Contact frequencies with nieces and nephews in Finland

Abstract

Based on maternity certainty and paternity uncertainty, one can predict that individuals will channel investment in their kin according to more genetically certain investment options. According to the preferential investment in more certain kin theory, if aunts and uncles have the option to invest in either their sisters’ or their brothers’ children they would prefer to invest in their sisters’ children. However, this question has not been previously explored in contemporary societies with nationally representative data from two generations of aunts and uncles. In our study, we have used data gathered in the Generational Transmissions in Finland project in 2012. The respondents represent older adults (born between 1945 and 1950, n = 1,604) and younger adults (born between 1962 and 1993, n = 1,159). We find that when aunts and uncles have nieces and nephews via both sisters and brothers, they have more contacts with their sisters’ children than their brothers’ children. Thus, the results are in accordance with the preferential investment theory.

Keywords

Aunts/uncles contact frequencies Finland lineage nieces/nephews paternity uncertainty

In humans, as well other species with long childhood dependency, individuals other than the biological mother of the child may influence that child’s well-being remarkably (Sear & Coall, 2011; Sear & Mace, 2008). These “allomothers” are usually genetically related to the children, and thus, they may increase their own inclusive fitness by investing in such offspring (Hamilton, 1964). In humans, the allomothers include, for instance, father, aunts, uncles, cousins, and grandparents who are often involved in investing in the offspring’s well-being (Hrdy, 1999, 2009). In this study, we have analyzed aunts’ and uncles’ contact frequencies with their nieces and nephews in contemporary Finland.

In humans, as in several other species, paternity uncertainty may influence the amount of investment channeled toward offspring (Platek & Shackelford, 2006). Paternity uncertainty means that human fathers can never be totally sure that their child is genetically related to them. In contrast, mothers, who by the fact that they give birth to their baby, are sure of their genetic relatedness to the child. Evolutionary researchers argue that paternity uncertainty is an adaptive problem for human males and thus there could be psychological adaptations that regulate the investment in offspring according to paternity uncertainty. In line with this prediction, studies have shown that men tend to invest more resources in children with facial and odor resemblance, that is, men invest more in children with whom they are more likely genetically related (Alvergne, Faurie, & Raymond, 2009; Anderson, Kaplan, & Lancaster, 1999; Burch & Gallup, 2000; Daly & Wilson, 1982). However, in humans paternity uncertainty influences not only the fathers’ (or putative fathers’) behavior but also the behavior of extended kin.

Until now, research into asymmetric investment patterns of extended kin has been dominated by studies on grandparental investment (see Euler, 2011, for review). These studies have shown that, in accordance with the prediction based on paternity uncertainty, maternal grandmothers (who by definition have no uncertain link of paternity with their grandchild) tend to invest the most, and paternal grandfathers (who have two uncertain links with the grandchild) the least, while the investments of both maternal grandfathers and paternal grandmothers (who have one uncertain link of paternity) lie somewhere between (see Coall & Hertwig, 2010; Euler, 2011, for reviews). Individuals’ investments in cousins are also found to vary according to the prediction made by paternity uncertainty (Jeon & Buss, 2007). Based on paternity uncertainty, maternal aunts and uncles are more likely to invest more in their nieces and nephews than paternal aunts and uncles (Michalski & Euler, 2008).

A study of 285 college students from Pittsburgh found that maternal aunts and uncles invested more in their nieces and nephews than paternal aunts and uncles (Gaulin, McBurney, & Brakeman-Wartell, 1997). Similar results were also found in a study of 398 university students from Germany (Hoier, Euler, & Hänze, 2001). Later, McBurney, Simon, Gaulin, and Geliebter (2002) gathered data from Orthodox Jewish college students, assuming that there is a very low rate of paternity uncertainty in this population. However, when they compared the study of Orthodox Jews with the Pittsburgh study, they found a similar biased investment pattern of aunts and uncles in both samples. Thus, McBurney and colleagues (2002) concluded that the biased investment pattern of aunts and uncles may reflect the paternity uncertainty in our evolutionary past rather than in current societies.

The main limitations of previous studies of the asymmetric investment pattern of aunts and uncles are that they have used small, nonrepresentative samples. In addition, the data from the previous studies are gathered from the receivers’ (i.e., nieces and nephews) rather than from the investors’ (i.e., aunts and uncles) point of view (but see Pashos & McBurney, 2008). When the respondents are aunts and uncles themselves, the information of their background variables is more accurate. In the present study, we have used large-scale, nationally representative data from two generations, where the respondents are aunts and uncles. We examined whether individuals who have offspring via a sister or a brother invest more in their sister’s than their brother’s children (e.g., controlling for sibling closeness), as assumed by the paternity uncertainty prediction.

Studies of the investment behavior of extended kin have shown that alternative investment options may influence individuals’ support toward their relatives. In their study of biased grandparental investment, Laham, Gonsalkorale, and Von Hippel (2005) formulated “the preferential investment in more certain kin” theory. This theory predicts that kin investment depends on individuals’ investment outlets. According to the preferential investment theory, individuals invest more resources in those kin members who are more likely to be genetically related to them and at the expense of those who are less likely to be related kin. For instance, in the case of grandparents, grandmothers and grandfathers often have a double role since they may have grandchildren via both daughters and sons (i.e., they are at the same time maternal and paternal grandparents). Preferential investment theory predicts that, in these cases, grandmothers and grandfathers should prefer their daughters’ children over their sons’ children, because there is an uncertain link of paternity between a son and his children, but no uncertain link with a daughter’s children. To our knowledge, no study has yet explored this prediction in the case of aunts and uncles. However, three studies have tested whether grandparental investment differs according to alternative investment options.

First, a study using a sample of 787 psychology students from Australia found that closeness toward maternal grandfathers and paternal grandmothers, who both have one uncertain link of paternity (maternal grandfather via himself and his daughter and paternal grandmother via her son and his child), was dependent on the presence of more certain investment options (Laham, Gonsalkorale, & Von Hippel, 2005). In addition, when both grandfather types were alive, Australian respondents felt closer toward their maternal than paternal grandfather. The second study used data from 193 U.S. college students who still had all four grandparents alive (Bishop, Meyer, Schmidt, & Gray, 2009). This study analyzed several grandparental investment variables (e.g., contact frequencies, financial transfers, and emotional closeness) and found that maternal grandparents invest more in their grandchildren than do paternal grandparents. However, the study did not find support for the preferential investment theory. The third study analyzed large-scale and nationally representative data from 13 European countries (Danielsbacka, Tanskanen, Jokela, & Rotkirch, 2011). The study found that grandmothers and grandfathers who had an option to invest either in their daughters’ or in their sons’ children were more likely to look after their daughters’ children. These results supported the preferential investment theory.

Aunts and uncles differ from grandparents, since in modern Western societies, aunts and uncles do not usually live in same household with each other, as opposed to grandmothers and grandfathers (OECD, 2012). In the case of grandparents, grandmothers may influence the investment of grandfathers and vice versa, while aunts’ and uncles’ investment toward their nieces and nephews is more independent of each other (Euler, 2011). This makes aunts and uncles a relevant group when studying the effect of the paternity uncertainty.

Based on paternity uncertainty, maternal aunts and uncles are more likely to invest more in their nieces and nephews compared to paternal aunts and uncles. In the case of aunts and uncles, compared to grandparents, paternity uncertainty does not predict sex differences since the relationship between siblings is horizontal. There is similar certainty between sister and sister and sister and brother. However, previous studies have shown that, in addition to lineage, the sex of the investors affects the investment in nieces and nephews, that is, aunts invest more than uncles (e.g., Gaulin et al., 1997; McBurney, Simon, Gaulin, & Geliebter, 2002; Pashos & McBurney, 2008). Previous studies have found that maternal aunts tend to invest more than maternal uncles (and paternal aunts more than paternal uncles), although they have the same genetic certainty in relation to their nieces and nephews (Pashos & McBurney, 2008). This could also be explained by cultural and psychological predispositions that lead women act as kin keepers, that is, the ones who provide care and support to kin (e.g., Bracke, Christiaens, & Wauterickx, 2008; Dubas, 2001).

In addition to sex and lineage, several other factors may influence the investment behavior of aunts and uncles. From the evolutionary point of view, the age of aunts and uncles is of interest since investment behavior is related to one’s own reproductive view. Nonreproductive aunts, in particular, may have fitness benefits by investing resources in their nieces and nephews (Lahdenperä, Gillespie, Lummaa, & Russell, 2012). However, if aunts and uncles are themselves at fertility age, they may invest in having their own children rather than in their extended kin (Hughes, 1988). In addition to the age of aunts and uncles, the age of their siblings may also be a factor. If their siblings are at fertility age, aunts and uncles may increase their own inclusive fitness by investing in their siblings and their children (Euler, 2011). The age of nieces and nephews may also play a role since younger offspring are more likely to need support than older ones (Euler & Michalski, 2008).

When considering individuals’ investment in nieces and nephews, one important factor is whether they have their own children. Previous studies have shown that childless women invest more in nieces and nephews than do those who are mothers themselves (Pollet, 2007; Tanskanen, 2015; see also Pollet & Dunbar, 2008). In addition, the marital status of aunts and uncles may be a factor since, especially among younger adults, having a spouse increases the probability of having their own children in the future (Tanskanen, Jokela, Danielsbacka, & Rotkirch, 2014). Again, from the inclusive fitness perspective, it could be more beneficial to invest resources in one’s own childbearing (either current or future) rather than in nieces and nephews. Especially in the case of older adults, a lack of spouse may decrease men’s investment in kin, but would not affect investment by single women, maybe as a result of women’s role as kin keepers. Previous studies have indeed found that the negative effect of divorce on family relations is usually stronger for men than for women (e.g., Danielsbacka & Tanskanen, 2012; Tomassini et al., 2004; Uhlenberg & Hammil, 1998).

The quality of relationships between aunts and uncles and their siblings may shape their relationships to their nieces and nephews. Those individuals who are closer emotionally to their siblings are also more likely to be closer emotionally to their nieces and nephews (Euler, 2011). The number of siblings, as well the number of nieces and nephews, may also be a factor since the more kin there are, the less time to invest in each of them (Michalski & Euler, 2008). Respondents’ financial condition may be a factor since the more the resources one have, the more one may be able to invest in kin. Finally, educational level may have an influence since those individuals with a higher level of education are found to have more contacts with kin than those with a lower level of education (e.g., Pollet, 2007; Tanskanen & Danielsbacka, 2014).

Hypotheses

In the present study, we examined whether alternative investment options influenced the investment behavior of aunts and uncles. Based on paternity uncertainty and the sex of the investor, we predicted the following hypothesis:

Hypothesis 1 (H1): Maternal aunts would have more contacts with nieces and nephews than maternal uncles or paternal aunts and uncles.

In addition, based on the preferential investment theory, we predicted the following hypothesis:

Hypothesis 2 (H2): If aunts and uncles had an option to invest either in their sisters' children or in their brothers' children, they would have more contacts with their sisters' children than their brothers' children.

Data and method

In this article, we have used data from the Generational Transmissions in Finland (Gentrans) project (see Gentrans, 2015). The aim of Gentrans is to gather longitudinal information on two generations: the Finnish baby boomer generation born between 1945 and 1950 (M = 1947, SD = 1.67; i.e., the older generation) and their adult children born between 1964 and 1993 (M = 1976, SD = 5.6; i.e., the younger generation). The first wave of Gentrans surveys was gathered in 2007. This article uses the second wave of nationally representative surveys, which were collected separately from the older and younger generations, older generation being the pivot generation, in 2012 by Statistics Finland via mail. Only one person per household participated in the study. During the 2012 data collection, the older generation’s respondents were approximately 65 years old (between 62 and 67) and the younger generation’s respondents approximately 36 years old (between 19 and 50). The older generation’s survey included 2,278 respondents (response rate = 65%) and the younger generation’s survey included 1,753 respondents (response rate = 50%; Danielsbacka et al., 2013; see also Tanskanen & Danielsbacka, 2014; Tanskanen, Danielsbacka, & Rotkirch, 2014, who have used the same data.)

According to a nonresponse analysis based on the whole sample (N = 3,492) of the older generation’s data, the data were fairly representative, although some groups answered more actively than others. Women had a higher response activity (71%) than did men (59%). The age distribution of respondents corresponded well to that of the whole sample which was expected because of the small age distribution in the sample (it included only birth cohorts born between 1945 and 1950). Childless respondents answered less actively (61%) than those who had children. Response activity among the divorced were lower (58%) compared to married respondents (69%). The difference between respondents and nonrespondents was sharpest with respect to educational background. Those with the second highest educational level responded more actively (83%) than did those with only a basic level of education (54%) with a linear effect (except the highest educational level of 77% response activity). Also socioeconomic background mattered so that those with a higher socioeconomic position (upper clerical worker: 72% and lower clerical worker: 75%) were more active respondents than were entrepreneurs (57%) or workers (60%).

According to a nonresponse analysis based on the younger generation’s data (N = 3,495), the data were fairly representative, although some groups answered more actively than others. Women had a higher response activity (59%) than did men (40%), as was the case in the older generation data. The age distribution of respondents corresponded well to that of the whole sample, with the exception of the youngest age-group (under 25-years-old) who had a very low response rate (36%). Response rates among respondents with children and childless respondents were fairly similar. Response rates among the divorced were lower (43%) compared to married respondents (54%), as was the case in the older generation data. The difference between respondents and nonrespondents was sharpest with respect to educational background. Those with the highest educational level responded more actively (74%) than did those with only a basic level of education (30%) with a linear effect. Also socioeconomic background mattered so that students (55%) and those with a higher socioeconomic position (upper clerical worker: 63% and lower clerical worker: 54%) were more active respondents than were entrepreneurs (39%), workers (39%), or the unemployed (37%).

In this study, we included only those participants who had at least one niece or nephew via biological sibling. In addition, we included only those cases where all the siblings’ children were his or her biological children. These selections resulted in a total of 1,159 respondents from the younger and 1,604 respondents from the older generation. In addition, for the test of the preferential investment hypothesis (H2), we have included only those respondents who have niece(s)/nephew(s) via both sister(s) and brother(s) (younger generation: n = 508 and older generation: n = 1,172).

The dependent variable measures respondents’ contact frequencies with nieces and nephews. Even though contact frequency does not measure investment in kin precisely, previous studies have shown that contact frequencies may measure overall kin investment fairly reliably, hence contacts tend to correlate with other forms of investment (see Pollet, 2005; Pollet, Nelissen, & Nettle, 2009). In the Gentrans survey, respondents were asked in a single question to report via a 5-point scale (ranging from 0 = never to 4 = several times a week) how often they had contact with their nieces and nephews in the last 12 months either face-to-face, by phone, or via the Internet. Contact frequencies were gathered separately for niece and nephew sets of four of the respondents’ oldest siblings. In the questionnaires, respondents were advised that when answering the question concerning contact frequencies with nieces and nephews, they should think about the specific sibling’s child (i.e., niece/nephew of the respondent) they have been in contact with the most. The contact frequency variables are normally distributed.

In addition, the younger generation’s respondents were asked to report how often they looked after their nieces and nephews during the last 12 months via a 6-point scale (ranging from 0 = never to 5 = over 50 times). Based on these reports, we were able to produce sensitivity analyses for younger generation. Since during the Gentrans data collection, older generation’s nieces and nephews were mostly adults (approximately aged 34 years old), older generation’s data did not include questions concerning childcare of nieces and nephews, and thus we were unable to run similar sensitivity analyses for the older generation.

For analysis purposes, the data were reshaped into a long format form, meaning that the present data sets were constructed so that observations were viewed from the perspective of the original respondent’s siblings who have children (on average 2.4 siblings with children in older and 1.2 siblings with children in younger generation’s data). The data include 3,884 observations in the older generation’s sample and 1,441 observations in the younger generation’s sample.

To test H1 and H2, we used linear regression analysis and adjusted the following variables: respondent’s birth year, marital status, number of children, educational level, financial condition, siblings’ birth year, emotional closeness between respondent and sibling, number of siblings, number of siblings’ children, and year of birth of youngest niece or nephew. In the case of H2, we also controlled for the respondents’ sex. With the exception of the respondent’s birth year, number of children, number of siblings, number of siblings’ children, and the year of birth of the youngest niece or nephew, all independent variables were categorical. For the analyses, we have transformed them into a dummy variable (see Table 1 for descriptive statistics).

Table 1.

Descriptive statistics (n and mean/%).

	Younger generation		Older generation
	n	Mean/%	n	Mean/%
Aunt/uncle type (%)
Maternal aunt	513	35.6	1,229	31.6
Maternal uncle	285	19.8	813	20.9
Paternal aunt	399	27.7	1,059	27.3
Paternal uncle	244	16.9	783	20.2
Birth year (mean)	1,159	1975	1,604	1947
Marital status (%)
Unmarried	194	16.8	95	5.9
Cohabitation	282	24.4	146	9.1
Married	627	54.2	1,092	68.3
Other	54	4.7	265	16.6
Number of biological children (mean)	1,159	2.6	1,604	3.7
Education (%)
Primary or lower secondary level	41	3.6	496	31.6
Upper secondary level	518	44.9	810	51.5
Lower degree level tertiary education	308	26.7	105	6.7
Higher degree level tertiary education or doctorate education	286	24.8	161	10.2
Perceived financial condition (%)
Low income	334	29.1	693	43.5
Middle income	586	51.1	633	39.7
Wealthy or comfortably of	228	19.8	268	16.8
Number of siblings (mean)	1,150	2.1	1,566	3.7
Sibling’s birth year (mean)	1,424	1974	3,617	1947
Emotional closeness between respondent and sibling (mean)	1,438	2.9	3,664	2.7
Number of sibling’s children (mean)	1,440	2.1	3,675	2.3
Year of birth of youngest niece/nephew (mean)	1,403	2005	3,228	1978

Note. Basic data: respondent’s birth year, marital status, existence of a biological child, education, financial condition, and number of siblings. Long-format data: Aunt/uncle type, sibling’s birth year, emotional closeness between respondent and sibling, number of sibling’s children, and year of birth of youngest niece/nephew.

We have illustrated the results by calculating the adjusted means and 95% confidence intervals (CIs) of niece and nephew contacts by maternal and paternal aunts and uncles (Figures 1 to 6). Since the data are clustered, we have used Stata’s statistical software cluster option to compute the standard errors. This method takes into account the nonindependence of contact frequencies with nieces and nephews reported by the same respondent (i.e., aunt or uncle).

Figure 1.

Younger generation’s contact frequencies with nieces and nephews (adjusted means and 95% confidence intervals).

Figure 2.

Younger generation’s contact frequencies with nieces and nephews (adjusted means and 95% confidence intervals).

Figure 3.

Younger generation’s contact frequencies with nieces and nephews (adjusted means and 95% confidence intervals).

Figure 4.

Older generation’s contact frequencies with nieces and nephews (adjusted means and 95% confidence intervals).

Figure 5.

Older generation’s contact frequencies with nieces and nephews (adjusted means and 95% confidence intervals).

Figure 6.

Older generation’s contact frequencies with nieces and nephews (adjusted means and 95% confidence intervals).

Results

Younger generation

Figure 1 and Table 2 reveal the overall pattern of younger adults’ contact frequencies with nieces and nephews. The results show that maternal aunts have significantly more contacts with nieces and nephews than do other aunts and uncles. The results are similar for both adjusted and unadjusted models.

Table 2.

Older and younger generation’s contact frequencies with nieces/nephews.

	Younger generation						Older generation
	β	SE	t	p	95% CIs		β	SE	t	p	95% CIs
	β	SE	t	p	Lower	Upper	β	SE	t	p	Lower	Upper
Aunt/uncle type
Maternal aunt (ref)
Maternal uncle	−0.36	0.08	−4.32	<0.001	−0.52	−0.20	−0.09	0.04	−2.18	0.029	−0.16	−0.01
Paternal aunt	−0.21	0.07	−2.97	0.003	−0.35	−0.07	−0.08	0.03	−2.54	0.011	−0.15	−0.02
Paternal uncle	−0.48	0.08	−5.95	<0.001	−0.64	−0.32	−0.13	0.04	−3.54	<0.001	−0.21	−0.06
Birth year	0.02	0.01	2.97	0.003	0.01	0.03	−0.003	0.01	−0.34	0.730	−0.02	0.01
Marital status
Unmarried (ref)
Cohabitation	−0.03	0.10	−0.25	0.800	−0.22	0.17	−0.11	0.08	−1.39	0.164	−0.28	0.05
Married	0.01	0.10	0.09	0.929	−0.18	0.20	−0.16	0.07	−2.20	0.028	−0.30	−0.02
Other	−0.10	0.13	−0.73	0.465	−0.35	0.16	−0.14	0.08	−1.82	0.068	−0.30	0.01
Number of biological children	−0.02	0.01	−1.26	0.207	−0.05	0.01	−0.01	0.004	−1.51	0.130	−0.01	0.002
Education
Primary or lower secondary level (ref)
Upper secondary level	−0.30	0.21	−1.47	0.141	−0.71	0.10	0.01	0.03	0.19	0.851	−0.06	0.07
Lower degree level tertiary education	−0.40	0.21	−1.91	0.057	−0.82	0.01	0.02	0.07	0.33	0.743	−0.11	0.15
Higher degree level tertiary education or doctorate education	−0.52	0.22	−2.37	0.018	−0.94	−0.09	0.06	0.05	1.12	0.262	−0.05	0.17
Perceived financial condition
Low income (ref)
Middle income	0.08	0.07	1.11	0.269	−0.06	0.22	−0.0005	0.03	−0.02	0.988	−0.07	0.06
Wealthy or comfortably of	−0.01	0.09	−0.10	0.919	−0.18	0.16	−0.02	0.05	−0.37	0.715	−0.11	0.07
Number of siblings	−0.07	0.02	−4.57	<0.001	−0.10	−0.04	−0.02	0.01	−3.65	<0.001	−0.03	−0.01
Sibling’s birth year	0.01	0.01	1.07	0.284	−0.01	0.02	−0.003	0.003	−1.20	0.232	−0.01	0.002
Emotional closeness between respondent and sibling	0.30	0.04	7.34	<0.001	0.22	0.12	0.25	0.02	15.67	<0.001	0.22	0.28
Number of sibling’s children	0.06	0.03	2.30	0.021	0.01	0.02	0.02	0.01	1.82	0.068	−0.002	0.05
Year of birth of youngest niece/nephew	0.003	0.01	0.51	0.612	−0.01	0.02	0.004	0.002	1.82	0.068	−0.0003	0.01
Adjusted R ²	0.18						0.13
n	1,350						3,125

Note. Results from two linear regression models; β coefficients, CI = confidence interval.

In addition to sex and lineage, several other factors were correlated with individuals’ contact frequencies with nieces and nephews (Table 2). Age and education of aunts and uncles were negatively associated with contact frequency. In addition, number of siblings was associated negatively, while number of children via specific sibling and emotional closeness with a particular sibling were associated positively with contact frequencies. Finally, the marital status, financial condition, number of children, siblings’ year of birth, and year of birth of the youngest niece/nephew were not significantly associated with contact frequency with nieces and nephews.

Next, we investigated the preferential investment hypothesis in younger adults. In this analysis, we included only those respondents who had niece(s)/nephew(s) via sister(s) and brother(s). Figure 2 shows that maternal aunts and uncles (which is the reference group) had significantly more contacts with nieces and nephews than did paternal aunts and uncles (unadjusted model: β = −.32, SE = .07, t = −4.65, p < .001, 95% CIs: lower = −.45, upper = −.18; adjusted model: β = −.20, SE = .07, t = −2.91, p = .004, 95% CIs: lower = −.34, upper = −.07, R ² = .20).

We then examined the alternate possibility, that is, the contact frequencies when aunts and uncles did not have nieces/nephews from both sister and brother. Based on the preferential investment theory, those who had nieces and nephews only via brothers should have invested in their brothers’ children more than those who had offspring via sisters and brothers. The unadjusted model in Figure 3 shows that aunts and uncles who had nieces/nephews only via brother had significantly more contacts with them than aunts and uncles who had nieces/nephews via sister and brother (unadjusted model: β = .23, SE = .08, t = −3.01, p = .003, 95% CIs: lower = .08, upper = .37). The difference remains significant after controlling for the other factors besides the number of siblings. However, after controlling for the number of siblings (in addition to other control variables), this difference was no longer statistically significant (adjusted model: β = .13, SE = .09, t = −1.51, p = .130, 95% CIs: lower = −.04, upper = .30, R ² = .17). This was probably because of the dilution effect of those who had offspring via several siblings (i.e., via brother and sister), since an increase in the number of siblings tends to result in a decrease in contact frequencies toward a specific sibling and his or her children.

Finally, we ran sensitivity analyses with childcare variable (i.e., we replicated the analyses using childcare variable instead of contact frequency). In these analyses, we included those younger generation’s respondents who had at least one not more than 14-year-old niece or nephew (results not shown). All sensitivity analyses with the childcare variable produced similar results as the analyses where the dependent variable was contact frequencies.

Older generation

Next, we analyzed the sample of older adults. Table 2 and Figure 4 show that, as in the case of the younger generation, the older generation’s maternal aunts had more contacts with nieces and nephews than did maternal uncles, paternal aunts, and paternal uncles. These results are similar for both adjusted and unadjusted models.

Table 2 also shows that some other factors were significantly correlated with niece and nephew contact frequency. Married respondents had fewer contacts with nieces/nephews than unmarried ones. Number of siblings was negatively associated with contacts with nieces/nephews. In addition, those who were emotionally closer to their siblings had more frequent contacts with their siblings’ children. There were no significant associations between other independent variables and niece/nephew contacts.

We then concentrated on the preferential investment hypothesis. In this analysis, we included only those respondents who had niece(s)/nephew(s) via sister(s) and brother(s). Figure 5 shows that individuals had more contacts with their maternal nieces and nephews than their paternal ones (unadjusted model: β = −.13, SE = .02, t = −5.65, p < .001, 95% CIs: lower = −.17, upper = −.08; adjusted model: β = −.06, SE = .03, t = −2.44, p = .015, 95% CIs: lower = −.11, upper = −.01, R ² = .14). Figure 6 illustrates that aunts and uncles who did not have nieces and nephews via sisters had significantly more contacts with their brothers’ children than they would have done if they had genetically more certain investment options available (i.e., offspring via sisters; unadjusted model: β = .15, SE = .04, t = 3.66, p < .001, 95% CIs: lower = .07, upper = .23; adjusted model: β = .10, SE = .04, t = 2.37, p = .018, 95% CIs: lower = .02, upper = .19, R ² = .12).

Discussion

In this study, we examined aunts’ and uncles’ contact frequencies with their nieces and nephews using two-generational data from contemporary Finland. First, in line with the prediction based on paternity uncertainty and sex effect, we found that maternal aunts had more contacts with nieces and nephews than did other types of aunts and uncles in both generations. Second, we tested the predictions of the preferential investment theory and analyzed whether alternative investment options influenced the investment behavior of aunts and uncles. In accordance with the preferential investment theory, we found that when aunts and uncles have an option to invest in either their sisters’ children or their brothers’ children, they reported having more contacts with their sisters’ children. Our results are also in line with the previous studies concerning women as kin keepers, which have shown that women tend to have stronger relationships with kin than males.

However, our results were not totally in line with the preferential investment theory. We found that, after controlling for the number of siblings, the younger generation’s aunts and uncles who had nieces and nephews only via their brothers did not have significantly more contacts with their brothers’ children compared to those aunts and uncles who had offspring via both sisters and brothers. This may be due to the dilution effect for those who had offspring via several siblings. The investment in nieces and nephews was most likely to be diluted if there were several “sets” of them (i.e., nieces and nephews via several siblings).

This dilution effect may have greater influence in the younger generation because representatives of the older generation have more (and older) siblings, and thus, they may have more brothers with children. In the younger generation, there are probably more individuals who have only one or two siblings. In addition, because men usually have children at an older age than women, the number of siblings with children may be emphasized among those younger generation representatives who have a sister and a brother (or only sisters), whereas the ones who have one or several brothers may have fewer nieces/nephews. To scrutinize the association between the dilution effect and the preferential investment theory more precisely, we would need larger data with more observations of younger adults who had nieces and nephews via several siblings, including via several brothers.

Our results are consistent with the findings of several previous studies that have shown that aunts and uncles tend to invest more in maternal nieces and nephews than paternal ones (e.g., Gaulin et al., 1997; McBurney et al., 2002; Pashos & McBurney, 2008). Compared to previous research, the advantage of our study is that we used nationally representative data from two adult generations, and we were able to control for several potentially confounding variables. Most importantly, this study is the first, to our knowledge, to analyze the preferential investment theory among aunts and uncles in modern societies.

Our results are in line with previous studies of grandparenting, which show that grandparents channel their investment according to alternative investment options (Danielsbacka et al., 2011; Laham et al., 2005; but see Bishop et al., 2009). These studies have shown that if grandparents have the option to invest in maternal or paternal offspring, they tend to prefer maternal offspring over paternal ones. We found the same investment behavior in our study of aunts and uncles. Future studies should, however, test the preferential investment theory in cousins. It is still an open question as to how far (genetically) the existence of more certain investment options influences the investment behavior of humans.

In addition to lineage, we found that several other factors were associated with contact frequencies with nieces and nephews. In line with the previous studies, we found that in both generations, aunts tended to have more contacts than did uncles (e.g., Gaulin et al., 1997; Hoier et al., 2001). Also, in both generations, those aunts and uncles who were emotionally closer to a particular sibling had more contacts with that sibling’s children. This aligns with the study by Pashos and McBurney (2008), which found high correlations between the emotional closeness of parents’ and siblings’ and the degree of investment in nieces and nephews. We also found a dilution effect in the case of older generation, given that aunts and uncles who had more siblings had fewer contacts with any one particular sibling’s children. However, it was only in the case of the younger generation that aunts and uncles with fewer nieces and nephews via a particular sibling had more contacts with them. Finally, contrary to previous studies of kin investment (e.g., Pollet, 2007; Tanskanen & Danielsbacka, 2014), we found that younger adults with a higher level of education have fewer contacts with nieces and nephews compared to those with a lower level of education.

Compared to previous studies of aunts and uncles (e.g., Gaulin et al., 1997; Pashos & McBurney, 2008), the present study has several strengths. Since we used nationally representative data from two generations and controlled for a number of potential confounding variables, the results may be more generalizable. In addition, the two generational data provided us opportunity to rule out the possible effects of cultural and societal changes. However, the present study has also some limitations. First, we have measured kin investment by contact frequencies. Even though previous studies have shown that contacts tend to correlate with other kin investments (e.g., care and financial transfers), all kin investment variables are different constructs and do not correlate perfectly (see e.g., Pollet, 2005; Pollet et al., 2009). Thus, contact frequency may underrepresent the construct of investment. In the case of younger adults, we were able to run the sensitivity analyses with a childcare variable, which produced similar results as the presented analyses. Thus, we may consider the results robust. However, we need future studies to examine whether these results remain robust when other kin investment variables, such as financial transfers or emotional support, are assessed.

Second, because of data limitations, we were not able to control for the distance between respondents and aunts/uncles or nieces/nephews. However, since we have measured not only face-to-face contact but also contact that via other mediums (e.g., via phone or e-mail), geographical distance may not be a crucial variable. In addition, a previous study on the same population shows that the bias in contacts between siblings remains even after geographical distance is controlled (Tanskanen & Danielsbacka, 2014). Moreover, the development of modern communication technologies may have reduced the effect of geographical distance (Salmon, 1999).

The results of this study highlight the importance of future cross-cultural studies. We analyzed data from only one country, but in future, how investment behavior of aunts and uncles differs in different cultural and family-policy contexts should be examined. In addition, aunts’ and uncles’ investment behavior should be studied with longitudinal data and with several kin investment variables (e.g., childcare, emotional support, and financial help). These studies would allow for examination of how the relationships between aunts and uncles and nieces and nephews develop over the course of their lives. Also the role of parents (i.e., the siblings of aunts and uncles) needs to be taken into account since parents may act as gatekeepers, either promoting or preventing contact between aunts and uncles and nieces and nephews—in particular, when the nieces and nephews are young children.

Previous studies have shown that in contemporary affluent societies, the investment of extended kin (i.e., grandparents) may increase parents’ likelihood of having another child (e.g., Waynforth, 2011) as well as improving children’s well-being (e.g., Attar-Schwartz, Tan, Buchanan, Flouri, & Griggs, 2009). Future studies should investigate whether the support provided by aunts and uncles is associated with parents’ childbearing decisions and the well-being of nieces and nephews in modern societies.

Footnotes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Academy of Finland (grant no. 250620) and Kone Foundation (M.D.).

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