The sociology of aging is both broad and deep. The breadth of the field can be highlighted in several ways. First, the sociology of aging encompasses investigations of aging as a process, of older adults as a group, and of old age as a distinctive stage of the life course. Second, aging research is performed at multiple levels of analysis, from macro level studies of age structure within and across societies, to mesolevel studies of labor force participation and family structure, to micro level investigations of health and well-being. Third, aging research uses the full repertoire of methods that characterize the discipline, including life tables and other demographic methods, survey research, ethnographic methods, and observational studies. The depth of the field results from the accumulation of scientific studies that now span more than three quarters of a century.
Any attempt to summarize concisely the state of the science in the sociology of aging will inevitably do justice neither to the breadth nor the depth of the field. Here, four major themes in theory and research on aging are reviewed. Selection of these themes is based on a review of appropriate reference works (e.g., handbooks, encyclopedias) and perusal of major journals and textbooks.
Outline
- Age Structure and Its Implications
- Aging as Context: The Significance of Cohorts
- Aging and Well-Being
- Aging as the Culmination of the Life Course
- References
Age Structure and Its Implications
Although primarily the province of demographers, both scientific and public interest in aging partially rests on the aging populations characteristic of the modern world. Age structure is based on the sizes of age groups in a given society. In turn, the sizes of age groups are a function of fertility and mortality rates. The theory of the demographic transition provides a portrait of the relationships between development (i.e., industrialization, urbanization, technological advances) and the age structures of societies (Bourgeois Pichat 1979). According to this theory, the demographic transition occurs in three stages. In the first, prior to and during the early years of modernization, both fertility and mortality rates are high. The result is an age structure that takes the form of a pyramid, with the largest age group consisting of children, and older adults comprising the smallest group. During the process of modernization (the second stage), mortality rates decline, but fertility rates remain high. The result is larger populations in total size and a young population. The dependency ratio, which is the proportion of the population in the labor market relative to the number of children and older adults not in the labor market, is high, but consists primarily of children. As societies achieve modernization (third stage), mortality rates continue to decline, but fertility declines as well. The theory of the demographic transition hypothesized that the third stage would lead to a steady state population size, in which fertility and mortality rates would be approximately equal and the age structure would take the form of a cylinder, with all age groups of approximately equal size, and the numerator of the dependency ratio including approximately equal numbers of children and older adults.
The first two stages of the theory of the demographic transition have been supported in empirical studies. Evidence for the hypothesized third stage is much weaker. Although both fertility and mortality rates have declined in modernized societies, fertility rates have declined faster than mortality rates, resulting in populations with disproportionately large numbers and percents of older adults. Two other demographic patterns have exacerbated the aging of the population in some societies. First, in the US and, to a lesser extent, in Western Europe and Australia, the end of World War II ushered in a decade or more of unusually high fertility, resulting in a baby boom, followed by the expected sizable declines in fertility. These unusually large cohorts delayed the expected declines in fertility, but because of the small cohorts that followed them, escalated the aging of the population. Second, countries in South America, Asia, and Africa have achieved substantial modernization with substantially smaller declines in fertility than expected.
The importance of the theory of the demo graphic transition is not its accuracy, but rather its attention to the age structures of societies and the effects of social change (in the form of fertility and mortality rates) on those age structures. Regardless of the indicator used (e.g., proportion of older adults, median age of the population), the population is aging rapidly in the US and other western societies.
Although initially slow to comprehend the significance of an aging population, both scientific and policy communities are now well aware of the challenges posed by an aging society. ‘‘Young’’ populations also pose problems for societies, but solutions to those problems (e.g., child welfare, schooling) evolved gradually in modern societies and became institutionally embedded in custom and law. The aging of modern populations occurred more rapidly, resulting in significant structural lag (Riley & Riley 1994) in institutional responses to the needs of older adults.
Demographic research has expanded substantially beyond questions of age structure per se. Most of what is now known about the prevalence, incidence, and course of disability is based on demographic research. Among the contributions of this research are findings that rates of disability among older adults have been gradually declining for approximately 20 years, that the higher rates of disability among women than men results from their greater longevity rather than higher incidence of disability onset, and that, although it is less common than the onset of disability, a sizable proportion of older adults recover or improve in functional status. The distinction between life expectancy (expected years of survival) and active life expectancy (expected years of disability free survival) also is a high priority issue. Interest in active life expectancy stems from concern that the increased longevity characteristic of modern societies has been achieved by prolonging life after the onset of frailty and disability. Evidence suggests that the length of disability prior to death has not increased over the past several decades; however, there also has not been a decrease in the interval between the onset of disability and death. As these topics illustrate, demographers now devote a significant proportion of their efforts to understanding heterogeneity in the older population.
A large proportion of sociological research on aging rests on the challenges posed by an aging society, although that impetus is not always explicit. Studies of public and private transfers of money, time, and in kind services rest in large part on their salience for sustaining an aging population. Studies of health, disability, and quality of life are important not only because they address threats to well-being, but also because they shed light on the factors that keep older adults from excessive reliance on public programs. Even studies of the caregivers of impaired older adults rest not only on concern about the health risks of chronic stress, but also on the desire to enable families to bear as much of the cost of care as possible, thus relieving public programs. Thus, age structure and its social implications is a significant and far reaching arm of aging research.
Aging as Context: The Significance of Cohorts
Multiple forces, both social and non social, determine the process and experience of aging. Historically, there was a tendency to attribute the aging process and the experience of late life to inherent biological and developmental processes. Most of us are relatively ignorant of the extent to which the process and experience of aging vary across historical time, finding it difficult, for example, to imagine a time when there was no retirement or when the odds of dying were essentially the same during child hood, adulthood, and old age. And yet, retirement as a predictable life course transition and odds favoring survival to old age both emerged in the twentieth century. The concept of cohort allows us to distinguish conceptually and empirically between inherent components of the aging process and patterns that result from social factors, especially social change and unique historical events or circumstances.
Although cohort membership can be based on any event, the term is typically used for birth cohorts (i.e., for persons born at the same or approximately the same time). Cohorts share more than the timing of their births; they also experience the same historical events and social structures throughout their lives. Cohorts share collective experiences that often differ from those shared by earlier and later cohorts. Thus, there often are sizable cohort differences in the process and experience of old age.
Cohort differences, often observed across cohorts born in relative proximity, can be generated by multiple conditions. First, cohorts can differ substantially in size and composition. Substantial evidence documents that unusually large and unusually small cohorts differ substantially, especially in economic opportunities, with the latter more plentiful in smaller cohorts. Cohort composition can be affected by many factors, including excess male mortality during wars, different birth rates across racial/ethnic groups, and changes in immigration policies.
Second, historical events can substantially alter the experiences of cohorts. When many cohorts experience the same historical event, effects differ depending on age at the time of the event (e.g., wars most strongly affect young men). Even in the absence of dramatic events or dislocations, historical developments imprint cohorts differently, creating persisting differences (e.g., racial identity among African Americans before and after the Civil Rights Movement). Substantial evidence suggests that historical events and social change generally affect adolescent and young adult cohorts more than they affect younger and older cohorts.
Third, social change creates cohort differences and the more rapidly social change occurs, the greater the differentiation across cohorts. Social change, of course, takes many forms, ranging from changes in public policies (e.g., Social Security and Medicare created large cohort differences in economic status during later life), changes in the norms governing social behavior (e.g., norms concerning the acceptability of fertility outside of marriage and cohabiting), and major structural changes such as the shift from an industrial to a service economy. Technological change also generates cohort differences, with varying implications for the older population. For example, devices that save household labor or provide assistance in compensating for disabilities enhance the likelihood that older adults can live independently. Conversely, diffusion of general technological changes often takes longer to reach older adults, distancing them from younger cohorts (e.g., personal computers and related use of the Internet).
Fourth, older cohorts are inevitably affected by the composition of and changes occurring in younger cohorts. Responses to those changes can create related changes in older cohorts. For example, the prevalence of custodial grandparents, although still uncommon, increased dramatically over the past two or three decades. This change in older cohorts is a direct result of changes in fertility and childcare practices of younger cohorts.
Cohort comparisons comprise a substantial proportion of sociological research on aging. An issue that receives considerable attention is comparisons of the assets and liabilities that different cohorts bring to late life. To date, research findings paint a rosy picture of this form of cohort change. For at least half a century, successive cohorts have entered old age with higher levels of resources and fewer liabilities than the cohorts that preceded them. This pattern has been especially consistent for health, education, wealth, and the availability of social support, all of which are valuable assets in late life. As Uhlenberg and Minor (1996) note, there is no reason to believe that this pattern will continue indefinitely. Indeed, some scholars predict that baby boomers will enter old age more disadvantaged than their parents; other scholars predict that the pattern will not reverse until the children of the baby boomers reach old age – but most scholars expect the pattern of increasingly resource rich older cohorts to peak at some point during the next 50 years.
The large volume of cohort comparison studies is too large to detail here, but includes issues as diverse as political affiliation and voting behavior, family structure (primarily cohort differences in divorce, remarriage, and single parent mothers), cognitive abilities, alcohol consumption, and rates of depression. Cohort comparisons also are important for policy planning and analysis. Comparison of cohorts before and after a major policy change, such as the enactment of Medicare, is one of the primary strategies used to evaluate the impact of broad scale public policies. Cohort comparison studies also remind us that public policies targeted at older adults are not the only policies that create differential advantage or disadvantage across cohorts. Policies that enhance educational attainment during adolescence and young adulthood have long term benefits, creating cohorts that are more advantaged as they enter old age than were older cohorts. The GI Bill, first made available to World War II veterans, for example, created dramatic increases in the educational attainment and economic resources with which those cohorts entered late life.
At the same time that cohort comparison studies have enjoyed success, a related body of research examines intracohort variability. Although there are often large differences across cohorts, cohorts are not homogeneous. Paralleling sociology more broadly, increased attention to heterogeneity has characterized aging research for the past quarter century. Intracohort variability has received both conceptual and empirical attention. Two bodies of research have contributed most to this research base.
First, the attention paid to social location, as indexed by basic ascribed and achieved statuses, has increased dramatically. Thirty years ago or so, gender differences, racial/ ethnic differences, marital status differences, and socioeconomic (SES) differences typically were examined perfunctorily, if at all. It was not until the mid to late 1970s, for example, that women’s retirement received empirical attention. There is now general consensus that age, race/ethnicity, gender, and SES represent basic social structural categories and are forms of social stratification. Investigation of these multiple forms of stratification has been incorporated into aging research and into the discipline more broadly.
Second, a compelling body of research demonstrates that historical events or conditions do not have uniform effects on cohort members. Some cohort subgroups are strongly affected by historical events; others are largely untouched by them. Several important studies demonstrated that the Great Depression had the strongest contemporaneous and long term effects on late adolescents whose families experienced the greatest economic deprivation (Elder 1999); that relatively few young adults participated in the political activism of the 1960s, but that there were persisting differences in the life patterns of those who did and did not (McAdam 1989); and that veterans’ emotional problems in middle and late life were largely a function of amount of combat exposure during World War II (Elder et al. 1997). Broad based cohort effects also have been observed for these and other historical events or conditions (e.g., the ‘‘children of the Great Depression’’ had greater concerns about financial security than earlier and later cohorts, regardless of the amount of deprivation experienced), but there is also great het erogeneity in the effects of historical events on cohort members.
Intercohort comparisons and studies of intracohort variability are arguably the core of sociological aging research. These studies demonstrate that aging is not solely – or even primarily – a biological process, but rather that the aging process and the experience of late life are shaped by social and historical context.
Aging and Well-Being
The vast majority of aging research falls under the general topic of aging and well-being, with well-being broadly defined to include any social asset (e.g., economic resources, life satisfaction). Social scientific interest in aging was spurred by concerns about the well-being of older adults in both absolute and relative (to other age groups) terms. This is probably not surprising. The history of sociology in general has been driven by concerns about social disadvantage – its prevalence, antecedents, and consequences.
The types of well-being examined in relation to aging are numerous. A partial list of the forms of well-being frequently studied in late life include longevity, physical health, dis ability, mental health, subjective well-being, economic status, and identity or sense of self.
Self perception during late life is an important and understudied topic relative to studies of physical and mental health and subjective well-being. Two primary dimensions of self perception are especially important: a sense of self worth (typically measured as self esteem or self acceptance) and a sense of competence (usually measured as self efficacy, mastery, or sense of control). These self perceptions are important in their own right – most of us consider adequate self esteem and sufficient self efficacy essential components of well-being. In addition, these self perceptions mediate many of the relationships between social factors and other forms of well-being, including physical and mental health and subjective well-being. For example, self esteem has been shown to mediate the effects of education on health (Murrell et al. 2003), of social support on subjective well-being and self rated health (Bisconti & Bergeman 1999), and of social stress on functional status (Forthofer et al. 2001). Traditionally, sociologists tended to view self perceptions as the province of psychology. There is now plentiful evidence, however, that the antecedents of these self perceptions are primarily social and that their distributions are concordant with multiple stratification systems. Adequate sociological explanations of variability in well-being will need to take these psychosocial processes into account.
Three major research strategies underlie most research on aging and well-being. First, some studies examine the well-being of older adults relative to that of younger age groups. Examples of this kind of research include age comparisons of rates of poverty, chronic physical illness, disability, and mental illness and levels of subjective well-being, self esteem, and self efficacy across age groups at a single point in time. These studies are of limited use in understanding the aging process because it is unclear whether differences across age groups are due to age per se or to cohort differences. But comparisons across age groups can be useful for both providing basic descriptive information about the relative status of older adults and for identifying issues important to public policy (e.g., whether it makes sense to target income maintenance programs at specific age groups). That is, policymakers typically are more concerned about the unmet needs of older adults than they are about disentangling age and cohort effects.
A second strategy for understanding the effects of aging on well-being is to study adults longitudinally as they move from middle age to late life and from being young old to being old old. The advantage of this strategy, of course, is that age related changes in well-being are directly observed. These studies focus on the status of the elderly relative to earlier points in their lives, rather than relative to younger age groups. The limitation of these studies is that findings may be cohort specific, rather than reflecting a consistent developmental pat tern. In theory, if one samples a large number of cohorts and studies them over long periods of time, investigators can determine whether patterns of change and stability are similar across cohorts. Unfortunately, few, if any, data sets are of sufficient breadth in both the number of cohorts studied and number of measurements over time to permit conclusions about whether patterns of change and stability are generalizeable or cohort specific.
Patterns of change and stability in the multiple forms of well-being that have been studied to date cannot be detailed here. Importantly, however, there is no consistent pattern of age related decline across all forms of well-being. Declines are the modal pattern for some forms of well-being, such as income and the prevalence and onset of chronic ill nesses. Stability or increases are the modal pattern for other types of well-being, including self esteem and life satisfaction – at least until very late life (i.e., age 80 and older).
A third strategy is to focus on variability within the older population – to assess variability in well-being among older adults and to identify the antecedents of that variability. Either cross sectional or longitudinal data can be used to study heterogeneity among older adults, but only longitudinal data permit investigators to establish temporal order between well-being and its presumed antecedents. Note that age is not the independent variable in studies of this type; instead, the independent variables are the presumed causes of variability in well-being.
Compared to studies of age structure and cohort comparisons, the theoretical underpinnings of studies of aging and well-being are typically richer and more complex. A broad range of theories is used in studies of well-being in late life. Most of these theories are imported in whole or in part from other domains of sociology. For example, stratification theories are used to examine both income dynamics and health inequalities in later life, stress theory is used in studies of physical and mental illness, network theory is used to understand older adults’ patterns of social support, and aspiration and equity theories are used in studies of subjective well-being. In addition to importing theories from other domains of sociology, a substantial proportion of research on aging and well-being rests on theories developed to highlight the distinctive conditions of later life. Examples include activity theory, which posits that multiple forms of well-being are enhanced in late life by sustaining high levels of activity and engagement – and adding new forms of activity to compensate for losses that often accompany aging; the double jeopardy hypothesis, which predicts that the combined statuses of being old and a member of a racial/ethnic minority have more damaging effects on health and well-being than their purely additive effects; and socioemotional selectivity theory (Carstensen 1995), which suggests that declines in social contacts in late life are a purposeful and effective strategy for sustaining high quality relationships. Clearly, the theories used to explain variations in well-being among older adults are rich and varied.
The independent variables used in studies of well-being during late life are typically measures of social status, social context, and social resources. Social context, as indexed by age, race, and gender, is related to economic well-being, physical and mental health, and longevity. Only the more social psychological forms of well-being, such as self esteem and life satisfaction, are either not significantly related or are weakly related to these basic demographic characteristics. As expected, traditional indicators of socioeconomic status are significant predictors of longevity, physical and mental health, self esteem and self efficacy, and subjective well-being. Social resources, especially social integration (e.g., organizational and religious participation) and social support also have positive effects on longevity, health, sense of self, and subjective well-being. As this brief description illustrates, we know a lot about the factors that explain heterogeneity in well-being in later life. These same social factors also explain much of the variability in well-being among young and middle aged adults. As the body of research that compares predictors of well-being across age groups documents, the distinctive feature of well-being in late life is not the specific antecedents of well-being, but rather the distribution of those antecedents across historical and biographical time.
Aging as the Culmination of the Life Course
During the past 20 years, the life course perspective has assumed increasing influence in sociological research, especially research on aging. The core of the life course perspective is the proposition that lives unfold over time and that events and conditions at earlier phases of the life course have persisting effects at later phases – either continuing direct effects or indirect effects via more temporally proximate events and conditions. Taking temporality seriously changes research questions and research methods in multiple ways (George 2003). Most importantly, perhaps, long term patterns of change and stability, often conceptualized as trajectories, are the primary focus of analysis. Investigators can study trajectories of independent variables (e.g., marital history), trajectories of dependent variables (e.g., pat terns of recovery, remission, and chronicity in depressive symptoms), or both. In addition to the ‘‘shape’’ of trajectories, duration in states of interest also may be important (e.g., length of time till recovery from disability).
Methodologically, life course studies require either multiple measurements over long periods of time or retrospective data about earlier phases of the life course. Longitudinal data are more accurate than retrospective data, but most life course investigators are willing to use retrospective data if they are all that is available. The statistical techniques most frequently used in life course studies (e.g., latent growth curve analysis) are newer and more complex than those used in cross sectional or short term longitudinal studies. Other methodological problems, ranging from substantial attrition in sample size to difficulties in selecting measurement tools that are applicable across adulthood, emerge when using longitudinal data covering long periods of time. Nonetheless, it is the way that research questions are conceptualized that is the hallmark of life course studies.
Life course studies provide important information about trajectories of vulnerability and resilience. At their best, they also incorporate the processes by which early events and conditions have persisting effects on outcomes of interest measured decades later. Work by Elder and colleagues on the long term effects of com bat exposure provides a compelling illustration of the knowledge generated by life course studies (Elder et al. 1997). This research is based on the Terman men, a sample of unusually intelligent males tested on multiple occasions from childhood to early old age. Most of these men participated in World War II, although not all of them were exposed to combat – and among those who were in combat, the amount of exposure varied widely. Elder and colleagues demonstrate that combat exposure is a significant predictor of physical and (especially) mental health problems 40 years later, controlling on other known predictors of physical and mental health in later life. They also identified the life course achievements that allowed some of these combat veterans to avoid or minimize subsequent health problems. Men who achieved greater socioeconomic success, those who sustained contacts with other combat veterans, and especially those who had lasting, high quality marriages were able to avoid or minimize the health risks posed by combat exposure. This research demonstrates the benefits of life course research, documenting both the persisting effects of early trauma and the mechanisms that allowed some men to avoid those risks.
In aging research, the life course perspective has been used most frequently to understand the effects of life course patterns of socioeconomic status on multiple forms of well-being in later life. The conceptual frame work underpinning most of this research is the theory of cumulative advantage/disadvantage. This theory was developed nearly a half century ago by Robert Merton (1957), as a framework for understanding occupational success among college and university professors. Merton observed that, at job entry, assistant professors looked very similar on standard measures of productivity and occupational success, regardless of the status of the institutions in which they were employed. Over time, however, variability increased dramatically in levels of productivity and occupational success among professors, with those employed at resource rich schools exhibiting patterns of increasing success and those at resource poorer schools exhibiting steady declines in productivity. Merton referred to the pattern of increasing success as cumulative advantage and the trajectory of declining productivity as cumulative disadvantage. In colloquial terms, the theory of cumulative advantage/disadvantage posits that ‘‘the rich get richer and the poor get poorer.’’
In general, what Merton observed among professors is true for socioeconomic status (SES) over the adult life course. That is, SES differences are smallest during young adulthood and largest during late life (Crystal & Shea 1990). This is true for income and SES differences are even more dramatic for wealth. Thus, cumulative advantage/disadvantage generates increasing economic heterogeneity over the adult life course.
The life course perspective also has been valuable in accounting for health inequalities across the life course. As is true for income and wealth, SES differences in health are minimal during young adulthood. By middle age, however, there are large differences in health between the lowest and highest SES quartiles in the US. Evidence is less clear during old age, with some investigators reporting that SES differences in health continue to widen during late life (Ross & Wu 1996). Other researchers, however, report that SES differences in health are largest during middle age and narrow somewhat during old age, although they remain significant (House et al. 1994). At some point in late life, SES differences in health are likely to narrow as the result of selective mortality (i.e., the earlier deaths of many lower SES individuals). Some of the mechanisms that account for SES differences in health also have been identified. The benefits of education, occupational status, income, and wealth are, of course, much of the basis of SES differences in health. Other mechanisms that mediate the effects of SES on health include health behaviors; stress, including lifelong accumulation of stressors; and psychological resources such as self esteem and mastery.
In addition to long term trajectories of assets and liabilities, the life course perspective also focuses attention on the persisting effects of early life events and conditions. For example, evidence demonstrates that parental SES predicts health during middle and late life, over and above the effects of individuals’ own SES trajectories (Hayward & Gorman 2004). Indeed, limited evidence suggests that fetal growth in utero plays a substantial role in health during late life (Barker et al. 2000). In addition to economic resources, lack of emotional support from parents during early childhood increases the risk of both depression and chronic physical illnesses in late life (Shaw et al. 2004). Similarly, a variety of childhood traumas – including child abuse, sexual abuse, and parental divorce – are known to increase the risk of depression many decades later, even with other known risk factors taken into account (Kessler et al. 1997).
Although the volume of life course research that extends to late life has increased dramatically during the past two decades, many other topics could be profitably addressed in a life course framework. For example, although there is compelling evidence that social relationships are powerful predictors of health and well-being in late life, little is known about the relative importance of lifelong patterns of social bonds as compared to the contemporaneous effects of social networks during late life. Similarly, religious participation has been demonstrated to be a strong predictor of mortality and morbidity in late life (Koenig et al. 1999). But this research is based on studies in which current religious involvement is measured. Virtually nothing is known about how length of exposure to religious participation affects health. In other words, we do not know how long individuals must participate in religious activities before health benefits are observed.
The life course perspective also renders the usual distinction between social selection and social causation moot. Studying the life course is the equivalent of studying patterns of selection and causation as they unfold across personal biography. And, of course, the effects of social causation observed earlier in the life course become selection effects for outcomes observed later in life.
The life course perspective focuses on the complex links between social/historical change and personal biography. In addition, the life course perspective is ideally suited to linking macro and mesolevel social conditions to individual behaviors and well-being, to tracing the effects of both structural opportunities and constraints of human agency (i.e., personal choices) over the long haul, and documenting the many ways that the past is indeed prologue to the future. Thus, life course research is an important and exciting part of the sociology of aging.
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