geographic distance and intergenerational contact: an empirical examination of the relationship

GEOGRAPHIC DISTANCE AND INTERGENERATIONAL CONTACT:

An Empirical Examination of the Relationship

B. GAIL FRANKEL and

DAVID J. DeWlT University of Western Ontario

ABSTRACT: Three phases of thought in the literature on intergenerational contact, especially between the elderly and their adult children, are discussed in an attempt to understand the disparate conclusions reached in each period. A number of methodological problems contribute to the contradictory problems. Spectficalty, we find ordinal-level data used in multivariate analyses, weak descriptive measures, and inappropriate construction of indices of interaction, and mispecification of a linear model in many studies. Using data from 454 elderly residents in a mid-size Canadian city, we examine the relationship between geographic distance and several indicators of intergenerational contact, controlling for a number of important so&demographic variables. Our findings are that distance is the most important predictor of all forms of contact, and that a curvilinear (quadratic) model generally provides the best$t to the data. It is argued that the complexity of the relationship needs to be examined in further studies of interaction between the elder& and their adult children

INTRODUCTION

The relationship between geographic distance and intergenerational ties has been studied both theoretically and empirically. In contemporary society, characterized by

Direct ail correspondence to: David J. DeWit, Department of Sociology, The University of Western Ontario, London, Ontario, N6A X2, Canada.

JOURNAL OF AGING STUDIES, Volume 3, Number 2, pages 139-162. Copyright @ 1989 by JAI Press, Inc. All rights of reproduction in any form reserved. ISSN: 0890-4065.

140 JOURNAL OF AGING STUDIES Vol. ~/NO. 2/l 999

higher rates of geographic mobility, adult children may be less likely to live in close physical proximity to their elderly parents. The theoretical debate has focused on three basic positions. The first, suggested by Parsons (1943), maintains that increased geographic distance is associated with a significant reduction in the amount of interaction with older parents. Supporters of this position include Robins and Tomanec (1962) and Gibson (1972), among others. The second position is derived from the work of Litwak (1960b) and Sussman (1953,1954,1959,1965), and receives support from Osterreich (1965), Rosenmayr (1968) and Shanas (1973). These authors contend that geographic distance has a far less important impact on the amount of interaction. The third interpretation of the relationship appears to favor a consensus, standing in partial agreement with both of the other stances. Those in support of this position (see, for example, Reiss 1962; Berardo 1967; Bultena 1969; Troll, Miller and Stehley 1979; Leigh 1982) maintain that geographic distance does have a negative impact on kinship interaction but that interaction still occurs, despite distance between households of adult children and their elderly parents.

What seems to be at issue in the debate is the degree of isolation of the nuclear family and the contribution of geographic distance to that isolation. While some attempts at reconciling differences of interpretation have concentrated on identifying certain antecedent methodological problems (see, for example, Adams 1968; Troll 1971; Ferraro 1974; Lee 1980), the question of isolation still remains largely unanswered (Sokolovsky and Cohen 198 1).

Presented in this article is a brief review of the sociohistoric context that gave rise to the controversy about the isolation of the nuclear family and the relationship between geographic distance and intergenerational contact, and the methodological issues associated with that controversy. (For a more detailed discussion and critical review of the literature see DeWit [ 19861; and DeWit and Frankel [1988].) The major purpose of this article, however, is to assess the exact nature of the relationship between geographic distance and intergenerational contact, taking into account some of the methodological problems that are identified as primary sources of disparate findings in the earlier literature.

A BRIEF REVIEW OF THE SOCIOHISTORICAL CONTEXT OF ADULT CHILD/OLDER PARENT INTERACTION

As noted earlier, we identify three phases of thought regarding the role of the family as providers of care to elderly kin that are distinguishable in terms of the importance attached to geographic distance as an influence on intergenerational ties. The first phase, occurring in the immediate postwar era (1945-1955), was dominated by Parsonian theory on family relations (Parsons 1943).

In very general terms, Parsons contended that urbanization and industrialization led to the rise of the isolated nuclear family unit. He also claimed that the demands of urban society would lead to higher rates of geographic mobility among adult children, increasing the physical distance between them and their elderly parents. In addition, smaller residences would reduce the ability of families to live together (see Ward 1979). The assumption seemed to be that isolation would follow and supportive ties between the elderly and their adult children would diminish. Thus, Parsons and this

Geographic Distance and Intergenerational Contact 141

early phase of thought, felt that the modern nuclear family would be relatively isolated and that the forces of modernization were too strong for regular contact between older parents and their children.

Parsons’ work generated considerable criticism and research during the second phase of thought, from 195% 1970. The dominant view of this period was expressed by Marvin Sussman (1953, 1954, 1959, 1965), who argued that moderate levels of interaction and contact occurred despite physical distance between elderly parents and adult children. Evidence from a variety of studies conducted during this period seemed to support Sussman’s notion that the isolated nuclear family was a myth (Litwak 1960a, b; Osterreich 1965; Rosenmayr 1968; Shanas 1973,1979; Sussman and Burchinal 1962).

The work of Sussman and his followers was influential in setting the stage for the third phase of thought that suggests that geographic distance does have an impact on kin interaction, but that interaction still occurs despite distance between the households of relatives. We describe this phase as a consensus position, proposing that contact continues but at reduced levels, regardless of distance (Berardo 1967; Bultena 1969; DeWit et al. 1988; Lee 1980; Leigh 1982; Marshall and Rosenthal 1987).

METHODOLOGICAL ISSUES AND PROBLEMS IN THE STUDY OF INTERGENERATIONAL TIES

It is our belief that at least some part of the differences in interpretation of the adult child/older parent relationship lies in a number of methodological problems, some of which were more prevalent during some phases of thought than others. In our earlier paper (DeWit and Frankel 1988), some 15 of these problems were identified and discussed. The remainder of this article is devoted to an examination of some of the major methodological issues.

A Reliance on Weak Descriptive Measures and Variations in Measures Selected

Many of the studies conducted in the early phases of thought relied on purely descriptive measures of kinship interaction and thus contributed little concrete empirical evidence that would refute or support theories about contact (Adams 1968). Many of these studies simply held geographic distance as a constant (Axelrod 1956; Key 1961; Sussman 1953). In addition, many studies (Osterreich 1965; Robins and Tomanec 1962; Sussman 1953) failed to consider either the quantity, quality, or frequency of contact (see Ferraro 1974). When contact is measured in its most simple and descriptive terms-percentage of relatives who exchanged “supportive aid’-it is very difficult to compare the results of studies. As well, little information is provided that allows for the discussion of the nature of contact between relatives. In other words, the question remains unanswered as to what precise level of contact occurs at certain points of distance between the elderly person and the adult child.

A related problem stems from the selection of items as indicators of interaction. Some studies used only visits or face-to-face contact as a measure of kin interaction (Litwak 1960a, b; Reiss 1962; Bultena 1969; Shanas 1973; Clark and Gordon 1979). In support of this position, Lopata (1978, p. 362) argues that compared with face-to-


face contact, “forms of interaction such as telephoning or letter writing are not of sufficient importance to be converted into actual supports, even emotional ones.” On the other hand, some studies include several measures whereas others combine several indicators to form a composite measure of interaction, despite differences in the mean- ing of the indicators (Hammel and Yarbrough 1973; Berardo 1967; Osterreich 1965; Petrovsky 1976).

The procedure of combining indicators of interaction to construct an index of contact is methodologically suspect for several reasons. First, the direction of the relationship between geographic distance and interaction may be either positive or negative, depending on the type of contact. For example, increased distance may be associated with decreased face-to-face contact and increased contact by letter or telephone. Combining such indicators of contact may be misleading and could seriously invalidate results.

A second methodological problem in constructing indices of contact is the assumption that different indicators of interaction may not act as substitutes for one another. In fact, Hammel and Yarbrough (1973) discovered that the extent to which contact items act as substitutes for one another varies by distance from the focal person. It is also possible that a given contact item may show both positive and negative relationships with distance. Thus any attempt to combine indicators into an index of interaction may be inappropriate.

This wide variation between studies and the alteration of the scope of the measure of contact contributes to conflicting results. The weight of evidence would appear to suggest that the effect of distance on interaction varies with the type of contact considered. In the analyses that follow, both a variable scale of distance and a wide range of single indicators of contact are included for study.

Another frequent problem in the literature on intergenerational contact concerns the assessment of the “qualitative” aspects of family and kin relationships. There appears to be an overemphasis on purely quantitative measures such as the amount of contact that would include number of visits, phone calls, letters, and so forth, among kin but an underemphasis on measures of feeling or affect. As Duffy (1982) points out, “measures of contact alone do not illustrate the motivational dynamics of that contact, nor its intensity or importance” (Duffy 1982, p. 5). Quantity of interaction then does not guarantee emotionally satisfying and supportive relationships.

In the present study, we include a measure of the importance or intensity of the adult child/older parent relationship. This measure, the frequency of important conversations between children and their parents, rests on the assumption that conversations defined as important by the older parent are likely to be qualitatively or substantively different from other conversations.

Problems with Levels of Measurement

Occasionally in the literature on intergenerational contact, researchers have applied multivariate techniques to ordinal-level data in their analyses. This practice can lead to imprecise estimates of regression coefficients. Distance is often measured by using categories such as “same neighbourhood,” “same city,” “within an hour’s drive,” and so forth, whereas interaction may be assessed as contact “within the past 24 hours,”


“more than 24 hours but less than once a week, ” “more than once a week but less than once a month,” and so forth (see, for example, Clark and Gordon 1979; Wilkening, Guerrero, and Ginsberg 1972). An additional problem here is that it may not be possible to construct midpoints for categories of distance or contact to create more or less quasi-interval-level data that would permit the appropriate use of multivariate techniques.

In the analysis that follows, a range of values is assigned to each of the original ordinal-level categories of both distance and contact measures. Midpoints are then derived for each category, in order to approach interval-level measurement. While the resulting scales do not assume precisely equal distances between categories, they do more closely approximate interval level measures than the original scales. (The original scales, new scale categories and derived midpoints are presented in Appendix A.)

Misspecification of a Linear Model

Much of the literature dealing with intergenerational contact implicitly assumes a linear model to represent the relationship between contact and distance, despite evidence that such models do not lit the data very well (cf. Mangen and McChesney 1985; Reiss 1962). There does not appear to be a sound theoretical explanation of nonlinearity in contact patterns, although Mangen and McChesney (1985) argue for abandoning “simplistic” views of the relationship and for addressing the issue of complexity.

It is suggested here that a reasonable explanation for nonlinearity might be found in three interrelated factors associated with the distance variable: (1) the notion of distance as a continuum wherein contact types cluster at certain locations; (2) the notion of a set of time/cost constraints operating more forcefully on contact behavior at certain locations than others; and (3) the notion of a threshold level of distance at which an individual makes a decision to more or less forgo a given type of contact in favor of another. In order to understand fully how these factors affect intergenerational contact to produce nonlinear patterns, a somewhat detailed elaboration is required.

First, it may be useful to picture geographic distance as a continuum with zero or minimal distance at one end and the most distant geographic location at the other. At the lower end, where distances are quite small, there is not only a greater clustering of types of contact, but also the likelihood that these contacts would be more intense and supportive (e.g., important conversations, face-to-face and telephone contact). At the opposite end of the continuum, where distance is large, contact by letter or overnight visit may be maintained with greater ease and regularity.

Overnight visits and telephone conversations may contribute to greater amounts of support over long distances; however, one would expect such contacts to be linked to the financial status of the persons involved. This expectation leads to the second factor mentioned above, namely that the relationship between intergenerational contact and the distance continuum is a function of a set of time/cost constraints that will vary with contact type. That is to say, a given contact type (telephone calls, for example) will place certain constraints or demands on an elderly individual or adult child that involve a measure of time invested and/or monetary cost. The relationship is also a function


of the demand for a particular contact type at a given distance. For example, a child living two blocks from an elderly parent will be less likely to have overnight visits than a child living more than a day’s drive away.

The magnitude of each constraint will depend on the distance between kin groups, the type of contact involved, and the costs (both monetary and nonmonetary) for both the initiator and the receiver of the contact. The degree to which this constraint influences individual behavior with respect to both the choice of contact type and the frequency of maintaining it, will depend on several inte~elated factors. Some of these are external factors, such as cultural norms and values, education and income, whereas others pertain to individual tastes and preferences for particular types of contact.

The issuerof personal convenience and time/cost constraints have been considered in the literature as variables that explain the salience of distance as a predictor of intergeneration~ contact (Hammel 1977; Robins and Tomanec 1962). However, these factors may also be used to explain nonlinear patterns of contact. Thus, as a formula- tion of our third point, it seems plausible that at some location along the distance continuum a distance threshold is reached wherein it becomes just too costly and time-consuming to maintain a given type of contact with sufficient ease and regularity. These time/cost constraints may lead individuals to forgo a particular type of contact in favor of another.

As a simple illustration of how the three factors above combine to evince nonlinearity in contact, consider contact by overnight visits. Frequent contact that involves overnight visits suggests that those persons initiating the contact are located at some extreme point along a distance continuum. For this type of contact, the time/cost constraint may be assumed to be large. DeWit and Frankel(1988) outline the nature of these constraints as follows:

The time or convenience factor consists of the travel time from the point of origin to the point of destination, the length of time spent at the place of destination and the travel time returning to the place of origin. The cost factor consists of the monetary costs of travel (DeWit and Frankel 1988, p. 37).

Given the heavy time/cost constraints bone largely by the initiator of contact, it seems plausible that overnight visits will occur most frequently somewhere “mid-way” on a distance continuum. On the first section of the continuum, frequent overnight visits are unlikely given that face-to-face contact is easily maintained on a daily or weekly basis. On the last or most distant part of the continuum, overnight visits would be expected to decline because of the heavy costs of time and money associated with traveling long distances. Here it is likely that contact by overnight visits will be fore- gone in favor of maintaining contact by letter or telephone, modes that are less costly and time-consuming to initiate.

In the present study, we test for nonlinear relationships to provide sound empirical support for a decision about the exact nature of the relationship between contact and distance. Once the relationship has been adequately described, more reasonable explanations for its form can be explored.


INTERGENERATIONAL CONTACT AMONG A SAMPLE OF ELDERLY RESPONDENTS

In the analyses that follow, the impact of geographic distance on separate facets or subdimensions of interaction is examined. The goal is not so much to explain or predict as it is to highlight patterns of interaction for different contact indicators.

Propositions

Given the exploratory nature of this work, two general propositions are formulated:

1. geographic distance is the most important antecedent of all types of contact; and 2. geographic distance will evince nonlinear patterns of interaction.

Variables

The propositions listed above consist of one common independent variable and five dependent variables. The independent variable is geographic distance between the elderly respondent and his or her adult children. The dependent variables are separate indicators of interaction, including frequency of face-to-face contact, frequency of telephone calls, frequency of writing letters, frequency of overnight visits and frequency of important conversations (see Appendix A). Questions about frequency of interaction were worded as follows: “How often do you talk to each other on the phone? Exchange letters? Talk over things that are important to you? See (spend time with) this child? Overnight visits?” The questions did not specify who initiated the contact.

In addition to the main predictor variable-“distance’‘-nine control variables will be introduced into the analysis. These include the child’s income, gender, marital status and age, and the education, ethnic background, gender, age and health of the elderly respondent. The purpose here is to observe any significant changes in the pattern of the relationship between distance and contact when other factors are included in the regression equation. Income, education, ethnicity, age, sex, and health are selected because of their hypothesized influence, in much of the literature, on face-to-face contact.

The variable “ethnicity” is dichotomized into traditional and modem groups based on earlier work using these data (see Wister 1985). This earlier research defined traditional families as those whose ethnic groups originated from Eastern, Central, and Southern Europe; Asia, and South America. More modem families were defined as those whose ethnic groups originated from Northern Europe. (See Lee [ 19801 and Troll [ 19711 for a review of literature in many of these areas; Duffy [ 19821 for a good discussion on marital status; and Treas [1977] for the treatment of gender as a predictor variable.)

These variables are derived from information reported by an elderly respondent on both a first and second child. The data set, described in a later section, is “hierarchical” in structure to the extent that information on several children (in this case four) is collected. The size of the study sample thus decreases when examining respondents with a successively higher number of children. For example, it is expected that most


elderly respondents will have at least one child, but that the number of respondents with two or three children will be less.

Normally, for the purposes of data analysis, there would be little probiem in selecting arbitrarily any two children. However, the problem becomes more complex in terms of the manner in which the fust child is defined. In this study, the first child is defined as living geographically closest to the elderly respondent. The inclusion of the tist child in the analysis is therefore necessary because of a potential problem of bias introduced by distance. For example, children living geographic~ly closest to the elderly respondent may be a select group somehow set apart from children living farther away. They may, on average, be older (or younger) than more distant children, or may include a greater proportion of separated or divorced persons, This category also contains the greatest number of sample cases. The child next farthest away (labeled as “Child Two” in the data set) is selected solely on the basis of its larger sample size, when compared to the smaller number of respondents having a third or fourth child.

The decision to conduct separate analyses for the nearest two adult children raises an important methodological concern not yet addressed in this article. It is quite likely that there is some degree of mutual causation between geographic distance and particular aspects of the adult child/older parent relationship. According to DeWit, Wister, and Burch (1988, p. 8), “while physical distance affects levels and types of contact, the reverse may also be true since physical distance may be linked to social distance. Thus, the closest family members in terms of intimacy may be closest in distance.” Close examination of the nearest two children in separate analyses, then, may serve to reduce any “confounding influence” of intimacy on geographic distance. (See Appendix B for the number and distribution of each child on distance and contact scales.)

Measurement

Geographic distance is initially measured using an eight-point ordinal scale. It would be incorrect to assume even roughly equal intervals between each of the eight units. Distance is expressed somewhat crudely in units of time. The categories of this scale range from “living together” (i.e., with the elderly ~di~dual) to “living outside con~en- tal North America” (see Appendix A). Frequency of contact/~teraction is also measured using an eight-point ordinal scale. This scale is also problematic to the extent that intervals between its points or categories cannot be assumed to be equal. The categories range from “little or no contact” to “contact on a daily basis” (see Appendix A).

In order to approach the interval level of measurement necessary to proceed with regression analysis, the ordinal-level distance and interaction scales were maimed. This modification procedure involved as its first step the deletion of the first and last categories of the distance variable. This decision was deemed necessary in that it would be nonsensical to conceive of “frequency of telephone calls” between persons living in the same household. The last category, “outside continental North America,” was problematic because it contained too few cases and because it could not properly be converted into the desired unit of meas~ement. In this instance, cases were assigned to the nearest category, “more than a day’s drive.”

In the second step of the procedure, each category of the independent and dependent variables was converted into a new unit or category. The independent variable


categories were converted into units of time or hours from the elderly respondent’s place of residence. This was achieved by constructing a range of values (in this case, number of hours) around each category and then arriving at a midpoint value. For example, the category “less than a day’s drive” was assigned a range of from one to six hours. The value 4 was selected as an appropriate midpoint. This procedure was repeated for the five remaining categories. The resulting interval-level distance scale (measured in hours) ranged in value from .05 or 3 minutes (corresponding to the old category of “walking distance”) to 13 hours (corresponding to the old category of “more than a day’s drive”) (see Appendix A).

The dependent variable categories were converted into the number of contacts in the period of one year. The same procedure for converting categories into new units was followed as outlined for the distance scale. For example, contact “2-3 times a week” was assigned to a midpoint value of 130, with a range of from 104 to 156. The category “once a year” was simply assigned a value of 1.

Data and Research Design

The data for this article were obtained from a 1983 survey of 454 elderly persons living in noncollective households in the city of London, Canada. The survey employed a cross-sectional research design. A proportionate random sample, stratified by age and sex, was selected. The sampling frame consisted of the 1982 Municipal Tax Assess- ment File for the city of London. By using a two-stage sampling scheme along with an anticipated nonresponse rate of 50%, an inflated sample size of 900 elements was generated. These 900 sample elements were broken down into eight categories by age and sex. Four age categories (i.e., 65-69, 70-74, 75-79, 80+) were selected for each gender category, creating a total of eight categories. The sample elements were then selected from the age-sex groups in the Assessment File using a simple random selection procedure. Data were collected by means of an interview schedule that consisted of both structured and open-ended questions. The schedule was subjected to a pre-test in order to achieve a refinement of the questions. From the total of 900 sample elements, roughly half or 454 interviews were completed in the study, very close to the goal of 450 elements.

Statistical Analysis

In this study, polynomial regression analysis is used as a means to test for any departure from linearity in the relationships between geographic distance and four different indicators of interaction. The last significant increment to R2 is the “order” of the polynomial, and only unstandardized regression coefficients are reported. Accord- ing to Pedhauzur (1982). . . .

polynomial regression analysis is carried out as ordinary multiple regression analysis,

except that powered vectors are included and the analysis is done hierarchically. That is, the

analysis is carried out in a series of steps, beginning with the first degree polynomial and

followed successively by higher degree polynomials. At each step, the proportion of vari-

ance of the dependent variable incremented by a higher degree polynomial is tested for statistical significance (Pedhauzur 1982, p. 406).


TABLE 1

Mean Levels of Contact in a One-Year Period

Child One Child Two x x

Face to face 68.6 40.4 Telephone calls 139.9 82.1

Writing letters 2.0 4.0

Overnight visits 2.4 3.6

Important conversations 23.9 18.4

Results and Discussion

Table 1 presents the mean levels of contact for Child One and Child Two for all five types of contact. Contact types more likely to be associated with the minimal distance end of the geographic distance continuum appear to be more frequent for the nearest child. Thus, mean levels of face-to-face and telephone contact are higher for Child One. Writing letters and overnight visits are more common for the child who lives farther away. The mean levels of important conversations lend some support to the notion that social distance and geographic distance are related. If important conversations are seen as an indicator of the quality of contact and the intimacy of the relationship, the nearer child (Child One) would be expected to have more important conversations than the more distant Child Two. This is, in fact, what is observed.

Table 2 presents zero-order correlations between geographic distance and the nine control variables, separately for Child One and Child Two. At the bivariate level,

TABLE 2

Zero-Order Correlation Coefficients Between Geographic Distance and Control Variables

for Child One and Child Two

Geographic Distance

Control Variables

Child’s income

Child’s gender

Child’s marital status

Child’s age Respondent’s health

Respondent’s education

Respondent’s ethnicity Respondent’s age

Respondent’s gender

Child One Child Two

.33*** .28***

-.05 -.Ol

.04 .05

-.07 .13** .09 .Ol .18*** .08

-.02 .Ol -.Ol .12*

-.03 .07

Notes: *p 5.05. **ps .Ol.

***p 5 .OOl.

Gender Variables-male = 1; female = 2; Marital Status-nonmarried = 1, married = 2; Ethnicity-traditional = 1, modem = 2;

(see note 1).


positive significant relationships are observed between child’s income and geographic distance for both children (r = .33, Child One, r = .28, Child 2). Thus children with higher income tend to live farther away from the elderly respondent. For Child One, child’s education is also significantly related to distance, with higher education being associated with greater distance. For Child Two, both child’s age and respondent’s age are significantly related to geographic distance. Older children live farther away, and, logically enough, older parents live farther away. Aside from income, however, the correlations are quite small. It seems likely that children with higher incomes may be in occupations requiring more mobility and thus may be living farther from their parents because of the demands of their jobs.

Table 3 presents zero-order correlation coefficients for the relationships between five contact variables and child’s geographic distance, gender, marital status and age, along with the elderly respondent’s income, health, education, ethnicity, age, gender, and health, for both Child One and Two. Several features from this table emerge as being important. One observation is that distance (relative to all characteristics of both child and respondent) is the most important correlate of interaction for four of the contact types, for both children. Only for important conversations is distance less important than other factors.

Second, the pattern of correlations between geographic distance and type of contact lends credence to our contention that certain types of contact are more likely to occur at certain points on the distance continuum. For both children, face-to-face and telephone contact are negatively related to distance, indicating that greater distance is associated with less of these types of contact. On the other hand, distance is positively associated with frequency of contact by letters and overnight visits. One would expect that when the distance between kin is greater, the frequency of overnight visits would be higher (as would letter writing) because the time required to travel greater distances would be more likely to lead to an overnight visit than other forms of face-to-face contact. The small negative relationships between distance and important conversations might well indicate that distance has little to do with the qualitative aspects of contact.

Income (next to distance) is the most important remaining correlate of interaction. Worth noting are the moderate negative correlations between child’s income and face-to-face and telephone contact. The coefficients indicate that children with high income are less likely to maintain contact with their parents by either visiting or telephoning, and more likely to maintain frequent contact by letter and overnight visits. It may be that children with higher incomes are more mobile, and may in fact live further away. The correlations between income and distance are .33 for Child One and .28 for Child Two (p I .OOl>, lending support to the notion of increasng distance with higher income (see Table 2). Thus, the correlations observed between income and frequency of contact may, at least in part, reflect the influence of distance on income.

It is also important to note that child’s income is unrelated to the frequency of important conversations. In fact it appears that the qualitative aspect of contact is only related to the age, health and gender of the older respondent, for Child One and the respondent’s gender only for Child Two. None of these relationships is particularly strong, but there is a tendency toward increased frequency of important conversations when the elderly respondent is in poor health, older, and female. In a sense, then,

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Geographic Distance and intergenerational Contact 151

important conversations appear to be more frequent when the need for supportive contact is higher.

Several other relationships in Table 3 are worthy of comment. First, female children are more likely to maintain contact by telephone; perhaps this finding is reflective of the nurturing role of women. It seems more likely that female children will maintain regular contact with their elderly parents than will their male siblings, especially on the telephone.

Younger children and single children have more face-to-face contact with their elderly parents. This may well be a result of less-developed social networks on the part of the children on the one hand, or continued reliance on parental guidance and support on the other.

In summary, on the bivariate level, geographic distance and child’s income are the most important correlates of frequency of contact of all types. The patterns of the correlations lend support to the notion of a continuum of geographic distance along which different types of contact are clustered at different points. The same patterns also support the idea of a time/cost constraint associated with different types of contact.

The results of the polynomial regression analyses are presented in Tables 4 through 8, for the five types of contact and the nine additional control variables, separately for Child one and Child Two. Several important findings emerge.

In support of the initial proposition, distance is by far the strongest predictor of all types of contact, adding substantially to explained variance in most cases. Results from Table 4 indicate that the linear distance vector contributes 10% to the explained

TABLE 4

Polynomial Regression of Face-to-Face Contact on Geographic Distance Vectors and Linear Independent Variables

Variable

Child One Child Two Stepwise Inclusion (N = 195) Stepwise Inclusion (N = 167)

I II 111 I /I III

Constant 326.61 272.58 203.92 Child’s income -15.34*** -7.61 -2.92

Child’s gender 16.98 13.26 14.66 Child’s marital status -61.45*** -69.37*** -79.89***

Child’s age -0.42 -1.15 -1.06 Respondent’s health -19.29* -16.49* -14.43* Respondent’s education -0.52 -0.02 0.33 Respondent’s ethnicity -1.03 -0.95 -0.79 Respondent’s age 0.36 0.96 1.36 Respondent’s gender -9.17 -5.63 -6.26 Distance: linear (XI) -36.61*** -85.35***

Distance: quadratic (X2) 16.76***

R2 .24 .34 .40 .15 .27 .35

109.12

-1.27**

5.05

-7.19

-2.23**

-0.2 1

-0.92

-0.75* 1.17

-1.54 -

-

71.24 34.99

-2.80 -0.85

1.53 2.48

-11.81 -19.94

-1.95** -1.46*

1.03 1.87 -1.25 -0.63

-0.62 -0.42

1.18 1.03 2.31 6.17

-23.25*** -52.75***

21.35**

Notes: *p 5 .05 **PI.01

***p 5 .OOl

Gender Variables-male = I, female = 2; Marital Status-nonmarried = I, married = 2; Ethnicity-traditional = I, modern _ 2.


variance in face-to-face contact for Child One and 12% for Child Two. The quadratic distance vector explains an additional 6% of the variance for Child One and 8% for Child Two. The remaining predictor variables combined explain 24% and 15% of the variance, respectively. Contrary to findings in the literature, figures here show that once distance vectors are entered into the regression equation, respondent’s gender and ethnicity have no significant impact on face-to-face contact. For both children, child’s income has no significant impact on contact once geographic distance is entered into the equation. This finding may be explained by the moderate positive correlations between income and distance presented earlier in this article. However, results do indicate that for Child One, respondents in poor physical health have more frequent face-to-face contact with their adult children, and that nonmarried children have more face-to-face contact. For Child Two, only child’s age is significant, with younger children having more face-to-face contact.

Results from Table 5 show that the linear distance vector again plays a dominant role, with 10% of the variance in contact by telephone explained for Child One and 14% for Child Two. All other predictor variables initially explain 15% and 14% of the variance for Child One and Child Two, respectively. In reference to telephone contact for Child One, only child’s gender is significant, with female children having more contact. For Child Two, female children and younger children have significantly more telephone contact. Once again, for both children, child’s income retains little or no predictive power with the addition of geographic distance to the regression equation.

TABLE 5

P~i~n~rnial Regression of Telephone Contact on Geowaohic Distance Vectors and Linear Independent Variables

Child One Child Two Stepwise inclusion (N = 195) Stepwise Inclusion (N = 767)

Variable I II NI t 11 111

Constant 43.52 -12.23 -64.00 -37.97 -96.44 -133.07 Child’s income -19.08*** -11.1 I* -7.57 -9.45** -2.54 -0.57 Child’s gender 46.22** 42.38** 43.43** 31.53* 35.36** 30.25** Child’s marital status 21.43 13.26 5.33 17.24 10.11 1.89 Child’s age -0.02 -0.76 -0.69 -3.16** -2.73** -2.23* Respondent’s health 1.49 4.38 5.94 3.68 5.60 6.45 Respondent’s education -1.23 -0.71 -0.45 0.32 -0.02 0.44 Respondent’s ethnicity -0.85 -0.77 -0.65 -1.05* -0.84 -0.64 Respondent’s age 0.83 1.45 1.74 2.61 2.62 2.47 Respondent’s gender 22.34 26.00 25.52 13.74 19.68 23.58 Distance: linear (XI) - -37.75*** -74.49*** - -35.89*** -65.70*** Distance: quadratic (X2) - - 12.64** - - 21.58**

R= .15 .25 .28 .I4 .28 .32

Notest *p 5.05 **p~.ol

***p ZG ,001 Gender Variables-male = 1, female = 2; Marital Status-nonmarried = I, married = 2; Ethnicity-traditional= I. modem = 2.

Geographic Distance and intergenerational Contact 153

TABLE 6

Polynomial Regression of Frequency of Wrung Letters on Geographic Distance Vectors and Linear independent Variables

Child One Child Two Stepwise inclusion Stepwise inclusion

(N = 195) (N = 167)

Vffriabk i ii i iI iii

Constant -16.57 -12.13 - 13.73 -5.18 -9.30 Child’s income 0.30 -0.34 2.02** 1.01* 1.23% Child’s gender 0.61 0.91 2.78 2.23 1.65 Child’s marital status -0.42 0.23 -2.19 -1.15 -2.07 Child’s age -0.01 0.06 -0.11 -0.17 -0.12 Respondent’s health 0.48 0.26 0.66 0.38 0.48 Respondent’s education 0.33 0.29 -0.39 -0.32 -0.25 Respondent’s ethnicity -0.0 1 -0.01 -0.02 -0.05 -0.03 Respondent’s age 0.17 0.12 0.11 0.11 0.09 Respondent’s gender -0.42 -0.7 1 3.96* 3.09 3.53* Distance: linear (XI) - 3.01** - 5.25** 1.89 Distance: quadratic (X2) - NSS - - 2.43*

R2 .05 .17 .I1 .27 .30

Nob: *p I .05 **p I ,001

Gender Variables-male = 1, female = 2; Marital Status-nonmarried = 1, married = 2; Ethnicity-traditional _ 1, modern = 2, NSS = not statistically significant.

Results from Table 6 show that the distance vectors (linear and quadratic combined) explain 12% of the variance in contact by letter for Child One and 19% for Child Two. For Child Two, results show that children with higher income are more likely to maintain contact by letter, again probably at~butabie to the increased distance associated with higher income. Also for Child Two, greater frequency of letter writing is associated with female parents.

Turning to Table 7, we see that the distance vectors are the only significant predic- tors of contact by overnight visits for Child One; child’s age is also significant for Child Two, with younger children having more overnight visits. The proportion of variance explained by the two distance vectors is 16% for Child One and 11% for Child Two.

Finally, in Table 8, it can be seen that none of the predictor variables, including distance, makes a significant contribution to explaining variance in the frequency of important conversations. It would seem that if situations arise that require important conversations, contact will occur regardless of distance, characteristics of the child, or characteristics of the elderly parent. This finding should provide additional impetus to examine other potential dete~inants of variation in the qualitative aspects of intergenerational contact.

A finding supportive of our second proposition is that nonlinear patterns emerge in the data for most types of contact. With the exception of contact by letter for Child

154 JOURNAL OF AGING STUDIES Vol. B/No. 2/l 989

TABLE 7

Polynomial Regression of Overnight Visits on Geographic Distance Vectors and Linear Independent Variables

Child One Child Two Stepwise inclusion (N = 795) Stepwise Inclusion (N = 7 67)

Variable I /I 111 I /I III

Constant Child’s income Child’s gender Child’s marital status Child’s age Respondent’s health Respondent’s education Respondent’s ethnicity Respondent’s age Respondent’s gender Distance: linear (XI) Distance: quadratic (X2)

R2 .06 .10 .22 .09

-2.00 -0.46 0.64** 0.42 0.65 0.76

-0.90 -0.67 -0.06 -0.40

0.44 0.36 -0.01 -0.03 -0.01 -0.03 -0.02 0.06

0.62 0.52 1.04**

3.71 0.13 0.67

-0.04 -0.05

0.24 -0.05 -0.01 -0.02

0.56 4.01***

- 1.02***

-3.35 0.65* 0.37

-3.41* -0.16

0.56 0.06

-0.04 0.17 0.81

-1.81 0.46 0.27

-3.23’ -0.17* 0.5 1 0.07

-0.04 0.17 0.66 0.95

-

.10

2.83 0.21 0.92

-2.19 -0.24** 0.39

-0.01 -0.07 0.19 0.16 4.72***

-2.73***

.20

Notes ‘p 5 .05

**p 5 .Ol ***p 5.001

Gender Variables-male = I, female = 2; Marital Status-nonmarried = I, married = 2; Ethnicity-traditional = I, modern = 2.

TABLE 8

Polynomial Regression of Frequency of Conversations on Geographic Distance Vectors and

Linear Independent Variables

Child One Child Two Stepwise inclusion Stepwise inclusion

(N = 195) (N = 167)

Variable I /I I /I

Constant -0.47 -7.30 44.76 36.79 Child’s income -1.51 -0.54 -1.61 -0.67 Child’s gender 0.54 -0.07 0.68 1.19 Child’s marital status -1.78 -2.78 -0.47 -1.44 Child’s age -0.06 -0.16 -0.14 -0.08 Respondent’s health -8.24 -7.88 -3.38 -3.12 Respondent’s education 0.23 0.29 0.48 0.41 Respondent’s ethnicity 0.2 1 0.23 -0.19 -0.16 Respondent’s age 0.52 0.59 -0.35 -0.35 Respondent’s gender 14.39 14.84 10.95 11.77 Distance: linear (XI) -4.62 - -4.89 Distance: quadratic (X2) - NSS - NSS

R2 .05 .06 .04 .05

Notes; Gender Variables-male = 1, female = 2; Marital Status-nonmarried = I, married = 2; Ethnicity-traditional = I, modern = 2; NSS = not statisti-

cally significant.


One, and important conversations for both children, the linear additive model is clearly inappropriate to achieve the best goodness of tit. In Table 4, we see that the addition of a quadratic term to the regression equation results in a significant increment in R2 from 34% to 40% for Child One and from 27% to 35% for Child Two. In Table 5, the addition of a quadratic term explains an additional 3% of the variance in contact by telephone for Child One (from 25% to 28%) and 4% of the variance in contact for Child Two (from 28% to 32%). In Table 6, the proportion of variance explained in writing letters increases with the addition of a quadratic term from 27% to 30% for Child Two. The quadratic term is not significant for Child One. Finally, results from Table 7 show an increment in R2 for overnight visits from 10% to 22% for Child One and from 10% to 20% for Child Two.

A close examination of these tables reveals that despite the addition of nine other predictor variables to the regression equations, nonlinearity persists in the relationship between distance and four of the five types of contact. This implies that the shape of the relationships has not been altered significantly because of the addition of these variables.

If the frequency of types of contact is portrayed graphically, it becomes evident that a substantial amount of substitution occurs between contact types. In Figure One, the frequency of face-to-face and telephone contact is shown across the geographic distance continuum. Although both of these types of contact decline as distance increases, there are differences in the pattern of contact at various locations. The patterns are very similar for Child One and Child Two. This confirms the findings discussed earlier that the results of all the analyses are markedly similar for both children. As distance increases from zero to four hours, face-to-face contact declines sharply while telephone contact declines more gradually. At four hours’ distance, face-to-face contact appears to reach a floor well below the level for telephone contact. After four hours’ distance, telephone contact begins to level off, particularly for Child One. Face-to-face contact also levels off, but only for Child Two. For Child One it shows an increase until nine hours’ distance, after which time no contact occurs. This finding is unexpected and may simply be due to an insufficient number of cases at nine hours’ distance, in effect distorting the true pattern of conduct.

Figure 2 displays patterns of contact by letter and overnight visits. The contact scales on Figures One and Two are different because the frequency of occurrence of the contact types vary considerably. Although the level of contact is much lower compared to contact by face to face and telephone, the patterns do suggest that some substitution does occur at great distances. It appears that some respondents forgo face-to-face and telephone contact in favor of contact types that are either less costly or more convenient.

Taken together, our findings show that geographic distance has a considerable impact on frequency of contact and on choices of type of contact. It has been suggested that some degree of substitution occurs between contact types at various points along the distance continuum. When distances are small, face-to-face contact and telephone contact are more frequent. As distances increase, face-to-face and telephone contact appear to be partially replaced by less frequent overnight visits and letter writing. Future research on the nonlinear relationships across the distance continuum observed here may uncover the exact point at which the substitutions occur, and what qualitative aspects of contact seem to be associated with the choice to substitute one type of

I-

)--

‘\ \ \ \

JOURNAL OF AGING STUDIES Vol. ~/NO. 2/l 989

\ \ \ \

GEOGRAPHIC DISTANCE (HOURS)

FIGURE 1

contact for another. Perhaps the most important observation to be made is that contact still occurs, albeit of different types, regardless of the distance between kin. This finding supports the consensus position on contact stated at the beginning of this article.

The additional findings from the polynomial regression analyses indicate that few of the variables considered make significant contributions to explaining variance in frequency of contact, when the effects of distance are included. Only child’s income appears to have a consistent relationship with contact. However, as with most other control variables, its impact on contact is also reduced when either the linear or quadratic distance vectors are included in the regression equations. As we have already indicated, higher income is likely to be associated with increased geographic mobility,

Geographic Distance and Intergenerational Contact

20

15

10

5

0

- CONTACT BY LETTER

------ CONTACT BY OVERNIGHT VISIT

GEOGRAPHIC DISTANCE (HOURS)

FIGURE 2

so that it may be the distance rather than income per se that is the underlying explana- tory factor. It is clear that further research could be directed at exploring this issue.

Finally, it would seem to be particularly important to investigate both the qualitative aspects of contact, and a range of other social and cultural factors that may also influence frequency of contact. Although we were successful in explaining a substantial proportion of the variance in face-to-face and telephone contact, much remains unex- plained. In addition, the near replication of findings for the two children in the present study is suggestive of a uniform pattern across the two children who live closest to their elderly parents. It would be important to examine these patterns for more children living at various distances from the elderly parents.


SUMMARY

In this article, we have attempted to examine the relationship between geographic distance and intergenerational contact. The analysis has substantially reduced but by no means eliminated some of the major methodological problems present in the literature on kinship interaction. Nevertheless, by taking account of the serious issues discussed earlier in this article, we have been able to specify more precisely than that which has previously been accomplished-the exact nature of the relationship between distance and interaction. Results here have supported a consensus position stating that despite sharp reductions in the levels of some types of contact with increased distance, moderate amounts of intergenerational contact still persist at distant locations. It seems apparent that when some types of contact become too costly or inconvenient to maintain, older parents or their adult children engage in other less-costly types. This strongly suggests the need to abandon the linear model in favor of a nonlinear model to represent the underlying relationship between distance and intergenerational contact.

Geographic Distance (ordinal level scale)

1.

2.

3.

4.

5.

6.

7.

8.

Live together

An adjacent dwelling

Within walking distance

Less than an hour’s drive

Less than a day’s drive

A day’s drive

More than a day’s drive

Outside continental North America

Frequency of Interaction (ordii level scale)

1. Daily (every day, almost)

2. 2-3 times per week

3. Once per week

4. Several times a month

5. Once per month

6. Several times a year

7. Once a year

8. Almost never/Never

APPENDIX A

Constructed Category Intervals (time)

-

(1 to 5 minutes)

(5 to 30 minutes)

(30 to 60 minutes)

(1 to 6 hours)

(6 to 12 hours)

(13 hours +) -

Constructed Category Intervals Wms per year)

(156 to 365)

(104 to 156)

52

(36 to 52)

12

(3 to 6)

0

Derived Midpoint of Intervals (approx.)

3 minutes

17 minutes

45 minutes

4 hours

9 hours

13 hours

Derived Midpoint of Intervals (approx.)

325*

130

52

44

12

5

1

0

*No& This value has been inflated to more adequately reflect contact on a daily basis.

Geographic Distance and Intergenerational Contact

APPENDIX B

Number and Percentage Distribution of Respndent’s Children on Distance and Interaction Scales

159

Geographic Distance (Tie)

1. An adjacent dwelling

2. Within walking distance

3. Less than an hour’s drive

4. Less than a day’s drive

5. A day’s drive

6. More than a day’s drive

7. Missing cases (D.K./N.A.)

Frequency of Interaction (Times per year)



3. Once per week


5. Once per month


7. Once a year

8. Almost never/never

9. Missing Cases (D.K.1N.A.)

Telephone Contact



3. Once per week


5. Once per month


7. Once a year



Child One Number %

6 1.3

50 11.0

174 38.3

75 16.5

7 1.5

9 2.0

133 29.3

Child One Number %

66 14.5

72 15.9

75 16.5

46 10.1

48 10.6

50 11.0

9 2.0

5 1.1

83 18.3

Child One Number %

82 18.1

99 21.8

68 15.0

39 8.6

13 2.9

11 2.4

2 .4

14 3.1

126 27.8

Child Two Number %

2 .4

15 3.3

115 25.3

95 20.9

17 3.7

34 7.5

176 38.8

Child Two Number %

8 1.8

32 7.0

39 8.6

39 8.6

42 9.3

82 18.1

29 6.4

13 2.9

170 37.4

Child Two Number %

25 5.5

67 14.8

60 13.2

42 9.3

45 9.9

28 6.2

2 .4

11 2.4

174 38.3

(continued)


Appendix B (continued)

Letters



3. Once per week


5. Once per month


7. Once a year


9. Missing Cases (D.K./N.A.)

Overnight Visits



3. Once per week


5. Once per month


7. Once a year



Important Conversations



3. Once per week


5. Once per month


7. Once a year


9. Missing Cases (D.K./N.A.)

Child One Child Two Number % Number %

0 0.0 0 0.0

0 0.0 0 0.0

4 .9 7 1.5

6 1.3 12 2.6

8 1.8 14 3.1

14 3.1 29 6.4

5 1.1 3 .7

299 65.9 214 47.1

118 26.0 175 38.5


0 0.0 0 0.0

0 0.0 0 0.0

2 .4 1 .2

1 .2 5 1.1

17 3.7 18 4.0

68 15.0 80 17.6

24 5.3 36 7.9

296 65.2 141 31.1

46 10.1 173 38.1


10 2.2 3 .7

19 4.2 7 1.5

29 6.4 18 4.0

59 13.0 30 6.6

30 6.6 35 7.7

112 24.7 82 18.1

18 4.0 24 5.3

95 20.9 81 17.8

82 18.1 174 38.3


ACKNOWLEDGMENTS The data on which this report is based were taken from a study supported by the Social Science and Humanities Research Council, Grant Number 492-82-0034 (Dr. T.K. Burch). The work in this article is based on an M.A. Thesis by David J. DeWit titled, “The Impact of Demographic Change On Kin Networks of the Elderly.”

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geographic distance and intergenerational contact: an empirical examination of the relationship

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