Skip to main content
  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

AACR logo

  • Register
  • Log in
  • My Cart
Advertisement

Main menu

  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

  • AACR Publications
    • Blood Cancer Discovery
    • Cancer Discovery
    • Cancer Epidemiology, Biomarkers & Prevention
    • Cancer Immunology Research
    • Cancer Prevention Research
    • Cancer Research
    • Clinical Cancer Research
    • Molecular Cancer Research
    • Molecular Cancer Therapeutics

User menu

  • Register
  • Log in
  • My Cart

Search

  • Advanced search
Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
  • Home
  • About
    • The Journal
    • AACR Journals
    • Subscriptions
    • Permissions and Reprints
    • Reviewing
  • Articles
    • OnlineFirst
    • Current Issue
    • Past Issues
    • CEBP Focus Archive
    • Meeting Abstracts
    • Progress and Priorities
    • Collections
      • COVID-19 & Cancer Resource Center
      • Disparities Collection
      • Editors' Picks
      • "Best of" Collection
  • For Authors
    • Information for Authors
    • Author Services
    • Best of: Author Profiles
    • Informing Public Health Policy
    • Submit
  • Alerts
    • Table of Contents
    • Editors' Picks
    • OnlineFirst
    • Citation
    • Author/Keyword
    • RSS Feeds
    • My Alert Summary & Preferences
  • News
    • Cancer Discovery News
  • COVID-19
  • Webinars
  • Search More

    Advanced Search

Research Articles

Recreational Physical Activity and Mammographic Breast Density Characteristics

Katherine W. Reeves, Gretchen L. Gierach and Francesmary Modugno
Katherine W. Reeves
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Gretchen L. Gierach
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Francesmary Modugno
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1158/1055-9965.EPI-06-0732 Published May 2007
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Increased mammographic breast density is considered an intermediate marker of breast cancer risk. Physical activity is believed to reduce breast cancer risk; however, its effect on breast density is not well understood. We studied the association between recreational physical activity and mammographic characteristics of the breast among a population of premenopausal and postmenopausal women enrolled as controls (n = 728) in a case-control study of mammographic breast density and breast cancer. Women were enrolled shortly after obtaining their regular screening mammograms, and participants reported their current and lifetime recreational physical activity history using a self-administered, reliable questionnaire at study enrollment. Linear regression was used to determine associations between physical activity variables and the dense breast area, non-dense area, total breast area, and percent density. Age-adjusted analyses revealed significant inverse associations between physical activity variables and the non-dense area and total area and positive associations with percent breast density. These associations were attenuated and nonsignificant after adjustment for body mass index (BMI). Adjustment for additional factors did not substantially change the results. Physical activity was not associated with the dense breast area before or after adjustment for BMI. Self-reported recreational physical activity was not significantly associated with the mammographic characteristics of the breast after adjustment for BMI in this population. These results suggest that the mechanism by which physical activity reduces breast cancer risk may not involve breast density. (Cancer Epidemiol Biomarkers Prev 2007;16(5):934–42)

  • Physical activity
  • breast cancer
  • mammography
  • body mass index
  • surrogate marker

Introduction

Breast cancer accounts for nearly one third of all cancers diagnosed among women in the United States and is the second leading cause of cancer mortality in this population (1). Although mortality from breast cancer decreased ∼2.3% each year in recent years, the incidence of breast cancer increased ∼0.3% each year during the same time period, likely due to broader use of mammography and detection of cancers that would not be found otherwise (2). To reduce the incidence of breast cancer, an improved understanding of its causal factors and the ability to intervene on such factors to prevent disease are needed.

The composition of the breast varies by individual. Fat tissue is radiolucent and appears dark on a mammogram, whereas epithelial and connective tissues are radiodense and appear bright. Breast density is determined by how much epithelial and connective tissue are present relative to fat (3-6). The density of the breast is qualitatively categorized into parenchymal patterns as described by Wolfe (7) or quantitatively reported as the percentage of the breast occupied by dense tissue. Mammographic breast density is positively associated with breast cancer risk using both qualitative (7-14) and quantitative (9, 14, 15) measurements. Mammographic breast density changes in response to factors such as age (16, 17) and use (18, 19) or cessation (20) of hormone therapy. Because of its strong association with breast cancer risk and its ability to be modified, much attention has focused on mammographic breast density as an intermediate marker for breast cancer.

Few studies have investigated the relationship between physical activity and mammographic breast density; yet, physical activity is believed to be an important and modifiable risk factor for breast cancer. The IARC determined that ∼10% of all breast cancers are related to lack of adequate physical activity (21). The Women's Health Initiative (WHI) Observational Study also reported that increased levels of recreational physical activity were related to decreased risk of breast cancer, with an 18% reduction in breast cancer risk from brisk walking for 1.25 to 2.5 h/wk (22). Eight reports to date have described the relationship between physical activity and mammographic breast density: one prospective (19) and four cross-sectional studies (23-26) reported no statistically significant association; one cross-sectional study of Hispanic women found a positive association with physical inactivity (27); and cross-sectional analyses conducted in a study of breast cancer survivors reported an inverse association between pre-diagnosis breast density and physical activity among obese postmenopausal women only (28), with a similar association observed 2 to 3 years after diagnosis (29). The methods of physical activity assessment as well as the characteristics of the study populations have varied widely among these studies, however.

Further research is necessary to elucidate the effect of physical activity on breast density and to determine if this relationship varies by breast cancer risk, body mass index (BMI), and/or other personal characteristics. Using the physical activity measure employed by the WHI (22), we evaluated associations between recreational physical activity and mammographic breast density among a group of premenopausal and postmenopausal women receiving screening or diagnostic mammograms.

Materials and Methods

Study Population

This study is a cross-sectional analysis of participants included as control women from a case-control study of hormonal determinants of mammographic breast density, the Mammograms and Masses Study (MAMS). Recruitment for MAMS took place from 2001 to 2005. Women were eligible for MAMS if they were age ≥18 and either (a) were receiving a breast biopsy or an initial surgical consultation after a diagnosis of breast cancer at Magee-Womens Hospital, Pittsburgh, PA or (b) were receiving a routine screening mammogram at a Magee-Womens Hospital mammography screening clinic throughout the greater Pittsburgh region. Women were excluded from MAMS if they met one or more of the following exclusion criteria: (a) reported a prior history of cancer other than nonmelanoma skin cancer, (b) drank more than 5 alcoholic beverages per day, or (c) weighed either <110 or >300 lbs.

Women recruited from the biopsy clinic who were determined to have a benign breast lesion were eligible as “benign” controls. Of the 856 women approached at the time of biopsy, 573 (67%) enrolled in the study and 313 (55%) of the enrolled women were counted as “benign” controls. A second control group (“well” controls) was selected from women receiving routine screening mammograms. Well controls were recruited through presentations given by research staff in the mammogram clinic waiting room or by flyers describing MAMS included with the mammogram reports sent to women with a negative mammogram. Of 100 women approached through the in-clinic presentations, 85 (85%) were enrolled in the study as “well” controls. A total of 21,606 flyers were sent, and 1,025 responses were received (5%). Of the respondents, 857 (84%) were eligible, and 471 (55%) enrolled in the study as “well” controls. This study was approved by the Institutional Review Board at the University of Pittsburgh. All participants provided written informed consent. The final study population consisted of 1,133 women, including 264 cases, 313 benign controls, and 556 well controls.

Only women who were enrolled as controls (either benign or well) were eligible for inclusion in the present analyses. We further excluded 114 women without mammogram data (66 benign and 48 well) and 27 women without physical activity data (23 benign and 4 well). Thus, 728 women were included in these analyses (224 benign and 504 well). Women who were excluded from the analysis were of similar age, ethnicity, and BMI as those included.

Data Collection

At enrollment, participants completed a self-administered questionnaire that collected extensive data including demographic factors and medical, medication, menstrual, hormone therapy use, reproductive, oral contraceptive use, family cancer, weight, recreational physical activity, smoking, and alcohol use histories. Height and weight were measured by a study nurse using a stadiometer and a standard balance beam scale while participants were wearing light clothing and no shoes. Height and weight were used to calculate BMI (weight in kilograms divided by height in meters squared). Age at menopause was calculated according to methods outlined by the WHI (30).

Recreational Physical Activity Assessment

Participants were asked about their usual levels of recreational physical activity (henceforth referred to as “physical activity”) at the time of questionnaire completion and at specific previous ages using the physical activity measure employed and tested in the WHI (22, 31). Women were first asked about the frequency, intensity, and duration of walking outside the home. The frequency categories for walking were rarely or never, one to three times each month, two to three times each week, four to six times each week, and seven times or more each week. Women were also asked to indicate the speed at which they normally walked: casual strolling or walking (<2 miles/h), average or normal (2-3 miles/h), fairly fast (3-4 miles/h), or very fast (>4 miles/h). Participants were then asked about the frequency and duration of exercise other than walking: mild (e.g., slow dancing or bowling), moderate (e.g., biking outdoors or easy swimming), or strenuous (e.g., aerobics or jogging). Frequency categories for mild, moderate, and strenuous exercise were none, 1 day/wk, 2 days/wk, 3 days/wk, 4 days/wk, and ≥5 days/wk. Duration categories for both walking and the three levels of exercise were <20 min, 20 to 39 min, 40 to 59 min, and ≥1 h. Finally, participants reported if they usually did mild, moderate, or strenuous exercise at least thrice a week at ages 18, 35, and 50.

Hours exercised per week and metabolic equivalent (MET) hours per week were calculated following the algorithms used in the WHI (22). Midpoint values were calculated for each category of frequency and duration, and these values were multiplied to calculate hours exercised per week. MET values were assigned to each level of activity: mild exercise, 3 MET; moderate exercise, 4 MET; and strenuous exercise, 7 MET. Average or normal speed walking was assigned a value of 3 MET; fast walking was assigned a value of 4 MET; and very fast walking was assigned a value of 4.5 MET. These MET values were multiplied by the values of hours exercised per week for each type of activity to determine MET-h/wk. A cumulative measure of current physical activity was calculated by summing the values for MET-h/wk over all four levels of physical activity (walking, mild, moderate, and strenuous exercise).

Mammographic Density Measurement

Copies of original screening mammograms were obtained with the permission of the participants and sent to Martine Salane, an expert reader (32-34), to determine mammographic density. Dense breast area was measured by outlining areas of mammographic density on the craniocaudal view, excluding biopsy scars, Cooper's ligaments, and breast masses. Total breast area and outlined dense regions were computed using a compensating polar planimeter (LASICO). Percentage of breast density was calculated by dividing the area of the outlined dense region by the total area of the breast. A subjective measure of film quality was also reported. To determine reproducibility of the readings, a random sample of 28 mammograms was reevaluated at a later time (8 from the lowest tertile of percent breast density and 10 each from the remaining two tertiles of percent breast density). The intraclass correlation coefficient for intra-observer agreement was ρ = 0.86 for the continuous measurement of dense area, ρ = 0.99 for total area, and ρ = 0.89 for percent breast density. Our intraclass correlation coefficient for percent density is consistent with Salane's reproducibility in the Breast Cancer Detection Demonstration Project (intraclass correlation coefficient ρ = 0.915 for 193 sets of films; ref. 34).

Statistical Analysis

Comparisons between benign and well controls were done using two-sample t tests for continuous measures and the χ2 test for discrete measures. The cumulative MET values were analyzed as continuous variables, and other categorical physical activity variables were grouped for analysis as in the WHI (22). Mild, moderate, and strenuous activities at ages 18, 35, and 50 were captured as yes/no variables. ANOVA was used to compare the mean dense area, non-dense area, total area, and percent breast density across the levels of the physical activity variables. For the ANOVA analyses only, the continuous MET values were categorized as in the WHI: no activity, <5, 5.1 to 10, 10.1 to 20, 20.1 to 40, and ≥40 MET-h/wk (22).

Separate multivariable linear regressions were done using dense area, non-dense area, total breast area, and percent breast density as dependent variables and the physical activity variables as the independent variable of interest. Regressions included only one physical activity variable at a time. The following variables were evaluated for inclusion as potential confounders in each regression as prior studies have shown associations with breast density and/or breast cancer: age (continuous), BMI (<25, 25 to <30, ≥30 kg/m2), race (White, other), smoking status (never, former, current), alcohol intake in year before enrollment (no regular consumption, <12 g/d, ≥12 g/d), current alcohol drinker (no, yes), hormone therapy status (never, former, current), age at menarche (<12, 12, 13, ≥14), menopausal status (premenopausal, postmenopausal), age at menopause (premenopausal, <40, 40-44, 45-49, 50-54, ≥55), number of live births (none, 1, 2, 3, ≥4), age at first pregnancy lasting more than 6 months (no live births/never pregnant, <20, 20-24, 25-29, ≥30), history of breast-feeding (not applicable/no, yes), family history of breast cancer (no, yes), previous breast biopsy (no, yes), number of previous breast biopsies (none, 1, ≥2), quality of the mammographic film (excellent, good, fair, poor), and interval between questionnaire date and mammogram date (continuous). Categorizations of the previous variables were based on common cut points (e.g., BMI) or from the original response categories with collapsing of categories to prevent small cell counts (e.g., age at menarche). These covariates were first evaluated for inclusion in the models using stepwise backward regression with multiple partial F tests; variables significant at the 0.10 level were included in the final adjusted model. All analyses were stratified by control type. The physical activity variables were added to the model after the significant confounders had been identified. Dummy variables were created for categorical variables as appropriate. Mammographic density measures and MET-h/wk were normally distributed, and analyses were conducted with these variables in the natural scale. All tests done were two sided, with P ≤ 0.05 considered statistically significant. All analyses were done using SAS version 9.1.

Results

Table 1 describes the demographic and breast cancer risk factor characteristics of the study population. Most participants in this analysis were well controls (69.2%), and benign and well controls differed significantly on most demographic characteristics. The average age varied by control type, with benign controls having a mean age of 54.2 (SD, 9.1; range, 40-84) and well controls having a mean age of 58.7 (SD, 9.9; range, 36-85; P < 0.0001). The vast majority (99.6%) of participants was age 40 or older and thus in the age group for which annual mammograms are recommended. Three well controls were below the typical screening age: two were age 39 and one was age 36 at the time of enrollment. Benign controls were more likely to be current smokers (14.7% versus 6.6%, P = 0.002) and current users of hormone therapy (33.9% versus 11.7%, P < 0.0001). Menopausal status also varied by control type, with 33.9% of benign controls and 20.6% of well controls being premenopausal (P = 0.0001). The vast majority (94%) of the study population was White, and this did not differ by control type.

View this table:
  • View inline
  • View popup
Table 1.

Descriptive characteristics of MAMS control study population, Pittsburgh, PA 2001-2005 (n = 728)

The reported current and past levels of recreational physical activity are displayed in Table 2 . History of exercise did not vary by control type, except for history of mild, moderate, or strenuous exercise at age 50. Benign controls were less likely to report engaging in physical activity at this age (this comparison included only women who were age 50 or older at the time of the survey). The reported cumulative MET hours of exercise per week was an average of 13.0 (SD, 15.5; range, 0.0-110.8) among benign controls and 15.7 (SD, 16.7; range, 0.0-110.3) for well controls (P = 0.04). Approximately 16% of benign controls and 11% of well controls reported engaging in no exercise, and about 20% of benign controls and 30% of well controls reported >20 cumulative MET-h/wk. The distributions of current exercise in the population were somewhat positively skewed, with 30.8% of benign controls and 38.3% of well controls having greater than the overall mean MET-h/wk of walking (4.76; SD, 6.40) and only 18.3% of benign controls and 26.8% of well controls having greater than the overall mean MET-h/wk of strenuous exercise (3.99; SD, 8.49; data not shown).

View this table:
  • View inline
  • View popup
Table 2.

Summary of self-reported recreational physical activity in the MAMS control study population

On average, a woman's mammogram was taken within 47 and 39 days of questionnaire completion for benign and well controls, respectively (Table 3 ). The age-adjusted average percent breast density in the population was 37.0% (SE, 1.3%) for benign controls and 32.4% (SE, 0.9%) for well controls (P = 0.004). Overall, very few of the films were considered to be of poor quality (8.2%), and the quality of films did not vary by control type.

View this table:
  • View inline
  • View popup
Table 3.

Summary of mammographic breast density characteristics in the MAMS control study population, age adjusted

For both benign and well controls, age-adjusted associations between current physical activity and breast density characteristics were apparent for the non-dense area, total breast area, and percent density but were generally not significant for the outcome of dense area (Tables 4 and 5 ). Selected results of the linear regressions are displayed in Tables 6 and 7 . Similar results were observed among benign and well controls. Although a modest positive association was found between hours per week of mild exercise and dense area among well controls (P = 0.04), no significant associations were observed between cumulative MET hours of exercise per week or hours of moderate and strenuous activity per week and the dense breast area in models adjusted for age only, age and BMI, or in the fully adjusted models. Similarly, no associations were observed between the other physical activity variables investigated and the size of the dense breast area (data not shown). In both benign and well controls, significant inverse associations were observed between many current and lifetime physical activity variables and the non-dense area and total breast area and positive associations with percent density, but only when adjusted for age. These associations were all attenuated after further adjustment for BMI. Overall, additional adjustment for other covariates did not substantially change the results. However, a statistically significant association was observed between hours of mild activity per week and percent density among well controls, with a 1.33 unit increase in percent density for each additional hour of mild exercise (P = 0.005). In general, similar results were observed for physical activity at ages 18, 35, and 50 and for MET hours of mild, moderate, strenuous, and walking exercise (data not shown).

View this table:
  • View inline
  • View popup
Table 4.

Bivariate associations between recreational physical activity variables and breast density variables, benign controls (n = 224)

View this table:
  • View inline
  • View popup
Table 5.

Bivariate associations between recreational physical activity variables and breast density variables, well controls (n = 504)

View this table:
  • View inline
  • View popup
Table 6.

Multivariable associations between recreational physical activity variables and breast density variables, benign controls (n = 224)

View this table:
  • View inline
  • View popup
Table 7.

Multivariable associations between recreational physical activity variables and breast density variables, well controls (n = 504)

Similar results were obtained when restricting analyses to women whose mammogram was taken within 6 months of their questionnaire date (97.3% of the study population) and when stratifying by menopausal status (data not shown).

Discussion

Although measures of current and past recreational physical activity were significantly associated with non-dense breast area, total breast area, and percent breast density in age-adjusted analyses, adjustment for BMI attenuated these results. Significant positive associations between hours of mild exercise per week and both dense area and percent density were observed among well controls in multivariable models; however, given the number of statistical comparisons, lack of other significant associations, and the inconsistency of this finding with all prior studies of physical activity and mammographic density (19, 23-29), these findings are likely due to chance. Physical activity was not significantly associated with dense breast area before or after adjustment for BMI.

Overall, the present findings are consistent with those of previous studies of recreational physical activity and breast density, most of which have reported no statistically significant association (19, 23-26). Also similar to our findings, Siozon et al. showed that associations between physical activity and breast density were no longer significant after adjusting for BMI (26). Conversely, two studies conducted in distinct populations have reported results consistent with an inverse association between physical activity and breast density (27-29). In a multi-ethnic study of 474 U.S. women, Irwin et al. reported that higher levels of sports/recreational physical activity were associated with lower dense breast area and percent density among obese postmenopausal women [mean (SD) MET-h/wk = 7.8 (12.6)] yet were associated with an increase in percent density among nonobese premenopausal women [mean (SD) MET-h/wk = 19.4 (21.8); ref. 28]. Although activity levels in these two subgroups are similar to the mean MET-h/wk observed in the comparable subgroups of women in MAMS, we did not observe significant associations with dense breast area or percent density when stratifying analyses by menopausal status. The Irwin et al. results may not be generalizable to cancer-free women, however, as the participants were women currently diagnosed with breast cancer, recalling their physical activity in the year before diagnosis, and the pre-diagnostic mammograms included in the study may have contained subclinical disease. Lastly, among 294 Hispanic women in Chicago, Lopez et al. observed higher percent breast density for women reporting at least 3.5 h/d of physical inactivity, defined as the average number of hours per day spent watching television, reading, knitting, or using a computer (27). These results may not be generalizable to non-Hispanic women; Mexican-American women report more physical inactivity than non-Hispanic Whites (35). However, we are unable to compare these results with those of the present study as we did not obtain a measure of physical inactivity.

Apart from lack of a true association between physical activity and mammographic density, an alternative explanation for the null findings is that physical activity may actually reduce absolute breast density, but studies thus far have been unable to detect such an association (28). Overall, levels of physical activity are fairly low in many populations. In our study, 13% of the total population of women reported no current physical activity, and only 24% reported a level of weekly strenuous activity that was greater than the mean. Similarly, of the non-cases in the WHI Observational Study, 13% reported no current physical activity, and 35% reported no current moderate or strenuous physical activity (22). National data show that 39.5% of adult women report no leisure-time physical activity, and only 30.6% report regular leisure-time activity (36). Indeed, the levels of physical activity needed to observe a significant change in breast density may be higher than are typical of most U.S. women.

The observed lack of an association between physical activity and breast density is surprising in light of the convincing evidence for a decreased risk of breast cancer with increasing levels of physical activity (21). Indeed, a previous analysis of data from the WHI, which employed the same questions and algorithms for assessing recreational physical activity as in the present study, reported that risk of breast cancer was reduced by 18% by walking for 1.25 to 2.5 h/wk (22). The association between physical activity and breast cancer, unlike what we report for the relationship between physical activity and breast density, remains significant when adjusted for measures of anthropometry such as BMI. Physical activity, therefore, does seem to have an independent effect that leads to a decrease in risk of breast cancer.

Thus, our results suggest that a mechanism other than breast density explains the association between physical activity and breast cancer risk. Our findings and one previous study (26) both found that associations between physical activity and breast density were attenuated after adjustment for BMI, suggesting that the effects of physical activity on the characteristics of the breast may be mediated through changes in weight. Specifically, we observed significant age-adjusted associations between physical activity and the sizes of the total breast area and non-dense area; however, these associations were no longer significant when adjusted for BMI. In contrast, physical activity was not associated with the size of the dense area both before and after adjustment for BMI. There was a suggestion that mild physical activity may be associated with dense area and percent density among well controls, but this finding is likely due to chance for the previously stated reasons. Together, these data suggest that whereas physical activity may not affect dense breast tissue (and hence not reduce mammographic breast density), physical activity may exert its protective effect on breast cancer through affecting the fatty tissue of the breast. Indeed, physical activity has been shown to result in reduced metabolically active fat mass (37), decreased levels of insulin and glucose (37), increased levels of insulin-like growth factor binding protein-3 (37), decreased levels of sex hormones such as estradiol (37), and decreased markers of systemic inflammation (38-41), all of which may be associated with reduced risk of breast cancer (42-45). Despite intriguing evidence for each of these pathways, however, the exact mechanism by which physical activity reduces the risk of breast cancer, but seemingly not mammographic density, remains elusive.

There are a number of limitations of the present study that must be considered. First, a significant limitation of this and other previous studies is the cross-sectional nature of the analysis. A second limitation results from the physical activity measure used, which included only recreational physical activity. This method neglected to capture occupational and household activities, which may be related to breast cancer and are likely to be important sources of physical activity for women (23, 46), potentially introducing nondifferential misclassification bias and biasing results toward the null. Although we used a previously tested, reliable questionnaire for measuring physical activity, it should be noted that the reliability of these recreational physical activity questions was tested in a somewhat different population of women, a random sample of postmenopausal women participating in the WHI. In the WHI, the test-retest reliability (weighted κ) for the physical activity variables ranged from 0.53 to 0.72, and the intraclass correlation coefficient for total physical activity expenditure in MET was 0.77 (22, 31). Hence, whereas this measurement tool was reasonably reproducible in the WHI, the reliability of this instrument may not extend to the premenopausal and postmenopausal women participating in MAMS. Again, inadequate classification of recreational physical activity could in part explain the observed null results.

This study is strengthened by its large sample size and, to our knowledge, is the largest study to date to have characterized the relationships between physical activity and the dense, non-dense, and total areas of the breast in addition to percent breast density. As percent density is highly related to body weight, it is important to consider other mammographic characteristics that are less confounded by body weight, such as the dense breast area, in studies examining mammographic density (47). In addition, we examined these relationships in cancer-free women who received screening mammograms or benign breast biopsies, a clinically meaningful subgroup of the population at risk for breast cancer in whom breast density has not previously been well studied with respect to physical activity. Nevertheless, because the MAMS population consists of this unique, nonrandom sample of cancer-free women, participants may not be entirely representative of the general population from which they were sampled. On average, MAMS women were more likely to be White and were better educated than same-aged women residing in Allegheny County, PA in 2005: 94% versus 87%3 were White (48), and 77% versus 61% reported completing post-secondary education, respectively (49). In addition, MAMS women seem to be healthier than the population from which they were recruited. MAMS women were less likely to be current smokers: 9% versus 16% (49). In addition, MAMS women were more likely to participate in physical activity (87% reporting any recreational physical activity in MAMS versus 77% of same-aged women reporting any leisure-time physical activity in 2005 in Allegheny County; ref. 49) and reported a greater prevalence of moderate or vigorous physical activity (54% versus 49%; ref. 49). When comparing MAMS women with 2005 Allegheny County residents of the same age who also reported having a mammogram within the past 12 months, these differences were still evident, likely reflecting a “healthy volunteer” effect. Hence, generalizability of results to other populations may be limited.

This study adds to the existing body of literature showing no association between recreational physical activity and mammographic breast density among cancer-free women. As the strong relationship between breast density and BMI may obscure this association, future research might explore the influence of physical activity on mammographic density over time, using serial mammograms. Such longitudinal studies could help to explain how changes in levels of physical activity relate to changes in the mammographic characteristics of the breast and may be more sensitive for detecting an association, if one does exist.

Acknowledgments

We thank the significant contributions of Glenn Allen, M.P.H.; Alana Hudson, B.S.; Martine Salane; Jennifer Simpson, Ph.D., M.S.N.; Jules Sumkin, D.O.; and Victor Vogel, M.D., M.H.S. to MAMS.

Footnotes

  • ↵3 These data were provided by the Bureau of Health Statistics and Research, Pennsylvania Department of Health. The Department specifically disclaims responsibility for any analyses, interpretations, or conclusions.

  • Grant support: NIH grants P20 CA103730, R25-CA57703, K07-CA80668, and R21-CA95113; Department of Defense grant DAMD17-02-1-0553; and PA Department of Health grant P2777693. Additional support was provided by funds received from the NIH/National Center for Research Resources/General Clinical Research Center grant MO1-RR000056.

  • The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

    • Accepted February 28, 2007.
    • Received August 29, 2006.
    • Revision received February 12, 2007.

References

  1. ↵
    American Cancer Society. Cancer facts and figures 2005. Atlanta: American Cancer Society, Inc.; 2005.
  2. ↵
    American Cancer Society. Breast cancer facts and figures 2005-2006. Atlanta: American Cancer Society, Inc.; 2005.
  3. ↵
    Bright RA, Morrison AS, Brisson J, et al. Relationship between mammographic and histologic features of breast tissue in women with benign biopsies. Cancer 1988;61:266–71.
    OpenUrlCrossRefPubMed
  4. Fisher ER, Palekar A, Kim WS, Redmond C. The histopathology of mammographic patterns. Am J Clin Pathol 1978;69:421–6.
    OpenUrlPubMed
  5. Page DL, Winfield AC. The dense mammogram. AJR Am J Roentgenol 1986;147:487–9.
    OpenUrlPubMed
  6. ↵
    Wellings SR, Wolfe JN. Correlative studies of the histological and radiographic appearance of the breast parenchyma. Radiology 1978;129:299–306.
    OpenUrlCrossRefPubMed
  7. ↵
    Wolfe JN. Risk for breast cancer development determined by mammographic parenchymal pattern. Cancer 1976;37:2486–92.
    OpenUrlCrossRefPubMed
  8. Salminen TM, Saarenmaa IE, Heikkila MM, Hakama M. Risk of breast cancer and changes in mammographic parenchymal patterns over time. Acta Oncol 1998;37:547–51.
    OpenUrlCrossRefPubMed
  9. ↵
    Saftlas AF, Hoover RN, Brinton LA, et al. Mammographic densities and risk of breast cancer. Cancer 1991;67:2833–8.
    OpenUrlCrossRefPubMed
  10. Gravelle IH, Bulstrode JC, Bulbrook RD, et al. A prospective study of mammographic parenchymal patterns and risk of breast cancer. Br J Radiol 1986;59:487–91.
    OpenUrlAbstract/FREE Full Text
  11. Carlile T, Kopecky KJ, Thompson DJ, et al. Breast cancer prediction and the Wolfe classification of mammograms. JAMA 1985;254:1050–3.
    OpenUrlCrossRefPubMed
  12. Threatt B, Norbeck JM, Ullman NS, Kummer R, Roselle P. Association between mammographic parenchymal pattern classification and incidence of breast cancer. Cancer 1980;45:2550–6.
    OpenUrlCrossRefPubMed
  13. Kato I, Beinart C, Bleich A, et al. A nested case-control study of mammographic patterns, breast volume, and breast cancer. Cancer Causes Control 1995;6:431–8.
    OpenUrlCrossRefPubMed
  14. ↵
    Byrne C, Schairer C, Wolfe J, et al. Mammographic features and breast cancer risk: effects with time, age, and menopause status. J Natl Cancer Inst 1995;87:1622–9.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    Boyd NF, Byng JW, Jong RA, et al. Quantitative classification of mammographic densities and breast cancer risk: results from the Canadian National Breast Screening Study. J Natl Cancer Inst 1995;87:670–5.
    OpenUrlAbstract/FREE Full Text
  16. ↵
    Brisson J, Sadowsky NL, Twaddle JA, et al. The relation of mammographic features of the breast to breast cancer risk factors. Am J Epidemiol 1982;115:438–43.
    OpenUrlAbstract/FREE Full Text
  17. ↵
    Grove JS, Goodman MJ, Gilbert FI, Jr., Mi MP. Factors associated with mammographic pattern. Br J Radiol 1985;58:21–5.
    OpenUrlAbstract/FREE Full Text
  18. ↵
    Greendale GA, Reboussin BA, Slone S, et al. Postmenopausal hormone therapy and change in mammographic density. J Natl Cancer Inst 2003;95:30–7.
    OpenUrlAbstract/FREE Full Text
  19. ↵
    McTiernan A, Martin CF, Peck JD, et al. Estrogen-plus-progestin use and mammographic density in postmenopausal women: Women's Health Initiative randomized trial. J Natl Cancer Inst 2005;97:1366–76.
    OpenUrlAbstract/FREE Full Text
  20. ↵
    Harvey JA, Pinkerton JV, Herman CR. Short-term cessation of hormone replacement therapy and improvement of mammographic specificity. J Natl Cancer Inst 1997;89:1623–5.
    OpenUrlFREE Full Text
  21. ↵
    Bianchini F, Kaaks R, Vainio H. Weight control and physical activity in cancer prevention. Obes Rev 2002;3:5–8.
    OpenUrlPubMed
  22. ↵
    McTiernan A, Kooperberg C, White E, et al. Recreational physical activity and the risk of breast cancer in postmenopausal women: the Women's Health Initiative Cohort Study. JAMA 2003;290:1331–6.
    OpenUrlCrossRefPubMed
  23. ↵
    Suijkerbuijk KP, Van Duijnhoven FJ, Van Gils CH, et al. Physical activity in relation to mammographic density in the Dutch prospect-European prospective investigation into cancer and nutrition cohort. Cancer Epidemiol Biomarkers Prev 2006;15:456–60.
    OpenUrlAbstract/FREE Full Text
  24. Gram IT, Funkhouser E, Tabar L. Moderate physical activity in relation to mammographic patterns. Cancer Epidemiol Biomarkers Prev 1999;8:117–22.
    OpenUrlAbstract/FREE Full Text
  25. Vachon CM, Kuni CC, Anderson K, Anderson VE, Sellers TA. Association of mammographically defined percent breast density with epidemiologic risk factors for breast cancer. Cancer Causes Control 2000;11:653–62.
    OpenUrlCrossRefPubMed
  26. ↵
    Siozon CC, Ma H, Hilsen M, Bernstein L, Ursin G. The association between recreational physical activity and mammographic density. Int J Cancer 2006;119:1695–701.
    OpenUrlCrossRefPubMed
  27. ↵
    Lopez P, Van Horn L, Colangelo LA, et al. Physical inactivity and percent breast density among Hispanic women. Int J Cancer 2003;107:1012–6.
    OpenUrlCrossRefPubMed
  28. ↵
    Irwin ML, Aiello EJ, McTiernan A, et al. Pre-diagnosis physical activity and mammographic density in breast cancer survivors. Breast Cancer Res Treat 2006;95:171–8.
    OpenUrlCrossRefPubMed
  29. ↵
    Irwin ML, Aiello EJ, McTiernan A, et al. Physical activity, body mass index, and mammographic density in postmenopausal breast cancer survivors. J Clin Oncol 2007;25:1061–6.
    OpenUrlAbstract/FREE Full Text
  30. ↵
    Chen Z, Maricic M, Bassford TL, et al. Fracture risk among breast cancer survivors: results from the Women's Health Initiative Observational Study. Arch Intern Med 2005;165:552–8.
    OpenUrlCrossRefPubMed
  31. ↵
    Langer R, White E, Lewis C, et al. The Women's Health Initiative Observational Study: baseline characteristics of participants and reliability of baseline measures. Ann Epidemiol 2003;13:S107–21.
    OpenUrlCrossRefPubMed
  32. ↵
    Haiman CA, Bernstein L, Berg D, et al. Genetic determinants of mammographic density. Breast Cancer Res 2002;4:R5.
    OpenUrlCrossRefPubMed
  33. Wolfe JN, Saftlas AF, Salane M. Mammographic parenchymal patterns and quantitative evaluation of mammographic densities: a case-control study. AJR Am J Roentgenol 1987;148:1087–92.
    OpenUrlCrossRefPubMed
  34. ↵
    Benichou J, Byrne C, Capece LA, et al. Secular stability and reliability of measurements of the percentage of dense tissue on mammograms. Cancer Detect Prev 2003;27:266–74.
    OpenUrlCrossRefPubMed
  35. ↵
    Crespo CJ, Smit E, Andersen RE, Carter-Pokras O, Ainsworth BE. Race/ethnicity, social class and their relation to physical inactivity during leisure time: results from the Third National Health and Nutrition Examination Survey, 1988–1994. Am J Prev Med 2000;18:46–53.
    OpenUrlCrossRefPubMed
  36. ↵
    National Center for Health Statistics. Health, United States, 2005, with Chartbook on Trends in the Health of Americans. Hyattsville (MD): National Center for Health Statistics; 2005.
  37. ↵
    McTiernan A, Ulrich C, Slate S, Potter J. Physical activity and cancer etiology: associations and mechanisms. Cancer Causes Control 1998;9:487–509.
    OpenUrlCrossRefPubMed
  38. ↵
    Abramson JL, Vaccarino V. Relationship between physical activity and inflammation among apparently healthy middle-aged and older US adults. Arch Intern Med 2002;162:1286–92.
    OpenUrlCrossRefPubMed
  39. LaMonte MJ, Durstine JL, Yanowitz FG, et al. Cardiorespiratory fitness and C-reactive protein among a tri-ethnic sample of women. Circulation 2002;106:403–6.
    OpenUrlAbstract/FREE Full Text
  40. Ford ES. Does exercise reduce inflammation? Physical activity and C-reactive protein among U.S. adults. Epidemiology 2002;13:561–8.
    OpenUrlCrossRefPubMed
  41. ↵
    Bermudez EA, Rifai N, Buring J, Manson JE, Ridker PM. Interrelationships among circulating interleukin-6, C-reactive protein, and traditional cardiovascular risk factors in women. Arterioscler Thromb Vasc Biol 2002;22:1668–73.
    OpenUrlAbstract/FREE Full Text
  42. ↵
    Coussens LM, Werb Z. Inflammation and cancer. Nature 2002;420:860–7.
    OpenUrlCrossRefPubMed
  43. O'Byrne KJ, Dalgleish AG. Chronic immune activation and inflammation as the cause of malignancy. Br J Cancer 2001;85:473–83.
    OpenUrlCrossRefPubMed
  44. Harris RE, Chlebowski RT, Jackson RD, et al. Breast cancer and nonsteroidal anti-inflammatory drugs: prospective results from the Women's Health Initiative. Cancer Res 2003;63:6096–101.
    OpenUrlAbstract/FREE Full Text
  45. ↵
    Renehan AG, Egger M, Minder C, et al. IGF-I, IGF binding protein-3 and breast cancer risk: comparison of 3 meta-analyses. Int J Cancer 2005;115:1006–7.
    OpenUrlCrossRefPubMed
  46. ↵
    Gammon MD, John EM, Britton JA. Recreational and occupational physical activities and risk of breast cancer. J Natl Cancer Inst 1998;90:100–17.
    OpenUrlFREE Full Text
  47. ↵
    Haars G, van Noord PA, van Gils CH, Grobbee DE, Peeters PH. Measurements of breast density: no ratio for a ratio. Cancer Epidemiol Biomarkers Prev 2005;14:2634–40.
    OpenUrlAbstract/FREE Full Text
  48. ↵
    Pennsylvania State Data Center at Penn State Harrisburg, 2005.
  49. ↵
    Centers for Disease Control and Prevention (CDC). Behavioral risk factor surveillance system survey data: selected metropolitan/micropolitan area risk trends. Atlanta (GA): U.S. Department of Health and Human Services, Centers for Disease Control and Prevention; 2005.
View Abstract
PreviousNext
Back to top
Cancer Epidemiology Biomarkers & Prevention: 16 (5)
May 2007
Volume 16, Issue 5
  • Table of Contents
  • Table of Contents (PDF)

Sign up for alerts

View this article with LENS

Open full page PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for sharing this Cancer Epidemiology, Biomarkers & Prevention article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Recreational Physical Activity and Mammographic Breast Density Characteristics
(Your Name) has forwarded a page to you from Cancer Epidemiology, Biomarkers & Prevention
(Your Name) thought you would be interested in this article in Cancer Epidemiology, Biomarkers & Prevention.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Recreational Physical Activity and Mammographic Breast Density Characteristics
Katherine W. Reeves, Gretchen L. Gierach and Francesmary Modugno
Cancer Epidemiol Biomarkers Prev May 1 2007 (16) (5) 934-942; DOI: 10.1158/1055-9965.EPI-06-0732

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Recreational Physical Activity and Mammographic Breast Density Characteristics
Katherine W. Reeves, Gretchen L. Gierach and Francesmary Modugno
Cancer Epidemiol Biomarkers Prev May 1 2007 (16) (5) 934-942; DOI: 10.1158/1055-9965.EPI-06-0732
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • Introduction
    • Materials and Methods
    • Results
    • Discussion
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF
Advertisement

Related Articles

Cited By...

More in this TOC Section

  • Urinary Melatonin in Relation to Breast Cancer Risk
  • Endometrial Cancer and Ovarian Cancer Cross-Cancer GWAS
  • Risk Factors of Subsequent CNS Tumor after Pediatric Cancer
Show more Research Articles
  • Home
  • Alerts
  • Feedback
  • Privacy Policy
Facebook   Twitter   LinkedIn   YouTube   RSS

Articles

  • Online First
  • Current Issue
  • Past Issues

Info for

  • Authors
  • Subscribers
  • Advertisers
  • Librarians

About Cancer Epidemiology, Biomarkers & Prevention

  • About the Journal
  • Editorial Board
  • Permissions
  • Submit a Manuscript
AACR logo

Copyright © 2021 by the American Association for Cancer Research.

Cancer Epidemiology, Biomarkers & Prevention
eISSN: 1538-7755
ISSN: 1055-9965

Advertisement