Abstract
PURPOSE:
Mammographic density is a strong risk factor for breast cancer. Although diet is associated with breast cancer risk, there are limited studies linking adult milk intake with mammographic density. Here, we investigate the association of milk intake with mammographic density in premenopausal women.
METHODS:
We analyzed data from 375 cancer-free premenopausal women who had routine screening mammography at Washington University in St. Louis in 2016. We used Volpara to measure volumetric percent density, dense volume, and non-dense volume. We collected information of recent milk intake (past 12 months), and categorized skim milk and low/reduced-fat milk intake into 4 groups: <1/week, 1/week, 2-6 times/week, ≥1/day, while whole and soy milk intake were categorized into 2 groups: <1/week, ≥1/week. We used adjusted multivariable linear regression model to evaluate the associations of milk intake and log-transformed volumetric percent density, dense volume, and non-dense volume.
RESULTS:
In multivariable analyses, volumetric percent density was 20% (p-value=0.003) lower in the 1 serving of low-reduced fat milk/week group, 14% (p-value=0.047) lower in the 2-6/week group, and 12% (p-value=0.144) lower in the ≥1/day group (p-trend=0.011) compared with women who drank low/reduced-fat milk <1/week. Attenuated and non-significant associations were observed for low/reduced-fat milk intake and dense volume. There were no associations of whole, skim and soy milk intake with volumetric percent density and dense volume.
CONCLUSIONS:
Recent low/reduced-fat milk intake was inversely associated with volumetric percent density in premenopausal women. Studies on childhood and adolescent milk intake and adult mammographic density in premenopausal women are needed.
Keywords: Milk intake, mammographic density, dairy, diet, breast cancer
INTRODUCTION
Mammographic density reflects the amount of epithelial and stromal tissues in relation to adipose tissue in the breast. Mammographic density is one of the strongest risk factors for breast cancer, with a 4-6 fold increased risk among women who have dense breast tissue ( >75% of the breast) compared with women who have little or no dense breast tissue [1-7]. Estimates of attributable risk suggest that having dense breasts may account for 26-39% of breast cancer cases in the US, with the population attributable risk proportion higher in premenopausal women (39.3%) than postmenopausal women (26.2%) [1, 2, 8]. About 27.6 million women aged 40 to 74 years in the US have extremely dense breasts, and women aged 40 to 49 years account for 44.3% (N = 12.3 million) [9]. Hence, strategies to reduce mammographic density, especially in premenopausal women could be important in breast cancer prevention.
Diet is modifiable, hence, a good understanding of the associations of diet with mammographic density may provide insight into how dietary modification could be utilized in reducing mammographic density and ultimately breast cancer incidence. Nevertheless, the associations of adult diet, including dairy intake (e.g. milk) with mammographic density have been inconsistent [10-15]. Two studies reported inverse associations between dairy foods and mammographic density in premenopausal women [10, 13], while others did not [11, 12, 14, 15]. Milk has many bioactive compounds that could impact mammographic density (e.g. calcium, branched chain fatty acids, rumenic acid, and cysteine-rich whey proteins) but only three studies have investigated the associations of milk intake with mammographic density [11, 12, 14] and only one in premenopausal women [11]. One of the studies reported an inverse association between milk intake and mammographic density [14] while the other two studies found no association between milk intake and mammographic density [11, 12].To address this knowledge gap, we evaluated the associations of different types of milk (skim milk, low/reduced-fat milk, whole milk, and soy milk) intake with mammographic density in premenopausal women.
METHODS
PARTICIPANTS
Annually, close to 5,000 premenopausal women undergo mammography at the Joanne Knight Breast Health Center (BHC), Washington University School of Medicine and Siteman Cancer Center, St. Louis. We recruited 383 participants among premenopausal women who had the routine screening mammogram at the BHC in 2016. The current study is limited to 375 women with complete data. The detailed description of the study population has been provided previously[16]. A participant flow chart of this study is included (Supplementary Figure 1). Briefly, premenopausal women who were scheduled for their annual screening mammography at the BHC were mailed study flyers by research coordinators two weeks to one month in advance. Follow-up calls were made within 7 days of the scheduled appointments to screen interested individuals and to provide further details on the study. To be eligible, participants had to be (i) premenopausal at the time of mammogram. We identified women as premenopausal if they had a regular menstrual period within the preceding 12 months, no prior history of bilateral oophorectomy, and not used menopausal hormone therapy, (ii) no serious medical condition that would prevent the participant from returning for her annual mammogram in 12 months, (iii) not pregnant, (iv) no history of cancer, including breast cancer, (v) and no history of breast augmentation or reduction. Study approval was granted by the Institutional Review Board (IRB) of the Washington University School of Medicine, Saint Louis, MO. All study participants provided informed consent.
QUESTIONNAIRE DATA
Participants completed a detailed questionnaire on the day of the screening mammogram. The questionnaire requested detailed demographic, reproductive and anthropometric information on breast cancer risk factors, including age (years), age at menarche (years), age at first birth (years), race (non-Hispanic White, Black/African American, others), education (pre-college, post-college), body mass index (BMI) (kg/m2), menstrual and reproductive history included parity (0, 1, 2, ≥3), use of oral contraceptive (yes/no), family history of breast cancer (yes/no), etc.
MILK INTAKE
Participants were asked, on the questionnaire, how many servings do they typically consumed of the following types of milk in the past 12 months: skim milk, low/reduced-fat milk, whole milk, and soy milk. A serving of milk is 1 cup or one regular 8-ounce container. Servings of milk intake were categorized into 7 groups: (i) Never, or <1/week, (ii) 1/week, (iii) 2-6/week, (iv) 1/day, (v) 2-3/day, (vi) 4-5/day, (vii) ≥6/day. Milk intake was low in our study population, hence, we re-categorized servings of milk intake based on the distribution in our study population. We re-categorized skim milk and low/reduced-fat milk fat milk into 4 groups: <1/week, 1/week, 2-6/week, and ≥1/day, while whole milk and soy milk were just re-categorized into 2 groups: <1/week and ≥1/week because of the small number.
Skim milk is fat free milk; 1% milk (low fat milk) contains 1% milk fat; 2% milk (reduced fat milk) contains 2% milk fat; and whole milk contains 3.25% milk fat by weight. Soy milk is made from soybeans and low in saturated fat.
VOLUMETRIC MAMMOGRAPHIC DENSITY MEASURES
We used Volpara (version 1.5, (Matakina Technology Ltd, Wellington, New Zealand)) to determine volumetric measures of mammographic density: volumetric percent density, dense volume, and non-dense volume. Volumetric percent density is calculated as the ratio of fibroglandular tissue volume to total breast volume. The method underlying Volpara has been described in detail [17]. Volpara volumetric percent density values range from 0.5-34.5% [17, 18]. In comparison with clinical two-dimensional methods, Breast Imaging Reporting and Data System (BI-RADS) density categories (5th edition), Volpara is mapped to an automated density grade using preset thresholds (automated density grade 1: <3.5%; grade 2: ≥ 3.5 and <7.5%; grade 3 ≥ 7.5 and < 15.5%; grade 4: ≥15.5%) [19].
STATISTICAL ANALYSIS
Descriptive statistics are presented as mean and standard deviation (SD) for continuous variables and percentages (%) for categorical variables. The parametric p-value was calculated using ANOVA for numerical variables and chi-square test for categorical variables. Volumetric percent density, dense volume, and non-dense volume were all natural log-transformed to ensure the normality of the residuals in all regression models. Multivariable linear regression models were used to evaluate the associations between categories of milk intake and log-transformed volumetric percent density, dense volume, and non-dense volume. All models were adjusted for age (continuous), BMI (continuous), parity (0, 1, 2, ≥3), oral contraceptive use (yes/no), family history of breast cancer (yes/no) and race (non-Hispanic White/African American/others). The variables were selected as potential confounders based on their associations with mammographic density and/or breast cancer risk in previous studies, and they retained significance in the multivariable model. BMI was calculated as current weight (kg) divided by current height squared (m2). Beta coefficients (β) and 95% confidence intervals from the regression models were evaluated and back transformed for easier interpretation. The back-transformed coefficients are presented as percentage difference (%), which is estimated as Diff % = (exp(β)- 1)*100, and comparing each group to the reference group. Trend across categories of milk intake was tested using Wald statistic by including the medians of milk intake categories as continuous variables in multivariable models. All the analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). All tests were two-tailed, and p < 0.05 was considered to be statistically significant.
RESULTS
The baseline characteristics of participants are shown in Table 1. The mean age at the time of screening mammogram was 47.5 years (SD=4.8, range= 32-58 years). The mean BMI was 30.8 kg/m2 (range =17.9-63.1 kg/m2), consistent with the BMI of women attending screening mammogram at the Joanne Knight Breast Health Center. Most (65.6%) of the participants were non-Hispanic White; 29.3% were Black/African American. The mean volumetric percent density was 9.5% (SD = 6.5), the mean dense volume was 80.7 cm3 (SD = 42.7), and the mean non-dense volume was 1079.0 cm3 (SD = 743.0). Milk intake was low among women in our study: 56.8% participants drank low/reduced-fat milk <1/week, 67.5% participants drank skim milk <1/week, 90.3% participants drank soy milk <1/week, 89.4% participants drank whole milk <1/week.
Table 1.
Characteristics of 375 premenopausal women recruited during the annual screening mammogram
| Number | Mean ± SD/ Percentage (%) | |
|---|---|---|
| Age (years) | 375 | 47.5±4.8 |
| Age at menarche (years) | 373 | 12.8±2.2 |
| Age at first birth (years) | 302 | 26.0±6.1 |
| BMI (kg/m2) | 375 | 30.8±8.1 |
| Parity | ||
| 0 | 70 | 18.8% |
| 1 | 67 | 18.0% |
| 2 | 138 | 37.1% |
| ≥3 | 97 | 26.1% |
| Ever breastfeed | ||
| Yes | 216 | 70.8% |
| No | 89 | 29.2% |
| Ever use of oral contraceptive | ||
| Yes | 333 | 88.8% |
| No | 42 | 11.2% |
| Family history of breast cancer | ||
| Yes | 88 | 23.5% |
| No | 287 | 76.5% |
| Race | ||
| Non-Hispanic White | 246 | 65.6% |
| Black/African American | 110 | 29.3% |
| Others | 19 | 5.1% |
| Education | ||
| Pre-College | 54 | 14.4% |
| Post-College | 319 | 85.1% |
| Mammographic density | ||
| Volumetric percent density (%) | 375 | 9.5±6.5 |
| Dense volume (cm3) | 375 | 80.7±42.7 |
| Non-dense volume (cm3) | 375 | 1079.0±743.0 |
| Milk consumption | ||
| Skim milk | ||
| <1/week | 220 | 67.5% |
| 1/week | 34 | 10.4% |
| 2-6/week | 39 | 12.0% |
| ≥1/day | 33 | 10.1% |
| Low/reduced-fat milk | ||
| <1/week | 188 | 56.8% |
| 1/week | 50 | 15.1% |
| 2-6/week | 53 | 16.0% |
| ≥1/day | 40 | 12.1% |
| Whole milk | ||
| <1/week | 271 | 89.4% |
| ≥1/week | 32 | 10.6% |
| Soy milk | ||
| <1/week | 269 | 90.3% |
| ≥1/week | 29 | 9.7% |
BMI Body mass index, SD standard deviation
Because low/reduced-fat milk was the most frequently consumed milk in our study population, we examined the distribution of mammographic density and known breast cancer risk factors among participants by categories of low/reduced-fat milk intake (Table 2). We observed significant differences in parity (p=0.030) and breastfeeding history (p=0.005) by categories of low/reduced-fat milk intake.
Table 2.
Distribution of known breast cancer risk factors in 375 premenopausal women by low/reduced-fat milk intake
| Low/reduced-fat milk intake | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| <1/ week | 1/week | 2-6/week | ≥1/ day | P-value | |||||
| N | Mean ± SD / Percentage (%) |
N | Mean ± SD / Percentage (%) |
N | Mean ± SD / Percentage (%) |
N | Mean ± SD / Percentage (%) |
||
| Age (years) | 188 | 47.5±5.0 | 50 | 46.6±4.9 | 53 | 47.4±4.7 | 40 | 48.5±4.0 | 0.358 |
| Menarche (years) | 187 | 12.7±2.6 | 50 | 12.7±1.4 | 52 | 12.9±1.8 | 40 | 13.3±1.7 | 0.488 |
| Age at first birth (years) | 139 | 26.6±6.0 | 43 | 25.3±5.3 | 50 | 25.9±6.1 | 33 | 24.9±7.6 | 0.394 |
| BMI (kg/m2) | 188 | 30.1±8.5 | 50 | 31.8±8.5 | 53 | 31.6±8.3 | 40 | 32.37±7.0 | 0.271 |
| Parity | |||||||||
| 0 | 48 | 25.67% | 7 | 14.0% | 3 | 5.7% | 5 | 13.2% | 0.030 |
| 1 | 36 | 19.25% | 5 | 10.0% | 10 | 18.9% | 9 | 23.7% | |
| 2 | 58 | 31.02% | 24 | 48.0% | 23 | 43.4% | 13 | 34.2% | |
| 3 | 45 | 24.06% | 14 | 28.0% | 17 | 32.1% | 11 | 29.0% | |
| Ever breastfeed | |||||||||
| Yes | 100 | 71.4% | 24 | 55.8% | 43 | 86.0% | 20 | 57.1% | 0.005 |
| No | 40 | 28.6% | 19 | 44.2% | 7 | 14.0% | 15 | 42.9% | |
| Ever use of oral contraceptive | |||||||||
| Yes | 165 | 87.8% | 45 | 90.0% | 49 | 92.5% | 37 | 92.5% | 0.687 |
| No | 23 | 12.2% | 5 | 10.0% | 4 | 7.6% | 3 | 7.5% | |
| Family history of breast cancer | |||||||||
| Yes | 45 | 23.9% | 15 | 30.0% | 13 | 24.5% | 5 | 12.5% | 0.271 |
| No | 143 | 76.1% | 35 | 70.0% | 40 | 75.5% | 35 | 87.5% | |
| Race | |||||||||
| Non-Hispanic White | 123 | 65.4% | 32 | 64.0% | 32 | 60.4% | 24 | 60.0% | 0.818 |
| Black/African American | 54 | 28.7% | 17 | 34.0% | 19 | 35.9% | 13 | 32.5% | |
| Others | 11 | 5.9% | 1 | 2.0% | 2 | 3.8% | 3 | 7.5% | |
| Education Level | |||||||||
| Pre-College | 21 | 11.2% | 10 | 20.0% | 8 | 15.1% | 6 | 15.0% | 0.195 |
| Post-College | 167 | 88.8% | 39 | 78.0% | 45 | 84.9% | 34 | 85.0% | |
BMI Body mass index, SD standard deviation
In multivariable adjusted analyses (adjusted for age, BMI, parity, oral contraceptive use, family history of breast cancer and race), we observed an inverse association between low/reduced-fat milk and volumetric percent density (Table 3). Volumetric percent density was 20% (β=0.80, 95% CI: 0.68-0.93) lower in the 1/week group; 14% (β=0.86, 95% CI: 0.74-1.00) lower in the 2-6 /week group; and 12% (β=0.88, 95% CI: 0.75-1.04; p-trend=0.011) lower in the ≥1/day group compared with <1/week group. There were no associations between whole milk, skim milk and soy milk and volumetric percent density (Table 3).
Table 3.
Multivariable adjusteda associations of milk intake and volumetric percentage density in 375 premenopausal women
| Servings of milk intake | Number | Volumetric percent density (%) | ||
|---|---|---|---|---|
| β (95% CI)a | P-value | P-trend | ||
| Low/reduced-fat milk | ||||
| <1/ week | 188 | Reference | ||
| 1/ week | 50 | 0.80 (0.68, 0.93) | 0.003 | |
| 2-6/ week | 53 | 0.86 (0.74, 1.00) | 0.047 | |
| ≥1/ day | 40 | 0.88 (0.75, 1.04) | 0.144 | 0.011 |
| Skim milk | ||||
| <1/ week | 220 | Reference | ||
| 1/ week | 34 | 0.84 (0.70, 1.01) | 0.069 | |
| 2-6/ week | 39 | 1.01 (0.85, 1.20) | 0.869 | |
| ≥1/ day | 33 | 1.06 (0.88, 1.27) | 0.571 | 0.817 |
| Soy milk | ||||
| <1/ week | 269 | Reference | ||
| ≥1/ week | 29 | 1.13 (0.93, 1.36) | 0.216 | - |
| Whole milk | ||||
| <1/ week | 271 | Reference | ||
| ≥1/ week | 32 | 0.98 (0.82, 1.18) | 0.870 | - |
β beta coefficient, 95% CI 95% confidence intervals, SD standard deviation
Adjusted for age (continuous), body mass index (continuous), parity (0, 1, 2, ≥3), oral contraceptive use (yes/no), family history of breast cancer (yes/no) and race (non-Hispanic White/African American/others)
The associations of low/reduced-fat milk intake with dense volume were attenuated in multivariable adjusted analyses (adjusted for age, BMI, parity, oral contraceptive use, family history of breast cancer and race) (Table S1). Dense volume was 15% (β=0.85, 95% CI: 0.74-0.98; p-value=0.026) lower among women who drank low/reduced-fat milk 1/week compared with women who drank <1/week, but no associations were observed for higher intake groups (2-6 /week, and ≥1/day). There were no associations between whole milk, skim milk and soy milk and dense volume (Table S1).
We also observed an inverse association between soy milk intake and non-dense volume (β=0.81 for ≥1/ week; p-value=0.039) (Table S1). This finding should be interpreted cautiously, however, given the small proportion (9.7%) of our participants who consumed soy milk ≥1/ week. There were no associations between other types of milk and non-dense volume (Table S1).
DISCUSSION
Our study is one of the few to investigate the associations of milk intake with mammographic density in premenopausal women. We observed that consumption of low/reduced-fat milk was inversely associated with volumetric percent density. Whole, skim, and soy milk intake were not associated with volumetric percent density.
Milk contains many bioactive compounds (e.g. calcium), which may be associated with breast density [20]. Calcium is involved in cell apoptosis, proliferation, and differentiation [21, 22], and may thus play a role breast physiology and influence mammographic density [23]. Studies have shown that calcium intake is inversely associated with percentage mammographic breast density in premenopausal women [10, 12, 24-27]. In addition, milk contains branched chain fatty acids, rumenic acid, and cysteine-rich whey proteins, which are associated with mammary cancer prevention in mice models [28]. Rumenic acid is a conjugated linoleic acid (CLA). CLA might exert anticarcinogenic effects in mammary tissues by targeting initiated epithelial cells within ducts, alveoli, and terminal end buds, or in transformed epithelial cells resulting in an inhibition of cell growth, alterations in differentiation, or induction of cell death [29].
Three other studies have previously investigated the associations of milk intake with mammographic density with conflicting results. Garcia-Arenzana et al. reported a positive association of whole milk intake, but no association of semi-skimmed milk with mammographic density [14], while the other two studies observed no associations of milk intake with mammographic density. These studies did not, however, evaluate various types of milk [11, 12]. The differences in our results when compared to previous studies may be due to differences in study population and how mammographic density was assessed (Table S2). Our study was limited to premenopausal women, hence, study population is younger (mean age 47.5 years), while the other studies included both premenopausal and postmenopausal women, all with mean age > 50 years, and analyses were not stratified by menopausal status[12, 14]. In addition, African Americans, who are more likely to have lactose intolerance, and hence consume less milk constitute 29.3% of our study, while participants in the others were mainly White-Hispanic, and Japanese ancestry. Further, our study determined mammographic density using Volpara which provides automated volumetric measures, while other studies used semi-quantitative [12, 14], or quantitative area-based methods [11]. We also evaluated types of milk intake (skim milk, low/reduced-fat milk, whole milk, and soy milk), similar to the study by Garcia-Arenzana et al. (whole milk, skimmed milk, and semi-skimmed milk), while Masala et al. did not categorize milk into different types [12], and Takata evaluated ‘fruit and milk’ together [11].
We observed no association between soy milk and volumetric percent density and dense volume. Similar to our findings, Maskarinec et al. reported no significant differences in mammographic density after two years of soy food intervention among premenopausal women [30]. Interestingly, the authors also reported that soy consumption was positively associated with mammographic density during early life but inversely associated with mammographic density during adulthood suggesting that soy intake at different periods in life may have differential effects on mammographic density [30]. Soy contains isoflavones, which are structurally similar to 17-beta-estradiol. Hence, soy isoflavones may compete with endogenous estrogens in binding with estrogen receptor (ER) [31, 32]. As noted, soy milk intake was low in our study, which is similar to what has been reported in other western population[33],
Our study has some limitations. First, it is cross-sectional, which limits causal inference. Second, although we adjusted for potential confounders, residual confounding of unmeasured factors cannot be ruled out. Next, we examined milk intake only, but it is possible that milk intake might be a proxy for other dietary factors (e.g. dairy intake) that might influence mammographic density, thus evaluating the effects of dietary patterns on the association between milk intake and mammographic density may provide more valuable insight. Further, the overall intake of milk in our study is low. Close to 30% of our study participants are African Americans, hence, there might be lactose intolerance which limits the amount of milk they consume [34]. In addition, milk intake was self-reported, nevertheless, we have no reason to believe there will be a differential recall of milk intake based on mammographic density. Several studies have shown that self-administered dietary questionnaire can provide reproducible information on specific dietary intakes and milk intake over 1 year is a good proxy for long-term intake [35, 36], hence, our assessment of recent milk intake (past 12 months) should reflect long-term intake. Growing epidemiological evidence suggests that childhood and adolescent exposures (e.g. adolescent body size, physical activity, and dietary intake) influence breast density and can affect susceptibility of breast tissue to cancer development in adulthood [16, 37-41], thus milk intake in earlier life should be evaluated in future studies.
Despite the limitations, our study has some strengths. Participants were recruited from women attending annual routine screening mammography at the Joanne Knight Breast Health Center, which enhances generalizability. To the best of our knowledge, this is the first study to investigate the associations of various types of milk intake with mammographic density in premenopausal women using Volpara, which provides volumetric measures of density and has been found to be highly reproducible [42]. We adjusted for known confounders in multivariable analysis.
CONCLUSION
In summary, we observed that low/reduced-fat intake was inversely associated with volumetric percent density in premenopausal women. Further studies on childhood and adolescent milk intake and adult mammographic density in premenopausal women are needed.
Supplementary Material
ACKNOWLEDGEMENTS
We acknowledge the study coordinators, especially Kellie Imm, and Linda Li who helped with participant recruitment and data entry.
FUNDING
The study is supported by funds from the Susan G. Komen Foundation (CCR15332379-ATT), Siteman Cancer Center Siteman Investment Program (supported by The Foundation for Barnes-Jewish Hospital Cancer Frontier Fund (BJFH CFF 3781 & 4035) and Washington University School of Medicine; Siteman Cancer Center Biostatistics Shared Resource. The Siteman Cancer Center is supported in part by an NCI Cancer Center Support Grant #P30 CA091842. Dr. Colditz is supported by the Breast Cancer Research Foundation. Dr. Han was supported by foundations from Barnes-Jewish Hospital and Breast Cancer Research Foundation (award ID: BCRF-17-028).The funders had no role in study design, data collection, analysis, interpretation of data, preparation of the report, or decision to publish.
ABBRVIATIONS:
- BI-RADS
Breast imaging reporting and data system
- BMI
Body mass index
- CLA
Conjugated linoleic acid
- ER
Estrogen receptor
- IRB
Institutional review board
- SD
Standard deviation
Footnotes
AVAILABILITY OF DATA AND MATERIALS
The datasets analyzed during the current study are available from the corresponding author on reasonable request.
CONFLICTS OF INTEREST
The authors declare that they have no conflicts of interest.
ETHICS APPROVAL
Ethical approval for this study was provided by the Washington University School of Medicine, Saint Louis, MO Institutional Review Board
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