It’s time to measure 21st century aging with 21st century tools

By Sergei Scherbov, IIASA World Population Program (This post was originally published on The Conversation)

The populations of most countries of the world are aging, prompting a deluge of news stories about slower economic growth, reduced labor force participation, looming pension crises, exploding health care costs and the reduced productivity and cognitive functioning of the elderly.

These stories are dire, in part because the most widely used measure of aging – the old-age dependency ratio, which measures the number of older dependents relative to working-age people – was developed a century ago and implies the consequences of aging will be much worse than they are likely to be. On top of that, this ratio is used in political and economic discussions of topics such as health care costs and the pension burden – things it was not designed to address.

Turning 65 in 2016 doesn’t mean the same thing as hitting 65 in 1916. So instead of relying on the old-age dependency ratio to figure out the impact of aging, we propose using a series of new measures that take changes in life expectancy, labor participation and health spending into account. When you take these new realities into account, the picture looks a lot brighter.

© The U.S. National Archives/Flickr

How facts from the census questionnaire were tabulated into statistics in 1950. © The U.S. National Archives/Flickr

Our tools to measure aging have aged
The most commonly used measure of population aging is the “old-age dependency ratio,” which is the ratio of the number of people 65 years or older to those 20 to 64.

But, since the old-age dependency ratio was introduced in the early 1900s, most countries have experienced a century of rising life expectancy, and further increases are anticipated.

For instance, in 1914, life expectancy at birth in Sweden was 58.2 years (average for both sexes). By 2014, it had risen to 82.2 years. In 1935, when the U.S Social Security Act was signed into law, 65-year-olds were expected to live 12.7 more years, on average. In 2013, 65 year-olds may expect to live 19.5 years more.

But these changes aren’t reflected in the conventional statistics on aging. Nor is the fact that many people don’t just stop working when they turn 65, and that people are staying healthier for longer.

To get a better sense of what population aging really means today, we decided to develop a new set of measures that take these new realities into account to replace the old-age dependency ratio. And instead of one ratio, we created several ratios to evaluate health care costs, labor force participation and pensions.

Who retires at 65 anymore?
One of these new realities is that the number of people working into their late 60’s and beyond is going up. In 1994, 26.8% of American men aged 65-69 participated in the labor force. That figure climbed to 36.1% in 2014 and is forecast to reach 40% by 2024. And the trend is similar for even older men, with 17% of those aged 75-79 expected to still be working in a decade, up from just 10% in 1994.

Clearly, these older people did not get the message that they were supposed to become old-age dependents when they turned 65.

This isn’t unique to the U.S. Rates like these in many countries have been rising. In the U.K., for instance, the labor force participation rate of 65- to 69-year-old men was 24.2% in 2014, and in Israel it was 50.2%, up from 14.8% and 27.4%, respectively, in 2000. In part this is because older people now often have better cognitive functioning than their counterparts who were born a decade earlier.

So, instead of assuming that people work only from ages 20 to 64 and become old-age dependents when they hit 65, we have computed “economic dependency ratios” that take into account observations and forecasts of labor force participation rates. This tells us how many adults not in the labor force there are for every adult in the labor force, giving us a more accurate picture than using 65 as a cutoff point. We used forecasts produced by the International Labor Organization to figure this out.

The old-age dependency ratio in the U.S. is forecast to increase by 61% from 2013 to 2030. But using our economic dependency ratio, the ratio of adults in the labor force to adults not in the labor force increases by just 3% over that period.

Clearly, doom and gloom stories about U.S. workers having to support so many more non-workers in the future may need to be reconsidered.

Is the health care burden going to be so high?
Another reality is that while health care costs will go up with an older population, they won’t rise as much as traditional forecasts estimate.

Instead of assuming that health care costs rise dramatically on people’s 65th birthdays, as the old-age dependency ratio implicitly does, we have produced an indicator that takes into account the fact that most of the health care costs of the elderly are incurred in their last few years of life. Increasing life expectancy means those final few years happen at ever later ages.

In Japan, for example, when the burden of the health care costs of people aged 65 and up on those 20-64 years old is assessed using only the conventional old-age dependency ratio, that burden is forecast to increase 32% from 2013 to 2030. When we compute health care costs based on whether people are in the last few years of their lives, the burden increases only 14%.

Pension ages are going up
The last reality we considered concerns pensions.

In most OECD countries, the age at which someone can begin collecting a full public pension is rising. In a number of countries, such as Sweden, Norway and Italy, pension payouts are now explicitly linked to life expectancy.

In Germany, the full pension age will rise from 65 to 67 in 2029. In the U.S., it used to be 65, is now 66 and will soon rise to 67.

Instead of assuming that everyone receives a full public pension at age 65, which is what the old-age dependency ratio implicitly does, we have computed a more realistic ratio, called the pension cost dependency ratio, that incorporates a general relationship between increases in life expectancy and the pension age. The pension cost dependency ratio shows how fast the burden of paying public pensions is likely to grow.

For instance, in Germany, the old-age dependency ratio is forecast to rise by 49% from 2013 to 2030, but 65-year-old Germans will not be eligible for a full pension in 2030. Our pension cost dependency ratio increases by 26% over the same period. Instead of indicating that younger Germans will have to pay 49% more to support pensioners in 2030 compared to what they paid in 2013, taking planned increases in the full pension age into account, we see that the increase is 26%.

Pranom Chartyothin, a 72-year-old bus conductor, sells and collects bus tickets in downtown Bangkok, Thailand. Photo Credit: Jorge Silva/Reuters, CC BY

Sixty-five just isn’t that old anymore
In addition to this suite of measures focused on particular aspects of population aging, it is also useful to have a general measure of population aging. We call our general measure of population aging the prospective old-age dependency ratio.

People do not suddenly become old-age dependents on their 65th birthdays. From a population perspective, it makes more sense to classify people as being old when they are getting near the end of their lives. Failing to adjust who is categorized as old based on the changing characteristics of people and their longevity can make aging seem faster than it will be.

In our prospective old-age dependency ratio, we define people as old when they are in age groups where the remaining life expectancy is 15 years or less. As life expectancy increases, this threshold of old age increases.

In the U.K., for instance, the conventional old-age dependency ratio is forecast to increase by 33% by 2030. But when we allow the old-age threshold to change with increasing life expectancy, the resulting ratio increases by just 13 percent.

Populations are aging in many countries, but the conventional old-age dependency ratio makes the impact seem worse than it will be. Fortunately, better measures that do not exaggerate the effects of aging are now just a click away.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

What does your walking say about your true age?

By Daniela Weber, research scholar in the IIASA World Population Program.

Did you ever notice that you walk faster than your friends, or are you the one lagging behind? Your walking speed doesn’t only reveal how fast you walk; it can predict survival and the “slowing down process” and – according to a recent study – it can tell how old you are in terms of your physical fitness. If you are highly educated, or work in a non-manual job, you could be up to 15 years younger when it comes to your “walking age”—the age you are supposed to be according to your physical performance.

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Your chronological age does not necessarily reflect your “walking age,” which can be much younger depending on your lifestyle.

For almost all of us, walking is necessary for our everyday lives. For instance, did you know that walking at about 1.1 meters per second (m/s) means that you can cross the street safely in time before the light changes? The decline in walking speed starts around age 60, previous research has found, and a speed of less than 0.6 m/s is associated with substantial impairments to daily life. In my new study, I investigated physical aging and particularly the walking age of older adults in England.

It’s well documented that higher socioeconomic status is positively associated, for older individuals especially, with better physical functioning, such as faster walking. My results confirmed the effects of education, occupation, and regional wealth on physical aging. For instance, a more highly educated 70 year old walked around 0.1 m/s faster at their normal pace than a less educated person of the same age. I noticed a gap of a similar magnitude comparing manual and non-manual workers, with a higher walking speed in those that worked in non-manual jobs.

Interestingly, living in a wealthier region was also associated with higher walking speed, although the difference is only minor. The positive effect of living in a wealthier area might be down to fitness as a result of daily routine. People living in wealthier, urban areas are more likely to walk to the shops or to catch public transport than their counterparts living in rural areas, where people tend to use their cars for shopping or commuting.

What does a difference of for instance 0.1 m/s mean and why is it important? I highlighted the differences by converting them into years of age. In a nutshell, less educated 70-year-olds walked on average at the same pace as more highly educated individuals who were 6.5-9 years older. At higher ages they had lost 2.5 years of walking age, which has been linked to many general health issues. Overall, the advantage of more education, non-manual work, or living in a wealthier region comprises up to 15 walking age years for men and up to 10 years for women. However, the size of the advantage declines with increasing age.

More information: IIASA Research Project: Reassessing aging from a population perspective

Reference
Weber D (2016) Differences in physical aging measured by walking speed: evidence from the English Longitudinal Study of Ageing. BMC Geriatrics, 16(1):31 [December 2016] doi:10.1186/s12877-016-0201-x

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

A futuristic view of farming

Within the next  few decades, the world will need to increase food production to support a growing population also striving for higher shares of animal protein in their nutrition. But food production always affects the environment: Nitrogen runoff from fertilizer has led to major pollution of waterways around the world, while deforestation to extend cropping areas and methane emissions from livestock increase the amount of greenhouse gases in the atmosphere, adding to the problem of climate change.  In order to increase food production, without further increasing nitrogen pollution and greenhouse gas emissions, agricultural systems will need to innovate.

In a recent study, IIASA researcher Wilfried Winiwarter explored the range of solutions for future agriculture, researching current literature for ideas and innovations, and examining their feasibility and potential.

“I call this a science fiction paper,” says Winiwarter. “It’s not about what exists and can be implemented immediately, but about the possible innovations that could conceivably be developed in the long-term.”

The study focused on innovations ranging from seemingly simple behavioral changes to radical technological fixes as discussed in more detail below. It reviewed existing scientific literature, mostly peer-reviewed, including design studies that quantified potential environmental effects of such innovations.Laboratory Plant

Precision Farming
Precision farming refers to technological solutions to improve yields and reduce waste in farming. On the one hand, precision farming can refer to the mechanization of agriculture that may not be environmentally benign, but on the other side, to optimized processes that reduce losses and impacts on the environment.

“Much is already happening,” says Winiwarter. For example, milk production in Europe now occurs mainly in large sheds, with indoor cows, not with free-ranging cows in idyllic meadows. While this industrial approach to agriculture makes food cheaper and more abundant, it also raises questions about animal welfare, and the massive scale of such operations can lead to increased greenhouse gas emissions.

Precision farming can also be used to reduce the amounts of fertilizers or irrigation used, for example, using soil sensors or other high-tech infrastructure to detect exactly what is needed and apply no more than necessary.

Genetic Modification
Genetic modification (GM) of crops allows scientists to equip organisms with certain traits in a much more directed way than traditional breeding. It presents the potential to increase yields, provide drought or pest resistance, or introduce additional nutrients to foods that lack them. GM is already widely used in some crops (mostly to increase pesticide resistance and thus also pesticide application), but in Europe the subject is controversial and GM foods are viewed negatively

Winiwarter notes that the side effects of genetic modification are in general not well understood, and thus possible impacts are quite unpredictable.

Urban Gardening
The study looked into the growing popularity of urban gardening, the “green” trend to grow food in individual gardens inside cities. While urban gardening is generally considered environmentally benign due to small-scale, low transport needs and high personal motivation, Winiwarter notes that it doesn’t have the potential to produce staple food required to feed large populations. One key background study calculated that urban gardens had the potential to produce 10% or less of the food needed in a given city.

“You need space to produce food,” says Winiwarter.

Vertical Farming
As people move to cities and land becomes scarcer, one logical concept is to construct skyscraper “farms” with multiple levels of vegetables growing in hydroponic or aeroponic tanks – like giant, multistory greenhouses. “Compared to an open field, you could produce 200 times as much food on the same space,” explains Winiwarter. “In a city like Vienna, you could conceivably produce all the food for the city within city limits.”

Another advantage of vertical farming is that it could be organized to avoid  waste: whereas fertilizer in a field runs off or percolates through the soil into the water table, a vertical farm would employ nutrient solutions that could be contained and recycled.

However, the sunlight needed for photosynthesis could not so easily be multiplied. Instead, the process would require artificial light, which means enormous amounts of energy – even if efficient LED lighting could be employed.  “The question is where you would get that energy,” he says.

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Cultured meat can now be grown in laboratories – but will it ever make sense on a large scale?

Cultured Meat
Another radical idea for food production is to take meat production off the farm, and instead culture animal cells in petri dishes to grow artificial meat in a laboratory in a nutrient solution. Indeed, the first hamburger from cultured meat was produced in 2013. But Winiwarter notes that meat from the laboratory may not be less resource-intensive than the real thing, since it would need energy, heat, light, and nutrients, which all would make the process extremely expensive, even under ideal conditions. He says, “Upscaling such a process may come with a number of negative surprises – from sanitary issues to pollution as a side-effect of tackling potential health threats. Little is known on the potential environmental effects in a life cycle.”

Dietary Changes
“In general, meat has a higher environmental footprint than a vegetarian diet,” says Winiwarter. “It takes more area to produce feedstock for an animal than it would to produce vegetarian food for humans.”

Europe in particular has a high level of meat consumption, Winiwarter explains, so cutting meat consumption in the region has a large potential. In much of the highly populated areas of Asia, people consume a mostly vegetarian diet. As these countries become richer, increased consumption of meat and milk production is observed when people tend to copy European lifestyle. If Europeans were able to cut down on meat consumption and treat themselves with a more healthy diet, positive environmental effects may even spread to world regions where European food patterns may serve as an example.

Agriculture, like a high-tech industry, will continue to develop dynamically in the future. Many paths of development can be imagined, and have been described in scientific or other literature. “There is no ‘silver bullet’ to resolve the environmental damage of agriculture”, Winiwarter says. Instead, future innovations will need to be carefully monitored and evaluated for potential environmental effects, in order to minimize damage of nitrogen pollution and maintain livelihood on earth.

Reference
Winiwarter W, Leip A, Tuomisto HL, Haastrup P. 2014. A European perspective of innovations towards mitigation of nitrogen-related greenhouse gases. Current Opinion in Environmental Sustainability. http://www.sciencedirect.com/science/article/pii/S1877343514000396

By Katherine Leitzell, IIASA Science Writer

Journey of your life: Demography for the demos

By Samir K.C., IIASA World Population Program

How old are you? This is the most basic demographic question about an individual, and an easy one to answer. What is the population of the world or your country? Well, many who read the news roughly know the number, about seven billion for the world and more than a billion in China and India. But when asked more detailed questions about demography, “What percentage of people are younger than you in the world or your country?” or “What’s the remaining life expectancy for you in your country and the world?” the eyes start rolling. Such questions are important because they lead to better knowledge and awareness about the population, especially the question of life expectancy.

(Photo: UN Photo/Sebastiao Barbosa)

(Photo: UN Photo/Sebastiao Barbosa)

This is why I, with my colleagues Wolfgang Fengler (World Bank), Benedikt Gross (data visualization designer), and many others, have developed a website where people can find out their respective place in the world population or the country population: population.io.  The website was launched last Saturday at the TEDxVienna.

How long will we live? Most of us in the general public do not know the answer.  But demographers and actuaries can actually project the expected date of death for populations, based on factors such as place of residence, age, and sex. Demographers use data on deaths occurring during a period and the population structure to estimate death rates. These death rates are then included in the life table calculations that show, among other details, expected number of years of remaining life given one’s place of residence, age, and sex.

On population.io, you can find your own expected death date, based on population projections and details such as where you were born, where you live, and your sex. Of course, this date is just an average with a distribution. If the remaining life expectancy for a 40-year-old is 30 more years,  that does not mean that all today’s 40-year-olds will die in 2044: roughly half will die earlier and half later. But we hope that exploring this tool will give people some insight into the world and their country’s population and their place within it.

How do we know how long you will live?
To answer this question, we use population projections. To make good population projections, demographers need information about the demographic structure, including current age and sex structure and assumptions about the future scenarios of mortality,  fertility, and migration. A “cohort component” method is then applied to calculate the future population size and structure and to obtain number of births, deaths, and migration. This method projects each cohort born in the same one- or five-year period forward in time, to replace the older cohort occupying the age. In the process some die or migrate out (population decreases) and some migrate in (population increases), while women in reproductive age groups might give birth to children, who will then enter the population as a new cohort. All of these numbers and assumptions are needed for many purposes within and outside the discipline of population studies including for a proper answer to our question, “How long will I live?”

Here’s how the calculations behind population.io work. As an example, I’ll take myself: For a male of my age,  40 years old, on average according to the current global mortality rates, my remaining life expectancy would be about 37 years. This is bit scary for me – that means as an average “global citizen, I would die at age 77. In Nepal, where I am from, my life expectancy would be a little more than one year less. However, since I will most likely live in Austria, my remaining life expectancy increases to 43 years, an increase of 7.4 years due to migration.

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On population.io, you can explore–among lots of other population data–how living in a different country would affect your life expectancy. Click to try it yourself!

Now, if I add that I belong to the highest category in terms of education, what will happen to my life expectancy? Though education is not yet included in the population.io, it turns out that that also depends to a large degree on where I live. In Portugal or Italy, a person with a university degree would have lesser advantage compared to those with lower secondary education or below (2.5 and 2.6 years more respectively) than someone living in Estonia (13.8 years more) or the Czech Republic (12.5 years), Hungary and Bulgaria (12.1 years).

What if I am a smoker? Do not exercise? These factors too play an important role in future life expectancy, and we plan to add them soon to the population.io Web site.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Towards old-age pensions for everyone in Mexico

By Larry Willmore, IIASA Research Scholar

Until recently, all old-age pensions in Mexico were earnings-related, financed with government subsidies and payroll taxes. For this reason only 22% of older Mexicans had pensions in the year 2000. By 2013, thanks to social pensions, coverage had risen to 88%. Social pensions are non-contributory benefits, which do not require a record of employment or contributions to a retirement scheme.

Ilya Frankazoid / Shutterstock.com

An elderly woman sells flowers on the street of San Miguel de Allende, Mexico

In a new paper published by HelpAge International, a London-based charity, I chronicle the rise of social pensions in Mexico, and discuss what remains to be done.

The rise in pension coverage began in 2001, with the introduction of a universal pension for residents of Mexico City (the Federal District) aged 70 and older. The scheme was extremely popular, and the governor, Andrés Manuel López Obrador, left office with high approval ratings. He left to campaign for the presidency, promising to extend universal pensions to the rest of the country. He was the only candidate to support a social pension in the 2006 presidential race. Although the promise of a universal pensions resonated with voters, Mr López lost narrowly to Felipe Calderón, who disliked social pensions in general, and universal pensions in particular.

Despite President Calderón’s opposition to social pensions, members of Congress were able to launch a universal 70 y más pension scheme, providing monthly benefits of MX$500 (US$45) for rural Mexicans aged 70 and over. In January 2012 the unthinkable happened – Calderón in his last year of office extended the 70 y más scheme to urban Mexico. The target population (rural and urban) increased from 2.0 to 3.5 million, even though the program now excluded those with earnings-related pensions, so was no longer universal.

In the meantime, 17 of Mexico’s 31 states had followed Mexico City’s lead by introducing social pensions on their own. The federal entities that introduced social pensions are diverse, and have little in common in terms of health, education, income or coverage by earnings-related pensions. Sub-national schemes also vary significantly in terms of coverage and benefit level. Interestingly, the only two federal entities to introduce universal pensions were, respectively, the most developed (Federal District) and the least developed (Chiapas).

By 2012 social pensions in Mexico had shifted from a marginal political issue supported by a single political party, to one supported by the presidential candidate of each major party. Enrique Peña Nieto promised to lower the age of eligibility from 70 to 65 years. He won the election and, on assuming office, immediately extended social pensions to those aged 65-69 while continuing to exclude recipients of an earnings-related pension.

Mexico has moved quickly from limited to near universal pension coverage, but progress is urgently needed in three areas:

  • Pension coverage is incomplete. Nearly one million older people have no pension. They should be added to the social pension registry as soon as possible.
  • The social pension currently covers only half the cost of food needed for bare subsistence. It should be doubled immediately, to reach the extreme poverty line.
  •  The social pension should be extended to those with an earnings-related pension, restoring the ideal of a universal pension. Without universality, it will be difficult, perhaps impossible, to increase the size of Mexico’s social pension to the extreme poverty line or higher.

Reference
Larry Willmore (2014). Towards universal pension coverage in Mexico. Pension watch briefing no. 13, HelpAge International, May 2014. http://www.helpage.org/download/537ccce61a7b6

 

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.