445

Publication of the International Union Against Cancer
Publication de l’Union Internationale Contre le Cancer
Int. J. Cancer: 73, 1–9 (1997)
r 1997 Wiley-Liss, Inc.
EFFECT OF PARITY AND AGE AT DELIVERY ON BREAST CANCER RISK
IN SLOVENIAN WOMEN AGED 25–54 YEARS
Chris ROBERTSON1*, Maja PRIMIC-ZAKELJ2, Peter BOYLE1 and Chung-Cheng HSIEH3
1Division of Epidemiology and Biostatistics, European Institute of Oncology, Milan, Italy
2Institute of Oncology, Epidemiology and Cancer Prevention Unit, Ljubljana, Slovenia
3University of Massachusetts, Cancer Center, Two Biotech, Worcester, MA
In 1988, a case-control study on breast cancer and oral
contraceptives with 624 cases and 624 matched controls in
the age range 25–54 years was undertaken in Slovenia. This
analysis assesses the relationship between parity and breast
cancer risk: the relative importance of age at first birth, age at
subsequent births and total parity. We also evaluate whether
a dual effect of an increased risk immediately after childbirth
followed by a long-term benefit exists. Three logistic regression models were used. Age at first delivery is an important
breast cancer risk factor: among parous women it was
associated with a 5.3% increase/year in the odds of breast
cancer. Multiparity was not shown to be an independent risk
factor. Age at subsequent deliveries was associated with a 1%
increase in risk for every 1 year increase of age at any birth,
but this contribution to the risk was not significant. In the
analysis stratified by parity the most important influence is
with the age at first birth. We find no evidence of an effect on
the odds of breast cancer associated with the age at the
second, or later, births. We do find that there is an increased
risk associated with the birth of the first child followed by a
longer term protective effect. A post-menopausal woman has
a reduced breast cancer risk compared with a pre-menopausal woman of the same age, adjusting for the same
number of deliveries and ages at these deliveries. Int. J. Cancer
73:1–9, 1997.
r 1997 Wiley-Liss, Inc.
Slovenia was one of the participating centers in the international
case-control study (in 7 locations of the world performed in late
1960s) demonstrating that the risk of breast cancer is decreased in
women who have their first child at an early age (MacMahon et al.,
1970; Ravnihar et al., 1971). There is still no consensus about the
effect of subsequent pregnancies. Some studies indicate that
multiparity has an independent protective effect against breast
cancer (Kelsey et al., 1993), while later re-analyses of the
7-countries study suggested that age at any birth was an independent risk indicator (albeit smaller than that for age at first delivery)
and that the parity effect was determined by the age of occurrence
of the component pregnancies (Trichopoulos et al., 1983). Some
authors have suggested that age at last pregnancy may be even
more important than age at the first one (Kalache et al., 1993; Kvale
and Heuch, 1987), but this finding has recently been questioned
(Hsieh et al., 1996). Several studies have demonstrated that a
full-term pregnancy exerts a short-term adverse influence and a
long-term beneficial influence on breast cancer risk (Kelsey et al.,
1993; Lambe et al., 1994; Hsieh et al., 1994).
In 1988, a new case-control study was undertaken in Slovenia to
evaluate further the relationship between breast cancer and oral
contraceptive use in the age range 25–54 years using a generalpopulation control group for the first time (Primic Zakelj et al.,
1995). In addition to the data on oral contraceptives and classical
risk factors, data on timing of all deliveries were also collected and
evaluated.
The main purpose of the present analyses is to assess the
relationship among parity, age at delivery and breast cancer risk.
We focus on 1) the relative importance of age at first birth; 2) the
effect of age at subsequent births; and 3) the effect of total parity on
breast cancer risks in young Slovenian women. Furthermore, we
evaluate whether a dual effect of pregnancy exists whereby the
birth of the first child is associated with an increased risk of breast
cancer followed by a long-term protective effect.
Three related approaches were used (Trichopoulos et al., 1983;
Hsieh and Lan, 1996; Rosner et al., 1994) and are described in the
Appendix. Each has a slightly different emphasis for modeling the
effect of age at any birth on breast cancer risk and provides separate
contributions to our understanding of the joint effects of parity and
age at delivery. The simplest approach is a logistic regression
model with separate terms for the age at any delivery and each
separate delivery (Trichopoulos et al., 1983). A stratified model
comparing uni- and nulli-parous women only to investigate whether
the effects of parity and age at first delivery are modified by age at
diagnosis is an extension of the simple model (Hsieh and Lan,
1996). In the proposed adaption of the Rosner et al. (1994) model,
the variables in the model are the durations since the births until the
age at diagnosis. This implies that age is a modifying factor for
parity and is also an extension of the model of Trichopoulos et al.
(1983).
SUBJECTS AND METHODS
Cases and controls
Women from the whole of Slovenia, aged between 25 and 54
years, with breast cancer confirmed histologically and/or cytologically between January 1, 1988, and December 31, 1990, were
included as cases. They were eligible if they had been permanent
residents of Slovenia since 1965, if they had not had previous
cancer (except non-melanoma skin cancer) and if they were
considered psychologically competent to participate in such a
study. Cases were identified at the Institute of Oncology in
Ljubljana and 4 Slovenian general hospitals at the time of patient
admission for diagnosis and/or primary treatment. Of 647 eligible
cases, 23 refused to participate, resulting in a participation rate of
94.4%.
For every case, one control was randomly selected from the
Population Registry of Slovenia. Each control date of birth was
matched to the case month and year of birth, and the control had to
live in the same commune (60 in Slovenia) as the case. The mean
age of cases and controls was 45 years. Other eligibility criteria
were the same as for the case patients. Controls were contacted first
by a letter; if they did not respond, they were contacted by
telephone or a second letter (if their name was not in the telephone
directory) within 2 weeks after the first letter was sent. If they did
not answer the second invitation, or refused, or if they did not meet
the selection criteria, another control was selected at random from
the Population Registry. Of 624 potential first controls, 21 could
not be traced and 71 were not eligible. The ineligibles arose
because of violations of the entry criteria: 59 had not been residents
Contract grant sponsor: Associazione Italiana per la Ricerca sul Cancro.
*Correspondence to: Division of Epidemiology and Biostatistics, European Institute of Oncology, via Ripamonti 435, 20141 Milan, Italy. Fax:
139 2 57489813. E-mail: [email protected]
Received 14 January 1997; Revised 20 May 1997
2
ROBERTSON ET AL.
in Slovenia since 1965, 8 had another cancer and 4 were considered
psychologically incapable of completing the study. From 532
eligible controls, 93 refused to be interviewed. These 185 controls were
subsequently replaced by second (130) or subsequent (55) choices.
Data collection
Most patients (82.4%) were interviewed on the wards during
their stay in the hospital for primary treatment, while 97 were
interviewed during follow-up visits and 13 at home. Controls were
visited and interviewed at home. The interviews were performed by
2 specially trained nurses; in most instances the matched pair (case
and control) was interviewed by the same nurse.
The interview lasted for approximately 30 min. It gathered data
on basic demographic characteristics, education, reproductive and
contraceptive history, family history of breast cancer, medical
history and some other characteristics. Clinical data were collected
from medical records. To assist better recall, a calendar was used on
which oral contraceptive use and reproductive events since menarche were recorded.
The date of diagnosis was taken to be the date of the first visit to
the outpatient clinic that the biopsy that turned out to be positive
was performed or the date of admission to the hospital on which
biopsy was performed and proved positive. For every control a
pseudo-diagnosis date was determined, the date on which she was
exactly the same age as the case at diagnosis. All the data were
collected prior to this date.
For this study, each pregnancy that ended after 24 weeks was
considered as ending with delivery. A woman was considered
menopausal if her last period was more than 6 months before
diagnosis/pseudo-diagnosis.
Statistical methods
The mathematical framework of the models is presented in the
Appendix. Multivariate logistic regression was used for the estimation of relative risk (Breslow and Day, 1980). As this is a matched
case-control study, conditional logistic regression was used. Nulliparous and uni-parous women are compared directly, as are
uni-parous and bi-parous women (Lambe et al., 1994; Hsieh and
Lan, 1996). In this case the matching is broken and an unconditional logistic regression model used, with age at diagnosis/
interview included in the model. This was especially important for
the comparison of nulli-parous and uni-parous women, as there
were only 62 parity eligible pairs, i.e., matched pairs with the case
being either nulli-parous or uni-parous and the control also of
parity 0 or 1.
Adjustment was made for education, age at menarche, menopausal status, age at menopause and family history of breast cancer
(mother) (Primic Zakelj et al., 1995). Adjusted and unadjusted
values are presented. Results are presented as odds ratios (OR) and
the corresponding 95% confidence intervals (95% CI). The analyses were performed for all the women together and for some
characteristics also by the following age groups: 25–34, 35–44 and
45–54 years old.
The first model considers that the risk of breast cancer is related
to the age at birth of any child, together with indicator variables
denoting the number of deliveries (Trichopoulos et al., 1983).
When the analysis was performed for parous women, only parity
eligible pairs were included and conditional logistic regression used.
The second part is an extension of the first and considers
interactions with parity and age at any birth and age at diagnosis
(Lambe et al., 1994; Hsieh and Lan, 1996). Also, it is stratified by
parity, and only adjacent parities are analyzed. Separate analyses
were carried out to estimate the effect of age at first birth among
women with parity 0 or 1, and to estimate the effect of age at second
birth among women with parity 1 or 2. This analysis will reveal if
the effects of parity and age at the birth of a child are modified by
the age at diagnosis.
The third part is also an extension of the first part and considers
that the risk of breast cancer is related to the number of years from
TABLE I – SUMMARY INFORMATION ABOUT THE WOMEN IN THE STUDY
Number of children (% of cases and controls)
Case
Control
0
1
2
3
41
Total
7.5
6.3
26.1
22.8
50.2
53.2
11.4
14.3
4.8
3.5
624
624
Delivery
Age (years) at
delivery of
children
1
Case
Control
2
Case
Control
3
Case
Control
4
Case
Control
Age (years) at
menopause
Case
Control
Age (years) at
menarche
Case
Control
Number
Mean
Standard
deviation
Minimum
Maximum
577
585
23.8
22.9
4.33
4.00
13
16
39
41
414
443
27.5
26.9
4.59
4.27
18
18
42
43
101
111
30.3
29.6
5.13
4.32
21
19
42
44
30
22
32.1
32.3
4.92
4.90
23
24
43
39
123
154
47.3
46.8
4.25
4.18
32
32
54
54
623
623
13.8
13.9
1.83
1.80
9
10
20
19
Education (number of years at school) (% of cases and controls)
Case
Control
1–8
9–12
131
Total
40.1
36.7
41.5
48.7
18.4
14.6
624
624
TABLE II – ESTIMATED EFFECTS OF AGE AT ANY BIRTH USING
THE TRICHOPOULOS ET AL. (1983) MODEL
Parity 1
Parity 2
Parity 3
Parity 41
Age at first delivery
centered on 23
Age at second delivery
centered on 27
Age at third delivery
centered on 30
Age at fourth delivery
centered on 32
Estimate1
SE
Estimate2
SE
20.1141
20.2177
20.4049
0.3197
0.0467
0.2515
0.2291
0.2694
0.3806
0.0186
20.1099
20.1635
20.4029
0.1963
0.0445
0.2573
0.2347
0.2753
0.3911
0.0192
0.0060
0.0206
0.0061
0.0209
0.0330
0.0345
0.0417
0.0352
20.0360
0.0609
20.0434
0.0618
1These estimates were obtained from a conditional logistic regression and were not adjusted for any other variables.–2Conditional
logistic regression adjusted for education, family history of breast
cancer, age at menarche, menopausal status and age at menopause.
menarche, the number of years since the birth of any child and the
number of years from menopause, together with indicator variables
for the birth of the first and subsequent children and for menopausal
status (Rosner et al., 1994; Rosner and Colditz, 1996).
RESULTS
Summary information is presented in Table I. The number of
deliveries ranges from 0 to 7 for both cases and controls. The
percentage of cases who are nulli-parous is 7.5% and the corresponding percentage for the controls is 6.3%. There are slightly more
deliveries among controls and, up to the third delivery, the controls
are slightly younger, on average, at each delivery than cases. There
PARITY, AGE AT DELIVERY AND BREAST CANCER RISK
3
TABLE III – DISTRIBUTION OF CASES AND CONTROLS WHO WERE NULLI-PAROUS OR UNI-PAROUS BY AGE AT
DELIVERY AND CURRENT AGE
Current age (years)
Nulli-parous
25–34
Cases
Controls
OR
95% CI
35–44
Cases
Controls
OR
95% CI
45–54
Cases
Controls
OR
95% CI
Uniparous: age at delivery (years)
13–19
20–24
25–29
30–41
5
4
1.00
—
4
3
0.95
0.12–7.58
9
10
0.58
0.11–3.15
7
2
2.61
0.31–22.02
—
—
—
—
18
17
1.00
—
7
7
0.99
0.28–3.44
15
16
0.91
0.35–2.41
17
13
1.26
0.47–3.37
12
5
2.19
0.63–7.57
24
18
1.00
—
2
11
0.14
0.03–0.70
37
34
0.81
0.38–1.76
28
24
0.87
0.39–1.98
25
17
1.10
0.46–2.63
TABLE IV – WEIGHTED AVERAGES OF THE ODDS RATIOS ACCORDING
TO DIFFERENT INTERVALS AFTER THE FIRST DELIVERY
BASED ON THE DIFFERENCE BETWEEN 5-YEAR CATEGORIES
OF CURRENT AGE AND AGE AT FIRST DELIVERY
Years after
delivery
0–10
OR
95% CI
11–20
OR
95% CI
211
OR
95% CI
1No
Uni-parous: age at delivery (years)
Nulli-parous
13–19
—1
—
1.00
—
20–24
25–29
30–41
0.86
1.56
1.39
0.18–4.16 0.45–5.35 0.46–4.20
1.00
—
0.51
0.86
1.03
1.51
0.22–1.14 0.49–1.51 0.55–1.92 0.70–3.25
1.00
—
0.32
0.81
0.82
0.11–0.91 0.41–1.60 0.37–1.82
—1
—
observations here.
is no difference in the age at menarche between cases and controls
nor is there any difference in age at menopause, although a greater
percentage of controls are post-menopausal, 24.7% compared with
19.7%. There was a family history of breast cancer among
first-degree relatives in 6.4% of cases and 4.0% of controls.
The first analysis was restricted to parous women and is based on
model 1 in the Appendix, without the interaction term. It looked for
the independent ‘‘main effects’’ of age at first delivery (continuous
variable) and multiparity (defined as 2 or more deliveries). The
coefficient for age at first delivery is statistically significantly
different from zero ( p 5 0.0017) and implies a 5.3% (95% CI
2.0–8.8) increase in the odds of breast cancer for every 1-year
increase in age at first delivery. The comparison of multiparity with
uniparity has a relative risk of 0.96 (95% CI 0.72–1.28) implying
that, on average, pregnancies beyond the first do not convey
significant additional protection against breast cancer. The relative
risk for the interaction between multiparity and age at first birth
was not significantly different from zero, at 1.03/year (95% CI
0.96–1.10; p 5 0.40).
From the model (Appendix model 2) exploring whether age at
any delivery is an independent determinant of breast cancer risk,
after controlling for parity we estimated regression coefficients
(Table II). The coefficient for age at first birth implies a 4.4% (95%
CI 1.01–8.56) increase in the odds of breast cancer for every 1 year
increase in age at first delivery.
The coefficients for age at subsequent deliveries were smaller
than that for the first birth and non-signficant. Since they showed no
substantial or systematic variation, they were combined into a
common OR of 1.01/year (95% CI 0.98–1.04), implying that for
every 1-year increase of age at any delivery after the first the odds
of breast cancer increase by 1% ( p 5 0.40).
To evaluate the hypothesis of a dual effect of pregnancy on
breast cancer risk the analysis was first restricted to nulli-parous
and uni-parous study subjects (210 cases and 181 controls) (Hsieh
and Lan, 1996). The distribution of nulli-parous and uni-parous
cases and controls by age at diagnosis and age at delivery and
age-specific odds ratios are presented in Table III. The CIs are all
wide as there are few observations; the pattern of the odds ratios is
important. All age groups have lower odds ratios compared with
nulli-parous women of the same age if the birth of the child was
early, at 13–24 years. If the delivery was later (25–41 years), then
there was an elevated OR relative to nulliparous women, particularly among the younger ages at diagnosis. Table IV shows that
within each strata of years since delivery, uni-parous women have
reduced ORs of breast cancer, compared with nulli-parous women,
if the delivery was at a younger age but that the odds increase with
increasing age at first delivery. Although individually not significant, the ORs are elevated soon after the delivery for uni-parous
women with late delivery compared with nulli-parous women.
The regression coefficients from model 3 in the Appendix (Hsieh
and Lan, 1996) are presented in Table V. The interactions with age
at diagnosis are included to investigate the relationship between
age at first birth and age at diagnosis. A reduction in the odds of
breast cancer by 0.85 (95% CI 0.51–1.43) was found for women
having one full-term pregnancy at age 23 compared with nulliparous women. Age at first birth is the only significant effect
( p 5 0.0260), and then only in the unadjusted model.
The predicted ORs of breast cancer relative to nulli-parous
women are plotted in Figure 1. These show a transient increase in
the odds soon after the first birth particularly among women with
older age at delivery. The odds decline as the number of years since
the birth increases. The estimated break-even point of about 15–20
years after delivery is consistent with the previous estimates (Hsieh
and Lan, 1996).
Bi-parous and uni-parous women were compared. The regression coefficients obtained from model 4 in the Appendix are
presented in Table V. No evidence suggests any effect of age at
second birth over and above the effect of age at first birth. The
distribution of cases and controls and age-specific ORs by age at
diagnosis over the age groups at second delivery are presented in Table
VI. The ORs for bi-parous women are in general lower than for
uni-parous women, though there is a tendency for ORs to increase
with older age at second delivery in age groups 35–44 and 45–54
years. However, none of the ORs are significantly different from
zero and there is no evidence of an effect of age at second birth.
The parameter estimates for model 5 in the Appendix are
presented in Table VII. The most important effects are age at first
birth, parity and menopausal status. At menopause there is a 40%
reduction in the odds ( p 5 0.03) compared with pre-menopausal
women of the same age, parity and ages at childbirth. Relative to a
ROBERTSON ET AL.
4
FIGURE 1 – Age at first birth and years since the birth. This graph shows the predicted odds ratios of breast cancer based upon the Hsieh and Lan
(1996) model for nulli- and uni-parous women. The horizontal line corresponds to nulli-parous women, who have an odds ratio of 1. There is a
separate predicted line for women with 1 birth only at ages 20, 25, 30 and 35.
TABLE V – REGRESSION COEFFICIENT ESTIMATES: MODELING WITH INTERACTION TERMS
Parity 1 vs. 0
Parity
Age at 1st delivery4
Parity 1 3 age5
Age at 1st delivery 3 age
Parity 2 vs. 1
Age at 1st delivery
Age at 1st delivery 3 age
Parity 2
Age at 2nd delivery7
Parity 2 3 age
Age at 2nd delivery 3 age
Estimate1
SE
Estimate2
SE
Hsieh and
Lan estimate3
20.1713
0.0544
20.0408
20.0031
0.2541
0.0244
0.0380
0.0038
20.1597
0.0364
20.0412
20.0028
0.2634
0.0263
0.0391
0.0040
21.0945
0.0686
0.0144
20.0011
0.0405
20.0005
20.0995
0.0003
0.0232
20.0003
0.0188
0.0031
0.1507
0.0211
0.0224
0.0035
0.0292
0.0004
20.1069
0.0027
0.0256
20.0005
0.0196
0.0032
0.1530
0.0213
0.0225
0.0036
—6
—6
20.3962
0.0182
4.7 3 1026
20.0002
1These estimates were obtained from an unconditional logistic regression (see text) and were not
adjusted for any variables other than age.–2Unconditional logistic regression (see text) adjusted for age,
education, family history of breast cancer, age at menarche, menopausal status and age at menopause.–
3Taken from Hsieh and Lan (1996).–4Age at 1st delivery centered on 23.–5Age at interview centered at
45.–6Estimate not quoted.–7Age at 2nd delivery centered on 27.
nulli-parous women with the same age at menarche and menopause, a women with parity 1 will have an instantaneous increase in
the odds of breast cancer at the delivery ( p 5 0.02), but thereafter
the odds will decrease by 5.2%/year ( p 5 0.002). In this way a first
delivery is associated with an increased risk initially but with a
longer term protection. There is no significant effect of a second
delivery over and above the first ( p 5 0.55).
Predicted odds ratios are presented in Figures 2–4 for a number
of scenarios of deliveries, including nulli-parous. All were based on
an age at menarche of 12 and an age at menopause of 50. These are
predictions based on a linear model, and their utility depends on the
adequacy of the model. Figure 2 looks at the effect of age at first
birth among women with only one birth. Relative to a women with
one birth at age 18, the later the first birth the greater the odds but
PARITY, AGE AT DELIVERY AND BREAST CANCER RISK
5
TABLE VI – DISTRIBUTION OF UNI-PAROUS AND BI-PAROUS CASES AND CONTROLS BY AGE
AT SECOND DELIVERY AND CURRENT AGE
Current age (years)
Uni-parous
25–34
Cases
Controls
OR
95% CI
35–44
Cases
Controls
OR
95% CI
45–54
Cases
Controls
OR
95% CI
Bi-parous: age at second delivery (years)
18–24
25–29
30–34
351
20
15
1.00
—
8
8
0.75
0.23–2.48
5
11
0.34
0.10–1.19
1
3
0.25
0.02–2.63
—
—
—
—
51
41
1.00
—
29
35
0.67
0.35–1.27
50
62
0.65
0.37–1.13
32
25
1.02
0.53–1.99
11
6
1.45
0.49–4.28
92
86
1.00
—
35
39
0.83
0.48–1.43
73
76
0.89
0.57–1.38
50
45
1.04
0.63–1.71
19
22
0.81
0.41–1.60
TABLE VII – REGRESSION COEFFICIENT ESTIMATES:
MODELING DURATION FROM EVENTS
Estimate1
Years since menarche3
Years since first
delivery4
Parity 11
Years since second
delivery4
Parity 21
Years since menopause4
Post menopause
SE
Estimate2
SE
0.0542 0.0336
0.0534 0.0341
20.0540 0.0170 20.0534 0.0175
1.0167 0.4095
0.0081 0.0152
0.9962 0.4173
0.0068 0.0152
20.2059 0.2823 20.1683 0.2846
20.0017 0.0393
0.0017 0.0395
20.4940 0.2314 20.5141 0.2333
1These estimates were obtained from a conditional logistic regression and were not adjusted for any other variables.–2Conditional
logistic regression adjusted for education and family history of breast
cancer.–3Two women had unknown age at menarche, and the pairs
were omitted. This parameter should be interpreted with care; see
Appendix.–4These variables all take the value zero if the event has not
occurred.
only after the birth. Relative to a women with one birth, nulliparous women have smaller odds but only in the period following
the birth, as the risk for nulli-parous women increases steadily
throughout their life until menopause, while for parous women the
increase following the first birth is at a much reduced rate. Relative
to a woman with one birth at 18, a woman with one birth only at age
28 is predicted to have a constant increased risk after the birth. The
lines are parallel after the birth because the only difference between
the 2 women is the time since the birth of their only children, which
for fixed time has a constant effect. A similar picture can be seen
with 2 births (Fig. 3). The drop in the OR associated with the
second birth is not precisely estimated and is not significantly
different from zero. Figure 4 shows a comparison of one late birth
with 2 late births; apart from an instantaneous slight reduction in
OR associated with the second birth, there is little long-term effect.
In all graphs the important conclusion is that the first birth is
associated with a transient increase in risk of breast cancer relative
to a nulli-parous woman of the same age and age at menarche. This
lasts for about 15–20 years following the birth. For women with 2
births within 3 years the transient increase in risk lasts for a slightly
shorter time.
DISCUSSION
As in most epidemiological studies, our study shows that age at
first delivery is an important breast cancer risk factor. Among
parous women it was associated with a 5.3% increase in the odds of
breast cancer for every 1 year increase in age at first birth, which is
close to the figure of 5.1% reported by Trichopoulos et al. (1983).
This is compatible with the observations from animal experiments
of pregnancy-induced irreversible terminal differentiation of mammary epithelium (Russo et al., 1982; 1990). The interaction term
between multiparity and age at first birth among parous women was
not significant in our study. The estimated increase in the odds of
2.7%/year is similar to that of Trichopoulos et al. (1983) (2.2%) but
has a larger standard error, partly as a consequence of the smaller
sample size here. Our finding does not contradict the hypothesis
that multiparity is modifying the effect of age at first delivery.
The estimated increase in the odds of breast cancer associated
with age at delivery of the first child of 4.4%/year is comparable to
estimates reported by Trichopoulos et al. (1983) (3.5%) and
Decarli et al. (1996) (4.7%). Age at subsequent deliveries was
associated with a 1% increase in risk for every 1 year increase of
age at any birth. Again, this estimate is similar to those estimated by
Trichopoulos et al. (1983) (0.9%) and Decarli et al. (1996) (0.7%).
This demonstrates that our data give comparable results to other
studies and that only the age at first birth is important in our data.
We find no significant independent effect of parity, which is
unusual. Part of the reason for this is that few of the cases in our
study are nulli-parous (7%) compared with, for example, 16% in
Italy (Decarli et al., 1996) and 19% in Sweden (Lambe et al.,
1994).
The most important influence of age at any birth is with age at
first birth. We find no evidence of an effect associated with age at
second birth when comparing uni-parous and bi-parous women.
The parameter estimates in Table IV are consistent with those
presented by Hsieh and Lan (1996). The assertion that age at
diagnosis is a modifying factor for age at first birth receives limited
support, as one of the interactions involving age at diagnosis are
significant.
Rosner et al. (1994) and Rosner and Colditz (1996) used cohort
data and modeled breast cancer incidence rates. As case-control
data are used here, there is no information on incidence rates;
however, the ORs that can be derived from Table VI are similar to
those derived from Rosner et al. (1994) and Rosner and Colditz
(1996). By using the year since the birth, age at diagnosis is
assumed to modify the effect of parity but not the age of delivery
(Robertson and Boyle, 1997), in contrast to the Hsieh and Lan
(1996) model, in which age modifies both effects. The odds of
breast cancer increase instantaneously at the delivery of the first
child but thereafter increase at a reduced rate compared with before
the birth.
Our results are consistent with a short-term increase in breast
cancer risk associated with the first birth (Hsieh and Lan, 1996).
Overall, nulli-parous women are at the greatest long-term risk, but
FIGURE 2
FIGURE 3
PARITY, AGE AT DELIVERY AND BREAST CANCER RISK
7
FIGURE 4 – Nulli-parous, uni-parous and bi-parous women (Rosner et al., 1994). This graph shows the predicted odds ratio of breast cancer for
nulli-parous women, or women with 1 birth at 35, or women with 2 births at ages 35 and 38 only relative to a woman with 2 births at ages 20 and
23. The horizontal line is the odds ratio for a women with 2 births at ages 20 and 23. The dotted curve corresponds to nulli-parous women.
within the child-bearing years nulli-parous women are predicted to
have a lower risk than parous women. This is the period when risk
of breast cancer is small; in older ages there is a much greater risk
of breast cancer among nulli-parous women.
Evidence of a small effect of age at second and subsequent births
has been reported (Trichopoulos et al., 1983; Lambe et al., 1994;
Rosner et al., 1994). No significant effect of age at second and
subsequent births was detected in this analysis. It is unlikely that
selection, recall or confounding bias could explain this result. Most
cases (96.2%) registered in The Cancer Registry of Slovenia were
interviewed, and parity status certainly did not influence the
response rate of general population controls. A calendar was used
to improve recall, and major confounding variables were taken into
FIGURE 2 – Nulli-parous and uni-parous women (Rosner et al.,
1994). This graph shows the predicted odds ratios of breast cancer for
nulli-parous women, or women with 1 birth only relative to a woman
with 1 birth at age 18. The horizontal line is the odds ratio for a woman
with 1 birth at age 18. The 2 lines with a step in them correspond to
women with 1 birth at age 28 and 1 birth at 38. The dotted curve
corresponds to nulli-parous women.
FIGURE 3 – Nulli-parous and bi-parous women (Rosner et al., 1994).
This graph shows the predicted odds ratios of breast cancer for
nulli-parous women, or women with 2 births only relative to a woman
with 2 births at ages 20 and 23. The horizontal line is the odds ratio for
a woman with 2 births at ages 20 and 23. The 2 lines with a step in them
correspond to women with 2 births at ages 30 and 33 and 2 births at
ages 40 and 43. The dotted curve corresponds to nulli-parous women.
account in the analysis. As the magnitude and sign of the estimates
of the effects obtained here are consistent with previously published estimates, the most likely scenario is that our study sample
was not large enough to detect the small additional effects of age at
deliveries subsequent to the first one on the risk of breast cancer.
The value of the statistical modeling is that we are able to assess
the joint effects of births and the age at which these births occur.
The models may be viewed in increasing order of complexity.
Those of Trichopoulos et al. (1983) are the simplest, as they do not
have interaction effects betewen age and the births. The other 2
models do have such effects. These models are used to investigate
whether age modifies the effects of parity and age at first and
subsequent births. We have significant evidence to support this
effect with respect to the birth of the first child but not the age at the
delivery. The Tricholoulos et al. (1983) model does not incorporate
any transient effects and in this instance should be viewed as a
necessary preliminary model. Each model can be seen from a
slightly different point of view and each provides related contributions to the estimation of the effects of parity and the age at which
the births occur on the risk of breast cancer (Robertson and Boyle,
1997).
ACKNOWLEDGEMENTS
This work was conducted within the framework of support from
the Associazione Italiana per la Ricerca sul Cancro (Italian
Association for Cancer Research).
ROBERTSON ET AL.
8
REFERENCES
BRESLOW, N.E. and DAY, N.E., Statistical methods in cancer research, Vol.
1. The design and analysis of case control studies. International Agency for
Research in Cancer, Lyon (1980).
DECARLI, A., LA VECCHIA, C., NEGRI, E. and FRANCESCHI, S., Age at any
birth and breast cancer in Italy. Int. J. Cancer, 67, 187–189 (1996).
HSIEH, C.-C., CHAN, H.-W., LAMBE, M., EKBOM, A., ADAMI, H.-O. and
TRICHOPOULOS, D., Does age at the last birth affect breast cancer risk?
Europ. J. Cancer, 32A, 118–121 (1996).
HSIEH, C.-C. and LAN S.-J., Assessment of post partum time dependent risk
in case control studies: an application for examining age specific effect
estimates. Stat Med., 15, 1545–1556 (1996).
HSIEH, C.-C., PAVIA, M., LAMBE, M. LAN, S.-J., COLDITZ, G.A., EKBOM, A.,
ADAMI, H.-O., TRICHOPOULOS, D. and WILLET, W.C., Dual effect of parity on
breast cancer risk. Europ. J. Cancer, 30A, 969–973 (1994).
KALACHE, A., MAGUIRE, A. and THOMPSON, S.G., Age at last full term
pregnancy and risk of breast cancer. Lancet, 341, 33–36 (1993).
KELSEY, J.L., GAMMON, M.D. and JOHN, E.M., Reproductive factors and
breast cancer. Epidemiol. Rev., 15, 36–47 (1993).
KVALE, G. and HEUCH, I., A prospective study of reproductive factors and
breast cancer. II. Age at first and last birth. Amer. J. Epidemiol., 126,
842–850 (1987).
LAMBE, M., HSIEH, C.-C., TRICHOPOULOS, D., EKBOM, A., PAVIA, M. and
ADAMI, H.-O., Transient increase in the risk of breast cancer after giving
birth. N. Engl. J. Med., 331, 5–9 (1994).
MACMAHON, B., COLE, P., LIN, T.M., LOWE, C.R., MIRRA, A.P., RAVNIHAR,
B., SALBER, E.J., VALAORAS, V.G. and YUSA, S., Age at first birth and breast
cancer risk. Bull. WHO, 43, 209–221 (1970).
PIKE, M.C., Age related factors in cancers of the breast, ovary and
endometrium. J. chron. Dis., 40, 59S–69S (1987).
PRIMIC-ZAKELJ, M., EVSTIFEEVA, T., RAVNIHAR, B. and BOYLE, P., Breastcancer risk and total contraceptive use in Slovenian women aged 25 to 54.
Int. J. Cancer, 62, 414–420 (1995).
RAVNIHAR, B., MACMAHON, B. and LINDTNER, J., Epidemiologic features of
breast cancer in Slovenia, 1965–1967. Europ. J. Cancer, 7, 295–306 (1971).
ROBERTSON, C. and BOYLE, P., Age at any birth and breast cancer risk.
Statist. Med. (1997) (in press).
ROSNER, B. and COLDITZ, G.A., Nurses’ Health study: log-incidence
mathematical model of breast cancer incidence. J. nat. Cancer Inst., 88,
359–364 (1996).
ROSNER, B., COLDITZ, G.A. and WILLETT, W.C., Reproductive risk factors in
a prospective study of breast cancer: the Nurses’ Health study. Amer. J.
Epidemiol., 139, 819–835 (1994).
RUSSO, J., GUSTERSON, B.A., ROGERS, A.E., RUSSO, I.H., WELLINGS, S.R.,
and VAN ZWIETEN, M.J., Comparative study of human and rat mammary
tumorigenesis. Lab. Invest. 62, 244–278 (1990).
RUSSO, J., TAY, L.K. and RUSSO, I.H., Differentiation of the mammary gland
and susceptibility to carcinogenesis. Breast Cancer Res. Treat., 2, 5–73
(1982).
TRICHOPOULOS, D., HSIEH, C.-C., MACMAHON, B., LIN, T.M., LOWE, C.R.,
MIRRA, A.P., RAVNIHAR, B., SALBER, E.J., VALAORAS, V.G. and YUSA, S.,
Age at any birth and breast cancer risk. Int. J. Cancer, 31, 701–704 (1983).
APPENDIX: MODELS FOR THE EFFECT OF AGE AT ANY BIRTH
Trichopoulos et al. (1983) published a model for estimating the
effects of age at any birth on breast cancer risk. The age at diagnosis
for cases and age at interview for controls is denoted by t. We let ti
represent the age at the time of the ith birth, and assume that there
are s births. The age ti is not defined if there are less than i births for
i 5 l, . . ., s. The first model uses only parous women and can be
written as
11 2 p2 5 µ 1 g (t 2 t*) 1 b p 1 a (t 2 t*)
p
ln
1
2 2
1
1
1
1 a2 (t1 2 t*)
1 p21 .
(1)
Age is centered on t*. The term (t1 2t1*)p21 is used to investigate
if multiparity (2 or more births) interacts with age at first birth. This
model is extended to investigate the separate contributions of all
births.
11 2 p2 5 µ 1 g (t 2 t*) 1 b p
p
ln
1
1 11
11 2 p2 5 µ 1 g (t 2 t*) 1 b p
p
ln
1
1 11
1 a1 (t1 2 t*)
1 p11
1 d1 (t 2 t*) p1 1 r1 (t 2 t*) (t1 2 t*)
1 p11 .
ln
(2)
The variables pi1 are indicator variables taking the value 1 if
there are greater than or equal to i births and zero otherwise. The
term (ti 2 t*i )pi1 serves to ensure that there is no contribution to the
model for ai from women with fewer than i births. Also, if s 5 0, as
it will be for nulli-parous women, the terms in a and b do not
contribute to the model. The estimates for this model are presented
in Table I.
The term b1 represents the effect of one or more births, where the
first is at age t1*, and b2 represents the additional effect of 2 or more
births, where the second is at age t*.
2 An increase in age at first birth
of 1 year is associated with an increase in the log odds of being a
case of a1 units, and a2 represents the effect of the age at second
birth given, the age at first birth.
Hsieh and Lan (1996) investigated the effect of the age at which
women gave birth through a time-dependent model of disease risk.
They also developed their model through a stratification to
compare parity 1 with parity 0, and parity 2 with parity 1. For
(3)
This model includes differential terms for the age at diagnosis for
cases or interview for controls, for nulli-parous and uni-parous
women, and this is the means by which time-dependent effects are
included. If the estimated effects of d or r are significantly different
from zero then there is evidence that age modifies the effects of a
birth (d), or the effect of the age at that birth (r). The predicted odds
ratios in Figure 1 are obtained from the above equation.
In the comparison of uni-parous with bi-parous women the
model is extended:
11 2 p2 5 µ 1 g (t 2 t*) 1 b p
p
1 b2 P2 1 · · · 1 bs ps1
1 a1 (t1 2 t*)p
1
11 1 a2 (t2 2 t*)
2 p21 1 · · · 1 as (ts 2 t*
s ps1) .
nulli-parous vs. uni-parous women, their model for estimating the
effect of age at any birth on breast cancer risk is:
1
2 21
1 a1 (t1 2 t*)
1
1 a2 (t2 2 t*)
2 p21 1 d2 (t 2 t*) p21
(4)
1 r1 (t 2 t*)(t1 2 t*)
1 1 r2(t 2 t*)(t2 2 t*)p
2 21.
This model has time-dependent effects for the age at second birth
over and above the time-dependent effects for the age at the first
birth. These are stratified models and are extensions to model 2,
restricted to 2 births. The parameter estimates for models 3 and 4
are presented in Table IV.
Rosner et al. (1994) published a modification of a mathematical
model for breast cancer incidence that was originally published by
Pike (1987). Subsequently, they developed a log incidence model
(Rosner and Colditz, 1996). These models are more involved than
the ones of Hsieh and Lan (1996) and of Trichopoulos et al. (1987)
in that they are based on the concept of breast tissue aging. Both of
these models were developed for cohort studies where estimates of
incidence can be obtained. We propose to adapt the Rosner et al.
(1994) model for use in case-control studies.
PARITY, AGE AT DELIVERY AND BREAST CANCER RISK
The model for breast cancer incidence at age t, I(t), is written as
I(t) 5 [d(t)]k, where d(t) denotes the breast tissue age at calender
age t, and k is an exponent determined by the rate of increase of
breast cancer incidence with breast tissue age. Breast tissue age is
written as a linear function:
d(t) 5 g1 (t 2 t0) 1 b1 p11 1 b2 p21 1 a1(t 2 t1) p11
1 a*[(t
2 t2) p21 1· · ·1 (t 2 ts) ps1] 1 g2 pm 1 g3(t 2 tm) pm .
2
Age at menarche is denoted t0 and in nulli-parous women breast
tissue is assumed to age at a rate of g1 a year since menarche. There
is no aging of the breast tissue before menarche. The variable pm is
an indicator of menopausal status and takes the value 1 for
post-menopausal women (0 otherwise). Age at menopause is
denoted tm and is defined for post-menopausal women only. This
model also assumes a common effect for the length of time since
the second and subsequent births, denoted a*.
2
We use a model similar to the Rosner and Colditz (1996) model:
11 2 p2 5 µ 1 g (t 2 t ) 1 b p
p
ln
1
0
1 11
1 b2 p2 1 a1(t 2 t1) p11
1 a*[(t
2 t2) p21 1· · ·1 (t 2 ts) ps1]
2
1 g2 pm 1 g3(t 2 tm) pm .
(5)
9
This is not an attempt to model the odds of being a case as a
function of breast tissue age but an attempt to model breast cancer
risk at a particular age as a function of the number of years since the
births. Essentially, we propose to use the functional form of the
model to relate the number of years since an event to the log odds of
breast cancer. The parameter estimates are in Table VI. This model
is also an extension to (2), with the effects of births after 3
constrained to be equal, in that an interaction with age and parity is
included.
It is important not to overinterpret this model within a casecontrol study. As cases and controls are matched for age and as
there are terms in the model for age some parameters are not
identifiable. Specifically, the coefficient g1 will just give the effect
of age at menarche (with a negative sign), rather than the time from
menarche. Furthermore, for a fixed age at menarche a 1-year
increase in years since menarche is the same as a 1-year increase in
age, which cannot be estimated within a case-control study. Thus
when we compare the effect of different patterns of birth the age at
menarche is always constant and so the number of years since
menarche is the same in the comparison groups. The other terms all
involve age through an interaction, and these are estimable and
interpretable within a case-control setting (Hsieh and Lan, 1996;
Breslow and Day, 1980).