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Record W2112297334 · doi:10.1093/ije/31.4.750

Misconceptions and misapprehensions about population ageing

2002· article· en· W2112297334 on OpenAlexaffabout
Ellen M. Gee

Bibliographic record

VenueInternational Journal of Epidemiology · 2002
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPopulation ageingWelfare statePopulationCitizenshipPolitical scienceSocial policyLiberalismPublic healthEconomic growthDevelopment economicsSociologyMedicineLawDemographyEconomicsPolitics

Abstract

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The last decade has seen the emergence of neo-liberal policies and agendas, and a parallel dismantling of the public provision of health and social services and programmes in most western countries. This neo-liberalism represents an endorsement of, or at the very least an accommodation to, the primacy of the individual and his/her efforts to ensure his/her own well-being, and a corresponding de-emphasis of conceptualizations of, and commitments to, shared risk, rights of citizenship, and the common good. Population ageing has played a fundamental role in this transition; the public costs of population ageing—particularly regarding health care and pensions—are purported to be unsustainable without considerable welfare state ‘reform’. Reform is of course a process, and it has taken differing shapes in various western countries. I focus on North America, and particularly Canada, examining the links between reform and (mis)perceptions about population ageing, concentrating on the latter. In the last few years, three monographs highlighting the fallacies of current, taken-for-granted understandings of population ageing have appeared: Demography is not Destiny,1 published in the US; the Canadian-based The Overselling of Population Aging: Apocalyptic Demography, Intergenerational Challenges, and Social Policy,2 and The Imaginary Time Bomb: Why an Ageing Population is not a Social Problem3 from the UK. These monographs were preceded by a few journal articles with the same theme.4–8 While the still dim voices of these demographers and gerontologists are beginning to be heard, more people have to pay attention. This paper seeks to deconstruct the misperception that population ageing is necessarily the social crisis/social problem that it is commonly believed to be; this will be done by illuminating untested and sometimes clearly wrong assumptions. This misperception contains (at least) four interrelated components that will be dealt with separately for the purposes of analysis. As a preface, it is useful to recognize the historical precedence for demographic scapegoating in the 20th century, i.e. the blaming of social ills/problems on demographic phenomena. As I have discussed elsewhere,9 two examples provide evidence of earlier demographic alarmism. One example is the eugenics movement that focussed on reproductive control as a way to preserve and improve the White race. In Canada, attempts were made to lower the fertility of non-Whites and less socially-desirable Whites (eastern Europeans, for the most part) in the early part of the 20th century; the most egregious being the forced sterilization of people deemed to be ‘unfit’, a highly disproportionate number of whom were of Aboriginal origins.10 Coupled with negative views about the higher fertility of the non-Anglo origin population were concerns about the unsuitability of immigrants of non-western European origins, concerns that culminated in the passing of the Oriental Exclusion Act in the 1920s (similar legislation was put into effect in the US at the same time). Thus, as North America was wrought with the social and economic changes associated with industrialization and modernization, fertility and migration (two key demographic processes) were being used in an attempt to preserve an earlier version of society. A second example of demographic alarmism is the formulation of the ‘population bomb’ in the decades following World War II. While it is true that population grew rapidly in the South at this time, it was the North that defined this growth as a ‘bomb’—a crisis of huge proportions. A massive infusion of western (largely US) money was put into the birth control movement, based on the simplistic notion that technology (i.e. methods of birth control) would lower the number of children that southern women would have and on the assumption that lowered rates of population growth would stimulate economic growth. The birth control movement failed, in the sense that fertility was not significantly lowered; I remember hearing John Rockefeller—one of its major leaders—declare its failure in a very crowded and tension-filled auditorium at the 1974 World Population Meeting in Bucharest. However, when one recognizes that the US political motivation behind birth control expenditures in the South was the exertion of western influence on uncommitted countries of the Third World that could have been attracted to Soviet development models, the birth control movement did succeed on one level. These examples may seem far from the topic of population ageing, but they are instructive in showing that demography can be, and has been, used to reconstruct and redefine social problems in ways that fit a political agenda or, at the least, that calibrate with current and popular ideological positions. One reason for this is that demographic phenomenon and projections are viewed as having a ‘scientific’ certainty that is not subject to question. Demographic crisis thinking depends on the acceptance of demographic projections. While no one is challenging that western (and other) populations are ageing (i.e. that the proportion of their populations aged 65 and over is increasing), demographic projections about the numbers and percentages of future elderly are based on assumptions about fertility, mortality, and net migration levels in the future. Assumptions are only assumptions, and many times in the past the assumptions built into demographic projections have proven to be off the mark. Similarly, there are uncertainties about future levels of mortality, fertility, and net migration. Mortality may not improve as much as projections assume, based on: trends in new and emerging diseases (e.g. HIV/AIDS); re-emerging infectious diseases (e.g. a few decades ago, we thought that smallpox had been eradicated, and that tuberculosis had been eliminated, at least in the west) and now we face the real possibility of bio-terrorism, as attested by the anthrax deaths in the US in the months after the September 11th assault; the appearance of more and more antibiotic-resistant bacterial strains and the possibility that changes in the natural environment (even slight changes in temperature caused by, say, air pollution) can alter the relationships among microbes, hosts, and intermediate vectors, setting the stage for the development of new microbes or for an unexpected epidemic. On the other side of the coin, advances in genetic engineering/ molecular biology may lead to significant improvements in mortality.11 Future fertility levels are especially hard to predict, since fertility is subject to a complex interaction of forces. Projections tend to assume that fertility in the west will stay fairly close to its current low levels; however, any number of changes could alter fertility. For example, the introduction of truly family-friendly policies in the workplace, changes in laws affecting access to abortion, and a trend toward nationalism/patriotism—more likely after September 11th—could significantly increase fertility. Given that fertility is the major determinant of age structure, any substantial increase would delay population ageing. Since net migration does not play a large role in determining national age structures, changes in assumptions about it have a lesser impact. However, if political exigencies result in the west having to absorb large numbers of refugees, the effect would be to ‘young’ the population. Although much less likely, if huge numbers of western youth moved to the South, the effect would be to accelerate population ageing in the west. Since population projections are dependent on the assumptions upon which they are based, three projections—termed high, medium and low variants—are usually calculated by demographers. For example, projections of the size of the American population aged 65 and over in 2040 range from 92 million (high variant) to 59 million (low variant)—a difference of 33 million people. Similarly, projections for the size of the US population aged 85 and over in 2040 range from 20.9 (high variant) to 8.3 (low variant) million people.1 However, these substantial differences are rarely reported, and we are led to believe that there is real certainty about how many older people there will be in the future. Even using medium variant assumptions, different agencies can produce quite different projections. To provide an example, the US Bureau of the Census estimates the population aged 65 and over in 2030 to be 69.3 million while The Urban Institute’s projected figure is 64.3 million. This approximate 5 million discrepancy may not seem very big, but it translates into a difference of 76 billion dollars in Social Security benefits (in 1998 dollars).1 Apocalyptic thinking about population ageing depends on, perhaps more than anything else, the acceptance of dependency ratios as meaningful measures of the economic and social impact of ageing. Dependency ratios measure the ratio of people in so-called dependent ages (arbitrarily defined as 0–15 or 0–18 or 0–20 and ages 65 and over) to people in the working ages of 15 (or 18 or 20) to 64. These dependent age groups can be separated to construct a youth dependency ratio and an aged dependency ratio, with their sum equalling the total dependency ratio. Crisis thinkers focus on the aged dependency ratio, and see a substantial increase over the past decades, and an even greater increase in the decades to come, especially in countries that experienced a significant post-World War II baby boom (such as Canada, the US, and Australia/New Zealand). However, it is important to look at youth and total dependency ratios, and not fixate on the aged dependency ratio only. This is necessary because the youth and aged dependency ratios have counterbalancing effects on the total dependency ratio. Canada provides a particularly good example of these counterbalancing effects. In 1951, the total dependency ratio in Canada was 0.83 (i.e. there were 83 dependents—old and young people—for every 100 people in the working ages).12 In 2041, it is expected to be 0.82 (subject to the provisos of projections). This basically unchanged situation is caused by a large increase in the aged dependency ratio (from 0.14 to 0.46) accompanied by a large decrease in the youth dependency ratio (from 0.69 to 0.36). It is also interesting to note that now (2001)—at approximate midpoint between 1951 and 2041—the overall dependency ratio is at an historical low point (0.62). This knowledge makes it difficult to accept the commonplace view that many of the social problems of the day (such as government debt and deficit, a crumbling health care system) are due to changes in the Canadian age structure, and population ageing in particular. Some may argue that it is misleading to equate youth and aged dependency, seeing as the elderly are bigger users of social programmes. This point has some validity, given that pensions and health care comprise the largest portion of the social envelope. It has been estimated that public expenditures are approximately two to three times higher for the aged than for the young.13,14 However, it is also important to remember that transfers are both public and private; as researchers, we tend to focus on public transfers only, often because of data availability.15 Denton et al.,12 in one of the first attempts to estimate the relative social (public and private) costs of the young and old, conclude that the total social costs of the elderly would have to be three times higher than for the young in order for Canada’s future overall dependency to be higher than what the country has already experienced. Seeing that public costs are two to three times higher for the elderly and that the elderly make economic and social contributions that are not counted in public transfer calculations, it does not appear that Canada faces much of a dependency problem due to population ageing. I have used dependency ratios to counter ‘population ageing as crisis’ thinking because they are the arithmetic tool commonly used to illustrate/forecast the upcoming ageing predicament—in other words, to fight fire with fire. However, dependency ratios themselves are problematic for a number of reasons. First, they make the arbitrary assumption that people below and above a certain age are dependents. There are many in the so-called dependent age groups who are not dependent, such as people who engage in paid labour after the age of 65—a percentage that is bound to increase as mandatory retirement at 65 legislation/ policy begins to fall by the wayside. Similarly, there are people in the ‘working ages’ who are dependent for various reasons. (As an aside, the disability movement may end up moving some of these people into waged labour, which would soften the impact of population ageing.) Second, dependency ratios do not count unwaged labour, and it is well-established that older women do a significant amount of caregiving for their spouses (as do elderly men, but this is statistically rarer). Also, many elderly people do a considerable amount of volunteer activity,16 that is similarly not factored into dependency ratios. Last, Robertson17 suggests that dependency ratios create a false dichotomy—between pepole who are dependent and those who are not—that ignores the relations of interdependence and reciprocity that make up the fabric of social life. Conceptualizing populations in terms of dependent and independent sub-groups has facilitated what is termed the intergenerational equity debate. On the one (and dominant) side are those who argue that the aged are getting more than they deserve from the public purse. Along with some academic research/ writing—such as Samuel Preston’s Presidential Address to the Population Association of America in the early 1980s18 and the work of economists on what is called generational accounting19 —a US political movement (AGE—Americans for Generational Equity) has become quite influential.20 By pitting age groups against one another with regard to public resources, the proponents of generational equity have been an important force in welfare reform that is based in demographic alarmism. Assisting in this process has been the tendency to homogenize people on the basis of age. Too often the aged are viewed as sick and frail non-contributors to society—as ‘users’ of social programmes who give nothing in return. This fallacy has been alluded to above, with countering evidence of the unwaged domestic and volunteer work performed by seniors. Interestingly, this stereotype of the elderly exists side by side with another quite different one—that of older people as ‘greedy geezers’ who are financially well-off and healthy people with leisure-time (especially tourists) taking advantage of social services they can afford to pay for themselves.21 Neither of these stereotypes of the aged are correct; the aged are much more diverse than they allow for. While some elders are well-off, the majority are not, and approximately 10% are poor.1 The poor are disproportionately likely to be unmarried (typically widowed) women.22 While some of the aged are frail, more than 60% have no disability, and disability rates among the American elderly are decreasing steadily.23 When thinking about the future, it is similarly important not to homogenize the elderly. It is expected that the baby boomers will be generally better off financially and healthier than today’s elderly.1 However, we must keep in mind that the baby boomers are a diverse group now, and will continue to be in later life.24 Some of the social policy changes currently being implemented may increase inequality in old age. The move toward pension privatization will favour the baby boomers who we called yuppies, but will disadvantage those without access to private pensions. In Canada, the virtual certainty of the dismantling of universal medical care will differentially affect baby boomers’ access to health care based on income. In an ironic way, then, actions taken based on fear of the costs of population ageing may actually operate to increase the costs of the aged in the future (and/or adversely affect people who have not been able to accumulate resources over their life course). One of the major contributors to demographic crisis thinking regarding population ageing is its fit with common sense notions about the elderly (as an homogenized group). For example, older people are sicker and frailer than younger people—therefore their increasing numbers and percentages will place strain on the health care system; older people rely on pensions —therefore, their increasing numbers and percentages will stress the public retirement income provision system. Here, space allows only for a consideration of ageing and health care utilization. A considerable amount of research, much of it conducted by Robert Evans and his colleagues at the University of British Columbia, shows that population ageing itself will account for only a small part of future health care costs and will require little, if any, increase in public expenditures for health care.25–29 Using administrative data from the province of British Columbia for the period from the mid-1970s to the late 1990s, Evans et al.29 found that: acute care hospitalization use rates fell dramatically, the result of declines in age-specific use rates; the use of physician services increased substantially, resulting from rises in age-specific use rates that are associated with increases in the number of physicians per capita and in billings per physician (especially among specialists); per capita expenditures on prescription drugs (for which there is comprehensive coverage for only certain categories of people in British Columbia, including all those aged 65 and over) rose far faster (over the period since 1985, the only data available) than would be projected on the basis of changes in the age structure, even if one focusses on the elderly population alone. What then has led to increased health costs (that are so often assumed to be the result of an ageing population)? An important component is rapidly rising costs for pharmaceuticals, the result of a combination of inflation and shifts in prescribing more expensive medications without scientific evidence of therapeutic benefit. The pharmaceutical industry is an important cost driver; one to this is the from the cost increases in the and of of new and an of Thus, while it makes that an ageing population to increased health care the least in terms of physician and the of age in affecting health care about the elderly and about population ageing This paper has to deconstruct these which are important because they play a role in current and welfare To all western countries are in the of unsustainable costs caused by the of an older population. this is highly is rarely perhaps because it so with neo-liberal even evidence that population ageing is not particularly for future public costs in the of demographic alarmism. For example, a of Canada estimates that public care costs will increase by per over the period from to of which will be due to population this same of and ageing population the of the health care The of demography to have such that it reason at a future that a social

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.042
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.042
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0090.076
Scholarly communication0.0150.024
Open science0.0050.010
Research integrity0.0130.027
Insufficient payload (model declined to judge)0.0030.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.198
GPT teacher head0.519
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations88
Published2002
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