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Age Standardization of Rates: A New WHO Standard

Authors:
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AGE STANDARDIZATION OF RATES:
A NEW WHO STANDARD
Omar B. Ahmad
Cynthia Boschi-Pinto
Alan D. Lopez
Christopher JL Murray
Rafael Lozano
Mie Inoue
GPE Discussion Paper Series: No.31
EIP/GPE/EBD
World Health Organization 2001
2
Summary
A recent WHO analysis has revealed the need for a new world standard population (see
attached table). This has become particularly pertinent given the rapid and continued
declines in age-specific mortality rates among the oldest old, and the increasing
availability of epidemiological data for higher age groups. There is clearly no conceptual
justification for choosing one standard over another, hence the choice is arbitrary.
However, choosing a standard population with higher proportions in the younger age
groups tends to weight events at these ages disproportionately. Similarly, choosing an
older standard does the opposite. Hence, rather than selecting a standard to match the
current age-structure of some population(s), the WHO adopted a standard based on the
average age-structure of those populations to be compared (the world) over the likely
period of time that a new standard will be used (some 25-30 years), using the latest UN
assessment for 1998 (UN Population Division, 1998). From these estimates, an average
world population age-structure was constructed for the period 2000-2025. The use of an
average world population, as well as a time series of observations, removes the effects of
historical events such as wars and famine on population age composition. The terminal
age group in the new WHO standard population has been extended out to 100 years and
over, rather than the 85 and over as is the current practice. The WHO World Standard
population has fewer children and notably more adults aged 70 and above than the world
standard. It is also notably younger than the European standard.
It is important to note, however, that the age standardized death rates based on the new
standard are not comparable to previous estimates that are based on some earlier
standard(s). However, to facilitate comparative analyses, WHO will disseminate trend
analyses of the completehistorical mortality data using on the new WHO World
Standard Population in future editions of the World Health Statistics Annual.
3
Introduction
In epidemiology and demography, most rates, such as incidence, prevalence, mortality,
are strongly age-dependent, with risks rising (e.g. chronic diseases) or declining (e.g.
measles) with age. In part this is biological (e.g. immunity acquisition), and in part it
reflects the hazards of cumulative exposure, as is the case for many forms of cancer. For
many purposes, age-specific comparisons may be the most useful. However,
comparisons of crude age-specific rates over time and between populations may be very
misleading if the underlying age composition differs in the populations being compared.
Hence, for a variety of purposes, a single age-independent index, representing a set of
age-specific rates, may be more appropriate. This is achieved by a process of age
standardization or age adjustment.
There are several techniques for adjusting age-specific rates. Among them are direct and
indirect standardization (Wolfenden, 1923), the geometric mean (Schoen, 1970),
equivalent average death rates (Hill, 1977), life table rates, Yerushalmys index
(Yerushalmy, 1951), cumulative death rates (Breslow and Day, 1981), absolute
probabilities of death and the comparative mortality index ((Peto et al, 1994, Breslow &
Day, 1980, 1981; 1987; Esteve et al, 1994). However, with the increasing availability of
age-specific rates, the use of direct age standardization has become the predominant
technique in most applications of demography and epidemiology.
Direct standardization yields a standardized or age-adjusted death rate, which is a
weighted average of the age-specific rates, for each of the populations to be compared.
The weights applied represent the relative age distribution of the arbitrary external
population (the standard). This provides, for each population, a single summary rate that
reflects the number of events that would have been expected if the populations being
compared had had identical age distribution. Symbolically, the directly standardized
mortality rate for populations A and B are given by the following equations:
where nis is the mid-year population in the ith age group of the standard population, ria
and rib are the death rates in age group i in populations A and B, respectively. The ratio of
two such standardized rates is referred to as the Comparative Mortality Ratio (CMR), a
very useful measure. If the age-specific rates in the populations being compared have a
roughly consistent relationship from one age group to the next, the selection of a standard
population will not substantially affect comparisons among groups or time periods. In
reality, however, the relative differences are usually not constant from one age group to
another. As such, both the comparison as well as the conclusions drawn are influenced
by the chosen standard.
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In this paper, we review the existing standard populations currently in use for
international comparison, the Segi (“world”) and the Scandinavian (European) standard
populations. Based on this review, a new WHO World Standard age-structure is
presented for epidemiological comparisons using the direct approach. The age
composition of the new standard has been chosen to better reflect the future age structure
of the worlds population for which comparative rates will be needed.
History of Direct standardization
By the middle of the nineteenth century, public health practitioners in England had began
to recognize that simple crude rates were inappropriate summary measures for comparing
population health when the age distribution of the geographic areas were markedly
different. Discussions centered around the development of a summary mortality index
free from the effect of age differences. In a paper he read to the Statistical Society of
London, Sir Edwin Chadwick, one of the early public health reformers in England,
proposed the use of the mean age at deathas a summary measure for comparing the
health condition of the various sanitary districtsaround London (Finer, 1952; Lewis,
1991). This index, he argued, represented a true summary of the age-specific risks of
dying. In response, Neison, a practicing actuary, disagreed with Chadwicks underlying
logic. He argued that since mortality increased with age, Chadwicks mean age at death
for geographic areas with a relatively older population would tend to overstate excess
mortality. In a subsequent article, Neison demonstrated the fallacy in Chadwicks
argument by comparing the crude mean age at death with the mean age computed by a
method of direct standardization (Neison 1844). Neison was, thus, the first to introduced
both the concepts of direct and indirect standardization, as well as the term standard
population.
The Registrar Generals report of 1883 was the first reported use of Neisons direct
standardization method, using the 1881 population census of England and Wales as the
standard (most current at the time). In subsequent reports, the standard was changed each
time there was a new census, i.e., every ten years (Woolsey, et al., 1959; Benjamin, et al.,
1980). These frequent changes of the standard were cumbersome since historical rates
had to be recalculated each time in order to assess current trends. As a solution, the 1901
population census was eventually adopted as a general standard in England and Wales,
and remained unchanged even when a new census became available.
In order to facilitate comparison with mortality rates in England and Wales, the United
States adopted the 1901 British standard. This practice continued until the early 1940s
when it was decided that the difference between the US population at the time and the
1901 English population was significant enough to warrant a change in standard. As a
result, the US adopted its 1940 census population (the most current at the time) as the
new standard. Recently, however, there has been growing concern that the 1940 standard
no longer reflects the increasingly older US age structure. In response, the National
Center for Health Statistics sponsored two national workshops in 1991 and 1997 on the
issue of a new US standard. The final report of these workshops recommended the
adoption of a new standard based on the projected 2000 population age distribution
(NCHS, 1998).
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An International Standard Population
The idea of a truly international standard was first suggested by Ogle in 1892. His
proposed standard was an amalgam based on the experience of seven European countries
(Ogle, 1892). There is, however, no evidence of its subsequent adoption for international
comparison by any country. Various standards have been proposed since then but none
adopted widely. The debate has centered largely around the question of whether any one
standard is more suitable than others. This question was discussed at a May 1965
subcommittee meeting of the International Union Against Cancer (IUAC) Conference in
London. Three standard populations were suggested. Each was deemed appropriate for
particular population types. One standard had a high proportion of young people and was
considered appropriate for making comparisons with populations in Africa (Knowelden
and Oettlé, 1962). The second (European) standard was based on the experience of
Scandinavian populations, which contained a relatively high proportion of old people and
was judged particularly suitable for comparison within Western Europe (Doll and Cook,
1967). The third was proposed by Segi (1960) as an intermediate “world” standard based
on the experience of 46 countries. The Europeanand “world” standards were
subsequently adopted by WHO for use in calculating age-standardized death rates. These
standards are shown in Table 1 together with the new WHO World Standard (shown in
abbreviated form for purposes of comparison).
As discussed earlier, the choice of a standard can markedly alter comparisons between
populations. Table 2 shows a time series of circulatory disease mortality among US
males for the period 1970-1995 using the three standards (Segi, Scandinavian and the
WHO World Standard). Even though the overall percentage decline from 1970 to 1995
is almost the same for all three standards (48-49%), the relative differences in the
standardized rates, using the WHO standard as baseline, varies from 20% in one
standard to +24% in the other. Table 3 compares twenty countries on the standardized
death rates for respiratory infections as well as the ranking of countries according to
rates. In general, the Scandinavian standard tends to yield rankings that are closer to
those obtained with the WHO World Standard. In about half the cases, there are only
minor differences in ranking between the three standards. In other cases, however,
substantial shifts in ranking occur when the standard is changed. For instance, the
Russian Federation ranks 9th on the Segi but 13th on the Scandinavian and WHO
standards. Similarly, Cuba ranks 10th on the Scandinavian, 11th on the WHO and 14th on
the Segi. The differences in the actual rates are even more dramatic. The age-
standardized mortality rate for respiratory infections for Hong Kong ranges from 44.9
using the Segi standard to 76.9 using the Scandinavian (European). Much larger
differences are evident in some of the other countries. If the choice of a population
standard for direct age-standardization can have such marked influence on comparisons
over time and between populations, how should a world standard be selected?
A New WHO World Standard Population
Age-structure varies tremendously across populations of the world at different levels of
the demographic transition. Should one, therefore, choose a standard population with
higher proportions in the younger age groups (thereby weighting events at these ages
disproportionately), or choose an older standard, or rather something in-between? There
6
is clearly no conceptual justification for choosing one standard over another, hence the
choice will eventually be arbitrary. Whatever standard is chosen should ideally be
maintained for a number of years, during which time the age-structure of populations will
alter. For this reason, attempting to match a particular standard to current population age
structures is insufficient justification for choosing one standard over another. Hence,
rather than selecting a standard to match the current age-structure of some population(s),
the standard must be chosen to reflect the average age-structure of all populations to be
compared over the period of use.
The approach proposed by WHO is to base the standard on the average age-structure of
those populations to be compared (the world) over the likely period of time that a new
standard will be used (some 25-30 years). The United Nations Population Division
carries out two-yearly comprehensive assessment of population age-structure for each
country by age and sex (the latest assessment is for 1998 - UN Population Division,
1998). Estimates are prepared for countries for each quinquinnial year from 1950 and
projected to 2025, based on population censuses and other demographic sources, adjusted
for enumeration errors. From these estimates, an average world population age-structure
is constructed for the period 2000-2025. Figure 1 shows the expected evolution of the
worlds population age-structure over the first quarter of the 21st century, and the average
composition which defines the new WHO World Standard.
The use of an average world population, as well as a time series of observations removes
the effects of historical events such as wars and famine on population age composition.
Table 4 gives the percentage of the population in each 5-year age group in the new WHO
World Standard population. Given the rapid and continued declines in age-specific
mortality rates among the oldest old, and the increasing availability of epidemiological
data for higher age groups, the terminal age group in the new standard population has
been extended out to 100 years and over, rather than the 85 and over as is the current
practice. The difference with respect to the Segi and Scandinavian standards can be seen
in Figure 2. The WHO World Standard population has fewer children and notably more
adults aged 70 and above than the Segi standard. It is also notably younger than the
Scandinavian standard. Implementation of this new standard will facilitate international
comparative analysis and reduce confusion among data users.
Discussion
To facilitate comparisons of sets of age-specific epidemiological and demographic rates
across populations with different age composition, it is useful to calculate summary
health statistics which remove the effects of variation in age structure. The dominant
method currently in use is the direct age-standardization of rates using an arbitrary
standard population. National (as exemplified by the United Kingdom and the United
States) and international experience suggest that population standards have been adopted
for arbitrary reasons and once adopted have been used for many decades. Given current
WHO initiatives, which involve comparisons of vastly different populations, existing
standards appear too extreme. We present a new WHO World Population Standard which
is especially defined to reflect the average age structure of the worlds population
expected over the next generation, from the year 2000 to 2025. Comparisons across
populations of the world should preferably be based on an average world population age
7
structure and that average age structure should correspond to the period of likely use of a
standard (20-30 years).
To facilitate comparisons globally, all age-standardized rates produced by WHO will be
made according to the new WHO World Standard Population. Hopefully, this single
standard will be widely adopted for global comparisons.
8
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Table 1. Standard Population Distribution (percent)
Age group Segi (“world”) standard Scandinavian (“European) standard WHO World Standard*
0-4 12.00 8.00 8.86
5-9 10.00 7.00 8.69
10-14 9.00 7.00 8.60
15-19 9.00 7.00 8.47
20-24 8.00 7.00 8.22
25-29 8.00 7.00 7.93
30-34 6.00 7.00 7.61
35-39 6.00 7.00 7.15
40-44 6.00 7.00 6.59
45-49 6.00 7.00 6.04
50-54 5.00 7.00 5.37
55-59 4.00 6.00 4.55
60-64 4.00 5.00 3.72
65-69 3.00 4.00 2.96
70-74 2.00 3.00 2.21
75-79 1.00 2.00 1.52
80-84 0.50 1.00 0.91
85+ 0.50 1.00 0.63
Total 100.00 100.00 100.00
* For purposes of comparison, the WHO Standard age group 85+ is an aggregate of the age groups 85-89, 90-94, 95-99
and 100+.
Table 2. Trend in Age-adjusted Circulatory Disease Mortality Rates Based on the Segi, Scandinavian and WHO
World Standard Populations and the Cumulative Death Rates - US Males (1970-1995)
Rates per 100,000
Standard 1970 1975 1980 1985 1990 1995 % Change 1970-1995
Segi 459.5 399.0 350.3 305.8 256.8 232.3 -49.4
WHO World 550.9 482.2 426.7 373.7 315.0 285.4 -48.2
Scandinavian 720.1 630.4 557.8 488.4 411.6 372.4 -48.3
Percent Difference in Rates Relative to WHO World Standard
Segi -20% -21% -22% -22% -23% -23%
Scandinavian 23% 24% 24% 23% 23% 23%
11
Table 3. Directly standardized male death rates from respiratory infections
and ranking of twenty countries using three different standard populations - (Around 1995)
Rates Per 100,000 Ranking of Countries ( by age-adjusted death rates)
Segi Scandinavian WHO World Segi Scandinavian WHO world
Australia 6.3
10.1
7.9
23
23
23
Barbados 28.8
41.9
33.8
12
12
12
Bulgaria 34.2
43.5
36.7
8
11
10
Canada 14.5
25.6
19.7
18
18
18
Cuba 27.2
44.2
34.6
14
10
11
Estonia 27.5
36.2
29.6
13
15
15
Germany 11.0
19.0
14.7
19
19
19
Hong Kong 44.9
76.9
59.1
5
3
4
Hungary 9.6
13.1
10.7
21
22
22
Iceland 26.9
49.1
37.9
15
8
8
Ireland 37.0
65.6
50.4
7
6
7
Japan 37.8
67.5
51.8
6
5
6
Latvia 29.5
38.1
31.7
11
14
14
Luxembourg 8.4
15.1
11.7
22
21
21
Mauritius 45.2
72.6
56.6
4
4
5
New Zealand 15.3
27.7
21.5
17
17
17
Portugal 21.0
35.1
27.4
16
16
16
Russian Federation 32.7
38.3
33.1
9
13
13
Singapore 71.9
120.8
93.3
3
1
1
Spain 10.9
18.6
14.5
20
20
20
Trinidad and Tobago 30.2
46.7
37.2
10
9
9
Turkmenistan 114.2
87.9
91.2
1
2
2
Uzbekistan 80.6
63.6
65.1
2
7
3
12
Table 4. WHO World Standard Population Distribution (%),
based on world average population between 2000-2025
Age group World Average 2000-2025
0-4 8.86
5-9 8.69
10-14 8.60
15-19 8.47
20-24 8.22
25-29 7.93
30-34 7.61
35-39 7.15
40-44 6.59
45-49 6.04
50-54 5.37
55-59 4.55
60-64 3.72
65-69 2.96
70-74 2.21
75-79 1.52
80-84 0.91
85-89 0.44
90-94 0.15
95-99 0.04
100+ 0.005
Total 100
Figure 1. World population by age group in percent of total population
2000 to 2025 and average of 2000 to 2025
0
2
4
6
8
10
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69
70-74
age group
percent of total population
2000
2025
Figure 2. Comparison of "Segi" and "Scandinavian" standards with world 2000-2025 average
population
-60
-40
-20
0
20
40
60
80
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59
60-64
Age group
percent difference with world 2000-2025 average population
Segi standard population
Scandinavian standard population
... Our objective was to mimic extremes in the proportion of the White and Black populations to help assess differences between the two races as a surrogate or imperfect proxy for racialized social segregation within each state. Age-standardized rates were made according to the new WHO World Standard Population to facilitate comparisons globally and remove the confounding effect of age [36]. In direct standardization, the rate is a weighted average of the age-specific rates, where the weights are the proportions of the World Standard Population in the corresponding age groups [37]. ...
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Background: Breast cancer (BC) is the most frequent cancer diagnosed in women worldwide, including Kazakhstan. Over the last decade, many factors influenced changes in the epidemiological indicators of BC in in Kazakhstan. This study aimed to explore the epidemiological data of BC from 2012 to 2021 in Kazakhstan. Materials and methods: Official statistics on BC were studied for the period 2012-2021 (“Report on patients with malignant diseases”, statistical data of the Committee on Statistics of the Ministry of National Economy of the Republic of Kazakhstan). Prevalence, incidence and mortality rates, average growth incidence and mortality rates, the proportion of BC cases detected in the early stage (I) were analyzed retrospectively. Results: The crude incidence rate (CIR) and age-standardized incidence rate (ASIR) of BC were 48.2 and 44.4 per 100,000 female population respectively. The crude mortality rate (CMR) from BC was 13.9 (95% CI 12.7-15.1) in study period, the age-standardized mortality rate (ASMR) from 2017 to 2021 was 11.2 (95% CI 10.1-12.3). The highest incidence and mortality rates of BC per 100,000 population were in Pavlodar region (39.2±1.8 and 10.7±0.9). The lowest rates of incidence and mortality of BC were amounted in Turkestan region (11.0±1.1 and 3.5±0.06). The mortality incidence coefficient was 0.28 average and varied by region from 0.21 (Karaganda region) to 0.41 (Zhambyl region). From 2017 to 2021 the proportion of patients diagnosed with BC in stage I was 28.8% and in stage II 55.7%. Conclusion: The epidemiological situation of BC in Kazakhstan showed a tendency for improvement, with a decrease in the mortality rate and a rise in the incidence rate. During the study period, the identification of patients with stage II breast cancer prevailed. Substantial variability of epidemiological data among the regions of Kazakhstan indicates the necessity of a detailed study of risk factors of BC and the effectiveness of mammographic screening in the regions in order to take impactful healthcare measures. Актуальность: Рак молочной железы (РМЖ) является наиболее частым онкологическим заболеванием, диагностируемым у женщин во всем мире, в том числе и в Казахстане. За последнее десятилетие на изменение эпидемиологических показателей РМЖ в Казахстане повлияло множество факторов. Целью нашего исследования было изучение основных эпидемиологических показателей РМЖ в Республике Казахстан (РК) за период 2012-2021г. Материалы и методы. Для проведения эпидемиологического анализа использованы данные официальных статистических отчетов за период 2012-2021г («Отчет о больных злокачественными заболеваниями», данные Комитета по статистике Министерства Национальной экономики РК). Изучены показатели распространенности, заболеваемости, смертности («грубые» и стандартизированные по возрасту), средний прирост заболеваемости и смертности, а также доля случаев РМЖ, выявленных в ранней стадии (I). Результаты. «Грубая» (CIR) и стандартизованная заболеваемость (ASIR) РМЖ составили 48,2 и 44,4 на 100 000 женского населения, соответственно. Средний показатель «грубой» смертности (CMR) за период 2012-2021г составил 13,9 (95% ДИ 12,7-15,1), стандартизированный показатель смертности (ASMR) с 2017 по 2021г. - 11,2 (95% ДИ 10,1-12,3) на 100 000 женского населения. Самые высокие показатели заболеваемости и смертности от РМЖ на 100 000 населения были в Павлодарской области (39,2±1,8 и 10,7±0,9). Самые низкие показатели заболеваемости и смертности от РМЖ отмечены в Туркестанской области (11,0±1,1 и 3,5±0,06). Соотношение смертности и заболеваемости (M/I ratio) в среднем составил 0,28 и варьировал по регионам от 0,21 (Карагандинская область) до 0,41 (Жамбылская область). С 2017 по 2021 г. доля больных с диагнозом РМЖ I стадии составила 28,8%, II стадии – 55,7%. Заключение: эпидемиологическая ситуация по РМЖ в Казахстане демонстрирует тенденцию к улучшению за счет снижения смертности на фоне роста заболеваемости. За изучаемый период превалировало выявление больных со II стадией РМЖ. Существенная вариабельность эпидемиологических данных по регионам Казахстана свидетельствует о необходимости детального изучения факторов риска РМЖ и эффективности маммографического скрининга в регионах для проведения эффективных лечебно-профилактических мероприятий. Кіріспе. Сүт безі обыры (СБО) бүкіл әлемде, оның ішінде Қазақстан Республикасында (ҚР) әйелдер халық арасында онкологиялық аурулармен сырқаттанушылық құрылымында жетекші ауру болып табылады. Соңғы онжылдықта ҚР сүт безі обырының эпидемиологиялық көрсеткіштерінің өзгеруіне көптеген факторлар әсер етті. Мақсаты: Біздің зерттеуіміздің мақсаты 2012-2021 жылдар аралығындағы ҚР сүт безі обырының негізгі эпидемиологиялық көрсеткіштерін зерттеу болды. Материалдар мен әдістер. Эпидемиологиялық талдау жүргізу үшін 2012-2021 жылдардағы ресми статистикалық есептердің деректері («Қатерлі аурулармен ауыратын науқастар туралы есеп», Қазақстан Республикасы Ұлттық экономика министрлігі Статистика комитетінің деректері) пайдаланылды. Таралу, сырқаттанушылық және өлім-жітім (өрескел және стандартталған) көрсеткіштері, олардың орташа өсуі, ерте кезеңде (I сатысы) анықталған сүт безі обыры жағдайларының үлесі зерттелді. Зерттеу нәтижелері. Сүт безі обырының өрескел (CIR) және стандартталған сырқаттанушылық (ASIR) 100 000 әйел халыққа шаққанда сәйкесінше 48,2 және 44,4 құрады. 2012-2021 жылдар аралығындағы өрескел өлім-жітімнің орташа коэффициенті (CMR) 13,9 (95% CI 12,7-15,1) 100 000 әйел халыққа шаққанда болды. 2017-2021 жылдарда стандартталған өлім-жітім көрсеткіші (ASMR) 11,2 (95% CI 10,1-12,3) байқалды. СБО сырқаттанушылық пен өлім-жітімнің 100 000 адамға шаққанда ең жоғары көрсеткіші Павлодар облысында (39,2±1,8 және 10,7±0,9) болды, ең төменгі көрсеткіштері Түркістан облысында (11,0±1,1 және 3,5±0,06) байқалды. Өлім-жітім мен сырқаттанушылық коэффициенті (М/І) орта есеппен 0,28 құрады және аймақтар бойынша 0,21-ден (Қарағанды облысы) 0,41-ге (Жамбыл облысы) дейін өзгерді. 2017-2021 жылдар аралығында сүт безі обырының І сатысы диагнозы қойылған науқастардың үлесі 28,8%, II сатысы – 55,7% құрады. Қорытынды. Қазақстанда СБО эпидемиологиялық жағдайы сырқаттанушылықтың артуы аясында өлім-жітім деңгейінің төмендеуіне байланысты жақсару тенденциясын көрсетеді. Зерттеу кезеңінде сүт безі обырының II сатысы бар науқастарды анықтау басым болды. Қазақстанның аймақтары бойынша эпидемиологиялық деректердің айтарлықтай өзгермелілігі сүт безі қатерлі ісігінің қауіп факторларын егжей-тегжейлі зерттеу қажеттілігін және тиімді емдеу мен алдын алу үшін аймақтарда маммографиялық скринингтің тиімділігін көрсетеді.
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In: Statistical Methods in Cancer Research, Vol. I, The Analysis of Case-Control Studies (IARC Scientific Publications No. 32), Lyon, International Agency for Research on Cancer, 1980. pp.42-81.