American Journal of Epidemiology
Copyright © 2000 by The Johns HopWns University School of Hygiene and Public Health
All rights reserved
Vol. 151, No. 3
Printed in U.S.A.
An latrogenic Epidemic of Benign Meningioma
Siegal Sadetzki,1 Baruch Modan,1 Angela Chetrit,1 and Laurence Freedman1'2
Head irradiation, the acceptable mode of treatment for tinea capitis in the past, is recognized today as a
causative factor for meningioma. This treatment was applied en mass to immigrants coming to Israel from North
Africa and the Middle East during the 1950s. In order to estimate the effect of the differential radiation treatment
on the rates of meningioma in the total population, the authors assessed time trends of this disease in Israel over
the past 40 years by main ethnic origin. Cohort analysis shows a marked incidence rise in the North African-born
cohorts born in 1940-1954 starting from the 1980s. A similar pattern is seen in the Middle Eastern born, although
the increase is not as sharp. In consequence, there is a crossover of the interethnic incidence curves in the
1940-1949 cohort. Comparison of the relative risk between 1940-1954 cohorts that comprised most of the
irradiated with 1930-1939 cohorts, who were largely free of the radiation, shows that the North African born have
the largest relative risk of 4.62, followed by the Middle Eastern born, with a relative risk of 1.95, while the EuropeanAmerican born have a relative risk close to 1. The differences between the three areas of birth are statistically
significant. The data illustrate the potential risk of administering highly potent therapy for an essentially benign
disease that led, in turn, to a drastic change in the national meningioma pattern. Am J Epidemiol2000; 151:266-72.
brain neoplasms; cohort studies; iatrogenic disease; meningioma; radiation; radiation effects
this time period. This study population was based on
the retrieval of records from the four main radiation
treatment centers in the country. In 1972, our group
showed that radiation caused at least a doubling of the
incidence rates of head and neck tumors, particularly
those of the brain and the thyroid gland (1). This pattern was repeatedly observed at three additional cutoff
points: 1981, 1986, and 1991 (5, 6). In this report we
investigate the possible impact of the selected mass
irradiation 4—5 decades ago on meningioma incidence
rates and differential time trends among the immigrant
Israeli Jewish population, by ethnic origin.
Head irradiation is the only proven etiologic risk
factor for the development of meningioma (1-3).
Official figures suggest that between 1948 and 1960
about 20,000 Israeli subjects, particularly children,
received radiation treatment to the brain for tinea capitis, an essentially benign fungal disease of the scalp
(4). This population was composed mostly of newly
arrived immigrants from North Africa and to a lesser
extent from the Middle East. Their modal age was 6-8
years, with an equal distribution of males and females.
Lately it has become evident that the size of this
exposed group is much higher, since a considerable
number of individuals were irradiated abroad, almost
exclusively in North Africa, as a prerequisite for their
immigration to Israel.
In 1965 our group established a cohort of 10,834
persons who received irradiation of the scalp for tinea
capitis. All subjects in this cohort emigrated to Israel
from North Africa and the Middle East between 1949
and 1960 or were born in Israel to such families during
MATERIALS AND METHODS
Incidence data for the current report on brain meningioma were obtained from the National Israel Cancer
Registry that has been in operation since 1960. Both
benign and malignant brain tumors are reported by law
to the Registry. The completeness rate for solid tumors
has been checked occasionally against hospitalization
records in the various hospitals and was found to be
between 90 and 95 percent. Benign meningioma is
classified in the Registry as a distinct entity by
International Classification of Diseases, Ninth
Revision, Clinical Modification, code 225 and morphological codes 9530/0-9539/0. Since the Registry is
based on several reporting sources and actively validates the diagnoses, the percentage of uncertain
meningioma cases in this study population is only 1.2
Received for publication November 30, 1998, and accepted for
publication April 14, 1999.
1
Department of Clinical Epidemiology, The Stanley Steyer
Institute for Cancer Epidemiology and Research, and the Tel Aviv
University Medical School, Tel Hashomer, Israel.
2
Biostatistics Unit, Gertner Institute for Epidemiology and Health
Policy Research, Chaim Sheba Medical Center, Tel Hashomer, and
Bar-llan University, Ramat Gan, Israel.
Reprint requests to Dr. Siegal Sadetzki, Chaim Sheba Medical
Center, Sackler School of Medicine, Tel Hashomer 52621, Israel.
266
Epidemic latrogenic Meningioma
percent. There has been practically no change in
reporting over time or between distinct ethnic groups.
Israel is an immigration country, comprising people
who came from all over the world. When the State was
established in May 1948, it included about 600,000
Jews and, at the end of 1994, that number reached
almost 4.4 million (table 1). For epidemiologic purposes the ethnic subgroups of the Jewish population are
identified in general terms in four categories:
European-American bom, North African born, Asian
born (exclusively Middle Eastern), and Israeli born.
Immigration waves varied by period, with regard to the
ethnic composition of the migrants. Consequently, the
proportional distribution of the ethnic groups has been
different in distinct decades. Accordingly, the composition of the Israeli born has also varied by origin with
time (7, 8).
The data presented below include all cases of benign
meningioma in Israeli immigrants who were diagnosed between 1960 and 1995, subdivided by 5-year
periods, 5-year age groups, sex, and area of birth. The
respective populations at risk, in these categories, were
used to calculate incidence rates. The Israeli-born subpopulation was not included in this analysis since it is
a heterogeneous group comprising primarily first generation native born with no information on their origin.
Furthermore, during the varying waves of immigration
to Israel, the internal distribution of parental origin of
the native born has changed over time.
The main part of the analysis aimed at comparing
the effect of cohort (year of birth) on meningioma
incidence according to area of birth. Since data were
available for ages 0-4, ..., 70-74, >75 years (16
groups) and for the periods 1960-1964, 1965-1969,
.... 1990-1994 (seven periods), we were able to identify data from 22 birth cohorts: 1880-1889,
1885-1894, ..., 1980-1989, 1985-1994, although in
the main analysis we use only cohorts from 1880-1889
to 1955-1959 (see below). Note that each cohort spans
10 years and that adjacent cohorts overlap by 5 years,
as always occurs when the source data are in 5-year
age and period groups.
The cohort analysis included all age groups over 30
years. Younger ages were not informative because of
the small number of cases. This means that the birth
cohorts from 1960-1969 up to 1985-1994 were not
included in this analysis. The analysis used a logistic
regression model with the following effects included:
area of birth, age of diagnosis x area of birth, cohort x
area of birth, sex x area of birth, and period of diagnosis. The interactions are equivalent to allowing the age
effects, cohort effects, and sex differences to vary
according to area of birth. Lack of interaction of period
of diagnosis with area of birth assumes that the period
effect is common to all areas of birth. This latter
assumption was based on the expectation that period
effects would mostly depend on changes in diagnostic
practices in the Israeli health system and that, since
access to health care is quite uniform across the Israeli
population, individuals from all areas of birth should
be affected in the same way. This is especially true
since, during the 40 years of the study period, 98 percent of the population had health insurance (today 100
percent) and since the immigrant groups are widely
spread across the country and are not confined to specific areas. It is well known that, in regression models
including age, period, and cohort effects simultaneously in a single population, one cannot obtain estimates for all effects without further assumptions (9).
However, from the logistic regression results with
three separate populations, we were able to estimate
the birth cohort effects and to compare them across the
populations (see Appendix). We wished to test statistically the possible effect of radiation given for tinea
capitis on brain meningioma incidence. We expected
that the main effect of radiation would be seen in the
TABLE 1. Distribution of the Israeli Jewish population by area of birth with tlme*,t,t
1948§
1979
1962
1994
No.
%
No.
%
No.
%
No.
%
Israeli population
Total
Israeli born
716,678
253,661
100.0
35.4
2,068,882
795,861
100.0
38.5
3,218,400
1,767,500
100.0
54.9
4,388,000
2,675,600
100.0
61.0
Foreign born
Total
Middle Eastern born
North African born
European-American born
463,017
57,768
12,236
393,013
100.0
12.5
2.6
84.9
1,273,021
304,331
274,997
693,693
100.0
23.9
21.6
54.5
1,450,900
304,300
338,200
808,400
100.0
21.0
23.3
55.7
1,712,300
259,000
332,100
1,121,200
100.0
15.1
19.4
65.5
* End of year except for 1948, where data are based on first census (November 8).
t Statistical Abstract of Israel. Jerusalem: Central Bureau of Statistics, 1963. (No. 14).
t Statistical Abstract of Israel. Jerusalem: Central Bureau of Statistics, 1995. (No. 46).
§ Year when the State was established.
Am J Epidemiol Vol. 151, No. 3, 2000
267
268
Sadetzki et al.
cohorts born in 1940-1954, since the radiation was
given primarily throughout the 1950s to children
between the ages of 5 and 15 years. The nearest
cohorts that were expected to be largely free of the
radiation effect were those born in 1930-1939 and
1955-1964. However, the incidence of meningioma in
the latter cohort is still relatively sparse. Therefore, we
based our test of the radiation effect on the relative risk
of disease in the cohort 1940-1954 versus the cohort
1930-1939. The maximum Likelihood estimate of the
log of this relative risk is estimated from the statistical
model by the mean of the cohort effects of 1940-1949
and 1945-1954 minus the cohort effect of 1930-1939.
This statistic was then compared between areas of
birth, and pairwise comparisons were constructed
using Z statistics based on large-sample theory (see
Appendix).
RESULTS
Figures 1-3 present age-specific incidence rates of
benign meningioma by period and area of origin.
Males and females were combined since their patterns
were similar. For all areas of birth a positive association with age is noted with a decline in the very old age
category. Also, there is a prominent increase in the
incidence of meningioma with time starting in the
1970-1979 period and continuing up to the latest
period (1990-1995). However, this increase with age
and period, especially in the 1990s, differs among the
three areas of origin. While among the EuropeanAmerican born (figure 1) the incidence rate peaks at
the 60- to 69-year age category, in Line with recent
observations in other developed countries, among the
North African born (figure 2), the rise in incidence
appears in the 40- to 69-year age group, starting in
1980-1989, and increases further in 1990-1995.
Among the Middle Eastern born (figure 3), the pattern
is similar to that for the North African bom, although
the increase in the early age group appears sharper in
the latter group. This observation is in Line with the
fact that a larger proportion of North African-born
immigrants were irradiated, as compared with the
Middle Eastern born. Thus, while in the 1960-1969
period the incidence rates of meningioma in those aged
40-49 years were 2.4/100,000 in the North African,
5.0 in the Middle Eastern, and 4.8 in the EuropeanAmerican born, in the 1990-1995 time period a different picture is seen with incidences of 12.9 , 10.0, and
4.5, respectively.
Figure 4 presents the estimated cohort effects for the
three areas of birth from our logistic regression analysis, converted to annual incidence rates. The rates are
adjusted for age, sex, and period through the regression model. It can be seen that there is a marked rise in
the incidence rates of brain meningioma in the North
African-born group among the cohorts born in
1935-1944, 1940-1949, 1945-1954, and 1950-1959,
20 -i
O
o
o
o
o
15-•-1960-69
-o-1970-79
wOH
-*-1980-89
-X-1990-95
0
15
25
35
45
55
65
70+
AGE CATEGORY
FIGURE 1. Age-specific incidence rates of benign meningioma in Israel by period, European-American bom, 1960-1995.
Am J Epidemiol
Vol. 151, No. 3, 2000
Epidemic latrogenic Meningioma
269
20 -i
o
o
15 -•-1960-69
©
—1970-79
10 -
W
-*• 1980-89
AH
-X-1990-95
W
H
0
<10
15
25
35
45
55
65
70+
AGE CATEGORY
FIGURE 2. Age-specific incidence rates of benign meningioma in Israel by period, North African born, 1960-1995.
20 -i
O
o
o
15
-•-1960-69
04 10
W
ft.
-°-1970-79
-
-*-1980-89
-*-1990-95
5
<10
15
25
35
45
55
65
70+
AGE CATEGORY
FIGURE 3.
Age-specific incidence rates of benign meningioma in Israel by period, Middle Eastern born, 1960-1995.
especially in the middle two periods. A similar pattern
is seen in the Middle Eastern born, although the
increase is not as sharp. There is little evidence of this
pattern, however, among the European-American-bom
group. In consequence, there is a crossover of the
interethnic incidence curves in the 1940-1949 cohort.
Table 2 presents the results of the statistical tests of
difference in patterns of incidence rates among the
Am J Epidemiol Vol. 151, No. 3, 2000
three categories of area of birth. Part one of the table
presents estimated relative risks among cohorts born in
1940-1954 and the cohorts born in 1930-1939, and
part two presents the pairwise statistical comparisons
among the three populations. It can be readily seen that
the North African bom have the largest estimated relative risk of 4.62, followed by the Middle Eastern bom
(relative risk = 1.95), while the European-American
270
Sadetzki et al.
30
O
©
©
©
20
- • - Nortb Africa
- ° - Middle East
-A- Europe-America
10
1910
1920
1930
1940
1950
YEAR OF BIRTH
FIGURE 4. Sex-, age-, and period of diagnosis-adjusted incidence rates of benign meningioma in Israel by year of birth (cohort effect) in three
areas of birth, North Africa, Middle East, Europe-America, 1910-1950.
TABLE 2. Comparison within the foreign-bom Israeli Jewish
population of relative risk estimates (cohorts 1940-1954 vs.
cohorts 1930-1939) in three areas of birth
Area of birth
and type
of comparison
Estimated
relative
risk
95%
confidence
Interval
4.62
1.95
1.01
2.59, 8.25
1.14,3.35
0.59, 1.73
North Africa
Middle East
Europe-America
North Africa versus
Middle East
North Africa versus
Europe-America
Middle East versus
Europe-America
Difference in
log relative
risks
Standard
error of
difference
Z value
0.86
0.30
2.87
0.004
1.52
0.29
5.24
<0.001
0.66
0.27
2.44
0.014
p value
born have a relative risk close to 1. The differences
among the three areas of birth are all statistically significant.
DISCUSSION
Three major changes occurred in the incidence of
meningioma in the study population over time: 1) an
overall increase; 2) a differential increase with age;
3) a crossover in the ethnic incidence pattern.
Descriptive epidemiologic data on the incidence of
brain tumors are limited and usually relate to variations among countries and among distinct population
groups. Some of these differences are not genuine,
resulting from variability in case ascertainment (such
as hospital/data registries/autopsies, and so on), as well
as from the introduction of modern diagnostic techniques (10-13).
Still, in recent years emphasis has been placed on a
general trend of an apparently increasing incidence of
brain tumors (14—17). An increase of this kind could
point either to past exposure to a newly introduced etiologic agent (e.g., pesticides and other chemicals) (18)
or just represent better diagnosis due to more advanced
methods. The apparent worldwide increase in the incidence of brain tumors is noted, especially in older age.
This pattern coincides closely with the introduction of
noninvasive diagnostic techniques, such as computerized tomography, and is accompanied by a more
aggressive diagnostic approach to the elderly.
Consequently, we believe that it probably reflects a
more prevalent diagnosis of brain tumors beyond age
60 (12). The consistent decline in the incidence of
brain tumors in the very old ages, in all ethnic groups,
is probably due to a still existing misdiagnosis among
the oldest old, even though for meningioma a decline
of this kind is not universal (19).
Am J Epidemiol
Vol. 151, No. 3, 2000
Epidemic latrogenic Meningioma
This "period effect" can, however, explain only some
of the age and time trends and does not resolve the differential ethnic pattern seen in our study. Our data show
an inversion in the respective risk of meningioma incidence at the 40- to 59-year age category in the more
recent period, as compared with the 1960s; that is, the
higher incidence in the European-American born disappears and is superseded by the rates in the North
African born. This newly developing excess of meningioma incidence in the non-European-American born is
most prominent in the 40- to 49-year age category,
which corresponds to the current modal age of the
cohort that had been exposed to radiation in the 1950s,
when they were 5-14 years of age. This effect represents a latency period of about 20-40 years, and it is in
line with the continuous appearance of meningioma in
this population segment to this very day. An epidemic
is defined as "the occurrence in a community or region
of cases of an illness, specific health-related behavior,
or other health-related events clearly in excess of normal expectancy. ... The number of cases indicating the
presence of an epidemic varies according to the agent,
size, and type of population exposed; previous experience or lack of exposure to the disease; and time and
place of occurrence. Epidemicity is thus relative to
usual frequency of the disease in the same area, among
the specified population, at the same season of the
year" (20, p. 54).
As mentioned above, assessment of time trends
serves as an optimal indicator for acute changes in
morbidity patterns. An observed trend could suggest
the introduction of a new etiologic agent into the population, a change in the composition of the population,
or a differential exposure. In our case, the etiologic
role of radiation in the development of meningioma is
now well established. Nevertheless, our data amplify
the sequel of interethnic differences in exposure,
which resulted from variation in socioeconomic status
and, consequently, a differential exposure to the underlying fungal disease. latrogenic disease is defined as
"illness resulting from a physician's professional
activity or from the professional activity of other
health professionals" (20, p. 81). Unfortunately, iatrogenic disease is not an entirely rare phenomenon. In
the area of oncology we are aware of the increased risk
of vaginal cancer in women whose mothers had
received diethylstilbestrol treatment during pregnancy
(21). However, it is unusual for an iatrogenic phenomenon to be so strong and widespread that its effect is
seen clearly in national incidence rates.
From a purely methodological perspective, our
study demonstrates the importance of descriptive epidemiology in the monitoring of population disease patterns, and it emphasizes the value of birth cohort
Am J Epidemiol
Vol. 151, No. 3, 2000
271
analysis, a method that is frequently overlooked. Thus,
our data illustrate vividly how a strong medical intervention (radiation), for a relatively innocuous condition (tinea capitis), led to a dramatic change in the
occurrence of a very serious disease (meningioma) that
ended in a long-term iatrogenic epidemic.
ACKNOWLEDGMENTS
This research was supported by funding from the Israel
Cancer Association.
The authors acknowledge the valuable assistance of Dr.
Micha Barhana, Director of the Israel Cancer Registry, and
of Dr. David Zucker, Hebrew University.
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and neck tumors. Lancet 1974; 1:277-9.
2. Ron E, Modan B, Boice JD Jr, et al. Tumors of the brain and
nervous system after radiotherapy in childhood. N Engl J Med
1988;319:1033-9.
3. Bondy M, Ligon BL. Epidemiology and etiology of intracranial meningioma: a review. J Neurooncol 1996;29:197-205.
4. Ron E, Modan B, Boice JD Jr. Mortality after radiotherapy for
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5. Modan B. Cancer and leukemia risks after low level radiation
controversy, facts and future. Med Oncol Tumor Pharmacother
1987;4:151-61.
6. Modan B, Chetrit A, Alfandary E, et al. Increased risk of breast
cancer following low dose irradiation. Lancet 1989;1:629-31.
7. Statistical abstract of Israel, no. 14. Jerusalem: Central Bureau
of Statistics, 1963.
8. Statistical abstract of Israel, no. 46. Jerusalem: Central Bureau
of Statistics, 1995.
9. Osmond C, Gardner MJ. Age, period and cohort models
applied to cancer mortality. Stat Med 1982; 1:245-59.
10. Davis DL, Hoel D, Fox J, et al. International trends in cancer
mortality in France, West Germany, Italy, Japan, England and
Wales, and the USA. Lancet 1990;336:474-81.
11. Ahlbom A. Some notes on brain tumor epidemiology. Ann N
YAcadSci 1990;609:179-85.
12. Modan B, Wagener DK, Feldman JJ, et al. Increased mortality
from brain tumors—a combined outcome of diagnostic technology and change of attitude to the elderly. Am J Epidemiol
1992;135:1349-57.
13. Inskip PD, Linet MS, Heineman EF. Etiology of brain tumors
in adults. Epidemiol Rev 1995; 17:47-64.
14. Bahemuka M, Massey EW, Schoenberg BS. International mortality from primary nervous system neoplasms: distribution
and trends. Int J Epidemiol 1988; 17:33-8.
15. Greig NH, Ries LG, Yancik R, et al. Increasing annual incidence of primary malignant brain tumors in the elderly. J Nad
Cancer Inst 1990;82:1621-4.
16. Boyle P, Maisonneuve P, Saracci R, et al. Is the increased incidence of primary malignant brain tumors in the elderly real? J
Nad Cancer Inst 1990;82:1594-6.
17. Wrensch M, Bondy ML, Wiencke J, et al. Environmental risk
factors for primary malignant brain tumors: a review. J
Neurooncol 1993; 17:47-64.
18. Davis DL, Bridbord K, Schneiderman M. Cancer prevention:
assessing causes, exposures, and recent trends in mortality for
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U.S. males, 1968-1978. Int J Health Serv 1983;13:337-72.
19. Central Brain Tumor Registry of the United States (CBTRUS).
1997 annual report Chicago: CBTRUS, 1997.
20. Last JM, ed. A dictionary of epidemiology. 3rd ed. New York:
Oxford University Press, 1995:1-180.
21. Herbst AL, Ulfelder H, Poskanzer DC. Adenocarcinoma of the
vagina. Association of maternal stilbestrol therapy with tumor
appearance in young women. N Engl J Med 1971;284:878-81.
APPENDIX
Let YlJk/ represent the annual incident proportion of
benign brain meningioma in Israel in period i, age
group j , sex group k, and area of birth/. In our analysis
there were seven periods (i = 1, ..., 7), 10 age groups
(j = I, ..., 10), two sexes (k = 1, 2), and three areas of
birth (f = 1, ..., 3). We adopted the statistical model:
l o g i t ( ^ ) = M,
where M, represents the area of birth effects, (A.M)j7
are the age effects within each area of birth group,
(GM)U are the sex effects in each area of birth group,
(C.M)(,+J_ ,)y are the cohort effects in each area of birth
group, and Pl are the period effects common to each
area of birth group.
For identifiability, standard linear restrictions were
adopted as follows: (A.M)6/ = 0 (making the 55- to 59year group the reference age group in each area of
birth); (GM)X/ — 0 (making males the reference sex
group in each origin); (C.M)g/ = 0 (making the cohort
born in 1915-1924 the reference cohort in each origin);
and P4 = 0 (making the period 1975-1979 the reference period). However, we found that one extra linear
restriction was required for the identification of all
parameters. We chose P5 = 0 (1980-1984) as the extra
restriction, since this appeared reasonable from the data
and the background knowledge regarding possible
period effects in Israel. (Note, however, that there is no
way to determine from the data themselves whether this
assumption is justified.) With this model we estimated
the cohort effects in each area of birth group using maximum likelihood and converted them to incidence rates
by the inverse logit transformation before plotting them
as shown in figure 2. More specifically, we plotted
exp((C.M), +J _ lt , + M , + (G.M)it/)
1 + exp((C.M) {/+y _ Ii0 + M, + (G.M)W)
for cohorts (1900-1909, ..., 1950-1959) and the three
areas of birth (f = 1, ..., 3).
The important point regarding our analysis is that
the differences between the estimates (C.M),-+y-_i?/l-
(CM),-+_,-_!j2 (i-e-> between the cohort effects in different origin groups) are unaffected by the choice of the
extra restriction (P5 = 0). We could choose any other
single linear restriction on the parameters and still
obtain the same difference between the estimates, even
though the estimates themselves would differ. Thus,
comparisons of cohort trends in the different groups
can be made without worrying about the choice of the
extra restriction.
As explained in the text, we estimated the effect of
radiation for tinea capitis in each area of birth group by
the mean of the effects of the cohorts 1940-1949 and
1945-1954 minus the effect of the cohort 1930-1939,
that is, J*[(C.M),3,, + (C.M)14i/] - (CM),!,, (/ = 1, ...,4).
We call this estimate R,. The value exp (R,) may be
interpreted as an estimated relative risk between the
respective cohorts. These values are presented in
table 1. The estimated variance of Rt is obtained from
the variance-covariance of the (CM) terms. Ninetyfive percent confidence limits for Rt are obtained by
Rf ± 2 Vvar(/?/) and can be converted to confidence limits for exp (R/) by exponentiation. To test
differences in the radiation effect between areas of
birth, we made pairwise comparisons of the three
estimates /?,, R2, R3. The variance of a paired comparison (e.g., Rx - R2) was also estimated from the
variance-covariance matrix of the estimates of the
(CM) terms obtained from the logistic regression.
The calculation is somewhat lengthy, and the formula
is not given here; since there are six (CM) terms in
each pairwise comparison, the variance of the difference involves summing multiples of six variances
and 15 covariances. Test statistics (Rn - Rf2) are
approximately normally distributed.
The fit of the logistic regression model above to
the data was quite satisfactory. The deviance was
452.6, based on 451 df, giving no evidence of lack of
fit. Note, however, that the model assumes that the
period effect (year of diagnosis effect), besides being
the same for each area of birth, is also the same for
all age groups. The latter is less plausible than the
assumption of equality for all areas of birth, as the
effects of changing diagnostic practices can easily
impact more on the diagnosis of the elderly than on
the young to middle aged, as was already observed in
the United States (18). We therefore relaxed this
assumption by including in the regression model
extra terms representing a linearly increasing effect
of period from age 50 years upward. Inclusion of
these terms had virtually no impact on our estimates
of the differences in the log relative risks as presented in table 1. Our conclusions therefore appear to
be robust to any dependence of the period effect upon
age.
Am J Epidemiol Vol. 151, No. 3, 2000