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1 Introduction

Why care about aging in rural places? Answering this question requires, first, understanding what is meant by population aging and, second, knowing something about people who are aging in rural places. To answer, we organize this chapter into two segments. The first examines the reasons why rural places are aging and why some rural places age faster than others. The second addresses characteristics of rural elders, including their family status and living conditions.

2 Population Aging

“Aging” is a term that is used loosely and in broad contexts to refer to physical, psychological and social change. The physical experience of aging differs from person to person and is largely associated with changes in life-course stages and events that begin at birth and continue throughout life, often including marriage, family formation, divorce, remarriage, retirement or widowhood and changes in residence. Each life-stage transition is itself associated with changes in life-style or health.

Population aging, also known as demographic aging, differs from individual aging in that it refers to the average age of the population in a geographic area—e.g., a country, state, or county. Some populations are quite young; others are much older. Researchers use two summary measures to describe the age of a population: the median age, that is the age at which half of the population is older and half is younger, and the percentage of the population 65 years of age and older.

The Philippines is an example of a country with a young population. As Table 2.1 reports it has a median age of just 22.5 years and only 4.1% of the population 65 years of age and older. On the other hand, Japan is quite old, with a median age of 44.4 and with 21.6% of its population 65 years of age and older (US Census Bureau 2009; US Central Intelligence Agency 2010). The median age and the percentage 65 years of age and older are important measures because they present different portraits of how rapidly an area is aging.

Table 2.1 Age characteristics of comparison countries, 2009
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Figure 2.1 shows that in the United States (US) the percentage of the population 65 years of age and older increased slowly since 1870 and subsequently fairly rapidly between 1920 and 1950. The increase reflects the aging of the native born population and that of a large number of immigrantsFootnote 1 and their children who entered the US between 1870 and the early 1920s. In 1924, US immigration policy changed, effectively cutting off most international immigration so that by 1960 the percentage of the foreign-born population 65 years of age and older had begun to decline, while the total population 65 years of age or older was climbing based on the aging native-born population. Between 1990 and 2000, little or no growth occurred in the percentage 65 years of age and older due to both low immigration and low birth rates between 1929 and 1946. Since 2000 the percentage 65 years of age and older has increased rapidly as the baby boomers, those Americans born between 1946 and 1964, began aging into the 65 and older age group. The median age, reported in Fig. 2.2, on the other hand, decreased between 1950 and 1970 reflecting the large numbers of children born during the baby boom but has increased steadily since then, rising sharply after 2000.

Fig. 2.1
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US percentage of total population 65 years of age and older and percentage of foreign-born population 65 years of age and older, 1870–2008 (Sources: US Census Bureau (2009, 2010))

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Fig. 2.2
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US median age and percentage 65 years of age and older, 1950–2030 (Source: US Census Bureau (1981, 2010))

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Comparing the pattern of change in the median age of the population to that of the percentage age 65 or older, one can see that aging is not a function of increasing life expectancies, although longer life spans do play a part. Rather, the aging of populations is more a result of decreasing birth rates. When birth rates are high relative to the proportion or numbers of elderly then populations become younger. As fewer infants are born, the median age of the population increases as the relative percentage of the population at older ages increases (Poston 2005; Goldstein 2009). Only when birth rates stabilize at low levels does the impact of advancing life expectancy begin to influence population aging (Goldstein 2009). In the case of the US, the post-World War II baby boom provided only a short interruption in the long, slow decline in birth rates and coincided with steady increases in life expectancy (Poston 2005; Goldstein 2009). The result has been population aging.

Influences on societal aging are similar across metropolitan (metro) and nonmetropolitan (nonmetro) populations. However another factor can also produce different patterns in the aging of urban and rural places. In- or out-migration of individuals in different age groups can change the proportion of a population that is very young or of retirement age. The age of a region or country at any point in time reflects both recent and historical interactions between birth rates, life expectancy and migration. Of these, birth rates and migration are generally more important than mortality. All three—birth rates, increased life expectancy and migration—have influenced and will influence the variability in aging between rural and urban places in the US in the twenty-first century.

While there is much concern over the aging of the US population, many other countries with similar post-industrial economies are even older. Post-industrial countries, including nearly all of Western and Eastern Europe, Australia, Japan, and several others, are listed in Table 2.1. Much of the difference between these nations and the US is a function of past birth rates and immigration policies. First, the US has had more lenient immigration policies since the mid-1960s than most other countries. Second, a majority of immigrants are young adults who are more likely to have children or to be planning to have children. The arrival of immigrants helps to keep a country or region young (Parrado 2011). In most cases, new immigrants move to urban places, not to rural ones. Gurak and Kritz (Chap. 18, this volume) discuss the issue of international immigrants in rural places, but we note here that nations that are net receivers of immigrants are also likely to be countries receiving younger persons in their childbearing years.

There are exceptions to this rule, however. Both Canada and Australia are immigrant nations, though both are older than the US. Post-World War II fertility rates help explain why. The end of the war, in 1945, coincided with a baby boom that was particularly pronounced in the US, Australia, and Canada, although the boom in the US was more distinct and of longer duration than elsewhere (Foot 1997; Linteau et al. 1991; Owram 1996; Salt 2004). This surge was not entirely unexpected and occurred in many countries, not just the US. At the end of wars, births usually increase as men return from the front, marry, and start families—events that have been postponed during combat and which are illustrated prominently in Fig. 2.3 by higher fertility rates and number of births following World War I and, more pronouncedly, following World War II. What was unexpected in the US was the persistence of the higher birth rates (National Center for Health Statistics 2010).

Fig. 2.3
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Fertility rates: US 1910–2006 (Sources: Taffel (1977) and Martin et al. (2009))

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3 Nonmetro Areas of the United States Age More Rapidly Than Metro Areas

While the aging of the baby boom means that the US as a whole will age, it does not mean that rural or nonmetro areas will automatically age more rapidly than urban or metro places. Yet nonmetro areas have been aging faster than metro areas in the US since the 1930s and will continue to do so for the foreseeable future (Clifford et al. 1985; Siegel 1993). Three broad trends account for the more rapid graying of the rural population. Two of these were evident throughout the twentieth century—declining birth rates and young adult out-migration from nonmetro areas. The third—the rural turnaround fueled by retirement migration—has been evident since the 1950s (Beale 1975; Johnson 2006).

3.1 Declining Birthrates

Having just discussed the baby boom, it may seem odd to refer to the long-term decline in US fertility rates. Yet as Fig. 2.3 illustrates, the baby boom interrupted, but did not halt, that long-term decline. The downward trend was more dramatic for rural than urban areas because birth rates were historically higher in rural areas but then rural fertility rates declined rapidly. In 1900, fertility rates were about 1.5 times higher in rural than urban places (US Census Bureau 1975, Series B 67–98). By the mid-1970s, fertility rates were the same across urban and rural areas, at replacement level, meaning that just enough children were being born to replace the previous generation (Fuguitt et al. 1991). Fertility rate differentials between metro and nonmetro places varied somewhat over the next several decades, particularly when the age of the mother in metro or nonmetro places was taken into account. Nonmetro mothers tended to have their children at younger ages than metro women so that nonmetro fertility rates for younger women tended to be slightly higher than metro fertility rates, but lower than metro fertility rates for older women (Fuguitt et al. 1991). As a result, in the twenty-first century, most growth or decline in nonmetro places has been and will continue to be determined by migration.

3.2 Rural Out-Migration of Young Adults

At the same time that natural increase, the excess of births over deaths, was the primary engine of population growth throughout the twentieth century, out-migration of young adults was the primary engine for population loss in nonmetro areas by the end of the twentieth century (Johnson 2006; Walser and Anderlik 2005). Throughout most of the twentieth century, nonmetro young adults left nonmetro for metro counties, and there was little or no net migration by young adults in the opposite direction (Johnson 1999; Garasky 2002; Brooks et al. 2010). Age-specific net-migration rates for each decade from 1950 through 1990 show out-migration from nonmetro areas for 20–29-year-olds in all decades (Johnson et al. 2005b). Net out-migration of teens 15–19 years of age also occurred in 1950, 1960, and 1980 (Johnson et al. 2005b).

Prior to about 1935, higher fertility rates in nonmetro areas balanced out-migration from rural places. Since then, net outmigration of youth has continued, and many counties are now experiencing natural decrease—i.e., the population of these counties decreases slightly each year (Johnson 2006). On the other hand, metro areas have had two sources of growth: the first through the in-migration of rural young adults, as well as international immigrants who generally target urban areas as their first place of residence.Footnote 2 Migrating young adults from rural places are in their prime childbearing years, adding to the natural increase in urban places. In addition, immigrants tend to have higher fertility rates than the resident population and are primarily young adults who bring their children and/or child-bearing capacity with them; these children, then, become additional sources of population growth for metro counties.

The effects of the declining birth rates and the out-migration of young adults can be seen with a simple comparison of median ages, or of percentages of persons 65 years of age and older in urban/metro and rural/nonmetro places, as shown in Table 2.2. Regardless of the unit of analysis, or of the measure used, whether rural versus urban or nonmetro versus metro, rural and nonmetro places have higher proportions of the population 65 years of age and older and higher median ages.

Table 2.2 Population age characteristics by US geographic areas, 2005–2009
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3.3 Rural Turnaround

Not all adult migration has targeted metro areas. During the twentieth century, metro counties grew faster than nonmetro counties until 1970. As late as 1969, a major text on urban economics predicted that this trend would continue for the foreseeable future (Thompson 1969). However, in 1973, population estimates for 1970–1973 showed that nonmetro counties were growing faster than metro counties (Beale 1975). At first, many thought that this was a continuation of a long term trend toward suburbanization which had accelerated after World War II with the building of mass produced subdivisions around major urban areas. Further analysis of the data showed that even nonmetro counties not adjacent to metro counties were growing and these trends were termed the “rural turnaround” and the “rural renaissance” (Johnson and Beale 1994). Since that time, researchers have followed the relative growth rates of metro and nonmetro counties closely and have discovered patterns of population growth and decline in rural areas that change based on economic factors, land-use changes and the retirement patterns and preferences of different age cohorts (Johnson 2006).

Specifically, the more rapid growth of nonmetro counties continued throughout the 1970s, slowing toward the end of that decade (Berry 2000). In the 1970s, net migration rates for those 30 years of age and older were higher than for any other age group. Surveys and interviews showed that many were migrating to rural areas for the amenities that rural living offered and were willing to sacrifice some income to achieve that lifestyle (Williams and Sofranko 1979; Jobes 2000; Rudzitis 1999). Specifically, counties with forested areas, lakes, mountains and moderate temperatures grew much faster than those that remained dependent on agriculture (McGranahan 1999).

Persons 55 years of age and older (pre-retirees and retirees) have generally been less likely to move than younger adults. However, the net in-migration rates to nonmetro counties of the older population began in the 1950s and remained higher than that for any other group, acting as a precursor to the rural renaissance. Even when other age groups were moving from nonmetro to metro counties, elders were moving to nonmetro places (Brown and Glasgow 2008; Johnson et al. 2005b).

During the 1980s, the rural turnaround ended. Nonmetro counties grew more slowly than metro counties, and some predicted that the turnaround was a decadal anomaly (Johnson 1989). Between 1980 and 1983 a severe recession (at the time the worst since the Great Depression) caused serious problems in several industrial sectors. The steel and auto industries, primarily located in metro counties in the mid-Atlantic and Northeastern states, declined with increased global competition and the high value of the American dollar. However, nonmetro counties generally experienced problems in all resource-based industries, including timber, fishing, mining and agriculture. Many counties did not begin to recover until 1986 or later (Johnson et al. 2005a). During that decade net out-migration from nonmetro counties occurred for nearly all age groups. A notable exception was for persons between the ages of 60 and 74. While net migration rates of this age group were lower than they had been during the 1970s, they were still positive (Johnson et al. 2005b).

The decade of the 1990s experienced a resurgence of growth for nonmetro counties, with positive net migration rates from all age groups except young adults between 20 and 34 years of age (Johnson et al. 2005b). Net migration rates for 50–74-year-olds were higher than in any of the previous three decades (Johnson et al. 2005b). Nonmetro counties with amenities—both natural (lakes, mountains, forests, oceans) and built (ski resorts, golf courses)—experienced positive net in-migration (McGranahan 1999; Cromartie and Nelson 2009). More important, there was increasing evidence that local entrepreneurship in nonmetro areas helped undergird this growth. But nonmetro counties still tied to resource based industries, especially agriculture, continued to experience net out-migration (Vias and Nelson 2006).

Estimates of county growth and net-migration from 2000 to 2009 once again show that nonmetro counties experienced net out-migration. As Fig. 2.4 shows, metro counties had a net migration rate of 72.03, while the rate was −11.21 for nonmetro counties. Out-migration is not unexpected because this decade experienced two recessionary periods—a short one in 2003, and a much more severe one beginning in 2008. Because nonmetro counties have smaller economies than metro counties, they tend to suffer more during a recession.

Fig. 2.4
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Net migration rate by nonmetropolitan county type, 1990–2009, for the continental 48 states, not by age (Farm, recreation and retirement counties are subsets of nonmetro counties) (Source: US Census Bureau (2010))

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The Economic Research Service (2007) categorizes nonmetro counties into sub-groups, of which three are of particular interest when discussing migration during this period. One subset, farm counties, experienced notable net out-migration. Another subset, recreation counties, had a net migration rate of 36.1. The rate for retirement counties at 82.1 was substantially higher than that for metro counties (Economic Research Service 2007). Retirement counties are nonmetro counties where the number of residents 60 years of age and older grew by 15% or more between 1990 and 2000 due to in-migration (Economic Research Service 2007). Thus retirement areas continued to experience substantial growth through net in-migration even during this decade.

Other research predicts that baby boomers who are just on the cusp of retirement will target nonmetro counties as destination areas (Cromartie and Nelson 2009). Thus, the very large age group about to enter retirement (the first baby boomers turned 65 in 2011) could set up nonmetro counties for another period of growth, especially in the older age groups (Brown and Glasgow 2008; Cromartie and Nelson 2009).

3.4 Two Types of “Old” Counties

Not all “old” US counties are the same. The historical patterns discussed above have produced two types of counties that are aging. Population-loss counties have a high concentration of older adults because of persistent out-migration of young-adults—outmigration that continues even in the twenty-first century. Retirement destination counties are aging as retirees and pre-retirees target them as places to live.

These two types of counties overlap with two types of counties classified by their economic base. Farm and population loss counties generally overlap with one another as do retirement destination and recreation counties. Johnson et al. (2005b) have shown that both farm and recreation counties have experienced the loss of young adults each decade from 1950 to 2000. However, in recreation only counties, the 20–29-year olds were out-migrants while 15–29-year-olds had net out-migration rates in agricultural counties. In addition, where there is net out-migration from recreation counties—which is not common—it is slower than in farm counties (Fig. 2.4).

Other characteristics also distinguish these two types of counties. In many population loss counties, businesses and services have declined with persistent out-migration. With these events, the tax base has declined and fewer services for older adults are available. Older adults tend to be poorer in population loss counties than in retirement counties. Thus the lack of services is a particular problem for this older population (Rogers 2002). Most retirement counties, on the other hand, have continued to grow, even during the recession of 2009, although their rates of growth have declined substantially (Pollard and Mather 2010).

4 Are Rural Elders Male or Female? Healthy? In Retirement Homes?

In 2010, an estimated 41 million Americans were 65 years of age or older, representing an increase of nearly 19% in the older population since 2001 (National Center for Health Statistics 2010, p. 159). By 2030, that number is estimated to reach 72.1 million, representing 19% of the total population. By comparison, the proportion of the population under 18 years of age was 24.2% in 2010 and is projected to remain at no more than 23.5% by 2030 (National Center for Health Statistics 2010).

4.1 Sex Ratio

Summary information provides some insights into older rural people. To begin, they tend to be more female than male. Because women in more developed countries tend to outlive men, as a population ages, the population tends to become “more female.” In the US, men who reach 65 years of age have an average life expectancy of another 14 years; females who reach 65 years of age can anticipate another 19 years of life (National Center for Health Statistics 2010). As a result on average in 2007 there were 85 men for every 100 women 65–74 years of age. Mortality differences mean that by 85 years of age and older, there are fewer than 48 men for every 100 women. Although the proportion of men in each age group, relative to women, has been increasing since 2000 (in 2000 there were 82 men for every 100 women 65–74 years of age and 41 men for every 100 women 85 years of age and older), it is unlikely that a time will come when males outnumber females in the oldest age groups.

Lutz and colleagues (2008) proposed that population aging could more accurately be estimated using life expectancy calculated for persons 60 years of age or older. People who survive to at least 60 years of age are likely to live a fairly lengthy additional number of years. Lutz et al. (2008) estimate that those in North America who have reached 60 years of age in 2010 are likely to have another 23 years of life, if female, and another 15 years, if they are male. Males are estimated to gain as much as another 3 years of life expectancy between 2010 and 2020 but females will gain only two more years by that time. The differential advances made by males relative to females will result in an increase in the sex ratio in older ages.

4.2 Family and Health

The differential in the proportion of males to females in the older ages is important for several reasons. First, more widows are in the elderly population than widowers. Divorce has also become more common during the last 60 years, with the older segments of the baby boom more likely to divorce than the younger half (Cohn 2010). As mortality declines, the risk of divorce increases (Kammeyer and Ginn 1986). The declining fertility rate that has contributed to the aging of the population also means that as widowhood occurs, or as persons age while divorced, if not-remarried, the burden of any long-term care for a disabled elder becomes greater for remaining family members, or can mean that elderly are at greater risk of having no familial support in the case of disability.

Second, marital status has long been thought to be associated with longer life and better health status. Although the relationship is complex, numerous studies have shown that married persons tend to live longer than the unmarried and that marriage seems to be something of an inoculation, particularly for males more so than for females (e.g., Lillard and Panis 1996). In rural areas, 26% of males over age 15 have never married; in urban places the percentage is 37%. The corresponding percentages for women are 20 and 30% respectively (US Census Bureau 2010). The higher marriage rates in rural compared to urban areas tend to result in slightly higher sex ratios among rural older people.

Waite (2009) has said that “Spouses act as a small insurance pool against life’s uncertainties, reducing their need to protect themselves against unexpected events” (p. 691). That is, spouses share and accumulate more economic and social capital than do singles. The effect of having more social capital, or friends and acquaintances, is to provide more contacts one can turn to for support when the need arises. Such individuals can serve as drivers, home health care assistants, house cleaners, and the like but also as sources of information about options available for support of older people.

The loss of a spouse results in the loss of economic assets, and it matters whether the male or female partner dies first. Holden and Smock (1991) showed that widows tend to have fewer economic assets after a husband dies than do widowers, whereas widowers tend to lose more social connections when their wife dies. Still, the higher marriage rate in rural places suggests that the health benefits of marriage will result in older persons remaining relatively healthy (Pienta et al. 2000).

Still, mortality rates in rural places have been slightly higher since 1984 and have been increasing relative to rates in metro places since that date, even with population age, sex, and other variables controlled (Cosby et al. 2008). The differential reverses a century-long trend and the reasons for it are unclear. The pattern may be one of the consequences of simply being in a rural place: rural places are more isolated from health care facilities; persons in rural places are less likely to have health insurance and are more often poor (Bailey 2008). In the poorest rural counties, in contrast to the life expectancy information reported above, life expectancies for women are now lower than or essentially the same as in the 1980s (Danaei et al. 2010). The poorest rural counties tend to be in the South, the southern Great Plains and Appalachia (Danaei et al. 2010). The health differences found in these counties, relative to metro counties, occur largely due to life style factors including, but not limited to, smoking and obesity rates, as well as lack of access to health care services, an increase in the uninsured and increasing income gaps (Bailey 2008). Males living in the western rural US and black low income females living in the rural South had lower life expectancies than males or females elsewhere largely due to differential health risks (Danaei et al. 2010). The same regions just cited as having poorer health outcomes coincide with those where overall population size is declining (Danaei et al. 2010) On the other hand, recent research by Lambert et al. (2010) implies that some growth in health care services and thus improved services for rural elders may follow retirement migrants to places of destination. Thus, for communities that are actively trying to attract retiree migrants, some health care services may follow.

4.3 Living Arrangements

Widowhood and/or living alone at earlier ages can often result in changes in living arrangements later in life. Different proportions of males and females are in this situation. The proportion of older women living alone is one in five, which is about twice that of men (United Nations Department of Economic and Social Affairs 2005). However, the baby boom generation and those cohorts following it have been more likely to marry and divorce, which has meant that, once widowed, older persons have more complex choices as to whether to stay put (remaining ‘in place’), move toward children or step-children, or to choose some other form of living arrangement.

Rates of institutionalization of older persons are surprisingly low, contrary to many people’s beliefs. In more developed countries, the rates range around 10%, although in Japan, the US and the UK rates are only 5–6% for persons 65 years of age or older but increase 2–10 times that for persons 85 years of age and older (Jacobzone 1999). In nonmetro areas, although there are more nursing home beds per capita than in metro places, (Duncan and Radcliff 2004), fewer other types of long-term residential settings are available for older individuals and the responsibilities of day-to-day care often fall to family, friends or other types of networks (Whitener 2005). Fertility decline and the increase in complex kinship ties referred to above as well as the outflow of younger relatives common from rural places make it more likely that an out-migration of older old from rural places occurs, or at least from non-retirement destination rural places (Scharf and Bartlam 2008). This pattern follows Litwak and Longino’s (1987) elderly migration paradigm, wherein they describe the possibility of a move around retirement age to a retirement destination county, for those with the wherewithal; then a second migration toward family; and finally a third migration to a health care facility or to live with someone who can provide care.

Nancy Folbre (2010) spoke of the role of family care noting that about 19% of US residents provide care to persons 50 years of age and older. She notes that “this unpaid work saves taxpayers a lot of money every year. However, when families are unwilling or unable to provide enough care, public support programs like Medicare and Medicaid and private long-term care insurance make up the difference. These alternatives are mostly inefficient and expensive” (Folbre 2010). Still, due to the growth in the oldest old population, even if the proportion of those requiring nursing home or other long-term care fell by one third, the estimated number of beds in traditional long-term care facilities would need to increase to meet demand (Sahyoun et al. 2001). As a point of reference, those future oldest old who are likely to inhabit long-term care beds are currently 50–60 years of age, the group that will increase the proportion of elderly so dramatically.

The Population Reference Bureau (PRB) (Stall 2010) has recently reported that the increase in the older population will require more health care services because more health care dollars are utilized at the end of life. At the same time, doctors and nurses are themselves aging and are retiring, as is the rest of the population. The result is to increase demand for health care professionals even as the proportion of the population in the working ages dwindles relative to those in the retirement ages (Stall 2010).

Still, not all elderly should be thought of as requiring health or medical assistance. Glasgow (2004) discussed the increasingly likely potential for healthy living into old age and pointed out that this potential has been much underestimated by the general public. Indeed, health care professionals increasingly comment on the wellness of older age groups and note that healthy aging is increasingly likely. There are, however, accessibility issues for the healthy aged. These issues are much like those associated with the Americans with Disabilities Act, and remediation may be costly. Sidewalks, walkways, non-slip surfaces, manageable housing, public transportation, libraries and the like must all be adapted to those with the somewhat more limited physical abilities of elderly populations. Such adaptations are expensive but can make healthy aging more likely. Accommodations like these are more expensive in rural places where infrastructure is sometimes older, or where there are fewer dollars available to support upgrades.

4.4 Other Characteristics of the Older Population

Beyond the factors discussed above, the older population has other characteristics that differentiate them from the rest of the population. For example, older persons are more likely to vote (Kirschner and Berry 2004). The Brookings Institution’s recent report (Berube et al. 2010) on metro America pointed out that the aging population is predominantly white, while nearly 40 % of those under 18 years of age in the US are non-white minorities. The implication of the report is that there is more than a generation gap between older and younger Americans; a diversity gap exists as well. The impact is that those who cannot yet vote are often the children of the foreign-born and may not be well represented in the voting age population, which has implications for property tax revenues and for those who vote for or against those taxes. At the same time, those who care for the older population in assisted living or other health care settings are often non-native born or are non-European descent whites. Indeed, the PRB (Stall 2010) report indicates that more than one in four health care pro­fessionals are internationally-trained doctors and nurses.

As a different example, the Iraq and Afghanistan wars, the longest in US history, have had a particular impact on rural people. The soldiers fighting in those wars have come disproportionately from rural and near rural places. Traditionally nonmetro youth have had fewer options for employment and thus often choose military careers just as they have been more likely to move from rural places for jobs. Thus rural, nonmetro families are feeling the impact of war casualties more frequently and more personally than metro families (O’Hare and Bishop 2006) often resulting in rural elders caring for children and grandchildren at higher rates than urban elders (US Census Bureau 2010, not shown).

5 What Is Unique About Aging in a Rural Place?

The problem with being rural is largely a problem of infrastructure (Krout 1983). Travel, whether to the doctor, to visit children or to the grocery store is often more difficult because of distance and lack of public transportation. The increased distances between places may require greater reliance on family and friends, and greater reliance on automobiles (Nemet and Bailey 2000). Access to other infrastructure (health care, elder day care centers, grocery stores, and other shopping) is also more complicated in rural places. The much smaller population base makes support of services more difficult. Poor access forces greater reliance on kin and friendship networks. Many elderly give up their cars only reluctantly but are even more reluctant in rural than urban places because of greater distances (Glasgow and Blakely 2000). A tendency to drive beyond one’s ability (whether that is 60 or 90) makes the roads less safe for older drivers themselves, other drivers and pedestrians in rural places. But whether metro or nonmetro, an elder relying on others often goes against the grain.

6 Conclusion

Rural and urban communities have known that population aging has been occurring for some time and have had much time to anticipate the impact of an older population. In urban communities, however, small or gradual change in the population has far less impact simply because larger population numbers diminish the influence of change. In nonmetro places, any change can have a profound impact. The small size of the populations of rural places means that even a 5% change in population size or composition dramatically influences tax revenues and the requirement for oncologists or pediatricians, teachers or gerontologists.

The phenomenon known as the second demographic transition (Van De Kaa 1987; Lesthaeghe and Neels 2002) is likely to influence population aging in both metro and nonmetro places. The second demographic transition describes the increasing trend for individuals to marry later in life or to remain single, have one or no children, and focus more on friendship relations than on kinship relationships. The impact of this transition, should it continue, will likely be felt more in future decades, but it emphasizes the reliance of older adults on friendships and institutions rather than on kin. The impact of this second revolution may be mitigated by increases in the foreign-born population of the US who are known to be more family-oriented than the native-born population and who have had larger families than have recent generations of native-born cohorts. If Van de Kaa and Lesthaeghe and Neels are correct, the aging of the population will mean an increased need for formal institutions such as assisted living centers to care for older populations.

From another perspective, one can think of the current boom in the elderly population as a type of elder dividend or, as Brown and Glasgow (2008) call them, “grey gold.” Baby boom elders are more likely to have higher levels of education than prior cohorts, even though rural elders generally have less education than their urban counterparts. Individuals just approaching retirement age—those 55–65 years of age—have relatively higher incomes than the younger population, and this group has more income than earlier cohorts of elders. Because women are now much more likely to be in the labor force than in the past, baby boom elderly are somewhat better off than elders have been in prior cohorts. As Rathge, Garosi and Olson (Chap. 5, this volume) point out, the contribution of this group to taxes over the next several years may serve to ease both nonmetro and metro counties out of the severe recession that began in 2008.

Among the dividends that come from having an older population is the reliability and productivity of older workers. Older workers having already raised their families are known to have less absenteeism, and to be more reliable employees. Older persons are also known to spend large amounts of time in volunteer positions helping other elderly, such as in Meals on Wheels programs or, the eponymously named, Elders Helping Elders (Brown and Glasgow 2008). By comparison, time devoted to voluntary work and care is minimal among those under 35 years of age and is highest among age groups 55 and older and continues to increase to around 70 years of age (Curnow 2000). Such labor tends to be ignored by labor statistics because it is unseen and unaccounted for in the GDP. An interesting study in Australia (Curnow 2000) even suggests that some housework for those under 35 years of age is accomplished by those over 50 years of age. This inter­generational transfer of time and labor goes undocumented and may amount to a surprisingly large amount of household labor and capital. Perhaps the most important thing about rural elders is that, as noted above, they and their families are accustomed to “making do” (Coward et al. 1990). This is not to cast aspersions on metro elders who, similarly, find ways of getting things done. The difference is merely one of scale. For rural elders, the problem of being in a rural place is largely one of distance: the distance between places, whether it is the distance from home to the nearest grocery, gas station, doctor, retirement facility, family member, or, for that matter, the nearest place to get the car repaired. Getting to places makes creativity in management important. Rural elders who cannot manage these functions have fewer options. These options include: (1) having to move away from family and friends in a long-term place of residence toward their children; (2) having their children move toward them; (3) forming informal networks of friends and kin to do one’s driving, as necessary, and to help with cleaning, shopping, or the like; or (4) moving to assisted living.

Regardless, it is in the interest of rural communities to promote the contributions elders can make. Older baby boomers have more money, education, and skills than any generation before them. Their abilities and skills, as well as their economic power, far outweigh that of any generation that has preceded them. Both elders and rural communities benefit when ways are found to keep baby boomer elders from moving away. Indeed, the unpaid work that these boomers can provide to a community, through house repairs for the boomers’ children; child care for their grandchildren; community volunteering; or simple or not so simple volunteering on a complex bridge project or an interesting folklore project, elders can provide so much more to a community than the current fear that “the old folks are coming” has implied.