK babies born involved ART. For the 35-39 age group that rose to just under 6%. However, for women in the 40-44 age group 11% of all the babies were enabled with ART.

The number of ART babies delivered to the under 35 year olds rose from 4712 in 2000 to 7939 in 2023. That is a 69% increase. The number delivered to the 40–44-year-olds increased by 330%. ART is increasingly involved in older women successfully having children. The success rates are lower 5% without donation. Twenty percent of all ART births involve donation of eggs, sperm or embryo’s. The majority to older women.

Will the Impact be Big Enough?

Data from Japan suggests that ART may be able to reduce the size of the “disappointment gap” by about a third. Japan has one of the highest incidences of ART. According to the latest comparative data, they provided 3603 IVF cycles per million of the population. This compares to a high of 5711 cycles in Isreal. That may be due partly to medical tourism. Denmark provided 3575 cycles. This is consistent with the 11% of all babies born this way. The USA offers only 922 cycles and China only 688. In absolute terms of course China leads the way with over 1m cycles, followed by the USA at just over 300,000.

How that provision is paid for varies dramatically. Provision in the UK is provided by the National Health Service in only 27% of cases. Couples are spending their life savings to continue treatment in the hope of a child. Companies vary dramatically in their support for employees going through this tortuous process. There is still pressure on women, especially, to feel a failure if they cannot conceive. Even though infertility in men seems to account for a third of all problems.

The Macro Problem.

UK baby girls born in 2025 are projected to have an average of 1.46 children throughout their life. The data suggests that they may look back at their childbearing years with disappointment. Fewer will have married and if they do it will be when they are older. They will have started families later. The incidence of infertility will be higher for them. Success rates for ART will have improved. It is 35% for couples aged between 18 and 34 today. Can the scale of the provision be created and funded to avoid that disappointment?

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The UK Example

The logic is the same all over the world. The National Institute for Healthcare Excellence (NICE) is the regulator for approving drugs to be used in the UK National Health Service. One of the criteria they use is the “Incremental Cost Effectiveness Ratio” (ICER). This is an assessment of the incremental value of a new drug or technology compared to the existing treatment. The incremental cost is relatively easy to compute. This is divided by the incremental “Quality Adjusted Life Year “or QALY. One QALY is one year of life in perfect health. The assessment includes the incremental impact on quality of life which can range from 1 down to 0 and how long it lasts.

Dividing the incremental cost by the incremental QALY gives a cost per QALY. NICE sets a threshold for acceptance of £20,000 to £30,000. Above that the treatment is viewed as too expensive. There are modifiers that can be included. These are based on the severity of the disease, health inequalities, terminal diseases etc. This can raise the threshold to £70,000.

Improving life expectancy and healthy ageing is therefore dependent on a valuation of quality of life. This is not surprising in reality. Healthcare budgets may be growing but they are not infinite. There has to be rationing. Within a fixed healthcare budget there is an opportunity cost of approving new more expensive treatments. Costs elsewhere have to be cut.

Different drugs have Different “Values”

Different drugs have different ICERS. A recent survey showed that cancer drugs have a median ICER of £30,000 per QALY. End-of-life cancer treatments have a higher threshold and can be £50,000 per QALY. A typical anti-infective drug is very cost effective at £6,478. There is no ICER approved for an Alzheimer drug. The cost would be £1.4Bn for to add less than half a year QALY for 70,000 patients. At least that is the number quoted by the BBC. This was judged to be poor value even though the drug was medically approved.

The Case of Multiple Sclerosis

This is a auto-immune disorder of the nervous system. The body attacks the spinal cord and the brain. This can produce multiple disability symptoms. The most common manifestation is episodic. Symptoms appear but then fade only to return at some “random” point in the future. There is no cure. Each episode causes permanent damage to the nervous system. These cumulate.

It was only in the 1990’s that it became possible to offer some relief. Disease Modifying Drugs (DMDs) were developed. These succeeded in reducing the number of relapses and minimizing the impact of each relapse. Prior to the drugs, life expectancy with multiple sclerosis was up to ten years shorter. With the drugs that difference has virtually disappeared.

DMD’s are some of the most expensive drugs. Their price has risen well above drug inflation since they were first introduced. A US study suggested that the cost for a single patient over their lifetime could be as high as $4m. (US drugs are notoriously expensive) . For most patients the cost of the drugs represents 80% of all treatment costs. The investment is still worthwhile. Not just on humanitarian grounds but on economic grounds. MS is a disease of young people. The most likely age at which it appears is between 20 and 50. It is a debilitating, affecting an individual’s life. Their ability to work and their productivity. Any mitigation of symptoms will improve quality of life over a long period of time. It will also benefit the economy.

New Drugs for an Ageing Population

Infectious diseases are no longer the threats that they once were. In their place, the chronic diseases of later life are driving medical costs and innovation. These are diseases for which there is no cure. The symptoms of arthritis can be relieved but not cured. Hips and knees can now be replaced in the worst cases. For many chronic disease drugs and procedures already exist. Hip and knee replacements were approved by NICE.

Treatment improvements in the UK, and elsewhere, will have to face the economic tests. Does the new treatment deliver incremental quality of life adjusted years? People are living longer so the benefits will last longer. Is the elderly healthy ageing incremental benefit worth the cost of the new drug or procedure?

Improvements in healthy ageing and life expectancy will increasingly depend on Societies’ tolerance for increasing healthcare budgets.

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Are we, like the mythical frog, missing the huge changes in Society. The changes in life for the elderly, because they are so gradual.

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The “Life Course Model”

The “Life Course” approach sees life as a series of events. As a concept it was first developed in sociology. It assumes ageing is an individual development process. Its perspective is that there are sequential life stages. The transitions from one stage to the next form pathways. Each transition generates stressors. Our responses to those stressors develop us. Those transitions can affect our financial status like “getting a job” or “buying a house”. They can be transformational when we move from being an “individual” to being a “parent”. Others can change our perspective on life. To lose parents or close friends can have profound effects on our motivations. The impact depends on our trajectory(See Newsletter #115 Models of Life).

In a single generation many of the pathways have change or been redefined. Most have moved to a later age. The milestones by which we manage our lives are moving. Each will have affected us but did we notice how we had been stressed and developed?

Bringing up Children: being a parent is different

Children stay at home for longer. The age for people to leave home in the UK today is 24. This is up from 21 only ten years ago. Today 22.4% of households have an adult child living at home. 61% of adult children living at home were men.

In the UK in 1980 15% of people went to university. Today that number is over 50%. There are many more students within families going away or staying at home. The age at which people start work has, however, not changed very much since 2011. It is 23 for men and 24 for women. Since the late 1990’s more women have gone to university than men. In 2022, 319,000 women started university versus 245,000 men. Young men are missing out and seem to be staying at home.

By the age of 28 half of children have left home and are living with a partner. In 2011 72% of them would have been married or in a civil partnership. This year that number fell below 50% for the first time. The ritual of the British family wedding is far less common. A generation ago in 1970 there were 415,000 weddings. In 2023 there were 224,000 from a much bigger population. The norms are changing and parents must adapt.

Becoming a Grandparent has changed

The age that a woman becomes a UK mother has increased dramatically in a single generation. In 1970 it was 21 years old. Their partners were 23. By 2000 that mother would be 51 years old and their daughter 30 years old. She will not have become a mother at 21. There will be no 9-year-old grandchild. By 2020 the age of becoming a mother had risen to 29 and today it is over 30. In 2021 more than half of all babies were born out of wedlock for the first time since records began.

The age at which a mother becomes a grandmother has moved with the age of motherhood. In 2011 20% of women aged 50 were already a grandmother. Today that number is 9%. The most likely age of becoming a grandparent has become 65. That is up from 61 only ten years ago.

Fertility has changed dramatically. It was 2.4 children per UK female in 1970. Today it is 1.5. Families are shrinking. Christmas lunches are more likely to include great grandparents. There will, however, be fewer children at the table(See Newsletter #170 Sitting on the fence).

Today half of the population owned their own home (with a mortgage) by the age of 36. That number was 32 twenty years ago. House price inflation has pushed the number back. Unless the “bank of mum and dad” has been able to help. Parents are becoming banks.

Becoming a Carer for young and old

Becoming a grandparent can often include a new role. Becoming a carer for grandchildren. To allow one’s children and their partners to continue working. In 1970 just over 50% of women were working. That has now risen to 72%, only 5% lower than the employment rate for men. However there has been a huge shift in roles in the home and at the workplace. The way your children live their lives is completely different to the model you know.

We care for ageing partners and siblings. Today a quarter of people in their fifties are already carers. The most likely age when people are providing unpaid care is now 59. Women still carry the bulk of the burden. At that age parents are also reaching their fourth age. They too need care from the same individuals who have a childcare role (See Newsletter #86 The Longevity Dividend III.

The End of Marriages

Some take on the role of divorcee. The incidence of divorces is growing, even though the number of marriages is declining. UK divorces peaked in numbers in 1993 and have declined since. Much of the decline is due to the drop in the number of marriages. Of the couples married in 1963, 7.8% of them were divorced before their tenth anniversary. 22.8% were divorced by their 20th anniversary and 27.1% by their 40th anniversary. Of those married in 2013 23.6% were divorced by their 10th anniversary and 40.7% by the 20th. For couples married in 2013 the rate has fallen to 16% divorced by their 10th anniversary.

Becoming a widow or widower is something that everyone faces. Men are expected to die first. However, life expectancies are equalizing and this trend is declining. At the age of 60-64 in 1991 18.5% of women could have expected to be a widow. That dropped to 9.4% in 2011 and 7.2% in 2021. (Widow here is defined as a woman who has been in a marriage or civil partnership). By the age of 75-79 in 1991 55.6% of women could have expected to be a widow. This fell to 41.8% in 2021. Men still have a shorter life expectancy. Today above the age of 85, 72% of women and 37.1% of men can expect to have lost their partner.

Perhaps the greatest surprise of all is that we are expected to live to the age of 90. Our parents died at much younger ages. (See Newsletter #242 Three Score Years and Ten). We can live longer, healthier but what do we with all that time?

The old are accused of not being innovative. Look what they have coped with. The number of milestones to life that have moved. What resilience they must have to cope with all that change.

This Newsletter was inspired by sa series of publications by the Office of National Statistics in the UK titled “milestones….”

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I have written many Newsletters about ageism.(See for example Newsletter #99 Age and ageism" How it impacts job opportunities, medical treatment and many areas of life. I turned recently to look at academic research. How ageism may be distorting the very results that I talk about.

Laboratory Experiments.

There are many studies done in the laboratories of psychology departments across the world. Experiments to look at the advertising are common. They ask things like “Are older people more sensitive to emotional advertising? Are older people less able to detect misinformation. Can older people be influenced by prescription drug advertising in the USA”.

The typical experiment creates two groups, one “old” and one “young”. They are shown some ads and asked to respond . The researcher then compares the scores for the groups and pronounces the results. There are multiple ageist biases that can and do creep in. Where do the samples come from? Don’t forget these laboratories are invariably on campuses. Students are recruited to be the “Young” group. Often, they receive extra course credit for participating. The “old” groups are also a “convenience sample”. They come from alumni, library members, campus or community groups for older people.

By using a convenience sample the researchers have adopted an ageist model. “All old people are the same”. Some studies provide a profile of their samples. The range of ages is 65 to 90. All are averaged out as “old”. We know that there will be declines in mental ability at some age. At 90 it may be present but at 66? Worse still the studies use different ages to define old. Some start as low as 50, others use 70. Many use 65 as some kind of “retirement” breakpoint. In this Newsletter we are learned that more and more people are not retiring then. In the UK state retirement age is 67.(See Newsletter # 111 Working Late) Most studies using longitudinal data show little cognitive decline until 80.

The researchers are just as ageist with the young group. They combine 18-year-old undergraduates with 26 year PHD students. They assume they are homogeneous. With such ageist based designs how much credence do we give to the results?

Ageism and Survey Research.

A lot of survey research takes age as an independent variable. It asks questions based on the format “ Does X increase as we get older?” Here we walk into a different ageism. This is another kind of homogeneous group problem. They assume that in fifty years time the forty year old in the sample will behave like the 90 year old. Unfortunately we know that there are generational effects. We are ageing more healthily in each generation. We only have to compare the health and behaviour of todays 75 year olds to those of a generation before. Our 40-year-old is on a different ageing “curve” to the ninety year old when they were 40

The Dangers of Averages

The Substack Community that looks at ageing is buzzing with a new study. It came from Becca Levy and was published this month. She is a famous researcher and has written extensively about ageism. It was her that theorized about the internal stereotypes we all hold. How they can become self-fulfilling. The article flags just how much ageing study conclusions are influenced by the stereotypes that we hold. Ageing is assumed to be about decline. After some pre-ordained age everything is decline.

Becca and her co-researcher set out to challenge this stereotype. The used a pre-existing longitudinal survey. From that survey they picked too measures. One assessed physical capability. The second was a standard measure of cognitive ability. They chose people over 65 who had been surveyed multiple times as part of the study. They started off by showing the dangers of averages. Across their large sample the average result showed a small decline in both measures year on year.

The problem with averages is that we do not know what they hide. Did everybody decline a little? Did most people stay the same and a few decline a lot? Where there a large group that declined and an only slightly smaller group that improved? There are many ways that the aggregate results could happen. Unfortunately decline is part of the stereotype. The average reader would assume that the vast majority of people declined and happily accept the results.( Did you?)

The disaggregated results are very different. They looked at the trajectory of individuals. A significant number of people showed an improvement. In fact 41% showed an improvement in either their physical or cognitive abilities. 32% improved in cognition and 28% in physical. Things got better after the age of 65. We can extend the logic by including those people whose scores did not change over the period. 51% of respondents were either stable or improved on cognition. 38% were stable or improved physically. These results covered some people up to the age of 90 and with up to 12 years’ worth of tracking.

These improvements were not marginal. Many people included in the stereotypical definition of old are not declining. Over half are not declining mentally.

Interpreting Ageing

We all hold stereotypes. It is part of the way our brain abstracts the multitude of information it receives. We have stereotypes of the citizens of a country or a particular town. We stereotype by race, religion and sex. If those stereotypes acquire negative connotations, we become prejudiced and discriminatory. That can influence something as apparently objective as academic work. Interpreting and generalizing across ageing studies we need to watch out for our own and the researcher’s ageism. Just because the results conform to our prejudices does not mean that they are correct. Just because a study makes it to the mainstream media does not mean it is well researched.

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Within forensic science there is a handwriting problem. Is spidery handwriting on an important document a forgery? Are the hesitations and trembles due to someone getting old. Alternatively because a forger is trying to imitate that signature?

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Studies attempt to identify how writing changes as we get older. Down strokes take longer. Loops and curves in our cursive become less secure. They wobble and tremble. It seems that our writing becomes less automatic. It takes longer. We are more inclined to review what we are doing. We need to visually check what is going on. The pauses change our signiature.

The Ageing of the Hand

Hands suffer from the same age driven changes as the rest of our body. They are however extremely complex “instruments”. To start with there are twenty-nine bones. That means that there are many small joints. There are also three bones found in no other primate. These are in our thumbs and allow them to bend.

We need to add 26 different muscles in each hand. Half are in the hand itself. The rest are in our arms but “operate” the hands. Each muscle in turn must be attached to the bones with tendons. We need 126 ligaments which make bone to bone attachments. We need a nervous system to operate the whole lot and a blood system to give it energy. There are three main nerves in the hand. There are another forty- five nerves which have specific names. We have two main arteries serving the hand. Our skin is extremely sensitive on our hands and we need a sensory system to feed back to the brain.

All of the components age in the same way as their counter parts in the rest of the body. The hands suffer from sarcopenia or the fading of muscle strength (See Newsletter #158 Sarcopnia"). By the age of eighty some people we can lose 50% of their muscle mass. The effect is to make it more difficult for us to pick up things. This is not helped by the fact that our fingernails grow more slowly when we age.

Signals in the nervous system normally travel at 270 miles an hour. It takes time for signals from the hand to reach the brain and it to respond. With age that time increases making “hand-eye” co-ordination more difficult.

At the same time the sensitivity of the skin is declining. The standard tests use two rods as small as a pin head. They are placed next to each other, and we are asked whether we feel one or two rods. They are then moved apart by a small amount and the test repeated. Our fingers are the most sensitive parts of our body. “Two-point discrimination” is less than one millimetre for the fingertips of young adults. That is we recognize that there are two rods when they are only 1mm apart. It is about fifteen millimetres for the forehead and thirty-five millimetres for the forearm and back(see Newsletter #028 Out of Touch"). The threshold increases by 1% per year between the ages of 20 and 80. It can accelerate after that. We need bigger keys, spaced further apart on smartphones and keypads.

The other parts of our hands are not spared. Blood flow to the hands declines with age. It is no accident that older people tend to get cold fingers. Reduced blood flow means tendons stiffen and ligaments even more so. Morning stiffness of the hands as we age is common, even without the danger of arthritis

It is hardly surprising that the complex art of handwriting suffers as we age. We may even be tempted to use a keypad!

Reading Health from your hands

We have a fortune teller read the palms of our hands to tell us about the rest of our lives. It turns out that instead we should measure our grip strength. A recent longitudinal study use grip strength as a predictor. It is easy to measure and has been used in many studies. It turned out that grip strength was a better predictor of when you were going to die than any other variable. The hands age along with the rest of your body. Grip strength is a reasonable measure of that ageing and hence is a good predictor. There is no indication that it is causal. Sorry, increasing your grip strength alone will not make you live longer.

Ageing Hands can be Improved.

Yes we should use moisturizer and sunscreen. That will preserve the skin. We can go much further and repair some of the declines. The best examples are stoke sufferers. They often lose some of the functionality in one of their hands. They are able to repair a lot through exercise. It was not a quick solution and requires support. The exercises were simple but boring! Progress is slow but over months the muscles , nerves, tendons and ligaments can be retaught. There are many general exercise programs for hands, wrists, strength and flexibility. They cannot stop ageing but they can slow the onslaught.

I would like to say that the decline in my handwriting is only down to ageing. Unfortunately it is more likely to be due to our old friend: “use it or lose it”.

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We increasingly see classrooms full of PC’s and iPads. Students taking their notes on a keyboard. When I was trying to revise for examinations I used to write out what I was trying to put into my brain. I still use cursive or joined up writing. It seems that I may have been correct.

Different Modes of Note Taking

Within higher education there has been a debate about the value of using PC’s and iPads in class to take notes. The bulk of the arguments were about the way PC’s distracted students. They would try to multi-task and be surfing the web or using their social media. Studies are now asking a more basic question. We want to learn and encode information to our memories. Which is better- using a keyboard or making handwritten notes? These studies have encompassed young children learning to read all the way to undergraduate students.

A University Classroom Study.

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Students were asked to watch five TED talks on subjects with which they were not familiar. They were told to take notes as they normally would in class. They were pre-selected so that half would normally use a pencil and paper and half a keyboard. After a distraction task, taking half an hour, they were tested. They were asked to recall both factual information and conceptual ideas. Typical questions might be;

Factual: “Approximately how many years did the Indus civilization last”

Conceptual: “How do Japan and Sweden differ in their approaches to inequality in their societies?”

The first finding was in the nature of the notes taken. Most people using a keyboard took a transcript of the presentation. They captured the majority of the words. Note takers with a pen synthesized the ideas and took far fewer notes. The test was repeated asking students with keyboards not to take verbatim tests. The vast majority could not stop themselves.

The results in terms of capturing the talks were different. Both groups scored similarly on the factual information. The Pen and Paper note takers recalled the conceptual ideas within the papers far better.

Some would argue that the keyboard method would allow for the revisiting of the information. This was tested. Another group of students performed the same tasks. They were told they would be retested in a week. Prior to that retest half of each group were allowed to revisit their notes. The results came out virtually the same. Verbatim notes even when reread did not help. The students could not outperform their note taking colleagues on conceptual questions.

In the early learning setting children who learned to read and write with cursive handwriting did better. They scored higher on their learning and memory of the words and letters they were being taught. There was something in the way that handwritten notes worked compared to using a keyboard and screen. That is why New Jersey and other states are re-introducing cursive writing, which was dropped from most curricula in 2010.

Brain Scans

Handwriting is more challenging and stimulating to the brain than is typing. Children find it harder for a reason. Scanning people’s brains can give an insight. It seems that typing activates very different parts of the brain. More than that, typing activates less of the brain. Cursive handwriting requires us to integrate visual and tactile feedback. The feel that we get when the pen touches the paper. It requires more than just hand-eye co-ordination. We need to engage fine motor skills. The brain engages the sensorimotor cortex, visual areas, and language centres more extensively. Typing predominantly activates motor regions associated with repetitive finger movements and visual processing. There is less direct engagement of areas associated with memory and language.

Research on the use of an electronic stylus provides an interesting insight. The effect of pen and paper can be reproduced much better if the surface provides feedback. With accentuators within the pad the pen can be made to resist in a way that mimics paper. The brain scans are different. Writing by hand, even with such a stylus, integrates activity from many parts of the brain. This improves attention and increases what is understood and memorized.

The Ageing Brain and Handwriting.

Moments of memory loss are common at all ages. They do seem to increase with age. There are two main theories of why this happens. One argues that the memory “fills up” with age. Older people have more to store and so find it more difficult to add new information to memory. The alternative is that there is a decline during “encoding”. Older people play less attention, especially to things that are less important to them. Information is not committed to memory.

Writing by hand activates more of the brain. It requires the brain to integrate many more operations and parts. It seems it may improve encoding.

Use it or Lose It.

Should then older people make notes on pencil and paper more often? Many things that use to be written are now typed. Few people write letters anymore. Most communication is digital. Smart phones mean that even shopping lists are now typed. There is lots of evidence that the brain deemphasises activities that are not used. We all use technology for cognitive “ offloading”. That means less work for our brain or that we can think of something else. AI will make this even easier. Where do we stop? Is an AI produced synthesis of a Zoom call helping us to understand?

We may stop writing notes and shopping lists. Do we then do Suduko or cross words to keep our brains active? Research suggests that such brain exercises need to be demanding. We need to learn a language or to play a musical instrument. It seems that writing with a paper and pencil does activate the brain. Perhaps we should brush up on our handwriting as we age? Certainly my handwriting could do with work!

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In the First Age we are “young, learning, dependent and maturing”. The Second Age begins when we start work. It is when we become “independent, take responsibility for our own lives and for our families”. Laslett defines the start of the Third Age as “retirement” and “the culmination of life”. It is an era for “personal achievement and fulfilment”. His Fourth Age is characterized by “dependence, decrepitude, and death”. Some authors have extended these three D’s of the Fourth Age to four and included “depression”.

Clearly in his model there are no fixed dates to move from one age to the next. There are huge variations across individuals. The Fourth Age does not start on a particular birthday and is a point on a continuum. Today even retirement is no longer a fixed point. His model however does have advantages. It avoids dividing life based an arbitrary cut of chronological age. Such as sixty-five to seventy-five, seventy-five to eighty-five etc., does.

The model has proved remarkably durable. It uses events in life rather than age. Its echo can be found in modern issues of defining the end of “healthy ageing”.

A Modern Version of the Fourth Age

Governments have wrestled with how to define their version of the Fourth Age. Different approaches have evolved to define its start. Some have used hard medical diagnoses. How many chronic diseases does an individual have and how severe they are? Most governments have turned to individual’s perceptions of their own health. The end of “healthy ageing” is therefore in the mind of the individual. It depends on them and their environment.

In the UK the survey question is:

“Do you have any physical or mental health conditions or illnesses lasting or expected to last for 12 months or more?’

“ Do any of your conditions or illnesses reduce your ability to carry out day-to-day activities?’

The second question has three possible answers: Yes a lot/ yes a little/ not at all. The first two are combined and used as the definition of what is effectively the start of a Fourth Age.

The Postponement of Disability Onset.

The UK measures have been taken since the 1980’s. Since that time life expectancy has moved. In 1980 the most likely age for someone to die was 77. Forty years later that had risen to 87. The good news is that the onset of disability has moved with it. The chart below shows the improvement from 1981 to 2017.

Source: Office of National Statistics.

The survey in 1981 measured what percentage of individuals had poor general health. It also measured the percentage reporting that they had a longstanding disability. The chart represents the difference between those numbers and the results from 2017. Across every age the percentage reporting poor general health were lower. At aged 73 they were 25% lower. Those reporting “Limiting Long Standing Disability” also declined at every age. In both cases the effect is most pronounced up to the age of 75.

Levels of poor general health for women aged 70 years in 2017 were around the same as for those aged 60 years in 1981. Levels of limiting longstanding illness were those of women aged around 64 years. For men, levels of poor general health at age 70 years in 2017 were around the same as for those aged 65 years in 1981. While levels of limiting longstanding illness were similar to those around 57 in 1981. In general women tend to have lower levels of perceived general health. Long term, disability inducing illnesses are about the same.

Remaining Life Expectancy (RLE)

The Fourth Age idea is reflected in the emergence of a new way of setting statutory retirement age. Instead of setting an arbitrary pensionable date it is based on life expectancy. In Denmark the age is set so that the average person will receive 14.5 years of pension. Effectively you receive pension for your fourth age, to cover the period when disability bites.

Researchers in Germany have used RLE as a health predictor. They showed that RLE is a better predictor than chronological age of the onset of many illnesses. This not for all illnesses. The majority however seem to be concentrated in the fourth age. That is irrespective of at what chronological age the fourth age starts. This is in line with the WHO definition of ageing as an incremental accumulation of deficits.

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Older people make financial decisions about investments and pensions. For this they need to have financial literacy. At the same time, they are making decisions about their care, their prescriptions and their health. Over the past two decades there have been a number of studies on financial and health literacy. Each tries to measure literacy declines that come with age.

This is still an emerging field. There is still a debate about these literacy measures. Are they measuring more than underlying cognitive ability. There are standardized scales especially for financial literacy. Studies have been done using large cross-sectional data. Others have tracked individuals over time in longitudinal designs.

What do we know?

Last year an article was published that reported an interesting sample and study. This was a longitudinal study of over 1000 people in the US. The average age at the start of the study was 81. None of the sample were suffering initially from dementia. Those individuals were then tested every year for an average of 6 more years. In some cases, people were tested for a further 10 years.

Literacy is understanding the fundamental concepts needed to make effective decisions. Individuals need to understand the terminology and concepts. Financial Literacy was measured using 23 questions. Eight simply measured numeracy. The other fifteen assessed knowledge of financial terms and concepts. There were nine questions on medical literacy. These assessed the ability to follow doctors’ multiple prescriptions. Knowledge about major health risks and assessing the probability of drug side effects.

At the start of the study the average financial literacy was 79% . Medical literacy was lower at 64%. The average decline was 1% per year in both. There was however huge variability as illustrated by the figure. This left hand side of the chart (A) shows the results for a sample of 100 people from the stidy. The chart on the right (B) shows the same data with a smoothed curve

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Each line represents and individual as they age. It is clear that there are people whose combined financial and medical literacy went up. There are others with steep decline. There are indications that education and affluence slow the decline. There are, however, huge variations which poses problems for policy makers and marketeers.

What is the impact of declines in financial and medical literacy?

Medical and Financial decision-making was tested. The results showed poorer decision making as literacy declined. Detailed cognitive ability assessments were taken as well. These were added to the analysis. The association between literacy score and test performance was reduced. However it still had a significant impact. The literacy measures are tapping into something different. The rate of decline also influenced the resulting test scores. This was in addition to the absolute score.

As part of the study these participants were having their psychological well-being assessed. Their level of literacy and the rate of decline both had a negative impact. Detailed analysis showed the importance of the ability to manage one’s health and money. They are part of the sense of purpose and control. It is not just the perceived absolute ability but the sense of decline that matters.

Longevity Literacy

These respondents are in the last decades of their lives. They will be coping with increasing numbers of chronic illnesses. Physical frailty will be increasing. They still do well. A different large cross-sectional study measured financial literacy across all age groups. Literacy grew and peaked in the mid-fifties. It plateaued and then declined from the age 65-69. By the age of 70-74 the average person still had the same literacy score as someone aged 25-29. This cross-sectional data showed a decline of between 1 and 1.5% per year. All data seems to support the decline and the risks.

One risk is of particular concern. Various organizations have looked at the susceptibility to scams with age. Tests of scam susceptibility were in this study. One of the questions, for example, was whether people would accept a cold call about a financial product. As financial and medical literacy fall the susceptibility to being scammed does increase. Other studies have shown that being scammed can impact health and wellbeing. The large cross-sectional study suggests one possible explanation. They measured financial literacy but also confidence in that ability. Confidence did not decline with age. There is a growing gap between what we can do and what we think we can do.

However, taking control away from anyone is traumatic. Removing control of health and money is as stressful as telling them to stop driving. Self-regulation in driving is well known. People adjust their use of a car to fit their abilities. That requires self-awareness. There is, it seems, less financial and medical literacy self awareness.

Ageing gracefully is about making your own decisions. Even if that is to stop driving or investing. How to make that possible?

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