Jpn. J. Health Phys.，55 (1), 32 〜 39 (2020)

DOI: 10.5453/jhps.55.32

Original Paper

Direct Risk Comparison between Radiation and Smoking on Cancer
Mortality among Nuclear Workers in Japan (J-EPISODE)
Shin’ichi KUDO,*1, # Akemi NISHIDE,*1 Jun’ichi ISHIDA,*1 Keiko YOSHIMOTO,*1
Hiroshige FURUTA*1 and Fumiyoshi KASAGI*1（Received on August 5, 2019）（Accepted on November 29, 2019）
The health effects of low-dose or low-dose rate of radiation are still controversial. There is little evidence to show if radiation
risk is greater than other risks, such as lifestyle or socio-economic factors, including smoking. This study aimed to directlycompare radiation and smoking risk on cancer mortality by deriving both risk factors simultaneously from one cohort. The
study population was Japanese nuclear workers who were engaged until the end of March, 1999. A lifestyle questionnaire
was distributed in 1997 and 2003 and smoking information was obtained. Radiation dose was supplied by Radiation Dose
Registration Center in Radiation Effects Association. Poisson regression was used to derive radiation excess relative risk (ERR)
per 100 mSv and smoking (ERR) per 20 pack-years. Radiation doses were lagged by 10 years. There were 71,733 subjects.
The total person-years was 591,000, and the number of deaths for all cancers excluding leukemia was 1,326. For all cancers
excluding leukemia, the ERR of radiation per 100 mSv was 0.08 (90% CI: −0.08, 0.28), and the ERR of smoking per 20 packyears was 0.57 (90% CI: 0.44, 0.73). In addition to all cancers excluding leukemia, stomach cancer, lung cancer, smokingrelated cancers showed significantly smaller radiation ERRs than smoking ERRs. These results suggest that, even if a lowdose radiation risk existed, it was much smaller than smoking risk.
KEY WORDS: low dose radiation, radiation risk, smoking risk, cancer, cohort study, epidemiological study.
I

INTRODUCTION

Although health effects of high-dose or high-dose rate ofradiation based on the studies of atomic bomb survivors 1–3) has
been demonstrated, the health effects of low-dose or low-dose
rate of radiation are still controversial. There is little evidence
to show if radiation risk is greater than other risks, such as
lifestyle or socio-economic factors, including smoking.
Some studies have compared the risk between radiationand smoking,4–6) however, comparison between cumulative
radiation dose and total amount of smoking among nuclear
workers are limited.
The Institute of Radiation Epidemiology (IRE) of
Japan’s Radiation Effects Association (REA) commenced
an epidemiological study on low-dose radiation effects(J-EPISODE) among radiation workers in Japan in 1990. To
examine non-radiation factors among radiation workers, theIRE conducted lifestyle questionnaire surveys among a sample
of workers in 1997 7) and 2003.
The present study aimed to quantify the excess relativerisk (ERR) of both radiation and smoking that were derived
simultaneously from one cohort, and to directly compare thetwo risk factors.
*1 Institute of Radiation Epidemiology, Radiation Effects Association;#

1–9–16 Kajicho, Chiyoda-ku, Tokyo 101–0044, Japan.
Corresponding author; E-mail: s_kudo@rea.or.jp

II

MATERIALS AND METHODS

1. Ethics statement
All procedures involving human participants were inaccordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki
declaration and its later amendments or comparable ethicalstandards. The study protocol was based on the Ethical
Guidelines for Medical and Health Research Involving Human
Subjects established jointly by Japan’s Ministry of Health,Labour, and Welfare, and Ministry of Education, Culture,
Sports, Science, and Technology. This work was reviewed andapproved by the Research Ethics Committee of the REA.
2. Cohort definition and follow-up of vital status
We conducted a follow-up of Japanese workers who
registered in the Radiation Dose Registration Center(RADREC), which manages workers’ radiation dose records
from nuclear facilities as of the end of March 1999. Copiesof the workers’ residence registration cards (RRCs) wereacquired from local government offices to ascertain theirvital statuses. Copies of RRCs were issued when subjects
were alive, and copies of deleted residence records, including
death dates or new addresses, were issued when subjects were
deceased or had moved.
For those whose deaths could be ascertained through RRCs,
causes of death were obtained by record linkage with the deathDirect Risk Comparison between Radiation and Smoking on Cancer

records approved for use and provided by Japan’s Ministry of
Health, Labour and Welfare. Indices used for record linkage
were date of birth, date of death, sex, and municipality codeof residence.8) A process to obtain individual informed consent
through an opt-out method was performed from 2007–2009.
The opt-out rate was approximately 7%. For those whose data
we obtained but who later refused participation, we stopped
all follow-up efforts, but included them among their cohort
until the last day on which their vital statuses were known.
The primary framework of the study population and follow-up
methods of the J-EPISODE have been described in detail inprevious papers.9–13)
3. Dosimetry
For this study, the individual recorded doses, including
photon, internal, and neutron doses, were used. The photon
doses were the external exposure records of equivalent doses
at a tissue depth of 10 mm [Hp(10) (mSv)] for all workers innuclear facilities who are registered in the RADREC dose
database. Neutron doses and internal doses were monitored,
but cases above the level to be recorded were rare. If they
were detected, they were added to external doses. The doserecords used in the analysis included the individual’s amountthat consisted of external, internal, and neutron doses by fiscal
year. In the present study, exposures below the detectable level
were set as zero mSv.
The use of nuclear energy in Japan commenced in 1957.
Therefore, the dosimetry records of workers from 1957 to
the time before the RADREC launched the registration in
1978, were retrospectively provided to the RADREC by therespective nuclear facilities that had stored the data. The
present study covers radiation dose records from 1957 to 2010.
4. Lifestyle questionnaire survey
To examine factors potentially confounding the risk
assessment of nuclear workers, lifestyle questionnaire surveys
were performed twice (1997 and 2003) to a sample of workers.
The questionnaire was self-administered and included
questions on smoking, alcohol intake, and history of engaging
in work involving hazardous materials, such as asbestos,benzene, etc. The first survey’s questionnaire (1997–1999) was
distributed to 55,271 workers in nuclear facilities; and almost
all respondents were working at the time of the survey. The
second survey’s questionnaire (2003–2004) was distributed
to 73,542 workers by postal mail to those who were 40 years
old or more on July 1, 2003. Based on cumulative doses asof March 31, 2002, all workers exposed to 10 mSv or more
were surveyed, while 40% of workers with less than 10 mSv
were sampled. The questions in the second survey were almost
identical to those of the first survey, with questions on socioeconomic status such as years of education added. For those
who answered both surveys, the first survey’s answers wereanalyzed in this study. Female workers were also distributed
to but were not included in the analysis because number of the
responses from female workers was too small (387 workers).
Those whose smoking status or pack-years were unknown
were excluded.

33

5. Risk comparison strategy
To compare radiation and smoking risks, we had to set
some assumptions on model and unit. In this study, a linear
model was assumed to apply to both radiation and smoking.
In radiation epidemiology field, a linear model is broadly
used, although a linear no threshold (LNT) model is still
controversial. The consensus is that determining low-level
radiation risk is difficult due to a huge cohort that is needed
to increase statistical power and adjustment for confounding
factors such as lifestyle or socio-economic status is generally
limited. LNT can be considered as a possible model undersuch situations. Therefore, a linear model was used forradiation risk estimate. To facilitate a comparison, linear model
was also used for smoking.
For risk estimate units, both radiation risk estimate andsmoking risk estimate vary by their unit. Workers who were
exposed to over 100 mSv comprised approximately 5% of thewhole cohort. Therefore, radiation risk estimate was based on
100 mSv to avoid underestimation of radiation risk. Smoking
risk estimate was based on 20 pack-years to allow comparison
with other studies.
6. Statistical analysis
All individuals contributed person-years from two years
after the response date of the questionnaire 14) until the earliestof (a) the date of final confirmation of vital status, (b) thedate of death, or (c) December 31, 2010. Poisson regression
models were applied to analyze radiation risks and smoking
risks.12, 13, 15–18) Each individual’s last residence was used to
stratify respondents into eight regions within Japan. Given the
differences between the characteristics of respondents to thefirst and second lifestyle surveys, as described above in the“lifestyle questionnaire survey” section, a binary indicator wasused to show whether the first or the second survey was used
for analysis.
Radiation cumulative doses were categorized into 14
groups by mSv levels: 0, > 0, 1–, 2–, 3–, 5–, 7.5–, 10–, 15–,
20–, 25–, 50–, 100–, 200+. Cumulative radiation doses were
updated monthly, with the assumption that annual doses were
distributed uniformly over the year. Cumulative doses were
lagged by ten years.12, 13, 15–18) The pack-years was defined
as follows: the number of cigarettes per day × (1 pack/20
cigarettes) × duration of smoking (the number of years since
the age at which an individual started to smoke, throughthe age on the survey date for current smokers). Pack-years
were categorized into eight groups: 0, > 0, 10–, 15–, 20–,
25–, 30–, 50+. We used only pack-years for current smokers
and added former smoker indicator as an adjusted variable.
Adjustment variables were attained age, calendar year, birthyear, residence, binary indicator of lifestyle questionnaire
survey, and binary indicator of former smoker. Cumulative
dose, attained age, and calendar period were treated as timedependent variables. The model used to estimate radiation andsmoking risks was a linear additive model (1):λ = λ0 (a, c, y, r, s) exp(αz) (1 + β1 z1 + β2 z2)

(1)

34

Shin’ichi KUDO, Akemi NISHIDE, Jun’ichi ISHIDA, Keiko YOSHIMOTO, Hiroshige FURUTA and Fumiyoshi KASAGI

We also fitted the data to a linear multiplicative model (2)and a log-linear model (3).
λ = λ0 (a, c, y, r, s) exp(αz) (1 + β1 z1)(1 + β2 z2)(2)

λ = λ0 (a, c, y, r, s) exp(αz + β1 z1 + β2 z2 )(3)

where λ is the death rate at dose z1 and pack-years z2. λ0 is the
background death rate (stratified by a: attained age (20–, 25–,..., 100+), c: calendar period (< 2000, 2000–2004, 2005–2010),
y: year of birth (< 1920, 1920–, 1925–, ..., 1970+), r: region(divided into eight areas), and s: survey indicator (1st, 2nd)),z indicates former smokers (1 = former smoker, 0 = current
smoker or never smoker); z1 represents the person-year
weighted cumulative dose, and z2 represents the person-year
weighted pack-years for current smokers. α represents thecoefficient of z and denotes relative risk for former smokers,and β1 and β2 represent the coefficient of z1 and z2, respectively.
The unit of z1 was 100 mSv, and the unit of z2 was 20 packyears. Therefore, β1 denotes radiation ERR per 100 mSv, andβ2 denotes smoking ERR per 20 pack-years. ERR denotes
an increase of risk by radiation or smoking, namely it isequivalent to relative risk minus one. We also calculated the
90% confidence interval (CI) based on likelihood. WhenCI based on likelihood was not converged, CI based on
Wald was calculated. Doses were lagged by 10 years, andsensitivity analyses were examined under five- and 15-year
lag assumptions, in addition to a 10-year lag. In addition, we
verified an interaction between radiation and smoking by using
the model as follows (4):λ = λ0 (a, c, y, r, s) exp(αz) (1 + β1 z1 + β2 z2 + β12 z1 z2) (4)where z1z2 denotes interaction term of z1 (radiation) and z2(smoking) and β12 represent the coefficient of z1z2.
The person-year table was created and the models werefitted using Epicure software.19) Using this model, we
compared the ERRs of both radiation and smoking.

Table 1

III

There were 75,442 male workers who responded tothe questionnaire survey. There were 3,709 workers (5%)
excluded due to unknown smoking status. As a result, 71,733
with smoking information were analyzed as the present study
cohort. Table 1 shows the cohort characteristics. There wereapproximately 591,400 person-years accumulated from 1999
to 2010 by 71,733 cohort members. The mean of cumulative
radiation dose which were lagged by 10 years and pack-years
at the end of follow-up was 21.0 mSv and 27.8 pack-years,
respectively. The age at the end of follow-up was 56.2 years
old.
Table 2 denotes the proportion of subjects by the packyears and dose categories at the end of follow-up. Some dose
categories are combined for clarification purposes. The tableillustrates positive correlation between the pack-years andradiation dose (p-value of Pearson correlation 20) < 0.001).
Namely, the proportion of non-smokers decreases withincreasing dose categories, while the proportion of current
smokers with 30 or more pack-years increases with increasing
dose categories. More than half of workers are classified in the< 5 mSv dose category, while 5% of workers are classified in
the 100+ mSv dose category.
Table 3 shows the distribution of deaths, person-years andmean attained age by dose category, smoking status and packyears. The mean attained age showed a positive trend withcumulative dose and pack-years.
The results derived by model (1, 2, 3) were almost identical.
For all cancers excluding leukemia, the ERR of radiation
per 100 mSv was 0.08 (90%CI: –0.08, 0.28) and the ERR ofsmoking per 20 pack-years was 0.57 (0.44, 0.73) by linear
additive model. The ERR of radiation per 100 mSv was 0.03
(90%CI: –0.08, 0.16) and the ERR of smoking per 20 packyears was 0.56 (0.43, 0.72) by linear multiplicative model. The
ERR of radiation at 100 mSv was 0.04 (90%CI: –0.07, 0.15)
and the ERR of smoking at 20 pack-years was 0.30 (0.25, 0.36)

Characteristics of Japanese nuclear workers.

Follow-up period
Number of subjects
Person-years
Age at first radiation exposure
Duration of radiation exposure (Years)
Cumulative radiation dose at the end of follow-up(mSv, Lagged by 10 years)
Age at start to smokea
Duration of smokinga (Years)
Pack-yearsa
Age at the end of follow-upa

RESULTS: Calculated among current smoker (N = 41,495).

MeanMedian (IQR)
MeanMedian (IQR)
MeanMedian (IQR)
MeanMedian (IQR)
MeanMedian (IQR)
MeanMedian (IQR)
MeanMedian (IQR)

1999–2010
71,733
591,400
30.0
27 (21–37)
17.1
17 (6–26)
21.0
4.5 (0.1–22.7)
19.5
20 (18–20)
24.1
24 (14–33)
27.8
25.0 (13.0–38.0)
56.2
56 (47–65)

Direct Risk Comparison between Radiation and Smoking on Cancer

35

Table 2 Number of subjects by smoking status, pack-years, and dose categories at the end of follow-up among Japanese nuclear
workers.
Smoking
statusPack-years

Never

0

Former–>0
10–

Current
20–
30+
Total
Proportion by dose category

03,954(25.2%)
3,716(23.7%)
1,483(9.5%)
1,472(9.4%)
1,520(9.7%)
3,545(22.6%)
15,690(100%)
21.9%

>0
5,085
(24.2%)
4,064(19.4%)
2,966(14.1%)
2,507(11.9%)
2,169(10.3%)
4,203(20.0%)
20,994(100%)
29.3%

Dose categories (mSv)a
5–
10–
20–
50–
1,331
1,759
1,862
833
(21.5%) (18.9%) (17.8%) (15.1%)
1,114
2,092
2,154
1,107
(18.0%) (22.4%) (20.6%) (20.1%)
892
902
845
322
(14.4%) (9.7%)(8.1%)(5.8%)
848
1,126
1,387
738
(13.7%) (12.1%) (13.3%) (13.4%)
713
1,141
1,436
914
(11.5%) (12.2%) (13.7%) (16.6%)
1,283
2,304
2,778
1,598
(20.8%) (24.7%) (26.6%) (29.0%)
6,181
9,324
10,4625,512(100%) (100%) (100%) (100%)
8.6%
13.0%
14.6%
7.7%

100–
388
(13.6%)
564(19.8%)
74(2.6%)
333(11.7%)
487(17.1%)
1,000(35.1%)
2,846(100%)
4.0%

200+
78
(10.8%)
137(18.9%)
10(1.4%)
51(7.0%)
133(18.4%)
315(43.5%)
724(100%)
1.0%

Total
15,290(21.3%)
14,948(20.8%)
7,494(10.4%)
8,462(11.8%)
8,513(11.9%)
17,026(23.7%)
71,733(100%)
100%

Note: Parentheses indicate percentage of pack-years within each dose category. Some categories are combined for clarification purposes.
a: Lagged by 10 years.

Table 3 Distribution of deaths, person-years and mean attained age by dose category, smoking status and pack-years among
Japanese nuclear workers.
Cause of death
All cancers
excludingleukemia
Total
1,326
Cumulative dose (mSv)
0
313
>0
312
5107
10–
181
20–
214
50–
132
100–
47
200+
20
Smoking status Pack-yearsa
Never
155
Former
372
>0
21
10–
52
Current
20–
386
30+
340

StomachcancerLiver cancer

Lung cancer

218

138

319

Smokingrelated
cancersb
952

58
44
16
31
37
24
5
3

31
33
8
14
25
17
9
1

68
65
33
45
54
33
17
4

223
206
82
128
166
97
38
12

79
92
22
44
42
31
7
5

19.3
16.5
4.5
6.1
6.9
3.6
1.8
0.4

44.9
48.8
50.0
53.2
53.6
54.7
56.2
58.7

26
53
6
9
59
65

19
35
1
5
45
33

19
89
3
7
102
99

94
247
13
37
283
278

50
110
6
11
91
54

12.7
10.8
7.6
8.2
10.7
9.2

48.1
56.9
33.6
42.0
53.5
56.6

Nonsmoking- Person-years/ Mean attained104
relatedage
ccancers
322
59.1
49.3

a

: Calculated among current smokers. (Zero for non-smokers.): Buccal and pharynx, esophagus, stomach, liver, pancreas, nasal cavity, larynx, lung, bladder, kidney, ureter.
C00–C16, C22, C25, C30.0, C31–C34, C64–C67.
c: All solid cancers other than smoking-related cancers.
C17–C21, C23–C24, C26–C29, C30.1–C30.9, C35–C63, C68–C80.
b

by log-linear model. These results showed lower radiation
ERR compared with smoking ERR by all models and suggeststhat our results were robust. The linear additive model
showed the best fit in all causes of death except non-smoking
related cancers. AIC’s of all cancers excluding leukemia were
9,540.680 for the linear additive model, 9,541.092 for the

linear multiplicative model and 9,554.756 for the log-linear
model, respectively. Therefore, the results from the linear
additive model were used for the rest of the analysis.
Table 4 shows the ERRs and 90% CIs of radiation andsmoking. No significantly higher ERR per 100 mSv wasshown, while significantly higher ERRs per 20 pack-years

36

Shin’ichi KUDO, Akemi NISHIDE, Jun’ichi ISHIDA, Keiko YOSHIMOTO, Hiroshige FURUTA and Fumiyoshi KASAGI

Table 4 Excess relative risk and 90% confidence interval of radiation and smoking by cause of death among Japanese nuclear
workers.
Causes of DeathAll cancers excluding leukemia
Stomach cancer
Liver cancer
Lung cancer

ICD10 codes

Observed Deaths

C00–C97
except C91–C95
C16

1,326

C22

138

C33–C34

319

Smoking-related cancersa
Nonsmoking-related cancersb

218

952
322

Radiation ERR per 100 mSv Smoking ERR per 20 pack-years
90%CI
90%CI
0.08
0.57
(–0.08, 0.28)(0.44, 0.73)
–0.24
0.71
(–0.55, 0.05)c(0.33, 1.09)c
0.71
0.61
(–0.004, 1.89)(0.26, 1.25)
0.19
2.14
(–0.21, 0.81)(1.33, 3.49)
0.09
0.87
(–0.13, 0.37)(0.65, 1.13)
–0.04
0.18
(-0.30, 0.22)c(0.03, 0.33)ca: Buccal and pharynx, esophagus, stomach, liver, pancreas, nasal cavity, larynx, lung, bladder, kidney, ureter.
C00–C16, C22, C25, C30.0, C31–C34, C64–C67.
b: All solid cancers other than smoking-related cancers.
C17–C21, C23–C24, C26–C29, C30.1–C30.9, C35–C63, C68–C80.
c: Wald based confidence interval.

were shown in all analyzed causes of death. For all cancers
excluding leukemia, significantly smaller radiation ERRs (0.08(90%CI: –0.08, 0.28)) compared with smoking ERRs (0.57(0.44, 0.73)) were observed. Stomach cancer, lung cancer, andsmoking-related cancers also showed significantly smaller
radiation ERRs compared with smoking ERRs. The radiation
ERR for liver cancer (0.71 (–0.004, 1.89)) was higher thanfor smoking ERR (0.61 (0.26, 1.25)) with regards to point
estimate.
For all cancers excluding leukemia, the ERR of radiation
was 0.08 (90%CI: –0.08, 0.26) and the ERR for smoking
was 0.57 (0.44, 0.73) when a five-year lag was assumed, andthe ERR of radiation was 0.09 (–0.09, 0.30) and the ERR
for smoking was 0.57 (0.44, 0.72) when a 15-year lag was
assumed. The lags were adapted only to radiation and were
not adapted to smoking. Therefore, the ERRs of smoking werequite stable. We verified that all cancers excluding leukemia,
stomach cancer, lung cancer and smoking-related cancers
showed significantly smaller radiation RRs compared withsmoking RRs when lag assumptions were five or 15-years(data not shown for stomach cancer, lung cancer and smokingrelated cancers).
We found no interaction between radiation and smoking.
The p-values of coefficient of the interaction term were 0.415
for all cancers excluding leukemia, and the p-values of othercauses of death were all greater than 0.1.
IV

DISCUSSION

1. Principal findings
In this study, direct comparison between radiation risk andsmoking risk on cancer mortality was examined. Significantly
smaller radiation ERRs per 100 mSv compared wtih smoking
ERRs per 20 pack-years were shown for all cancers excluding
leukemia, stomach cancer, lung cancer, and smoking-related
cancers. For all cancers excluding leukemia, ERR of radiation

per 100 mSv was approximately one seventh of smoking ERR
per 20 pack-years. Considering that the mean cumulative
dose of this cohort was 21.0 mSv, the estimated risk of cancer
mortality by smoking per 20 pack-years was over 30 times
larger than that of radiation risk for ordinary nuclear workers.
2. Liver cancer radiation risk
The radiation ERR for liver cancer was higher than othercauses of death and the point estimate was also higher than forsmoking ERR. We have examined the adjustment for alcohol
consumption status as follows:
λ = λ0 (a, c, y, r, s) exp(αz + γy)(1 + β1 z1 + β2 z2)(5)where y denotes alcohol consumption status (1 = current
drinker, 2 = former drinker, 3 = never drinker, 4 = unknown)and γ denotes coefficient of y. Exp(γ) means relative risk
by each alcohol category. After adjustment for alcohol
consumption status, the results were almost stable. The ERRof radiation was 0.72 (0.006, 1.90) and smoking ERR was
0.56 (0.22, 1.17). This suggests the possible existence of otherfactors, such as hepatitis virus 21, 22) or that radiation itself
may increase ERR. However, the results of other radiation
epidemiology studies showed no significant increase in livercancer.15, 16) The high radiation ERR for liver cancer might becaused by chance, but this cannot be verified.
3. Comparison with other studies
Table 5 shows the comparison of ERRs of radiation for
all cancers excluding leukemia and lung cancer with otherstudies. An atomic bomb survivor’s life span study (LSS),3, 4)15-country study 15) (Pooled analysis include Australia,
Belgium, Canada, Finland, France, Hungary, Japan, Korea,
Lithuania, Slovakia, Spain, Sweden, Switzerland, UK andUSA), National Registry for Radiation Workers’ study 16)(NRRW: Cohort study performed by UK), International

Direct Risk Comparison between Radiation and Smoking on Cancer

37

Table 5 Comparison of excess relative risk and 90%
confidence interval of mortality by radiation with otherstudies.

Table 6Comparison of excess relative risk and 90%
confidence interval of mortality by smoking with otherstudies.

All cancers excluding
leukemia
Observed deaths
ERR per 100 mSv
90% CI
1,326
0.08a(–0.08, 0.28)
5,235
0.03bc(0.02, 0.04)d
5,024
0.10c
(0.03, 0.18)
7,455
0.03c
(0.002, 0.06)
19,0640.05c(0.02, 0.08)

All cancers excluding
leukemia
Observed deaths
Smoking ERR
90% CI
1,326
0.57ab(0.44, 0.73)
2,513
0.93cde(0.72, 1.19)f342
0.41cdg(–0.06, 1.10)f

Study

J-EPISODE

LSS

15-country

NRRW-3INWORKSMayak

Lung cancer
Observed deaths
ERR per 100 mSv
90% CI
319
0.19a(–0.21, 0.81)
1,445
0.08ae(0.02, 0.15)d
1,457
0.19c
(0.05, 0.36)
2,230
0.01cf(–0.04, 0.07)
5,802
0.05c
(0.00, 0.11)
446
0.01g
(–0.004, 0.04)d

Study

J-EPISODE

JACC

JPHC

Three-Prefecture

LSS

Mayak

a

a

b

b

: Derived by linear additive model.
: All solid cancers.
c: Derived by linear model.
d: 95% confidence interval.
e: Incidence.
f: Trachea, bronchus and lung cancer.
g: Derived by linear multiplicative model.

Nuclear Workers Study 17, 18) (INWORKS: Pooled analysis
include UK, US, France) and study of Russia’s Mayak nuclear
facility 6) were chosen for comparison of radiation risk. The
ERR for all cancers excluding leukemia of present study
per 100 mSv was comparable with other studies. The ERR
for lung cancers of the present study was also comparable,
althought the point estimate of the present study was slightly
higher than other studies.
Japan Collaborative Cohort Study for Evaluation on Cancer(JACC),23) Japan Public Health Center-based Prospective
Study on Cancer and Cardiovascular Diseases (JPHC),24, 25)
Three-Prefecture Cohort study,26) LSS 3) and Mayak 6) werechosen for comparison of smoking risk (Table 6). The ERR
for all cancers excluding leukemia of present study per 20
pack-years was compatible with JPHC. However, the point
estimate was lower than JACC, although the confidence
interval overlapped. The ERR for lung cancer of the present
study was compatible with JACC, JPHC and Three-Prefecture
study, but was significantly lower than LSS or Mayak. Thismay be caused by the difference in pack-years unit. While, 20
pack-years was used in our study, 50 pack-years was used in
the LSS study. The smoking category (current, former, never)
was used in the Mayak study, and it showed exceptionally highLung cancer
Observed deaths
Smoking ERR
90% CI319
2.14ab
(1.33, 3.49)645
2.97ce(1.96, 4.32)f
1,354
3.69ch(2.32, 5.62)e339
1.10ce(0.62, 1.71)f
1,445
5.70aij(4.10, 8.07)f
446
9ch(5.4, 17)f

: Derived by linear additive model.
: Smoking excess relative risk at 20 pack-years vs 0 pack-years.
c: Denoted as relative risk or hazard ratio in original paper.
They are denoted as excess relative risk in this table byextracting one.
d
: All cancers.
e: Smoking relative risk at 20–39 pack-years vs 0 pack-years.
f: 95% confidence interval.
g: Smoking relative risk at 20–29 pack-years vs 0 pack-years.
h: Smoking relative risk of current smoker vs non-smoker.
i: Incidence.
j: Smoking excess relative risk at 50 pack-years vs 0 pack-years.

ERR (9, 95%CI (5.4, 17)). The most likely possibility wasthat many of the Russian workers smoked strong cigarettes,
usually without filters and in large quantities, as stated by theauthors.5)
Risk estimates of radiation in the present study werecomparable with other studies (Table 5), while risk estimatesof smoking were slightly smaller than in other studies (Table
6). Nevertheless, our study’s results showed that radiation
risks were smaller than smoking risks (Table 4). Therefore,
it was likely that, if a low-dose radiation risk existed, it wasmuch smaller than smoking risk.
4. Limitations and strengths of this study
Our study includes some limitations, one of which was
deficiency of statistical power. Wide confidence intervals forradiation ERR comparing with other studies were causedby short person-years (591,400) and observed deaths (1,326
for all cancers excluding leukemia). Another limitation was

38

Shin’ichi KUDO, Akemi NISHIDE, Jun’ichi ISHIDA, Keiko YOSHIMOTO, Hiroshige FURUTA and Fumiyoshi KASAGI

that smoking information was outdated to some extent, since
the original questionnaires were performed in 1997 and2003, while the follow-up period closed at the end of 2010.
Significantly higher ERR per 20 pack-years was shown for
nonsmoking-related cancer, although the point estimate wasslightly smaller compared with other causes of deaths. Thismay be caused by confounding factors other than smoking.
To overcome these limitations, a new lifestyle questionnaire
survey is currently underway. The results of this new survey
may lead to more conclusive results for future research.
V

CONCLUSION

The present study provided the evidence suggesting that,even if a low-dose radiation risk for cancer mortality existed, it
was much smaller than smoking risk. This study was importantin deriving the risks of radiation and smoking simultaneously
from one cohort.
ACKNOWLEDGEMENTS
We are grateful to Professor Richard Wakeford for his
fruitful comments on the manuscript. We also thank the many
people who provided support in developing and updating thecohort.
CONFLICTS OF INTEREST
The authors indicated no conflicts of interest.
SOURCES OF FUNDING
This study was funded by the Nuclear Regulation Authorityof the Government of Japan. The funder had no role in the
study’s design, data analysis, or data interpretation or in thewriting of this manuscript.
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工藤 伸一（くどう しんいち）
1991 年，（公財）放射線影響協会放射線
疫学調査センター統計課採用。2017 年，
2019 年，日本保健物理学会論文賞受賞。
2019 年，首都大学東京大学院人間健康科学研究科人間健康科学専攻放射線科学域において，博士（放射線学）を取得。
E-mail: s_kudo@rea.or.jp