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Since the first applications of evolutionary theory to human behavior (Wilson, 1975), kin selection has played a key explanatory role. Studies of parental investment (Daly & Wilson, 1988), food sharing (Gurven, Allen-Arave, Hill, & Hurtado, 2001), residence decisions, and violence (Chagnon, 1979) show that individuals favor close relatives over distant ones (or nonrelatives) as targets of altruism, consistent with inclusive fitness theory (Hamilton, 1964). However, kin altruism can be disrupted if there is local competition over resources because this can lead to competition among nondispersing relatives, reducing or negating the effects of relatedness on promoting altruism (Boyd, 1982, Frank, 1998, Hamilton, 1967). While research on nonhumans demonstrates that the extent of nepotism among kin can depend critically on resources available to parents or sibships in insects (Griffin et al., 2004, West et al., 2001), our understanding of the sensitivity of human kinship relations to resource competition derives largely from folklore (Cinderella's scrubbing of the kitchen floor on the night of the prince's ball at the behest of her stepsisters) or historical anecdote (the antics of the battling sons of Eleanor of Aquitaine).
Here, I present demographic data from Kenya, leveraging large variation in land ownership among Kipsigis agropastoralists, to determine the interactions between local resource competition and the role of kin in enhancing child survival. As predicted, in this patrilineal, patrilocal population, where polygyny generates large coresident aggregations of paternal relatives competing for inheritances, there is an interaction between resource availability and the extent to which paternal relatives apparently buffer young children from mortality. Additional unanticipated evidence suggests that maternal relatives also appear to protect children against mortality, although only in situations where paternal kin control inadequate resources to raise children. These results shed light on the ecological and social factors affecting when kin might affect the success of their relatives' reproductive careers. While there has been discussion of some of the possible contingencies influencing why certain categories of kin might (or might not) help (e.g., Beise, 2005, Hames & Draper, 2004, Hrdy, 2005, Leonetti et al., 2005, Sear & Mace, 2006), this study presents an empirical analysis of how the resources available to lineages affect the behavior of kin in such a way as to influence child survival outcomes.
To place the somewhat counterintuitive expectations that paternal Kipsigis kin are not necessarily very helpful when resources are strained, I review some previous research on this population, adding ethnographic observations. Armed with the principal scholarly source on the Kipsigis (Peristiany, 1939), I first arrived in a Kipsigis neighborhood (Tabarit) expecting to find strong localized patrilineages with marked patterns of respect and economic obligation. Almost immediately, I learned of intense fraternal strife, conflicts over land and bridewealth (livestock) distributions that are often taken to the neighborhood moots (or courts). When a young man from a neighboring community turned down funds to study journalism in Canada because of fear “that my brother and cousins will take my land and cattle if father dies in my absence” (Kab Gelegele resident, February, 1982), the truly pervasive influence of intralineage conflict dawned on me. Empirical analyses confirm the extent to which brothers hinder each other's marriage, inheritance, and reproductive chances (whereas sisters are an asset, Borgerhoff Mulder, 1998).
Ethnographically, the story is more complicated. Over the months, I began to see instances of extraordinary cooperation over blood feuds, over the hosting of the all-important circumcision ceremonies, and in crises resulting from severe illness, theft, or livestock loss. Agnates would appear from far away and deal with the disaster. Looking back into Peristiany (1939), I found that he, too, saw the same things: “(T)he economic obligations between paternal relations are only enforced during moments of exceptional need” (p. 98) and “the solidarity of the paternal family can be seen functioning … in the case of a murder committed by one of its members” or “if the harvest is bad” (pp. 98 and 100).
With this knowledge of how paternal kin and lineages operate in contemporary and traditional Kipsigis communities, and receiving letters from Kipsigis friends whose lives were being destroyed by competitive kinsmen, I watched with some amazement a burgeoning literature on the cascades of positive kin effects on survival and growth (reviewed in Hrdy, 2005, Sear & Mace, 2006). Previous analyses of Kipsigis data had already shown negative effects of siblings (Borgerhoff Mulder, 1998) and cowives (Borgerhoff Mulder, 1990, Borgerhoff Mulder, 1997) on rates of child survival, indicative of intrafamilial resource competition. The motivation for the present study therefore lay in continuing to investigate such competition beyond the confines of sibships and polygynous marriages, guided by ongoing developments in kinship and reproductive skew theory to which I now turn.
1.1. Child mortality and social support
Although child mortality in the developed world is rare (6 deaths per 1000 live births), the developing world exhibits a 29-fold higher rate (175 per 1000 for sub-Saharan Africa; Black, Morris, & Bryce, 2003). This mortality level reflects the coincidence of an evolved set of life history traits, specifically the rapid production of altricial young requiring high levels of parental investment (Kaplan & Lancaster, 2003), and the poor socioeconomic conditions typical of many regions within the developing world, including food insecurity, high pathogen exposure, low education, and negative effects of global markets (Armelagos et al., 2005, Cesar et al., 2003). While within-population variation in child welfare and survival are clearly a function of household income, parental education, season of birth, maternal age, and child and maternal nutrition, public health scholars have recently extended their investigations to the importance of social support networks, often made up of kin, in promoting positive health outcomes through buffering households against risk of food shortages (Cohen, Underwood, & Gottlieb, 2000).
As regards such familial networks, biologists expect kin to assist their relatives in successfully raising offspring, even if at personal cost, because of inclusive fitness benefits. Hamilton's kin selection theory (Hamilton, 1964) provides an explanation for such altruism: altruistic behavior is favored wherever rb−c>0, where r is the genetic relatedness between actor and beneficiary, b is the benefit of receiving the altruistic behavior, and c is the cost of performing the behavior. Evolutionary anthropologists have made specific tests of Hamilton's rule regarding nepotism and investment within human families (e.g., Alexander, 1979, Chagnon, 1982, Chagnon & Bugos, 1979) and, in some cases, found quite close fits between predicted patterns of altruism and empirical data (Bowles & Posel, 2005).
It is often forgotten that Hamilton also recognized the potential for competition among kin in viscous populations where dispersal is limited (Hamilton, 1967). In studies of nonhumans, competition between relatives over resources has been convincingly shown to reduce selection for cooperation among relatives (Griffin et al., 2004, West et al., 2001) and to bias sex ratios away from the competing sex (Clarke, 1978, Gowaty, 1993); this is because although limited dispersal raises levels of relatedness among interacting individuals, it can also lead to more local competition among relatives (Frank, 1998). In a separate theoretical literature on reproductive skew, some of the transactional models in which dominants are assumed to control the reproduction of subordinates, specifically the concessions model (Johnstone, 2000, Keller & Reeve, 1994), predict that relatedness within a group can exacerbate reproductive differentials among kin, leading to the prediction that some relatives can suffer from living in high aggregations of kin.
In humans, there is clear evidence that within-family inequities exist (Boone, 1986, Hrdy & Judge, 1993) and that families can be suffused with tension (Alexander, 1979, Emlen, 1995). Furthermore, psychologists have explored health and educational differentials among siblings (Hertwig, Davis, & Sulloway, 2002), in some cases within the framework of resource dilution (Downey, 2001). Nevertheless, there has been no systematic examination of the implications of local resource competition for constraining the role of relatives as cooperators or competitors, with the exception of Hadley's (2004) study of Tanzanian Pimbwe in which he examined statistical interactions between socioeconomic status and kin effects. Ultimately, a perspective focusing on the intersections of kin effects and resources could be brought to bear on explaining cross-cultural variation in kinship systems, but in this analysis, I focus on the more tractable question of within-population variability.
1.2. Predictions for a Kipsigis community
The Kipsigis of Kenya are a Nilotic agropastoral population, inhabiting the fringes of the White Highlands, living on now demarcated plots of land on which they keep livestock and grow crops for subsistence and cash. They have, at least, since the late 18th century, been patrilineal, polygynous, and patrilocal (Mwanza, 1977). Marriages are sealed with a bridewealth payment from the groom to the bride's lineage, whereupon a woman moves from her natal to her husband's homestead and, as a new lineage member, becomes entirely dependent on her husband's resources (Peristiany, 1939). A woman's sons inherit land exclusively from their father.
The study area on the borders of Kericho and Narok Districts was settled in the 1930s and 1940s by Kipsigis men and their families escaping the overcrowded “Native Reserves” established by the British colonial government (Borgerhoff Mulder, 1990). The nontraditional practice of land enclosure (through fencing, Manners, 1967) that emerged throughout the century was exacerbated by a 1980s World Bank initiative for land registration in the area. Land ownership, together with rapid population growth and interethnic territorial tensions, have, to some extent, inhibited the traditional pattern of married sons establishing farms adjacent to that of their father, and, increasingly, all sons settle on their father's land or on a plot of land purchased by their father. Unsurprisingly, many demographic traits are affected by the size of a man's land holding, including polygynous marriage (Borgerhoff Mulder, 1987a, Borgerhoff Mulder, 1990), fertility, and offspring survival (Borgerhoff Mulder, 1987b). Perhaps, unsurprisingly, there can be intense competition among brothers over inheritances and reproductive opportunities, including bridewealth (Borgerhoff Mulder, 1998). As cooperation among kin may be restricted when local competition is intense, I predict that the effects of paternal kin on child survival will be stronger in wealthier than in poorer households. This hypothesis predicts wealth interaction effects, not necessarily a reverse in the sign of the statistical relationship across wealth categories.
Analyses are based on 785 births to 129 women and 107 men between 1945 and 1990, collected from retrospective interviews with members of all households in four neighborhoods (kokwetinik; singular, kokwet) intensively studied in 1982–1983 and 1990–1991. Of these live births, 15% failed to reach their fifth birthday, a percentage that varied over time: 19% of those born prior to 1980 (n=392) and 10% of those born in 1980 or later (n=393). As shown elsewhere, the principal cause of mortality for children below 5 years old is disease—malaria, diarrhea, measles, and influenza (Borgerhoff Mulder, 1987b)—all of which are treated with traditional and modern medicine. Consistent with analyses showing no gender-biased survival (Borgerhoff Mulder, 1989), child sex dropped out of all the models.
Kipsigis households, as defined here, consist of a woman, her children, and her husband. They are typically located within larger extended residential units of patrilineally related kin, units that include the households of a woman's cowives, of sons and their wives, and of the husband's father and his wives and that retain ultimate rights of ownership to land and livestock. Each woman owns her own hut; after a year or so of marriage, she obtains rights of use to land and livestock and builds her own granary. Reproductive histories were taken for all women in the four neighborhoods who had produced one or more children. Births to individuals deceased at the time of the interview were recorded [10 men (9.3% of the sample) and 12 women (9.3% of the sample)] by means of questions with a living spouse who fell in the sample.
Survival status or age at death was determined for each birth. Of special interest were the survival status and residence of the father's mother (FM) and father (FF) and the number of the father's brothers (FB), as well as those for maternal kin—mother's mother (MM), mother's father (MF), and mother's brothers (MB). The number and/or status of kin in these categories was determined from the full demographic sample (Borgerhoff Mulder, 1987a, Borgerhoff Mulder, 1987b). This was straightforward for paternal kin, given the strong patrilineal residence patterns among the Kipsigis, with men and their brothers very commonly living on the same or adjacent plots of land. Fortuitously, systematic data on wives' relatives had been collected as part of a bridewealth study (Borgerhoff Mulder, 1995). Additional kin effects considered in the model are the survival status of the focal child's mother and father.
Each parent and each grandparent of a child were coded as dead if this individual had died before or within the focal child's first 5 years of life. Because the date of the specified relative's death could not always be narrowed down to month and year, this approximation seemed more appropriate than restricting analysis to better educated individuals with more precise recall of exact dates. The number of a child's FB or MB was determined on the basis of questions regarding the number of currently living (1982–1983) brothers of the father and mother and their residential histories; it is therefore fixed for a sib set and can be considered only an approximation for any given child; these variables are accordingly treated as categorical variables (FBCAT, MBCAT). For FM, FF, MM, and MF, it was possible to determine whether this relative lived in the same set of adjacent kokwetinik as the child (generally within a 15-km range, an easy day's walk, termed “local”) or at a further distance (generally more than an easy day's walk, termed “distant”); even where relatives lived beyond the adjacent kokwetinik that constituted the sample of this study, the distance rarely exceeded 25 km. In this sample, the mode, median, and range of the ego's FM's residence and MM's residence are 0, 0, and 0–11 km and 0, 3, and 0–128 km, respectively. Unless other information was available, it was assumed that residence patterns observed in 1982–1983 and confirmed in 1991 had been constant. Very infrequent land sales and minimal labor migration justify such an assumption.
To study the independent effects of kin factors on focal child survival and their interactions with wealth, these measures were linked to the full demographic and socioeconomic records. Wealth is measured as land available to the child's mother, because of the significance of this factor in previous analyses of this population (Borgerhoff Mulder, 1987b). Used as control variables were data on year of birth (for secular changes in survival), gender, twin status, mother's age at birth of child, previous birth interval, birth order, polygynous status of mother, mother's education, wealth (as defined above), and the number of the focal child's brothers (both full and half). These variables allow for both a finer determination of the effects of kin and a more nuanced interpretation of the correlational results.
Cox's regression, a form of event history analysis (Allison, 1984), was used to determine probability of survival within the first 60 months of life, using STATA (v 8.1). This method is appropriate in that it allows for the inclusion of censored cases, in this case, children who have survived to various ages but not yet reached their fifth birthday. Four analytical steps were taken. First, to identify unobserved variability between siblings born to the same mother, all independent variables were investigated for shared frailty using the STATA “share” command and entering the mother's ID as a covariate. Theta values (a single variance parameter that measures heterogeneity in survival times across the children of different mothers) were consistently very small (0.00–0.086) and never significant, indicating that there is no intermother variance in frailty; in other words, all full sib sets have the same unobserved frailty (Gutierrez, 2002). This results in part because many of the covariates of interest, such as wealth, status of grandparents, number of siblings, and so forth, vary much less within families than between families. The same analysis with similar outcomes was conducted for shared fathers and shared lineages. Each of these terms was investigated in the full model and, again, was observed to be very small, reflecting the fact that multiple independent variables capture much of the variation and leave little residue to be explained as unobserved heterogeneity. Since shared frailty parameters never contributed significantly to any of the models, they were dropped from the presentation of the final analyses.
The second step entailed identifying the effects of a range of control variables, defined as variables expected to affect survival times but not of primary interest in the current analysis. This was done by determining the increased probability of dying in the first 5 years of life as a function of a change in the specified independent variable. Models were fit using the Cox's proportional hazards model in STATA (see Table 1). Model A drops individuals for whom there are missing data, whereas Model B uses the full sample, dropping variables for which there is incomplete information. The results are largely congruent. Interpretation of the proportional hazard ratio is as follows. The estimated hazard ratio of 0.974 for birth year (in the reduced sample, Model A) indicates that an individual born in any given year has a 2.6% reduced likelihood of dying than does an individual born in the preceding year (i.e., the ratio of their respective hazards is 0.974). This ratio does not differ significantly from 1, on the basis of a Wald χ2 statistic (3.117), although it shows a statistically significant trend. Now, consider birth intervals, coded as a categorical variable. Compared to children born after the shortest interval, the 23- to 25-month group has a nonsignificant 37% greater chance of dying, the 26- to 36-month group a 36% reduced chance of dying, and the longest category an even more (61%) reduced chance of dying. While only the ratio of the first to the last category is significantly different from 1, there is an overall significant effect as indicated by the Wald χ2 statistic (11.741). Hazard ratios show that children with a later birth year are less likely to die (Table 1, Panel 1) and that twins have higher mortality than single births (Panel 3). Mortality declines with the length of the preceding birth interval (Panel 5), among children of middle birth order (Panel 6, Model A only), among children born to women with no cowives (Panel 7, B only), with each year of maternal education (Panel 8), with an intermediate number of full and half brothers (Panel 9), and as the size of the land holding increases (Panel 10). These are well-established and commonly observed effects found previously both in this and many other developing nation populations (Rutstein, 1984, Rutstein, 2000) and receive no further discussion here except with respect to their interactions with kin variables.
|Variable||Model Aa||Model Bb|
|n||Proportional hazard ratio and Z-score significance level||Wald χ2 and significance level||n||Proportional hazard ratio and Z-score significance level||Wald χ2 and significance level|
|1. Birth yearc||582||0.974||3.117†||785||0.957||15.975⁎⁎⁎|
|4. Mother's age (in years) at birthe||0.571||1.341|
|5. Previous IBI (in months)f||11.741⁎⁎|
|6. Birth orderg||6.050†||3.382|
|7. Polygyny (no. of cowives)e||3.211||10.120⁎⁎|
|8. Education (in years)ch||582||0.930||3.463†|
|9. Number of full and half brothers||7.213⁎||11.028⁎⁎|
|Full model χ2 likelihood statistics||60.371, df=17, p<.001||78.715, df=13, p<.001|
“Previous IBI” and “education” are dropped from Model B, leaving an n of 582 (there is an overlap in cases with missing values).
Reduced sample: individuals with missing data were dropped.b
Full sample: variables with missing data were dropped.c
Calculated at the time of birth of the child.f
Data on previous IBI are missing for 146 observations.g
Birth order was categorized this way to maximize capture of inverted U shape survival by parity.h
Data on education are missing for 87 observations.⁎
The third step entailed single-variate analyses of kin effects for the full sample of births (Table 2, Model C). The raw survival curves are presented in Fig. 1, Fig. 2, Fig. 3, Fig. 4. The fourth step examined a series of multivariate models with control and kin variables considered together (Table 3, Model D), split by wealth (Model E), and with wealth interactions (Model F). The third and fourth steps are presented in Section 3.
|Proportional hazard ratio and Z-score significance level||Wald χ2 and significance level|
|1. Parental survival|
|2. Paternal kin|
|3. Maternal kin|
Fig. 2. The effects of the number of FB on child survival (<60 months) splitting the population into a poorer and a richer half. Compared to the baseline (FBCAT 0 to 1), the proportional hazard ratio for 2, 3, and 4–6 FB are 0.996, 1.161, and 1.973 (Wald χ2=6.173) for the poorer households and 0.861, 0.232, and 0.124 (Wald χ2=18.603, p<.001) for the richer households, yielding a significant interaction (Wald χ2=20.823, p<.001). For the multivariate model statistics, see Table 3.
Fig. 4. The effects of the number of MB on child survival (<60 months) splitting the population into a poorer and a richer half. Compared to the baseline (MBCAT 0 to 1), the proportional hazard ratio for 2, 3, and 4–7 MB are 0.730, 0.409, and 0.197 (Wald χ2=9.539, p<.05) for the poorer households and 1.264, 1.425, and 1.837 (Wald χ2=0.777, ns) for the richer households, yielding a significant interaction effect (Wald χ2=6.681, .05<p<.10). For the multivariate model statistics, see Table 3.
|n||Model D||Model E||Model Fa|
|Proportional hazard ratio and Z-score significance level||Wald χ2 and significance level||Proportional hazard ratio and Z-score significance level||Wald χ2 and significance level||Proportional hazard ratio and Z-score significance level||Wald χ2 and significance level||Wald χ2 and significance level|
|1. Parental survival|
|2. Paternal kin|
|3. Maternal kin|
|4. Control variables|
|No. of cowives|
|No. of full or half brothers|
|Full model log likelihood χ2||785||138.001, df=23, p<.001||78.34, df=23, p<.001||107.27, df=23, p<.001|
Model F is not strictly a single model. It results from a rerunning of Model D 12 times, each time with a wealth interaction term added for the specified variable.b
3.1. Parental effects
As shown in the first panel of Table 2, a child is 77% less likely to die if his or her mother is alive during the first 5 years of life than if the mother dies during this period; living fathers have no significant effect on survival. This pattern is retained in the full model (Table 3, Model D) and holds in both the richer and the poorer (at marginal significance) halves of the population (Table 3, Model E). There is a marginally significant interaction between mother and wealth, indicating that mothers' survival is more strongly associated with child survival in rich than in poorer households, an unpredicted trend we return to in Section 4.
3.2. Paternal kin effects
The effects of paternal kin on survival (Fig. 1) are shown in the second panel of Table 2. Single-variate analyses (Model C) show that children with a living FM and children with a living FF are significantly less likely to die than those without these paternal kin.
The principal paternal grandparental effect lies between those who are deceased and those who are alive and live either locally or distant. This indicates that for this category of kin, the distance at which they live is not a major factor in providing support, conforming to ethnographic observations: paternal kin amass at times of conflict over land, interlineage conflicts, or family crises in current times, as they did in the early years of the 20th century (Peristiany, 1939).
Examining paternal kin effects in a full model in which all demographic and economic variables are entered (Table 3, Model D) shows that both a surviving FM and the number of FB are retained as significant factors reducing child mortality, although the latter is only marginally statistically significant. In other words, paternal kin raise survival chances, independent of the positive effect associated with the number of MB (Panel 3, and see below) and of control variables (see Table 3, Panel 4), including wealth.
Splitting the sample by wealth shows clear wealth interactions. As expected, the positive association between FB (FBCAT) and child survival is stronger in the richer than in the poorer section of the population (Fig. 2). Children with a large number of FB show reduced mortality in the wealthier but not in the poorer half of the population. These results hold in the fully controlled model (Table 3, Model E), and there is a significant interaction effect between number of FB and wealth (Model F). The reasons why the FB might enhance survival in wealthy but not in poor households are examined in Section 4. A further wealth interaction indicates that the association between the FM and child survival is stronger in the poorer than in the richer half of the population, another unexpected result addressed in Section 4.
3.3. Maternal kin effects
The effects of maternal kin on survival (Fig. 3) are shown in the third panel of Table 2. Single-variate analyses (Model C) reveal that the status of the MM has no overall effect on child survival and that there is only a marginally significant trend for the MF and MB.
These marginally statistically significant effects reflect low mortality (high proportional hazard ratio) in cases where the MM and MF are alive but living beyond the neighborhood compared to those who are either deceased or alive and present. This suggests an unusual but ethnographically quite plausible maternal kin effect—a woman benefits if her parents live at some distance from her marital home. This “refuge” effect is explored in Section 4.
Examining the effects of maternal kin in the full analysis (Table 3, Model D) reveals that neither the effect of MM nor the MF retains significance. There is, however, a strong independent and positive effect of the number of MB on child survival. In other words, children whose mothers have three or more brothers experience a significantly reduced mortality risk, independent of whether the mother herself is alive (Panel 1), of the effects of the FM and FB (discussed above, Panel 2), and of other control variables (Panel 4).
Splitting the sample by wealth shows that the apparently beneficial effects of the MB are, in fact, most marked in the poorer half of the population (Fig. 4). Statistically, this is preserved in the full model (Table 3, Model E) where the number of MB is marginally significantly associated with child survival only in poorer households, yielding a marginally significant interaction between MB and wealth (Table 3, Model F). Adding to the model a further interaction term that identified whether the MB lived locally or not (as gauged by the location of the mother's parents) shows that the number of MB is associated with higher survival in poor households when these brothers live at a distance (Wald χ2=9.17, df=3, p<.05).
3.4. Control variables and the role of competition among kin
Analyses showing that nepotism toward grandchildren, nephews, and nieces within patrilineages varies by wealth provide only indirect evidence that kin are motivated to help their relatives as a function of potential competition over resources within the patrilineage. The most convincing evidence for this interpretation comes, unsurprisingly, from ethnographic observations (see Sections 1 and 4). Further indication of competition contributing to offspring survival in resource-stressed situations is found in the patterning of the effects of the control variables in these analyses. First, consistent with previous analyses, the number of a child's mother's cowives is negatively associated with child survival (Borgerhoff Mulder, 1990, Borgerhoff Mulder, 1997), an effect that is observed in poorer but not in richer households (although the interaction term is not significant). Second, again consistent with previous analyses (Borgerhoff Mulder, 1998, Table B1, and here just focusing on male siblings—the most likely competitors), survival chances are negatively associated with the number of a child's full or half brothers. As with the analysis of mother's cowives, this effect is stronger in poorer than in richer households (Model F).
Examining control variables in this way provides statistical support for the claim that competition within poorer patrilineages is modulated by wealth availability. On the other hand, it is important to stress that these imputed patterns of competition are not entirely accounted for by wealth since both the main effects and the wealth interaction terms are independent of the wealth covariate (acres). Furthermore, an anticipated interaction between birth date, wealth, and child survival (reflecting increased competition over time with escalating land shortages) was not found, probably because, in recent years, child mortality has declined substantially and wealth nowadays shows higher correlations with fertility than with offspring survival (Borgerhoff Mulder, 1987b).
The motivations for maternal kin to assist with the raising of grandchildren, nephews, and nieces are more difficult to evaluate since we know less about their circumstances; this is because many of them reside outside of the study area. The present analyses do, however, indicate that these lineages help out their daughters when their daughters find themselves married to men with limited resources.
In this study, demographic correlations between the availability of kin and the survival of children prior to their fifth birthday are presented to examine how kin cooperation affects reproduction in human societies. The principal finding is that paternal kin play a larger role in affecting child survival than maternal kin, no doubt reflecting patrilineal social institutions in the Kipsigis. As predicted by the local resource competition model, there is a significant interaction between wealth and number of FB, suggesting that the apparently protective role of paternal uncles is stronger in richer than in poorer lineages. An unanticipated finding is the apparent buffering effect of maternal kin in situations where paternal kin control limited resources.
The mechanisms whereby kin do, or do not, improve child survival are not identified in this study but are likely to entail provision of food, labor, and cash at critical family crises—food shortages, crop loss, cattle disease, political disputes, and acute illness. As mentioned in Section 1, public health scholars are increasingly impressed with the importance of kin networks in promoting positive health outcomes (Cohen et al., 2000). My ethnographic observations with Kipsigis provide abundant evidence of the role kin often play in supporting one another in child rearing, whether this involves taking a child to a traditional or Western health practitioner, providing money for care, slaughtering livestock in times of drought or temporary food shortage, helping with the tasks of firewood and water collection, assisting with agricultural work, or providing direct childcare (Borgerhoff Mulder & Milton, 1985). More diffusely, and as noted by Peristiany and myself, patrilineal kin amass at times of crisis and provide critical assistance with events surrounding circumcision, weddings, and blood payment negotiations (Peristiany, 1939, p. 98). Although neighborhoods (kokwetinwek) have strong cooperative institutions for coordinating daily tasks (Peristiany, 1939), relatives are usually the most reliable partners even within a neighborhood.
Although much of what we know about cooperative breeding in humans is based on correlational data (as reviewed in Sear & Mace, 2006), we should caution that correlation is not causation. Since relatives share not only genes but many environmental factors as well, underlying heterogeneities between families may account for some of these correlations. To some extent, this problem is mitigated here by the examination of the shared frailty parameters, which, perhaps unsurprisingly, proved to be nonsignificant given the number of independent variables available in this study. Furthermore, if phenotypic correlations were important, we would expect positive associations between child survival and all categories of equally related relatives, but this is not the case. A further problem with analyses of the type reported in this article is that contingencies are not explored. In other words, no attempt is made to determine how the loss of one relative, for example, a mother, might render other relatives more, or less, important in terms of affecting child survival; this could be the subject of further analysis and would undoubtedly add texture to our understanding of the facultative aspects of kinship behavior.
4.1. Evidence for local resource competition
Why do paternal kin, and specifically FB, enhance survival in wealthy households but not in poor households? A man and his brothers and half brothers are direct competitors over their father's land and livestock. Kipsigis custom dictates an equal division of resources among sons, a practice that worked well in a traditional system in which livestock was the principal wealth source. During the colonial period, the ownership of cultivable land became important. Unlike cattle, land is an inelastic resource, and plot sizes are shrinking across generations as population grows. Violent cases of strife over land among brothers, among brothers' wives, and among the cowives married to polygynously married men were observed during fieldwork, including the following: a man burning down the house of his brother, with wife and children inside; a woman attempting to poison the children of her husband's elder brother; attempts to “move” fences (effectively brush piles) over night prior to the formal delineation of fields; witchcraft accusations; and local court cases. Equally notable were instances of supreme altruism and fraternal cooperation (such as shouldering the medical expenses of a brother's children or providing secondary school fees for a nephew or niece). The unexpected observation that living paternal grandmothers improve child survival in poor but not in rich households suggests that these grannies can perhaps buffer young children from mortality in patrilineages wrought with resource conflict.
The suggestion that brothers cooperate more in richer than in poorer patrilineages likely results from two specific features of Kipsigis society and ecology. First, patrilineally related kin tend to be equivalent in wealth status, reflecting the traditional egalitarian inheritance system and limited access to off-farm employment in this population. Second, the relationship between resource availability and fitness shows diminishing marginal benefits as wealth increases (Borgerhoff Mulder, 1987a). Under such circumstances, a poor man might find that the inclusive fitness benefit (b) of making a resource transfer to a sick nephew or niece is eclipsed by the direct fitness cost (c) of the lost resource; conversely, for a rich man, the marginal benefit of transferring resources to save the life of an ailing nephew or niece could outweigh the small, direct fitness cost. If this is the logic underlying these empirical patterns, nepotism would indeed be more likely to trump direct fitness costs in richer than in poorer lineages. This framework helps to explain why, in a study of the Tanzanian Pimbwe, Hadley (2004) found exactly the opposite pattern to the one reported here. The presence of mother's sisters in the village was positively associated with child weight-for-age scores only in families of low socioeconomic status, a more intuitively understood and possibly widespread pattern (e.g., Stack, 1997, for African Americans). Why is the Pimbwe pattern so different from the Kipsigis? With little to no inherited possessions, poorer families have few material assets to compete over and have much to gain from cooperation. In fact, because close relatives can vary enormously in wealth, it is the rich individuals who report being pestered by their poorer relatives into providing a costly resource stream (Hadley, 2004).
An alternative but unlikely explanation for the Kipsigis results is that it is not the b and c terms in Hamilton's equation that vary with wealth but rather r. Thus, relatedness among agnatic kin might be higher in richer than in poorer households, reflecting greater mate guarding potential on the part of husbands or lower temptations to infidelity on the part of women. However, extramarital affairs are heavily sanctioned in this population and lead to acute punitive outcomes for women, which (anecdotally at least) appear unrelated to wealth. Insofar as richer people tend to be more educated and cosmopolitan, one might expect (if anything) richer households to show lower r, although this is pure supposition.
These results can be placed in the broader framework of family conflict (Emlen, 1995). Hill and Hurtado (1996), after failing to show effects on survival associated with individual relatives, turn to the use of the ratio of related helpers to potential recipients in the Ache to indicate kin assistance in the context of competing demands on their time. In Dominica, Quinlan (2005) shows how the number of brothers in a community negatively affects reproductive success, a pattern elsewhere linked to competition over inheritance and marriage payments (East Africa, Mace, 1996) and land inheritance (agrarian Sweden, Low, 1994). Furthermore, in many parts of the world, strong negative effects of the number (Knodel, Havanon, & Sittitrai, 1990) and sex (Parish & Willis, 1994) of siblings are seen on health and educational outcomes (Downey, 2001, Garg & Morduch, 1998) as parents strategize within offspring sets. Specific links can be drawn between parental strategies and resource shortages in a historical German peasant population, where differential investment in sons and daughters is shown to vary in relation to habitat saturation (Voland & Dunbar, 1995). The demographic evidence presented here on the Kipsigis, a population with a strong ethos of equal inheritance to sons and an almost exclusive reliance on inherited resources of land and livestock, demonstrates how the balance between apparent kin assistance and kin competition pivots on the availability of resources. On these grounds, we might also expect that as rural populations become integrated into a cash economy (with wealth ultimately held individually in bank accounts), the importance of kin networks for resource transfers will decline, as is occurring in India (Shenk, 2005); kin networks may nevertheless continue to play an important political role (Munshi & Rosenzweig, 2005).
The implication of these results is that for humans, as with other species (Griffin et al., 2004, West et al., 2001), patterns of dispersal and resource distributions are key to the development of more precise predictions regarding altruism. This might explain why, in many domains of human behavior, altruism is only loosely explained by relatedness; for example, only one third of the variability in cash remittances in South Africa is attributable to a model of kin selection that includes reproductive value (Bowles & Posel, 2005). Furthermore, local competition among kin over resources may explain why, in some situations, kin of equal relatedness but different categories, such as those related through maternal or paternal ties, may evince very different patterns of nepotism (Alvard, 2003, Quinlan, 2005).
4.2. The role of other kin in contributing to child welfare
We now turn to the effects (and lack thereof) of parents, of the maternal grandmother, and of other maternally related kin on child survival among the Kipsigis and implications for understanding the role of kin as caretakers in human societies.
First, consider parents. Loss of a mother but not of a father is a strong determinant of offspring survival in the Kipsigis, as would indeed have been expected. Mother loss is an important influence on mortality in the first years of life in many populations (recently reviewed in Sear & Mace, 2006). While mother loss does not precipitate infanticide in the Kipsigis (unlike in some populations, e.g., the Paraguayan Ache, Hill & Hurtado, 1996), breast-feeding children are inevitably weaned rapidly, triggering potentially serious health complications that threaten survival, and weaned children move to the house of the deceased mother's cowife or sister-in-law where they are in direct competition with other children. Father loss, in contrast, has no evident survival costs. High mortality risks among children with a deceased father are most commonly attributed to the mother's new marriage, specifically the stepparent (Daly &Wilson, 1985, Voland, 1988); indeed, the stress that accompanies divorce may be more detrimental than the death of a father per se (Sear, Steele, McGreggor, & Mace, 2002). In the Kipsigis, remarriage does not occur. Widowed mothers are subject to “widow inheritance,” a practice whereby the woman is effectively passed on to one of her brothers-in-law; the fact that widowed women do not remarry but cohabit with their late husband's brother likely contributes to the finding that widowed Kipsigis women do not experience higher child mortality than nonwidowed women. Finally, the anomalous and unanticipated finding that maternal loss is more prejudicial to child survival among the wealthy than among the poor most likely reflects the fact that, in this small sample, children in the wealthy sector were somewhat older at their mother's death.
Second, we examine the absence of a maternal grandmother effect. Generally, maternal grannies are thought to be natural caretakers of their daughters' children as opposed to their sons' children because of the greater certainty of relatedness, and across many studies, their presence is found to be associated with positive survival outcomes (Sear & Mace, 2006). In the Kipsigis, however, it is the paternal grandmother whose presence has a beneficial effect on the survival of small children, no doubt reflecting the strongly patrilineal organization of Kipsigis (also see Gibson & Mace, 2005, Leonetti et al., 2005, Lycett et al., 2000). This suggests a facultative component not only to paternal grandparental behavior (as often surmised) but also, more surprisingly, to maternal grandparental roles.
We turn now to other maternal kin. In the Kipsigis, the status of maternal kin, specifically maternal brothers, is associated with child survival only in the poorer half of the population. This suggests that maternal relatives provide help primarily in situations where limited nepotism from a child's father's lineage can be expected. This is the case despite the fact that there is relatively little cultural emphasis on matrilineal as compared with patrilineal relatives in this population. These results speak to the obvious but often ignored fact that inheritance rules do not dictate behavior (Dickemann, 1982), as well as to the more specific point that patrilineal inheritance rules do not preclude an important role for maternal kin under certain circumstances, a phenomenon much appreciated by earlier ethnographers of African kinship (Radcliffe-Brown & Forde, 1950) and, indeed, by Peristiany who singled out a mother's true brother as a person “of astounding importance” (Peristiany, 1939, p. 100) for the Kipsigis. The data presented here do, indeed, suggest that maternal kin can play a key role in situations where they observe a patrilineage unable or unwilling to provide adequate care to their grandchildren. A similar effect is found among the patrilineal Ethiopian Oromo, where maternal grannies work hard in their daughters' households; accordingly, living maternal grannies tend to have taller granddaughters, although they have no significant effects on the survival of their daughters' children (Gibson & Mace, 2005).
Interestingly, the role of maternal kin as indirect providers of child welfare is only in evidence when they live at a distance (over a day's walk) from the mother's marital household. This is opposite to the Ethiopian pattern where child survival is enhanced by the presence of unspecified maternal kin in the village (Gibson & Mace, 2005). An effect superficially similar to the Kipsigis is found for non-coresiding maternal grandmothers among the Northern Indian Khasi (Leonetti et al. 2005) but is attributed to self-selection, specifically the decisions of grannies to live with otherwise disadvantaged daughters. The explanation in the Kipsigis is rather different (since women change residence at marriage, not in grandmotherhood) and suggests a “refuge” hypothesis. In a cultural group where divorce is practically nonexistent (Orchardson, 1961, Peristiany, 1939), women are typically unhappy during at least some period of their marital life. In such circumstances, and particularly when violence ensues, women run away (or at least take their children away) to the home of their parents, where their brothers also usually live. Several such instances were observed during fieldwork. When the natal homestead is near to the marital homestead, the husband and his kin arrive in person to demand the wife and her children back. When the natal homestead is at a distance, such delegations demanding the wife's return, to the extent that they occur, are generally less successful. This is primarily because a patrilineage typically lacks political allies beyond the area where it is localized. I therefore view this effect as evidence of the wife finding safe haven, for herself and her children, with her natal family. To what extent absent kin play this role in other populations is not known.
How has this analysis of the implications of local resource competition for constraining the role of relatives as cooperators or competitors advanced our understanding of the evolution of the human family? Evolutionary anthropologists already know that across different societies, distinct categories of kin assist mothers in the arduous tasks of child rearing. Indeed, in many respects, the greater role of paternal than maternal kin in the patrilineally organized Kipsigis was to be expected. Evolutionary anthropologists have speculated that this variation reflects a facultative response to different ecological and social conditions (e.g., Hames & Draper, 2004) and to the distinct objectives of different sets of relatives (Sear, Mace, & McGreggor, 2003). However, there has been no application of general theory in regard to this variation.
To promote a more general model for which kin help and why, this study explored the role of resource competition in shaping kin effects, albeit presenting only correlational evidence. The principal finding is that the roles of maternal and paternal kin are conditioned by the wealth of the household into which the child is born. Clearly, there are many factors likely to promote, or curtail, a facultative role for kin in promoting (or inhibiting) child survival. These include the availability of kin, the sensitivity of child survival to assistance from outside the nuclear family, and the potential for competition among kin, all of which are at least indirectly assayed in this study (through kin survival and residence patterns, wealth, and a count of competing siblings). Another important factor might be transaction costs, here and elsewhere modeled through residential propinquity (although, in this study, it turned out that distance does not impede imputed patterns of patrilineal assistance and might actually enhance maternal kin contributions). Yet, other factors that should be considered include competing demands on helpful kin, something that is difficult to measure without a very different sampling strategy.
While there are doubtless many factors promoting or inhibiting kin assistance, the importance of local resource competition (and enhancement) is analytically tractable and has potential generality, especially in systems where resources are inherited across generations. While this study has restricted focus to the significance of local resource competition for constraining the role of relatives as cooperators or competitors within a single population, the findings suggest that the variation in kin roles across societies will be strongly influenced by the elasticity of the resource base, the pattern of inheritance, and the divisibility of the inherited resources. We now need to shift scholarly attention that has focused primarily on the factors responsible for the cohesiveness of kin groups (Hughes, 1986, Jones, 2000) to the source of their fragmentation, or in other words, to situations in which relatives transmute from friend to potential foe.
Alexander, 1979 1.Darwinism and human affairs. . Seattle: University of Washington Press; 1979;.
Allison, 1984 2.Event history analysis. . Newbury Park, CA: Sage; 1984;.
Alvard, 2003 3.Kinship, lineage, and an evolutionary perspective on cooperative hunting groups in Indonesia. . Human Nature. 2003;14:129–163.
Armelagos et al., 2005 4.Evolutionary, historical and political economic perspectives on health and disease. . Social Science & Medicine. 2005;61:755–765.
Beise, 2005 5.The helping grandmother and the helpful grandmother: The role of maternal and paternal grandmothers in child mortality in the 17th and 18th century population of French settlers in Quebec, Canada. . In: Voland E, Chasiotis A, Schiefenhoevel W editor. Grandmotherhood: The evolutionary significance of the second half of the female life. New Brunswick: Rutgers University Press; 2005;p. 215–238.
Black et al., 2003 6.Where and why are 10 million children dying every year?. . Lancet. 2003;361:2226–2234.
Boone, 1986 7.Parental investment and elite family structure in preindustrial states: A case study of late medieval–early modern Portuguese genealogies. . American Anthropologist. 1986;88:859–878.
Borgerhoff Mulder, 1987a 8.On cultural and reproductive success: Kipsigis evidence. . American Anthropologist. 1987;89:617–634.
Borgerhoff Mulder, 1987b 9.Resources and reproductive success in women, with an example from the Kipsigis. . Journal of Zoology. 1987;213:489–505.
Borgerhoff Mulder, 1989 10.Reproductive consequences of sex-biased inheritance for the Kipsigis. . In: Standen V, Foley RA editor. Comparative socioecology. Oxford: Blackwell Scientific Publications; 1989;p. 405–427.
Borgerhoff Mulder, 1990 11.Kipsigis women's preferences for wealthy men: Evidence for female choice in mammals. . Behavioral Ecology and Sociobiology. 1990;27:255–264.
Borgerhoff Mulder, 1995 12.Bridewealth and its correlates: Quantifying changes over time. . Current Anthropology. 1995;36:573–603.
Borgerhoff Mulder, 1997 13.Marrying a married man. . In: Betzig L editors. Human nature: A critical reader. Oxford: Oxford University Press; 1997;p. 115–117.
Borgerhoff Mulder, 1998 14.Brothers and sisters: How sibling interactions affect optimal parental allocations. . Human Nature. 1998;9:119–162.
Borgerhoff Mulder & Milton, 1985 15.Factors affecting infant care in the Kipsigis. . Journal of Anthropological Research. 1985;41:231–262.
Bowles & Posel, 2005 16.Genetic relatedness predicts South African migrant workers' remittances to their families. . Nature. 2005;434:380–383.
Boyd, 1982 17.Density-dependent mortality and the evolution of social interactions. . Animal Behaviour. 1982;30:972–982.
Cesar et al., 2003 18.Applying an equity lens to child health and mortality: More of the same is not enough. . Lancet. 2003;362:233–241.
Chagnon, 1982 19.Sociodemographic attributes of nepotism in tribal populations: Man the rule-breaker. . In: K.C.S. Group editors. Current problems in sociobiology. Cambridge: Cambridge University Press; 1982;p. 291–318.
Chagnon, 1979 20.Mate competition, favoring close kin, and village fissioning among the Yanomamo Indians. . In: Chagnon NA, Irons W editor. Evolutionary biology and human social behavior. North Scituate: Duxbury Press; 1979;p. 86–131.
Chagnon & Bugos, 1979 21.Kin selection and conflict: An analysis of a Yanomamo ax fight. . In: Chagnon NA, Irons W editor. Evolutionary biology and human social behavior. North Scituate: Duxbury Press; 1979;p. 213–237.
Clarke, 1978 22.Sex ratio and local resource competition in a prosimian primate. . Science. 1978;201:163–165.
Cohen et al., 2000 23.Social support measurement and intervention: A guide for health and social scientists. . Oxford: Oxford University Press; 2000;.
Daly &Wilson, 1985 24.Child abuse and other risks of not living with both parents. . Ethology and sociobiology. 1985;6:197–210.
Daly & Wilson, 1988 25.Evolutionary social psychology and family homicide. . Science. 1988;242:519–524.
Dickemann, 1982 26.Commentary on John Hartung's “Polygyny and inheritance of wealth”. . Current Anthropology. 1982;23:8.
Downey, 2001 27.Number of siblings and intellectual development: The resource dilution explanation. . American Psychologist. 2001;56:497–504.
Emlen, 1995 28.An evolutionary theory of the family. . Proceedings of the National Academy of Sciences of the United States of America. 1995;92:8092–8099.
Frank, 1998 29.Foundations of social evolution. . Princeton: Princeton University Press; 1998;.
Garg & Morduch, 1998 30.Sibling rivalry and the gender gap: Evidence from child health outcomes in Ghana. . Journal of Population Economics. 1998;11:471–493.
Gibson & Mace, 2005 31.Helpful grandmothers in rural Ethiopia. . Evolution and Human Behavior. 2005;26:469–482.
Gowaty, 1993 32.Differential dispersal, local resource competition, and sex ratio variation in birds. . American Naturalist. 1993;141:263–280.
Griffin et al., 2004 33.Cooperation and competition in pathogenic bacteria. . Nature. 2004;430:1024–1027.
Gurven et al., 2001 34.Reservation food sharing among the Ache of Paraguay. . Human Nature. 2001;12:273–297.
Gutierrez, 2002 35.Parametric frailty and shared frailty survival models. . Stata Journal. 2002;2:22–44.
Hadley, 2004 36.The costs and benefits of kin: Kin networks and children's health among the Pimbwe of Tanzania. . Human Nature. 2004;15:377–395.
Hames & Draper, 2004 37.Women's work, child care, and helpers-at-the-nest in a hunter–gatherer society. . Human Nature. 2004;15:319–341.
Hamilton, 1964 38.The genetical evolution of social behavior, I and II. . Journal of Theoretical Biology. 1964;7:1–52.
Hamilton, 1967 39.Extraordinary sex ratios. . Science. 1967;156:477–488.
Hertwig et al., 2002 40.Parental investment: How an equity motive can produce inequality. . Psychological Bulletin. 2002;128:728–745.
Hill & Hurtado, 1996 41.Aché life history: The ecology and demography of a foraging people. Foundations of human behavior. . New York: Aldine de Gruyter; 1996;.
Hrdy, 2005 42.Cooperative breeders with an ace in the hole. . In: Voland E, Chasiotis A, Schiefenhoevel W editor. Grandmotherhood: The evolutionary significance of the second half of female life. New Brunswick: Rutgers University Press; 2005;p. 295–317.
Hrdy & Judge, 1993 43.Darwin and the puzzle of primogeniture—An essay on biases in parental investment after death. . Human Nature. 1993;4:1–45.
Hughes, 1986 44.Kin coalitions and social dominance. . Journal of Theoretical Biology. 1986;123:55–66.
Jones, 2000 45.Group nepotism and human kinship. . Current Anthropology. 2000;41:779–809.
Johnstone, 2000 46.Models of reproductive skew: A review and synthesis. . Ethology. 2000;106:5–26.
Kaplan & Lancaster, 2003 47.An evolutionary and ecological analysis of human fertility, mating patterns, and parental investment. . In: Wachter KW, Bulatao RA editor. Offspring: Human fertility behavior in biodemographic perspective. Washington, DC: National Academies Press; 2003;p. 170–223.
Keller & Reeve, 1994 48.Partitioning reproduction in animal societies. . Trends in Ecology & Evolution. 1994;9:98–102.
Knodel et al., 1990 49.Family size and the education of children in the context of rapid fertility decline. . Population and Development Review. 1990;16:31–62.
Leonetti et al., 2005 50.Kinship organization and grandmother's impact on reproductive success among the matrilineal Khasi and patrilineal Bengali of N.E. India. . In: Voland E, Chasiotis A, Schiefenhoevel W editor. Grandmotherhood: The evolutionary significance of the second half of the female life. New Brunswick: Rutgers University Press; 2005;p. 194–204.
Low, 1994 51.Men in the demographic transition. . Human Nature. 1994;5:223–253.
Lycett et al., 2000 52.Longevity and the costs of reproduction in a historical human population. . Proceedings of the Royal Society of London. Series B. 2000;267:31–35.
Mace, 1996 53.Biased parental investment and reproductive success in Gabbra pastoralists. . Behavioral Ecology and Sociobiology. 1996;38:75–81.
Manners, 1967 54.The Kipsigis of Kenya: Culture change in a “model” East African tribe. . In: Steward J editors. Contemporary change in traditional societies. Vol. 1:Urbana: University of Illinois Press; 1967;p. 207–359.
Munshi & Rosenzweig, 2005 55.Economic development and the decline of rural and urban community-based networks. . Economics of Transition. 2005;13:427–443.
Mwanza, 1977 56.A history of the Kipsigis. . Nairobi: East African Literature Bureau; 1977;.
Orchardson, 1961 57.The Kipsigis. . Nairobi: Kenya Literature Bureau; 1961;.
Parish & Willis, 1994 58.Daughters, education and family budgets: Taiwan experiences. . Journal of Human Resources. 1994;28:862–898.
Peristiany, 1939 59.The social institutions of the Kipsigis. . Oxford: Oxford University Press; 1939;.
Quinlan, 2005 60.Kinship, sex, and fitness in a Caribbean community. . Human Nature. 2005;16:32–57.
Radcliffe-Brown & Forde, 1950 61.In: Radcliffe-Brown AR, Forde D editor. African systems of kinship and marriage. London: Oxford University Press; 1950;.
Rutstein, 1984 62.Infant and child morality: Levels, trends and demographic differentials. World Fertility Survey Comparative Studies No. 43. . Voorburg, Netherlands: International Statistical Institute; 1984;.
Rutstein, 2000 63.Factors associated with trends in infant and child mortality in developing countries during the 1990s. . Bulletin of the World Health Association. 2000;78:1256–1270.
Sear & Mace, 2006 64.Sear, R., & Mace, R. (2007). Evolution and the human family: A review of the evidence. Evolution and Human Behavior, in press.
Sear et al., 2003 65.The effects of kin of female fertility in rural Gambia. . Evolution and Human Behavior. 2003;24:25–42.
Sear et al., 2002 66.The effects of kin on child mortality in rural Gambia. . Demography. 2002;39:43–63.
Shenk, 2005 67.Kin investment in wage-labor economies: Effects on child and marriage outcomes. . Human Nature. 2005;16:81–114.
Stack, 1997 68.All our kin. . New York: Basic Books; 1997;.
Voland, 1988 69.Differential infant and child mortality in evolutionary perspective; data from late 17th to 19th century Ostfriesland (Germany). . In: Betzig L, Borgerhoff Mulder M, Turke PW editor. Human reproductive behaviour: A Darwinian perspective. Cambridge: Cambridge University Press; 1988;p. 253–261.
Voland & Dunbar, 1995 70.Resource competition and reproduction: The relationship between economic and parental strategies in the Krummhorn population (1720–1874). . Human Nature. 1995;6:33–49.
West et al., 2001 71.Testing Hamilton's rule with competition between relatives. . Nature. 2001;409:510–513.
Wilson, 1975 72.Sociobiology: The new synthesis. . Cambridge, MA: Belknap Press; 1975;.
Department of Anthropology/Center for Population Biology/Graduate Group in Ecology, University of California at Davis, Davis, CA 95616, USA
☆ Fieldwork was funded by the National Geographic Society. Additional funding for analysis came from the University of California at Davis.
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