Dietary Fat Intake During Adolescence and Breast Density Among Young Women

Abstract

BACKGROUND Lack of association between fat intake and breast cancer risk in cohort studies might be attributed to disregard of temporal effects during adolescence when breasts develop and are particularly sensitive to stimuli. We prospectively examined associations between adolescent fat intakes and breast density. METHOD Among 177 women who participated in the Dietary Intervention Study in Children, dietary intakes at ages 10–18 were assessed on five occasions by 24-hour recalls and averaged. We calculated geometric mean and 95% confidence intervals for MRI-measured breast density at ages 25–29 across quartiles of fat intake using linear mixed-effect regression. RESULTS Comparing women in the extreme quartiles of adolescent fat intakes, percent dense breast volume (%DBV) was positively associated with saturated fat (mean=16.4% vs. 21.5%; Ptrend<0.001). Conversely, %DBV was inversely associated with monounsaturated fat (25.0% vs. 15.8%; Ptrend<0.001) and the ratio of polyunsaturated fat to saturated fat (P/S ratio; 19.1% vs. 14.3%; Ptrend<0.001). When examining intake by pubertal stages, %DBV was inversely associated with intake of polyunsaturated fat (20.8% vs. 16.4%; Ptrend=0.04), long-chain omega-3 fat (17.8% vs. 15.8%; Ptrend<0.001), and P/S ratio (22.5% vs. 16.1%; Ptrend<0.001) before menarche, but not after. These associations observed with %DBV were consistently observed with absolute dense breast volume but not with absolute non-dense breast volume. CONCLUSIONS In our study, adolescent intakes of higher saturated fat and lower mono- and polyunsaturated fat are associated with higher breast density measured approximately 15 years later. IMPACT The fat subtype composition in adolescent diet may be important in early breast cancer prevention.

Chemically induced carcinogenesis in rodent models of aging: assessing organismal resilience to genotoxic stressors in geroscience research

“…The results strikingly show that early onset anorexia in pre-adolescent and adolescent girls result in a significant reduction in breast cancer risk (standardized incidence ratio/the ratio of observed-to-expected number of cases 0.4), whereas adult onset anorexia has no significant effect (Papadopoulos et al 2009). Overconsumption of calories and childhood obesity also affect the hormonal milieu during development, including a significant rise in circulating IGF-1 (Silfen et al 2002;Thissen et al 199 4), which con tr ib ute t o develo pmental reprogramming of susceptibility to mammary carcinogenesis (Gunther et al 2015;Jung et al 2016). Indeed, recent data have shown a strong association between higher body mass index during adolescence and increased risk for several malignancies, including colorectal cancer and breast cancer and in adulthood (Weihrauch-Bluher et al 2018).…”

Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

“…Forty-one studies did not meet the selection inclusion criteria: no adequate breast density data (n = 20), qualitative analysis (n = 12), editorials (n = 4), conference abstracts (n = 3), post-mortem study (n = 1), and phantom study (n = 1). Finally, 38 studies attained the inclusion criteria [1,2,3,5,11,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57] and were included in the analysis as shown in Table 1.…”

“…Several MRI sequences were used to enable the precise differentiation between adipose and fibroglandular tissues; of these, non-contrast-enhanced T1-weighted was widely used either with 2D spin echo or 3D gradient echo. In fact, 16 studies (41.03%) used non-contrast-enhanced T1-weighted [1,2,26,27,28,29,31,33,35,44,45,48,49,50,51,53], while in 12 studies (30.77%) non-contrast-enhanced images were integrated with contrast-enhanced images [25,36,37,38,39,40,41,42,43,44,47,49]. In terms of breast density segmentation/measurement, the majority of the studies (20 studies; 51.28%) used FCM clustering algorithm [1,2,11,25,26,27,28,29,31,32,33,34,35,36,37,38,39,40,41,42], while 7 studies (17.95%) used FCM and N3 algorithm [45,46,47,48,49,50,51], 4 studies (10.26%) interactive thresholding algorithm [3,5,52,53], 4 studies (10.26%) in-house customized software [29,53,54,55], one study (2.56%) manual software […”

“…Among the thirty-eight studies included in the systematic review and meta-analysis, 21 studies qualified for meta-analysis since they reported the percent breast density using an identical expression of measurement and dispersion [1,3,11,25,26,27,28,29,30,31,32,36,37,38,45,48,49,50,53,54,55] (Table 2). However, for the remaining 17 studies, the percent breast density was reported in different format: in eight of these studies, it was defined as a median and interquartile range (IQR) [2,39,40,41,42,43,44,47], and in the other nine, it was reported either in different measurement unit or the subject’s sets were not independent, due to multiple usage [5,33,34,35,46,51,52,56,57]. To perform the meta-analysis precisely, all the measured quantities should be reported in an identical expression of measurement and dispersion, thus we decided to exclude them from the meta-analysis.…”

The Lack of Association between Plant-Based Dietary Pattern and Breast Cancer: a Hospital-Based Case-Control Study

“…Factors that may be modifiable include late pregnancy, avoidance of breastfeeding, radiation exposure [ 4 ], and the use of hormone replacement therapy (HRT) [ 5 6 ]. Some of the factors contributing to BrCa can be completely changed, including body mass index (BMI) [ 7 ], lifestyle [ 8 ], eating habits [ 9 ] and, diet [ 6 ].…”