Maternal Grandmothers do go the Extra Mile : Factoring Distance and Lineage into Differential Contact with Grandchildren

Evolutionary Psychology
www.epjournal.net – 2007. 5(4): 832-843
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Original Article
Maternal Grandmothers do go the Extra Mile: Factoring Distance and Lineage
into Differential Contact with Grandchildren

Thomas V. Pollet, Centre for Behaviour and Evolution, Henry Wellcome Building for Neuroecology,
Newcastle University, Framlington Place, NE2 4HH, Newcastle upon Tyne, United Kingdom. Email:
T.V.Pollet@ncl.ac.uk (Corresponding author).

Daniel Nettle, Centre for Behaviour and Evolution, Henry Wellcome Building for Neuroecology, Newcastle
University, Framlington Place, NE2 4HH, Newcastle upon Tyne, UK.

Mark Nelissen, Behavioural Biology, University of Antwerp, Groenenborgerlaan, Antwerp, Belgium.

Abstract: Several studies conducted from an evolutionary perspective have documented
differential investment in grandchildren by lineage. The majority of these studies have used
retrospective ratings by grandchildren, but only a fraction of these studies have examined
actual grandparental behavior. Here we focus on the interaction between distance and
lineage on face-to-face contact with a (random) grandchild in a large scale sample. Our
main prediction is that maternal grandparents are significantly more willing to travel in
order to see their grandchild. While controlling for initiative of contact, urbanization, sex
and age of the grandchild, educational attainment, marital status and age we found a
significant interaction between distance and grandparent type on frequency of contact with
a grandchild. Maternal grandmothers were significantly more inclined than paternal
grandfathers and grandmothers to maintain frequent face-to-face contact, as distance
between grandparent and grandchild increased. The results are discussed with reference to
evolutionary theories of grandparental investment.

Keywords: grandparental solicitude, paternity uncertainty, family relations, social
interaction, distance, lineage.
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Introduction

Consistent with predictions based on paternity uncertainty, differences in solicitude
between maternal and paternal grandparents have been found in historical (Voland and
Beise, 2002) and modern societies (Euler and Weitzel, 1996; Euler, Hoier, and Rohde,
2001; Michalski and Shackelford, 2005; Pollet, Nettle, and Nelissen, 2006). Typically,

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Factoring lineage and distance into grandparental investment
maternal grandmothers invest most in their grandchildren, followed by maternal
grandfathers, and paternal grandmothers, with paternal grandfathers investing least
(Eisenberg, 1988; Hoffman, 1979-1980, Kahana and Kahana, 1970; Rossi and Rossi,
1990). Even though paternity uncertainty in contemporary societies is assumed to be
relatively low (Anderson, 2006), consistent differences in solicitude have been found
between maternal and paternal grandparents. Such differences have also been documented
for uncles and aunts (Gaulin, McBurney, and Brakeman-Wartell, 1997; McBurney, Simon,
Gaulin, and Geliebter, 2002; Pashos, 2007). In general, individuals thus appear to invest
more in their matriline than in their patriline (but see Pashos, 2000).
Evolutionary studies of grandparental investment in modern societies have mainly
focussed on retrospective ratings by grandchildren, rather than grandparental behavior
(Chrastil, Getz, Euler, and Stark, 2006; Euler and Weitzel, 1996; Euler, et al., 2001;
Laham, Gonsalkorale and von Hippel, 2005; Pashos, 2000; but see Michalski and
Shackelford, 2005). The main argument for using this method has been that grandparents
would give socially desirable answers and would claim to treat all grandchildren equally
(Euler and Weitzel, 1996; Hoffman, 1979-1980). However, research from a family studies
perspective has analysed the grandparent-grandchild dyad from the grandparent’s point of
view, and has found consistent differences in grandparent-grandchild contact frequencies
by lineage (Uhlenberg and Hamill, 1998). Michalski and Shackelford (2005), however,
have argued that contact frequencies are a poor measure for investment, mainly because
they do not take into account who initiates contact. Yet, social network research commonly
uses contact frequency measures and these measures relate to emotional and financial
support, regardless of whom initiates contact (see House, Umberson and Landis, 1988). It
is thus reasonable to examine contact frequency data from a grandparent perspective for
evidence of lineage-based differences, as we did in a previous paper (Pollet et al., 2006).
Here we extend our analysis and test for a lineage x distance interaction effect on
contact frequency as a measure of grandparental investment by using a large dataset. We
use a multivariate design that allows us to control for initiative of contact and a large
number of other factors affecting the grandparent-grandchild tie. Following paternity
uncertainty, the main prediction is that, when other factors are controlled for, there will be
consistent differences in how much individuals are willing to travel in order to see their
grandchild as a function of lineage. Namely, maternal grandmothers/grandfathers, rather
than paternal grandmothers/grandfathers, will be more inclined to have very frequent
contact with their grandchild, even when that grandchild lives far away. So we predict a
grandparent type x distance interaction effect on contact frequency with a grandchild. Such
an interaction is evidence for stronger investment by matrilineal grandparents than
patrilineal grandparents. This would indicate differential investment as travel is evidently
costly in terms of time and money.
However, paternity uncertainty does not necessarily lead to predict that maternal
grandfathers will invest more than paternal grandmothers, as is commonly found. This
finding has been attributed to co-residence of grandparents (see Gaulin et al., 1997;
McBurney et al., 2002 but see Euler and Weitzel, 1996) or sex-specific investment in
matrilines (Euler and Weitzel, 1996; Euler and Michalski, 2007). Laham and colleagues
(2005) explained higher investment by maternal grandfathers than paternal grandmothers in
terms of the availability of more certain “outlets”. If alternative investment options (e.g.
cousins via a sister) are available to paternal grandmothers, they should invest less in
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Factoring lineage and distance into grandparental investment
grandchildren than maternal grandfathers do. Differences between maternal grandmothers
and paternal grandparents and between maternal grandfathers and paternal grandfathers in
investment would thus suggest that psychological mechanisms attuned to paternity
uncertainty are operating. Differences between maternal grandfathers and paternal
grandmothers, on the other hand, can be explained by co-residence of grandparents, sex-
specific investment strategies or available investment outlets.

Materials and Methods

Sample and assessment procedures
The Netherlands Kinship Panel Study (NKPS) dataset was obtained through the
Netherlands Interdisciplinary Demographic Institute (NIDI). The NKPS is a large scale
study (n= 8,161), designed to investigate family and kin relations in the Netherlands
(Dykstra et al., 2004). The main study aimed to reach 8,500 non-institutionalized
individuals between 18 and 79 years old (Dykstra et al., 2004: 23-ff.). These individuals
were randomly drawn from a large Dutch address register. The study yielded a final sample
with data for 8,161 persons (M age= 46.43; SD = 15.13; Dykstra et al., 2004). The sample
was unbalanced in terms of gender, with more female than male respondents (nmen= 3,420;
nwomen= 4,741).
Individuals were interviewed face-to-face by trained researchers between October
2002 and October 2004 about various aspects of their family life (Dykstra et al., 2004). The
average interview lasted 74 minutes during which data was collected for a wide variety of
family-related variables, e.g. relationships with and characteristics of family members
(mainly for fathers, mothers, siblings, husband/spouse, children, grandparents,
grandchildren, but also for close friends). Respondents also provided detailed information
on a wide range of socio-demographic variables (e.g., educational attainment, marital
status, employment history). The sampling procedure, representativeness, the survey
method and other aspects of the study are described in much more detail by Dykstra and
colleagues (2004).
From this dataset we selected all individuals who had a grandchild between zero
and fifteen years old at the time of the interview (M = 6.45 years; SD = 4.23 years).
Limiting the analyses to grandchildren between zero and fifteen years old, allows for
controlling of initiation of contact on their behalf, rather than by the grandparent (see
Michalski and Shackelford, 2005). It is reasonable to assume that contact frequency
represents initiative and investment on behalf of the grandparent rather than the grandchild,
for young grandchildren. There is no data available on the genetic relatedness between the
parent and grandchild but only on genetic relatedness between grandparent and parent. Five
cases where the grandparent was never married were excluded from analysis, as this
category is problematic for obtaining estimates in the multinomial logistic regression. Only
cases where the grandchild was living with the child of the respondent were used and
“missings” on variables were treated list wise for the multinomial logistic regression (Final
sample: n = 831). The variables used are described in Dykstra and colleagues (2004), with
the exception of constructed or recoded variables (age of grandchild, education,
geographical distance, marital status grandparent). Initiative of contact, whether it was by
the grandparent or by the parent of the grandchild, was surveyed as: When you’re in touch
with {name, description}, do you usually get in touch at your initiative, at the other’s
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Factoring lineage and distance into grandparental investment
initiative, or is it more or less equal? (Dykstra et al., 2004). The dependent variable,
frequency of contact, was surveyed as: How often have you seen {name, description} over
the past 12 months. This variable was recoded from seven to five categories, by merging
the first two in order to avoid categories with too few cases (Table 1). The variables used,
their associated predictions and descriptives are summarized in table 1. Multinomial
logistic regression (MLR) was used to investigate the independent effects of the variables
from Table 1 on contact frequency (Hosmer and Lemeshow, 1989; Menard, 1995; Pampel,
2000). Multinomial logistic regression as statistical technique is relatively free of
assumptions and statistically robust. It allows the examination of relationships between
independent variables and a dependent variable that consists of multiple categories. Unlike
ordinary least square regression, parameters are estimated by maximum likelihood. Here
we will report the likelihood ratio tests for variables (pllr) in the model and the parameter
estimates for the model (see Peng, Lee, and Ingersoll, 2002). As we use many independent
variables, we will not discuss all effects in detail (see Pollet et al., 2006). Our main focus is
the interaction between grandparental type and distance on frequency of face-to-face
contact.
We also performed an additional event history analysis by Cox regression which
allows examining the likelihood of an event as time, or in this case, distance progresses
(Allison, 1984; Cox, 1972). We will present the final model using the same independent
variables as for the multinomial logistic regression, but will use the log (distance)
transformation for the graphical display. As event we selected maintaining frequent contact
(a few times a week or daily) with a grandchild, with increasing distance.

Results

The descriptive statistics and predictions are summarized in Table 1. There were no
significant differences between grandparents in distance to their grandchild (ANOVA: F(1,
827) = 1.03; p = 0.38; all contrasts p > .17).
Using multinomial logistic regression, we found the predicted interaction effect
between grandparent type and distance on frequency of face-to-face contact (Likelihood
Ratio test; ?² = 42.1; p = .0003; Table 2). The final model had a Nagelkerke R² of 0.621
(model fit -2LL = 1816.97; ?² = 746.85; df = 70; p < .0001). The overall model thus
performed very well. Urbanisation, marital status of the child, educational attainment,
relatedness to the child, sex of the grandchild did not predict face-to-face contact between
grandparent and grandchild (all likelihood ratio tests; p > .05). The effects for the variables
were in the predicted direction of Table 1, however (Table 2, see Pollet et al., 2006).The
effect of relatedness between grandparent and parent, while not significant, was in line with
the predicted direction, with respondents having a tendency to have more contact with a
related grandchild than an unrelated grandchild (?² = 9.35; df = 5; pllr = .096). As distance
increased, grandparents had significantly less contact with their grandchild (Table 2).
Grandparent type also influenced contact frequency (see Pollet et al., 2006). However, the
presence of a significant interaction effect indicates that the effect of grandparent type is
contingent upon how far the grandparent lives away from the grandchild (Table 2).
Therefore, we focus on the odds ratios for this interaction effect.


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Factoring lineage and distance into grandparental investment
Table 1: Descriptive statistics and concomitant predictions (prediction number in brackets)

Variables
Categories
Frequencies/means
Prediction
References
Education
Incomplete, primary or lower vocational
n = 335
More contact if higher educated
Barranti (1985)
Baydar and Brooks-Gunn
(3 cat.)
Secondary or higher vocational
n = 468
(1)
(1998)

University or postgraduate
n = 28


Baydar and Brooks-Gunn
Marital status
Widowed
n = 169
Divorced and widowed
(1998)
grandparent Divorced
n = 101
grandparents will have less
Denham and Smith (1989)
(3 cat.)
Married
n= 562
contact than married
King (2003)



grandparents. (2)
Reitzes and Mutran (2004)
Marital status
Married
n = 682
More contact if divorced or
Denham and Smith (1989)
parent
Cohabiting (but not married)
n = 115
widowed.
Johnson (1988)
(5 cat.)
Widowed (no resident partner)
n = 2
(although contingent upon sex)


Divorced (no resident partner)
n = 20
(3)


Never married (no resident partner)
n = 12


Urbanization
Very strongly urbanised (> = 2500 addr/km²)
n = 91
More contact in less urbanized
King and Elder (1995)
(respondent)
Strongly urbanised (1500-2500 addr/km²)
n = 239
regions
King et al. (2003)
(5 cat.)
Moderately urbanised (1000-1500 addr/km²)
n = 172
(4)


Hardly urbanised (500-1000 addr/km²)
n = 199



Not urbanized (< 500 addr/km²)
n = 130


See Michalski and
Initiative of
Initiative grandparent
n = 663
(control variable)
Shackelford (2005)
contact
Balanced
n = 71
(5)

(3 cat.)
Initiative parent
n = 288


Grandparent type
Maternal grandmother (MGM)
n = 288
Contact will be larger for MGM
Euler and Weitzel (1996)
(4 cat.)
Maternal grandfather (MGF)
n = 197
followed by MGF, PGM and
Michalski and Shackelford

Paternal grandmother (PGM)
n = 215
PGF, with PGF having the least
(2005)

Paternal grandfather (PGF)
n = 131
contact. (6)
Chrastil et al (2006)
Relatedness
Not fully related (adopted or partner’s)
n = 14
More contact if fully related
Sanders and Trygstad (1989)
with parent
Fully related
n = 817
(7)

Geographical
(interval) ; see Dykstra et al., 2004 for
27.04 km (SD= 41.99)
Less contact if increase
Lawton et al. (1994)
distance
additional information

in distance (8)
Uhlenberg and Hamill (1998)
Baydar and Brooks-Gunn
Number of ever
(interval)
2.68 children
Less contact if more children
(1998)
born children
(includes adopted children)
(SD = 1.15)
(9)
Uhlenberg and Hamill (1998)
Gender
Male
n = 411
(Slightly) more contact with
Euler, Hoier and Rohde (2001)
granddaughters than grandsons
grandchild Female
n = 420
(10)

Age grandchild
(interval)
6.45 years (SD = 4.23) More contact if younger (11)
Kivett, (1985).
63.21 years (SD =
Baydar and Brooks-Gunn
Age grandparent
(interval)
7.59)
Less contact if older (12)
(1998)
Contact over past
Not at all or once
n =13 (dependent)

12 months
A few times
n =96


At least once a month
n =242


At least once a week
n =229


A few times a week
n =192

Daily
n =52


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Factoring lineage and distance into grandparental investment
By examining odds ratios, we found that if a respondent was a maternal
grandmother, instead of a paternal grandmother the odds (of having contact a few times a
week versus not at all or once) became 1.22 times larger for each kilometre she lives
further away. By substituting reference categories we are able to calculate estimates for
each comparison (Table 3).

Table 2: Likelihood ratio tests from multinomial logistic regression; Variables are tested against the null
prediction that they do not influence contact frequency. *= there are no associated tests with these as the
degrees of freedom are fixed.


Model
Fitting
Likelihood Ratio Tests
Variable
Criteria

-2 LL
?²
df
P
Intercept
1816.97*
-
-
-
Initiative of contact
1844.18
27.21
10
.002
Marital status grandparent
1869.27
52.30
10
< .0001
Distance
1816.97*
-
-
-
Age grandchild
1859.22
42.25
5
< .0001
Age grandparent
1836.06
19.09
5
.002
Number of ever born children
1840.30
23.32
5
.0002
Grandparental type
1840.16
23.19
15
.080
Grandparental type * distance
1857.90
40.93
15
.0003

There are consistent differences between maternal grandmothers and paternal
grandmothers in how distance affects contact frequency (Table 3). Comparisons with
paternal grandfathers were not definitively positive but the trend was positive. This is due
to the lack of paternal grandfathers who had contact on a daily basis with their grandchild
(n = 4). However, the findings appear largely limited to comparisons between having
contact daily or a few times a week versus other categories.
Subsequent analysis by use of Cox Regression, did however show consistent
differences between paternal grandfathers and other categories in the likelihood of still
having contact daily or a few times a week as distance increased (Wald tests; p < .05;
Figure 1).
Grandparent type was a significant predictor in the Cox regression. Figure 1 clearly
shows that maternal grandparents continue to have frequent contact with their
grandchildren as distance increases. It shows a clear and significant separation between
maternal grandparents and paternal grandparents.








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Factoring lineage and distance into grandparental investment
Table 3: Odds ratios for comparisons (grandparent x distance). * = p < .05; ? = pos. estimate with .05 < p <
.1 (these estimates are not presented as they are extremely large). For example: 1.89 (top right corner) means
that if a respondent was a maternal grandmother, instead of a maternal grandfather the odds (of having
contact daily versus not at all or once) become 1.89 times larger for each kilometre the respondent lives
further away.

Interaction

a few
at least
at least
a few times daily
with distance
times
once a month
once a week a week

once or
MGM vs MGF
n.s.
n.s.
n.s.
n.s.
1.89*
not at all
MGM vs PGM
n.s.
n.s.
n.s.
1.22*
n.s.

PGM vs PGF
n.s.
n.s.
n.s.
n.s.
?

MGF vs PGM
n.s.
n.s.
n.s.
n.s. n.s.

MGM vs PGF
n.s.
n.s.
n.s.
n.s.
?

MGF vs PGF
n.s.
n.s.
n.s.
n.s.
?
a few times
MGM vs MGF
-
n.s. n.s.
n.s.
1.39*

MGM vs PGM
-
n.s. n.s.
1.25*
n.s.

PGM vs PGF
-
n.s.
n.s.
n.s.
?

MGF vs PGM
-
n.s.
n.s.
n.s.
n.s.

MGM vs PGF
-
n.s.
n.s.
n.s.
?

MGF vs PGF
-
n.s.
n.s.
n.s.
?
at least
MGM vs MGF
- -
n.s. n.s.
1.94*
once a
MGM vs PGM
- -
1.04* 1.25*
n.s.
month
PGF vs PGM
- -
n.s. n.s.
n.s.

MGF vs PGM
- -
0.962*
n.s.
n.s.

MGM vs PGF
- -
n.s.
n.s.
?

MGF vs PGF
- -
n.s. n.s.
?
at least
MGM vs MGF
- -
-
n.s. n.s.
once a
MGM vs PGM
- -
-
1.2*
n.s.
week
PGM vs PGF
- -
-
n.s.
n.s.

MGF vs PGM
- -
-
n.s.
n.s.

MGM vs PGF
- -
-
n.s.
n.s.

MGF vs PGF
- -
-
n.s.
n.s.
a few
MGM vs MGF
- -
-
- n.s.
times
MGM vs PGM
- -
-
- n.s.
a week
PGM vs PGF
- -
-
- n.s.

MGF vs PGM
- -
-
- n.s.

MGM vs PGF
- -
-
- n.s.

MGF vs PGF
- -
-
- n.s.












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Factoring lineage and distance into grandparental investment





Figure 1: Cumulative likelihood of still having contact a few times a week or daily with a grandchild by
log(distance). * = p< .05; **p < .01; ***p < .001 indicating significant differences in likelihood (Wald tests).



Beside grandparent type, type of child, number of ever born children, urbanisation,
educational attainment, marital status and age of the respondent were predictors of still
having contact a few times a week or daily, as distance increases (Wald tests; p < .05).
These effects were in the predicted direction as described in Table 1. Age and sex of the
grandchild as well as initiative of contact and marital status of the child, were not
significant predictors of frequent contact as a function of distance (Wald tests; p > .25). The
effect of type of child was reverse to the prediction. As distance increased the respondent
was more likely to have contact with children that were not related (adopted or of the
partner) to him or her. The effect is due however to a few outlying cases (Unrelated child
but contact of a few times a week or daily: n = 4). In addition, the loss of ?² is not
significant if this variable is dropped from the model (p = .076).
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Factoring lineage and distance into grandparental investment
Discussion
Grandparent categories did not differ in how far they lived from a grandchild. This
difference might be because of the high degree of urbanization in and the size of the
Netherlands, compared to the USA, for example. There was a significant interaction effect
between distance and grandparent type on face-to-face contact with a grandchild. This
indicates that maternal grandparents, especially maternal grandmothers, are more inclined
to maintain frequent contact with their grandchild as distance increases. The parameter
estimates showed that the effects were however limited to comparisons of a few times a
week or daily, compared to a different category. Further analysis by Cox regression showed
that as distance between grandparent and grandchild increased, maternal grandparents were
significantly more likely than paternal grandparents to maintain frequent contact with their
grandchild. As in our previous paper (Pollet et al., 2006), we find support for the majority
of predictions listed in Table 1, both in the logistic and Cox regression analysis (MLR:
support for predictions: 2,5,6,8,9,11,12; Cox regression: support for predictions:
1,2,4,5,9,11). Relatedness proved marginally significant in the logistic regression, with
unrelated individuals having less contact than related individuals. In the Cox regression, by
contrast, relatedness influenced contact frequency in the opposite direction. The lack of any
conclusive findings or opposite findings for relatedness can be attributed to the very small
number of cases where the grandparent was unrelated to the child.
In line with other studies (e.g., Euler and Weitzel, 1996; Michalski and Shackelford,
2005) we thus find consistent differences between matrilines and patrilines in investment.
Yet, the differences between paternal grandmothers and paternal grandfathers and between
maternal grandmothers and maternal grandfathers were not significant and appear
inconsistent with the paternity uncertainty hypothesis. However, the lack of differences can
be explained by co-residence and marriage of grandparents. When a grandchild visits his or
her grandparent, he or she usually meets the partner of the married grandparent as well
(Gaulin et al., 1997; McBurney et al., 2002, but see Euler and Weitzel, 1996). There was no
conclusive evidence for more contact with maternal grandfathers than with paternal
grandmothers. Our data do not support or allow distinguishing between explanations based
on alternative outlets (Laham et al., 2005), sex-specific investment (Euler and Weitzel,
1996; Euler and Michalski, in press) or co-residence. Unlike Michalski and Shackelford
(2005), we found consistent differences not only between maternal grandmothers and
paternal grandfathers, but also between maternal grandmothers and paternal grandmothers,
and between maternal grandfathers and paternal grandfathers in investment, measured here
as maintaining frequent contact with increasing distance.
In conclusion, we show consistent differences between matrilines and patrilines in
how distance affects face-to-face contact with a grandchild. These findings appear robust
and in line with the paternity uncertainty hypothesis. The findings cannot be attributed to a
wide variety of factors listed in Table 1. If the necessary conditions are met, namely
measures against social desirability and adequate control variables, the study of contact
frequencies between grandparents and grandchild allows testing evolutionary hypotheses,
such as the paternity certainty hypothesis. In the future we hope to address whether or not
these differentials in contact frequency according to lineage are maintained over the life
span. The Netherlands Kinship Panel Study is a longitudinal study and the future waves
should allow addressing this question. Further research can also investigate whether and
Evolutionary Psychology – ISSN 1474-7049 – Volume 5(4). 2007. -840-

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Factoring lineage and distance into grandparental investment
how these differences between grandparents in contact frequency benefit grandchildren. In
addition, further research is necessary to show how contact frequencies relate to measures
of financial investment.

Acknowledgements: We wish to thank Harald Euler and Alexander Pashos for helpful
comments. We are also very grateful to the Netherlands Interdisciplinary Demographic
Institute (NIDI) for access to the NKPS data.

The Netherlands Kinship Panel Study is funded by grant 480-10-009 from the Major Investments
Fund of the Netherlands Organization for Scientific Research (NWO), and by the Netherlands
Interdisciplinary Demographic Institute (NIDI), Utrecht University, the University of Amsterdam
and Tilburg University.

Received 18 September 2007; Revision submitted 26 November 2007; Accepted 27
November 2007

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