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Logo of eurojageEuropean Journal of Ageing
 
Eur J Ageing. 2008 September; 5(3): 215–222.
Published online 2008 August 23. doi:  10.1007/s10433-008-0085-5
PMCID: PMC2760926
NIHMSID: NIHMS99784

The degree of kinship and its association with reciprocity and exchange in the relationships of visually impaired older adults

Abstract

This study draws on an evolutionary model of exchange in relationships to examine the nature of perceived reciprocity in the context of kin and non-kin relationships among a sample of visually impaired older adults (age 63–99). Further, we examined the direct and moderating impact of functional impairment and adaptation to visual impairment on the nature of perceived reciprocity. Results showed that the greater the degree of genetic relatedness the more imbalanced the exchange. It was also found that degree of adaptation to visual impairment moderated the association between genetic relatedness and perceived exchange, such that the greater the degree of genetic relatedness the more people reported they gave rather than received except at very low levels of adaptation, when people received more than they gave the greater the degree of genetic relatedness. Thus, an evolutionary model was supported such that imbalanced exchange was found more with greater degrees of genetic relatedness, but the direction of exchange was different for high versus low levels of adaptation to vision impairment.

Keywords: Older adults, Evolutionary model, Exchange, Reciprocity, Vision impairment

Introduction

Reciprocity is a central issue in the study of relationships and the degree of reciprocity has been found to vary depending on the type of relationship and goals of those involved. For example, those with communal goals such as kinship groups place less emphasis on the balance of give and take in relationships than those with exchange goals such as peer groups (Clark 1981; Fiske 1992). Especially in close relationships, direct exchange is not requested and reciprocity can be achieved over time (Trivers 1971). One potential explanation for differences in patterns of reciprocity across relationship types is that genetic relatedness moderates the need for balanced exchange (Lang and Neyer 2005). According to this evolutionary model, a relationship between close kin holds a smaller expectation of reciprocation than relationships between far kin or non-related persons. Because helping or supporting kin increases the chance that shared genes will survive, an advantage in fitness can be achieved even when support is not reciprocated (Hamilton 1964). However, dependency is also likely to shape the nature of exchange in relationships. For example, among older adults, impairment may limit the ability to give and also increase the need for support from others. In the present study, we apply a genetic model of reciprocity to the relationships of older adults with vision impairment and examine how the direction of exchange in relationships may change based on the level of functional ability and degree of coping with impairment.

Kinship, exchange, and reciprocity

In society, a general norm of reciprocity exists (Uehara 1995). It was adaptive in evolution to detect cheaters because the failure to detect cheaters could result in a great fitness loss (Cosmides 1989). Additionally a lack in cooperation is punished even when the punishment is costly for the individual itself (altruistic punishment; Fehr and Gächter 2002). As a result, especially in long lasting relationships a higher degree of reciprocity leads to more positive evaluation of relationship satisfaction (Van Ypern and Buunk 1990). Lang and Neyer (2005) argue that reciprocity is an important mechanism in cooperation relationships that helps shape the nature of kin and non-kin relationships depending on their adaptive function. Their theory draws on Hamilton’s (1964) work, where it was proposed that investment in kin may contribute to one’s own reproductive success, but investment in non-kin may not and that genetic advantage shapes social relationships. Differences in exchange among kin versus non-kin relationships have been found across cultures (Burnstein et al. 1994), supporting an evolutionary explanation whereby individuals achieve advantages in evolution by increasing their inclusive fitness (Burnstein et al. 1994; Davis and Daly 1997). Essentially, an individual’s genes are passed on via one’s own or one’s relatives’ reproductive success. Thus, an investment in one’s kin group is an investment in one’s own reproductive success, essentially balancing the investment made in the group. However, among non-kin relationships there should be a higher expectation of reciprocal exchange and relationships which do not fulfill this expectation should be ended (Lang and Neyer 2005). Consequently, non-kin relationships should be more reciprocal than kin relationships. Cole and Teboul (2004) argue that a non-zero-sum is expected in friendships but that in times of need close friends give more which can be paid back later. Building on this evolutionary perspective, Lang and Neyer (2005) propose that the greater the degree of genetic relatedness between relationship partners, the less reciprocity matters. An exception is spouses, who are non-kin (in terms of genetic relatedness) but they are also primary attachment figures and are important non-kin involved in genetic perpetuation. Compared to other non-kin relationships, marital partners are likely to have relatives in common, namely their biological children. There is strong evidence that pair-bonding developed in evolution as an adaptation of solving the problem of jointly handled parental care (Fraley et al. 2005). Thus, the attachment to the spouse can be characterized as a quasi-kinship relationship.

Other models focus more on aspects of delayed reciprocation. For example, Antonucci and Jackson (1990) have discussed the idea of the “support bank” where individuals bank their support resources (give more than receive) throughout their lives, and then in times of need (e.g., poor health), they withdraw or request the needed support from those to whom they had previously provided support. Other researchers have explained an imbalance in expectations of reciprocity in kin relations due to their long-term nature and familial norms of obligation (e.g., Bengtson and Roberts 1991).

Further support for the evolutionary model of kinship and exchange among older adults comes from a study which found that in threatening situations, people are more likely to help those who are closely related rather than those who are moderately related or not related (Burnstein et al. 1994). In addition, relationships with close relatives are more likely to be continued than more distant kin relationships especially when exchange in the relationships is unbalanced (Klein Ikkink and van Tilburg 1998; Van Tilburg 1998).

Age-related disability and exchange

Decline in physical functioning in later life increases the need for social support (Baltes 1997; Freund and Baltes 2002) and decreases the ability to provide social support (Bennett 2005), and thus, likely changes the nature of exchange in relationships. It has been found that perceived support, both given and received, is associated with the overall health of older adults (Van Tilburg and van Groenou 2002; Wahrendorf et al. 2006). However, in terms of received support, the relational context matters in that older adults are more at ease with the family helping them than with help from other sources such as neighbors or other non-kin (Klein Ikkink and van Tilburg 1998), or from formal service providers (Howse et al. 2005). Support from family and friends plays an important role in adaptation to vision loss among older adults (Reinhardt 1996, 2001). But here as well, Reinhardt et al. (2003) found relationship type differences such that with loss of function over time, instrumental support from family members (but not friends) increased, and affective support from friends (but not family) decreased. Studying the social support of older adults in the context of visual impairment is important given that approximately 20% of adults of age 60 or older have some degree of vision impairment (Horowitz et al. 2005).

In sum, exchange and the nature of reciprocity in relationships have been found to vary depending on the degree of kinship and the type of relationship. We test the limits of exchange in kin and non-kin relationships with a sample of visually impaired older adults. An evolutionary model suggests that the degree of reciprocity (i.e., balanced exchange) declines with greater genetic relatedness. Thus, we predict that the greater the genetic relatedness the more imbalanced the exchange in relationships will be. However, diminished functioning or poor coping with age-related impairment such as vision loss, likely changes the nature of exchange in relationships. We expect that the more limited people are in their functioning and the lower their levels of adaptation to vision impairment, the less they will give and the more they will receive in their relationships. Finally, we predict that the association of kinship with exchange will be moderated by degree of impairment. Specifically, we expect that the imbalance in exchange typically found in kin relationships compared to non-kin relationships will diminish with greater levels of impairment.

Methods

Sample

Data were drawn from a study of the social resources of visually impaired older adults (Reinhardt 2001). Participants were recruited from the pool of applicants at a major vision rehabilitation agency in the Northeastern United States. Eligibility criteria included dwelling in the community, speaking English, and being age 65 or older. Analyses were conducted with responses of 570 individuals, ranging in age from 63 to 99 (M = 80.14, SD = 6.99), 50.5% of whom were female. Participants had various eye disease diagnoses including cataracts (35%), macular degeneration (67%), and glaucoma (27%). Slightly over half (54%) had only one of these diagnosis, 37% had two diagnoses, and approximately 9% had more than two diagnoses. Participants completed in-home interviews that lasted on average 90 min and were administered by trained graduate students.

For this study, we focus on both the characteristics of the primary participants as well as their reports on their relationships. The participants were asked to list members of their social network up to 15 persons, starting with family members. In total, 5,044 relationships were reported, including spouses (4.3%), family (50.7%; with 0.2% parents, 21.4% children, 7.0% siblings, 0.3% aunts and uncles, 2.2% cousins, 6.9% niece and nephews, 12.7% grandchildren), and friends (45.0%). Thus, the 5,044 relationships that were the units of analysis are nested within the 570 participants on whose reports the present analyses are based; thus the observations are not independent and the participant reports will likely have correlated errors. Multilevel analyses were conducted using SPSS software (version 13) to examine the associations of perceived exchange with the degree of relatedness, functional disability, and adaptation to visual impairment. This approach was selected because the data (relationships nested within participants) are multilevel in nature (Bryk and Raudenbush 2002). Hierarchical linear modeling (HLM) procedures account for the independence assumption and allow for correlated error structures (Luke 2004). Since typical analyses based on the assumption of independence cannot be used (e.g., linear regression, correlation, reliability analysis), for most analyses, we used HLM to test not only our primary research questions, but also to develop the rationale for some of the measures used. The two levels in these analyses include characteristics of the relationships (Level 1 variables) such as degree of genetic relatedness and nature of the exchange and the characteristics of the study participant within whom those relationships reports are nested (Level 2 variables), such as age, gender, vision impairment, and degree of adaptation.

Demographics and vision impairment

Age was self-reported. Gender was coded such that female = 1 and male = 0. Race was self-reported with categories collapsed to non-white (14%) and white (86%). Income adequacy was measured with a single item, namely: “How adequate do you think your income is? Would you say you have: 3 = enough for everything you need and any extras you want, 2 = just enough for the things you need but not for extras; or 1 = not enough even for the necessities” (M = 2.41, SD = 0.65). Twelve percent had achieved a college degree or higher (1) versus 88% with no college degree (0). The Functional Vision Screening Questionnaire (FV) was used to measure vision impairment severity (Horowitz et al. 1991). Fifteen self-report items assesses the extent to which vision loss causes difficulty in specific functional areas (e.g., difficulty reading labels on medicine bottles, 0 = no difficulty, 1 = difficulty; M = 10.59, SD = 3.18).

Social factors

Marital status was coded as married = 1, else = 0. Thirty-nine percent were married, the remainder being widowed or single. Network size is the sum of up to fifteen relationships participants were allowed to list (M = 8.91, SD = 3.90). Contact frequency is the sum of seeing each relationship partner (0 = not seen at least once during the past month, 1 = seen at least once during the past month) and speaking with each relationship partner (0 = not spoken with at least twice during the last month, 1 = spoken with at least twice during the last month; M = 1.42, SD = 0.70). The relatedness coefficient (degree of kinship) was coded by analyzing the different relationship types and the probability of genetic relatedness from 1.00 (100% relatedness, i.e., monozygotic twins) to 0 (0% genetic relatedness; e.g., non-kin friends) (Burnstein et al. 1994; Neyer and Lang 2003). Among the relationships reported by participants, none had a genetic relatedness of 1.0, 28.5% had a genetic content of 0.50 (parents, children, siblings), 19.9% had a genetic content of 0.25 (grandparent, grandchildren, and avuncular relationships), 2.2% had a genetic content of 0.1255 (cousins) and 49.3% were not related (genetic content of 0; spouses, relatives-in-law, friends, and neighbors).

Functioning and adaptation

Functional disability was assessed using the Older Americans Resources and Services (OARS) Multidimensional Functional Assessment Questionnaire (Center for the Study of Aging and Human Development 1975). The scale assesses difficulty in the performance of instrumental (7 items) and personal (7 items) daily living tasks. The 14 items were rated on a 3-point scale (0 = ‘no difficulty’ to 2 = ‘need help/cannot do task’; M = 9.74, SD = 7.53) and summed with a higher score indicating greater functional impairment. Adaptation to vision loss (AVL) was measured with a 24-item scale which assesses the extent to which the participant accepts vision loss in a realistic manner, has a positive attitude toward rehabilitative training, and a positive outlook toward maintaining relationships with family and friends (Horowitz and Reinhardt 1998). The items were scored on a 4-point Likert scale (0 = rarely to 3 = most of the time) and summed (M = 49.41, SD = 13.09) with higher scores indicating better adaptation to visual impairment.

Direction of exchange was measured by subtracting support given from support received for each relationship, similar to the approach used by Klein Ikkink and van Tilburg (1998) and Van Horn et al. (2001). Perceived social support was measured with participant self-report responses to the Arizona Social Support Interview Schedule (Barrera et al. 1981). Support received from network members is the sum of the participant ratings of affective (yes = 1 and no = 0 to each of intimate interaction, advice, and positive feedback) and instrumental support (yes = 1 and no = 0 to each of material aid, physical assistance, and checking in on/watching home) received from each of their relationships (M = 1.47, SD = 1.50). Support given is the sum of participant ratings of affective (yes = 1 and no = 0 to each of intimate interaction, advice, and positive feedback) and instrumental (yes = 1 and no = 0 to each of material aid, physical assistance, and checking in on/watching home) support provided in each of their relationships (M = 1.62, SD = 1.51). Affective and instrumental support scores were summed in this study as reciprocity is not considered to be task specific. For example, a visually impaired older adult may provide affective support to a friend and receive affective support from that friend. In another relationship, that elder may provide affective support yet receive instrumental support in return. Both of these support exchanges are considered reciprocal. Thus, by subtracting support given from support received, positive values indicate a tendency toward receiving more than giving, negative values indicate a tendency toward giving more than receiving, and a value of zero indicates equally balanced support given and received. It is noted that this is a more indirect measure of reciprocity as it is computed based on the participant’s report of support received and provided. It is not a measure of perceived reciprocity. The latter may actually be prone to bias and over-reporting of reciprocity according to some researchers (Jung 1990).

HLM analyses were conducted to further explore the associations of the self-reported received and given affective and instrumental support with each other as well as with key demographic characteristics (results not shown). Each kind of support (support received and given, both affective and instrumental) was significantly associated with the other at p < 0.001 level. For the exchange variable, participants believed they gave slightly more support than they received (M = −0.12, SD = 1.28).

The reciprocity measure was created by calculating the absolute value of the exchange variable, such that 0 = balanced reciprocity and 6 = the maximum inequality of exchange (M = 0.87, SD = 0.94).

Results

General patterns of reciprocity

First, the association of degree of relatedness with reciprocity was examined in a general linear model, specifying participant ID as a random factor. Patterns of the average levels of reciprocity across the six kin and non-kin groups are displayed in Fig. 1. Higher values on the measure of reciprocity indicate greater exchange inequality. Results showed a main effect on the degree of relatedness (F = 30.02, p < 0.001). Specifically, in post hoc comparisons, the 0.50 genetic relation group had significantly greater exchange inequality than the 0.25 genetic relation group (M = 1.10 vs. M = 0.79; p < 0.001), the friends (M = 1.10 vs. = 0.73; p < 0.001), and the “other” non-kin group (neighbors, colleagues or other acquaintances; M = 1.10 vs. M = 0.73, p < 0.001). The spouses show significantly greater exchange inequality than friends (M = 1.00 vs. M = 0.73, p < 0.05) and the “other” non-kin group (M = 1.00 vs. M = 0.73, p < 0.05).

Fig. 1
Average reciprocity across the six kin and non-kin groups. Higher values indicate a greater degree of inequality of exchange

HLM models

In order to focus on the unique association of genetic relatedness with exchange and reciprocity, we controlled for demographics and vision impairment as well as factors associated with relationship dynamics and exchange such as marital status and network characteristics since we wished to examine the association of genetic relatedness with exchange in relationships above and beyond these factors.

Genetic relatedness, reciprocity, and exchange

Associations of participant and relationship factors with reciprocity are described in the text, and associations of participant and relationship factors with direction of exchange are displayed in Table 1. The greater the degree of genetic relatedness in relationships, the less balanced the reciprocity (Estimate = 0.63, p < 0.001), bearing in mind that a value of 0 indicates equality and values >0 show imbalance in reciprocity. Regarding the direction of exchange, degree of kinship was related to the balance of exchange in relationships. Specifically, the ratio was in the direction such that the greater the genetic relatedness, participants gave more than they received (Table 1; model 1). Similarly, having higher levels of income adequacy and a greater network size were associated with giving more than one received. Conversely, greater contact frequency and greater age were associated with receiving more than one gave (Table 1, Model 1).

Table 1
Multilevel models depicting the association of level of genetic relatedness, functional disability, and adaptation to vision loss with direction of exchange

Functional disability, adaptation to visual impairment, and exchange

There were no significant associations of functioning (OARS) or adaptation to vision loss (AVL) with the measure of reciprocity. In terms of the direction of exchange, functional disability (OARS) was not significantly associated with exchange (Table 1, Model 2). Similarly, adaptation to vision loss (AVL) was not significantly associated with direction of exchange (Table 1, Model 4).

Association of exchange with relatedness moderated by adaptation to vision loss

To test whether the association of exchange with the degree of relatedness varied by functioning or degree of adaptation, we calculated two interactions. First, the functional impairment (OARS) by relatedness interaction was not statistically significant (Table 1, Model 3). Next, the Adaptation to Vision Loss (AVL) by relatedness interaction was statistically significant (Table 1, Model 5).

To examine the nature of this interaction, we used an online interactive calculator for probing interactions and calculating regions of significance in multilevel models developed by Preacher et al. (2006). In this case, direction of exchange is the outcome variable, the focal predictor (degree of genetic relatedness) is a Level 1 variable and the moderator (AVL) is a Level 2 variable, meaning that this is a cross-level interaction. The method developed by Preacher and colleagues (Preacher et al. 2006) draws on the Johnson-Neyman technique that defines the regions of significance, namely, the range within which the simple slope of the outcome variable on the focal predictor is significantly different from zero depending upon the moderator. To obtain the output necessary to test the interaction, Model 5 of Table 1 was re-analyzed with all indicator variables mean-centered. The estimates for the intercept, focal variable, moderator, and the interaction term were entered in the calculator along with appropriate coefficient variances and the range of possible values for reciprocity and degree of adaptation to vision loss. Results from the calculator (Fig. 2) illustrate the nature of simple slopes for degree of kinship and direction of exchange. The straight central diagonal line represents changes in the simple slopes (y axis) by ratings of adaptation to vision loss (x axis). The two curved diagonal lines above and below the central line are confidence bands that indicate at what point the simple slopes differ significantly from zero. The region of significance on the moderator (AVL) ranges from the mean-centered values of −27.44 to −5.41, corresponding to the regular AVL values of 25 and 44, respectively. Thus, the simple slopes of exchange associated with degree of kinship are significant only at levels of AVL in the lowest fifth percentile (to the left of the dashed line), and the highest 70th percentile (to the right of the dashed line). This pattern suggests that for the highest 70th percentile of AVL, the more people think they give versus receive the greater the degree of genetic relatedness in the relationship, but for the lowest 5th percentile this pattern is reversed, such that people believe they receive more than they give the greater the degree of genetic relatedness.

Fig. 2
Significance of the association of exchange with genetic relatedness moderated by degree of adaptation to vision loss

Discussion

The aims of this study were to examine the associations of genetic relatedness with reciprocity and the nature of exchange regarding support given and support received in the relationships of older adults coping with vision impairment. We found that exchange was more imbalanced in relationships with kin than in relationships with non-kin but the direction of the imbalance differed depending on the participant’s level of adaptation to impairment. Specifically, at high levels of adaptation, participants reported giving more support than they received from kin, but at low levels of adaptation participants reported receiving more from kin than they gave to those kin.

The results showing the greater imbalance of exchange for kin versus non-kin is directly predicted from inclusive fitness theory because an individual’s inclusive fitness benefits from their investment in kin and thus these investments do not need to be reciprocated to have fitness value. By contrast, investments in non-kin demand eventual reciprocation to have any fitness value. The fact that the nature of the imbalance in exchange with kin changes as a function of level of adaptation to vision impairment is consistent with the nature of the exchange rule in communal relations (Clark 1981; Fiske 1992). Specifically, in communal relations, of which kinship is the prototypical example, support is provided according to the needs of the parties involved without keeping a running track on the quantity of investment by each party. In other words, in communal relations such as kinship relations, whoever has the greatest need at any given time receives the greatest support, which fits the patterns we found. It is perhaps remarkable, that even among a sample of visually impaired older adults, the tendency is to perceive that one gives more than one receives, more so for kin relationships than non-kin, and this tendency only reverses at very low levels of adaptation to vision impairment. It seems that being able to give remains important for older adults with vision impairment and when the adaptation to vision loss gets worse, the relationship to kin is subjectively more balanced.

Showing that genetic relatedness and reciprocity have an impact on relationships over time would strengthen our conclusions. Specifically, future research should examine the impact of changes in impairment or adaptation to vision loss on kin and non-kin relationships, with the prediction that kin will remain in the network even when the imbalance in exchange increases due to increasing dependence. There may be an identifiable instance where an acceptable imbalance is in the direction of the elder receiving more than they provide as they become more functionally impaired, and the relationship evolves into more of a caregiving relationship. For example, an elder who is high in functional disability may receive a lot of instrumental help from her daughter and probably also some affective support. That elder may, in turn, provide some affective support to her daughter. However, the total support received is still greater than that provided in this situation. As noted earlier, older adults are more at ease with family helping them in times of need, than with help from other sources such as neighbors or other non-kin (Klein Ikkink and van Tilburg 1998). Elders are not expected to reciprocate, nor are they able to reciprocate under the circumstances of poor health and functional disability, and that is acceptable.

Perceived loss of control is another factor which could influence the decrease of well-being in this particular case (Liang et al. 2001). Thus, further work is needed to examine the mental health consequences of imbalance of exchange among post-reproductive and impaired older adults. Those who provide help to elders who are experiencing increasing levels of functional disability, may want to be careful that they target their assistance specifically to tasks where the elder truly need it. It is not often necessary to take over all daily tasks, and doing so could result in excess dependence on the part of the elder. It is important not to impede independent task completion where possible for older adults with functional disability, and also to facilitate any support provision to others where possible (e.g., affective support) given the positive impact that has on well-being for all persons.

Acknowledgments

This research was supported by National Institute of Mental Health Grant R29MH53285.

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