First to distinguish between senescent and non-senescent mortality

Senescent mortality is the result of biological aging; reflects the types of death that generally increase with age; it can be postponed through medical interventions and lifestyle adjustments, but it cannot be avoided

Non-senescent mortality is unrelated to aging; involves things like accidents and many infections; also called background mortality

“Children and the elderly: Divergent paths for America’s dependents.” Demography, 21(4), 435-457.

- Between 1971 and the early 1980s, the proportion of the population made up of children declined substantially, while the proportion of the population made up of the elderly increased substantially

- A Malthusian argument would suggest that children should now have more resources and the elderly less

- However, Preston argues that exactly the opposite has occurred, and that demographic change has been intimately involved in these developments

Changes in the family

- For many years now, children have relied more on their family for their wellbeing than have the elderly (the elderly rely more on public transfers)

- Increased incentives to divorce (changing labor force participation) and increased willingness to act on those incentives (rise of individualism) have harmed the wellbeing of children

- Elderly have not been as affected by these changes because of their prior disengagement from the conjugal family

Changes in politics

- The elderly make up a huge voting block, whereas children are not allowed to vote

- Moreover, many working age adults vote on behalf of their future elderly selves, and not on behalf of children

- As a result, public expenditures for the elderly have increased dramatically, whereas those for children have declined

- The incidence of poverty among children under 14 in 1970 was 37% less than among the elderly; in 1982 it was 56% greater than among the elderly

 Changes in industry

- The quality of our education system has deteriorated

- Education majors do not tend to be the best students, and teachers who remain in education are even worse than the average education student

- Preston argues that decreasing school enrollment has led to a drop in teachers’ salaries, which has caused even more negative selection among teachers

- In contrast, medical school is very competitive and investments in medicine are on the rise

- Preston concludes by noting that unlike expenditures on the elderly, expenditures on children are an investment in our common future

- Rather than urging families to take more responsibility for their children, public expenditures should play a bigger role

Etimate that combined sex life expectancy in the US would equal 86.1 in 2065, whereas official estimates suggested it would equal 80.7

Aging experts

view successful aging as the confluence of 3 factors:

1) decreasing the risk of diseases and disease-related disability,

2) maintaining physical and mental functioning, and

3) being actively engaged with life

“Demographic conditions responsible for population aging.” Demography, 26(4), 691-704.

Objective of article is to shed light on the sources of population aging by developing and applying 2 expressions that the relate the rate of change in the mean age of the population to other demographic processes

- The stable population model tells us that population aging cannot be attributed to high or low levels of fertility or mortality, because whatever these levels are, as long as they have been in place long enough (typically 2 or 3 generations) the proportionate age structure of the population will be fixed

- One way to express population aging is in terms of birth and death rates and the current mean ages of people living and dying

- Immigration and emigration can affect the mean age of the population by pulling it up or down

- Comparing the factors responsible for population aging in the US and Japan reveals that Japan’s rate of aging in 1970-1980 is substantially larger than the US’s due to Japan’s lower death rates and the US’s higher rates of immigration

- Population aging can also be expressed as a function of age-specific growth rates

Aging populations are nothing more than ones in which growth rates are higher at older ages than at younger ages

The derivative of the mean age of the population equals the covariance between age and the age specific growth rate

- How much age-specific growth rates for each age interval contribute to the overall change in the mean age in the population depends upon the proportion of the population at a given age (interval) and the distance between that age and the current mean age of the population

- Authors find that about 2/3 of the increase in the mean age of the US population between 1980-1985 was due to mortality decline at older ages and the rest was due to a decline in birth rates

- Because age-specific growth rates are a function of the history of change in births, mortality, and migration, these two expressions actually reflect the same information

In sum, we can conclude that populations are aging when their birth rates and death rates are sufficiently low that a positive correlation exists between age and age-specific growth rates

“Death and taxes: Longer life, consumption, and Social Security.” Demography, 34(1), 67-81.

Paper examines the influence of mortality decline on the long run finances of the Social Security system (excluding Medicare)

- Estimate the adjustments that must be made to an individual’s present level of consumption or labor earning to provide for the additional years of life gained through reductions in mortality

- Review of how mortality decline affects the age distribution of the population

- The age distribution of a stable population depends on the population growth rate and on the shape of the survival schedule

- Changes in fertility only affect the growth rate of the population

- In contrast, changes in mortality affect both the growth rate the survival schedule

- For instance, declines in mortality cause more people to reach reproductive age and have more births, thereby lowering the mean age of the population, and they cause more people to survive to older ages, thereby raising the mean age of the population

- In countries that already have low mortality at younger ages, like the US, the second effect predominates, making populations older

- Official SSA forecasts of mortality declines tend to be much smaller than those indicated by recent trends

- Rates of decline among the oldest-old have been accelerating quite rapidly

- In another paper, Lee and Carter (1992) estimated that combined sex life expectancy in the US would equal 86.1 in 2065, whereas official estimates suggested it would equal 80.7

- Uncertainty about the future course of mortality entails uncertainty about the future financial adequacy of Social Security

- Gains in life expectancy at older ages (a period of leisure and consumption) require that consumption be reduced or labor supply be increased to fund these extra years

- Authors estimate that each additional year of life expectancy entails a 3.6% increase in payroll tax rate or a 3.6% reduction in benefits

- Authors propose that generations that are predicted to benefit from these gains in life expectancy should be the ones to pay the extra cost

“The future of human longevity: A demographer’s perspective.” Science, 280, 395-397.

- The future of human longevity poses questions for public policy and fiscal planning

- Demographers typically extrapolate future mortality levels from past trends

- Wilmoth generally believes that extrapolation is a sound method for predicting future mortality because. . .

a. Mortality decline is drive by a widespread, perhaps universal, desire for a longer, healthier life

b. Historical data shows that mortality has been steadily decreasing for at least 100 years in developed societies

c. Gains in longevity have been shown to result from a wide array of changes, including standards of living, public health, hygiene, and medical care

d. Much of these gains can be attributed to the directed actions of individuals and institutions, whose efforts to improve healthy will continue in the future

- However, Wilmoth also recognizes that a number of errors may result from extrapolation

- One common error of extrapolation is to predict mortality farther into the future than is warranted given the length of time that forms the basis of the extrapolation

- A second common is undue emphasis on recent trends in life expectancy

- In recent decades, increases in life expectancy have slowed while decreases in death rates have increased

- These two trends are not contradictory because they reflect changes in the age patterns of mortality risks

- Reducing death rates at young ages contributes more to increases in life expectancy than reducing death rates at older ages

- Causes for optimism about the future of human longevity include acceleration of mortality decline among the elderly in recent decades, the unusual longevity of certain groups (such as Mormons) that may hint at particular beneficial lifestyle practices, and occasional technological breakthroughs

- However, we must remember that medical breakthroughs have occurred in the past (think Koch’s isolation of the bacteria that causes TB), and that extrapolation from past trends implicitly assume a continuation of scientific advancements

- Causes for pessimism about the future of human longevity include the potential biological limits of human life

- However, trends in death rates at very old ages show no sign of approach a finite limit

- Although extrapolation could not have predicted the rise in mortality in the 1990s in former Society countries or the emergence of AIDS, this is less an indictment of extrapolation than a demonstration of the great social and political uncertainties affecting future mortality trends

- The human population is projected to reach 9 billion by 2050

- This will be accompanied by downward growth in Europe and Japan

- Nearly all future growth is expected to occur in less developed regions (Africa, Asia, and Latin America)

- The world population is also expected to age dramatically

- Factors influencing population growth include fertility, mortality, migration, and population momentum

- Over half of the expected population growth by 2050 is attributable to the momentum inherent in the young age structure found in the developing world

3 steps to population projections using the cohort-component method

1) Collection of baseline data to determine the current size of the population,

2) projection of component rates (fertility, mortality, and migration by age), and

3) calculation of population projections

Issues with this method

- Difficult to predict future trends in vital rates

- Feedback from population size to vital rates not considered

    - For instance, environmental constraints may lead to changes in the birth and death rates

- The role of social policy is difficult to consider

- No probabilities associated with high, medium, and low variants of population projection developed by the UN

AT 65+ men are more likely than women to live with a spouse.

41% of men and 72% of women live with a spouse

Women are more likely than men to live along

17% of men and 40% of women live alone.

conclude that life expectancy has been increasing with surprising linearity over the past 150 years.

Predict that LE will continue to rise with surprising linearity.

State that experts repeatedly declare we are reaching a ceiling but this finding is consistently been wrong.

“Population aging and the rising cost of public pensions.” Population and Development Review, 30(1), 1-23.

Objective of study was the demonstrate that current trends in public pension expenditures are unsustainable and to calculate sensitivities to policy options

- Uses the pensioner-worker ratio (PWR) and the pensioner-expenditure ratio (PER) to assess dependency burden

- The pensioner-expenditure ratio is a function of the benefit ratio (average public pension divided by average earnings), the old-age dependency ratio (number of ppl aged 65+ divided by population aged 15-64), the pensioner-ratio (population receiving pension divided by population aged 65+), and the employment-ratio (number employed divided by population aged 15-64)

- The pensioner-expenditure ratio reflects the total amount of annual spending on public pensions divided by the total pre-tax earnings of workers

- Projections indicate that the pensioner-worker ratio will increase substantially in most Western countries by 2050

- Italy projected to have a ratio of 1.55

Bongaarts proposes 4 potential policy options to reduce public pension expenditures

1. Counteract population aging through increased fertility/immigration

2. Increase labor force participation among those aged 15-64

3. Raise the age of retirement

4. Reduce public pension benefits

“Global aging: The challenge of success.” Population Bulletin, 60(1).

Overview of the social and economic implications of the world’s aging population

Some key facts

- People usually associated the growth of older populations with developed countries; however 60% of the world’s older population now live in less developed countries

- In 2004, Italy had the largest percentage of people 65+ (19.1%) followed by Japan (19.0%), Greece (18.6%), and Germany (18.3%); US ranks 38^th, with 12.4% of its population age 65+

- The elderly support ratio is not necessarily a good measure of those who need financial assistance, because it doesn’t reflect only economically active people in the denominator or exclude economically active people from the numerator

-If these factors were taken into account, the alternative elderly support ratios would be even higher in most industrialized nations (Japan is one exception)

- Declines in fertility is number one reason for population aging

- Declines in fertility have been incredibly rapid in developing countries (aging proceeded much more gradually in developed countries)

- For example, sudden drop in fertility is expected to cause rapid aging in China; the number of Chinese aged 65+ is expected to swell from 88 million in 2000 to 199 million in 2025 and 349 million in 2050

- The demographic transition has not proceeded smoothly in Sub-Saharan Africa due high prevalence of AIDS

- HIV/AIDS has thrust older people into the role of primary providers for children

- Within countries, the elderly tend to be more concentrated in rural areas as the young move to cities

- The compression of morbidity refers to the hypothesis that as life expectancy rises, so too will the average age of the onset of chronic illness (phrase first used by Fries in the 1980s)

- This appears to be what is happening, at least in the US

- Older married people tend to be healthier and more financially secure than unmarried

- Male widows are more likely than female widows to lose most of their support system after their spouse dies

- Increasing trends toward childlessness will affect the availability of old age support

- Increasing life expectancy implies increasing contact across generations

- Debate over whether or not the family is “declining”

- Living arrangements among the elderly have changed dramatically in recent decades

- For example, in Japan in 1960 87% of elderly lived with their child and 4% lived alone; in 2010, 42% are expected to live with their child at 13% are expected to live alone

- Wealthier countries tend to have much lower labor participation rates among the elderly than do poorer countries

- Aging experts John Rowe and Robert Kahn view successful aging as the confluence of 3 factors: 1) decreasing the risk of diseases and disease-related disability, 2) maintaining physical and mental functioning, and 3) being actively engaged with life

- Currently in OECD countries poverty rates living standards among the elderly is quite good; in 1960 one-third of all older US citizens were below the poverty line, whereas by the mid-1990s, only 10% were below poverty (lower than the rate for children)

“Long-term trends in life expectancy and active life expectancy in the US.” Population and Development Review, 32(1), 81-105.

Increasing life expectancy and the dramatic growth of the US elderly and oldest-old populations have implications of federal health policy—specifically for the Old Age Insurance, Medicare, and Medicaid

- Authors use multiple data sources to produce estimates of life expectancy and active life expectancy at various dates from 1935-2080 to identify the burden assumed by Social Security and its relation to Medicare and Medicaid

- Use Sullivan method of the proportion of people without disability at a given age to estimate active life expectancy with cross-sectional data

Results

- From 1935-1982 (institution of Social Security and year at which change in age necessary to receive benefits occurred) life expectancy and active life expectancy grew at about the same rate

- Between 1982 and 1999, ALE grew much faster than LE

- The ratio of ALE/LE at ages 85+ in 1935 was 23.3%, whereas in 1999 it was 63.0%

- A 65 year old in 1999 could expect to live 13.9 more years in an economically and socially productive state

- Active life expectancy at age 65 in 2022 is projected to be 16.4 years, and it 2080 it is projected to be 20.8 years

- In light of these findings, the authors recommend raising the age at which people start receiving Social Security benefits  (suggest age should be set at 72.0 years by 2022)

- This would still provide an average of 8.8 years of Social Security benefits to persons in an active state (the same as when SS was first introduced in 1935)

- Authors also recommend lowering the age requirement for Medicare so more people can stay healthy enough to remain economically productive in old age

- However, one factor that may throw a wrench in these projections is obesity

- Previous research has yielded mixed resulted regarding the magnitude of the effects of obesity on LE and ALE

Aging in Subsahara Africa

63% of people aged 60+ live in LDC. 

In 25 years, 73% of people aged 60+ willl be in LCD

The probation of old to youngers in LDC is still small, but it's growing faster than in MDC. 

Those 80+ are increasing faster

60+ of population:

                                         2005             2030

Europe                               20.7%           30.6%

N. America                         16.9%           25.4%

Oceania                             14.4%           21.6%

Asia                                   9.4%            17.5%

L. American and Carribean  6.9%            16.8%

Near East/ N. Africa            6.8%            12.4%

Sub-Saharan Africa            4.7%            5.5%

- tempo effects in mortality- Cohort mortality is different from life-table period mortality.  The expectation of life someone would live now is not much beyond the cohort.

“Chronic conditions and the decline in late-life disability.” Demography, 44(3), 459-477.

- Recent evidence suggests that the prevalence of late-life disability has been declining

- Objective of paper is to determine the extent to which declines in late-life disability are due to declines in the prevalence of chronic conditions that cause disability versus declines in the risk of disability among those that have these conditions

- Measured disability by looking at the Activities of Daily Living (ADLs) and the Instrumental Activities of Daily Living (IADLs)

General trends

- Find that between 1997 and 2004, the percentage of Americans living with disability declined by about 11%

- Prevalence of many of the potentially debilitating conditions increased significantly

- Cancer, heart and circulatory conditions, diabetes, obesity, and arthritis all increased

- Only severe mental distress and visual impairments decreased

- The probability of disability given a chronic condition was lower in 2004 than in 1997

Decomposition of these trends

- Declines in heart and circulatory conditions as causes of disability were the largest contributors to the disability decline

- Expanding medical and rehabilitative treatments have limited the amount of disability resulting from these conditions

- Declines in overall prevalence of sensory impairments were next

- Increases in the prevalence of obesity contributed to increases in reported disability

- The gender gap in disability declined over this period; women were experiencing less disability relative to men

 - This could perhaps reflect increases in women’s ses relative to men’s

- Education had a mixed effect on disability

- Increased proportion of elderly with more than a high school education contributed to decreased disability

- However, the disadvantage of having less than a high school education increased over this period, which caused overall shifts in education to push disability upward over this period

“The exceptionally high life expectancy of Costa Rican nonagenarians.” Demography, 45(3), 673-691.

 2 major hypotheses exist for why mortality rates are declining and the death rates of the oldest-old are decelerating

1. The heterogeneity in frailty hypothesis suggests that frail people die off when conditions are harsh at younger ages, leaving only the hearty among the oldest old

- Past improvements in health conditions at early ages may be benefiting today’s elderly

2. The heterogeneity in frailty hypothesis suggests that poor conditions early in life may strengthen a cohort at older ages

- Absence of accurate data about old-age mortality in low-income populations has been a major obstacle to examining this hypothesis

- Author hopes to shed some light on this theory using data from Costa Rica

- Costa Rica has notoriously good vital statistics and exceptionally high old-age longevity

Results

- Costa Rica does have significantly higher life expectancy at age 90 than low-income countries

- A comparison with the US and Sweden suggests that this advantage is mostly due to lower cardiovascular disease mortality among Costa Ricans

- Costa Ricans also have much lower prevalence of obesity

- Government emphasis on health care may also contribute to advantage

- The Costa Rican advantage (compared to high-income countries) is particularly large for males, although male life expectancy at age 90 is still 0.3 years less than that of females

- Although this analysis cannot really get at why these patterns occur, author suspects it may be due to a heterogeneity of frailty effect, in light of the fact that this cohort of individuals survived exceptionally high infant mortality rates due to infectious diseases

- If this is the case, the exceptional longevity of Costa Ricans may decline as new, less hearty cohorts age

 “Trends in senescent life expectancy.” Population Studies, 63(3), 203-213.

 Mortality can be divided into two components

Senescent mortality is the result of biological aging; reflects the types of death that generally increase with age; it can be postponed through medical interventions and lifestyle adjustments, but it cannot be avoided

 Non-senescent mortality is unrelated to aging; involves things like accidents and many infections; also called background mortality

Makeham was the first to distinguish between these two types of mortality in the 1860s

- Bongaarts first estimates trends in senescent and background mortality

- Senescent life expectancy rose at an average rate of 1.54 years per decade between 1960 and 2000

- Overall life expectancy has been converging on senescent life expectancy due to large declines in non-senescent mortality

- Future improvements in life expectancy at birth will come largely from continuing declines in senescent mortality, as declines in non-senescent mortality appear to have largely run their course

compression of mortality

rectangular shape of survival curve. declining variance in the time of death

(Wilmoth and Horiuchi 1999-  argues that the rectangularization of mortality while a historical phenomena hasn't occurre)

Lee 2008

Lee and Carter 1992

predict life expectancy will continue to rise indefinitely

forecast had more of a slow down in LE grow

(while Vaupel and Oeppen have surprising linearity)

find clear break with continued expanding LE in the french revolution

The well-known Oeppen–Vaupel straight line of maximum female life expectancies showed that the highest life expectancy observed in a given year increased linearly from 1840 to 2000. Their analysis fueled major controversy, especially when used to extrapolate future improvements in life expectancy at the same pace. We improve on the empirical analysis by enriching the dataset, expanding the period to 1750–2005, and considering both maximum life expectancy at birth and lowest age-specific survival rates. It clearly appears that the original Oeppen–Vaupel straight line must be divided into several segments characterized by different slopes and that each segment corresponds to a major advance in the health transition. There is room to push life expectancy higher, but unless some new breakthrough increases the human life span, progress will very likely decelerate as mortality reduction affects individuals at older and older ages. The main key to the future lies not in knowing whether the observed straight line can be extrapolated but in anticipating the next major health improvement that will lead to an additional increase in life expectancy.