RADIATION RESEARCH 177, 229–243 (2012)0033-7587/12 $15.00
Ó2012 by Radiation Research Society.
All rights of reproduction in any form reserved.
DOI: 10.1667/RR2629.1

Studies of the Mortality of Atomic Bomb Survivors, Report 14, 1950–2003:
An Overview of Cancer and Noncancer Diseases
Kotaro Ozasa,a,1 Yukiko Shimizu,a Akihiko Suyama,a Fumiyoshi Kasagi,a,b Midori Soda,a Eric J. Grant,a Ritsu
Sakata,a Hiromi Sugiyamaa and Kazunori KodamacaDepartment of Epidemiology and cChief Scientist, Radiation Effects Research Foundation, 5-2 Hijiyama-koen, Minami-ku, Hiroshima, 732-0815,
Japan; and b Institute of Radiation Epidemiology, Radiation Effects Association 1-9-16, Kaji-cho, Chiyoda-ku, Tokyo, 101-0044, Japanno evidence of a radiation effect for infectious or externalcauses of death. Ó 2012 by Radiation Research Society

Ozasa, K., Shimizu, Y., Suyama, A., Kasagi, F., Soda, M.,
Grant, E. J., Sakata, R., Sugiyama, H. and Kodama, K.
Studies of the Mortality of Atomic Bomb Survivors, Report14, 1950–2003: An Overview of Cancer and Noncancer
Diseases. Radiat. Res. 177, 229–243 (2012).

INTRODUCTION

The Radiation Effects Research Foundation (RERF), andits predecessor the Atomic Bomb Casualty Commission(ABCC), has conducted a mortality study since 1950 on a
fixed population [Life Span Study (LSS) cohort] of about
120,000 subjects including atomic bomb survivors andresidents of Hiroshima and Nagasaki who were not in either
city at the time of the bombing to determine the late healtheffects of ionizing radiation derived from the atomic bombs
in Hiroshima and Nagasaki. Periodic analyses of the LSS
mortality data have resulted in a series of LSS Reports (1,2). This is the 14th report in the series, which covers theperiod 1950–2003, including an additional 6 years offollow-up since the last comprehensive report (2). The
impact of changing to the DS02 dosimetry system (3) fromthe earlier DS86 system on radiation risk estimates has beenreported for mortality from all solid cancer and leukemia
through 2000 (4). The risk of radiation for solid cancer
incidence through 1998 was also reported (5). However, thisis the first time the DS02 dosimetry system has been usedwhile examining mortality from a wide range of causes ofdeath.
The most important finding regarding the late effects of
A-bomb radiation exposure on mortality is an increased riskof cancer mortality throughout life (2). The rates of excess
solid cancer deaths have continued to increase in approximate proportion to radiation dose as the cohort ages.
Significant radiation-associated increases in risk have been
seen for most sites of solid cancer. The dose–response
relationship for these sites has tended to show anapproximately linear increase with radiation dose. The
relative risks for many cancer sites were higher in those
exposed as children. The relative risks declined withincreasing attained age of the subjects as well as thenumber of years after the bombing, although the excess
absolute rates continued to increase with attained age. In

This is the 14th report in a series of periodic generalreports on mortality in the Life Span Study (LSS) cohort ofatomic bomb survivors followed by the Radiation Effects
Research Foundation to investigate the late health effects of
the radiation from the atomic bombs. During the period
1950–2003, 58% of the 86,611 LSS cohort members with
DS02 dose estimates have died. The 6 years of additional
follow-up since the previous report provide substantiallymore information at longer periods after radiation exposure(17% more cancer deaths), especially among those under age
10 at exposure (58% more deaths). Poisson regression
methods were used to investigate the magnitude of theradiation-associated risks, the shape of the dose response, andeffect modification by gender, age at exposure, and attained
age. The risk of all causes of death was positively associatedwith radiation dose. Importantly, for solid cancers the
additive radiation risk (i.e., excess cancer cases per 104
person-years per Gy) continues to increase throughout life
with a linear dose–response relationship. The sex-averagedexcess relative risk per Gy was 0.42 [95% confidence interval(CI): 0.32, 0.53] for all solid cancer at age 70 years after
exposure at age 30 based on a linear model. The riskincreased by about 29% per decade decrease in age at
exposure (95% CI: 17%, 41%). The estimated lowest dose
range with a significant ERR for all solid cancer was 0 to 0.20
Gy, and a formal dose-threshold analysis indicated nothreshold; i.e., zero dose was the best estimate of thethreshold. The risk of cancer mortality increased significantly
for most major sites, including stomach, lung, liver, colon,
breast, gallbladder, esophagus, bladder and ovary, whereas
rectum, pancreas, uterus, prostate and kidney parenchyma
did not have significantly increased risks. An increased risk of
non-neoplastic diseases including the circulatory, respiratoryand digestive systems was observed, but whether these arecausal relationships requires further investigation. There was
1 Address for correspondence: Department of Epidemiology,
Radiation Effects Research Foundation, 5-2 Hijiyama-park, Minami-ku, Hiroshima, 732-0815, Japan; e-mail: ozasa@rerf.or.jp.

229

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OZASA ET AL.

TABLE 1
Number of LSS Cohort Members by DS02 Dose, City and Sex
Subjects with known DS02 dosea [weighted colon dose (Gy)]
Total
Hiroshima
Nagasaki
Male
FemaleTotal,0.0050.005

0.1

0.2

0.5

1.0

2.0þ

Unknownb

NICc

Total

86,61158,494
28,11735,68750,92438,50921,697
16,812
15,951
22,55829,961
22,733
7,228
12,342
17,619

5,974
5,037
937
2,382
3,592

6,356
5,067
1,289
2,482
3,874

3,424
2,373
1,051
1,414
2,010

1,763
1,152
611
813
950

624
435
189
303
321

7,058
3,442
3,616
3,287
3,771

26,52920,1796,350
11,143
15,386

120,32182,214
38,10750,17570,146Note. Among the total of 120,321subjects, 123 were unavailable for the study because of misidentification or insufficient information.
aThese numbers exclude the NIC and unknown-dose groups. This group was used for estimating radiation effects.
b
Those with unknown doses had insufficient location information or were in complex shielding situations where dose could not be estimatedreliably.
c
NIC: Not in the cities of Hiroshima or Nagasaki at the time of bombing.

contrast, the risk of leukemia increased in the early period
after the bombing and then decreased, and the dose–
response relationship for leukemia showed a linearquadratic association (6, 7). Those different onset anddose–response patterns imply a different pathogenesis
between leukemia and solid cancer.
This report provides an overview of the updated results
and characterizes the risk of radiation based on the DS02
dosimetry system for total deaths and major causes of death
including solid cancer, leukemia and various types of
noncancer disease. Due to the elongation of the follow-up
period compared to the previous reports and the consequent
increased number of outcomes, new findings have emerged
for the risks of radiation for cancer and noncancer diseasemortality. The purpose of this report is to (1) compare themortality from a wide range of causes of death using acommon model as an overview, (2) conduct more detailed
analyses on dose–response relationships and effect modification by age at exposure and attained age, and (3) describechanges in the shape of the dose response for solid cancer
and noncancer diseases over the long observation period. A
discussion on the effects at low exposure levels such as doseand dose-rate effectiveness factor (DDREF) was also
included. For leukemia, since detailed analyses haverecently been reported for mortality over the period 1950–
2000 based on the DS02 dosimetry system (7), further
detailed analyses were not conducted.
MATERIALS AND METHODS
Study Population and Follow-Up
The LSS cohort includes a large portion of the atomic bomb
survivors who were within 2.5 km of the hypocenters at the time of thebombings, together with an age- and sex-matched sample of people
who were between 2.5 and 10 km from the hypocenters. The cohort
also includes a sample of about 26,000 persons who were registered as
residents of either Hiroshima or Nagasaki in 1950 but were not in thecities (NIC) at the time of the bombings. LSS Report 8 and the later
LSS reports have excluded the NIC group from analyses of radiation
risk because of concerns about the comparability of their mortality
rates to those for other zero-dose cohort members, likely due tosociodemographic or other differences (1, 8, 9). The subjects wererecruited from the 1950 Japanese National Census, which had asupplementary questionnaire about A-bomb exposures, plus two
surveys conducted by the Atomic Bomb Casualty Commission(ABCC) in 1950 and 1951, and the resident surveys by Hiroshima
and Nagasaki cities in 1953 and 1950, respectively (1). Comprehensive mortality follow-up began on October 1, 1950 (1). The final
number of subjects was 120,321 members (82,214 in Hiroshima and38,107 in Nagasaki) (10). Among them, 123 subjects were unavailable
for the study and were excluded from the analyses because of
misidentification or insufficient information. Individual DS02 dose
estimates are available for 86,611 survivors. Another 7,058 survivors
do not have dose estimates, mainly due to insufficient or uncertain
information on location and shielding at the time of the bombing, andwere excluded from these analyses (11). The total number of subjects
and the distribution of DS02 dose categories by city and sex are shownin Table 1.
Mortality follow-up was facilitated by the family registry system(koseki), which covers the whole of Japan and is .99% complete. A
small number were lost to follow-up due to migration out of thecountry and were censored at the time of emigration. In this report,
follow-up data until December 31, 2003 were analyzed. We found 19
individuals who were born before 1900 and presumed to be alive by
the koseki as of January 1, 2004 (104 years of age or older). They werechecked at municipal office registries: five were documented as alive,
six migrated to other countries, seven were deleted from the residence
registries because the municipality offices could not confirm theirresidence status, and no information was obtained for one person. The
six individuals who migrated overseas were treated as censored at thetime of migration. The seven individuals who were deleted fromresidence registries were treated as deceased at the time of deletion due
to unknown causes. The one with no information was treated as
censored at the end of the follow-up.
Cause of death for the subjects was classified by trained staff in the
ABCC/RERF according to the International Classification of Diseases(ICD), 7th to 10th editions (12–15). The list of disease categories,
corresponding ICD numbers, and applicable years are shown in the
Appendix found on page 243. We analyzed all solid cancer, cancer ofmajor sites, hemato-lymphoid malignancies, and broad classificationsof noncancer diseases including diseases of the blood and bloodforming organs, circulatory system, respiratory system, digestivesystem, and genitourinary system, infectious and parasitic diseases,
and external causes.
Dosimetry
This report is the first to apply DS02, which includes a number of
improvements over the previous system (3, 11), to the mortality
experience from a wide range of causes of death in the LSS Reportseries. The primary systematic change effected by DS02 was anincrease of about 10% in c-ray estimates for both Hiroshima andMORTALITY OF ATOMIC BOMB SURVIVORS, 1950–2003

Nagasaki, consequently causing the estimated risks from radiation
exposure to be slightly lower than before (4). Weighted dose, which isthe sum of the c-ray dose plus 10 times the neutron dose, was used toallow for the greater biological effectiveness of neutron doses and isexpressed in units of gray (Gy). Although the relative biologicaleffectiveness (RBE) of neutrons is thought to be a decreasing functionof dose, with values possibly higher than 10 at low doses, we could
not precisely estimate the neutron RBE for the atomic bombs ofHiroshima and Nagasaki. Therefore, we used a constant RBE of 10,
which has been used previously (6, 27).
DS02 includes calculated doses for 15 organ sites. In keeping withpast reports, analyses of all solid cancer used colon dose as
representative for all organs, while those of hemato-lymphoidmalignancies used the dose to bone marrow. Analyses for site-specificcancers and noncancer diseases of major organs used corresponding
specific organ doses. For individual dose estimates, shielded kerma
estimates above 4 Gy (317 members) were truncated to 4 Gy because
they are likely to represent misinformation on exposure factors such as
shielding or exact location. To correct for dose uncertainties due torandom measurement error, unadjusted DS02 estimates were replacedby expected survivor dose estimates using the method developed by
Pierce et al. (16) and assuming 35% measurement error in individual
doses.
Statistical Methods and Organization of Data for Analysis
Poisson regression methods for grouped survival data were used todescribe the dependence of risk on radiation dose and to evaluate thevariation of the dose response with respect to city, sex, age at
exposure, and attained age (17). Significance tests and confidence
intervals (CI) were based on likelihood ratio statistics. The results
were considered statistically significant when the two-sided P , 0.05.
The models used here, which were also used in previous reports (2,5), are as follows.
Excess Relative Risk (ERR) model:
k0 ðc; s; b; aÞ½1 þ ERRðd; s; e; aÞ;
Excess Absolute Risk (EAR) model:
k0 ðc; s; b; aÞ þ EARðd; s; e; aÞ;
where k0 is the baseline or background mortality rate at zero dose,
depending on city (c), sex (s), birth year (b), and attained age (a). k0
was modeled by stratification for the ERR model and by parametricfunction involving relevant factors for the EAR model. ERR or EAR
depends on radiation dose (d) and, if necessary, effect modification bysex, age at exposure (e), and attained age. In effect, the ERR and EAR
functions are described as parametric functions of the formq(d)e(e,s,a), in which q(d) describes the shape of the dose–response
function and e(s,e,a) describes the effect modification.
First, we estimated ERR for major causes of death using a linear
dose–response model (L) (q(d) ¼ b1d) without effect modification
because this simple model can be applied to most cancer sites tocompare them in a common way. The ERR model is as follows:
k0 ðc; s; b; aÞ½1 þ b1 d:For leukemia, a linear-quadratic model (LQ) (q(d) ¼ b1d þ b2d2) wasused since previous LSS reports have indicated that it had the bestdose response for leukemia among the LSS (4, 7).
Next, we took account of effect modification by sex, age at
exposure, and attained age in the linear dose model for ERR and EAR,
respectively, for all solid cancer and cancer of selected sites because
the model can estimate the radiation risks more accurately and also canbe applied to selected major sites with sufficient numbers of excess
cases. Effect modification was described using multiplicative-function
models as follows:231eðe; s; aÞ ¼ expðse þ t lnðaÞÞð1 þ rsÞ;where s, t and r were the coefficients for effectmodification by age at exposure, attained age, and sex,
respectively. The term that includes sex (s ¼ 1 for men and s¼ 1 for women) as a modifier allows the b1 parameter torepresent sex-averaged risk estimates. Therefore, ERR andEAR models were, respectively,
k0 ðc; s; b; aÞ½1 þ b1 d  expðse þ t lnðaÞÞ  ð1 þ rsÞ;k0 ðc; s; b; aÞ½b1 d  expðse þ t lnðaÞÞ  ð1 þ rsÞ:In addition to the simple L model, we have considered LQ and pure
quadratic (Q) (q(d) ¼ b2d2) models with effect modification (by sex,
age at exposure, and attained age) for all solid cancers. The curvatureof the dose response was examined using the ratio of the quadratic andlinear coefficients (h ¼ b2/b1) in the LQ model. h can range from zerofor a pure linear model to infinity for a pure quadratic model.
To evaluate the radiation effects in limited dose ranges, the ERRs
for all solid cancer for selected dose ranges were estimated based on
the linear model with effect modification by sex, age and age at
exposure [ERR ¼ (bld þ bhd) exp(s e þ t ln(a)  (1 þ r s))], where bld
is the coefficient for the lower dose range and bhd for the higher dose
range. Coefficients for the effect modification terms were common to
the two parts of the dose range. The lowest dose range with astatistically significant ERR dose response for all solid cancer was
estimated by testing the null hypothesis that the low-dose slope waszero by stepping up the cut point by 0.01 Gy. Threshold doses for all
solid cancer were also estimated using the linear model as q(d) ¼ b1(d– d0) for d . d0 or q(d) ¼ 0 for d  d0, where d0 was the threshold, andadjusted for sex, age and age at exposure with modification by sex,
age and age at exposure. A wide range of possible values for d0 were
examined by stepping up by 0.01 Gy, and the point with the greatest
maximum likelihood value was determined. The minimum deviance
was used to determine the dose threshold and the dose yielding adeviance of the minimum plus 3.84 (which corresponds to v2 1 degreeof freedom cutoff point) determined its upper and lower 95% CI. If thelower limit of the 95% CI of the threshold exceeded 0 Gy, we would
conclude that a threshold exists, while the upper limit indicates the
maximum threshold value that is compatible with the data.
It has been suggested that the LSS cohort constructed in 1950
suffers from selection bias in that members of the cohort who survived
from the time of bombings to 1950 may have been healthier and hence
more resistant to the radiation effects (2, 18). To investigate this effect,
the dose–response relationships of noncancer diseases were evaluatedusing an LQ model without effect modification for both the early
period of follow-up (1950–1965) and the later period (1966–2003)
using an ERR model. For reference, the same analysis was also
conducted for all solid cancer using the linear-quadratic model witheffect modification by sex, age at exposure, and attained age.
Attributable fractions were estimated from the numbers of radiationassociated excess deaths and the corresponding total numbers ofdeaths from solid cancer and noncancer diseases except for nonneoplastic blood diseases based on the linear ERR model with effectmodification by sex, age at exposure, and attained age to allow
comparisons between the two classes of outcomes. CIs for estimatingexcess deaths were estimated by the multivariate delta method.
Analyses are based on detailed tabulations of the data crossclassified by city, sex, age at exposure, attained age, follow-up period,
and radiation dose. The categories of age at exposure were 5-year
categories for ages 0 through 69 and 70 or more. Attained age wascategorized by 5-year intervals for ages 5 though 99 plus 100 or more.
The dose category cut points were 0.005, 0.02, 0.04, 0.06, 0.08, 0.1,
0.125, 0.15, 0.175, 0.2, 0.25, 0.3, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0,
2.5 and 3 Gy. The follow-up period was divided into 5-year intervals.

232

OZASA ET AL.

TABLE 2
Observed Person-Years and Number of Deaths in the LSS Cohort Members with Known DS02
Doses, as of January 1, 2004, by Age at Exposure
Age at exposure(years)
0–9
10–19
20–29
30–39
40–49
50þ
Total

Number of
subjects

Observed
person-years

Number ofdeathsa

Alive

17,833
17,563
10,891
12,27013,504
14,55086,611

910,347
848,826
494,021462,694
365,240
213,079
3,294,210

2,200
4,887
5,178
10,41013,397
14,54850,620

88%
72%
52%
15%
1%
0%
42%

a
These numbers do not include the subjects who were NIC, unknown dose, or censored because of deletionfrom koseki by municipality offices and other reasons.

The basic data for each cell in the tabulations were the number ofdeaths for specific causes and time at risk in terms of person-years.
The cell-specific mean values were included for c-ray and neutron
dose and each age/time variable. Parameter estimation and tests werebased on likelihood using Epicure software (19). When the lower limit
was not estimable, an implicit lower bound on the ERR was thought tobe 1/d_max, where d_max was the maximum individual dose.

RESULTS

Among the 86,611 subjects with estimated DS02 doses,
50,620 subjects (58%) died in the follow-up period (Table2). While 99.6% of those who were exposed to A-bombradiation at age of 40 years or older had died, fully 80% of
those under age 20 at that time were still alive. The numbersof subjects who died of specific causes of death is shown in
Table 3. Twenty-two percent of deaths were due to solidcancer, 1.4% to lymphoid and hematopoietic malignancies,
71% to non-neoplastic diseases, and 5% to external causes.
Site-Specific Cancer Excess Risks

Radiation risks for major causes of death, including major
cancer sites, are shown in Fig. 1 (ERRs in the simple L
model). The ERR per Gy (ERR/Gy) for total deaths was
statistically significant, 0.22 (95% CI: 0.18, 0.26). Also therisk estimate for all solid cancer was 0.47 (95% CI: 0.38,0.56). The highest ERR was observed for cancer of the renal
pelvis and ureter, then cancers of the breast (female only),
other digestive system, bladder, ovary (female only), lung,colon, esophagus, gall bladder, liver and stomach indescending order, although the CIs for these estimates
overlapped considerably. The ERR estimate for renal pelvis
and ureter was notably unstable because of the small
number of cases. Other cancers such as rectum, pancreas,
uterus (female only), prostate (male only), or kidneyparenchyma did not have significantly increased risks.
Sex-specific ERRs along with 95% CIs are shown in
Table 3. The sex-specific ERR/Gy in females was around
twice as high as that in males for both total deaths and allsolid cancer. The ERRs for cancers of most sites were also
higher in females. There were some notable differences in

the magnitude of radiation effects between sexes. Cancer ofthe gallbladder and renal pelvis and ureter had increased
risks in males but not in females, whereas cancers of thestomach, rectum and other digestive diseases showed
increased radiation risk in females but not in males;
however, the CIs for males and females overlapped in allcases.
The sex-averaged ERR of leukemia was 3.1 (95% CI: 1.8,
4.3) at 1 Gy and 0.15 (0.01, 0.31) at 0.1 Gy in the LQ
model. However, the ERR was not significant for malignant
lymphoma or multiple myeloma (Fig. 1). There were someapparent sex differences; namely, there were significant
increases for malignant lymphoma in males only and for
multiple myeloma in females only (Table 3).
The estimates of effect modification of the ERR by sex,
age at exposure, and attained age are shown in Table 4 forall solid cancer and cancer of the selected major sites. The
left column shows the sex-averaged ERR/Gy for the
subjects at an attained age of 70 years after exposure at
the age of 30. The right columns show the parameter
estimates of the effect modifiers. The ERR/Gy for females
was around two times higher than males and the ratios weresignificantly greater than unity for all solid cancer andcancers of the stomach and lung. The ERR/Gy for solidcancer declined 29% per 10-year increase of age at
exposure and also declined in proportion to the 0.86 powerof attained age, and both effect modifiers were significant,as illustrated in Fig. 2. The age effects for cancers ofspecific sites were similar to those for all solid cancer, but
most were not statistically significant.
The estimates for the same cancers using the EAR model
are shown in Table 5 (three sites were omitted because ofnonsignificant results in the ERR or effect modification
terms in Table 4). The left column shows the sex-averaged
EAR/104 person-years/Gy. The right columns show theparameter estimates of effect modifiers. There were no sex
differences in EAR for all solid cancer or for major
individual types of cancer. The EAR significantly declined
19% per 10-year increase in age at exposure for all solidcancer, as illustrated in Fig. 3. Estimates for specific cancer

MORTALITY OF ATOMIC BOMB SURVIVORS, 1950–2003

233

FIG. 1. Estimates of excess relative risk (ERR) per Gy and 95% CI for major causes of death. a ERR was estimated using the linear dose model,
in which city, sex, age at exposure, and attained age were included in the background rates, but not allowing radiation effect modification by thosefactors. b Confidence interval. Horizontal bars show 95% confidence intervals. c The size of plots for site-specific cancers was proportional to thenumber of cases. d ERR (95% CI) of leukemia was 3.1 (1.8, 4.3) at 1 Gy and 0.15 (0.01, 0.31) at 0.1 Gy based on a linear-quadratic model with
318 cases (not displayed in the figure). e The lower limit of 95% CI was lower than zero, but not specified by calculation.

234

OZASA ET AL.

TABLE 3
Number of Deaths, Excess Relative Risk (ERR) Estimates per Gy for Specific Causes of Death by Sex

Cause of death
All causes
CancerAll solid cancer
Esophagus
StomachColon
RectumLiver
Gallbladder
Pancreas
Other digestivesystemLung
BreastUterus
Ovary
Prostate
Bladder
Kidney parenchyma
Renal pelvis andureterOther
Lymphoid andhematopoietic
malignancies
Leukemia
Malignant lymphoma
Multiple myeloma
Other neoplasms
Non-neoplastic diseases
Blood diseases
Circulatory disease
Respiratory disease
Digestive disease
Genitourinary
diseaseInfectious disease
Other disease
External causes

Based onradiationdose to:Males

FemalesNumber ofdeaths

ERR/
Gya

P

Number ofdeathsERR/
Gya(95% CIb)(95% CIb)

P

Colon

22302

0.15

(0.10, 0.20),0.001

28318

0.30

(0.24, 0.35),0.001

Colon
StomachStomachColon
Bladder
Liver
Liver
Pancreas

5235
260
1689
262
199
879
121
210

0.31
0.39
0.13
0.50
–0.26
0.30
0.85
0.22

(0.21, 0.42)(0.006, 0.97)(0.02, 0.30)(0.09, 1.09)(NAc, 0.19)(0.08, 0.58)(0.19, 1.9)
(0.17, 0.83)(NAc, 2.33),0.001
0.054
0.09
0.01
0.18
0.006
0.005
0.33

5694
79
1436
359
228
640
298
303

0.66
1.1
0.51
0.58
0.66
0.46
0.23
–0.06

(0.52, 0.80)(0.04, 3.0)
(0.28, 0.78)(0.16, 1.1)
(0.06, 1.5)
(0.15, 0.85)(0.12, 0.76)(NAc, 0.43),0.0010.04,0.001
0.003
0.03
0.002
0.24
.0.5

Colon
Lung
BreastUterusOvary
Bladder
Bladder
Colon

33
901
6
–
–
130
100
42

0.26
0.40
9.1

(0.17, 0.67)(0.52, 128).0.5
,0.001
0.01

2.6
1.1
1.5
0.22
0.79

(0.51, 6.6)
(0.68, 1.6)
(0.93, 2.3)
(0.09, 0.64)(0.07, 1.9)

0.005
,0.001,0.001
0.19
0.03

0.33
0.88
0.11

(NAc, 1.2)
(0.02, 2.3)
(NAc, 1.4)

0.30
0.04
.0.5

51
657
324
547
157
–
83
38

1.5
1.5

(0.21, 3.8)
(0.01, 4.9)

0.02
0.049

Colon
Colon

13
390

3.5
0.36

(0.25, 14)(0.02, 0.83)

0.02
0.04

20
474

1.9
0.54

(NAc, 8.0)
(0.14, 1.0)

0.13
0.005

Bone marrow
Bone marrow
Bone marrow
Colon

163
125
34
224

4.6
0.70
0.11
0.30

(3.0, 6.9)
(0.08, 1.7)
(NAc, 1.6)
(0.10, 0.88),0.001
0.02
.0.5
0.17

155
159
59
294

3.9
–0.18
0.86
1.1

(2.5, 6.1)
(0.21, 0.24)(0.02, 2.5)
(0.44, 2.0)

,0.0010.33
0.04,0.001Bone marrow
Colon
Colon
Colon

80
7607
2401
1659

1.8
0.07
0.16
0.05

(0.68, 3.8)
(0.001, 0.16)(0.02, 0.31)(0.09, 0.23),0.001
0.053
0.02
0.50

158
11447
2718
1735

1.6
0.14
0.28
0.18

(0.76, 2.8)
(0.06, 0.23)(0.11, 0.47)(0.01, 0.40),0.001,0.001,0.001
0.07

Colon
Colon
Colon
Colon

449
1043
1830
1372

–0.07
0.01
0.03
–0.24

(NAc, 0.28)(0.16, 0.22)(0.12, 0.21)(NAc, 0.11)

.0.5
.0.5
.0.5
0.001

860
919
3017
1060

0.28
–0.07
–0.01
0.14

(0.01, 0.62)(NAc, 0.18)(0.15, 0.15)(0.07, 0.41)

0.04
.0.5
.0.5
0.21

a
ERR was estimated using the linear dose model, in which city, age at bombing, and attained age were included in the background rates, but
not as radiation effect modifiers.
b
The lower limit was not estimable, but an implicit lower bound (1/d_max) was 0.28 for males and 0.27 for females (see text).

sites tended to be similar, but most were not significant. The
EAR significantly increased as the 3.4 power of attained age
as an effect modifier for all solid cancer and alsosignificantly increased for cancer of major sites (Table 5).
The fits of the L, LQ and Q models were compared for all
solid cancer in the full dose range (left columns of Table 6).
They did not show a significant difference of deviances
between the L and LQ models (P ¼ 0.36), indicating that aquadratic term was unnecessary. The Q model had asignificantly worse model fit than the L or LQ models.
Furthermore, the L model showed the smallest Akaike
Information Criterion (AIC) (20), the LQ model had a 1.2point larger value than the L model, and the Q model was

23.7 points larger, again indicating that it provided thepoorest fit. Those differences were calculated from thedeviances in Table 6. Consequently, the L model was
selected as the best model in the full dose range. Figure 4
shows the estimated plots of dose dependence according to
the L and LQ functions.
Although the linear model provided the best fit in the full
dose range, statistically significant upward curvature wasobserved when the dose range was limited to 0–2 Gy (h ¼0.81, P ¼ 0.02) (Tables 6 and 7). The curvature over the 0–
2-Gy range has become stronger over time, going from h ¼
0.20 for the period 1950–1985 to 0.81 for 1950–2003, andhas become significant with longer observation (Table 7).

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MORTALITY OF ATOMIC BOMB SURVIVORS, 1950–2003

TABLE 4
Effect Modification of the Excess Relative Risk (ERR) Modela for Major Cancers
Sex (r)Age at exposure (s)Sex-averaged ERR/Gyb (ERR ratio: female/male) (Percentage change per 10-year increment) Attained age (t) (power)(95% CIc)
All solid cancer
Esophagus cancer
Stomach cancer
Colon cancer
Liver cancer
Gallbladder cancer
Lung cancer
Breast cancerd
Bladder cancer
Ovary cancer

0.42
0.60
0.33
0.34
0.38
0.48
0.75
0.90
1.19
0.20

(0.32, 0.53)(NA, 1.64)(0.17, 0.52)(0.05, 0.74)(0.11, 0.62)(0.12, 1.02)(0.51, 1.03)(0.30, 1.78)(0.27, 2.65)(NA, 1.30)(95% CI)
2.1
4.3
3.7
1.4
1.6
0.42
2.7
–
1.7
–

(1.4, 3.1)
(0.54, .100)(1.3, .100)(0.39, 6.6)
(0.43, 7.9)(,0.001, 2.4)
(1.3, 6.8)–
(0.2, 9.0)–

(95% CI)
29%
35%
18%
3%
8%
27%
–7%
45%
2%
22%

(41%, 17%)(28%, 184%)(47%, 20%)
(51%, 63%)(62%, 42%)
(76%, 40%)
(35%, 29%)
(67%, 17%)(62%, 92%)
(96%, 218%)(95% CI)
0.86
–3.7
0.74
5.8
0.02
1.9
–0.04
0.17
0.49
4.1

(1.60, 0.06)(9.6, 1.0)
(2.5, 1.2)
(10.4, 2.2)(2.8, 4.2)
(6.6, 7.8)
(2.2, 2.6)
(2.7, 2.3)
(3.6, 6.1)
(33, 1.9)

a
The ERR model was defined as k0(c,s,b,a) [1 þ b1d  exp(s e þ t ln(a))  (1 þ r s)], where d is dose, s is sex, b is birth year, e is age at
exposure, and a is attained age. s, t and r are coefficients for effect modification.
b
The sex-averaged ERR/Gy is shown for subjects at the attained age of 70 years after exposure at age 30.
c
95% confidence interval.
dFemale only.

However, the estimated ERRs under 0.3 Gy were nominallyhigher than the best-fitting linear slope or the LQ function
for either 0–2 Gy or the full dose range in Fig. 4. A
quadratic-spline function with a knot at 0.2 Gy that allowed
higher estimates at the low-dose level did not provide asignificantly better fit than the LQ function (P ¼ 0.16). It
was particularly notable that the ERR/Gy estimates forlinear functions calculated for various low-dose ranges
showed higher values for ranges less than 0.1 Gy comparedto estimates obtained from higher dose ranges (Fig. 5), i.e.,the slope was not shallower in the low-dose range than athigh dose levels.
The lowest dose range with a significant ERR for all solidcancer was 0 to 0.20 Gy with an estimated ERR/Gy of 0.56
(95% CI: 0.15, 1.04, P ¼ 0.01) and included 74,444 persons
with 9,063 solid cancer deaths. For the range of 0 to 0.18,
the ERR/Gy was 0.43 (95% CI: 0.0047, 0.91, P ¼ 0.052)
and included 8,920 deaths (Fig. 5). The maximum
likelihood estimate of a dose threshold was 0.0 Gy (i.e.,no threshold) with an estimated upper bound of 0.15 Gy for
95% CI as determined by minimizing the deviance.
Noncancer Disease Excess Risks

FIG. 2. Modification of the excess relative risk (ERR) for all solidcancer by age at exposure and attained age.

The risks were significantly elevated for non-neoplastic
diseases of the blood (ERR/Gy ¼ 1.7, 95% CI: 0.96, 2.7),
circulatory system (0.11, 95% CI: 0.05, 0.17), andrespiratory system (0.21, 95% CI: 0.10, 0.33). Among thenonmalignant respiratory diseases, the risk of pneumonia
and influenza was significantly elevated (ERR/Gy ¼ 0.24,
95% CI: 0.10, 0.40, with 3,244 deaths). Other nonneoplastic diseases including infectious diseases did notshow any increased radiation risk in either sex except for
genitourinary diseases in females. There were no doserelated excess mortality risks from external causes (Fig. 1,
Table 3).
As for the changes in dose response over the long followup period, the risks of circulatory, respiratory and digestive
diseases were all significantly elevated during the period
after 1965 (Table 8). The risk of pneumonia and influenza
was also higher in the latter period (ERR/Gy ¼ 0.25, 95%
CI: 0.10, 0.43), but liver cirrhosis, a major digestive disease,
did not show any increased radiation risk during the whole
period or for the period after 1965 (ERR/Gy ¼ 0.11, 95%
CI: 0.07, 0.34 and 0.17, 95% CI: 0.04, 0.42, respectively).

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OZASA ET AL.

TABLE 5
Effect Modification of the Excess Absolute Risk (EAR) Modela for Major Cancers
Sex-averaged EAR/
104 PY/Gyb

Sex (r) (EAR ratio:
female/male)c(95% CI)(95% CI)All solid cancer
Stomach cancer
Colon cancer
Liver cancer
Lung cancer
Breast cancerd
Bladder cancer

26.4
4.1
1.6
3.4
6.5
2.3
1.2

(20.3, 32.8)(2.1, 6.7)
(0.5, 3.0)
(0.7, 5.9)
(4.3, 9.0)
(1.0, 3.8)
(0.3, 2.4)

Age at exposure (s)(Percentage change per 10-year increment)

1.1
1.8
0.98
0.69
0.78
–
0.40

(0.80, 1.74)(0.66, 32)(0.34, 4.5)
(0.19, NA)(0.40, 1.8)–
(0.0, 5.3)

Attained age (t) (power)(95% CI)
–19%
18%
–30%
–25%
–16%
–51%
–1%

(31%, 7%)
(18%, 62%)
(58%, 2%)(66%, 15%)
(37%, 6%)(68%, 30%)(65%, 80%)(95% CI)
3.4
2.0
3.2
6.0
6.2
3.0
7.5

(2.7, 4.1)
(1.0, 3.6)
(1.3, 5.3)
(3.2, 12)
(4.5, 8.2)
(1.7, 4.7)
(3.1, 15)The EAR model was defined as k0(c,s,b,a) þ b1d  exp(s e þ t ln(a))  (1 þ r s), and parameters are indicated in Table 4.
The sex-averaged EAR/104 person-years/Gy is shown for subjects at the attained age of 70 years after exposure at age 30.
c
95% confidence interval.
dFemale only.
ab

The dose–response relationships of noncancer diseasemortality for the early period (1950–1965) and late period(1966–2003) of follow-up are shown in Fig. 6. The
relationship for the early period (dotted line) showedessentially no radiation effect below about 1.5 Gy whilethat for the late period showed an approximately linear
dose–response relationship for noncancer diseases as awhole, and the difference in shapes was significant between
the periods (panel A, P ¼ 0.02). Among noncancer diseases,
circulatory diseases did not show a difference between the
periods (panel B, P , 0.05), but both respiratory anddigestive diseases showed marginal differences between
periods (panel C, P ¼ 0.07 and panel D, P ¼ 0.06,
respectively), and the temporal difference for all solidcancers was not significant (Panel E, P ¼ 0.18). A
comparison between L and LQ fit for each period showedthat the LQ function fit significantly better in the early
period for total noncancer diseases (P ¼ 0.04) but not for thelate period (P ¼ 0.29). A similar pattern was found forrespiratory diseases (P ¼ 0.01 and P ¼ 0.35, respectively).
There were no differences between the L and LQ fits ineither period for circulatory diseases (P ¼ 0.23 for the earlyand P . 0.5 for the later), digestive diseases (P , 0.5 and P¼ 0.22, respectively), or solid cancer (P , 0.5 and P ¼ 0.39,
respectively).
Estimates of the numbers of radiation-associated excess
deaths in the LSS between 1950 and 2003 are shown in
Table 9. The excess deaths of solid cancer were estimated as
527 (95% CI: 157, 899). About 8.3% (¼525/6308) (95% CI:
2.6%, 14%) of the deaths among cohort members withcolon dose of 0.005 Gy or higher (mean dose of 0.2 Gy)
appeared to be associated with radiation. The percentages
attributable to radiation were 5.8%, 13%, 25%, 35% and
57% at dose ranges of 0.1–0.2, 0.2–0.5, 0.5–1, 1–2 and 2
Gy and higher (the person-year-weighted mean doses were
0.14, 0.31, 0.72, 1.4 and 2.5 Gy), respectively. The excess
deaths for noncancer diseases were estimated as 353 (95%
CI: 252, 958) using the ERR model with effect modifiers.
About 1.8% (95% CI, 1.2%, 4.8%) among those withcolon dose of 0.005 Gy or higher appeared to be associatedwith radiation. The value was 1.9% (95% CI, 1.2%, 2.7%)
when the ERR model without effect modifiers was usedbecause those effect modifiers were estimated less precisely
due to small ERRs and high background rate.
DISCUSSION

FIG. 3. Modification of the excess absolute risk (EAR) for all solidcancer by age at exposure and attained age.

The most important finding regarding the late effects of
A-bomb radiation exposure on mortality is an increased riskof cancer mortality throughout life (2). The current data
showed that the risk for all solid cancer deaths has
continued to increase throughout the survivors’ lifetimes
in approximate proportion to radiation dose. The sexaveraged relative excess of solid cancer deaths was 42% per
Gy at age 70 years after exposure at age 30 based on a linear

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MORTALITY OF ATOMIC BOMB SURVIVORS, 1950–2003

TABLE 6
Parameter Estimates of the Dose–Response Models for Excess Relative Risk (ERR) for all Solid Cancer in the Full Dose Rangeand for the Range of 0–2 Gy
,2 Gy

Full
Dose range modela
b1: linear
b2: quadratic
Effect modification
r: sex (female ¼ 1; male ¼ 1)
s: age at exposure (year)t: attained age (log(age/70))
Deviancedf
Test (vs. LQ model )

Lb

LQ

Q

L

LQ

Q

0.42
–

0.36
0.038

–
0.22

0.44
–

0.22
0.18

–
0.33

0.34
–0.035–0.86
18301.253147
P ¼ 0.36

0.35–0.034–0.86
18300.4
53146
–

0.40
–0.035–0.90
18324.953147
P , 0.001

0.28–0.033–0.84
17557.349577
P ¼ 0.02

0.29–0.034–0.89
17551.6
49576
–

0.29
–0.035–0.97
17557.249577
P ¼ 0.02

Note. Bolded columns are the selected models.
a
The ERR model was defined as k0(c,s,b,a) [1 þ q(d)  exp(s e þ t ln(a))  (1 þ r s)], where d is colon dose, s is sex, b is birth year, e is age at
exposure, and a is attained age. q(d) was b1d for the linear model, b1d þ b2d2 for the linear-quadratic model, and cd2 for the quadratic model. s, t
and r are coefficients for effect modification.
b
L: linear, LQ: linear-quadratic, Q: quadratic.

model with effect modification by age at exposure andattained age. The sex-averaged excess death rate of all solidcancer was 26/10,000 person-years per Gy under the same
conditions. The second important finding is that those who
were exposed at younger ages had a higher relative risk forcancer death; e.g., the sex-averaged ERR of solid cancer
deaths was 0.83 at age 70 in those who were exposed at 10
years of age compared with 0.30 in those exposed at age 40.
For solid cancers the relative risk declined with increasing
attained age of the subjects as well as years after thebombing, although, importantly, the excess absolute rates
continued to increase with attained age and the rates werehigher in those exposed at younger ages among those withthe same attained age. These findings suggest that young
people are more sensitive to radiation than older people,
possibly at the initiation stage in carcinogenesis at the timeof exposure, and imply an overall increase in lifetime risk
for those exposed at younger ages.
To provide continuity, the methods of analysis and risk
indicators are the same as those in previous reports since1987 (2, 10). In a previous report, mortality data up to 2000
were examined for changes in the estimated risk of radiation
due to changes in dosimetry between DS86 and DS02 (4).
In that report the estimates of solid cancer risk per unit
radiation dose decreased about 8% due to the upwardrevision in the c-ray dose estimates (4). The ERR/Gy for all
solid cancer decreased from 0.45 based on DS86 to 0.42
based on DS02 for 1950–2000 (4). The estimates of ERR/
Gy and modifiers for solid cancer in this study (Table 4)
were similar to those in the latter report (4). The effectmodification results showed substantially similar tendencies
to previous estimates using DS86 and less follow-up time(2,5).
Effect modification was evaluated for the ERR (Table 4)
and EAR (Table 5) models. The ERR estimates were
TABLE 7
Change in Dose–Response Curvature For Excess Relative
Risk (ERR) of Solid Cancer in The range of 0–2.0 Gy by
Observation PeriodaCurvature (h)95% CIb
Significance (P)cFIG. 4. Excess relative risk (ERR) for all solid cancer in relation toradiation exposure. The black circles represent ERR and 95% CI for
the dose categories, together with trend estimates based on linear (L)with 95% CI (dotted lines) and linear-quadratic (LQ) models using thefull dose range, and LQ model for the data restricted to dose ,2 Gy.

1950–1985

1950–1995

1950–2003

0.20(0.23, 3.2)
0.50

0.40
(0.09, 3.2)
0.16

0.81
(0.08, 8.6)
0.02

a
The ERR model was defined as k0(c,s,b,a) [1 þ b1(d þ hd2) exp(s e þ t ln(a))  (1 þ r s)] separately for each period of analysis,
where d is colon dose, s is sex, b is birth year, e is age at exposure, anda is attained age. s, t and r are coefficients for effect modification.
b
Confidence interval.
cLikelihood test.

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OZASA ET AL.

TABLE 8
Excess Relative Risk (ERR) Estimates per Gy for Noncancer
Deaths, 1966–2003
Number ofdeathsERR/Gya

Cause of deathcNoncancer disease
Circulatory disease
Respiratory disease
Digestive disease
Genitourinary disease
Infectious disease
Other disease25,618
14,586
4,190
2,226
951
781
2,884

0.13
0.11
0.23
0.20
0.18
–0.03
0.03

(95% CIb)

P(0.08, 0.18) ,0.001(0.05, 0.18) ,0.001(0.11, 0.36) ,0.001(0.05, 0.38)
0.009(0.06, 0.46) 0.15
(0.22, 0.23) .0.5
(0.11, 0.19) .0.5

a
ERR was estimated using the linear dose model, in which city,
sex, age at exposure, and attained age were included in the backgroundrates, but not allowing radiation effect modification by those factors.
bConfidence interval.
cNon-neoplastic blood diseases were excluded from noncancer
diseases.

FIG. 5. Excess relative risk per Gy (ERR/Gy) for all solid cancer
for selected dose ranges. The figure shows the ERR/Gy and 95% CI
for a dose range from zero to a given dose based on the linear modelfor the full data that allowed for different ERRs below and above thegiven dose and taking radiation effect modifiers as common to the twodose ranges. The increased ERR/Gy in the low-dose levels less than
0.1 Gy corresponds to the estimates of ERR higher than the expected
linear line in Fig. 4.

substantially higher for women than men, but the EAR
estimates were not. This appears to be a function of the factthat the background mortality rates of cancer were
substantially higher in men than in women in this cohort.
Similarly, it was observed that cancers having a low
background mortality rate tend to have a relatively high
ERR, and vice versa. The gender similarity in EAR
estimates suggests that the excess of deaths due to radiation
is mostly constant in rate rather than in ratio (i.e., more
additive than multiplicative) to the background cancer rates.
This interpretation is consistent with the differences in ERR
between sites of cancer mentioned above.
Age at exposure is an important modifying factor inradiation-induced carcinogenesis. Both the ERR and theEAR were higher for younger ages at exposure (Tables 4
and 5, Figs. 2 and 3). However, other reports [for example,
the BEIR VII and UNSCEAR 2006 Reports (6, 23)] haveindicated that the ERRs for those exposed at age 60 years orolder were similar to or higher than risks for those exposed
at age 40 or 50 years, especially for cancer incidence data
(5, 21, 22). The nonparametric category-specific estimatesof age-at-exposure effects on all solid cancer mortality riskin the current study were similar to the corresponding
figures reported by Walsh (22), in which an increased risk at
an old age at exposure was less remarkable than in the
figure reported by Preston et al. (5).
The linear dose–response relationship provided the best
fit to the solid cancer data across the entire dose range inthis study, but significant upward curvature was observed

over the truncated dose range of 0–2 Gy (Table 7), which
had been hinted at in previous reports (4, 5). DDREF is
defined by dividing the slope of a nonlinear function at lowdose levels by the slope of the extrapolated linear
nonthreshold function based on the whole dose range(23), so that this upward curvature may imply a DDREF
greater than one. However, the dose–response slope wasnominally higher at doses below 0.1 Gy than it was overall
or for the dose range 0–2 Gy (Fig. 5). The apparent upwardcurvature appears to be related to relatively lower than
expected risks in the dose range 0.3–0.7 Gy (Fig. 4), afinding without a current explanation. A recent paper (24)compared the risk of cancer mortality and incidence in 12
studies of low-dose-rate, moderate-dose exposure (mostly
external) with those values in the LSS. The ERR per dosefor each study was calculated using the same gender
distribution, average age at exposure, and average attained
age as in the LSS. The expected DDREF based on the ratioof ERR per dose in those studies to that in the LSS appeared
to be close to 1.0, nominally lower than the factors
suggested by BEIR VII (1.5) (23) and ICRP (2.0) (25).
However, the number of examined studies was limited tothe publication period of 2002–2007 with conditions
allowing calculation of the values matching the LSS (24),so the arguments are still controversial.
The high risks per unit dose observed in the low-dose
range are difficult to interpret. One suggestion was thatcumulative exposures to diagnostic medical radiation overthe many years of follow-up may have reached aconsiderable proportion of the estimated individual A-bombdoses at the low-dose levels (26). However, to impact the
ERR estimates, medical exposures or other sources of
exposure, including fallout and residual radiation, would
have to have preferentially exposed subjects with very low
doses. In the LSS, zero-dose subjects were located at around
4 km or farther from the hypocenter while the subjects withdoses of up to 50 mGy were located around the range of 2 to

239

MORTALITY OF ATOMIC BOMB SURVIVORS, 1950–2003

FIG. 6. Comparison of dose–response curvea for early period (1950–1965, shown with dashed line) and for late period (1966–2003, shownwith solid line) from noncancer diseases (based on LQ without any effect modification) and all solid cancer (based on LQ with effectmodifications). aBased on the ERR model defined as the linear-quadratic model without effect modifications for noncancer diseases: k0(c,s,e,a) [1þ b1(d þ hd2)], and the model with effect modifications for all solid cancer: k0(c,s,e,a) [1 þ b1(d þ hd2)  exp(s e þ t ln(a))  (1 þ s s)], where d iscolon dose, s is sex, e is age at exposure, and a is attained age. The figure for all solid cancer shows the sex-averaged estimates for e ¼ 30 years
and a ¼ 70 years. bSignificance of the difference between the two curves.

TABLE 9Observed and Excess Deaths from Solid Cancer and Noncancer Diseases
Noncancer diseasesb

Solid cancer
Colon dose(Gy)
,0.0050.005–
0.1–
0.2–
0.5–
1–
2þ
Total
a
b

Number of
subjects

Person-years

Number ofdeathsNumber ofexcess casesa

Attributablefraction (%)

Number ofdeathsNumber ofexcess casesb

Attributablefraction (%)

38,50929,961
5,974
6,356
3,424
1,763
624
86,611

1,465,240
1,143,900
226,914239,273
129,333
66,602
22,947
3,294,210

4,621
3,653
789
870
519
353
124
10,929

2
49
46
109
128
123
70
527

0
1.3
5.8
12.5
24.7
34.8
56.5
4.8

15,906
12,304
2,504
2,736
1,357
657
221
35,685

1
36
36
82
86
76
36
353

0
0.3
1.4
3.0
6.3
11.6
16.3
1.0

Based on the ERR model was defined as the linear model with effect modification: k0(c,s,b,a)[1 þ b1d  exp(s e þ t ln(a))  (1 þ r s)].
Non-neoplastic blood diseases were excluded from noncancer diseases.

240

OZASA ET AL.

4 km. Thus, with such a large geographical distribution,differential exposures to additional radiation sources seem
implausible, although we have insufficient information
about fallout or residual radiation to completely rule out
this possibility.
Potential causes other than radiation include selection bias
due to early mortality prior to study initiation in a mannerthat correlates with dose (e.g., high doses among urban
people and lower doses among rather rural people) (1, 2, 5,
27, 28). Suggestively lower baseline mortality has beenshown in the low-dose but relatively proximal survivors
compared to the more distant survivors, which suggests thatsociodemographic factors such as urban-rural differences
may be more important than dose-based selection effects (1,2, 27, 28). However, sociodemographic selection effects
might have weakened because of modernization of theJapanese lifestyle over the decades. The issues related to the
influences of dose, latency and sociodemographic-lifestylefactors on mortality from noncancer diseases in the LSS
require further investigation.
A variety of studies of risks for site-specific cancers fromexternal exposure to low-LET (linear energy transfer)radiation are documented in the UNSCEAR 2006 Report(6). Most studies were based on either subjects with highdose radiation such as radiotherapy or radiation workers
with low-level exposures. Thus the LSS is often thought toprovide the most reliable estimates of radiation effects
because of its large size, wide range of relatively precise
individual doses, observation of numerous diseases, andlong follow-up period. Cancers of the esophagus, stomach,colon, lung, breast, ovary and bladder and transitional cell
carcinoma of kidney, pelvis and ureter are thought to be
associated with low- and high-dose radiation based on the
LSS and other studies (6). A strong interaction between
radiation and smoking was observed in the risk of lungcancer (29), so high ERRs of smoking-related cancers might
be partly due to such an interaction. Rectal cancer is thought
to be inducible after high-dose radiotherapy exposures (6),but no association has been observed among the LSS. On
the other hand, an association of liver cancer with radiation
exposure has not been demonstrated in studies of medical
and occupational exposure to low-LET radiation, while the
LSS showed a significant increase in risk (6). It isinconclusive whether there was a synergism between
HCV infection and radiation (30) or independent effects
by each of them (31). Cancers of the pancreas, prostate anduterine cervix are not thought to be associated with radiation(6), which is consistent with the results of this study.
Uterine corpus and kidney parenchymal cancers are
possibly associated with a high-dose radiation exposure(6), but this association was not observed in this study.
Most excess cases of leukemia occurred shortly after theatomic bombings, even before the beginning of the LSS(32), and a modestly elevated risk has continued at a low
level over the last several decades (1, 7). In this study, theestimated ERR at 1 Gy for total leukemia was 3.1 (95% CI:

1.8, 4.3) using a linear-quadratic model without effectmodification, based on 313 cases, which is similar to a
recent, more detailed leukemia report (7). An analysis ofmalignant lymphoma mortality in the LSS was conducted
recently based on the subset of males of working age at thetime of the bombing (33). The present study similarly foundan excess for males [ERR/Gy of 0.70 (P ¼ 0.02)] but noassociation for women [ERR/Gy ¼ 0.18 (P ¼ 0.33)]. We
have no explanation for the disparity between the male andfemale results and believe the radiation effect should beinterpreted cautiously due to both the gender disparity andthe diversity of malignancies under the rubric of lymphoma.
Earlier LSS reports of multiple myeloma mortality (34) did
not show statistically significant excesses. But, based onhematologically reviewed incident cases from leukemia
registries and tumor registries, Preston et al. (35) showed an
ERR/Gy ¼ 0.25 (P . 0.5) based on 30 first primary caseswith shielded kerma under 4 Gy and ERR/Gy ¼ 0.9 (P ¼
0.02) after adding seven cases of second primaries and thosewith shielded kerma .4 Gy. In the present study (all withbone marrow doses 4 Gy), ERR/Gy of multiple myeloma
was 0.11 (P . 0.5) in males and 0.86 (P ¼ 0.04) in females
based on 34 and 59 cases, respectively.
In this overview, risk of noncancer diseases was reported
using a broad classification of disease types. The elevatedrisk of diseases of the blood and blood-forming organs may
be genuinely due to the effects of radiation or to possible
misdiagnoses of hematopoietic malignancies as non-neoplastic conditions, since many death certificates werecompleted without intensive investigations as to the causeof death (8). The risk of circulatory diseases was
significantly higher. This is important because circulatory
diseases are the leading cause of death in developed
countries (6); detailed results for circulatory disease deaths
among the LSS have been reported elsewhere (36). The riskof respiratory diseases was also significantly elevated due tothe increased risk of pneumonia and influenza, whichconstituted 63% of the deaths from respiratory diseases.
However, characteristics of pneumonia and influenza
appeared to be different between the periods of observation;
namely, it was associated with acute epidemics in the early
period but was more likely to be associated with terminal
diseases among the elderly in the more recent period. Hencea problem in interpreting pneumonia and influenza deaths isthat they may be associated with other concurrent or
underlying diseases. Although digestive diseases showed an
association with radiation during 1966–2003, liver cirrhosis,
which constituted 43% of digestive disease deaths duringthat period, did not show any increased radiation risk.
Therefore, further detailed analyses of both respiratory anddigestive diseases are planned. There was no association ofradiation dose and death due to external causes or to
infectious/parasitic diseases.
The strengths of this LSS mortality study are, as statedpreviously (2, 4, 34), (1) a large, representative sample
across all age groups of A-bomb survivors who were alive

MORTALITY OF ATOMIC BOMB SURVIVORS, 1950–2003

in 1950, using stratified sampling to enrich the higher-dose
portion of the sample, (2) reasonably precise estimates ofindividual doses, (3) a wide range of doses in the cohort, (4)complete ascertainment of mortality and cause of deathusing the koseki system, and (5) a long observation periodwith a large number of deaths. Those strengths provide ahigh-quality, informative epidemiological study.
A potential limitation of the LSS was that the subjects
were the ‘‘survivors’’ of physical injuries and burns fromthe A-bomb explosion and biological injuries due todeterministic radiation effects. Additional stressors included
poor nutrition and bad hygienic conditions in Japan in the
postwar period. Those conditions might have led to earlymortality and hence selective exclusion of vulnerable
people, including vulnerability to radiation, from theavailable subjects in 1950. Nevertheless, the stochastic latehealth effects such as cancer development are not likely tobe affected by such selection bias, which is supported by the
negligible discrepancies in the dose–response curves
between the early and late periods for all solid cancer(Fig. 6). A careful analysis of this phenomenon would
require breakdowns by period, cancer site and other factors.
Another unavoidable exclusion is that perhaps an appreciable number of leukemia cases occurring before 1950 werelost to the study (32). On the other hand, the significant
discrepancy between the early and late calendar periods fornoncancer diseases (P ¼ 0.02) implies a potential selection
bias for noncancer diseases as a whole. The discrepancy
was not observed in circulatory diseases, while borderline
differential patterns were observed for respiratory anddigestive diseases. More detailed analyses are required.
In conclusion, the risk of death from malignant neoplasms
in most sites and selected noncancer diseases increased in adose-dependent fashion among LSS subjects over the period
1950–2003. The relative risk of radiation for solid cancer
was largest among those exposed at young ages. The resultsof this study, which extended the observations for 6 years,
are consistent with previous reports and continue to show
increased cancer risks throughout the survivors’ lifetimes.
Since epidemiological evaluation can be done only after thedevelopment of outcomes, we sincerely pay our respects to
those who have died. It would be our pleasure if
clarification of late health effects of A-bomb radiation
could offer fundamental information for the survivors’
welfare. Clearly the LSS will continue to provide increased
precision in risk estimation and additional information
regarding risk modification by other factors, as 42% of thesurvivors in LSS subjects overall, and 80% of those who
were exposed to radiation at the age of 20 years or younger,
were still alive at the end of follow-up in 2003.
ACKNOWLEDGMENTS
The Radiation Effects Research Foundation (RERF), Hiroshima andNagasaki, Japan is a private, non-profit foundation funded by the Japanese
Ministry of Health, Labour and Welfare (MHLW) and the U.S.

241

Department of Energy (DOE), the latter in part through DOE Award
DE-HS00000031 to the National Academy of Sciences. This publication
was supported by RERF Research Protocol RP 1–75. The views of theauthors do not necessarily reflect those of the two governments.
Received: March 23, 2011; accepted: November 28, 2011; published
online: December 15, 2011

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APPENDIXClassification of Cause of Death in This Report
Edition of International Classification of Diseases (ICD) and applicable years

Neoplasm
All solid cancer
Esophagus
StomachColon
RectumLiver
Gallbladder
Pancreas
Other digestive system
Lung
BreastUterus
Ovary
Prostate
Bladder
Kidney parenchyma
Renal pelvis,
other urinary tract
Other solid cancer
Leukemia

ICD-7
1950–1968

ICD-8
1969–1978

ICD-9
1979–1997

ICD-10
1998–2003

140–205, 210–239, 251
140–199
150
151
153
154
155 (0, 8), 156
155.1
157
158, 159
162 (0, 1, 8), 163
170
171, 172, 174
175
177
181
180

140–239
140–199
150
151
153
154
155, 197.8
156
157
158,159
162
174
180, 182.0, 182 (9)
183
185
188
189

140–239
140–199
150
151
153
154
155 (0, 1, 2)
156
157
158,159
162
174,175
179–180, 182
183
185
188
189

C00–C97
C00–C80
C15
C16
C18
C19–C20
C22 (0–4, 7, 9)
C23, C24
C25
C26, C48
C33, C34
C50
C53, C54, C55.9
C56, C57 (0, 1, 2, 3, 4)
C61
C67
C64

180
Others in 140–199
204

189 (1, 2)
Others in 140–199
204–207189 (1, 2)
Others in 140–199
204–208

C65, C66
Others in C00–C80
C91 (0–3, 5, 7, 9), C92 (0–5, 7, 9),
C93, C94 (0–3, 7), C95
C81–C85, C91.4, C96
C88. (7, 9), C90
C94.4, D00–D48, Q85.0

Malignant lymphoma
200–202, 205
200–202200–202
Multiple myeloma
203
203
203
Other neoplasms
210–239, 251
208, 210–239
210–239
Non-neoplastic diseases
Blood disease
290–299, 468 (0, 1, 2)
209, 280–289
280–289
D50–D75, D77, C94.5
Circulatory disease
330–334, 400–467, 468.3
390–458
390–459
I00–I99, G45, M30
Respiratory disease240–241, 470–527
460–519
460–519
J00–J64, J66–J99, R09.1
Pneumonia and influenza
480–493
470–486
480–487
J10–J18
Digestive disease
530–587
520–571
520–571
K00–K92
Liver cirrhosis
581
571
571
K70, K73, K74
Genitourinary disease(*additional for female)
590–617, 620–637*
580–607, 610–629* 580–608, 610–629*
N00–N50, N60–N98*
Infectious Disease001–138
000–136001–139
A00–A32, A35–B99, D86, J65, M35.2
External causes
N800–N999
N800–N999
800–999
S00–T98