Which of the following best describes the type of growth in Stage 3 of the demographic transition?

Demographic transitions are changing the health needs of the population. Care for the chronically ill and for people with disabilities is a growing challenge in practically all societies. Long-term care (LTC) includes activities undertaken for persons who are not fully capable of self-care on a long-term basis by informal caregivers (mainly the family) and by formal caregivers. All developed countries have established LTC programs under the auspices of health and welfare services, and many developing countries are in the initial stages of some development. However, there is no single paradigm. The article focuses on critical key issues in the organization and provision of LTC, providing insight for development of care policies.

Future Convergence?

Demographic transition theory assumes convergence, that is, the size and complexity of households decreasing as societies industrialise. This view assumes current heterogeneity in household structures merely reflects different rates of transition. Debates over the extent of convergence relate to different interpretations of cultural or ideational factors on demographic trends, rather than solely economic determinants. Trends in household size and composition in Europe and North America since the mid-nineteenth century are consistent with convergence theory. Nevertheless, differences between broad categories of countries, for example, the Nordic countries compared with Southern Mediterranean countries, are indicative of the impact of distinct political cultures and policy contexts across industrialised nations. There is limited support for convergence in developing countries, and some indication of trends to smaller and predominantly nuclear households.

Demography

Demography is “the study of populations, especially with reference to size and density, fertility, mortality, growth, age distribution, migration, and vital statistics and the interaction of all these with social and economic conditions” (Last, 2001). Demography is based on vital statistics reporting and special surveys of population size and density; it measures trends over time. It includes indices such as fertility, birth, and death rates; rural–urban residential patterns; marriage and divorce rates and migrations; and their interaction with social and economic conditions. Since public health deals with disease as it occurs in the population, the definition of populations and their characteristics is fundamental.

Vital statistics include births; deaths; and population by age, gender, location of residence, marital status, socioeconomic status (SES), and migration. Birth data are derived from mandatory reporting of births and mortality data from compulsory death certificates. Other sources of data include population registries, including marriage/divorce, adoption, emigration, and immigration, residential patterns, as well as census data, economic and labor force statistics, and data from special household surveys conducted by home visits, telephone, or electronic media methods.

A census is a survey covering the entire population of a defined geographic, political, or administrative entity. It is an enumeration of the population, recording the identity of all people in every residence at a specified time. The census provides important information on all members of the household, including age, date of birth, gender, occupation, national origin, marital status, income, relation to head of the household, literacy, education level, and health status (e.g., permanent disabling conditions). The census also covers residents of health and social facilities such as nursing homes or similar care facilities. Other information on the home and its facilities may be included. A census may assign people according to their location at the time of the enumeration (de facto) or to the usual place of residence (de jure). A census tract is the smallest geographic area for which census data are aggregated and published. Data for larger geographic areas (metropolitan/regional statistical areas) are also published. More extensive data may be collected for representative samples of the population. These surveys are carried out over a period of years by a specialized national agency (e.g., Bureau of the Census in the USA and the Central Bureau of Statistics, Office of Population, Censuses and Surveys in the UK).

Census data are published in multiple-volume series with availability for research on computer disks, CD-ROMs, and the Internet. Intercensus surveys are systematically collected information sets, without prior hypothesis, usually by questionnaires with questions carefully composed and tested for validity and consistency (Last, 2007). They may include interviews, biological samples and physical examination. An outstanding example is the US National Health and Nutrition Examination Surveys (NHANES) conducted by the US Center for Health Statistics. These are carried out to determine trends in important economic or demographic data such as individual and family incomes, nutrition, employment, and other social indicators. Such a complex and costly process can never be 100 percent accurate, but great care is taken to maximize response and standardization in interview methods and processing to ensure precision.

Despite its limitations, the census is accepted as the basis of statistical definition of a population. It is well established in developed countries, but is problematic in developing countries where birth and death registration may be inadequate, requiring community-based registration systems. In the Scandinavian countries, population censuses have been replaced by continuously updated databases containing information about all inhabitants, who are assigned a personal identification number at birth or upon immigration.

Demographic transition is a long-term trend of declining birth and death rates, resulting in substantive change in the age distribution of a population. Population age and gender distribution is mainly affected by birth and death rates, as well as other factors such as migration, economics, war, political and social change, famine, or natural disasters. Biodemography, the study of the senescent process, focuses on aspects such as the length of life, the length of healthy life, and the limits to the lifespan. Economic development has a profound effect on population patterns, and demographic transition may be characterized by the following stages:

Traditional – high and balanced birth and death rates.

Transitional – falling death rates and sustained birth rates.

Low stationary – low and balanced birth and death rates.

Graying of the population – increased proportion of elderly people as a result of decreasing birth and death rates, and increasing life expectancy.

Regression – low birth rates, migration, or increasing death rates among young adults due to trauma, acquired immunodeficiency syndrome (AIDS), early cardiovascular disease (CVD) mortality, or war can result in a steady or declining population (i.e., demographic regression).

Fertility, mortality, disease patterns, and migration are the major influences on this transition within the population. The many factors that affect fertility decline and increasing longevity are outlined in Box 3.1. Education of women, urbanization, improved hygiene and preventive care, economic improvement with better living conditions, and declining mortality of infants and children are the major factors. This is an important issue in developing countries where high fertility rates and declining mortality of children contribute to rapid population growth and poverty.

BOX 3.1

Factors in Fertility Decline and Increasing Longevity

Birth rates in the industrialized countries have fallen over the past half-century and are continuing to fall in many countries to levels below rates needed to sustain or maintain population size and age distribution. This contributes to aging of the population, with important economic and societal effects. Economic prosperity, efficient and easily available methods of birth control, and greater education and work opportunities for women in the workforce are major factors in choices made in terms of the number of children a woman wishes to have, and her right to determine the number and spacing of pregnancies. In some countries, access to prenatal diagnosis of the gender of the fetus has resulted in wide-scale abortion of females because of birth policies, with parental preference for male children in China and India as examples. This is resulting in a major numerical deficiency of young women in the population with many attendant social and political effects. Reduced fertility and mortality, as in Japan and many countries in Western Europe, also have many societal and economic consequences, as a smaller workforce has to maintain a higher elderly population dependent on social security benefits.

Health Needs of the Population

Demographic transition posits that with improvements in health, mortality rates start to drop faster than fertility rates. This results in a short-lived increase in family size. Due to the lag between mortality and fertility, population will increase. The sheer increase in the number of individuals in a country increases health needs. However, over time as fertility rates decline the proportion of elderly tends to increase as a percentage of the total population, and this change in population structure affects the need and demand of health-care services. Another factor affecting health needs is the epidemiological transition that countries go through. ‘Epidemiological transition’ refers to the fact that with economic development and declines in fertility rates the disease profile of countries changes from a preponderance of communicable diseases, maternal and perinatal conditions, and nutritional deficiencies to one in which noncommunicable conditions account for a large part of the disease burden. Thus both the demographic and epidemiological transitions affect the health needs and subsequently the health demands of populations, and this in turn has an impact on health expenditures.

In the next 50 years, the share of world population aged 60 or more will double from 10% to 22%, tripling to 30% by 2100. The root causes for this are advances in medical care, improved nutrition, changes in lifestyle, and decreased fertility.

How will this change in demographics affect health expenditures? An article by Alistair Gray of the University of Oxford analyzed data from 13 OECD countries where data were available and concluded that population aging would increase age-related expenditures from under 19% of GDP in 2000 to almost 26% of GDP by 2050 with expenditures on health accounting for half of these increases (Gray, 2005). Other studies conducted with developed country data also support the hypothesis that the demographic structure of a population is a significant variable in explaining health expenditures (Anderson et al., 2003). In a recent study published in Health Affairs the authors project that health spending in the United States is expected to account for 20% of GDP by 2015 and that population aging will account for a “small but rising” share of total health expenditures between 2004 and 2015 (Borger et al., 2006).

In recent years there have been a few studies that have tried to estimate the impact of aging on health expenditures in low- and middle-income countries. Two studies conducted under the Partners for Health Reform Plus (PHRplus) project funded by USAID analyzed this issue in the context of Jordan and the Philippines. The Jordan study modeled expenditures on the elderly under different scenarios of macro-economic growth. The study concluded that whereas the elderly as a percentage of the population were projected to increase from 7% in 2000 to 9% in 2015, their share of total health expenditures was projected to increase from 20.2% in 2000 to 23.2% under the high-growth scenario, to 32.7% under the medium-growth scenario, and to 38% under low-growth assumptions. The study done in the Philippines concluded that the share of health expenditures going to services for the elderly will rise from 19.5% in the year 2000 to 29.5% in the year 2020. In the Philippines most of this increase was due to the aging of the population, but this would not affect the share of health spending going to the young. However, the study concluded that this is likely to change beyond 2020 when significant aging in the Philippines will begin to take place (Mason et al., 2004).

Lifestyles also affect health expenditures. Healthy lifestyles tend to improve health and reduce health expenditures, and unhealthy lifestyles result in poor health and increased health expenditures. A good example of this is to look at how obesity affects health expenditures in the United States. It is estimated that in 1998 overweight and obesity attributable medical expenditures accounted for 9.1% of total health expenditures amounting to $78.5 billion dollars. Medicare and Medicaid financed roughly half these costs (Finkelstein et al., 2003).

Why Was Fertility Transition So Slow to Emerge in Sub-Saharan Africa?

The delay in initiation of fertility transition in sub-Saharan Africa was the subject of considerable speculation, particularly during the 1970 and 1980s (see, e.g., Lesthaeghe, 1989). Several different explanations were set forth, reflecting economic, social, and cultural factors. Before examination of these explanations, we consider a conceptual framework that is useful for examining fertility transition.

Abstract

The Second Demographic Transition (SDT) is a term used to describe dynamic interrelationships between fertility rates, a constellation of innovative demographic behaviors, and changing values in countries characterized by sustained below-replacement fertility. Key demographic changes accompanying the emergence of very low fertility include delayed marriage and childbearing, and substantial increases in cohabitation, nonmarital fertility, childlessness, maternal employment, and divorce. The core shift in values associated with the SDT involves movement away from viewing marriage and childbearing as either unquestioned or obligatory toward a life orientation in which family formation is something purposively chosen for its role in self-actualization.

Development Impacts on Population Growth

While the rate and character of population growth clearly influences development, population growth is also influenced by, and responds to, development in varying ways in different parts of the globe. In demography, the most influential stream of thought about this relationship is known as the demographic transition theory, most often associated with the demographic transition model (DTM). This model was developed based on observed and expected population changes in the Global North, especially Northwest Europe. In both academic and societal debates, however, it is often applied with the assumption that it will eventually be a globally applicable model, with different world-regions being in different stages of the model.

The DTM consists of four stages:

High-level equilibrium: both fertility and mortality are high, resulting in very low population growth and a low life expectancy at birth;

Early expanding phase: fertility remains high while mortality declines, resulting in rising population growth and a rising life expectancy at birth;

Late expanding phase: fertility declines rapidly, while mortality also keeps declining but at a lower rate than in stage 2. Population growth continues, but much is less than in stage 2, and life expectancy at birth keeps rising;

Low-level equilibrium: fertility and mortality reach a new balance, or mortality may even fluctuate above fertility. Fertility reaches a level of two children or less per woman, below the replacement level of 2.1. Population growth slows down and eventually population may even stagnate or decline.

In demographic transition theory, changing fertility and mortality and the demographic transitions caused by these changes are related to economic, technological, medical, social, and cultural changes in (Western) Europe since the 19th Century. Until the 1970s, most demographers considered the shift from high-level to low-level equilibrium between fertility and mortality as one transition. In the 1980s, however, Van de Kaa and Lesthaeghe coined the term “Second Demographic Transition” (SDT), mainly focusing on what was until then considered to be stage 4 of the DTM. They considered low fertility at below-replacement levels as a structural change, beyond what the DTM would predict; a new transition instead of merely the final phase of the first demographic transition. Their explanation for this mainly focused on changes in the social institutions affecting fertility: marriage at later age, the rise of cohabitation without marriage, rising divorce rates, the disconnection between marriage and having children, postponing having children, or not having children at all, etc. These changes were related to processes like changing societal norms regarding relationships and societal processes like secularization, emancipation, and individualization. The combination of below-replacement fertility and rising life expectancy also leads to an aging population. International migration may partly, but by far not fully compensate for this.

While the SDT theory was developed as a departure from the DTM, both DTM and SDT were subject to quite similar critiques. Both may apply well to Europe and some other parts of the Global North, but less or not to most of the Global South. Even within Europe, North America, and several other countries with comparable demographics such as settler colonies of European origin (e.g., Australia, New Zealand, South Africa, and most Latin American countries), considerable variations in demographic trajectories can be found that do not fit well in the DTM. Within such countries there may be considerable unevenness in fertility and mortality between indigenous and (former) settler groups as well as between (former) settler groups of different countries of origin. The DTM expectation that it would eventually be a universal model in which all parts of the world would develop toward a similar “end state” was considered unrealistic. This expectation may apply at least equally, but probably even more, to the SDT, since the societal and cultural changes it is related to may be specifically European, or even Northwest European, and less likely to spread across the globe. Additional critique on the SDT addressed the extent to which it should really be seen as a new demographic regime, rather than merely being a continuation of stage 4 of the DTM.

2.2 Public Financing Overview

The demographic transition in birth and death rates has therefore led to a demographic transition in long-term care. Prior to the demographic transition, long-term care of elderly is always a family responsibility. We observe a profound change in the supply and financing of long-term care as a result of the demographic transition: there is a shift in responsibility from the family to the state. Eventually, all developed countries provide some publicly funded long-term care. There is a shift in financing from self-insurance (each family bears its own responsibility) to some form of social insurance. The supply of long-term care shifts from informal care provided by the extended family to formal care paid for, at least in part, by the government. The responsibility of providing health care, from acute to chronic to terminal care, gradually moves to the public sector. All developed countries provide some form of long-term care insurance, although the details vary widely in the scope of services and the form of financing.

While an exhaustive list of the details of each country's long-term care system is beyond the scope of this chapter, it is instructive to describe some of the different systems to understand the broader social forces. In 1965, the United States began funding nursing home care for poor elderly who were eligible for Medicaid (usually due to means testing), along with deliberately limited funding of postacute care stays in skilled nursing facilities for all Medicare beneficiaries. In Europe, social insurance for long-term care has spread gradually, starting in the Netherlands in 1968 (Schut and van den Berg, 2010). Unlike the United States, in the Netherlands coverage was universal and mandatory. The generous nature of the Dutch system led to a series of cost-savings reforms aimed at regulating use, controlling wages, and restricting choice. The universal German system began in 1994 to replace a system that was means tested (Rothgang, 2010). Despite having a strict definition of dependency and strict benefit caps, the fiscal health of the German system has varied over the years. The Japanese long-term care insurance system began in 2000 in response to political pressure from women who no longer wanted to bear the burden of caring for aging relatives (Hanaoka and Norton, 2008; Ikegami, 2007). Spain passed national long-term care reform in 2007, but implementation of the shared federal and local system has been slow (Costa-Font, 2010). The Czech Republic reformed its long-term care system in 2007, relying on a system of directed cash benefits (Österle, 2010). The French system is more fragmented, with a strong private long-term care insurance market in parallel with government support that is cash targeted toward specific care appropriate for the recipient (Le Bihan and Martin, 2010). The French have not yet gone for the full mandatory social insurance. The English system is means tested and limited to those with high dependency needs (Comas-Herrera et al., 2010). The benefits and eligibility vary widely due to local administration. Italy has a decentralized system, with strong local control of funding and benefit levels (Costa-Font, 2010). The rest of Central and Southeastern Europe, aside from the Czech Republic, has yet to implement strong national long-term care systems (Österle, 2010).

The OECD classifies public long-term care systems by whether benefits are universal, only granted as a safety net, or a mixed system using both. Many Scandinavian and northern European countries have a universal system financed through taxes or social insurance. Many other countries have opted for a mixed system, with some elements available to all and others requiring means testing. At the other end of the spectrum, England and the United States rely on a safety net system limited to those who are poor or who have spent down their assets to become poor. Countries are listed in Table 1 according to this simple system (Chomik and MacLennan, 2014). Within each general system, of course, there are a variety of specific ways to finance the system (the details are beyond the scope of this chapter).

Table 1. OECD classification of public spending on long-term care

From Chomik, R., MacLennan, M., 2014. Aged care in Australia: part I—policy, demand and funding. CEPAR Research Brief 2014/1, fig. 7, p. 12.

Several trends emerge from a review of the long-term care systems in developed countries. First, there are a wide range of solutions to the problem of public provision of long-term care. There is variation in the kinds of providers both across countries and within countries, reflecting local control. Some countries place more responsibility on the individual for financing, while others use some combination of means testing, social insurance, and public funding to provide care. There are differences also in the degree to which risk is pooled across society (as in universal systems) or left to be borne by individuals (Chomik and MacLennan, 2014). The diversity in providers and systems reflects the wide range of demand for different services and the different political and economic systems in the countries. It also may reflect differences in culture and underlying preferences.

Second, governments play a larger role over time in funding long-term care (Österle, 2010). We see this in the pattern of how developed countries eventually develop formal governmental policies about long-term care. Developing countries rely on family for providing long-term care. Families are the de facto insurance program in developing countries for elderly. But after going through a demographic transition, countries eventually implement social insurance for long-term care.

Third, long-term care is hard to fund. As will be discussed later in this chapter, unlike acute care insurance, long-term care insurance has a long time horizon, with uncertainty and benefits stretching as far as the eye can see into the future. Changing demographics and economic fortunes can turn a solvent system insolvent quickly. Therefore, the only constant is reform. All government systems seem to be constantly reforming to strike a balance between cost and quality, universalism and targeted need, and between government standards and local control.

Fourth, the wide variety of providers and insurance coverage also has caused some to refer to these systems as patchwork because no single insurer is responsible for all care and coordination of care. Governments are seeking innovative ways to provide care at low cost. The following subsection discusses a system that is gaining in popularity around the world. It uses a combination of both government funding and family support. Therefore, even with the expanded role of government in long-term care insurance and provision, there is still a strong role for the family. The next main section of this chapter explores the economics of informal care, and how with an aging population the dynamics of informal care affect not only the elderly care recipient but also the middle-aged informal care provider.

Aging trend: ‘growing old before growing rich’

The rapid demographic transition in China, and particularly the dramatic decline in the birth rate, have resulted in an accelerated aging process for China’s population.24 Around 21.4 percent of the world’s elderly people live in China and their numbers are set to rise 3.2 percent annually.25 The age structure of China’s population pyramid is gradually inverting itself as the ‘young population’ morphs into an adult and elderly one.

Despite the current economic development in China, the declining birth rate indicates that the workforce will begin to shrink in the next ten years as the number of retired elderly increases. Consequently, the ratio of non-working to working population will almost double by the middle of the twenty-first century.26 This workforce shortage, caused by a growing number of retirees, is already critical in Shanghai where 20 percent of the city’s population is over the age of 60,27 forcing manufacturing businesses to relocate. Other parts of China are facing similar shortages that could threaten the sustainability of China’s economic growth.28

It must be noted that the present aging problem in China is not due primarily to natural demographic transition but to the implementation of a rigid family planning control system. With the largest population in the world and at the present stage of economic development, it essentially means China will ‘grow old before it grows rich.’29 Therefore to sustain economic growth in an aging but not affluent society, developing the labor market to create more jobs for all age groups is fundamental to any solution.30

China is likely to be saddled with a severely aging population in the early stage of its modernization process before the implementation of an adequate social security and social service system for the elderly.31 The aging problem will not only increase the strain on the country’s finances but also put pressure on socio-economic development as the dependency ratio (i.e. those not in the labor force to those in the labor force) increases.32

2 Stages of the Demographic Transition

The ‘demographic transition’ refers to a sequence of three periods. In the first period, fertility and mortality rates are high and mortality tends to be highly variable, with population growth fluctuating widely about a moderate long run trend of growth or decline. Short run responses in fertility (and mortality) can be attributed to cycles in weather or harvests or possibly to other exogenous variables using time series statistical methods, such as vector-auto-regression.

In the second period, age-specific mortality rates decrease gradually, raising life expectancy at birth from 30–35 years in pre-industrial Europe, to 70–75 today in the high income countries, and from 25–30 years in the low income countries in the 1920s, to levels which today range from about 45–73, excluding countries ravaged by war or the AIDS epidemic. This second period is one of accelerating population growth, which some observers such as Malthus attributed to improved food supplies, and more specifically to nutrition, often initiated by technical progress in agriculture, followed by improved industrial productivity, and advances in transportation and communication (Fogel 1999). A free press capable of publicizing food shortfalls in the twentieth century may have further alleviated excess mortality in the wake of periodic famines. Improvements in private and public health technologies are assigned an important role in reducing mortality, but not much before the start of the twentieth century.

In the third period, the secular decline in fertility begins, after which the number of births per woman falls by more than half, from five or six to about two, in the high income countries, and six to eight to about two or three in most low income countries. When historically high fertility levels have declined by more than 10 percent, they are not expected to rise again on a sustained basis (National Research Council 2000). Medium-term swings in fertility are nonetheless distinguished from time series, occurring in response to business cycles (e.g., the post-World War II baby boom), wars, and economic shocks, as during the transition from centra lly planned to market oriented economies in the 1990s in Eastern Europe and Russia, or recently due to reversals in sub-Saharan Africa.