Sánchez-Contador, et al.. Alcohol, tobacco, and mammographic density: a population-based study. Breast Cancer Research and Treatment, Springer Verlag, 2011, 129 (1) Screening Program network. The association between MD, alcohol consumption and tobacco use was evaluated by using ordinal logistic models with random center-specific intercepts.We found a weak positive association between current alcohol intake and higher MD, with current alcohol consumption increasing the odds of high MD by 13% (OR=1.13; 95% CI 0.99-1.28) and high daily grams of alcohol being positively associated with increased MD (p for trend=0.045). There were no statistically significant differences in MD between smokers and non-smokers. Nevertheless, increased number of daily cigarettes and increased number of accumulated lifetime cigarettes were negatively associated with high MD (p for trend 0.017 and 0.021). The effect of alcohol on MD was modified by menopausal status and tobacco smoking: whereas alcohol consumption and daily grams of alcohol were positively associated with higher MD in postmenopausal women and in women who were not currently smoking, alcohol consumption had no effect on MD in premenopausal women and current smokers. 4Our results support an association between recent alcohol consumption and high MD, characterized by a modest increase in risk at low levels of current consumption and a decrease in risk among heavier drinkers. Our study also shows how the effects of alcohol in the breast can be modified by other factors, such as smoking.

High mammographic density (MD) is a phenotype risk marker for breast cancer. Body mass index (BMI) is inversely associated with MD, with the breast being a fat storage site. We investigated the influence of abdominal fat distribution and adult weight gain on MD, taking age, BMI and other confounders into account. Because visceral adiposity and BMI are associated with breast cancer only after menopause, differences in pre- and post-menopausal women were also explored. We recruited 3,584 women aged 45–68 years within the Spanish breast cancer screening network. Demographic, reproductive, family and personal history data were collected by purpose-trained staff, who measured current weight, height, waist and hip circumferences under the same protocol and with the same tools. MD was assessed in the left craniocaudal view using Boyd’s Semiquantitative Scale. Association between waist-to-hip ratio, adult weight gain (difference between current weight and self-reported weight at 18 years) and MD was quantified by ordinal logistic regression, with random center-specific intercepts. Models were adjusted for age, BMI, breast size, time since menopause, parity, family history of breast cancer and hormonal replacement therapy use. Natural splines were used to describe the shape of the relationship between these two variables and MD. Waist-to-hip ratio was inversely associated with MD, and the effect was more pronounced in pre-menopausal (OR = 0.53 per 0.1 units; 95 % CI = 0.42–0.66) than in post-menopausal women (OR = 0.73; 95 % CI = 0.65–0.82) (P of heterogeneity = 0.010). In contrast, adult weight gain displayed a positive association with MD, which was similar in both groups (OR = 1.17 per 6 kg; 95 % CI = 1.11–1.23). Women who had gained more than 24 kg displayed higher MD (OR = 2.05; 95 % CI = 1.53–2.73). MD was also evaluated using Wolfe’s and Tabár’s classifications, with similar results being obtained. Once BMI, fat distribution and other confounders were considered, our results showed a clear dose–response gradient between the number of kg gained during adulthood and the proportion of dense tissue in the breast.

The youngest women, the most sedentary women, and those who had a lower educational level and socioeconomic status registered worse diet quality. Ex-smokers and postmenopausal women obtained better scores, probably reflecting a keener concern about leading a healthy life.

We developed a semi-automated tool to assess mammographic density (MD), a phenotype risk marker for breast cancer (BC), in full-field digital images and evaluated its performance testing its reproducibility, comparing our MD estimates with those obtained by visual inspection and using Cumulus, verifying their association with factors that influence MD, and studying the association between MD measures and subsequent BC risk.Three radiologists assessed MD using DM-Scan, the new tool, on 655 processed images (craniocaudal view) obtained in two screening centers. Reproducibility was explored computing pair-wise concordance correlation coefficients (CCC). The agreement between DM-Scan estimates and visual assessment (semi-quantitative scale, 6 categories) was quantified computing weighted kappa statistics (quadratic weights). DM-Scan and Cumulus readings were compared using CCC. Variation of DM-Scan measures by age, body mass index (BMI) and other MD modifiers was tested in regression mixed models with mammographic device as a random-effect term.The association between DM-Scan measures and subsequent BC was estimated in a case–control study. All BC cases in screening attendants (2007–2010) at a center with full-field digital mammography were matched by age and screening year with healthy controls (127 pairs). DM-Scan was used to blindly assess MD in available mammograms (112 cases/119 controls). Unconditional logistic models were fitted, including age, menopausal status and BMI as confounders.DM-Scan estimates were very reliable (pairwise CCC: 0.921, 0.928 and 0.916). They showed a reasonable agreement with visual MD assessment (weighted kappa ranging 0.79-0.81). DM-Scan and Cumulus measures were highly concordant (CCC ranging 0.80-0.84), but ours tended to be higher (4%-5% on average). As expected, DM-Scan estimates varied with age, BMI, parity and family history of BC. Finally, DM-Scan measures were significantly associated with BC (p-trend=0.005). Taking MD<7% as reference, OR per categories of MD were: OR7%-17%=1.32 (95% CI=0.59-2.99), OR17%-28%=2.28 (95% CI=1.03-5.04) and OR>=29%=3.10 (95% CI=1.35-7.14). Our results confirm that DM-Scan is a reliable tool to assess MD in full-field digital mammograms.Electronic supplementary materialThe online version of this article (doi:10.1186/2193-1801-2-242) contains supplementary material, which is available to authorized users.