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4
Networks, Neighborhoods, and Institutions: An Integrated “Activity
Space” Approach for Research on Aging
Kathleen A. Cagney, Christopher R. Browning, Aubrey L. Jackson, and Brian Soller
The concept of community, both physical and social, has been central to social science
inquiry on aging. Notions such as aging-in-place are predicated on the assumption that older
adults would prefer to continue residing where they have established social ties and routines and
where they have experienced seminal events over the life course. Research suggesting these
preferences (Evans, Kantrowitz, and Eshelman, 2002; Rowles, Oswald, and Hunter, 2003),
coupled with a burgeoning literature on neighborhood context effects across age groups (e.g.,
Sampson, Morenoff, and Gannon-Rowley, 2002), has led researchers on aging to examine the
features of neighborhood context most salient for older adult well-being. In this chapter, we
focus on the conceptualization and measurement of the social space that older adults inhabit,
exploring implications for research on residential context. We approach this review broadly,
incorporating research on social networks and institutional contexts that bear on the
interpretation of “neighborhood effects.” Our initial aim is to illustrate that community can take
many forms, and that networks, neighborhoods, and institutions, independent or interdependent,
combine to shape the social environment in which older adults are embedded. Our subsequent
aim is to argue that neighborhood effects research would benefit from alternative
conceptualizations of the relevant spatial unit of analysis. We argue that residents, through their
actions, define the activity space that they traverse and collectively constitute communities of
routine interaction. This approach requires both new theory and new methods, which we
elaborate upon later in this chapter.
We begin by reviewing literature focused on the dyad or network in social interaction.
We then shift to the neighborhood-level, describing select work that has been influential in the
field and that brings insight to neighborhood-aging analyses. Next we review literature on the
role of institutions and their import in understanding how networks and neighborhoods may be
connected. This concludes our initial aim. We then turn to an overview of a multi-contextual
theoretical perspective on the social context of aging anchored on the concept of “activity space”
(that is, those places and spaces in which one engages in routine activities). We close with
suggestions for future directions in context-related research in aging.
SOCIAL NETWORKS
Extant research suggests that the quality, extent, and type of social network ties are
consequential for health. Reviews and theoretical expositions of this extensive literature can be
found elsewhere (e.g., Berkman et al., 2000; Uchino, 2006) so we highlight the literature most
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relevant for older adults. Focusing first on the quality of social network ties, Thomas's (2009)
analysis of data from the Social Networks in Adult Life survey indicates that receiving and
providing social support are associated with better well-being among adults ages 50 and older,
although these associations vary by the type of relationship to the alter (i.e., nominated network
member) and the number of alters supported. Using longitudinal data from the Midlife in the US
study, Seeman et al. (2010) find that frequency of social contact and social support are positively
associated with cognitive function.
An expanding literature has emphasized patterns of change in network size as adults age
and the implications of the extent or quantity of social ties for health and well-being. For
instance, Cornwell, Laumann, and Schumm (2008), using data from the National Social Life,
Health and Aging Project, find that older respondents report smaller networks and decreased
closeness with network members. The volume of contact with network members also varies by
age; contact volume tends to decrease with age until adults reach their mid-60s, at which point
the association between age and contact flattens. Beginning in their mid-70s, however, the
authors observe a positive association between contact volume and age. This U-shaped
relationship may reflect changes in ties to social institutions—such as work—and an increased
need for care late in life. Aartsen et al. (2004), based on a Dutch sample, find that as adults age,
their networks increasingly consist of family members, although network size interacts with
cognitive and physical decline to determine the network replacement of neighbors and friends
with family members.
Finally, using longitudinal data from the Health Professionals Follow-up Study, Eng et al.
(2002) find that over a 10-year period, older adult men are at a greater risk of mortality across
multiple causes of death if they have fewer social ties. They also find socially isolated men have
an increased risk of fatal coronary heart disease. Differences in network size across the life
course may have significant implications for health and well-being. Loneliness may be one
manifestation of decreased social ties and the concepts of loneliness and social isolation have
received increasing attention in research on aging (e.g., Hawkley et al., 2008). A meta-analysis
of research on adults’ loneliness suggests social contact, especially the quality of contact and
contact with friends, is protective against loneliness (Pinquart and Sorensen, 2003). Cacioppo et
al. (2006) find that loneliness is positively associated with subsequent depression net of initial
depressive symptoms.
Recent research has also emphasized the type and structure of social networks within
which older adults are embedded and their implications for health. Litwin and Shiovitz-Ezra
(2006), for instance, find that the association between network type and mortality was important
primarily to persons 70 and older; those in diverse, friend-focused, and, to a lesser extent,
community-clan networks experienced lower risk of all-cause mortality. Cornwell (2009)
examined patterns of network bridging among older adults (an individual acts as a “bridge” if he
or she connects two otherwise disconnected individuals). Individuals who occupy bridge
positions within their networks are hypothesized to benefit from improved access to diverse
resources and better control over the exchange of information and resources between network
members. Cornwell finds that older adults are more likely to serve as bridges if they exhibit good
cognitive and functional health.
Research on networks and aging has also considered the potential downside of network
embeddedness. Cornwell and Laumann (2011) find that the frequency of contact between a
man’s female partner and his network members (i.e., partner betweenness) contributes to male
sexual dysfunction, arguing that overlapping networks between heterosexual partners
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undermines a man’s independent control of social resources—contrary to traditional notions of
masculinity. These findings are consistent with research emphasizing the potential for
detrimental effects of social connections (Baum 1999; Browning, Feinberg, and Dietz 2004;
Lynch et al., 2000; Portes 1998) and relates to a developing literature that emphasizes
contingencies in the impact of social ties depending on features of the relationships and networks
in which older adults are embedded.
NEIGHBORHOOD CONTEXT
Research in psychology suggests that attachments to place grow stronger with age
(Gitlin, 2003; Zingmark, Norberg, and Sandman, 1995). The immediate neighborhood
environment is typically understood to play an increasingly important role in shaping daily life as
retirement and mobility limitations diminish the radius of routine activity, although the claim that
neighborhood exposures grow more relevant with age has not been directly tested (Cagney and
York Cornwell, 2010). Older adults also experience comparatively lower rates of residential
mobility. In 2000, only 4 percent of adults aged 65 and older changed residences in the past year
compared to 15.6 percent of the younger population. As older adults age in place, the
opportunities and constraints presented by their neighborhood environments become increasingly
relevant to health and well-being (He, Sengupta, Velkoff, and DeBarros, 2005). The findings
below are consistent with the claim that neighborhoods are consequential for older adult health,
with patterns of influence varying by individual-level factors such as stage in the life course,
gender, and race. Drawing on key theoretical approaches that have been used to frame research
on neighborhoods, we review health-related implications of neighborhood social structural and
social process environments for older adults.
Research on the neighborhood context of health across the life course has drawn heavily
from social disorganization theory—a longstanding theoretical approach with roots in the
Chicago School of sociology. Social disorganization theory proposes that neighborhood
structural characteristics—concentrated economic disadvantage, racial or ethnic heterogeneity,
and residential instability—influence the shared capacity of residents to achieve common goals
and maintain effective social control (Sampson, 2003; Shaw and McKay, 1969). Poverty limits
the availability of resources (including time and material) that can be deployed toward local
ends; residential instability hampers the development of neighborhood social networks and
weakens incentives to participate in voluntary organizations serving the community, and
racial/ethnic heterogeneity may inhibit the development of ties across communities divided by
language and customs—although typically not shared values regarding community functioning
(e.g., norms regarding a crime-free environment). While originally used to explain the
differential distribution of crime and delinquency rates across urban areas, social disorganization
theory has been enlisted to better understand the clustering of poor health outcomes, with
increasing attention to older adult morbidity and mortality (Cagney, Browning, and Wen; 2005;
Wen and Christakis, 2005).
Of the three structural factors emphasized in the social disorganization approach, research
on the effects of concentrated economic disadvantage is most common in studies of health and
older adult well-being (e.g., Freedman, Grafova, and Rogowski, 2011). Poverty and other
indicators of socioeconomic disadvantage are associated with greater risks of mortality (Diez
Roux et al., 2004) and morbidity (Merkin et al., 2007), as well as declines in mental health
(Aneshensel et al., 2007), mobility (Lang et al., 2008), and self-rated health (Cagney, Browning,
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and Wen, 2005). Although this research consistently finds detrimental effects of neighborhood
structural disadvantage, Cagney et al. (2005) find that the prevalence of affluent residents
exhibits more robust associations with self-rated health than does disadvantage. Regardless of
the operationalization, a growing body of evidence suggests that neighborhood socioeconomic
status (SES) matters for the health of older adults, with some research finding evidence that
neighborhood SES explains older adult health disparities between race groups (Cagney,
Browning, and Wen, 2005; Yao and Robert, 2008).
Increased attention to neighborhood context has led researchers to consider the conditions
under which neighborhood structural factors exert more pronounced influence. For instance,
research suggests that individual-level SES (Wen and Christakis, 2005) and race (Diez Roux,
2004) may moderate the relationship between neighborhood SES and older adult health
outcomes. Yao and Robert (2008) find that neighborhood disadvantage explains baseline
differences in self-rated health but not changes over time. Robert and Li (2001), however, find
that neighborhood SES has the strongest effect on adult health at middle ages, its effect
diminishing during early and late adulthood. Some research also suggests that neighborhood
SES has little or no effect at older ages (Waitzman and Smith, 1998), perhaps due to selective
mortality or study outcomes—such as mortality—that often are rare at younger ages (Glass and
Balfour, 2003). Finally, LeClere, Rogers, and Peters (1997) find the changing influence of
neighborhood SES across ages may vary by race.
Findings on the effects of racial and ethnic composition of neighborhoods have been
equivocal. The Latino Paradox suggests that despite typically socioeconomically disadvantaged
communities, Latinos tend to benefit from residence in highly immigrant or Latino-concentrated
neighborhoods. Research suggests that such high concentrations may be protective against
stroke, cancer, hip fracture, and mortality (Eschbach et al., 2004) as well as depressive symptoms
(Ostir et al., 2003). Yet research also finds that the proportions of blacks and Hispanics in a
neighborhood are positively associated with depressive symptoms (Aneshensel et al., 2007).
Alternatively, some studies suggest that black concentration has no effect on depressive
symptoms (Subramanian et al., 2006) or on self-rated health (Hybels et al., 2006; Kubzansky et
al., 2005).
Residential instability generally has been shown to be detrimental to health, including
outcomes such as self-rated health (Subramanian et al., 2006) and disability (Beard et al., 2009).
Research also suggests that residential instability may influence perceived social environmental
stress (Schulz et al., 2008). In contrast, Hybels et al. (2006) find no association between
residential instability and depressive symptoms.
A fourth structural factor also has been considered in research motivated by the social
disorganization framework—age (Cagney, 2006). Studies show that older adults benefit from
high concentrations of older adults in their neighborhoods. Elevated concentrations are
associated with better self-rated health (Subramanian et al., 2006), mental health (Kubzansky et
al., 2005), and are protective against older adult mortality during disasters (Browning et al.,
2006). But as with residential instability, Hybels et al. (2006) find no effect of neighborhood age
structure on depressive symptoms. A related finding suggests that for older adults who have lost
a spouse, aspects of neighborhood composition, such as the proportion of widowers, shape
opportunities for interaction, social connectedness, and, ultimately, mortality (Subramanian,
Elwert, and Christakis, 2008).
Finally, a related structural construct focuses on characteristics of the built environment,
including physical features of the environment as well as the quality of local amenities. We
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include discussion of the built environment within the larger body of research on structural
features because the type and quality of infrastructure can either facilitate or inhibit social
interaction. Research suggests that heavy traffic, excessive noise, inadequate lighting, and poor
sidewalks may discourage physical activity among older adults (Balfour and Kaplan, 2002;
Gallagher et al., 2010; Giles-Corti and Donovan, 2002; Mendes de Leon et al., 2009; Strath,
Isaacs, and Greenwald, 2007). Older adults may be particularly responsive to specific aspects of
the built environment (e.g., walkable sidewalks, curb cuts) since physical limitations are more
prevalent; mobility declines or inability to drive may mean that neighborhood conditions
favorable to walking become more salient for older adults’ healthful living (Clarke, Ailshire, and
Lantz, 2009). The press-competence model suggests that individual competencies interact with
environmental conditions to influence health outcomes (Glass and Balfour, 2003).
Relatively few studies of neighborhood influences on aging-related outcomes have
directly measured the social processes thought to mediate the influence of neighborhood
structural characteristics on older adult health. An emerging literature, however, draws on recent
data collection efforts that attempt to assess the social climate of (largely urban) neighborhoods
in which older adults reside. Findings from this incipient literature suggest that features of the
social environment such as characteristics of neighbor networks and “collective efficacy”—the
level of mutual trust and willingness to intervene on behalf of shared local goals—may
independently contribute to older adult well-being. Wen and Christakis (2005), for instance, find
that a higher quality social environment—as measured by levels of collective efficacy, social
support, participation in voluntary associations, and (lower levels of) perceived violence—
prolongs survival following disease onset. Browning et al. (2006) find that collective efficacy
protects against mortality among older adults, although this effect fails to persist under extreme
conditions (i.e., during a heat wave). In contrast, however, Mendes de Leon et al. (2009) find
neighborhood-level social cohesion is not associated with walking after accounting for
individual-level perceptions of social cohesion.
Some investigators have examined the extent to which social process measures and
perceptions of them vary by key demographic indictors such as age. For instance, Galinsky,
Cagney, and Browning (2012) compare two measures of collective efficacy, one originally
developed through the Project on Human Development in Chicago Neighborhoods (PHDCN)
and the other through the Neighborhood Organization, Aging and Health Study (NOAH). The
measure developed for NOAH substituted some of the original collective efficacy items of the
PHDCN related to informal monitoring of children with those believed to be more relevant for
older adults (e.g., neighbors shovel snow, neighbors check on older adults during a heat wave,
neighbors intervene to protect a threatened older adult). Both the original and older adult
versions performed well, but item non-response was much improved with the measure tailored
for older adults (suggesting that respondents were more interested in, or better able to answer,
questions when the substance resonated with their experiences).
Research on the neighborhood context of older adult health remains incipient, but
suggests the importance of neighborhood environments in shaping health outcomes.
Neighborhoods may create opportunities for positive social network influences to take hold, as
described earlier, and may foster the presence of institutions that promote older adult well-being.
We now turn to a description of these institutions, highlighting the type and form that bear on the
lives of older adults.
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INSTITUTIONS
Institutional settings, both formal and informal, can be critical to older adult social
integration and may have downstream effects for health. Sociological research like Slim’s Table
(Duneier, 1994) illustrates the import of local gathering places, such as restaurants, for the
maintenance of social connections. And Hochschild’s classic The Unexpected Community:
Portrait of an Old Age Subculture (1973) intimates that community can be created though any
number of institutional forms.
In this chapter we consider institutions to be physical locations where some form of
organized social activity takes place. Our focus is on institutional settings that promote social
integration and social and physical contact. When initially considering institutional settings that
may be important to aging, care arrangements such as formal long-term care facilities, home care
services, and hospitals and other health services may come to mind. While we acknowledge that
these institutional arrangements are critical for the well-being of older adults, their reason for
being stems from health and long-term care service delivery. We choose instead to focus on the
types of institutions that might not readily be identified with older adults or care provision, but
that serve to link older adults to one another, and to the community, and indirectly influence
health and well-being.
The density and quality of the institutional environment may have important implications
for older adult health and may also mediate the influence of residence in a disadvantaged
neighborhood context on aging-related outcomes. We consider institutional involvement and
access across a continuum from more formal organizations, to availability and quality of local
businesses, to informal and unstructured but patterned interaction. For instance, older adults’
involvement in religious organizations has been the subject of extensive inquiry (e.g., Dupre,
Franzese, and Parrado, 2006; Norton et al., 2008). However, a wide variety of institutions may
be relevant to shaping the quality of daily life for older adults and providing access to ongoing
sources of support (e.g., community-based senior centers) (Miner, Logan, and Spitze, 1993).
Participation in voluntary organizations and even regular but informal gatherings in local
restaurants, clubs, or recreational facilities may contribute to a richer social experience.
Increasing evidence suggests that organizational and institutional involvements have
beneficial effects for older adults. York Cornwell and Waite (2009) find that social
connectedness based on personal and group-oriented ties is positively associated with self-rated
health and mental health. Shankar et al. (2011), with cross-sectional data from the second wave
of the English Longitudinal Study of Ageing, find that increases in loneliness as well as increases
in a combined measure of social isolation from family, friends, organizations, religious groups,
and committees are associated with greater likelihood of inactivity, a heightened risk of smoking,
and higher systolic and diastolic blood pressure. And, Eng et al. (2002) find religious service
attendance and participation in social groups each is associated with a decreased risk of all-cause
mortality.
Caveats in this body of research include cohort differences that are not examined and
results related to age that are equivocal. Some research (e.g., Putnam’s Bowling Alone [2000])
suggests that successive cohorts will neither have the taste for organizational involvement nor
the range of formal organizations to join. On age, Bukov, Maas, and Lampert (2002) examined
social participation among adults ages 70 and older. They find that social participation is more
likely among those with greater educational and occupational resources, and that declines in
participation are explained, in part, by aging and declines in health. In contrast, Cornwell et al.
(2008) find that age is positively associated with religious service attendance and volunteering.
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Collecting more precise data from older adults on their specific institutional involvements could
potentially contribute to an understanding of disparate findings related to age.
Evidence pointing to the role of institutional and organizational participation in older
adult well-being highlights the need for a better understanding of the processes that shape access
and opportunity. Critically, geographic isolation may limit access to beneficial health-related
facilities, food outlets, recreational activities, and other amenities. Such isolation is pronounced
in rural areas (Durazo et al., 2011), although differences within urban and suburban areas also
exist. Pearce, Witten, and Bartie (2006) found substantial variation in proximity to health-related
institutions—including shopping, education, and recreation—between rural and urban areas and
within urban areas of New Zealand. In the United States, low SES neighborhoods are less likely
to have recreational facilities (Moore et al., 2008) and free-for-use physical activity resources
(Estabrooks, Lee, and Gyurcsik, 2003) than are higher SES neighborhoods. Research also
suggests that residents in predominantly white neighborhoods are more likely to have better
access to healthful food outlets, such as supermarkets, than those residing in predominantly black
neighborhoods (Morland et al., 2002; Zenk et al., 2005). Finally, Yamashita and Kunkel (2011)
assessed older adults' access to healthful food outlets in Hamilton County, Ohio. They find older
adults are concentrated in areas with lower densities of healthful food outlets and conclude that
the majority of older adults in the county do not live within walking distance of such an outlet.
Institutional and organizational involvement appear consequential for older adult health,
but differentially accessible by geographic location. Although individuals’ predispositions to
avail themselves of local institutional opportunities clearly differ, teasing out the
interrelationships between opportunity, inclination, and participation is difficult. The role of
institutions, and the social network connections they provide, may be better understood with
better data. For instance, more precise information could capture not only the institutions
frequented but their physical location, and the extent to which other social network members
spend time there.
CHALLENGES
Despite the substantial promise of research on the social context of aging, this area of
inquiry has faced a number of challenges. Although the criticisms directed at contextual
research are not unique within the social sciences, addressing these issues has proved particularly
vexing given the nature of the questions and the data typically involved. We focus on three
major challenges to the literature: (1) the tendency for contextual research to be “silo’d” with
respect to both theoretical formulation and empirical execution; (2) difficulties in establishing the
causal impact of context on health; and (3) the substantial data and measurement shortfalls of
existing resources. These challenges may apply to contextual research more generally, but
specific aspects are particularly consequential for research on aging and will be discussed in
detail accordingly.
Silos in Contextual Research and Implications for Theoretical Integration
As suggested in our review of the extant literature on the social context of aging, the role
of network, residential neighborhood, and institutional contexts in shaping aging-related
processes cannot be easily disentangled. For example, theories of neighborhood effects on
health often invoke the influence of local institutions and access to neighbor networks as key
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mechanisms (Sampson, Morenoff, and Gannon-Rowley, 2002). Institutional influences are
difficult to understand in the absence of information on the local embeddedness of these
organizations and their capacity to extend influence beyond the most formal aspects of
organizational involvement through informal network processes. In addition, face-to-face social
network interactions always occur in a geographic and more or less structured social setting.
Understanding the emergence and quality of social networks as sources of support for older
adults may require richer information on the settings that shape and sustain social networks.
These points highlight the inherent limitations of “uni-contextual” theoretical approaches
to understanding social influences on health. Indeed, as Cook (2003) argues, the restricted scope
of contextual studies leads to a number of potential concerns about the nature of extant findings.
First, focusing on an arbitrarily limited set of contexts precludes assessment of the combined
effects of multiple relevant contexts on aging-related outcomes. A joint contextual effect may be
substantially greater than the effect of any given context in isolation. As noted, studies that
simultaneously incorporate information on networks, neighborhoods, and institutions are
exceedingly rare. Second, accounting for only a subset of older adult exposures may lead to
biased contextual effects (i.e., if effects of measured contexts on individual outcomes are
confounded with omitted characteristics of unmeasured contexts). Third, simultaneous
assessment of multiple contexts allows insight into inter-context mediational processes that more
limited-scope approaches cannot detect. Fourth, research designs that incorporate a limited
number of contexts restrict the capacity to assess the influence of inter-context interactions on
older adult outcomes (e.g., the negative impact of a disadvantaged neighborhood may be
buffered by participation in highly supportive institutions such as churches or community
centers). These concerns point to the need for theoretical approaches and data collection efforts
that explicitly consider the multiple contexts relevant to older adults
Although our review highlighted emerging areas of research that attempt to combine
contextual influences, these efforts remain the exception. In some instances, this may be due to a
tendency to underemphasize theoretical motivation. For instance, although some neighborhood
research has drawn on theory to combine an emphasis on the effects of social structural
characteristics on older adult health with attention to the mechanisms—such as social cohesion—
that may explain structural effects, this literature remains incipient. Indeed, some have argued
that neighborhood research on older adult populations has tended to neglect theory (Macintyre
and Ellaway, 2003). In their comprehensive review of articles published between 1997 and 2007,
Yen et al. (2009a) identified 33 articles on neighborhoods and older adult health. Only three of
these publications explicitly mention a theoretical model.
Incorporating theory in contextual research more generally will help better elucidate the
processes that link contexts with health for older adults and draw attention to the inherently
interconnected nature of social contexts as they shape older adult outcomes. Substantial advances
in this area, however, will require more complex theoretical models that explicitly acknowledge
the multifaceted nature of social contextual influence. Extant theoretical models point toward
this insight, but few efforts to understand the simultaneous and interactive effects of social
network, geographic, and institutional influences have been attempted.
Causality and Selection
A second challenge relates to the seemingly intractable problem of establishing causality
in studies of social context effects on health. Such studies face the inevitable criticism that
individuals who select into disadvantaged contexts may be at high risk for poor health outcomes
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at the onset. One could argue that selection is an even more intractable problem for research on
older adults since it could be compounded by time and residential history in ways we cannot
address with available data (e.g., Li and Ferraro, 2005). In the neighborhood literature, for
instance, substantial attention has been devoted to determining whether observed effects of
neighborhood variables are compositional or contextual in nature. Compositional effects are
attributable not to the context itself, but to the aggregation of similar individuals who
consequently have comparable health outcomes. If only compositional effects exist, then
relocation to a new context would not produce different health outcomes as individual-level traits
persist. Compositional effects may be observed because individual traits that influence health
also help determine where people live either through selective migration or through constraints
on mobility. Furthermore, selection or constraint criteria may change over the life course.
Compared to younger adults, older adults benefit less from services such as public schooling, and
they likely have less flexible budgets if retired. It is therefore not surprising that low property
taxes, for example, help determine whether and to where older adults move (Duncombe et al.,
2001; Hui, 2010; Sabia, 2008). Neighborhood residence also may be determined by an
individual’s health. Relocation or the expectation of moving is associated with changes in
physical limitations, self-rated health, cognitive impairment, and proximity to a child (Sabia,
2008; Silverstein and Angelelli, 1998).
Unlike compositional effects, contextual effects are not attributable to aggregated
features of individuals; hence, similar people may experience different health outcomes
depending on their contextual exposures (Curtis and Rees Jones, 1998; Macintyre and Ellaway,
2003). Multilevel modeling techniques enable researchers to better distinguish compositional
from contextual effects. These analytic strategies allow context- and individual-level effects to
be modeled simultaneously, thereby allowing researchers to distinguish variance in individual
outcomes attributable to neighborhood versus individual characteristics (Diez Roux, 2004).
Yet, multilevel models are no panacea in the absence of adequate control for the
individual-level factors associated with selection into neighborhoods. Unfortunately, the
perennial challenge of estimating unbiased contextual effects is extremely difficult to overcome
with standard research designs. Studies such as the Moving to Opportunity (MTO)
Demonstration have attempted to approximate an experimental design in an effort to understand
the “treatment” effect of moving from a high- to a low-poverty neighborhood among younger
populations. The capacity of these approaches to isolate the treatment effect of interest has been
questioned (Sampson, 2008). A major concern in the case of the MTO study surrounds the
extent to which the residential move from a high- to a low-poverty neighborhood actually
resulted in sustained differences in the routine exposures of study participants (Clampett-
Lundquist and Massey 2008). As we describe below, targeted data collection efforts motivated
by multicontextual theoretical approaches offer some promise for improved estimation of
contextual effects.
Data and Measures
Theory cannot be adequately tested, nor can efforts to address problems of selection and
causation, in the absence of high-quality data collection efforts. An obvious advance would be
to incorporate social contextual measures into ongoing, longitudinal investigations of older adult
well-being. Despite the advantages of over-time data, Yen et al. (2009b) identified only eight
longitudinal studies of neighborhoods and older adult health. Typically, longitudinal
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investigations of aging populations focus on individual-level characteristics. Thus, changes in
neighborhood characteristics are unobserved and their potential influence impossible to assess.
Effective measurement of social context is a significant challenge. Boundary
specification problems are endemic to this research, often resulting in arbitrary or convenience-
based decisions regarding the operationalization of the context of interest. For instance,
neighborhood research faces the ongoing challenge of defining the “neighborhood.”
Neighborhoods have been defined by individual perceptions, administrative boundaries, and
sociogeographic landscape. Although theory and the specific research question should inform
the size of the relevant boundary (Raudenbush, 2003), available data usually restrict researchers
to using predefined boundaries, such as the census tract, and consider only residential location.
Research also is limited by the relative lack of data on whole (as opposed to ego-
centered) networks. Many studies rely on ego-centric networks that bound networks based on
first degree connections. Such studies often use measures of perceived levels of support or
weight network ties based on the level of intimacy. But as Granovetter’s (1973) work suggests,
weak ties may have important consequences as well. Smith and Christakis (2008) argue that
health research should consider characteristics of the whole network. For example, Christakis
and Fowler (2007) identified obesity clusters using over-time whole network data. They find that
direct connections to obese alters (i.e., friends), as well as connections to individuals separated
by up to three degrees, influence the ego’s likelihood of becoming obese. Although this research
has been criticized on methodological grounds (Lyons, 2011), findings from these studies have
sparked substantial interest in the health effects of embeddedness in network structures and raise
important questions regarding the appropriate measurement of networks to capture health
influence.
Finally, research has not fully explored the intersection of geographic location and global
(or complete) networks, and their effects on health. As we discuss later in this chapter,
individual-level reports of sociospatial ties can be combined to identify aggregate patterns of
interaction. The interrelationship between social ties and social interaction, and the exact
location in which ties are maintained, could potentially inform neighborhood-based interventions
for older adults. If it is known, for instance, that certain neighborhood institutions create
consistent opportunities for interaction, and that ties formed there are of some consequence,
efforts can focus on protecting or sustaining those institutions. The frame to describe institutions
may also be extended; perhaps they need not exist in a formal sense or even under a roof. For
instance, Chicago’s Hyde Park neighborhood is able to sustain more than one location
(generally, a park) where older adults gather on a regular basis to play chess. The ability to
efficiently identify this form of activity may be possible with newly designed social survey and
tracking methods—we turn to a description of these below.
NEW DIRECTIONS
Despite the substantial challenges facing investigation of social context effects on aging,
emerging directions in conceptualization and measurement hold the promise to significantly
advance research in this area. Specifically, we focus on the concept of activity space as an
integrative approach to capturing older adult spatial, social, and institutional exposures. Activity
spaces may be understood to encompass all of the locations that individuals come into contact
with as a result of their routine activities (Golledge and Stimson, 1997). Below we describe how
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incorporating activity space exposures into theoretical models and data collection efforts may aid
in addressing the challenges facing contextual research on aging.
Reorienting Theory
First, theoretical approaches that emphasize the effects of one or another set of contexts
on aging-related outcomes would benefit from conceptualizing individual exposures through the
concept of activity space. For instance, research on neighborhoods, aging, and health largely has
focused on the residential location. But individuals travel outside of their residential
neighborhoods as they carry out routine activities such as work, grocery shopping, health and
dental care, and recreation. It is plausible that these non-home contexts also influence individual
outcomes (Kwan, 2009). Moreover, the degree of exposure to these contexts varies. Thus,
research should consider characteristics of residential and nonresidential environments as well as
the time spent, activities performed, and social interactions occurring at these locations (Kwan et
al., 2008). This approach is explicitly multicontextual, acknowledging the potential for
substantial inter-individual variability in daily routines.
Consideration of activity space may help explain differential effects of neighborhood
characteristics across individuals. For example, the protective effects of high immigrant
concentration within the residential neighborhood may be attenuated if individuals spend
considerable time outside their neighborhoods. Conversely, the harmful effects of concentrated
disadvantage might be alleviated when individuals are routinely exposed to more affluent or pro-
social contexts. Although advanced age and disability may limit the potential to travel beyond
the residential neighborhood, as noted earlier, the assumption of age-constricted routine activity
spaces has not been investigated empirically (Cagney and York Cornwell, 2011). Although it is
likely true that, on average, the circumference of turf declines in size with age, inter-individual
variability in this process may be substantial (and life course theory suggests that we might
expect even greater heterogeneity at later ages [Elder, 1975]). Research thus should consider
how individuals’ activity spaces change as they age, and whether these changes shape the
influence of traditionally emphasized contexts such as residential neighborhoods.
Attention to Institutional Interactions
As with neighborhood contexts, consideration of activity spaces could help improve
understanding of older adults’ interactions with various institutions. By collecting data that
directly assess older adults’ exposures to institutional contexts, the impact of such exposures can
be more precisely estimated. Activity space data also may provide information on the specific
venue where an individual spends time, offering the opportunity to capitalize on rapidly
expanding publicly available data on institutions and public space (e.g., Google Maps, Street
View, etc.). An emphasis on activity space data marks an important shift from the dominant
survey-based approach to understanding institutional participation that relies on abstract
categories of institutional participation (e.g., church attendance or membership in clubs and
voluntary organizations, broadly construed) without observing actual social and spatial
exposures. These methods do not replace survey-based approaches, which are still critical to
gleaning perceptions, but suggest that surveys can be combined with Global Positioning System
(GPS) technology and other space-time tracking systems to situate older adults in their social and
geographic space.
Moreover, activity space information allows for assessment of the geographic proximity
of institutions with which individuals are actually involved. Do residential neighborhoods
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provide institutional exposures or do older adults travel outside their immediate neighborhood
contexts for some institutional involvements? The typical approach to estimating the impact of
neighborhood institutional environments is to simply enumerate the presence of relevant
organizations, businesses, and local facilities in a neighborhood and estimate the impact of
institutional density on aging-related outcomes. Although this approach may tap potential
opportunities or the community’s orientation toward pro-social organizations, it does not assess
actual participation in local institutions by older adult residents and therefore cannot accurately
measure the impact of institutional participation.
Activity space measures also allow researchers to disentangle the primary and secondary
benefits of institutional presence. For instance, institutions may exert beneficial influence on
participants directly, but also may indirectly influence the outcomes of other neighborhood
residents through second and third-order network ties (e.g., information passed through informal
gatherings at a local coffee shop is passed on through neighbor networks), social psychological
influences (e.g., a successful local youth organization engenders trust and a sense of security
among older adults), or ecological processes (e.g., a new store brings conventional activity and
“eyes on the street” to the surrounding area, promoting monitoring and informal social control
[Browning et al. 2011; Jacobs, 1961]). By incorporating direct exposure to geographically
identified institutions into theoretical models of social context effects, researchers will be
encouraged to think about the complex influences of institutions through participation, social
networks, and proximate spatial processes.
Multicontextual Analysis Opportunities
In addition, a multicontextual approach to social network influences on aging would
allow for detailed assessment of network partner characteristics while simultaneously capturing
the embeddedness of network interactions in geographic, institutional, and social settings. The
characteristics of settings in which network partnerships are enacted (e.g., local, public,
accessible) may have important implications for the extent to which network interactions
translate into actual and perceived social support (Small, 2009). Moreover, the availability of
public or casual social ties—e.g., those ties that are routinely available through local public
venues such as restaurants, coffee shops, and parks—may provide a source of security and
informal network-based monitoring that more intimate but less regularized family ties may not
offer. The pioneering work of Jane Jacobs (1961) highlighted the critical role of overlapping
routines and casual contact among neighborhood residents in developing public trust. In the
absence of activity space information, the potential for such contact characterizing a given
residential area is difficult to observe. To our knowledge, research on the social context of aging
has not sought to integrate network information with data collected in real time on activity space
and routine activities.
Framing theoretical approaches and analyses using the activity space concept may also
help develop research designs that are better equipped to infer causal effects of social contexts.
Clearly, the challenge of establishing causal effects of social contextual variables is one that
social scientists will not easily overcome. However, activity space data provide a means of
improving on standard approaches. Precise exposure data offer the opportunity to determine
whether a specific “treatment” has occurred and the duration of exposure, where relevant. For
instance, hypotheses regarding the role of institutions in the lives of older adults might capitalize
on exogenous changes in the institutional environment to determine whether and how such
changes influence older adult well-being. The impact of opening a recreation center with older
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adult programming on the activity patterns of local elderly is an obvious example but other
institutional changes could matter as well. For instance, a new elementary school in the
neighborhood could renew life on the street and encourage older adults to leave their homes
more often. Research questions examining the impact of time spent with social network partners
in fostering older adult well-being (along a variety of dimensions) could benefit from more
accurate assessment of network dynamics through space-time data on social network
interactions. Although the challenges associated with inferring causation from analyses of social
context effects are exceedingly difficult to surmount, activity space data will offer an opportunity
to, at a minimum, assess theoretically relevant characteristics of a contextual treatment with
greater accuracy.
Promising Technological Advances
Finally, the data collection and measurement requirements of precise activity space
information clearly extend beyond the traditional survey interview, but are becoming
increasingly feasible with new technologies. GPS technology is now a standard feature of
cellular telephones and most smartphone operation systems can accommodate applications to
collect relatively precise location data. Smartphones also are increasingly used to collect real-
time information from respondents on settings, social interactions, mood, and other phenomena
using Ecological Momentary Assessment (EMA) (Cain et al., 2009). EMA uses smartphones to
directly contact respondents with questions that can be answered, in the moment, using the
device, limiting problems associated with recall of events and locations (potentially more
effective if short-term memory is compromised). Question content can be crafted such that
respondents are queried not only about what they are doing, whom they are with, and how they
feel in the moment—three typical foci of EMA-based data collection efforts (Shiffman et al.,
2008)—but also about the nature of the social exchange and the quality of it (Stafford et al.,
2011). Moreover, the content of exchanges, personal or material, is rarely collected in
traditional survey-based approaches because detailed recall of activity and context would be too
onerous. Although older adult populations are less familiar with smartphone technology, a
number of studies have successfully used these devices to collect EMA data (Cain et al., 2009).
Moreover, the rapid spread of mobile phone technology ensures that each new cohort of older
adults will experience fewer burdens associated with smartphone-based data collection. Apart
from technological familiarity, EMA and GPS tracking may be less invasive (particularly the
passive tracking of respondent movements) so may be well suited for older adults who lack the
comfort or stamina to interact with interviewers and recount interactions and locations.
Sampling activity spaces in a geographically contained population also may allow
investigators to measure the extent to which neighborhood residents share activity locations
within a given boundary or more generally. Consistent with Jacobs’ (1961) approach, patterns of
residential interconnection through shared activity locations may capture important features of
the social organization of a neighborhood. For instance, the pattern of these actor-location ties or
“co-location networks” may have consequences for neighborhood processes such as social
network formation and sustainability, the emergence of trust and neighborhood attachments, and
shared expectations for informal social control and action on behalf of the local community
(Browning et al., 2011). These factors have been linked with older adult health and well-being
in the extant literature (e.g., Cagney, Browning, and Wen, 2005), but the social and ecological
dynamics that tend to promote these features of neighborhood social organization have remained
elusive. Moreover, by measuring the co-location network more precisely, researchers may be
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able to leverage social network analysis techniques to characterize routine activity patterns using
sophisticated global network measures and identify an individual’s location in the network (e.g.,
through various measures of centrality) (Browning et al., 2011). We include a stylized example
of just such potential. The network diagram (Figure 4-1) illustrates how individuals (the circles)
interact with places (the squares) in a hypothetical community. The sizes of the circles and
squares suggest the network centrality of the person or the place. We could imagine that the
larger squares could be churches, parks, or shopping centers—places that are central to routine
activity. Graphically representing where people go, and how they may co-locate, could indicate
both places that are successful at bringing together disparate groups and potentially identify
shared tastes and norms. Rich measures of activity space may help uncover the social structure
of community embeddedness that older adults experience.
These advances represent the frontier, but they also come with unforeseen challenges.
The sheer volume of data points that will be available from data collection processes such as
GPS tracking is one example of the emerging challenges of “big data” (Nyerges, Couclelis, and
McMaster, 2011). Investigators could benefit from establishing “best practices” for how to
manage, store and clean these data so they are useful for analytic purposes. Another area that
deserves attention is that of human subjects, how to protect their data and how to ensure their
confidence in researchers’ ability to do so. Older adult participation in activity space research
will be contingent on the field’s grasp of these sensitive issues.
CONCLUSIONS
We have spent a significant portion of this chapter building a case for activity space
approaches in contextual research on aging. These approaches hold promise because they
release us from pre-determined boundaries of influence and allow respondents to reveal where
they go and how they share their social spaces. We believe this is the next “turning point” in
neighborhood effects research and that aging-related scholarship will particularly benefit. We
think this is so because relatively little is known about older adults’ routine activities and the
extent to which they are altered with life course transitions and changes in health.
Research on the social context of aging faces a variety of challenges and opportunities in
the coming years. Significant advances have characterized research on specific social contexts,
demonstrating the role of social networks, neighborhoods, and institutions in shaping trajectories
of older adult health and well-being. Nevertheless, capitalizing on these advances will require
increasingly integrated, multicontextual theoretical and methodological approaches and
concomitant data resources. We suggest that studies incorporating the concept and measurement
of older adult activity space hold substantial promise for advancing contextual research on older
adults and will benefit from ongoing rapid innovation in technologies for the collection of real-
time data on spatial and social exposures.
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FIGURE 4-1 Affiliation network of older adults and neighborhood places.
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