American Journal of Epidemiology
Copyright O 1997 by The Johns Hopkins University School of Hygiene and Public Health
All rtght3 reserved
Vol. 145, No. 4
Printed in U.S.A
Explaining the Relation Between Education and Postmenopausal Breast
Cancer
Katherine E. Heck and Elsie R. Pamuk
The authors examined the relation between socioeconomic status, as defined by education level, and
postmenopausal breast cancer incidence using data from the National Health and Nutrition Examination
Survey I Epidemiologic Followup Study. Female participants in the study were followed from 1971-1974 to
1992-1993. Cox proportional hazards modeling was used to determine the relation between breast cancer
incidence and education level. There was a direct dose-response association between education level and
postmenopausal breast cancer risk. Several breast cancer risk factors, including height and reproductiverelated risks such as nulliparity, were found to mediate this relation. Adjustment for these factors reduced, but
did not eliminate, the positive relation between education level and risk of postmenopausal breast cancer;
however, the association was no longer statistically significant. The association between higher education and
increased risk of breast cancer appears to be largely explained by differences in the known risk factors for
breast cancer. Am J Epidemiol 1997; 145:366-72.
breast neoplasms; education; socioeconomic factors
Unlike most other illnesses, breast cancer has been
associated with higher socioeconomic status. This correlation has appeared at both the individual and the
community level. Case-control studies in the United
States, Canada, and Israel (1, 2) indicate that women
with more than 12 years of education have a significantly increased risk of breast cancer. In a Canadian
study (3), education was not related to breast cancer
risk, but cases tended to have greater family incomes
than controls. A number of ecologic analyses of US
data (4-9) have found higher rates of breast cancer
incidence and mortality among women living in more
affluent communities. Smaller, individual-level studies (10-15) have suggested the same disparity. Research in countries as diverse as Brazil (16), Finland
(17-19), Italy (20), Denmark (21), and Australia (22)
have found positive relations between breast cancer
incidence and socioeconomic status.
Although most research suggests this link between
higher socioeconomic status and breast cancer, few
US studies have been able to examine nationally representative individual-level data or to control for mediating variables. The first National Health and Nutri-
tion Examination Survey (NHANES I) Epidemiologic
Followup Survey (NHEFS) has been used to examine
multiple risk factors for breast cancer because it provides an opportunity to use individual-level data to
examine the incidence of breast cancer among a nationally representative cohort of several thousand
women, followed for up to 22 years, and to examine
the effects of known breast cancer risk factors as well
as socioeconomic variables. In one study using
NHEFS, Carter et al. (23) found that education past
high school was associated with a greater risk of breast
cancer. Another socioeconomic variable, income, also
has been positively associated with breast cancer risk
in NHEFS (24).
Additional examination of the link between breast
cancer and socioeconomic status may provide more
information about the etiology of the disease and why
breast cancer risk appears to increase with higher
socioeconomic status. Determining the extent to which
the unusual association between breast cancer and
socioeconomic status is explained by known risk factors should provide more specific information about
which women are at high risk of acquiring the disease.
Received for publication April 12, 1996, and accepted for publication October 9, 1996.
Abbreviations: NHANES I, first National Health and Nutrition Examination Survey; NHEFS, NHANES I Epidemiologic Followup
Study.
From the National Center for Health Statistics, Hyattsville, MD.
Reprint requests to Katherine E. Heck, National Center for Health
Statistics, 6525 Belcrest Road, Room 730, Hyattsville, MD 20782.
MATERIALS AND METHODS
The research question to be addressed by this analysis was whether socioeconomic status is related to the
incidence of breast cancer and whether such a relation
could be explained by variation in reproductive and
366
Education and Postmenopausal Breast Cancer
other breast cancer risk factors, which may vary between women of different socioeconomic standing.
The NHEFS data include several indicators of socioeconomic status, such as education, income, poverty
level of the census tract, and urban/rural status. However, many women in the sample were older than
retirement age, when income and other social circumstances can change rapidly. Education was chosen to
represent socioeconomic status because it is a more
constant measure of lifelong social status than variables such as income or residence.
The sample available for this study consisted of all
women (n = 8,596) who took part in the NHANES I
Epidemiologic Followup Study (25). NHANES I, a
survey and physical examination focusing on nutrition
status and other health issues, was conducted during
1971-1975 on a national probability sample of the
noninstitutionalized population of the United States.
The NHEFS sample consisted of all NHANES I participants who were 25-74 years of age at the original
survey. NHEFS participants were tracked and subsequently surveyed in three periods, 1982-1984, 1987,
and 1992-1993. Participants older than 55 years at
baseline were also surveyed in 1986. The NHEFS
collected health and demographic information through
an interview of the subject or a proxy, obtained death
certificates for participants who had died, and requested medical records from hospitals in which the
subject or proxy reported an overnight stay during the
follow-up period. The response rate to the full
NHANES I (survey and medical examination) was
69.5 percent. Of the original sample, 93 percent were
traced by the 1982-1984 wave, and 87 percent were
either interviewed or a proxy was interviewed, with a
loss to follow-up of 3.5 percent between 1982-1984
and the 1992-1993 follow-up survey.
The study population excluded female participants
who were not traced (n = 376), women of a race other
than black or white (n = 87; race in NHANES I was
collected by interviewer observation, and no ethnicity
information was collected), women with missing information on education level (n = 51), and women
identified as having breast cancer prevalent at baseline
(n = 56).
Staff of the National Cancer Institute completed a
medical record review of breast cancer cases in
NHEFS in August 1996. This study used the National
Cancer Institute designations of case status and date of
diagnosis. Case ascertainment and determination of diagnosis date was made from a thorough review of
available medical records, self-reports, and death certificates. For the eight cases for whom ascertainment
was made only through the death certificate, a date of
diagnosis was imputed based on age-specific survival
Am J Epidemiol
Vol. 145, No. 4, 1997
367
rates from the Surveillance, Epidemiology, and End
Results (SEER) cancer surveillance program.
There were too few premenopausal cases to examine separately, so this analysis was limited to postmenopausal breast cancer. Women who never reached
menopause during the follow-up period or who had an
incidence of premenopausal breast cancer were excluded (n = 1,669), as were 96 additional women for
whom data were missing for the variables of interest.
The final sample consisted of 229 cases and 6,032
noncases.
The relative risk of breast cancer incidence at four
levels of education by years of completion (<12, 12,
13-15, or s l 6 ) was estimated using Cox proportional
hazards modeling in SUDAAN (26). Effects were
calculated as age-adjusted relative risks with 95 percent confidence intervals. The dependent variable was
time to incidence of breast cancer. Because the outcome being evaluated was postmenopausal breast cancer, only postmenopausal follow-up time was included
in the model. Thus, all follow-up time was included
for women who were postmenopausal at baseline, and
women who went through menopause during the
follow-up period contributed only the postmenopause
portion of their follow-up time. Time was counted as
days between menopause or baseline and diagnosis
date of breast cancer for cases, or between menopause
or baseline and last date known alive (usually last
interview date or date of death) for noncases. All
models controlled for age at baseline, entered as a
continuous variable. The sample originally was stratified on race, since both breast cancer risk factors and
education level differed among white and black
women. Overall, however, the results were similar; so
the two were combined in the final analyses.
The following variables were examined as possible
mediators of the education-breast cancer relation:
nulliparity/age (in years) at first birth (nulliparous, age
30 or older at first birth, age 25-29, age 20-24, or
teenage mother); age (in years) at menarche (<13,
^13); age (in years) at menopause (£45, >45; using
date of oophorectomy if earlier than or in lieu of
natural menopause and using a value of 51.3 if otherwise missing, based on a study of average age at
natural menopause (27)); any alcohol use in the 12
months before baseline; height in quintiles; body mass
index (weight/height2) in quintiles; having a first
degree family history of breast cancer; ever having
taken oral contraceptives; ever having taken hormone
or estrogen replacement therapy; and family income
in the year before baseline, in approximate quartiles
(<$7,000, $7,000-9,999, $10,000-14,999, > $ 15,000).
Age at first birth was not measured during the initial
examination but was asked of respondents and proxies
368
Heck and Pamuk
placement therapy) was added, followed by alcohol
use, then body mass index, and then height. Finally,
income was added to the model to examine whether it
explained the remaining socioeconomic variability in
breast cancer risk.
in each wave beginning in 1982. This variable was
imputed for 750 women who said at baseline that they
had had a birth, but for whom age was missing from
follow-up data; these women were assigned educationand age-specific first birth values. Other variables
were measured at baseline, except for parity, age at
menopause, oral contraceptive use, and hormone replacement therapy use, which were also asked in the
follow-up surveys; later values were used for missing
data in the first wave.
Bivariate models were used to estimate the associations between breast cancer and each potentially mediating variable. A multivariate model was then calculated to examine the relative risk associated with
level of education, controlling for other risk factors.
The mediating variables were added to the model in
the following order: first, race and family history of
breast cancer; then the reproductive-related variables
of nulliparity/age at first birth, age at menarche, and
age at menopause. Hormone use (ever having taken
oral contraceptives, ever having taken hormone re-
RESULTS
The association between the variables of interest
and the women's educauon levels was calculated for
the study population (table 1). Higher education was
associated with postmenopausal breast cancer. Educated women had fewer births and were older at their
first birth than women with fewer years of education.
They were more likely to have ever taken oral contraceptives and hormone replacement therapy. More educated women were more likely to have had at least
one drink of alcohol in the past year than were less
educated women.
A plurality of women had 12 years of education;
45.1 percent of the weighted sample had more than a
TABLE 1. Characteristics* by education level of female partidpants in the National Health and
Nutrition Examination Survey I Epidemiologic Followup Study, 1971-1992
Characteristic
<12
(n » 3,604)
Breast cancer cases (%)
Mean age at baseline (years)
White race (%)
Family history of brea3t cancer
Education level (years)
12
13-15
(n = 3,080)
(n = 962)
4.1
3.7
4.8
51.6
83.6
43.9
92.7
44.2
92.5
2:16
(n = 814)
6.6
42.6
94.5
5.5
5.7
5.6
5.2
20.8
23.7
13.2
47.6
22.8
2.5
12.9
48.1
12.8
48.3
26.1
1.7
12.8
49.5
Ever took oral contraceptives
Ever took hormone replacement therapy
Any alcohol use
17.5
30.4
56.7
36.3
42.7
77.0
42.0
43.4
79.2
46.7
46.6
82.3
Body mass index quintiles (kg/m2) (%)t
>29.48
25.48—29.48
23.03-25.47
20.91-23.02
<20.91
28.3
21.5
20.9
15.1
14.1
17.9
17.7
21.0
21.8
21.6
12.5
17.8
18.7
26.6
24.5
16.9
18.9
29.0
Height quintiles (cm) (%)
>166.5
163.0-166.5
159.8-162.9
156.3-159.7
<156.3
15.4
16.6
19.9
23.1
25.0
22.2
23.1
20.9
19.0
14.8
26.1
21.3
20.6
18.3
13.7
32.5
22.7
20.3
15.3
56.1
20.9
14.8
22.8
22.4
30.3
24.5
20.4
17.2
23.5
38.9
11.5
13.5
23.2
51.7
Mean
Mean
Mean
Mean
age at first birth (years)
no. of births
age at menarche (years)
age at menopause (years)
Income (%)f
<$7,000
$7,000-9,999
$10,000-14,999
£$15,000
3.3
8.2
2.1
7.7
27.5
9.2
* VEilues are weighted percentages or means of each educational group,
t Percentages may not total 100 due to rounding.
Am J Epidemiol
Vol. 145, No. 4, 1997
Education and Postmenopausal Breast Cancer
high school education. When we controlled for age,
education level at baseline was a strong predictor of
breast cancer incidence in the NHEFS sample during
the follow-up period (table 2). There was a strong and
direct dose-response relation between years of education and postmenopausal breast cancer risk.
Certain reproductive factors were related to breast
cancer. Women who were nulliparous and those who
were older at menopause tended to have a slightly
higher risk of breast cancer. Age at menarche had a
somewhat negative association with breast cancer;
TABLE 2. Bivariate age-adjusted associations with
postmenopausal breast career risk among black and white
female participants in the National Health and Nutrition
Examination Survey I Epidemlologic Followup Study,
1971-1992
Variable
Relative
risk*
95%
confidence
Interval
Education (years)
£16
13-15
12
<12
2.3
1.4
1.0
White race (compared with black)
Family history of breast cancer
1.0
1.3
0.5-2.1
0.7-2.3
Nulliparity/age at first birth (years)
Nulliparous
First birth at age £30
First birth at age 25-29
First birth at age 20-24
First birth at age <20
1.7
0.7
1.6
1.0
0.9-3.1
0.4-1.3
1.0-2.7
0.7-1.6
Age at menarche <13 years
Age at menopause >45 years
0.7
1.4
0.5-1.1
0.9-2.1
1.1
0.8
1.1
0.6-2.2
0.6-1.2
0.8-1.6
1.0
1.3
1.2
1.2
0.6-1.8
0.8-2.3
0.6-2.1
0.6-2.2
Ever took oral contraceptives
Ever took hormone/estrogen therapy
Any alcohol use
Body mass index (kg/m2)
>29.48
25.48-29.48
23.03-25.47
20.91-23.02
<20.91
Height (cm)
>166.5
163.0-166.5
159.8-162.9
156.3-159.7
<156.3
Income
£$15,000
$10,000-14,999
$7,000-9,999
<$7,000
0.8-2.4
0.7-1.5
1.0f
1-0t
Vol. 145, No. 4, 1997
however, this variable was missing for many women,
some of whose menses began decades before baseline.
Postmenopausal hormone use and oral contraceptive
use were not significantly associated with breast
cancer.
Women with a family history of breast cancer had a
slightly increased risk of the disease. Body mass index
was unrelated to breast cancer risk, but height had a
strong association. The tallest women in this sample
had a risk of breast cancer three times that of the
shortest women.
The association between education and breast cancer decreased to nonsignificance but did not disappear
when we controlled for the various breast cancer risk
factors (table 3). Adding the reproductive risk factors
to the model decreased the relative risk. The variables
with the greatest effect in decreasing the relative risk
were the reproductive risks, including nulliparity, and
height. The final multivariate model continued to demonstrate a slight positive association between postmenopausal breast cancer incidence and education
level during the follow-up period; however, this difference was no longer statistically significant.
The addition of income to the model did not further
explain the socioeconomic disparity in postmenopausal breast cancer risk (table 4). Income did not
have the same dose-response relation to breast cancer
that education had; only women at the highest level of
income were at greater risk for breast cancer.
DISCUSSION
1.0f
3.0
2.1
1.6
1.3
1.0t
1.8-4.9
1.2-3.6
1.0-2.8
0.8-2.1
1.7
0.9
1.1
1.1-2.5
0.6-1.6
0.6-1.9
I.Of
* Relative risk of having an occurrence of postmenopausal
breast cancer. All models control for age at baseline,
t Reference group.
Am J Epidemiol
369
We hypothesized that higher education level would
be associated with a greater incidence of breast cancer
but that the association among more educated women
might be explained by other factors such as nulliparity,
being older at first birth, and greater use of synthetic
hormones. The hypothesis that higher education would
be associated with breast cancer incidence was confirmed, and the association was largely explained by
the addition of known breast cancer risk factors to the
model. After adjustment for differences in nulliparity/
age at first birth, height, menarche and menopause,
and other risk factors for breast cancer, the effect of
higher education on breast cancer incidence was substantially reduced and no longer statistically significant.
The addition of income to the multivariate model
did not reduce the association between education and
breast cancer. This suggests that factors other than
income per se are more likely to contribute to the
etiology of postmenopausal breast cancer, or that income was not well measured by the baseline evaluation. A single measure of household income may not
adequately reflect average lifetime financial resources,
370
Heck and Pamuk
TABLE 3. Multlvariate age-adjusted models of
postmenopausal breast cancer risk among black and white
female participants In the National Health and Nutrition
Examination Survey I Epldemiologlc Followup Study,
1971-1992
Relative
risk*
Variable
95%
confidence
interval
Model 1: Education + race + family history of breast cancer
Education (years)
2.3
1.4
1.0
£16
13-15
12
<12
1.2-4.3
0.8-2.4
0.7-1.5
1.0+
Model 2: Model 1 + nulliparity/age at first birth +
age at menarche + age at menopause
Education (years)
£16
13-15
12
<12
1.9
1.5
1.0
1.0t
1.0-3.4
0.9-2.5
0.7-1.5
Model 3: Model 2 + oral contraceptive use +
hormone replacement
Education (years)
£16
13-15
12
1.8
1.5
1.0
1.0+
1.0-3.2
0.8-2.5
0.7-1.5
Model 4: Model 3 + alcohol use + body mass
Education (years)
£16
13-15
12
1.7
1.4
1.0
1.0+
1.0-3.1
0.8-2.5
0.6-1.5
Model 5: Model 4 + height
Education (years)
£16
13-15
12
1.5
1.3
0.9
1.0+
0.8-2.7
0.8-2.3
0.6-1.5
The associations previously delineated between
breast cancer and various risk factors tended to be
borne out in this study. For example, being childless,
having a family history of breast cancer, and being tall
were all found to be associated with a higher risk of
breast cancer, replicating previous research. The lower
breast cancer risk among women in this study whose
first birth occurred after age 30 may be an artefact of
the small number of women in this category among
this older cohort. Certain associations that we found to
be weak have generated mixed results in previous
studies, and these include the association with hormone replacement therapy (28-32), oral contraceptives (32-36), and body mass index (37-41), often
associated with premenopausal but not postmenopausal breast cancer (1, 42). The association between
moderate alcohol consumption and breast cancer is
disputed in the literature (43-45).
In an earlier study that used this data set of the
association between alcohol use and risk of breast
cancer, Schatzkin et al. (46) found a slightly increased
risk among postmenopausal alcohol users (relative
risk = 1.3). In this sample, which included a longer
follow-up period and more cases, drinking was not
associated with breast cancer. However, the simple
baseline measure of any drinking in the 12 months
before baseline rather than a more comprehensive
lifetime assessment of alcohol intake may have been
too insensitive to provide an accurate estimate of the
breast cancer risk associated with alcohol use.
Using the NHEFS data set, Madigan et al. (24)
found a greater relative risk of breast cancer (relative
TABLE 4. Multivarlate fully adjusted models* of
postmenopausal breast cancer risk, by Income and education
level, among black and white female participants in the
National Health and Nutrition Examination Survey I
Epldemlologic Followup Study, 1971-1992
* Relative risk of having an occurrence of postmenopausal
breast cancer. Models 1-5 control for age at baseline. Each model
adds progressively more variables without eliminating prior ones.
+ Reference group.
variable
Relative
risk*
95%
confidence
Interval
Education (years)
particularly among a group so varied in age at baseline. A similar association with income has been found
in earlier studies using this data set (23, 24).
Certain breast cancer risk factors could not be examined in this analysis due to inadequate data. Breastfeeding information was not sufficient for analysis,
nor was access to health care information available.
However, many women were older than 65 years
during most or all of the study period, so Medicare
may have reduced the effect of differential access to
care due to socioeconomic status. Certain reproductive
variables, such as abortion history and first pregnancy
outcome, were also not available for examination.
£16
12
1.7
1.4
1.1
<12
1.0+
13-15
Income
£$15,000
$10,000-14,999
$7,000-9,999
<$7,000
1.3
0.8
1.0
0.9-3.2
0.8-2.5
0.7-1.7
0.8-2.1
0.5-1.4
0.5-1.7
1.0+
• Relative risk of having an occurrence of postmenopausal
breast cancer. The models above control for age at baseline,
education, Income, race, family history of breast cancer,
nulliparity/age at first birth, age at menarche, age at menopause,
oral contraceptive use, hormone replacement therapy, alcohol use,
body mass index, and height
+ Reference group.
Am J Epidemiol
Vol. 145, No. 4, 1997
Education and Postmenopausal Breast Cancer
risk = 1.8-2.5) associated with family history of
breast cancer than was found in this study. Previous
results of NHEFS studies may be expected to vary
somewhat due to the longer follow-up time and the
more complete case ascertainment used here. In addition, family history of breast cancer is associated with
earlier and more aggressive disease, so the longer
follow-up time will tend to reduce the relation.
That higher education in itself should be a risk
factor for breast cancer seems unlikely. The biologic
factors hypothesized to mediate this relation, such as
nulliparity or an older age at first birth among more
highly educated women, did not fully explain the
excess risk among the most highly educated group,
although the residual risk attributed to this group was
no longer statistically significant. Variability in the
reproductive histories of older women in this sample
may not have been measured well enough to exhibit
the expected differential; misclassification of some
variables, such as menarche, may have blunted their
effects. Other unmeasured factors, such as breastfeeding, diet, use of therapeutic abortion, exposure to environmental toxins, or access to diagnostic services,
might further explain the variation in this data set.
The mixed age of this cohort may have reduced the
magnitude of the socioeconomic effect on breast cancer. The meaning of education may have changed over
time: A college education was less common in earlier
decades, so a given education group may represent a
mix of socioeconomic categories, related to age.
Women in the cohort who were younger than 65 years
might appear to have variability in incidence because
those with access to care could have cancer diagnosed
earlier, whereas among older women in the cohort, the
ascertainment-related variability would be reduced because Medicare diminishes socioeconomic differences
in access to care. In addition, the breast cancer differential by social class may have diminished over time.
A Finnish incidence study (18) found greater social
class variability in breast cancer among women born
before 1930. Finally, abortion may be related to breast
cancer risk. One researcher (47) has suggested that
abortion was more common among higher socioeconomic status women before 1973, whereas in more
recent years, poorer and younger women are more
likely to obtain abortions. Thus, the socioeconomic
effect on breast cancer may have been blunted by
combining women of different age groups.
This study provided new information about the relation between postmenopausal breast cancer incidence and socioeconomic status. The results confirm
the findings of several analyses that breast cancer is
related to higher socioeconomic status and, in particular, a higher education level. That highly educated
Am J Epidemiol
Vol. 145, No. 4, 1997
371
women are at greater risk is partially explained by
their tendency to have no children, to be older at
menopause, and to be tall. Simultaneously controlling
for several known breast cancer risk factors reduced
the elevation in risk among well-educated women to
nonsignificance. This study helps to confirm that the
higher breast cancer risk seen among well-educated
women appears to be attributable to these women's
greater exposure to breast cancer risk factors.
ACKNOWLEDGMENTS
The authors thank Dr. Rachel Ballard-Barbash for her
assistance with the case definitions for this study and Dr.
Nancy Krieger for her helpful comments on an earlier
version of this manuscript.
REFERENCES
1. Paffenbarger RS Jr, Kampert JB, Chang H-G. Characteristics
that predict risk of breast cancer before and after the menopause. Am J Epidemiol 1980;] 12:258-68.
2. Helmrich SP, Shapiro S, Rosenberg L, et al. Risk factors for
breast cancer. Am J Epidemiol 1983;117:35-45.
3. Choi NW, Howe GR, Miller AB, et al. An epidemiologic
study of breast cancer. Am J Epidemiol 1978;107:510-21.
4. Baquet CR, Horm JW, Gibbs T, et al. Socioeconomic factors
and cancer incidence among blacks and whites. J Natl Cancer
Inst 1991;83:551-7.
5. Krieger N. Social class and the black/white crossover in the
age-specific incidence of breast cancer: a study linking census-derived data to population-based registry records. Am J
Epidemiol 1990;131:804-14.
6. Polednak AP. Cancer mortality in a higher-income population
in New York State. Cancer 1990;66:1654-60.
7. Wagener DK, Schatzkin A. Temporal trends in the socioeconomic gradient for breast cancer mortality among US women.
Am J Public Health 1994;84:1003-6.
8. Farley TA, Flannery JT. Late-stage diagnosis of breast cancer
in women of lower socioeconomic status: public health implications. Am J Public Health 1989;79:1508-12.
9. Wells BL, Horm JW. Stage at diagnosis in breast cancer race
and socioeconomic factors. Am J Public Health 1992;82:
1383-5.
10. Devesa SS, Diamond EL. Association of breast cancer and
cervical cancer incidences with income and education among
whites and blacks. J Natl Cancer Inst 1980;65:515-28.
11. Diehr P, Yergan J, Chu J, et al. Treatment modality and
quality differences for black and white breast-cancer patients
treated in community hospitals. Med Care 1989;27:942-58.
12. Dayal HH, Power RN, Chiu C. Race and socio-economic
status in survival from breast cancer. J Chronic Dis 1982;35:
675-83.
13. Freeman HP, Wasfie TJ. Cancer of the breast in poor black
women. Cancer 1989;63:2562-9.
14. Kimmick G, Muss HB, Case LD, et al. A comparison of
treatment outcomes for black patients and white patients with
metastatic breast cancer. Cancer 1991;67:2850-4.
15. Ayanian JZ, Kohler BA, Abe T, et al. The relation between
health insurance coverage and clinical outcomes among
women with breast cancer. N Engl J Med 1993;329:326-31.
16. Gomes Al, Guimaraes MD, Gomes CC, et al. A case-control
study of risk factors for breast cancer in Brazil, 1978-1987.
Int J Epidemiol 1995;24:292-9.
372
Heck and Pamuk
17. Rimpela AH, Pukkala El. Cancers of affluence: positive social
class gradient and rising incidence trend in some cancer forms.
Soc Sci Med 1987;24:601-6.
18. Pukkala E. Cancer risk by social class and occupation: a
survey of 109,000 cancer cases among Finns of working age.
Basel, Switzerland: Karger, 1995.
19. Hakama M, Soini I, Kuosma E, et al. Breast cancer incidence:
geographical correlations in Finland. Int J Epidemiol 1979;8:
33-40.
20. Faggiano F, Zanetti R, Costa G. Cancer risk and social inequalities in Italy. J Epidemiol Community Health 1994;48:
447-52.
21. Ewertz M. Risk of breast cancer in relation to social factors in
Denmark. Acta Oncol 1988;27:787-92.
22. Williams J, Clifford C, Hopper J, et al. Socioeconomic status
and cancer mortality and incidence in Melbourne. Eur J Cancer 1991;27:917-21.
23. Carter CL, Jones DY, Schatzkin A, et al. A prospective study
of reproductive, familial, and socioeconomic risk factors for
breast cancer using NHANES I data. Public Health Rep 1989;
104:45-50.
24. Madigan MP, Ziegler RG, Benichou J, et al. Proportion of
breast cancer cases in the United States explained by wellestablished risk factors. J Natl Cancer Inst 1995;87:1681-5.
25. National Center for Health Statistics, BB Cohen, HE Barbano,
et al. Plan and operation of the NHANES I Epidemiologic
Followup Study, 1982-84. Vital and health statistics. Public
Health series 1, no. 22. Washington, DC: Government Printing
Office, 1987. (DHHS publication no. (PHS) 87-1324).
26. Shah BV, Barnwell BG, Bieler GS. SUDAAN user's manual:
software for analysis of correlated data, release 6.40. Research
Triangle Park, NC: Research Triangle Institute, 1995.
27. Avis NE, McKinlay SM. The Massachusetts Women's Health
Study: an epidemiologic investigation of the menopause. J Am
Med Women's Assoc 1995;50:45-9, 63.
28. Stanford JL, Weiss NS, Voigt LF, et al. Combined estrogen
and progestin hormone replacement therapy in relation to risk
of breast cancer in middle-aged women. JAMA 1995;274:
137-42.
29. Nachtigall MJ, Smilen SW, Nachtigall RD, et al. Incidence of
breast cancer in a 22-year study of women receiving estrogenprogestin replacement therapy. Obstet Gynecol 1992;80:
827-30.
30. Hulka BS. Links between hormone replacement therapy and
neoplasia. Fertil Steril 1994;62:168S-75S.
31. Risch HA, Howe GR. Menopausal hormone usage and breast
cancer in Saskatchewan: a record-linkage cohort study. Am J
Epidemiol 1994;139:670-83.
32. Colditz GA, Hankinson SE, Hunter DJ, et al. The use of
estrogens and progestins and the risk of breast cancer in
postmenopausal women. N Engl J Med 1995;332:1589-93.
33. Rookus MA, van Leeuwen FE. Oral contraceptives and risk of
breast cancer in women aged 20-54 years: Netherlands Oral
Contraceptives and Breast Cancer Study Group. Lancet 1994;
344:844-51.
34. Paul C, Skegg DC, Spears GF. Oral contraceptives and risk of
breast cancer. Int J Cancer 1990;46:366-73.
35. Romieu I, Berlin JA, Colditz G. Oral contraceptives and breast
cancer: review and meta-analysis. Cancer 1990;66:2253-63.
36. Harris RE, Zang EA, Wynder EL. Oral contraceptives and
breast cancer risk: a case-control study. Int J Epidemiol 1990;
19:240-6.
37. De Stavola BL, Wang DY, Allen DS, et al. The association of
height, weight, menstrual and reproductive events with breast
cancer: results from two prospective studies on the island of
Guernsey (United Kingdom). Cancer Causes Control 1993;4:
331-40.
38. Radimer K, Siskind V, Bain C, et al. Relation between anthropometric indicators and risk of breast cancer among Australian women. Am J Epidemiol 1993;138:77-89.
39. Ursin G, Paganini-Hill A, Siemiatycki J, et al. Early adult
body weight, body mass index, and premenopausal bilateral
breast cancer data from a case-control study. Breast Cancer
Res Treat 1995;33:75-82.
40. Goodman MT, Nomura AM, Wilkens LR, et al. The association of diet, obesity, and breast cancer in Hawaii. Cancer
Epidemiol Biomarkers Prev 1992;l:269-75.
41. Harris RE, Namboodiri KK, Wynder El. Breast cancer risk:
effects of estrogen replacement therapy and body mass. J Natl
Cancer Inst 1992;84:1575-82.
42. Willett WC, Browne ML, Bain C, et al. Relative weight and
risk of breast cancer among premenopausal women. Am J
Epidemiol 1985; 122:731-40.
43. Freudenheim JL, Marshall JR, Graham S, et al. Lifetime
alcohol consumption and risk of breast cancer. Nutr Cancer
1995;23:1-11.
44. Longnecker MP. Alcoholic beverage consumption in relation
to risk of breast cancer: meta-analysis and review. Cancer
Causes Control 1994;5:73-82.
45. Simon MS, Carman W, Wolfe R, et al. Alcohol consumption
and the risk of breast cancer: a report from the Tecumseh
Community Health Study. J Clin Epidemiol 1991;44:755-61.
46. Schatzkin AS, Jones DY, Hoover RN, et al. Alcohol consumption and breast cancer in the epidemiology follow-up study of
the first National Health and Nutrition Examination Survey.
N Engl J Med 1987;316:1169-73.
47. Krieger N. Exposure, susceptibility, and breast cancer risk: a
hypothesis regarding exogenous carcinogens, breast tissue development, and social gradients, including black/white differences, in breast cancer incidence. Breast Cancer Res Treat
1989;13:205-23.
Am J Epidemiol
Vol. 145, No. 4, 1997