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Am J Epidemiol. 2010 January 15; 171(2): 221–232.
Published online 2009 December 2. doi:  10.1093/aje/kwp355
PMCID: PMC2800240

A Prospective Study of Dairy Intake and Risk of Uterine Leiomyomata

Abstract

Rates of uterine leiomyomata are 2–3 times higher among black women than white women. Dietary factors that differ in prevalence between these populations that could contribute to the disparity include dairy intake. During 1997–2007, the authors followed 22,120 premenopausal US Black Women's Health Study participants to assess dairy intake in relation to uterine leiomyomata risk. Because soy may be substituted for dairy, the effect of soy intake was also evaluated. Diet was estimated by using food frequency questionnaires in 1995 and 2001. Incidence rate ratios and 95% confidence intervals were estimated with Cox regression. There were 5,871 incident cases of uterine leiomyomata diagnosed by ultrasound (n = 3,964) or surgery (n = 1,907). Multivariable incidence rate ratios comparing 1, 2, 3, and ≥4 servings/day with <1 serving/day of total dairy were 0.94 (95% confidence interval (CI): 0.88, 1.00), 0.87 (95% CI: 0.78, 0.98), 0.84 (95% CI: 0.70, 1.01), and 0.70 (95% CI: 0.58, 0.86), respectively (P-trend <0.001). Incidence rate ratios comparing the highest (≥2 servings/day) with the lowest (<1 serving/week) intake categories were 0.81 (95% CI: 0.66, 0.99) for high-fat dairy, 0.80 (95% CI: 0.70, 0.91) for low-fat dairy, and 0.78 (95% CI: 0.68, 0.89) for milk. Soy intake was unrelated to uterine leiomyomata risk. This large prospective study of black women provides the first epidemiologic evidence of reduced uterine leiomyomata risk associated with dairy consumption.

Keywords: African Americans, dairy products, leiomyoma, prospective studies, soy foods

Uterine leiomyomata, benign neoplasms of the myometrium (13), are the primary indication for hysterectomy (4, 5) in the United States and account for $2.2 billion annually in health care costs (6). Although the pathogenesis of uterine leiomyomata is poorly understood, steroid hormones (7, 8) and growth factors (9) are thought to play a role. The incidence of uterine leiomyomata is 2–3 times higher in black women than white women (4, 1012), but risk factors such as reproductive history and obesity do not explain the racial disparity (10, 1315). Dietary factors are of interest because of their antioxidant effects and their ability to modify endogenous hormones. However, there has been little study of dietary factors that differ in prevalence between black women and white women that could contribute to the uterine leiomyomata disparity, such as dairy intake (1619).

National surveys show that black Americans consume fewer mean daily servings of dairy foods than white Americans do, and they have lower mean intakes of calcium, magnesium, and phosphorus (20). Specifically, mean daily dairy intake for black Americans is approximately 60% that for white Americans, and most of this difference is attributable to lower intake of reduced-fat or skim milk, with whole-milk intake being higher for black Americans (21). Black Americans are also less likely to take vitamin and mineral supplements (22, 23). Dairy foods have antitumorigenic components, including calcium, vitamin D (24), butyric acid (25), branched-chain fatty acids (25), and milk proteins (25). Conversely, milk contains estrogens and progesterone (26, 27), and high-fat dairy products in the United States contain fat-soluble hormones and growth factors (28) that may increase risk of hormone-dependent neoplasms.

To our knowledge, the only study that has examined dairy intake and uterine leiomyomata risk, a case-control study of Italian women (17, 18), found no association with milk or cheese consumption. Studies of other hormone-responsive conditions, such as breast and endometrial cancers, have produced mixed results. While earlier case-control and cohort studies of dairy intake and breast cancer have yielded conflicting findings (29), some (3033) but not all (3436) prospective studies have reported inverse associations between dairy intake and breast cancer, particularly among premenopausal women (3133). In a meta-analysis, the pooled odds ratio for a one-serving increase in dairy intake associated with endometrial cancer was 0.97 (95% confidence interval (CI): 0.93, 1.01), but results varied across studies (37).

We prospectively evaluated the relation of dairy intake and some of its components—calcium, phosphorus, vitamin D, and butyric acid—to risk of uterine leiomyomata in the Black Women's Health Study, a large US prospective cohort study. Because black women experience a higher prevalence of lactose maldigestion than white women do (38, 39) and may substitute soy products for dairy, we also assessed the association of soy foods with uterine leiomyomata risk.

MATERIALS AND METHODS

Study population

The Black Women's Health Study is a national prospective cohort study of 59,000 African-American women aged 21–69 years (40). In 1995, participants enrolled by completing self-administered questionnaires mailed primarily to subscribers of Essence magazine. Questionnaires are mailed biennially to update exposures and identify new illnesses. Cohort retention exceeded 80% through 2007. The institutional review board of Boston University Medical Center approved the study protocol.

Assessment of outcome

On the 1999 and 2001 follow-up questionnaires, women were asked whether they had been diagnosed with “uterine fibroids” in the previous 2-year interval, the calendar year in which they were first diagnosed, and whether their diagnosis was confirmed by “pelvic examination” and/or by “ultrasound/hysterectomy.” On the 2003, 2005, and 2007 follow-up questionnaires, we changed “hysterectomy” to “surgery (e.g., hysterectomy)” to capture data on women who had other surgeries, and we divided “ultrasound” and “surgery” into separate questions. Cases were classified as “surgically confirmed” if they reported diagnosis by “surgery” on the 2003 or later questionnaires or if they reported diagnosis by “ultrasound/hysterectomy” and “hysterectomy” under a separate question in 1999 or 2001.

Ultrasound, the standard procedure used to confirm diagnoses in clinical practice (3), has high sensitivity (99%) and specificity (91%) relative to histologic evidence (41, 42). We used an expanded outcome definition that includes cases diagnosed by surgery and ultrasound because surgically confirmed cases represent only 10%–30% of cases for whom ultrasound is available and because studies of such cases may spuriously identify risk factors associated with severity or treatment preference (43). To maximize the specificity of uterine leiomyomata classification, pelvic examination cases (n = 505) were treated as noncases because these diagnoses could have represented other gynecologic pathology (44).

Assessment of diet

Diet was assessed in 2 questionnaire cycles (1995 and 2001) by using a modified version of the National Cancer Institute–Block short-form food frequency questionnaire (FFQ) (45, 46). In 1995, a 68-item FFQ was used to collect data on the consumption of specified foods during the previous year, with frequencies ranging from “never or <1 per month” to “≥2 per day” and portion sizes of “small,” “medium,” or “large” (46). Beverage frequencies ranged from “never or <1 per month” to “≥6 per day.” The 2001 FFQ added several items and an extra portion size (“super size”).

The FFQ provided data on specific foods, fat, protein, carbohydrate, vitamins, minerals, fiber, and total energy intake. For the 1995 FFQ, values for calcium, phosphorus, and other nutrients were calculated by using DIETSYS software (version 4.01) (45). Software for the 2001 FFQ (DIETCALC version 1.4.1; National Cancer Institute, Rockville, Maryland) provided estimates for calcium, phosphorus, vitamin D, and individual fatty acids. In 1995, participants reported their use of multivitamins, calcium supplements, and calcium with vitamin D supplements in the past year. Multivitamin use was updated on all follow-up questionnaires, whereas use of calcium and calcium with vitamin D supplements was updated in 1997 only.

The dairy group included skim milk/1% milk/buttermilk, 2% milk, whole milk, milk/cream in coffee or tea, ice cream (1995), regular ice cream (2001), low-fat ice cream (2001), frozen yogurt, yogurt, cheese and cheese spreads (not cottage cheese), and butter. Total dairy intake was calculated by summing servings of all dairy foods except butter because it is composed almost entirely of fat. Low-fat dairy intake was calculated by summing servings of skim/low-fat milk, yogurt, and low-fat ice cream (2001). High-fat dairy intake was calculated by summing servings of whole milk, milk/cream in coffee or tea, regular ice cream (2001), and cheese and cheese spreads (not cottage cheese). The 1995 FFQ included “ice cream” as a single line item. Therefore, we classified women into “regular” and “low-fat” categories based on their response to the question, When you eat the following foods, how often do you eat a low-fat or nonfat version of that food? (always = 100% regular, sometimes = 50% each type, rarely = 100% low fat). Total soy intake, assessed on the 2001 FFQ only, was estimated by summing the servings of soy milk, tofu, and soy and soy/veggie burgers.

Assessment of covariates

On the baseline survey, we collected data on age at menarche, oral contraceptive use, parity, age at each birth, height, weight, alcohol intake, smoking, education, marital status, occupation, and geographic region. We asked about household income in 2003 and about recency of pelvic examination and ultrasound screening in 2007. Reproductive factors, weight, smoking, marital status, and region were updated on follow-up questionnaires and were modeled as time-varying covariates in analysis.

Validation studies

Uterine leiomyomata.

We assessed the accuracy of self-report in a random sample of 248 cases diagnosed by ultrasound or surgery. Cases were mailed supplemental surveys regarding their initial date of diagnosis, method(s) of confirmation, symptoms, and treatment and were asked for permission to review their medical records. We obtained medical records from 127 of the 128 women who gave us permission and confirmed the self-report for 122 (96%). Among the 188 (76%) who provided supplemental survey data, 71% reported uterine leiomyomata–related symptoms prior to diagnosis and 87% reported that their condition came to clinical attention because they sought treatment for symptoms or because a tumor was palpable during a routine pelvic examination. There were no appreciable differences between cases who did and did not release medical records with respect to risk factors for uterine leiomyomata (47).

Diet.

A validation study of the 1995 FFQ was conducted in 1996–1998 (46). Approximately 400 Black Women's Health Study participants provided 3 nonconsecutive 24-hour telephone recall interviews and one 3-day food record over a 1-year period. Energy-adjusted and deattenuated Pearson correlations comparing nutrient estimates from the FFQ with averages from the combined recall/record data ranged from 0.5 to 0.8 (46). The correlation for calcium comparing FFQ with combined recall/record data was 0.6 (95% CI: 0.2, 0.9). In separate analyses, food group servings were compared with those estimated from the average of 3 dietary recalls (48). Mean servings per day for the “dairy” group were 1.0 (standard deviation, 1.3) for the FFQ and 1.1 (standard deviation, 1.0) for the dietary recalls.

Restriction criteria

Follow-up began in 1997 because method of uterine leiomyomata diagnosis was first included on the 1999 questionnaire. Of the 53,153 respondents to the 1997 questionnaire, we excluded postmenopausal women (n = 16,594) in whom uterine leiomyomata are rare (3); women with a history of uterine leiomyomata (n = 10,626); women lost to follow-up after 1997 (n = 980); cases without data on diagnosis year (n = 125) or method (n = 120); and women with missing covariate data (n = 582), implausible energy intakes (<500 or ≥3,800 kcal/day), or 10 or more missing items on the baseline FFQ (n = 2,006), leaving 22,120 women followed up from 1997 through 2007. Those excluded were less educated than those included, but they were similar with respect to parity, age at menarche, and other uterine leiomyomata risk factors.

Data analysis

Cases were women who reported a first diagnosis of uterine leiomyomata confirmed by ultrasound or surgery. Person-years were calculated from March 1997 until uterine leiomyomata diagnosis, menopause, death, loss to follow-up, or March 2007 (end of follow-up), whichever occurred first. Age- and period-stratified Cox regression was used to estimate incidence rate ratios and 95% confidence intervals for the associations of interest.

Foods were categorized on the basis of their frequency distributions within the analytic sample. Nutrients were categorized into quintiles after adjustment for total energy intake by using the nutrient residual method (49). Because the average of 2 or more FFQs may provide a more valid assessment of long-term dietary intake (50), we assessed 1995 diet in relation to uterine leiomyomata diagnosed through 2001 (1997–2001) and the average of 1995 and 2001 FFQs in relation to uterine leiomyomata diagnosed through 2007 (2001–2007). Participants with missing or implausible data for the 2001 FFQ (n = 6,563) were assigned their 1995 FFQ data for 1997–2007.

A covariate was included in multivariable analyses if it was either an established risk factor for uterine leiomyomata (based on the literature) or a potential risk factor for uterine leiomyomata associated with exposure at baseline (Table 1). On the basis of these criteria, we constructed 2 sets of multivariable models: one that controlled for age (1-year intervals), time period (1997–1999, 1999–2001, 2001–2003, 2003–2005, 2005–2007), and energy intake (quintiles); and one that additionally controlled for reproductive and hormonal factors (51), including age at menarche (years), parity (0, ≥1 births), age at first birth (years), years since last birth (<5, 5–9, 10–14, 15–19, ≥20), oral contraceptive use (ever, never), and age at first oral contraceptive use (years), as well as the following lifestyle and socioeconomic factors (5254): body mass index (<20, 20–24, 25–29, 30–34, ≥35 kg/m2), vigorous exercise (hours/week), smoking (current, past, never), current alcohol intake (<1, 1–6, ≥7 drinks/week), education (≤12, 13–15, 16, ≥17 years), marital status (married/partnered, divorced/separated/widowed, single), occupation (white collar, non-white-collar, unemployed, missing), household income (≤$25,000, $25,001–50,000, $50,001–100,000, >$100,000, missing), geographic region (South, Northeast, Midwest, and West), and diabetes (no, yes).

Table 1.
Characteristics of 22,120 Participants According to Dairy and Soy Intake, Black Women's Health Study, United States, 1997–2007a

Tests for trend were conducted by modeling a continuous version of the exposure variable assigned the median value of each category (55). To examine whether diet–uterine leiomyomata associations were modified by body mass index (<25, 25–29, ≥30 kg/m2), total fat intake (tertiles), education (<16, ≥16 years), income (≤$50,000, >$50,000), or use of multivitamins and other supplements, we stratified by these factors. P values from interaction tests were obtained by using the likelihood ratio test comparing models with and without cross-product terms between the covariate and dietary factor. Departures from proportional hazards were evaluated in the same manner by using cross-product terms between each dietary factor and age (<35, ≥35 years) and time period (1997–2001, 2001–2007). Analyses were performed with SAS statistical software, version 9.1 (56).

RESULTS

Sample characteristics according to dairy and soy intake are shown in Table 1. High-fat dairy intake was positively associated with current smoking, non-white-collar occupations, energy intake, parity, and living in the Northeast and was inversely associated with exercise and income. Low-fat dairy intake was positively associated with body mass index, exercise, education, diabetes, supplement use, energy intake, and living in the Midwest and was inversely associated with current smoking and living in the South. Soy intake was positively associated with exercise, education, income, supplement use, and living in the Northeast and West and was inversely associated with body mass index, parity, diabetes, and living in the Midwest. Soy intake was inversely associated with high-fat dairy and positively associated with low-fat dairy intake.

During 164,358 person-years, 5,871 incident cases of uterine leiomyomata diagnosed by ultrasound (n = 3,964) or surgery (n = 1,907) were reported. Dairy intake was inversely associated with uterine leiomyomata risk (Table 2). Multivariable incidence rate ratios comparing 1, 2, 3, and ≥4 servings/day with <1 serving/day of total dairy were 0.94 (95% CI: 0.88, 1.00), 0.87 (95% CI: 0.78, 0.98), 0.84 (95% CI: 0.70, 1.01), and 0.70 (95% CI: 0.58, 0.86), respectively (P-trend <0.001). Multivariable incidence rate ratios comparing the highest with lowest intake categories of high-fat and low-fat dairy were nearly identical. Further control for total dairy intake in each of these models (to estimate the effect of substituting high-fat for low-fat dairy, and vice versa) attenuated the dairy-specific incidence rate ratios (data not shown), suggesting that any dairy food, regardless of fat content, was protective. Inclusion of butter as a high-fat dairy food made little difference in the incidence rate ratios (data not shown).

Table 2.
Risk of Uterine Leiomyomata in Relation to Dairy Food Intake, Black Women's Health Study, United States, 1997–2007

Milk accounted for 49% of mean total dairy consumption. Milk intake was inversely associated with uterine leiomyomata risk (≥14 vs. <1 serving/week: incidence rate ratio (IRR) = 0.78, 95% CI: 0.68, 0.89; P-trend <0.0001), and associations were similar for high-fat and low-fat milk. Intakes of cheese, ice cream, and butter were not materially associated with uterine leiomyomata, but yogurt showed a weak inverse association (Table 2). Soy intake was not associated with uterine leiomyomata with or without adjustment for total dairy (Table 3).

Table 3.
Risk of Uterine Leiomyomata in Relation to Soy Food Intake, Black Women's Health Study, United States, 2001–2007

We examined vitamins, minerals, and fatty acids commonly found in dairy foods, including calcium, phosphorus, vitamin D, and butyric acid (Tables 4 and and5).5). Incidence rate ratios comparing the highest with the lowest quintiles of dietary calcium and phosphorus were 0.93 and 0.96, respectively, before adjustment for total dairy intake (Table 4). The association between uterine leiomyomata and calcium-to-phosphorus ratio, a measure of bioavailable calcium, was stronger than for each of these nutrients alone (IRR = 0.88, 95% CI: 0.81, 0.96; P-trend <0.001). Control for total dairy intake attenuated the incidence rate ratios for each of these nutrients. Dietary vitamin D was not associated with uterine leiomyomata risk (Table 5). Butyric acid, a fatty acid found predominantly in high-fat dairy foods, was inversely associated with uterine leiomyomata before adjustment for total dairy intake.

Table 4.
Risk of Uterine Leiomyomata in Relation to Dietary Calcium and Phosphorus Intake, Black Women's Health Study, United States, 1997–2007
Table 5.
Risk of Uterine Leiomyomata in Relation to Dietary Vitamin D and Butyric Acid Intake, Black Women's Health Study, United States, 2001–2007

In multivariable models without dietary factors, incidence rate ratios for calcium supplements, calcium with vitamin D, and multivitamins were all close to 1.0 in the overall sample (IRR = 1.03, 95% CI: 0.96, 1.11; IRR = 1.03, 95% CI: 0.94, 1.13; and IRR = 1.04, 95% CI: 0.98, 1.10; respectively) and among women consuming <1 serving/day of total dairy (IRR = 1.01, 95% CI: 0.92, 1.11; IRR = 1.00, 95% CI: 0.89, 1.12; and IRR = 1.02, 95% CI: 0.95, 1.10, respectively). Results were similar when we 1) restricted our sample to the 5,828 women (26.4%) not using any supplements (IRRs for total dairy intake comparing 1, 2, 3, ≥4 vs. <1 servings/day = 0.86, 0.82, 0.65, and 0.65, respectively; P-trend = 0.003); 2) controlled for all 3 supplements when assessing the effects of total dairy and dietary calcium; and 3) controlled for multivitamins and calcium with vitamin D when assessing the effect of dietary vitamin D (data not shown).

Incidence rate ratios did not vary appreciably by case definition (ultrasound vs. surgery), body mass index, total fat intake, education, income, or recency of pelvic examination (data not shown). Associations for total dairy intake persisted among women aged <35 years, for whom uterine leiomyomata misclassification is lower (12): incidence rate ratios comparing 1, 2, 3, and ≥4 servings/day with <1 serving/day of total dairy were 0.94 (95% CI: 0.85, 1.05), 0.82 (95% CI: 0.67, 0.99), 0.71 (95% CI: 0.51, 0.98), and 0.69 (95% CI: 0.50, 0.96), respectively (P-trend = 0.001). Finally, use of a simple update method (i.e., using the 2001 FFQ for 2001–2007 instead of averaging the 1995 and 2001 FFQs) produced incidence rate ratios similar to those using the cumulative-average method (data not shown).

DISCUSSION

In the present study, both high-fat and low-fat dairy intakes were inversely associated with uterine leiomyomata risk among black women. Two components of dairy, calcium-to-phosphorus ratio and butyric acid, were also inversely associated with risk. However, control for total dairy intake attenuated the incidence rate ratios for these individual nutrients, suggesting that the inverse associations were operating through dairy intake.

Our results conflict with those from the sole study known to have examined dairy consumption and uterine leiomyomata, a case-control study (17) in which neither milk nor cheese consumption was related to risk of surgically diagnosed uterine leiomyomata. Our study differs from that one in that we collected prospective dietary data, thereby avoiding recall bias; we used a validated FFQ; and we controlled for energy intake, which can account for unmeasured confounding (57) and reduce measurement error (58).

A protective effect of dairy consumption on uterine leiomyomata risk is plausible. Calcium, a major component of dairy foods, may reduce fat-induced cell proliferation by maintaining intracellular calcium concentrations (59, 60). Because phosphorus and calcium compete for absorption in the intestine, a low dietary calcium-to-phosphorus ratio decreases calcium bioavailability (61). Therefore, the inverse association observed for calcium-to-phosphorus ratio supports the hypothesis that calcium protects against uterine leiomyomata. Butyric acid, present in milk fat, is a potent antitumorigenic agent that induces differentiation and apoptosis, and it inhibits proliferation and angiogenesis (25). The inverse, albeit weaker, association between butyric acid and uterine leiomyomata suggests another mechanism by which dairy foods might exert a protective effect. The lack of effect for dietary vitamin D is not entirely surprising because the largest sources of bioavailable vitamin D are derived from sun exposure and vitamin supplements (62).

We found no association between soy intake and uterine leiomyomata risk, but soy intake in US populations is low relative to that in countries such as Japan (19, 63) and is substantially lower than dairy intake (64). Soy is a primary source of phytoestrogens, specifically isoflavones (65), which may act as antiestrogens by competing with estrogen for receptor binding, possibly decreasing the bioavailability of estrogens (66, 67) or altering estrogen biosynthesis (68, 69). In vitro studies suggest that high levels of genistein, a soy-derived phytoestrogen, inhibit proliferation of cultured uterine leiomyomata cells (70, 71). Conversely, phytoestrogens can mimic estrogen activity (69). Although a case-control study found that urinary excretion of lignans (found in soybeans) was inversely associated with uterine leiomyomata (18), no association was found with urinary isoflavones. Likewise, a cross-sectional study found no association between intake of soy isoflavones and uterine leiomyomata (19).

Strengths of our study include the prospective design and use of validated measures for key variables. With prospective data collection, error in the reporting of diet is likely random, which generally biases results toward the null. Averaging diet measured at 2 time periods may reduce measurement error (50). We adjusted for multiple uterine leiomyomata risk factors and socioeconomic status measures associated with diet (72). High cohort retention, which decreases the potential for selection bias, is an additional strength. When we compared active participants with those lost to follow-up, minimal differences were found according to dairy intake or uterine leiomyomata risk factors.

A potential limitation of our study is that some uterine leiomyomata cases were likely missed, particularly those with asymptomatic disease. Although self-report was confirmed for almost all participants from whom we obtained medical records, not all participants were screened. This concern was partly addressed by our observation of similar associations for dairy intake among women with a recent pelvic examination and younger women, for whom uterine leiomyomata misclassification is reduced (12). Our inability to directly assess vitamin D status through blood levels is another limitation, precluding us from examining its role as a mediator of the dairy effect. We were also unable to assess the role of lactose intolerance in explaining our dairy intake–uterine leiomyomata association. Although dairy intakes vary substantially among people who test positive for lactose intolerance (39, 73), there could be common or related genetic factors associated with dairy intake and uterine leiomyomata.

The Black Women's Health Study, although based on a large national cohort, is a self-selected sample of women with higher levels of education than the general black population. Nevertheless, prevalence estimates of uterine leiomyomata risk factors, such as age at menarche and parity, are similar to those found in national studies (74). In addition, FFQ estimates for dairy foods are consistent with national data on adult female African Americans (20, 21). Because the association between dairy intake and uterine leiomyomata did not vary appreciably by other factors, we expect our findings to extend to the general population of black women.

In summary, we found that high dairy intake was inversely associated with uterine leiomyomata risk among black women. Because dairy intake is appreciably lower among US black women than white women, differences in dairy intake may contribute to the racial discrepancy in rates of uterine leiomyomata. Future studies including black women and white women could test this hypothesis directly. Our case group likely represents women with symptomatic disease given that most validation study cases reported symptoms, a low percentage were detected incidentally, and uterine leiomyomata rates were similar to rates based on hospital-discharge data (47). Symptomatic disease has the greatest impact on a woman's quality of life and health care utilization (6). Confirmation of these findings is therefore a high priority.

Acknowledgments

Author affiliations: Slone Epidemiology Center, Boston University, Boston, Massachusetts (Lauren A. Wise, Rose G. Radin, Julie R. Palmer, Lynn Rosenberg); and Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania (Shiriki K. Kumanyika).

This work was supported by National Cancer Institute grant CA58420 (Principal Investigator: Lynn Rosenberg) and National Institute of Child Health and Human Development grant HD055211 (Principal Investigator: Lauren A. Wise).

The authors gratefully acknowledge the ongoing contributions of the Black Women's Health Study staff.

Conflict of interest: none declared.

Glossary

Abbreviations

CI
confidence interval
FFQ
food frequency questionnaire
IRR
incidence rate ratio

References

1. Buttram VC, Jr, Reiter RC. Uterine leiomyomata: etiology, symptomatology, and management. Fertil Steril. 1981;36(4):433–445. [PubMed]
2. Coronado GD, Marshall LM, Schwartz SM. Complications in pregnancy, labor, and delivery with uterine leiomyomas: a population-based study. Obstet Gynecol. 2000;95(5):764–769. [PubMed]
3. Stewart EA. Uterine fibroids. Lancet. 2001;357(9252):293–298. [PubMed]
4. Wilcox LS, Koonin LM, Pokras R, et al. Hysterectomy in the United States, 1988–1990. Obstet Gynecol. 1994;83(4):549–555. [PubMed]
5. Farquhar CM, Steiner CA. Hysterectomy rates in the United States 1990–1997. Obstet Gynecol. 2002;99(2):229–234. [PubMed]
6. Flynn M, Jamison M, Datta S, et al. Health care resource use for uterine fibroid tumors in the United States. Am J Obstet Gynecol. 2006;195(4):955–964. [PubMed]
7. Rein MS, Nowak RA. Biology of uterine myomas and myometrium in vitro. Semin Reprod Endocrinol. 1992;10:310–319.
8. Rein MS, Barbieri RL, Friedman AJ. Progesterone: a critical role in the pathogenesis of uterine myomas. Am J Obstet Gynecol. 1995;172(1 pt 1):14–18. [PubMed]
9. Sozen I, Arici A. Cellular biology of myomas: interaction of sex steroids with cytokines and growth factors. Obstet Gynecol Clin North Am. 2006;33(1):41–58. [PubMed]
10. Marshall LM, Spiegelman D, Barbieri RL, et al. Variation in the incidence of uterine leiomyoma among premenopausal women by age and race. Obstet Gynecol. 1997;90(6):967–973. [PubMed]
11. Brett KM, Marsh JV, Madans JH. Epidemiology of hysterectomy in the United States: demographic and reproductive factors in a nationally representative sample. J Womens Health. 1997;6(3):309–316. [PubMed]
12. Day Baird D, Dunson DB, Hill MC, et al. High cumulative incidence of uterine leiomyoma in black and white women: ultrasound evidence. Am J Obstet Gynecol. 2003;188(1):100–107. [PubMed]
13. Kjerulff KH, Guzinski GM, Langenberg PW, et al. Hysterectomy and race. Obstet Gynecol. 1993;82(5):757–764. [PubMed]
14. Kjerulff K, Langenberg P, Guzinski G. The socioeconomic correlates of hysterectomies in the United States. Am J Public Health. 1993;83(1):106–108. [PubMed]
15. Kjerulff KH, Langenberg P, Seidman JD, et al. Uterine leiomyomas: racial differences in severity, symptoms, and age at diagnosis. J Reprod Med. 1996;41(7):483–490. [PubMed]
16. Terry KL, Missmer SA, Hankinson SE, et al. Lycopene and other carotenoid intake in relation to risk of uterine leiomyoma. Am J Obstet Gynecol. 2008;198(1):37.e1–37.e8. [PMC free article] [PubMed]
17. Chiaffarino F, Parazzini F, La Vecchia C, et al. Diet and uterine myomas. Obstet Gynecol. 1999;94(3):395–398. [PubMed]
18. Atkinson C, Lampe JW, Scholes D, et al. Lignan and isoflavone excretion in relation to uterine fibroids: a case-control study of young to middle-aged women in the United States. Am J Clin Nutr. 2006;84(3):587–593. [PubMed]
19. Nagata C, Nakamura K, Oba S, et al. Association of intakes of fat, dietary fibre, soya isoflavones and alcohol with uterine fibroids in Japanese women. Br J Nutr. 2009;101(10):1427–1431. [PubMed]
20. Fulgoni V, 3rd, Nicholls J, Reed A, et al. Dairy consumption and related nutrient intake in African-American adults and children in the United States: continuing survey of food intakes by individuals 1994–1996, 1998, and the National Health and Nutrition Examination Survey 1999–2000. J Am Diet Assoc. 2007;107(2):256–264. [PubMed]
21. Beydoun MA, Gary TL, Caballero BH, et al. Ethnic differences in dairy and related nutrient consumption among US adults and their association with obesity, central obesity, and the metabolic syndrome. Am J Clin Nutr. 2008;87(6):1914–1925. [PMC free article] [PubMed]
22. Radimer K, Bindewald B, Hughes J, et al. Dietary supplement use by US adults: data from the National Health and Nutrition Examination Survey, 1999–2000. Am J Epidemiol. 2004;160(4):339–349. [PubMed]
23. Picciano MF, Dwyer JT, Radimer KL, et al. Dietary supplement use among infants, children, and adolescents in the United States, 1999–2002. Arch Pediatr Adolesc Med. 2007;161(10):978–985. [PubMed]
24. Giovannucci E. The epidemiology of vitamin D and cancer incidence and mortality: a review (United States) Cancer Causes Control. 2005;16(2):83–95. [PubMed]
25. Parodi PW. Dairy product consumption and the risk of breast cancer. J Am Coll Nutr. 2005;24(6 suppl) 556S–568S. [PubMed]
26. Hartmann S, Lacorn M, Steinhart H. Natural occurrence of steroid hormones in food. Food Chem. 1998;62(1):7–20.
27. Henderson KM, Karanikolas M, Kenealy L, et al. Concentrations of oestrone sulphate during pregnancy in milk from Jersey and Friesian dairy cows differing in milk yields and composition. N Z Vet J. 1994;42(3):89–92. [PubMed]
28. Outwater JL, Nicholson A, Barnard N. Dairy products and breast cancer: the IGF-I, estrogen, and bGH hypothesis. Med Hypotheses. 1997;48(6):453–461. [PubMed]
29. Boyd NF, Martin LJ, Noffel M, et al. A meta-analysis of studies of dietary fat and breast cancer risk. Br J Cancer. 1993;68(3):627–636. [PMC free article] [PubMed]
30. Knekt P, Järvinen R, Seppänen R, et al. Intake of dairy products and the risk of breast cancer. Br J Cancer. 1996;73(5):687–691. [PMC free article] [PubMed]
31. Hjartåker A, Laake P, Lund E. Childhood and adult milk consumption and risk of premenopausal breast cancer in a cohort of 48,844 women—the Norwegian women and cancer study. Int J Cancer. 2001;93(6):888–893. [PubMed]
32. Shin MH, Holmes MD, Hankinson SE, et al. Intake of dairy products, calcium, and vitamin D and risk of breast cancer. J Natl Cancer Inst. 2002;94(17):1301–1311. [PubMed]
33. Kesse-Guyot E, Bertrais S, Duperray B, et al. Dairy products, calcium and the risk of breast cancer: results of the French SU.VI.MAX prospective study. Ann Nutr Metab. 2007;51(2):139–145. [PubMed]
34. Pala V, Krogh V, Berrino F, et al. Meat, eggs, dairy products, and risk of breast cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Am J Clin Nutr. 2009;90(3):602–612. [PubMed]
35. Cho E, Spiegelman D, Hunter DJ, et al. Premenopausal fat intake and risk of breast cancer. J Natl Cancer Inst. 2003;95(14):1079–1085. [PubMed]
36. Toniolo P, Riboli E, Shore RE, et al. Consumption of meat, animal products, protein, and fat and risk of breast cancer: a prospective cohort study in New York. Epidemiology. 1994;5(4):391–397. [PubMed]
37. Bandera EV, Kushi LH, Moore DF, et al. Consumption of animal foods and endometrial cancer risk: a systematic literature review and meta-analysis. Cancer Causes Control. 2007;18(9):967–988. [PMC free article] [PubMed]
38. Jackson KA, Savaiano DA. Lactose maldigestion, calcium intake and osteoporosis in African-, Asian-, and Hispanic-Americans. J Am Coll Nutr. 2001;20(2 suppl) 198S–207S. [PubMed]
39. Scrimshaw NS, Murray EB. The acceptability of milk and milk products in populations with a high prevalence of lactose intolerance. Am J Clin Nutr. 1988;48(4 suppl):1079–1159. [PubMed]
40. Rosenberg L, Adams-Campbell LL, Palmer JR. The Black Women's Health Study: a follow-up study for causes and preventions of illness. J Am Med Womens Assoc. 1995;50(2):56–58. [PubMed]
41. Loutradis D, Antsaklis A, Creatsas G, et al. The validity of gynecological ultrasonography. Gynecol Obstet Invest. 1990;29(1):47–50. [PubMed]
42. Dueholm M, Lundorf E, Hansen ES, et al. Accuracy of magnetic resonance imaging and transvaginal ultrasonography in the diagnosis, mapping, and measurement of uterine myomas. Am J Obstet Gynecol. 2002;186(3):409–415. [PubMed]
43. Schwartz SM, Marshall LM. Uterine leiomyomata. In: Goldman MB, Hatch MC, editors. Women and Health. San Diego, CA: Academic Press; 2000. pp. 240–252.
44. Myers ER, Bastian LA, Havrilesky LJ, et al. Management of adnexal mass. Evid Rep Technol Assess (Full Rep) 2006;130:1–145. [PubMed]
45. Block G, Hartman AM, Naughton D. A reduced dietary questionnaire: development and validation. Epidemiology. 1990;1(1):58–64. [PubMed]
46. Kumanyika SK, Mauger D, Mitchell DC, et al. Relative validity of food frequency questionnaire nutrient estimates in the Black Women's Health Study. Ann Epidemiol. 2003;13(2):111–118. [PubMed]
47. Wise LA, Palmer JR, Stewart EA, et al. Age-specific incidence rates for self-reported uterine leiomyomata in the Black Women's Health Study. Obstet Gynecol. 2005;105(3):563–568. [PMC free article] [PubMed]
48. Mitchell DC, Lancaster KJ, Smiciklas-Wright H, et al. Comparison of food group intakes assessed by food frequency questionnaire vs. 24-hour dietary recalls in the Black Women's Health Study dietary substudy [abstract] Presented at the 4th International Conference on Dietary Assessment Methods. Tucson, Arizona, September 17–20, 2000.
49. Willett WC, Stampfer MJ. Implications of total energy intake for epidemiologic analysis. In: Willett W, editor. Nutritional Epidemiology. 2nd ed. New York, NY: Oxford University Press; 1998. pp. 273–301.
50. Hu FB, Stampfer MJ, Rimm E, et al. Dietary fat and coronary heart disease: a comparison of approaches for adjusting for total energy intake and modeling repeated dietary measurements. Am J Epidemiol. 1999;149(6):531–540. [PubMed]
51. Wise LA, Palmer JR, Harlow BL, et al. Reproductive factors, hormonal contraception and risk of uterine leiomyomata in African-American women: a prospective study. Am J Epidemiol. 2004;159(2):113–123. [PMC free article] [PubMed]
52. Wise LA, Palmer JR, Harlow BL, et al. Risk of uterine leiomyomata in relation to tobacco, alcohol and caffeine consumption in the Black Women's Health Study. Hum Reprod. 2004;19(8):1746–1754. [PMC free article] [PubMed]
53. Wise LA, Palmer JR, Rosenberg L, et al. Risk of uterine leiomyomata according to birthplace and geographic region in the Black Women's Health Study [abstract] Ann Epidemiol. 2004;14:622.
54. Wise LA, Palmer JR, Spiegelman D, et al. Influence of body size and body fat distribution on risk of uterine leiomyomata in U.S. black women. Epidemiology. 2005;16(3):346–354. [PMC free article] [PubMed]
55. Breslow NE, Day NE. Statistical methods in cancer research. Vol 2. The design and analysis of cohort studies. IARC Sci Publ. 1987;(82):1–406. [PubMed]
56. SAS Institute, Inc. Cary, NC: SAS Institute, Inc; 2004. SAS/STAT user's guide, version 9.1.
57. Willett W. Nutritional Epidemiology. 2nd ed. New York, NY: Oxford University Press; 1998.
58. Willett W. Commentary: dietary diaries versus food frequency questionnaires—a case of undigestible data. Int J Epidemiol. 2001;30(2):317–319. [PubMed]
59. Jacobson EA, James KA, Newmark HL, et al. Effects of dietary fat, calcium, and vitamin D on growth and mammary tumorigenesis induced by 7,12-dimethylbenz(a)anthracene in female Sprague-Dawley rats. Cancer Res. 1989;49(22):6300–6303. [PubMed]
60. Newmark HL. Vitamin D adequacy: a possible relationship to breast cancer. Adv Exp Med Biol. 1994;364:109–114. [PubMed]
61. Calvo MS. The effects of high phosphorus intake on calcium homeostasis. Adv Nutr Res. 1994;9:183–207. [PubMed]
62. Holick MF. Deficiency of sunlight and vitamin D. BMJ. 2008;336(7657):1318–1319. [PMC free article] [PubMed]
63. de Kleijn MJ, van der Schouw YT, Wilson PW, et al. Intake of dietary phytoestrogens is low in postmenopausal women in the United States: the Framingham Study (1–4) J Nutr. 2001;131(6):1826–1832. [PubMed]
64. Chun OK, Chung SJ, Song WO. Estimated dietary flavonoid intake and major food sources of U.S. adults. J Nutr. 2007;137(5):1244–1252. [PubMed]
65. Reinli K, Block G. Phytoestrogen content of foods—a compendium of literature values. Nutr Cancer. 1996;26(2):123–148. [PubMed]
66. Adlercreutz H. Western diet and Western diseases: some hormonal and biochemical mechanisms and associations. Scand J Clin Lab Invest Suppl. 1990;201:3–23. [PubMed]
67. Folman Y, Pope GS. Effect of norethisterone acetate, dimethylstilboestrol, genistein and coumestrol on uptake of [3H]oestradiol by uterus, vagina and skeletal muscle of immature mice. J Endocrinol. 1969;44(2):213–218. [PubMed]
68. Setchell KD, Cassidy A. Dietary isoflavones: biological effects and relevance to human health. J Nutr. 1999;129(3):758S–767S. [PubMed]
69. Vaya J, Tamir S. The relation between the chemical structure of flavonoids and their estrogen-like activities. Curr Med Chem. 2004;11(10):1333–1343. [PubMed]
70. Shushan A, Ben-Bassat H, Mishani E, et al. Inhibition of leiomyoma cell proliferation in vitro by genistein and the protein tyrosine kinase inhibitor TKS050. Fertil Steril. 2007;87(1):127–135. [PubMed]
71. Moore AB, Castro L, Yu L, et al. Stimulatory and inhibitory effects of genistein on human uterine leiomyoma cell proliferation are influenced by the concentration. Hum Reprod. 2007;22(10):2623–2631. [PMC free article] [PubMed]
72. Darmon N, Drewnowski A. Does social class predict diet quality? Am J Clin Nutr. 2008;87(5):1107–1117. [PubMed]
73. Rao DR, Bello H, Warren AP, et al. Prevalence of lactose maldigestion. Influence and interaction of age, race, and sex. Dig Dis Sci. 1994;39(7):1519–1524. [PubMed]
74. Abma JC, Chandra A, Mosher WD, et al. Fertility, family planning, and women's health: new data from the 1995 National Survey of Family Growth. Vital Health Stat. 1997;23(19):1–114. [PubMed]

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