Introduction
High mammographic breast density has been proven to be a strong independent risk factor for breast cancer [
1,
2]. A woman’s breast consists of adipose, epithelial, and connective tissue. Adipose tissue is nondense tissue and appears translucent on a mammogram. Epithelial and connective tissue are radiodense and appear white on a mammogram. Percent density, which is determined by dividing the absolute dense area by the total breast area, multiplied by 100, is the most commonly used density measure. However, some argue that using dense area as a breast density measure is more appropriate since percent density is strongly influenced by the amount of adipose tissue in the breast. Both a higher absolute dense area and a higher percent density have been found to be associated with a higher breast cancer risk [
3].
High weight, body mass index (BMI), and also adult weight gain are associated with a higher postmenopausal breast cancer risk [
4‐
6]. At the same time, higher weight and BMI are associated with lower percent density since the measures of adiposity are associated with a higher breast fat content, resulting in a lower proportion of mammographic dense tissue [
7‐
9]. So, although high weight and high mammographic percent density are both associated with higher postmenopausal breast cancer risk, they are inversely associated with each other [
9‐
14].
Cross-sectional studies looking into the relation between BMI or weight and absolute dense area show mixed results. Some show that higher BMI or weight is significantly [
8,
10,
12,
15‐
18] or nonsignificantly [
9,
19] associated with a lower dense area, whereas others show that higher BMI or weight is associated with higher dense area [
13,
20] or dense volume [
16‐
19,
21,
22]. Longitudinal studies actually observing how breast measures change with a change in BMI or weight might give more insight into this process.
As far as we know, only one observational study (Reeves et al.) investigated the possible relation between natural (no organized intervention) changes in BMI and weight and changes in mammographic density measures [
20]. They found that percent density decreases when BMI and weight increase in women transitioning through menopause and that there was no association between weight change and dense area.
An explanation for the apparent contradiction that high BMI and weight and weight gain, on the one hand, and high mammographic percent density, on the other hand, are associated with an increased postmenopausal breast cancer risk could be that dense area and the adiposity measures influence breast cancer risk independently from each other. Another explanation could be that increasing BMI and weight gain are accompanied by an increase, or slower decrease, in absolute dense area. Therefore, in this article, we investigated in a longitudinal design how changes in weight are related to changes in mammographic breast measures.
For this study, we used longitudinal data of women participating in the Prospect-EPIC study [
23], which is part of the EPIC-NL prospective cohort study [
24]. We selected all women who went through menopause within 5 years after recruitment. We focus on these women as large decreases in breast density and changes in weight are often observed around menopause [
25‐
27]. The aim of this study is to investigate how percent density, absolute dense area, and absolute nondense area change over menopause and whether these changes differ between women who lose weight, maintain a stable weight, or gain weight over menopause.
Results
All women (n = 591) in this study were pre- or peri-menopausal at baseline and post-menopausal at follow-up. Our study population was comparable to the total group of Prospect-EPIC participants who went through menopause after baseline but before the first follow-up questionnaire with regard to age and weight at baseline and weight change. The follow-up questionnaires were filled out at a median of 4 years after baseline (interquartile range (IQR) of 3–5 years). The postmenopausal mammogram was taken at a median of 11 months after the follow-up questionnaire was filled out (IQR of 7–17 months). The median time between the pre- and post-menopausal mammogram was 5 years (IQR of 4–6 years).
Characteristics of the study population are presented per weight change group in Table
1. One hundred nine women lost more than 3 % of their baseline weight, 255 women maintained a stable weight (did not lose or gain more than 3 % of their baseline weight), and 227 women gained more than 3 % of their baseline weight over menopause. Age at baseline was comparable between weight change groups, as were age at menarche, number of children, age at first delivery, and time span between pre- and post-menopausal mammograms and baseline and follow-up questionnaires.
Table 1
Study population characteristics according to weight change categories (n = 591)
Number of women, n (%) | | 109 (18.5) | 255 (43.1) | 227 (38.4) |
Weight change (%), median (IQR) | | −5.8 (−8.1; −4.0) | 0.0 (−1.5; 1.5) | 6.3 (4.5; 10.3) |
Weight change (kg), median (IQR) | | −4.0 (−6.5; −3.0) | 0.0 (−1.0; 1.0) | 4.0 (3.0; 6.5) |
Weight at baseline (kg), median (IQR) | | 69.0 (62.5; 82.0) | 67.0 (61.5; 73.0) | 66.0 (60.0; 71.5) |
Age at baseline (years), median (IQR) | | 51 (50; 53) | 51 (50; 53) | 50 (50; 52) |
BMI at baseline (kg/m2), median (IQR) | | 26.0 (23.0; 30.0) | 25.0 (22.0; 27.0) | 24.0 (23.0; 26.0) |
BMI at follow-upa (kg/m2), median (IQR) | | 24.3 (21.8; 27.6) | 24.7 (22.3; 26.7) | 25.9 (24.2; 28.4) |
Waist at baseline (cm), median (IQR) | | 82.0 (75.0; 92.5) | 80.0 (74.0; 86.0) | 79.0 (73.0; 84.0) |
Age at menarche (years), median (IQR) | | 13 (13; 14) | 13 (12; 14) | 13 (13; 14) |
Age at menopause (years), median (IQR) | | 52 (50; 54) | 52 (50; 54) | 52 (50; 53) |
Number of children | | 2 (2; 3) | 2 (2; 3) | 2 (2; 3) |
Age at first deliveryb ( years), median (IQR) | | 25 (23; 27) | 25 (23; 27) | 24 (22; 27) |
Time span between pre- and post-menopausal mammogram (years), median (IQR) | | 5 (4; 6) | 5 (4; 6) | 5 (4; 6) |
Time span between baseline and follow-up questionnaire (years), median (IQR) | | 4 (3; 5) | 4 (3; 4) | 4 (3; 5) |
Age at first childbirthb, n (%) | No children | 14 (12.8) | 28 (11.0) | 30 (13.2) |
| ≤20 years | 8 (7.3) | 14 (5.5) | 23 (10.1) |
| 21–25 years | 50 (49.5) | 112 (43.9) | 97 (42.7) |
| 26–30 years | 30 (27.5) | 79 (31.0) | 61 (26.9) |
| 31–35 years | 7 (6.4) | 18 (7.1) | 12 (5.3) |
| >35 years | 0 (0.0) | 4 (1.6) | 4 (1.8) |
Pre- and post-menopausal breast and weight measures and the change in breast and weight measures are presented in Table
2. The median increase in weight is 1.0 kg (IQR of −1.0; 3.5) over menopause. Median percent density (−6.8 %, IQR of −15.6; 0.5), dense area (−12.4 cm
2, IQR of −25.4; −4.1), and breast area (−9.6 cm
2, IQR of −26.1; 2.1) all decreased over menopause, whereas the median amount of adipose (nondense) tissue slightly increased over menopause (0.3 cm
2, IQR of −13.2; 14.8). Changes in breast measures over menopause per weight change group are presented in Table
3. The percent density decreased in all three weight change groups; the decrease was largest in the weight gain group and smallest in the weight loss group (
P-trend = 0.001). The dense area decreased similarly among women in all weight change groups (
P-trend = 0.437). There was an average decrease in nondense area in the weight loss group and to a smaller extent in the stable weight group as well, while the nondense area increased in the weight gain group. The change in nondense area is linearly associated with change in weight (
P-trend < 0.001).
Table 2
Pre- and post-menopausal breast measures and changes in breast measures over menopause (n = 591)
Breast density, % | 44.6 (27.6; 59.1) | 33.6 (16.5; 52.4) | −6.8 (−15.6; 0.5) |
Dense area, cm2
| 42.7 (30.4; 57.5) | 26.8 (14.5; 37.3) | −12.4 (−25.1; −4.1) |
Nondense area, cm2
| 57.3 (36.0; 88.5) | 65.4 (34.0; 94.2) | 0.3 (−13.2; 14.8) |
Breast area, cm2
| 105.3 (84.2; 133.7) | 94.6 (68.0; 120.1) | −9.6 (−26.1; 2.1) |
Weightb, kg | 67.0 (61.0; 73.0) | 68.0 (62.0; 75.0) | 1.0 (−1.0; 3.5) |
Table 3
Changes in density measures over menopause in weight change groups (n = 591)
Number of women, n (%) | 109 (18.5) | 255 (43.1) | 227 (38.4) | |
Δ Breast density (%), mean (95 % CI) | −5.0 (−8.0; −2.1) | −6.8 (−9.0; −4.5) | −10.2 (−12.5; −7.9) | 0.001 |
Δ Dense area (cm2), mean (95 % CI) | −16.7 (−20.1; −13.4) | −16.4 (−18.9; −13.9) | −18.1 (−20.6; −15.5) | 0.437 |
Δ Nondense area (cm2), mean (95 % CI) | −6.1 (−11.9; −0.4) | −0.6 (−4.9; 3.8) | 5.3 (0.9; 9.8) | <0.001 |
Similar results were found for weight change groups of 2 kg and 4 % change of weight (data not shown).
The results of the linear regression analyses with weight as a continuous independent variable were in line with the other results, showing that an increase in weight is statistically significantly associated with a decrease in percent density and an increase in nondense area. No association was found between weight change and change in dense area (Table
4).
Table 4
Association between percentage weight change and changes in breast (density) measures (n = 591)
Δ Breast density, % | | | | |
Percentage weight change | −0.13 | 0.06 | −0.25; −0.02 | 0.023 |
Δ Dense area, cm2
| | | | |
Percentage weight change | −0.05 | 0.06 | −0.18; 0.08 | 0.436 |
Δ Nondense area, cm2
| | | | |
Percentage weight change | 0.44 | 0.11 | 0.22; 0.65 | <0.001 |
The stratified analysis by BMI at intake did not lead to different conclusions when compared with the overall results shown in Table
3. The decrease in percent density is largest in women who gain weight and smallest in women who lose weight. In the two BMI groups,
P values for change in percent density over the three weight change groups are 0.013 and 0.053, respectively. As the size of the change estimates in the two BMI groups are comparable (for BMI of not more than 25: −4.5 % (95 % CI −8.7; −0.3), −6.8 % (95 % CI −9.7; −3.8), and −9.9 % (95 % CI −12.7; −7.0) and for BMI of more than 25: −5.9 % (95 % CI −10.2; −1.6), −6.1 % (95 % CI −9.6; −2.6), and −10.4 % (95 % CI −12.8; −7.0) for the weight loss, stable weight, and weight gain groups, respectively), the borderline significance in the group with a BMI of more than 25 is probably caused by a lack of power because of the low number of women in this group. In both BMI groups, no linear trend was observed for change in dense area over the weight change groups. A statistically significant linear trend was observed in both BMI groups for the change in nondense area over the weight change groups (
P
BMI ≤ 25 = 0.006 and
P
BMI > 25 = 0.028). In both BMI groups, nondense area decreased in women who lost weight and increased in women who gained weight.
Discussion
In this analysis of women going through menopause, both percent density and dense area decreased over menopause in all three weight change groups (loss, stable, and gain). An increase in weight was found to be associated with an increase in nondense (adipose) tissue and a decrease in percent density. No association was found between changes in weight and changes in dense area. Therefore, the larger decrease in percent density in women who gained weight than in women who remained stable or lost weight can probably be explained by changes in nondense area and not by a decrease in dense area.
A possible explanation for the apparent contradiction that both high weight and BMI and weight gain, on the one hand, and high mammographic percent density, on the other hand, are associated with a high postmenopausal breast cancer risk would be that weight gain is accompanied by an increase, or slower decrease, in absolute dense area. However, this possible explanation was not confirmed by our study results.
Our findings confirm the idea described by Reeves et al. that increases in weight appear to result in the accumulation of fat in the breast rather than altering the dense breast tissue [
20]. To the best of our knowledge, only Reeves et al. investigated the association between changes in weight and breast density measures in a longitudinal observational design. They used data of 834 pre- and peri-menopausal women who were an average of 46.5 years old at enrollment and who were followed for an average of 4.8 years (standard deviation (SD) of 1.8). At the end of follow-up, 68.0 % of the women were late perimenopausal or postmenopausal. Annual change in weight was 0.32 kg (SD of 1.46), and annual changes in percent density and dense area were −1.14 % (SD of 3.60) and −0.77 cm
2 (SD of 4.49), respectively. In our study population, the annual median changes in weight, percent density, and dense area were 0.20 kg, −1.36 %, and −2.48 cm
2, respectively. The larger changes in percent density and, especially, dense area in our study population might be caused by our older study population (median age at baseline of 51 years and IQR of 50–53) and the fact that all women in our study population went through menopause compared with only 68.0 % in the study population of Reeves et al. Despite differences between the study populations, their results are comparable to ours. Reeves et al. observed also a negative association between changes in weight and changes in percentage breast density in women going through menopause and no association between changes in weight and changes in the absolute dense area. They did not study the association between weight and nondense area.
Two other studies on the associations between weight or BMI and changes in breast measures used trial data [
7,
38]. Boyd et al. investigated the effect of a 2-year, low-fat, high-carbohydrate diet on breast density in 30- to 65-year-old women showing radiologic densities in at least 50 % of the breast area [
38]. Woolcott et al. used data from a trial of a 12-month aerobic exercise intervention among postmenopausal women and looked at changes in BMI in relation to changes in both area and volumetric breast measures [
7]. The time spans over which changes were measured were an average of 2.3 years (SD of 0.4) in the study by Boyd et al. and 1 year in the study by Woolcott et al. The intervention groups in both studies showed weight losses over the study period of −0.3 kg (no measure of statistical dispersion reported) and −2.3 kg (95 % CI −2.9; −1.7), respectively. The women in the control arm showed a weight gain (0.9 kg, no measure of statistical dispersion reported) and no significant change (−0.5 kg, 95 % CI −1.0; 0.1), respectively [
38,
39]. In the study by Boyd et al., dense area changed by −3.74 cm
2 (95 % CI −5.14; −2.35) in the intervention group and −1.27 cm
2 (95 % CI −2.5; −0.1) in the control group during the study period. In a study by Woolcott et al., dense area changed by −0.3 cm
2 (standard error of 0.7) in the intervention group and did not change in the control group (0.0 cm
2, standard error of 0.7) [
40]. Both studies found that a decrease in weight or BMI was associated with an increase in percent density and this is in agreement with our results. Regarding nondense area, Woolcott et al. also found comparable results; namely, a decrease in BMI was correlated with a reduction in nondense area. However, the association between weight or BMI and dense area showed contrary results: Woolcott et al. found that a decrease in BMI was correlated with an increase in dense area, whereas Boyd et al. found that weight loss was associated with a decrease in dense area, and we did not find an association between changes in weight and dense area at all.
An important difference between the study by Boyd et al. and our study is that in the former both the decrease in weight and the decrease in dense area are at least partly induced by the intervention, a low-fat high-carbohydrate diet. They do not show separate results for intervention and control groups in regard to the association between changes in weight and dense area. Therefore, it is unclear whether the significant relationship between weight change and change in dense area is confined to the intervention group or is observed in the control arm as well.
Woolcott et al. included only postmenopausal women, whereas our population goes through menopause during follow-up. Any dense area change caused by involution of glandular tissue during menopause might be much larger compared with changes due to weight change. We found a median decrease in dense area of 12.4 cm2 in 5 years (IQR of −25.1; −4.1), whereas Woolcott et al. found a change of only −0.1 cm2 (IQR of −4.1; 3.2) over 1 year. The estimated change over 5 years would be around −0.5 cm2. This might explain why we cannot detect an association between weight change and change in dense area in women going through menopause. However, Woolcott et al. found no significant correlation between change in BMI and change in dense volume, indicating that the negative relationship between change in BMI and dense area may also have been caused by chance.
Both high weight and dense area are postmenopausal breast cancer risk factors. Although less is known about the relationship between weight change and breast cancer risk, a recent meta-analysis shows evidence that weight gain too is significantly associated with higher postmenopausal breast cancer risk [
5]. To investigate whether this relationship between high weight and weight gain, on the one hand, and breast cancer risk, on the other hand, might be mediated by dense area, we studied whether change in weight is associated with change in dense area. Our results show no association between changes in weight and changes in dense area. Therefore, it is unlikely that the effect of weight (gain) on breast cancer risk can be explained by (changes in) dense area. Weight (gain) and dense area are presumably two independent postmenopausal breast cancer risk factors.
We observed a strong relationship between weight change and a change in nondense area. For the last few years, the association between nondense area and breast cancer risk has been gaining attention in the literature. In 2014, authors of a published meta-analysis found that a larger nondense area could be inversely associated with breast cancer risk. However, it is still unclear whether this association is independent of the effect of the absolute dense area, since in most studies showing a protecting effect of nondense area on breast cancer risk, this effect disappeared after adjustment for dense area [
3].
A strength of this study is its longitudinal design, enabling us to study prospectively the influence of weight change on changes in breast measures, and this is in contrast to cross-sectional studies. Two other strengths are that the sample size was almost 600 women and that all mammograms were read by the same observer.
A disadvantage of this study is that the breast measures may have been subject to measurement error since they were taken on digitized film-screen mammograms (FSMs). No information was available on the amount of radiation and compression force used during mammography. Since the amount of radiation and compression force can influence the breast density measurements, measurement errors might have occurred, causing misclassification. It is therefore important to confirm the results of this study by using volumetric breast measures from full-field digital mammograms. Another limitation is that postmenopausal mammograms were not taken on the same day as the reporting of weight. The first mammogram taken after the self-reported weight served as the postmenopausal mammogram. The median durations between weight reporting and postmenopausal mammogram were 11 months (IQRstable 8; 17, IQRgain 6; 17) in the stable weight and weight gain groups and 12 months (IQRloss 6; 18) in the weight loss group. This might have led to random misclassification, attenuating the relationships under study. In addition, premenopausal weight was measured by a research nurse, and postmenopausal weight was self-reported. It is known that especially heavy women often underreport their weight. However, we did not find different associations between weight change and change in breast measures for women who start out with a normal weight and women who are overweight or obese at intake. Therefore, we think that in our study the influence of the limitation of self-reported weight on the conclusions is minimal.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
JW performed the data analysis and wrote the manuscript. MB and WV were involved in data analysis and interpretation of the data and critically reviewed the manuscript. PP is the principal investigator of the Prospect-EPIC study and has made contributions to the data acquisition and has been involved in this study by drafting and critically reviewing the manuscript. CG was the project leader of this research project and therefore was involved in all stages of this study. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work that has been done.