Differential Mortality Between the Sexes: An Inevitable Pattern in the Middle Ages?

Svenja Weise

Introduction:

“Being male is now the single largest demographic risk factor for early mortality in developed countries” (Kruger & Nesse, 2004)

Material and methods:

The burials in the parish cemetery S:t Jörgen cover a period lasting from around AD 1300, the establishment of the town, until

the dawn of the reformation in Malmö in the 1520s. It was a period of growth and well being for the city, mainly caused by the

prosperous herring trade.

The whole skeletal collection comprises 4182 individuals, of whom a sub-sample of 986 were chosen for this analysis. Their age

estimates were derived by Transition Analysis (Boldsen, 2002): a formal method of ageing skeletons by scoring multiple traits.

The scores are combined by Maximum Likelihood Estimation to derive Ages-at-death (MLA) with point estimates and 95%

confidence intervals. Only individuals older then 16 and with known sex were included.

Comparative data were taken from the skeletal collection of the small rural village of Tirup, Denmark, (AD 1150-1350, N= 155;

Boldsen, 2005) and period life tables for Sweden (1751-1759; Human Mortality Database).

For the two skeletal collections, the Mortality Rate Ratio was estimated based on 5 year groups for ages 20 to 75 years.

Age Female Male % Total

16 - 20 100 112 21.5 212

20 - 40 192 298 49.7 490

40 + 117 167 28.8 284

Total 409 577 986

References:

Boldsen, JL. 2005. Leprosy and mortality in the Medieval Danish village of Tirup. American Journal of

Physical Anthropology, vol. 126, pp. 159-168.

Boldsen, JL, Milner, GR, Konigsberg, LW, Wood, JW. 2002. Transition analysis: A new method for

estimating age from skeletons. In Paleodemography. Age distributions from skeletal samples, Hoppa,

RD,Vaupel, JW, eds, Cambridge, Cambridge University Press, pp. 73-106.

Human Mortality Database.  University of California, Berkeley (USA), and Max Planck Institute for

Demographic Research (Germany) (data downloaded on 3/20/2007).

Kruger & Nesse 2004. Sexual selection and the Male:Female Mortality Ratio. Evolutionary Psychology,

vol. 2, pp. 66-85.

Acknowledgement:

The author wishes to thank Prof. Jesper Lier Boldsen, who generously yielded the data of the

Tirup cemetery for this comparison. He and Ulla Freund (ADBOU) did a wonderful job in the

osteological analysis of the Malmö material. Thanks to Jim Oeppen (MPIDR) for his helpful

comments and a short brush-up on qx.

Max Planck Institute for Demographic Research

RostockGermany

This is a new phenomenon in human history. In ancient samples, women from their early twenties until the end of their fertile

period usually showed higher mortality rates than men. Around age 50, male mortality started to exceed female mortality.

Since the middle of the 18th century – at the latest – higher life expectancy for females can be universally observed, and was

associated with lower female mortality for all age groups.

• Biology “Dangerous fertile years”- higher mortality due to childbearing or maternal depletion

• Behaviour Women’s role includes caring for the sick and cooking

• Resources Unequal distribution of nutrition and health care between the sexes

Most likely, each of these reasons influences the different patterns of mortality. If so, the general level of economic and social

development of a community might govern the mortality regimes of the individuals living in it. This can be examined for Malmö, a

“boom town” in the Öresund region in Southern Scandinavia in the late Middle Ages. Skeletal data from a parish cemetery in

Malmö, Sweden, is compared with skeletal data from Tirup, an early medieval rural village in Denmark, and with life table data

for historical Sweden.

Hypothesis:

The late medieval society with its newly established towns

was a turning point between the different mortality regimes.

Horticulture and foraging Urban (partly) market integrated agriculture Urban (fully) market integrated agriculture Figure 2. Age at death distribution by sex

Anthropological Database Syddansk University

OdenseDenmark

Figures 5 – 7. Ratio of female to male probability of dying by age (qx) for Tirup, Malmö and Sweden.Table 1. Number of deaths for different age groups

05

10

15

20

25

30

15 25 35 45 55 65 75 85

Num

ber

of

indi

vidu

als

Age (years)

Malmö S:t Jörgen

Results:

Though nearly 50% of the deaths in Malmö occurred in the adult age group from 20 to 40 years (Table 1), there is no evidence

for excess female mortality during the childbearing years. The median of the distribution of ages-at-death is approximately

similar for both sexes (Fig. 2).

The survival curves of Tirup and Malmö show a clear difference in the mortality regimes in early adulthood (Fig. 3 + 4). (Continued above right)

Women Men

20

30

40

50

60

70

80

Figure 1. Age at death distribution for both sexes (years)

Age

(ye

ars)

Women Men

What shapes this excess female mortality in young adulthood is still a matter of debate. Three general factors seem to play a role:

20 30 40 50 60 70

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

20 30 40 50 60 70

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

20 30 40 50 60 70

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Age (years) Age (years)Age (years)

F:M

Mor

talit

y R

atio

F:M

Mor

talit

y R

atio

F:M

Mor

talit

y R

atio

Tirup Malmö S:t Jörgen Sweden AD 1751-1759

Figures 3 + 4.

Survival curves conditioned

on survival to age 16 for

males and females from

Tirup (left) and Malmö (right).

20 30 40 50 60 70 80

0.0

0.2

0.4

0.6

0.8

1.0 Males

Females95% C.I. Females

Tirup

Survivaltime (years)

Sur

viva

l pro

babi

lity

20 30 40 50 60 70 80

0.0

0.2

0.4

0.6

0.8

1.0 Males

Females95% C.I. Females

Sur

viva

l pro

babi

lity

Malmö S:t Jörgen

Survivaltime (years)

In Tirup, the lower survival probability for women compared to men is apparent for the ages from 20 to 38. After the childbearing

years, it remains nearly constant up to age 65, when it falls again. The Female:Male Mortality Ratio (F:M MR) in Fig. 5 shows

the change to higher male mortality around age 38.

Female survival probability in Malmö is only slightly lower than male in the years from age 20 to 35. Male survival lies in the

female 95% confidence intervals from age 30 upwards. The F:M MR indicates an even lower female than male mortality for the

ages 25 to 43 (Fig. 6). From 45 to 65 the mortality rates are very low which can exaggerate the relative risk.

The data for Sweden display a higher male mortality for all age groups (Fig. 7).

Possible causes for the observed changes in mortality could be a changing lifestyle during young adulthood over time. Marriage

occurred later in life and therefore led to fewer children and reduced risk of dying in childbirth. Young men immigrated to the

newly established towns and were confronted with new diseases. It is possible that the higher number of men than women in

towns resulted in an increase of male risk behaviour to compete for mates.

Conclusion:

There is an epidemiological transition in young adult mortality patterns during the Middle Ages and Early History: from an

increased female mortality during the reproductive years through a period of nearly equal risk of dying for both sexes to a

surplus mortality of young males.

This transition runs parallel to important changes in the subsistence patterns between the analysed communities: from

horticulture and foraging to an urban life and fully market integrated agriculture.

The data analysed here support the hypothesis that the level of social and economic development of a community influences

the shape of sex-specific mortality.