Bushman birth spacing: Direct tests of some simple predictions

Bushman Birth Spacing: Direct Tests of Some Simple Predictions Nicholas

Blurton Jones

Graduate School of Education and Departments Psychiatry, University of California Los Angeles

of Anthropology

and

Blurton Jones and Sibly (1978) developed a model of costs (weight of food and baby carried while foraging) of !Kung women’s reproduction under ecological-economic constraints that were described by Lee (1972). Predictions are drawn from thii model and tested on Howell’s (1979) data from reproductive histories of 172 individual women. Women were rated on a scaie of dependence on bush or cattiepost foods. The ratings were compared with what is known about the places at which the women gave birth to their children. Agreement was good and the population was divided into two groups for study: 65 women most dependent on bush foods and 70 women substantially dependent on agricuhurai produce. Thirty-seven women of uncertain or intermediate status were omitted. As predicted by the model, among the women who were dependent on bush foods: (1) first interbirth intervals (IBI) were shorter than were later IBI; (2) the survivorship of children in fmt IBIS was not strongly related to length of IBI, with shorter IBI giving as good survivorship as longer IBI; (3) IBIS lengthen as the number of surviving children increases, until the fourth child; (4) after the fourth child IBIS do not differ signiflcantIy although they tend to be shorter (contrary to the prediction, a nuii hypothesis whose statistical support is consequently poor); (5) for IBIS after the fmt IBI, mortality increased markedly as IBI decreased; (6) mortality was even more closely related to backloads entailed by each IBI, as calculated by Blurton Jones and Sibly (1978); (7) mortality was less closely related to backloads calculated from an alternative version of the model from which weight of food was excluded; (8) as reported by Howell (1979), a new pregnancy followed rapidly after the death of the preceedhtg child but (9) as predicted, a new pregnancy did not follow so fast after the death of older children; (10) for the cattiepost women IBIS were shorter than for women dependent mainly on bush foods; and (11) there was no significant relationship between IBI and mortality for the cattlepost women, and mortality at short IBI was lower than in bush women. The assumption that the benefit accruing from more births wiU be balanced against the costs (costs to survivorship assumed to result from the work entailed by caring for each child) was successful in giving many predictions coniirmed by the data. The significance and Ihuitations of this “optimization” study are discussed.

Received July 17, 1984; revised January 19, 1987. Address reprint requests to: Nicholas G. Blurton Jones, D.Phil., Graduate School of Education, Room 112, Moore Hall, University of California, Los Angeles, 405 Hilgard Avenue, Los Angeles, CA 90024. Ethology and Sociobiology 8: 183-203 (1987) 8 Elsevier Science Publishing Co., Inc., 1987 52 Vanderbilt Ave., New York, New York 10017

0162-3905/87/!$03.50

184

N. Blurton Jones

KEY WORDS:

Birth spacing; Hunter-gatherers;

Optimality;

Parental investment;

In-

fant mortality.

INTRODUCTION

L

ee (1972, 1979) showed that short interbirth intervals would lead to a !Kung mother carrying great weights during her walks into the bush gathering food, for instance, often having to carry two children rather than one. Lee suggested that the wide (4 years) intervals between births [interbirth intervals (IBI), i.e., the time between the birth of one child to a woman and the birth of her next child, further defined in the section on The Sample of Interbirth Intervals] of the !Kung were in some sense an adaptive response, keeping the mother’s work load acceptably low (particularly the work involved in carrying babies) since if birth is delayed the older child will be of an age when it can walk or be left at home. Blurton Jones and Sibly (1978) (“BJ&S”) extended Lee’s analysis by adding to Lee’s computation the weight of food gathered to support the number of children that result from different IBI. Lee had computed weight of baby and proportion of time it was carried, for children of different ages. BJ&S used this, and other data of Lee’s on weights and nutritional values of !Kung foods. Food turns out to be an important component of mother’s load and this analysis strengthened Lee’s original conclusion that shorter IBIS entail significantly greater amounts of work for the mother [Figure 4 in Blurton Jones and Sibly (1978), reprinted as Figure 1 in Blurton Jones (1986)]. A woman who has a baby every 2 years not only will sometimes be carrying two children but will also soon have more children to feed and thus a bigger weight of food to gather and carry home than will a woman who has a child every 5 years. I use the term “backload” to denote the weight of baby and food that the BJ&S model predicts a woman will have to carry home from her trip into the bush to gather food, if she adheres to a particular interbirth interval. Blurton Jones and Sibly proposed that increased work for mother might lead to increased risk of mortality for mother, or, if she avoided this, a shortfall of food for her family and increased mortality of children. They then discussed whether the long IBI might also be adaptive in the strict sense of evolutionary biology. Since an adaptive trait is one that leaves more descendents than an alternative trait, long IBIS would appear maladaptive, giving fewer births. However, if short IBIS were accompanied by very high mortality of children or parents they would lead to fewer descendants than would longer interbirth intervals. Thus there would be some optimal IBI that leaves most descendants. BJ&S, noting the sharp upturn in predicted backload when there are less than 4 years between births, suggested that the observed mean IBI of somewhere about 4 years might be that optimum.

Bushman Birth Spacing

185

In a previous paper (Blurton Jones 1986) I reported a test for optimal IBI using Howell’s data that seems to confirm that IBIS of around 4 years do maximize the yield of surviving teenagers. If we continue to propose that !Kung women and their reproductive systems maximize reproductive success, then the BJ&S model allows several more predictions. In this report I describe direct tests of these predictions, again using Howell’s reproductive histories of actual women, Adaptationist interpretations of demographic data are rare, and there seem to be no other models that have been developed to predict human reproductive performance from an adaptationist perspective. Therefore, this approach must be considered exploratory, being able to take guidance only from models of optimization of reproductive schedules in animals (e.g., Lack 1966; Pert-ins 1965, 1979). This “adaptationist” approach concerns consequences of performance, not proximate, physiological causes. It is assumed that the proximate causal mechanisms will be capable of producing on adaptive response to a range of circumstances. Thus neither this paper nor that of Blurton Jones (1986) or Blurton Jones and Sibly (1978) is intended to address the physiological mechanisms by which long IBIS are achieved. Nowhere do we suggest that backload is a direct, physiological cause of reduced fertility; rather we suggest that it is a consequence of having children that might in turn influence mortality, with mortality determining what IBI is the most adaptive IBI. The physiological mechanisms influencing fertility and birth spacing have been studied by Konner and Worthman (1980), Howie and McNeilly (1982) and elsewhere, and others reviewed by Short (1983) and in Dobbing (1985). Possible effects of mother’s nutritional status continue to be investigated (Dobbing 1985). Effects of exercise on reproductive cycles has been related to anthropological evidence by Bentley (1985), Graham (1985), and Peacock (1985). Research on mechanisms is progressing rapidly with the use of radioimmunoassay measurements of endocrine performance (Ellison et al., in press). I have worked in isolation from most of the physiological research, and my predictions were mostly made from BJ&S, before I had access to Howell’s data. Bentley (1985) presented the argument that a mother’s energy expenditure might indeed have direct physiological influences on fecundability. Thus there might be a direct route by which backload influences birth intervals. My concern with costs and adaptiveness can be viewed as a concern with why Bentley’s might be an adaptive mechanism to evolve.

THE PREDICTIONS The proposition in Blurton Jones and Sibly’s model was that as backload increased so the probability of mortality to offspring and/or mother increased. Thus differences in backload between one IBI and another led us

186

N. Blurton Jones

to expect differences in mortality, or compensatory adjustments to IBI. For instance, the BJ&S model shows that backload would be very low between first and second birth (when there are no older children for whom to bring food) compared to later births. This first interbirth interval can be shortened considerably before backload reaches the levels that characterize later intervals. Thus we expect to find that for first intervals there is no clear relationship of mortality to interval length, or that mortality is lower than for comparably short later intervals. Also, if the reproductive system is maximizing number of surviving offspring, then we expect it to shorten the first interval, gaining time at little cost in mortality. In making these predictions I have treated length of reproductive career as a constant. Of course it varies. My assumption is that it can vary independently of IBI. Whatever the length of career, more or fewer births, with more or less mortality, can be fitted into the years available. There may be other ways in which length of career is actually related to IBI and survivorship but we will not examine them here. Some of the predictions were stated in Blurton Jones and Sibly (1978); others, stated here for the first time, are clearly implicit in the 1978 paper. Some, such as “replacement” and lengthening IBI as family size increases (which may translate into a decline in fertility with age), are already described from several populations. One “prediction” was already demonstrated by Lee (1972)-the shorter IBI of women who settle at the cattleposts-but this finding has been contradicted for a slightly different sample by Harpending and Wansnider (1982). Hat-pending and Wansnider reported that Ghanzi cattlepost women (more settled and longer settled than Ngamiland cattlepost women) had lower mortality among their children. Because we share his emphasis on the constraints due to the loads carried by women, our expectation is that Lee should be right on this issue. Eleven predictions were derived from the model. Two of them concern the first IBI, as outlined above: 1. First intervals should be short. 2. These short intervals should not carry the penalty of mortality found in short later IBIS, and thus the survivorship of the children of first intervals should be less strongly influenced by the length of the interval. Figure 2 in Blurton Jones and Sibly (1978) shows that backload should increase with parity, up to the fourth child, and then remain fairly constant. This is because from the first to the fourth birth the mother carries home food for more children (so long as they have survived). After the fourth birth the first child is assumed to have become self-sufficient, and the mother no longer carries its food. According to the ethnographies, !Kung teenagers are not significant providers of food, so the teenager then drops out of the model. One may wonder why the teenager does not do more to help raise its younger siblings. We return to this issue in the Discussion section. Lengthening each

Bushman Birth Spacing

187

IBI can reduce this increase in backload (and the presumed costs), and thus we predict that 3. As the family grows from the first surviving child to four surviving children, IBIS should get longer. 4. After that point they should stay the same. Figure 3 in Blurton Jones and Sibly (1978) shows that backload climbs rapidly as interbirth interval shortens. Thus, 5. For intervals after the first interval, we expect mortality to increase as interbirth interval shortens. There should be a strong association between IBI and mortality (even when we remove “replacement” intervals from the sample). 6. If backload is as important as Blurton Jones and Sibly imply, then observed mortality will be associated more strongly with backload calculated to be required by each IBI than with IBI itself. To test the importance of the weight of food as a cost of rearing !Kung children, the BJ&S model can be run with weight of food omitted. The curves that result from this differ from those produced by the full model. Backload does not climb so steeply as IBI decreases. Thus the next prediction is that 7. Observed mortality will relate less closely to backload predicted version of the model that ignores weight of food.

by the

Some short interbirth intervals will be results of mortality and not causes of mortality. Howell (1979) showed that pregnancy usually occurred quickly after the death of a baby. This is an efficient response because less time is lost (a smaller proportion of the total reproductive career). But the backload model adds the view that an older child cannot be replaced-only the most recent child can be replaced. We have two predictions. One is that the death of the current infant will lead to a shortened interbirth interval, and the other is that the death of the child born previous to the current infant will not lead to such a greatly shortened interval. This is because the loss of the previous child saves only the weight of its food (but unlike first intervals may still leave the mother carrying food for older children), whereas the loss of the current infant saves the weight of baby carried plus the food needed to support lactation. Thus we predict that 8. Shorter IBI will follow death of the latest baby. 9. A shortened current IBI will not follow from the death of a previous child. A further prediction [the one already confirmed by Lee (1972) but contradicted by Hat-pending and Wansnider (1982)] is that women with a more settled, or cattlepost-dependent life, using nonbush resources, will be able to avoid the constraints of the BJ&S model, and thus 10. Interbirth intervals will be shorter among cattlepost dwelling women [as reported by Lee (1972)].

women than bush-

188

N. Blurton Jones

11. The relationship of mortality to IBI will be less sharp, and the child mortality of short IBI will be lower for cattlepost women than for forager women. Some of these predictions differ slightly from the population figures reported by Howell (1979) (e.g., length of first interval). It is important to realize that Howell was giving a demographic account of the whole population. In contrast the predictions from BJ&S concern specific detailed comparisons, e.g., between first and later IBIS of women living as foragers, and between IBIS of women who are living purely as foragers and women who are largely dependent on cattlepost food sources. In the appendix I present some comparisons that show that there is no contradiction between my analysis and Howell’s analysis.

THE SAMPLE POPULATIONS One hundred seventy-two women were classified according to their subsistence economy as described in Blur-ton Jones (1986). These classifications were completed before any analysis of IBI began. Some cases remained difficult to classify with any confidence. These 37 were omitted of our analyses. There was a predominantly bush food group of 65 women, and a predominantly cattlepost group of 70 women. These samples differ in age, and this has to be remembered in our comparison of bush and cattlepost people. Fewer of the cattlepost people had reached 45 years of age, and they were still of reproductive age. If IBIS are longer in older women we would obtain artificially enlarged differences between bush and cattlepost IBI. Consequently for this comparison we took only IBIS up to and including the third from the bush women’s histories, and up to the fourth IBI of the cattlepost women. This is the most cautious comparison for testing our prediction. To use all the intervals from the bush women would risk a false confirmation of our prediction. Howell (1979) reported a secular trend in infant and child mortality. So I selected a yet smaller control group from the bush-living !Kung for comparison with cattlepost people. Most of the cattlepost women were born after 1920, so I took bush women born after 1920 for further comparison with cattlepost women. This leaves a very small sample (n = 16 intervals), as most bush-living women were born before 1920. This small sample is adequate for comparing lengths of intervals but it is very small for a comparison of rates of mortality between the children of cattlepost and bush women.

The Sample of Interbirth Intervals The methods by which the data were collected were described in detail by Howell (1979). Questions about Howell’s original methods were discussed

Bushman Birth Spacing

189

in Blurton Jones (1986), where I concluded that the difficulties introduce noise and not bias. This analysis was done from Howell’s data sheets. The sheets contain a summary of each woman’s reproductive history and include reported season of birth and calculated year of birth. From these I counted the length of interbirth intervals, with help, guidance, and some independent checks from Howell. These data sheets also show whether each child survived or died, and if it died when, and the time of the last record of the child being alive. Three cases were omitted because they may have died just before or just after the next pregnancy began. The methods for measuring and categorizing interbirth intervals was the same as in Blurton Jones (1986). By IBI I mean the time from one birth to the next birth by the same woman. IBIS were worked out from the calculated year of birth and the mother’s report of the season of birth, and recorded in months, Because the field data have their obvious limits, IBIS congregate around the year points. Consequently when data were grouped it was in lyear blocks centered on 24, 36, 48, and 60 months, etc. A child may die soon after birth, or it may survive into adulthood and old age. Howell’s analyses showed that if a child survives past 10 years of age its chances of surviving to adulthood are good. I thus took survival to 10 years of age as a criterion for successful child rearing. A child who survived to 10 years is treated as a gain to mothers reproductive success. A child who died before the age of 10 years was not a gain. Such a child also represents a loss of time and effort. An interval was characterized as a “success” if it added one more live teenager to the family, or as a “failure” if either or both of the children delineating an interval died. Each interval was designated as “replacement,” “first,” or “later.” First interval in this case means the interval after the first child that a woman bears that survives at least until the next birth to that woman. Since the backload model predicts that backloads will be lower (and less affected by IBI) for first intervals than later intervals, first intervals and later intervals are treated as separate groups. The way first intervals are defined is specially tailored to our prediction. The prediction derives from the discovery that even if the first child survives, the loads of baby and food that mother has to carry are not very great even when there is a short interval to the next birth, nor do they appear to change much as IBI shortens. In a woman’s reproductive career there may be one or more intervals in which the first child dies before the next pregnancy. These are often short, but we cannot claim that their shortness has anything to do with our prediction about first intervals. Thus our attending to the interval after the birth of the first survivor is a fairer and tougher test of our prediction about first IBI. “Replacement” intervals (when the first child dies before the next pregnancy; Fig. 1E) are also separated for this analysis, because it seems clear that in these intervals mortality determines the interval and not vice versa.

190

N. Blurton Jones

Figure 1A"Succers" ChildA

Born <

ChildB

Born < 4

IB!

>

Stiff alive affer10years

>

Still alive after10 years

*

Still alive after10 years

f

Diesbefore 10yearsold

>

Dies before IOyears aid

>

Still alive after 10 years

_,

Diesbefore xlyearsold

*

Diesbefore 10yearsold

>

Figure1B 'Tailwe“ ChildA

8om

<

ChildB

Born 4 4

IBf

>

FigureKC “Failure" ChildA

Born f

Child6

Born F *

IBI

>

FigureID "Failure" ChildA

&ml

-

Child8

tml

c

IBI

f

F

Figure 1’6 “Replacement”

Child A

Born

+-----+

Dies

Child B

+-----4

Criterion period

12 months or more >

<

IBI

Born 6-4

Figure 1F “It31 Following Death of an Older Child” Child A

Born

Child B

-S----S

Dies >

Born 45

Child C

M

Criterion period

12 months or more <

lBl FIGURE I.

Categories

of inter-birth

Born +--+

> interval.

Bushman Birth Spacing

Table 1. IBI

191

First IBI. Bush Sample. Total

Failures

Successes

Percent Success

;:8-29)

12

8

4

33.3

$0-41)

16

9

I

43.7

48 (42-53) 60 (54-65) 72 (66-77) (8748-89)

10

6

4

40

9

5

4

44.4

4

1

3

75

2

1

1

50

gO-101)

1

0

1

100

108

3

1

2

66.6

57

31

26

45.6

An additional group was separated just for comparison with the “replacement” intervals. I looked for instances where an older child died after its next sibling had been born, and measured the IBI between this younger sibling and the next birth (Fig. 1F). I did this in order to see whether loss of an older child, no longer carried but still fed by mother’s foraging, had a different effect on length of IBI. There is a possible bias arising from these procedures that should be discussed. Mortality rates decline rapidly from infancy to childhood. More l-year olds die than 3- and 4-year olds. There will usually not be another birth by the time the l-year old dies, and so the interval will fall into the replacement category. This might mean that short intervals are underrepresented in the nonreplacement category. Only those few 3- and 4-year olds who die will qualify the interval that follows their birth as a nonreplacement interval that fails. The sample of losses of the older child caused by IBIS could be biased towards long IBIS. Since most of my predictions assume that losses will be associated with short IBIS this bias works against the predicted findings. Disregarding this bias is thus a conservative approach to testing the predictions. Figure 1 represents the categories of interbirth interval distinguished in this study and allows us to define the source of each column in Tables l6. Time travels from left to right across the diagrams. Figure 1A shows a nonreplacement IBI. Child B is born after child A is born and while child A is still alive. If both children live to 10 years of age or more this interval will be classified as a “success” and will add to the count in, for example, column 4 of Tables l-3. Figure lB-ID show the pattern that I treated as providing data about influences of IBI upon death of children (in contrast to Fig. lE, in which it

192

N. Blurton Jones

Table 2.

Later IBI. Bush Sample Failures

Successes

Percent Success

IBI

Total

24 (18-29)

6

5

1

16.7

23

14

9

39.1

29

13

16

55.2

16

7

9

56.2

6

0

6

100.0

7

0

7

100.0

2

0

2

100.0

7

4

3

42.8

96

43

53

55.2

::0-41) 48 (42-53) g-65) ;kJ-77) (8748-89) 96 (90-101) 108 (102Total

)

is more likely that IBI was influenced by the death of the child). Child A is born and lives some years. Child B is born while child A is still alive. The IBI is the time between the two births and it can be very short or very long. Then either or both of the children dies at less than 10 years of age. This IBI then adds to the count of “failures, ” intervals that failed to add a survivor to the family. It will add to the count in column 3 of Tables 1-3. Figure 1E shows a replacement IBI. Child A is born and then dies before its mother is pregnant with her next child. I adopted a cautious criterion for “before.” The death had to occur 12 months or more before the birth, to cover pregnancy plus a margin of error. For a death to be categorized as

Table 3.

Cattle People. Later IBI

IBI

Total

Failures

Successes

Percent Success

:f8-29,

6

2

4

66.6

::0-41)

13

6

7

53.8

48 (42-53) 60 (54-65) 72 (66-77) ;;8-89)

9

1

8

88.9

2

0

2

100.0

1

1

0

0

0

0

0

~~0-101~

1

0

1

100.0

2

0

2

100.0

34

IO

24

70.6

108 (102Total

-

)

Bushman Birth Spacing

193

after the next pregnancy it had to occur after the next birth, unless it was recorded that the mother said clearly that the baby died after she was already pregnant with her next child. These harsh criteria led to the exclusion of only three intervals from the analyses. Figure 1F shows the other category that I compared with replacement intervals. Child A is born and lives a few years. Child B is born while child A is still alive. Child A then dies before its mother is pregnant with child C (again “before” means 12 months or more before the birth of child C). I examined the interval between the birth of child B and the birth of child C to compare them with “replacement” intervals as defined in Figure 1E.

RESULTS Length of the First Interbirth Interval The mode of first intervals is 36 months, and the next most frequent interval is 24 months. This contrasts with 48 and 36 months for later IBIS (Tables 1 and 2). The mean for first intervals is 45 months, and for later intervals 55 months. However, while the later intervals approximate a normal distribution the first intervals clearly do not, being piled up at the low end. That the first intervals are shorter than the later intervals is confirmed by the Mann-Whitney U test, which with Ni = 96 and N2 = 57 gives z = 2.38, p = 0.0087.

Mortality and IBI in First Intervals As predicted, the relationship of length of first interval to mortality seems to be very slight (Table 1). Comparing deaths and survivals from intervals of less than 42 months with longer intervals we find no significant relationship for the first intervals (medians test, Fisher’s exact test, p = 0.168), whereas we have a clear relationship for later intervals (see below). A logistic regression also shows no significant relationship of mortality to length of first IBI (x2 to enter = 1.40, df = 1, p = 0.236). If the data on first IBI are split at 53 months (i.e., not adhering to the normal procedure of the medians test) or if a nonparametric test is used a significant difference can be obtained (Spearman’s r = 0.86, N = 8, p = 0.01). Thus contrary to the prediction, there may be some relationship of mortality to IBI for the first intervals, but it is not statistically significant.

Length of IBI as Number of Surviving Children Accumulates Interbirth intervals that follow the birth of a second child (when one previous child is still alive) are longer than the first IBI (Wilcoxon signed pairs test, 23 second intervals longer, 16 shorter, one tailed, p = 0.035). IBIS that follow

194

N. Blurton Jones

the birth of a third child (when two previous children have survived) are longer than the “second” IBI (Wilcoxon test, 26 third intervals longer, 9 shorter, one tailed, p = 0.0015). In other words, as predicted, IBIS become longer up to the birth of the fourth surviving child.

Subsequent

IBIS

When four children still survive, subsequents IBIS were expected to be the same length as the previous IBI. The proposed hypothesis is a null hypothesis that would be disproved if the intervals were either shorter or longer. The IBIS when four children survive were in fact more often shorter than the preceding IBI (12 shorter, 5 longer, sign test, two tailed, p = 0.144, Wilcoxon test, two tailed, p = 0.170). This result is far from significant and we could conclude that the prediction was confirmed. However, with this small sample size, just one fewer case in which the later interval was longer would give a significant departure from the null hypothesis. The test is thus not powerful and while my prediction is not disproved it clearly receives only very weak support. Howell (1979) shows that few women had any more children after this point. If we included the “infinite” IBI after the final child in the woman’s reproductive career then these later IBIS tend to be much longer than earlier ones (Howell 1979, p. 151, Figure 7.4). I cannot claim that this prediction was convincingly fulfilled, nor clearly disproved.

Later Intervals:

Mortality and IBI

Logistic regression of the original ungrouped data summarized in Table 2 confirmed that IBI and mortality were strongly associated (x2 = 10.23, df = 1, p = 0.001). For the grouped data only curvilinear relationships between mortality and IBI reach significance. Further analysis of this relationship was reported in Blurton Jones 1986. For the purpose of this prediction both analyses show the predicted decrease in mortality at longer IBI.

Backload and Mortality A plot of the raw data and a plot of a running average of mortality against IBI suggest that mortality follows a curve remarkably close to the curve of backload calculated by BJ&S. Rather than trying to fit complex curves to the relationship of mortality to IBI, a simple way to test the fit with the BJ&S-calculated backload curve is to test for a linear relationship of mortality against calculated backload (as reported in Blurton Jones 1986). If mortality does follow the curve of calculated backload against IBI, then mortality should be linearly related to calculated backload. This can be tested with logistic regression. The prediction of mortality from calculated backload is very good (x2

Bushman Birth Spacing

Table 4.

IBI

Length of Replacement

Intervals,

Nonreplacement Intervals (Figs. IA-1C)

Compared

Replacement Interval (Fig. 1E)

195

to Other Intervals IBI Following Death of Older Child (Fig. 1F)

Time from Death of B to Next Birth

0

1

0

6

$3-29)

6

7

0

14

::0-41)

23

12

2

13

48 (42-53) ;4-65)

29

10

3

7

16

7

6

0

:626-77)

6

3

2

0

:;8-89)

7

0

2

0

96 (90-101) 108 (102) Total

2

0

1

0

7

0

1

0

96

40

17

40

to enter = 15.47, df = 1, p < 0.0001; Hosmer goodness of tit x2 = 7.35, df = 8, p = 0.50, a good fit). The significance and goodness of fit is rather better than from IBI itself (discussed further in Blurton Jones 1986).

Backload Without Food The prediction of mortality from backload calculated by the version of the model that excludes weight of food was less good (logistic regression: x2 to enter = 12.51, df = 1, p = 0.0004; Hosmer goodness of fit x2 = 6.31, df = 3, p = 0.09, a poor fit). A stepwise regression shows that the “no-food” model fails to remove the contribution of the “with-food” model to predicting success or failure of an interval.

Replacement

Births

Pregnancies that follow the death of the current infant come sooner after the previous birth than do pregnancies that occur while the latest child still lives (Table 4, U test N1 = 40, N2 = 96, z = 2.78, p = 0.0027) (comparing IBI in Fig. 1E with IBI in Figs. lA-IC). Births followed very rapidly after the death of the current infant (Table 4, column 5, median 24 months).

Replacement Child

Compared to IBI Following Death of an Older

Interbirth intervals following the death of a child who is not the current infant were significantly longer than intervals in which the current infant

196

N. Blurton Jones

Table 5.

Mortality for IBI of up to 42 MonthP

Failures Cattlepost Bush y Fisher’s

8 19

Successes 11 10

exact test, p = 0.068.

died before the next pregnancy (Fig. 1F versus 1E; Table 4, column 4, U test, N1 = 17, N2 = 40, z = 2.84, p = 0.0023). The 17 intervals of this type were no different in duration from “control” intervals (Figs. lA-ID).

Cattlepost

People: Length of IBI

The distribution of interbirth intervals for cattlepost people is shown in Table 3. The U test shows that cattlepost people have significantly shorter intervals than do the bush controls (N, = 34, NZ = 42, z = 2.76, p < 0.01). The IBI of the bush controls are indistinguishable from the whole bush sample. The small subsample that controls for the secular trend (bush-food women born after 1920) shows the same result. Their interbirth intervals are longer than those of the cattlepost women (U test, Ni = 34, N2 = 16, z = 2.84, p < 0.01).

Cattlepost

People: Mortality and IBI

Among the cattlepost people there is no significant relationship of IBI to mortality (logistic regression, x2 to enter = 0.51, df = 1, p = 0.4683). Mortality may actually be lower in the cattlepost people. Although’the difference is not significant when we compare totals in Tables 2 and 3, if we compare shorter IBI there is a marginally significantly lower mortality for cattlepost children (Fisher’s exact test, p = 0.068) (Table 5).

DISCUSSION The assumptions (1) that the reproductive system maximizes descendants by balancing the benelit of more births against the costs of mortality, and (2) that infant mortality is related to mother’s backload, produced 11 predictions. Ten were fulfilled. Such success is unlikely if the propositions that number of descendants was being maximized, and that backload was a good reflection of the costs, were untrue. But this apparent success needs to be examined carefully. Because the subjects of this study were people, and because the issue of whether people maximize reproductive success is controversial, we may be inclined to interpret the results as a demonstration that the human reproductive system does maximize reproductive success. However, it is prob-

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ably more productive to take the framework suggested by Maynard-Smith (1978) for animal optimization studies. He suggests that we seldom question, and anyway can seldom prove, adaptiveness or that organisms mazimize fitness. We should use the fit between predicted optimal performance and actual performance in order to judge the extent to which the model that we used captures the actual costs and benefits of the performance, the factors influencing these costs and benefits, and the way in which they interact. In this framework the present study suggests that the BJ&S backload model has quite successful1 identified a major component of costs of child rearing for the Dobe !Kung. However, several of the findings are known from other populations, and thus might have been expected in this one [see reviews in Howell (1979), Scrimshaw (1982), and Handwerker (1983)l. Examples are “replacement,” and changes in IBI with family size, which might be “explained” as a result of age changes in fertility, even though generalizing from one population to another is not an explanation. To discuss alternative theories in full would take too much space, but “replacement” and “target fertility” seem unlikely to predict all these findings. An alternative version of the backload model, with weight of food removed, gave different predictions, and these fit the data less well. However, the most stringent test of both the model and the approach concerns prediction to different populations and different circumstances. The greatest attraction of the cost-benefit, maximization approach is its promise for predicting performance in circumstances different from those studied. The predictions about IBI and mortality for cattlepost !Kung are of this sort. But more valuable would be predictions to other populations from whom the data are not yet available. I will make such predictions, partly in order to illustrate the hazards, and partly in order to discuss the strengths and weaknesses of the BJ&S model. BJ&S was developed from data very specific to !Kung ecology. Can this model apply to other populations? Although much of the numerical data that went into the model are specific to !Kung ecology the predictions are actually derived from features of the model that are completely general. The predictions depend on (1) the shape and dimensions of the curve of costs of rearing a child (which in this case is the calculated backload curve), (2) the assumption that these costs are additive (the current cost of one child is added to the current cost of another child), and (3) the assumption that the costs are a cost to fitness and therefore must be offset against the benefits of more births. Many aspects of mother’s work and ecology might fit these assumptions and give a curve similar to the BJ&S curve. Indeed, any curve of costs that resembled the original BJ&S backload curve for a single child and its food and its mother’s food (BJ&S, Figure I), would give the same predictions. Then we could obtain false confirmations of our predictions: the prediction might be successful because costs other than those examined gave the same shaped curve as was used to make the predictions.

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One way to explore this issue is to discuss predictions for populations that seem to resemble the !Kung in many aspects of ecology: mobility, hunting by men, gathering by women, and women carrying small babies and food. One could make a prediction for the Hadza, hunter-gatherers in African savanna like the !Kung but in an area with more abundant game and an apparently easier life (Woodburn 1968) and whose women walk less far and carry smaller loads [comparing Vincent (1985) with Lee (1972)]. The less intense work associated with women’s gathering leads me to expect lower backloads of food (and perhaps of baby since babysitting may be more available for the short duration of many Hadza foraging trips). This in turn leads us to expect shorter IBIS and less lengthening of IBI as family size increases. Efforts to gather the demographic data to test this prediction have so far been frustrated. We might think the same predictions reasonable for hunter-gatherers in which women simply contribute less of the food, such as the Ache. It seems as if they may indeed fit the expectation of shorter IBI or greater fertility (Hill and Kaplan, in preparation). But do we really know that the costs of child rearing are lower for Ache women than for !Kung women, and what about all the other possible costs of raising a child that an overzealous application of the BJ&S model could lead us to ignore? The situation becomes even more uncertain when we consider the Agta. Agta women bear children to a greater age than !Kung women (Goodman et al. 1985). But Agta women are reported to hunt. Thus we cannot match their subsistence ecology to the backload model. Many would suggest that costs of raising children must be very low for Agta women to hunt at all. But in the absence of a study of costs of child rearing in the Agta we are unable to relate the Agta case to the backload model and maximization proposition. The potential for predicting performance in a variety of situations is attractive, even if fraught with problems. In studies of animal behavior the assumption of fitness maximization has aided the development of predictive models of how performance is expected to vary with circumstances. It is well worth the effort to continue exploring the ability of similar models to predict variation in human performance.

The Importance

of Babysitters

Neglect of variation in babysitting seemed to be BJ&S’s most risky a priori assumption (Blurton Jones and Sibly 1978, p. 139). The one prediction that was not clearly fulfilled, though not statistically significantly disproven, was that IBI should not change after the fourth surviving child. There appeared to be a tendency for this interval to be shorter than previous intervals. This is interesting since it may be one place where variation in supply of babysitters actually becomes the dominant effect. The BJ&S model suggests that backload should no longer climb after the fourth child because the age at

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which the first surviving child is assumed to become self-sufficient tends to coincide with this late IBI. Thus weight of food to be collected by mother no longer increases. However, the oldest child may not only become selfsufficient in food but may become a significant addition to the supply of babysitters. We have no data on amount of babysitting available to individual mothers. Thus we are unable to test this post hoc reason for our one failed prediction. Variation in babysitting (and in father’s provisioning) may of course account for much of the unexplained variance in IBI. But it is quite surprising that only in one prediction may it have overwhelmed the variation in backload costs that we have used to make our predictions. This is all the more surprising because one would not expect use of babysitters to vary orthogonally to backload. Like Peacock (1985), we might expect, and have found, that women with higher potential costs from reproduction are the ones who seek and obtain most help from other people.

The First Demographic

Transition

The slightly lower level of mortality of the cattlepost children is interesting in the light of Harpending and Wansnider’s report on the long-settled Ghanzi bushmen. These authors show that Ghanzi mortality levels are lower than those among Ngamiland !Kung. They attribute population increase on settling to lowered mortality and not to shortened intervals. Handwerker (1983) has suggested a revision of the interpretation of the neolithic population explosion on the basis of their claims, contrasting them with Lee’s (1972) evidence for shortening interbirth intervals. The results presented here suggest that these views are not to be treated as oppositions. A decline in mortality at short IBI or a flatter curve of mortality against IBI is expected to lead to more short IBI because this produces more descendants. There are serious problems with Harpending and Wansnider’s method of calculating interbirth intervals, which, when derived from population figures rather than from individual histories, fail to isolate replacement intervals and are thus artificially lengthened by lower mortality. In addition, in both bodies of data there are difficulties and puzzles related to the apparently short reproductive careers of cattlepost !Kung women. Another difficulty concerning the data on cattlepost women was pointed out by Howell (personal communication). She suggested that a woman may sometimes settle at a cattlepost because she has too many children, or too short a last IBI to survive in the bush. If this choice is available one might well expect the woman to take it. Thus short IBIS would cause people to settle, not vice versa. One might expect this argument to be least applicable to the IBIS of women who stayed at cattleposts most of their life, and most applicable to those whose births were divided between bush and cattlepost. The latter mostly fall into the group of 37 women of undetermined economic status who were left out of this study. Though the extent of the historical move from bush to cattlepost makes me think it unlikely, it remains possible

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that women of high fertility settled at cattleposts, while women of lower fertility found life better in the bush. The adaptationist perspective represented here implies that changes in IBI would be expected as a rapid response to changing circumstances of child mortality and mother’s work. The reproductive system is expected to be opportunistic, and capable of rapid response. Our evolutionary history must have consisted of numerous microdemographic transitions. The discovery of hunter-gatherer populations with higher fertility than the Dobe !Kung (e.g., Dyson 1977; Hill and Kaplan, in preparation; Goodman et al. 1985) or agricultural populations with lower fertility than the !Kung (Wood et al. 1985) should not surprise us.

How Efficient are the Physiological IBI?

Mechanisms

That Influence

This study suggests that the physiological mechanisms that control IBI are very efficient: they produce many adaptive adjustments. The best described mechanism, the effect of suckling on return of ovulation, seems able to account for much of the variation that we see. To do their job the mechanisms should respond to (1) the chance of raising a new offspring and (2) the effect of a new birth on the survivorship of the current offspring. The latter will be influenced by the vulnerability and needs of the current offspring, which we may expect to be closely reflected in its tendency to suckle. Its survivorship will also be influenced by its mother’s ability to produce enough milk, and to collect enough food to produce milk and to feed the current offspring. The chance of raising the next offspring might also be indicated by the ease with which the mother is able to gather enough food. Thus some mechanism relating the mother’s work to her fecundability would best estimate her chances of raising both the current offspring and the next offspring. However, if the mother’s work reduces her milk supply then the baby will presumably suckle more often and more vigorously. If the mother is having difficulty providing for her family and herself the baby may suckle more often (it gets less solid food, and perhaps less milk at each feed). A direct effect of the mother’s work or nutrition may be unnecessary. The suckling mechanism could cover both requirements, assessing both offspring needs and mothers work. Thinking about these aspects of the ecology of !Kung child rearing does not allow us to say with total confidence that we expect a physiological mechanism additional to the suckling mechanism. However, parent-offspring conflict theory (Trivers 1974) makes one expect that the suckling mechanism could be exploited by the offspring to mother’s disadvantage. The optimum tradeoff of risk of infant’s death against number of siblings raised is different for baby and for mother. The baby benefits more from longer IBI than does mother. Babies will be selected to exaggerate their suckling demands. Whatever adjustments to threshold are

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made in the mother’s physiology, they could still be countered by increases in the baby’s demand. Selection would favor mothers who are able to break out of this potential “arms race.” Thus the mother needs a mechanism that responds to her circumstances independently of baby’s demands. Despite all the ecological analysis, this seems to be the strongest adaptationist argument for our expecting factors additional to suckling to influence the mother’s return to ovulation.

This investigation was made possible by Nancy Howell’s generous spirit of scientific cooperation. She shared her data and her advice for an investigation from a perspective quite foreign to her own. Faults of interpretation are mine and not hers. The existence of the data is entirely her responsibility. I shared none of the endurance, persuasiveness, and meticulousness that it takes for the kind of fieldwork that Howell did and to build up the data base that she did. Richard Lee kindly helped with the classification of the women on their degree of dependence on bush or cattlepost foods. I also wish to thank for helpful discussions on statistics and other things: Drs. A. Forsyth, L. Fairbanks, R. Weigel, K. Hawkes, K. Hill, H. Kaplan, M. Hurtado, J. O’Connell, R. M. Sibly, N. Peacock, R. Bailey, P. Draper, and H. Harpending.

APPENDIX:

COMPARISONS

WITH HOWELL’S

In this appendix I dismiss some apparent search and Howell’s book (1979).

contradictions

ANALYSIS between

this re-

The Samples and Their Size Out of Howell’s 500 births to 165 women I have mainly worked on 272 births to 65 women classified as living predominantly on bush foods and 84 births to 70 women classified as living mainly on cattlepost resources. One hundred eleven births to 37 women were omitted as not clearly classified. Some births could be used by Howell but had to be left out by me because I needed to be sure that we knew whether the child had survived to 10 years of age or not. Some women had only one child and thus give us no interbirth interval to work with (this was true of more cattlepost women than bush women). Thus the differences between my sample size and Howell’s is accounted for by the unclassified women, single births, births that are too recent for me to ascertain survivorship, and my omission of cattlepost replacement births and first intervals.

The Results In my papers I attend much of the time to interbirth intervals whose mean is 55 months. Howell reported mean interbirth interval for Dobe !Kung women of completed reproduction as 4.12 years (49.44 months). There is no contradiction. My 55 months is the mean for intervals following the first live interval, that are not “replacements,” and that come only from women

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Table Al.

Comparison

Count from Raw Data Mortality up to 10 years 36.8 (131/356) Mortality to 20 years 42.4 (151/356)

of Mortality Scores in This Study and in Howell’s Study

Count from Tables

Howell Table 4.1 (loo-Lx)

40.4 (106/262)

34.2 -

-

41.7 -

whose reproductive lives were predominantly spent living on bush foods. If I add the other categories-first intervals, replacement intervals, and cattlepost and unclassified women- I get a mean from the data that I used and with my calculations of interbirth interval from the raw data, of 49.02 months. For bush-dwelling women only (few of the cattlepost women were of completed reproduction) the mean was 50.57 months. I have shown that as predicted by the backload model, first intervals following a child that survives are shorter than later intervals for bush-dwelling women. It is important to remember that my “first intervals” are intervals following the first child that survives to the next pregnancy and are contrasted with later intervals following children that survive to the next pregnancy. If I make the same comparison as Howell did, including replacement intervals, the mean is 49.01 months for first intervals compared to 50.57 for the whole bush sample, also not a significant difference. This is the same finding as Howell’s (1979, p. 134, Table 6.5). Of the 356 births used, 131 of the children died before 10 years of age. This 36.8% mortality agrees closely with Howell’s estimate. If we include children who died before they were 20 we obtain even closer agreement to Howell’s figures (Table Al). If we work from the tables that present information on survivorship and interbirth interval (and add cattlepost first births, and replacement births for cattle and bush women) we have a record of 106 children dying out of 262 births. This gives a mortality of 40.4%. This is a little higher than Howell’s figure. We might expect single births to survive well, and we might expect the unclassified people to have lower mortality than the bush people. Thus there is no good reason to think that this figure contradicts Howell’s figures. Thus there is no contradiction between my results and Howell’s results. The two analyses differ because they have different goals, each was appropriate to its goals, and each used the data accurately. Howell’s purpose was a demographic account, an aggregate description of the sort essential for, for example, forecasting changes in population. My purpose was to obtain evidence about the ecology of individual reproductive performance.

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