FormalPara Overview

  • Health and social networks are central domains in later life.

  • There are three hypotheses on the social gradient of health in old age: continuity, divergence, and convergence hypothesis.

  • One of the most important hypotheses on social networks in old age is the activity hypothesis. It states that high life satisfaction can be achieved by maintaining social interactions.

  • Risk of mortality, dementia, and depression are associated with both socioeconomic status and social network characteristics.

  • The mediating mechanisms of socioeconomic status, health, and social network cannot yet be adequately explained by existing studies.

  • The majority of network characteristics are collected indirectly through proxies. Established quantitative and qualitative methods of network analysis have played a subordinate role in gerontological research so far.

  • Research designs that focus solely on qualitative or quantitative network characteristics systematically underestimate the real effect of social integration on health in old age.

1 Introduction

Thanks to improvements in living standards and health behavior as well as medical progress since the second half of the twentieth century, old age has become a life phase in its own right. This phase usually begins by the transition from working life to retirement (Kohli, 2000). Both the chance of reaching retirement and the life expectancy after retirement have increased significantly (Eisenmenger & Emmerling, 2011). The post-work phase spans several decades for many people now. In addition, people who retire are considerably healthier and more independent than their peers of earlier birth cohorts (Crimmins, 2004). The expansion of this phase of life has been accompanied by a differentiation of older people in terms of health and independence: healthy and active people experience this phase, as do people in need of help and care. This fact is considered by distinguishing between old and very old people (Baltes, 2007). Characteristics of old age are absence of non-compensable health restrictions, self-determination of various activities (e.g., traveling, hobbies, voluntary work), and strong social integration. Overall, the demands of old age can be coped well in this phase. Very old age is characterized by an increase in physical and cognitive losses and diseases, and a decrease in the abilities and possibilities of compensating for deficits (Baltes, 1997; Baltes & Smith, 2003).

Health and social networks become central domains of life in old age and show special characteristics compared to earlier life phases. The risk of diseases with slow progressions, which often cannot be completely cured, increases. The causes are the rise in age-physiological changes, the accumulation of risk factors during the life course, and long latency periods concerning diseases that have already started at an early age (Tesch-Römer & Wurm, 2009). In addition, multimorbidity, that is, the simultaneous occurrence of several chronic diseases, occurs more frequently with increasing age, which threatens functional health (Müller et al., 2014). Furthermore, the importance of subjective health increases with age. Compared to objective health, subjective health is a more reliable measure of quality of life, life expectancy, and the prognosis of disease progression in old age. In comparison to disease diagnoses, subjective health, which includes not only physical and mental health but also one’s own life situation and lifestyle, reflects the individual state of health more comprehensively (Spuling et al., 2017).

The structural and functional patterns of social networks in old age are mainly shaped by the status transition from working life to retirement and by the health of the older person and their contacts in the network. Health is especially important for the social network in later life, compared to young and middle adulthood (Hoogendijk et al., 2016). One’s social network in old age is significantly changed by the death of important network members, functional limitations, or the need for care. For example, from the age of 60 to 65 years and older, the decrease in network size is estimated at one person per decade (Wrzus et al., 2013).

2 Theories

2.1 Theories on Health Inequalities in Old Age

Three assumptions on the association between social inequality and health in old age are often discussed. The continuity hypothesis assumes a continuation of health inequality: The extent of health inequality in old age corresponds to the extent in earlier life phases (Atchley, 1989). It assumes that social inequality in retirement is reproduced from the social inequality of the working phase (Kohli, 2000). The socioeconomic position that a person reaches in the course of his or her life by following educational and occupational paths is maintained in old age. This implies a temporal stability of social inequality within a cohort until old age (status-maintenance hypothesis) (Henretta & Campbell, 1976). It also implies a constant effect of social inequality on health. The divergence hypothesis assumes an increase of health inequality with age. It is the result of an accumulation of health risks in lower status groups over the course of life (Tews, 1993). Furthermore, in the case of poor health, compensatory resources (such as income) are unequally available in the different social strata (Mayer & Wagner, 2010). This process is intensified when material resources of higher status groups accumulate over time (cumulative-advantage hypothesis) (Lampert et al., 2017). The convergence hypothesis takes the opposite position. It states that health inequality decreases with age. Four arguments are used to support this hypothesis. Firstly, biological aging processes are universal, so that the influence of social factors on health and life expectancy increasingly vanishes (Age-As-Leveler-Hypothesis) (Lampert et al., 2017; Mayer & Wagner, 2010). Secondly, welfare state regulations reduce differences in socioeconomic status and its influence on health (von dem Knesebeck et al., 2003). Thirdly, burdens of middle age (e.g., as a consequence of employment), which vary according to social class and influence health status, become less important with retirement (House et al., 1992). Fourthly, the convergence theory is justified by socially selective mortality: The risk of dying before retirement age is greater in lower status groups than in higher ones. Thus, survivors in the lower status groups represent a positive selection with regard to health status (Markides & Machalek, 1991; McMunn et al., 2008).

2.2 Theories on Social Networks in Old Age

An early sociological theory on social networks in old age constitutes the disengagement theory, which bases on structural functionalism (Cumming & Henry, 1961). It assumes that a successful adaptation to old age is achieved by “disengagement,” understood as the withdrawal of older people from social roles and relationships. Functional complementarity between individual and society is assumed. The desire for retreat corresponds with the society’s need to ensure its continued functioning. The process of disengagement is neither due to poor health nor to loss of income in old age. Rather, it starts as soon as the person relinquishes his or her professional role or becomes a widow. Life satisfaction is experienced by the fact that the withdrawal reduces social control, for example, by colleagues and superiors, which entails liberation from everyday norms. Only in those cases in which no alternative social roles are available, such as voluntary work, the reduction in the number or diversity of social contacts is seen as a crisis. There is little empirical evidence for this theory. Although important social roles do indeed disappear with the end of employment and through widowhood, existing social contacts, for example, with children, grandchildren, and neighbors, are not loosened but, on the contrary, often intensified. A voluntarily initiated withdrawal from social ties in good health is not typical (Maddox & Eisdorfer, 1972; Neugarten et al., 1969; Shanas et al., 1968).

The activity theory can be regarded as an alternative to the disengagement theory. It states that high life satisfaction in old age is achieved through continued social activity, the maintenance of interactions, or an active lifestyle. The age-related loss of social roles (e.g., professional activity) and social activities should be countered by taking up new activities (e.g., voluntary work) (Tartler, 1961). This connection between activity and satisfaction in old age is empirically well established (Adams et al., 2011; Katz, 1996; Lemon et al., 1972). According to social exchange theory, which is based on rational choice theory, interactions take place through a norms-driven exchange of social goods (instrumental, emotional, and material). The reciprocity norm is regarded as central. Concerning old age, the theory assumes that older people have fewer and fewer resources such as social position, money, and health, and thus lose their attractiveness for potential exchange partners (Bengtson & Dowd, 1981). Ways out of the imminent imbalance between giving and receiving are seen in the focus on those interaction partners with whom reciprocity is possible. This can be through targeted selection of existing relationships or the establishment of new ones, which is ultimately seen as positive for well-being. Criticism of this theory is directed primarily at the difficulty of empirically testing these assumptions, since “social goods” can mean very different things to individuals. Moreover, the interpretation of reciprocity also depends on the quality and significance of social relations. However, quality is not taken into account in the theory of social exchange (Tesch-Römer, 2010).

The model of inter-generational solidarity (Bengtson & Roberts, 1991) and the model of inter-generational ambivalence (Lüscher, 2000) are specifically geared toward the relationships between parents at an advanced or old age and their adult children. The former model focuses on the mutual support between the generations in a family, described by means of seven dimensions: “structure” (in the sense of opportunity structures for interaction), “association” (extent of personal contacts), “affect” (extent of mutual affection), “consensus” (extent of agreement between values and attitudes), “normative beliefs” (strength of commitment), “functional exchange” (degree of mutual support), and “conflict” (frequency of conflicts). The latter model assumes a contradiction in social relationships between parents and adult children and formulates assumptions about how to resolve it.

Structural change of social networks in old age is explicitly addressed by the socioemotional selectivity theory (Carstensen, 1993) and the social convoy (Antonucci et al., 1997). The former theory assumes that life satisfaction and positive feelings remain stable into old age despite the shrinking networks because there is an increasing focus on interaction partners who are the source of positive experiences. This selection process is regarded as functional for mental health. The second theory states that the inner core of the network, which includes partners, children, parents, and close friends, accompanies a person over the course of life, while the outer core, consisting of neighbors, service providers, and work colleagues, is characterized by substitution. Here, the network does not shrink per se, but rather changes in terms of its composition. Thus, contact with (former) work colleagues may decrease and contact with neighbors and caregivers may increase. Among other things, substitution is an expression of changing opportunities and needs in old age. According to the social convoy model, even distant, less emotionally regulating contacts can thus be functional for physical and mental health in old age.

3 Social Inequality and Health

While there is a long-established correlation between socioeconomic status and health in middle adulthood, age is considered a relatively young field of research (von dem Knesebeck & Vonneilich, 2009). The following presentation focuses on three consequences of social inequality that are mainly relevant in old age. These are differences in the risk of mortality, in the age-related decline in cognitive functioning with its associated risk of dementia, and in the risk of depression.

3.1 Mortality Risk

According to empirical results from the German Ageing Survey (DEAS), in old age, socioeconomic status has a continued influence on health (Schöllgen et al., 2010; Spuling et al., 2017). This, in turn, is potentially related to socioeconomic/social inequality in mortality. For example, according to register data from 2003, the mortality risk among male German pensioners aged 65 and over was three times higher in the lowest socioeconomic fifth (quintile) than in the highest; the further life expectancy was 12.5 years versus 20 years (Shkolnikov et al., 2007). Yao and Robert (2008) found similar disparities in their US long-term study in an older population of 1631 people aged 60 and over: Black seniors had worse subjective health and a higher risk of mortality than White seniors. This difference can be partly explained by a lower socioeconomic status of Black seniors both at the individual and neighborhood level. Lleras-Muney (2005) also showed a causal relationship with census data from 1960, 1970, and 1980 in the USA: With every additional year of education, the probability of adult mortality fell by 3.6% within the next 10 years. This trend of inequality is not limited to Germany and the USA: In an international comparison of 22 European countries, Mackenbach et al. (2008) have impressively shown that people with a low socioeconomic status are systematically exposed to a higher risk of dying than people with a higher socioeconomic status. The age-adjusted status-based difference in mortality risk was particularly high in the Eastern European and Baltic countries (e.g., Czech Republic and Lithuania) and lowest in the southern countries, such as Italy and Spain. The analysis referred to almost 3.5 million deceased people with a minimum age of 30 years from official death registers.

3.2 Cognitive Progression and Dementia Risk

There is consensus that cognitive abilities, which include the dimensions “language,” “memory,” “knowledge,” “problem solving,” and “orientation,” show a high inter-individual variability in old age (Christensen et al., 1994). In addition, abilities vary according to the respective areas of performance. Age-related differences in the dimensions “problem solving” and “memory” are much more pronounced than in “acculturated knowledge” (Finkel et al., 2007; Reischies & Lindenberger, 2010).

If the decline is pathological, that is, it decreases beyond a normal age-related decline in cognitive functioning and is medically diagnosed, then it is called dementia. Dementia is a psychiatric condition that occurs in degenerative and non-degenerative diseases of the brain. A disease most commonly associated with symptoms of dementia is Alzheimer’s disease. Dementia is characterized by severe impairment of memory (especially short-term memory), speech, motor skills, and sometimes personality structure. The risk of dementia increases exponentially with age. For example, the prevalence of Alzheimer’s type dementia is estimated to be 1% in the group of 60-year-olds and doubles every 5 years thereafter (Ferri et al., 2005). From the age of 85 onward, risk of dementia is drastically increased and measures about 25%. The cognitive processes and the risk of developing dementia—a possible but not inevitable consequence of an unfavorable trajectory—are determined by a variety of social and socioeconomic factors (Müller & Kropp, 2011, 2012).

Probably the strongest factor in this respect is intelligence or intellectual capacity, often measured by educational attainment in surveys. The cognitive reserve hypothesis (Liberati et al., 2012; Scarmeas & Stern, 2003) assumes that people with higher educational attainment and occupational status have a larger repertoire of coping strategies that delay and mitigate the decline in cognitive functioning in old age than people with lower educational attainment. This implies that alternative regions of the brain are more likely to be activated when needed, to take over the functions of less efficient regions affected by dementia or Alzheimer’s disease. Not education per se, but the associated potential for intellectual stimulation by the social and professional environment is seen as an explanation (Gow et al., 2012; Lee & Chi, 2016; Then et al., 2013; Wang et al., 2012).

The association between education and risk of dementia is empirically well established: According to a meta-analysis of 69 studies, older people with a low level of education have a 1.61 times higher risk of developing dementia than older people with a high level of education (Meng & D’Arcy, 2012). An interesting finding is the so-called hurdle effect: greater cognitive reserves delay the diagnosis of dementia, but once dementia sets in, it progresses faster. This is because the compensatory processes of the cognitive reserve mask the decrease in cognitive functions for a long time. However, by the time the decline is clinically diagnosed, the pathological processes may have manifested (Bruandet et al., 2008).

Cognitive reserve is closely related to a stimulating social environment. Several theoretical approaches therefore explicitly postulate a relationship between social embedding and cognitive functioning. First of all, the use-it-or-lose-it hypothesis (Hultsch et al., 1999) expects that the brain, similar to a muscle, needs to be trained regularly to remain fully functional. Social relationships help by stimulating people to engage in social and physical activities [physical activity is another predictor of cognitive function (Fratiglioni et al., 2004)] and provide complex intellectual input (Schooler, 1984). The stress buffer hypothesis (Fratiglioni et al., 2004) assumes a positive effect of emotionally supportive relationships in times of crisis. Stress is considered a factor promoting Alzheimer’s disease because it is associated with structural changes in the hippocampus (Wilson et al., 2003). According to this hypothesis, people benefit particularly from so-called functional networks rich in support, regardless of the actual number of relationships or network size. The main effect hypothesis (Cohen, 2004) assumes that highly integrated people have more motivation (also norms and social pressure), knowledge, and resources for a healthy lifestyle. In this hypothesis, so-called structural aspects are also relevant, such as embedding in complex and diverse networks of relationships. All three hypotheses are complementary in their predictions, as they focus on different mechanisms that can be effective simultaneously.

3.3 Depression

Depressive disorders are characterized by a state of distinctly sad mood, disinterestedness, and reduced drive over a long period of time. In old age, depression is the most common mental disorder. Luppa et al. (2012) in their meta-analysis of older people aged 75 years and older show prevalence of 17% for depressive symptoms and 7% for major depression. Depression in old age increases suicidal mortality, is associated with losses in subjective and functional health, and often affects the outcome of treatment for somatic disorders. Depression is also a risk factor of coronary heart disease (Carney & Freedland, 2017). There are links between depression and neurodegenerative diseases, such as Alzheimer’s dementia and Parkinson’s disease (den Brok et al., 2015; Mourao et al., 2016). Chronic pain in old age increases the risk of depression (Zis et al., 2017). Lorant et al. (2003) found convincing evidence in their meta-analysis, which included people in old age, that low socioeconomic status is associated with a higher risk of depressive disorders. Although the studies included in the meta-analysis show both directions of the association (socioeconomic status influences the risk of depression in the sense of the causation hypothesis; depression causes socioeconomic status in the sense of the drift hypothesis), most of the findings of this meta-analysis support the causation argument. Current studies on aging confirm the findings of a social gradient in depression (Domènech-Abella et al., 2018; Han et al., 2018; Lei et al., 2014; McEniry et al., 2018). Of particular interest is the result of a Japanese study, in which the authors demonstrate the late effects of early life experiences: People who grew up in families with a low socioeconomic status had a 44% higher risk of developing depression decades later, in old age, than those whose parents had a high socioeconomic status (Tani et al., 2016).

4 Social Networks and Health

Researchers have investigated a wide range of health parameters in relation to social networks in old age, with a particular focus on mortality risk, cognitive processes, and depression. Selected studies on these three focal points are presented below.

4.1 Mortality Risk

Network embeddedness is associated with risk of early mortality. This conclusion was reached by Holt-Lunstad’s research team in their meta-analysis of 70 studies on subjective and objective social isolation (Holt-Lunstad et al., 2015): Loneliness increased the risk of mortality by 26% as compared to social integration (i.e., absence of loneliness), and living alone increased the risk of mortality by 32% as compared to not living alone. This result builds on an earlier meta-analysis by Holt-Lunstad: Across 148 studies she found a 50% higher probability of mortality for weakly embedded persons compared to strongly embedded persons (Holt-Lunstad et al., 2010). Embeddedness was measured by functional (e.g., receiving social support, loneliness) and structural network measures (e.g., number of social relationships, household size). This difference in mortality, which is roughly comparable to the health risk of smoking and class III obesity, was consistent across age groups, gender, original health status, cause of death, and observation period of the studies. Interesting differences were found with regard to the network measures used: the relationship between embeddedness and mortality was strongest when functional and structural networks measures were combined.

4.2 Cognitive Trajectories and Risk of Dementia

Several meta-analyses have already summarized the impressive number of studies on social integration and cognitive functioning. In a meta-analysis by Kuiper et al. (2015), three out of 43 studies showed a significant correlation between cognitive decline and network size. Older people with smaller networks showed a stronger decline in the observation period than older people with larger networks (Chi & Chou, 2000; Holtzman et al., 2004; Hughes et al., 2008). This association was stronger than for functional aspects such as low social activity.

In another review of 19 longitudinal studies, Kuiper et al. (2015) found a positive correlation between the risk of dementia and low social participation, low frequency of contact, and high levels of loneliness. The authors compared the effect sizes with those of low education, low physical activity, and depression. However, results on network size and satisfaction with the network remained inconsistent, as no significant correlation was found: Only two out of the eight studies that considered network size showed an increased likelihood of dementia—in older people with small networks (James et al., 2011; Saczynski et al., 2006).

Fratiglioni et al. (2004) came to a similar conclusion in their meta-analysis of 13 studies. Three out of six studies that analyzed social networks found a reduced risk of dementia for highly socially integrated people (Fratiglioni et al., 2000; Scarmeas et al., 2001; Wang et al., 2002). Five out of seven studies found a lower decrease in cognitive functioning. In addition, the reverse causal relationship is also shown: When cognitive abilities decrease strongly with age, the size of the social network shrinks (Aartsen et al., 2004) because the social and physical radius of action is reduced. Increasing cognitive impairments can thus encourage a retreat into family relationships.

4.3 Depression

In their systematic review, Schwarzbach et al. (2014) analyzed a total of 37 studies that examined the association between social networks and depression in older people. While findings on functional network aspects were generally consistent (little social support and low relationship quality are associated with depression), findings on structural aspects (such as marital status, network size, and frequency of contact) were mostly heterogeneous. In contrast, it was unanimously shown that people living alone do not have a higher risk of depressive symptoms. To some extent, relationships are moderated by the cultural context. In Eastern cultures such as in China and Japan, for example, a high contact frequency was associated with a lower risk of depression. For Western cultures, however, this correlation could not be confirmed. Antonucci et al. (1997) found evidence in their analysis that functional and structural network aspects each have independent effects on depressive symptoms in old age. Litwin and Stoeckel (2016) have shown the significance of social networks for the relationship between functional impairments and depressive symptoms in their work. They found that functionally impaired people have more depressive symptoms when they have no social network than impaired people with network partners.

5 Social Inequality, Social Networks, and Health

Studies analyzing the relationships between social inequality, social networks, and health in old age are comparatively rare. They consider both functional (i.e., all forms of support) and structural (i.e., network size and frequency of contacts) aspects. The following presentation of existing findings is structured along three hypotheses:

  1. 1.

    Characteristics of social networks mediate the association between socioeconomic status and health; that is, socioeconomic status affects health status via social networks.

  2. 2.

    Characteristics of social networks moderate the association between socioeconomic status and health; that is, network characteristics influence the strength of the association between socioeconomic status and health status.

  3. 3.

    Socioeconomic status moderates the association between social networks and health; that is, socioeconomic status influences the strength of the association between network characteristics and health status.

5.1 Social Network as Mediator

Using a German sample of persons aged 60 and over living in their own household, Von dem Knesebeck (2005) tested the hypothesis that social networks mediate the relationship between socioeconomic status and health. Dependent variables regarded subjective health, depressive symptoms, and functional limitations. Socioeconomic status was measured with education, income, and occupation. The two proxies “frequency of contact with friends/acquaintances” and “frequency of contact with family members” as well as the perceived availability, use, and adequacy of emotional support mapped the social network. The results overall showed weak mediating effects of social networks on the social gradient of health: Controlling for “frequency of contact with friends,” “frequency of contact with family,” and “availability of emotional support,” both the positive correlation between income level and subjective and functional health and the negative correlation between income level and depressiveness decreased only slightly and remained significant. Correlations between education or occupation and the three health indicators became even stronger after controlling for the aforementioned network characteristics (von dem Knesebeck, 2005). Depressive symptoms were further examined in the Korean study by Han et al. (2018). The authors showed that reciprocity of social exchange mediates the association between household income and depression. Vonneilich et al. (2012) investigated subjective health in the German Heinz Nixdorf Recall Study. Data stem from baseline and a 5-year follow-up (4146 men and women aged 45–75 years). Structural characteristics were measured with the “Social Integration Index” (SNI) (Berkman et al., 2004). Functional characteristics were measured with the “New Haven Established Population for Epidemiologic Studies of the Elderly Questionnaire” (EPESE) (Seeman & Berkman, 1988). Both structural and functional network characteristics mediated the association between socioeconomic status and subjective health. In contrast, in the prospective follow-up study (observation period of 3 years) by Nilsson et al. (2010) no mediator effects were found for the social network in the association between socioeconomic status (measured with financial assets) and functional health (measured with the number of mobility activities that can be carried out without help from others). Network indicators included cohabitation, social participation, network diversity, and satisfaction with social contacts (Nilsson et al., 2010). Neither did the study by Yan et al. (2013), which was based on a follow-up study covering an observation period of 11.5 years, support the mediator hypothesis. Their American sample consisted of 64–100-year-old persons. The authors examined the prevalence of ischemic stroke in relation to socioeconomic status of the residential area (i.e., neighborhood socioeconomic status). Network characteristics were assessed using the “Interpersonal Support Evaluation List” (Cohen et al., 1985), which measures the perceived availability of social support, and the “Lubben Social Network Scale” (Lubben, 1988). The latter is a tool especially developed for the elderly population, which in addition to emotional and instrumental support also asks for the actual size of the network. In summary, the reported findings do not provide a clear answer to the question of a mediating effect of structural network features in old age.

5.2 Social Network as Moderator

Using data from the fourth wave of the SHARE study (Survey of Health, Ageing, and Retirement in Europe), Olofsson et al. (2018) investigated the moderating effects of social networks. The sample consisted of 54,751 people aged 50 years and older from 16 European countries. Central indicators concerned education and subjective health. Network size and satisfaction with the social network were assessed with a network generator. The results point to a moderating effect of network satisfaction among men and women in Northern Europe: The correlation between socioeconomic status and health is stronger when satisfaction is high, but weaker when satisfaction is low. The authors argue that especially people with lower education seek and find help in the social network (which is associated with high satisfaction) when they are in poor health. Furthermore, it is assumed that low satisfaction with network contacts can be the result of emotionally stressful relationships that weaken well-being and reduce the social gradient (Olofsson et al., 2018). This study supports the hypothesis of the moderating effect: The social gradient is more pronounced when satisfaction with the social network is high.

5.3 Socioeconomic Status as Moderator

Using longitudinal data from the MacArthur Study of Successful Aging, Unger et al. (1999) examined the role of socioeconomic status (measured by income) for the influence of social networks on changes in functional health over a 7-year period. The sample included people aged 70–79 years. Network measures captured structural and functional characteristics of social networks. People with a larger social network had less functional impairments than those with a small network. This association was particularly pronounced among men. However, income did not operate as a moderator variable. In the aforementioned study by von dem Knesebeck (2005), moderator effects were tested in addition to mediator effects. Moderator effects turned out inconsistent, as they depended on specific health indicators and network characteristics. The positive association between network characteristics (frequency of contact with friends and family) and subjective health or functional health was weakest in the middle status group. The negative association between contact frequency with friends and family and depression was strongest in the high status group: people with infrequent contact and deficient social support had a higher risk of depression than people of low socioeconomic status. The Heinz Nixdorf Recall Study (Vonneilich et al., 2011) also showed few statistically significant interaction effects of socioeconomic status with social networks on subjective health and depression, which further varied between men and women.

The reported findings only partially support the assumption that socioeconomic status moderates the empirically established association between structural network characteristics and health in old age.

6 Summary and Critical Reflection

At an advanced age, there are associations between socioeconomic status and the risk of mortality, dementia, and depression. However, the presented findings do not provide a clear answer to the question of how health inequalities play out over the course of life. The reviewed studies confirm both the continuity and the divergence thesis. For example, the studies on mortality risk tend to indicate that status-related differences in mortality risk continue over the life span (continuity hypothesis). As early as 1990, House et al. (1990) suggested that research on health in old age requires a stratified view against the background of individual socioeconomic status. In addition, health risks in old age also increase for persons with a lower socioeconomic status due to their higher risk of developing dementia and depression (divergence thesis). This ambiguity of findings with regard to health inequalities over the course of life has often been noted in the research literature. This ambiguity is also due to the different operationalizations of socioeconomic indicators (education, occupational status, and income) and the different health dimensions. Furthermore, conventional indicators may not be suitable for adequately capturing differences in the accumulated socioeconomic conditions in old age (education and occupation date back a long time, are only comparable to a limited extent for men and women, ownership structures provide more information on the accumulation of resources) (Clemens, 2008; Kohli et al., 2000; Leopold & Engelhardt, 2011; von dem Knesebeck & Schäfer, 2009). For parents in old age, for example, it is conceivable that health inequalities are further influenced by unequal socioeconomic resources of their adult children (such as the extent of support in care services, knowledge about diagnosis and treatment options) (Rueda & Artazcoz, 2009; Saraceno, 2010). Moreover, as shown by the example on depression, parental socioeconomic status in childhood can play a role for health in old age and therefore may not be underestimated (Brandt et al., 2012; Pakpahan et al., 2017). Future research may take a closer look not only at the socioeconomic position of the older person but also that of their parents and adult children.

Empirical findings on the interplay between structural network characteristics and the risk of mortality, dementia, and depression support the activity theory: The maintenance of social interactions even in retirement seems to be an important protective factor for health. Network size is less important than the extent of social embeddedness. According to the socio-emotional selectivity theory, strong embeddedness can be experienced even when the network size decreases. An explanation for this could lie in the stability of the contacts in the network, who, according to the theory of the social convoy, belong to the inner core. For a concluding statement, however, more research is needed on the number and role diversity of social relationships (Ellwardt et al., 2015a) and other structural network characteristics, such as network density and bridge relationships. In addition, the cultural context should be taken into account when analyzing the links between social networks and health (Li & Zhang, 2015; Schwarzbach et al., 2014). Importantly, both functional and structural characteristics can make independent contributions explaining the variance of health parameters among older people (Antonucci et al., 1999). Furthermore, it became apparent that associations with health were particularly strong when complex measures were analyzed (e.g., both lifestyle and network integration and experience of the network relationship). Research designs focusing either solely on qualitative or quantitative network characteristics run the risk of systematically underestimating real effect sizes of social embeddedness. Thus, several indicators should be tested in parallel (Ellwardt et al., 2015b) combined, for example, in the form of network types (Ellwardt et al., 2016). For the construction of a typology, people are classified based on different characteristics of their networks, for example, in groups with large high-functional versus small low-functional networks. Next, these groups of people are compared in terms of their health. Another critical point is that often proxies are used to operationalize social networks, for example, contact frequency and household composition. Research has shown the added value of applying original network analyses for explaining health in old age (Li & Zhang, 2015; Schwarzbach et al., 2014; Youm et al., 2014). So far, longitudinal analyses have focused primarily on testing network effects on health. Research gaps exist with regard to the opposite direction, that is the influence of health deterioration on social networks.

The overview at hand on the associations between the three areas of “socioeconomic status,” “health,” and “social network” focused primarily on depression and functional and subjective health. However, risk of mortality and dementia is still largely unexplored. The mechanisms of mediation of socioeconomic status, health, and social network in old age cannot yet be sufficiently explained based on previous research. According to the current state of knowledge, moderating effects of network characteristics on health inequalities in old age seem most likely.

Previous research has produced at least three conclusive points for a future research agenda. Firstly, there is a focus on people living in their own homes. It remains largely unclear to what extent existing findings are generalizable to people living in care institutions. This research gap needs closing. Secondly, analytical designs incorporating complex network measures are more suitable for investigating the associations between “socioeconomic status,” “health,” and “social network” than designs consisting of only either quantitative or qualitative measures. Thirdly, in gerontological research, mostly network characteristics are assessed indirectly through proxies. Established quantitative and qualitative methods of network analysis have so far played a subordinate role in research on older people. The potential of “true” network analysis could be exploited more in future studies.

Recommended Readings

  • Vonneilich, N., Jöckel, K.-H., Erbel, R., Klein, J., Dragano, N., Siegrist, J., & von Dem Knesebeck, O. (2012). The mediating effect of social relationships on the association between socioeconomic status and subjective health-results from the Heinz Nixdorf Recall cohort study. BMC Public Health, 12(1), 285. This study is one of the first to examine the effect of SES on the association between social relationships and health (average age of the sample: 60 years). It found only a few statistically significant interaction effects of socioeconomic status and social network on subjective health or depression, which also vary between men and women.

  • Ellwardt, L., van Tilburg, T., Aartsen, M., Wittek, R., & Steverink, N. (2015). Personal networks and mortality risk in older adults: a twenty-year longitudinal study. PloS one, 10(3), e0116731. Data from the Longitudinal Aging Study Amsterdam (LASA) are used to report relationships between mortality and network features that reflect both structural and functional aspects.

  • Goldman, A. W., & Cornwell, B. (2015). Social network bridging potential and the use of complementary and alternative medicine in later life. Social Science & Medicine 140, 69–80. The study uses data from the first wave of the National Social Life, Health, and Aging Project (NSHAP) to test the hypothesis that people who connect otherwise unconnected groups, that is, who have a bridging function and use complementary medicine more often than other network members.

  • Carr, D. (2019). Golden years?: Social inequality in later life. Russell Sage Foundation.

  • Roth, A. R. (2020). Social networks and health in later life: A state of the literature. Sociology of Health & Illness, 42(7), 1642–1656.

Data Sets/Overview

  • “SHARE” (The Survey of Health, Ageing and Retirement in Europe)

The study started in 2004 as a representative survey of the population aged 50 and over. Eleven European countries (Belgium, Denmark, Germany, France, Greece, Italy, the Netherlands, Austria, Switzerland, Sweden, Spain) participated in the baseline survey. Cross-sectional and longitudinal data are available from seven survey waves and participants from 27 European countries as well as Israel. In the fourth and sixth wave, the social network was surveyed via name generators.

  • “Heinz Nixdorf Recall Study”

This is a population-based cohort study. Participants live in the Metropole Ruhr and were 45–75 years old at baseline in 2000–2003. A second wave took place in 2006–2008 and a third wave in 2010–2013. Cardiovascular diseases in particular are investigated. Network instruments include the “Social Integration Index” (SII) and the German adaptation of the “New Haven Established Population for Epidemiologic Studies of the Elderly (EPESE) Questionnaire.”

  • “LASA” (Longitudinal Aging Study Amsterdam)

The study focuses on physical, emotional, and social aging processes using a Dutch sample. For the baseline study in 1992, the participants in the study were aged 55–85 years. Follow-up examinations are carried out every 3 years; in each wave, data on personal networks are collected.

  • “HRS” (The Health and Retirement Study)

The initial sample of this American longitudinal study contained people born between 1931 and 1941. They were first examined in 1992. New examinations are carried out every 2 years. Indicators of the social network record its composition, number of close relationships, and frequency of contact.

  • “NSHAP” (National Social Life, Health, and Aging Project)

The baseline examination of this American study took place in 2005–2006; the sample participants were aged 57–85. A second wave was realized in 2010–2011 and a third wave in 2015–2016. Egocentric networks are surveyed using name generators.