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Demography of the Hadza an increasing and high density population of savanna foragers.

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AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 89:159-181 (1992)
Demography of the Hadza, an Increasing and High Density
Population of Savanna Foragers
NICHOLAS G. BLURTON JONES, LARS C. SMITH,
JAMES F. OCONNELL, KRISTEN HAWKES. AND C.L. KAMUZORA
Departments of Education, Anthropology, and Psychiatry, University of
California Los Angeles, Los Angeles, California 90024-1521 (N.G.B.J.);
11 Rue Waasserklapp, L-5681, Dalheim, Luxembourg (L.C.S.);
Archaeological Center, Department of Anthropology, Uniuersity of Utah,
Snlt L u h ~City. TJtnh 841 12 fJ.F.O.’C.): Ikpnrtmmt ofAnthro.polog~,
Universitn, of Utah, Salt Lake City, Utah 84112 (K.H.1; Demography
Unit, IJniuersity of Dar es Salaam, P.O. Box 35047, Dar es Salaam,
Taiizania (C.L.K.)
KEY WORDS
Hunters and gatherers, Costs of children, Demography, Sub-Saharan Africa
ABSTRACT
This is a report on the demography of the Hadza, a population of East African hunter-gatherers. In it, we describe the results of a
census, and our estimation of age structure, survivorship, mean age of women
at childbearing, number of live children, total population size and density,
and rate of change since 1967. We show that relevant measures fit closely the
stable population model North 6 chosen by Dyson to represent Hadza demography in the 1960s.
We compare aspects of Hadza demography with surrounding non-Hadza
and with the !Kung. Among other things, we find that the Hadza have a
higher population density, higher fertility, and a faster population growth
rate than do the !Kung. These demographic differences are consistent with
our expectations, which were based on differences in the costs and benefits of
foraging in the two regions.
We also show that Hadza demographic parameters display remarkable
consistency over the past 20 years. Since neighboring populations have been
encroaching on the area used by the Hadza, and Hadza foragers have been
subject to interludes of externally imposed settlement, this consistency is
surprising. We discuss some of the implications. o 1992 Wiley-Liss, Inc.
In this paper our first aim is to present
data on the demography of the Hadza, a
hunting and gathering population of eastern
Africa. Our second and more general goal is
to contribute to inquiry into hunter gatherer
reproductive strategies and the ways in
which these may be shaped by features of
local ecology. To this end we test some simple predictions, drawn from biological principles, about differences between the Hadza
and the !Kung.
The demography of people who obtain
their food by hunting and gathering, and especially the demography of the !Kung, has
strongly influenced ideas about human pop0 1992 WILEY LISS, INC.
ulation regulation, behavior, and evolution.
The !Kung deserve attention because they
have been so well studied (e.g., Howell,
1979; Lee, 1979). But they also have been
considered important because, as foragers
in the sub-Saharan savanna, they have been
held to present the best available model of
Pleistocene forager adaptations (e.g., Lee
and DeVore, 1968). Given the shortage of
material on sub-Saharan savanna huntergatherers, it seems important to present
data on a second population.
Received February 11,1991;accepted March 19,1992.
160
N G BLURTON JONES ET AL.
Contemporary discussion of hunter-gatherer population regulation took its lead from
Birdsell (1953, 1968). Investigating the ecologically reasonable expectation that population would be linked to resources, Birdsell
showed that aboriginal Australian population densities were greater in areas of
greater rainfall. He assumed rainfall to be a
good proxy measure of resources, an assumption supported by the observations of
Coe et al. (1976). Martin and Read (1981)
obtained the same result for a small sample
of Atrican hunters and gatherers iiduJing
the Hadza. While biological anthropologists
and some demographers pursued the physiological, proximate causes of fertility (Wood
et al., 1985; Wood and Weinstein, 1988; Ellison, 1990), others continued to pursue ecological, ultimate causes. Many anthropologists followed the zeitgeist of the 1960s and
1970s towards the group function, “prudent
breeder” side of the argument among Birdsell’s biological contemporaries, and concluded that hunter-gatherers were able to
achieve zero population growth safety below
“carrying capacity,” and to receive with this
a good deal of leisure time. In biology, individual-centered adaptationist thinking prevailed, and gave rise to evolutionary or behavioral ecology. Recently this has reentered anthropology (Winterhalder and
Smith, 1981).
Subsequently, three views of modern
hunter-gatherer society and population became widely influential. One portrays them
as the “original affluent society,” unencumbered by the “infinite wants” of commercial
societies. Free of market temptations, they
want little, and so spend little time at work,
share what they have, and prudently restrain their reproduction t o remain safely
below a Malthusian equilibrium with their
resources (e.g., Sahlins, 1972; Harris, 1988:
250-251; Haviland, 1989: 363-371). The
second view portrays modern hunter-gatherers as specialized components of regional
or larger economies, whose behavior is determined by their dependence on farmers or
herders or trading involvements with the
world political economy (Headland and
Reid, 1989). They may be seen as the lowest
underclass. Dispossessed of lands and resources, and subject to fluctuating opportu-
nities for trade and employment, they are at
the bottom of a deeply stratified international economy, their behavior determined
by the exploitation of those better placed t o
gain from the world system (Schrire, 1980;
Wilmsen, 1989).
Each of these two views may serve a useful purpose, countering, on the one hand, a
notion that foraging is a poor and unsatisfying way to make a living and, on the other,
that foragers are timeless isolates who have
no neighbors and no history. But the first
implie; r; suspensior, of M d t h t l s i 3 n processes that deserves careful scrutiny. And
both these influential portraits suggest a
sameness in habits among hunter-gatherers
which available ethnography shows to be
false. Each implies that variation in patterns of living among foragers in different
places is due to differences in the temporal
depth and extent of colonial domination
(Service, 1962; Steward, 1955; Solway and
Lee, 1990).
The third view, which has provoked the
greatest body of recent quantitative fieldwork, attends to the particular features of
local plant and animal resources and the
way these alter the costs and benefits for
varying solutions to the problems of living
which people confront day by day. This view
is often characterized by predictions drawn
from models and thinking in evolutionary
ecology (Smith and Winterhalder, in press;
Hill and Hurtado 1989). and holds that people vary opportunistically in behavior ar?d
reproductive patterns, their largely culturally transmitted behavior conforming to
normal biological concepts such as adaptation. An adaptationist approach draws its
predictions by more or less rigorous argument, from the proposition that organisms
maximize fitness. For example, the combinations of fertility, offspring survivorship,
and offspring reproductive success that
maximizes lifetime reproductive success can
be examined (e.g., Smith and Fretwell,
1974; Pennington and Harpending, 1988).
In many circumstances expenditure on increased fertility will pay more than increased expenditure on offspring survivorship. Conversely, lowering fertility could
pay off in circumstances in which its beneficial effect on offspring survivorship was suf-
DEMOGRAPHY (3F THE HADW
ficiently large. We assume here that on the
whole, where it is easier to feed offspring
and thus easier t o keep them alive, lifetime
reproductive success is more likely to be
maximized by increasing fertility than
where it is difficult to feed offspring. How
much of the variation in behavior within and
between populations of hunter gatherers
can be explained by reference to differences
in these trade-offs of costs and benefits is an
empirical question.
Some of our expectations about Hadza behavior and demography, and their differences from the !Kung, stem from models
used in this third view. Using Howell’s reproductive histories, Blurton Jones (1986,
1987)has shown that in spite of the average
four-year interval between births, !Kung
women may have been maximizing the rate
at which they produced children who survived to reproductive age (Pennington and
Harpending [ 19881, who present no data on
inter-birth intervals, imply that another
component of reproductive success, the total
number of births, which is influenced by the
length of the reproductive career, must be at
least as important as inter birth interval).
Blurton Jones’s analyses showed that many
features of the birth spacing patterns made
biological sense given quite specific features
of local wild resources and their spatial distribution. A critical determinant seems to
have been the marked dependence of !Kung
children on their mothers for food, and the
great distance between niongongo nut
groves and dry season water (Blurton Jones
and Sibly, 1978).
The finding that Hadza children gather
much of their food for themselves (Blurton
Jones et al., 1989), suggests that a Hadza
woman who withholds provisioning effort
from her children in order to support another pregnancy risks their survival less
than would a !Kung woman, whose children
are entirely dependent on her and other
adults (see also Blurton Jones et al., in
press). Expecting women to maximize their
reproductive success, we then expect Hadza
women to divert effort to their next pregnancy earlier in the life of each child, and
thus to produce more children. In short we
expect the Hadza to have shorter inter birth
intervals and higher fertility than the
161
!Kung. If these expectations are met they
will add further weight to the mounting evidence that quite specific features of local
ecology have important effects on the reproductive costs and benefits of foraging and
childcare alternatives and so on the behavioral and reproductive strategies that people
display.
Furthermore, if we expect forager populations to perform according t o biological common sense, the apparently richer habitat of
the Hadza might be expected to lead to a
more dense population. If we expect forager
populations to be subject to density dependent control like many other biological populations, we should also not be surprised to
find some forager populations which are increasing, and in contrast to find others like
the apparently constant !Kung population.
Many alternative explanations for differences between the demographic parameters
of populations can be entertained. Post hoc
explanations greatly outnumber predictions. For example, Harpending and Draper
(19901, and Harpending (pers. comm.) suggest that the low fertility of the !Kung may
result from sexually transmitted diseases
(STD), and that the region of African low
fertility should be extended to enclose
Ngamiland. It would be easy to attribute differences between !Kung and Hadza fertility
to differences in STD or treatment. But in
the absence of good data on incidence of STD
and availability of antibiotics it would be
hard to raise these ideas to the level at
which predictions could be derived. Predictions can however be drawn from ecology.
THEEASTERNHADZA
The Eastern Hadza occupy a 2,500 km2
area in the Eastern Rift Valley, southeast of
Lake Eyasi (Woodburn, l964,1968a,b). This
region has a warm, dry climate, with a
marked 6-7-month rainy season (mean annual rainfall 300-600 mm [Schultz, 19711).
Much of the country is rock-strewn and
hilly. Vegetation is primarily mixed savanna woodland (Schultz, 1971); medium
and large mammals are locally abundant
(Smith, 1980).
The Hadza divide this region into several
loosely bounded units, including Mangola in
the north, Siponga in the east, Tli’ika in the
162
N G BLURTON JONES ET AL
southwest (Woodburn, 1968b). These terms
are used often in the analyses reported below.
At the time of European contact, around
the beginning of this century, the Hadza had
this country largely to themselves, according to Woodburn (1964, and references
therein). They apparently lived entirely by
hunting and gathering, except at the southwestern extreme of their range. Local incursions by non-Hadza pastoral and agricultural groups are recorded in historic times
as early ds the bagirmiilg d Lhe 20th century
(Obst, 1912), and the 1920s (Woodburn,
1964, 1988; McDowell, 1981). Archaeological evidence indicates the periodic presence
of farmers and pastoralists over several millennia (Mehlman, 1988). Non-Hadza settlement is now heaviest in Mangola and Siponga.
During the past 50 years, various segments of the Hadza population have been
subjected to a series of government- and
mission-sponsored settlement schemes designed to encourage them to abandon foraging in favor of full time farming (McDowell,
1981; Ndagala, 1988). None of these
schemes has been successful; and in every
case, most of the Hadza involved have returned to the bush, usually within a few
months. In each instance, some Hadza have
managed to avoid settlement altogether,
and continued to live as full-time huntergatherers. One settlement scheme, at Yaeda
(south Siponga), was more substantial than
most. Scores of Hadza were moved there in
1964, and many children attended the local
school. One hundred forty-two of the 380
eastern Hadza censused by Barnicot’s team
in 1967 (see next section) were at Yaeda.
The settlement broke up in the mid-1970s;
in Smith’s census in late 1977 only 35 Hadza
were living a t Yaeda, and by 1985, only
about a dozen Hadza were still living there.
Throughout this period and before, Hadza
families have also farmed at the village of
Munguli (south Tli’ika [Woodburn, 1964,
1968a; see also Cooper, 19491).A school and
clinic were built there in the 1970s by missionaries, who have since left. The village
remains a thriving community. South of
Munguli, a few Hadza live in the Isanzu village of Mwangeza.
PREVIOUS DEMOGRAPHIC WORK
AMONG THE HADZA
The Hadza were subjects of demographic,
genetic, and biometric investigation in
1966-67 as part of the International Biological Program (IBP), Human Adaptability
Project. The project was instigated and led
by Nigel Barnicot, funded by The Royal Society. As the ethnographer of the Hadza, with
several years of fieldwork behind him, the
role of James Woodburn in this fieldwork
was clearly vital to its SIICCPC‘: These inyestigators conducted a census, measured
heights and weights, estimated ages, and
collected blood, stool, dermatoglyphic and
urine samples. These data were for a time
kept as an archive a t University College
London, Anthropology Department, available to interested researchers. Publications
resulting from this work have covered topics
in anthropometry, demography, dermatoglyphics, and epidemiology (e.g., Barnicot
et al., 1972; Bennett et al., 1970, 1973; Hiernaux and Hartono, 1980).
The 1967 census data were studied by W.
Brass and Tim Dyson, whose analysis provides a basis for much of the work reported
here. In particular, Dyson used data from
women’s reproductive histories to estimate
infant mortality, and an age structure using
age estimates made in the field by Woodburn and Bennett. From these he selected a
stable population model (North, level 6,
Coale and Demeny. 1966) with similar characteristics, and then used the model to estimate fertility and mortality rates for the
population as a whole.
Lars Smith conducted a second census in
the dry season of 1977. In it, he recorded the
height, weight, approximate age, parentage,
and household affiliation of all Hadza encountered. Smith’s data on the ages of infants have proven especially useful in the
analyses described below.
METHODS
Procedures for studying demography of
small populations of people who keep no
written records have been most clearly set
out by Howell (1979). Both Howell and Dyson used stable population models in their
analyses. The use of such models has its own
DEMOGRAPHY OF THE W Z A
inherent robustness. The model populations
are those that inevitably arise from long
term persistence of given schedules of fertility and mortality. Many measures of populations are quantitatively dependent on each
other, to extents displayed in the model life
tables. For instance, a certain fertility rate,
coupled with a certain mortality rate, inevitably implies a certain rate of population increase or decrease. A certain combination of
mortality rate and fertility rate is inevitably
tied to a certain age structure. Given two or
more such parameters it is possible to select
a model and read from it several other parameters which inevitably follow from those
measured. If observed values do not approximate the expected levels, either some measure is wrong, or an assumption of the model
is seriously violated. Conversely, if several
independent measures support the same
model, we may have increased faith in their
accuracy and in the likely accuracy of other
predictions of the model.
The models assume limited migration in
or out of the population, and unchanging
levels and patterns of age specific fertility
and mortality. In reality these must vary to
greater or lesser extents but if they do not
vary too much, nor vary in a consistent direction we may expect the models to perform
adequately. Commenting on departures between observed and modeled values, Howell
remarks that “the vital rates in the stable
population model should be expected t,o
characterize not a particular year, but
rather a much longer period, perhaps as
long as a century. The stable population
model, then, should describe the population
on the average over many points of time, but
not at every point” (1976:144).
Like Howell (1979) we approach the problem of determining the demographic characteristics of a hunter gatherer population not
as an empirical, inductive, problem, but by
using what data we can acquire to test the
null hypothesis that the population conforms to a stable population model. Furthermore, instead of attempting to select a
model de nouo, we test two null hypotheses:
that our data fit the model chosen by Dyson
t o represent the Hadza censused in 1967, or
that our data fit the model chosen by Howell
for the Kung.
163
We report whatever data we could obtain
that can be compared to Dyson’s and Howell’s data or models. We are fortunate that
several measures could be obtained, and
that they were independent of assumptions
about which model was appropriate for the
Hadza. We present five sets of figures to
compare the Hadza in 1985 with the Dyson
and Howell models:
1. The age structure of the population in
1985, derived from an age ranking, and the
place in this ranking of 35 people itf hiLu*ii
age.
2 . Survivorship to 1985 of people who featured in the 1967 census.
3. Mean age a t childbearing, for mothers
of small babies in 1985, and in previous censuses (we collected no reproductive histories).
4. Number of live children per woman
against age of woman.
5. Calculation of the total population in
1967 using a “capture-recapture” argument,
and then using the difference between the
1967 and 1985 populations to estimate rate
of increase.
To help place the Hadza in a broader perspective we use data from the Tanzanian
national census to compare the Hadza age
structure with the age structure of three
electoral wards that surround (and include)
Hadza country.
1985 census procedures
The 1985 census was conducted by Smith
and Blurton Jones, with the help of two
Hadza field assistants. The goal was to identify all Hadza currently living on or near
traditional Eastern Hadza country. Starting
at the northernmost camp in Mangola region a t the beginning of June, the census
team worked south, at each camp asking
where nearby camps were to be found, and
recruiting help in locating them. The tour
ended at the villages of Munguli and
Mwangeza in the last days of the month. In
each camp they visited, team members recorded the names, parentage, and household
affiliations of all residents. Data were collected from a total of 36 camps plus the two
villages, including about five camps in Si-
164
N G BLURTON JONES ET AL
ponga not visited by the team, but reported
by residents visiting camps where team
members were working. Data from these reports were cross checked by Smith and the
two field assistants.
Periodically, at two or three camps in each
local area, team members gathered groups
of four or five older people for interviews on
the survivorship of individuals recorded in
the 1967 census. (This exercise was facilitated by the availability of anthropometric
data obtained from the University College
IBP archive wilh iliie pcliiii&un Uf'khe then
head of the Anthropology department.) Similar groups were assembled to discuss the
age rank of individuals listed in the 1977
and 1985 censuses.
The two Hadza field assistants played a
crucial role in this exercise. Both are young
married men who are literate, have attended secondary school, and had worked
with Smith on the 1977 census. Each has an
encyclopedic knowledge of Hadza identities
and genealogies. Their role was to collect the
basic census data, i.e., to enumerate camp
membership by observation, and to develop
information on parentage and household affiliation through discussion with camp residents. This approach overcame the extreme
resistance, sometimes overt hostility, shown
by many Hadza to questions about their
names. Such questions are especially important because the Hadza often change their
names, or are known by more than one
name. Clarity about names is vita! ic: questions about age ranking, survivorship of the
1967 census population, and the identities of
individuals recorded as infants in the 1967
and 1977 censuses.
We have two independent checks on the
accuracy of the family compositions and genealogies collected in this census. One is
provided by Smith himself, who lived with
the Hadza for four years in the rnid-l970s,
and in the process came t o know many individual Hadza well. More recently, Blurton
Jones, Hawkes, and OConnell have conducted extended periods of behavioral ecology fieldwork in Tli'ika (Blurton Jones et al.,
1989; Hawkes et al., 1989; O'Connell et al.,
1988a,b, 1990),and as a result, know most of
the 200-250 people who normally live there.
Data gathered in the 1985 census match
well with information developed during
these longer periods of fieldwork. Data from
both sources also match those recorded in
the 1967 census. As a result of all this, we
have substantial faith in the validity of our
data.
ANALYSIS AND RESULTS
Hadza numbers and density
The 1985 census recorded 719 Eastern
Hadza. This is a slight underestimate of the
actual Hadza population. Fic!dwork cmditions, coupled with the Hadza habit of
changing names, led to various omissions
and overinclusions: 719 people were recorded in the census but 13 of these did not
receive an age ranking. Our box of cards
used for age ranking contained 775 cards
and all these were placed in the ranking.
Subsequently we discovered that 22 people
were entered twice in the age ranking (but
only once in the census). Forty-seven people
had been age ranked but were not recorded
in the census. They were known to us from
previous censuses, and known to our assistants and informants. Some were living
alone or with non-Hadza. Thus the actual
number of eastern Hadza in June 1985 was
probably around 750.
The census includes 125 people living at
Munguli and Mwangeza, most involved in
both farming and foraging; 233 in Tli'ika, all
essentially full time hunter-gatherers (see
also Bunn et al., 1988); and about 180 each
in Sipunga and Mangola, foraging, working
for farmers, or farming themselves (McDowell, 1981; Vincent, 1985). The mean population of 36 bush camps is 16.5; the range is
2-48. Camp size varies with season.
To calculate population density we measured the area occupied by the Hadza from
the Lake Manyara 1/250,000 scale map (series Y503, sheet SA-36-16, edition 1-TSD),
published by the Surveys and Mapping Division, Ministry of Lands, Housing, and Urban Development, Tanzania, 1980. On this
map, we identified twenty-six 10 x 10 km
squares in which Hadza were living at the
time of the census. Since several of these
squares include areas where Hadza seldom
go, we conservatively subtracted one square
from the total. Still included is the Yaeda
D E M O G W H Y O F THE HADZA
Plain, which the Hadza regularly cross, but
rarely exploit. The resulting figure is somewhat lower than Woodburn’s (1968a: 49) estimate of “well over” 1,000 mi2.
Given our estimate that Hadza country
includes some 2,500 km2, the overall regional population density for the Hadza is
about 0.30/km2 (0.74/mi2). Actual density
varies locally and with the seasons, probably
reaching a peak in Tli’ika during the late dry
season, when large game animals are concentrated around a small number of water
sources (Smith, 1980; O’Cofinel! et a].,
1988a,b). Excluding villagers, the regional
density is about 0.24/km2(0.61/mi2).
The density of the Hadza population is
nearly an order of magnitude greater than
the figure reported for the central Kalahari
San (0.03/km2; Tanaka, 1976) and three to
six times higher than those noted for the
Dobe !Kung (0.042-0.080/km2). Yellen and
Lee (1976: 28) give “the Dobe-/Du/da region”
as 11,O.OO km2, while Lee (1979: 41) makes
the Dobe area about 140 x 65 km, or
“roughly 9,000 km2” (actually 9,100 km2).
Lee (1979: 42-43) gives the “Dobe area” population as 379-584 (the number varies from
year to year), which in an area of 9,100 km2,
yields densities in the range 0.042-0.064
people/km2. Some doubt remains about including the /Du/da people. If we count these
145 souls, and use Lee’s 9,100 km2 area figure, the population density is 0.08Okm’. If
we use Yellen and Lee’s 11,000 km2 figure,
we get 0.066/km2.
The use of stable population models supposes limited migration. We believe that
Hadza migration is quite limited, both as
emigration, and as movement between eastern and western Hadza. There are apparently some 200-300 Western Hadza. Smith
has visited them and noted that they have
for some time led a much more village centered life than most Eastern Hadza. We concur with Woodburn (1968a): “Little contact
occurs between the eastern and western
Hadza: only very occasionally have individuals moved temporarily or, more rarely, permanently from one of these areas to another.” Our efforts to locate survivors from
the 1967 census give some information
about emigration. Of people aged less than
20 in 1967 (the group most likely to have
165
emigrated by 19851, 9 out of 63 males and 6
out of 73 females were living outside Eastern or Western Hadza country. Immigration
would prima facie seem impossible. But the
ancestries of a number of Hadza include
Isanzu parents. (The Bantu speaking Waisanzu farmers live to the south of Hadza
country.) Barnicott et al. (1972:634) report
that ‘‘for 437 subjects the proportions of the
ancestral components are Hadza 79.8%,
Isanzu 17.3%, Sukuma 1.7% and Iramba
l.2%.” (These figures apparently include
gra1idpdieiitb.j Of the 275 children in the
1985 census, nine had non-Hadza fathers.
Age structure
Developing an age structure for the Hadza
is fairly difficult. As is common for modern
hunter-gatherers, there is no comprehensive set of written birth records to which an
investigator can refer, and most Hadza
know neither their own age nor the year in
which they were born. Moreover, relative
age appears not to be extensively distinguished in Hadza kinship nomenclature,
nor is it generally given attention.
Age ranking
While they lack the !Kung concern with
relative ages, the Hadza showed some interest in comparing people on the basis of who
was born first. Informants worked long
hours on this task with Smith. Major problems involved the relative ages of people
from different parts of Hadza country. who
are not well known to all informants, and
those of children, who may have changed
names often, or who may be confused with
siblings. The final ranking includes 775 individuals, ranked from oldest (1)to youngest
(775). Of these, 706 are listed in the 1985
census, 22 turned out to be duplicates (for
instance due to changing their name between 1977 and 19861, another 47 were
known from previous censuses but not encountered during 1985. Thirteen people recorded in the 1985 census were inadvertently excluded from the age ranking.
Known ages
Forty-four people in the ranking are of
known ages, ranging from 1-29 years. These
data come from several sources. Some of
166
N.G. BLURTON JONES ET AL.
these individuals were small babies in the
1967 census, and we assume their ages were
accurately estimated to the nearest year by
IBP investigators Woodburn and Bennett,
both of whom had lengthy experience working with people in East Africa. These people
were thus about eighteen years of age in
1985. Others were small babies at the time
of the 1977 census, and therefore about
eight years old in 1985. Still others had their
birth years or dates recorded, either in the
IBP data or Smiths mid-1970s journal.
Some r , c x ~ b c r ~were
s
dse noted dixing
Blurton Jones and Smiths visits in 1982
and 1984.
Ages of four older people are estimated
less directly, and unfortunately the estimates for three of them are not in every respect independent of all the measures one
would wish to predict. Nonetheless, these
estimates are not based on visual estimates
of their ages as old people, since many are
not prepared to believe older folks are as old
as they look, and because margins of error
are undoubtedly greater for seniors. Woodburn (1964) provides lists of adults, camp
compositions, and genealogies recorded during his 1959-60 fieldwork. Some of these
people are identifiable in the 1985 census
and age ranking. We assume, on the basis of
our own later field experiences, that the
youngest man in our ranking listed by
Woodburn as married in 1960 would then
have been 20-25 years of age, the youngest
woman then married, 15-20. We estimated
their ages in 1985 accordingly.
Cooper (1949) provides an account of his
visit t o the Hadza in 1945. In it, he gives the
name of his guide and information about the
guide’s parents. These data match precisely
with a man listed in both the 1967 and 1977
censuses, but who died before 1985. Judging
from a photograph taken by Cooper, the
man was in his late 20s at the time of Cooper’s visit. This fits well with Woodburn and
Bennett’s estimate of age 50 twenty-two
years later, and gives him an age of 68 had
he survived to 1985. We allotted the age 68
to the rank of his closest 1967 contemporary
still living in 1985.
Least direct is our estimate of the age of
an old woman who died early in 1986. At the
time of the 1985 census, she had four surviv-
ing children, all placed in the age ranking.
The older two also appear in the 1967 census. We made visual estimates of the ages of
the oldest and youngest, the former a man of
about 60, the latter a woman in her low thirties, well known to us from our ecological
fieldwork, who also appeared in the 1977
census as a young woman with two small
children. The old woman herself appeared to
be in her late 70s in 1985. Since it seems
unlikely that she had her first child when
she was younger than sixteen, or her oldest
when She was more than 46 we estimate her
age in 1985 at 76.
Fitting ages to age ranks
Our procedure for calculating ages for age
ranks differs from that used on the !Kung by
Howell (1979: 23-46), who fitted her rank
order to a stable population model. Our results are independent of any assumption
about the shape of Hadza age structure. We
simply fitted a (three-term) polynomial regression (Dixon, 1981) of individuals of
known age (n = 48) against the distribution
of all individuals by age rank, and used the
regression equation to estimate ages for
each rank. Estimated ages are obtained
from this program by including age ranks as
if they were data, but with age as missing
data, a useful trick not described in the
BMDP manual.
We chose polynomial regression because
the technique will fit any curve if enough
terms are added. We wanted t o minimize
the assumptions built into our procedure for
deriving an age structure. The only assumption inherent in this technique is that the
age structure is fairly smooth, i.e., individual ages are neither massively under- nor
over-represented.
Checks on the age calculations
Howell (1979: 31-41) checked for systematic distortions in the calculation of ages
from age ranks by examining differences in
age between mothers and their children, expecting these differences to be constant
across all age ranks. The particular measure
used was age of mother at birth of first child.
Lacking detailed reproductive histories for a
large number of women in the census, this
167
DEMOGRAPHY OF THE HAUZA
TABLE 1. Age structure of‘the eastern Hazda population in 1985 (706 individuals eensused and age-ranked) and in
1967 C380 eastern 93 western Hadza ceiisused)
1985
_______________
N in
Age
( y r L - -
5
10
15
20
25
30
35
40
45
50
55
60
65
70
701
Total
interval
( 0 4 _, _etc
)
_ -__
112
84
79
67
61
48
47
39
32
0“
Y‘
27
21
24
20
18
706
Q below
age
~
15 9
27 7
39 1
48 6
57 2
64 0
70 7
76 2
80 7
34 1
88 2
91 2
94 6
97 4
100 0
Dyson
model
(% below age)
-___
16 4
29 1
40 3
50 2
59 0
66 7
73 4
79 1
84 1
ss 2
91 7
94 6
96 8
98 3
100 0
-
~~
1967
_______________
N in
__-___~
~
Dyson
interval
observed
( 0 4 , __etc )________ (‘?c below
age)
- ___ -75
15 9
82
33 2
42
42 1
26
47 6
27
53 3
37
61 1
39
69 3
46
79 1
27
84 4
~
5
04
3i
14
9
15’
94 9
96 8
__
__
473
15 people over 60 years old
A second way to check our age estimates is
measure is unavailable to us. The oldest surviving child of a woman in our sample might to compare them with those made visually
be her second or third born. Instead, we cal- by Woodburn and Bennett for people listed
culated age differences for all possible in both the 1967 and 1986 censuses. Visual
mother-child pairs in the 1985 census. Mean estimation has often been criticized as misdifference in ages of mother and oldest sur- leading (e.g., Howell 1979: 23-24), yet we
viving child is essentially the same for moth- found strong correlations between the reers aged 40-50 as for mothers aged over 50 sults of our method and those of the Wood(30 years for the latter, 29 for the former, burn-Bennett visual estimates: r = 0.9717,
some of whom might yet raise their score by and slope 0.9376 for men (n = 122,
giving birth again). Mean ages of mothers of P < 0.001), r = 0.9546 with the slightly less
children born in census years (discussed be- impressive slope of 0.8945 for women
low) are also similar across all three census in = 121. P c; 0.001).
There are almost certainly some errors in
cohorts. Both results indicate no systematic
both the age rankings and in the estimates
distortions in age estimates.
Age estimates for older people are very of ages of particular individuals. The errors
sensitive to variation in the ages given for are potentially most important in analyses
the four oldest adults of “known”age. They involving subsamples of older individuals.
are also sensitive to the number of terms Nevertheless, we are confident that our age
used in the polynomial. If the regression calculations provide an accurate overall picprogram is allowed to run until it reduces ture of Hadza age structure in 1985.
the residuals for the four oldest “known”age
adults t o very low levels, then a strong dis- Resulting age structure
crepancy emerges in the age gap between
The age structure is a count of people remother and child for mothers over 60 versus
those aged 40-60. More consistent results corded in the 1985 census. People listed in
are produced by the three-term equation, previous censuses who were alive, but not
which in effect smooths out the estimates of counted in the 1985 census are excluded,
the four “known” age adults, rather than by even if they had been ranked on relative age.
insisting that we regard our estimates as Table 1and Figure 1show the age structure
given by our aging system. Table 1 also
precisely correct.
N.G. BLURTON JONES ET AL
168
Hadza Age Structure
70-
1
65-69
-
fi0-64
.
55-59
.
50-54
.
45-49
-
40-44
*
30-34
20-24
,.
,“
,-
‘ 0
10-14
I
1
0-4
60
40
20
No of males
0
20
40
60
No of females
Fig. 1. Age pyramid for Eastern Hadza in 1985
shows Dyson’s observed and modeled age
structure for the 1967 census, based on
Woodburn and Bennett’s visual estimates. A
Kolmogoroff-Smirnoff test indicates that
our 1985 age structure is not significantly
different from either the 1967 age structure
or Dyson’s model. Comparison of the 1985
Hadza data with Howell’s model of the
!Kung indicates that the Hadza population
is significantly younger (Table 1)(Kolmogoroff-Smirnov test. P < 0.01, Siegel, 19561.
We return to these results below.
However, Hadza age structure varies with
location. Specifically, the Tli’ika population
(foragers in unencroached habitat who obtain more than 95% of their food by hunting
and gathering) is markedly younger than
the Hadza population as a whole, and the
Siponga and Mangola populations (with
more mixed subsistence in the most degraded habitat) correspondingly older. Table 2 shows the age structure in three Hadza
regions and the village of Munguli. (The
small number of people found in the north of
the region called Han!abe are included in
Mangola, where they often spend time.
Those found in the southern border of Han!abe and Tli’ika are included in Tli’ika). We
can compare the figures in various ways, for
example by examining the proportion of peo-
ple aged less than 15. This proportion
ranges from .4469 for Tli’ika to .3351 for Siponga. Changing the cut-off point makes little difference (Table 2). Tli’ika and Munguli
have substantially younger populations
than Siponga and Mangola. The latter regions, most heavily settled by other tribes in
recent decades, are significantly older than
Tli’ika (testing proportion under 15, chi
square = 5.98, P < .025 > .01).
The regional differences among the
Hadza, while they confuse the overall demographic pictiirr-.,arP likely te FW;C instructive about the costs and benefits of various
resource acquisition, parenting and mating
strategies. The data suggest that those who
live in the bush, or who farm in a predominantly Hadza village, have the most living
children, and differ most strongly from the
!Kung, while those who have least surviving
children are those who live in areas where
people of other tribes farm, who occasionally
employ Hadza as laborers.
Survivorship over the past 18 years:
An estimate of age specific mortality
In 1985, Smith and Blurton Jones asked
Hadza about the identities of all individuals
listed in the 1967 census, whether they were
alive or dead, and if alive, where they were
living. The process was repeated many
times, and multiple reports of a death were
required before it was considered confirmed,
Efforts were made to locate all survivors. Of
the 380 Hadza listed in that census, 102
(27%) were dead, 258 (68%) alive, and 20
(5%)unaccounted for (Table 3 ) . Eight of the
20 unaccounted for were males aged 23-28
(a group with predictably great mobility) in
1985. Since 1985 we have encountered 5 of
the 20. We conclude that it is incorrect to
assume that those unaccounted for were
dead, and we have omitted all 20 from our
calculations.
Table 3 and Figures 2 and 3 show the 18
year survivorship of the 1967 sample, compared with the survivorship calculated for a
series of Coale and Demeny (1966)model life
tables chosen to vary about the models chosen by Howell to represent the !Kung (West
5 ) ,and Dyson to represent the Hadza (North
6). Thc scrics comprised West levels 1, 5,
169
DEMOGRAPHY OF THE HADW
TABLE 2. Percentage below each age point for each, Hadza region, compared to Dyson and LKung models
5
10
15
20
25
30
35
40
45
50
55
60
65
70
100
16.4
29.1
40.3
50.2
59.0
66.7
73.4
79.1
84.1
88.2
91.7
94.6
96.8
98.3
100
17.7
28.3
44.7
53.1
61.1
67.2
72.6
79.2
82.3
84.1
88.9
93.2
35.6
97.8
100
11.4
24.7
35.5
43.9
54.2
61.4
68.7
72.3
77.7
84.3
88.5
89.7
93.9
96.9
100
18.7
29.31
41.5
51.2
60.1
64.2
69.1
73.9
82.1
86.2
89.4
90.2
33.;
96.7
100
15.7
27.2
33.5
45.0
52.9
61.8
70.7
76.9
80.1
83.8
86.4
90.8
94.6
97.9
100
11.8
21.9
31.5
40.6
49.2
57.2
64.5
71.2
77.3
82.8
87 6
91.6
Y4.Y
97.3
I on
TABLE 3. Deaths and survivorship to 1985 by people in 1967 census and traced i n 1985'
Women
___
Fate
unknown
Age (yr)
Dead
Alive
0-4
11
3
2
4
6
6
1
27
24
9
7
6
6
16
16
5
6
4
2
3
1
0
5-9
10-14
15-19
20-24
25-29
30-34
35-39
4044
4549
50-54
55-59
60
+
1
1
0
1
0
1
0
1
0
0
1
Dead-~
4
11
3
2
1
4
3
2
2
5
3
4
4
.
Alive
____
10
26
20
8
8
11
12
7
9
10
6
2
0
Men
._
Fate
Unknown
1
6
2
0
0
1
0
1
0
0
0
0
0
Observed
survivorship
_____.-____.
,7115
,7813
,8750
,7931
,7368
,6957
,7143
,3333
.0833
'Column on right uses people dead or located alive, ignores people of unknown fate
and 9; and North levels 1 , 6 , and 9; with life
expectancies at birth of 20, 30, 32, and 40
years.
Expected survivorships for each 5 year
cohort (5-9, 10-14, 15-19, etc.) over the following 18 years was calculated as follows. P(x + 2 t o x + 20) = I(x + 20)/1(x + 21,
where P = probability of survival for next 18
years; x = age a t start of age interval in
which the individual belonged in 1967;
1 = number of survivors in a model cohort of
100,000 births, at time x (from Coale and
Demeny tables). The quantity l(x + 2) is
calculated by linear interpolation as
L(lx + 2) = LOX) - ([I(x) - l(x + 5)] X .4).
Expected survivorship for the 0-4-yearold cohort was calculated by interpolating
l(x + 2) using x = 1 instead of x = 0. The
assumption here was that the 1967 sample
of under 5s would include few under l-year-
'7
09
0.8
0.7
p 0.6
v)
:0.5
f 0.4
.-
0.3
0.2
0.1
p
3 $ oq L
4
o ? mr n, % ,x Js %,S o
, %, g ,
O l E % F i R 8 5 L ? 8
age cohorts
Fig. 2 Observed survivorship over 18 year interval
between censuses, plotted with survivorship predicted
from models West 1,5,9.
olds, and that linear interpolation from 0 to
5 would be misleading. Since mortality declines rapidly from birth to 5 this method
,
8
170
N.G. BLURTON $JONESET AL
TABLE 5. Models allowed calculation of total expected
dead after 18 years (Table presents goodness of fit of
observations to the models)
0.9
0.8
0.7
~
.
_
_
Dead
_
_
~
_
Alive
_
Chi square'
~
~
CL
r 0.6
West
Y)
.s5
0.5
1
5
9
North
1
6
9
Observed
0.4
0.3
north 6
0.2
north 9
147
113
87
213
247
273
23.3
1.55
3.41
146
105
85
102
214
255
275
258
22.3
0.11
4.45
Data differ significantly from model prediction when chisauared 23.84 df = 1.
Fig. 3. Observed survivorship over 18 year interval
between censuses plotted with survivorship predicted
from models North 1, 6,9.
The models allow us to predict the total
number of deaths expected in the 1967 census population. The match of the observaTABLE 4. Comparison of the fit of the model predictions to
tions to the predictions is summarized in
observed survivorship ofeach, 5 year cohort over 18 years
Table 5 . Again, the closest match is to North
Significance
6, and next closest to West 5 . There are
Goodness of fit
of difference
from
model
Model
chi-squared
significant differences from West 1 and
. _ _ _ _ ~ . . _ _ _ _ _
North 1.
West 1
45.7
P < ,001"
5
20.5
P > .05 < .10
While it is impressive that this parameter
9
25.6
P > .01 < ,025"
so closely to model North 6 we must note
fits
North 1
41.6
P i ,001"
that the differences from models predicting
6
15.6
P > .10
9
22.0
P > ,025 < .05"
substantially lower mortality levels are
barely significant. When only 100 deaths
* Data significantly differ from model, P < 0.05.
are observed, the standard errors of predicted survivorship is around 5% (Coale and
Demeny in Howell 1979, Table 5.2, p. 111).
could have predicted too high a survivorship This sets the 95% confidence limits for
for the 0 4 cohort. As a check, the calcula- model West 5 a t around the levels of model
tions were repeated, examining survivor- West 1 and model West 9. We must accept
ship of under 3 -year-olds separately from that our analysis of mortality cannot be very
the 14-year-olds. This increased all the chi- sensitive. Although on inspection of Figure 2
squareds slightly (but also the d.f.1, suggest- one is drawn to the high mortality of several
ing a closer fit to West 5 ( P > .10) than young age groups, and the low mortality of
shown in Table 4 but leaving other signifi- the older age groups, this observation cancance levels, and the overall result un- not be taken as more than a stimulus to
further research.
changed.
We are unable to demonstrate a difference
Inspection of Figures 2 and 3 suggests
that the data vary widely about the model from either null hypothesis. Our mortality
West 5 and North 6 predictions. However data are most closely compatible with Dysome of the visually impressive data points son's estimate for the Hadza, but are indisare based on very small samples. The fit tinguishable from Howell's estimate for the
between the observations and the models Kung. Hadza mortality is within the range
was tested with chi-squared. The closest fit expected for people living a hard life, with
was with North 6, closely followed by West limited access to medical facilities.
5 . Mortality was significantly lower than
Mean age at childbearing
predicted from models West 1 and North 1,
We have data on age of mother at birth for
and somewhat higher than predicted from
three sets of live, censused babies, those remodels West 9 and North 9 (Table 4).
~
171
DEMOGRAPHY OF THE HADZA
TABLE 6. Age of mothers at birth of babies recorded in
each census (See comments in text about oldest ages)
1985
1977
1967
Combined total
n
Mean
SD
Range
22
9
27
58
31.07
30.67
30.85
30.90
11.7
11.6
6.1
9.44
19-53
18-45
2 2 4 0 [91
19-53
TABLE 7. Numbers o f births to mothers older and
younger than 35, comparing Hadza data from 198.5, 1977.
and 1967 with !Kung data from Howell 1979 (page 141,
Table 7.2, and page 124, Table 6.1
Mother‘s age at birth of child
>35
__
s35
. . ~
Hadza
!King (1963-1973)
41
153
17
26
__58
179
‘The value of this comparison i s reduced by rounding errors for ages in
1967 census, and by comparing cross-sectionas with longitudinal data.
corded in the 1967,1977, and 1985 censuses,
respectively. Ages of mothers of 1985 babies
are calculated from the 1985 age rankings,
with the exception uf ulie 01 t w u iliutlirrj
who were babies themselves in 1967 and so
are of known ages. Ages of 1977 mothers are
calculated from their estimated 1985 ages,
and 1967 mothers from the Woodburn and
Bennett estimates (because older bearers of
children in 1967 had died by 1985, and so
received no age ranking).
The resulting age estimates for each cohort are very similar (Table 6). Examination
of the raw data suggests that it is common
for a Hadza woman t o bear a child when
aged 40-45. The extreme value of 53 seen in
Table 6 could arise from an error in age
ranking.
These figures, with overall mean 30.9
years, are higher than Howell’s estimated
average age for !Kung mothers at birth:
27.93 t 6.58 years. A t-test indicates that
the combined Hadza mean is significantly
different from the !Kung mean (t = 2.23,
P < 0.05). This difference has two dimensions: l i the difference in age structures, 2!
differences in age specific fertility. The latter may in turn have two components. First,
Hadza women may marry at a later age than
do !Kung women. Later marriage would on
average be expected to lead to later first
births. Second, Hadza women also appear to
continue giving birth at later ages than do
the !Kung. Table 7 shows the number of
Hadza women in the combined sample aged
older and younger than 35 at birth of child in
the sample years, and the number of !Kung
women similarly divided for births over a 10
year period, 1963-73. The difference is significant (chi-squared = 10.04, P < 0.011. A
greater proportion of births are to women
aged 35 or more among the Hadza than
among the !Kung. Given that !Kung have a
slightly older age structure than Hadza, this
suggests that Hadza indeed have higher feriility ill th& 30s than do !Kung. Phtllips
et al. (1991) suggest that Hadza age specific
fertility remains high after 35 years of age.
Number of live children
Based on the 1967 reproductive histories,
Dyson (1977) calculated the number of children ever born and the number that had
died for women in various age groups. The
number alive can be tallied from his summary tables. Our recent census allows us to
compute the number of children alive and
living in Hadza territory in 1985. Because
this figure is not based on reproductive histories, it is likely t o be an underestimate.
Some children may have left the area, or
been missed in the census.
As Table 8 indicates, our numbers are
similar to Dyson’s. One-sample t-tests show
no significant differences from Dyson’s figures.
Determining rate of increase by
estimating the size of the 1967
Hadza population
The 1967 census was partial; no serious
effort was made t o include every Hadza.
Nevertheless, data were recorded on a total
of 473 individuals, including 380 Eastern
and 93 Western Hadza. Here we use a kind
of “capture-recapture” argument to estimate
the number of Eastern Hadza in 1967. From
this number, we can then calculate an annual rate of change in population size.
As indicated above, Smith, Blurton Jones,
and their Hadza assistants counted and age
ranked 706 Eastern Hadza in the course of
the 1985 census. Of these, 384 were 18 or
older, and thus had been born at the time of
the 1967 census. Two hundred fifty-eight of
these had been recorded in the 1967 census.
N.G. BLURTON JONES Er AL
172
TABLE 8. Numbers of live children for wom,en of uarious ages (Comparison of 1985 datu
with Dyson’s report o f 1967 data)
1985
Age of
women (yr)
..-.._-._______
20-29
30-39
4049
.50 +
___
No. of
__
children
alive
No. of
Women
__
62
117
85
146
No. of
52
40
27
61
___
No. of
Dyson
__
alive
ever born
children
alive
No. of
women
Mean
children
alive
1.19
2.93
3.15
2.39
66
164
71
41
103
42
31
32
12
1.32
3.22
3.5
-
-
__
T
-1.29
--0.35
--0.37
‘Mothers more than 50 years old have fewer living children than young:er mothers. This cannot he taken to indicate lower fertility in bygone
years. It may instead arise because their children have died a t a n ad\ranced age, having been subjected to the reduced survivorship of the
over-40s.
This leaves 126 of the 1985 adults who must
have been alive, but missed in the 1967 census. These 126 must also be survivors of a
larger group alive in 1967, some of whom
have since died or disappeared. Let us assume that their number is proportionally
similar to those who died or disappeared
from the group seen in 1967. Of the 380
Eastern Hadza counted in 1967, 258 were
seen in 1985, another 102 were reported
dead, and another 20 were unaccounted for
in 1985. Thus from 122 missing/258 seen, we
get the proportion 0.473. We calculate that
.473 of the 126 seen in 1985 but missed in
1967 must have been alive in 1967 but died
or disappeared by 1985. This number is 60
(0.473 x 126). Thus the total missed by the
1967 census includes those who survived to
1985 (126), plus those who didn’t (60),or 186
in all. The total 1967 population must have
comprised these uncensused 186, plus the
censused 380, or 566 in all.
The difference between the estimated
1967 (566) and censused 1985 (706) populations permits us to calculate the average
rate of increase (r)as follows:
(formula presented in the U.S. Bureau of the
Census publication: ISP Supplemental
Course Series No 2. Demography Lectures
p. 9.) The resulting rate of increase is 13.0
per thousand per year. Dyson (1977) estimated the rate at 13.90 per thousand
(1.39%).These figures are much closer than
necessary for a reasonable match. Rate of
increase is inexorably determined by fertility and mortality. Since our independent es-
timate of this rate matches t.hat implied by
the model indicated by age structure and
mortality data, we are justified in having
greater confidence in the appropriateness of
the chosen model for describing Hadza demography.
Comparison with
neighboring populations
The Hadza can be placed in local demographic perspective by comparison with the
results of the Tanzania National Census for
1978. Table 9 gives the population by age
group in each of three electoral wards which
collectively encompass Hadza territory:
Mangola on the north, Yaeda Chini on the
east, and Matongo (including the villages of
Munguli and Mwangeza) on the south. The
census does not distinguish individuals by
language or tribal affiliation, but most of
people in these wards are farmers and herders. Their numbers far exceed those of the
Hadza.
A Kolmogoroff-Smirnov test indicates
that the age structure in each ward is significantly younger than that derived above for
the Hadza (two-sample, two-tailed tests,
P < 0.01). This suggests a much higher fertility for at least some non-Hadza, and an
even higher rate of population increase,
Mangola is an area of noticeable immigration; the other wards may have low levels of
emigration. Mortality is also lower among
non-Hadza (Sembwaje, 1984). Although we
have emphasized the younger age structure
and apparent greater fertility of the Hadza
relative to the !Kung, they are, as one might
have expected, older and less fertile than
173
DEMOGRAPHY OF THE HADZA
TABLE 9. Conzparison of Hadza age structure with age structure in neighboring villages enumerated in national census
.
Age
(w)
5
10
15
25
35
45
55
65
65 +
Total
.-
...--
Hadza
___________
No.
%
112
84
79
128
95
71
54
45
38
706
15.9
27.7
39.1
57.2
70.7
80.7
88.2
94.6
~
No. of people in age group and o/c people below age
Matongo
Mangola
____
No.
56
No.
IC
1,979
1.888
1,462
1,757
1,166
815
633
512
18.3
35.8
49.3
65.5
76.3
83.8
89.7
94.4
600
10,812
their non-Hadza farming and herding
neighbors.
1,339
1,158
756
1,150
863
653
422
269
236
6,846
19.6
36.5
47.5
64.3
76.9
86.5
92.6
96.5
-.__
~-
Yaeda
chini
~ _ _
No.
570
1,941
1,661
1,189
1,469
1,057
757
494
331
394
9,293
20.9
38.7
51.5
67.4
78.7
86.9
92.2
95.7
demographic characteristics of the Hadza in
1985, as recorded and analyzed by us, are
very similar to the Hadza in 1967, as reDISCUSSION
corded by Barnicott et al. and analyzed by
We have presented data on age structure, Dyson. The data and analyses in these studmortality, mean age at childbearing, and ies are substantially independent of each
numbers of live children, for the eastern other, which makes the agreement between
Hadza censused in 1985, and an estimation the two all the more striking. The Hadza
of the change in population since 1967. To probably have had, over the long term, a life
interpret these data we have compared expectancy at birth of 31-32 years, a populathem with the analysis by Dyson of the 1967 tion growth rate of 1.3-1.4% per annum, and
Hadza data, the analysis by Howell of the a total fertility rate of 6.15. Their vital rates
Kung data, and data from the Tanzanian must be close to the figures given by Dyson
national census for the surrounding vil- in 1977: birth rate 46.7, death rate 32.8, natlages. The comparisons raise several impor- ural increase 13.9 per thousand. Thus this
tant issues, some pertinent primarily to the analysis suggests, surprisingly, that there
Hadza case, others more general.
have been no meat changes in Hadza demography since the IBP data were collected
Comparison with Dyson’s analysis of the
in 1966-1967.
Hadza in 1967
Comparison between the Hadza
Dyson based his analysis on age strucand the !Kung
ture, and on reproductive histories collected
We suggested that comparing the Hadza
by Woodburn. He drew his estimate of the
level of mortality from the infant mortality with the Kung would be instructive. On the
reported in the reproductive histories. He one hand, the Hadza might have displayed
indicated the need for information on adult very low fertility, low population density,
mortality. We have provided such data, and and near zero population growth as do the
they best fit the model chosen by Dyson. Kung, fitting the pattern often treated as
This is particularly encouraging since the typical of hunter gatherers. Such a finding
source ofour data on mortality is so different could have strengthened either the view
from the source of Dyson’s estimates of mor- that human populations depart from Maltality. Our calculation of rate of increase (a thusian expectations, or the view that marcapture-recapture method), which was inde- ginality to the world system shapes the bependent of our choice of model, results in havior of modern hunter gatherers to much
complete agreement with the figure Dyson of a sameness. But the data show the Hadza
to differ from the Kung in the directions exderives from his model.
We are inclined to interpret our findings pected from the details of local ecology and
as strengthening Dyson’s conclusions. The biological common sense: higher foraging re-
174
N G BLURTON JONES ET AT,.
turns are observed for Hadza adults (Blurton Jones et al. 1990), and children (Blurton
Jones et al., 1989), Hadza show higher density, higher fertility, and a higher rate of
increase than the !Kung.
Elsewhere, we reported data showing that
Hadza children are economically “cheap”to
raise (Blurton Jones et al., 1989). They can
provide about half their own food from the
age of five, and perform many useful services for adults. Hadza women are thus
spared many of the constraints that apparelilly piuCluLe a sharp increase ir, offspring
mortality as interbirth intervals shorten
among the !Kung (Lee, 1972; Blurton Jones
and Sibly, 1978; Blurton Jones, 1986,1987).
For these reasons, we expected Hadza mothers to give birth to a greater number of children at shorter intervals (Blurton Jones
et al., 1989).
The available demographic data, ours and
those of Barnicot et al., as analyzed by Dyson, imply that the Hadza are indeed substantially more fertile than the !Kung. The
Hadza have a significantly younger age
structure, and there was no evidence that
their mortality was substantially different.
The difference in age structure can then be
comfortably attributed to differences in fertility. We have done no reproductive history
interviews, but our data are compatible with
Dyson’s conclusion, that Hadza total fertility rate averages 6.15 (compared to the
!Kung rate of 4.7 for women over 45 in 1968).
As Dyson points out, the Hadza rate is similar to that of many traditional agricultural
populations. Indeed, it coincides with the
mean of Campbell and Wood‘s (1989) entire
sample of natural fertility populations. The
Hadza cannot be said to duplicate the Kung
restraint on fertility. The Hadza age structure is, however, not so young as that of surrounding village populations.
Both the Hadza and the !Kung populations under comparison here include individuals who have not always lived as
hunter-gatherers. We must ask whether differences between the two populations could
arise merely from differences in the fraction
of each associated with agricultural or pastoral settlements. !Kung who lived primarily as foragers had longer inter-birth intervals than !Kung who lived largely on
resources at cattle posts (Lee, 1972; Blurton
Jones, 1987). The cattle post subset might
therefore be expected to have a younger age
structure than the bush living subset. Our
data (Table 2) show that the Hadza pattern
is just the reverse: bush dependent Hadza
have a younger age structure than Hadza
who have more contact with settlements.
Thus, bush living Hadza are more different
from the !Kung as a whole, and so presumably even more different from the bush living !Kung, than are the Hadza as a whole.
Differences between the two popiilatinne.
cannot be due merely to differences in the
proportions living more or less settled lives.
Although the Hadza are more fertile than
the !Kung, we have yet to demonstrate anything about their inter-birth intervals. Indeed, the greater number of births to Hadza
women may be partly due to the practice of
continuing their reproductive careers to a
greater age than do !Kung women. However,
they may also begin their reproductive careers slightly later than do the !Kung. Both
of these patterns would require explanation.
Nevertheless, the data and analyses presented here give us no reason to reject our
prediction based on the abundance of resources and independence of children:
Hadza IBI’s should be shorter than those
documented for the !Kung.
The very much higher density of Hadza
population, and the high rate of increase of
the Hadza, are incompatible with the notion
that hunter gatherers prudently maintain
their population a t a low density and almost
zero population growth. That the Hadza
population is increasing shows that it is neither constant nor at carrying capacity.
Hadza population increase may be a recent phenomenon, due to successful exploitation of modern opportunities leading to a
new carrying capacity. However, if the population models are interpreted to summarize
long standing conditions (constant mortality
during the preceding 25-30 years, and constant fertility for some two generations
(United Nations 19671, desiderata that our
match across an 18 year interval begins to
approach) the increase may represent long
standing conditions, such as recovery from a
population crash some decades ago, or removal of some previous constraint such as
DEMOGRAPHY f3F THE HADZA
hostile neighbors (discussed by Obst 1912).
Remarks by earlier visitors, including
Woodburn (in the field 1958-60), Cooper
(1949, in the field 19451, Kohl-Larsen (1958,
fieldwork in 1931-19361, and Obst (19121,
are compatible with a steady increase in the
numbers of Hadza from the beginning of the
century a t the rate of increase reported for
1967 and 1985.
175
effects. The method was certainly not designed to examine individual, short-term,
and sub-population differences in reproductive strategies and it should come as no surprise if it fails to do this. It remains an excellent descriptive tool, with the attraction that
it describes major patterns and long term
trends. Nonetheless we should discuss the
effects that we expect encroachment, and
time at settlements to have upon Hadza ferOn the use of stable population models
tility, mortality and migration. In addition,
Our data and analysis could be taken to given this doubt that we have cast on the
illustrate the strength and robustness ofthe value ofthe close fit between our predictions
stable population method. Several indepen- and findings, we must consider some of the
dent measures each fit the same model. Our alternative explanations for differences bedata set, and Dyson’s collected largely inde- tween Hadza and !Kung demographic papendent of each other and 18 years apart, rameters.
both support the same model. But is this
robustness gained a t a cost t o sensitivity? Why do we see no demographic effect of
settlement schemes?
Our apparently tidy results must be disIt has been widely accepted that sedentacussed in relation t o recent changes in the
rization produces many changes. Changes
Hadza environment.
Recent decades have witnessed an accel- in fertility andlor mortality are among the
erated influx of non-Hadza into the region most commonly claimed (Harpending and
and a series of government and mission set- Wansnider, 1982; Handwerker, 1983; Lee,
tlement schemes. We have shown that there 1972, Roth, 1985). Thus one expectation
are differences in age structure between might be that Hadza who spend time a t setHadza regions, with the most encroached- tlements, or who have more contact with
upon areas having the oldest age structures, farmers and villagers might show higher
suggesting lowered fertility. Yet this has not fertility than those who live primarily upon
changed the overall picture since 1967, nor bush foods. Our regional comparisons sugis there any trace in our age structure of the gest the opposite. The most fertile Hadza
excess 11-20-year-olds who would result appear to be those who live in the bush. This
from a baby boom during the life of the could of course be an effect of migration, inYaeda settlement. Individuals of’known age cluding emigration of young adults to seek
bracket the main period of the Yaeda settle- the opportunities of village life. This in turn
ment. The proportions of people under 20 in implies the decision on the part of parents to
1985 and over 10 do not differ from the num- stay in the bush. As Cooper (1949) rebers expected from Dyson’s model (North 6 marked, the numbers of children in Hadza
with increase at 1.0% or 1.5%; chi- bush camps are truly impressive. When peosquared = 1.33 and 0.86, respectively).
ple moved to a recent forcefully promoted
Can the stable population method be ex- settlement scheme, some of the last people
pected to be sensitive to effects of such in the bush were children, left there with
changes in ecology? If the method is insensi- their grandparents for food and safety. We
tive to these presumably large ecological in- see no reason to assume that settlement influences can we still claim that such ecologi- creases fertility or survivorship of Hadza.
cal features as foraging return rates of The records of epidemics, and the Hadza
adults and children are responsible for the view that the arrival of people of other tribes
observed differences between Kung and in settlements presages disease, suggest
Hadza demographic parameters?
that mortality may even increase in settleMost demographers would argue that we ments. If people pursue their reproductive
are expecting too much of the stable popula- interests, we would expect settlements that
tion method when we expect it to show such people have to be pressured to join to have
176
N G RLURTON JONES ET AL
different demographic effects from spontaneous settlement. That considerable pressure to settle has been exerted on the Hadza,
while many !Kung settle spontaneously, is
another interesting difference between
these populations.
The encroachment upon Hadza country
has included noticeable destruction of vegetation, including trees, valuable berry
bushes, and wildlife habitat. One might expect this loss of resources to be damaging to
Hadza fertility and survivorship. But Hadza
who lire near farmers are a h a~puseciLO a
greater variety of economic opportunity.
These include helping harvest sweet potatoes (not helping to plant them!), and guarding maize fields as harvest time approaches.
In exchange for protecting the crop from
wild animals (an excellent hunting opportunity) Hadza are allowed an apparently unmonitored share of the crop. Some exchange
of meat for maize may occur at any time of
the year where there are villagers. Thus
even the loss of habitat cannot be assumed a
priori to have detrimental effects upon
Hadza reproduction. However, we were able
to show a difference in age structure between encroached and non-encroached regions. We cannot at this stage dismiss local
migration as a reason for this. But the differences strengthen our attribution of the differences between the !Kung and the Hadza
to the differences in ease of acquiring food
from the bush.
Alternative explanations for differences
between !Kung and Hadza
What are the other plausible competing
explanations for the difference between
Hadza and !Kung density, fertility, and population change? One might be that the differences are indeed due to ecology but to
very general features such as overall productivity of the habitat, further illustrating
the principle demonstrated by Birdsell, and
are not due to the microscopic and particular
features (distance between food and water
in the dry season) to which we have attended. Thus the association shown by Martin and Read (1981) between rainfall and
population density may be all there is to be
said. But it is worth noting that the Hadza
populatiuri is more dense than predicted by
their regression of density on rainfall. We
are tempted to attribute this to the local
proximity of food and water, and the success
of children’s foraging.
Another explanation might be to claim
that the Hadza have lost the traditional restraints upon reproduction shown by the
!Kung. Since (even after re-reading the discussion ofthe topic in Lee and DeVore, 1968)
we know little about such restraint and how
it is held to arise, it is hard to say what kind
of event might remove it. One could, however, argue that the recent history of the
Hadza has been more disrupted than that of
the !Kung as portrayed by Lee (1972,19791,
though less disrupted than the !Kung as portrayed by Wilmsen (1989,1990).
We have not investigated the proximal
causes of higher Hadza fertility but age a t
weaning is surely the first place to look.
Hadza evidently wean about a year earlier
than !Kung (Blurton Jones et al., 1989). The
physiological effect of weaning on fecundability is now well known (Konner and
Worthman, 1980; Wood et al., 1985; Ellison,
1990) and the importance of this effect for
demographic parameters has been demonstrated. But there is little research on what
determines the time of weaning. We seek
answers to this question among ecological
variables such as the “costs” of rearing a
child. Age a t weaning seems unlikely to be
explained by availability of “weaning foods.”
In both societies children are eating substantial quantities of adult food from about a
year old. A recent paper by Lee et al. (1991)
shows that mammals tend to wean when the
offspring reaches 4 x birthweight. We might
seek relationships between human infant
growth rates and age at weaning. Both
mother and baby might be expected to try to
adjust weaning to the survival prospects of
the infant, though not to agree on its exact
timing (Trivers, 1974, and others). Weight
might be a good predictor of these prospects.
Research on the effects of mothers diet
and activity upon fertility is also underway
(Ellison, 1990, and others). We may note
that Hiernaux and Hartono (1980) comment
on the weight and relative fatness of Hadza
women. Hadza women are the same height
as !Kung women but some 8 kg heavier.
While Hadza women forage daily and their
DEMOGRAPHY OF THE HADZA
digging must be energy expensive, their
journeys are shorter (Hawkes et al., 19891,
in a less demanding climate (Blurton Jones
et al., 1989). Thus we are not short of potential proximal causes of higher Hadza fertility. But the thrust of our research has been
to see how these proximal mechanisms may
serve or fail t o serve the selective pressures
that brought them into being.
Suggestions by Harpending based on recent observations on the Herero (Harpending and Draper, 1990; Harpending pers
c0mrn.l. ahout the possible influence of sexually transmitted diseases (STD) in the history of southern African populations provide
a compellingly simple alternative hypothesis about low fertility among the !Kung and
about some of the differences between the
!Kung and the Hadza. One way to identify a
substantial effect of STD is to compute the
number of older women who have borne no
children. Belsey (1976) contrasts populations in which this figure is 3 4 %with others where it ranges between 25 and 40%.
Since we have no reproductive histories we
are unable to give this figure for the Hadza.
Howell (1979, p. 127) reports a figure of 10%
for the !Kung.
To properly test the implications of
Harpending’s suggestions, that Hadza have
been less exposed to sexually transmitted
diseases than !Kung, or have had better access to antibiotics, we need detailed documentation and dating of the history of contact with populations infected with syphilis,
gonorrhea, chlamydial, and other infections
of the reproductive tract, and similar detailed history of access to antibiotics. Bennett et al. (1973) reported a surprisingly low
incidence of antibodies to treponemal infection among the Hadza in 1967 but informants listed STD as one reason for leaving
in search of modern medical help. Incidence
of STD would be a good candidate for explaining the regional variation observed
among the Hadza. But the apparent recent
increase in contact with outsiders does not
coincide with a discernible overall decline in
fertility. Among many populations, changes
in access to STDs and to antibiotics must be
accompanied with so many other changes
that it would be hard to disentangle their
effects. Howell (1979) appeared to deal ade-
177
quately with the issue of infertility due to
STDs, and it is hard to see how the presence
of STD would account for the numerous features of !Kung reproduction successfully
predicted by Blurton Jones and Sibly’s ecological model (Blurton Jones, 1986, 19871,
such as the close relationship between interbirth interval and child mortality.
Those who hold the view that contemporary hunter gatherers are best understood
as a rural proletariat could explain the demographic differences, if they claimed that
the !Kung have been and still are more exploited than the Hadza. There might be
some truth to this, despite the massive difference in proximity to much higher population densities. Hadza have for long lived in
the vortex of a whirlpool of major African
language families. They have been close
neighbours on all sides of quite densely populated and successful agricultural and herding societies-Sukuma,
Iramba, Isanzu,
Iraqw, Datoga, and Masai. Woodburn (1988)
discusses in depth the relations between
Hadza and their neighbors. He argues that
the Hadza “immediate returns” ethos enhances their independence from their neighbors. We support much of Woodburn’s masterly social analysis, and from our more
materialist perspective would emphasize
only two additional factors. The demands
put upon the Hadza by their neighbors may
differ from the demands put on the !Kung.
For example, the apparent disinterest
among the Datoga in employing Hadza as
herdsmen contrasts with the Herero and
Tswana, and as far as we know the Datoga
do not offer the inducements to laborers that
Herero and Tswana offer. The relative richness of Hadza and !Kung environments may
play its part. The Hadza bush environment
around Lake Eyasi may provide greater
opportunities, which enables Hadza to resist exploitation more effectively than the
!Kung. Note that Hadza take employment
protecting and harvesting a crop, not planting it!
Another aspect of Hadza history may be
even more germane. We argued that Hadza
population may have been increasing
throughout this century. If we extrapolate
back far enough the Hadza vanish sometime
in the nineteenth century! It seems likely
178
N G BLURTON JONES ET AL
that the increase in Hadza population represents a recovery from a decline, or the removal of some previous external restraint.
Three possibilities are presented by the literature. Obst (19121, Bleek (19311, and
Kohl-Larsen (1958) were told of wars with
the Masai. Oral history among contemporary Hadza and Datoga informants matches
these accounts. The effects of this seem not
to have lasted long, except for one Datoga
sect who lost their livestock and took to the
hills and lived for a time as foragers alongside thc Hsdza. The Masai had apparently
left this area by the time of Obst’s visit.
Obst’s informants reported another external
influence-raids by Isanzu and Sukuma
who abducted women and children. Obst
gives no indication that these raids were to
capture people for trade as slaves but slave
trade from far in the interior was extensive
until the 1870s (Sheriff, 1979). Obst’s Hadza
informants claimed that these raids had declined as the abundance of elephants (the
main target of the visits) declined. These
raids may have held Hadza population at a
level well below the carrying capacity of the
environment, either through the direct effect of removal of women, or by rendering
access to some resources too risky. The decline and eventual cessation of the raids as
they became forbidden by central authority
may have permitted an increase of Hadza
population that has yet to end. The rate of
the increase may have been determined by
the natural resources and the technology
used to acquire them.
A historical factor that may underlie both
the above, and which seems t o be being neglected in the discussions of Kalahari and
!Kung history, is discussed by Kjekshus
(1977). The rinderpest epidemic late in the
19th century apparently had radical effects
on African economies and populations.
Herders were subject to famine, epidemics
of smallpox broke out, along with other diseases (Ferguson, 1980) and tsetse flies enlarged their range, spreading sleeping sickness with them. The Hadza could have been
subjected t o these hazards, or have gained
from the weakening of their neighbours.
Thus in our comparison of the Hadza and
the !Kung we may not be comparing two
populations a t equilibrium. We have al-
ready established that at least one of them,
the Hadza, was not at carrying capacity. We
may be comparing rates of recovery from
late 19th-century disaster. These rates,
given that both populations whether by
choice or by the removal of other opportunities, were largely subsisting on non-domesticated foods, may well be shaped by the
richness of the environments and the ecological constraints upon foraging success.
It seems to us, in conclusion, that attempting to account for forager demography
without ecolow. would be a t least as difficult and potentially misleading as attempting the account without examining the history of relationships with neighbours.
ACKNOWLEDGMENTS
We are grateful to the following for help
and advice in the field, David Bygott and
Jeannette Hanby; Mrs. Flora Matemu, Nick
and Bridget Evans; Michael Leach; Margaret Gibb and many of her staff; our field
assistants Gudo Mahiya and Sokolo Mpanda
and the small teams of informants they
gathered in each locality, without whom we
would have collected no accurate data in the
census; and to all those Hadza who have
tolerated our intrusions.
During the lengthy process of trying to
learn demographic methods some of us received much help and tutelage from Nancy
Howell. Any mistakes that remain are ours.
Helpful comments on earlier drafts were
also received from Tim Dyson, Henry
Harpending, Robert Bailey, JGm Hill, and
two anonymous referees. N.B.J. wishes to
thank David Coleman, Fred Brett and Geoffrey Harrisson (convenor of the IBP Human
Adaptability program) for leading him to the
IBP archive, and R.D. Martin for permission
to use it. We are grateful to Lynne Fairbanks, Henry Harpending, Linda Muthen,
and Rich Cincotta for advice on statistics
and computing, to Gabriella Kopahl for
translating Obst, and Darlene Smucny for
translating Kohl-Larsen, and to Darlene
Smucny and Diane Crumley for entering
data on the computer.
We are grateful to The Tanzanian Commission on Science and Technology for permission to do research in Tanzania, and t o
Mrs. A. Lyaruu for help, guidance and en-
DEMOGRAPHY OF THE HADZA
couragement. The fieldwork was conducted
with support from The National Science
Foundation, The Swan Fund, and UCLA International Studies Program.
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