Abstract B12: The effect of physical activity and body size on mammographic density in high-risk, BRCA mutation-negative women
Authors: Moran Olivia M. , Nikitina Dina , Gunasekara Anoma , Yaffe Martin J. , Metcalfe Kelly A. , Narod Steven A. , Kotsopoulos Joanne 
Published: May 2019

Purpose: Mammographic density (MD) reflects the proportion of dense tissue in relation to non-dense tissue in the breast and is the strongest biological marker of breast cancer risk. MD is known to be higher among women with a family history compared to women in the general population. We have previously demonstrated that women with a strong family history of breast cancer but no BRCA mutation face an elevated lifetime risk of breast cancer estimated at 40% compared to 11% in the general population. Various lifestyle factors, such as physical activity and body mass index (BMI), have been shown to modify MD in the general population. It is of interest to determine if such an association exists among high-risk women.

Objective: To evaluate the relationship between physical activity, BMI and MD in high-risk women.

Methods: This study included 100 women enrolled in an on-going prospective study of high-risk women with a strong family history of breast cancer (two first-degree relatives with breast cancer under age 50 or three cases at any age) and no identified BRCA mutations in their families. Current physical activity levels and BMI were collected using self-reported questionnaires. Physical activity was defined as moderate to vigorous physical activity (MVPA). Two dichotomous variables were created to define high vs. low MVPA levels: 1) based on the Canadian Society for Exercise Physiology guideline of 2.5 hours of MVPA per week and 2) the 75th percentile of MVPA in the sample (3.5 hours per week). A BMI of 25 or more was defined as high using the World Health Organization criteria of overweight. Mammograms were assigned a percentage of density (0 - 100%) using a computer-assisted method (Cumulus 6). Multivariate linear regression modelling was used to evaluate the relationships between both MVPA and BMI with MD while adjusting for age, menopausal status, and parity. BMI models also adjusted for MVPA (continuous) and MVPA models adjusted for BMI (continuous).

Results: Among all women, those with a high BMI had significantly lower mean percent density compared to women with a low BMI (13% vs. 23%; P = 0.01). This association was stronger for premenopausal (27% vs. 37%; P = 0.06) vs. postmenopausal (12% vs. 20%; P = 0.10) women. Women who engaged in MVPA for 2.5 hours per week or more had significantly greater mean percent density compared to women who were less physically active (29% vs. 22%; P = 0.04). This relationship did not vary by menopausal status (P ≥ 0.15). Based on the 75th percentile of MVPA, women with high MVPA levels had significantly greater mean percent density compared to women with low MVPA levels (31% vs. 22%; P = 0.02). This relationship was significant for postmenopausal (26% vs. 13%; P = 0.04) but not premenopausal (31% vs. 25%; P = 0.27) women.

Conclusion: In this cohort of high-risk women, high BMI was associated with lower MD that was suggestively stronger for premenopausal women. Although preliminary, these findings suggest a possible mechanism by which a lifestyle factor may influence MD, and possibly breast cancer risk, in high-risk women. Further evaluation with a larger sample size is needed to elucidate the relationships between physical activity, as well as other modifiable factors, and MD in this cohort of women. This study adds to the growing evidence supporting the inclusion of MD into breast cancer risk prediction models, in order to improve individualized treatments and prevention strategies for women at an increased risk for disease.

Citation Format: Olivia M. Moran, Dina Nikitina, Anoma Gunasekara, Martin J. Yaffe, Kelly A. Metcalfe, Steven A. Narod, Joanne Kotsopoulos. The effect of physical activity and body size on mammographic density in high-risk, BRCA mutation-negative women. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B12.