Radiation Epidemiological Studies in Russian National Medical and Dosimetric
Registry: Estimation of Cancer and Non-cancer Consequences Observed
among Chernobyl Liquidators
Marat M. MAKSIOUTOV
Medical Radiological Research Center, Russian Academy of Medical Sciences,
National Radiation and Epidemiology Registry
Koroleva st. 4, Obninsk, 249020, Russia: nrer@obninsk.com

Abstract
In June 1986 the USSR Ministry of Health Care initiated a large-scale program to establish AllUnion Distributed Registry of persons exposed to radiation. The Research Institute of Medical
Radiology of Russian Academy of Medical Sciences in Obninsk (currently Medical RadiologicalResearch Center of RAMS) was appointed as the leading organization to create and manage theRegistry. Two tasks were set before the Registry: first, assessment of health effects due to the Chernobyl
accident with a view to develop an optimal strategy for alleviating the accident consequences for humanhealth and, second, organization of many-years epidemiological studies primarily directed to estimating
the actual radiation risks. By 1 December 2001, the Russian National Medical and Dosimetric Registry(RNMDR) included medical and dosimetric data for 585,121 persons exposed to radiation as a result of
the Chernobyl accident and residing in the territory of Russian Federation. At present the Registry
includes 187,596 liquidators (32.1% of total number of registered).
This article presents comprehensive radiological and epidemiological analysis of individual
medical and dosimetric data for the cohort of liquidators available in the RNMDR. Particular emphasis
is placed on the issue of estimating radiation risks in induction of cancer and non-cancer diseases. This isdue to the fact that the coefficients recommended by ICRP are primarily based on the Japanese
epidemiological studies of 1945 atomic bomb survivors of Hiroshima and Nagasaki (the LSS cohort).
Statistically significant estimates of radiation risk coefficients for the Japanese cohort, however, werereceived in the individual dose range above 0.3 Sv. For low doses (up to 0.2 Sv), only extrapolation
models without direct epidemiological ascertainment were used. Therefore, the RNMDR is the first to
estimate radiation risks for low radiation doses using individual medical and dosimetric information
available for the liquidators cohort.
The article consists of five parts. Chapter 1 describes the organizational structure and basic
principles of operation of the Russian National Medical and Dosimetric Registry, and provides
characterization of the liquidators cohort in the RNMDR. Chapters 2-4 deal with direct radiationepidemiological studies aimed at estimating and predicting radiation risks using the actual data of theRegistry. Radiation risk estimates derived from incidence data on leukemias, solid cancers andnoncancer diseases among the liquidators are discussed. The last chapter 5 deals with estimatingmortality rate among the Chernobyl liquidators and establishing a possible dose response relationship for
mortality. The submitted material is based on scientific papers prepared by the experts of the Registry
and published in the famous Russian and international scientific magazines.

1. The short description of the Registry
In 1986 the USSR Ministry of Health Care initiated a program to establish All-Union Distributed
Registry (UDR) of persons exposed to radiation due to the Chernobyl accident. The computer center ofResearch Institute of Medical Radiology of USSR RAMS (Obninsk) became the core of the Registry. The
UDR was formed with contributions from all republics of the former Soviet Union, many scientific research
168

institutions and practical organizations [1]. Information to the UDR was mainly supplied by republican
information computer centers of Ministries of Health Care of Belarus, Russian Federation and Ukraine. In
1992 after the disintegration of USSR, on the base of the UDR the Russian National Medical and Dosimetric
Registry (RNMDR) was set up in Medical Radiological Research Center of RAMS (former ResearchInstitute of Medical Radiology). The principal objective of the Registry was organization of long-term
automated individual recording of persons exposed to radiation effects of the Chernobyl accident, theirchildren and subsequent generations as well as assessment of their vital status.
1.1. Organizational structure and tasks of the Registry
The Registry is a multilevel information system covering all regions of Russian Federation. The
Registry provides for four levels: federal, regional, province and district.
In each of the 11 administrative and economic regions of Russia a regional center of the RNMDR was
set up to collect individual medical and dosimetric information supplied from districts and provinces and topass it on to the national level (Fig. 1.1). In addition to regional centers established by the territorial
principle, the RNMDR has affiliation centers in Ministry of Defense, Ministry of Internal Affairs, Ministryof Railways, Ministry of Atomic Energy and Federal Security Service. Affiliations with the same status asregional centers were also set up in the regional cities the population of which was worst exposed toradiation as a result of the Chernobyl accident, namely Bryansk, Kaluga, Tula and Oryol.
The Registry is designed to provide information support and to improve the quality and effectiveness ofthe following:• clinical examination of the population;• treatment and health promotion activities;• studies of the incidence pattern, dynamics and trends of health outcomes in the monitored contingent;• recommendations on improving prevention, diagnosis and treatment of diseases, conducting protection
measures and perfecting the health care system;• special scientific studies on the health effects of the Chernobyl accident and other radiation disasters
and incidents.
The tasks of the Registry include:• automated recording of passport and registration data for persons exposed to radiation as a result of theChernobyl accident and other radiation disasters and incidents;• automated recording and determination of individual radiation doses among the population;• automated recording of chronic diseases in the monitored cohort before the accident and automatedFig. 1.1. Distribution of regional centers of the Registry across the territory of Russia.
169

recording of health status after the accident;• retrieval of data on request of users;• quality control for data completeness and medical follow-up.
The users of the Registry are Ministry of Health Care of Russian Federation and Ministry of Emergencyof Russian Federation. Other organizations are entitled to get access to materials of the Registry withpermission of appropriate health care authorities.
The structure of the Registry was devised with allowance for the experience of similar registries in theworld, in particular, the Japanese Registry of atomic bomb survivors in Hiroshima and Nagasaki as well as
registries in other countries [2].
1.2. Monitored groups and operational procedures in the Registry
By 1 December 2001, the Registry included medical and dosimetric data for 585,121 persons exposed
to radiation as a result of the Chernobyl accident and residing in the territory of Russian Federation. The
contingent of the registered persons consists of four groups:
1st group - persons involved in clean up works at the Chernobyl NPP (liquidators). These include:- persons who were involved in mitigation of the Chernobyl accident consequences in the exclusionzone in 1986-1990 (including temporary workers and those on a mission), persons dealing with public andcattle evacuation or working at the Chernobyl NPP, military servicemen including air force staff irrespectiveof where they were stationed and what works involved, and senior and junior militia personnel servicing in
the exclusion zone in 1986-1990. These include specialists, servicemen and reservists called up for
mitigation works and having a certificate of Chernobyl liquidator of established format. At present theRegistry included 187,596 liquidators (32.1% of total registered in the Registry).
2nd group - persons evacuated (among them volunteers) from the exclusion zone in 1986 (areas fromwhich the population was evacuated in 1986 by the radiation safety regulation) including children, among
them prenatal at the evacuation time (1.7 %).
3rd group - persons living in the monitored territories (relocation zone) or having lived there
immediately after the accident (later moved to another area) (61.1%).
4th group - children born to parents in 1st group involved in mitigation of the accident consequences in
1986-1987 (5.1%).
1.3. Doses for liquidators in the Registry
Let us consider the density f(D) of the distribution of absorbed dose D for liquidators. In what follows,
we give a step-by-step approximation to f(D), which by the definition for the dose interval (D, D+∆D) isequal to:f(D)=∆N ( D ),∆D ⋅ N(1.1)

where: ∆N(D) is the number of liquidators with a dose between (D,D+∆D);
N is the total number of liquidators in the group analyzed.
We then form groups of liquidators depending on the date of their entry into the contamination zone:
1986; 1987; 1989 and 1990. This classification corresponds to the type of work performed (from the end of
May to November 1986: the construction of the sarcophagus) and differs with regard to the radiation
situation [3,4].
Fig. 1.2 shows unnormalized histograms of the density of the distribution function D-∆N(D) for theabove groups. For convenience of comparison, the interval of histograms was taken to be the same for allgroups. As can be seen in Fig. 1.2, the distribution of absorbed doses for all liquidators (the group of 119,416
persons with known doses and places of accommodation and work) is rather complex and has peaks at doses
170

N=119416, 1986-1990

N=48575, 1986

16000

4000

14000
3000

∆N(D), persons∆N(D), persons

12000
10000
8000
6000
4000

2000

1000

2000
0

0
0

50

100

150

200

250

300

350

400

450

500

0

50

100

150

N=48077, 1987

300

350

400

450

500

350

400

450

500

400

450

500

6000

12000

5000

10000

∆N(D), persons∆N(D), persons

250

N=18208, 1988

14000

8000
6000
4000

4000

3000

2000

1000

2000
0

0
0

50

100

150

200

250

300

350

400

450

500

0

50

100

150

200

250

300

D, mGyD, mGyN=5475, 1989

N=1004, 1990

2500

600

500

∆N(D), persons

2000∆N(D), persons

200

D, mGyD, mGy

1500

1000

500

400

300

200

100

0

0
0

50

100

150

200

250

300

350

400

450

500

0

50

100

150

200

250

300

350

D, mGyD, mGyFig. 1.2. Unnormalized density ∆N(D) of the distribution of absorbed doses D in liquidators
registered in the RNMDR and densities ∆N(D) for liquidators with different dates of entry
into the contaminated areas - 1986, 1987, 1988, 1989, 1990.
of 10, 50, 100 and 200 mGy. At doses higher than 250 mGy the distribution density decreases sharply, whichsuggests proper management of doses during recovery operations (preventing the excess above the dose limitof 250 mGy for most liquidators) or can be explained by other, possibly, subjective reasons.
For the liquidators of 1986 the dose distribution density has maxima in the range of low doses up to 10
mGy (these doses are most probably attributable to the liquidators who were not involved in Recovery
Operations in heavily contaminated areas) and in the range of high doses of 200-250 mGy. For 1987 theindicated maxima are added with a sharp maximum at doses about 100 mGy. This is the dose limit which
was established for most of the liquidators in 1987. In the following years, the dose distribution was shiftedto even lower values with the maxima at about 10 and 50 mGy.
2. Prediction of long term stochastic effects for liquidators
There are currently two models of radiation risk used for prediction of the temporal trend of radiogenic
cancers: the model of relative risk (multiplicative) and the model of absolute risk (additive) [5, 6]. In this171

work the multiplicative model is used, since experts of the ICRP consider it to be preferable for most solidcancers.
In a simple multiplicative model for the i-th disease the increment to the cancer mortality rate due toradiation is written as:∆λi ( u, t , d ) = ERR i 1 Sv ( u , t ) × λi ( u, t ) × f ( d ) ,ERRi1Sv is the excess relative risk of mortality for the i-th disease per unit dose [1/Sv];f(d) is the dose response function (usually linear or linear-quadratic);λi(u,t) is the spontaneous mortality rate for the i-th disease in the stratum of the age group, t and thetime period, u.
In the additive model:∆λi ( u , t , d ) = EAR i 1 Sv ( u, t ) × f ( d ) ,EARi1Sv is the excess absolute risk of mortality for the i-th disease [104 person-years Sv]-1.
Obviously, ERRi1Sv = EARi1Sv/λi .
In case of rare diseases (for example, leukemia) or diseases with low survival rate and short diseasetime course, these models can be used to estimate additional incidence rate due to the radiation factor by
substitution of mortality rates for incidence rates.
Knowing the distribution of population density for liquidators with time and dose response coefficients,
frequency of radiogenic cancers for the i-th disease ∆IMi(t,d) (additional mortality due to radiation induced
cancers) can be estimated:umax∆IM i ( t , d ) = ∫ n( u, t ) × ∆λi ( u, t , d )du ,umin

where n(u,t) is the time variations in the size and age structure of the cohort. For calculation of thisvalue one can use survival tables or apply the approach to solve the equation accounting for variations in the
population.
Additional mortality rate from all radiogenic cancers is given by∆IM ( t , d ) = ∑ ∆IM i ( t , d ) .
i

For estimation of the contribution of radiogenic cancers to cancer mortality we estimate the value of
attributive risk equal to the ratio of the number of radiogenic cancers to the total spontaneous and radiogenic
cancers, i.e. to the detected number of cancers.
As exposure of liquidators was protracted in time (the dose rates are lower than in the LSS cohort [7])we used the dose and dose rate effectiveness factor (DDREF) of 2 for estimating radiogenic cancers.
Frequency of radiogenic cancers is calculated with allowance for the latent period (10 years for solid cancers
and 2 years for leukemias).
2.1.Calculation models of excess mortality risk for solid cancers and leukemias
In calculation of additional mortality from radiogenic solid cancers and leukemias the approximants ofexcess relative risk given in [21] were used.
The model used for describing the risk of radiogenic solid cancers has the following form (designations
are as in the original):

ERR( d , s , e ) = β s × d × exp( γ × ( e − 30 )) .
Here s is the sex attribute;d is the dose;
e is the age at exposure;βs is the risk coefficient dependent on sex and cancer localization (ERR/Sv). For all solid cancers thecoefficient is equal to 0.38;
172

Table 2.1. Age dependence of parameters βe and δe for leukemias
Age at exposure

0-19

20-39

40+

βe
δe

-0.553-0.0370.708-1.542-0.6880.173

Leukemia: In accordance with [21] the model of excess absolute risk of radiogenic leukemias formales is written as:

EAR( d , s , e , t ) = ( d + θ × d 2 ) × exp( β e + δ e × log( t / 25 )) .
The parameters βe and δe dependent on age at exposure account for the level and temporal trend of risk
for leukemias, respectively. The values of these parameters as a function of age at exposure are given in
Table 2.1. The value of θ is taken to be 1.53.

Cumulative number of radiogenic leukemias

2.2.Prediction of mortality from radiogenic cancers in the liquidators
Leukemia
Effects of exposure to ionizing radiation are characterized by the increase of the leukemia incidence rate
because, according to current concepts, radiation risks of leukemia are much higher than those for solidcancers. The time elapsed since the accident is now sufficient for leukemia induction (the latent period isabout 2 years). A prediction of expected mortality from radiogenic leukemias in the Chernobyl liquidators ispresented in Fig. 2.1. The expected life-time number of radiogenic leukemias is 32 cases (per 100,000
persons with the mean dose 0.11 Sv).
The attributive risk of radiogenic leukemias changes significantly with time since the accident. The peakin the attributive risk of 41% is expected 5 years after the accident. Such dependence of the attributive risk isdue to a similar time dependence of the excess relative risk. This means that today the peak in induction ofradiogenic leukemias has passed. The attributive risk is currently 35%, i.e. each third leukemia in the cohortof liquidators is radiation induced. Even 50 years after the accident the attributive risk of leukemias will
exceed the risk for solid cancers and be equal to 10%.
Solid cancers
Fig. 2.2 shows occurrence of solid radiogenic cancers in the cohort of liquidators as a function of timesince the accident (per 100,000 persons), the mean dose is 0.11 Sv (mean dose for liquidators). The expected
life-time number of radiogenic solid cancers is 320 cases (per 100,000 persons). The peak in the incidence
rate is expected to occur 30-35 years after the accident and will approximately be equal to 10 cases per year.
40

30

20

10

0
0

10

20

30

40

50

60

Time since the accident (years)

Fig. 2.1. Temporal pattern of radiogenic leukemias in the cohort of liquidators(per 100,000 persons).
173

Number of radiogenic cancers per 100000

350
300
250
200
150
100
50
0
0

10

20

30

40

50

60

Time since the accident (years)

Fig. 2.2. Temporal pattern of radiogenic solid cancers in the liquidators. (per 100,000 persons).
Table 2.2. Temporal pattern of the attributive risk of radiogenic cancers (%).
Time since the accident (years)
Malignant neoplasms
5
1020
Solid cancers
1.5
1.6
Leukemias
40.5
34.4
23.3
Digestive system diseases
1.5
1.7
Respiratory system diseases
8.4
3.3

50
2.4
10.1
2.3
0.9

The attributive risk increases with time and reaches 2.4% 50 years after the accident. The growth of theattributive risk with time is due to a greater contribution from liquidators exposed at younger age because theradiation risk of solid cancers increases as the age at exposure decreases.
Table 2.2 contains the values of the attributive risks for solid cancers, leukemia and malignant
neoplasms for the digestive and respiratory systems.
The presented results of predicting the excess cancer mortality due to radiation in liquidators are
preliminary. As was indicated, the estimates are rather approximate because of uncertainties in parameters
used in predictions. This is, first of all, the uncertainty in the risk coefficients which were obtained for
different exposure conditions (doses and dose rates) and for other populations. All this lets us assume that the
projection based on the models currently accepted in the world radiation epidemiology and discussed in thischapter may be underestimation. As a consequence, the expected stochastic effects can, in fact, be more
pronounced. Optimization of measures to minimize health effects of the Chernobyl accident becomes of evenmore social significance. Solutions to these problems can be sought in many-years radiation-epidemiologicalstudies in the RNMDR system based on the Chernobyl data.
3. Trends of cancer incidence among liquidators: estimation of radiation risks
One of the issues related to radiation effects on liquidators that has not been adequately covered in theliterature is how frequency of malignant diseases can be modified by risk factors. At the same time,
malignant neoplasms are known to be radiogenic [8], as confirmed by both clinical and radiationepidemiological studies [5].
The long-term study of the 1945 atomic bomb survivors in Hiroshima and Nagasaki has revealed anincrease in risk of malignant diseases and corresponding mortality with increase in radiation dose [2].
This chapter deals with calculating cancer incidence rates and assessing radiation risks for theliquidators in the period from 1986 to 1997-1998. The analysis is based on the data available in the RNMDR
about radiation risks of leukemia (ICD-9: 204-208) and solid tumors (ICD-9: 140-165, 170-195). The
174

incidence of leukemia and solid tumors was analyzed using the cohort methodologies [9,10]. Particularattention was attached to deriving a relationship between incidence rates and different risk factors. The
incidence rates are primarily dependent on age of liquidators, external radiation dose and time of entry into
the zone. The absolute values of incidence rates tend to increase with time since the Chernobyl accident.
3.1. Analytical method for radiation risk assessment
In cohort epidemiological studies long-term systematic surveillance of a group of persons is carried out
to collect individual information on their health status.
For each person the time at risk to develop a disease of a particular class is calculated as a difference ofdates T1 and T0, where T0 is time of arrival to the 30-km zone and T1 is one of the following dates: the dateof the first diagnosis for the class of diseases under study, the date of the latest medical examination or thedate of death. The incidence rate used in this study is defined as a ratio of the total cases to the total times atrisk measured in person-years.
At first, in order to estimate the difference in cancer incidence between liquidators and the population of
Russia as a whole, Standardized incidence ratio (SIR) is calculated. Age-specific incidence rates for the malepopulation of Russia were used in SIR calculations.
Secondly, to derive the dependence of incidence rates on dose, the individual data about liquidators
have been grouped in a multidimensional table. In the present study the data are grouped into 10 strata byage ([18-20), [20-25), [25-30), [30-35), [35-40), [40-45), [45-50), [50-55), [55-60), [60+) years), into 6
groups according to dose ([0-50), [50-100), [100-150), [150-200), [200-250), [250+) mGy) and groups bycalendar year (from 1986 to last year of surveillance).
Let i be the index of age-time group and j be the index of dose group.
Let Yij be the number of cases, Pij is person-years and Mij is the incidence rate in stratum ij. In theseterms Mij for a given class of diseases can defined as:(3.1)
Mij = Yij / Pij .
It is reasonable to assume [11,12] that Yij values are independent Poisson random variables withmathematical expectation E(Yij) = PijMij. To determine the dose dependence of Mij it is necessary to present
Mij in the form of parametric function and determine its parameters using the maximization of likelihood
function:(3.2)
l = Σ {Yij ln(PijMij) - PijMij},
where Mij = f(Dij) where Dij is the average dose in stratum ij.
Simple functions are used in this work:(3.3)
f(Dij) = Mi0 exp(adij),
dij = 0 for j = 0 and dij = 1 for j > 0.
(3.4)
f(Dij) = Mi0 (1 + bDij).
(3.5)
f(Dij) = Mi0 + yDij.
Equation (3.3) is used to determine the relative risk RR = exp(a), and equation (3.4) is used todetermine the significance of dependence of relative risk on dose. The statistical test applied for these
purposes is the test of ratios of likelihood maxima at null hypothesis b=0. The 0-50 mGy group is used asbaseline dose group (j=0, internal control).
Estimation of parameters of equations (3.3-3.4), statistical tests and determination of confidence
intervals are performed on the software AMFIT [12].
For calculation of the dose dependence of leukemia incidence rates, equation (3.5) was used withstratification solely by age.
3.2. Results of radiation risk assessment
Leukemia
The cohorts of liquidators in this study total 99,024 people [13]. All worked within the 30-km zone.
175Members of the cohort reside in the European part of Russia. In 1986, 44,057 individuals served, and theirmean dose from external penetrating radiation was 0.168 Gy. In 1987, 35,689 people served; their mean dose
was 0.093 Gy. For the three-year period 1988-1990 inclusive, additional 19,278 persons, with a mean dose of
0.033 Gy, from the Russian Federation were involved in recovery operations related to the Chernobyl
accident.
The incidence of leukemia in these liquidators has been followed up to the end of 1997. Standardized
incidence ratios (SIR) together with related information are provided in Table 3.1 for all leukemia, chronic
lymphocytic leukemia, and chronic myeloid leukemia in the liquidators. The results have been tabulated
separately for the early period (April 1986-1990), the later period (1991-1997) and for the entire period of
follow-up. The SIR values are relative to the comparable age-, sex- and period-specific rates for the RussianFederation as a whole.
The SIR for all leukaemia was elevated for both periods, but slightly more for 1991-1997. The question
is to what extent these elevated values may reflect the effect of differential case ascertainment for theliquidators compared to that for the general population of Russia. Table 3.1 provides the standardized
incidence ratios for chronic lymphocytic leukemia (deemed a subtype not increased by radiation exposure)and chronic myeloid leukemia (a subtype for which incidence can be increased by radiation exposure) for
these same periods. The elevated standardized incidence ratio for chronic lymphocytic leukemia indicatesthat a substantial effect of screening exists. However, the standardized incidence ratio for chronic myeloid
leukemia is some two-fold higher than that for chronic lymphocytic leukemia in the same 1991-1997 period,
Table 3.1 Standardized incidence ratio for various types of leukemia in Russian liquidators.
ExpectedStandardized
incidence ratio a
(SIR)

8.6
17.7
26.3

1.98 (1.15-3.17)
2.71 (2.00-3.59)
2.47 (1.91-3.15)

Number of cases
PeriodPerson-years

1986-1990
1991-1997
1986-1997

398 630
613 203
1 011 833

Observed
Leukaemia (ICD-9: 204-208)
17
48
65

Chronic lymphocytic leukaemia (ICD-9: 204.1)
1986-1990
1991-1997
1986-1997

398 630
613 203
1 011 833

1986-1990
1991-1997
1986-1997

398 630
613 203
1 011 833

4
14
18

1.7
4.5
6.2

2.33 (0.62-5.96)
3.10 (1.70-5.20)
2.89 (1.71-4.56)

Chronic myelogenous leukaemia (ICD-9: 205.1)
4
21
25

1.3
2.7
4.0

3.01 (0.81-7.72)
7.76 (4.81-11.9)
6.20 (4.01-9.16)

a 95% CI in parentheses.

Table 3.2. Standardized incidence ratio and excess relative risk for leukemia among Russianliquidators with documented individual doses.
Number of cases
PeriodPerson-years

Observed

ExpectedStandardized
incidence ratio a(SIR)

Excess relativerisk a(Gy)-1

Leukaemia (ICD-9: 204-208)
1986-1990
1991-1997
1986-1997

288 917454 867
743 784

16
36
52

6.1
12.6
18.7

2.63 (1.15-4.28)
2.85 (1.99-3.94)
2.78 (2.07-3.64)

n.a.
0.83 (-1.62-3.31)
1.16 (-1.17-3.52)

Leukaemia excluding chronic lymphocytic leukaemia (ICD-9: 204-208 excluding 204.1)
1986-1990
288 91713
4.9
2.55 (1.41-4.54)
n.a.
1991-1997
454 86727
9.5
2.84 (1.88-4.14)
2.93 (-0.83-6.72)
1986-1997
743 78440
14.4
2.78 (1.99-3.79)
4.58 ( 0.51-8.60)
a 95% CI in parentheses.

176

Table 3.3. Incidence of solid cancers among Russian liquidators.
PeriodPerson-years
of follow-up

Number of cases
Observed

ExpectedStandardized
incidence ratio(SIR) a293

0.95 (0.84-1.07)

1 259

0.91 (0.86-0.97)

Nuclear workers
1991-1998

107 133

278
Previously not nuclear workers

1991-1998

704 375

1 152

a 95% CI in parentheses.

Table 3.4. Standardized incidence ratio and excess relative risk of solid cancers among Russianliquidators with documented individual doses in the range of 0.001-0.3 Gy.
PeriodPerson-years
of follow-up

Number of cases
Observed

ExpectedStandardized
incidence ratio a(SIR)

Excessrelative risk a(Gy)-11.01 (0.86-1.20)

0.56 (-1.23-2.79)

0.94 (0.88-1.01)

0.82 (0.28-1.37)

Nuclear workers
1991-1998

56 356

149

146

Previously not nuclear workers
1991-1998

514 101847

898

a 95% CI in parentheses.

suggesting the possibility of radiation-related excesses.
The question whether radiation exposure from their work in the 30-km zone may have led to excess
leukemia was addressed by examining the excess relative risk (ERR) per Gy in the liquidators for whom
individual measurements of external dose were available. With this criterion, the number of person-years offollow-up (Table 3.2) is about three-quarters of the total in Table 3.1. The SIR for all leukemia is given in
Table 3.2 for this group with documented individual doses; 2.85 (95% CI: 1.99-3.94) for the period 19911997, which is essentially identical to the value of 2.71 (95% CI: 2.00-3.59) in Table 3.1 for the entire
cohort. The ERR per Gy for all leukaemias was not significantly associated with radiation dose. For theforms of radiogenic leukemia (all leukemia excluding chronic lymphocytic leukemia), however, a significant
association with dose is observed over the entire period of follow-up (1986-1997). For the period 1991-1997,
however, ERR per Gy is elevated but not significantly so.
Solid cancers
For investigation of solid cancers, Russian liquidators were divided into two different groups. The firstgroup comprised 16,280 persons who had been nuclear workers before the accident occurred. The second
group is larger (comprising 96,982 persons) and consists of those who had not been nuclear workers prior totheir participation in recovery operations within the 30-km zone.
A five-year latency period was employed for the analysis of solid cancers. The SIR values for solidcancer appearing 1991-1998 are provided in Table 3.3 for the two groups of the liquidators. The control isthe age-and sex-standardized rates for the whole of Russia. SIR were <1 for both groups, while for those who
had not previously been nuclear workers SIR was significantly low, indicating a significant healthy worker
effect.
The correlation of solid cancer incidence with dose was examined for those workers who had
documented individual doses (the range 0.001-0.3 Gy was selected). This selection decreased the personyears of follow-up by about 50% for those who had been nuclear workers (comparing Table 3.3 with Table
3.4) and by about 30% for those who had not previously been nuclear workers. The SIRs for those with
documented individual doses, however, were similar to those shown for the entire group. While the point
estimates of ERR were greater than zero for both groups (Table 3.4), the ERR was significant only for those
who had not been nuclear workers prior to their participation in recovery operations (0.82 (0.28-1.37)). The
ERR was not significant in the case of those who had been nuclear workers previously (0.56 (-1.23-2.79)).
Some words about risk assessment for other solid cancer sites. Table 3.5 contains estimates of radiation
177

Table 3.5. Excess relative risk for malignant neoplasm of the digestive and respiratory systems.
SignificanceDisease class
ICD-9 code
ERR/Gylevel
0.85
Malignant neoplasm of the digestive system
150-159.9
0.2(-0.3,2.04)
1.13
0.14
Malignant neoplasm of the respiratory system
160-165.9(-0.24,2.4)
risks for malignant neoplasm of the digestive and respiratory systems. For both types of the solid tumors
were detected non-statistically significant excesses in the incidence of malignant neoplasm.
The estimates of radiation risks for solid cancers in the previous studies of cancer incidence inliquidators [14] are consistent, within statistical errors, with the results of the present study. In our present
study the ERR per Gy for solid cancers is estimated to be 0.82 (0.28-1.37), which is somewhat higher thanthe values previously presented [15,16]. It should be pointed out, however, that the sex and age patterns ofthese cohorts are different, as well are the systems of health care, methods of data collection, estimation ofradiation doses etc. In order to assess the influences of all these factors, detailed long-term studies are
required. Further study of the Chernobyl liquidators will serve to reduce uncertainties in interpretation of theeffects of radiation on human health.
4. Radiation-epidemiological analysis of incidence of non-cancer diseases in liquidators.
Most of studies of health consequences of the Chernobyl accident and related radiation risks areconcerned with dose response relationship of cancer incidence and mortality. But in the last few years a
possible relationship between radiation exposure and frequency of non-cancer diseases is being discussed inscientific publications in Russia and abroad. Therefore it becomes particularly important to estimate
radiation risks of non-cancer diseases from low doses within the study of the health status of liquidators. This
chapter presents results of radiation-epidemiological studies of the cohort of liquidators registered in the
RNMDR. This chapter discusses the dose response relationship for non-cancer incidence [17].
For this epidemiological analysis we formed a retrospective cohort consisting of 68,309 maleliquidators, for each of which external gamma radiation dose was known and health information wasavailable in the RNMDR (at least one entry from 1986 to 1996) and all were registered before 1.01.1992. Forradiation risk assessment the analytical method described in chapter 3.1 was used. The 0-50 mGy group was
taken as the baseline group (internal control).
4.1. Results of radiation risk assessment

All non-cancer classes
This section provides estimates of the excess relative risks (ERR) for main classes of non-cancer
diseases derived from the cohort of liquidators.
As can be seen from Table 4.1, the statistically significant dose dependency with 95% confidence
interval was derived for four classes of non-cancer diseases [18]:1. endocrine diseases and metabolic disorders (ERR=0.58 with 95% CI (0.30; 0.87));
2. mental disorders (ERR=0.40 with 95% CI (0.17; 0.63));
3. diseases of the nervous system and sensory organs (ERR=0.35 with 95% CI (0.19; 0.52));
4. diseases of the digestive system (ERR=0.24 with 95% CI (0.05; 0.43)).
Two other classes of diseases have been estimated to be close to their statistical significance. These
classes are:
1. diseases of the circulatory system (ERR=0.23 with 95% CI (-0.03; 0.50));
2. diseases of the genitourinary system (ERR=0.43 with 95% CI (-0.02; 0.87)).
For other classes of diseases under study no statistically significant dose dependencies were observed. We also
calculated ERR for liquidators separately with different time of arrival to the emergency zone. It is only the endocrine

178

Table 4.1. Estimation of parameters of dose dependency of incidence rates for different non-cancer
diseases among liquidators.
DiseaseICD-9 codes

P

Infectious and parasitic diseases

001-1390.152

Endocrine and metabolic diseases

240-279<0.001

Diseases of blood and blood-forming organs

280-289

0.701

Mental disorders

290-319<0.001

Diseases of the nervous system and sensory organs

320-389<0.001

Diseases of the circulatory system

390-459

0.077

Diseases of the respiratory system

460-519

0.893

Diseases of the digestive system

520-579

0.013

Diseases of the genitourinary system

580-629

0.048

Diseases of the skin and subcutaneous tissue680-709

0.377

Diseases of the musculoskeletal system and connective
tissue710-739

0.319

Injuries and poisoning

800-999

0.161

ERR (1/Gy)-0.49(-1.12; 0.15)
0.58(0.30; 0.87)-0.17(-1.00; 0.67)
0.40(0.17; 0.64)
0.35(0.19; 0.52)
0.23(-0.03; 0.50)
0.11(-0.15; 0.18)
0.24(0.05; 0.43)
0.43(-0.02; 0.87)-0.22(-0.70; 0.26)
0.09(-0.09; 0.26)
0.24(-0.11; 0.59)

and metabolic diseases for which statistically significant estimates of ERR were obtained for both 1986 and 1987. The
values of ERR for the liquidators of 1986 was 0.57 with 95% CI (0.19; 1.00) and for the liquidators of 1987 the value of
ERR was 0.75 with 95% CI (0.28; 1.22). Below listed are diseases for which statistically significant estimates of ERR
were obtained when the group was separated according to the year of arrival to the zone:• mental disorders, 1986 (ERR=0.53 with 95% CI (0.21, 0.85));• diseases of the nervous system and sensory organs, 1986 (ERR=0.45 with 95% CI (0.22; 0.68));• diseases of the digestive system, 1986 (ERR=0.27 with 95% CI (0.01, 0.52));• diseases of the genitourinary system, 1987 (ERR=0.89 with 95% CI (0.10, 1.68)).
Thus, as a result of the radiation-epidemiological analysis of the dose dependency of non-cancer
diseases a series of classes of diseases were identified which show a statistically significant growth withincrease in dose. For diseases of the genitourinary system, the statistically significant relative risk was
obtained only for the liquidators of 1987, whereas for all liquidators the estimate of relative risk is notstatistically significant.
Cardiovascular diseases
Table 4.2 gives calculated radiation risks of the diseases of the circulatory system among liquidators.
The conducted studies have revealed, first of all, a statistically significant estimate of ERR for
cerebrovascular diseases (ERR=1.17 with 95% CI (0.45; 1.88) and essential hypertension (ERR=0.52 with
95% CI (0.07; 0.98)). It has also been demonstrated that for the liquidators who arrived to the zone in 1986
the value of ERR for cerebrovascular diseases was higher than for the cohort as a whole and equals 1.29
(95% CI (0.34; 2.24)) and for essential hypertension among the liquidators of 1987 the value ERR is 0.88
with 95% CI (0.10; 1.66).
Among diseases of the circulatory system attention should be paid to the class as a whole, in which thevalue ERR is 0.23 with 95% CI (-0.03; 0.50), and hypertension (ERR=0.35 with 95% CI (-0.05; 0.74)). The
lower boundary of these two diseases is almost 0, i.e. there is a clear tendency, even though not statistically179

Table 4.2. Estimated parameters of the dose dependency of incidence of diseases of the circulatory
system among liquidators.
DiseaseICD-9 codes

P

Diseases of the circulatory system

390-459

0.077

Hypertensive disease401-405

0.071

essential hypertension

401

0.016

hypertension with heart affection

402

0.814

Ischaemic heart disease (IHD)

410-4140.735

acute myocardial infarction

410

0.702

other acute IHD

411

0.642

angina pectoris

413

0.372

other chronic forms of IHD

414

0.970

Other heart diseases

420-429

0.927

Cerebrovascular diseases

430-438<0.001

Diseases of arteries, arterioles and capillaries

440-448

0.167

Diseases of veins, lymphatic vessels and otherdiseases of the circulatory system

451-459

0.341

ERR(1/Gy)0.23(-0.03; 0.50)
0.35(-0.05; 0.74)
0.52(0.07; 0.98)-0.08(-0.76; 0.60)
0.08(-0.39; 0.55)
0.29(-1.23; 1.81)-0.35(-1.74; 1.05)
0.31(-0.40; 1.01)-0.04(-0.64; 0.57)-0.04(-0.83; 0.90)
1.17(0.45; 1.88)
0.56(-0.31; 1.44)-0.25(-0.75; 0.26)

significant.
We also studied robustness of radiation risk estimates depending on dose group ranges and effect ofstratification by the arrival year on these estimates. The study has shown that division into smaller dosegroups does not result in noticeable differences in radiation risk estimates.
It should be noted that the study did not allow for recognized risk factors such as excessive weight,
hypercholesterolemia, smoking and alcoholism. Therefore, there is no way thus far to single out the radiation
component in incidence of diseases of the circulatory system and other somatic diseases among liquidators.
This requires in-depth studies considering all risk factors of both radiation and non-radiation nature andconducting detailed questioning of liquidators under study.
5. Mortality among the liquidators: estimation of radiation risksThis part of the article is based on the paper [19] and deals with estimating mortality rate among theChernobyl liquidators and establishing a possible dose response relationship for mortality (radiation risks).
The importance of these issues is associated with two aspects: first, from the epidemiological standpoint it isvital to study a possible dose response of mortality rate, considering low doses in the cohort under study (themean external gamma radiation dose to liquidators is 0.1 Sv), and secondly, because mortality and its
dynamics is a reflection of social, economic and political conditions in the country.
The size of the cohort of liquidators (65,905 persons) considered in the present paper is comparable tothat of the above mentioned cohorts and these data may be of interest as an additional source of information
about relationship of low radiation doses (<0.3 Sv) and mortality.
In the present work, the term dose implies a documented external radiation dose for a specificliquidator. In order to reduce the uncertainty in the marginal dose intervals, the analysis of dose response wasbased on data on liquidators with the doses from 5 to 300 mSv. A total of 65,905 liquidators with a
180

0.06
Alive
DeathsDistribution density

0.05
0.04
0.03
0.02
0.01
0.00
0.00

0.05

0.10

0.15

0.20

0.25

0.30

Dose (Sv)Fig. 5.1.Distribution of the alive liquidators and deaths by external radiation dose.
documented dose falling in this dose interval (follow up 1991-1998) were entered in the cohort under study.
The number of follow-up person-years in 1991-1998 in this cohort was 426,304.
Distribution of liquidators by external dose is shown in Fig. 5.1. It is seen from Fig.5.1 that the
distribution has four pronounced peaks. The peaks of 0.05, 0.10 and 0.25 Sv are dose limits establishedadministratively. The limit of 0.25 Sv was set for liquidators working in the zone in 1986, 0.1 Sv - forliquidators of 1987 and 0.05 Sv - for the remainder.
The analysis included 4,995 deaths with documented cause of death and doses in the selected doseinterval 5-300 mSv.
Basically, four classes of causes of death were considered as based on the International Classificationof Diseases (ICD) [18]:- malignant neoplasms: code of ICD-9 140-239.9;- cardiovascular diseases: code of ICD-9 390-459.9;- injuries and poisoning: code of ICD-9 800-E 999;
Table 5.1. Mean dose characteristics for death cases as a function of working time in the zone
(the range 5-300 mSv).
Mean length of stay
Mean dose rate
Year of working
Mean dose
Population(days)a(mSv day-1)atime(mSv)a
1986
1978
171
68.2
2.9
1987
2169
97
74.2
1.4
1988
636
37
74.5
0.4
1989
206
40
108.5
0.5
1990
16
43
30.0
0.5
1986-1990
4995
116
72.4
1.8
a
Person-year weighted averages.
Table 5.2. Number of deaths and SMR with 95% confidence intervals for main mortality classes.
Noncancer causes of death
MalignantCardiovasAll causes
Parameter
Injuries andneoplasms
cular
Other
Total
poisoningdiseases
Number of
515
1728
1858
894
4480
4995
deaths
SMR
0.87
1.07
0.78
0.82
0.85
0.85
(0.80, 0.95)(1.03, 1.13)(0.74, 0.81)(0.77, 0.88) (0.83, 0.88) (0.82, 0.87)(95%CI)
181

- diseases other than the above: code of ICD-9 0-139.9, 240-389.9 and 460-799.9.
Subclasses were not considered because of the short observational period and limited number ofdeaths.
The main dosimetric characteristics for cases of death are shown in Table 5.1.
The number of deaths included in the analysis of the mortality pattern is shown in Table 5.2.
For analysis of mortality rates and estimation of risk coefficients (using the external control), thegeneral spontaneous mortality rate in Russia in 1991-1998 obtained from official statistics sources was used.
5.1. Analytical method for radiation risk assessment
The performed descriptive analysis of mortality is based on using the standardized mortality ratio(SMR). The expected number of deaths is calculated using the dynamics of person-years in the cohort andthe age-specific mortality rate (males) for the population of Russia in the period from 1991 to 1998. The
confidence intervals for SMR were calculated using the approach proposed in [11]. The projection of themortality pattern is based on estimates of expected number of deaths.
Risk coefficients were estimated by the method of maximum likelihood, assuming that the numbers ofdeaths are the non-stationary Poisson series of events. We considered the non-stationary process to allow forchanges in the spontaneous mortality in the considered time period.
The significance tests were derived from asymptotic properties of the likelihood ratios. The analysis isbased on individual information about external radiation dose, number of observational person-years and age
at exposure time.
The risk estimates were made using both the external (spontaneous mortality in Russia as a whole) andthe internal control group. The logarithm of the likelihood function L for the given sample is [20]:
n

fpi

N

fpi

i =1

k =0

j =1 k =0

ln L( f , ERR1Sv ) = ∑ (ln( λi , fpi ) − ∑ λi ,k ) − ∑∑ λ j ,k .

(5.1)

Risk coefficients were estimated using the linear model.
Model for the external control
In calculations using the external control group the risk model takes the form:

λi ,k = λoi ,k ⋅ f ⋅ ( 1 + ERR1Sv ⋅ d i ) .

(5.2)

Where λi,k is the intensity of the events series (here the mortality) for person i at the k-th time interval;
fpi is the period of follow-up for the cohort member i (the time lapse from the start of follow up to thedate of death or the period of the follow-up for an alive member of the cohort);n is the number of deaths in the observational period;
N is the number of alive members of the cohort included in the analysis;

λoi ,k is the spontaneous mortality rate in Russia corresponding to the attained age of the i-th cohort
member at the k-th time interval;
di is the external radiation dose for the i-th cohort member;
ERR1Sv is the excess relative risk per unit dose (sought parameter);f is the coefficient (sought parameter) accounting for the difference between the spontaneous mortality
in the liquidators cohort and the general population of respective age in the time period considered. In theused model this coefficient is equal to the SMR for unexposed members of the cohort. The variation of thecoefficient f from unity may be explained by completeness and reliability of mortality data in the Registry or
a possible «healthy workers effect», as the liquidators were subject to additional medical checks before going
to work in the zone. The selected risk model has the advantage that it estimates both the dose response andthe difference in spontaneous mortality in the followed up cohort and the referent Russian population.
The spontaneous mortality rate for each person was equal to the corresponding national rate for theattained age at a given time moment. We believe that individual information is preferable for risk estimation182

because it makes possible to minimize the influence of subjective factor and loss of information in datagrouping and stratification.
Thus, it is only the relative age distribution of spontaneous mortality rates that is used for risk
estimation and this is a more robust characteristic than the absolute distribution. The value of f was assumed
to be the same for all age groups.
The 95% likelihood intervals were determined from the likelihood function profile.
Model for the internal control
When risk coefficients were estimated using the internal control, data were stratified by attained age
and calendar time, and the spontaneous mortality was determined from the balance of the observed andexpected number of cases in a given stratum.
The risk model is written as:
λi ,k = λiEW,k ⋅ ( 1 + ERR1Sv ⋅ d i )(5.3)

Where:λiEW,k -is the spontaneous mortality rate among liquidators in the stratum by the attained age andcalendar time in which the i-th person under study falls.
The spontaneous mortality in the stratum by attained age j, at time moment k was taken to be as
follows:
λEW
j ,k =

n j ,k

(5.4)∑ PYi ,k ⋅ ( 1 + ERR1Sv ⋅ d i )i⊂ j

5.2.Results
Fig. 5.2 shows the SMR dynamics from all causes in the studied cohort of 65,905 individuals.
The mortality from all causes is lower than the general Russian rate and is basically a reflection of thecorresponding pattern in Russia as a whole in the considered period. It should be pointed out, however, thatthe mortality rate in the cohort of liquidators is gradually approaching the general Russian one. In 1998 themortality from all causes was about 8 deaths per 1,000 persons.
Table 5.3 shows that for the considered dose interval (5-300 mSv) the spontaneous mortality ofliquidators is lower than the general Russian one and equals about 82% of the general all-Russian mortality
for the population of corresponding age. The observed difference in the spontaneous mortality (thecoefficient f=0.82) can be either because of incomplete data on mortality in the general population or due tothe «healthy workers effect» in the liquidators.

1.00
0.95
0.90
0.85

SM R

0.80
0.75
0.70
0.65
0.60
0.55
0.50
90

91

92

93

94

95

96

97

Calendaryears

Fig. 5.2. SMR dynamics from all causes.
183

98

99

Table 5.3. Estimates of risk coefficients for deaths among liquidators.
Parameter

Non cancer
Cancer: ICD9 140-208

Number of
cases

515

Non cancer:
Other than
ICD-9 140208

Injuries andpoisoning:
ICD-9 800Е999

Cardiovasculardiseases: ICD9 390-459.9

Other than incolumns 3
and 4: ICD-9
0-139.9,240-389.9,
460-799.9

4480

1858

1728

894

All causes

4995

Risk coefficients derived using the external control (spontaneous mortality in Russia)
2.11
0.13
-0.36
0.54
0.23
0.27
ERR Sv(1.31, 2.92)(-0.09, 0.35)(-0.68, -0.04)(0.18, 0.91)(-0.26, 0.73)(0.06, 0.48)
0.70
0.84
0.81
1.01
0.80
0.82
Coefficient f(0.64, 0.76)(0.81, 0.87)(0.77, 0.85)(0.97, 1.06)(0.75, 0.85)(0.80, 0.85)
Risk coefficients calculated using the internal control (spontaneous mortality derived from the balance of theobserved and expected mortality in the strata at attained age and calendar time.
In parentheses are 95% likelihood intervals-1

ERR Sv-1

2.04(0.45,4.31)

0.15(-0.24,0.60)-0.36(-0.89,0.26)

0.79(0.07,1.64)

0.18(-0.67,1.26)

0.31(-0.08,0.74)

Fraction of the total number of deathes

The mortality pattern for the considered causes of death is shown in Fig. 5.3. The observed pattern is ingood agreement with the expected.
The proportion of deaths from malignant neoplasms and other causes (except the circulatory systemdiseases and injuries and poisoning) remains nearly constant at 10 and 20%, respectively, which is consistent
with the prognosis. The percentage of the deaths due to cardiovascular diseases grows, while deaths frominjuries and poisoning decrease. It is worth noting that the fraction of mortality from injuries and poisoning
among liquidators in 1986-1992 was significantly higher than in the same age group in the country as awhole.
The mortality from cardiovascular diseases becomes predominant (about 42% in 1998) and corresponds
to changes in the general mortality pattern for a given age group in Russia.
The SMR dynamics for cancer in Fig. 5.4 show a little lower mortality than the control (all-Russian). In
1998 the mortality rate from this cause was 110 deaths per 100,000 persons. Dynamics of SMR fromcardiovascular diseases is shown in Fig. 5.5
With respect to all causes of death as a whole and separate categories, the mortality pattern in theconsidered cohort reflects the general trends in Russia. The mortality among liquidators is lower than in the

0.7
Expected
Malignant neoplasms
Cardiovascular diseases
Injures and poisoning
Other

0.6

Actual

0.5
0.4
0.3
0.2
0.1
0.0
86

88

90

92

94

96

98

Calendar years

Fig. 5.3. Pattern of overall mortality by disease categories for liquidators.
184

1.10
1.05
1.00
0.95
0.90

SM R

0.85
0.80
0.75
0.70
0.65
0.60
0.55
0.50
90

91

92

93

94

95

96

97

98

99

Calendaryears

Fig. 5.4. SMR dynamics from malignant neoplasms.

1.4

1.2

SM R

1.0

0.8

0.6

0.4
90

91

92

93

94

95

96

97

98

99

Calendaryears

Fig. 5.5. Dynamics of SMR from noncancer diseases in liquidators(cardiovascular diseases).
corresponding age group in the country. An exception is the mortality from cardiovascular diseases forwhich the mortality became the same level as all-Russian by the end of the follow-up period.
Table 5.2 contains results of SMRs over the whole follow-up period. Comparing the SMR values from
Table 5.2 with the values of coefficients f (SMR for non-exposed liquidators) from Table 5.3, it can be seenthat the confidence intervals of these two estimates for various death causes are practically the same.
Results of estimation of the radiation risk coefficient for the mortality (ERR per Sv) are presented inTable 5.3. As follows from Table 5.3, the ERR values obtained using external and internal controls are close
and the difference does not exceed, on the average, 10-15% (the greatest difference of 46% is observed forthe death from cardiovascular diseases). It should be noted that the range of likelihood intervals derived
using the approach proposed by the authors is very narrow, which suggests, as mentioned above, an increasein estimate accuracy.
As is seen from the presented results for all causes of death, except cancer and cardiovascular diseases,
radiation risks are not statistically significant. For injuries and poisoning the dose relationship is actually
inverse: the risk is decreasing with dose.
The ERR of death from malignant neoplasms of 2.11 (1.31, 2.92 95% CI) (with external control) and2.04 (0.45, 4.31 95% LI) (with internal control) are statistically significant for the considered dose interval(0.005-0.3 Sv).
Thus, the results of the study lead us to conclude that there is a dose response relationship for mortality
185

from cancer in the cohort of liquidators. Given the above considerations and remembering that no account
was taken of the minimal latent period (10 years) preceding the development of malignant neoplasms, thederived values of risk should be treated as preliminary.
It should be also recognized that even with reliable estimates of risk, the dose values being low,
induction of radiogenic cancers will be insignificant. If the maximum risk estimate of 2.04 Sv-1 is adopted,
the attributive risk of induction of radiogenic cancers will be 20% (with the mean dose 0.1 Sv), whichcorresponds to 20 annual radiation-induced deaths per 100,000 liquidators.
In conclusion we would like to point out that the approach to estimation of risk coefficients using therelative age distribution of spontaneous mortality normalized to national rates (external control) seems to bejustified. The risk coefficients (ERR per Sv) estimated with the external and internal controls appear to beclose each other. The values of SMR (Table 5.2) and the coefficient f (Table 5.3) and their confidence
intervals for various death causes, which reflect no dose response, are also very close. We believe that the
proposed approach will have an advantage for rare death causes, for example leukemia, when the accuracy ofdetermination of spontaneous mortality in strata is not very high.
5.3. Conclusion
1. The mortality in liquidators is mostly lower than the all-Russian one and correlates with the trends in thecorresponding age groups of the Russian population. The SMR for liquidators varies from 0.62 to 0.90.
2. The observed pattern of mortality is consistent with the predicted. At present the percentage of deaths
from malignant neoplasms is about 10%, deaths from injuries and poisoning - 30%. Predominant are
deaths from cardiovascular diseases which account for 40% of the overall mortality.
3. The values of the excess relative risk per unit dose (ERR Sv-1) for malignant neoplasms andcardiovascular diseases are estimated as 2.11 (1.31, 2.92 95% CI) and 0.54 (0.18, 0.91 95% CI),
(external control), and as 2.04 (0.45, 4.31 95% CI) and 0.79 (0.07, 1.64 95% CI) (internal control),respectively. The risk of death from all noncancer causes is not statistically significant and close to
zero. The derived estimates of risk coefficients, however, are preliminary.
References
1.

2.
3.

4.

5.
6.
7.
8.

Tsyb A.F., Dedenkov A.N., Ivanov V.K., Stepanenko V.F., Pozhidaev V.V., Pitkevich V.A., Matveenko E.G.,
Ispenkov E.A., Stadnik O.E., Maksyutov M.A., Gagin E.A., Airapetov S.A., Polsky O.G., Turaev R.N., Romanenko
A.E., Ledoshchuk B.A., Omelyanets N.I., Sytnik A.S., Buriak V.N., Stezhko V.A., Losev G.A., Linge I.I.
Development of All-Union Registry of persons exposed to radiation as a result of the Chernobyl accident//Medical
Radiology. - 1989. - No 7. - P. 3-6 (in Russian).
Shigematsu I., Ito C., Kamada N., Akiyama M. and Sasaki H., eds. Effects of A-bomb radiation on the humanbody. - Tokyo, Japan: Harwood Academic Publishers, Bunkodo Co., Ltd., 1995.
Pitkevich V.A.(b), Ivanov V.K., Chekin S.Yu., Tsyb A.F. About exposure burden for the Chernobyl emergency
workers registered in the Russian National Medical and Dosimetric Registry//Radiation Biology. Radioecology. 1996. - V. 36, Issue5. - P. 747-757 (in Russian).
Pitkevitch V.A., Ivanov V.K., Tsyb A.F., Maksyoutov M.A., Matiash V.A., Shchukina N.V. Exposure levels for
persons involved in recovery operations after the Chernobyl accident. Statistical analysis based on the data of theRussian National Medical and Dosimetric Registry (RNMDR)//Radiat. Environ. Biophys. - 1997. - V. 36, No. 3. P. 149-160.
BEIR V. Committee of the biological effects of ionizing radiation. The Health Effects on Populations of Exposure
to Low Levels of Ionizing Radiation. - Washington: National Academy Press, 1990.
ICRP. Recommendations of the International Commission on Radiological Protection. ICRP Publication 60. Oxford: Pergamon Press, 1991.
Shimizu Y., Pierce D.A., Preston D.L., Mabuchi K. Studies of the mortality of atomic bomb survivors. Report 12,
Part II. Non-cancer mortality: 1950-1990//Radiation Research. - 1999. - V. 152, N 4. - P. 374-389.
Gofman J. Radiation and human health. - San Francisco: Sierra Club Books, 1981.

186

9.

Ivanov V.K., Tsyb A.F., Maksioutov M.A., Pitkevich V.A., Gorsky A.I., Rastopchin Eu.M., Korelo A.M., Chekin
S.Yu., Konogorov A.P., Nilova E.V. Radiation epidemiological analysis of the data of the National Chernobyl
Registry of Russia: prognostication and facts nine years after the accident//Radiation Protection Dosimetry. - 1994.
- N 64. - P. 121-128.
10. Ivanov V.K., Tsyb A.F., Maksioutov M.A., Rastopchin Eu.M., Gorsky A.I., Konogorov A.P., Chekin S.Yu.,
Pitkevich V.A., Mould R.F. Cancer morbidity and mortality among Chernobyl accident emergency workers
residing in the Russian Federation//Current Oncology. - 1995. - N 2. - P. 102-112.
11. Breslow N.E., Day N.E. Statistical Methods in Cancer Research. Vol. II. - The Design and Analysis of Cohort
Studies. Scientific Publication 82. - Lyon: IARC, 1987.
12. Preston D.L., Lubin J.H., Pierce D.A. EPICURE User's Guide. - Seattle: Hirosoft International Corp., 1992.
13. United Nations Scientific Committee on the Effects of Atomic Radiation. Fiftieth session of UNSCEAR“Radiation-related cancer resulting from the Chernobyl accident”. - Vienna, 2001.
14. Ivanov V.K., Rastopchin E.M., Gorsky A.I., Ryvkin V.B. Cancer incidence among liquidatorsof of the Chernobyl
accident: solid tumors, 1986-1995//Health Physics. - 1998. - V. 74(3). - P. 309-315.
15. Ron E., Preston D.L., Mabuchi K., Thompson D.E., Soda M. Cancer incidence in atomic bomb survivors. Part IV:
Comparison of cancer incidence and mortality//Radiation Research. - 1994. - V. 137. - P. S98-S112.
16. Thompson D.E., Mabuchi K., Ron E., Soda M., Tokunaga M., Ochikubo S., Sugomoto S., Ikeda T., Terasaki M.,
Izumi S., Preston D.L. Cancer incidence in atomic bomb survivors. Part II: Solid tumors, 1958-1987//Radiation
Research. - 1994. - V. 137. - P. S17-S67.
17. Ivanov V.K., Maksioutov M.A., Chekin S.Yu., Kruglova Z.G., Petrov A.V., Tsyb A.F. Radiation-epidemilogicalanalysis of incidence of non-cancer diseases among the Chernobyl liquidators // Health Physics. - 2000. - 78(5) P.
495-501.
18. International Classification of Diseases, 9th Revision. - Geneva: WHO, 1977.
19. Ivanov V.K., Gorsky A.I., Maksioutov M.A., Tsyb A.F., Souchkevitch G.N. Mortality among the Chernobyl
emergency workers: estimation of radiation risks (preliminary analysis)//Health Physics. - 2001. - 81(5) P. 514521.
20. Cox D.R. and Hinkley D.V. Theoretical Statistics. - London: Chapman and Hall, 1974. - P. 25.
21. Pierce D.A., Shimizu Y., Preston D.L., Vaeth M., Mabuchi K. Studies of the mortality of atomic bomb survivors.
Report 12, Part I. Cancer: 1950-1990//Radiation Research. - 1996. - V. 146. - P. 1-27.

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