RADIATION RESEARCH 177, 86–98 (2012)0033-7587/12 $15.00
Ó2012 by Radiation Research Society.
All rights of reproduction in any form reserved.
DOI: 10.1667/RR2841.1

Effects of Radiation and Lifestyle Factors on Risks of Urothelial Carcinoma
in the Life Span Study of Atomic Bomb Survivors
E. J. Grant,a,1 K. Ozasa,a D. L. Preston,d A. Suyama,a Y. Shimizu,a R. Sakata,a H. Sugiyama,a T-M. Pham,aJ. Cologne,b M. Yamada,c A. J. De Roos,e K. J. Kopecky,f M. P. Porter,e N. Seixasg and S. DaviseaDepartment of Epidemiology, b Department of Statistics and c Department of Clinical Studies, Radiation Effects Research Foundation, 5-2 Hijiyama
Park, Minami-ku, Japan; d Hirosoft International, Eureka, California; e Department of Epidemiology, School of Public Health, University ofWashington, Seattle, Washington; f Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington; andg
Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington

revealing though there was no evidence of significant
departures from either the additive or multiplicative joint
effect models. Among the LSS cohort members with doses
greater than 0.005 Gyw (average dose 0.21 Gyw), theattributable fraction of urothelial carcinoma due to radiation
was 7.1% in males and 19.7% in females. Among current
smokers, the attributable fraction of urothelial carcinoma
due to smoking was 61% in males and 52% in females.
Relative risk estimates of smoking risk were approximately
two for smokers compared to nonsmokers. After adjustment
for lifestyle factors, gender-specific radiation risks and the
F:M ERR/Gyw, the ratios of excess urothelial carcinoma risk
were similar to the estimates without adjusting for lifestylefactors. Smoking was the primary factor responsible forexcess urothelial carcinoma in this cohort. These findings led
us to conclude that the radiation risk estimates of urothelial
carcinoma do not appear to be strongly confounded or
modified by smoking, consumption of alcohol, fruits, orvegetables, or level of education. Ó 2012 by Radiation Research Society

Grant, E. J., Ozasa, K., Preston, D. L., Suyama, A., Shimizu,
Y., Sakata, R., Sugiyama, H., Pham, T-M., Cologne, J.,
Yamada, M., De Roos, A. J., Kopecky, K. J., Porter, M. P.,
Seixas, N. and Davis, S. Effects of Radiation and Lifestyle
Factors on Risks of Urothelial Carcinoma in the Life Span
Study of Atomic Bomb Survivors. Radiat. Res. 177, 86–98(2012).

Among the Life Span Study (LSS) of Atomic-bomb
survivors, recent estimates showed that unspecified bladdercancer had high radiation sensitivity with a notably highfemale-to-male excess relative risk (ERR) per radiation dose
ratio and were the only sites for which the ERR did notdecrease with attained age. These findings, however, did notconsider lifestyle factors, which could potentially confound or
modify the risk estimates. This study estimated the radiation
risks of the most prevalent subtype of urinary tract cancer,
urothelial carcinoma, while accounting for smoking, consumption of fruit, vegetables, alcohol and level of education (asurrogate for socioeconomic status). Eligible study subjects
included 105,402 (males ¼ 42,890) LSS members who werecancer-free in 1958 and had estimated radiation doses.
Members were censored due to loss of follow-up, incident
cancer of another type, death, or the end of calendar year
2001. Surveys (by mail or clinical interview) gathered lifestyledata periodically for 1963–1991. There were 63,827 participants in one or more survey. Five hundred seventy-threeincident urothelial carcinoma cases occurred, of which 364
occurred after lifestyle information was available. Analyses
were performed using Poisson regression methods. The excess
relative risk per weighted gray unit (the gamma component
plus 10 times the neutron component, Gyw) was 1.00 (95% CI:
0.43–1.78) but the risks were not dependent upon age at
exposure or attained age. Lifestyle factors other thansmoking were not associated with urothelial carcinoma risk.
Neither the magnitude of the radiation ERR estimate (1.00
compared to 0.96), nor the female-to-male (F:M) ERR/Gyw
ratio (3.2 compared to 3.4) were greatly changed after
accounting for all lifestyle factors. A multiplicative model ofgender-specific radiation and smoking effects was the most

INTRODUCTION

Numerous epidemiological studies have reported associations between ionizing radiation (IR) exposure and bladdercancer (1–6), while others have reported associations
between lifestyle factors and bladder cancer, particularly
smoking (7–11). In the most recent cancer incidence reporton the Life Span Study (LSS) of A-bomb survivors, theurinary bladder had the highest excess relative risk (ERR)
per unit dose of radiation of any of the solid cancers otherthan the female breast (ERR/gray weighted bladder dose ¼
1.23) (1). Despite the known associations of bladder cancer
with lifestyle factors, studies attempting to quantify the riskof bladder cancer after ionizing radiation exposure haveoften not evaluated the effects of lifestyle factors. Concernsthat smoking or other unaccounted for factors may
confound or modify established bladder radiation risk
estimates have been voiced in recent UNSCEAR and ICRP
reports, and in the last LSS cancer incidence report (1, 12–14). Recently, evidence of ionizing radiation and smoking
joint effects have been reported for lung cancer in the LSS,

1 Address for correspondence: Radiation Effects Research Foundation, Epidemiology, 5-2 Hijiyama Park, Minami-ku, Japan; e-mail:egrant@rerf.or.jp.

86

RADIATION AND LIFESTYLE RISKS OF UROTHELIAL CARCINOMA

which further raises the possibility that lifestyle factors
could modify bladder cancer risk estimates (15). The
purpose of this study was to estimate the ionizing radiation
risk of the most common subtype of bladder cancer(urothelial carcinoma) in the LSS cohort using the same
methods as those used to derive the most recent ionizing
radiation risk estimates, but with the inclusion of lifestylefactors to establish whether urothelial carcinoma radiation
risk estimates were either confounded or modified bylifestyle factors.
Rather than use the broader classification of bladdercancer to define our cases, we decided to include only
persons diagnosed with urothelial carcinoma. Urothelial
carcinomas are more closely associated with lifestylefactors, whereas non-urothelial carcinoma bladder cancers
are often associated with infections, foreign bodies orinvasive cancers from neighboring organs (16). Ninety
percent of all cancers that occur in the bladder (17–19) andin the urothelium of the upper urinary tract (20) areurothelial carcinoma. Due to the common epithelium oforigin, all urothelial carcinoma have similar risk factors (18,21).
In Japan, the world age-standardized rate for the incidenceof bladder cancer was 8.2/100,000 in males and 2.0/100,00
in females accounting for 2.6% of all cancers estimated tohave occurred in 2000 (22). A higher incidence in males isseen consistently regardless of country (23). Western
European and North American rates are generally higher
than Asian rates (17).
Lifestyle factors reported to be clearly associated withbladder cancer include smoking (7, 8), occupational
exposures to certain chemicals, particularly aromatic amines(9, 10), and excessive use of certain analgesics (24).
Tobacco from cigarettes is the most common factor in theoccurrence of excess bladder cancer, accounting for 30–
50% of all cases, with a relative risk of 2–3 for smokers
compared to nonsmokers (17, 18). A diet that includes fruits
and vegetables is generally thought to offer some protection
against bladder cancer, although the literature is mixed on
the association with vegetables (11, 25). Conflicting resultson the association between urothelial carcinoma and alcohol
intake have been reported, ranging from positive (26), to no
association (27–29) to an inverse association (30). Because
socioeconomic status is broadly associated with overall
health (31), we included level of education as a surrogate forsocioeconomic status.
To determine if lifestyle factors confound or modify
ionizing radiation risks of bladder cancer, this study
estimated radiation risks of urothelial carcinomas while
adjusting for relevant lifestyle factors where data wereavailable. Lifestyle factors included smoking, level of
education, consumption of fruit, vegetables and alcohol.
Standard risk factors (e.g., age, gender, etc.) used to model
background rates were the same as in the previous incidence
study.

87

METHODSThe RERF LSS cohort consists of 120,321 A-bomb survivors. The
cohort includes a substantial fraction of all survivors who were within
2.5 km of the hypocenters at the time of the bombings along with astratified sample of survivors who were 2.5–10 km away from the
hypocenters, and a separate control group who were registered as
residents but who were not in the cities (NIC) at the time of thebombings. Eligibility was defined as LSS cohort members who havean individual radiation dose to the bladder assigned by Dosimetry
System 2002 (DS02, N ¼ 7,070 excluded) (32), and were alive and not
known to have been diagnosed with cancer when comprehensive
cancer incidence surveillance was initiated in January 1958 (33) (anadditional 7,849 excluded).
DS02-assigned gamma and neutron doses from external sourceswere based on the characteristics of the bombs and an individual’s
distance and shielding circumstances; no allowance was made forpossible doses via fallout or ingestion, the incidence of which wereconsidered to be small (34), as well as highly problematic to estimate
due to the lack of individual histories for large portions of the cohort in
the period immediately following the bombings. Radiation dose
estimates used in this analysis were adjusted to account for random
errors in the individual radiation dose estimates (35) and the total dose
was calculated as the gamma component plus 10 times the neutroncomponent to account for the greater biological effectiveness ofneutron exposures, as is typically carried out when analyzing the Abomb survivor cohort.
The total number of eligible subjects was 105,402 (males ¼ 42,890;
females ¼ 62,512). An outcome event was the diagnosis of a firstprimary, malignant urothelial carcinoma [International Classificationof Diseases — Oncology Codes 188, 189.1, 189.2 (Revision 2), andC65-C67 (Revision 3) with a morphology code 8010, 8050, 8120, or
8130] detected among persons residing within the catchment areas of
the tumor registries. Those diagnosed without histology information(i.e. from death certificates only, N ¼ 44 of 695 bladder, ureter or renal
pelvis diagnoses) were generally assigned as ‘‘Carcinoma, nototherwise specified’’ (morphology code 8010) and were therefore
included as cases. Right censoring analysis occurred at the time of a
non-urothelial carcinoma cancer diagnosis, death, or end of study
period (December, 2001).
Lifestyle factors were ascertained from four mailed questionnaires(1965, 1969, 1979, 1991) (36–39) and three clinic-based questionnaires given to a subset of the LSS from 1963–1968 (36, 40) (Fig. 1).
Despite high participation rates, different questionnaires were targeted
at different subgroups (for example, the 1965 survey targeted only
males aged 40–69 and the 1979 and 1991 questionnaires did notinclude the NIC members), resulting in less than 100% coverage of thecohort. The total number of eligible cohort members (cancer-free witha known radiation dose) who participated in a questionnaire was63,827 and the cumulative total of questionnaires was 118,170. Since
questionnaire data were not collected until after cancer surveillance
had begun, lifestyle factors were initially assigned to the ‘‘Unknown’’
category and continued to be in that category until they were assigned
to a derived value one year after the date the survey results wereobtained. Methods of calculating the derived survey values aredescribed below.
Smoking
Smoking data were available from all surveys. ‘‘Never’’, ‘‘Current’’and ‘‘Former’’ smoking categories were assigned for each questionnaire in a logically consistent manner (i.e. a transition from ‘‘Never’’to ‘‘Current’’ was allowed, but a transition from ‘‘Current’’ to‘‘Never’’ was not allowed). The last known status continued until theend of follow-up. For those who smoked, the earliest start age and thelatest stop age were calculated. Smoking intensity was recorded foreach questionnaire. Time varying values for ‘‘years since started
smoking’’, ‘‘years since quitting smoking’’ and pack-years (by88GRANT ET AL.

Alcohol Consumption
Alcohol consumption data were available from all questionnaires
except the 1965 mail survey. For each survey, total grams of ethanol
consumption per week were calculated from alcohol type andconsumption frequency. The median value across surveys wasdetermined for each individual and this value was assigned as of thedate of the first questionnaire plus one year and continued, unchanged,
throughout the follow-up period; prior to this date, they were assignedto ‘‘Unknown’’. Results are reported in drinks/week (defined as one
drink/15 grams of ethanol).
Education

FIG. 1. Mail and clinical questionnaires of the Life Span Study
cohort conducted by the Radiation Effects Research Foundation. Eachsurvey is shown in a box that details the number of eligible subjects
who participated in the survey and the cohort members targeted. The
bullets within the dotted box indicate which lifestyle factors were
included on each survey. The gray area indicates the total number of
persons with known lifestyle data by calendar year while thehorizontal lines indicate the cumulative number of unique survey
responders (right axis). The clinical subset survey was actually three
repeated surveys each of approximately 9,000 persons; the number
indicated (11,892) is the total number of unique, eligible responders.
Cancer surveillance started in 1958 and the number of eligible cohort
members was 105,402. A total of 63,829 unique persons weresurveyed.
integrating period-specific smoking intensity) were calculated. Whenknown smokers failed to record start age (or intensity) on allquestionnaires, the median value from LSS smoking peers of the samegender and birth year (five-year intervals) was assigned (males ¼
1,214; females ¼ 709). Values were assigned 1 year after receipt ofeach questionnaire. For example, a person who started smoking in
1940 (two packs/day) and responded to their first questionnaire in
1965 would be assigned an intensity of two packs/day, 25 ‘‘years since
started smoking’’, 0 ‘‘years since quitting smoking’’, and 50 packyears as of a year after their questionnaire (1966). Time-dependent
values (in this case, ‘‘years since started smoking’’ and ‘‘pack-years’’)
would accumulate with each additional year of follow-up or until (ayear after) newer information was ascertained via a later questionnaire;
all smoking-related variables would be assigned to ‘‘Unknown’’ prior
to 1966.
Fruit and Vegetable Consumption
Food frequency questions targeting fruit and vegetable consumption(separately) were available from two of the three clinical questionnaires as well as from the 1969 and 1979 LSS mail questionnaires.
The clinical questionnaires and the 1969 mail questionnaire used 3level frequency checkboxes (0–1/week, 2–4/week, almost daily). The
1978 mail questionnaire had 4-level frequency checkboxes (never, 1/
week, 2–4/week, almost daily), which was collapsed to three
categories by combining the two lowest frequency categories. A
single category (0–1/week, 2–4/week, almost daily) was assigned foreach person by first assigning a category (0, 1 or 2) for each survey
and then taking the median value for each person across all surveys(median values of 0.5 and 1.5 were assigned to the center category 1).
The derived category was assigned for the duration of follow-up as ofthe date of the first questionnaire plus one year; prior to this date, they
were assigned to the ‘‘Unknown’’ category.

Highest obtained level of educational was used as a surrogate forsocio-economic status. All questionnaires, except the last clinicalsurvey, included a question on the highest level of education. Three
categories were used (less than high school, high school, college oruniversity), and the highest reported category was assigned starting
one year after the receipt of the first questionnaire (assigned to‘‘Unknown’’ prior to this date).
Statistical Analyses
Poisson regression methods (41, 42) were used to model
background rates and the effects of ionizing radiation exposure as
ERR, and excess absolute rates (EAR). Lifestyle effects were modeled
as either a component of the background term or a separate ERR term.
The data set was cross-tabulated on city, gender, NIC status, age at
exposure (5-year groups, 0, 5, 10,..., 70 years), attained age (5-year
groups, 0, 5, 10, ..., 85–100 years), calendar year (cut points at: 1961,
1966, 1971, 1976, 1981, 1986, 1988, 1991, 1996, 1999), and radiationdose to the urinary bladder (cut points at: 5, 20, 40, 60, 80, 100, 125,
150, 175, 200, 250, 300, 500, 750, 1000, 1250, 1500, 1750, 2000,
2500, 3000 mGy). NIC members consist of a broad range of
nonexposed subjects. Additional cases from the NIC members
enhanced stability of the background rates of urothelial carcinoma
incidence. For those who smoked, cross-tabulation included timevarying levels of intensity (cut points at: 3, 8, 13, 18, 23, 33, 43.
cigarettes/day), duration of smoking, and years since quitting (cutpoints at: 5, 10, 20, 30. years). Cut points were generally chosen to
make counts similar across the groups. Alcohol consumption was also
cross-tabulated (cut points at: 0, 100, 200, 300. grams of ethanol/
week, roughly 0, 1, 2, 3. drinks/day, respectively). Other lifestylefactors (fruit consumption, vegetable consumption and level of
education) were cross-tabulated using the categories described above.
Each lifestyle factor included an ‘‘Unknown’’ category. For eachcross-tabulated cell, totals of person-years and incident cases were also
calculated. The final data set contained 466,429 cells. The cancer
registries are only able to track cancer cases that occur within the
Hiroshima and Nagasaki prefectures, which means that we will not beaware of some portion of cases that occur among those who havemigrated outside of the catchment areas. Therefore, adjustments weremade to cell-specific person-year totals depending on city, gender, age
and calendar year to account for migration into and out of thecatchment areas of the cancer registries. Migration estimates are based
upon contacting rates within RERF’s clinical follow-up cohort and areage, gender and birth-year dependent as described in Sposto et al.
(43).
The excess relative risk model was written as:
Expected rate of urothelial carcinoma¼ background rate ðc; g; n; e; a½; fÞð1 þ bdose½modifiersÞ:
Eq: ð1Þ
A gender-specific parametric model was used for background rates.
This function was the same as the Preston et al. model (1) except forRADIATION AND LIFESTYLE RISKS OF UROTHELIAL CARCINOMATABLE 1
Number of Persons, Person-Years and Case Counts
All subjects
Count
Person-years
Age at time of bombing(average)
Incident cases
Responders
Count
Person-years
Age at time of bombing(average)
Age at first questionnaire(average)
Incident cases

Males

FemalesAll

42,890108 3 104

62,512
180 3 104

105,402288 3 104

26.1
375

27.9
198

27.2
573

24,68838 3 104

39,13974 3 104

63,827112 3 104

23.6

24.0

23.9

52.4
243

52.6
121

52.5
364

Notes. The upper section is for all subjects over the full duration of
the study (1958–2001). The lower section is for subjects who
responded to a questionnaire. ‘‘Person-years’’ and ‘‘Incident cases’’ inthe lower section accrue one year after participating in a survey.
the inclusion of optional lifestyle factors. The log of the expectedbackground rate was dependent upon:c: city (Hiroshima 0, Nagasaki 1);
g: gender (male 1, female 2);
n: not-in-city status (0 in city, 1 NIC), also included an interaction
term by city;
e: age at the time of the bombing (piecewise quadratic function,centered at age 30);
a: attained age (piecewise quadratic function of log attained age,centered at age 70);
f: lifestyle factor (optionally included, as defined above).
The ERR term was linear with dose and included optional effectmodifiers that could be either continuous or categorical using indictor
variables. Optional effect modifiers included gender, age at exposure,attained age, and lifestyle factors. Models that included lifestyleeffects used all person-years and all events, but only person-years withknown information on lifestyle factors contributed to lifestyle effects
estimates. Lifestyle effects were alternatively modeled as ‘‘multiplicative’’ or ‘‘additive’’ to the radiation risks. If the lifestyle was acomponent of the background term, the radiation effect was relative to,or ‘‘multiplicative’’ of the lifestyle-adjusted background rates. If thelifestyle factor was removed from the background term and includedin the ERR term, then the radiation and lifestyle effects were‘‘additive’’ and their summed effects were relative to the backgroundrates. Statistical tests for departures from the preceding multiplicativeor additive ERR models were also performed [see Pierce et al. for amore complete development of these methods (44)]. Sub-analyses
included calculations of radiation and smoking attributable fractions
using an additive ERR model. Another sub-analysis modeled packyears of smoking as an additive ERR term to model total smoking
exposure as suggested by Lubin et al. (45).
A separate model form evaluated the excess absolute rates (EAR) of
urothelial carcinoma due to radiation exposure, which takes the form:
Expected rate of UN ¼ background rateðc; g; n; e; a½; fÞþ EARðd; g; e; aÞ

Eq: ð2ÞThe ‘‘background rate’’ term is the same as the ERR model (i.e. a
log-linear parametric model that can optionally include lifestylefactors). The EAR term models the excess absolute rate of cases due toradiation exposure (d) and can be modified by any factor that89

contributes to the background rates, in particular gender (g), age at
exposure (e), and attained age (a).
Point estimates and 95% confidence intervals (two-sided) based on
Wald statistics were reported for factors modeled in the log-linear
background term. Confidence intervals based on the profile likelihood
function were reported for ERR, EAR, and female-to-male risk ratio
point estimates. Gender-averaged ERR estimates were arithmetic
means of the gender-specific risks (not weighted means). ERR andEAR models were fit and evaluated using Epicure (46). Trends oflifestyle effects on urothelial carcinoma risks were tested by assigningordinal values (0, 1, 2, ...) for ordered categories and evaluating the Pvalue for a linear fit (double-sided, significant at P , 0.05).
Associations of radiation exposure with categories of lifestyle factors
were assessed using tertiles of radiation exposure (excluding the NIC
group) and testing using the Kruskal-Wallis equality-of-populations
rank test as well as a nonparametric test for trends across orderedgroups (47). Likelihood ratio tests (LRT) were used to quantify
statistical improvements of model fit. Akaike Information Criteria(AIC) were used to compare goodness of fits among nonnested models(48).
This study was approved by RERF’s Human Investigation
Committee.

RESULTSOf the 105,402 eligible subjects, 57.6% of males and62.6% of females participated in one or more surveys (Table1). The total number of incident urothelial carcinoma cases
was 573, of which 364 (64%) occurred at least one year
after the subject had participated in a questionnaire. Nearly
twice as many cases occurred in males as in females. Those
who participated in a questionnaire were about 3.6 years
younger at the time of the bombing compared to the overall
cohort. Crude incidence rates of urothelial carcinoma weresimilar regardless of whether or not a cohort member
ultimately participated in a survey (Nonresponders: 2.06/
10,000 person-years; Responders: 1.96/10,000 personyears, data not shown).
The effects of gender-averaged lifestyle factors on
urothelial carcinoma risk are shown in Table 2. Lifestylefactors were modeled as components of the background andeach was modeled independently using an ERR model [Eq.
(1)]. The radiation risk estimates while adjusting for eachlifestyle factor, are presented separately (Table 3). A‘‘baseline model’’ that did not include lifestyle factors
was used as a null model for likelihood ratio tests. The
structure of the baseline model was the same as used by
Preston et al. (1) ERR model, only differing in the casedefinition, exit date, and lack of age-related radiation effectmodifiers; the effect modifiers were removed because
neither was statistically significant and their inclusion did
not improve model fit (P . 0.50; data not shown). In thelifestyle-adjusted models, those suffering an event when
their lifestyle information was ‘‘unknown’’ were included ina separate category; those results are not reported. Urothelial
carcinoma risks generally decreased slightly with increasinglevels of education, vegetable and fruit consumption;
however none of the trend tests were significant (modelinga single term with the ordinal values and one degree of

90

GRANT ET AL.

TABLE 2
Associations of Individual Lifestyle Factors with Urothelial Carcinoma
Lifestyle-related risks
LifestyleCasesaRelative risk

95% CI

P (trend)

LRT

None (baseline model)
EducationLess than High School
High School
College
Vegetable
0–1/week
2–4/week
4þ/week
Fruit
0–1/week
2–4/week
4þ/week
Alcohol
0 drinks/day
0–1 drinks/day
1–2 drinks/day
2–3 drinks/day.3 drinks/day
Smoking
Never
FormerCurrent

573

-

-

-

-

176
135
40

Ref
0.93
0.81

0.74–1.17
0.57–1.15

0.24

.0.50

81
109
40

Ref
0.72
0.75

0.54–0.97
0.51–1.10

0.11

0.07

54
85
103

Ref
0.71
0.81

0.51–1.02
0.58–1.14

0.39

0.34

109
65
40
41
36

Ref
1.17
0.99
0.97
0.97

0.86–1.60
0.67–1.47
0.66–1.43
0.64–1.46

.0.50

.0.50

99
45
213

Ref
1.21
1.99

0.83–1.78
1.50–2.63,0.001,0.001

Notes. Relative risk, 95% confidence intervals, P value for trend test, and the improvement in model fit asdetermined by the likelihood ratio test (compared to the ‘‘baseline model’’, which was not adjusted for lifestylefactors). All estimates were derived with categories of a lifestyle modeled as part of the background term. Eachmodel also included radiation as a gender-averaged excess relative risk term (ERR/weighted-Gy). Lifestyles
were modeled individually and were not adjusted for each other. Radiation estimates adjusted for lifestyle factors
are reported in Table 3.
aCase totals in lifestyle-adjusted models are less than the ‘‘baseline model’’ as they accrue only after
questionnaire data have been ascertained. Also, case totals may not match in lifestyle-adjusted models due tomissing data.

freedom), nor did the likelihood ratio tests indicate any
improvements in overall model fits (each category modeled
independently with three degrees of freedom). There was nosuggestion of an association between urothelial carcinoma
and alcohol consumption. On the other hand, the relativerisk of smokers compared to never smokers was 1.99 (95%
CI: 1.50–2.63), while those who indicated that they had quit

smoking had a marginally elevated relative risk of 1.21
(95% CI: 0.83–1.78). The trend test for smoking (never,former, current) was highly significant as was the
improvement in model fit (P , 0.001).
Table 3 shows the radiation risk estimates of urothelial
carcinoma while adjusting for lifestyle factors. Genderaveraged ERR estimates of urothelial carcinoma and

TABLE 3
Radiation-Related Risks Adjusted for Lifestyle Factors
Radiation-related excess relative risks (ERR/Gywa)

Radiation-related excess absolute ratesb (EAR/Gyw)

Adjusted forLifestyle Factor Casesc Gender-averaged

95% CI

Gender ratio(F:M)

95% CI

Gender-averaged

95% CI

Gender ratio(F:M)

95% CI

Education
Vegetable
Fruit
Alcohol
Smoking

0.43–1.78
0.42–1.78
0.44–1.82
0.44–1.84
0.42–1.77
0.41–1.77

3.26
3.23
3.16
3.23
3.20
3.71

0.88–.10
0.87–.10
0.86–.10
0.89–.10
0.85–.10
0.97–.10

3.02
2.97
3.11
3.13
3.10
2.40

1.05–5.40
0.98–5.35
1.10–5.51
1.12–5.54
1.10–5.49
ND–4.75

0.70
0.71
0.65
0.71
0.67
1.02

0.19–4.86
0.19–.10
0.18–.10
0.20–.10
0.18–.10
0.19–.10

573
351
230
242
291
349

1.00
1.00
1.03
1.04
1.00
0.99

Note. Categories of lifestyle factors (modeled as gender-averaged background terms) were as shown in Table 2.
aWeighted gray (Gyw) is the gamma component plus 10 times the neutron component.
bRates are per 10,000 PYGyw.
cCase totals in lifestyle-adjusted models accrue only after questionnaire data have been ascertained and may not match due to missing data.

RADIATION AND LIFESTYLE RISKS OF UROTHELIAL CARCINOMA

91

FIG. 2. Radiation dose categories compared to lifestyle categories
in men. The percentages of men in the hypothesized at-risk categories
are shown for 4 levels of radiation exposure. The ‘‘at-risk’’ categories
were defined as the lowest category of vegetable and fruit
consumption (0–1/week), the lowest category of education (less thanhigh school), current smokers (as of the last questionnaire) and morethan one drink of alcohol per day. P values associated with tests
excluded ‘‘not in city’’ persons, as they were not included inquestionnaires after 1965. ‘‘Equality’’ P values refer to the null
hypotheses that frequencies of lifestyle categories (as defined in Table2) were the same for each radiation exposure level (tertiles) using the
Kruskal-Wallis equality-of-populations rank test. ‘‘Trend’’ P values
were derived from a nonparametric test for a trend across orderedgroups.

FIG. 3. Radiation dose categories compared to lifestyle categories
in women. The percentages of women in the hypothesized at-risk
categories are shown for 4 levels of radiation exposure. The ‘‘at-risk’’categories were defined as the lowest category of vegetable and fruit
consumption (0–1/week), the lowest category of education (less thanhigh school), current smokers (as of the last questionnaire) and morethan zero grams of alcohol per day. P values associated with tests
excluded ‘‘not in city’’ persons, as they were not included inquestionnaires after 1969. Equality P values refer to the null
hypotheses that frequencies of lifestyle categories (as defined inTable 2) were the same for each radiation exposure level (tertiles)
using the Kruskal-Wallis equality-of-populations rank test. Trend P
values were derived from a nonparametric test for a trend acrossordered groups.

female-to-male ERR per weighted-gray ratio (F:M ERR) are
shown in Table 3. Lifestyle categories were the same as in
Table 2. ERR risk estimates were largely unchanged when
adjusting for each lifestyle factor and ranged from 0.99/Gyw(95% CI: 0.41–1.77) for the smoking-adjusted model to
1.04/Gyw (95% CI: 0.44–1.84) for the model adjusted for
fruit consumption. These estimates were nearly the same asthe ‘‘baseline model’’ estimate of 1.00/Gyw (95% CI: 0.43–
1.78). Similarly, the F:M ERR ratios were quite stable
ranging from 3.16–3.71 compared to the ‘‘baseline model’’estimate of 3.26 (with very large confidence intervals for all
ratio estimates). Only the smoking-adjusted model was
significantly improved over the unadjusted model, yet the
ERR estimate was nearly unchanged while the F:M ERR
estimate increased modestly.
The right panel of Table 3 shows EAR and female-tomale EAR per weighted-gray ratio (F:M EAR) risk
estimates with and without adjustments for gender-averaged
lifestyle factors. The EAR model is the same as that used by
Preston et al. (1), including the age-related radiation risk
modifiers (again differing in case definition and exit date).
Gender-averaged EAR/Gyw estimates ranged from 2.40–
3.11 cases/10,000 P-Y-Gyw (person-years* weighted-gray)for the lifestyle-adjusted models compared to 3.02 (95% CI:
1.05–5.40) cases/10,000 P-Y-Gyw for the unadjusted model.
The F:M EAR estimate was approximately 0.70 for allmodels except the smoking-adjusted model, in which thefemale risk was greater than the male risk (1.02), albeit withlarge confidence intervals (0.19–.10.0).

Figures 2 and 3 show the percentage of persons in the(presumed) most deleterious category of various lifestyles(i.e., lowest fruit, vegetable or education levels; smoker asof the last questionnaire; more than 1 drink per day among
men and more than 0 drinks per day among women). To test
whether radiation exposure levels possibly led to different
choices in lifestyles, gender-specific tertiles of radiation
exposure were tested against categories of lifestyle factors(as defined in Table 2). While NIC persons were included in
Figs. 2 and 3, they were not included in this sub-analysis as
they were excluded from many of the surveys, including the
major surveys occurring in the later years of follow-up. For
nearly all lifestyles, there was evidence to reject the null
hypothesis that radiation exposure levels were not associated with different levels of lifestyle factors. However, there
was little evidence to support trends of the orderedcategories of lifestyle factors by radiation tertiles, particularly among men. There did appear to be higher levels of
education associated with higher levels of radiation
exposure among both men and women.
Notable results for bladder cancer from Preston et al. (1)included a female-to-male (F:M) excess relative risk ratio ofover 3 and a rise of ERR estimates with increasing attained
age with follow-up through 1998 (1). Those bladder cancer
results are compared to radiation risk estimates of urothelial
carcinoma with three additional years of follow-up shown in
Table 4 (438 cancers were common to the two studies).
Without considering lifestyle factors (‘‘Current Data’’),urothelial carcinoma significantly increased with ionizing

92

GRANT ET AL.

TABLE 4Comparison of Previous Analysis of Radiation-Associated Bladder Cancer Risk and Current Risk Estimates ofUrothelial Carcinoma
Background ratesa
Model

Male

FemalePreston et al.
Current datae
Current data, adjusted for all lifestyle factors f

7.8
9.1
5.0

1.6
2.1
2.6

Preston et al.
Current datae
Current data, adjusted for all lifestyle factors f

7.8
9.2
5.0

1.6
2.2
2.9

Radiation risks
Gender-averaged Male Female F:M ratio
Excess relative risks (ERR/Gywd)
1.23
0.61
1.9
3.1
1.00
0.47
1.5
3.2
0.96
0.44
1.5
3.4
Excess absolute risksg (EAR/Gyw)
3.2
3.8
2.6
0.68
3.0
3.6
2.5
0.70
2.7
2.9
2.5
0.87

Radiation risk age modifiers
Age ATBb

Age (power)c

–3%
–1%
–5%

0.33
–0.34
–0.27

–19%
–21%
–25%

6.3
5.8
6.0

Notes. The previous analysis was for bladder cancer for the period 1958–1998 (N ¼ 469 cases) whereas these analyses are for urothelial
carcinoma during the period 1958–2001 (N ¼ 573 cases). Variables in the background term are identical in all three models except for the
inclusion of lifestyle information in the last model. Inclusion of the ‘‘age modifiers’’ does not significantly improve any of the ERR models. The‘attained age’ modifier in the EAR models was highly significanta
Per 10,000 PY (estimated at ATB of 30 years with an attained age of 70 years).
b
Percentage change per decade increase in age at the time of bombing (ATB). Parameter was centered: (ATB-30)/10.
c
Power of attained age. Parameter was centered: log(age/70).
d
Weighted gray (gamma component plus 10 times the neutron component).
eSame model as the Preston et al. model using urothelial carcinoma as cases and follow-up through 2001.
fSame as the Preston et al. model but included gender-specific lifestyle categories in background term.
g
Excess cases per 10,000 P-Y-Gyw.

radiation exposure having a gender-averaged estimate of
1.00 ERR/Gyw, which was slightly less than Preston et al.
estimated for bladder cancer using a shorter follow-up
period and non-urothelial carcinoma bladder cancers (1.23
ERR/Gyw) (1). The F:M ERR was nearly the same forurothelial carcinoma and for the value previously reported
for all bladder cancer (3.2 compared to 3.1). Age-related
radiation effect modifiers (attained age and age-at-exposure)
were not statistically different than those derived by Preston
et al. After adjusting for all lifestyle factors simultaneously,
all ERR parameter estimates were nearly unchanged,
compared to the unadjusted estimates.
A comparison of the estimates for EAR is shown in Table
4. Again, bladder cancer and urothelial carcinoma risks
were similar. Adjustments for lifestyle factors modestly
reduced the EAR/Gyw in males while it had no effect amongfemales. Note that in both the ERR and EAR models,
redefining the background to include lifestyle factors
resulted in substantial changes to the rates in the referencegroup, indicating that lifestyle factors (primarily smoking inmales) were strongly associated with urothelial carcinoma
risk.
The attributable fractions of cases caused by radiation
exposure and smoking are shown in Table 5. These
fractions are based on fitted background and excess cases
using an additive risk model (Eq. 1, with both radiation andsmoking modeled as ERR terms without effect modifiers).
Among those with radiation dose greater than 0.005 Gyw(average ¼ 0.21 Gyw), the attributable fraction of urothelial
carcinoma due to radiation exposure was 7.1% (11.5/161.4)
in males and 19.7% (19.1/97.0) in females, while for theentire cohort, the population attributable fraction ofurothelial carcinoma due to radiation was 3.1% in males

and 9.7% in females. The population attributable fraction ofurothelial carcinoma due to smoking was 53.4% in males
and 5.2% in females, while among current smokers (only),
the smoking attributable fraction was 61.0% in males and52.1% in females.
Substituting pack-years of smoking for smoking categories (Never, Former, Current) in the same ERR additivemodel described in the previous paragraph (Eq. 1), the ERR/
pack-year was 0.028 in males and 0.060 in females. By
dividing the gender-specific ERR estimates of radiation by
the ERR estimates of pack-years of smoking, roughequivalencies can be calculated. We find the risk of 1
Gyw of radiation exposure to the urothelial carcinoma tract
is equivalent to the risk of smoking for about 25 pack-years.
This value is roughly the same for both males and females(male: 0.85 Gyw1/0.028 PY1 ¼ 30; female: 1.4 Gy1/0.060
PY1 ¼ 23). Said another way, one abdominal CT-scan with
20 mGy dose to the bladder has about the same urothelial
carcinoma risk as smoking 10 cigarettes/day for one year.
By including a time-varying modifier of years sincequitting for ex-smokers, the estimated reduction in urothelial carcinoma risk for each additional year of smoking
cessation was about 5% but this value was not statisticallysignificant.
Table 6 shows the gender-specific effects of smoking onurothelial carcinoma risk using more detailed measures ofsmoking habits. While the data aren’t shown, prevalence ofsmoking among males was very high (84% ever smokers)
and quite low among females (16% ever smokers). As withthe results shown in Table 2, smoking measures were
included in the background term while the radiation effectwas modeled as an excess relative risk. The radiation risksof urothelial carcinoma risks are not shown, but are stable

93

RADIATION AND LIFESTYLE RISKS OF UROTHELIAL CARCINOMATABLE 5Attributable Fraction Based on Fitted Counts of Background and Excess (radiation and smoking) Urothelial Carcinoma by
Gender and Radiation Dose and Current Smoking Status (all values rounded to one decimal place)
Dose category(weighted-Gya)
Males by radiation dose
NICb
0–,0.005
0.005–0.1
0.1–0.2
0.2–0.5
0.5–1.0
1.0–2.0.2.0
Total (all)Total (dose .0.005)
Total (current smokers)
Females by radiation dose
NICb
0–,0.005
0.005–0.1
0.1–0.2
0.2–0.5
0.5–1.0
1.0–2.0.2.0
Total (all)Total (dose .0.005)
Total (current smokers)

Fittedtotal cases

Fittedbackground

Fittedradiation excess

Fittedsmoking excess

Radiation
attributable fraction

Smoking
attributable fraction

98.1
115.5
93.9
19.9
21.6
13.3
9.4
3.2
375.0
161.4
183.3

42.9
52.4
42.1
8.6
8.8
4.8
2.8
0.8
163.2
67.9
65.1

0.0
0.0
1.1
1.0
2.2
2.7
3.0
1.5
11.5
11.5
5.4

55.2
63.0
50.7
10.4
10.6
5.8
3.6
1.0
200.3
82.1
112.8

0.0%
0.0%
1.2%
4.8%
10.4%
20.3%
32.0%
45.5%
3.1%
7.1%
3.0%

55.2%
53.0%
59.6%
57.9%
44.0%
44.8%
25.5%
50.4%
53.4%
52.6%
61.0%

42.9
58.1
49.6
12.8
15.7
10.3
6.2
2.3
198.0
97.0
27.4

41.0
55.4
44.9
9.8
9.9
4.9
2.0
0.5
168.5
72.0
11.2

0.0
0.1
2.0
2.0
4.6
4.8
3.9
1.8
19.2
19.1
2.0

1.9
2.6
2.7
1.0
1.1
0.7
0.3
0.1
10.3
5.9
14.3

0.0%
0.1%
4.0%
15.9%
29.5%
46.5%
62.6%
75.7%
9.7%
19.7%
7.3%

4.4%
4.5%
5.5%
7.4%
7.2%
6.5%
5.0%
2.6%
5.2%
6.0%
52.1%

a

Weighted gray (gamma component plus 10 times the neutron component).
Not in city at the time of the bombing.

band consistent with those obtained in the left panel of Table
3. Those who reported they had quit smoking had asignificantly lower risk of urothelial carcinoma than did
those who continued to smoke (P ¼ 0.002). Point estimatesfor duration of smoking (by decade) were elevated for alltimes and for all gender categories, but were generally notsignificant until smoking 20 years. The trend test for
greater risks with longer smoking duration was highly
significant. Similar results were observed when modelingthe smoking risk using intensity (cigarettes/day) and packyears of smoking. Regardless of the measure of smoking(duration, intensity or pack-years), urothelial carcinoma
risks of smoking rose quickly, generally reaching a nearmaximum level in the first or second ordinal category above
the reference category, and then leveling off at a relativerisk of roughly 2. Spline models to account for this plateau
effect did not significantly improve the model fit over linear
models (results not shown). Comparisons of all urothelial
carcinoma risk models tested (Tables 3 and 6) found that an
ERR model with gender-specific smoking categories in the
background term had the lowest AIC value.
Using Lubin’s suggested model for total smoking
exposure,2 a parametric dose-response curve [b: 0.023(NS), /1 ¼ 0.74 (NS), /2 ¼ 0.17 (NS)] as well as point
2 ERR ¼ b
2
 packyears  eintensity where intensity is: u1loge(cigs/day) þ u2(loge(cigs/day))2.

estimates for different values of smoking intensity were
derived and plotted in Fig. 2 (point estimates were plotted at
the average intensity for each group). Due to the model
structure, the shape of the curve in Fig. 4 is predictably
consistent with Lubin’s results. However, the apparent
modification of smoking risk by intensity was not
significant (LRT P ¼ 0.24).
Joint effects of radiation and smoking were also
investigated. There was no evidence (P ¼ 0.46) of astatistically significant departure from a model in which thejoint effect of radiation and smoking was assumed to be
multiplicative (AIC ¼ 6216.9). However an additive model
described the data equally well (AIC ¼ 6214.6), and a test
for a departure from additivity was also not significant (P ¼
0.13).
DISCUSSIONHigh radiation risks of urothelial carcinoma were evident
in both males and females with a high F:M ERR ratio.
Models that estimated urothelial carcinoma risks afterradiation exposure while simultaneously adjusting for all
considered lifestyle factors did not appreciably change theionizing radiation risk estimates. Although a number ofother lifestyle factors were considered as additional
urothelial carcinoma risk factors, a model with genderspecific smoking categories (Never, Former, Current) in the

94

GRANT ET AL.

TABLE 6Urothelial Carcinoma Risks by Gender and Various Measures of Smoking
Males
Cases
Smoke
Never
17
Former39
Current
185
Duration (years)
Never
17.0–,106
10–, 209
20–,3025
30–,404140–,5064
5079
Intensity (cigarettes/day)
0
56
1–,8
14
8–,1348
13–,1813
18–,2376
3
34
Pack-years
0171–,1010
10–,2014
20–,3042
30–, 4067
40–, 5047
50
44

Females

Relative
risk

CI

P

Ref
1.68
2.74

0.95–2.98
1.67–4.52

Ref
1.82
1.59
2.58
2.43
2.64
2.76

Both Sexes

Cases

Relative
risk

Cases

Relative
risk

CI

P

CI

P

0.07
,0.001

82
6
28

Ref
1.24
2.20

0.54–2.86
1.43–3.38.0.5,0.001

99
45
213

Ref
1.21
1.99

0.83–1.78
1.50–2.65

0.32,0.001

0.72–4.63
0.71–3.58
1.39–4.80
1.37–4.31
1.54–4.52
1.62 4.70

0.21
0.26
0.003
0.002
,0.001,0.001

82
4
6
7
4
8
5

Ref
1.71
2.24
2.07
1.17
2.50
2.32

0.63–4.69
0.97–5.13
0.95–4.47
0.43–3.21
1.20–5.18
0.93–5.76

0.29
0.06
0.07
.0.50
0.01
0.07

99
10
15
32
45
72
84

Ref
1.48
1.44
1.90
1.66
1.95
2.05

0.77–2.87
0.82–2.51
1.25–2.89
1.13–2.43
1.38–2.75
1.45–2.91

0.24
0.20
0.003
0.01
,0.001,0.001

Ref
1.77
2.15
1.42
2.03
2.06

0.93–3.02
1.45–3.17
0.78–2.61
1.44–2.88
1.33–3.18

0.08,0.0010.25,0.001
0.001

88
6
13
5
3
1

Ref
1.40
2.66
3.20
1.65
2.70

0.61–3.22
1.48–4.76
1.30–7.87
0.52–5.22
0.38–19.4

0.42
0.001
0.01
0.40
0.32

144
20
61
18
79
35

Ref
1.51
2.10
1.56
1.85
1.88

0.95–2.44
1.53–2.87
0.95–2.58
1.37–2.49
1.27–2.78

0.08,0.0010.08,0.001
0.002

Ref
2.44
1.76
2.50
2.54
2.34
3.21

1.11–5.33
0.87–3.57
1.42–4.41
1.49–4.34
1.34–4.08
1.82–5.65

0.02
0.12
0.001
,0.001
0.003,0.001

82
10
16
5
2
1
0

Ref
1.58
2.40
1.43
2.74
8.69
-

0.82–3.06
1.40–4.11
0.58–3.53
0.67–11.2
1.20–62.6

0.17
0.001
0.44
0.16
0.03
-

99
20
30
47
69
48
44

Ref
1.74
1.74
1.75
1.84
1.73
2.38

1.07–2.82
1.14–2.64
1.20–2.54
1.29–2.61
1.16–2.56
1.57–3.62

0.02
0.01
0.003
,0.0010.006,0.001

Note. Smoking was modeled as part of the background term while radiation was modeled as an excess relative risk (radiation estimates notshown).

background term and ERR ionizing radiation effects with nodependence on age-at-exposure or attained age, had thelowest AIC value. The estimated number of excess cases
attributable to radiation exposure was approximately 11 inmales and 19 in females, corresponding to an attributablefraction of 7.1% and 19.7%, respectively, among those
exposed to more than 0.005 Gyw. The estimated number ofexcess cases due to smoking was 200 in males and 10 infemales. We calculated that one abdominal CT scan with 20
mGy dose to the bladder has about the same urothelial
carcinoma risk as smoking 10 cigarettes/day for one year.
Urothelial carcinoma is the dominant form of bladder,ureter and renal pelvis cancers. Of the three cancer sites,
bladder cancer is by far the most frequent. Therefore,
comparisons of urothelial carcinoma to bladder cancer inother studies should be valid in most situations. The primaryadvantages of defining the cases as urothelial carcinoma
were to exclude cases that may not be related to lifestylefactors and to increase the case counts by using additionalsites.
Of the five lifestyle factors considered, only smoking was
significantly associated with urothelial carcinoma risk,
however, some suggestion of a lowered background risk
was evident for higher levels of education, fruit andvegetable consumption. The lack of significant associations
with dietary factors were somewhat surprising as Nagano etal. found protective effects for vegetable consumption andmarginal protective effects for fruit consumption in thesame cohort (49). Our results, however, were not qualita-

FIG. 4. Gender-averaged excess relative risk of urothelial
carcinoma per pack-year of smoking, modified by intensity. The‘‘total exposure’’ model suggested by Lubin et al.

RADIATION AND LIFESTYLE RISKS OF UROTHELIAL CARCINOMA

tively inconsistent with those findings and there were anumber of differences between the two studies that may
account for the lack of full agreement. In particular, Nagano
et al. limited their study to only those who participated in
the 1979 LSS mail questionnaire (114 incident cases) with
13 years of follow-up.
Preston et al. reported high ionizing radiation risks of
bladder cancer with a high F:M ERR ratio (1). We observedslightly lower gender-specific point estimates and a similar
F:M ERR ratio using urothelial carcinoma as an end pointand 3 years of additional follow-up data. While the finding
was not significant, Preston et al. noted that ERR increased
with attained age, a finding that was not consistent withmost solid organs. Our point estimate indicated a decreased
risk with attained age that was not significant. Generally
speaking, radiation excess relative risk estimates tend to
decrease with attained age, but only a limited set of organs
are strongly age dependent. Also of note is the similarity of
our findings to the mortality-based ERRs reported among
the A-bomb survivors for the follow-up period 1950–1997(50). In that report, the ERR/Gy for bladder cancer deaths
among males was 1.1, while it was 1.2 in females(compared to 0.44 and 1.5, respectively, in this report).
Women treated for cervical cancer with high doses ofradiation (30–60 Gy bladder dose) were reported to have ahigh relative risk of bladder cancer (as well as renal pelvis
and ureter cancers). They also noted that controlling forsmoking did not alter the radiation risk, and that there was
no evidence that ionizing radiation and smoking effects
interacted multiplicatively (3). Weiss et al. reported a
relative risk of bladder cancer death of approximately 2 after
exposure to an average of 2.2 Gy with no dependence on
years since exposure; the study did not attempt to control forsmoking (6). In studies of lung cancer incidence andsmoking among the A-bomb survivors, Pierce et al. (44)reported statistical evidence to reject an additive model, but
not a multiplicative model, while Furukawa et al. (15),using additional follow-up data, rejected both additive andmultiplicative models in favor of a generalized interaction
model in which multiplicative effects were observed amonglight smokers, but additive effects were observed among
heavy smokers. Lung cancer, however, is more strongly
associated with smoking than urothelial carcinoma andthose studies had many more incident cases, which afforded
greater power to detect interactions. Both Pierce andFurukawa reported a reduction of the F:M ERR in models
that included smoking. In this study, it was not possible toreject either additive or multiplicative joint effects but theresults suggest that the combined effects lay somewhere
between additive and multiplicative.
Lifestyle factors could conceivably confound the relationof radiation exposure and urothelial carcinoma if a factor isassociated with both radiation exposure and outcome. The
city centers were more urban than surrounding areas andtherefore, it is not unreasonable that the education level inthe city centers may be higher than in the surrounding areas

95(this is supported by Figs. 2 and 3), indicating a higher
socioeconomic status and likely better access to healthcarewith a higher estimated radiation dose. If this scenario weretrue, the radiation risk estimate may be underestimated if thelevel of education was ignored. It is also conceivable thatsurrounding areas may have had more agricultural land andlocal farming, raising their intake of vegetables and fruits intheir diet (possibly resulting in an overestimation of healthcare radiation risk by preferentially lowering the background risk among the distal survivors). Lifestyle factors
could also conceivably be on a causal pathway between
radiation exposure and outcome. This could happen if aperson decided to smoke or drink more after surviving the
A-bombing. In these cases, unadjusted health care radiation
risk estimates would be a combination of both risk factors.
The adjusted risk estimates would be ‘‘over and above’’ therisks incurred by the resultant lifestyle change, and more
appropriate models would be required to assess the total andmediated risks for radiation.
Despite the heterogeneity of lifestyle factors by radiation
exposure tertiles, and the plausibility that lifestyle factors
could confound or modify urothelial carcinoma radiation
risks, we did not observe any major changes in either thegender-averaged or gender-specific radiation risk estimatesof urothelial carcinoma after adjusting for lifestyle factors(Table 4). This indicates that the gender-averaged, genderspecific and F:M ERR and EAR ratio estimates of bladdercancer risks reported in previous incidence studies of the
LSS cohort were unlikely to have been strongly affected byignoring smoking effects or other considered lifestylefactors. The primary impact on the models is the change
in background rates for the reference group. When adjusting
for lifestyle factors, the background rate for nonsmokers
dropped by about 40% in males compared to all men,regardless of smoking status. This difference does not
greatly affect the radiation risks, but it does alter theattributable fraction (i.e., shifting the cause of cases tosmoking and away from radiation exposure). Preston et al.
reported that the radiation attributable fraction of bladdercancers was 16.4% among those with greater than 0.005
Gyw exposure (1). Among the same group, we calculate theattributable fraction of urothelial carcinoma due to radiation
was 11.8% overall, and only 7.1% among males (Table 5).
This study has a number of strengths and limitations. In
terms of strengths, all data were collected prospectively.
Cancer incidence and censoring due to mortality werecarried out using consistent methods over a period of 45
years. The cohort was large and radiation doses to thebladder were well characterized. In terms of study
weaknesses, recorded lifestyle factors were not collected
in a consistent manner (self-reported or recorded during aclinical interview) and some categories of lifestyle habitswere not consistent across questionnaires. Collection oflifestyle factors began in 1963 and the last update oflifestyle data was collected in 1991; NIC members were notincluded in the last two major questionnaires. Cancer

96

GRANT ET AL.

follow-up did not begin until 1958, 13 years after thebombings. Dietary questionnaires were fairly crude bytoday’s standards, simply using food frequency of broad
categories of foods without any regard to portion size.
Accounting for migration into and out of the catchment
areas is difficult to validate and may not be free of bias.
Finally, another known risk of urothelial carcinoma is
occupational exposure to certain chemicals and these were
not considered in this analysis. However, none of theselimitations is likely to greatly impact the results orinvalidate the conclusions of the research.
Due to the size and long follow-up period of this Japanesecohort, the estimated effects of smoking on urothelial
carcinoma risk may be of general interest. We found the riskof urothelial carcinoma increased with increasing levels ofintensity, duration, and pack-years of smoking, consistent
with other published studies. When modeling the effects ofradiation and smoking as gender-specific additive excess
relative risks (Eq. 1), the ERR/pack-year of smoking was
0.028 in males and 0.060 in females. Risk estimates using
any measure of smoking intake level quickly plateaued. The
population (i.e. the full cohort) attributable fraction ofurothelial carcinoma due to smoking in males was 53%
while it was only 5% in females. The prevalence of everhaving smoked among females, however, was small (16%).
Among current smokers, the gender-specific attributablefractions were similar: 61% in males and 52% in females.
The smoking-related risk of urothelial carcinoma has beenreported to be similar for both males and females (51) whilesome have reported that the risk is higher in females (52). A
recent report among the Japanese ages 40–69 at the start offollow-up (1990) and followed over 15 years showed anrelative risk of 1.7 for male smokers and an relative risk of
5.4 for female smokers (compared to never smokers) (53).
Our results indicated that male smokers had a slightly
higher risk compared to female smokers. With regard toquitting smoking, we found that smokers who quit had
lower risks than those who continued to smoke which isconsistent with other reports, the time-course of the reduced
risks is unclear in this study. Some reports have indicatedthat beyond 15 years, the risk in former smokers is the sameas in those who never smoked (51) whereas others havereported an immediate decrease in risk (54) that neverreaches nonsmoker levels (18). We found no dependence on
the years of cessation, but if the risk reduction occurred
rapidly, the timing of our questionnaires may not haveallowed us to detect time trends.
At least two studies have applied Lubin’s total smoking
exposure model (pack-years modified by intensity) to casecontrol bladder cancer data. Lubin (45) and Baris (55) foundincreased excess odds ratios per pack-year of smoking at
lower levels of smoking intensity. We found no statisticalevidence that smoking intensity modified pack-years ofsmoking risk estimates.
With our findings generated from a cohort of A-bomb
survivors, there may be some concern as to whether thesmoking findings are affected by the unique nature of thecohort. However, as most of the excess urothelial carcinoma
cases were attributable to smoking and not radiation, thesmoking findings detailed above should not be largely
influenced by the radiation exposure.
In conclusion, a number of models incorporating radiation
exposure and different measures of lifestyles were examined
and compared. Radiation risk estimates for urothelial
carcinoma were largely unchanged when incorporating allof the lifestyle factors into the analyses. Smoking was
associated with urothelial carcinoma risk, but the nature of
the joint effects of smoking and ionizing radiation onurothelial carcinoma risks could not be determined
precisely. Some evidence of heterogeneity of lifestyle factor
categories was evident among different radiation dose
categories, which will require further investigation. Researchers and others concerned that RERF radiation risk
estimates for urothelial carcinoma or bladder cancer may bemarkedly biased by unaccounted for lifestyle factors should
be reassured by these findings.
ACKNOWLEDGMENTS
We thank the members of the LSS for their participation. The Radiation
Effects Research Foundation (RERF), Hiroshima and Nagasaki, Japan is a
private, nonprofit foundation funded by the Japanese Ministry of Health,Labour and Welfare (MHLW) and the U.S. Department of Energy (DOE),
the latter in part through DOE Award DE-HS0000031 to the National
Academy of Sciences. This publication was supported by RERF ResearchProtocol RP A7-08. The views of the authors do not necessarily reflect
those of the two governments.
Received: October 24, 2011; accepted: February 7, 2012; published
online: May 25, 2012

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