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The association between recreational physical activity and mammographic density

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The association between recreational physical activity and mammographic density

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Content THE ASSOCIATION BETWEEN
RECREATIONAL PHYSICAL ACTIVITY AND MAMMOGRAPHIC DENSITY
Copyright 2003
by
Conchitina Chato Siozon
A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(APPLIED BIOSTATISTICS/EPIDEMIOLOGY)
December 2003
Conchitina Chato Siozon
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UNIVERSITY OF SOUTHERN CALIFORNIA
THEGRABUATE SC H O O L
UNIVERSITY PARK
LOS ANGELES, CALIFORNIA 90089-1695
This thesis, written by
( Z o ^ C M UifJA { ^ - S i o Z o M
under the direction o f h &h thesis committee, and
approved by all its members, has been presented to and
accepted by the Director o f Graduate and Professional
Programs, in partial fulfillment o f the requirements fo r the
degree o f
Director
Thesis Committee
Chair
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ii
ACKNOWLEDGEMENTS
I would like to give my most sincere gratitude and appreciation to Drs. Giske
Ursin, Leslie Bernstein and Anny Xiang for their exceptional guidance and support
in analyzing and writing this Master’s Thesis. In addition, I am also extending my
gratitude to Huiyan Ma and Jane Sullivan-Halley for their programming support and
Sylvia Tan for her additional suggestions and comments.
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iii
TABLE OF CONTENTS
Acknowledgments................. .ii
List of Tables ............. iv
Abstract ...... v
Introduction.......... ...... 1
Materials and Methods............. ........4
Parent Study ...... .........4
MammograpMc Density Study .............. ...A
Assessment of Physical Activity. ..... ...1
Statistical Analysis ................................... 8
Results........................ 10
Discussion .................................... 21
References ...... ...27
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iv
LIST OF TABLES
Table i A. Least-squares mean (LSM) percent mammographic density in 375
women by age and covariates ..................................................................................... 11
Table IB. Least-squares mean (LSM) absolute mammographic density in 375
women by age and covariates ..... 13
Table 2A. Least-squares mean (LSM) percent mammographic density in 375
women by age and “overall” physical activity hours per w eek ..... 16
Table 2B. Least-squares mean (LSM) absolute mammographic density in 375
women by age and “overall” physical activity hours per w eek ...................................17
Table 3A. Least-squares mean (LSM) percent mammographic density in 375
women by age and “strenuous” physical activity hours per week ..... 19
Table 3B. Least-squares mean (LSM) absolute mammographic density in 375
women by age and “strenuous” physical activity hours per week ............. 20
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V
ABSTRACT
Physical activity has been associated with a reduced risk of breast cancer risk.
However, little is known about the association between recreational physical activity
and mammographic density.
We determined the association between recreational physical activity and
mammographic density by using mammograms from 375 white and African
American women without breast cancer who served as controls in the Los Angeles
component of the Women’s Contraceptive and Reproductive Experiences (CARE)
Study. All analyses were stratified by age at mammogram screening (<50, >50
years). Four time periods of activity were defined: from menarche to mammogram
screening, the first 10 years after menarche, and the recent 10 years and 4 years prior
to mammogram screening. We used a multivariate linear regression modeling
approach to estimate least-squares mean values of absolute and percent
mammographic density within categories of physical activity.
Overall, we found no evidence that physical activity reduced absolute or
percent mammographic density.
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1
INTRODUCTION
Participation in physical activity has been found to reduce breast cancer risk.
However, the exact magnitude of the effect is not clear. The International Agency
for Research on Cancer (IARC) Handbook of Cancer Prevention on weight control
and physical activity found sufficient evidence that physical activity reduces the risk
of breast cancer (IARC 2002). Based on more than 30 epidemiological studies
conducted from Asia, Europe and North America, women who actively participated
in physical activity had lower risk of breast cancer. The studies demonstrated an
average of 20-40% decrease in risk. Studies that further investigated trend with
physical activity found evidence of a dose-response relationship for a decrease in
risk as physical activity increases. The associations were observed in different types
and measurements of physical activity and in different subgroups of women such as
pre- and postmenopausal women and also in women of different ethnicity (IARC
2002).
The association between physical activity and breast cancer risk is quite
complex due to the various biological mechanisms involved and the different effects
it may have on subgroups of women. Physical activity delays menarche (Warren
1980; Frisch and others 1981; Moisan and others 1991; Merzenich and others 1993),
reduces the levels of endogenous sexual and metabolic hormones (Toniolo and
others 1997; Hoffinan-Goetz and others 1998), possibly alters Immune functions
(Shepard and others 1995), and Increases lean body mass (Hoffinan-Goetz and others
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1998). Mechanisms involved in the physical activity breast cancer relationship may
differ by menopausal status. In premenopausal women, physical activity may result
in decreased frequency of ovulatory menstrual cycles and therefore ultimately reduce
exposure to estradiol and progesterone, which are important in the development of
breast cancer (Feicht and others 1978; Bonen and others 1979, 1981; Frisch and
others 1980; Jurkowski and others 1981; Wakat and others 1982; Russell and others
1984; Bernstein and others 1987). In postmenopausal women, obesity may result in
an increased exposure to estrogen through conversion of androgens to estrogen in
adipose tissue (Hoffinan-Goetz and others 1998). Increased physical activity
decreases fat mass and thereby decreasing the level of circulating estrogen
(Hoffinan-Goetz and others 1998). Cauley and colleagues found that increasing
physical activity have a direct negative impact on circulating hormones such as
estrone in postmenopausal women (Cauley and others 1989). Estrone is the primary
estrogen found in postmenopausal women. Postmenopausal women who were more
physically active had lower levels of estrone (Cauley and others 1989).
Mammographic density patterns of the breast are based on the relative
amounts of fat, connective and epithelial tissues (Boyd and others 1998). Epithelial
and connective tissues are radiographicaly dense (white) areas on mammographic
films while fat is dark. Mammographic density is a strong independent risk factor
for breast cancer (Saflas and others 1987; Oza and others 1993; Boyd and others
1995, 1998; Byrne and others 1995; Ursin and others 2003).
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The association between physical activity and mammographic density is
mostly unclear. The two prior studies that investigated this association used different
measures for both physical activity and mammographic density (Gram and others
1999; Vachon and others 2000). Gram and colleagues (Gram and others 1999) used
Tabar parenchymal patterns classification (Gram and others 1997) and found that
women who participated in more than 2 hours per week of recent moderate physical
activity were at a non-statistically significant lower risk for a high-risk
mammographic pattern; (odds ratio, OR, 0.8; 95% confidence interval, Cl, 0.6-1.1)
(Gram and others 1999). Vachon and colleagues (Vachon and others 2000)
estim ated percent mammographic density in discrete five-unit increments from
digitized mammographic films. They used the reported frequency of moderate and
vigorous physical activities over the woman’s lifetime to create an index (low,
moderate, high) of physical activity (Vachon and others 2000). They found no
association between this physical activity index and percent mammographic density
in either premenopausal (P=0.56) or postmenopausal women (P=0.25) (Vachon and
others 2000).
We examined whether recent, past or lifetime patterns of physical activity are
associated with reduced measures of mammographic density in this report.
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MATERIALS AND METHODS
Parent Study
Subjects participating in this study served as controls in the Los Angeles part
of the Women’s Contraceptive and Reproductive Experiences (CARE) Study. This
was a multi-center, population-based case-control study consisting of five centers
including one in Los Angeles (Marchbanks and others 2002). All the subjects in the
Women’s CARE study were US bom, white and African American women with ages
ranging from 35 to 64 years. The Los Angeles County Cancer Surveillance Program
identified breast cancer patients who were newly diagnosed with a first primary
breast cancer between June 1994 and August 1998. Controls were recruited using
random digit dialing (RDD) methods and were frequency matched to cases within 5-
year age strata, ethnicity and residence in Los Angeles County. All subjects were
interviewed using structured questionnaires to capture information on known breast
cancer risk factors including details on previous mammograms and lifelong physical
activity. The participation rates in Los Angeles were as follows: 71.9% for African
American cases, 70.6% for African American controls, 74.6% for white cases and
76.2% for white controls (Marchbanks and others 2002).
Mammographic Density Study
The details of this study have previously been described (Ursin and others
2003). Although we collected mammograms from both cases and controls in the Los
Angeles portion of the Women’s CARE Study, we restrict these analyses on control
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subjects only, in order to assess the impact of physical activity on mammographic
density in the absence of disease. In Los Angeles, controls were eligible If they had
undergone at least one mammogram in the 5 years prior to being Identified by RDD.
We obtained signed mammogram consent forms from each eligible woman in order
to request the most recent mammogram up to diagnosis date (cases) or 12 months
after initial study phone call (controls). In total, we identified 619 eligible women
(331 (53%) whites and 288 (47%) African Americans). The Institutional Review
Board at the University of Southern California approved the protocol for this study.
O f the 619 eligible controls, we were unable to retrieve mammograms for
201 (32%) because 43 had no records at the facility, 69 no longer had available
mammograms, 52 had incomplete reports, 23 had mammograms at facilities that no
longer existed, and 14 had mammograms at facilities that did not respond within the
time allotted. Thus, we obtained one or more mammograms for 418 (68%) women,
of whom 247 (59%) were whites and 171 (41%) were African Americans.
We digitized the craniocaudal mammograms using Omnimedia XRS 6cx
scanner (Lumisys, Sunnyvale, CA) or a Cobrascan CX312T scanner (Radiographic
Digital Imaging, Torrance, CA) which yielded 8-bit (256 shades) gray scale images
that is linear within an absorbance range of 0-2.8 at a resolution of 150 pixels/inch
(59 dots/cm). We found no differences in density assessment between images
scanned by the two scanners.
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The scanned mammograms of 4 women (1 white and 3 African Americans)
could not be used because the quality of the film was too poor for density
measurement. Therefore we obtained mammographic density results for 414 (99%)
women.
The left or right image was randomly selected for each control subject while
assuring an equal number of left and right breasts in controls to match the
distribution of unaffected (contralateral) breasts of the cases within each age group
(Ursin and others 2003). We used the digitized cradiocaudal mammographic images
for density assessments. Dr. Ursin estimated the density for each image, while a
research assistant trained by Dr. Ursin outlined the breast area. They both used the
University of Southern California computer-assisted method, “Madena” that has
been previously described (Ursin and others 1998). To sum m arize in brief, the
“Madena” software assigns pixel values in the images for the following shades: 1) 0
to the darkest (black) shade, 2) 255 to the lightest (white) shade, and 3) intermediate
values to different shades of gray. The research assistant uses an outlining tool to
outline the total area of the breast and the number of pixels within that outline is
summed by the software. To assess the density, Dr. Ursin outlines a region of
interest (ROI). The ROI consists of the entire breast, without the pectoralis muscle,
prominent veins and fibrous strands. Then Dr. Ursin uses a tinting tool to apply
yellow tints to dense pixels with gray levels at or above some threshold X (between 0
and 255). The software measures the number of tinted pixels within the ROI. This
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represents the absolute density of the mammogram. Percent density represents the
fraction (%) of the breast area that contains absolute density.
Assessment o f Physical Activity
Using a calendar of life events to assist in recall, participants in the Women’s
CARE Study provided lifetime histories of participation in physical activity. We
recorded type of activity, ages started and stopped, seasonality of the activity,
months per year, and hours per week spent exercising. Each type of activity was
classified as “non-strenuous” or “strenuous” based on assigned metabolic equivalent
of energy expenditure score (METs). The MET score is defined as the ratio of the
associated metabolic rate for a specific activity to that of the resting metabolic rate
(Anshel and others 1991). The average adult has a MET value of 1 kcal/kg per hour
of oxygen while sitting quietly (Ainsworth and others 2000). For this study, we
classified all physical activities with a score of >6 METs as “strenuous” (Ainsworth
and others 2000). A sample of activities included running, soccer, and competitive
swimming. Examples of activities that were classified as “non-strenuous” are leisure
walking, recreational swimming and tennis. We estimated the total hours per week
each woman spent in each activity for each year. We estimated the average hours
per week of physical activity throughout life and at specific time periods. The time
periods we were interested in were: 1) from age at first menstrual period (FMP) to
age at mammogram screening, 2) within the 10 years after FMP, 3) within the 10
years preceding age at mammogram screening, and 4) within the 4 years preceding
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age at mammogram screening. For these time periods, we estimated the average
amount of time spent in any physical activity as well as the time spent in “non-
strenuous” or “strenuous” activities. The physical activity variables were
categorized using the following intervals: 0, 0.1-1.9, 2+ hours per week of physical
activity. Women who did not participate during the time intervals of interest were
the baseline comparison group. Two analyses were performed to assess the
association of physical activity with mammographic density. The first analysis
focused on an “overall” (both “strenuous” and “non-strenuous” activities) assessment
of physical activity within each time period. The second analysis restricted activity
to those which were considered “strenuous” based on the MET score (Ainsworth and
others 2000).
Statistical Analysis
A multivariate linear regression model approach was used to determine the
relationship between absolute or percent mammographic density and known
potential confounders. We also used the linear regression model approach to
determine the differences in least-squares arithmetic means (LSM) of
mammographic density across levels of physical activity (“overall” and “strenuous”)
while adjusting for possible confounders. Confounders included: ethnicity (white vs.
African American), body mass index (kg/m2 BMI) 5 years before reference date
(continuous), age at mammogram (continuous), age at menarche (continuous),
number of full term pregnancies (0, 1, 2, >3), age at first full-term pregnancy (<20,
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20-24,25-29, >30+/no pregnancy), first- (breast cancer in a mother or a sister) and
second- (breast cancer in an aunt or grandmother) degree breast cancer family
history (yes/no), oral contraceptive use (yes/no) and menopausal and hormone use
status (premenopausal, postmenopausal and current user of estrogen-progestin
replacement therapy (EPRT) or estrogen-alone replacement therapy (ERT) use,
postmenopausal and not currently using EPRT/ERT (either ex-user or never user).
We conducted multivariate analyses of the relationship between physical activity and
mammographic density with and without BMI in the model, as we considered BMI
as both a possible confounder and a possible intermediate variable. Because women
under age 50 had substantially mean higher percent mammographic density than
women aged 50 years or older (P <0.0001) even after adjustment for ethnicity and
BMI (PO.OOOl), all estimated LSM for absolute and percent mammographic density
were stratified by these two age at mammogram screening groups (<50 and >50
years). F-test p-values were used for the following: 1) to compare LSM for absolute
or percent mammographic density between the two age groups, and within the
subgroups of non-ordinal covariates by age group, 2) to test for linear association
between absolute or percent mammographic density and the ordinal covariates
within age groups, and 3) to test for interactions between the two age groups and the
non-ordinal covariates. Z-test was used to assess the equality of slopes of absolute
and percent mammographic density obtained in a single multivariate regression
models fitting terms for each of the two age groups. A one degree of freedom tests
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for trend was used to determine whether a linear (monotonic) relationship existed
between physical activity and absolute or percent mammographic density using the
three categories of physical activity. All analyses were performed using the SAS
software package (SAS Institute Inc., Cary, NC). All P values reported are two-
sided.
In order to maintain a consistent sample size for all analyses, we excluded: 24
women with unknown menopausal status, 1 woman with unknown oral contraceptive
use, 1 woman missing age at first full-term pregnancy, 3 women missing age at
menarche, and 10 women who were adopted or who did not know the breast cancer
family history on more than half of their first-degree family members. An additional
29 women had unknown family history for 1-2 family members, but had known
negative family history for the rest. We have included these 29 women in the
analyses, coding them as having no known family history of breast cancer.
Therefore, 375 women were used for our final analyses.
RESULTS
The distributions and estimated least-square means for percent and absolute
mammographic density across levels of the possible confounders, are reported in
Table 1A & Table IB respectively.
Fewer M l term pregnancies and later age at first full term pregnancy were
associated with increased mean percent mammographic density. Results were
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Table 1 A: Least-squares mean percent mammographic density in 375 women by age and covariates1
1. Least square mean (LSM) percent mammographic density stratified by age at mammography (< 50 years, >50
years) and adjusted for ethnicity (white and African American) and age at mammography (continuous variable)
for all covariates except ethnicity (adjusted for only age at mammography).
2. F test p value comparing LSM percent mammographic density between two age groups (< 50 years, >50 years)
after adjustment for ethnicity.
3. F test p value testing linear association between a covariate and percent mammographic density after
stratification by age at mammography (< 50 years, >50 years) and adjustment for ethnicity (white and African
American) and age at mammography (continuous variable).
4. Z test p value comparing regression coefficients between two mammographic age groups (< 50 years, >50
years) after adjustment for ethnicity (white and African American) and age at mammography (continuous
variable).
5. F test p value comparing LSM percent mammographic density among subgroups in a covariate after
stratification by age at mammography (< 50 years, >50 years) and adjustment for ethnicity (white and African
American) and age at mammography (continuous variable) except for ethnicity (that was adjusted for only age at
mammography).
6. F test p value testing interaction between age at mammography (< 50 years, >50 years) and a covariate after
adjustment for age at mammography (continuous variable) and ethnicity. When checking interaction with
ethnicity, only age at mammography was adjusted.
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Age < 50 Years Old Age >= 50 Years Old
N(%) Least- N(%) Least- p-value
squares squares
means means
(std err) (std err)
% Mammographic Density 176(46.9) 36.4(1.6) 199 (53.1) 23.5 (1.5)
p-value2 <0.0001
Number of M l term pregnancies
None 39(22.1) 42.6 (3.7) 28(14.1) 24.3 (3.6) 0.89 4
1 32 (18.2) 41.8(4.0) 23 (11.6) 26.6 (4.0)
2 63 (35.8) 31.7(2.9) 50(25.1) 24.3 (2.7)
3+ 42 (23.9) 33.7 (3.5) 98 (49.2) 22.0(1.9)
p-value3 0.02 0.37
Age at first full term pregnancy (years)
<20 yrs old 45 (25.6) 28.9 (3.4) 51 (25.6) 20.6 (2.7) 0 .1 9 4
20-24 36 (20.4) 35.1 (3.9) 76 (38.2) 22.5 (2.2)
25-29 36 (20.5) 41.9(3.8) 30(15.1) 23.6 (3.5)
>30 & no pregnancy 59(33.5) 39.6 (3.0) 42(21.1) 28.5 (2.9)
p-value3 0.02 0.05
Age at menarche (years)
<12 yrs old 97 (55.1) 33.9 (2.3) 108 (54.3) 21.9(1.8) 0.26 4
13 yrs old 41 (23.3) 41.3 (3.6) 45 (22.6) 27.7 (2.9)
>13 yrs old 38 (21.6) 37.6 (3.7) 46(23.1) 22.8 (2.9)
p-value3 0.24 0.52
Body mass index (kg/m2)
<23.3 80 (45.5) 46.5 (2.4) 46(23.1) 31.5(2.8) 0.93 4
>23.3 - 27.4 48 (27.3) 35.0 (3.0) 77 (38.7) 25.5(2.1)
>27.4 48 (27.3) 21.0 (3.0) 76 (38.2) 16.5 (2.1)
p-value3 <0.0001 <0.0001
Family history o f cancer
None 131 (74.4) 37.1 (2.0) 159(79.9) 21.6(1.5) 0.02 6
Yes 45 (25.6) 34.4 (3.5) 40 (20.1) 30.9 (3.0)
p-value5 0.50 0.005
Ever use oral contraceptives
No 19(10.8) 32.7 (5.4) 60(30.1) 21.9(2.5) 0.84 6
Yes 157 (89.2) 36.9(1.8) 139 (69.9) 24.1 (1.6)
p-value5 0.46 0.46
Menopausal and hormone use status
Premenopausal 132 (75.0) 38.8 (2.0) 15(7.5) 34.1 (5.1) 0.46 s
Postmenopausal current EPRT/ERT use 24(13.6) 31.2 (4.8) 105 (52.8) 20.8 (1.9)
Postmenopausal ex/never EPRT/ERT use 20(11.4) 26.9 (5.1) 79 (39.7) 24.8 (2.2)
p-value3 0.05 0.04
Ethnicity
White 109(61.9) 37.6 (2.2) 117(58.8) 24.6(1.8) 0.92 s
African American 67 (38.1) 34.4 (2.8) 82(41.2) 21.8(2.1)
p-value5 0.37 0.30
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Table IB : Least-squares mean absolute mammographic density/1000 in 375 women by age and covariates1
1. Least squares mean (LSM) absolute mammographic density stratified by age at mammography (< 50 years,
>50 years) and adjusted for ethnicity (white and African American) and age at mammography (continuous
variable) for ail covariates except ethnicity (adjusted for only age at mammography).
2. F test p value comparing LSM absolute mammographic density between two age groups (< 50 years, >50
years) after adjustment for ethnicity.
3. F test p value testing linear association between a covariate and absolute mammographic density after
stratification by age at mammography (< 50 years, >50 years) and adjustment for ethnicity (white and African
American) and age at mammography (continuous variable).
4. Z test p value comparing regression coefficients between two mammographic age groups (< 50 years, >50
years) after adjustment for ethnicity (white and African American) and age at mammography (continuous
variable).
5. F test p value comparing LSM absolute mammographic density among subgroups in a covariate after
stratification by age at mammography (< 50 years, >50 years) and adjustment for ethnicity (white and African
American) and age at mammography (continuous variable) except for ethnicity (that was adjusted for only age at
mammography).
6. F test p value testing interaction between age at mammography (< 50 years, >50 years) and a covariate after
adjustment for age at mammography (continuous variable) and ethnicity. When checking interaction with
ethnicity, only age at mammography was adjusted.
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Age < 50 Years Old Age >= 50 Years Old
N(%) Least-
squares
means (std
err)/1000
N(%) Least-
squares
means (std
err)/1000
p-value
Absolute M ammographic Density 176 (46.9) 165.9 (9.6) 199(53.1) 122.9 (9.0)
p-value2 0.0012
N umber o f full term pregnancies
None 39(22.1) 175.4(21.3) 28(14.1) 126.6(23.4) 0 .8 1 4
1 32(18.2) 220.1 (23.2) 23 (11.6) 119.0(26.0)
2 63 (35.8) 145.1 (16.6) 50(25.1) 128.2(17.5)
3+ 42 (23.9) 145.2 (20.3) 98 (49.2) 120.9(12.5)
p-value3 0.07 0.86
Age at first full term pregnancy (years)
<20 yrs old 45 (25.6) 152.7(20.4) 51 (25.6) 114.3(17.8) 0.39 4
20-24 36 (20.4) 176.5 (22.8) 76 (38.2) 122.1 (14.2)
25-29 36 (20.5) 176.3 (22.6) 30(15.1) 130.7 (22.6)
>30 & no pregnancy 59 (33.5) 161.9(17.9) 42(21.1) 131.1 (19.1)
p-value3 0.80 0.48
Age at menarche (years)
<12 yrs old 97 (55.1) 167.3 (13.6) 108 (54.3) 121.9(11.9) 0 .8 6 4
13 yrs old 41 (23.3) 179.5 (20.9) 45 (22.6) 126.3 (18.5)
>13 yrs old 38(21.6) 145.6 (21.6) 46(23.1) 123.4(18.6)
p-value3 0.51 0.91
Body mass index (kg/m2 )
<23.3 80 (45.5) 170.9(15.2) 46(23.1) 109.8(18.6) 0.54 4
>23.3 - 27.4 48 (27.3) 184.4(19.3) 77 (38.7) 133.3(14.0)
>27.4 48 (27.3) 137.5(19.5) 76 (38.2) 121.2(14.3)
p-value3 0.23 0.75
Family history o f cancer
None 131 (74.4) 172.1 (11.7) 159 (79.9) 121.1 (9.7) 0.22 6
Yes 45 (25.6) 146.3 (20.3) 40(20.1) 132.0(19.4)
p-value5 0.28 0.61
Ever use oral contraceptives
No 19(10.8) 128.2 (31.1) 60(30.1) 114.0(16.3) 0.57 s
Yes 157 (89.2) 170.0(10.6) 139(69.9) 127.3( 10.6)
p-value5 0.21 0.50
Menopausal and hormone use status
Premenopausal 132 (75.0) 172.1 (11.7) 15 (7.5) 119.9(33.3) 0.92 s
Postmenopausal current EPRT/ERT use 24(13.6) 148.4 (28.0) 105 (52.8) 127.3 (12.3)
Postmenopausal ex/never EPRT/ERT use 20(11.4) 142.5 (29.9) 79 (39.7) 118.6(14.3)
p-value5 0.53 0.90
Ethnicity
White 109(61.9) 155.7(12.8) 117(58.8) 113.7(11.3) 0.95 s
African American 67 (38.1) 181.4(16.3) 82(41.2) 137.0(13.5)
p-value5 0.21 0.19
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15
statistically significant for younger women (Table 1 A, both P for trend=0.02).
Means percent mammographic density declined with increasing BMI levels
within each age group (Table 1 A, both P for trend <0.0001). A first or second
degree family history of breast cancer was associated with increasing percent
mammographic density for older, but not younger women (Table 1 A, P=0.005
for older women). This effect modification by age group was statistically
significant (Table 1 A, P=0.Q2). Mean percent mammographic density differed
by menopausal status within each age group (Table 1 A, P=0.05 for women <50
years and P=0.04 for women >50 years). Premenopausal women had higher
mean density than did postmenopausal women in both age groups.
The results for absolute mammographic density (Table IB) showed
similar results to percent mammographic density, but no differences were
statistically significant. In particular, the association of decreasing absolute
density with increasing BMI was not statistically significant in younger women
(Table IB, P for trend=0.23). In older women, absolute mammographic density
increased as BMI increased but was not statistically significant (Table IB, P for
trend=0.75). In addition, whites had lower absolute densities compared to
African Americans (Table IB, P=0.21 & P=0.19).
No statistically significant inverse associations between mammographic
density and “overall” physical activity were observed (Table 2A & Table 2B).
However, for physical activity from age at menarche to age at mammogram
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16
Table 2A: Least-squares mean percent mammographic density in 375 women by age and "overall" physical
activity hours/week
Age < 50 Years Old Age > = 5 0 Years Old
Time periods o f overall N (%) Without BMI With BMI in N (%) Without BMI With BMI in
physical activity in full model1 full model2 in full model1 full model2
From menarche to
mammogram screening
0 34(19.3) 28.6 (3.9) 30.5 (3.6) 40(20.1) 20.5 (3.1) 20.9 (2.9)
>0.1-1.9 82 (46.6) 37.3 (2.5) 37.4 (2.2) 97 (48.7) 23.8 (1.9) 24.2(1.8)
2+ 60 (34.1) 39.6 (2.9) 38.4 (2.6) 62 (31.2) 24.7 (2.4) 23.9 (2.3)
p-value3 0.04 0.12 0.31 0.48
10 years time period
after menarche
0 76 (43.2) 34.9 (2.7) 36.5 (2.4) 103 (51.8) 22.3 (1.8) 22.8 (1.7)
>0.1-1.9 45 (25.6) 35.7 (3.4) 36.3(3.1) 39 (19.6) 24.6 (3.0) 22.7 (2.9)
2+ 55 (31.3) 39.1 (3.1) 36.5 (2.8) 57 (28.6) 24.7 (2.5) 25.0 (2.4)
p-value3 0.32 0.99 0.40 0.47
10 years time period
prior to mammogram
screening
0 60(34.1) 31.6(2.9) 32.3 (2.6) 68 (34.2) 21.7(2.3) 22.2 (2.2)
>0.1-1.9 54 (30.7) 40.3 (3.0) 40.5 (2.8) 57 (28.6) 21.2(2.5) 22.1 (2.4)
2+ 62 (35.2) 37.7 (2.8) 36.8 (2.6) 74 (37.2) 26.7 (2.2) 25.6(2.1)
p-valueJ 0.14 0.23 0.12 0.25
4 years time period
prior to mammogram
screening
0 82 (46.6) 32.9 (2.5) 33.9(2.3) 81 (40.7) 21.5(2.1) 22.0 (2.0)
>0.1-1.9 37(21.0) 38.8(3.7) 38.8 (3.4) 37(18.6) 20.4(3.1) 21.9 (3.0)
2+ 57 (32.4) 39.9 (3.0) 38.5 (2.7) 81 (40.7) 26.7(2.1) 25.6 (2.0)
p-valueJ 0.07 0.19 0.08 0.20
1. & 2. Least squares mean (LSM) percent mammographic density stratified by age at mammography (<50 years,
>50 years) and both adjusted for age at mammography (continuous variable), age at first full-term pregnancy
(<20, 20-, 25-, >30 and never full term pregnancy), number o f full term pregnancy (0, 1, 2, >3), age at menarche
(continuous variable), oral contraceptive use (yes, no), first-(breast cancer in a mother or sister) and second-
breast cancer in an aunt or grandmother) degree breast cancer family history (yes, no), menopausal and hormone
use status (premenopausal women, postmenopausal women: current user o f estrogen-progestin replacement
therapy (EPRT)/ or estrogen-alone replacement therapy (ERT) user, not current EPRT/ERT user), and ethnicity
(white and A frican American).
2. LSM percent mammographic density stratified by age at mammography (<50 years, >50 years) also adjusted
for body mass index (continuous variable).
3. F test p value testing linear association between “overall” physical activity and percent mammographic density
after stratification by age at mammography and adjusted by above variables from footnote 1 & 2.
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17
Table 2B: Least-squares mean absolute mammographic density in 375 women by age and "overall" physical
activity hours/week
Age < 50 Years Old A ge >= 50 Years Old
Time periods o f overall N (%) Without BMI With BMI in N (%) W ithout BMI With BMI in
physical activity in full model full model2 in full model1 full model2
From menarche to
mammogram screening
0 34 (19.3) 158.8 (23.5) 162.2(23.5) 40(20.1) 98.9 (20.8) 99.4 (20.8)
>0.1-1.9 82 (46.6) 168.8(14.8) 169.1 (14.7) 97 (48.7) 134.9(13.0) 135.5(13.1)
2+ 60(34.1) 164.7(17.4) 162.4(17.3) 62 (31.2) 120.8 (16.3) 119.6(16.3)
p-valueJ 0.89 0.95 0.55 0.60
10 years time period
after menarche
0 76 (43.2) 176.8(15.6) 179.9(15.6) 103 (51.8) 119.0(12.5) 119.9(12.5)
>0.1-1.9 45 (25.6) 161.0(20.1) 162.0 (20.0) 39 (19.6) 104.5 (20.5) 101.4(20.7)
2+ 55 (31.3) 153.6(18.2) 148.4(18.3) 57 (28.6) 143.8(17.0) 144.3 (17.0)
p-value3 0.34 0.20 0.32 0.33
10 years time period
prior to mammogram
screening
0 60(34.1) 147.4(17.1) 148.6(17.0) 68 (34.2) 114.9(15.9) 115.5(15.9)
>0.1-1.9 54 (30.7) 189.7(18.0) 190.2(17.9) 57 (28.6) 125.3 (17.1) 126.6 (17.2)
2+ 62 (35.2) 161.9(16.8) 160.3 (16.7) 74 (37.2) 129.4(15.0) 127.9(15.1)
p-value3 0.57 0.64 0.52 0.59
4 years time period prior
to mammogram
screening
0 82 (46.6) 150.7(14.7) 152.4(14.7) 81 (40.7) 117.9(14.4) 118.6(14.4)
>0.1-1.9 37(21.0) 175.9 (22.0) 175.8(21.9) 37(18.6) 135.6(21.7) 137.9 (21.8)
2+ 57 (32.4) 179.9(17.8) 177.5 (17.8) 81 (40.7) 123.1 (14.3) 121.3(14.4)
p-value3 0.20 0.27 0.81 0.90
1. & 2. Least squares mean (LSM) absolute mammographic density stratified by age at mammography (<50
years, >50 years) and both adjusted for age at mammography (continuous variable), age at first full-term
pregnancy (<20, 20-, 25-, >30 and never full term pregnancy), number o f full term pregnancy (0, 1, 2, >3), age at
menarche (continuous variable), oral contraceptive use (yes, no), first-(breast cancer in a mother or sister) and
second-(breast cancer in an aunt or grandmother) degree breast cancer family history (yes, no), menopausal and
hormone use status (premenopausal women, postmenopausal women: current estrogen-progestin replacement
therapy (EPRT)/estrogen-alone replacement therapy (ERT) user, not current EPRT/ERT user), and ethnicity
(white and African American).
2. LSM absolute mammographic density stratified by age at mammography (<50 years, >50 years) also adjusted
for body mass index (continuous variable).
3. F test p value testing linear association between “overall” physical activity variables and absolute
mammographic density after stratification by age at mammography and adjusted by above variables from
footnote 1 & 2.
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18
screening, there was a suggested positive association with percent density in younger
women (higher percent density among more physically active women), but this
association diminished and was no longer statistically significant when additionally
adjusting for BMI (Table 2A, P for trend=0.12). A weak inverse pattern was
observed in younger women within the 10 years after menarche between absolute
density and physical activity after additionally adjusting for BMI (Table 2B, P for
trend=0.20). A weak, but non-statistically significant positive association was found
among younger, but not older women between physical activity and absolute
mammographic density within the 4 years prior to the mammogram screening even
after additional adjustment of BMI (Table 2B).
We found no evidence of a statistically significant inverse association
between “strenuous” recreational physical activity and mammographic density
(Table 3 A & Table 3B). In older women we observed a positive association between
physical activity and percent mammographic density from menarche to mammogram
screening, but this diminished after additionally adjusting for BMI (Table 3 A, P for
trend=0.O6).
We further stratified our analyses by ethnicity and found no statistically
significant association between physical activity and mammographic density (results
not shown).
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19
Table 3A: Least-squares mean percent mammographic density in 375 women by age and "strenuous" physical
activity hours/week
Time periods o f strenuous
physical activity
Age < 50 Years Old Age >= 50 Years Old
N (%) Without BMI
in full model1
With BMI in
full model2
N (%) Without BMI
in full model1
With BMI in
full model2
From menarche to
mammogram screening
0 92 (52.3) 35.1 (2.4) 36.7 (2.2) 134 (67.3) 21.1 (1.6) 21.4(1.5)
>0.1-1.9 66 (37.5) 36.4 (2.8) 35.1 (2.6) 56(28.1) 28.7 (2.5) 28.1 (2.4)
2+ 18 (10.2) 43.2 (5.4) 39.7 (5.0) 9(4.5) 25.4 (6.2) 24.2 (5.9)
p-value3 0.24 0.84 0.03 0.06
10 years time period after
menarche
0 126 (71.6) 37.7 (2.0) 38.5 (1.8) 162 (81.4) 22.8 (1.5) 23.0(1.4)
>0.1-1.9 32 (18.2) 31.9(4.1) 30.2 (3.7) 24(12.1) 25.3 (3.9) 23.7 (3.7)
2+ 18 (10.2) 35.6 (5.4) 32.8 (4.8) 13 (6.5) 28.1 (5.3) 27.8 (5.0)
p-value3 0.40 0.08 0.27 0.41
10 years time period prior
to mammogram screening
0 120 (68.2) 34.3 (2.1) 35.1 (1.9) 157(78.9) 22.5 (1.5) 22.8(1.4)
>0.1-1.9 39 (22.2) 40.1 (3.7) 38.7 (3.4) 30(15.1) 26.9 (3.5) 25.4 (3.3)
2+ 17(9.7) 43.0 (5.7) 40.6 (5.2) 12 (6.0) 27.2 (5.5) 26.5 (5.2)
p-value3 0.08 0.23 0.21 0.36
4 years time period prior
to mammogram screening
0 137(77.8) 36.0(1.9) 36.6(1.8) 165 (82.9) 22.8 (1.4) 23.0(1.4)
>0.1-1.9 21 (11.9) 38.9 (5.1) 38.0 (4.6) 21 (10.6) 25.8 (4.2) 24.1 (4.0)
2+ 18(10.2) 36.8 (5.6) 33.2 (5.0) 13 (6.5) 27.3 (5.3) 27.5 (5.0)
p-value3 0.76 0.65 0.32 0.39
1. & 2. Least squares mean (LSM) percent mammographic density stratified by age at mammography (<50 years,
>50 years) and both adjusted for age at mammography (continuous variable), age at first full-term pregnancy
(<20, 20-, 25-, >30 and never full term pregnancy), number o f full term pregnancy (0, 1, 2, >3), age at menarche
(continuous variable), oral contraceptive use (yes, no), first-(breast cancer in a mother or a sister) and second-
breast cancer in an aunt or grandmother) degree breast cancer family history (yes, no), menopausal and hormone
use status (premenopausal women, postmenopausal women: current user o f estrogen-progestin replacement
therapy (EPRT)/estrogen-alone replacement therapy (ERT) user, not current EPRT/ERT user), and ethnicity
(white and African American).
2. LSM percent mammographic density stratified by age at mammography (<50 years, >50 years) also adjusted
for body mass index (continuous variable).
3. F test p value testing linear association between “strenuous” physical activity and percent mammographic
density after stratification by age at mammography and adjusted by above variables from footnote 1 & 2.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
20
Table 3B: Least-squares mean absolute mammographic density in 375 women by age and "strenuous" physical
activity hours/wk
Time periods o f strenuous
physical activity
Age < 50 Years Old Age >= 50 Years Old
N (%) Without BMI
in full model1
With BMI in
full model2
N (%) Without BMI
in full m odel1
With BMI in
full model2
From menarche to
mammogram screening
0 92 (52.3) 157.6(14.3) 160.2(14.3) 134 (67.3) 113.6(11.0) 114.1 (11.0)
>0.1-1.9 66 (37.5) 172.4(16.8) 170.3 (16.8) 56(28.1) 147.3 (17.1) 146.4(17.2)
2+ 18(10.2) 180.3 (32.1) 174.8 (32.2) 9 (4.5) 117.6 (42.8) 116.0 (42.8)
p-value3 0.43 0.61 0.24 0.28
10 years time period
after menarche
0 126 (71.6) 171.8(11.9) 173.3 (11.8) 162 (81.4) 123.0(10.0) 123.4(10.0)
>0.1-1.9 32 (18.2) 147.9(24.3) 144.8 (24.2) 24(12.1) 111.6 (27.0) 109.3 (27.0)
2+ 18(10.2) 152.2 (31.8) 147.2(31.7) 13 (6.5) 148.0 (36.4) 147.5 (36.4)
p-value3 0.39 0.28 0.73 0.78
10 years time period
prior to mammogram
screening
0 120 (68.2) 158.5(12.3) 159.8(12.3) 157(78.9) 118.1 (10.2) 118.5(10.2)
>0.1-1.9 39 (22.2) 179.5(21.9) 177.2(21.9) 30(15.1) 150.8(23.9) 148.9(24.1)
2-r 17 (9.7) 182.6 (33.8) 178.5 (33.8) 12 (6.0) 122.0 (37.5) 121.1 (37.5)
p-value3 0.37 0.47 0.47 0.52
4 years time period prior
to mammogram
screening
0 137 (77.8) 165.7(11.4) 166.7(11.4) 165 (82.9) 118.5 (9.9) 118.7(9.9)
>0.1-1.9 21 (11.9) 172.2 (29.9) 170.6 (29.8) 21 (10.6) 158.5 (28.9) 156.4(29.0)
2+ 18(10.2) 156.4 (32.7) 150.0(32.8) 13 (6.5) 127.4(35.8) 127.7(35.8)
p-valueJ 0.87 0.71 0.43 0.46
1. & 2. Least squares mean (LSM) absolute mammographic density stratified by age at mammography (<50
years, >50 years) and both adjusted for age at mammography (continuous variable), age at first full-term
pregnancy (<20, 20-, 25-, >30 and never full term pregnancy), number o f full term pregnancy ( 0 ,1, 2, >3), age at
menarche (continuous variable), oral contraceptive use (yes, no), first-(breast cancer in a mother or a sister) and
second-(breast cancer in an aunt or grandmother) degree breast cancer family history' (yes, no), menopausal and
hormone use status (premenopausal women, postmenopausal women: current estrogen-progestin replacement
therapy (EPRT)/estrogen alone replacement therapy (ERT) user, not current EPRT/ERT user), and ethnicity
(white and African American).
2. LSM absolute mammographic density stratified by age at mammography (<50 years, >50 years) also adjusted
for body mass index (continuous variable).
3. F test p value testing linear association between “strenuous” physical activity variables and absolute
mammographic density after stratification by age at mammography and adjusted by above variables from
footnote 1 & 2.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
21
DISCUSSION
Our study found no evidence that recreational physical activity reduces
percent or absolute mammographic density. We did find modest relationsMp, both
inverse and positive, in certain subgroup of women, but none were statistically
significant, especially after additionally adjusting for BMI. In younger women, we
found some evidence of an inverse effect of “overall” physical activity on absolute
mammographic density when basing the physical activity measure on activity during
the 10 years following menarche. This inverse effect was also evident between
“strenuous” physical activity and percent mammographic density in the same age
group and time period of physical activity. In contrast, we found some evidence of a
positive association between “overall” physical activity and percent mammographic
density using average lifetime activity from menarche to mammogram screening,
and absolute mammographic density within the 4 years prior to mammogram
screening. For all analyses where a modest positive association with physical
activity was observed, the association diminished after adjusting for BMI.
Two previous studies investigated the association between mammographic
density and physical activity. Gram and colleagues (Gram and others 1999) found a
weak, and statistically non-significant association between Tabar parenchymal
patterns and moderate physical activity (OR, 0.8; 95% Cl, 0.6-1.1) when the subjects
had graded their own recent physical activity history. They also used Tabar
classification of mammographic parenchymal patterns into five groups, patterns I-V
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22
(Gram and others 1997). For their analysis, the low-risk group was defined as
having patterns I through III and the high-risk group, patterns IV and V (Gram and
others 1997). Their subjects were Norwegian women aged 40-56 years. Their
physical activity measure assessed both occupational and recreational activity. Only
10% of the women in the study reported participating in the highest level of
recreational physical activity, moderate activity. Few women participated in
strenuous physical activity and more than 50% of the women were sedentary. They
further stratified their analyses by menopausal status, parity and BMI.
Vachon and colleagues (Vachon and others 2000) found no association
between physical activity and percent mammographic density in either
premenopausal or postmenopausal women when physical activity was categorized
into three levels, (low, moderate, and high) and percent mammographic density was
visually estimated (Vachon and others 2000). The subjects were family members of
women with breast cancer. The family members included sisters, daughters, nieces
and granddaughters and women who were spouses of the male relatives of the breast
cancer patients. Physical activity was indexed into categorical levels of low,
moderate, and high (Vachon and others 2000). The women that had mammographic
density information were younger and moderate exercisers compared to the women
that did not have mammographic density information.
Our study population and measurement of physical activity and
mammographic density differed from the two previous studies. We used digitized
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23
scanned mammograms from whites and African Americans in the US. We also used
a highly rated assessment method for physical activity (Ainsworth and others 1998)
from Bernstein and colleagues (Bernstein and others 1994; Carpenter and others
1999). Our findings are consistent with the overall results of the previous two
studies (Gram and others 1999; Vachon and others 2000).
The magnitude of the effect of physical activity on mammographic density is
quite complex and unclear due to the various possible intermediate or biological
pathways. Physical activity also affects body composition and possibly, as a result,
the production of estrogen in peripheral tissue. This would be expected to yield a
reduced percent mammographic density. On the other hand, the reduction in body
fat also means less fat in the breast area, which should lead to increased percent
density (but no effect on absolute mammographic density). Therefore, physical
activity, menopausal status, BMI, and mammographic density provide a complex
array of intermediate and biological pathways to breast cancer risk.
The acute response of the ovarian hormones to physical activity among
premenopausal women is increased levels of estradiol and progesterone (Bonen and
others 1979; Jurkowski and others 1981). In contrast, the long term effects of
intense physical activity include the shortening of the luteal phase of the menstrual
cycle (Bonen and others 1981; Ellison and others 1986), reduced levels of follicle-
stimulating hormones, (Bonen and others 1979, 1981), reduced levels of
progesterone in the luteal phase (Frisch and others 1981), secondary amenorrhea,
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24
especially during adolescence (Feicht and others 1978; Frisch and others 1980;
Wakat and others 1982; Russell and others 1984), and reduced frequency of
ovulatory menstrual cycles (Bernstein and others 1987). We observed a modest
inverse relationship between physical activity in the first ten years after menarche
and mammographic density in younger women. This is consistent with reduced
breast cancer risk observed among younger women in association with recreational
physical activity (Bernstein and others 1994) and suggests that mammographic
density may be a marker of this altered risk.
In general, physical activity promotes lean body mass. The lower the body
fat content, the denser the breast tissue due to less fat in the breast. Thus, when the
duration of physical activity increased, mammographic density is increased as
observed from our analyses. The tendency for an increasing pattern of percent
mammographic density as physical activity increases was seen in both age groups
and in certain time periods in a woman’s life when participating in physical activity.
The confounding effect of BMI on the association between physical activity and
mammographic density could have resulted in spuriously biasing the association in a
positive direction away from the null since BMI is found to be negatively associated
with both physical activity and percent mammographic density. BMI Is less of a
confounder of the physical activity and absolute density association, given that BMI
is less associated with absolute density. Our study only used BMI as an
anthropometric measure in our analyses, which may not be the ideal proxy for the
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25
real confounder: body fat. Given the complex interactions between body fat,
physical activity and mammographic density, future studies should consider other
anthropometric measures than simply body weight and height.
Although unlikely, it is possible that our lack of strong evidence for an
inverse association between recreational physical activity and absolute or percent
mammographic density was due to the following bias and errors. Recall bias is
possible in ascertaining past history of physical activities. Women may have
overestimated the hours per week they participated in physical exercise in the past
compared to their current physical activity. Recall of recent activity and strenuous
physical activity is known to be more accurate than past activity and light or
moderate activity (Chasan-Taber and others 2002; I ARC 2002). However, we used
Bernstein and colleagues’ assessment methods for physical activity history
(Bernstein and others 1994; Carpenter and others 1999), which was highly rated by
Ainsworth and colleagues (Ainsworth and others 1998). It is also possible that there
could be some measurement error in mammographic density assessment even though
the method used has been previously validated (Ursin and others 1998) and found to
be strongly associated with breast cancer risk in this study (Ursin and others 2003).
Another possible limitation of this study is that percent or absolute mammographic
density was measured at one time point against different time points of physical
activity. Mammographic density may change throughout the course of a woman’s
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26
life and the effects of physical activity during those specific time periods may vary
specially during premenopausal and postmenopausal years.
Despite the overall lack of protective effect of recreational physical activity
on mammographic density, participation in physical activity provides protective
effects against diseases such as coronary heart disease, diabetes mellitus,
osteoporosis, colon and breast cancer (Powell and others 1989; Helmrich and others
1991; Stemfeld and others 1992; Fridenreich and others 2002; IARC 2002). The
importance of maintaining a consistent regimen of physical activity throughout a
woman’s life from adolescence through adulthood is important in maintaining a
healthy lifestyle and the possible prevention of diseases.
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27
REFERENCES
Ainsworth BE, Stemfeld B, Slattery ML, Daguise V, Zahm SH. 1998. Physical
activity and breast cancer: evaluation of physical activity assessment
methods. Cancer 83:3611-3620.
Ainsworth BE, Haskell WL, Leon AS, Jacobs DR Jr., Montoye HJ, Sallis IF,
Paffenbarger RS Jr. 2000. Compendium of Physical Activities: classification
of energy costs of human physical activities. Medicine and Science in Sports
and Exercise 32:498-504.
Anshel MH, Freedson P, Hamill J, Haywood K, Horvat M, Plowman SA. 1991.
Dictionary of the sports and exercise sciences. Champaign, IL: Human
Kinetics Publishers. 163p.
Bernstein L, Ross RK, Lobo R, Hanisch R, Krailo MD, Henderson BE. 1987. The
effects of moderate physical activity on menstrual cycle patterns in
adolescencedmplications for breast cancer prevention. British Journal of
Cancer 55:681-685.
Bernstein L, Henderson BE, Hanisch R, Sullivan-Halley J, Ross RK. 1994. Physical
exercise and reduced risk of breast cancer in young women. Journal of the
National Cancer Institute 86:1403-1408.
Bonen A, Long WY, MacIntyre KP, Neil R, McGrail JC, Belcastro AN. 1979.
Effects of exercise on the serum concentrations of FSH, LH, progesterone,
and estradiol. European Journal of Applied Physiology 42:15-23.
Bonen A, Belcastro AN, Ling WY, Simpson AA. 1981. Profiles of selected
hormones during menstrual cycles of teenage athletes. Journal of Applied
Physiology 50:545-551.
Boyd NF, Byng I, Jong R, Fishell E, Little L, Miller AB, Lockwood G, Tritchler D,
Yaffe M. 1995. Quantitative classification of mammographic densities and
breast cancer risks: Results from the Canadian National Breast Screening
Study. Journal of the National Cancer Institute 87:670-675.
Boyd NF, Lockwood GA, Byng JW, Little LE, Yaffe MJ, Tritchler DL. 1998. The
relationship of anthropometric measures to radiological features in
premenopausal women. British Journal of Cancer 78:1233-1238.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
28
Boyd NF, Lockwood GA, Martin LJ, Knight JA, Byng JW, Yaffe Ml, Tritchler DL.
1998. Mammographic densities and breast cancer risk. Breast Disease
10:113-126.
Byrne C, Schaixer C, Wolfe J, ParekhN, Salane M, Brinton LA. 1995,
Mammographic features and breast cancer risk: effect with time, age, and
menopause status. Journal of the National Institute of Cancer 87:1622-1629.
Carpenter CL, Ross RK, Paganini-Hill A, Bernstein L. 1999. Lifetime exercise
activity and breast cancer risk among post-menopausal women. British
Journal of Cancer 80(11):1852-1858.
Cauley JA, Gutai JP, Kuller LH, LeDonne D, Powell JG. 1989. The epidemiology of
serum sex hormones in postmenopausal women. Amercian Journal of
Epidemiology 129:1120-1131.
Chasan-Taber L, Erickson JB, Nasca PC, Chasan-Taber S, Freedson PS. 2002.
Validity and reproducibility of a physical activity questionnaire in women.
Medicine & Science in Sports & Exercise 34(6):987-992.
Ellison PT, Lager C. 1986. Moderate recreational running is associated with lowered
salivary progesterone profiles in women. American Journal of Obstetric
Gynecology 143:1000-1003.
Feicht CB, Johnson TS, Martin BJ, Sparkes KE, Wargner WW Jr. 1978. Secondary
amenorrhea in athletes. Lancet 2:1145-1146.
Friedenreich CM, Orenstein MR. 2002. Physical activity and cancer prevention:
Etiologic evidence and biological mechanisms. American Society for
Nutritional Sciences (supplement) 3456s-3464s.
Frisch RE, Wyshak G, Vincent L. 1980. Delayed menarche and amenorrhea in ballet
dancers. New England Journal of Medicine 303:17-19.
Frisch RE, Gotz-Welbergen AV, McArthur JW, Albright T, Witschi J, Bullen B,
Bimholz J, Reed RB, Hermann H. 1981. Delayed menarche and amenorrhea
of college athletes in relation to age at onset of training. JAMA 246:
1559-1563.
Gram IT, Funkhouser E, Tabar L. 1997. The Tabar classification of mammographic
parenchymal patterns. European Journal of Radiology 24:131-136.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
29
Gram IT, Funkhouser E, Tabar L, 1999. Moderate physical activity In relation to
mammographic patterns. Cancer Epidemiology, Biomarkers & Prevention
8(2): 117-122.
Helmrich SP, Ragland DR, Leung RW. 1991. Physical activity and reduced
occurrence of non-insulin-dependent diabetes mellitus. New England Journal
of Medicine 325:147-152.
Hoffman-Goetz L, Apter D, Demark-Wahnefried W, Goran MI, McTieman A,
Reichman ME. 1998. Possible mechanisms mediating an association between
physical activity and breast cancer. Cancer Supplement 83(3):621-628.
I ARC Handbooks of Cancer Prevention, Volume 6. Weight Control and Physical
Activity. Lyon, France: I ARC Press, 2002.
Jurkowski IE, Jones NL, Walker WC, Younglai EV, Sutton JR. 1981. Ovarian
hormonal responses to exercise. Medical Science Sports Exercise 13:
109-114.
Marchbanks P, McDonald JA, Wilson HG, Burnett NM, Daling JR, Bernstein L,
Malone KE, Strom BL, Norman SA, Weiss LK, Liff JM, Wingo PA,
Burkman RT, Folger SG, Berlin JA, Deapen DM, Ursin G, Coates RJ, Simon
MS, Press MF, and Spirtas R. 2002. The NICHD women’s contraceptive and
reproductive experiences study: methods and operational results. Annals of
Epidemiology 12:213-222.
Merzenich H, Boeing H, Wahrendorf J. 1993. Dietary fat and sports activity as
determinants for age at menarche. American Journal of Epidemiology
138:217-224.
Moisan J, Meyer F, Gingras S. 1991. Leisure physical activity and age at menarche.
Medicine Science in Sports Exercise 23:1170-1175.
Oza AM, Boyd NF. 1993. Mammographic parenchymal patterns: a marker of breast
cancer risk. Epidemiological Review 15:196-208.
Powell KE, Caspersen CJ, Koplan JP, Ford ES. 1989. Physical activity and chronic
diseases. American Journal of Clinical Nutrition 49:999-1006.
Russell JB, Mitchell D, Musey PI, Collins DC. 1984. The relationship of exercise to
anovulatory cycles in female athletes: hormonal and physical characteristics.
Obstetrics and Gynecology 63:452-456.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
30
Saflas AF, Szklo M. 1987. Mammographic parenchymal patterns and breast cancer
risk. Epidemiological Review 9:146-147.
Shepard RJ, Rhind S, Shek PN. 1995. The impact of exercise on the immune system:
NK cells, interleukins 1 and 2, and related responses. Exercise & Sport
Sciences Reviews 23:215-241.
Stemfeld B. 1992. Cancer and the protective effect of physical activity: the
epidemiological evidence. Medicine Science in Sports Medicine 24:
1195-1209.
Toniolo PG. 1997. Endogenous estrogens and breast cancer risk: the case for
prospective cohort studies. Environmental Health Perspectives 105(3):
587-592.
Ursin G, Astraham MA, Salane M, Parisky YR, Pearce JG, Daniels JR, Pike MC,
Spicer DV. 1998. The detection of changes in mammographic densities.
Cancer Epidemiology, Biomarkers & Prevention 7:43-47.
Ursin G, Ma H, Wu A, Bernstein L, Salane M, Parisky YR, Astrahan M, Siozon CC,
Pike MC. 2003. Mammographic density and breast cancer in three ethnic
groups.Cancer Epidemiology, Biomarkers & Prevention 12:332-338.
Vachon CM, Kuni CC, Anderson K, Anderson E, Sellers TA. 2000. Association of
mammographically defined percent breast density with epidemiologic risk
factors for breast cancer (United States). Cancer Causes and Control
11:653-662.
Wakat DK, Sweeney KA, Rogol AD. 1982. Reproductive system function in women
cross-country runners. Medicine Science in Sports and Exercise 14:
263-269.
Warren M. 1980. The effects of exercise on pubertal progression and reproductive
function in girls. Journal of Clinical Endocrinologic Metabolism 51:
1150-1157.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

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Creator Siozon, Conchitina Chato (author)

Core Title The association between recreational physical activity and mammographic density

Degree Master of Science

Degree Program Applied Biostatistics and Epidemiology

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag biology, biostatistics,health sciences, public health,OAI-PMH Harvest

Language English

Contributor Digitized by ProQuest (provenance)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-313316

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Legacy Identifier 1420400.pdf

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Document Type Thesis

Rights Siozon, Conchitina Chato

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

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