SOURCES, EFFECTS AND RISKSOF IONIZING RADIATION
United Nations Scientific Committee on the
Effects of Atomic Radiation
UNSCEAR 2017
Report to the General Assembly,
with Scientific Annexes

UNITED NATIONSNew York, 2018

NOTE
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ANNEX B
EPIDEMIOLOGICAL STUDIES OF CANCER RISKDUE TO LOW-DOSE-RATE RADIATION FROMENVIRONMENTAL SOURCESCONTENTSI.

INTRODUCTION ................................................................................................................................... 67
A. Background and aims ............................................................................................................... 67
B. Scope and study selection....................................................................................................... 68

II. STUDIES ON ENVIRONMENTAL EXPOSURE RESULTING FROM HUMAN ACTIVITIES... 70
A. The Techa River Cohort studies in the Russian Federation ......................................... 70
1. Setting and sources of exposure ................................................................................... 70
2. Study population and follow-up ................................................................................... 71
3. Dosimetry............................................................................................................................... 74
4. Cancer incidence and mortality ..................................................................................... 89
B. Studies of residents in 60Co-contaminated buildings in Taiwan, China ............... 96
III. STUDIES OF ENVIRONMENTAL EXPOSURE TO NATURAL RADIATION ............................. 98
A. Studies in Karunagappally, Kerala, India ............................................................................ 99
1. Radiation sources ................................................................................................................ 99
2. Study population............................................................................................................... 100
3. Dosimetry............................................................................................................................. 102
4. Cancer incidence ............................................................................................................... 107
B. Studies in Yangjiang, Guandong Province, China ........................................................ 109
1. Radiation sources .............................................................................................................. 109
2. Population characterization and follow-up ............................................................. 110
3. Dosimetry............................................................................................................................. 110
4. Cancer mortality ................................................................................................................ 114

65

66 UNSCEAR 2017 REPORT

C. Other studies .............................................................................................................................. 116
1. Guarapari, Brazil ................................................................................................................. 116
2. Ramsar, Islamic Republic of Iran .................................................................................. 117
IV. STUDIES ON BACKGROUND RADIATION AND CHILDHOOD LEUKAEMIA .................... 118
A. Studies on natural background radiation ........................................................................ 118
1. Studies in the United Kingdom .................................................................................... 118
2. The Swiss study .................................................................................................................. 120
3. The Finnish study .............................................................................................................. 122
4. The French study ............................................................................................................... 123
B. Studies of environmental exposure from human-made sources ........................... 124
1. The case-control study in Belarus, the Russian Federation andUkraine .................................................................................................................................. 124
V. BIOLOGICAL DOSIMETRY ............................................................................................................... 126
VI. COMPARATIVE EVALUATIONS OF SELECTED STUDIES ....................................................... 127
A. Studies in areas with elevated environmental radiation levels ............................... 128
1. Review of selected studies ............................................................................................. 128
2. Summary .............................................................................................................................. 138
B. Childhood leukaemia studies............................................................................................... 140
1. Review of selected studies ............................................................................................. 140
2. Summary .............................................................................................................................. 147
C. Comparison with studies of acute exposure .................................................................. 148
VII. FUTURE RESEARCH NEEDS ............................................................................................................ 152
VIII. CONCLUSIONS ................................................................................................................................... 153
ACKNOWLEDGEMENTS .......................................................................................................................... 155
Members of the Expert Group on Epidemiological Quality....................................... 155
REFERENCES ............................................................................................................................................... 157

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 67

I. INTRODUCTION

A. Background and aims
1.
The United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR)
defined low dose rates of low-linear-energy-transfer (LET) radiation as those below 0.1 mGy per min
averaged over an hour [U4, U12]. The effect of different low dose rates on the magnitude of cancer risk
after exposure to ionizing radiation is, as yet, unclear. In the particular case of exposure to high-LET
ionizing radiation, such as radon and its progeny inhaled into the lung, an inverse exposure-rate effect(also called a protraction enhancement effect) was detected from high cumulative exposure but was notseen for low cumulative exposure [G8, L9, W3]. In an inverse exposure-rate effect, for equal total dose,a greater risk is incurred by those whose total dose is accumulated at a lower rate over a longer duration
than at a higher rate over a shorter duration. Regarding low-LET radiation, as pointed out by the
UNSCEAR 1972 Report [U3], animal studies suggested that risks per radiation dose at lower dose rates
could be lower than those at higher dose rates. The report also suggested that the risk estimates basedon epidemiological studies of groups exposed at high dose rates would be overestimated for doses anddose rates received from environmental sources.
2.
The Committee in its UNSCEAR 2000 Report suggested that the cancer risk coefficients per unit
dose obtained from human populations exposed to low-LET radiation at low dose rates were notdifferent from those obtained for the Japanese survivors of the atomic bombing, although the estimateshave wide confidence intervals* 1 [U6]. However, the Committee also pointed out that much still
remained to be learned despite extensive knowledge of radiation risk gained through epidemiologicalinvestigations [U6]. Since then, new results obtained from various epidemiological studies have been
published on low-dose-rate exposure to low-LET radiation from environmental sources, including
studies on high natural background radiation (HNBR) areas and other settings.
3.
Some populations are exposed to natural background radiation at levels that are several foldhigher than the average worldwide [H4, N4, T3]. In addition, some populations have been exposed to
low-dose-rate radiation from environmental releases of radioactivity due to human activities [H11, K8,
P11, T18]. Epidemiological studies of these populations exposed to radiation delivered at low dose
rates over long periods leading to cumulative doses up to several hundred milligrays (mGy) offer an
opportunity to investigate the health effects associated with low-dose-rate radiation exposure. The
Committee is well aware of the importance of such studies, but past UNSCEAR reports have not fully
discussed the direct evidence of health effects due to low-dose-rate exposure [U5, U6, U8].
4.
The epidemiological studies of populations exposed to environmental sources of radiation offer an
opportunity to obtain risk estimates for the induction of cancer from low-dose-rate radiation exposure
up to a cumulative dose of 500 mGy or more [B15]. The interest in the risk of cancer and other healtheffects in the general population due to radiation exposure at low doses (<100 mGy [U13]) and low
dose rates has increased as a consequence of the Fukushima Daiichi nuclear accident on 11 March 2011
[W2]. A systematic examination of the risks associated with radiation exposure at low doses and low
dose rates is, therefore, particularly timely.
1

Technical terms are explained in a detailed glossary, and are marked with an asterisk (*) the first time that they appear.

68 UNSCEAR 2017 REPORT5.
The Committee discussed the relevance of the dose and dose-rate effectiveness factor in thecontext of scientific evaluations of epidemiological studies of cancer risk from low-dose-rate exposure,which is defined as the reduction in effect per unit dose observed at low doses and low dose rates,
compared with the effect per unit dose at high doses and high dose rates and first introduced by theInternational Commission on Radiological Protection (ICRP) [I3] for radiation protection purposes andthen used by the Committee in its UNSCEAR 1993 Report [U4] to estimate cancer risk at low-dose andlow-dose-rate radiation exposure on the basis of data obtained from high-doses and high-dose-rates.
6.
At the time of applying the concept, the Committee defined low doses as those of 200 mGy or
less and low dose rates as 0.1 mGy/min (averaged over one hour) or less for low-LET radiations suchas X-rays and gamma rays [U4]. Meanwhile, the Committee has defined low dose by doses of less than
100 mGy [U13]. The Committee concluded generally that response functions would depend on a large
number of factors that the scientific evidence for a reduction in the radiation-induced effects at low
doses and low dose rates relative to acute exposures with moderate or high doses could not be
expressed by a single value. Instead, the Committee is evaluating the effect of dose and dose rate bycancer type separately, and continues to review the developments in epidemiological, biological andstatistical analyses that contribute to improved inference and estimation of low-dose and low-dose-rate
health effects. Further, because radiation protection is not within the remit of the Committee, the use ofsuch a reduction factor concept will not be discussed in this annex.

B. Scope and study selection
7.
The present annex reviews epidemiological studies of cancer risk from exposure to low-dose-rateradiation from environmental sources, concentrating on studies with quantitative risk estimates derived
from individual dose assessment. All major cohort and case-control studies on environmental exposure
to natural and human-made sources of radiation that fulfil this requirement and were published by 2016
are included. The literature search was based on the PubMed database, and also on reference lists ofidentified reports and studies reported by experts to ensure the inclusion of studies published outside
peer-reviewed journals. The review is based on studies that provide quantitative risk estimates per unit
dose based on individual exposure estimates. The strengths and weaknesses of these studies, including
their design and methods of dose estimation, are considered. Biodosimetric information is also included
in order to explain the dosimetric quantities and to clarify any limitations and uncertainties associated withthe current estimates of the health risk from low-dose and low-dose-rate environmental radiation exposure.
8.
Some ecological (geographical correlation) studies and studies using standardized mortality ratio
and/or standardized incidence ratio (SIR) (with the general population as a reference) are also
described, but they are not evaluated in detail because of the inherent limitations. They can assesscorrelations between various population characteristics, and relate average levels of exposure to overall
disease occurrence patterns, but cannot assess whether exposure and disease occur in the same
individuals (see annex A). Some studies of environmental radiation exposure are not covered here
because of their low statistical power (small study size), lack of dose–response analyses, or major
methodological limitations. Studies evaluating cancer risk among residents in the vicinities of nuclear
power plants, nuclear fuel processing plants and uranium mines or mills, or populations exposed toatmospheric bomb testing fallout were not included, except where substantial environmental exposure
resulting in doses well above the normal background level has been documented and quantitative risk
estimates reported.

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69

9.
The Hanford Thyroid Disease Study [D6] could not evaluate the risk of thyroid cancer due to thesmall number of malignant cases. Likewise, the studies on cancer risk among residents of MarshallIslands due to fallout from atomic weapons testing did not provide meaningful risk estimates for cancer
related to radiation exposure due to the small number of cases [S18]. Studies of residents in Utah andNevada, United States did not have individual dose estimates or failed to provide quantitative risk
estimates per unit dose [G3, S27]. Studies on cancer risk due to fallout from the Semipalatinsk test sitein Kazakhstan had methodological shortcomings [A1, B9]. Some case-control studies of leukaemia did
not evaluate dose response in a quantitative fashion and therefore failed to provide quantitative risk
estimates comparable with other studies [A20].
10. This annex does not cover thyroid cancer risk after the Chernobyl accident because this was
thoroughly reviewed by the Committee in its UNSCEAR 2008 Report [U11]. Studies on cancer otherthan childhood leukaemia in the Russian Federation and Europe after the Chernobyl accident are also
excluded. These studies might be considered ecological (geographical correlation) analyses, because
the dose estimation relies solely on area-based assignments and not on strictly individual
characteristics. Such area-based exposure estimates are regarded as inferior to individual dose
estimates, as they have greater uncertainty.* Further, dose levels among residents of areas contaminatedby the fallout are very low so that the power to discern an effect is low. However, several importantstudies on childhood leukaemia in relation to background radiation published in the 2010s are included.
These include major studies on natural background radiation, and also a large study in areas with aconsiderable fallout level from the Chernobyl accident.
11. Further, this annex excludes epidemiological studies of radon exposure because they have alreadybeen well documented by the Committee in its UNSCEAR 2006 Report (annex E) [U9] and others (e.g.
[T9, W8]). Worker studies, while relevant to effects of low-dose-rate exposure, differ fromenvironmental radiation exposure in the sense that they have a narrower range of exposed populations
with limited generalizability, and were also covered in the UNSCEAR 2006 Report [U9]. Hence, they
are mentioned only briefly.
12. Epidemiological studies of cancer risk associated with both external and internal exposure toionizing radiation were the subject of extensive reviews by the Committee in its UNSCEAR 1994, 2000
and 2006 Reports [U5, U6, U8]. The UNSCEAR 2000 Report [U6], described the limitations ofstatistical power and the possibility of bias* or confounding* frequently constraining the ability todetect small increases in cancer risk. The report also emphasized that not all epidemiological studies
were equally informative or of similar quality, and illustrated this point using some examples of dose–
response relationships obtained from epidemiological studies and assessed their ability to detect cancer
risk at low dose.
13. As noted by the Committee in its UNSCEAR 2006 Report [U8], epidemiological studies always
have the possibility of bias or confounding, which may give rise to spurious results. Bias in a study may
be defined as any process at any stage in the design or conduct of a study that tends to produce results
or conclusions that differ systematically from the truth [S6]. Critical bias can arise in caseascertainment, subject selection and exposure assessment. Confounding is another major cause oferroneous results, and is caused by correlations between radiation exposure and other risk factors of thehealth outcomes studied [U8]. Thus, it should be noted that, particularly in low-dose studies, even asmall degree of bias or confounding can distort study results substantially due to the small true excess
risk. Therefore, consideration of methodological issues is especially important in such studies.
14. A detailed outline of procedures and quality criteria for the assessment of epidemiological studies
is given in annex A, along the lines of guidance used in past UNSCEAR reports [U6, U8]. Annex Aemphasizes a comprehensive selection of studies, with a consistent approach in evaluating the potential

70 UNSCEAR 2017 REPORT

for bias and the contribution to the question being evaluated. These include (a) selection bias* in the
study population; (b) information bias* with regard to exposure and outcome; (c) confounding by otherrisk factors for the health outcome of interest; (d) statistical power (study size relative to dose level,
background risk and length of follow-up); (e) availability of dose estimates for the relevant organ at
individual level; (f) information on other sources of radiation exposure than that being evaluated, which
is needed to avoid exposure misclassification*; and (g) comprehensive assessment of the outcome
based on consistent diagnostic criteria. The procedures, as described in annex A, were applied here
when reviewing epidemiological studies of cancer risk from exposure to low-dose and low-dose-rateradiation from environmental sources.
15. In accordance with annex A and the Governing Principles 2 of the Committee, potential conflict ofinterest of investigators was evaluated for all studies included in this annex. No conflict of interest
jeopardizing impartiality was reported in the studies discussed here, though several lacked explicit
statements. Funding sources were reported by most studies and some had received support from sourcesthat may have financial interests.

II. STUDIES ON ENVIRONMENTAL EXPOSURE RESULTINGFROM HUMAN ACTIVITIES

A. The Techa River Cohort studies in the Russian Federation
1.

Setting and sources of exposure

16. The Techa River is a medium-sized river that flows from a small lake located near the Mayak
Production Association, a plutonium production complex, about 100 km northwest of Chelyabinsk Cityin the Southern Ural Mountains in the Russian Federation. The Techa River flows for about 240 km
through rural areas in Chelyabinsk and Kurgan Oblasts in the Ural regions (an oblast corresponds to a
province, a large geographical region) before merging with the Iset River. In the early 1950s, there
were 41 villages on the river banks (26 in Chelyabinsk Oblast and 15 in Kurgan Oblast) withpopulations ranging in size from fewer than 100 to slightly more than 3,000 inhabitants. There were
only 10 communities with populations of over 1,000 [K11].
17. Doses from background sources of natural radiation for the Techa River communities were thesame as for other communities in the region. The average annual external background dose for the rural
residents of Chelyabinsk Oblast is about 0.83 mSv a−1 [S20]. The average annual effective dose from40
K is equal to 0.2 mSv a−1. Doses from radon and its daughters in the Techa River region were
1.7–6.2 mSv a−1 [Z8].
18. There were three potential sources of exposure related to the Mayak Production Association in the
Ural region: (a) dumping of radioactive waste into the Techa River in the early 1950s; (b) the explosion(non-nuclear) of a storage tank in 1957 (the Kyshtym accident) that created the Eastern Ural2

http://www.unscear.org/unscear/en/about_us/governingprinciples.html

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

71

Radioactive Trace (EURT); and (c) the dispersion of radioactive dust in 1967. The radioactive
contamination resulted from the huge accumulation of radioactive waste from atomic weapon
production at the Mayak Production Association, which began operating its first atomic reactor andradiochemical plant for plutonium separation in 1948. The process of plutonium separation at this plant
resulted in the accumulation of a large amount of liquid waste consisting of mixtures of radionuclides.
Beginning in March 1949, when the specially designed tanks that were initially used for storing liquidradioactive waste proved to be of limited capacity, another approach was used which involved releasesof liquid waste into the Techa River, and into the Karachay Lake [D9]. Dumping radioactive waste into
the river and Kyshtym accident caused contamination by long-lived radionuclides, mainly 90Sr (a halflife of 28.8 years), in a large area in the Ural region.
19. As the nature and extent of the releases became apparent, a number of countermeasures were
undertaken. These included application of engineering, administrative and agricultural radiation
protection activities and, most importantly, resettlement. Although the efficacy of these measuresproved to be low because of the delays in implementation, between 1954 and 1960 up to 8,000 people
residing in 19 villages on the upper and middle reaches of the river were resettled. For those who
continued living in the Techa riverside villages, restrictions were imposed on use of the river and thefloodplain for any purposes. It should be noted that a portion of the Techa riverside residents were once
more exposed to radiation due to the waste storage tank explosion in 1957 [A6].

2.

Study population and follow-up(a) Study population
20. The first specialized medical examinations for residents of the Techa riverside villages took placein 1951, two years after the initial releases. The examinations were performed by visiting teams ofspecialists from the Biophysics Institute, USSR Ministry of Health, and the Mayak Production
Association Clinic. Since 1955, the residents of the Techa riverside villages have been followed up byphysicians of the clinic of the Urals Research Centre for Radiation Medicine (URCRM) under theFederal Medical-Biological Agency of the Russian Federation [A7, A10, K11]. The URCRM is
working closely with local hospitals, specialized oblast health centres and organizations (e.g. Office of
Health Statistics, oncology dispensaries), and its clinic is the only health centre specializing in radiation
medicine with the goal of rendering medical services to the exposed population of the Ural region.
Thus, the exposed people have received specialized medical examinations and treatment at the same
health centre for a long period (over six decades).
21. In 1967, the URCRM research staff initiated the process of identifying all people who lived in
Techa riverside villages between 1950 and 1960, using five major sources of data: (a) local tax books;(b) medical examination records; (c) population surveys; (d) lists of evacuees resettled in
uncontaminated villages; and (e) death certificates (for residents who died in the 1950s). Primarily, theTecha River Cohort (TRC) included residents who were born before 1 January 1950, and lived in a
Techa riverside village in the period from 1 January 1950 through 31 December 1952, at the time thehighest amounts of radioactive waste were released. The development of the Techa River Dosimetry
System (TRDS), which exists in two versions (TRDS-2000 and TRDS-2009) provided a means for theenhancement of the TRC by including residents who had come to live in the Techa riverside area in the
period from 1953 through 1960 (late entrants). Thus, the TRC now includes those born before
1 January 1950 who lived in riverside villages at any time during the period from 1 January 1950
through 31 December 1960. As of 2011, the TRC included 29,730 persons. Table 1 shows the

72 UNSCEAR 2017 REPORT

distribution of TRC members by sex, ethnicity and age as of 1 January 1950. The preponderance of
women over men in the TRC (58% vs 42%), especially in the age group ≥15, is connected with theconsequences of World War II.
Table 1. Distribution of TRC members by age, sex and ethnicity

a

Men

Women

Age group(year) a

Total

Slavs

Tartars/
Bashkirs

Total

Slavs

Tartars/
Bashkirs

Total TRC

<1

556

78.6%

21.4%

476

77.5%

22.5%

1 032 (3.5%)

1–14

3 971

77.0%

23.0%

4 168

75.5%

24.5%

8 139 (27.4%)

15–49

6 517

81.0%

19.0%

9 168

80.6%

19.4%

15 685 (52.7%)

≥50

1 514

81.2%

18.8%

3 360

85.4%

14.6%

4 874 (16.4%)

All ages

12 558

79.7%

20.3%

17 172

80.2%

19.8%

29 730 (100%)

As of 1 January 1950.

(b) Follow-up
22. The follow-up of the exposed population has been conducted by the URCRM research staff with
due observance of privacy codes, and under the control of the URCRM Internal Review Board. The
URCRM database is constantly updated through input of new information on health status, findings of
medical examinations, cancer cases, birth of children, changes of family names due to marriage, andchanges of addresses.
23. Health status information was verified via regular interviews of exposed residents at the URCRM
clinic, which they visit regularly to have medical examinations, and via interviews at their places ofresidence. Information obtained from Chelyabinsk and Kurgan Oblast address bureaus was also used
for this purpose. The main sources of information on cause of death were death certificates obtained
from regional health statistics offices (ZAGS) and medical death certificates (completed at the time ofdeath). All underlying causes of death determined by local physicians were reviewed by oblast ZAGS
officers, and also by the URCRM trained coders. All death certificates for residents of the study
catchment area for the period 1950 through 1996 were copied from archives of the Chelyabinsk andKurgan Oblasts ZAGS; and original medical death certificates from 1997 through 2007 were received
from the Chelyabinsk and Kurgan Oblast ZAGS. According to the data of the Chelyabinsk Oblast
Statistics in 2013–2014, 25% of deaths occurred in hospitals. It is believed that such a proportion was
lower in the past. During the Soviet period, more than 90% of hospital deaths underwent autopsy, andautopsy was obligatory for all deaths at home among men younger than 60 years old and women
younger than 55. Generally, autopsy rates were 20−30% [Z3], with similar rates in TRC members.
24. Since there are some limitations in the ascertainment of incident cancer cases for Kurgan
residents, the cancer incidence analyses are currently limited to the subcohort of TRC members who
were exposed originally in Chelyabinsk Oblast. This group has been called the Chelyabinsk Oblast
subcohort, which accounts for 60% of the total TRC. Since the mid-1950s in the former USSR, andcurrently in the Russian Federation, all diagnosed cancer cases are required to be registered at the oblast
oncology dispensaries [K11]. A certificate called the cancer notification form is filled out for every
cancer case diagnosed for the first time, and is registered in the raions (districts) through which the
Techa River flows (five raions of Chelyabinsk Oblast and two raions of Kurgan Oblast). Copies ofcancer notification forms have been regularly collected by URCRM staff since 1956. Additional

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73

information sources include case histories and outpatient charts retained at the URCRM and other
health centres in Chelyabinsk City, interviews with the next of kin, cytology and histology logs kept by
the Chelyabinsk Oblast Oncology Dispensary, records of the Oblast Oncology Bureau of the medicalsocial commission of experts, and the unified computer registry for the exposed South-Ural population.
The updated URCRM database contains virtually complete information on cancer diagnoses among theexposed population registered in five regions of Chelyabinsk Oblast and Chelyabinsk City during
1956–2016.
25. Follow-up for leukaemia incidence in Chelyabinsk and Kurgan Oblasts started in 1953. In
1953–1954, the sources of information for leukaemia patients exposed in the Southern Urals wereclinical records of the Ozyorsk town hospital and the Clinical Department of the Moscow Biophysics
Institute, copies of which are stored in the URCRM archives. Since 1955, the URCRM clinicaldepartment has been functioning as a major haematology centre providing treatment and medical
assistance to people exposed in all the Techa riverside raions [K15].
26. In the TRC study, a substantial proportion (14%) of cohort members are known to have moved tonearby cities and towns in Chelyabinsk, Sverdlovsk and Kurgan Oblasts, and a small proportion(3−4%) moved to distant areas [K10]. The dates and places of migration have been obtained fromaddress bureaus in the relevant oblast and were included in the MAN-database, which was created in
the URCRM to support the follow-up of exposed people [A8]. The loss to follow-up* status wasunrelated to dose levels (non-selective). For cohort members living outside the Chelyabinsk or Kurgan
Oblasts, the chance of determining current vital status or date and cause of death is small because it is
not feasible to send queries to address bureaus throughout the country. Also, URCRM staff do not haveaccess to ZAGS records in other areas [K11]. The catchment area for non-leukaemia malignancies islimited to the five Chelyabinsk raions in the original catchment area and Chelyabinsk City.
27. Descriptive characteristics of the cohort, namely, catchment area, follow-up period, cases
included in the mortality and incidence studies in different periods, are presented in table 2. The “lost tofollow-up” group includes persons who were excluded from analysis after migration from thecatchment area (the exact date of migration is known) or after the latest ascertainment of their vital
status in the catchment area (i.e. migrants and persons with unknown status taken together). Migration
rates for incidence analysis, especially for solid cancers, were higher than for mortality analysis because
the catchment area for solid cancer incidence analysis was limited to five Chelyabinsk Oblast raions
and Chelyabinsk City whereas for the mortality analysis, the catchment area included the whole
Chelyabinsk and Kurgan Oblasts.

74 UNSCEAR 2017 REPORT

Table 2. Summarized characteristics for TRC studies performed in different periods
Lost tofollow-up d(%)

Unknowncause ofdeath (%)

MCA

23.5
(14.0+9.5)

1161 (including
12 CLL)847 877

MCA

21.5(14.8+6.7)

9.8

99 (including
27 CLL)

1950–2007

927 743

MCA

22.7(15.8+6.9)

9.0

2 303 (22 bone
cancers
excluded)

1956–2007

472 788

ICA

26.8(21.1+5.7)

9.2

1 933 (excluding
non-melanoma
skin cancers)

Cohortsize aPeriod offollow-up

Personyears

Catchment
area b, c

Leukaemia
mortality,
TRDS-2000 [K16]29 8731950–1999

865 811

Leukaemia
incidence,
TRDS-2009 [K18]28 223e

1953–2007

Solid cancer
mortality,
TRDS-2009 [S3]29 730Solid cancer
incidence,
TRDS-2009 [D5]17 435f

Study

Number ofcases

aNumbers of cohort members differ in different years because periodically duplicates were identified (most of them were women
who changed their family names at marriage).

b

MCA (mortality catchment area) includes two oblasts: Chelyabinsk Oblast+Kurgan Oblast.

c

ICA (incidence catchment area) includes five raions in Chelyabinsk Oblast+Chelyabinsk City.

d% of migrants+% of persons with unknown status at the end of follow-up are indicated in parenthesis.

eNumber of cohort members excluding those who had died or migrated from MCA before 1 January 1953.

f

Number of cohort members excluding those who had died or migrated from ICA before 1 January 1956.

3.

Dosimetry(a) Radiation source terms
28. The main source of environmental contamination was the release of liquid radioactive waste into
the Techa River in 1949–1956. Massive releases started in September 1950 and reached a maximum in
October 1951. The TRDS-2000 and TRDS-2009 estimates of the releases are shown in figure I. The
total release for 1949–1951 was estimated as 1.14 × 1017 Bq [D16, S12]. The releases represented a
mixture of the radionuclides 89Sr, 90Sr, 137Cs, 95Zr, 95Nb, 103Ru, 106Ru and rare-earth isotopes. About halfof the waste was released late in 1951 [D16]. Parameters of the Techa River source term used in
TRDS-2000 were taken from the Mayak Production Association reports based on expert estimates[I6, J8]. More reliable estimates were used in TRDS-2009 [D16, G4, G5].
29. There were routine releases from the radiochemical plant and accidental releases due to leaks ofhigh-level waste from the special tank-storage facility [D16]. A major accidental release took place
during 8−12 October in 1951. On 28 October 1951, major releases were switched to Karachay Lake,and this resulted in a significant decrease in discharges into the Techa River in the subsequent five
years. The releases into the river totalled 3.5 × 1014 Bq in 1952 and (2–7) × 1013 Bq a−1 in 1953–1956(figure I). In 1956, the river bed of the upper Techa was dammed, and the penetration of radioactivity to
the lower parts of the river decreased to about 7 × 1012 Bq a−1. The construction of another dam andbypass canals in 1963 effectively isolated the contaminated upper Techa region.

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

75

30. The routine and accidental releases differed in characteristics such as radionuclide compositionand distribution of activity released in solution and adsorbed on solid particles. The characteristics oftypical routine releases and the major accidental release are shown in table 3.
31. In September 1957, a tank with high-level waste exploded and discharged 7.4 × 1016 Bq into theatmosphere. The fallout from the radioactive plume formed the EURT. About 66% of the activity was
144
Ce+144Pr; 25% was 95Zr+95Nb; 5.5% was 90Sr+90Y and 0.04% was 137Cs [A19, B2, J8].

Table 3. Amounts of radionuclides that entered Techa River with routine and accidental releases(in soluble form and adsorbed on solid particles) for particular calendar periods, as reconstructed [S12]
Accidental release in TBq d−1(8–12 October 1951)

Routine release in TBq d−1(September 1950–April 1951)

NuclideIn solution

On solid particles

Total

In solution

On solid particles

Total

Sr

2

0.7

2.7

50

200

250

Sr

18

6

24

30

120

150

Cs

16

0

16

50

200

250

106

Ru

6

11

17

60

240

300

144

Ce

0.2

5

5.2

550

2 200

2 750

Zr

2.5

4

6.5

100

400

500

Nb

3.7

6

9.7

150

600

750

90
89

137

85
85

Figure I. Previous (TRDS-2000) and new (TRDS-2009) estimates of dynamics of total activity ofradioactive releases from Mayak Production Association into the Techa River in 1949–1956(according to [D16])
Averages for one-month periods are given for October 1951–September 1952

76 UNSCEAR 2017 REPORT(b) Environmental radionuclide levels
32. The first data on environmental contamination in the area adjacent to the Mayak Production
Association in the early 1950s had been presented in archived documents, which were later published inpeer-reviewed journals [A11, A12, I6]. The level of river water contamination decreased with distancefrom the point of release due to dilution with non-contaminated water, sedimentation of suspended
particles in up-river ponds and sorption of radionuclides by bottom sediments and floodplain soils along
the river.
33. Models describing radionuclide transport in the Techa River were developed to evaluate theconcentration of particular radionuclides in the water, bottom sediments and flooded soils, for the initialperiod of contamination (1949–1951) when environmental monitoring data were scarce [M5, S10, S12,
V6]. A simple model described in a study by Vorobiova and Degteva [V6] was used in the TRDS-2000
for dose reconstruction purposes. An improved model, developed after the TRDS-2009, correlates therevised parameters of the source term and available historical data on environmental contamination[S12]. The model output provides concentrations of all source-term radionuclides, including short-lived
radionuclides in the river water, bottom sediments and floodplain soils at different distances from thesite of radioactive releases. The outputs of the model show good agreement with historicalmeasurements (figure II).
Figure II. Specific (total beta) activity of water in relation to distance along free-flowing Techa Riverin 1951 (according to [S12])
D-4 is the designation of dam number 4 located at 7 km from the release site and separated the free-flowing Techa River fromup-river ponds. Vertical bars indicate standard deviations of measurements

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

77

34. Temporal changes that occurred in contaminated areas is described in the scientific literature[B4, M4, V6, V7]. Figure III shows that the specific activity of water decreased with time as a result of
reduction and subsequent cessation of discharges and of radioactive decay of radionuclides [T14]. Since
the 1970s, river water contamination was predominantly due to 90Sr, and the concentration of 137Cs inwater was an order of magnitude less [M4].
35. A fairly rapid decrease in the levels of radioactive contamination was observed in the EURT after
1957 due to decay of 95Zr, 95Nb, 106Ru and 144Ce [A19, B2, J8]. Since the fifth year after the accident,
soil contamination was almost completely due to 90Sr.
Figure III. Specific (total beta) activity of water in Techa River measured in different calendar years
near the reference settlement Muslyumovo located at 78 km from release site [T14](c) The Techa River Dosimetry System (TRDS)
36. The TRDS version created in 2000 (TRDS-2000) was used initially to derive risk coefficients for
TRC members [K15, K16, K17]. An improved version, TRDS-2009, introduced in 2009, calculates
deterministic values of dose estimates and is currently used to derive risk estimates [D5, K18, P12, S3].
TRDS-2017, under preparation, will incorporate improvements made since 2009, including the use of a
two-dimensional Monte-Carlo procedure that will result in the calculation of stochastic dose estimates.
37. Dose reconstruction in the TRDS was based on the use of a large number of measurements oflong-lived radionuclides in the human body [K12, K14] and in the environment, and also on themeasurements of exposure rates performed directly in places where people lived. The traditional
approach of analysing all steps of the pathway of exposure was used as a backup only when otherapproaches were exhausted, in particular for reconstruction of doses from short- and intermediate-lived
radionuclides released into the Techa River in 1949–1951 [D9, D10, D12, D13].

78 UNSCEAR 2017 REPORT

38. The TRDS calculates doses from the major routes of environmental exposure: external exposure
from staying (mainly living and working) in the areas along the banks of the Techa River and in theregion of the EURT; and internal exposure from intakes acquired along the banks of the Techa Riverand in EURT villages. Individual residence history data are used for dose calculations. The time of theend of dose accumulation is also determined individually (e.g. date of death or date of emigration).

(d) External exposure
39. The absorbed doses due to external exposure were estimated on the basis of dose measurements of
gamma rays (a) along the banks of the river; (b) on the shore within a few hundred metres from thewater in specified areas of villages; and (c) inside some of the houses [D8]. Outdoor measurements
were conducted periodically at 25 monitoring posts along the shoreline of the river. Dose rates along
the river decreased significantly with distance from the discharge point. Measurements were also
performed at different distances from the shoreline in a residential area located on the upper part of the
Techa River [D12, D13] because substantial external exposure occurred when people were in thecontaminated floodplain [D12, D13].
40. The ratios between outdoor and indoor air kerma rates were obtained from a 1954 survey of
10 houses, and were used to estimate the indoor absorbed dose in air. The length of time spent on theriver bank and the indoor occupancy factors were derived from observational data obtained in the
1950s. For hours spent at each of those three locations, age-specific values were used [D10]. The
occupancy factors are based on limited historical data, and the uncertainty in external dose estimation
due to these factors is unlikely to be improved after more than 50 years.
41. The TRDS provides average external dose estimates for groups of subjects of the same age who
lived at the same time in the same location on the Techa River. External doses significantly decreased
with distance from the site of release (figures IV and V). The external dose rate was highest in 1951,
and then it decreased with time.
42. The cumulative absorbed dose to an organ o of a resident who lived at location L on the Techa
River in the period from tbegin to tend was calculated according to the following equation:
tend

ext
o,L

D

[

]

L
age
= ∫ PrivL (t ) T1age + Rout
+ Rin / outT3age ) Aoage dt/ riv (T2tbeginwhere:

Doext, L=absorbed dose of external exposure in organ o accumulated to individual who lived at
location L in the period from tbegin to tend;

PrivL (t ) =absorbed dose rate in air near the river shoreline at location L in year t;

LRout/ riv =

ratio of dose rate in air outdoors at homes to the dose rate by the river at location L;

Rin / out =

A0age

=

0.45 - ratio of dose rate indoors to that outdoors (derived from historical exposurerate measurements);
conversion factor from absorbed dose in air to organ o (function of age);

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

79

T1age , T2age , T3age = periods of time spent by residents on river bank, outdoors and indoors, respectively(functions of age); TRDS-2009 includes the dose-conversion factors for 23 organs/tissues [E1, P4, S5, S15].
43.

L

Dose rates in air above the river shoreline Priv (t ) are shown in figures IV and V [S10]. The dose

rate in air at the river bank was evaluated with the use of data on radionuclide concentrations in thefloodplain soil for all villages located at different distances from the release site [S10, S12] andcoefficients obtained by Monte-Carlo simulations of air kerma [E1]. The modelled dose rates along theriver (figures IV and V) depend on site-specific contamination of the river shore determined bytopography, and soil and hydrological properties. A notable peak in the dose rate at a distance of 50 km(figure IV) is determined by a presence of a blind fork, which resulted in increased sorption ofradionuclides in this stagnant reservoir. The dip in the dose rate at 202 km (figures IV and V) is
determined by the fact that the floodplain in this location was washed with clean water from a
non-contaminated tributary of the Techa River. Modelled values within the uncertainty range are in
reasonable agreement with the data of the systematic monitoring of exposure rate, which was carriedout on the Techa River banks from the summer of 1952 (figure V).
Figure IV. Dose rate in air at Techa River shoreline at different distances downstream from the site ofradioactive releases derived from the Techa River transport model and source terms for different
months of 1951 [S10]Modelled dose rates depend on site-specific contamination of the river shore determined by local topography andhydrological properties

80 UNSCEAR 2017 REPORT

Figure V. Modelled and measured dose rate in air at Techa River shoreline at different distances
downstream from site of radioactive releases in 1952–1958 [S10]Vertical bars indicate standard deviations for repeated measurements, single measurement results are shown without uncertainties

44.

L

Outdoor-to-river bank ratios ( Rout / riv ) were derived from exposure-rate measurements

performed at different distances from the shoreline in different locations [V7]. The village-averageLvalues of Rout / riv were used in the TRDS.
45.

age

Parameters T1age , T2age , T3

were derived from data from the 1950s of typical lifestyle patterns

for different age groups of the Techa riverside residents [D13]. Age-dependent conversion factors fromage

absorbed dose in air to absorbed dose in organs ( A0

) were taken from the literature [E1, P4].

46. Three methods were used for validation of external doses on the Techa River: the luminescencemethod with bricks [B17, J1, T5, W9]; the electron paramagnetic resonance (EPR) method with humanteeth [D11, S14]; and the fluorescence in situ hybridization (FISH) method with human lymphocytes[B8, D11, V9]. Luminescence measurements of anthropogenic dose in bricks from old buildings
located on the Techa River banks were converted to cumulated dose in air and the results were found to
be consistent with calculations performed using the TRDS parameters [T5, T6, U2]. EPR- and
FISH-based estimates of external dose for residents of settlements located in the upper reaches of the
Techa River were consistent with the TRDS-based absorbed doses in tooth enamel and muscle [D17].

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

81

47. For reconstruction of external dose on the EURT, dose rates in air per unit-deposition density of90
Sr were used. These values and data on original soil contamination by 90Sr for different settlements
were published by Bakurov et al. [B2].

(e) Internal dose reconstruction
48. Internal exposure was due to ingestion of radionuclides through drinking river water andconsuming local foodstuffs. An extraordinarily powerful flood in April to May 1951 led to theradioactive contamination of the land adjacent to the river. The flood-lands were used by some of the
inhabitants for cattle breeding and for making hay. Up to this point radionuclides had been ingested
mainly with water; now, contaminated food began to play a role, especially milk and vegetables fromflooded kitchen gardens.
49. The reconstruction of internal dose relies strongly on the results of measurements of 90Sr in
residents of the Urals, which includes the results of nearly 10,000 post-mortem measurements ofradionuclide concentration in bone samples obtained in 1951–1993, the results of in vivo measurementsof surface-beta activity of anterior teeth for 17,500 persons (1959–1997), and measurements of90
Sr-body burden by means of a unique whole-body counter for 20,500 persons (1974–1997)[D13, K12, K14, T15].
50. According to a basic approach to internal dose estimation, the absorbed dose in organ oaccumulated through calendar year Y for a resident who lived at location L on the Techa River in the
period from tbegin to tend is calculated as:
t end

DoY, L = ∑ ∑ I *y , r , L (τ i ) DFr ,o ,Y − y (τ i )y = t begin

r

where

DoY, L=absorbed dose of internal exposure in organ o accumulated through calendar year
Y by individual i who lived at location L in the period from tbegin to tend;y=year of intake of radionuclides;r=

identifier of ingested radionuclide (89Sr, 90Sr, 95Zr, 95Nb, 103Ru, 106Ru, 137Cs, 141Ce,
Ce);

144

τi

=

the age of individual i in year y;

I*y,r,L=

intake function (Bq) for year y, radionuclide r, and location L (function of age τ,
related to y);I*=

I × ξi, where ξi is a modifier predetermined for individual i equal to 1 or IMRi or HSRi;

DFr,o,Y-y =conversion factor (Gy Bq−1) for dose accumulated in organ o in year Y-y from intakeof radionuclide r in year y (function of age, related to y); TRDS-2009 includes thedose-conversion factors for 23 organs/tissues [E1, P4, S5, S15].

82 UNSCEAR 2017 REPORT

51. The intake function Iy,r,L is a complex, time-dependent function derived from a combination ofdata from tooth beta counting and the whole-body counter. The village-average intake function Iy,r,L foreach year y is calculated as:

I y , r , L (τ ) = I ySr,R90 × ατSr,R90 × f LSr 90 × R yL, r / Sr

,

where

I ySr,R90

90=

ατSr,R90

Sr intake for adult residents of the reference settlement in year y (Bq);=90

Sr intake for the other age group tau relative to that for adults living in thereference settlement R;

f LSr 90 =ratio of 90Sr intake for location L to 90Sr intake for residents of the reference settlement;

R yL, r / Srratio of radionuclide (r)-to-90Sr intake for location L in year y.

52.

=

Sr 90

The 90Sr intake in the reference settlement R ( I y ,R ) during the first years (y) after the beginningof the discharges was reconstructed using the data on 90Sr measurements in teeth, and supplementary
data on water consumption and diet composition for adults and children, and measurements of90
Sr-body burden in adults [T15]. A new method of solving an inverse problem was developed by using
an integral equation associating 90Sr-intake dynamics with the age-dependency of 90Sr content in teeth.
This allowed the assessment of the relative intake function for adult residents of the reference
settlements during the period of maximum intake [Z2]. Parameters of the integral equation, describing
ratios of semi-annual 90Sr intake for different age groups to that for adults living in the reference
settlement, were evaluated on the basis of data on the daily composition of diet [T15].
53. The 90Sr intake depends on the village of residence, which is actually a surrogate for the source ofdrinking water (contaminated river/wells). The assessment of the village-average 90Sr intake is based on
the assumption that the ratio between 90Sr intake in a particular settlement and 90Sr intake in
Muslyumovo is equal to the ratio between the average value of 90Sr-body burden for the particular
settlement and the corresponding value for Muslyumovo, obtained on the basis of internal radiationdose assessment with whole-body counter.
54. Radionuclides other than 90Sr were also released into the Techa River, including 137Cs andshorter-lived uranium-fission products (89Sr, 95Zr, 95Nb, 103,106Ru, 141,144Ce). Because river water was themain source of internal exposure, ratios of radionuclide concentrations to that of 90Sr, calculated using
the Techa River model were used for assessment of their intakes with river water [D9, D10]. In
addition, the intake of 137Cs with cows’ milk was considered in TRDS-2009 because it became a major
pathway after the flood in April 1951 [T14].
55. Radionuclide intakes normalized per 1 Ci/km2 of 90Sr deposition in the EURT area were derived
from measurements of radionuclides in local foodstuffs in reference settlements [T13]. Data on 90Sr
deposition for other EURT settlements were used to reconstruct the intake for the residents [B2].
56. Dose-conversion factors representing absorbed dose in organ per unit intake (DFr,o,Y-y) were
calculated using biokinetic models (describing time-dependent retention of radionuclide insource-tissues) and dosimetric models (describing energy deposition in target-tissue from radiation
emitted by source-tissues). The dosimetric model of bone tissue was used for calculation of doseabsorbed in red bone marrow (RBM) from 89,90Sr incorporated in the skeleton [S24]. Dose conversion
factors for other radionuclides were based on the models from the ICRP Publication 67 [I4].

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

83

57. A special age- and sex-dependent biokinetic model was used for 89,90Sr dose calculation [S8, S13].
This model has a similar structure to the ICRP-67 model (described by Leggett [L3]) and is based on thesame approach. The difference is that the model parameters were evaluated separately for men andwomen in a wider age range (0–80 years). The Techa River data on 90Sr in humans, recent data on
age- and sex-dependencies of calcium content in the skeleton, and data on bone remodelling were used forparameter evaluation. Figure VI shows that model calculations, corresponding to intake levels in
Muslyumovo, satisfactorily describe 90Sr-body burdens obtained from whole-body counter radiation
monitoring. The age peaks in 90Sr-body burden correspond to the maximum in skeletal calcium accretion
rate associated with the growth spurt at puberty (13 years for females and 15−17 years for males).
Figure VI. Age-dependencies in 90Sr-body burdens for residents of Muslyumovo 30 years after beginningof intake (according to [S13])
Calculations obtained with the age- and sex-dependent model are compared with whole-body counter data averaged for males
and females; the peak ages correspond to the age at growth spurt at puberty (13 years for females and 15–17 years for males)

58. TRDS-2009 includes different protocols for the calculation of internal dose depending on thequality of individual input data (figure VII). For persons with whole-body counter dosimetry, the valueof individual-to-model ratio (IMR) is determined as the average of the ratios of an individual’s
whole-body counter radiation measurements to the respective reference-model values. IMRs serve as
age- and time-normalized values, which permit reduction in uncertainty in internal dose estimates. The
uncertainty in the IMR value depends on the number of measurements with whole-body counter andtheir dispersion for a particular person. For those who do not have individual measurements, the valueof household-specific relationship (HSR) can be determined as the average of IMRs for measured
members of a household. The refinement of individual internal dose is based upon IMR and HSR for
27% of the entire TRC [D14, S9].

84 UNSCEAR 2017 REPORT

Figure VII. Probability distributions of estimates indicating uncertainties in RBM internal doses forresidents of Muslyumovo: (a) village-average dose estimate used in TRDS-2000; (b) householdspecific dose estimates; and (c) individual dose estimates (according to [D14])
HSR: household-specific relationship, IMR: Individual-to-model ratioANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

85(f) Medical exposure
59. TRC members were subjected to routine medical exposure in regional hospitals of rural areas of
Chelyabinsk and Kurgan Oblasts similarly to other residents. Routine medical diagnostic X-ray
examinations were conducted with a frequency of 570–620 procedures per year per 1,000 persons, andresulted in annual effective doses of 0.6–0.8 mSv per person [P8]. The doses from routine X-ray
procedures for TRC members were, on average, the same as for other people in the region.
60. At the same time, TRC members were invited to the URCRM clinic for special surveys, which
included X-ray examinations. About 22% of TRC members (6,411 persons) received diagnostic X-ray
examinations over the period 1956–2000. Those who were invited to the clinic were more likely tohave health problems related to chronic radiation exposure. Therefore, there is a possibility that theircumulative doses of medical exposure dose are related to individual radiation dose from environmental
exposure.
61. Reconstruction of individual medical radiation doses at the URCRM clinic is based on data on
X-ray diagnostic procedures, including fluoroscopy, available for each person examined.
Approximately 1,000 TRC members underwent fluoroscopy of the stomach. Organ dose per typical
X-ray procedure was calculated with the use of a phantom. The calculation took into account the X-ray
examination parameters characteristic for the X-ray machines used at the URCRM clinic [D15, S11].
Individual doses from medical exposure varied substantially from person to person, and were different
for different organs (table 4). Due to the skewed distribution, the mean was higher than the 75th
percentile for some organs. However, those doses are not large enough to distort the excess relativerisk* (ERR) estimate per unit dose substantially among residents with relatively high cumulative doses.
In particular, only 1.5% of TRC members received a stomach dose exceeding 100 mGy, and medical
exposure to the RBM contributed only 5% to the overall dose [D15, S11].
Table 4. Distribution of absorbed dose due to medical exposure of TRC members at the URCRM clinic[D14, D15]
Organ

Absorbed dose (mGy)
MeanMedian25th percentile

75th percentile

Bone marrow

27

16

1.3

34

Bone surface

37

17

2.4

42

Breast

11

6.1

1.1

12

Small intestine

24

4.6

0.03

19

Upper large intestine

21

4.4

0.03

21

Lower large intestine

12

1.6

0.002

7.4

Lungs

33

20

3.2

40

Stomach

33

23

0.3

38

86 UNSCEAR 2017 REPORT(g) Results of dose reconstruction
62. The mean annual stomach dose estimates for the Techa River incidence cohort [D5] based on
TRDS-2009 are shown in table 5. The annual stomach dose peaked in 1951 and reached 28 mGy a−1.
From 1951 to 1960, the dose rate decreased by two orders of magnitude and the decline continued also
after that, at a slower rate. Annual average doses in 1951 decreased with distance from the release site,from approximately 200 mGy a−1 in the upper reaches to about 20 mGy a−1 in the middle course androughly 4 mGy for the lower parts of the river [P12]. The mean cumulative stomach dose for TRC
members was 43 mGy and the median was 12 mGy, with a maximum of approximately 1 Gy [D7].
63. The mean annual RBM doses for the Techa River leukaemia incidence study based on
TRDS-2009 are also shown in table 5. The RBM dose rate showed a similar time trend to that of thestomach dose, but the levels were substantially higher, and decreased more slowly with time. In 1951,
the annual doses were close to 400 mGy a−1 in the upper reaches, approximately 200 mGy a−1 in the
middle course and roughly 50 mGy a−1 for the lower parts of the river [P12]. Although the cumulative
doses to some individuals in the TRC are substantial, they were accumulated over many years of
exposure. The external and internal dose rates for even the most-exposed individuals were more than
two orders of magnitude lower than the current definition of low dose rate of 0.1 mGy/min. The mean
cumulative RBM dose for TRC members was 0.43 Gy and the median was 0.27 Gy. The maximum
RBM dose in the TRC exceeded 5 Gy [D7].
Table 5. Mean dose rates for the period (1950–1980) of the Techa River incidence studies [D5, K18]
Calendar year

Mean absorbed dose rate (mGy a−1)
Stomach

RBM

1950

5.9

68

1951

28

135

1952

14

60

1953

9.7

50

1954

5.9

38

1955

1.7

27

1956

1.0

21

1957

0.59

17

1958

0.37

14

1959

0.36

11

1960

0.31

9.4

1970

0.06

2.3

1980

0.02

0.8

64. In RBM dose, the relative contribution of external exposure to the internal exposure wasdependent on the distance from the releasing point since 90Sr, the major internal-exposure contributor to
RBM dose, reached areas far down the river. In settlements located in the upper Techa region (within
about 75 km from the release site), external exposure was the main source of RBM dose. In the lower
Techa region, more than 50% of RBM dose was from internal exposure [D12, D13].

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

87

65. TRDS-2009 included the calculation of doses from confounding exposure due to residence on the
EURT area for 16% of the TRC (other cohort members did not reside in the EURT area). For the
average cohort member, most of the dose came from residence in villages along the Techa River, andthe contribution from EURT was less than 1% [D7].

(h) Uncertainties of dose estimations
66. Preliminary analysis based on a Monte-Carlo simulation, assuming different distributions for eachparameter, gave an estimated ratio of the 95% range of values of individual doses. The magnitude of
uncertainties varied depending on location and duration of individual exposure, but the results fromreference individual calculations indicated that the range of uncertainty was about a factor of four tofive for the external doses [N6, N8].
67. Regarding external exposure, a sensitivity analysis indicated that key parameters contributing to
the uncertainty were outdoor/river bank dose rate ratio (45%) and dose rate at the river bank in 1951(20%). Major efforts were recently undertaken to decrease the uncertainty in these parameters [S10].
68. Internal dose calculations have uncertainties associated with the biokinetic and dosimetric models
used. Study-specific conversion factors were used instead of standard factors and the quantities reported
here are from original publications and not always consistent across studies. The main source of
uncertainty is the inter-individual biological and behavioural differences between the study subjects[S13]. For internal doses estimated using the TRDS-2000, the range of uncertainty (ratio of the 95%
range of values of the dose distribution) depended on sources of drinking water, which were specific fordifferent riverside settlements [N6]. For villages with the Techa River as the sole source of drinking
water, the range of uncertainty was a factor of 20 to 30. For villages with mixed sources (contaminatedriver and non-contaminated wells), the ratio of the range could be over two orders of magnitude. This
indicated that the uncertainty in internal dose could be greatly reduced by using the individual wholebody counter results. This was later realized in TRDS-2009 [D14, S9]. In other words, thereconstruction of internal dose relies strongly on the results of 90Sr measurements taken from about one
third of TRC members.
69. An approach has been developed which identifies the nature of the various input parameters andcalculation methods incorporated in the TRDS-2009, and a stochastic calculation model has been
prepared to estimate the uncertainties in the dose estimates [N7]. This approach is based on a
two-dimensional Monte-Carlo analysis [N8, N9]. A two-stage Monte-Carlo computer code is used; its
output agrees with the deterministic version of TRDS-2009 and it can separate the influence ofshared/unshared parameters and uncertainties due to grouping/measurement (Berkson/Classical error*),for various exposure pathways. The first results for RBM internal dose by Napier et al. [N7] showedthat the individual dose estimates from the Techa River appeared to be log-normally distributed with ageometric standard deviation of about 2 to 2.5; uncertainties in individual dose estimates from EURT
have a geometric standard deviation of about 3 (but the doses are much smaller). Generally, theuncertainties in cumulative stomach dose are less than those for RBM. While both organs are exposed
to similar external doses, the individual variability in stomach dose from an intake is small but theindividual variability in deposition and retention in bone tissues over long time periods increases theuncertainties in bone marrow dose, although dose to both organs remains strongly correlated.

88 UNSCEAR 2017 REPORT(i) Biological dosimetry
70. The first cytogenetic studies of the Techa riverside residents were performed 20 years, and then
40–50 years, after the onset of exposure. The findings showed an increased frequency of unstable
chromosome aberrations (dicentrics and rings) in peripheral blood lymphocytes of exposed persons
compared to unexposed persons of the same sex and age. However, no dependence on the RBM dose
was found [A9, P6, V4, V8].
71. The frequency of stable aberrations (translocations) was first estimated in 1993 for residents ofthe middle and lower Techa regions [A5]. No demonstrable difference was found between 34 exposedand 10 unexposed (control) subjects [A5]. The next study was based on a more representative sample ofpersons who lived in the upper and middle Techa regions (73 exposed and 39 unexposed participants)
and showed a significantly increased mean frequency of translocations among exposed persons
compared to the controls (12.8±1.5 and 5.7±1.0, respectively, per 1,000 cells) [B8]. The highest
translocation frequency was observed in persons who had lived permanently in the Techa riverside
villages during the maximum radioactive release (1950–1951) [B8].
72. In 2009–2012, an international study using the FISH method examined two exposed groups:
18 residents of the middle Techa region, who were exposed predominantly due to ingestion of 89,90Sr;and 20 residents of the upper Techa, who were exposed to both external and internal radiation [V9]. In
the first group, a significant linear relationship between translocation frequency and individual RBM
dose from incorporated 89,90Sr was found [V9]. The slope of 0.006±0.002 translocations/GE cell/Gyfound in this group allowed quantification of the translocations caused by exposure to 89,90Sr. Individual
doses from external exposure estimated from the FISH results for the second group ranged up to
2.1 Gy. The average FISH-based dose of external radiation for the second group was estimated as
0.48±0.16 Gy [V9].
73. The main objective of the recent biodosimetry studies was validation and verification of external
dose estimates by comparing the TRDS-based doses for TRC members with the results of two
independent methods: EPR measurements of tooth enamel (I) and FISH analysis of chromosometranslocations in circulating lymphocytes (II). The main issue in the application of the EPR and FISH
methods for external dose reconstruction for the Techa riverside residents was the contribution ofstrontium radioisotopes incorporated in teeth and bones [D11, D17]. A methodology for adjustment for
the effects of 89,90Sr on the FISH results was developed [V9]. In order to estimate and subtract doses
from incorporated 89,90Sr, the EPR and FISH assay measurements of 90Sr-body burdens were used and90
Sr concentrations in dental tissue estimated by the luminescence method [D17, S14].
74. Comparative analysis of EPR and FISH results in residents of the upper reaches of the Techa
River during the period of radioactive discharges (133 persons) was performed in 2015 [D17]. The dose
estimates derived from EPR and FISH measurements and adjusted for the confounding strontium wereconsistent: the mean values tended to decrease with distance along the river from 0.51–0.55 Gy for thevillages located close to the site of radioactive release to 0.13–0.16 Gy for the more distant villages.
The upper bound of individual estimates for both methods was estimated as 2.2–2.3 Gy [D17].
75. The findings from recent biodosimetry studies were used for validation of the TRDS-2009 [D17].
Individual doses were calculated using a TRDS code for each subject in the EPR and FISH studies on
the basis of their age at exposure and residence histories. For correct comparison with the EPR- and
FISH-based estimates, two sources of exposure accounted for external exposure and internal exposure
from 137Cs incorporated in the subjects’ soft tissue. The EPR- and FISH-based estimates were inagreement within the uncertainty bounds the TRDS-based absorbed doses in tooth enamel and muscles.
The agreement supported the validity of external doses calculated with the TRDS-2009 [D17].

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

4.

89

Cancer incidence and mortality

76. Analyses of cancer and leukaemia risk for TRC members were performed repeatedly over a long
period of follow-up of the cohort [D5, E2, E3, K15, K16, K17, K18, P12, S3]. The first studies [K8,K9] covered 32- and 39-year follow-up periods (1950–1982, 1950–1989) and were limited in terms of
quality and completeness of information and of dose estimates [D8, K13]. Despite their limitations, theresults of these studies suggested that the mortality from leukaemia and solid cancers increased withincreasing radiation dose. Also, they implied that the TRC had future potential to provide quantitative
estimates of the risk of chronic low-dose-rate radiation exposure for an unselected general population.
Over the subsequent period, the TRC was expanded to include the residents in the riverside villages
from 1953 through 1960; and the total number of cohort members has reached about 30,000. The
information accumulated in the URCRM as of 2013 included data on cancer cases for TRC members in
the catchment area for 1956–2012, and deaths in the two-oblast catchment area for 1950–2007 [S3]. A
dosimetry system (TRDS-2000) for the TRC with individual dose estimates was developed. The
dosimetry system was improved and updated in 2009 (TRDS-2009) owing to availability of new
information on exposure sources and radioactive mixture hold-up time, and also to improvements in themodel itself (as described before in the dosimetry section). The internal exposure dose estimation in the
TRC study has considerable uncertainties. It should be pointed out that those uncertainties are not fully
taken into account in cancer risk estimation. Therefore, caution should be exercised when themagnitude of risk estimate per dose unit is discussed.

(a) Solid cancer incidence and mortality
77. The main methodological features of the TRC study are summarized in tables 6 and 7. Detailed
analysis of solid cancer mortality risk for 29,730 subjects over the period 1950–2007 based on the
TRDS-2009 was reported in 2013 [S3]. This updated analysis obtained risk estimates of a linear dose
response between radiation exposure from the Techa River contamination and cancer mortality
consistent with the previous findings [K16]. During the follow-up period, 2,303 solid cancer deaths
were registered in the mortality catchment area with 927,743 person-years. For men, lung, stomach andoesophagus cancers were the most frequent causes of cancer death. For women, uterine (corpus andcervix), stomach and breast cancers accounted for the largest numbers of cancer deaths. The ERR for
mortality from all solid cancers was 0.061 per 100 mGy (95% CI: 0.004, 0.127).
78. The ERR estimates in the linear dose–response models did not change greatly when the analyses
excluded the 22 bone and 73 colon cancers (ERR=0.054 per 100 mGy; P=0.07). These analyses havebeen performed because the doses to the bone and colon were markedly higher than the stomach doses,
which were relevant for most other solid cancers. Doses to the bone surface were markedly higher due
to exposure to 90Sr and other radionuclides, and doses to the colon were higher due to the contribution
from short-lived radionuclides, which had low levels of absorption in the gastrointestinal tract and,
therefore, mostly influenced the colon dose [S3].
79. It is estimated that approximately 2% (49.7) of solid cancer deaths were associated with radiation
exposure (table 8). While allowing for a linear-quadratic dose response provided no evidence against
linearity (P>0.5), a pure-quadratic dose response described the data as well as a simple linear model.
There was no evidence of a threshold. The potential influence of various factors on the estimated risk
coefficient but no statistically significant differences were found due to the uncertainties remaining
unchanged [S3]. Overall, the findings of the TRC study demonstrate that major uncertainties in thequantitative risk estimate in the low-dose range remain, despite the confirmed dose response.

Characteristic

Description

Study design

Cohort study

Study population

Eligible subjects were those born before 1950 and living in 41 villages of Chelyabinsk and Kurgan Oblasts along the Techa River during the period 1950–1960(N=29 730). Those subjects were identified by extensive review of official documents, including taxation books, vital statistics and medical records during theperiod between the late 1960s and the 1980s

OutcomeCancer mortality

Identification of cancer deaths

Chelyabinsk Oblast (region) and Kurgan Oblast were the catchment areas of mortality follow-up. The primary sources of vital status information are the regional
address bureaus and the office of the civil registrar (ZAGS). The sources of cause of death information were death certificates from ZAGS or Regional Statistical
Bureau Office

Follow-up/migration

The follow-up period was 1950 onwards. At the end of follow-up, approximately 23% of the cohort had migrated out of the catchment area (i.e. distal migrants)

Exposure

The TRDS-2009 was used and the mean cumulative stomach dose was 0.035 Gy. Radiation exposure resulted from a combination of external radiation exposure
from contaminated river sediments and flood plain soil, and internal exposure from the consumption of contaminated water, milk and food products. Internal
exposure was primarily from 90Sr and 137Cs but also 89Sr and, to a lesser extent, from other uranium fission products. Parameters for external dose reconstruction
were derived from exposure-rate measurements performed in the 1950s in different locations near the river bank and also from modelling radionuclide
deposition in river sediment and soil. The external dose rate peaked in 1951 and has declined over time
Extensive efforts have been made to reconstruct exposure for cohort members and to reduce the uncertainties, which were found to be relatively large in
TRDS-2000. A thorough uncertainty analysis is in progress

Confounding

Only demographic information (sex, age at entry, attained age, ethnicity, oblast of exposure) is available (the cohort is 80% Slav and 20% Tartar and Bashkir)

Medical exposure

Medical exposure was not substantial and was not taken into account in the risk analysis

Statistical power

No formal power calculations were reported but, in retrospect, result precision appears sufficient to detect overall cancer risks. However, statistical power is not
sufficient to detect risks for individual cancer sites

Analysis

The main analysis was to estimate an ERR per unit dose, which was estimated using Poisson regression methods

Main results

ERR for mortality from all solid cancers was 0.061 per 100 mGy (95% CI: 0.004, 0.127)

90 UNSCEAR 2017 REPORT

Table 6. Techa River cancer mortality study (1950–2007) [S3]

Table 7. Techa River cancer incidence study (1956–2007) [D5]Characteristic

Description
Cohort study

Study population

A subset of the TRC. This subcohort (N=17 435) includes cohort members born before 1950, initially exposed in riverside villages of Chelyabinsk Oblast, alive and not
known to have had cancer prior to 1 January 1956, who lived near the river in five Chelyabinsk Oblast raions and Chelyabinsk City at some time between 1 January
1956 and 31 December 2007

OutcomeCancer incidence

Case ascertainment

Since the mid-1950s, all diagnosed cancer cases have been required to be registered at the oblast oncology dispensaries [K11]. URCRM staff have collected copies ofcancer notification forms registered in the catchment areas since 1956. Additional sources of information include case histories and outpatient charts kept at
URCRM and other health centres in Chelyabinsk City, interviews with next of kin, cytology and histology logs kept at the Chelyabinsk Oblast Oncology Dispensary,records of the Oblast Oncology Bureau of the medical-social commission of experts, and the unified computer registry for the exposed South-Ural population.
Health status information was verified via regular interviews of exposed residents at the URCRM clinic, which they visited regularly to undergo medical
examinations. Regarding leukaemia cases, the URCRM database is considered to contain complete information on patients registered in the catchment areas since1953 because its clinical department has been functioning as the main haematology centre providing treatment and medical assistance to the residents in thecatchment areas

Confounding

Data on smoking were recorded during the interviews of cohort members who visited the URCRM clinic. When smoking history information only prior to age 20 wasavailable, cohort members were treated as having unknown smoking status. Smoking history was summarized using a simple time-dependent variable with three
categories: ever-smoker, never-smoker and unknown smoking status. Smoking status was considered to be unknown prior to the date at which they first provided
information on their smoking history. Individual information on smoking intensity and duration were not available for these analyses

Medical exposure

Medical exposure was not taken into account in risk analysis

Statistical power

No formal power calculations were reported, but in retrospect, precision of results appears sufficient to detect overall cancer risks similar to LSS based on confidence
interval width. Statistical power was not sufficient to detect risks similar to those in LSS for individual cancer sites, assessing departure from linearity or differencesin risks between subgroups

Analysis

The main analysis was to estimate an ERR per unit dose, which was done using Poisson regression methods. The median dose to the stomach was 15 mGy (mean
52 mGy) based on TRDS-2009. Results provide ERR values taking into account a smoking status

Main results

For solid cancer incidence ERR per 100 mGy 0.077 (95% CI: 0.013, 0.15), for leukaemia incidence ERR of 0.12 per 100 mGy (95% CI: 0.04, 0.25)

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 91

Study design

92 UNSCEAR 2017 REPORT

Table 8. Excess solid cancer mortality cases by dose category using TRDS-2009 in TRC [S3]TRDS-2009

Dose category (Gy)with 5-year lag period

Person-years

Background cases

Excess cases0

132 593

149.7

0

<0.01

386 880

951.9

2.9

0.01–<0.05

273 436

777.9

10.2

0.05–<0.1

63 297174.4

6.8

0.1–<0.15

27 651

80.3

5.8

0.15–<0.3

21 70751.5

6.5

0.3–<0.5

21 074

63.7

16.1

≥0.5

1 105

4.0

1.4

Total

927 743

2 253.4

49.7

80. The results regarding solid cancer incidence risk analysis for the Chelyabinsk Oblast subcohort of
the TRC, based on doses estimated using the TRDS-2009, were published by Davis et al. [D5]. Of thecases, 19% overall were based on death certificate alone (lower proportion after 1990). The values of
the ERR for radiogenic solid cancer development estimated for the Techa River subcohort supplement
those from the mortality analysis for the total Techa cohort, and present clear evidence of an increased
rate of solid cancer with radiation exposure. While incidence and mortality analyses gave comparable
ERR estimates, there are several major differences in the analyses. As was indicated above, since
comprehensive data on cancer incidence are available only for cohort members initially exposed in
Chelyabinsk Oblast, the incidence cohort contains only about 60% of the full TRC and loss tofollow-up due to migration was more common than in the mortality analysis.
81. Despite the reduced cohort size and follow-up time (1956–2007) for solid cancer incidence data,
the analyses were based on approximately the same number of cases (1,933 cases, excluding
non-melanoma skin cancers) as the previous mortality analyses (2,303 deaths). Fifty per cent of the
1,933 solid cancers were diagnosed in men. The most common sites for men were the lung (30%) andthe stomach (22%), while the most common sites for women were the uterus (including cervix uteri)(21%), the stomach (16%) and the breasts (12%) [D5].
82. The dose response with adjustment* for ever vs never smoking, was significant (P=0.02) in a
linear ERR model. The estimated ERR per 100 mGy was 0.077 (95% CI: 0.013, 0.15). The risk
estimate without smoking adjustment was 0.087 per 100 mGy (95% CI: 0.02, 0.16). Table 9summarizes the distribution of solid cancer incidences, person-years and fitted values in five-year
lagged cumulative dose categories. Using a linear dose–response model, it was estimated that 61 of the
1,933 cases (3%) were associated with radiation exposure. There is no indication that a linear-quadraticmodel fitted better than a simple linear model (P=0.2). A pure-quadratic dose-response model gave an
ERR of 0.022 per 100 mGy (95% CI: 0.005, 0.04), which is less than half of that predicted by the linear
ERR model. When non-parametric smoothing was used, the results suggested that the response over the
low-dose region (<0.1 Gy) falls between the linear- and pure-quadratic models [D5].

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Table 9. Observed and fitted solid cancer incidence from linear-ERR smoking-adjusted models using
TRDS-2009 (1956–2007) [D5]Fitted cases

Dose category (Gy)with 5-year lag period

Person-years

ObservedcasesaBackgroundb

Excessb

0

11 870

17

16.2

0.0

>0−0.01

154 221

630

600.1

2.5

>0.01−0.05

196 764

799

871.5

16.6

>0.05−0.1

58 522

246

179.9

9.1

>0.1−0.15

23 616

105

96.1

8.6

>0.15−0.3

16 731

71

59.9

9.2

>0.3

11 065

65

47.9

15.3

Total

472 788

1 933

1 871.7

61.3

aSolid cancers among cohort members resident in the catchment area at the time of diagnosis (including alive and deathcertificate-only cases) excluding non-melanoma skin cancers.

b

The number of background and excess incidences are based on a linear ERR model without effect modification.

83. Site-specific analyses based on the linear model showed statistically significant radiation dose
effects only for cancers of the oesophagus (ERR=0.46 per 100 mGy; 95% CI: 0.04, 1.2) and uterus(ERR=0.21 per 100 mGy; 95% CI: 0.01, 0.51). Oesophageal cancer risk estimates were modified by
ethnicity and sex, but not by smoking. While the solid cancer rates are attenuated when oesophageal
cancer estimates are removed (ERR=0.063 per 100 mGy; 95% CI: 0.00, 0.14), a dose–response
relationship is present and it remains likely that radiation exposure has increased the risk for most solidcancers, despite the lack of power to detect statistically significant risks for specific sites [D5].
84. As these results indicate, while these data provide the evidence of dose response, there isconsiderable uncertainty about the magnitude of the risk at very low doses. Adjustment for smoking
reduced the overall ERR from 0.087 per 100 mGy to 0.077 per 100 mGy (95% CI: 0.013, 0.15). ERR
per unit dose tended to increase with attained age and age at entry, though there was little indication ofeffect modification* (P>0.5 for the interaction* terms). The ERR was comparable for men and women.

(b) Leukaemia incidence
85. The TRC offers an opportunity to assess leukaemia risk after long-term exposure not only to
external gamma radiation, but also to internal exposure of RBM due to 90Sr. Internal exposure of the
population due to ingestion of river water and local food products resulted in significant intakes ofbone-seeking 90Sr which, unlike the uniformly distributed 137Cs, is accumulated mostly in the bone
tissue and bone marrow. RBM contains the precursors of haematopoietic tissue, and a disturbance of
haematopoietic processes may lead to the development of leukaemia. It may be assumed, therefore, thatleukaemia represents one of the main reactions of the body to radiation exposure manifest in somemembers of the TRC. In the process of long-term follow-up of the cohort, leukaemia risk was assessed
repeatedly [K8, K9, K15, K16, K18, O4]. In spite of their many limitations, the studies were able toprovide a reasonably precise estimate of dose response for leukaemia incidence.
86. The results reported by Krestinina et al. in 2013 (in the framework of the Russian-American
project) extended the period of follow-up by two years from the previous report [K15]. The mean
cumulative RBM dose was 0.42 Gy. The newer dosimetry included a larger contribution of 89Sr in the

94 UNSCEAR 2017 REPORT

period of maximum releases (1950–1951), and it increased the RBM dose due to internal exposure to137
Cs [D7]. The wider dose range reflected a better individualization of the TRDS-2009 dose estimates.
87. About 848,000 person-years have accumulated for cohort members residing in Chelyabinsk andKurgan Oblasts over the 55-year follow-up period, and 170 haematopoietic malignancies (including 99
first primary leukaemia cases, 18 Hodgkin’s diseases, 36 non-Hodgkin’s lymphomas and 17 multiple
myelomas) were identified. No leukaemia cases were identified in cohort members who had not yet
reached 10 years of age, and only three cases in those aged 10–20 years. The number of leukaemia
cases was 45 in males and 54 in females; 68 cases in Slavs and 31 in Tartars/Bashkirs; and 83 out of 99
leukaemia cases in those aged 40 or older. Leukaemia types and confirmation rates are shown intable 10. More than half of the leukaemia cases (58 out of 99) were classified as chronic, and 41 asacute or subacute. The diagnosis was microscopically confirmed for 82% of the cases. The proportionof cases identified solely from death certificates—often referred to as death certificate only (DCO)—
has declined over time, ranging from about 25% for the years prior to 1990 to less than 10% over thelast 17 years of follow-up.
Table 10. Microscopic confirmation rates of leukaemia types for TRC members [K18]Type of leukaemia
Acute myeloid
Acute lymphoid
Other acute/subacute
Chronic myeloid
Chronic lymphoid
Other or unspecified

b

Total

a

Cases

Microscopic confirmation (%)

Mean age (year)

8

100

48

1

100

76

32

72

51

25

88

57

27

89

64

6

50

62

99

82

57

a

Includes one acute monocytic leukaemia case, two acute erythraemia cases, two subacute leukaemia cases, and 27 cases
classified as acute leukaemia of unspecified type.

b

Includes three cases classified as myeloid leukaemia of unspecified type and three classified as leukaemia of unspecified type.

88. It was estimated, on the basis of a linear dose–response model, that 32% of the 99 leukaemia
cases were associated with radiation exposure, with an estimated linear ERR of 0.12 per 100 mGy (95%
CI: 0.04, 0.25). There was no evidence of a dose response for CLL (ERR=0.01 per 100 mGy; 95% CI:<0, 0.12). The analysis, focusing on leukaemia other than CLL, showed that about 47% of the non-CLL
leukaemia cases were associated with radiation exposure. Table 11 presents the observed numbers of
non-CLL leukaemia cases by dose category, along with estimates of the number of expected cases
obtained from the baseline rates* and radiation-associated excess cases based on a simple linear dose–
response model with no effect modification. For non-CLL leukaemia, the ERR per 100 mGy in a linear
dose–response model was 0.22 (95% CI: 0.08, 0.54).
89. The model fit did not improve by adding a quadratic term (P>0.5). In contrast to the previous
studies, the analysis conducted in 2013 showed that a pure-quadratic dose-response model was also
positive (ERR=0.009 per 100 mGy; 95% CI: 0.003, 0.019), but it did not fit the data quite as well as did
the linear model. There was no evidence of statistically significant modification of the radiationassociated risk of non-CLL leukaemia by sex (for females, RR=1.0; 95% CI: 0.14, 6.7), or ethnicity (forTartars/Bashkirs relative to Slavs, RR=1.4; 95% CI: 0.58, 4.4). It was also found that ERR tended toincrease with attained age, but this effect was not statistically significant (P>0.5).

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Table 11. Observed and fitted cases of leukaemia other than CLL in TRC using TRDS-2009 cumulative
dose categories [K18]Calculation based on fitted model

Marrow dose (Gy)with a two-year lag

Person-years

Observed cases

Background
cases

Excess cases

Attributablefraction (%)<0.01

100 034

6

4.4

0

0

0.01–0.05

102 300

2

4.7

0.3

6

0.05–0.1

55 077

4

2.5

0.4

13.8

0.1–0.2

109 182

10

5.1

1.5

22.7

0.2–0.5

222 137

13

10.1

6.8

40.2

0.5–1.0

152 752

20

6.9

10.1

59.4

>1.0

106 395

17

4.6

14.7

76

Total

847 877

72

38.3

33.8

46.9

90. Overall, the TRC study has been one of the most important new studies in the past decades and it
has contributed to evidence about cancer risk from radiation. While challenges remain to quantify thedose–response relationship at low doses, risk estimates from this study provide important information
about cancer risks from long-term whole-body radiation exposure, which can be applicable in othersettings with an accident resulting in wide-scale environmental contamination. Results for leukaemia
are based on relatively small numbers of cases, but they are unlikely to be affected by confounding or
selection bias. The risk estimates from analyses of mortality reported in 2005 [K16] and incidence
reported in 2013 [K18] differ more widely than those for solid cancers. Incomplete case ascertainmentand diagnostic verification may add misclassification and could bias the risk estimates downward. For
solid cancer results, the pattern of site-specific findings, with significant excess risks found only foroesophageal and uterine cancers, is not consistent with other major studies. The patterns of effectmodification by age and sex are not similar to the Life Span Study (LSS), but the differences in risk by
subgroup are small and should not be overemphasized. Adjustment for incomplete smoking information
reduced the risk estimates for solid cancer, which suggests that there may be residual negative
confounding. The different exposure modes, including long period of exposure and a marked internalradiation component may also contribute to the differences between the two studies.
91. The strengths of the TRC include a wide range of doses, long follow-up time, and availability ofdata on both cancer incidence and mortality. Exposure in the TRC population is complex, as it involves
both external and internal exposure, and has varied over time, which adds to the uncertainties in
estimated doses. However, extensive work on characterization of exposure, including uncertainties, isan advantage. Nevertheless, the uncertainties in dose estimates remain large. Incidence data are not,however, available for the entire cohort, and their quality is suboptimal, particularly for the early
period. Furthermore, information on confounding factors is scarce. The proportion of subjects lost tofollow-up (>20%) and deceased with unknown cause (roughly 10%) was relatively high.

96 UNSCEAR 2017 REPORT

B. Studies of residents in 60Co-contaminated buildings in
Taiwan, China
92. A building constructed with radioactive building material was found in Taipei City in 1992. The
source of the radiation was steel contaminated with 60Co, which was suspected to have been obtained
illegally with scrap metal [A17]. One of the major steel reprocessing factories in Taiwan, China,
mishandled a 60Co-orphan source and melted it during a steel-rod (rebar) manufacturing process during
1982–1983, producing radioactive steel, which was used throughout northern Taiwan, China. By theend of 2000, 1,607 housing units in 181 buildings were found to have radioactive rebar [C4]. All thebuildings with radiation contamination were built between 1982 and 1984. Many families had resided
in these buildings for various periods, mostly around 10 years. Regarding the method to estimate annual
dose received by residents, Chen stated [C4]: “The highest specific point or space dose equivalent rate
was taken as the dose equivalent rate for that room or compartment for further calculation”.
93. Chromosome aberrations of peripheral lymphocytes were examined in 30 residents (17 males and
13 females) in radiation-contaminated buildings. The estimated cumulative radiation doses for thoseresidents ranged from 20 to 280 mSv. As a control group, 15 individuals (eight males and sevenfemales) from laboratory personnel were recruited. G-banding was carried out for at least
500 metaphase spreads for each individual with the exception of one sample. All the recognizable
structural aberrations of chromosomes or chromatids were recorded. The frequency of cells withaberrant chromosomes in residents of buildings with radiation contamination was non-significantly
larger (4.5% vs 3.6%) than that in the control group [C3]. However, Liu et al. [L7] showed dicentricfrequencies of 0.69 vs 0.33 in 136 residents compared with 15 non-exposed controls. A study of
90 exposed and 45 non-exposed subjects showed a higher frequency of any structural chromosomal
aberration in exposed women (3.9 vs 3.0 per 100 cells), but no significant difference by exposure status
in men (3.8 vs 3.5 per 100 cells) [W4]. The time since last exposure was not clearly reported.
94. Another study examined 1,913 exposed residents (average age: 18 years) of the contaminatedbuildings. Blood samples were taken five–eight years after relocation. The control group of this study
consisted of 176 residents in a local community (average age: 30 years). Lymphocytes were cultured
for 48 hours and a total of 208,900 metaphases were prepared. Increased frequencies of translocations(2.1 vs 0.2 per 1,000), and also rings and dicentrics (0.6 vs 0 per 1,000 for both) were reported in the
exposed group relative to the control group [H7]. The elapsed time since end of exposure may be toolong to observe an effect on unstable aberrations (dicentrics and rings). The frequency of stable
aberrations (translocations) appears very high, given the dose level. In the interpretation of theseresults, it should be borne in mind that unstable chromosomal aberrations such as dicentrics are
eliminated over time and are not expected to occur any longer when several years have elapsed since
the end of radiation exposure.
95. Hwang et al. examined cancer risk in a cohort of 7,271 residents in cobalt-contaminated buildings
with a dose assessment system known as the Taiwan cumulative dose (TCD), using questionnaires ofhouse occupancy and building structure [H10]. The average excess cumulative dose was approximately
47.8 mSv (range: <1–2,363 mSv), with incremental annual dose on average 10 mSv a−1 (ranging up to>1,400 mSv a−1), though the distribution was highly skewed with 79% receiving <5 mSv a−1. The
subjects were identified from the national household registry and linked to other registries using
national identification numbers. A questionnaire survey was conducted, but the data were not used in
the analysis. A total of 1,025 persons were excluded due to lack of individual occupancy factors. A
follow-up of the cohort for 1983–2002 (on average 16.1 years) accumulated 101,560 person-years at
risk. The start of the follow-up was the date of moving into a contaminated building. Deaths in thecohort were ascertained by record linkage with the National Mortality Registry of Taiwan Province ofANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

97

China, which had been maintained by the Bureau of Health Statistics since the early 1950s. Personyears of follow-up are reported, but not numbers of deaths or people emigrating. Cancer cases wereidentified through the National Cancer Registry, which was established in 1979 by the Department of
Health, and which collects information on all newly diagnosed cancer patients from all health-care
sectors in Taiwan, China. The proportion of cases based on death certificate alone was 10% in 1990–1994
and 3% in 1995–1999. Standardized incidence ratios (SIRs), adjusted for age and sex, were calculatedwith regional reference rates. The latent periods of leukaemia and solid cancers were assumed to be twoand ten years, respectively. After the latent period, the follow-up of the cohort ascertained sevenleukaemia cases and 88 cases of all cancers excluding leukaemia. The SIR for leukaemia, except forchronic lymphocytic leukaemia (N=7), was 2.2 (95% CI: 0.9, 4.6). The SIRs for all cancers excluding
leukaemia were 0.7 (95% CI: 0.5, 0.9) for men and 0.9 (95% CI: 0.7, 1.2) for women. For dose-gradientanalyses, only three dose categories were compared (<1, 1–50 and >50 mGy). A non-significant trend
was observed for leukaemia and a significant trend reported for breast cancer. The decreased risk for all
cancers excluding leukaemia suggests methodological problems with possible explanations including
confounding, selection bias and incomplete follow-up or case ascertainment.
96. Extended follow-up of the same cohort reported 117 cancer cases diagnosed during the period
between 1983 and 2005, with average follow-up of 19 years. No expected numbers were given to assess
the overall cancer risk. In this study, quantitative risk estimates were obtained unlike in the earlier
paper. A trend with radiation dose was observed for leukaemia, excluding chronic lymphocytic
leukaemia, with an ERR of approximately 1.9 per Gy (90% CI: 0.1, 3.1) on the basis of six cases (onefewer than in the previous report). Breast cancer (N=17) also exhibited a suggestive increase in risk
with dose (ERR=0.012 per 100 mGy; 90% CI: −0.01, 0.21). All solid cancers (N=106) showed an ERR
of 0.03 per 100 mGy (90% CI: −0.04, 0.09) [H11]. Only linear risk estimates were reported, and nodata shown by dose category to allow more detailed assessment of the findings. The authors chose toshow 90% confidence interval instead of 95%, presumably based on a one-sided hypothesis test ofradiation exposure increasing the cancer risk (see also annex A).
97. The limitations of the study of 60Co-contaminated buildings include uncertainties in exposure
assessment, low statistical power and lack of confounder control. Exposure assessment is not describedin depth and the dosimetric quantities are not defined in detail. Interviews and questionnaires were used
to reconstruct doses retrospectively on the basis of recalled occupancy and time spent in each room of
the residence. Such estimates could be obtained for 86% of the cohort members. Dose-rate
measurements were not conducted extensively, but rather concentrated on performing large numbers ofmeasurements in a small number of residences and people to provide models for characterizing typicaldose rates [H11, L2, T18]. Extensive dose reconstruction efforts were also hampered by subsequently
installed shielding and replacement of contaminated rebars. No indicators of data quality for caseascertainment (such as proportion of microscopically verified cases, death certificate only cases, orcases with unknown primary site) were reported. A questionnaire survey was conducted, but no data
were reported on any of the major confounders. The confidence intervals seem very narrow, given thesample size, which raises some concerns about the statistical analyses. However, the study was
included in this annex, despite the clear methodological limitations and small study size, because it uses
individual dose estimates and is able to provide a quantitative risk estimate so that it fulfils the key
inclusion criteria. Table 12 summarizes the study of 60Co-contaminated buildings in Taiwan, China.
Recently, an update of the study has been published with extended follow-up, larger numbers of cancer
cases and some site-specific analyses [H8].

98 UNSCEAR 2017 REPORT

Table 12. Summarized characteristics of the cohort study of residents in 60Co-contaminated buildingsin Taiwan, China
Characteristic

Description

Study design

Partly retrospective and partly prospective cohort study

Study population

A cohort of 6 242 residents of approximately 100 buildings constructed using
60
Co-contaminated steel (rebars) since 1982

OutcomeCancer incidence

Mortality follow-up

Mortality registry by Bureau of Vital Statistics

Cancer case ascertainment

Cancer cases ascertained from the population-based cancer registry

Follow-up/migration

From the computerized household registration system

Exposure

Exposures reconstructed retrospectively from self-reported occupancy by building
area. Cumulative doses calculated from time-weighted mean dose rates

Confounding

No data on confounding factors reported; questionnaire data on occupation andeducation mentioned in reports

Medical exposure

Information on medical radiation exposure was not collected

Statistical power

No formal power calculations reported

Analysis

Hazard ratios per 100 mGy reported leukaemia and all solid cancer combined, and also
some individual cancer types. Adjustment for gender and year of birth was used. A
minimum latency of two years for leukaemia and 10 years for solid cancers was used

Main results

For solid cancer incidence ERR of 0.03 per 100 mGy (90% CI: −0.04, 0.09)

III. STUDIES OF ENVIRONMENTAL EXPOSURE TO NATURAL
RADIATION
98. Natural background radiation, which originates from the terrestrial environment, varies
tremendously worldwide and within countries as well. The average annual dose from external terrestrial
radiation is 0.48 mSv, with typical values ranging 0.3–1 mSv a−1 [U10]. The primary radioactive
elements in the earth’s crust that lead to human exposure are potassium, uranium, thorium, and theirradioactive decay products (e.g. radium, radon). A high natural background radiation (HNBR) area isdefined as an area where the total cosmic radiation and natural radioactivity in soil, indoor and outdoor
air, water and food lead to chronic external and internal exposure to the public [H4]. The annual
effective dose in HNBR areas has been classified into four levels: low (approximately 5 mSv a−1) orabout twice the global average of 2.4 mSv a−1 reported by UNSCEAR [U10]; intermediate(5-20 mSv a−1); high (20–50 mSv a−1); and very high (>50 mSv a−1) [S22, S23]. In this chapter, major
cancer epidemiological studies in HNBR will be described. They focus on areas where typical annual
doses from external terrestrial gamma radiation alone is of the order of magnitude of 2 mSv a−1, andcumulative lifetime doses are in range of 20–50 mSv and higher.

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99

A. Studies in Karunagappally, Kerala, India
1.

Radiation sources

99. The mineral monazite, an anhydrous phosphate of the cerium group of the rare earths, was named
by Breithaupt [B18]. Monazite sand is an orthophosphate of thorium and rare earths and typicallycontains thorium oxide (8% on average) and uranium oxide (0.3% on average) along with phosphorous
pentoxide, rare earths, titanium oxide, cerium oxide, iron oxide and silicon dioxide [B11, O5, S29].
Most monazite is various shades of yellow. Shades of yellowish brown, brown, reddish brown, red,
yellowish green, green, and greenish brown are locally common in detrital monazite from streams andlakes and in accessory monazite in schist, gneiss, granite and, particularly, pegmatite [O5].
100. The large monazite deposits in the coastal belt of Kerala, India, were discovered already in 1909
[K19]. The coastal zone from Chavara-Neendakara in the south to Purakkad in the north, which isflanked by the Arabian Sea in the west and Western Ghats in the east, is known to have thoriumcontaining monazite sand and a large quantity of other minerals. The radiation dose in terms of air
kerma ranges from <1 to 45 mGy a−1. The HNBR area extends from the outlet of the Ashtamudi Lakein the south up to the Kayankulam Lake in the north. There is a canalized lagoon on the eastern sideand the Arabian Sea on the west. So this area constitutes an island, which is 55 km long, and 0.5 km
wide in the south and 1.5 km wide in the north. It has alternating bands of light and heavy minerals up
to a depth of about 15 m [W7].
101. The beach boulders, include khondalites, chamockites, gneiss and granites, are lying in thehinterland granulitic terrain in parts of Tamil Nadu and Kerala. They were brought to the sea by fluvial
transportation [P2, S30]. The largest of these streams, the Kallada River, empties into the Ashtamudi
Lake, which is separated from the Arabian Sea by the Neendakara bar. The Warkilli series ofsedimentary rocks in the lake are further transported to the coast by rivers that drain into the sea. The
rocks of the Warkilli series are intermediate host rocks for monazite between the original source rocks
and the beach boulders. Three rivers in the south of Kerala, i.e. Neyyar, Karamana and Vamanapuram,are also suspected of transporting more radioactive elements than the larger Kallada River due to higher
levels of radioactive minerals in the hinterland rocks [P10].
102. Monazites and other heavy minerals in the beach are considered to be reconcentrated by wind,
waves and currents. Ordinarily, monazite makes up less than 10% of the beach sand, possibly about
2–3% of the raw sand [B20, K1, W1]. However, at favourable localities, such as the coastal region ofChavara-Neendakara, tidal currents and waves selectively remove minerals of low specific gravity andleave behind minerals of high specific gravity [O5]. The raw black sand, however, contains 50–90% of
ilmenite and 3–30% of monazite, containing 8% of 232Th on average [I7, O5]. Coastal configurations
and sea currents in the south of Kerala are also suspected to be factors contributing to the deposition ofthese elements in the Chavara-Neendakara area [P10].
103. The first report of the WHO’s Expert Committee on Radiation (Effects of Radiation on Human
Heredity) was published in 1959 [W7]. It mentioned that “one untapped source of informationsuggested was the study of populations exposed to relatively large amounts of background radiation,that is, radiation of the order of one ‘rem’ per year”, and that “the Kerala area of India would appear tobe the only area now known, which might profitably be investigated”. According to the report,
approximately 60,000 people living in the radioactive milieu of the Chavara-Neendakara area were
subjected to low-level chronic radiation exposure and presumably have been exposed for generations.

100 UNSCEAR 2017 REPORT104. The WHO report summarized the population characteristics in the 1950s. The main features were:(a) approximately half the population were Christian and the rest Hindu; (b) the great majority lived
from fishing; and (c) the percentage of literacy was high. Consanguineous marriages were fairly
common among the Hindus. It was preferred that a man married his full cousin who was his paternal
aunt’s daughter (and therefore, would probably be brought up in another village). Among Hindus, fullcousin marriage rate was considered to be about 10–20%.
105. The infant mortality rate in this area was higher than 100 per 1,000 live births, indicating thatpublic health conditions in this area were poor, though the situation has improved in Kerala since the1960s. Twelve deaths per 1,000 births were reported in 2011, while it was as high as 44 deaths in theentire country [O1].

2.

Study population(a) Cohort characterization
106. Baseline survey. The Chavara-Neendakara area is in the coastal belt of the Karunagappally taluk(administrative district). A cohort of all residents in the Karunagappally taluk (population size: 385,103
according to the population census in 1990) was established in the 1990s to evaluate the health effectsof HNBR [N4]. From 1990 to 1997, house-to-house visits were conducted to measure indoor andoutdoor air kerma rates and to collect personal information using a standardized questionnaire. This
included questions on sociodemographic factors, lifestyle, including dietary habits, and tobacco andalcohol use. In total, this household survey collected personal information on 359,619 subjects in
71,674 households, which corresponds to 93% of the population and 94% of households in
Karunagappally by the 1990 census. No attempt was made to re-interview the cohort members.
107. Among male adults (aged 30–84 years), 73% were Hindu and 18% Moslem. Only 6% were
illiterate. More than 60% of the study subjects said they had smoked bidis in the past or did socurrently. Bidi is made of 0.15–0.25 g of sun dried flaked tobacco rolled into a conical shape in a dried
rectangular piece of Temburni leaf (Diospyros melanoxylon) and a thread securing the roll [S26].
Among the subjects aged 70 or older at the time of interview, bidi smokers accounted for more than
70%. Tobacco chewing was reported by 24% of the cohort members and, among those aged less than
70 at the time of interview, more than 50% were past or current tobacco chewers. Approximately 50%
were past/current alcohol drinkers [J4]. The most popular alcohol beverages in this population are
locally produced, including toddy (palm wine) and arrack (a strong liquor made from coconut flowers,
sugarcane or other locally grown plants) [J5]. Fishing is the main source of livelihood for the coastal
residents. Among men aged 30 years or older, fishermen and farmers accounted for nearly 20% of
residents. However, since this group was reported to have 20–30% higher lung cancer incidence thanthe other occupational groups [J6], it is strongly suspected that smoking is a more common habit than inother occupations.
108. Among adult women (aged 30–84 years), 72% were Hindu and 20% Moslem. Among the female
cohort members, fewer than 5% were fisherwomen and farmers, and 17% were illiterate. Tobaccosmoking and alcohol drinking are rare among women [J4].
109. In summary, the population in Karunagappally and other areas in Kerala evidently has better
public health and education levels than found in other areas in India. The main industry in
Karunagappally was agriculture until the late 19th century. Since then, it has been rapidly urbanized.

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101

Fishing is the main source of livelihood for the coastal residents. Further, a regional cancer registry has
been in existence since 1990, interviews have been conducted with most of the population, and efforts
have been made to obtain dose estimates based on measurements for individuals. However, there isevidence of under-ascertainment of cancer cases. The International Agency for Research on Cancer(IARC) stated in 2002 “However, the percentage of cases with primary site unspecified or ill-defined isvery high, as is the proportion of cases registered on the basis of a death certificate alone, suggesting a
degree of under-ascertainment” [N2].
110. For radiation risk analysis, six panchayats, including four panchayats with relatively highenvironmental doses (Alappad, Chavara, Neendakara and Panmana) and two panchayats with relatively
low environmental doses (Oachira and Thevalakkara), were chosen in coastal areas. The Kollam area
was not included since this area is much more urbanized than the Karunagappally taluk, as pointed out
by WHO’s Expert Committee on Radiation [W7]. The control areas in this cohort are Oachira andThevalakkara panchayats, located in the northern and eastern areas of this taluk. This decision iscompatible with the WHO committee’s notion, which is that: “a defined strip of north of Kayamkulam
bar would probably be most suitable as a control area”. The population of those six panchayats selected
for radiation-related risk analysis consisted of 173,067 individuals. This subcohort will hereinafter becalled “the radiation subcohort”.
111. There were 71,399 men and women aged 30–84 in this subcohort. Those younger than 30 were
excluded because (a) cancer risk was low in that age group and (b) the cumulative radiation dose was
expected to be relatively low. Rare-earth technology workers, who might have been exposed to various
types of occupational exposure (N=1,196), and those who had died or had been diagnosed with cancer
before the baseline survey were excluded. Thus, there were 69,958 individuals for statistical analysis.

(b) Follow-up
112. Cancer cases in the cohort were ascertained by the cancer registry in Karunagappally, establishedin 1990. One of the main activities to identify cancer cases was monthly routine visits to the Regional
Cancer Centre in Trivandrum, which is situated 70 km south, and is the comprehensive cancer centre in
the state of Kerala. More than half of the cancer cases registered in the Karunagappally cancer registrywere those who sought medical treatment in the Regional Cancer Centre [J6]. Further, annual visits tothe following medical facilities were conducted: (a) Trivandrum Medical College Hospital in
Trivandrum; (b) major pathological laboratories in the Karunagappally taluk and its neighbouring areasand in Trivandrum; and (c) all the hospitals and medical practitioners in the Karunagappally taluk. In
addition, three to four times a year, the registry workers visited three primary health centres in the taluk,which have cancer screening facilities. Cancer cases were also ascertained by (a) monthly clinics toprovide follow-up care for local cancer patients, and (b) the cancer screening camps conducted twice ayear on average in all panchayats in the taluk. The registry data have been included in the recent
editions of “Cancer Incidence in Five Continents”, which indicates that it fulfils the quality
requirements for inclusion in IARC monographs [I2].
113. Death reports were obtained from the death registers kept in the health statistics divisions of thepanchayats. Visits to homes of the deceased were made to supplement information on the cause ofdeath. The extent of migration of radiation subcohort members (N=173,067), including control-area
residents, was assessed by conducting a door-to-door survey of all the households in 2001. Movement
within the panchayat was 9.5% while migration to outside the taluk was 6% in the 13-year study period.
Most migration took place for job opportunities in the Gulf countries. Only 0.7% was lost to follow-up.

102 UNSCEAR 2017 REPORT114. The entry into the cohort was the date of interview, which ranged from 1 January 1990 to
31 December 1997. The follow-up ended on the date of (a) cancer diagnosis; (b) death; (c) migrationout of the study area; (d) attainment of 85 years; or (e) the 31 December 2005 (follow-up termination),
whichever occurred first. In person-year calculations, the migration that had taken place until the
migration survey in 2001 was taken into account.

3.

Dosimetry

115. The HNBR in Karunagappally is mainly from thoron progenies and relatively high air kerma rates
are found mainly in the coastal zone of Karunagappally taluk. In the Karunagappally study, exposure
was mainly from external gamma [N4] and indoor air kerma rate measurements were made at every
house in the 1990s. Outdoor dose rates were measured only at the front gate. Air kerma rates at schoolor at work locations (including sea for fishermen and farmland for farmers) were not measured.
Information that would enable an evaluation of the correlation between ambient dose rates at school (orat work) and in the home was not available. Because women tended to stay at home longer than men,the cumulative dose estimates for women seemed more reliable than those for men. Sex- andage-specific house occupancy was determined on the basis of information collected from the survey ofrandomly selected residents in the study area (N=7,711). No information was available on occupancy athome and other locations for each resident. The indoor and outdoor air kerma rates of those panchayats
are shown in table 13.
Table 13. Annual air kerma in six panchayats in Karunagappally, Kerala, India
Annual air kerma(mGy a−1)

Panchayats
OachiraThevalakkara

Panmana

Neendakara

AlappadChavaraINDOOR MEASUREMENTSMedian

1.07

1.22

2.29

2.52

3.14

3.90

Maximum

9.18

9.56

21.4

53.6

25.3

42.9

OUTDOOR MEASUREMENTSMedian

0.92

1.07

3.21

4.21

4.51

5.28

Maximum

12.1

29.8

30.6

76.5

43.1

63.0

116. Individual radiation dose (excluding cosmic rays) was estimated from the HNBR area on the basisof outdoor and indoor air kerma rates, taking into account sex- and age-specific occupancy factors. One
indoor and one outdoor measurement of air kerma rates from gamma rays were conducted in 71,674
houses, using seven sodium iodide (NaI) detector-based scintillometers and six plastic scintillometers,
which were designed and supplied by the Bhabha Atomic Research Centre, Mumbai, India. All thesewere cross-calibrated every day using a standard 137Cs source in the laboratory before fieldmeasurements were made. The mean of three readings was taken for every measurement. For indoor
measurement, the room with maximum occupancy was selected and the readings were taken in thecentre of the room at a height of 1 m above the ground for five minutes. For outdoor measurement,
five-minute readings at a height of 1 m above the ground were taken at a point 3 m away from the main
entrance of the house.
117. Information on house occupancy was not collected through the baseline survey. As the populationin the radiation cohort was very large, only a sample population was interviewed to obtain informationon the fraction of time spent indoors and outdoors [N3]. In 2002, 2% of all houses were randomly

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

103

selected and information on occupancy was obtained for 7,711 residents (3,783 males and 3,928
females) in all age groups living in the selected houses. The house occupancy factor varied from 0.5 to
0.89 depending on sex and age, which are comparable with the value of 0.8 cited by UNSCEAR [U7].
118. Assuming the air kerma values for the cosmic ray component of the measured radiation level tobe 0.227 mGy a−1 for indoors and 0.252 mGy a−1 for outdoors [A4, B13, U4, U7], the annual absorbed
dose for each individual was calculated using the formula:
Annual colon/RBM dose (mGy) = [(Kindoor y−1 – 0.227) × OFindoor + (Koutdoor y−1 – 0.252) × OFoutdoor] × CF

where Kindoor y−1, and Koutdoor y−1 are annual mean indoor and outdoor air kerma rates for the ward or
panchayat. OF is the occupancy factor and CF is the conversion factor for air kerma to organ-specificabsorbed dose presented in the ICRP Publication 74 [I5]. The CF for 232Th used in the present study
was 0.782 for the colon and 0.791 for RBM. The CFs for children aged 1–14 years and infants aged lessthan one year were increased by 10% and 30%, respectively. Colon dose was used for risk analysis
since the LSS reports of cancer risk analysis of atomic bombing survivors also used it [P14]. Assumingthat the external radiation from HNBR was whole-body exposure, total body exposure was represented
by absorbed dose of the colon. The cosmic ray component (0.252 and 0.227 mGy a−1 outdoors andindoors, respectively) was subtracted from the measured dose in order to estimate the radiation dosefrom terrestrial radiation exposure. The individual cumulative dose was calculated by adding up theannual dose over time and the average was reported as 161 mGy in the exposed cohort [N4].
119. Information on migration was taken into account when estimating the cumulative dose of thecohort subjects in the following manner. When migration occurred into the Karunagappally taluk, themean outside and inside radiation doses of the Oachira panchayat (a control area) were assigned to theages of the immigrants before migration. When a subject moved within the Karunagappally taluk, theaverage outdoor air kerma rate of the ward in which the house was located and the average indoor air
kerma rate of all the houses in the same ward were assigned. If the ward was not known, the mean
outdoor air kerma rate of the panchayat was taken.
120. The measurements of scintillometers was compared with thermoluminescent dosimeters (TLD),
which showed a good correlation (regression coefficient 0.97) [N4]. It would have been ideal to use
TLD for dose measurements but using it for measuring the outdoor and indoor dose of 75,000 houses
would have been extremely difficult. In order to calculate the annual dose based on scintillometer spot
readings, it was necessary to confirm the correlation between the spot reading and long-term exposurelevels. For this purpose, TLD measurements and scintillometer spot readings were conducted for one
year in 800 houses, randomly selected from 12 panchayats. Natural calcium fluoride powder was placed
inside a brass capsule with a diameter of 3 mm, a length of 8 mm and a wall thickness of 1.5 mm.
About 50 mg of the powder was dispensed inside the capsule using a vibrator volume dispenser. Twosuch capsules were placed inside a plastic locket with a wall thickness of 2 mm. The locket was placed
inside the house taped below a cot or table at a height of 50–100 cm above the ground in a room withmaximum occupancy. The TLD was read under a constant nitrogen flow of 5 L min−1, using a Harshaw
3,000 reader calibrated with a 137Cs source. The dose was measured in quarterly integrating cycles forthe whole year at the same place. A scintillometer reading was taken at the same height in the same
house every quarter. The mean of the four spot readings (µR h−1) was converted to the annual dose(mGy a−1), using a conversion factor of 0.0765 (= 8.73 × 24 × 365.25/106) [N3].
121. The study examined the correlation between scintillometer readings converted to annual dose andthe annual dose evaluated using TLD. The correlation coefficient was 0.93 and the TLD dose was 0.97
times the scintillometer-based annual dose. The scintillometer measured an outdoor dose at the door
and indoor doses at each house, and individual doses had a wide distribution. However, the high104 UNSCEAR 2017 REPORT

correlation coefficient indicates that the major radiation source of studied subjects are from theresidence and areas near the residences. The annual radiation doses (mGy a−1) used in the cancer risk
analysis were obtained by converting the scintillometer-based annual dose to TLD equivalent annual
dose, multiplying by 0.97.

(a) Internal exposure122. Indoor radon and thoron concentrations, and also thoron progeny, were measured in 259
dwellings of the Karunagappally taluk: 183 in HNBR areas and 76 in low-background-radiation areas[O3]. Internal doses due to ingested and inhaled radionuclides were not considered in the cumulative
dose estimation, but measurements were made to evaluate them. This survey used the passive
monitoring device named raduets, which has a twin-cup monitor with two CR-39 solid-state nuclear
track detectors to measure indoor thoron and radon gas concentrations separately. Indoor thoron
progeny concentrations (equilibrium equivalent thoron concentrations) were also determined, using apassive device with CR-39 solid-state nuclear track detectors to count alpha particles emitted only from
deposited thoron progenies. The monitors were deployed for about six months. Indoor radon gas
concentrations in the study area were low (table 14), below 10 Bq m−3 in most houses [O3]. Indoor
radon gas and thoron gas concentrations had no correlation. Similar results were obtained in the second
series of the survey (table 14).
123. The median effective annual dose from indoor radon and its progeny was estimated as 0.1 and thatfrom thoron decay products as 0.4 mSv a−1 (table 15). It is also noted that radon and thoron gas
concentrations and thoron progeny concentration were not correlated with the indoor air kerma rate
obtained from instantaneous measurements by a semiconductor detector with electrostatic collection,
grab sampling of thoron progenies and a CsI (Tl) scintillation survey meter. The absence of significant
correlation could be explained with the fact that building material contained uranium decay series
nuclides, thorium decay series nuclides and 40K, which are major contributors to air kerma rate in the
study area. However, the magnitude of their contributions can vary from house to house. Anotherexplanation may be that the rate of entry of thoron in a dwelling is highly variable according to thebuilding material and to the flooring. Mean indoor concentrations of radon and thoron progeny are alsoslightly lower in HNBR areas than in other areas.
124. The meals of residents did not contain a large proportion of food grown in their neighbourhood.
Therefore, it is unlikely that lifetime radiation doses from internal exposure differed substantiallybetween areas within Karunagappally. The thorium burden of 87 residents in Karunagappally wasdetermined by a thoron-in-breath analysis [N3, N5]. The mean 232Th body burden for 16 subjects fromnormal background level areas (mean 0.72 mGy a−1) was 6.3 Bq. For 33 subjects from medium
background radiation level areas (mean 2.04 mGy a−1), the mean 232Th body burden of 8.9 Bq wasestimated and 38 subjects from high-background radiation areas (mean 15.64 mGy a−1) had a mean of
10.91 Bq. These results show that the subjects from high and medium indoor radiation level areas show
a significant increase in the thorium body burden (P=0.0094) compared to those from low indoor
radiation level areas.

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105

Table 14. Indoor radon and thoron gases and thoron progeny concentrations in Kerala, India [O3]Survey a

Source

1st survey

HNBR areas

Concentration (Bq m−3)Houses (NAb)

MeanMedian

Range

c

Radon

53 (22)

5±3

4

1–13

Thoron68 (7)

53±28

46

15–128

Thoron progeny

66 (9)

2.15±1.57

1.48

0.59–6.72

Radon

37 (13)

8±5

9

1–21

Thoron48 (2)

47±44

31

11–212Thoron progeny

44 (6)

2.32±1.51

1.91

0.36–8.00

Radon

80 (28)

5±4

4

1–30

Thoron104 (4)

26±20

20

3–151

Thoron progeny

63 (45)1.56±1.01

1.21

0.52–5.72

Radon

14 (13)

7±11

4

1–43

Thoron26 (1)

30±35

16

7–133

Thoron progeny

18 (9)

1.69±1.74

1.22

0.45–7.53

Other areasd

2nd survey

HNBRc areas

Otherd areasa

The first survey was conducted during June 2010–February 2011. The second survey was conducted during December
2010-June 2011. In both studies, raduets were in place for about six months.

b

NA: data are not available (“below the detectable level” is included). The lower limit of detection for radon and thoron
measurements are around 1.0 Bq m−3 and 2–43 Bq m−3, respectively. The lower limit of detection for thoron progeny
measurement is 0.003 Bq m−3.
c

The HNBR areas are Panmana, Neendakara, Alappad and Chavara panchayats in Karunagappally taluk.

d

Other areas are Oachira and Thevalakkara panchayats in the taluk.

106 UNSCEAR 2017 REPORT

Table 15. Effective doses from internal exposure due to inhalation of indoor radon and thoron
progeny in Kerala, India [O3]The conversion of indoor radon and thoron concentrations to effective doses was based on [U7]Area
All areas

HNBR areas

Other areas

SourceEffective dose (mSv)

Housesa (NAb)

MeanMedianRange cRadon

184 (76)0.14±0.12

0.10

0.02–1.07

Thoron191 (69)

0.55±0.40

0.40

0.10–2.24

Total

191 (69)0.65±0.44

0.50

0.13–2.60

Radon

133 (50)0.12±0.09

0.09

0.02–0.75

Thoron129 (54)0.52±0.38

0.39

0.15–1.88

Total

129 (54)0.61±0.39

0.49

0.18–1.98

Radon

51 (26)0.19±0.18

0.16

0.02–1.07

Thoron62 (15)0.60±0.44

0.44

0.10–2.24

Total

62 (15)0.74±0.52

0.64

0.13–2.60

aTwo series of the survey in 260 houses: 183 in Panmana, Neendakara, Alappad and Chavara panchayats (HNBR areas) and77 in Oachira and Thevalakkara panchayats (other areas) in Karunagappally taluk.
b

NA: data are not available (“below the detectable level” is included).

cRange: effective doses from the concentrations “below the detectable level” or being not evaluated are excluded [O3].

(b) Biological dosimetry
125. Researchers from the Bhabha Atomic Research Centre, Mumbai, India carried out cytogenetic
investigations on newborns (from 1986 to 2007) in conjunction with a study of congenital anomalies toestimate and compare the incidence of karyotype anomalies (both structural and numerical) and thefrequency of chromosomal aberrations (both stable and unstable aberrations) following in utero
radiation exposure [R1]. A total of 1,267,788 metaphases from 27,295 newborns (14,062 males and13,233 females) were analysed for chromosomal aberrations and karyotype anomalies, of which 17,298
newborns (964,390 cells) were from HNBR areas (>1.5 mSv a−1), and 9,997 newborns (303,398 cells)
were from relatively low-level background radiation areas (<1.5 mSv a−1). There were 162 (5.94‰)
karyotype anomalies (90 numerical and 72 structural) observed in these newborns, of which 95 werefrom HNBR areas (55 numerical and 40 structural) and 67 (35 numerical and 32 structural) from therelatively low-background radiation areas (the control area). Newborns in the two areas had no
statistically significant difference in the frequency of overall karyotype anomalies (5.49‰ vs 6.7‰). Its
relative frequency (RF) was 0.82 (95% CI: 0.60, 1.12). No statistically significant area difference wasobserved for numerical anomalies (3.18‰ vs 3.5‰; RF: 0.91; 95% CI: 0.59, 1.39) or structuralanomalies (2.31‰ vs 3.2‰; RF: 0.72; 95% CI: 0.45, 1.15). The data did not suggest any dose-related
trend in numerical, structural or overall karyotype abnormalities.
126. The spontaneous frequency of different types of chromosomal aberrations in those newborns wasanalysed and reported per 10,000 cells. The two groups showed no significant difference in the baselinefrequency of dicentrics (1.90±0.14 in HNBR-area group and 2.01±0.26 per 1,000 in the control-areagroup; RF: 0.94; 95% CI: 0.71, 1.26). Similarly, baseline frequency of stable aberrations(translocations, inversions) in the two groups did not show any statistically significant differences(4.42±0.19 in HNBR areas as compared to 4.17±0.21 in the control area; RF: 0.80; 95% CI: 0.67, 0.96).

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No area difference was found in the frequency of all chromosomal aberrations, which included
dicentrics, translocations, inversions, rings, fragments and minutes (8.32±0.29 in HNBR areas and9.29±0.55 in the control area; RF: 0.89; 95% CI: 0.78, 1.02) [C5, R1].
127. The spontaneous frequency of micronuclei was determined in 271 newborns (61 from the control
area and 210 from HNBR area) born to mothers between 17 and 37 years of age (mean maternal age:24.1±4.2 years). The frequency of micronuclei in newborns was 1.40±0.12 per 1,000 binucleated cells
in the control and 1.33±0.04 in HNBR areas. When the samples were categorized into six different
groups on the basis of the level of background radiation, no dose response was observed. The
spontaneous frequency of micronuclei in newborns in HNBR and control areas showed no statisticallysignificant difference, suggesting that slightly elevated levels of background radiation during the foetal
period had no significant effect on induction of micronuclei in the newborns [D2].
128. To assess the effect of HNBR on the adult population, chromosomal aberrations in lymphocytesof adult individuals living in HNBR areas were investigated at the Regional Cancer Centre, Kerala[H2]. Blood samples from the female inhabitants, aged 30–58 years, in the HNBR and control areas
were collected and examined for the frequency of dicentric and ring chromosomes in peripheral
lymphocytes. The selected subjects had been born and brought up in the HNBR area or in the control
area, and had been living there for a minimum of 30 years. A total of 23,673 cells from eight subjects in
HNBR areas and 23,718 cells from eight subjects in control areas were examined. The estimatedindividual cumulative doses in the control area were 12–18.5 mSv (average=15.6 mSv, SD=2.4 mSv)
and those in the HNBR area were 16.8–402.6 mSv (average: 187.5±157.7 mSv). The cytogenetic
analysis revealed that the average numbers of chromosomal aberrations per 1,000 cells were 0.76±0.77
in control areas and 13.8±6.8 in HNBR areas.
129. No increase in DNA double-strand breaks in terms of gamma-H2AX was found in 61 adultresidents of the HNBR areas compared with 30 from the control area in mononuclear cells fromperipheral blood (0.095±0.009 and 0.084±0.004 per cell; P=0.22) [J2].
130. In another cytogenetic study, the frequencies of micronuclei were analysed in 94 adult men fromthe HBNR areas and 47 from control areas [J2, K2]. An average of 1,835 binucleated cells per
individual were scored. The mean frequencies of micronuclei in the HBNR (11.7±SD 6.6) and control
areas (11.6±6.7) were not statistically significantly different (P=0.59).
131. No differences in telomere length were found in two studies examining adults or newborns in the
HNBR area compared with the control area. In the adult study with 233 exposed subjects the mean
telomere length was 1.22±0.15 for the lowest and 1.12±0.11 for the highest group [D3]. In the newborn
study, the average was 1.03±0.01 in the 128 exposed and 1.10±0.03 in the 43 control infants [D4],however, it is not indicated whether adjustment for age was used in the adult analysis.

4.

Cancer incidence

132. In the Karunagappally cohort study of 69,958 subjects [N4], a total of 1,349 cancer cases werereported. The three most common cancers were oropharyngeal, lung and breast cancer (220, 189 and125 cases, respectively). Of the cancer cases, 13% had an unknown primary site. In addition, there were
30 leukaemia cases (including 10 CLL).
133. Statistical analysis was based on the data in cross-tabulations by sex, attained age (five-year
category) and other covariates. The entry into the cohort was the date of the baseline survey (date ofinterview). Poisson regression analysis of grouped survival data [B19] was conducted. To allow for a

108 UNSCEAR 2017 REPORT

possible latent period between radiation exposure and its consequences, cumulative doses were laggedby 10 years for all cancers except leukaemia where a lag of two years was used. Statistical power was
not calculated prior to the establishment of this cohort.
134. Assuming a linear dose response, the ERR of all cancers except leukaemia in relation to
cumulative dose was estimated using the following Poisson regression model:
H0(sex, attained age, follow-up interval, bidi smoking, education, occupation) [1 + β D]
where D is cumulative radiation dose calculated over time, and β, the coefficient of D, describes therelative change in rates associated with dose. H0 is the baseline cancer rate, depending on sex, attained
age, follow-up intervals and other covariates (sociodemographic factors and bidi smoking). Analysis ofcohort data, stratified* by sex, attained age, and follow-up interval, showed no excess cancer risk fromexposure to terrestrial gamma radiation.
135. The excess relative risk of all cancers, excluding leukaemia, was estimated to be −0.013 per
100 mGy (95% CI: −0.058, 0.046). In site-specific analysis, no cancer site was significantly related tocumulative radiation dose (ERR=0.03 per 100 mGy for oropharyngeal and 0.01 for digestive tract
cancer, lower confidence bounds not defined, upper bounds approximately 0.25). Leukaemia was not
significantly related to background radiation (ERR=0.6 per 100 mGy, lower confidence limit not
defined, upper limit 34). The follow-up period of the Karunagappally cohort study was recently
extended by four years. The major methodological features of the Karunagappally study aresummarized in table 16.
136. The Kerala programme of studies has several strengths: (a) the cumulative dose to date, 161 mGy
average, is relatively large; (b) potential confounding factors such as tobacco use and socioeconomic
status (SES) have been obtained by interview and can be adjusted for in the analysis; and (c) a cancer
registry, described in Cancer in Five Continents (IARC), has existed since 1990 and thus data on cancer
incidence (but not mortality) are available. Details of smoking adjustment were not, however, reported.
The baseline interview covered the amount of both cigarette and bidi smoking, and also smoking status
at interview (never, past, current), but the study report mentioned only adjustment for “bidi smoking”.
However, there are uncertainties in dose estimates mainly due to exposure outside the residence, lack of
exposure data for full residential history, and use of aggregate estimates rather than individual data for
occupancy. The numbers of cases for several cancer sites are still relatively small. A quarter of thecases lacked pathological verification of the diagnosis. Furthermore, case ascertainment may be
incomplete, given the low health-care level in the area. The primary occupation is fishing and,currently, there are few major environmental pollutants in these coastal regions, but potential
differences in lifestyle between the populations of the high exposure area on the coast and the lower
exposure area further inland need to be considered. Migration was also taken into account whencalculating individual cumulative dose [J3, N1, N2]. In summary, while the findings in this study arereasonably robust, the confidence intervals obtained from the study are still wide and cannot
convincingly discount risks similar to those reported from the LSS.

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Table 16. Summarized characteristics of the Karunagappally cancer incidence study [N4]Characteristic

Description

Study design

A prospective cohort study

Study population

A cohort of 69 958 residents whose information was collected at the time of baseline
survey (1990–1997). Those who were diagnosed with cancer before the time of baseline
survey were excluded from the cohort

OutcomeCancer incidence

Mortality follow-up

Official vital statistics supplemented by the field surveys conducted by investigators

Cancer caseascertainment

Cancer cases in the cohort were ascertained by the cancer registry in Karunagappally,
established in 1990

Follow-up/migration

Surveys to identify out-migrants were conducted in 2000 and 2001

Exposure

Individual cumulative colon doses from external irradiation were estimated on the basis ofmeasured indoor and outdoor air kerma dose rates and sex- and age-specific occupancy
factors. Indoor and outdoor air kerma dose rates were measured at each house.
Information on house occupancy factors was obtained from a survey of 7 711 residents in
2002. The uncertainties in the estimates of individual cumulative colon doses have notbeen evaluatedConfounding

Data on socioeconomic status (SES) and lifestyle factors were collected in the baseline
survey conducted during 1990–1997

Medical exposure

Information on medical radiation exposure was not collected

Statistical power

No formal power calculations are available, confidence interval width does not distinguishbetween effect size similar to LSS and no risk

Analysis

The main analysis was to estimate an ERR per unit dose, which was estimated using
Poisson regression methods. Cumulative dose was lagged by 10 years for solid cancer
risk analysis. Subjects used for analysis were those aged 30 years or older at the time ofbaseline survey and attained ages of 30–84 during the follow-up period, which starts atthe time of baseline survey and ends at the time of migration, death, cancer
development or the end of follow-up (the end of year 2005)

Main results

For incidence of cancer other than leukaemia ERR −0.01 per 100 mGy (95% CI: −0.06, 0.05)

B. Studies in Yangjiang, Guandong Province, China
1.

Radiation sources

137. The Yangjiang area in Guandong Province, China, is known for its natural HNBR. In this region,
fine particles of monazite are washed down the mountains by rain to the surrounding basin regions,giving rise to soil with high levels of radioactive nuclides such as 232Th and 238U [Y2]. Morishima et al.
suspected that the main source of HNBR was the natural radioactive nuclide concentrations in building
material using such soil [M6]. The average annual doses of external radiation from natural sources,
including thorium, in the HNBR and control areas were estimated to be 2.10 and 0.77 mSv a−1,
respectively [M6, Y2].

110 UNSCEAR 2017 REPORT

2.

Population characterization and follow-up

138. The HNBR area of Yangjiang covering a total area of about 540 km2 [H5], consists of the
Dong-anling and Tongyou regions, which had 21,838 and 44,786 residents, respectively, at the time of
the national census conducted on 1 January 1979. The residents are of the Han nationality, and 90% of
the population had been living in those areas for six or more generations. The control area of the study
is the Wudianmeihua region in Enping, located 50 km west of Dong-anling, which is 60 km east of
Tongyou. Wudianmeihua had 25,924 residents at the time of the census. The primary occupation is
farming, which might involve some exposure to insecticides.
139. The cohort consists of approximately 90,000 residents of the study area, including control areas,
who were alive as of 1 January 1979. The most recent study analysed the mortality data of 31,604 men
and women who attained the age of 30–74 during the follow-up period of 1979–1998 [T3]. It was
decided to exclude those younger than 30 years because: (a) cancer risk was low in that age group;(b) the cumulative radiation dose was expected to be relatively low; and (c) childhood cancer isconsidered to have aetiological backgrounds different from adult cancer. In addition, cumulative doses
remain relatively low for those young age groups. Those aged 75 years or older were also excluded
from the analysis, because the elderly were less likely to seek medical care for cancer and chronic noncancer diseases and, thus, the inclusion of this age group might result in a lower accuracy of diagnosis.
140. In order to compare lifestyles, socioeconomic conditions and other factors in the study areas,
Chinese investigators conducted studies on confounding factors including diet and nutrition, drinking
water, pesticide residue and aflatoxin B1 in food, medical radiation exposure, tobacco smoking andalcohol consumption. The studies showed that the distribution of those potential confounding factors
did not substantially differ in the two areas [T4, Z4]. However, no individual-level data were collectedon major cancer risk factors for the cohort members.
141. In order to ascertain deaths in cohort members, trained local census takers surveyed the hamlets ofthe study areas to collect information on deaths and migration of inhabitants in each hamlet. The
collected information was recorded on a demographic survey sheet prepared for each household in thehamlet. The task group on the mortality follow-up survey then visited the study areas and reviewed thesurvey sheets. In order to ascertain the cause of death, they visited the relevant hospitals in the study
areas, reviewed medical records of deceased subjects and extracted relevant information. If necessary,
the task group revisited the local village doctors and the family members or next of kin to collectfurther information on the cause of death. The underlying causes of death were determined on the basisof pathological information for 240 (26%) deaths.

3.

Dosimetry

142. The doses from external radiation from HNBR in Yangjiang are due mainly to gamma rays fromradionuclides of the 232Th decay series. Indoor air kerma rates were measured at approximately one
third of houses at a village selected for indoor dosimetry (measurements available for the analysis
covered 8,028 households in total). Therefore, the individual cumulative dose for a resident is based on
the average dose in the village of residence. However, inter-house differences were not large [M6].
Indoor and outdoor ambient gamma dose rates were 110–370 and 100–220 nGy h−1, respectively.
Doses received from indoor terrestrial radiation were estimated to be 0.6–1.8 mSv a−1 [O2]. Outdoor air
kerma rates were measured in most of the locations where a villager spent some time, and were foundto be more heterogeneous than indoor absorbed dose rates in air [M6, Y1, Y2]. Although the hours
spent in each location in a village differ by sex, age and occupation, whether those points were taken

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111

into account or not is unclear. It should be noted, however, that indoor exposure contributes more to thetotal dose than outdoor exposure in this study area. House occupancy factors were collected by a surveyof approximately 5,291 subjects during 1991–1993 [T3, Y1]. Air kerma rates in schools or workplaces
were measured. More detailed descriptions on dosimetry are given below.
143. Individual radiation dose from the HNBR was estimated on the basis of outdoor and indoor air
kerma rates and sex- and age-specific occupancy factors. Environmental dose rates were measured with
Chinese NaI (TI) scintillation survey-meters, FD71 or FD3013 [Y2]. In every hamlet, indoor
measurements were conducted in about one third of all households, and measurements for 8,028
households in total were available for the analysis. Indoor gamma radiation doses were measured in themain bedroom, the sitting room and the kitchen in each of those households. Outdoor doses were
measured on main roads, alleys, open recreational areas, rice paddies, areas adjacent to wells, dry land
and the banks of ponds for each hamlet.
144. House occupancy factors specific for sex and age were obtained from a questionnaire survey of
5,291 subjects (0–92 years old, mean age=54, SD=22) in over 88 hamlets conducted from 1991 to 1993
[Y1]. Age categories were listed in five-year periods between 30−34 and 70–74. The sex- and agespecific occupancy factors represented the time spent in bed, and at the other indoor places [Y1, Y2].
145. The annual absorbed dose for each individual Dindividual y–1 (mGy) was calculated using:
Dindividual y−1 = [(Kmain bedroom y−1 – CRindoor y−1) × OFmain bedroom + (Kother rooms y−1 – CRindoor y−1) × OFother−1−1
rooms + (Koutdoor y – CRoutdoor y ) × OFoutdoor] × CF
where Kmain bedroom y−1, Kother rooms y−1 and Koutdoor y−1 are annual doses for the main bedroom, for therooms other than the main bedroom, and for outdoors, respectively; CRindoor y−1 and CRoutdoor y−1 areindoor and outdoor annual cosmic ray doses, respectively; OFmain bedroom, OFother rooms and OFoutdoor are theoccupancy factors for the main bedroom, for the rooms other than the main bedroom, and for outdoors,
respectively; and CF is the conversion factor for air kerma to organ-specific absorbed dose given in
ICRP Publication 74 [I5].
146. The Dmain bedroom is an average gamma radiation dose measured 1 m above the floor in the main
bedrooms of ten houses in the hamlet where the study subjects were living at the time of the dosimetry
survey. The Dother rooms, the indoor dose for the rooms other than the main bedroom, was also the average
dose that was calculated using the same approach as the Dmain bedroom. Doutdoor is the average of gamma
radiation dose measured at 1 m above the ground in public places and farmland in the corresponding
hamlet. The individual cumulative dose was calculated by integrating the annual dose over time [S28, Y2].
147. Using this formula, colon dose was calculated and was used for risk analysis. Assuming that theexternal radiation from HNBR was whole-body exposure, this was represented by the absorbed dose of
the colon (as in the Indian cohort study). This is the same approach as that used by the LSS of solidcancer risk analysis of the Japanese atomic bombing survivors, which also used colon dose to analyse
solid cancer risk [P14]. For leukaemia risk analysis, RBM dose was calculated using this formula. The
CF of 232Th used in the present study was 0.627 for the colon and 0.791 for RBM. The CFs of children
aged 1–14 years and infants aged less than one year were increased by 10% and 30%, respectively. The
cosmic ray component was subtracted from the measured dose in order to estimate the radiation dosefrom terrestrial radiation exposure by using an air kerma value for the cosmic ray component of themeasured dose of 0.259 mGy a−1 for indoors and 0.288 mGy a−1 for outdoors [A4, B13, U4, U7].
148. Morishima et al. measured indoor and outdoor air kerma rates, using a NaI(Tl) scintillation survey
meter (Aloka TCS-166) in 200 houses in the Madi hamlet in the HNBR area, and in 22 houses in thecontrol area (Hampizai hamlet) with a dose rate less than 0.1 μGy h−1 [M6]. They also conducted112 UNSCEAR 2017 REPORT

individual dosimetry, using electronic pocket dosimeters (Aloka PDM-101) and TLDs (National Co.
UD-200S), which were set for 24 hours and two months, respectively. The scintillation survey meters
could not measure cosmic rays which were outside the scope of detectable energy of the device, so themeasured data were corrected accordingly. There was wider variation in dose rates in HNBR areas thanin control areas. In the HNBR region, dose rates tended to be higher indoors than outdoor rates due toradiation from building material. Also, the relationship between environmental and individual dose
rates was less straightforward.

(a) Internal exposure149. A small survey (N=215) using radopots was conducted in 2003 to measure indoor radon
concentrations [O3]. The average indoor radon concentration was 37 Bq m−3 (SD=44; range=3, 284). In
a recent radon and thoron survey, using raduets, of 59 houses in four hamlets in Yangxi and Yangdongcounties (HNBR areas) during about six months, indoor radon and thoron concentrations showed wide
variations from house to house. The mean indoor radon concentration was 124 Bq m−3 (median 115)
and the average indoor thoron concentration was 1,247 Bq m−3 (median 859) [K20]. The radopot andthe raduet used in those surveys were passive monitoring devices with CR-39 solid-state nuclear track
detectors. The internal dose due to ingested and inhaled radionuclides was not considered in the
cumulative dose estimation.
150. Air kerma rate was also measured using a CsI (Tl) scintillation pocket survey meter in the
bedrooms of eight houses in the same hamlets. It is noted that the air kerma rate was not correlated withradon and thoron gas concentrations or thoron progeny concentration obtained from instantaneous
measurements by a semiconductor detector with electrostatic collection and grab sampling of thoron
progenies. The estimated effective doses from internal exposure to radon/thoron and from external
exposure are summarized in table 17. Effective doses from internal exposure from indoor radon andthoron and their progenies were larger than those from external exposure. This is contrary to thesituation in Karunagappally in Kerala, where the internal exposure from indoor radon and thoron is oneorder of magnitude smaller than the external exposure. Internal exposure was not considered in risk
analysis since the indoor radon and thoron survey covered only a small number of houses in the study
area. However, radiation dose from internal exposure can increase lung cancer risk in HNBR areas.
Nevertheless, the lung cancer mortality in HNBR areas was smaller than that in the control area,
probably reflecting differences in smoking habits [T2].
151. Yukawa et al. measured the concentration of 238U and 232Th in the food samples collected in
Yangjiang, using ICP-MS [Y3]. The annual effective doses from radionuclides from 238U and 232Th
series through ingestion were estimated to be 0.3 and 1.9 μSv a−1, respectively, in the HNBR area while
the corresponding values were 0.01 and 0.2 μSv a−1, respectively, in the control area [W6].

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Table 17. Effective annual doses in houses from internal exposure (indoor radon and thoron)compared to external exposure in Yangjiang, China [K20, O2]
The conversion of indoor radon and thoron concentrations to effective doses was based on [U7]Effective annual doses (mSv)

Source of exposure
External exposure

Internal exposure b(inhalation)aMinimum

Maximum

Mean

0.6

1.8

1.2

Radon

0.7

12.0

3.1

Thoron

0.2

10.1

2.2

Total

1.5

16.4

5.3

a

Doses were estimated from eight houses in four hamlets in Yangxi and Yangdong county.

b

Doses were estimated from 59 houses in the four hamlets above. The average radon and thoron concentrations were usedduring the period between July 2013 and January 2014.

(b) Biological dosimetry
152. Cytogenetic studies were performed as a validation of the physical dose assessment. In 1990,
Wang et al. reported the results obtained from their thyroid study in Yangjiang [W5]. This study,
conducted in collaboration between Chinese and United States researchers, examined chromosomes inlymphocytes obtained from residents, and revealed elevated frequencies of chromosomal aberrations in
the HNBR area of Yangjiang. The frequency of stable chromosomal aberrations was 0.29±0.06 (meanand standard error per 100 metaphases) in the HNBR area and 0.18±0.04 in the control area. The
difference was not significant (P=0.14). In contrast, the frequencies of unstable chromosomal
aberrations were 0.16±0.04 and 0.06±0.02 in HNBR and control areas, respectively, indicating asignificant difference (P=0.04).
153. Jiang et al. reported a dose-effect relationship of unstable chromosomal aberrations. Peripheral
lymphocytes were taken from 22 inhabitants of different ages in the HNBR area and 17 inhabitants inthe control area of the study [J7]. Cumulative dose from birth to the time of blood sampling ranged
from 30.9–358.9 mGy and 6.0–59.2 mGy for HNBR and control areas, respectively. The variation of
cumulative doses in controls was caused mainly by age because cumulative dose is a function of age.
About 2,600 cells per subject on average were analysed. The average frequencies of dicentrics andcentric rings were 2.4±0.32 per 1,000 cells for the HNBR-area residents and 1.4±0.23 per 1,000 for thecontrol-area residents. The slope for age, reflecting also increasing cumulative dose, was steeper for the
subjects from the HNBR area and there was also a significant effect of dose, but only when age was ignored.
154. When the frequency of dicentrics and rings per 1,000 cells was plotted against the age of eachindividual, the increase with age in the control group was not significant, but the slope was similar to
the reported Japanese atomic bombing survivor data [T16]. In contrast, the increase with age in the
HNBR-area was significant, and the slope was about three times steeper than that of the control group.
155. Concerning stable chromosomal aberrations, Zhang et al. analysed translocation frequencies insix children and 28 elderly persons in HNBR areas and in eight children and 24 elderly persons incontrol areas [Z5, Z6]. About 4,800 cells per subject were analysed on average. Except for two outliersin the elderly group due to medical radiological exposure by fluoroscopy for one and an unknown
reason for the other, the mean frequencies in children were 3.8±1.1 per 1,000 cells in the HNBR area

114 UNSCEAR 2017 REPORTand 3.2±2.0 in the control area. In elderly persons, the values were 11.3±3.6 in the HNBR area and
10.0±3.8 in the control area. Whether the two outliers were excluded or not, no significant difference
was found between HNBR and control areas.

4.

Cancer mortality

156. The Yangjiang study examined cancer mortality only, and not cancer incidence. However, mostcancers other than that of the thyroid and skin were fatal for local farmers, who could not afford
expensive cancer treatment. In the most recent study, a cohort of 31,604 men and women aged 30–74
years living in the study area in Guangdong Province, China, was followed during the period 1979–
1998 [T3]. The follow-up study accumulated 736,942 person-years at risk, and ascertained 6,005
deaths, including 956 cancer deaths (of which 15 were from leukaemia) and 4,525 non-cancer disease
deaths. The number of cancer deaths did not increase in the latest update because the oldest age group(>75 years) was excluded, unlike in the earlier report [S28]. The mean cumulative radiation doses frombackground radiation in residents were 84.8 mGy in the HNBR and 21.6 mGy in the control areas [T3].
The data for those with attained ages below 30 years were excluded, as in the Indian HNBR study [N4].
157. Statistical analysis was based on the data in cross-tabulation by sex, attained age (five-year
category) and follow-up interval. The entry into the cohort was 1 January 1979. The follow-up ended
on the date of death or the date of attaining the age of 75 if either occurred before the end of follow-up.
Cumulative external radiation dose, lagged by two years for leukaemia and ten years for all othercancers, was estimated for each individual on the basis of hamlet-specific indoor and outdoor air kerma
rates, and sex- and age-specific house occupancy factors.
158. The ERR for all cancers, excluding leukaemia, was estimated to be −0.101 per 100 mGy (95% CI:−0.253, 0.095), consistent with, though lower than the estimate of −0.011 per 100 mGy (95% CI:−0.067, 0.069) reported in an earlier study [S28]. This study did not, however, exclude residents withattained ages below 30, and internal doses of 4.273 mSv a−1 and 1.651 mSv a−1 were added to annual
doses of HNBR- and control-area residents, respectively.
159. Guangdong Province, including the Yangjiang area, is well known for a high frequency of livercancer, which is due to a high prevalence of hepatitis B virus (HBV) infection in this area [L10]. The
prevalence of the HBV antigen, a marker of HBV carrier state, was 17% in the HNBR area (Tongkou)
and 14% in the control area (Enping in Taisha County) [L5]. In site-specific analysis, liver-cancer
mortality was related inversely to the cumulative dose (ERR −0.338 per 100 mGy; 95% CI: −0.516,−0.061). However, accurate diagnosis of liver cancer is difficult as the distinction between liver cancer
and liver cirrhosis, or primary liver cancer and metastasis from another cancer site can be challenging.
Therefore, an analysis was conducted combining liver cancer and other liver diseases. No association
with dose was observed and the ERR estimate was 0.025 per 100 mGy (95% CI: −0.203, 0.350) forliver cancer and other liver diseases combined. The ERR for all cancers, excluding leukaemia and livercancer, was 0.019 per 100 mGy (95% CI: −0.187, 0.304). Non-cancer disease mortality was not related
to cumulative radiation dose. The main characteristics and features of the Yangjiang cohort study aresummarized in table 18.

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Table 18. Summarized characteristics of the Yangjiang cohort study [T3]Characteristic

Description

Study design

Prospective cohort study

Study population

The cohort consists of approximately 90 000 residents of the study area, including control
areas, who were alive as of 1 January 1979

OutcomeCancer mortality

Mortality follow-up

Deaths and migration of cohort members were ascertained by trained local census takers.
The task group on the mortality follow-up survey then visited the study areas andreviewed the information recorded by census takers. In order to ascertain the cause ofdeath, they visited the related hospitals in the study areas, reviewed medical records ofdeceased subjects and extracting relevant information. If necessary, the task grouprevisited the local village doctors and the family members or next of kin to collect further
information on the cause of death

Exposure

Individual doses were estimated on the basis of outdoor and indoor doses and sex- andage-specific house occupancy factors. In every hamlet, indoor measurements wereconducted in about one third of all households. Outdoor doses were measured on main
roads, alleys, open recreational areas, rice paddies, areas adjacent to wells, dry land andthe banks of ponds for each hamlet. Annual average dose from external radiation wasapproximately 2 mGy a−1

Confounding

No baseline survey was conducted to collect information on major risk factors for cancer(such as smoking) and, therefore, the study involved no control for confounders.
Differences between the exposed and control area in some cancer rates suggest
potential confounding

Medical exposure

Information on medical radiation exposure was not collected

Statistical power

The study does not have sufficient power to detect an ERR as large as what is expectedfrom the Japanese LSS

Analysis

The main analysis was to estimate an ERR per unit dose, which was estimated using
Poisson regression methods. Cumulative dose was lagged by 10 years for solid cancer
risk analysis. Subjects used for analysis were those aged 30 years or older at the time of
the baseline survey and attained ages of 30–74 during the follow-up period, which starts
at the time of the baseline survey and ends at the time of migration, death, cancer
development or the end of follow-up (the end of year 1998)

Main results

For incidence of cancers other than leukaemia, ERR: −0.10 per 100 mGy (95% CI: −0.25,
0.10). After exclusion of liver and nasopharyngeal cancers, the risk estimate was positive,
though the confidence interval remained wide and still included negative values

160. The cancer mortality study in Yangjiang did not find increased cancer risk in relation to
background radiation. However, the ERR estimate obtained from this study has a wide confidence
interval because of the relatively small population size, and rather low cumulative doses, which
contribute to low statistical power. These aspects reduce its potential to demonstrate an effect of the
anticipated size, given exposure levels. Further, accuracy and completeness of ascertainment of cancer
deaths are likely to be below those in highly developed areas. A major limitation of the study is the lackof data on confounders at individual level. The slightly higher rates of viral infections in the control
area and differences in mortality from some cancer types suggest confounding, though risk factor
surveys have not shown major differences between the regions. A substantial proportion (45%) of allcancer deaths were due to liver cancer and nasopharyngeal cancer, both associated with virus
infections. Exclusion of these cancers from the overall analyses of all cancers reverses the direction of
the association with background radiation (ERR=0.024; 95% CI: −0.053, 0.149, instead of −0.011 per

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100 mSv; 95% CI: −0.067, 0.069) [S28]. Similarly, in the updated analysis, the ERR for solid cancer
was positive after exclusion of liver cancer (ERR=0.19; 95% CI: −1.87, 3.04) [T3].
161. Advantages of the study include the minimal effect of migration from these areas during theperiod and also the reasonably good estimates of radiation dose, based on extensive outdoor dose
measurements in each village and indoor dosimetry at selected houses (one third of houses in a village)
supplemented by personal monitors, but the levels are too low to be able to discern possible radiation
effects. There was also meaningful exposure to indoor radon and thoron in HNBR areas. Cytogenetic
studies of blood lymphocytes have indicated higher levels of chromosomal aberrations in persons living
in HNBR areas, conﬁrming the difference in population exposure observed in physical dosimetry. The
doses in the China HNBR areas (annual effective dose from external exposure 2.1 mSv a−1 and frominternal exposure 4.3 mSv a−1) [Y1], however, appear too small and the dose distribution too narrow toprovide convincing evidence of the presence or absence of radiation effects. At such low doses, even
80,000 subjects can be considered insufﬁcient to detect an excess risk, given that one existed, i.e. thestudy has low statistical power.
162. In summary, while the strengths of this study include the relatively large population, the careful
environmental dosimetry programme and low migration, there are limitations. The weaknesses include
the uncertainties in dose estimates actually received by individuals, the low and narrow range of
cumulative doses, and the possibility that key demographic and lifestyle factors might differ between
the high background and control populations. Better access to medical care could mean more accurate
and more frequent diagnosis of cancer and less misattribution of causes of death. Inaccuracies inassigning causes of death would be likely to dilute any differences, assuming that the quality of deathcertificates is similar for the exposed and control populations, while a difference in the quality between
the areas could bias the results in either direction.

C. Other studies
1.

Guarapari, Brazil

163. Environmental radiation and residents: Guarapari, the coastal region of Espirito Santo State, isknown for HNBR derived from monazite sands along the Atlantic coast [P7]. The principal
radionuclides in monazite are from the 232Th series, but some uranium is also present. High levels of
external radiation on beach sand and in some major streets of Guarapari were reported in the past [C6].
However, recent assessments found that radiation levels in Guarapari were near the average global
level, except at hot spots on the beaches and in the fishing village of Meaipe [S1]. The decrease ofradiation levels is due to urbanization, including the paving of streets and the construction of tallbuildings in this area over the years, in addition to the removal of monazite-containing black sand fromthe beaches. Analysis of chromosomal aberrations was conducted using 13,242 lymphocytes from202 persons in Guarapari and 9,001 lymphocytes from 147 persons in control areas. However, theculture period of lymphocytes in this study was too long (72 hours) for analysing aberrations specific toradiation [B6].
164. Other major HNBR areas in Brazil are Poços de Caldas and Araxá in the State of Minas Gerais.
The HNBR area in Poços de Caldas is characterized by a huge alkaline intrusion of uranium andthorium anomalies [B2, P7]. Araxá in State of Minas Gerais is known for its spa area, where several

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minerals rich in uranium and thorium are found [C1]. Six thousand people reside in the rural HNBR
area in Poços de Caldas (population 120,000). The population size of Araxá is approximately 80,000.
165. The average annual effective dose in the rural residents in Poços de Caldas was estimated to be
13 mSv a−1, with the range of 6–16 mSv a−1 [A14]. In the dose assessments conducted by Veiga et al. in
the 2000s, the indoor air kerma rate was 0.2 mSv a−1 (geometric SD=1.3) in the rural area. The averageindoor radon concentration in 41 houses was 220 (geometric SD=2.9) of Bq m−3 [V2]. A survey ofpatients in the Araxá spa estimated the mean annual effective dose due to natural sources. It wasreported to be 2.4 mSv a−1.
166. An ecological (geographical correlation) study was conducted of Guarapari and Araxá thatshowed no excess of cancer mortality compared with national rates [V3]. In contrast, increased
mortality from cancer overall, from stomach, lung and breast cancer, and leukaemia was reported forPoço de Caldas. No cancer risk estimates per unit dose could be provided. Interpretation of thisecological study is limited by the lack of individual doses, the problem of migration not being
addressed, and the inability to control for potential confounding factors. The SMR analysis does notallow inference on radiation-related cancer risk.

2.

Ramsar, Islamic Republic of Iran167. Ramsar is located 160 km northwest of Tehran on the coast of the Caspian Sea. It contains some
HNBR areas of a few square kilometres, caused by 226Ra deposited from water flowing from hot
springs. In addition, travertine with elevated levels of thorium was used as a building material inside thewalls of some houses. Exceptionally high environmental dose rates are found in buildings with building
material rich in travertine and in areas in close proximity to the hot springs [S21].
168. Dosimetry studies indicated that environmental measurements of ambient dose rate levels of
gamma radiation, coupled with house occupancy factors gained by interview, would be inadequate toprovide accurate estimates of dose for individuals unless they were supplemented with personal
dosimetry measurements. The variation of doses in the homes and in the areas near the hot springs
seemed too great for accurate estimation of individual doses. However, the size of the exposed
population, only about a few thousand in the highest dose rate areas, is manageable and estimates ofindividual cumulative doses could be made using focused studies, such as screening for thyroid andpossible cataract disorders.
169. A study examined chromosomal aberrations, using lymphocytes collected from 50 long-term
inhabitants of Ramsar (with annual effective doses between 1.6 and 42 mSv) [G1]. The frequencies ofboth unstable and stable chromosomal aberrations in lymphocytes were compared with those in 30 agematched inhabitants of a nearby control area where the mean annual effective dose was 2.3±0.1 mSv.
Significantly increased frequencies of both aberration types were observed in the lymphocytes ofRamsar inhabitants as compared with the control area (mean frequencies for stable aberrations
6.0%±2.1 vs 1.5%±0.95 and unstable 4.6%±2.0 vs 1.6%±1.2). In order to further investigate thebiological effects of exposure to low-dose radiation and to assess the dose-effect relationship in HNBRarea residents in Ramsar, unstable aberrations were examined, using lymphocytes collected from15 healthy elderly women in Talesh mahalle, an HNBR area of Ramsar, and in 10 elderly women living
in a nearby control area with normal background radiation [Z1]. In total, 77,714 cells were analysedwith 48,819 cells from HNBR-area residents and 28,895 cells from control subjects. On average, 3,108
cells per subject were analysed (range 1,475–5,007 cells). Significant differences were found in thefrequency per 100 cells of dicentric plus centric rings (0.207±0.103 vs 0.047±0.027; P<0.0005), total

118 UNSCEAR 2017 REPORT

chromosome-type aberrations (0.86±0.44 vs 0.23±0.17; P<0.0005), and chromatid-type aberrations(3.31±2.01 vs 1.66±0.63; P=0.01) between HNBR- and control-area residents. No positive correlation
was found between the frequency of dicentric plus centric ring aberrations and the cumulative dose of
the inhabitants estimated by direct individual dosimetry.
170. An analysis of population-level cancer mortality rates showed no increase in about 3,000 people
in the highest dose areas [M7]. Similar to studies in Brazil, this analysis cannot provide a quantitative
estimate of radiation-related cancer risk, as such ecological studies cannot take possible confounding
factors into account, including smoking, alcohol, dietary habits and exposure to various chemicals. The
statistical power is also low due to the small sample size. Similar ecological studies have also been
carried out in areas with lower background radiation level, but they are not covered here as they do not
fulfil the inclusion criteria [A13, F1, K7].

IV. STUDIES ON BACKGROUND RADIATION AND CHILDHOOD
LEUKAEMIA

A. Studies on natural background radiation
171. The association between environmental exposure to natural background radiation and leukaemia
risk in children and young adults has not been addressed in HNBR studies in the past, mainly due to thesmall number of cases. However, recently, several studies have evaluated this association. In thischapter, the large-scale studies are reviewed.

1.

Studies in the United Kingdom

172. The United Kingdom Childhood Cancer Study (UKCCS) was a prospective, interview-based
case-control study conducted to examine associations between childhood cancer risk and natural
gamma-radiation exposure and other potential aetiological factors [U1]. Eligible children were thoseborn in Great Britain (England, Scotland and Wales) who were not in local authority care. Subjects
were ineligible if they themselves or their parents had lived outside Great Britain for the three months
leading up to diagnosis. In England and Wales, the UKCCS population was defined as children (0–14 years)
registered with one of the 98 family health services authorities (FHSAs). Note that, under the National
Health Service, all general practitioners (GPs) and their patients are registered with their local FHSA.
This comprises around 98% of the total population. In Scotland, where the system is similar but
independent, the study population was defined as children registered with one of the 15 Health Boards(HBs) and has been described separately.
173. Case accrual was conducted during 1991–1994 in Scotland and 1992–1996 in England and Wales.
The majority of cases were notified by paediatric oncologists belonging to the study group in regional
treatment centres. Crosschecks were made against regional cancer registries and against the National
Registry of Childhood Tumours. For leukaemia, the principal diagnostic sources were the Medical
Research Council’s treatment trials. Individual haematologists in participating centres diagnosed acutelymphocytic leukaemia (ALL) and acute myeloid leukaemia (AML) based on morphological, standard

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staining and immunophenotyping. Central review was performed by a panel of three haematologists aspart of the Medical Research Council’s trial protocol. This panel ascribed individual patients to an
appropriate French–American–British morphological classification type. To obtain reliable information
about the diagnosis of cancers other than leukaemia, a histopathology review database was speciallycreated for the purposes of the study.
174. Two age and sex matched controls were randomly selected from the same (former) FHSA/HB as
the case child [U1]. The parents of 3,838 children with cancer (1,736 with leukaemia) and 7,629
children without cancer were interviewed, representing 87% of eligible cases and 64% of eligible
controls. The UKCCS investigators found that there was a social class bias in those cases and controls
who agreed to participate with more participants in higher socioeconomic groups [U1].
175. At interview, a full residential history for the child was collected with all dwellings inhabited forsix months or more targeted for measurement. Indoor gamma-ray levels were measured for six months,
using two TLDs, one placed in the main bedroom and one in the main living area. Investigators tried toobtain a complete set of measurements but this proved difficult and, in the final analysis, only theaddress at diagnosis was used. Measurements were obtained from the home at diagnosis of 2,165 cases(56% of the families interviewed) and 5,086 controls (67% of the families interviewed). Nearly all(97%) estimates were based on readings obtained from both the bedroom and the living room.
176. For the risk analysis, odds ratios (OR) were calculated, using conditional logistic regression
modelling. The data were checked for confounding by SES and adjusted using a deprivation score. No
evidence was found to support an association between higher background gamma radiation levels andrisk of childhood ALL (OR=0.95; 95% CI: 0.66, 1.37 for the highest exposure category with
>1 mGy a−1) or other leukaemias (OR=0.68; 95% CI: 0.26, 1.82 for the highest exposure category), andno significant trends emerged across exposure categories. The investigators concluded that “it isunlikely that a relative risk of this magnitude predicted by modelling would be detectable in the present
study after its statistical power, modest variations in dose rate and limitations of data collection aretaken into account”.
177. The low participation rate of controls (64%) is a concern as are the low proportions of residencies
measured (49% of the originally eligible case and 43% of the originally eligible controls). Participation
rates were affected by the deprivation score, a SES indicator, which was related to environmental dose.
Medical exposure was not considered, nor birth weight or parental age as potential confounders.
Exposure from radiation treatment is unlikely since children with prior malignancies were not eligible.
Although this study found no association with measured values of gamma-ray exposure in homes, itdoes not have sufficient power to detect an ERR as large as what is expected from the LSS and thepotential for serious participation bias must be considered.
178. A historical, record-based case-control study of childhood cancer examined associations withnatural background radiation in Great Britain [K3]. The principal end point of interest in this study wasleukaemia, but all types of cancer were included in the cases. This study examined a large number ofcases (27,447, including 9,058 with leukaemia), comprising children born and living in Great Britain
who were diagnosed before their 15th birthday, during the period 1980–2006. Lymphoid leukaemia
accounted for more than 80% of all leukaemia cases. Those cases in children aged less than 15 years
were ascertained through the National Registry of Childhood Tumours, which is an essentiallycomplete population-based registry of cancer diagnosed in Great Britain from 1962 onwards. A control
was selected for each case from the same birth register, matching on sex and date of birth (within six
months). For cases diagnosed in 2000 and later years, a second control was selected in a similar way.
Controls, which numbered 11,912 for leukaemia, were cancer-free at the time of diagnosis of theirmatched cases. There were no differences in SES between cases and controls.

120 UNSCEAR 2017 REPORT179. Cumulative doses from gamma-ray exposure were calculated, using mean gamma-ray dose rates
for county districts where the mothers of cases or controls lived at the time of the child’s birth(generally defined to a few metres). Mean dose rates in county districts were obtained from the
National Survey of natural background radiation based on 2,283 measurements of gamma radiation inhouses [W10]. There are 459 county districts (or equivalent) in Great Britain with a mean surface areaof 500 km2 and the child population ranging from 300 to 213,000 (mean 24,000). About half the casesin the study had moved between birth and diagnosis. In an additional analysis, the effects of mobility on
the association between leukaemia risk estimate and natural radiation dose were assessed as likely to besmall [K4, K5]. Indoor radon levels were also estimated, using predictive maps based on domestic
measurements grouped by geological boundaries, and cumulative radon exposure and RBM doses were
calculated. The median gamma dose was 3 mGy among both cases and controls (interquartile range
from 1 mGy to 5–6 mGy). ERRs per unit dose were estimated from ORs calculated using logistic
models. SES was taken into account either through area-based deprivation measures or paternal
occupation from the birth certificate. ERRs for all leukaemia and all cancers excluding leukaemia were
9 per 100 mGy (95% CI: 2, 17) and 2 per 100 mGy (95% CI: −2, 6), respectively. For bone marrowdose from gamma rays, the ERRs for all leukaemia, lymphoid leukaemia and acute myeloid leukaemia
were 12 per 100 mGy (95% CI: 3, 22) and 13 per 100 mGy (95% CI: 2, 24) and 5 per 100 mGy (95%
CI: −13, 28), respectively.
180. The information for this study was obtained by record linkage, so no interviews were used. The
drawback was that neither individual residential histories nor direct radiation measurements of thehomes of study subjects could be obtained. The leukaemia cases were identified through the National
Registry of Childhood Tumours. The accuracy of leukaemia diagnosis can be considered high.
Exposure estimates were based on mean dose rates in county districts, which are relatively large
geographical units, of the residence at time of the birth. Interview of study subjects was not sought. The
strength of this study is the large number of cases and controls, accurate and virtually complete caseascertainment, and also lack of participation bias. Of concern are uncertainties regarding dose
estimates, which were area-based average dose rates at birth place obtained for large area units from a
relatively small number of measurements, and lack of full residential history. This ignores house-tohouse variability within a geographical unit, reducing the precision of exposure assessment, presumably
in direct relation to the size of the unit used in the analysis. A previous report [L6] indicated that the
sample of this study should provide reasonable power to detect the risk from natural backgroundgamma radiation predicted by standard risk models. Hence, the study appears to have sufficient power
to detect an ERR as large as that expected from the Japanese LSS. Although information on medical
exposure is lacking, during the study period (1980–2006) medical exposure is unlikely to have been
large enough to materially affect the results of risk analysis unless strongly correlated with natural
background radiation. Departure from linearity was not formally examined.

2.

The Swiss study

181. In a nationwide, record-based study of a cohort of children identified by the Swiss National
Census in 1990 and in 2000, the relationship between the incidence of childhood cancer andbackground radiation exposure was examined [S25]. Study subjects were residents aged younger than
16 in Switzerland. Follow-up began at the first census in which a child was recorded (entry time) andended on the earliest of following events: diagnosis, death, emigration, the child’s 16th birthday andadministrative censoring on the 31st December 2008. Cases diagnosed during the period 1990–2008
were ascertained by the record linkage through the Swiss Childhood Cancer Registry. From 2,093,660
children included at the census, 530 incident cases of leukaemia were identified.

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182. In Switzerland, the central alpine massif has relatively high natural background radiation levels
due to the relatively high radioactivity of crystalline rocks when compared to the sedimentary northern
alpine foreland (Jura, Molasse Basin) [R8, R9]. Exposure was based on residential location at census.
External background radiation levels in children’s homes were estimated from a database of outdoor
gamma radiation measurements, using a model which predicted dose rates for each cell of a
2 km × 2 km grid as the sum of cosmic radiation, natural terrestrial gamma radiation, and radiationfrom human-made sources [R8, R9]. For a child who was found to have lived at different locations in
the 1990 and 2000 censuses, the 1990 exposure was updated in 1995 or 2000 depending on whether or
not the child lived at the new location five years before the census in 2000 taking the information fromcensus questionnaires. On average, the effective cumulative dose was approximately 9 mSv. Natural
terrestrial radiation contributed most with 54 nSv h−1, cosmic radiation 45 nSv h−1 and anthropogenic
terrestrial radiation with only 8 nSv h−1.
183. Several factors were considered as potential confounders, including traffic-related air pollution(distance to nearest highway as a proxy), electromagnetic fields from radio and TV transmitters, andfrom high voltage power lines (distance to nearest 380 kV or 220 kV power line), degree ofurbanization of municipality (urban, suburban, rural), SES based on the Swiss neighbourhood index ofsocioeconomic position (Swiss-SEP), education of the household reference person (compulsory,secondary, tertiary, from the national census) and crowding (the number of persons per room), birthweight and birth order of the child. Information on education and crowding was obtained from national
census data. Birth weight and birth order of the child, which were obtained from the birth registry, wereavailable for approximately 60% the study subjects. The Swiss-SEP is an area-based measure ofsocioeconomic position [P1]. This index is defined for neighbourhoods of 50 households withoverlapping boundaries using Census 2000 and road network data, and is based on median rent per
square metre, proportion of households headed by a person with primary education or less, proportion
headed by a person in manual or unskilled occupation and the mean number of persons per room wereanalysed in principle component analysis.
184. Cox regression models were used to assess associations of cancer risk with dose rates andcumulative dose since birth. The hazard ratio for the cumulative dose of external radiation was 1.04
per mSv (95% CI: 1.00, 1.08) for leukaemia, corresponding approximately to an ERR per 100 mSv of
4 (95% CI: 0, 8). In this study, the excess leukaemia risk was virtually restricted to children exposed to>200 nGy h−1. Adjustment for a range of potential confounders had little effect on the results.
185. Interview of study subjects was not sought. Information necessary for follow-up and exposure
assessment, and on SES was obtained by record linkage. Area-based measures of exposure were usedinstead of individual estimates and they were estimated for the dwelling of the child at the census.
Migration was at least partially taken into account and an analysis restricted to children with stable
residence gave higher hazard ratios. Internal exposure was not considered in this analysis (thoughevaluated in a parallel publication). Besides leukaemia, a similar positive relationship was also foundfor several other tumour types and it was close to significance for CNS tumours and other CNS andlympho-haematological malignant tumours, unlike in the UKCCS [K3]. The increased risks werelargely due to a high risk in the highest exposure category, with little indication of excess in theintermediate exposure groups. The strengths of this study include virtually complete caseascertainment, lack of participation bias and the availability of information on several potential
confounders. However, the number of leukaemia cases was relatively small, given the anticipated effectsize (and smaller than in some other studies). Of concern are uncertainties regarding area-based dose
estimates related to a single welling. Information on medical radiation exposure was not collected. The
statistical power was not sufficient for detecting an effect of similar size to the LSS.

122 UNSCEAR 2017 REPORT3.

The Finnish study

186. A nationwide register-based case-control study was conducted to examine childhood leukaemia
risk associated with background radiation [N10]. Subjects were children aged 2–15 years in Finland(the entire nation). Cases (N=1,093) were identified through the Finnish Cancer Registry (known for its
high quality). Three controls were selected for each case matching on sex and year of birth from thedatabase at the Population Register Centre (N=3,279).
187. Complete residential histories and previously collected survey data of the background gamma
radiation in Finland were used to assess the exposure of the study subjects to indoor and outdoor
gamma radiation. Outdoor dose was from the data encoded in a map of 8 km × 8 km grids based on anationwide mobile survey carried out in 1978–1980 obtained from Radiation and Nuclear Safety
Authority [A16]. The nationwide average dose rate outdoors was 51 nSv h−1. For the residencies abroad(N=63, 0.8% of all residencies), the world’s average natural background radiation value reported by
UNSCEAR (55.3 nSv h−1 effective dose rate) was used [U10]. The indoor doses of gamma radiation
were based on measurements in 346 randomly chosen dwellings. The national average dose rate inhouses was 41 nSv h−1 and in flats/apartments 70 nSv h−1 [A16]. The difference is due mainly to theconcrete used as the building material in blocks of flats. The indoor rates were correlated with local
outdoor gamma-radiation levels. These correlations were used for converting local outdoor dose rates toindoor dose rates. The percentage of time spent indoors (indoor occupancy) was modelled according toa Finnish study providing age group specific estimates [M1].
188. The mean annual effective dose from medical radiation in Finland is 0.45 mSv in 2012, but forchildren it is markedly lower due to strict imaging guidelines especially with CT scans, whichconstitute the largest contribution to the annual dose from medical exposure [M8, U10]. Furthermore,
CT use in Finland is less frequent than in many other industrialized countries and only 1.7% of CT
scans in Finland were performed on children [H3]. Since average population doses from medical
procedures are relatively small compared to annual doses from background radiation (0.59 mSv toRBM) in this study and no correlation with background radiation was anticipated, medical radiation
exposure was judged unlikely to cause confounding.
189. Data on diagnosis of Down’s syndrome were obtained from the Register of Congenital
Malformations by the National Institute of Health and Welfare. Data on gestational weeks and birthweights were obtained from the Medical Birth Register for all but 184 (18.6%) cases and 511 (15.6%)
controls. Maternal smoking data were obtained from the Medical Birth Register and data were missing
for 200 cases (18.3%) and 563 controls (17.2%).
190. Conditional logistic regression analyses were adjusted for Down’s syndrome, birth weight (large
for gestational age) and maternal smoking. Investigators stated that this study has sufficient power(≥80%) to detect a linear dose response with OR of 1.06 or greater per 10 nSv h−1 increase in dose rate.
This study reported ORs per unit dose rate and ORs per unit cumulative dose. Investigators did not
clearly state which leukaemia subtype was the main target of the risk estimate. Regarding dose rate, theoverall OR for leukaemia was 1.01 (95% CI: 0.97, 1.05) for each 10 nSv h−1 increase in the equivalentdose rate to RBM. Regarding cumulative dose, the OR was 0.97 (95% CI: 0.89, 1.06) for a 1 mSv
increase in cumulative equivalent dose to RBM. In subtype-specific analysis, only the relationshipbetween ALL and dose rate gave an OR larger than 1, which was 1.02 (95% CI: 0.98, 1.07).
Cumulative dose was not positively associated with any of the leukaemia subtypes. In age-specificanalysis, ORs per 10 nSv h−1 were 1.05 (95% CI: 1.00, 1.10) for ages 2–6 years and 0.93 (95% CI: 0.86,1.00) for ages 7–15. For cumulative dose, the ORs were 1.27 (95% CI: 1.01, 1.60) and 0.93 (95% CI:
0.85, 1.02) per 1 mSv, respectively. The OR for the younger age group approximately corresponds to
ERR per 100 mSv of 27 (95% CI: 1, 60). The increased risk is significant for ages 2–6 years, however,ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

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it may still be a chance finding, given the wide confidence interval. The statistical power presented in
the study was low for the effect sizes predicted from LSS.
191. In this study, cases were ascertained through the Finnish Cancer registry, which covers the entire
nation, and is known to be of high quality [D1, T8]. Investigators estimated lifetime cumulative doses
and average dose rates to RBM from background gamma radiation using information on indoor andoutdoor survey data and housing types during the lifespan of the children. One of the advantages of thisstudy in dose estimation is the fact that the residential history of every study subject was collected. A
disadvantage was the lack of residential dose rate measurements. Information on medical exposure isalso lacking but, as the investigators concluded, medical exposure is unlikely to distort the risk estimate
substantially in a country where CT use has been strictly controlled. Information on SES was not
obtained (and therefore not adjusted for) in this study.

4.

The French study

192. A study combining small-area-based incidence analysis and a case-control study investigated theassociation between acute leukaemia and location-based estimated exposure to natural backgroundradiation in France [D18]. The incidence study identified 9,056 acute leukaemia cases during the period
1990–2009 through the French National Registry of Childhood Cancer. Complementary analyses usedthe data obtained from the so-called “GEOlocalisation des CAncers Pédiatriques (GEOCAP) study,
which examined 2,763 acute leukaemia cases diagnosed during the subperiod 2002–2007, and 30,000
control children with geocoded addresses randomly sampled by the French National Institute for
Statistics and Economic Studies, using the income and council tax databases for households.
193. Since residential history was not available in this study, cumulative exposure to radon or gamma
radiation were calculated on the basis of residence at diagnosis or inclusion and the assumption that thesame exposure had prevailed since birth. According to an interview-based study [R7], 66% of the children
had been living in the same municipality since birth. The correlations between exposure estimates at birthand at diagnosis/inclusion were 0.86 for radon exposure and 0.89 for gamma-radiation exposure.
194. Dose from environmental radiation exposure was estimated on the basis of the 36,326
municipalities in France and geocoded addresses of the residences, which were available at the time ofdiagnosis (cases, 1990–2009) or inclusion (controls, 2002–2007). Natural background exposure wasdetermined at the town centre for radon, and as the mean exposure over the municipality territory for
gamma radiation, in the incidence study, and at the residence address and the town centre, respectively,in the case-control study. The radon domestic exposure was estimated from two datasets: (a) 10,843
measurement results of indoor radon concentration performed by the Institute for RadiologicalProtection and Nuclear Safety and Health Ministry during a national campaign (1982–2003), and(b) the French map of the geogenic radon potential. A mathematical model using both datasets wasdeveloped, enabling estimates of the indoor radon concentration measured in a 1 km × 1 km grid.
Exposure to natural background gamma radiation was calculated as the sum of exposures to cosmic
gamma radiation and terrestrial gamma radiation. The determination was based on 97,595 measurement
results of indoor gamma dose rate conducted by the Institute for Radiological Protection and Nuclear
Safety in 17,404 dental surgeries and veterinary clinics throughout France, using radio photoluminescent dosimeters, exposed for several months in 2011–2012. To estimate the indoor telluric
gamma dose rate, multicollocated co-kriging was conducted on 1 km × 1 km grid in a geostatisticalmodel that used two datasets: the indoor terrestrial gamma radiation dose-rate measurement results andthe French map of geogenic uranium potential. For the 30,000 GEOCAP controls, the arithmetic meanradon exposure estimated at the place of residence was 67.8 Bq m−3 (SD=45.5), the 5th percentile was124 UNSCEAR 2017 REPORT

24.9 Bq m−3 and the 95th percentile was 145.3 Bq m−3. The arithmetic mean gamma radiation exposure
was 98.2 nSv h−1 (SD=24.9), the 5th percentile was 70.1 nSv h−1 and the 95th percentile was
148.5 nSv h−1.
195. The potential for confounding by SES was taken into account by stratification on the quintiles ofthe first component in a principal component analysis of four census variables: median income andpercentages of baccalaureate holders, labourers and unemployed. This was based on the 1999 census
and was strongly correlated with the indicators based on the 1990 and 2006 censuses. In addition, the
GEOCAP case-control study was used to evaluate potential confounding by environmental factors
available at the address of residence by exclusion (vicinity of nuclear power plants or proximity tohigh-voltage power lines) or by adjustment (proximity of high-traffic roads). There was no confounding
effect of census-based socio-demographic indicators, or environmental factors (road traffic, highvoltage power lines, vicinity of nuclear plants) related to acute leukaemia in the GEOCAP study.
196. The power to detect an association between acute leukaemia and dose to RBM in the incidence
analysis based on the UNSCEAR 2006 Report [U8] exponential multiplicative model assuming
ERR 20 per Gy was 92% for exposure to natural gamma radiation (using simulation with the observed
exposure distribution). A standardized incidence ratio (SIR) was calculated as a ratio between theobserved and expected numbers of cases by exposure category; the expected number of cases wascalculated on the basis of the age-specific incidence rate and number of person-years in that stratum.
The power calculation did not consider any attenuation due to exposure misclassification from use ofaggregate data instead of individual measurements.
197. Acute leukaemia, irrespective of subtype and age group, was not significantly associated with themunicipality-specific gamma radiation exposure level in terms of annual dose at age reached and thecumulative exposure to RBM dose. In the incidence analysis, acute leukaemia risk showed a small
increase with gamma dose rate (SIR=1.01 per nSv h−1; 95% CI: 1.00, 1.02), but no association withcumulative gamma dose (SIR=1.00 per mSv; 95% CI: 0.99, 1.01). The results were not changed byincorporating a time lag of 24 months in the analysis. In the case-control analysis, no association withbackground gamma radiation dose rate was found (OR=1.00 per 10 nSv h−1; 95% CI: 0.98, 1.01).
198. This is a large record-based study using a reliable source of childhood acute leukaemia cases, andthe power to detect the predicted effect is high. The number of indoor dose-rate measurements is also
large although the exposure range appears quite narrow for evaluating the association between
childhood leukaemia risk and background radiation as the third quartile of the cumulative dose wasonly 50% higher than the first quartile. Municipality-level estimates of radiation exposure and lack offull residential history (a third of the subjects had moved at least once) were other potential weaknesses.

B. Studies of environmental exposure from human-made sources
1.

The case-control study in Belarus, the Russian Federation and Ukraine

199. A population-based case–control study of acute leukaemia was conducted in the areas of theformer Soviet Union that were contaminated by radioactivity from the Chernobyl accident [I8]. Eligible
subjects (cases and controls) were children who were in utero or <6 years of age at the time of theChernobyl accident and were in contaminated regions of Belarus, the Russian Federation and Ukraine,
which were the Gomel’skaya and Mogilevskaya Oblasts in Belarus, the Bryanskaya Oblast in the

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125

Russian Federation (the most contaminated oblast), and the Rovenskaya, Zhytomirskaya,
Chernigovskaya, and Cherkasskaya Oblasts in Ukraine (Chernigovskaya and Cherkasskaya Oblasts
were on average significantly less contaminated than the Rovenskaya and Zhytomirskaya Oblasts).
200. Eligible for the study were acute leukaemia cases diagnosed in these geographic regions during
26 April 1986 and 31 December 2000. They were identified from records of the Pediatric Oncology
Centre in Belarus, the national Belarus Tumour Registry and the Bryansk Oncology Registry in the
Russian Federation. In Ukraine, case ascertainment was based on the archival records of regional
cancer hospitals. A group of haematological morphologists and haematologists from Belarus, Israel, theRussian Federation, Ukraine and the United States verified the diagnosis of leukaemia on the basis ofhaematology slide review. In 67 cases, diagnosis was made on the basis of other information, such as
the results of laboratory tests, medical records from the diagnosing institution, and patient therapy data.
Of 463 identified potential acute leukaemia cases, a diagnosis was made in 95% (442 cases).
201. A total of 20 potential controls were selected from the clinical records for each case andinterviews were scheduled for the first two. If the first or second potential controls could not bereached, the next individuals on the list were contacted. Controls were matched to each case on sex,
birth year and residence. Eligible controls were those who were alive at the reference date, which was
the date of diagnosis of the corresponding case. The protocol of matching on residence differed
between republics. Investigators described it as follows: “In Russia, controls were matched to cases onraion of residence of the case at the time of accident. In Ukraine, controls were initially matched onraion of residence of the case at the time of accident (118 or 22% of the controls), and subsequently
were to be randomly selected from a raion different from that of the case, but within the same oblast. In
Belarus, controls were matched to cases on raion of residence on the reference date and randomly
selected from any raion of residence at the time of accident with the selection weighted by raion
population”.
202. Trained physicians and dosimetry specialists interviewed the cases and controls to collectinformation on demography, general health interview, leukaemia risk factors, maternal and paternal
occupational history and radiation exposure, using questionnaires. For deceased cases, the interview
was administered to substitutes, preferably the subject’s mother or another close relative. The dosimetry
questionnaire included questions on the sources, types and consumption of milk; sources andconsumption of food; residence and occupation; relocation and migration; personal protective measures
after the accident; type of housing; and time spent indoors and outdoors after the accident.
203. Cumulated radiation dose absorbed by the bone marrow was estimated for cases and controls
from the time of the accident until the reference date, taking account of dose changes over time.
External dose for a particular residence was calculated on the basis of field measurements. Internal dose
estimates relied on food, water and milk consumption. For study subjects who were possibly exposed inutero (61 cases), the mother’s residence and dietary history were also obtained in order to estimate thedose received in utero. The uncertainties of individual doses were estimated by Monte-Carlo simulationof the variability of each of the input parameters used for dose calculations. Median estimated radiationdose of participants was 10 mGy.
204. In statistical analysis, logistic analysis adjusted for matching was conducted. A log-linear model
used by investigators gave an ERR of 32 per Gy (95% CI: 8.8, 84). An increase in leukaemia risk withincreasing radiation dose to the bone marrow was found only in Ukraine (ERR=79 per Gy; 95% CI: 22,
213). Investigators admitted that “the large and statistically significant dose response might beaccounted for, at least in part, by an overestimate of risk in Ukraine”.

126 UNSCEAR 2017 REPORT

205. The risk estimate reported is very large and mainly driven by the Ukrainian data (particularly
Cherkasskaya Oblast), with a different matching from the other countries. Whether the control series
represents the catchment population of the case series or not is unclear. Medical exposure was notconsidered. The general conclusions of the Committee thus remain that there is little convincing
evidence to suggest a measurable increase in the risk of leukaemia among those exposed as children to
the radiation resulting from the accident at Chernobyl [U11]. This conclusion is consistent with theearlier cancer registry studies of childhood cancer risk in Europe following the Chernobyl accident[A18, H6, P3, P5].

V. BIOLOGICAL DOSIMETRY
206. In the TRC study, two methods were used for the validation of estimates of external absorbed
dose: EPR on human teeth and stable-type chromosomal aberrations in human lymphocytes [D11, V9].
The results of these studies were generally correlated with the estimates of the external absorbed dose
calculated for the residents of Metlino. As this is the closest settlement to the discharge point, theresidents there received the highest levels of external exposure. In the Yangjiang and Karunagappally
studies, the analysis of chromosomal aberrations was also performed in order to validate the physicalestimates of absorbed dose. In both areas, increased frequency of unstable chromosomal aberrations(dicentrics and rings) has been demonstrated, but no excess of stable aberrations (translocations) has
been shown compared with inhabitants from areas with lower levels of background radiation.
207. While analysis of chromosomal aberrations has contributed to the estimation of absorbed dose,
uncertainties and limitations are, nevertheless, involved in their application to the estimation of dosefrom prolonged low-level radiation exposure [V5], especially from internal emitters [A3]. One of thereasons for the uncertainty is the low number of aberrations induced by chronic low-level radiation
exposure and the low cumulative dose. Though unstable chromosomal aberrations are recognized as asensitive and specific marker for exposure to ionizing radiation, a large number of cells must be scoredto minimize the uncertainty when the dose is low. The frequencies of spontaneous translocation werereported to be of the order of one per hundred cells [S17], higher than those of dicentrics and rings, ofthe order of one per thousand cells [I9]. This is because translocations can be induced by manyclastogens in contrast to dicentrics and rings, where induction is relatively specific for radiation
exposure. Therefore, this makes it difficult to distinguish translocations induced by radiation from thoseinduced by other clastogens. An increased frequency of dicentrics and centric rings has been reported invitro at an acute dose of about 20 mGy, but for human biological dosimetry, in practice a detection limit
of approximately 0.1 Gy is realistic [I9, L8, S31].
208. The complexity of the elimination rate of aberrant lymphocytes in vivo is another reason for theuncertainty. The elimination of lymphocytes with unstable chromosomal aberrations might be affectedby other factors, such as age and elapsed time between exposure (or end of chronic exposure) and blood
sampling [S2]. The information available from biological dosimetry studies in the assessment of healtheffects from low doses of radiation is currently limited because of the low detection limits, theresources required for large studies and incomplete participation. They are, nonetheless, useful markers
of exposure and provide some assurance that the estimates of dose are generally consistent.
Furthermore, several of the studies are difficult to interpret because of the lack of understanding of theinfluence of internal radiation on chromosomal aberrations.

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127

209. For stable chromosomal aberrations, which are considered to persist for longer than the unstable
type, a significant dose–response relationship has been observed in studies of radiology technologists[B12] and radiation workers [T7]. Because translocations can be introduced by many clastogens otherthan ionizing radiation, they increase with age [S17], and individual variation is large. This makes it
difficult to demonstrate the difference between radiation-induced translocations and those caused byother factors, such as smoking or chemicals. In spite of these uncertainties and limitations, cytogenetic
methods could be successful in validating relatively high cumulative doses.
210. The detection threshold for FISH-based analysis of translocations depends on the type of
exposure (uniform whole-body vs partial body, radiation quality), number of cells scored, age, andco-exposure such as smoking. Estimates of detection limit have ranged 200–500 mGy and lower doses
are detectable for exposed groups (population average) than at individual level. Chromosomal
aberrations have been shown to predict subsequent cancer risk, which seems to reflect partly innate
DNA repair capacity and partly the influence of external exposure [B14, B16]. Further studies tovalidate their capacity for predicting cancer risk from low-dose radiation exposure would be important.
211. Unstable and stable aberrations are produced in equal proportions and the latter could lead tocancer [H1]. However, despite an excess of unstable aberrations in the residents of HNBR areas in
Yangjiang and Karunagappally, no increase was observed in cancer mortality (Yangjiang, China) orcancer incidence (Karunagappally, India). Studies of newborns do not appear informative, despite theadvantage of being free from influence of other exposure. It seems that the potential higher sensitivityof infants is offset by the low in utero exposure levels in HNBR.

VI. COMPARATIVE EVALUATIONS OF SELECTED STUDIES
212. In this chapter, studies on solid cancer and childhood leukaemia will be compared and evaluatedfurther. In addition, the TRC study, unlike other studies reviewed here, has provided reasonably precise
and valid risk estimates for adult leukaemia. The main focus here will be to reach a synthesis ofavailable evidence, with assessment of the methodological features of the studies, applying the quality
criteria of annex A. The main outcomes of different studies were analysed by all cancer types (except
all leukaemia combined) and by childhood leukaemia separately. Combining a variety of cancer types
into a single category can result in poor comparability of the findings, which is discussed below.
Further, specific cancer types pose less of a problem in this respect, but statistical power is substantiallylower. Several studies assigned environmental exposure estimates based on area of residence linked
with dose-rate measurements instead of strictly individual measurements. Even in the LSS, individual
radiation dose was not measured but estimated retrospectively on the basis of location and shielding.
Aggregate level studies without individual data (ecological studies or geographical correlation studies)
are not addressed here, as they were judged as not informative enough for risk assessment.
213. Statistical power is an important point for consideration. Most epidemiological studies on
low-dose-rate exposure (<0.1 mGy min−1) have relatively low cumulative doses (<200 mGy). The
potential cancer risk from such low doses is very small, and can be easily missed or, alternatively,
spuriously produced by bias and confounding. In the most recent LSS report on cancer incidence inJapanese atomic bombing survivors, exposure to 1 Gy of gamma radiation at age 30 increased solidcancer incidence at age 70 by 47% [G7]. If we can assume that the ERR per unit dose is proportional tothe dose, a radiation dose of 200 mGy increases solid cancer risk in men by approximately 9% (=47/5),
which corresponds to a RR of 1.09 and an ERR of 0.09.

128 UNSCEAR 2017 REPORT

A. Studies in areas with elevated environmental radiation levels
1.

Review of selected studies

214. In this section, studies will be compared that provided a quantitative estimate of cancer risk perunit dose of environmental radiation for general population. Table 19 summarizes the main features ofradiation exposure and its sources in those studies. Associations between environmental radiation andcancer risk observed in those studies vary in degree but they are not inconsistent because of large
confidence intervals. They have the potential to provide new knowledge on the magnitude of excess
risk from low-dose-rate radiation exposure and to some extent too on modifiers of such risk and risk
related to specific cancer sites. Tables 20–23 summarize methodological features of those studies.
215. The Karunagappally study and the Yangjiang study are prospective cohort studies. The TRC wasestablished mainly in the late 1960s through 1980 (the majority of subjects were identified in the late1960s), and follow-up was conducted partly retrospectively, partly prospectively. Case ascertainment
for cancer incidence and mortality is a major factor in epidemiological studies, and comprehensive andhigh-quality case ascertainment is particularly important for the interpretation of low-dose/low-doserate studies. Ascertainment in the studies of high-background radiation areas may not be adequate foraddressing the effects of low-dose radiation, particularly in the early follow-up period.
216. In the TRC study, the follow-up of cancer was started for mortality in the 1950s and for cancer
incidence in 1956 and is still continued up to now. There was no national cancer registry in the Soviet
Union and follow-up of cancer incidence in TRC members started only from 1956. In the TRC study,
the proportion of cases identified solely through death certificate notification decreased throughout thefollow-up period from 35% for 1956–1969 to 9% for 1990–2007, while the proportion of cases withmorphological or radiological confirmation (e.g. based on X-rays, ultrasound) increased from 33% to82% between the above time periods. The investigators of the TRC cancer incidence study [D5]concluded that for the studied period “the ascertainment of solid cancers is thought to be largely
complete for cohort members residing in the study regions”.
217. In the early follow-up of the study, the cancer registry in Karunagappally had approximately 10%of cases based on death certificate only, which is higher than desirable, particularly in a low-dose study.
In the Yangjiang study, with only mortality follow-up, the ascertainment of deceased cases was
virtually complete except for subjects who moved out of the study area permanently. That isparticularly so for old residents, who tend not to migrate. However, the accuracy of cause-of-death data
can be a problem and it will be discussed later.

Table 19. Main features of radiation exposure in cohort studies on cancer risk from low doses of radiation from environmental sources
FeatureMain sources of external exposure
Sources of internal radiation
exposure-

Ingestion-

Inhalation

Techa River study [D5, K18, S3]

Karunagappally study [N4]Cs and shorter-lived fission products

Sr, 89Sr, 137Cs

Negligible

Negligible

Negligible

Radon: <10 Bq m−3

Radon: 10–100 Bq m−3

Lifetime

Lifetime

90

Lifetime; highest exposure: 1950–1956

Dose rate

Mean RBM dose: 135 mGy a in 1951, 10–60 mGy ain 1952–1960, <10 mGy a−1 afterwards
−1

−1

232

Th and its decay products

1–15 mGy a (colon dose from external
exposure)

1–5 mGy a−1 (colon dose from external exposure)

188 mGy (colon dose from external exposure)

85 mGy (colon dose from external exposure)−1

Mean stomach dose: 28 mGy a−1 in 1951, 0.3–15 to
15 mGy a−1 in 1952–1960, <1 mGy a−1 afterwards
Mean cumulative doses

RBM dose: 430 mGy; Stomach dose: 43 mGy

Table 20. Features related to study populations in cohort studies on cancer risk from low doses of radiation from environmental sources
FeatureTecha River study [D5, K18, S3]

Karunagappally study [N4]

Yangjiang study [T3]

Study design and study
population

A cohort study of rural residents (mainly farmers),
12 558 men and 17 172 women of all ages. Cancer
incidence study is based on a subcohort (N=17 435)
consisting of residents in Chelyabinsk Oblast

A cohort study of rural residents, 32 085 men
and 37 873 women, aged 30–84 years

A cohort study of rural residents (mainly farmers),
16 045 men and 15 559 women, aged 30–74 years

Eligible subjects

All residents born before 1950 who lived in 41
villages along the Techa River in 1950–1960

All residents whose information was collected
at the time of baseline survey (1990–1997)

All residents of the study area, including control
areas, who were alive as of 1 January 1979

Selection bias of study subjects

It is unlikely that there could be selection bias since,
according to the Soviet law in the 1950s, the list ofresidents of any village was constantly updated by
the local administration. All persons were membersof collective farms and could not leave a workplace
without official permission. Residents of villages
had no passports till the 1960s. Moreover, allresidents were listed in tax books, which were
updated for each farm. Loss to follow-up was
relatively high, but unrelated to exposure levels

Selection bias is unlikely since it is a
prospective cohort study, in which incident
cancer cases were identified in a prospective
follow-up after a baseline survey

Selection bias is unlikely as there is no reason tosuspect that the identification of study subjects is
affected by vital status and exposure status

Comparability of the exposed andcontrol/comparison groups

Lower dose groups tend to be located in more
remote places

Some highly exposed areas are located near
the major fishery ports

The control areas are closer to metropolitan areas

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 129

Period of exposureTh and its decay products

Yangjiang study [T3]

232

137

Feature

Techa River study[D13, D14, D16, S10, S12]

Karunagappally study[N3, N4,O3]

Yangjiang study[K20, M6, O2, T3, Y1]

Ages at exposure / exposure
periods

Lifetime exposure since 1949. The main exposure took
place in the early 1950s

Lifetime exposure from birth time for those without
migration

Lifetime exposure from the birth time for those
without migration

Individual dosimetry

Individual external dose estimates were based on
exposure rate measurements along the banks of theriver and on the shore within a few hundred metresfrom the water in specified areas of settlements. The
estimates for each settlement were calculated as aweighted sum of the dose rates at locations with highoccupancy, including houses. Individual internal dose
estimates were based on measurements of 90Sr in thesubjects (post-mortem concentrations in bone
samples, in vivo measurements of surface activity ofanterior teeth, body-burden measurements)

Individual external dose estimates were calculated as a weighted sum of the average ambient dose rates at
locations with high occupancy, including homes. The time spent at the corresponding location is used as
the statistical weight

External dosimetry(outdoors)

Measurements conducted periodically at 25 monitoring
posts along the shoreline of the river

Measurements conducted at the front gate of all thehouses in the study area

Measurements conducted at major activity areas(e.g. roads, open recreational areas, ricepaddies) in all the hamlets in the study area

External dosimetry (indoors)

The ratios between indoor and outdoor air kerma
rates were obtained from a survey of 10 houses
conducted in 1954

Indoor air kerma rate measurements were made in theroom with maximum occupancy at every house at
the time of the baseline survey during 1990–1997

Indoor dosimetry was conducted in the main
bedroom, the sitting room and the kitchen in
one third of houses in each hamlet

External dosimetry(indoors, non-residential)

Measurements were conducted in the areas within
400 m all along the Techa River (about 200 km long),
including farmland

Not conducted. Air kerma rates at school or at work
were not measured

Air kerma rates in schools and also at farmlandin each village were conductedOccupancy factors

Took into account only the age-dependent variationin the hours spent at the shoreline, outdoors andindoors. Ignored possible sex and ethnic differencesSex- and age-specific house occupancy factors
obtained from a survey of 7 711 residents in 2002.
Only information on occupancy in homes

Used sex-and age-specific population averageobtained from a survey of 5 291 subjects inover 88 hamlets conducted in 1991–1993

Residential history

Lifetime migration history was taken into account in dose accumulation

Internal dosimetry (ingestion)

Mainly through ingestion of water and milk
contaminated primarily by 89Sr, 90Sr and 137Cs

Considered negligible

Through inhalation of radon and its progenies

Internal dosimetry(inhalation)

Doses from radon progeny substantial in some areas
including Muslyumovo but ignored

Measurements of radon and thoron progeny weremade in 259 dwellings. The mean equivalent dose tolung is similar to that from external irradiation, but
ignoredThe mean equivalent dose to the lung due toinhalation of radon and thoron progenies wasfound to be greater than the corresponding
value for external irradiation

130 UNSCEAR 2017 REPORT

Table 21. Features related to exposure and exposure assessment in cohort studies on cancer risk from low doses of radiation from environmental sources

Feature

Techa River study[D13, D14, D16, S10, S12]

Karunagappally study[N3, N4,O3]

Yangjiang study[K20, M6, O2, T3, Y1]

Individual medical doses received at the URCRM clinic
for special surveys were reconstructed. Medical
doses deemed not to be large enough to affectcancer risk estimate

Medical exposure is considered infrequent

Medical exposure is considered infrequent

Organs considered in dose
calculation

Twenty-three organs and tissues, including RBM andstomach wall, are considered in the dose calculation.
Air kerma rates, occupancy factors and agedependent conversion factors were used to calculate
external dose. Age-dependent radionuclide intake
and dose coefficients per unit intake were used to
calculate internal dose

Colon dose for solid cancer, calculated using air kerma
and ICRP 74 organ dose conversion coefficient [I5]Colon dose from external radiation for solidcancer, calculated using air kerma rate and ICRP
74 organ dose conversion coefficient. Effective
dose (instead of lung equivalent dose) for
intakes of radon and thoron progenies

Dose validation

EPR- and FISH-based dose estimates, carried out on alimited number of subjects, agreed well with thedose estimates derived from the use of the TRDS.
Luminescence measurements of anthropogenic
dose in bricks from old buildings located on the
Techa River banks were also found to be consistent
with calculations performed using the TRDS
parameters

TLD measurements and scintillometer spot readings
were conducted for one year in 800 houses,
randomly selected. The estimated annual doses
derived from the spot readings correlated well with
the TLD-measured annual doses. Also, the frequencyof chromosomal aberrations was found to increase inproportion to the cumulative dose in adult females

Individual dose estimates obtained frommeasured indoor and outdoor air kerma rates(indirect method) were compared withindividual dose estimates measured using
pocket dosimeters and TLDs (direct method)(N<100). There was a good correlation
between the results obtained with the two
methods

Dose uncertainties

Substantial efforts have been made to evaluate theuncertainties in the individual dose estimates.
Preliminary results, dating back to 2000, indicatedthat the uncertainties in external doses ranged inabout a factor of 4 to 5 and that the ratios of the 97.5
and 2.5 percentiles for the internal dose estimates
were in the range of 20–30 and could reach 100 or
more. Since 2000, major work has been performed
to reduce these uncertainties and to separate theshared and the unshared uncertainties. The first
results for internal dose to the RBM showed that theuncertainties in the individual dose estimatesappeared to be log-normally distributed with ageometric standard deviation of about 2 to 2.5. The
complete results of this thorough uncertainty
analysis have yet to be published

Uncertainties in the individual dose estimates were notquantified. It is likely that the contribution of theunshared errors is larger than that of the sharederrors because the individual dose estimates are
based on measured indoor and outdoor dose rates ineach dwelling

Uncertainties in the individual dose estimates
were not quantified. It is likely that thecontribution of the shared errors is larger thanthat of the unshared errors because most of
the individual dose estimates are based onvillage-averaged parameter values

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 131

Medical radiation exposure
and others

MV: morphologically verified; IM: Instrumental Methods (X-rays, CT, ultrasound, bronchoscopy etc.)

Techa River study
on cancer mortality [S3]Techa River study
on cancer incidence [D5, K18]

OutcomeCancer deaths in Chelyabinsk andKurgan Oblast

Incident cancer case in Chelyabinsk
OblastIncident cancer case

Cancer death

Case ascertainment

Death certificates from regional ZAGS
and Regional Statistical Bureau
OfficeThroughmandatorycancerregistration since the mid-1950s.
Own additional systematic efforts

Case ascertainment, which was throughregional cancer registry established in
1990, may be affected by SES

Own systematic efforts to identify
deceased subjects and to determine
cause of deathCompleteness of caseascertainment

Some incompletenessThe completeness may not besatisfactory in early years

Completeness in the 1990s may beunsatisfactory

Some under-ascertainment likely due tolow level of health-care use and quality

Accuracy of diagnosis

91% with defined cause of death
confirmed by death certificates,
generally 10–30% of deceased
cases underwent autopsy

During 1990–2009, MV% was 67%
and IM% was 19%. During 1956–
2009, MV% was 55% and IM% 14%.
No pathological panel review for
diagnostic verification

MV%>65%. May be affected by SES. No
pathologicalpanel
reviewfordiagnostic verification. Proportion ofcases with unknown primary site highMV 26%. Probably unsatisfactory,
considering the quality of medical care.
No pathological panel review for
diagnostic verification

Most common site ofcancer

For men, cancers of the lung and stomach; and for women, cancers of theuterus, stomach and breast

For men, cancers of the lung and headand neck; for women, cancers of thebreast and head and neck

Hepatocellular carcinomas and nasopharyngeal cancers are the mostcommon cancers

Migration

At the end of follow-up, approximately
16% of the cohort had migrated
out of the catchment area (i.e.
distal migrants)<10% during the follow-up<10% during the follow-up

Feature<20%

Karunagappally study[N4]

Yangjiang study[T3]

132 UNSCEAR 2017 REPORT

Table 22. Features related to outcomes in cohort studies on cancer risk from low doses of radiation from environmental sourcesTable 23. Statistical analysis, information bias, and confounding in cohort studies on cancer risk from low doses of radiation from environmental sources
FeatureTecha River study
on cancer mortality [S3]Techa River study
on cancer incidence [D5, K18]

Karunagappally study[N4]

Yangjiang study[T3]

Data on SES and lifestyles werecollected by the baseline survey
conducted during 1990–1997

No baseline survey was conducted
and therefore no adjustment for
confounders

Information on exposure levels is unlikely to be affected by vital status

ConfoundersNobaselinesurveywasconducted. Only demographic
information is available. Social
conditions for rural populationsin the Soviet years were very
similar in study areas

Adjustment for confounders

A recent cancer incidence study was adjusted for smoking

Adjusted for smoking and SES

Not conducted

Risk factors similar acrossexposure levels

Smoking was not positively related to exposure levels. Most TRC members
were poor collective-farmers in the Soviet era. Demographic factors
including ethnicity, were adjusted in risk analysis. Number of migrants andloss to follow-up, methods of confirmation of cancer diagnosis do notcorrelate with radiation exposure

Smoking and SES, which can be
related to exposure levels, were
adjusted in risk analysis

Prevalence of smoking and alcoholuse, medical exposure and SES were
found to be similar in HNBR andcontrol areas in small-scale surveys
on potential confounders

Lag time

Cumulative dose was lagged by 5 years

Cumulative dose was lagged by
10 years

Cumulative dose was lagged by
10 years

Statistical model

Poisson regression analysis was conducted

Data on smoking recorded at the URCRM
clinic were collected (smoker andunknown smoking status). Social
conditions for rural populations in theSoviet years were very similar in study
areas

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 133

Information bias

134 UNSCEAR 2017 REPORT218. In the Yangjiang study, extensive surveys were conducted periodically to identify deceased cohort
members. Although no effort was made to evaluate the completeness of cancer death ascertainment, it
was not difficult to enumerate deceased cases in the countryside, where residents knew each other well,and permanent migration was infrequent. However, the accuracy of cause of death could be far from
ideal since farmers could not afford expensive treatment for cancer or other serious diseases. In themortality study [T3], of the 941 deaths of cancer, excluding leukaemia, the underlying causes of death
were determined on the basis of pathological information for 26% of the deaths, and on radiological or
ultrasonographic diagnosis for 62%. Particularly of concern is the diagnosis of liver cancer, which isdifficult to diagnose accurately due to difficulties in distinction between liver cancer, liver cirrhosis andhepatic metastases of other cancers.
219. The TRC study examined not only cancer incidence but also cancer mortality. The catchment areaof cancer mortality follow-up was larger than that of cancer incidence, covering the entire territories of
the Chelyabinsk and Kurgan Oblasts. The mortality follow-up was virtually complete. However, it isdifficult to evaluate the accuracy of cause of death, particularly those that occurred at home.
220. It is often easier to obtain data on cancer mortality than on cancer incidence, because deathcertification tends to be more widely available and more complete than cancer registration. In addition,
cancer incidence studies are more likely to be affected by loss to follow-up because of migration, unlessthere is a high-quality nationwide cancer registry. Nevertheless, cancer is often more accurately
reported than most other causes of death [R5]. However, cancer deaths are fewer than incident cases,
though depending on prognosis.
221. Since the ratio between cancer incidence and mortality rates is usually in the range 1.5–2, amortality study cannot identify the 33−50% of cancer cases that are non-fatal, even if the data arecomplete and the information on the death certificates is accurate. As mortality depends on bothincidence and prognosis, variation between populations also reflects availability and effectiveness oftreatment. Inclusion of contributing causes of death improves the coverage, but not substantially [S4].
222. In the TRC study, almost 25% of the cohort members are known to have left the study area during
1949–1989. Roughly 80% of the cohort members who left the area moved to nearby cities and towns in
Chelyabinsk, Yekaterinburg (formerly Sverdlovsk) and Kurgan Oblasts. Therefore, the proportion ofemigrants who were lost to follow-up is not exceedingly large. Furthermore, emigration was unrelated
to exposure level. Generally speaking, permanent migration is infrequent in rural areas of India andChina. The cohort members of the Karunagappally study were mainly farmers, fishermen andblue-collar workers [N4]. The survey conducted in 2001 showed that migration outside Karunagappallywas 6% in the 13-year survey period. The populations in the Yangjiang study were mainly farmers
working on collective farms in rural areas. Their families had lived in the area for generations [H5].
Although Yangjiang is close to areas that have witnessed rapid economic development, it is difficult for
local farmers to change their family registration to city areas and settle there.
223. In all the studies reviewed in this chapter, individual dose estimates from external exposure were
calculated as a weighted sum of the average ambient dose rates at locations with high occupancy,
including homes. The time spent at the corresponding location is used as the statistical weight. Thisapproach requires information on indoor and outdoor air kerma in the places—such as residences,schools and workplaces—where a subject spent a significant amount of time. In addition, it is necessary
to collect information on time spent in those places.
224. Collection of exposure information throughout lifetime is challenging. Exposure to natural
background radiation already starts before birth. Data on possible changes over time in indoor andANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 135

outdoor air kerma and occupancy factors is difficult to obtain. In the TRC study, residents had shorter
periods of exposure than residents in HNBR areas, but more variability in exposure over time. Theiroccupancy during the early years was also reported retrospectively, relying on recall, which adds
uncertainty. Even so, it is practically impossible to measure radiation doses comprehensively that werereceived by residents throughout the study period.
225. In the TRC study, external exposure was the main contributor to organ doses other than RBM
dose. For RBM dose, internal exposure from ingestion is a major component of exposure. Doseestimation in the TRC has been improved over the years [D7]. Few measurements were made in 1951,
when the highest release levels occurred and, thus, short-lived fission products that contributed to organdose had to be estimated on the basis of surveys conducted later. Uncertainties are related to mixing
data on internal and external doses and to measurements made years after the intake of internal doses.
Biokinetic models also contain uncertainty with regard to key assumptions related to isotope
depositions and detection decay after intake.
226. In the Karunagappally and the Yangjiang studies, the evaluation of internal exposure has not been
conducted systematically. In Karunagappally, the radionuclide concentration in local food was not high.
The results from a meal survey suggest that internal exposure from radium intake in meals is negligible
in comparison with that of 40K. The activity concentration of radium in meals did not show any
difference between HNBR and other areas as only a minor proportion of the food commonly consumed
by the residents was grown locally. Therefore, it is unlikely that lifetime radiation dose from internal
exposure was significantly different in the high and low exposure areas within Karunagappally [T12].
In the Yangjiang study, local foods did not have high concentrations of radionuclides [Y3].
227. In the two natural HNBR areas, thorium can be a possible source of internal exposure. The
thorium burden of 87 residents in Karunagappally was determined by a thoron-in-breath analysis,
indicating ingested level of thorium [N3, N5]. These results showed that the subjects from high andmedium indoor radiation level areas had a significantly elevated thorium body burden compared to thosefrom low indoor radiation level areas. No such evaluation has been conducted in the Yangjiang study.
228. Internal exposure from inhalation is another potential problem. In the TRC study, doses fromradon and its daughters in the Techa River region were reported to be 1.7–6.2 mSv a−1 [Z8], and wereignored in risk analysis. Exposure to radon and its progenies in the Karunagappally study can beignored because their indoor concentrations were low [T11]. In the Yangjiang study, indoor radonlevels were higher (close to 50 Bq m−3) but still too small to substantially increase lung cancer risk
[T10]. Further, lung cancer risk in the HNBR area of Yangjiang is similar to that in the control area
[T2]. Both the Karunagappally and Yangjiang studies ignored internal exposure from ingestion.
229. It is possible to measure individual doses from HNBR during a short period (e.g. a few months).
In all the studies reviewed in this annex, individual dosimetry using selected subjects was conducted fora short period and the measured doses were compared with estimated doses. However, the correlation
between such a dose and the “real” cumulative dose up to the time of measurement is practically
impossible to evaluate. Moreover, the accuracy of the dosimetry is sometimes questionable because it is
not possible to tell whether the dosimeters were properly worn by residents.
230. Another possible approach to evaluating HNBR doses received by residents is to examine
chromosomal aberrations. However, unstable aberrations, which are almost exclusively induced byionizing radiation, do not reflect long-term cumulative doses as cells with such aberrations are
eliminated relatively quickly. Stable chromosomal aberrations are related to cumulative radiation doses.
Yet, because they are also caused by factors other than radiation [S17], their association withcumulative doses is weak at best, and require relatively large cumulative doses for an increase to be136 UNSCEAR 2017 REPORT

detectable. There is evidence that chronic exposure produces increased chromosomal aberrations inradiation workers at a lower rate than acute exposure [T7, T17]. Given that the half-life of human
lymphocytes is considered to be about three years [I1], frequencies of unstable chromosomal
aberrations induced by chronic irradiation could be expected to reach a plateau after several years [S2].
However, unstable chromosomal aberrations accumulate over the periods of half-lives of lymphocytes
in mice, according to dose rate in the range of one to hundreds mGy d−1 [T1]. Even in humans, there isa report suggesting that unstable-type aberrations could accumulate during longer periods than thehalf-life of lymphocytes [B3]. The kinetics of turnover of lymphocytes could become slower at low
dose [R2] and low dose rate [A15]. In most studies in HNBR areas, an increased frequency ofchromosomal aberrations has been found, despite some inconsistencies. The dose response iscomparable with studies of higher dose levels, but one has to keep in mind that the precision ofchromosomal aberration studies in the low dose range is poor, in particular, when the number of
metaphases scored is low.
231. All the studies have limitations in dose assessment despite extensive efforts. The uncertainties are
related to use of area-based measurements instead of individual data, and assumptions on occupancy
and exposure outside home over long periods. Even if the uncertainties cause non-differential
misclassifications, in the comparison between the exposed and unexposed groups, non-differential
misclassifications typically bias ERRs and RRs toward the null value (0 and 1, respectively). However,if the exposure categories are divided into three or more groups, non-differential misclassification may
bias the dose response away from the null value [D19]. Dosimetric uncertainties shared among
subgroups of a study population can bias dose response, either masking or exaggerating a true effect[G2, L1]. It is desirable to evaluate dosimetric uncertainties shared by subgroups, as is being done in
the TRC study, and to conduct dose–response analysis to account for those uncertainties [S19].
232. Since women in the HNBR study areas tend to stay at home, annual dose is more easily estimatedfor women. However, residential stability is lower for women, as a considerable number of women
moved into their current residence after marriage. Doses at the houses before marriage are more likely
to be missed in the dosimetry survey, which was conducted at the time of the baseline survey during theperiod 1990–1997 in the Karunagappally study. This problem can be more serious if women moved
from high-dose areas to low-dose areas before the baseline survey.
233. Medical exposure was infrequent in Karunagappally and Yangjiang, because the areas are mainlyrural and access to medical facilities was neither easy nor affordable. On the other hand, in the TRC
study, subjects underwent X-ray diagnostic procedures as part of their medical examinations. No
attempt was made to examine the correlation between cumulative doses from medical exposure and
HNBR in the Indian and Chinese studies. However, the contribution of medical exposure was small
compared to the environmental doses, with the average doses to major organs ranging between 11 and
33 mGy [D15].
234. Several risk factors have a stronger effect on solid cancer risk than low-dose radiation. As a result,even a weak association of radiation exposure with such a factor can confound the relationship between
radiation exposure and cancer risk. In HNBR and Techa River areas, radiation levels are determined
mainly by geography, which can be associated with lifestyle factors related to cancer risk and indicatorsof such factors including SES, religion, ethnicity and occupation.
235. Information on several lifestyle factors such as smoking and alcohol use and also SES was morecomprehensive in the Karunagappally study than in the TRC study or Yangjiang study. The lack ofdetailed information on confounders is a major drawback. The TRC study could not collect information
on lifestyles and socioeconomic factors from the entire cohort. However, because the TRC study
populations consist mainly of farmers working in collective farms in rural areas, their lifestyles were

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 137

relatively homogeneous, particularly during the Soviet era. Differences in smoking habits and alcohol
use are, however, very likely. On the other hand, lifestyle can be correlated with sex and ethnicity.
Adjustment for these proxy indicators of behavioural risk factors in risk analysis should diminish
confounding to some degree.
236. The TRC cancer incidence study [D5] used data on smoking that were recorded during interviews
for TRC members of the cohort who visited the URCRM clinic. Individual information on smoking
intensity and duration were not available for risk analysis.
237. The Karunagappally study collected information on lifestyle and SES in the baseline survey, andthe collected information was used in the cancer risk analysis. However, the study reported by Nair etal. [N4] was, for unclear reasons, not adjusted for tobacco chewing, which is a major cancer risk factor
in the study area for cancers of the upper digestive tract organs, even if the information were available.
238. One of the main concerns in the Yangjiang study is the comparability of lifestyles and otherpotential confounders in HNBR and control areas. It has been criticized that a slightly low cancer
mortality rate in the HNBR area reported by the first international publication [H5] might be due todifferences in living standards and lifestyles in HNBR and control areas. The Yangjiang study collected
information on those factors for only a small portion of the cohort members. On the basis of thosesurveys on the selected residents, it has been concluded that the distributions of several potential
confounding factors – including diet and nutrition, drinking water, pesticide residue and aflatoxin B1 infood, medical exposure, tobacco smoking and alcohol consumption in HNBR areas – were notsubstantially different from those in the control area [T4, Z4]. Differences were noted, however, forinfections such as tuberculosis.
239. The cumulative dose was lagged by five years in the TRC study, and was lagged by 10 years in
the Karunagappally and the Yangjiang studies, assuming that cancer risk is not increased during the lagtime, i.e. before a minimum latency* has elapsed. If cancer risk is already increased during theexcluded lag time, absolute risk due to radiation, such as lifetime risk, will be underestimated though
the ERR estimates may be either underestimated or unaffected [R6].
240. Statistical power is calculated before a study is conducted to assess whether there is sufficient
likelihood of finding an effect of a given size, provided that it exists. The number of cases attributable
to exposure is a good indicator of the amount of information from a study, as it reflects both effect size
and number of cases. Effect magnitude depends on exposure level (and potential modifiers of risk), andthe number of cases on baseline risk. After a study is conducted, confidence intervals indicate the rangeof risks consistent with the observed results. Of the studies on environmental radiation exposure
resulting from human activities, the TRC study has a statistical power higher than 80% for showing arisk estimate similar to the LSS, while the Taiwanese study does not. Of the HNBR studies, theYangjiang study had fewer cases and lower average doses in the exposed group than the
Karunagappally study and, therefore, also lower statistical power.
241. Even studies of low statistical power, such as several of the natural background radiation studies
presented here, are informative if they can indicate levels of risk that are unlikely, given the observations.
If an expected estimate of ERR per unit dose and its standard errors are available, the statistical power of agiven study to find this expected ERR per unit dose can be calculated in retrospect. In the Karunagappally
study, the ERR estimate per 100 mGy for solid cancer was −0.013 per 100 mGy (95% CI: −0.058, 0.046).
After adjustment for attained age, the LSS estimate was 0.062 at 100 mGy (95% CI: 0.053, 0.071). The
statistical power to detect an ERR per unit dose similar to the LSS with an alpha of 10% is >80% for the
Karunagappally study. The lack of overlap in the confidence interval in the risk estimates per unit dose,138 UNSCEAR 2017 REPORT

suggest influence by some of numerous differences between the two studies in exposure (e.g. dose rateand distribution of cancer sites and age at exposure) and/or conduct of the studies.
242. In the evaluation of results from individual studies, consistency of results with previous
epidemiological literature is needed for proper interpretation. Validity* requires solid study design andappropriate data analysis, and credibility can be assessed also by comparing reported patterns of risk
with earlier studies. In the TRC study, the reported excess risk was largely driven by two cancer sites,cancer of the cervix and uterus and the oesophagus. Uterine and cervical cancer have not been
convincingly linked to ionizing radiation, and the association with oesophageal cancer in the TRC was
found only in women and not in men. Further, the oesophageal cancer risk was concentrated only in
one ethnic group. Moreover, in the TRC study the ERR tends to increase with age at exposure, whereas
in the LSS and other studies, relative risk has decreased with age at exposure. Likewise, the TRC
indicated a tendency of relative risk increasing with attained age, whereas in other studies it decreased
with attained age. The differences between age groups in the TRC were, however, not significant. The
differences between the TRC study and the LSS should not be overemphasized since they can be due tostatistical imprecision. The number of excess cancer cases in the TRC study [S3] is around 50 and,
therefore, its statistical power to evaluate risk modification or risk by cancer site is much lower thanthat of the LSS. Variability* in risk within the study population also tends to decrease the statisticalpower (precision) [L6].

2.

Summary243. The epidemiological cancer studies reviewed here have advantages and drawbacks in various
aspects. Dosimetry is always a challenge in studies of environmental exposure, as it is practicallyalways based on retrospective reconstruction of spatial distribution of dose rates, with efforts to accountfor factors such as shielding and occupancy. For internal exposure, information is also needed for pastintake and sources of food and water. The case ascertainment is suboptimal, especially in comparison
with other cancer incidence studies such as the LSS, and studies of workers and patients. The risk
estimates in studies of environmental exposure can be distorted by biases and confounding. However,
the magnitude of those biases and confounding are difficult to evaluate without extensive sensitivity
analysis. Fewer major risk factors are known for leukaemia than for various solid cancers and,
therefore, the findings on leukaemia are less likely to be influenced by confounding. Someheterogeneity in solid cancer risk may also stem from the fact that even if all studies excluded
leukaemia from analyses of other cancers, exclusion of other lympho-haematological malignancies was
not entirely consistent in various studies. The limitations need to be considered when drawing inference
about radiation-induced risks from the observed rates reported in the studies evaluated here (see alsoannex A and the glossary).
244. The LSS reported for solid cancer mortality an ERR of 0.042 per 100 mGy for those with attained
age 70 and exposed at age 30 (the male-female ratio is assumed to be 1:1). In the TRC study, the ERR
for mortality from all solid cancers was 0.061 per 100 mGy (95% CI: 0.004, 0.127), which is close to,though slightly higher, the reported value in the LSS.
245. Using the solid cancer risk model given in the recent analysis of cancer incidence in the LSS, thesex-averaged estimate of ERR per Gy at age 65 for a person exposed at age 25 (which corresponds
roughly to the mean age at initial exposure and age at diagnosis in the current TRC data) is about
0.06 per 100 mGy, which is very close to the LSS results. The direction of the estimated sex, age andage at initial exposure effects on the ERR in the TRC are different from those in the Japanese survivorsof the atomic bombings [G7, H9]. However, these effect modification parameters are imprecise, andtheir confidence intervals are wide and therefore, cautious interpretation is needed, as it is unclear

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 139

whether they reflect methodological shortcomings or differences between the effects of protracted
low-dose-rate exposure compared with acute radiation exposure.
246. The mean RBM dose in the TRC was 0.42 Gy and there were 99 incident leukaemia cases in thecohort (82% microscopically verified diagnoses). The ERR per 100 mGy was 0.22 (95% CI: 0.08, 0.54)
for non-CLL leukaemia. This is higher than reported from the LSS, with more than 300 non-CLL cases(ERR 0.08 at 100 mGy based on the linear component which predominated at doses <1 Gy), but
comparable to, for example, the recent results from the INWORKS study of radiation workers (with>500 non-CLL cases but very low average doses) showing ERR 0.3 at 100 mGy [L4]. Of leukaemia
subtypes, the combined group of acute leukaemias and chronic myelocytic leukaemias showed a dose
response, while CLL and lymphomas were not associated with radiation exposure. Attrition due toemigration and loss to follow-up, as well as unknown causes of death and possible under-ascertainmentof cases in the early follow-up reduced the precision of the results as for other analyses, butnevertheless the leukaemia findings are the most robust results from the TRC study.
247. The ERR of solid cancer obtained from the TRC cancer mortality study was 0.061 (95% CI:
0.004, 0.127) [S3] and the TRC cancer incidence study gave 0.077 (95% CI: 0.013, 0.150) [D5]. The
corresponding estimate from the Karunagappally study [N4] was −0.013 (95% CI: −0.058, 0.046) andfrom the Yangjiang study [T3] was 0.019 (95% CI: −0.187, 0.304, excluding liver cancer). The study of
the residents of 60Co-contaminated buildings from Taiwan, China, showed an ERR 0.03 (90% CI:−0.04, 0.09) but it is substantially smaller than the other studies and has some unresolved
methodological issues. In the TRC incidence study, the ERR per 100 mGy became 0.063 (95% CI:
0.00, 0.14) after the exclusion of oesophageal cancer. The ERR estimates obtained from those studies
have wide confidence intervals and overlap each other. Continued follow-up of these relatively
low-dose cohorts, in particular the Karunagappally study, can potentially improve the precision, bettercharacterize the uncertainties in these risk estimates, and provide some insight into effect modificationand dose-rate effects on the magnitude of the risk.
248. When making comparisons between those ERRs per unit dose in those studies, it should be notedthat cancer patterns differ. In the TRC, the most common cancers are cancers of the stomach and lung.
On the other hand, in the Yangjiang study, hepatocellular carcinoma and nasopharyngeal cancers
accounts for nearly 50% of all cancers, known to be aetiologically associated with HBV and EpsteinBarr virus. In the Karunagappally study, lung cancer was the most common site, as was the case in the
TRC. However, the second most common cancer in men is head and neck cancers. These different
cancer patterns may be an explanation for differences in ERR estimates per unit dose, as the risk
coefficients are likely to vary by site. Ideally, assessment of radiation-induced risk should be evaluatedby specific cancer site, but this is limited by low statistical power.
249. Further improvement in the quality of HNBR studies would make them more valuable. This could
be done by improving cancer registries in that they provide long-term follow-up of residents, enhancing
cause of death assignment and data on non-radiation risk factors, and refining risk estimates for subgroupsof the population. Additional follow-up is likely to enhance the power of the Karunagappally study more
quickly than that of the Yangjiang study, because the cancer incidence rate in the former is higher than thecancer mortality rate in the latter. In the interpretation of the findings from the HNBR studies, there is also
the fact that the study populations have resided and received the constant exposure levels often for several
generations. Hence, if the adaptive responses shown in laboratory studies have relevance for cancer risk inhuman populations, such potential adaptive responses may reduce the effect magnitude.
250. An alternative source of information for risks from protracted exposure to low doses of radiationis through studies of occupationally exposed groups. Large studies have been conducted, a threecountry analysis of nuclear workers (INWORKS) as a recent example [L4, R3]. Occupational studies

140 UNSCEAR 2017 REPORT

also have strengths and weaknesses (e.g. lack of data on confounders, and study populations restricted
to working-age population, mostly men). Studies of anthropogenic radiation in the environment,
including those on the effects of the Chernobyl and Fukushima accidents, will also provide important
information about cancer risk from low doses of radiation. A third opportunity for studying low-doserisks is from diagnostic uses of radiation. The exposed subjects are, however, examined for a disease or
suspicion of disease, which makes it difficult to disentangle the effect of the indication for theexamination from that of the radiation exposure from the examination, unless similar patients can be
identified who were not examined radiologically.

B. Childhood leukaemia studies
1.

Review of selected studies

251. The association between leukaemia and environmental radiation exposure observed in the studies
is not consistent. However, all studies reported childhood leukaemia risk in relation to unit RBM doseor dose estimate have the potential to provide new knowledge on the dose response, the magnitude ofexcess risk and modifiers of the relationship between childhood leukaemia risk and low-dose-rateradiation exposure. Based on the quality criteria for the Committee’s reviews on epidemiologicalstudies elaborated in annex A, the main quality features of studies presented here (Finland, France
Switzerland and the United Kingdom as well as the Chernobyl study conducted in Belarus, the RussianFederation and Ukraine) are summarized in tables 24 and 25.
252. In a population-based control study, controls are so selected from the population that they
represent distribution of the exposure of interest and relevant co-variables, including potential
confounders, of the base population (usually, they are randomly selected from a comprehensive
population registry or a representative population roster). In the Chernobyl childhood leukaemia study,
two controls were selected from hospital records in each study raion, matching to each case on sex,
birth year and residence. In this case, it is difficult to tell whether the catchment population of cases is
the same as the population that controls are supposed to represent and from which the cases arise. In theother studies the base population or the control series was more clearly defined. The controls wereselected from the census record or family and birth registers.
253. Dependence of case ascertainment rate on exposure results can distort the association between
risk and exposure. The studies conducted in Finland, France, Switzerland and the United Kingdom
identified leukaemia cases through nationwide cancer registries. The quality of those registries wasshown to be good [B7, D1, T8] and therefore, such a concern is not warranted.
254. There are several subtypes of leukaemia, outlined in detail by the WHO classifications [V1]. In
epidemiological studies, however, classification as detailed as for selection of treatment is not used andthe emphasis is not on the prognosis. The main types include acute myeloid leukaemia (AML), chronic
myeloid leukaemia (CML), acute lymphocytic leukaemia (ALL) and chronic lymphocytic leukaemia(CLL) [B5]. CLL is considered aetiologically unrelated to ionizing radiation exposure even thoughsome recent studies have suggested otherwise [G6]. The possible differences between leukaemia
subtypes in terms of radiation-induced risk are not entirely clear, i.e. it is not well established whichsubtypes are more strongly related to radiation. ALL has an incidence peak at age 3–5 years [B5]. In
myelocytic leukaemia, the peak incidence is already at age one year and in infant leukaemia the
predominance of ALL is not as clear as in childhood leukaemia at older ages [B5].

Table 24. Main quality features of childhood leukaemia studies in Belarus, the Russian Federation and Ukraine (Chernobyl study) and in the United Kingdom
Criteria

Chernobyl case-control study [I8]

UKCC study [U1]2nd UK study [K3]1. STUDY POPULATION/PARTICIPANTS
0–20

0–15

0–15

Study design

Case-control study

Nationwide population-based case-control study

Nationwide population-based case-control
study

Eligible subjects

421 cases, inclusion criteria unclear

2 165 cases selected on the basis of family
registerCases (N=27 447) were collected frommultiple sources and cross-checkedagainst birth registers. Controls (N=36 793)
were selected from birth registers

Controls

835 hospital-based controls, matched by year ofbirth, sex and residence

Family health service authority or GP list or
health board matched by date of birth, sex andregion of residence (N=3 637)

Cases and controls were matched on sex
and date of birth (to within six months)

Selection bias

Considerable, as the population represented by
the control series is unclear

A serious participation bias is a concern

Unlikely

2. EXPOSURE
Individual dosimetry (assessed for accuracy)

Not directly measured

Indoor dose was measured at the current
residence

Record-based (taken as the mean for thecounty district); no data on building
characteristics

Residential history

Collected

Collected

Not collected

Effect of migration on dose estimation

Investigated separately with indications that
doses at successive addresses are strongly
correlated

Radon exposure

Not measured

Measured

Examined

Other internal exposure

Mainly through milk consumption

Not examined

Not examined

Organ doses calculated

RBM

RBM

RBM

Dose range

Median cumulative dose <10 mGy

0–20 mSv a−1 (average 0.8 mSv a−1)

Mean: 109 mSv; median: 103 mSv;
range: 55–383 nSv h−1

Medical exposure

Not examined

Not examined

Not examined

Effect of other exposure on dose estimate

Unclear

Probably negligible

Negligible in early years

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 141

Age at exposure (years)

Chernobyl case-control study [I8]

UKCC study [U1]2nd UK study [K3]3. OUTCOME
Number of leukaemia cases421

Not reported (total number of all childhood
cancers 2 165)

9 058

Leukaemia subtypes

Acute leukaemia was the end point

ALL is distinguished from the others

Leukaemia subtypes available

Case identification

Hospital records and cancer registry

Hospital records and cancer registry

Through the nationwide cancer registry

Complete case ascertainment

UnclearConsidered almost complete for leukaemia

Considered to be very highPathological review of cases for diagnostic
verification

A review was conducted for most cases

A central review was performed

No re-evaluation

Years of diagnosis

1986–2000

1992–1996 (1991–1994 in Scotland)

1980–2006

4. BIAS AND 5. CONFOUNDING
Information on confounders

Collected, but not on SES

Risk factors similar across exposure levels

Collected

Sex, age, county and SES (both individual
measures of SES and averages for Census
wards with a mean population of ~5 000)

SES is related to exposure

SES is related to exposure

6. STATISTICAL METHODS/ANALYSIS
Adjustment for confounders

Statistical analysis was adjusted for matching
factors. SES not considered

SES (area-based level of deprivation)

Adjustment for SES (county-level
deprivation index) did not affect theresults

Statistical analysis

Conditional logistic analysis (matched factors
taken into account)

Conditional logistic analysis (matched factors
taken into account)

Conditional logistic analysis (matchedfactors taken into account)

Latency period

No latency period was assumed

No latency period was assumed

9 or 12 months

Sensitivity analyses

Done

Done

7. REPORTING
ERR or equivalent (95% CI) for all leukaemias

Not reported

Not reported

12 (3, 22) per 100 mGy

ERR or equivalent (95% CI) for leukaemia
subtypes

ERR: 3(1, 8) per 100 mGy for acute leukaemia

No estimate per unit dose (or dose rate) reported.
For ALL, in the highest exposure category
OR=0.95 (95% CI: 0.66, 1.37); trend p=0.11

10 (2, 19) per 100 mGy for lymphoidleukaemia

142 UNSCEAR 2017 REPORT

Criteria

Table 25. Main quality features of childhood leukaemia studies in Finland, France and Switzerland
Criteria

Finnish case-control study [N10]French case-control study [D18]

Swiss cohort study [S25]1. STUDY POPULATION/PARTICIPANTS
0–15

0–14

0–15

Study design

Nationwide case-control study

Nationwide population-based case-control study

Nationwide population-based cohort study

Eligible subjects

Cases (N=1 093) from national cancer registry,
controls (N=3 279) selected from national
population register

2 763 cases were diagnosed during 2002–2007,
collected through the National Registry ofChildhood Cancers

Selected from census records, with 530
incident leukaemia cases

Controls

Cases and controls were matched on gender andyear of birth

30 000 controls were randomly selected fromincome and council tax databases ofhouseholds

No matching

Selection bias

Unlikely

Unlikely

Unlikely

Individual dosimetry (assessed for accuracy)

Record-based (mainly based on 8×8 km grid
average), also using building characteristics ofthe child’s residence

Record-based (1×1 km2 grid) for residence andtown centre; building characteristics notconsidered

Record-based (based on 2×2 km2 grid
average); no data on building
characteristics

Residential history

Complete residential history was obtained fromthe Population Register Centre

Not collected. Doses at diagnosis or inclusion
were used to estimate lifetime exposure

Residential address histories of patientswere obtained from the Childhood Cancer
Registry

Effect of migration on dose estimation

Collected and utilized

UnclearAvailable; stronger association among thosewith stable residenceRadon exposure

Considered ignorable

Estimated

Considered ignorable

Other internal exposure

Fallout of the Chernobyl accident was taken into
account (the data were collected by anationwide mobile survey in 1986–1987)

Not examined

UnclearOrgan doses calculated

RBM

RBM

RBM

Dose range

Cumulative dose:<12 mSv

Mean annual dose:
1 mSv a−1 (95% CI: 0.8, 1.7)

Cumulative dose: mean 9.06 mSv; median
9.12 mSv;
range 0.03–49.4 mSv

Medical exposure

Not examined

Not examined

Not examined

Effect of other exposure on dose estimate

Negligible, as postulated

Negligible in early years

Negligible in early years

2. EXPOSURE
2ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 143

Age at exposure (years)

Finnish case-control study [N10]French case-control study [D18]

Swiss cohort study [S25]

3. OUTCOME
Number of leukaemia cases

1 093

9 056 in incidence analysis,
2 763 in case-control analysis

530

Leukaemia subtypes

ALL, AML and others

Leukaemia subtypes available

ALL is distinguished from the others

Case identification

Through the nationwide cancer registry

Nationwide cancer registry

Through the nationwide cancer registry

Complete case ascertainment

Considered to be very highConsidered very highConsidered to be very highPathological review of cases for diagnostic
verification

No re-evaluation

No re-evaluation

No re-evaluation

Years of diagnosis

1990–2011

2002–2007

1990–2008

4. BIAS AND 5. CONFOUNDING
Information on confounders

Sex, age and other risk factors (Down’s
syndrome, birth weight, gestational age,maternal smoking)Risk factors similar across exposure levels

Sex, age and SES (individual measures) –excluded were subjects living in the vicinity of
nuclear power plants and proximity highvoltage power line at the time of diagnosis or
inclusion of SES and averages for Census wards
with a mean population of ~5 000

Sex, age, SES and other risk factor (birthweight, birth order, traffic density,
environmental EMF)

SES is related to exposure

SES and others are related to exposure

6. STATISTICAL METHODS/ANALYSIS
Adjustment for confounders

Adjustment for Down’s syndrome, birth weight,
maternal smoking did not affect the results; noadjustment for SES

Adjusted for SES (county average)

Adjustment for SES, proximity to highways
or powerlines, urbanization or crowding
did not affect the results

Statistical analysis

Conditional logistic analysis (matched factors
taken into account)

Unconditional logistic analysis, adjusting for age

Cox regression analysis

Latency period

Two years in the main analysis

No latency period was assumed

No latency period was considered

Sensitivity analysis

7. REPORTING
ERR or equivalent (95% CI) for all leukaemias

Overall −3 (−11, 6) per 100 mSv; 27 (1, 60)
for ages 2–7

Cohort analysis SIR=0 per 100 mGy (−2, +1);
results from case-control analysis reported only
for dose rate

ERR or equivalent (95% CI) for leukaemia
subtypes−1 (−10, 9) per 100 mSv for ALL

Cohort analysis:
ALL SIR=1 per 100 mGy (−1, +2)

Approximately 4 (0, 8) per 100 mGy

144 UNSCEAR 2017 REPORT

Criteria

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 145

255. A problem in case-control studies with interview/dosimetry is the collection of information on the
exposure of interest (radiation) and other co-variables after the development of the disease of interest.
Even for indoor dosimetry that does not involve interview, it is too naive to assume that behaviour andconditions, including occupancy, did not change after detection of symptoms and diagnosis. However,in the case of gamma-radiation measurements, such a problem is unlikely to be serious. If an interview
is involved, the impact of the disease may be more pronounced. If case subjects are too ill to beinterviewed or deceased, surrogates, including family members, will be interviewed for information on
occupancy, lifestyle and other factors. However, this kind of retrospective approach may introduce
inaccuracy and bias to the information, and may distort the relationship between leukaemia risk andradiation exposure.
256. Children commonly spend most of their time in the home in their early childhood. However, as
they get older, they tend to spend a relatively longer time outside home, for instance in day care.
Therefore, a study to estimate individual dose would ideally need to measure not only exposure athome, but also cover exposure at nurseries and schools, playgrounds, shopping centres, parks,
greenspaces and so on. However, comprehensive dosimetry including exposure outside the home isdifficult and unlikely to be feasible in a large-scale epidemiological study. In recent years, increased
unwillingness to participate in research for various reasons, including increased awareness of privacy
issues, has decreased coverage for population studies in many countries. Generally, participation ishigher among those concerned about the exposure/disease of interest.
257. In record-based studies, radiation dose estimates are not based on information obtained from eachstudy subject, but on area-based or other group-level dose estimates. The validity of such estimates
hinges on the homogeneity of dose distribution within the child’s everyday sphere, including occupancy
and variability of exposure within an area. Exposure can vary substantially in a child’s environment.
Systematic differences due not only to residential location, but also to other features such as shielding
by building structures/material as a source of background radiation should also be considered for
accurate exposure assessment. A key problem with area-based dose estimates is that they cannot takeaccount of inter-house variation in the way that direct measurements do. Unfortunately, the feasibilityof individual measurements in thousands of houses is limited by prohibitive cost and, furthermore,incomplete participation tends to introduce bias.
258. In the United Kingdom record-based study, if dose distribution is fairly uniform within a county
district (a county consists of up to seven county districts), and the child’s sphere of daily life
corresponds to that of the district, individual dose represented by county-district-specific average doses
can be reasonably accurate. In the Swiss study, investigators used 2 km × 2 km grids to represent thesphere of children’s everyday life. Although a smaller area is more likely to have more homogeneous
dose distribution, the actual sphere of everyday life is likely to extend beyond the specified area.
259. Theoretically, if the frequency of medical exposure such as CT imaging is associated with natural
background gamma-radiation exposure, medical exposure would cause exposure misclassification.
However, such associations seem unlikely, and medical exposure of RBM is unlikely to be large
enough to affect risk per dose unit in the studies reviewed here.
260. Studies of childhood leukaemia relied largely on area-based measurements for exposure
assessment. The size of the area varied (mapped grid data with 2 km × 2 km in the Swiss study and
8 km ×8 km in the Finnish study to administrative units of varying sizes in the United Kingdom andFrench studies), with presumably larger errors for larger area units. The measurement data included
outdoor dose-rate measurements (Swiss and Finnish studies) and surveys of residential (UKCCS,
N=2,283) or other buildings (France, N>17,000). The coverage of residential history also ranged from146 UNSCEAR 2017 REPORT

only the place of residence at diagnosis (France) or birth (UKCCS) to the entire residential history(Finland). In several studies, approximately half of the children had lived in more than one dwelling.
The details of the type of building affecting shielding and also building material as a source of radiation
were incorporated only in the Finnish study. The directly ionizing component of cosmic radiation wasincorporated in the measurements, but only terrestrial radiation was used in the analyses in somestudies. In addition, fallout from Chernobyl was taken into account in the Swiss and Finnish studies (theexposure levels from Chernobyl were lower in France and in the UKCCS). All studies with area-based
measures assumed a similar occupancy for all subjects and ignored exposure at other places such as
kindergartens and schools. No data on medical exposure were obtained in these studies though, overall,
the dose from CT and other diagnostic procedures is likely to be substantially lower than that fromenvironmental gamma radiation. Radon causes also some dose to the RBM but it was evaluated only in
the UKCCS and the Swiss study. Other sources of radiation exposure (missed doses) are likely to resultin some non-differential exposure misclassification with possibly minor bias toward the null, assumingthat other exposure is uncorrelated with background gamma radiation. For radon, this is, however,questionable, as radon tends to be correlated with other geogenic radionuclides but RBM doses aresubstantially lower than those from background gamma radiation. Only one study (UKCCS) was able
to obtain direct measurements of natural background gamma radiation at individual level (with only one
residence measured per subject, the residence at diagnosis or equivalent for controls), but participation
was incomplete and compliance was lower among controls than cases, which raised concerns ofpossible selection bias.
261. Potential confounding factors include the well-established risk factors for childhood leukaemia
such as some congenital conditions, including Down’s syndrome (21 trisomy) and some rare hereditarydiseases (ataxia telangiectasia, Fanconi anaemia, Bloom syndrome) [B10, M2]. Boys have slightly
higher rates than girls, heavy birth weight is associated with a slightly increased risk for Caucasian thanchildren of other ethnicities [M3, R4]. In addition, older parental age is associated with higher risk [S7].
Parental benzene and insecticide exposure and child’s exposure to pesticides are also suspected risk
factors [B1, C2, Z7]. Extremely low frequency electromagnetic fields have also been consistently
associated with elevated risk in epidemiological studies [A2, K6]. Higher SES has been associated withhigher childhood leukaemia risk in several studies, though the results have not been consistent acrosscountries and study types [P9]. Furthermore, the effects of several risk factors differ between
lymphocytic and myelocytic leukaemia.
262. The Finnish and Swiss record-based studies obtained individual information from birth registries,
population census, and other sources, enabling them to adjust for potential confounders such as birthorder and maternal smoking. Several studies had area-based measures of SES and the Swiss and French
studies included data on some environmental exposure, such as residential proximity to major trafficarteries, power lines and nuclear installations However, none of the studies had information on parental
occupational exposures or children’s day breast feeding, allergies or care attendance or pesticide
exposure. Lack of comprehensive adjustment for potential confounders indicates possibility ofconfounding, assuming that other exposure sources are correlated with natural background radiation.
263. The importance of adjustment for deprivation as an area-based measure of SES is frequently
pointed out. In the UKCCS, similar to the Swiss study [R8, R9], mean dose rates were higher inchildren classified in lower socioeconomic categories [K4, K5]. In the UKCCS, deprivation was also
positively related to annual dose [U1].
264. The direction of bias is difficult to predict in a particular study, as it depends on the correlation
between the confounder and radiation exposure. Nevertheless, it is important to collect information on
confounding factors and adjust for them in the risk analysis if needed. Other key issues in evaluation ofconfounding are the effect magnitude of the confounder and its frequency of occurrence (orANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...]

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prevalence). The maximal extent of bias is equal to the effect of the confounder (when there is a perfectcorrelation between the exposure of interest and the confounder). The effect of a rare but strong
confounder is most effectively dealt with by excluding subjects with the confounder. A good exampleof this is Down’s syndrome, which is associated with 20- to 50-fold risk of leukaemia, but only
approximately 1 in 800 newborns are affected. Even if most recognized risk factors have small tomodest effects and are relatively uncommon, they remain a concern as the expected effect range isbelow OR 1.2–1.3 because of the low exposure levels and modest exposure contrasts between subjects
in studies of natural background radiation and risk of childhood leukaemia.
265. The potential confounding factors were addressed to some degree in the childhood leukaemia
studies. The UKCCS was adjusted for SES only; the Swiss study for SES, electromagnetic fields andair pollution from traffic; the Finnish study for birth weight, Down’s syndrome and maternal smoking;and the French study for traffic density and power lines.
266. All studies of childhood leukaemia conducted in Europe had comparable exposure levels and,
therefore, comparison of statistical power between them is based largely on sample size. A case-control
study with multiple controls per case is likely to approach the power of a cohort study with similar
numbers of cases. Misclassification of exposure can also decrease power, so studies with full residential
history or measured doses have some advantage. The UKCCS investigators wrote: “It is unlikely that a
relative risk of this magnitude would be detectable in the present study after its statistical power,
modest variations in dose rate and limitations of data collection are taken into account”. It is a matter of
debate whether or not the relatively low statistical power and possible participation bias in the UKCCS
can be offset by the superiority of measurements made on actual residents and not area-wide-based
estimates used in the record-based study and other recent studies. However, the subgroup analyses do
not have sufficient statistical power. An example is the analysis of ALL in children aged 2–7 years in
the Finnish study [N10], with an OR of 1.27 (95% CI: 1.01, 1.60) per 1 mSv, which approximately
corresponds to an ERR of 27 per 100 mSv. This estimate is an order of magnitude larger than the LSS
estimate and, therefore, does not appear highly plausible. Furthermore, the studies are not adequately
powered for assessing the shape of the dose response (departure from linearity).

2.

Summary267. In studies of natural background radiation and childhood leukaemia, radiation exposure may beassessed by direct measurement in the homes of the study subjects or estimated using models or small
area averages. The former has the advantage of being better able to take inter-house variation into
account, i.e. the fact that radiation exposure in adjacent residences may vary considerably. Exposure
assessment relying on models or area-based estimates can provide only mean expected values andtypically have substantial uncertainty, which reduces statistical power and can bias results.
Nevertheless, direct measurements are often affected by low compliance, making them prone toselection bias. Also, residential measurements do not cover other exposure circumstances, such as day
care or schools.
268. The first UKCCS has the advantage of individual measurements instead of area-based estimates.
However, the dosimetry does not cover the entire sphere of children’s everyday life. Studies based oninterview and individual dosimetry may, however, be limited by low participation. In the UKCCS, theparticipation of cases and controls in the interviews was 87% and 64%, respectively, and for radiation
monitoring among participants, 55% and 67% (48% of the cases and 43% of the controls with both). If
the participation rates are differential and related to radiation dose, selection bias can occur, potentiallydistorting the results.

148 UNSCEAR 2017 REPORT269. Recently, several studies using area-based dose estimates have been conducted. In such studies,
statistical power can be increased by large sample size since, in the absence of any need for empiricalmeasurements, exposure estimates can easily be generated for large numbers of residences. A clear
disadvantage is uncertainties involved in estimation of individual dose based on area-based approaches.
However, the magnitude of dose measurement errors* in this approach depends on the variability of
exposure within an area. Comprehensive evaluation of radiation exposure throughout a child’s lifetimeis also a challenge and requires the construction of residential history, with exposure assessment in eachdwelling. In several studies, about half the cases in the study had moved between birth and diagnosis.
Overall, the uncertainties in dosimetry in the childhood leukaemia studies are larger than in the TRC or
Karunagappally studies. An advantage of the register-based studies is the nearly complete enrolment ofstudy subjects, when no contribution from the subjects is required. In countries and areas with highmedical standards, the accuracy of leukaemia diagnosis is not of concern, either, even if diagnosis
cannot be confirmed by expert panel review.
270. Residual confounding is another concern. In some countries, information on possible confounders
including SES and birth weight for each study subject can be obtained comprehensively through record
linkage with census and other register data. All the recent studies of natural background gamma
radiation and childhood leukaemia have been able to adjust for some of the other established orsuspected risk factors, but none comprehensively. Also, adjustment for area-based measures ofpotential confounders is likely to result in some residual confounding, due to misclassification fromvariability within an area unit. The extent of confounding depends on the strength of the effect of theconfounder, and its prevalence and degree of correlation with the exposure under study, which are
likely to vary between populations and study settings. The lack of individual information on medical
exposure is also an issue, particularly in populations with high standards of health care. The degree ofconfounder control by adjustment depends on how well the effect is captured by the measurement andany imperfection in validity or accuracy reduces the effectiveness of control. However, unless themagnitude of risk is large and the confounder closely correlated with radiation exposure, the extent ofdistortion by confounding can be assumed to be small, even though it needs to be related to the anticipatedtrue effect magnitude of radiation exposure. More efforts to collect information on all sources of radiation
exposure and accurate confounder data are necessary for future studies to improve the risk estimates.

C. Comparison with studies of acute exposure271. It is of interest to compare cancer risk estimates obtained from high-dose-rate studies such as the
LSS with those obtained from studies of low-dose-rate radiation from environmental sources. However,valid comparisons of the risk estimates are difficult because of differences in methodologicalapproaches, and uncertainties in the studies. A major difficulty in comparing solid cancer risks is theextreme variation in background cancer rates between populations and over time. China, India, Japanand the Russian Federation have differing cancer rates and distributions by primary site, and changes
from the 1950s to the current time. Combining all cancers, including those not convincingly linked toradiation, is problematic and could distort the validity of any comparisons. The studies also differ in
epidemiological design and methodological quality, including differences in case ascertainment,
dosimetry, and the handling of other sources of exposure such as diagnostic radiography and internal
exposure. Any residual confounding may also distort the comparison of results. Further, the risk
estimates from studies of environmental exposure are rarely precise enough to allow assessment of the
shape of the dose response and, for most analyses, a linear no-threshold model is applied. Further, they
do have sufficient power or precision to empirically evaluate the latency but have generally applied
assumptions of a minimum latency of two years for leukaemia and ten years for solid cancers.

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149

272. Cancer risk from radiation is not consistent across population subgroups, but depends on sex, age
at exposure and other factors. Such patterns of variation (effect modification) provide an opportunity to
examine the consistency of findings across studies and this is particularly important for studies of low
doses, where the extent of effects is small and results can be unstable due to statistical uncertainty
reflecting small numbers of radiation-induced cancers. However, expecting complete consistency may
not be justified, because risk patterns may depend on dose or dose rate (differences may reflect realvariation of effect). The complexity is further increased by the fact that such patterns of variation in risk
may differ across cancer sites and types. Even if the cancer types most easily induced by radiation may
be consistent across populations, differences in the underlying risk and demographic features may
affect the sites for which an excess can be observed. Results based on different cancer types combined
into a single category such as solid cancers are not always comparable because, in different studies, theaggregate risk estimate is composed of different proportions of specific cancer sites (reflecting variation
in baseline risks). As pointed out earlier in the Committee’s UNSCEAR 2000 Report [U6], comparison
across studies can be difficult if background rates and modifying factors such as demographic factors
differ between studies.
273. Studies on residents in HNBR areas provide opportunities to examine health risks in relation to
low-dose-rate exposure to low-LET radiation. For example, despite lack of significant excess risk, therisk estimates from the Karunagappally in Kerala, India and the Yangjiang, China studies arecompatible with the LSS results, although they can exclude only very high risks or strong protective
effects due to their wide margin of uncertainty (figure VIII).
Figure VIII. Relative risks comparison of the LSS [P16] with the Karunagappally [N4] and the Yangjiang[T3] studies

150 UNSCEAR 2017 REPORT274. On the other hand, in the TRC, the ERR of solid cancer mortality was 0.061 per 100 mGy (95%
CI: 0.004, 0.127), which is somewhat higher than that reported for solid cancer mortality in the LSS of
the Japanese atomic bombing survivors. The LSS reported an ERR of 0.042 per 100 mGy for thosewith attained age 70 and exposed at age 30. However, the wide 95% CI of the TRC estimate includes
the LSS estimate. The differences between results of studies on natural background radiation may
reflect differences in study design, in dose assessment, in methodology, and in case ascertainment; orbe due to combining all solid cancers and making comparisons from different countries, and also theinability to adjust for confounding influences.
275. The ERR estimate for non-CLL leukaemia in the TRC was comparable to that seen in the atomic
bombing survivors [P13, P15], who received acute high-dose-rate exposure. However, the dose response
for the Japanese atomic bombing survivors had a significant upward curvature at high doses, higher risk
for those exposed at young age, and the ERR estimates were somewhat smaller than the ones observed in
the TRC. These differences may be related to different situations of exposure: acute (LSS) vs chronic
exposure (TRC), external only (LSS) vs external and internal exposure through intake of water and food(TRC), and differences in baseline rates. The main criteria and results of the studies are summarized in table 26.
276. As noted above, the age structure of the study population may affect the results owing to themodifying effect of age (dependence of risk on age at exposure and age at observation). Anotherchallenge is handling age at exposure in continuous exposure. These features complicate the assessmentof consistency between the results of studies of low-dose environmental radiation and those assessing
effects of acute exposure, as comparability in terms of various age parameters (age at exposure, age
attained) is needed. Because radiation exposure is continuous in HNBR studies (and long-term in TRC),
age at exposure is not a single value but can be crudely summarized as the mean age (at a specific timeor during a given period). In the LSS, age at exposure shows an approximately inverse relation to ERRs
per unit dose for ages below 50 years [P16]. Therefore, the use of an arithmetic mean to represent theage at exposure during an exposure period of below 50 years seems a reasonable approach.
277. The average attained age of the TRC population is approximately 45 years, whereas the average
age at diagnosis of solid cancer is approximately 65 years [S3]. At an average attained age of 45 years
in the TRC study, the ERR per unit dose from the recent mortality analysis (0.061 at 100 mGy) is
approximately two thirds of the LSS estimate. Furthermore, the analysis of modification of ERR byattained age in the TRC study showed a tendency of increasing ERR values with increasing attained
age. However, the observed risk modification was not significant. A recent analysis evaluated the solidcancer and leukaemia risk estimates from the LSS and TRC, and it showed that the results from the twostudies are compatible, when the average attained age and average age at initial exposure are taken into
account [P17]. In the TRC study, the ERR for solid cancer incidence was 0.08 (95% CI: 0.01, 0.15)
compared to 0.06 (95% CI: 0.05, 0.07) for LSS; and the ERR for leukaemia was 0.22 (95% CI: 0.08,0.54) and 0.15 (95% CI: 0.03, 0.32), respectively.
278. An extensive analysis of 22 epidemiological low-dose-rate studies on risk of solid cancer withmore than 800,000 subjects and 30,000 cancers was published after the literature review for this report[S16]. A large majority of the data were from studies of occupational radiation exposure, but also thefour cohort studies of environmental radiation exposure evaluated here were included. The findings
suggested materially lower risk estimates per unit dose (by a factor of three) for solid cancers comparedwith the LSS results, but the findings were heavily influenced by the Mayak worker cohort with very
low risk estimates (accounting for 91% of the total variance for cancer mortality and 80% for cancer
incidence). If that study were excluded, the pooled risk estimate would be consistent with the LSS
results. Restricting the analysis to studies with mean doses <100 mGy gave yield coefficients similar to
LSS in analyses of mortality, though incidence results of those studies yielded a lower point estimate.

Table 26. Summary of the main criteria of studies on cancer risk from low dose and dose rate from environmental sources in comparison with the LSS
Techa River Cohort[D5, K18, S3]

Criteria
Size of study population

29 730 (mortality),

60

Taiwan, China
Co-contaminated buildings[H8, H10, H11]

6 242

Yangjiang, China[T3]
31 604

Karunagappally, India[N4]
69 958

Atomic bombing survivors study, LSS[G7, H9]80 205 (incidence)

17 435 (incidence)Median dose, mGy

43 (stomach)

6.3

Typical annual dose

Peak 10–20 mGy a ,−1

85 (colon)

161 (colon)

230 (colon)<5 mGy a~2 mGy a external

2–5 mGy a

Instantaneous exposure

−1

−1

−1

<10 mGy a after 1955 (stomach)−1

1 933 incident cases, 2 303 deaths

106 incident cases

956 deaths

1 349 incident cases

22 538 incident cases

Solid cancer ERR/100 mGy(95% CI)

Incidence 0.08 (0.01, 0.15)

0.03 (−0.04, 0.09)−0.10 (−0.25, 0.10)−0.01 (−0.06, 0.05)

Incidence 0.047 (0.039, 0.055)

Leukaemia cases (non-CLL)

99 (72) incident cases

6 incident cases

15 deaths

30 (20) incident cases

416 incident cases (other than CLL or
adult T-cell leukaemia)

Mean RBM dose, mGy

420

48 (whole-body dose, not RBM)

107

163

100

Leukaemia ERR/100 mGy

0.12 (0.04, 0.25) all leukaemias,

0.19 (0.01, 0.31)

1.1 (<0, ∞)0.6 (not defined, 34)

0.08 (0.003, 0.18) linear component,

Mortality 0.06 (0.004, 0.12)

0.22 (0.08, 0.54) non-CLL

0.01 (0.03, 0.18) quadratic component,
incidence

ANNEX B: EPIDEMIOLOGICAL STUDIES OF CANCER RISK DUE TO LOW-DOSE-RATE RADIATION [...] 151

Solid cancer cases

152 UNSCEAR 2017 REPORTVII. FUTURE RESEARCH NEEDS
279. Epidemiological studies use observations from populations with contrasting exposure to the
exposure of interest. There are few major opportunities for studies of cancer risk from low-dose-rate
exposure to environmental radiation, because large (or very large) studies are required to achievesufficient statistical power for detecting the predicted excess risks of modest size. Ideally, such studies
would be conducted in populations that are otherwise highly comparable, but with a stark contrast inradiation exposure. Similarities should include major risk factors for cancer, and a comprehensive
source of high-quality cancer diagnoses, and also deaths and migration (with minimal loss tofollow-up). Accurate and detailed dosimetry for all major sources of radiation (including diagnostic
radiography and radon where appropriate) and repeated surveys of smoking behaviour, alcohol
consumption and other major non-radiation risk factors for cancer would be important. Assuming that it
is not practicable to obtain individual dose measurements for large groups of study subjects over long
periods in an unselective fashion, constructing accurate prediction models with detailed data on eachresidence of the study subjects (and exposure levels outside) based on dose-rate surveys with large
numbers of measurements may be the optimal approach for radiation exposure assessment. A morecomprehensive account of the factors influencing quality of epidemiological studies is given in annex A.
280. Cohort studies are typically established by constructing an exposed group and then finding areference group that is not exposed or has a materially lower level of exposure. Few dose measurement
databases exist where individual doses would be comprehensively recorded though such data sources
would be ideal. Dose monitoring of occupationally exposed radiation workers is the only setting wheresuch measurements are systematically available. Very large population-based cohort studies aimed at
representative population samples have been initiated in several countries recently—such as the United
Kingdom Biobank, and German and Danish national cohort studies—to assess the role of genetic andother factors in common diseases.
281. The Swiss study of childhood leukaemia and background radiation used a nationwide cohort, andillustrates the limitations of such an approach. The exposure levels were low and differences in exposure
within the study population narrow, limiting the power of the study. Information on several possible (butnot all) confounding factors was available but information on medical radiological exposure could not be
obtained. These features suggest that cohort studies may not be ideal research strategies. There are a few
populations with radiation doses from natural background radiation several times higher than the global
average but such high exposure levels occur in relatively small areas that do not have high-quality data
available on cancer incidence and mortality. Thus, large sample sizes would be needed, with a thousandcancer cases or more for accurate risk estimates at low dose levels.
282. Continued follow-up of existing studies, particularly Karunagappally, with cancer incidence data
and baseline survey on behavioural risk factors, is likely to yield improved estimates of cancer risk
from low-dose-rate radiation from natural sources. Future analyses should focus on individual cancer
types, such as leukaemia, for which estimated relative risks are large and for which residual
confounding may not be as serious an issue as for other cancers. Childhood leukaemia is an obvious
choice, as it has a high relative risk coefficient, and residual confounding is likely to be a lesser issue
than for other cancers due to both few well-established major risk factors and to the limited range of
exposure of children compared with that of adults.

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283. Pooling data from several studies conducted using comparable methods and data sources provides
one possibility of improving the precision of risk estimates. As stated in annex A, pooling data in ameta-analysis requires compatibility of the studies, which is best ensured by using a joint protocol or, atthe very least, being able to construct a minimum set of key data that are comparable across studies.
Pooled analysis* of individual-level data often provides the best comparability and, hence, most
uniform synthesis of study results with evaluation of dose response, which is a key objective in any
study aimed at radiation risk estimation.
284. Taking this information into account, the Committee concluded that key challenges for future
research could be summarized as:−

Improving individual dose estimates from all sources of exposure;−

Ensuring comprehensive and high-quality cancer registration;−

Enhancing tracing of loss to follow-up through death or migration in cohort studies;−

Improving control of confounding by key non-radiation risk factors;−

Developing and implementing improved methods (with user-friendly software) for
accommodating the impact of non-sampling errors, such as dosimetric uncertainties andresidual confounding, in risk estimates and hypothesis testing results.

VIII. CONCLUSIONS
285. This annex evaluated epidemiological studies reporting cancer risk per unit dose on the basis ofindividual cumulative doses from exposure to low-LET radiation from environmental sources. Inherent
limitations of epidemiological studies impede the precision of direct estimates in the very low dose
range. Nonetheless, studies of populations exposed to low-dose-rate radiation accumulating to levels,
where observable effects are anticipated, are highly valuable. The TRC study has demonstrated
dose-dependent increases in occurrence of solid cancer and leukaemia, though associations withradiation exposure were also found for cancer types that have not been commonly increased following
radiation exposure in other studies. No discernible increases were reported for solid cancer or
leukaemia in the Karunagappally or Yangjiang HNBR studies, though the low precision of the risk
estimates does not rule out either absence of an excess risk of cancer or substantially higher risks perdose unit than those reported in high-dose and dose-rate studies.
286. The five childhood leukaemia studies, except for the French GEOCAP-study, give largely
consistent, though not highly precise estimates of ERR per unit dose in the low dose range. However,since the confidence intervals are wide, it is difficult to confirm whether the ERR per unit dose issimilar to estimates obtained from studies of acute exposure such as the LSS.
287. Overall, the results of the studies of cancer risk due to radiation exposure at low dose rates fromenvironmental radiation do not provide strong evidence for materially lower risks per unit exposure
than in studies of high radiation doses and dose rates, though the findings are consistent with a range ofrisk estimates. The current results warrant a cautious interpretation of the magnitude of cancer risk perunit radiation exposure at low dose rates from environmental sources. The studies reviewed here haveshortcomings, such as small sample size and methodological weaknesses that limit the conjectures/conclusions that can be drawn from their results. In the future, nested case-control studies within these154 UNSCEAR 2017 REPORT

cohorts may be able to overcome some of the limitations. Longer follow-up with larger numbers ofcases can be expected to improve the precision of the results.
288. For solid cancer, the risk estimates from the three major studies in China, India and the RussianFederation can be regarded as consistent with each other due to large uncertainty partly related tostatistical imprecision, even if no increases in cancer rates could be demonstrated in HNBR studies,
unlike the TRC study. Dose estimation is always a major challenge in studies of environmental
radiation exposure, because it often requires retrospective reconstruction of residential history,
occupancy, and for internal exposure, amounts and sources of food and water intake. This isparticularly demanding when exposure levels have changed markedly over time, as in the Techa Riverregion. Hence, in addition to low statistical power due to the limited sample size relative to theanticipated magnitude of effect, further uncertainty stems from exposure measurement error that isoften not accounted for in the analysis. This can distort the results and, therefore, realistic estimation of
the amount of measurement error is important, particularly when it can be assumed to be substantial.
The TRC study is the only one that has yielded a precise estimate also for adult leukaemia andincorporated information on the health effects from internal exposure. It should be noted that the natureof exposure in the TRC study is different from that of the Karunagappally and Yangjiang studies. In the
TRC study, maximum internal and external exposure took place over one to two decades and decreasedmaterially with time, while the exposure in the two other studies was mainly external and lifelong.
289. Previous studies—including those on the Japanese survivors of the atomic bombings, and also
medical and occupational exposures—show that some cancer types are more strongly associated withradiation exposure than others. In the LSS, for example, the ERR per unit dose after childhood
exposure is materially higher for leukaemia than for solid cancers. Similarly, the ERR per unit dose forthyroid cancer in those exposed in childhood is materially higher than for other solid cancers. Although
the differences in risk estimates between solid cancer types are less striking in those exposed in
adulthood, there is major uncertainty in using a single estimates for all solid cancers combined forcomparisons across studies, because the background rates of various cancer types differ strongly acrosspopulations (for instance China, India and the Russian Federation) and the proportion of a cancer site of
all cancers affects the weight it has in the risk estimate for all cancers combined. Therefore, combining
all cancer types could result in mixing differing dose responses for various cancer types, with dissimilar
composition of the combined category of all cancer types between the study populations. All solidcancers combined comprise malignancies with different aetiology and risk coefficients per unit
radiation dose (including some that are not consistently linked to radiation) and, therefore, the estimatesobtained for risk coefficients of all solid cancers can differ between studies for these reasons alone.
Differences in radiation-related risk estimates across studies may also be due to the variations in risk
modifiers such as age, sex, and behavioural (e.g. tobacco and alcohol use) and genetic factors. Focusing
on specific cancer types would result in better comparability between studies and should be pursued,
although small numbers are likely to pose problems of interpretation.
290. Radiation exposure at low dose rates typically, although not necessarily, results in low doses and,
therefore, risk estimation can be readily affected by confounding from other cancer risk factors. This isan essential challenge in trying to detect a very small radiation effect from low doses against a sizable
background rate. This may add to the differences between study results, because the prevalence ofconfounders and their association with radiation exposure can vary. Also, inaccuracy in assessing
confounders leads to poorer ability to control for their effects. An analysis accounting for the effects ofconfounders also sets requirements for sample size in a study, which in itself might be constrained
when the entire exposed population is studied and cannot be increased. Precise and valid risk estimates
require sufficient follow-up, case ascertainment through high-quality cancer registry systems, andaccurate information on risk factors other than radiation exposure. This emphasizes the need forprospective long-term follow-up studies with high-quality dosimetry and accurate outcome data.

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155

291. In conclusion, the Committee recognizes that studies of low-dose-rate exposure fromenvironmental sources have potential to make a contribution to understanding radiation-induced cancer
risk. Direct evidence from such studies would be valuable because most radiation exposure in thegeneral population is obtained from low doses received over extended periods. However, improvements
would be needed to overcome the key limitations of these studies including low statistical power,
dosimetric uncertainties, imperfections in control of confounding, and any other biases. Studies of
low-dose-rate exposure are more susceptible to such limitations than studies of high dose exposure.
Differences in results of environmental radiation exposure studies may be due to problems in study
quality, including bias from under-ascertainment of cases (deaths or diagnoses), inaccurate cancer
diagnosis, imprecise dose assessment, and residual confounding. Further improvement in the quality ofsuch epidemiological studies could be achieved by improving the quality of clinical cancer diagnoses
and cancer registries, collecting accurate data on risk factors for specific cancer types and causes ofdeath, and improving dose estimation, to obtain reliable ERR estimates for specific cancer types andpopulation subgroups.

ACKNOWLEDGEMENTS
The Committee wishes to acknowledge with gratitude the work of the consultants and the Expert Groupon Epidemiological Quality involved in preparing this annex and especially J. Boice (United States) for
critically reviewing the manuscript. In particular, the Committee would like to thank A. Auvinen and
H. Zeeb (consultants), who elaborated this annex based on a draft prepared by S. Akiba (Japan). The
views expressed in the annex remain those of the Committee and do not necessarily represent the viewsof individual experts, the United Nations or its Member States.

Members of the Expert Group on Epidemiological Quality
P. Smeesters (Belgium); Q. Sun (China); A. Auvinen and S. Salomaa (Finland); W.-U. Müller,
R. Michel and H. Zeeb (Germany); S. Akiba, K. Kodama and S. Saigusa (Japan); M. Tirmarche(France), A. Akleyev and V. Ivanov (Russian Federation); R. Wakeford (United Kingdom); andJ. Boice, A. Bouville, B. Napier, D. Pawel and R. Shore (United States).

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