Cumulative inequality theory for research on aging and the life course

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Robert Merton’s (1968a, 1988) articulation of the Matthew effect in science is
one of the key concepts that led to theoretical developments related to cumula-
tive advantage and disadvantage.
1 The idea that early advantage can be lever-
aged for greater gain has since received conceptual development and empirical
support in research on a variety of topics ranging from school-tracking systems
to age heterogeneity. Merton’s focus was how advantage accumulates, parallel
Kenneth F. Ferraro
Tetyana Pylypiv
Shippee
Markus H. Schafer
Cumulative
Inequality Theory
for Research on
Aging and the
Life Course 22
We appreciate the comments of Glen H. Elder Jr., Stephani Hatch, Ann
Howell, Shalon Irving, and Timothy Owens on an earlier version of this
chapter. Address all correspondence to Kenneth F. Ferraro, Center on
Aging and the Life Course, Purdue University, Young Hall, 302 Wood
Street, West Lafayette, IN 47907-2108. E-mail: ferraro@purdue.edu; voice:
765-494-6388.
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414 Handbook of Theories of Aging
to what is considered a tournament-mobility model: early success provides
opportunities for rapid career advancement. Advantage for some, however,
often means disadvantage for others. Indeed, this is part of the metaphor of the
Matthew effect: accumulating benefits for those already advantaged but accu-
mulating loss for those who are disadvantaged early.
The concepts of cumulative advantage and disadvantage are useful for
sociological inquiry, and our aim is to aid the development and application of
these concepts for research on aging and the life course. We know that early life
events and status rankings are important to later life, but a logical next step is
to explicate how these early life experiences are translated into later outcomes.
Do early events have effects that are inexorable in their impact? Can early dis-
advantage be overcome? Are there compensatory mechanisms that can coun-
ter the general principle that the “race is to the swift?” What role does human
agency play in the process of cumulative disadvantage? These and many other
questions merit attention if the concepts of cumulative advantage and disad-
vantage are to be transformed into a theory.
To enhance this transformation, we build on the contributions of others to
develop a theory of cumulative inequality. Our approach to doing so is twofold.
First, useful theories have elements subject to falsification (Turner, 1982) and
“sufficient formality” to differentiate closely related concepts (DiPrete & Eirich,
2006). Therefore, we explicate this theory in axiomatic form with propositions
in order to make its elements empirically testable and subject to falsification.
Second, although we draw from several sociological theorists and the literature
on life course epidemiology, we give special attention to integrating life course
theory into the study of cumulative inequality (Elder & Shanahan, 2006; Willson,
Shuey, & Elder, 2007).
Cumulative Inequality Theory
Although our theoretical development draws heavily on the work of Dannefer
(1987, 1988, 2003) and O’Rand (1996), we prefer to use a different name for this
theoretical perspective: cumulative inequality theory. Our rationale for doing so
is fivefold. First, the published record of CAD theory does not explicitly con-
sider many elements that we deem essential to a theory for the study of cumu-
lative inequality. One example that we articulate here is the intergenerational
transmission of inequality. Thus, a slightly different phrase may help distin-
guish this articulation from the exemplary contributions of previous authors.
Second, as is discussed, we think it is highly unlikely that cumulative advantage
is the opposite of cumulative disadvantage. Whether the effect of disadvantage is
parallel to that of advantage is an empirical question, but combining advantage
and disadvantage in the name of the theory may be misleading. Third, cumula-
tive inequality theory places the emphasis on system properties in generating
inequality. Advantage and disadvantage are often seen as outcomes for given
individuals, but the term inequality may help convey the importance of systemic
properties in how individuals become stratified. Fourth, cumulative inequality
theory gives explicit attention to perceptions of disadvantage rather than just
the objective conditions of their situations, which has been the dominant ap-
proach in studies of accumulating disadvantage. Fifth, cumulative inequality is
more concise than the phrase cumulative advantage/disadvantage.
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
We propose cumulative inequality as a middle-range theory—not derived
from a single theory—but incorporating various theories in a synthetic way; it is,
in Merton’s (1968b) words, “consolidated into wider networks of theory” (p. 68).
Cumulative inequality theory incorporates elements of macro- and microsocio-
logical content in an attempt to bridge both levels of analyses. Useful theories
incorporate empirical generalizations and link hypotheses in a coherent frame-
work. One of the ways to provide a coherent and useful framework is to develop
axioms and propositions (Zetterberg, 1965).
To clarify what is meant by cumulative inequality (CI) theory, we offer
five interrelated axioms—and propositions for each—that should facilitate
both hypothesis testing and further development of the theory. We recog-
nize that the axioms will be revised as empirical research accumulates and
as others help illuminate theoretical linkages. The axioms are, nonetheless,
a cogent way to articulate the essential elements of the theory and to direct
future tests of it.
Social Systems Generate Inequality, Which Is Manifested
Over the Life Course Through Demographic and
Developmental Processes
Inequality is present in all societies, with some persons having more resources,
opportunities, and influence than others. Although some viewpoints regard in-
equality as the result largely of personal action (human agency), we conceptu-
alize the major antecedents of inequality as systematically structured. People
make choices that influence inequality, but the choices available throughout the
world are quite varied, signifying that human agency is “always constrained by
the opportunities structured by social institutions and culture” (Elder, Johnson, &
Crosnoe, 2003, p. 8). We will discuss human agency further, but we launch this
axiom by recognizing the primacy of how inequality is systematically generated
and, thereby, difficult to eliminate (Bourdieu, 1996).
Although many scholars recognize the existence of structural determinants
of inequality, what CI theory adds is greater articulation of how these deter-
minants are manifested through demographic and developmental processes.
For this chapter, demographic processes refer to cohort-linked stimuli, events,
and experiences. Developmental processes refer to age-linked stimuli, events,
and experiences that can be observed in individuals. What may not be read-
ily apparent, however, is that scores of scholars interpret these two sets of
processes from a single indicator: age. Although gerontologists have long
recognized that age is a crude indicator that is often confounded with period
or cohort (the age–period–cohort [APC] confound), this fact often escapes the
view of many studying how inequality accumulates over the life course.
As noted previously, inequality is systematically generated, and the cohort
is a fundamental unit of social organization (Easterlin, 1987; Elder, 1974, 1998b).
Not only do cohorts reflect the ages of persons who share a time of birth, but
cohort membership marks population processes such as how large is the cohort
into which a person is born and migration patterns. Cohorts also provide the
context for development; they structure access to opportunity. Aging is highly
dependent on social context, reflecting gene pools and social organization at
that point in history.
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416 Handbook of Theories of Aging
Recognizing the demographic/developmental dialectic, CI theory holds that
childhood conditions are important to adulthood. Based on research during
the past decade, we now have compelling evidence that childhood conditions
structure the life course. This is not just in terms of personality formation and
stability but also in terms of achievement and well-being. Scholars have long
seen the interconnectedness of life stages, but what has been most stimulating
to this area of inquiry is whether early insults have long-term consequences.
Are later-life outcomes dependent on childhood experiences? Does gestational
health influence health in later life? The answers to these questions appear to
be affirmative, but isolating the mechanisms for these long-term connections
remains a matter of continuing inquiry (Barker, 2003; Holland et al., 2000; Irving &
Ferraro, 2006).
Beyond childhood as a life stage, we assert that gerontologists would be
wise to recognize that reproduction is a fulcrum for defining the life course
trajectories and population aging. Missing from much of the discussion of
cumulative disadvantage in gerontology is the pivotal role that reproduction
plays in life course processes.
Puberty is widely accepted as a key biological step in the transition to adult-
hood, and reproduction is a marker for adulthood in many societies. But what
follows reproduction? When we think of aging as a life stage of “growing older,”
we are probably referring to the postreproductive stage of life. There may be
some arbitrariness to such demarcations of growing older, and the reproductive
schedules of men and women are distinct. The point is that gerontologists would
profit from greater attention to conceptualizing the reproductive period as a piv-
otal life phase (Waters, 2007), one that leads to nonlinearities in accumulation
processes. In addition, CI theory privileges gender differences in the accumula-
tion of inequality by noting the distinct processes for men and women that lead
to inequality. Inequality exists between the sexes in part because of biology but
within each sex because the accumulation processes are often distinct.
Biologists often refer to the postreproductive period as senescence. For
instance, Spence (1989) describes senescence as “a term used to describe the
group of deleterious effects that lead to a decrease in the efficient function-
ing of an organism with increasing age, and leads to an increased probability
of death” (p. 8). This decrease in efficient functioning is most often attributed
to an increase in molecular disorder (Hayflick, 1998). We think of defining the
life course with more fluid boundaries but nonetheless feel that gerontologists
should give greater attention to how the pre- and postreproductive stages of life
sandwich the time during which individuals are able to reproduce.
As noted earlier, a major distinction between CAD and cumulative inequality
theory is that the latter gives explicit attention to the intergenerational nature
of inequality; family lineage is a major source of inequality (Pearlin, Schieman,
Fazio, & Meersman, 2005; Wickrama, Conger, & Abraham, 2005). Despite
the legacy of sociological research on the intergenerational transmission of
inequality, we have not been able to identify systematic coverage of this topic in
Dannefer’s work on CAD. Angela O’Rand (2006), another major contributor to
the development of the CAD theory, recently discussed “intergenerational flows
of resources from older to younger members of the population” (p. 147), but we
assert that the intergenerational nature of inequality is an essential element of
how inequality is reproduced.
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
For instance, a growing body of research illuminates that many adult chronic
diseases are the result of “longer-term consequences of the . . . complex accu-
mulation and interaction, across generations, of early and later-life exposures”
(Lynch & Smith, 2005, p. 2, emphasis added). Such statements challenge the no-
tion of disadvantage starting and ending within one’s lifetime, pointing instead
to how inequality is passed across generations. We assert that family lineage
is a major component of how social structures influence inequality over the
life course.
Family lineage may influence the accumulation of inequality in many ways,
but we identify four primary mechanisms: biological, social psychological,
economic, and ecological. Biological processes are manifested via genetic and
nutritional factors, social psychological via modeling and norms, economic via fi-
nances and wealth, and ecological via environmental and spatial arrangements.
Any one of these mechanisms may be used to identify the influence of family
lineage, but they frequently combine together.
Regardless of genetic background, ecology remains an important axis on
which to advance the study of cumulative inequality. Ecological context is im-
portant as a mechanism for family lineage (e.g., shared environmental exposure),
but this mechanism also unfolds over the life course. Moreover, status hierar-
chies are often correlated with spatial arrangements. For instance, poverty as
a form of social disadvantage is often concentrated in geographic areas. Indi-
viduals of lower socioeconomic status tend to live in impoverished neighbor-
hoods or rural areas that struggle to provide residents with social and economic
resources, such as formal services or employment opportunities. Beyond the
individual-level attribute of low income, there is the contextual effect of con-
centrated poverty that makes upward mobility more difficult to achieve. The
bulk of the literature identifies hazards associated with segregation or poverty
(Jackson, Anderson, Johnson, & Sorlie, 2000), but some forms of voluntary seg-
regation may be associated with higher levels of social capital, which may be
beneficial to physical and mental health (Lee & Ferraro, 2007). The point is that
social systems generate inequality on multiple levels, and scientists are giving
renewed attention to spatial effects in how inequalities develop.
Finally, multilevel models may have special utility for research on cumula-
tive inequality. This should be straightforward with the applying the contextual
or clustered-observations model for analyzing how ecological forces shape in-
equality. A second application of multilevel models may be in dealing with the
APC confound mentioned earlier. For time-specific social and behavioral phe-
nomena, each factor may have important explanatory relevance, yet because of
their linear dependency, each effect cannot be identified in standard applica-
tions of the general linear model. Yang and Land (2006) recently provided a
solution for the APC confound by using a multilevel model approach, thereby
allowing the analyst to examine explanatory factors at the level of age, period,
and cohort and account for random variability at each level.
This is an important breakthrough for the study of cumulative inequality
for at least two reasons. First, because social processes are inherently dynamic,
inequalities take form over time. Time, as the APC challenge makes clear, how-
ever, occurs in multiple dimensions (biographical, historical, and generational
time). A sound approach for studying age and inequality therefore must be very
cautious in its a priori assumptions about differences between persons located
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Handbook of Theories of Aging
within cohorts located within history and instead treat this multidimensionality
as an empirical question. Second, the multilevel-model strategy makes statisti-
cally explicit the issue of heterogeneity by isolating the different levels of time
and showing how much random variability exists at each level. A key assump-
tion of cumulative inequality theory is that inequality is rooted in the structural
components of social life, thus determining the extent of heterogeneity at age,
period, and cohort levels.
Five propositions are developed from this axiom:
a. Childhood conditions are important to adulthood, especially when differ-
ences in experience or status emerge early in the life course.
b. Reproduction is a fulcrum for defining life course trajectories and population
aging.
c. Influenced by genes and environment, family lineage is a key source of life
course inequality, especially for the early stages of the life course.
d. Cohorts provide the context for development, structuring risks, and oppor-
tunities.
e. Given the confounding of age, period, and cohort, investigators should
consider the inter- and intraindividual processes that lead to cumula-
tive inequality and seek to explain variability on multiple levels and/or in
multiple domains.
Table 22.1 summarizes each axiom and proposition and identifies relation-
ships between CI theory and other theoretical perspectives. The table is in-
tended not to be a comprehensive inventory but to identify key links in our
development of CI theory. We cite mostly theoretical works that most closely
link to our axioms and propositions, although the connections are less direct or
nonexistent in some cases.
Disadvantage Increases Exposure to Risk, but Advantage
Increases Exposure to Opportunity
The concepts of cumulative advantage and cumulative disadvantage have been
used to explain the processes by which cohorts become differentiated and how
the Matthew effect operates in shaping personal trajectories (Dannefer, 1988,
2003). Although Merton was focused on advantage, most applications of the
concepts of cumulative advantage and disadvantage have focused on disadvan-
tage or adversity (Hatch, 2005).
The underlying assumption for many scholars, however, has been that dis-
advantage and advantage accumulate inversely—the failure to accumulate ad-
vantage is presumed to be synonymous with the accumulation of disadvantage.
Although this is possible, it may mask potential differences in the processes.
Would we expect an advantage that is one standard deviation from the mean
to have the same magnitude (absolute value) of an effect as a disadvantage one
standard deviation from the mean? Most sociologists would likely attribute
greater impact to dis advantages than to advantages. Thus, it may be useful to
differentiate advantage from disadvantage, especially when testing differences
in a quantitative variable. For instance, rather than treating income as continuous,
Willson et al. (2007) found it useful to differentiate low income and high income
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(
continued
)
22.1 Relationships Between Axioms and Propositions of Cumulative Inequality Theory and
Other Theories or Perspectives
Axioms and propositions
(abbreviated) CAD (Dannefer, O’Rand) Life course (Elder)
Other theories or
perspective
1. Social systems generate inequality—
manifested over the life course via
demographic and developmental
processes.
a. Health risks related to
childhood disadvantage
(O’Rand & Hamil-Luker, 2005)
b. Family attributes affect health in
later life; intergenerational flows of
resources (O’Rand, 2003, 2006)
c. Cohorts shape the reproduction
of inequality (Dannefer, 2003;
O’Rand, 1996)
d. Inequality results from the
interplay “between institutional
arrangements and individual life
trajectories” (O’Rand, 1996, p. 230).
a. Childhood conditions affect
adult outcomes (Elder, 1998a;
Elder & Johnson, 2003)
b. Lives are interdependent
(Elder & Johnson, 2003; Elder &
Shanahan, 2006)
c. Life course “embedded in and
shaped by historical times and
places” (Elder, 1998b, p. 3).
a. Childhood conditions are pivotal
for life course development
(Bronfenbrenner, 1979)
b. The postreproductive period is
characterized by less physiologic
reserve (Waters, 2007)
c. Inequality is transmitted across
generations (Wickrama et al.,
2005)
d. Cohort flow is a vital process for
age stratification (Riley et al. 1972)
e. Multilevel models offer a rigorous
way to account for the APC
confound (Yang & Land, 2006).
a. Childhood conditions are important
to adulthood, especially when
differences in experience or
status emerge early
b. Reproduction is a fulcrum for defining
life course trajectories and population
aging
c. Influenced by genes and environment,
family lineage is critical to status
differentiation early in the life course.
d. Cohorts provide the context for
development, structuring risks and
opportunities
e. Consider inter- and intraindividual
processes and use analytical
techniques that explain variability on
multiple levels or in multiple domains.
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2. Disadvantage increases exposure to risk,
but advantage increases exposure to
opportunity.
a. Consequences of advantage may not
be the inverse of disadvantage
b. Inequality may diffuse across life
domains (e.g., health and wealth)
c. Trajectories are affected by the
onset, duration, and magnitude of
exposures.
a. Disadvantage accumulates
(Dannefer, 2003), leading to “other
disadvantages” (O’Rand &
Hamil-Luker, 2005, p. 117).
Advantage arises via “cumulative
process of differentiation”
(Dannefer, 1988, p. 16) or a
precocious work career
(O’Rand, 1996).
a. Behavioral consequences can
lead to “cumulating advantages
and disadvantages” (Elder,
1998a, p. 7)
b. Duration between transitions
affects individual outcomes
(Elder et al., 2003; Elder &
Johnson, 2003).
a. Risks exist in chains
(Kuh et al., 2003)
b. Disadvantages lead to additional
negative outcomes
(George, 2003)..
3. Life course trajectories are shaped
by accumulation of risk, available
resources, and human agency.
a. Human agency and resource
mobilization may modify trajectories
b. Turning points in the life course may
alter the anticipated consequences of
a chain of risk
c. The dialectic of human agency
and social structure is essential to
cumulative inequality
a. Modification of “cumulation
processes” possible only within
existing structural conditions
(Dannefer, 1988, p. 16)
b. Resource allocation shapes
life course outcomes
(Elman & O’Rand, 2004)
c. Institutions, agency, and chance
affect trajectories (O’Rand, 1996,
2003).
a. Resources and human agency
affect trajectories (Elder &
Shanahan, 2006; Hitlin &
Elder, 2007)
b. Study lives in motion (Elder,
1998; Elder & Shanahan, 2006)
c. Choice within structural
constraints (Elder & Johnson,
2003)
d. Resources affect rate of health
change (Willson et al., 2007).
a. Social and biological resources
can protect positive trajectories
(Hatch, 2005)
b. Personal agency affects stress
management and social
adjustment (Pearlin et al., 2005;
Settersten, 1999; Thoits, 2006).
22.1 Relationships Between Axioms and Propositions of Cumulative Inequality Theory and
Other Theories or Perspectives (
continued
)
Axioms and propositions
(abbreviated) CAD (Dannefer, O’Rand) Life course (Elder)
Other theories or
perspective
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d. Unfavorable trajectories can be
mitigated by the magnitude, onset, and
duration of resources; resources can
also accelerate favorable trajectories.
4. The perception of life trajectories
influences subsequent trajectories.
a. Social comparisons shape
trajectories
b. Favorable life review linked to
self-efficacy
c. Perceived life course timing
influences psychosomatic processes.
a. Perceptions of lived experience
influence the life course (Elder
& Shanahan, 2006).
a. Thomas theorem (Merton, 1995)
b. Mastery shaped by status
attainment, hardship, and coping
(Pearlin et al., 2007).
5. Cumulative inequality leads to premature
mortality, perhaps giving the appearance
of decreasing inequality in later life.
a. Cumulative inequality creates
compositional change in a population
b. Population truncation may give the
appearance of decreasing inequality
c. Test for selection effects
d. Interpret results in light of event
censoring and cohort inclusiveness.
a. Selective survival and sample
attrition affect assessments of
inequality in later life (O’Rand, 2003;
O’Rand & Hamil-Luker, 2005)
b. and d. Pseudovariable approach
for predicted probabilities with
incomplete data (O’Rand &
Hamil-Luker, 2005).
a. Selective mortality complicates
assessments of inequality
(Willson et al., 2007)
b. and d. Propensity scores
to account for nonrandom
selection (Willson et al., 2007).
a. Cohort flow is accompanied
by cohort shrinkage (Riley et al.,
1972)
b. Magnitude of inequality affected
by selective mortality (Noymer,
2001).
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422 Handbook of Theories of Aging
from a middling reference group, concluding that “long-term exposure to advan-
tage produces more gradual rates of over-time health decline, while long-term
exposure to disadvantage produces steeper rates of decline” (p. 1912, emphasis
added). Viewed from an analytic perspective, there is value in testing for non-
linear relationships.
The distinction between advantage and disadvantage is also important
because most people will simultaneously hold positions of advantage and dis-
advantage across life domains. A person may be economically advantaged but
health disadvantaged nonetheless (or vice versa). Although disadvantages may
cluster across a person’s life, it is better to identify hierarchies within the multi-
ple domains of the person’s life rather than to presume omnibus disadvantage.
Although many scholars use the terms disadvantage and risk interchange-
ably, we draw a distinction here as well. We define disadvantage as an unfa-
vorable position in a status hierarchy due to structural determinants and/or
behavior that reflects the past and the present circumstances of one’s life. By
contrast, we refer to risk as the probability of a hazard or negative event occur-
ring in the future. Once a risk eventuates in a negative outcome, it becomes a dis-
advantage; the pernicious cycle is that disadvantage heightens risk, which may
lead to subsequent disadvantage. O’Rand and Hamil-Luker (2005) argue that
“disadvantages lead to other disadvantages” (p. 117), and this is how many think
of the phrase cumulative disadvantage. Although we agree with their statement,
we believe that an important and logical next step is to identify the mechanisms
by which disadvantage accumulates. We think it is useful to first conceive of
disadvantage as increasing exposure to risks. This conceptualization provides
room for resource mobilization and/or human agency to modify the process of
how one disadvantage may lead to another (Settersten, 1999). Many trajectories
have been reshaped by adequate resources and/or compensatory actions on the
part of the person exposed to the risk (Thoits, 2006).
The mechanism specified herein is similar to a chain of risk as described
in life course epidemiology. The concept of a chain of risk refers to “a sequence
of linked exposures that raise disease risk because one bad experience or ex-
posure tends to lead to another and then another” (Kuh, Ben-Shlomo, Lynch,
Hallqvist, & Power, 2003, p. 779). Including risk in the conceptualization of how
cumulative inequality operates also permits one to conveniently integrate find-
ings regarding the onset and duration of exposures (Elder & Shanahan, 2006).
When studying health, long-term exposure to risk is typically more important
than short-term exposure, and this has been demonstrated in many studies
such as exposure to low income (Willson et al., 2007) and obesity (Ferraro &
Kelley-Moore, 2003; Schafer & Ferraro, 2007). The consequences of short-term
risk exposure are more equivocal because onset can vary more than is the case
for long-term risk exposure. Moreover, inequalities are shaped over the life
course as a result of the magnitude, time of onset, and duration of exposures.
Disadvantages accumulate within specific life domains (e.g., health and
wealth) but may also diffuse across domains. Negative health-related behaviors,
for example, may raise the risk of disease, loss of income, and poor mental health.
Given the tendency toward “stress proliferation—the propensity for stressors to
multiply and ‘spill over’ into life domains beyond that in which the original stress
occurred” (George, 2003, p. 170), it is likely that disadvantage in one domain may
influence other areas in one’s life (see also Pearlin et al., 2005).
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
Advantage, by contrast, refers to a favorable position in a status hierarchy.
Although advantage may reduce risk exposure, there is another process that
extends beyond risk reduction; advantage provides opportunities through dis-
tinct networks, resources, and prestige (i.e., Matthew effect). Opportunity refers
to the probability of future achievement, and structural advantage provides
greater opportunity. Seeding in tournaments is a simple illustration of this prin-
ciple. Top-ranked competitors face the lowest-ranked opponents in the early
rounds. Rankings do not guarantee success; they simply make it more likely.
One of the contributions from previous analyses of cumulative disadvan-
tage is how it may alter the life course in enduring ways. Considerable vari-
ability exists in the consequences of disadvantage, which are usually negative
(O’Rand, 2001) but can also be positive (e.g., health benefits of mild stress;
Minois, 2000). Future research should identify how advantage and disadvantage
shape opportunities and risks, which ultimately influence outcomes. Doing so
requires attention to how life course trajectories are shaped and may be modi-
fied in an unanticipated way (i.e., two-tailed statistical tests). We should not
underestimate the role of personal agency, especially for people who display
resilience (Masten et al., 2004).
Three propositions may be articulated from this axiom:
a. The consequences of advantage may not be the inverse of the consequences
disadvantage.
b. Many individuals hold positions of both advantage and disadvantage across
various life domains. Whereas inequality may diffuse across domains, it is use-
ful to integrate additional life domains into studies of cumulative inequality
(e.g., health and wealth).
c. Trajectories are shaped by the magnitude, time of onset, and duration of
exposures. By magnitude, we refer to the degree to which an exposure deviates
from a measure of central tendency (i.e., the severity or dose). (For exposure to
physical activity, how do sedentary and athletic lifestyles compare to an aver-
age amount of activity?) By duration of exposure, we refer to the length of time
that an individual experiences the condition (either risk or opportunity), and
onset refers to when the exposure began.
As shown in Table 22.1, life course theorists and scholars in life course epi-
demiology have given priority to the concept of risk and opportunity exposure.
Life Course Trajectories Are Shaped by the Accumulation of
Risk, Available Resources, and Human Agency
Trajectories do not develop in a vacuum; they are socially generated. We follow
George’s (2003) definition of trajectories as “long-term patterns of change and
stability” (p. 162) that exist across a variety of outcomes. Thus, each person has
many trajectories—examples include financial, functional, spiritual, and cognitive
trajectories—and scientists seek to track change and stability within and between
individuals on these outcomes. In physics, we think of a trajectory as the flight
curve of a projectile. When an object remains in flight, we have the known trajec-
tory (past) and a projection of the curve (future). Of course, outside forces may
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424 Handbook of Theories of Aging
alter future movement. When major change occurs in a flight curve, we think of
splines in the curve or inflection points to capture nonlinearities in the trajectory.
For example, one could argue that health is much more likely to change
with transition points and nonlinearities; rarely does it proceed in a simple lin-
ear fashion, especially because illness onset often entails a social encounter.
Thus, one way to conceptualize human trajectories is as a sequence of transi-
tions (e.g., loss of functional capacity). This may also involve entry into and exit
from different roles and “states” (Elder & Shanahan, 2006). Indeed, some transi-
tions involve turning points that can redirect trajectories and contribute to life
course discontinuities.
Rooted in social inequality, trajectories are strongly influenced by the ac-
cumulation of risk. As noted earlier, disadvantage increases exposure to risk,
which, in turn, may lead to further disadvantage. Hence, the tenet inequality
accumulates. Early disadvantage shapes the trajectory, most often bringing ad-
ditional risks. As the risks accumulate, further disadvantage is likely to result
unless measures are undertaken to offset the exposure to risks. A good start in
life can have long-lasting effects for the individual and the cohort of which he
or she is a member. This is not to say that the trajectory is fixed by early disad-
vantage, but that early disadvantage exposes one to additional risks—and early
advantage provides additional opportunities (Easterlin, 1987).
A common approach to studying the enduring effects of resources is by test-
ing an interaction term between age and the resource (e.g., Ross & Wu, 1996).
This has been helpful for advancing research on cumulative inequality, but we
think the research must move beyond this approach for at least two reasons.
First, as described in axiom 5, such tests are highly dependent on sample com-
position and may be indicative of cohort rather than age (maturational) effects.
Second, we assert that cumulative inequality is a more complex process than can
be described with one interaction term, whether with cross-sectional or longitu-
dinal data. We do not presume that the effect of early disadvantage is inexorable.
Rather, a key question for the study of inequality is discovering which forces can
alter the anticipated trajectory. (If not, what is the aim of public policy reform?)
Although some may interpret cumulative disadvantage to require both the long-
term effects of early disadvantage and heightened inequality in later life, we be-
lieve there are forces that can attenuate or counteract the consequences of early
disadvantage, perhaps leading to reduced inequality. Chief among the modifying
factors are available resources (Luthar, Cicchetti, & Becker, 2000; Merton, 1988;
Schieman & Meersman, 2004).
Figure 22.1 is presented to illustrate how resource mobilization is critical
to shaping trajectories—in this case how disability develops (Verbrugge & Jette,
1994). Although many studies of cumulative disadvantage focus on the long-
term consequences of early disadvantage, we present five cases that begin at
the same intercept but that diverge because of the onset and duration of re-
source mobilization. We contend that resource mobilization has the capacity
to retard the disablement process, but rarely can it stop it during adulthood.
In Figure 22.1, A represents the projected increase in disability without modifi-
cation, B indicates late and short-lived resource mobilization, C indicates early
and short-lived resource mobilization, D represents a trajectory affected by
relatively late and sustained resource mobilization, and E represents early and
sustained resource mobilization. These five trajectories were all disadvantaged
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
early, but their final observed levels of disability are affected by the timing of
the resources—onset and duration. Moreover, in our illustration, the resource
magnitude (or dose) was fixed. Parallel to axiom 2, however, we assert that un-
favorable trajectories may be mitigated by the magnitude, onset, and duration
of resources.
More generally, social, economic, and psychological resources can retard or
accelerate trajectories. Individuals have a convoy of social relations over the life
course, which may play a major role in shaping trajectories. Significant others
help define situations and provide meaning for decisions over the life course.
The information provided may not necessarily be correct or useful, but it helps
define the situation, whether or not the person realizes it. Economic resources
are recognized as the great compensator. As noted earlier, many tests of cumu-
lative disadvantage theory have focused on the advantages experienced by per-
sons with more education and higher incomes. Although financial resources are
not the panacea for personal problems, they enable one to more easily resolve
some disadvantages.
Psychological resources are also important in the development of trajecto-
ries, and there is a large literature on mind–body relations to underscore this
assertion. If early disadvantage increases the likelihood of perceived failure, an
individual may be less likely to envision overcoming the disadvantage. Conflict
resolution, adaptation, and social participation are examples of important life
course tasks, and psychological resources—both cognitive and emotional—are
important for performing such tasks.
22.1
Illustration of disability pathways affected by the onset and duration of resource
mobilization.
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426 Handbook of Theories of Aging
Structural influences are important for cumulative inequality theory (axiom 1),
but axiom 3 counterbalances the structuralist view by considering the dialectic
of structural forces and human agency. It is difficult to overstate the influence of
structural forces, but neither should one neglect the influence of human agency
(Hitlin & Elder, 2007). Some people face enormous disadvantage but emerge
remarkably well by resource mobilization or by choosing wisely and/or expend-
ing extraordinary effort (Thoits, 2006). Such cases may be less common, but
Black history in America provides exemplars to better understand the role of
human agency against staggering odds (e.g., Rosa Parks). As stated in axiom 2,
disadvantage increases exposure to risk, but axiom 3 is needed to identify tra-
jectories as the product of risk accumulation, available resources, and human
agency.
The importance of human agency in shaping trajectories is also manifest
in the systematic study of resilience. For instance, living through the economic
challenges of the Great Depression had a beneficial effect on mental health
for middle-class women (Elder & Liker, 1982), and growing up during the De-
pression had a positive mental health effect on children with good adaptation
(i.e., resilient) (Elder, 1974). Disadvantage is important, but social context and
human agency may transform apparent disadvantages into beneficial effects
(Thoits, 2006).
Four propositions are developed from this axiom:
a. Disadvantage accumulates, but trajectories may be altered by resource
mobilization and/or human agency.
b. Turning points in the life course may alter the anticipated consequences of
a chain of risk.
c. Human agency and social structure must be considered simultaneously in
the development of the life course trajectories.
d. Unfavorable trajectories can be mitigated by the magnitude, onset, and duration
of resources; resources can also accelerate favorable trajectories.
The Perception of Life Trajectories Influences
Subsequent Trajectories
Although the word trajectory may not be used, most people are aware of the
many changes they experience over the life course; it is their life story. Some
persons may look at change in a shorter time frame, while others use more of
a “wide-angle lens” for viewing their experiences. Indeed, lower socioeconomic
status may be associated with a shorter-term horizon for conceptualizing change
over one’s life because of the financial exigencies of everyday living. Neverthe-
less, people have a sense that things are getting better, worse, or staying about
the same. Cumulative inequality theory holds that perceptions of such change,
whether positive or negative, are related to the subsequent shape of the trajec-
tory (Carstensen, 2006).
In some ways, this may be viewed as an extension of proposition 3c
(i.e., structure–agency dialectic), but it also incorporates elements of symbolic
interactionism such as the Thomas theorem (Merton, 1995). People reflect on
their lives, become aware of their place in hierarchies, and develop ways of think-
ing about their position in a social system. One’s view of his or her status is not
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
structurally determined. It can be understood only in light of the structure, but
it is the perception of relative advantage or disadvantage that is most important.
Actors seek meaning for their position, and the interconnectedness of human
lives may predispose them to view their positions in ways that are parallel to
their associates (Elder & Shanahan, 2006). Moreover, people seek out associates
on the basis of their views, leading to homophily in reference groups.
The perception of upward socioeconomic mobility—real or imagined—may
give a psychological lift to other perceptions of life course trajectories (Ennis,
Hobfoll, & Schröder, 2000); see axiom 2b. The sense that one is doing better than
one’s parents, one’s siblings, or one’s own earlier experiences can be a source
of confidence. If a person feels that his or her life is progressing at a good pace
(e.g., ahead of one’s cohort), this may be cause for attempting more ambitious
activities or “coasting” after a gain has been reaped. Several studies show that
perceptions of one’s socioeconomic standing are better predictors of health than
are objective measures of status (e.g., Sapolsky, 2004). In addition, perceptions of
unmet need, regardless of actual need, have the power to elevate mortality risk
(Blazer, Sachs-Ericsson, & Hybels, 2005).
School and family reunions are occasions that prompt evaluations of per-
sonal change, an opportunity to benchmark accomplishments. Pivot ages, such
as 18, 21, 50, and 65, encourage one to consider life changes. The evaluations in
the early years are more likely to be linked to occupational status achievement,
while those in middle and later life are more likely geared to health issues or
the status achievement of children. These evaluations are an important part of
one’s sense of achievement, and negative evaluations may initiate psychoso-
matic processes.
The sense of progress toward the “good life”—or the lack thereof—is conse-
quential to well-being. A feeling of a lack of progress may stimulate one to work
harder or, alternatively, to cut back on efforts to get ahead. In the latter case, be-
lieving that “the system” cannot be beat may lead to a type of fatalism, perhaps
even a sense of resignation. In common vernacular, some people feel the wind in
their face and slow down; others push harder into it. Social, economic, and psy-
chological resources influence this disposition, but awareness of one’s past trajec-
tory is an important part of determining the shape of the future (Pearlin, Nguyen,
Schieman, & Milkie, 2007).
There is a fairly substantial literature regarding how affective states influ-
ence health (e.g., Ryff, Singer, & Love, 2004; Steptoe, Wright, Kunz-Ebrecht, &
Iliffe, 2006). Scores of studies show that dispositional optimism is correlated
with health behaviors but that it has independent effects on health beyond
simply avoiding behaviors such as smoking and excessive calorie consump-
tion. Unfavorable life reviews, therefore, are likely to lead to more hopelessness
and pessimism, which in turn have been shown to elevate mortality risk among
older people (Stern, Dhanda, & Hazuda, 2001). We see both a direct effect of
optimism on health as well as an indirect effect via selective participation in
behaviors that can aid or compromise health.
Three propositions are derived from this axiom:
a. Personal review of the life course entails social comparisons about progress
on trajectories.
b. A favorable review of a trajectory is associated with self-efficacy.
c. The sense of one’s life course timing may influence psychosomatic processes.
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428 Handbook of Theories of Aging
As shown in Table 22.1, Elder and Shanahan (2006) contend that perceptions
of lived experience are consequential over the life course. Dannefer and Uhlen-
berg (1999) acknowledge the symbolic interest of life course scholars but do not
discuss how perceptions of life trajectories influence subsequent trajectories.
Cumulative Inequality May Lead to Premature Mortality;
Therefore, Nonrandom Selection May Give the
Appearance of Decreasing Inequality in Later Life
A basic premise of cumulative inequality theory is that inequality is consequen-
tial over the life course. Although it may be beneficial for some persons, espe-
cially those who are socially advantaged or possess a higher-than-average level
of psychological resources (e.g., resiliency), cumulative inequality is likely to be
deleterious for those who are structurally disadvantaged or exposed to many
risks. If the risks accumulate to influence health, then accumulated disadvan-
tage will result in premature mortality. Indeed, dozens of epidemiologic inves-
tigations show the importance of how social inequality is linked to mortality
(Jackson et al., 2000). As Willson et al. (2007) recently concluded, “The process
of cumulative inequality in health is shaped by the finite nature of the human
life span and confronts forces of senescence and mortality over time” (p. 1892).
Although it may seem pedantic that social inequality is related to mortality risk,
the consequences of this may not be fully appreciated. The difficulty exists in that
the premature mortality associated with accumulated risks—selective survival—
will result in compositional change to a population. Cohorts shrink in a nonrandom
manner, leading some to refer to this process as leveling population heterogeneity.
Moreover, it is possible that “cohort inversion” may occur: a cohort that was initially
disadvantaged may appear better than before because mortality selection will re-
move persons with the most health problems from the population. Thus, mean
scores may rise, giving the appearance of decreasing inequality (Noymer, 2001).
When characterizing an older adult population, it is tempting to refer to it as
beset by disease, disability, and depression. Assuredly, these and other health-
related outcomes are present, but the older adult population that survives may
also be described as an elite—at least in comparison to those members of its
cohort who died earlier. Perhaps more than any other distinguishing character-
istic, the fact that advanced age represents survival speaks to the compositional
change as cohorts age.
Both demographers and proponents of age stratification theory have long
noted the importance of cohort shrinkage when interpreting the aging process
(Riley, Johnson, & Foner, 1972). A recent article by Dupre (2007) uses multilevel
models to effectively separate changes due to sample compositional from those
due to the individual-level trajectory. His findings reveal that two hypotheses
that have long been seen as competing—cumulative disadvantage and aging as
leveler—are actually complementary. In studying the relationship between ed-
ucation and disease, Dupre found that compositional change led to a leveling of
differences but that individual-level processes reflected cumulative disadvan-
tage. This is a promising way to consider the importance of both compositional
change and individual trajectories, reflecting the demographic and develop-
mental processes involved in the accumulation of inequality (axiom 1).
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
It is also important to recognize more generally that special care needs to
be given to interpreting the findings of cohort-centric studies designed to test
cumulative inequality. Previous tests of cumulative disadvantage have been per-
formed on samples of various ages; examples include 22 to 42 (Elman & O’Rand,
2004), 25 to 74 (Dupre, 2007), and 65 to 74 (Holland et al., 2000). The diversity
in designs is good, but what if inconsistent findings on the same topic emerge
from cohort-inclusive and cohort-centric studies? Although one may be drawn
to the cohort-inclusive study for more compelling results, that study would have
greater opportunity for nonrandom selection to be observed. If the investiga-
tors examined and tested for how the nonrandom mortality might shape the
conclusions, the cohort-inclusive study may be preferred. If the investigators
fail to account to selective mortality, however, there is probably a greater chance
to be misled by the cohort-inclusive study. If nonrandom mortality is substan-
tial, this may give the appearance of decreasing inequality.
Nonrandom mortality selection speaks more generally to the concept of
event censoring. We assert that left and/or right censoring of events is criti-
cal to interpretations of cumulative inequality. For example, the Longitudinal
Study on Aging II is a national sample of persons 70 years or older and contains
exemplary information on functional limitations and disability. If one used this
study to examine Black/White differences in disability, the higher mortality risk
among Black people may make it more difficult to observe cumulative inequal-
ity because frail Black persons would likely be eliminated from the analysis.
This may give the appearance of little or no racial difference in disability.
The issues of selection bias and event censoring are keener when one rec-
ognizes that surveys and experiments often add another layer of nonrandom
selection. If experiments rely on volunteer subjects, the bias is often obvious.
Even for surveys, however, the ability to respond is a favorable attribute. Persons
in institutions and those physically or cognitively unable to respond to sur-
vey questions are often excluded. For longitudinal studies, the situation is even
more complicated because continued availability and willingness to respond
likely results in a positive bias in the sample subjects who provide the most
data. Indeed, longitudinal research demonstrates how subjects with complete
data often have less disease, disability, and depression at the study’s start than
those with incomplete data (Kelley-Moore & Ferraro, 2005).
All these processes converge to truncate a sample, and much of the trun-
cation is probably due to social inequality. If inequality-induced truncation is
operant, the distribution of inequality itself is bound to change over time. As
such, it is likely that both population and sample truncation will result in the
appearance of decreasing inequality in middle or later life. Investigators need
to account for nonrandom selection in their generalizations regarding the ef-
fects of cumulative inequality on what may appear to be an increasingly select
population and sample. With cohort shrinkage, investigators also need to test
for statistical power to be certain that the lack of significant relationships is not
due to insufficient power.
Four propositions are derived from this axiom:
a. Cumulative inequality will likely result in compositional change as a popu-
lation ages; the greater the inequality, the more compositional change will
transpire.
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430 Handbook of Theories of Aging
b. Population truncation and nonrandom selection in samples may give the
appearance of decreasing inequality.
c. Studies of cumulative inequality should apply methods to test and, if need be,
account for nonrandom selection.
d. The limitations of cohort-centric studies of cumulative inequality, especially if
carried out within a narrow historic period, should be clearly identified. Schol-
ars should attend to how event censoring may constrain conclusions.
As shown in Table 22.1, O’Rand (2003) and Willson et al. (2007) identify
how selective survival and sample attrition may influence the assessment of
inequality in later life.
Conclusion
Sociologists have long been interested in the pervasive and enduring effects of
disadvantage such as poverty or child abuse. Research shows that such adversi-
ties may continue to affect individuals throughout the life course and that the
disadvantage may compound over time. This is especially the case when the
disadvantage is experienced early in life and/or when the available resources
at the time of the original experience are not sufficient to compensate for the
potential negative effects. In this context, we seek to better explain how inequality
accumulates.
The five axioms and 19 propositions were presented to articulate a theory
to explain core processes of how inequality accumulates over the life course.
Cumulative disadvantage has proved to be an intriguing model of stratification
processes, but we sought to provide greater formality to the model in order to
develop a theoretical perspective with more elements subject to falsification.
We have drawn from cumulative disadvantage, life course, and other theo-
retical perspectives to synthesize a framework that provides new insights into
the development of cumulative inequality. Part of our effort has been to seek
points of integration between CAD and life course theory. Although the former is
focused on population and cohort differentiation (Hagestad & Dannefer, 2001),
we believe that much can be gained by the synthesis outlined herein. In doing so,
cumulative inequality theory privileges the structural generation of inequality
but counterbalances it with the structure–agency dialectic. Moreover, we do not
view cumulative inequality as solely disparities in outcomes; rather, we view it as
the process that leads to disparities in outcomes across the life course.
Note
1. Sociologists have shown keen interest in the concepts of cumulative advantage and
disadvantage. This has been manifest in the study of earnings (Crystal & Shea, 1990), crime
(Sampson & Laub, 1997), disease (Dupre, 2007), and health (Ross & Wu, 1996) as well as
in DiPrete and Eirich’s (2006) recent review of how cumulative advantage operates as a
mechanism for inequality. Dale Dannefer (1987, 2003) has been one of the major architects of
what he refers to as cumulative advantage/disadvantage theory (CAD) for understanding life
course inequality and growing heterogeneity in later life. He defines CAD as the “ systematic
tendency for interindividual divergence in a given characteristic (e.g., money, status) with the
passage of time” (Dannefer, 2003, p. 327). His focus has been on “a set of social dynamics that
operate on a population, not individuals” (Douthit & Dannefer, 2007, p. 224).
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Chapter 22 Cumulative Inequality Theory for Research on Aging and the Life Course
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