Abstract
Studies of adult diet and risk of breast cancer have yielded mainly null results, but this does not rule out a possible impact of adolescent diet. This study examined associations between components of adolescent diet and risk of proliferative benign breast disease (BBD), a marker for breast cancer. The study population consisted of 29,494 women in the Nurses’ Health Study II who completed a questionnaire on adolescent diet in 1998 and who were 33–53 years of age at that time. A total of 470 new cases of proliferative BBD were identified between 1991 and 1997. Incidence rate ratios (RRs) and 95% confidence intervals (CIs) were calculated for quartiles of energy-adjusted intakes, using the lowest quartile of each as the reference group. Total fat intake during adolescence was unrelated to risk of proliferative BBD, although there were positive associations for intakes of animal fat and monounsaturated fat and an inverse association for intake of vegetable fat. For vitamin E intake, the multivariate RRs were 1.13, 0.88, and 0.79 (95% CI, 0.61–1.04) for women in the second, third, and highest quartiles, respectively (P for trend = 0.05). The multivariate RRs were 0.94, 0.99, and 0.75 (95% CI, 0.57–0.98) for women in increasing quartiles of fiber intake (P for trend = 0.05). Vegetable fat, vitamin E, and fiber intakes during adolescence were inversely associated with risk of proliferative BBD in this population. Confirmation of these associations may suggest a means for prevention of breast cancer.
Introduction
BBD5 is a heterogeneous group of lesions including a variety of tissue abnormalities. Certain subtypes of BBD are associated with increased breast cancer risk. Compared with women with nonproliferative lesions, women whose biopsies show proliferative changes without atypia have a 1.5–2-fold greater risk of developing breast cancer in the future, and women with atypical hyperplasia have a 3.5–5-fold greater risk (1). These findings suggest that proliferative BBD may be a marker for breast cancer.
The relation of diet to breast cancer risk has been investigated in numerous epidemiological studies. Although ecologic studies and some case-control studies originally suggested that adult intakes of total and saturated fat might be positively associated with breast cancer risk (2, 3), more recent prospective studies have not supported these earlier findings (4, 5, 6). Carotenoids and vitamins C and E have antioxidant properties that may contribute to reduced breast cancer risk (7, 8), and vitamin A also may confer some protection by regulating cell differentiation (9, 10). Results from epidemiological studies of these micronutrients have been inconclusive (2), although a recent prospective study showed decreasing risk of breast cancer with increasing serum carotenoid levels (11). Similarly, studies of adult diet and BBD have not identified any clear and consistent associations (12, 13, 14, 15).
The lack of evidence supporting the role of adult diet in relation to risk of breast cancer does not rule out a possible impact of childhood and adolescent diet. Reviewing the epidemiological evidence on the potential role of early life factors, Colditz and Frazier (16) concluded that exposures between menarche and first birth may exert important effects on future risk. Furthermore, studies of mammary gland development in rats have shown that breast tissue may be most vulnerable to carcinogens during this time period due to rapid proliferation of cells and lack of terminal differentiation (17). Hence, previous studies may have focused on the wrong time period, because adolescent diet may have a stronger influence on risk than adult diet.
To date, only a few studies have examined the role of adolescent diet in the etiology of breast cancer (18, 19, 20, 21). In a population-based case-control study that included 172 cases and 190 controls, a nonsignificant inverse association between adolescent fat intake and premenopausal breast cancer risk was seen (19). Total fiber intake during adolescence was associated with increased breast cancer risk in postmenopausal women (odds ratio for highest versus lowest quartile, 6.6; 95% CI, 1.5–29.6), but fiber from grains was associated with decreased risk in both premenopausal and postmenopausal women. In a larger population-based case-control study including 1647 incident breast cancer cases and 1501 controls, there was a nonsignificant inverse association between fruit and vegetable consumption during adolescence and breast cancer risk (odds ratio for highest versus lowest quartile, 0.9; 95% CI, 0.7–1.1), whereas adolescent intakes of animal fat, high-fat foods, high-fat snacks and desserts, and dairy products had no clear relation to risk (20). Neither of these studies examined associations between intakes of specific micronutrients during adolescence and breast cancer risk. In a recent retrospective analysis in the Nurses’ Health Study that included 843 incident cases of breast cancer, higher consumption of eggs, vegetable fat, and fiber during adolescence were associated with decreased breast cancer risk (21). The 24-item FFQ used in this study, however, did not allow complete assessment of total energy intake or specific nutrients, due to the restricted list of foods.
If dietary factors are involved in the early stages of breast cancer development, important associations may exist between components of adolescent diet and marker lesions such as BBD. To examine this hypothesis, we studied intakes of total fat and specific types of fat, micronutrients, fiber, and foods during adolescence in relation to risk of proliferative BBD within the Nurses’ Health Study II.
Materials and Methods
Study Design and Population.
The Nurses’ Health Study II is a prospective cohort study that began in 1989, when 116,671 female nurses between the ages of 25 and 44 years completed a mailed, self-administered questionnaire including information on a variety of health behaviors and conditions. Since 1989, questionnaires have been sent to these women every 2 years to obtain updated information on lifestyle factors and recent medical events. The response rate during each 2-year period has been ≥90%.
The present study was a retrospective analysis within the Nurses’ Health Study II. The study population included 45,947 women who completed a questionnaire on adolescent diet (described below) in 1998 and had plausible values for total energy intake (between 600 and 5000 kcal/day). We excluded 16,057 women who had a self-reported or histologically confirmed diagnosis of BBD before return of the 1991 questionnaire because pathology specimens were only collected for incident cases diagnosed after the 1991 cycle. A total of 396 women were excluded because of a prior diagnosis of cancer other than non-melanoma skin cancer. The final study population consisted of 29,494 women. This investigation was approved by human research committees at the Harvard School of Public Health and Brigham and Women’s Hospital.
Adolescent Diet Questionnaire.
In 1998, a semiquantitative FFQ with 131 items on adolescent diet was completed by 45,947 women who had previously indicated that they would be willing to participate. This self-administered questionnaire was a modified version of the validated FFQ used to assess adult diet in the Nurses’ Health Study and several other cohorts. Participants were asked to report how often they consumed a specified quantity of 122 foods and beverages during high school, further defined as ages 13–18 years.
A reproducibility study conducted among a random sample of women in a separate cohort showed moderately high correlations between two separate recalls, 8 years apart, of consumption of 24 food items during high school (22). The average Spearman correlation coefficient for the first and second recall was 0.57, although values ranged from 0.38 to 0.74. The mean correlation between reported high school diet and current diet was only 0.25, which may indicate that current diet did not strongly affect recall of remote diet. Although data on the validity of the adolescent diet questionnaire are not yet available, research in survey methodology shows that provision of a clear definition of the reference time period (high school, in this case) enhances recall on self-administered questionnaires (23).
Energy, fat, and micronutrient intakes were derived from participants’ responses on the FFQ using an extensive food composition database maintained by a team of research dietitians. Because the composition of some foods has changed over time, food composition data from the relevant time period (1960s and 1970s) were used, when available, to provide the best approximation of intakes during adolescence.
Identification of Cases of BBD.
On the 1989 baseline questionnaire, all women were asked if they had ever received a diagnosis of fibrocystic or other BBD from a physician. On each of the subsequent biennial questionnaires in 1991, 1993, 1995, and 1997, women were asked if they had received a diagnosis of BBD since the previous questionnaire and if the diagnosis had been confirmed by biopsy and/or aspiration. A total of 2,454 participants reported a first diagnosis of biopsy-confirmed BBD between 1991 and 1997. Of these cases, 1,022 (42%) contributed information on diet during adolescence. This is similar to the overall proportion of women in the entire Nurses’ Health Study II cohort with adolescent dietary data [45,947 of 116,671 (39%)].
Because proliferative BBD, in contrast with other subtypes, is associated with increased risk of breast cancer, proliferative BBD with or without atypia was the primary outcome of interest. Women who reported a first diagnosis of biopsy-confirmed BBD on the 1993, 1995, or 1997 questionnaires were contacted to confirm the diagnosis and to acquire permission to review their pathology specimens. Among the 987 women with adolescent diet information who were initially contacted, 89% (883) confirmed the BBD diagnosis and granted permission for review of their biopsy records and pathology slides. Adequate pathology material was obtained and reviewed for 800 women (91% of those who had given their permission); 754 (94%) of these were confirmed to be eligible cases, and a valid diagnosis was obtained. The main reasons for exclusion were that the pathology specimen did not contain breast tissue or that the biopsy date was before June 1991. Women were also excluded if their biopsy date was after the date they reported BBD or if they had a prior cancer, a diagnosis of breast cancer within the same questionnaire cycle, or a diagnosis of breast carcinoma in situ. Included cases were slightly older and reported greater alcohol consumption between ages 18 and 22 years than cases not included in the analysis, but included and excluded cases were similar in terms of other characteristics (data not shown).
Biopsy materials were reviewed by one of four pathologists (S. J. Schnitt, J. L. Connolly, T. W. Jacobs, or G. Peiro) who had no knowledge of participants’ exposure information. All slides from the breast biopsies were classified as normal or nonproliferative, proliferative without atypia, or atypical hyperplasia, according to the criteria of Dupont and Page (24). Any biopsies that showed atypia or questionable atypia were jointly reviewed by two pathologists (S. J. Schnitt and J. L. Connolly) with one of the other pathologists (T. W. Jacobs or G. Peiro) and a consensus diagnosis was reached. Biopsy tissue with intraductal papilloma, radial scar, sclerosing adenosis, fibroadenoma, fibroadenomatous change, or moderate to florid ductal hyperplasia in the absence of atypical hyperplasia was classified as proliferative without atypia.
Of the 754 cases identified among eligible participants, 470 (62%) were classified as proliferative (with or without atypia) by the study pathologists. Because there were only 39 cases of atypical hyperplasia, this was not examined as a separate outcome in the main analyses. Consistent with a previous report from this cohort, proliferative cases were less likely to report a family history of breast cancer and more likely to have had menarche before age 12 years compared with nonproliferative cases (25).
Statistical Analysis.
Cohort analyses were conducted among the 29,494 women who completed the adolescent diet questionnaire and met the other eligibility criteria, using proliferative disease with or without atypia as the primary outcome. Secondary analyses were also performed using all self-reported BBD and self-reported BBD confirmed by biopsy as outcomes. Eligible participants contributed person-time of follow-up from the time they returned the 1991 questionnaire until the return date of the 1997 questionnaire, death from any cause, report of BBD or cancer other than non-melanoma skin cancer, or loss to follow-up. This method allows for the updating of time-varying covariates every 2 years.
Total fat, types of fat, and specific micronutrients were the main exposures of interest. To adjust for total energy intake (26), total fat and types of fat were examined as nutrient densities, computed as percentages of total caloric intake. For micronutrients, energy-adjusted intakes were calculated using the residual method, in which energy-adjusted values are the residuals from a regression model with total caloric intake as the independent variable and absolute nutrient intake as the dependent variable (26). Fat densities and energy-adjusted micronutrient residuals were then divided into quartiles based on the distributions of values for all women who completed the adolescent diet questionnaire.
Age-adjusted incidence RRs for proliferative BBD were calculated for quartiles of energy-adjusted fat and micronutrient intakes, using the lowest quartile of each as the reference group, and two-sided tests for trend were also conducted. Cox proportional hazards regression was used to estimate RRs and 95% CIs for quartiles of fat and micronutrient intakes while controlling for relevant covariates simultaneously. The multivariate Cox models adjusted for the following variables: age in months, time period (three periods), age at menarche (<12, 12, 13, or ≥14 years), menopausal status (premenopausal, postmenopausal, or uncertain), body mass index at age 18 years (<19, 19–20.4, 20.5–21.9, 22–24.9, ≥25 kg/m2), history of breast cancer in mother or sister (yes/no), alcohol intake between ages 18 and 22 years (0, <5, 5–14, ≥15 g/day), and multivitamin use between ages 13 and 18 years (yes/no). These variables were selected based on their established or hypothesized associations with breast cancer, BBD, or adolescent diet. Terms for quartiles of total energy intake were also included in multivariate models to adjust fully for potential confounding, and types of fat were also mutually adjusted for one another.
Further analyses of associations between individual foods and proliferative BBD were also conducted. The original frequency categories for a serving of each food (ranging from “never or less than once per month” to “6 or more per day”) were used first, and then categories with small numbers of participants were combined to improve the stability of the estimates. Foods were selected according to their contributions to macro- and micronutrients that appeared most important in the previous set of analyses. In addition, three major food groups (fruits and vegetables, meats, and dairy foods) were examined in relation to risk of proliferative BBD. Categories for servings of these food groups were determined based on their distributions among women who completed the adolescent diet questionnaire, and total energy intake was included in the multivariate models.
Results
Between 1991 and 1997, 29,494 women in the study contributed 165,141 person-years of follow-up. The baseline distributions of selected characteristics of participants are presented in Table 1, according to their intakes of fat and vitamins A, E, and C during adolescence. Age, family history of breast cancer, age at menarche, menopausal status, alcohol intake between ages 18 and 22, and body mass index at age 18 did not vary substantially across quartiles of intake.
We observed no association between total fat intake during adolescence and incidence of proliferative BBD (Table 2). There was some suggestion of a positive association for animal fat intake and an inverse association for vegetable fat intake, however. Compared with women in the lowest quartile of animal fat intake, the multivariate RRs for proliferative BBD were 1.24 (95% CI, 0.94–1.63) for women in the second quartile, 1.16 (95% CI, 0.87–1.54) for women in the third quartile, and 1.33 (95% CI, 1.00–1.78) for women in the highest quartile (P for trend = 0.08). For vegetable fat intake, the multivariate RRs were 0.89 (95% CI, 0.70–1.14), 0.92 (95% CI, 0.71–1.18), and 0.73 (95% CI, 0.55–0.96) for women in the second, third, and highest quartiles, respectively (P for trend = 0.04). Because animal fat and vegetable fat intake are negatively correlated, we also included both animal fat and vegetable fat in the same multivariate model to mutually adjust for one another. Although the RRs were somewhat attenuated and the trends were no longer statistically significant, the directions of both associations remained the same.
In addition, monounsaturated fat was positively associated with risk of proliferative BBD. The multivariate RRs were 1.21 (95% CI, 0.90–1.64), 1.33 (95% CI, 0.95–1.85), and 1.52 (95% CI, 1.05–2.21) for women in the second, third, and fourth quartiles of monounsaturated fat intake, respectively, after adjustment for other types of fat (P for trend = 0.03). Polyunsaturated fat intake showed a nonsignificant inverse association with risk, whereas saturated fat and trans-unsaturated fat intakes were unrelated to risk.
Of the micronutrients that were examined, only vitamin E and total vitamin A intakes were inversely associated with risk of proliferative BBD (Table 3). Intakes of vitamin C, retinol, carotenoids, and folate were not related to risk. The weak inverse association for vitamin E was most apparent in the two quartiles with highest intake. Compared with women in the lowest quartile of vitamin E intake, the multivariate RRs for proliferative BBD were 0.88 (95% CI, 0.68–1.14) for women in the third quartile and 0.79 (95% CI, 0.61–1.04) for women in the highest quartile (P for trend = 0.05). The inverse association for vitamin A was slightly weaker, and the trend was nonsignificant. The multivariate RR was 0.84 (95% CI, 0.64–1.11) for women in the highest versus the lowest quartile of total vitamin A intake (P for trend = 0.07). These associations were still apparent when only vitamins from food sources, as opposed to supplements, were included.
Because vegetable fat was inversely associated with risk of proliferative BBD, and vegetable fat is a major source of dietary vitamin E, we included both vitamin E and vegetable fat in the same multivariate model. The inverse association for vegetable fat was somewhat attenuated after adjustment for animal fat and vitamin E; the RR for women in the highest quartile versus the lowest quartile was 0.87 (95% CI, 0.59–1.28; P for trend = 0.59). The inverse association for vitamin E was also attenuated after adjustment for vegetable fat, with a RR of 0.88 (95% CI, 0.63–1.22; P for trend = 0.38) for women in the highest quartile versus the lowest quartile. The directions of both associations, however, remained the same.
In addition, we observed a significant inverse association between fiber intake and proliferative BBD (Table 4). The multivariate RR was 0.75 (95% CI, 0.57–0.98) for women in the highest versus the lowest quartile of fiber intake (P for trend = 0.05). Neither fruit nor vegetable intake, separately or combined, was significantly associated with risk of proliferative BBD.
Both total meat intake and red meat intake were positively associated with risk of proliferative BBD (data not shown). For total meat intake, the multivariate RR for women who ate 3 or more servings/day compared with those who ate less than 1.5 servings/day was 1.50 (95% CI, 1.01–2.22; P for trend = 0.03), whereas for red meat intake, the multivariate RR for women who ate 2 or more servings/day compared with those who ate less than 1 serving/day was 1.33 (95% CI, 0.97–1.84; P for trend = 0.03). These RRs were somewhat attenuated after adjustment for animal fat, but the directions of both associations remained unchanged. No associations were observed for intakes of milk or total, high-fat, or low-fat dairy foods.
We also calculated age-adjusted and multivariate ratios for associations between intakes of individual foods and proliferative BBD. We examined foods that contributed substantially to intakes of animal fat, vegetable fat, vitamin E, vitamin A, and fiber during adolescence. Consumption of nuts and raw carrots were inversely associated with risk of proliferative BBD. For nuts, the multivariate RRs for women who ate 2–3 servings/month, 1 serving/week, and >1 serving/week were 1.03 (95% CI, 0.82–1.29), 0.93 (95% CI, 0.73–1.18), and 0.64 (95% CI, 0.45–0.91), respectively, compared with women who ate 1 serving/month or less (P for trend = 0.02). The multivariate RRs for intake of raw carrots were 0.87 (95% CI, 0.68–1.11) for women who ate 1–3 servings/month, 0.74 (95% CI, 0.57–0.96) for women who ate 1 serving/week, and 0.70 (95% CI, 0.52–0.92) for women who ate ≥2 servings/week, compared with those who ate <1 serving/month (P for trend = 0.02). This inverse association was not observed for intake of cooked carrots. Nonsignificant inverse associations were also observed for intakes of grapes, strawberries, oranges, and fruit juice. Consumption of hot dogs was positively associated with risk of proliferative BBD; multivariate RRs for women who ate 1–3 servings/month, 1 serving/week, and ≥2 servings/week were 1.02 (95% CI, 0.76–1.38), 1.11 (95% CI, 0.81–1.50), and 1.49 (95% CI, 1.04–2.13), respectively (P for trend = 0.01). This association remained significant even after adjustment for animal fat. There were also nonsignificant positive associations between intakes of processed meats (e.g., cold cuts), bacon, and pork and proliferative BBD.
Finally, in the secondary analyses using all self-reported BBD as the outcome (5012 cases), we observed no consistent associations for intakes of total fat or any types of fat. Restricting the outcome to cases that participants reported as confirmed by biopsy (998 cases), we observed a weak inverse association for vegetable fat intake; however, the trend was not statistically significant (P = 0.18) and was no longer apparent after adjustment for vitamin E. Animal fat intake was not associated with risk of biopsy-confirmed BBD. There was a nonsignificant positive association for monounsaturated fat intake, whereas saturated, polyunsaturated, and trans-unsaturated fat intakes were unrelated to risk. There were significant inverse associations for intakes of vitamin C, vitamin E, vitamin A, β-cryptoxanthin, fiber, and fruits and self-reported BBD; however, the actual risk reduction in the highest quartile of each of these was small, approximately 10% or less. For self-reported BBD confirmed by biopsy, some of the same inverse associations were apparent, but the inverse association for vitamin E was the only one that was statistically significant; the multivariate RRs were 0.94 (95% CI, 0.79–1.11), 0.88 (95% CI, 0.74–1.05), and 0.84 (95% CI, 0.70–1.00) for women in increasing quartiles of vitamin E intake (P for trend = 0.04).
Discussion
In this study, we observed that vitamin E and fiber intake during adolescence were inversely related to the incidence of proliferative BBD. Women in the highest quartiles of vitamin E and fiber intake had approximately 20% and 25% lower risk of proliferative BBD compared with women in the lowest quartiles, respectively. Polyunsaturated fat and vegetable fat intake (which are highly correlated with each other) were also inversely associated with risk of proliferative BBD. However, the associations between vitamin E and vegetable fat in relation to proliferative BBD were greatly attenuated after mutual adjustment for one another, making it difficult to determine which factor is responsible for the observed inverse associations. Monounsaturated fat intake during adolescence (derived mainly from animal sources such as beef, milk, and pork in this population) was positively associated with risk of proliferative BBD, whereas total fat, saturated fat, and trans-unsaturated fat intakes were unrelated to risk. The patterns for vitamin E, vegetable fat, monounsaturated fat, and fiber were still apparent when the study population was restricted to participants who reported having a mammogram or clinical breast exam within the previous 2 years (data not shown), suggesting that selective referral for biopsy and subsequent diagnosis of BBD based on adolescent diet is not a viable explanation for these results.
An important limitation of this study is the retrospective assessment of adolescent diet and the potential for recall bias: a diagnosis of BBD between 1991 and 1997 could have influenced participants’ recall or reporting of adolescent diet in 1998. If women diagnosed with BBD systematically over- or under-reported their consumption of certain foods during adolescence in comparison with women who did not develop BBD, this could bias our results. A nested case-control study in a similar but older population (27) examined the impact of recall bias by comparing observed associations between fat intake and breast cancer risk using prospective and retrospective diet assessments; the investigators found some differences in the direction and magnitude of observed associations based on the timing of the diet assessment. In this study, however, both diet assessments referred to a time period only a few years before the breast cancer diagnosis. A disease diagnosis may have a greater effect on recall of recent diet than on recall of diet in the remote past. Other studies have shown little or no difference between cancer cases and controls in the reliability of long-term recall (28, 29, 30). Furthermore, whereas the relationship between fat and breast cancer has been the focus of numerous epidemiological studies and has received substantial attention in the popular press, increasing the chance that participants would be aware of hypothesized associations, there has been little information about the association of diet with BBD in the scientific literature or popular press, making it less likely that recall bias could explain the findings of the present study.
A related issue is the influence of adult diet on recall of adolescent diet. If current diet is strongly correlated with recall of past diet and is related to risk of BBD, then current diet could confound observed associations between adolescent intake and BBD. However, as mentioned earlier, the average correlation between two separate recalls of foods consumed during high school in a similar population was much higher than the correlation between current consumption of those foods and the first recall of high school diet (22). Furthermore, women participating in the present study were younger than the women in the previous reproducibility study when they completed the high school diet questionnaire, which should lead to more accurate recall.
Recall bias and the influence of current diet on recall of adolescent diet may be particularly relevant to the findings for vitamin E. Although their clinical efficacy has not been proven, vitamin E supplements have been used to treat symptoms of BBD for a number of years (31, 32). Therefore, a greater proportion of women with a confirmed diagnosis or symptoms of BBD may be taking vitamin E supplements compared with women with no diagnosis or symptoms. If women with BBD who are currently taking vitamin supplements have a tendency to over-report their use of vitamin supplements in high school, this could bias the estimate of the association between adolescent vitamin E intake and proliferative BBD, making vitamin E look less protective. However, because the reported prevalence of multivitamin use during high school (15.7%) among women in the study was fairly low, and the correlation between adolescent vitamin E intake and adult vitamin E intake reported in 1991 (r = 0.12) was small, it is unlikely that this bias had an important impact on our results. Alternatively, if study participants were aware of a potential inverse association between vitamin E intake and BBD, it is possible that women with BBD may have under-reported their use of vitamin supplements during adolescence compared with noncases, which could induce a spurious inverse association between vitamin E and BBD. This type of biased recall is also unlikely, however, given that the hypothesized association between vitamin E intake and BBD has not been widely publicized and that supplements accounted for only slightly more than 1% of total vitamin E intake during adolescence among participants.
Another limitation of the study pertains to the comparability between actual and recalled adolescent diet. The validity of recall of adolescent diet 20–40 years later has not been established, and nondifferential misclassification of participants’ true consumption of foods and nutrients could bias associations toward the null. A study is currently being conducted to examine the reproducibility and validity of recall of adolescent diet in this cohort. The reproducibility study conducted in a similar cohort showed moderately high correlations between two separate recalls, 8 years apart, of consumption of 24 food items during adolescence (22). Studies that have examined the validity of recall of diet from the distant past in other populations have had mixed results (20, 28). Given the exploratory nature of this analysis and the absence of dietary data actually recorded during adolescence, however, recall of adolescent diet currently provides the best available information on diet during this time period. Future studies that collect data on childhood and adolescent diet prospectively are needed to confirm these findings.
Uncontrolled confounding is always a possibility in observational research. Although it is unlikely that adolescent diet is strongly correlated with adult risk factors for BBD, it may be associated with other early life and adolescent lifestyle exposures that affect risk of BBD and breast cancer (although few such exposures have been identified to date). To address this concern, we have presented age-adjusted results as well as results adjusted for age and time period, age at menarche, body mass index at age 18, alcohol intake between 18 and 22 years, multivitamin use during adolescence, family history of breast cancer, and menopausal status. The age-adjusted and multivariate RRs were very similar, suggesting that there is minimal confounding by these known risk factors for breast cancer. Although there may be some degree of confounding by other factors, it is unlikely that uncontrolled confounding could entirely account for our findings.
Many dietary factors were considered in this study, which may increase the probability of observing a falsely significant result simply due to chance. Because the comparisons of interest were specified before the data were examined, it was not necessary to make a uniform adjustment to the significance level (33). Readers should exercise caution, however, in the interpretation of the results, paying close attention to internal consistency, findings from other studies, and biological plausibility.
The similar findings for vegetable fat and vitamin E provide evidence for internal consistency; both vegetable fat and vitamin E intakes during adolescence were inversely associated with incidence of BBD, and vegetable oils are a major source of vitamin E. Other evidence for internal consistency comes from the analyses of food sources of nutrients. Although foods were not the primary focus of this study, the findings for the individual foods and food groups that were examined were generally consistent with the results from the nutrient analyses. For example, nuts contain vegetable fat, and nut consumption was inversely associated with incidence of proliferative BBD. Higher consumption of all meat and red meat were associated with increased risk of proliferative BBD, which is consistent with the positive associations for animal fat and monounsaturated fat. In addition to demonstrating internal consistency, the findings are compatible with those from a recent retrospective study in a similar cohort, in which higher consumption of vegetable fat and fiber during adolescence were related to lower breast cancer risk (21), and with those from a retrospective case-control study in British Columbia, in which consumption of vegetable oils in childhood was associated with reduced risk of premenopausal breast cancer (18).
Biological plausibility of the observed associations should also be considered in the interpretation of these findings. Fiber has been hypothesized to be related to lower breast cancer risk by decreasing circulating levels of estrogens, which stimulate proliferation of mammary cells. Fiber inhibits reabsorption of estrogens in the gastrointestinal tract (34) and has been associated with increased levels of sex-hormone binding globulin, which binds to estrogen and thereby reduces its bioavailability (35). Vitamin E has long been believed to be protective against the development of some cancers, including breast cancer, through its function as an antioxidant, neutralizing free radicals that can cause DNA damage and thereby inhibiting mutagenesis and cell transformation (7, 8). More recently, vitamin E has also been shown to induce apoptosis in vitro and to inhibit the growth of breast cancer cells in vitro and in vivo (36). The effects of these and other nutrients may be particularly important during adolescence because cells of the mammary gland are undergoing rapid development between menarche and first birth and, thus, may be vulnerable to malignant transformation (16, 17). Data from epidemiological studies on the relationship between intakes of vitamin E and fiber and breast cancer have yielded weak and inconsistent results (9, 37, 38, 39, 40, 41). Our results suggest that previous studies may have had null findings because they were focusing on diet during adulthood, which may not be the most relevant time period.
An important strength of this study is our definition of proliferative BBD. There is likely to be some misclassification in the reporting of BBD because BBD is a heterogeneous group of lesions and may be confused with other breast disorders. This misclassification could result in attenuation of the effect estimates. Restricting the outcome definition to cases for whom tissue samples were available and using a uniform, centralized pathology review to classify the cases as proliferative or nonproliferative reduces the likelihood of misclassification. A small study that was conducted to examine inter-rater reliability showed that the pathologists’ classification of the confirmed cases as proliferative or nonproliferative was highly reproducible.6 The decision to focus only on proliferative cases was based on evidence from a number of studies showing that proliferative lesions are associated with increased risk of breast cancer, whereas nonproliferative lesions do not confer any increase in risk (1). These findings suggest that proliferative BBD is the most etiologically relevant indicator of breast cancer risk.
In summary, this study examined the relationship between intakes of fats and micronutrients during adolescence and incidence of proliferative BBD. These results suggest that monounsaturated fat intake is positively associated with risk of proliferative BBD, whereas vegetable fat, vitamin E, and fiber intakes are inversely associated with risk. Confirmation of these associations may suggest a means for prevention of breast cancer.
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Grant support: Supported by NIH Grant CA50385 and United States Department of Defense Grant DAMD17-00-1-0165.
Requests for reprints: Heather J. Baer, Channing Laboratory, 181 Longwood Avenue, Boston, Massachusetts 02115. Phone: (617) 525-2101; Fax: (617) 525-2008; E-mail: [email protected]
The abbreviations used are: BBD, benign breast disease; FFQ, food frequency questionnaire; RR, rate ratio; CI, confidence interval.
Unpublished data.
. | Total fat quartileb . | . | Total vitamin A quartilec . | . | Total vitamin E quartilec . | . | Total vitamin C quartilec . | . | ||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
. | 1 (low) . | 4 (high) . | 1 (low) . | 4 (high) . | 1 (low) . | 4 (high) . | 1 (low) . | 4 (high) . | ||||
No. of women | 7658 | 7140 | 7474 | 7313 | 7340 | 7519 | 7358 | 7371 | ||||
Percentage of group | ||||||||||||
Family history of breast cancer in mother or sister(s) | 8 | 9 | 8 | 8 | 8 | 9 | 8 | 9 | ||||
Age at menarche < 12 yrs | 25 | 25 | 24 | 25 | 23 | 26 | 24 | 25 | ||||
Premenopausal in 1991 | 98 | 98 | 98 | 98 | 98 | 98 | 98 | 98 | ||||
Mean | ||||||||||||
Age in 1991 (yrs) | 34 | 37 | 35 | 36 | 37 | 35 | 36 | 35 | ||||
Alcohol intake between ages 18 and 22 (g/day) | 5 | 6 | 6 | 5 | 5 | 6 | 5 | 5 | ||||
BMI at age 18 (kg/m2) | 21 | 22 | 21 | 21 | 21 | 22 | 22 | 21 | ||||
Adolescent fat intake (% of energy) | 35 | 46 | 42 | 39 | 40 | 42 | 43 | 38 | ||||
Adolescent fiber intake (g/day, energy-adjusted) | 25 | 18 | 18 | 25 | 19 | 23 | 18 | 25 |
. | Total fat quartileb . | . | Total vitamin A quartilec . | . | Total vitamin E quartilec . | . | Total vitamin C quartilec . | . | ||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
. | 1 (low) . | 4 (high) . | 1 (low) . | 4 (high) . | 1 (low) . | 4 (high) . | 1 (low) . | 4 (high) . | ||||
No. of women | 7658 | 7140 | 7474 | 7313 | 7340 | 7519 | 7358 | 7371 | ||||
Percentage of group | ||||||||||||
Family history of breast cancer in mother or sister(s) | 8 | 9 | 8 | 8 | 8 | 9 | 8 | 9 | ||||
Age at menarche < 12 yrs | 25 | 25 | 24 | 25 | 23 | 26 | 24 | 25 | ||||
Premenopausal in 1991 | 98 | 98 | 98 | 98 | 98 | 98 | 98 | 98 | ||||
Mean | ||||||||||||
Age in 1991 (yrs) | 34 | 37 | 35 | 36 | 37 | 35 | 36 | 35 | ||||
Alcohol intake between ages 18 and 22 (g/day) | 5 | 6 | 6 | 5 | 5 | 6 | 5 | 5 | ||||
BMI at age 18 (kg/m2) | 21 | 22 | 21 | 21 | 21 | 22 | 22 | 21 | ||||
Adolescent fat intake (% of energy) | 35 | 46 | 42 | 39 | 40 | 42 | 43 | 38 | ||||
Adolescent fiber intake (g/day, energy-adjusted) | 25 | 18 | 18 | 25 | 19 | 23 | 18 | 25 |
Except for the data on mean age, all data shown are standardized to the age distribution of the cohort in 1991.
Quartile of percent calories from fat.
Quartile of energy-adjusted nutrient residuals.
. | Quartile of percentage of calories from fat . | . | . | . | P for trend . | |||
---|---|---|---|---|---|---|---|---|
. | 1 (low) . | 2 . | 3 . | 4 (high) . | . | |||
Total fat | ||||||||
Intake (% of energy)a | 35.6 | 39.4 | 42.1 | 45.5 | ||||
Cases of BBDb | 106 | 122 | 109 | 133 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.15 (0.89–1.49) | 1.01 (0.77–1.33) | 1.24 (0.95–1.61) | 0.22 | |||
Multivariatec | 1.00 (referent) | 1.10 (0.85–1.43) | 0.98 (0.75–1.29) | 1.17 (0.90–1.52) | 0.37 | |||
Animal fat | ||||||||
Intake (% of energy)a | 19.5 | 24.0 | 27.6 | 32.4 | ||||
Cases of BBDb | 94 | 121 | 119 | 136 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.26 (0.96–1.67) | 1.24 (0.92–1.67) | 1.55 (1.15–2.09) | 0.03 | |||
Multivariatec | 1.00 (referent) | 1.24 (0.94–1.63) | 1.16 (0.87–1.54) | 1.33 (1.00–1.78) | 0.08 | |||
Additional adjustment for vegetable fat | 1.00 (referent) | 1.18 (0.89–1.57) | 1.07 (0.79–1.45) | 1.19 (0.86–1.65) | 0.40 | |||
Vegetable fat | ||||||||
Intake (% of energy)a | 10.2 | 13.3 | 15.8 | 19.3 | ||||
Cases of BBDb | 136 | 120 | 121 | 93 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 0.88 (0.69–1.13) | 0.94 (0.74–1.21) | 0.69 (0.52–0.92) | 0.02 | |||
Multivariatec | 1.00 (referent) | 0.89 (0.70–1.14) | 0.92 (0.71–1.18) | 0.73 (0.55–0.96) | 0.04 | |||
Additional adjustment for animal fat | 1.00 (referent) | 0.91 (0.70–1.18) | 0.95 (0.72–1.25) | 0.77 (0.56–1.06) | 0.15 | |||
Saturated fat | ||||||||
Intake (% of energy)a | 13.3 | 15.2 | 16.8 | 18.9 | ||||
Cases of BBDb | 100 | 121 | 118 | 131 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.23 (0.94–1.60) | 1.12 (0.85–1.49) | 1.30 (0.98–1.72) | 0.12 | |||
Multivariatec | 1.00 (referent) | 1.15 (0.88–1.51) | 1.09 (0.83–1.44) | 1.19 (0.90–1.56) | 0.30 | |||
Additional adjustment for monounsaturated, polyunsaturated, and trans-unsaturated fats | 1.00 (referent) | 1.02 (0.76–1.37) | 0.88 (0.63–1.23) | 0.87 (0.59–1.27) | 0.36 | |||
Monounsaturated fat | ||||||||
Intake (% of energy)a | 12.6 | 14.1 | 15.1 | 16.5 | ||||
Cases of BBDb | 101 | 117 | 120 | 132 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.18 (0.90–1.54) | 1.23 (0.94–1.60) | 1.32 (1.01–1.72) | 0.04 | |||
Multivariatec | 1.00 (referent) | 1.15 (0.88–1.50) | 1.19 (0.91–1.56) | 1.28 (0.99–1.67) | 0.06 | |||
Additional adjustment for saturated, polyunsaturated, and trans-unsaturated fats | 1.00 (referent) | 1.21 (0.90–1.64) | 1.33 (0.95–1.85) | 1.52 (1.05–2.21) | 0.03 | |||
Polyunsaturated fat | ||||||||
Intake (% of energy)a | 5.2 | 6.1 | 6.9 | 8.1 | ||||
Cases of BBDb | 124 | 121 | 126 | 99 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.02 (0.79–1.30) | 1.04 (0.81–1.34) | 0.81 (0.62–1.06) | 0.22 | |||
Multivariatec | 1.00 (referent) | 1.00 (0.78–1.29) | 1.07 (0.83–1.38) | 0.81 (0.62–1.06) | 0.17 | |||
Additional adjustment for saturated, monounsaturated, and trans-unsaturated fats | 1.00 (referent) | 0.97 (0.75–1.25) | 1.00 (0.77–1.31) | 0.74 (0.55–1.00) | 0.06 | |||
Trans-unsaturated fat | ||||||||
Intake (% of energy)a | 1.6 | 2.0 | 2.5 | 3.2 | ||||
Cases of BBDb | 115 | 128 | 126 | 101 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.17 (0.90–1.50) | 1.13 (0.87–1.47) | 0.89 (0.67–1.67) | 0.48 | |||
Multivariatec | 1.00 (referent) | 1.18 (0.91–1.52) | 1.16 (0.90–1.51) | 0.92 (0.70–1.21) | 0.39 | |||
Additional adjustment for saturated, monounsaturated, and polyunsaturated fats | 1.00 (referent) | 1.17 (0.90–1.51) | 1.14 (0.87–1.50) | 0.91 (0.68–1.21) | 0.33 |
. | Quartile of percentage of calories from fat . | . | . | . | P for trend . | |||
---|---|---|---|---|---|---|---|---|
. | 1 (low) . | 2 . | 3 . | 4 (high) . | . | |||
Total fat | ||||||||
Intake (% of energy)a | 35.6 | 39.4 | 42.1 | 45.5 | ||||
Cases of BBDb | 106 | 122 | 109 | 133 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.15 (0.89–1.49) | 1.01 (0.77–1.33) | 1.24 (0.95–1.61) | 0.22 | |||
Multivariatec | 1.00 (referent) | 1.10 (0.85–1.43) | 0.98 (0.75–1.29) | 1.17 (0.90–1.52) | 0.37 | |||
Animal fat | ||||||||
Intake (% of energy)a | 19.5 | 24.0 | 27.6 | 32.4 | ||||
Cases of BBDb | 94 | 121 | 119 | 136 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.26 (0.96–1.67) | 1.24 (0.92–1.67) | 1.55 (1.15–2.09) | 0.03 | |||
Multivariatec | 1.00 (referent) | 1.24 (0.94–1.63) | 1.16 (0.87–1.54) | 1.33 (1.00–1.78) | 0.08 | |||
Additional adjustment for vegetable fat | 1.00 (referent) | 1.18 (0.89–1.57) | 1.07 (0.79–1.45) | 1.19 (0.86–1.65) | 0.40 | |||
Vegetable fat | ||||||||
Intake (% of energy)a | 10.2 | 13.3 | 15.8 | 19.3 | ||||
Cases of BBDb | 136 | 120 | 121 | 93 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 0.88 (0.69–1.13) | 0.94 (0.74–1.21) | 0.69 (0.52–0.92) | 0.02 | |||
Multivariatec | 1.00 (referent) | 0.89 (0.70–1.14) | 0.92 (0.71–1.18) | 0.73 (0.55–0.96) | 0.04 | |||
Additional adjustment for animal fat | 1.00 (referent) | 0.91 (0.70–1.18) | 0.95 (0.72–1.25) | 0.77 (0.56–1.06) | 0.15 | |||
Saturated fat | ||||||||
Intake (% of energy)a | 13.3 | 15.2 | 16.8 | 18.9 | ||||
Cases of BBDb | 100 | 121 | 118 | 131 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.23 (0.94–1.60) | 1.12 (0.85–1.49) | 1.30 (0.98–1.72) | 0.12 | |||
Multivariatec | 1.00 (referent) | 1.15 (0.88–1.51) | 1.09 (0.83–1.44) | 1.19 (0.90–1.56) | 0.30 | |||
Additional adjustment for monounsaturated, polyunsaturated, and trans-unsaturated fats | 1.00 (referent) | 1.02 (0.76–1.37) | 0.88 (0.63–1.23) | 0.87 (0.59–1.27) | 0.36 | |||
Monounsaturated fat | ||||||||
Intake (% of energy)a | 12.6 | 14.1 | 15.1 | 16.5 | ||||
Cases of BBDb | 101 | 117 | 120 | 132 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.18 (0.90–1.54) | 1.23 (0.94–1.60) | 1.32 (1.01–1.72) | 0.04 | |||
Multivariatec | 1.00 (referent) | 1.15 (0.88–1.50) | 1.19 (0.91–1.56) | 1.28 (0.99–1.67) | 0.06 | |||
Additional adjustment for saturated, polyunsaturated, and trans-unsaturated fats | 1.00 (referent) | 1.21 (0.90–1.64) | 1.33 (0.95–1.85) | 1.52 (1.05–2.21) | 0.03 | |||
Polyunsaturated fat | ||||||||
Intake (% of energy)a | 5.2 | 6.1 | 6.9 | 8.1 | ||||
Cases of BBDb | 124 | 121 | 126 | 99 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.02 (0.79–1.30) | 1.04 (0.81–1.34) | 0.81 (0.62–1.06) | 0.22 | |||
Multivariatec | 1.00 (referent) | 1.00 (0.78–1.29) | 1.07 (0.83–1.38) | 0.81 (0.62–1.06) | 0.17 | |||
Additional adjustment for saturated, monounsaturated, and trans-unsaturated fats | 1.00 (referent) | 0.97 (0.75–1.25) | 1.00 (0.77–1.31) | 0.74 (0.55–1.00) | 0.06 | |||
Trans-unsaturated fat | ||||||||
Intake (% of energy)a | 1.6 | 2.0 | 2.5 | 3.2 | ||||
Cases of BBDb | 115 | 128 | 126 | 101 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.17 (0.90–1.50) | 1.13 (0.87–1.47) | 0.89 (0.67–1.67) | 0.48 | |||
Multivariatec | 1.00 (referent) | 1.18 (0.91–1.52) | 1.16 (0.90–1.51) | 0.92 (0.70–1.21) | 0.39 | |||
Additional adjustment for saturated, monounsaturated, and polyunsaturated fats | 1.00 (referent) | 1.17 (0.90–1.51) | 1.14 (0.87–1.50) | 0.91 (0.68–1.21) | 0.33 |
Values for % of energy are medians of each quartile.
A total of 470 cases of proliferative BBD (with or without atypia) were diagnosed during the follow-up period.
The multivariate models are adjusted for the following: age in months, time period (3 periods), total energy intake (quartiles), age at menarche (<12, 12, 13, or ≥14 years), menopausal status (premenopausal, postmenopausal, or uncertain), body mass index at age 18 (<19, 19–20.4, 20.5–21.9, 22–24.9, or ≥25 kg/m2), history of breast cancer in mother or sister (yes/no), alcohol intake between ages 18 and 22 (0, <5, 5–14, or ≥15 g/day), and multivitamin use between ages 13 and 18 (yes/no).
. | Quartile of energy-adjusted micronutrient intake . | . | . | . | P for trend . | |||
---|---|---|---|---|---|---|---|---|
. | 1 (low) . | 2 . | 3 . | 4 (high) . | . | |||
Vitamin C (including supplements) | ||||||||
Intake (mg/day)a | 81 | 120 | 158 | 228 | ||||
Cases of BBDb | 126 | 131 | 104 | 109 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.03 (0.81–1.32) | 0.81 (0.53–1.05) | 0.87 (0.67–1.12) | 0.11 | |||
Multivariatec | 1.00 (referent) | 1.05 (0.82–1.34) | 0.82 (0.63–1.07) | 0.90 (0.68–1.18) | 0.24 | |||
Vitamin E (including supplements) | ||||||||
Intake (mg/day)a | 11 | 12 | 13 | 15 | ||||
Cases of BBDb | 128 | 137 | 108 | 97 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.11 (0.88–1.42) | 0.86 (0.66–1.11) | 0.76 (0.58–1.00) | 0.02 | |||
Multivariatec | 1.00 (referent) | 1.13 (0.89–1.44) | 0.88 (0.68–1.14) | 0.79 (0.61–1.04) | 0.05 | |||
Vitamin A (including supplements) | ||||||||
Intake (IU/day)a | 6316 | 9399 | 12771 | 19634 | ||||
Cases of BBDb | 121 | 142 | 108 | 99 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.18 (0.92–1.50) | 0.91 (0.70–1.18) | 0.81 (0.62–1.06) | 0.04 | |||
Multivariatec | 1.00 (referent) | 1.17 (0.91–1.49) | 0.92 (0.71–1.20) | 0.84 (0.64–1.11) | 0.07 | |||
Retinol | ||||||||
Intake (IU/day)a | 1486 | 2023 | 2697 | 5145 | ||||
Cases of BBDb | 112 | 129 | 128 | 101 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.19 (0.92–1.53) | 1.17 (0.91–1.51) | 0.94 (0.72–1.23) | 0.72 | |||
Multivariatec | 1.00 (referent) | 1.21 (0.93–1.56) | 1.21 (0.94–1.57) | 0.99 (0.72–1.38) | 0.71 | |||
Total carotenoids | ||||||||
Intake (IU/day)a | 4012 | 6622 | 9466 | 16228 | ||||
Cases of BBDb | 120 | 129 | 117 | 104 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.08 (0.84–1.38) | 0.98 (0.76–1.26) | 0.85 (0.65–1.10) | 0.17 | |||
Multivariatec | 1.00 (referent) | 1.07 (0.83–1.37) | 0.96 (0.74–1.25) | 0.87 (0.67–1.14) | 0.19 | |||
α-Carotene | ||||||||
Intake (mcg/day)a | 353 | 694 | 1074 | 2105 | ||||
Cases of BBDb | 114 | 123 | 127 | 106 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.08 (0.84–1.40) | 1.11 (0.86–1.43) | 0.91 (0.70–1.19) | 0.58 | |||
Multivariatec | 1.00 (referent) | 1.07 (0.83–1.39) | 1.09 (0.85–1.41) | 0.93 (0.71–1.22) | 0.44 | |||
β-Carotene | ||||||||
Intake (mcg/day)a | 1753 | 2814 | 3952 | 6252 | ||||
Cases of BBDb | 123 | 127 | 113 | 107 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.04 (0.81–1.33) | 0.92 (0.72–1.19) | 0.87 (0.67–1.12) | 0.18 | |||
Multivariatec | 1.00 (referent) | 1.04 (0.81–1.33) | 0.92 (0.71–1.19) | 0.88 (0.68–1.15) | 0.24 | |||
β-Cryptoxanthin | ||||||||
Intake (mcg/day)a | 63 | 122 | 189 | 287 | ||||
Cases of BBDb | 111 | 130 | 114 | 115 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.15 (0.89–1.48) | 1.01 (0.78–1.31) | 1.02 (0.79–1.33) | 0.87 | |||
Multivariatec | 1.00 (referent) | 1.17 (0.90–1.51) | 1.02 (0.78–1.33) | 1.04 (0.80–1.36) | 0.92 | |||
Lycopene | ||||||||
Intake (mcg/day)a | 3604 | 5190 | 7152 | 12119 | ||||
Cases of BBDb | 110 | 124 | 136 | 100 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.15 (0.89–1.48) | 1.26 (0.98–1.62) | 0.95 (0.73–1.25) | 0.98 | |||
Multivariatec | 1.00 (referent) | 1.16 (0.90–1.51) | 1.31 (1.01–1.69) | 0.97 (0.74–1.27) | 0.56 | |||
Lutein & zeaxanthin | ||||||||
Intake (mcg/day)a | 1022 | 1674 | 2387 | 3841 | ||||
Cases of BBDb | 125 | 108 | 130 | 107 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 0.88 (0.68–1.13) | 1.05 (0.82–1.34) | 0.88 (0.68–1.14) | 0.58 | |||
Multivariatec | 1.00 (referent) | 0.86 (0.66–1.11) | 1.04 (0.82–1.33) | 0.88 (0.68–1.14) | 0.57 | |||
Folate | ||||||||
Intake (mcg/day)a | 233 | 286 | 333 | 421 | ||||
Cases of BBDb | 122 | 127 | 114 | 107 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.05 (0.82–1.35) | 0.95 (0.74–1.22) | 0.95 (0.73–1.23) | 0.43 | |||
Multivariatec | 1.00 (referent) | 1.07 (0.83–1.38) | 0.97 (0.75–1.26) | 1.00 (0.76–1.31) | 0.84 |
. | Quartile of energy-adjusted micronutrient intake . | . | . | . | P for trend . | |||
---|---|---|---|---|---|---|---|---|
. | 1 (low) . | 2 . | 3 . | 4 (high) . | . | |||
Vitamin C (including supplements) | ||||||||
Intake (mg/day)a | 81 | 120 | 158 | 228 | ||||
Cases of BBDb | 126 | 131 | 104 | 109 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.03 (0.81–1.32) | 0.81 (0.53–1.05) | 0.87 (0.67–1.12) | 0.11 | |||
Multivariatec | 1.00 (referent) | 1.05 (0.82–1.34) | 0.82 (0.63–1.07) | 0.90 (0.68–1.18) | 0.24 | |||
Vitamin E (including supplements) | ||||||||
Intake (mg/day)a | 11 | 12 | 13 | 15 | ||||
Cases of BBDb | 128 | 137 | 108 | 97 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.11 (0.88–1.42) | 0.86 (0.66–1.11) | 0.76 (0.58–1.00) | 0.02 | |||
Multivariatec | 1.00 (referent) | 1.13 (0.89–1.44) | 0.88 (0.68–1.14) | 0.79 (0.61–1.04) | 0.05 | |||
Vitamin A (including supplements) | ||||||||
Intake (IU/day)a | 6316 | 9399 | 12771 | 19634 | ||||
Cases of BBDb | 121 | 142 | 108 | 99 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.18 (0.92–1.50) | 0.91 (0.70–1.18) | 0.81 (0.62–1.06) | 0.04 | |||
Multivariatec | 1.00 (referent) | 1.17 (0.91–1.49) | 0.92 (0.71–1.20) | 0.84 (0.64–1.11) | 0.07 | |||
Retinol | ||||||||
Intake (IU/day)a | 1486 | 2023 | 2697 | 5145 | ||||
Cases of BBDb | 112 | 129 | 128 | 101 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.19 (0.92–1.53) | 1.17 (0.91–1.51) | 0.94 (0.72–1.23) | 0.72 | |||
Multivariatec | 1.00 (referent) | 1.21 (0.93–1.56) | 1.21 (0.94–1.57) | 0.99 (0.72–1.38) | 0.71 | |||
Total carotenoids | ||||||||
Intake (IU/day)a | 4012 | 6622 | 9466 | 16228 | ||||
Cases of BBDb | 120 | 129 | 117 | 104 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.08 (0.84–1.38) | 0.98 (0.76–1.26) | 0.85 (0.65–1.10) | 0.17 | |||
Multivariatec | 1.00 (referent) | 1.07 (0.83–1.37) | 0.96 (0.74–1.25) | 0.87 (0.67–1.14) | 0.19 | |||
α-Carotene | ||||||||
Intake (mcg/day)a | 353 | 694 | 1074 | 2105 | ||||
Cases of BBDb | 114 | 123 | 127 | 106 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.08 (0.84–1.40) | 1.11 (0.86–1.43) | 0.91 (0.70–1.19) | 0.58 | |||
Multivariatec | 1.00 (referent) | 1.07 (0.83–1.39) | 1.09 (0.85–1.41) | 0.93 (0.71–1.22) | 0.44 | |||
β-Carotene | ||||||||
Intake (mcg/day)a | 1753 | 2814 | 3952 | 6252 | ||||
Cases of BBDb | 123 | 127 | 113 | 107 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.04 (0.81–1.33) | 0.92 (0.72–1.19) | 0.87 (0.67–1.12) | 0.18 | |||
Multivariatec | 1.00 (referent) | 1.04 (0.81–1.33) | 0.92 (0.71–1.19) | 0.88 (0.68–1.15) | 0.24 | |||
β-Cryptoxanthin | ||||||||
Intake (mcg/day)a | 63 | 122 | 189 | 287 | ||||
Cases of BBDb | 111 | 130 | 114 | 115 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.15 (0.89–1.48) | 1.01 (0.78–1.31) | 1.02 (0.79–1.33) | 0.87 | |||
Multivariatec | 1.00 (referent) | 1.17 (0.90–1.51) | 1.02 (0.78–1.33) | 1.04 (0.80–1.36) | 0.92 | |||
Lycopene | ||||||||
Intake (mcg/day)a | 3604 | 5190 | 7152 | 12119 | ||||
Cases of BBDb | 110 | 124 | 136 | 100 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.15 (0.89–1.48) | 1.26 (0.98–1.62) | 0.95 (0.73–1.25) | 0.98 | |||
Multivariatec | 1.00 (referent) | 1.16 (0.90–1.51) | 1.31 (1.01–1.69) | 0.97 (0.74–1.27) | 0.56 | |||
Lutein & zeaxanthin | ||||||||
Intake (mcg/day)a | 1022 | 1674 | 2387 | 3841 | ||||
Cases of BBDb | 125 | 108 | 130 | 107 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 0.88 (0.68–1.13) | 1.05 (0.82–1.34) | 0.88 (0.68–1.14) | 0.58 | |||
Multivariatec | 1.00 (referent) | 0.86 (0.66–1.11) | 1.04 (0.82–1.33) | 0.88 (0.68–1.14) | 0.57 | |||
Folate | ||||||||
Intake (mcg/day)a | 233 | 286 | 333 | 421 | ||||
Cases of BBDb | 122 | 127 | 114 | 107 | ||||
RR (95% CI) | ||||||||
Age-adjusted | 1.00 (referent) | 1.05 (0.82–1.35) | 0.95 (0.74–1.22) | 0.95 (0.73–1.23) | 0.43 | |||
Multivariatec | 1.00 (referent) | 1.07 (0.83–1.38) | 0.97 (0.75–1.26) | 1.00 (0.76–1.31) | 0.84 |
Values for intake are medians of each quartile, adjusted for total energy intake using the residual method.
A total of 470 cases of histologically confirmed proliferative BBD occurred during the follow-up period.
The multivariate models are adjusted for the following: age in months, time period (3 periods), total energy intake (quartiles), age at menarche (<12, 12, 13, or ≥14 years), menopausal status (premenopausal, postmenopausal, or uncertain), body mass index at age 18 (<19, 19–20.4, 20.5–21.9, 22–24.9, or ≥25 kg/m2), history of breast cancer in mother or sister (yes/no), alcohol intake between ages 18 and 22 (0, <5, 5–14, or ≥15 g/day), and multivitamin use between ages 13 and 18 (yes/no).
. | Cases of BBDa . | Age-adjusted RR . | Multivariate RRb . |
---|---|---|---|
Fiber (g/day, energy-adjusted) | |||
Quartile 1 (lowest) | 133 | 1.00 (referent) | 1.00 (referent) |
Quartile 2 | 118 | 0.91 (0.71–1.17) | 0.94 (0.73–1.21) |
Quartile 3 | 127 | 0.96 (0.75–1.22) | 0.99 (0.78–1.27) |
Quartile 4 (highest) | 92 | 0.71 (0.54–0.92) | 0.75 (0.57–0.98) |
P for trend | 0.03 | 0.05 | |
Fruits (servings/day) | |||
<1 | 92 | 1.00 (referent) | 1.00 (referent) |
1.0–1.9 | 150 | 0.97 (0.74–1.25) | 0.95 (0.73–1.23) |
2.0–2.9 | 128 | 0.97 (0.74–1.27) | 0.96 (0.73–1.27) |
≥3 | 100 | 0.84 (0.64–1.12) | 0.85 (0.63–1.16) |
P for trend | 0.25 | 0.34 | |
Vegetables (servings/day) | |||
<2 | 157 | 1.00 (referent) | 1.00 (referent) |
2.0–2.9 | 138 | 1.02 (0.81–1.28) | 1.02 (0.81–1.29) |
3.0–3.9 | 99 | 1.15 (0.89–1.48) | 1.17 (0.90–1.52) |
≥4 | 76 | 0.93 (0.71–1.23) | 0.97 (0.72–1.30) |
P for trend | 0.96 | 0.91 | |
Fruits and vegetables combined (servings/day) | |||
<3 | 93 | 1.00 (referent) | 1.00 (referent) |
3.0–3.9 | 88 | 1.11 (0.83–1.48) | 1.10 (0.82–1.48) |
4.0–4.9 | 96 | 1.23 (0.92–1.63) | 1.23 (0.92–1.65) |
5.0–5.9 | 70 | 1.11 (0.82–1.52) | 1.12 (0.81–1.55) |
≥6 | 123 | 0.97 (0.74–1.27) | 1.00 (0.74–1.35) |
P for trend | 0.66 | 0.77 |
. | Cases of BBDa . | Age-adjusted RR . | Multivariate RRb . |
---|---|---|---|
Fiber (g/day, energy-adjusted) | |||
Quartile 1 (lowest) | 133 | 1.00 (referent) | 1.00 (referent) |
Quartile 2 | 118 | 0.91 (0.71–1.17) | 0.94 (0.73–1.21) |
Quartile 3 | 127 | 0.96 (0.75–1.22) | 0.99 (0.78–1.27) |
Quartile 4 (highest) | 92 | 0.71 (0.54–0.92) | 0.75 (0.57–0.98) |
P for trend | 0.03 | 0.05 | |
Fruits (servings/day) | |||
<1 | 92 | 1.00 (referent) | 1.00 (referent) |
1.0–1.9 | 150 | 0.97 (0.74–1.25) | 0.95 (0.73–1.23) |
2.0–2.9 | 128 | 0.97 (0.74–1.27) | 0.96 (0.73–1.27) |
≥3 | 100 | 0.84 (0.64–1.12) | 0.85 (0.63–1.16) |
P for trend | 0.25 | 0.34 | |
Vegetables (servings/day) | |||
<2 | 157 | 1.00 (referent) | 1.00 (referent) |
2.0–2.9 | 138 | 1.02 (0.81–1.28) | 1.02 (0.81–1.29) |
3.0–3.9 | 99 | 1.15 (0.89–1.48) | 1.17 (0.90–1.52) |
≥4 | 76 | 0.93 (0.71–1.23) | 0.97 (0.72–1.30) |
P for trend | 0.96 | 0.91 | |
Fruits and vegetables combined (servings/day) | |||
<3 | 93 | 1.00 (referent) | 1.00 (referent) |
3.0–3.9 | 88 | 1.11 (0.83–1.48) | 1.10 (0.82–1.48) |
4.0–4.9 | 96 | 1.23 (0.92–1.63) | 1.23 (0.92–1.65) |
5.0–5.9 | 70 | 1.11 (0.82–1.52) | 1.12 (0.81–1.55) |
≥6 | 123 | 0.97 (0.74–1.27) | 1.00 (0.74–1.35) |
P for trend | 0.66 | 0.77 |
A total of 470 cases of histologically confirmed proliferative BBD occurred during the follow-up period.
The multivariate models are adjusted for the following: age in months, time period (3 periods), total energy intake (quartiles), age at menarche (<12, 12, 13, or ≥14 years), menopausal status (premenopausal, postmenopausal, or uncertain), body mass index at age 18 (<19, 19–20.4, 20.5–21.9, 22–24.9, or ≥25 kg/m2), history of breast cancer in mother or sister (yes/no), alcohol intake between ages 18 and 22 (0, <5, 5–14, or ≥15 g/day), and multivitamin use between ages 13 and 18 (yes/no).
Acknowledgments
We thank the participants of the Nurses’ Health Study II for their dedication to this study, Drs. Timothy Jacobs and Gloria Peiro for assistance with classifying the biopsies for the BBD cases, and Sue Malspeis for technical support.