MORTALITY PATTERNS AND THEIR IMPLICATIONS
France MESLÉ and Jacques VALLIN
Institut national d’études démographiques (INED), Paris
Summary
The diversity of mortality levels and patterns around the world is currently
greater than ever. This directly results from the new historical perspective
engaged two and half centuries ago, when some North-Western European
countries started to become efficient in their fight against disease and death. But
the road of progress has not been straightforward. Until the late 1960s, it was
possible to rather clearly oppose high mortality levels of developed countries to
the low levels of developing ones. Today, both groups of countries radically split
into those that were the most successful and those that lagged behind. Many
authors, starting with Abdel Omran and its epidemiological transition theory tried
to find out the rationale for the historical mortality changes, and continuing with
those who tried to extend Omran’s theory to the new facts that contradicted it and
with those who preferred to try to assess a new theory, the health transition
theory, to take in account non epidemiological factors. However the current
situation if so complex that it is not possible to describe it as the result of only
one stream of changes that could universally explain all the different trajectories
of individual populations. It appears that the history of human mortality is made
of the achievement of successive steps of development that occurred with quite
different timing from one population to another, in order to produce at each step a
divergence and then convergence wave. And a wave can easily start when the
previous one is not completed. Thus explained, the large to-day inequity is far
from being reduced. That would need that the most advanced population be
stopped in their progress by a supposed biological limit of the human life span. A
limit that nothing allows us to fix today.
Keywords : mortality, life expectancy, infant mortality, health transition,
epidemiologic transition, death rate, cardiovascular diseases, infectious diseases,
man made diseases, AIDS, developed countries, developing countries, world,
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Sub-Saharan Africa, Eastern Europe, Western countries, mortality forecasts,
maximum life span, mortality theories
Introduction
Mortality was high in all human populations up until the eighteenth century.
With sometimes brutal variations, the crude death rate stood around 40 per 1,000
population, more or less equivalent to the birth rate. However, crude death rate,
obtained by dividing the number of deaths observed during one calendar year by
the total mean population of the same year, does not depends only on the level of
mortality but also on the age pattern of the population. Indeed, since mortality
risks are much higher for old people than for young people, same mortality risks
will give an higher crude death rate in a population where the proportion of old
people is higher than in a population where such proportion is lower. This is the
reason why demographers calculate the life expectancy at birth, which is the
mean duration of life that would be experienced by the individuals of a
hypothetical birth cohort that would be affected all along the life by age-specific
deaths rates observed in the year for which it has been computed. It is an
indicator of the level of mortality, independently from the age structure of the
population, quite comparable across time and space. Until the eighteenth century
life expectancy scarcely exceeded 25 years. Approximately half of all newborns
died before the age of five and even 30% before the age of one. To easily focus
on the historical importance of the latter, infant mortality rates are very simply
computed by dividing the number of deaths under one year of age observed
during one calendar year by the number of births observed during the same year.
Of course this very simple indicator is also independent from the population age
pattern and it allows to fairly represent mortality levels when in the past or more
recently in developing countries mortality was very high and data too poor to
compute life expectancy precisely.
From the eighteenth century on, the battle against the major epidemics
became more efficient, largely thanks to political and administrative progress,
while famines became less frequent as a result of agricultural development,
improved means of communication, and the opening up of trade. Northwest
Europe was the first to benefit from this. By the middle of the nineteenth century,
life expectancy in England, the Scandinavian countries and the Netherlands,
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reached — and even exceeded — 40 years. In the second half of the nineteenth
century, the health transition reached North America and Japan while at the same
time spreading to southern and eastern Europe. But it did not reach Latin
American and parts of Asia and the Middle East until the interwar period, and
only spread to the rest of the world after World War II.
Boosted by the economic development that resulted from the industrial
revolution, sanitary progress spread world-wide but with major discrepancies of
time and pace. Some countries, such as Japan in the past and many developing
countries today, benefited from the experience of others and caught up —
sometimes even overtaking the forerunners. The result, until recently, was a
broad range of situations. But in the past twenty years the trend has been towards
a concentration of populations at the higher levels of life expectancy, while
maintaining that range.
One might suppose that this trend will ultimately lead to equality of health
and the realization, at last, of the World Health Organization’s (WHO) slogan
“Health for all by the year 2000”. But things are never so simple. Some countries,
notably in sub-Saharan Africa, clearly lag behind. Conversely, many developing
countries are catching up and even overtaking the life expectancies of the
developed countries, because they are winning the battle against infectious
diseases but have yet to be hit by the increase in cardio-vascular diseases and
cancers that struck most of the developed world during the 1950s and 1960s.
Is the future likely to see a possible convergence of all the countries in the
world towards a life expectancy that some researchers place at 85 years (Fries,
1989; Olshansky and Ault, 1986)?. That would suppose that the most developed
countries do not rise above their present rates, and that those who still lag behind
rapidly catch up with them. Recent developments do little to confirm this
hypothesis however.
I. The variety of situations today
All countries have been affected by the improvement in life expectancy and
the worst situations today resemble the once-privileged situation in Europe, North
America and Japan at the beginning of the century. Table 1 summarizes the
mortality levels observed in all countries with a population of more than 15
million according to the three classic indicators, in three major regions of the
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world. Data used in this table are coming from systematic computations done by
the Population Division of the United Nations. It is well known that the quality of
these estimates varies a lot with the availability and the quality of national data.
UN experts do their best to select the most reliable data from each country and to
use the best indirect methods to estimate desired indicator that cannot be
computed from direct observation. Indeed estimates for some developing
countries must be considered as rough estimates and international comparison
must be used with caution. Nevertheless, UN databases are the most appropriate
to give a rather good overview of the actual diversity of situation.
Table 1. Mortality indicators for 2000-05 in 62 countries with a population
of more than 15 million in 2005, ranked according to life expectancy at birth
(e0 = life expectancy at birth, IMR = infant mortality rate, CDR = crude death rate)
AREA, country
World
More developed countries
Intermediate countries (Less developed – Least developed)
Least developed countries
Japan
Australia/New Zealand
Australia
Western Europe (North without Baltic c., South, West)
Spain
Italy
France
Germany
Netherlands
United Kingdom
Northern America
Canada
United States of America
Eastern Asia (without China and Japan)
Taiwan
Republic of Korea
Dem. People's Republic of Korea
China (including Hong Kong and Macao, excluding Taiwan)
Latin America (including the Caribbean)
Chile
Mexico
Argentina
Venezuela
Colombia
Brazil
Peru
South-Eastern Asia
Malaysia
Viet Nam
Philippines
Indonesia
4
Population
2005
6514751
1215636
4532300
766816
127897
24407
20310
426240
43397
58646
60991
82652
16328
60245
332245
32271
299846
96966
22770
47870
23616
1290079
557979
16295
104266
38747
26726
44946
186831
27274
557669
25653
85029
84566
226063
e0
IMR
CDR
2000-05 2000-05 2000-05
66.0
49.4
8.8
75.6
7.1
10.2
66.6
43.5
7.6
52.7
87.9
13.3
81.9
80.2
80.4
78.8
80.0
79.9
79.6
78.7
78.7
78.5
77.6
79.8
77.4
74.3
77.3
77.0
66.7
72.0
72.0
77.9
74.9
74.3
72.8
71.7
71.0
69.9
68.5
73.0
73.0
70.3
68.6
3.2
4.5
4.4
5.0
4.2
5.0
4.2
4.3
4.7
4.8
6.2
4.8
6.3
16.1
5.5
4.1
48.2
23.0
21.6
7.2
16.7
13.4
17.0
19.1
23.6
21.2
27.4
8.9
19.5
23.1
26.6
8.0
6.9
6.8
9.7
8.7
9.9
9.2
10.3
8.7
10.2
8.2
7.2
8.3
6.5
5.8
5.4
9.3
6.6
6.0
5.0
4.7
7.7
5.0
5.6
6.3
6.2
6.7
4.5
5.2
5.1
6.6
Thailand
63003
68.6
10.6
8.6
Myanmar
47967
59.9
66.0
10.2
Western Asia
212088
68.3
39.3
6.2
Syrian Arab Republic
18894
73.1
16.0
3.6
Saudi Arabia
23612
71.6
18.8
3.8
Turkey
72970
70.8
27.5
5.8
Yemen
21096
60.3
58.6
8.6
Iraq
27996
57.0
81.5
10.6
Eastern Europe (including Baltic countries)
304847
67.9
13.4
14.3
Poland
38196
74.6
6.7
9.6
Romania
21628
71.3
14.9
12.2
Ukraine
46918
67.6
12.8
15.8
Russian Federation
143953
64.8
16.6
15.9
Northern Africa
189562
67.1
38.3
6.7
Algeria
32854
71.0
31.1
5.0
Egypt
72850
69.8
29.3
5.9
Morocco
30495
69.6
30.6
6.0
Sudan
36900
56.4
64.9
11.2
India
1134403
62.9
55.0
8.7
South-central asia without india
511387
62.4
65.0
8.3
Sri Lanka
19121
70.8
11.0
7.3
Iran (Islamic Republic of)
69421
69.5
30.6
5.5
Uzbekistan
26593
66.5
55.0
6.8
Kazakhstan
15211
64.9
24.1
10.6
Pakistan
158081
63.6
67.5
7.7
Bangladesh
153281
62.0
52.5
8.2
Nepal
27094
61.3
53.9
8.7
Afghanistan
25067
42.1
157.0
21.6
Melanesia, micronesia, polynesia
9003
60.5
50.7
8.6
Southern africa
54900
52.5
46.4
13.8
South Africa
47939
53.4
44.8
13.5
Tropical Africa (Eastern, Middle, Western)
677549
48.4
96.2
15.3
Ghana
22535
58.5
56.6
10.0
Madagascar
18643
57.3
65.5
11.0
Kenya
35599
51.0
64.4
13.2
Ethiopia
78986
50.7
86.9
14.4
Cameroon
17795
49.9
87.5
15.0
United Republic of Tanzania
38478
49.7
72.6
14.6
Uganda
28947
47.8
76.9
15.5
Côte d'Ivoire
18585
46.8
116.9
16.5
Nigeria
141356
46.6
109.5
17.5
Democratic Republic of the Congo
58741
45.0
113.5
19.3
Mozambique
20533
44.0
95.9
19.2
Angola
16095
41.0
131.9
22.1
Source : United Nation 2006 World Population Prospects (for Taiwan, see http://www.moi.gov.tw/stat/english/).
5
Angola
Mozambique
Dem. Republic of the Congo
Nigeria
Côte d'Ivoire
Uganda
United Republic of T anzania
Cameroon
Ethiopia
Kenya
Madagascar
Ghana
T ropical Africa
South Africa
Southern Africa
Melanesia, Micron. Polyn.
Afghanistan
Nepal
Bangladesh
Pakistan
Kazakhstan
Uzbekistan
Iran (Islamic Republic of)
Sri Lanka
South-Central Asia
India
Sudan
Morocco
Egypt
Algeria
Northern Africa
Russian Federation
Ukraine
Romania
Poland
Eastern Europe
Iraq
Yemen
T urkey
Saudi Arabia
Syrian Arab Republic
Western Asia
Myanmar
T hailand
Indonesia
Philippines
Viet Nam
Malaysia
South-Eastern Asia
Peru
Brazil
Colombia
Venezuela
Argentina
Mexico
Chile
Latin America & Caribbean
People's Republic of China
Dem. People's Rep. of Korea
Republic of Korea
T aiwan
Eastern Asia
United States of America
Canada
Northern America
United Kingdom
Netherlands
Germany
France
Italy
Spain
Western Europe
Australia
Australia/New Zealand
Japan
40
45
50
55
60
65
70
75
80
Figure 1. Life expectancy at birth in 2000-2005, in 62 countries with a
6
85
population of more than 15 million in 2005
Source: United Nations, 2006 (for Taiwan, see http://www.moi.gov.tw/stat/english/)
In Angola, the least favoured nation today, the crude death rate is close to
22 per 1,000 (versus 18 in England/Wales, 20 in Japan and 22 in France in 1900),
infant mortality is 132 per 1,000 (versus 154, 215 and 164 in 1900 for the same
three countries respectively), and life expectancy at birth is 41 years (versus 47,
38 and 45). But however bad, these cases are still a far cry from the severe
conditions that existed before the health transition and that still prevailed in many
countries at the end of World War II.
Nevertheless, there is a broad disparity of situations. Going from one
extreme to another in the six-country list, Angola’s life expectancy of 41 years is
to be compared with Japan’s 82 (Figure 1). But this disparity does not simply
contrast developed nations with developing ones. It occurs within the same
region, for instance in South Asia where Afghanistan (life expectancy of 42.1
years) is almost as far removed from Sri Lanka (70.8 years) as it is from the
Western countries. In Southeast Asia, life expectancy ranges from 59.9 years in
Myanmar to 73 in Malaysia, while in North Africa it ranges from 56.4 years in
Sudan to 71 in Algeria, and so forth.
Infant mortality rate (p. 1 000)
Crude death rate (p. 1 000)
180
25
Angola
Afghanistan
160
140
Afghanistan
20
Angola
120
Russia
Côte d'Ivoire
DR Congo
Ukraine
15
100
Eastern Europe
Tropical Africa
Nigeria
Romania
80
United Kingdom
10
Japan
60
40
South Africa
5
Saudi Arabia
20
Syria
Japan
0
0
35
45
55
65
75
85
Life expectancy at birth (years)
35
45
55
65
75
Figure 2. Correlation between life expectancy at birth and infant mortality
rates (a) and between life expectancy at birth and crude death rate (b) in
7
85
Life expectancy at birth (years)
2000-2005
(the white diamonds correspond to countries while the black squares correspond to regions)
Of the three indicators in Table 1, only two, life expectancy and the infant
mortality rate are a true reflection of a populations’ state of health. The third, the
crude death rate, obviously depends on the age distribution of the population.
This is easy to see from Figures 2a and 2b. As it was said above, data plotted here
are not all of the same quality. In particular, for some developing countries, the
UN made indirect estimates of life expectancy, sometimes based on infant and
child mortality rates. However, only countries with more than 15 million
population are selected here and in only few of them data on adult mortality are
totally lacking. Indeed if all low levels of life expectancy would have been
deduced from infant mortality rates only, the correlation would be perfect for the
left upper part of the graph, which is not the case.
Thus, Figure 2a confirms the close correlation between life expectancy and
infant mortality; while Figure 2b reveals two distinct sets of countries: the
industrial nations that are already demographically aged by the long-standing low
birth rates, and the developing countries where the population pyramid still
comprises a large proportion of young people. Indeed, some countries with fairly
similar life expectancy levels, such as Chile and Germany (77.9 and 78.7 years)
nevertheless have crude death rates that vary by a factor of two (5.0 for Chile
versus 10.3 p. 1,000 for Germany).
One might be tempted to reject crude rates as a mortality indicator.
However we believe it is useful to mention their distribution here, since it is the
difference between the crude death rate and the birth rate which determines
population growth, depending on countries’ stage of progress in their
demographic transition. Comparing the crude death rate with specific mortality
indicators thus broadens the diversity of health situations by placing it in its
historic context.
II. The end of the Third World concept
The range of mortality rates continued to grow from the onset of the health
transition in Western Europe up to the moment it reached the countries of sub-
8
Saharan Africa. However, until the 1950s the result was to create a wide gap
between the northern countries and what was then called the Third World. In
terms of major population groups, that was certainly the peak in divergence.
From the 1950s to 2000, this gap began to close rapidly because of the variety of
situations within the third world itself. From the health point of view, the “third
world” notion had practically disappeared. Life expectancy and infant mortality
rates were no longer common characteristics of the impoverished South. To
illustrate this important aspect in developments during the past decades, we have
shown (in Figures 3a, b and c) the total world population according to life
expectancy at birth in three different five-year periods (1950-1955, 1975-1980
and 2000-2005), identifying developed and developing countries according to the
United Nations definition.
9
Total population (millions)
2000
Total population (millions)
2000
1950-1955
1500
Total population (millions)
2000
1975-1980
1500
Developing countries
1500
Developing countries
1000
2000-2005
Developed
countries
1000
1000
500
500
Developed
countries
Developing countries
Developed countries
500
Sub-Sah.Africa
Sub-Sah.Africa
Sub-Sah.Africa
East. Europe
0
0
30
40
50
60
70
East. Europe
East. Europe
80
0
30
40
50
60
70
80
Life expectancy (years)
Life expectancy (years)
Figure 3 : Aggregate populations by life-expectancy
10
30
40
50
60
70
80
Life expectancy (years)
In 1950-1955, most of the developing countries were concentrated around
the 35-47 years life expectancy mark, far behind the major developed countries
who were grouped around 65-70 years. In 1975-1980, the rich counties remained
grouped together but had gained five years in the meantime, whereas the poor
countries were suddenly scattered due to a large population whose life expectancy
had grown much closer to that of the rich countries. In 2000-2005, the change is
still more pronounced and the developing countries’ histogram shows a strong
concentration in the 60-75 range, very close to that of the developed countries,
even though these had gained a further five years. There is even an overlap
between the ex-third world and the industrialized countries because of the recent
divergence in the two first worlds: East and West. The central European countries
are now in the same life expectancy range as China, while Russia stands in the
same category as India. At the same time a fairly large portion of the developing
nations, namely the countries of sub-Saharan Africa, lags far behind.
In 50 years, the geography of mortality has changed completely. The top
map in Figure 4 is a clear illustration of the situation that prevailed at the
beginning of the 1950s. The contrast between the North (including Australia and
New Zealand) where life expectancy was above 60 years in most of the countries,
and the South where it was less than 45 years, is striking. In-between these two
very distinct worlds were the South and Central American countries, which began
to progress during the interwar period, and had a life expectancy at birth of
around 55 years. Half a century later, this simple dichotomy in the geography of
mortality no longer applies (bottom map of Figure 4).
In 2000-2005, the map of life expectancies at birth reveals the contrasting
situation in both sub-Saharan Africa and Eastern Europe with the rest of the
world. While there has been a clear convergence for the great majority of
countries, life expectancy remains at low levels in these two regions. The
situation is particularly serious in Africa where 20 countries have still a life
expectancy of less than 50 years. On the other hand, some countries have made
spectacular progress. That is the case of China (Bannister, 1987) and Southeast
Asia, as well as North Africa. This rapid progress contrasts with the relative
deterioration of the situation in most of the Eastern European countries (Meslé,
1991), and especially in Russia (Meslé et al., 2000; Meslé et al., 2003).
Figure 4. Life expectancy at birth in the world in 1950-1955 and 2000-2005
Figure 5 shows life expectancy since 1950 in some of the most denselypopulated countries of the world, with the most detail available. It reveals a dual
12
trend of convergence/divergence. Among the industrialized nations, Japan
advanced at a fast and regular pace compared with Russia, which caught up in the
1950s but fell back considerably after the mid-1960s. Between these two
extremes, the US and France followed similar intermediate trajectories, with
France being the more dynamic of the two at the start and end of that period.
Life expectancy at birth (years)
85
Japan
France
75
USA
Russia
China
65
Indonesia
India
Mexico
55
Zambia
45
Nigeria
35
China
25
1950
1960
1970
1980
1990
2000
Figure 5: Evolution of life expectancy in several large countries
Sources: China: Banister 1987, and the UN 2006, US: Census Bureau: 1975, 1985 and 1992,
Japan: Institute of Population Problems 1993, Nanjo et al. 1985, Russia: Meslé et al. 2003,
France: Vallin and Meslé 2001, other countries: UN 2006.
Among the developing nations, China largely succeeded in catching up with
countries such as the US and France in the space of twenty-five years (from 1950
to 1975) despite the disastrous Great Leap Forward and caught up with Mexico –
supposedly ahead among the developing nations – as early as 1965. However,
since the end of the 1970s China has been advancing at a slower pace. India, and
Indonesia have made rapid progress, particularly the latter, and have succeeded in
13
considerably narrowing the gap with the industrial nations. We should not attach
too much importance to the regular pace of the progress, which is pieced together
in this figure from the United Nations’ five-yearly estimates, but the general
trends are significant. This is especially true for the sharp divergence between
these two countries and Nigeria or Zambia. Africa as a whole has, of course,
made progress, but far less than the rest of the third world, and countries most
affected by AIDS, such as Zambia, have lost several years of life expectancy.
III. The stages of health transition
According to Omran’s epidemiologic transition theory (1971), populations
progressed from an “age of pestilence and famine” to an “age of degenerative and
man-made diseases” by controlling infectious diseases. This simplification fitted
in well with the advances, that, in the 1970s, had visibly occurred since the end of
the war. In just 25 years, the discovery and propagation of simple medical
techniques (vaccinations, antibiotics, DDT) had made considerable inroads
against infectious diseases throughout the world, irrespective of levels of
economic development. The 1950s and 1960s were times of great progress worldwide, and infant and child mortality fell sharply thanks to a large reduction in
infectious mortality.
Since 1970 trends have become more complex. For the first time, progress
levelled off in advanced countries. As Omran predicted, after infectious diseases
had been defeated, the rise or stagnation in mortality from degenerative diseases
seemed to prohibit more substantial progress in life expectancy. However, very
quickly, weapons were found to fight these modern plagues and the
cardiovascular revolution of the 1970s launched a new period of progress (Vallin
and Meslé, 2001).
Without criticizing the basic premises of the epidemiologic transition
theory, Jay Olshansky and Brian Ault (1986), followed by Richard Rogers and
Robert Hackenberg (1987), introduced the idea of a "fourth stage" (Olshansky
and Ault referred to "A fourth stage of the epidemiologic transition"; Rogers and
Hackenberg referred to a "new" or an "hybristic" stage) during which the
maximum point of convergence of life expectancies would increase thanks to
achievements in the treatment of cardiovascular diseases. Jay Olshansky et al.
(1990) set this new maximum at 85 years, the same as that chosen for all
countries by the United Nations at the end of the 1980s (United Nations, 1989) to
14
make their world population projections. Today, however, the 85-year threshold
is strongly criticized by many authors who believe that such a limit cannot be
determined (Vaupel, 2001; Carey and Judge, 2001; Barbi et al., 2003).
The very high life expectancy levels obtained by countries such as Japan or
France are due to a combination of factors which together have contributed to the
reduction of mortality, especially in old age. Among these factors, we may cite
prevention campaigns against excess alcohol consumption and tobacco smoking,
the systematic screening of hypercholesterolemia and hypertension, supply of
new therapeutics, development of emergency care system, early screening of
uterus or breast cancer.
Conversely, the gains achieved in the West did not spread to central and
eastern Europe. Life expectancy in all East European countries began to plateau
or even decrease, especially for males. The huge gap between two parts of
Europe continued to widen for at least two decades, resulting in a yawning divide
by the mid 1980s. The divergence was not only a matter of trends in life
expectancy but the result of major changes in age and the cause-of-death structure
of mortality (Meslé et al., 2003, Meslé and Vallin, 2002, Vallin and Meslé,
2004). However, from the mid 1980s, changes in these unfavourable trends
differed in the former Soviet Union countries and in central Europe. While large
fluctuations were observed in former USSR countries and gave rise to the current
situation — which is even worse than the previous one — central European
countries clearly returned to a steady improvement in life expectancy. Figure 6
summarises this succession of converging and diverging trends by focussing on
three Western industrialized countries (France, the USA and Japan), two Central
European countries (Czech Republic and Poland), and two former Soviet Union
countries (Russia and Ukraine). The figure clearly shows the impressive
convergence which brought all the industrialised countries very close to the 70year level, and then the divergence between Western and communist countries
from 1965 to 1985 and finally the divergence between Central Europe and the
former USSR since 1985
15
Life expectancy at birth (years)
Japan
80
France
75
USA
Czech R.
Poland
70
Ukraine
Russia
65
60
55
1950
1960
1970
1980
1990
2000
Figure 6. Life expectancy at birth in central and eastern European countries
compared to certain industrialized countries.
Source : Meslé and Vallin, 2007
The favourable trends observed in Western Europe back in the early 1970s
have now spread to the countries in central Europe. These are similarly affected
by the dramatic decrease in cardiovascular mortality. It is still difficult to assess
the main determinants of such a reversal. The progress probably results from a
combination of several factors, such as changes in diet, the growth of systematic
prevention and screening, the spread of new forms of treatment, and cardiac
surgery. Such a progress seems to extend to all the central European countries,
including the Baltic states. Unfortunately this has still not reached Russia and the
Ukraine (Meslé and Vallin, 2007).
16
At the other end of the range of countries, we have already stressed the
backwardness of sub-Saharan Africa in this respect. A growing number of
countries in this region appear to be missing out on the phase of rapid progress
experienced by other developing countries before them, largely because of the
world economic crisis which has affected this area of the world more than any
other. Not only did these countries fail to control the old infectious diseases such
as tuberculosis, which is now re-emerging, or malaria for which drug resistance is
increasing, but they also had to face the abrupt appearance of AIDS. In the 2006
United Nations projections, the present and future life expectancy trends for some
of the African countries hardest hit by AIDS are very pessimistic (Figure 7).
Life expectancy at birth (years)
65
South Africa
Botswana
Namibia
60
Kenya
55
Zimbabwe
50
Zambia
45
40
35
1955
1965
1975
1985
1995
2005
Figure 7. Life expectancy at birth in the six countries hardest hit by AIDS
Source: United Nations, 2006
In Botswana, for instance, United Nations estimates show a 17-year
decrease in life expectancy from 64 years in 1985-1990 to 46 in 2000-2005.
South Africa also suffers greatly from this increase in mortality due to AIDS,
with an anticipated life expectancy of 49 years in 2005-2010 whereas it had
17
reached 62 years in 1990-1995. In all regions, life expectancy is back to levels
observed in the 1960s or even before. It will take several decades before these
countries return to their 1990 levels.
IV. What assumptions for the future?
Yet these failures, however significant, do not question the epidemiologic
transition theory as such. But they do indicate that some countries, for reasons
inherent to their own history, economic development or culture, have encountered
serious obstacles that have prevented them from completing certain stages of the
transition. In Eastern Europe, the communist regimes relied almost too
exclusively on the centralized administration of modern health care, whereas the
shift towards a new stage of epidemiologic transition requires significant changes
in behaviour, making individuals actively responsible for their own health. In
addition, the economies of those countries, which were involved in a ruinous
arms and space race with the West, did not have sufficient means to create an
efficient health system for dealing with chronic diseases. The countries of subSaharan Africa, which are much more vulnerable to the generalized transmission
of HIV due to widespread multiple partnership practices and the wide variability
of partner age differentials, were very hard pressed by the epidemic just at a time
when their very fragile economies were facing a global economic crisis which, in
itself, had already wrought its inevitable consequences on poor local health
services. Prevention methods, and, more recently, medical treatment for AIDS do
exist and have proven to be effective in the northern countries, but for the time
being Africa cannot afford them. In all cases, health care policies need to be
improved and adequately funded for these countries to achieve their
epidemiologic transition.
Abdel Omran's theory of epidemiologic transition may run up against a
more profound contradiction in the renewed sharp rise in life expectancy
observed in Western countries since the 1970s. Would adding a fourth phase to
Omran's initial theory (Olshansky and Ault, 1986; Rogers and Hackenberg, 1987;
Omran, 1998) as well as a fifth one to take on board AIDS (Olshansky et al.,
1998) suffice to take into account this phenomenon? Perhaps the theory itself
needs to be revised. First, as we have said, the reasons behind the emergence or
resurgence of infectious diseases are no different from those governing the
second phase of Omran's transition: the danger of infection can never be
18
completely eradicated, only brought under control, and if the battle is fought in
unfavourable conditions, all that has been gained may suddenly be lost, as shown
by the dramatic situation in Africa. In fact, the situations in Eastern Europe and
Africa do not so much challenge Omran's theory, as question the idea that life
expectancies are rapidly converging towards a maximum level. In addition,
Western advances in the treatment of cardiovascular diseases since the 1970s can
be explained by the development of a new strategy based on advanced medical
technology and changes in individual behaviour, especially diet. But not all
countries are equally prepared to adopt these new strategies, as may be seen in
eastern Europe. The question arises for many developing countries which have
exceeded a life expectancy of 70 years: will they manage to catch up with
Western countries in this, as they did with infectious diseases (Vallin, 1992)?
Following the proposal made ten years ago by Julio Frenk et al. (1991), the
concept of epidemiologic transition might usefully be replaced by the wider
concept of "health transition", which would include not only the development of
epidemiologic characteristics within the overall health situation, but also the ways
in which societies respond to a health situation and vice versa (Caselli, 1995;
Meslé and Vallin, 2006).
Arguably, every major improvement in matters of health is likely to lead
first to a divergence in mortality, since the most favoured segments of the
population benefit most from the improvement. When the rest of the population
has access to the benefit of the improvement (through better social conditions,
behavioural changes, health policies, etc.), a phase of convergence begins and can
lead to a standardization until a new major advance occurs. The entire health
transition process thus breaks down into successive stages, each including a
specific divergence-convergence sub-process. From the 18th century to the
present, at least two and perhaps even three of these successive stages have
occurred or are occurring: the vanquishing of infectious diseases (Omran’s
epidemiologic transition, in fact), the cardiovascular revolution, and finally the
fight against ageing (Vallin and Meslé, 2004).
V. Divergence and convergence
After being powerless in the face of death for thousands of years, in the
space of two centuries — from Molière’s doctors to the discovery of antibiotics,
via Pasteur and his vaccines — humankind finally acquired efficient means with
19
which to fight infectious diseases. At the outset this only benefited a tiny fraction
of humanity in Western Europe, where these means had been discovered and
developed, resulting in a deep division in the life expectancies of those countries
and the rest of the world. Gradually however, these recipes for progress in health
spread to southern Europe, North America, the East as far as Meiji-era Japan and
finally to the third world after World War II. The initial divergence thus gave way
to a general movement of convergence which peaked in the 1960s and inspired
Omran’s theory of epidemiologic transition, but also blinded him to the
possibility of other changes causes by other forms of progress.
We know the rest: in the thirty years from the 1970s to the end of the
twentieth century the revolution in cardiovascular medicine broke through that
ceiling which, according to Omran, capped all degenerative diseases. Once again,
before the third world countries could catch up with the West, a new phase of
deep divergence arose between Western countries in the industrialized nations
which had developed the new technologies for treating cardiovascular disease,
and the Communist countries with antiquated health strategies. The life
expectancy in the West thus rose above the 76 years in Jean Bourgeois-Pichat’s
table of biological mortality. It is true that since the fall of the Berlin Wall, a few
countries from the former Communist bloc — those in central Europe and the
Baltic — have also entered the “cardiovascular revolution”, and begun a new
movement of convergence, but that is not the case with Russia, the Ukraine, or
Byelorussia. And just to make matters more complicated, that was the moment
when AIDS burst onto the scene and furthered aggravated the fragmentation in
the third world, leading to a spectacular lowering of life expectancy in several
African countries.
But the movement did not stop there. A new phase of divergence between
the most advanced countries of the planet appears to have started during the last
decade of the twentieth century. Whereas the rise in female life expectancy as a
result of the cardiovascular revolution is slowing down in certain countries such
as the US or the Netherlands, it is continuing at a regular, or even a faster pace in
some countries such as France and Japan. These two countries appear to have
reached a new stage in the battle against ageing, leaving the others behind.
However speculation increases when questions are raised about possible
future mortality trends in countries where mortality has already dramatically
decreased. What is the limit? Is there a limit? Those questions are at the heart of
the debate today.
20
VI. Is there any limit to life expectancy growth?
An optimistic standpoint might envisage that mortality from the main causes
of death, such as cardiovascular disease and cancer, will decrease further thanks
to a better control of the risk factors and increasingly effective therapies. One
might even expect that neuro-degenerative diseases, such as Alzheimer’s or
Parkinson’s disease, may be controlled effectively. But many researchers believe
that there will remain a hard core of pathologies, related to the physiological
senescence of the body, that will be impossible to treat. Back in 1952, Jean
Bourgeois-Pichat made a distinction between endogenous mortality, in theory
unavoidable, and exogenous mortality, which depends on external factors
(Bourgeois-Pichat, 1952). However the concept of endogenous mortality itself
varies with time and medical progress. Cancer, for instance, was often considered
to be an endogenous cause of death because it is closely linked to body ageing,
but it also depends largely on external factors such as tobacco or infectious
agents. Indeed, the distinction between endogenous and exogenous is quite vague
since the frontier between avoidable and unavoidable mortality is not fixed but
moves according to medical progress.
Mortality assumptions usually refer explicitly or implicitly to a biological
limit to human life. The limit specific to the human species is generally estimated
at around 120 years. Until now, life expectancy increased because an increasing
number of people could hope for a life span that was growing ever closer to the
possible maximum, but the maximum itself has remained unchanged. Moreover,
that maximum was probably not the same for all. Assuming that future medical
and biological progress allows us to avoid all causes of premature death and that
a life span depends only on the ageing process, it is possible to produce
hypotheses about the importance of individual variations. According to various
authors, the mean of these theoretical individual life spans could range from 85 to
100 years (Olshansky et al., 1990; Duchêne and Wunsch, 1990).
Regarding the most advanced countries, one might reasonably ask whether
limiting the ceiling to 85 years, as is assumed in the United Nations projections,
does not constitute too pessimistic a view for the long term. Admittedly, this
figure is the one put forward by the proponents of an unreachable biological limit
to life (Fries, 1989, Olshansky et al., 1990). However, some demographers
(Myers and Manton, 1984; Bourgeois-Pichat, 1988) as well as some biologists
(Walford, 1984) vigorously refute such a hypothesis and believe that a
technological revolution should, very soon, enable man to control the ageing
21
process of cells thus making it possible to extend life expectancy beyond 100
years. Mortality trends in the extremely old would seem to support this second
hypothesis (Kannistö, 1994, 1996). Whichever of these two hypotheses turns out
to be true, the effects will only have a bearing on reality in the fairly distant
future, it would be wrong to dismiss them as mere conjecture, for both will exert
a strong influence on the ageing of populations already affected by recent gains in
life expectancy at very advanced ages. These developments call for a
reorganisation of industrial societies which will necessarily require some time to
put in place.
VII. Conclusion
Leaving aside the slogan “Health for all in the year 2000”, recent world
mortality trends shed light on the persistence or appearance of crucial issues in
public health. The economic crisis affecting so many African countries, the
resurgence of infectious diseases, the gradual backward slide of Eastern Europe
and the uncertainty surrounding the biological limit to life, provide an abundance
of public health issues that will surely count among the main problems to be
tackled by economic and social policies in the coming decades.
If the extreme diversity of situations runs counter to the hopes raised by the
WHO slogan, it may nevertheless be explained. The severe deterioration of the
health situation as a result of AIDS in Africa is the cruel proof that advances in
health cannot last if they are not accompanied by economic and social
development. And this is certainly where Omran’s theory falls flagrantly short.
Infectious diseases were obviously not the sole factor to be dealt with in
prolonging human life, and Omran’s second error was to have not intuited this.
Lastly, if we admit that every major source of progress naturally triggers off a
first movement of divergence, because not every society is equally ready to
benefit from it, it may be possible to untangle the web of current complexities. In
order to achieve convergence again, the countries who lagged behind at the start
must first obtain the means with which to benefit from it. But one divergenceconvergence process does not have to be completed before another begins. The
diversity of situations can continually increase, so long as there is scope for
further progress in health. Uncertainties as to the biological limits of human life
bring the phenomenon to its climax by opening the door to unlimited progress.
Instead of converging in “health for all”, are we not on a path to a growing
22
inequality of health situations that will only end when the whole of humankind is
in a position to benefit equally from new health innovations?
Table 2. Trends in life expectancy by region and for the 62 countries of more
than 15 million people in 2005, ranked according to the 2000-2005 value
Region and country
World
More developed countries
Intermediate countries (Less developed – Least developed)
Least developed countries
Japan
Australia/New Zealand
Australia
Western Europe (North without Baltic c., South, West)
Spain
Italy
France
Germany
Netherlands
United Kingdom
Northern America
Canada
United States of America
Eastern Asia (without China and Japan)
Taiwan
Republic of Korea
Dem. People's Republic of Korea
China (including Hong Kong and Macao, excluding Taiwan)
Latin America (including the Caribbean)
Chile
Mexico
Argentina
Venezuela
Colombia
Brazil
Peru
South-eastern Asia
Malaysia
Viet Nam
Philippines
Indonesia
Thailand
Myanmar
Western Asia
Syrian Arab Republic
Saudi Arabia
Turkey
Yemen
Iraq
Eastern Europe (including Baltic countries)
Poland
23
Life expectancy at birth
1950-55 1975-80 2000-05 2025-30 2045-50
46.4
60.2
66.0
71.9
75.4
66.1
72.2
75.6
79.8
82.4
41.5
59.2
66.6
72.9
76.4
36.2
46.2
52.7
61.4
67.2
63.9
75.5
81.9
85.2
87.1
69.6
73.3
80.2
83.8
85.9
69.6
73.5
80.4
83.9
86.0
66.6
73.1
78.6
82.1
84.3
63.9
74.3
80.0
83.2
85.4
66.0
73.6
79.9
82.9
85.0
66.5
73.7
79.6
83.0
85.1
67.5
72.5
78.7
81.8
84.1
72.1
75.3
78.7
82.0
84.0
69.2
72.8
78.5
81.9
84.1
68.8
73.4
77.6
80.9
83.3
69.1
74.2
79.8
83.2
85.3
68.9
73.3
77.4
80.7
83.1
50.6
66.7
74.3
78.4
80.6
59.3
71.6
77.3
81.4
83.5
47.5
64.8
77.0
81.4
83.5
50.1
67.2
66.7
70.7
73.4
40.8
65.3
72.0
76.6
79.3
51.4
63.0
72.0
77.1
79.6
54.7
67.1
77.9
80.7
82.2
50.8
65.0
74.9
79.6
81.3
62.5
68.5
74.3
78.5
80.7
55.1
67.5
72.8
77.1
79.6
50.6
63.8
71.7
76.7
79.0
50.9
61.5
71.0
76.6
79.5
43.9
58.4
69.9
75.6
78.2
40.9
55.3
68.5
75.5
78.6
48.5
65.3
73.0
77.5
80.1
40.4
55.8
73.0
77.9
80.3
47.8
60.1
70.3
75.8
78.7
37.5
52.7
68.6
75.7
78.6
50.8
62.5
68.6
74.8
78.1
36.3
56.1
59.9
69.9
74.6
45.2
60.1
68.3
75.2
78.3
45.9
61.2
73.1
77.5
80.0
39.9
58.7
71.6
76.3
79.1
43.6
59.5
70.8
75.5
78.5
32.5
44.2
60.3
70.4
75.0
45.3
60.4
57.0
72.1
76.1
64.2
69.0
67.9
72.6
75.9
61.3
70.9
74.6
78.6
80.9
Romania
61.1
69.5
71.3
76.4
Ukraine
65.9
69.4
67.6
72.0
Russian Federation
64.5
68.0
64.8
69.7
Northern Africa
41.8
53.9
67.1
73.3
Algeria
43.1
58.0
71.0
76.2
Egypt
41.9
53.3
69.8
75.6
Morocco
42.9
55.7
69.6
75.5
Sudan
38.6
47.8
56.4
65.4
37.4
54.2
62.9
71.4
India
South-central Asia (without India)
41.3
52.3
62.4
69.6
Sri Lanka
57.6
65.9
70.8
75.1
Iran (Islamic Republic of)
44.9
57.7
69.5
75.4
Uzbekistan
55.8
64.7
66.5
70.8
Kazakhstan
55.0
64.2
64.9
73.2
Pakistan
43.4
54.0
63.6
71.4
Bangladesh
37.5
46.9
62.0
71.2
Nepal
36.2
46.7
61.3
71.1
Afghanistan
28.8
38.4
42.1
50.8
Melanesia, Micronesia and Polynesia
39.4
53.6
60.6
66.0
Southern Africa
44.7
55.4
52.5
55.7
South Africa
45.0
55.5
53.4
56.0
Tropical Africa (Eastern, Middle, Western)
36.9
46.7
48.4
57.6
Ghana
43.1
51.8
58.5
66.4
Madagascar
36.7
46.9
57.3
65.6
Kenya
42.3
56.2
51.0
61.2
Ethiopia
34.1
44.5
50.7
60.8
Cameroon
38.5
49.4
49.9
57.3
United Republic of Tanzania
41.2
49.9
49.7
59.7
Uganda
40.0
50.4
47.8
59.8
Côte d'Ivoire
40.5
52.4
46.8
55.8
Nigeria
36.3
44.5
46.6
54.4
Democratic Republic of the Congo
39.1
47.8
45.0
53.3
Mozambique
31.3
42.5
44.0
49.4
Angola
30.0
39.5
41.0
50.3
Source : United Nation 2006 World Population Prospects (for Taiwan, see http://www.moi.gov.tw/stat/english).
24
79.1
75.2
73.4
76.7
79.0
78.6
78.6
70.3
75.6
74.0
77.6
78.4
74.3
76.9
75.7
75.5
75.5
58.7
70.5
62.4
62.6
64.4
70.9
71.3
67.2
67.3
64.4
66.1
65.2
62.6
62.1
60.9
57.2
58.2
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mortality trends and cause-of-death patterns in the European countries during the second
half of the XXth century. French version]
VALLIN (Jacques) et MESLÉ (France), 2001. – Trends in mortality in Europe since 1950 : age-,
sex-and cause-spécific mortality, in : COUNCIL OF EUROPE (ed), Trends in mortality and
differential mortality, p. 31-186. – Strasbourg, Council of Europe Publishing, 334 p.
(Population Studies n° 36). [A comprehensive view and discussion of mortality trends and
cause-of-death patterns in the European countries during the second half of the XXth
century. English version]
VALLIN (Jacques) et MESLE (France), 2004. – Convergences and divergences in mortality. A
new approach to health transition, Demographic Research, p. 12-43. (Special Collection 2.
Determinants of Diverging Trends in Mortality). [A attempt to renew the interpretation of
the historical changes and geographical disparities in human mortality]
VAUPEL (James W.), 2001. – Demographic insights into longevity, Population, An English
Selection, vol. 13, n° 1, p. 245-260. [A short overview on longevity facts, models and
theories]
WALFORD (Roy), 1984. – Maximum life span. – New York, Avon, 230 p. [The prediction of a
large biological room for human longevity extension]
Glossary
Cardiovascular revolution. The new approach of cardiovascular diseases that
led the Western industrialized countries to reduce dramatically their
cardiovascular mortality, starting in the 1970s.
Crude death rate. Number of deaths observed during one calendar year divided
by the total mean population of the same year. This indicator depends not only
on the level of mortality but also on the age pattern of the population. Indeed,
since mortality risks are much higher for old people than for young people,
same mortality risks will give an higher crude death rate in a population where
the proportion of old people is high than in a population where such proportion
is low.
Degenerative diseases. Diseases originated in the degradation of the human
body either because of ageing process (like many cardivascular diseases) or
because of disruption of physiological equilibriums (like cancer). This concept
oppose that of diseases provoked by the invasive action of external agents like
infectious diseases or accidents.
Endogenous mortality. Concept proposed by Jean-Bourgeois Pichat in the early
1950s to characterize mortality due to biological weakness or deficiencies of
individuals. Opposed to exogenous.
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Epidemmiologic transition. The words used by Abdel Omran to found his
explanatory theory of historical mortality change on the basis of the change
causes-of-death patterns.
Exogenous mortality. Concept proposed by Jean-Bourgeois Pichat in the early
1950s to characterize mortality due to external agression (mainly infectious
diseases). Opposed to endogenous.
Health transition. Expression used by Julio Frenk and many other authors to
found a new explanatory theory of historical changes in mortality, not only
based on cause-of-death patterns but also on the type of development and the
level of achievements of the societies.
Infant mortality rate. Number of deaths under one year of age observed during
one calendar year divided by the number of births observed during the same
year.
Life expectancy. Mean duration of life that would be experienced by the
individuals of a hypothetical cohort that would be affected all along the life by
age-specific deaths rates observed in the year for which it has been computed.
Life expectancy can be calculated at birth (it is then the total mean duration of
life) or at any age (the mean duration of life after that age). For a population,
life expectancy at birth is an indicator of its level of mortality independent of
its age structure. This indicator allows to compare mortality of very different
populations and to trace actual mortality changes of a changing population.
Man made diseases. Diseases caused by human activity or behaviour, like work
accident, professional diseases, traffic accident, alcoholism, tobacco-related
diseases, suicide, homicide, etc.
Third World. An expression forged in the 1950’s by Alfred Sauvy to focus on
the political emergence of third world in between the first one (the
industrialized Western countries) and le second one (the Eastern countries
under communist regime) then opposed by the cold war. The Third World was
made of numerous poor countries getting soon their political independence.
From a demographic point of view they were charaterized by very high levels
of fertility and mortality and by heavy proportions of young children as well as
by an accelerating population growth. Today, there are so huge differences in
mortality and fertility among these countries that the concept no longuer fit
with their actual situation.
Biographical sketches
France Meslé. Medical Doctor and demographer, France
Meslé is directrice de recherche at the Institut national d’études
démographiques (INED) in Paris, where she heads the research unit
« Mortalité, santé, épidémiologie ». Her main works deal with
mortality and causes of death in many different countries She is
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particularly involved in long run mortality change analyses, based on the reconstruction
of cause-of-deaths statistics according to a constant medical definition. For many years,
she heads a broad project on the health crisis that hit countries of the ex-USSR since the
1960s, in collaboration with the Centre for Demography and Human Ecology in
Moscou, the Max Planck Institute for Demographic Research in Rostock and several
other research teams from former Soviet Republics. She has been responsible for the
creation of the INED Website and chief redactor of the European Population Journal
from 2000 to 2005. She teaches doctoral students both in Paris and Rostock, Germany.
She is author or co-author of several books and of many articles published in
demographic or epidemiological journals.
Jacques Vallin. Doctor in economics and demographer
Jacques Vallin is directeur de recherche émérite at INED. He mainly
explored two research fields, starting with population growth
components in developing countries and then dealing with mortality
trends and cause-of-death patterns in developed countries. He
founded with France Meslé a method to reconstruct long term series
of cause-of-deaths statistics according to a constant medical
definition, first applied to 1925-1978 French data. A method that
allowed later to make the same type of reconstruction in different
countries, including the former Soviet Union countries. From 1994
to 1997 Jacques Vallin has been appointed as director of the Centre français sur la
population et le développement (CEPED) to straighten its reseach activity and
publications. Back to INED, he founded the research unit « Population et
développement » and developed research activities in the research unit « Mortalité,
santé, épidémiologie ». Member of the IUSSP (International Union for the Scientific
Studiy of Population) Council (1993-97), then vice-president (1998-2001) and President
(2002-2005), he is now Honorary President of the Union. He is author or co-author of
about 15 books and hundred of articles published in demographic or epidemiological
journals.
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