PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Breast Cancer Res Treat. Author manuscript; available in PMC Aug 1, 2013.
Published in final edited form as:
PMCID: PMC3687532
NIHMSID: NIHMS476403

Cardiometabolic factors and breast cancer risk in U.S. black women

Abstract

Previous studies have suggested that metabolic syndrome may be associated with an increased risk of breast cancer, particularly in postmenopausal women, but U.S. black women have not been assessed. We examined the associations of abdominal obesity, type 2 diabetes, hypertension, and high cholesterol individually and in combination with breast cancer incidence in the Black Women’s Health Study. By means of Cox regression models, we estimated incidence rate ratios (IRR) and 95 % confidence intervals (CI) for the associations of baseline and time-dependent values of self-reported abdominal obesity, type 2 diabetes, hypertension, and high cholesterol with breast cancer incidence. During 516,452 person years of follow-up (mean years = 10.5; standard deviation = 2.9) from 1995 to 2007, 1,228 breast cancer cases were identified. After adjustment for age, education, body mass index at age 18, physical activity, and individual cardiometabolic factors, neither individual nor combinations of cardiometabolic factors were associated with breast cancer incidence overall; the multivariable IRR was 1.04 (95 % CI 0.86–1.25) for the combination of ≥3 factors relative to the absence of all factors, and 1.17 (0.85–1.60) for having all four factors. Among postmenopausal women, however, the comparable IRRs were 1.23 (0.93–1.62) and 1.63 (1.12–2.37), respectively. Our findings provide some support for an association between cardiometabolic factors and breast cancer incidence among postmenopausal U.S. black women.

Keywords: Metabolic syndrome, Obesity, Insulin resistance, Breast cancer

Introduction

Metabolic syndrome, also called insulin resistance syndrome, is defined as the clustering of three or more of the following conditions: abdominal obesity (waist circumference ≥ 88 cm), elevated blood pressure (≥130 mmHg systolic over ≥85 mmHg diastolic), elevated fasting glucose (≥100 mg/dL), hypertriglyceridemia (≥150 mg/ dL), and low high-density lipoprotein (HDL) cholesterol (<50 mg/dL) [1]. The prevalence of each of the components of metabolic syndrome is greater among black women than among white women [2]. In black women, the prevalence of abdominal obesity, elevated blood pressure, elevated fasting glucose, hypertriglyceridemia, and low HDL cholesterol has been estimated to be 62.1, 43.3, 15.5, 14.4, and 34.0 %, respectively [2]. The overall prevalence of metabolic syndrome is estimated to be approximately 26 % among U.S. black women [3].

Limited epidemiologic evidence suggests that metabolic syndrome may be associated with an increased breast cancer risk, particularly among postmenopausal women [410]. Individual cardiometabolic factors, such as abdominal obesity, type 2 diabetes, high blood pressure, and high cholesterol, have been associated with increased risks of breast cancer in some studies [46, 1122], but not in others [5, 7, 2325]. The majority of studies have been composed predominantly of white women [49], and if the existing evidence applies to black women remains unknown.

No previous studies have examined the combined effects of cardiometabolic factors on breast cancer risk in U.S. black women, and information on effects of the individual risk factors is relatively sparse. We examined the association between breast cancer incidence and the following cardiometabolic factors: abdominal obesity, type 2 diabetes, hypertension, and high cholesterol, both individually and in combination, using data from the Black Women’s Health Study (BWHS).

Methods

Study population

The BWHS is a prospective cohort study of approximately 59,000 U.S. black women aged 21 through 69 years at entry in 1995 [26]. The baseline questionnaire collected information on demographic and lifestyle factors, reproductive history, anthropometric measurements, medical conditions, and medications [26]. Deaths were identified through the National Death Index, postal service, and friends or relatives. The cohort is followed biennially by mailed questionnaire, and 80 % of the original cohort had been followed through 2007.

Women were excluded from the analysis if they did not complete at least one follow-up questionnaire (N = 53), had prevalent cancer at baseline (N = 1,414), did not complete the baseline waist circumference question (N = 7,976), or had type 1 diabetes (N = 412).

The Boston University Medical Center Institutional Review Board has approved this study.

Cardiometabolic factors

BWHS participants were asked to measure their waist at their navel in the baseline questionnaire. In a validation study among 115 participants, the Spearman correlation coefficient for waist circumference reported in the baseline questionnaire (1995) with a clinical measurement taken in 2001 was 0.75 [27]. We defined abdominal obesity as a waist circumference of 88 cm or greater [1].

Participants were asked at baseline and in follow-up questionnaires if a physician had told them that they had any of a list of medical conditions that included diabetes, hypertension, and high cholesterol. They were also asked to report medications used ≥3 times per week, such as insulin, pills to treat diabetes, diuretics, and blood pressure lowering drugs. Cholesterol-lowering medications were reported in an open-text question in the medications section of the baseline questionnaire and the 1997 follow-up questionnaire. Subsequent questionnaires asked specifically about these medications. We defined type 2 diabetes as self-reported diagnosis of diabetes at age 30 years or older [28]; in a validation study of 115 participants who reported diabetes, the physician had confirmed the diagnosis for 95 % [28]. We defined hypertension as reported high blood pressure plus use of diuretics or hypertensive medication [29]; the positive predictive value for self-reported drugtreated hypertension was 99 % in a sample of 139 women for whom medical record data were obtained [29]. We defined high cholesterol as self-reported high cholesterol; no validation data were available for self-report of physician-diagnosed high cholesterol.

Potential confounding variables

Candidate confounding variables were identified a priori from the existing literature [3036]. Educational attainment at baseline was used as a surrogate for socioeconomic status. We used self-reported height and weight to calculate body mass index (BMI, weight in kilograms divided by height squared in meters). A woman was considered postmenopausal if she reported natural menopause or bilateral oophorectomy, or if she had hysterectomy with removal of <2 ovaries and was age 57 (90th percentile of age at natural menopause in BWHS) or older. She was considered premenopausal if she reported being premenopausal, or if she had a hysterectomy with removal of <2 ovaries and was less than age 43 (10th percentile of age at natural menopause in BWHS). Menopausal status was considered unknown if the woman had a hysterectomy with removal of<2 ovaries and was 43–56 years of age. Family history of breast cancer in a first degree relative (mother, sister), and age at menarche were reported at baseline. Information on parity, age at first birth, oral contraceptive use, female hormone use (i.e., postmenopausal hormone replacement therapy), alcohol consumption, physical activity, smoking, and mammography receipt was collected at baseline and in each follow-up questionnaire. Vigorous physical activity was defined as participation in activities such as basketball, swimming, running, and aerobics. This measure was validated in a BWHS study in which the participants wore activity monitors during their waking hours for 1 week; reported vigorous activity was significantly associated with counts recorded by the activity monitors [37].

Breast cancer ascertainment

Among the 59,000 women included in the BWHS cohort, a total of 1,429 breast cancer diagnoses were reported on follow-up questionnaires from 1997 through 2007. To date, medical records or cancer registry data have been obtained for 1,151 reported cases, of which 99.4 % cases were confirmed. Disconfirmed cases were excluded, leaving a total of 1,228 cases for analysis after previous exclusions.

Statistical analysis

Women were followed from baseline in 1995 until breast cancer diagnosis, death from any cause, loss to follow-up, or the end of follow-up in 2007, whichever came first. Incidence rate ratios (IRRs) and 95 % confidence intervals (CIs) for the association of individual and combinations of cardiometabolic factors with breast cancer risk were estimated using Cox proportional hazards regression models, with duration of follow-up as the time scale [38]. The Cox proportional regression analyses incorporated the Andersen–Gill data structure to account for the time-dependent nature of the cardiometabolic factors [39]. Departures from the proportional hazards assumption were tested by the likelihood ratio test comparing models with and without age by covariate interaction terms [38]. No violations of this assumption were observed. IRRs and 95 % CIs also were calculated for mutually exclusive individual and combinations of cardiometabolic factors compared with the absence of any factor. We also calculated the effect of individual cardiometabolic factors relative to the absence of that risk factor (i.e., hypertension compared with the absence of hypertension). Models were jointly stratified by age (1-year intervals) and questionnaire cycle, and also adjusted for education (≤12, 13–15, and ≥16 years), BMI at age 18 (<20, 20–24, 25–29, and ≥30 kg/m2), vigorous physical activity (none, <5 h per week, ≥5 h per week), and each of the other cardiometabolic factors. Vigorous physical activity was treated as a time-dependent variable in the Cox models. Adjustment for reproductive history, female hormone use, and oral contraceptive use did not appreciably change the results, and these variables were not included in the final multivariable models.

We also examined the association between baseline values of cardiometabolic factors and breast cancer risk.

All statistical tests were two-sided and conducted using SAS, version 9.1 (Cary, North Carolina).

Results

The final analytic sample consisted of 49,172 BWHS participants, among whom 1,228 incident cases of breast cancer were reported over 516,452 person–years of followup (mean years = 10.5; standard deviation = 2.9) through 2007. The median age at diagnosis among participants with breast cancer was 50 years. Women excluded because they did not report a waist circumference had a higher BMI and were less physically active at baseline than participants included in the analysis. The proportions of participants who reported cardiometabolic factors were as follows: abdominal obesity, 28 %; type 2 diabetes, 3.9 %; drugtreated hypertension, 15 %; and high cholesterol, 28 % (Table 1). Women with any of the cardiometabolic factors were older, more likely to use female hormones, more obese at baseline and at age 18, less physically active, and had an earlier menarche and fewer years of education than women with no cardiometabolic factors (Table 1).

Table 1
Frequencies and age-standardized percentagesa for descriptive demographic, reproductive, and behavioral characteristics across individual cardiometabolic factors at baseline in U.S. black women (N = 49,172)

Results from time-dependent analyses of mutually exclusive individual and combinations of cardiometabolic factors, relative to the absence of all cardiometabolic factors, are presented in Table 2. No individual factor or a combination of factors was significantly associated with an increased risk of breast cancer. The multivariable incidence rate ratio (mIRR) for having three or more cardiometabolic factors was 1.04 (95 % CI 0.86–1.25), and for all four factors, it was 1.17 (95 % CI 0.85–1.60).

Table 2
Mutually exclusive individual and combinations of time-dependent cardiometabolic factors in relation to breast cancer risk in U.S. black women

Table 3 presents time-dependent analyses for individual and combinations of cardiometabolic factors stratified by menopausal status. Among postmenopausal women, having all four cardiometabolic factors was significantly associated with breast cancer risk (mIRR = 1.63; 95 % CI 1.12–2.37). The mIRR for any ≥3 cardiometabolic factors was 1.23 (95 % CI 0.93–1.62). No individual or combination of cardiometabolic factors was associated with breast cancer risk among premenopausal women (Table 3). When the analysis was restricted to the subset of 362 postmenopausal cases who never used hormone therapy, mIRRs for all four cardiometabolic factors (mIRR = 1.77; 95 % CI 1.14–2.77) and ≥3 factors (mIRR = 1.30; 95 % CI 0.92–1.83) did not change appreciably from those for all postmenopausal women.

Table 3
Mutually exclusive individual and combinations of time-dependent cardiometabolic factors in relation to breast cancer risk, stratified by menopausal status

When we repeated the analyses using baseline values of cardiometabolic factors, no significant associations were observed. The mIRRs were 1.09 (95 % CI 0.70–1.71) for having all four cardiometabolic factors, and 1.04 (95 % CI 0.84–1.29) for ≥3 cardiometabolic factors. Among post-menopausal women, the IRR for any three or more cardiometabolic factors was 1.37 (0.91–2.01), based on 73 affected cases. Only two cases had all four factors at baseline.

Table 4 presents mIRRs and 95 % CIs for time-dependent analyses in which cardiometabolic factors are each considered separately, not as mutually exclusive variables. MIRRs for breast cancer were estimated for the presence of a given factor relative to the absence of that factor. None of the cardiometabolic factors was associated with breast cancer risk overall or by menopausal status; mIRRs ranged from 0.80 to 1.13.

Table 4
Individual time-dependent cardiometabolic factors in relation to breast cancer risk compared with the absence of that factor, overall and stratified by menopausal status

Discussion

In this large prospective study of U.S. black women, we found evidence of an increased risk of breast cancer among postmenopausal women associated with having all four cardiometabolic factors under study, with a possible smaller increase for having at least three factors. No such association was observed among premenopausal women. A significant association was observed when cardiometabolic factors were updated over time, but not when baseline exposure was considered, but numbers of affected women were smaller in the latter analyses.

Several hormonal factors, most of which lead to increased levels of circulating estrogen, have been proposed as the underlying mechanisms for the association of breast cancer with individual components of the metabolic syndrome [11, 14, 16]. After menopause, estradiol is produced primarily in adipose tissue. Thus, heavier women tend to have higher circulating levels of estradiol. High estradiol levels are associated with an increased risk of breast cancer, particularly hormone-receptor positive tumors [40]. High levels of circulating insulin also have been associated with breast cancer risk in some studies [41, 42], but not in others [42, 43]. When insulin levels increase, cell proliferation also increases, while sex-hormone binding globulin (SHBG) levels and cell apoptosis decrease [44]. Insulin reduces the production of SHBG and the combination of low SHBG and high triglycerides increase estradiol levels [45]. Adiponectin, an antiinflammatory protein, also may play an important role in a potential pathway between metabolic syndrome and breast cancer. Levels of adiponectin tend to be lower in individuals with low HDL cholesterol, high triglycerides, abdominal obesity, type 2 diabetes, and hypertension [11]. Low levels of adiponectin have been associated with an increased breast cancer risk among postmenopausal women [46]. Moreover, adiponectin levels are lower among women with breast tumors with aggressive characteristics, such as larger tumor size, higher grade, and estrogen receptor-negative status [11]—common characteristics of breast cancer among African-American women [47].

There is growing epidemiologic evidence indicating that metabolic syndrome increases the risk of breast cancer among postmenopausal women [410]. Our findings support findings from the Women’s Health Initiative (WHI) study of postmenopausal women, which indicated that time-dependent metabolic syndrome (any combination of ≥3 components) was positively associated with a 77 % (95 % CI 1.01–3.12) increased rate of breast cancer [5]. Osaki et al. [10] reported that metabolic syndrome increased breast cancer risk in Japanese women ≥55 years old (89 breast cancer cases), regardless of the definition of metabolic syndrome used. BMI was used as a proxy for abdominal obesity [10]. Rosato et al. [8] combined data from two hospital-based case–control studies of Italian and Swiss women and observed that the presence of ≥3 components of metabolic syndrome was associated with an 80 % increase in risk of breast cancer among postmeno-pausal women (191 cases), and over a threefold increase in breast cancer risk among women ≥70 years. Preliminary findings from a cross-sectional study (50 cases) [6], an Italian nested case–control study (181 cases) [4], and a Brazilian matched case–control study (81 cases) [9] also suggest that metabolic syndrome is positively associated with breast cancer risk among postmenopausal women. In contrast to these positive associations, the MEtabolic syndrome and CANcer Study (Me-Can) cohort, a study of six cohorts from Austria, Norway, and Sweden, found no association of metabolic syndrome with breast cancer risk among women ≥50 years old (IRR = 1.04; 95 % CI 0.97–1.12) [7], and there was an inverse association of metabolic syndrome with breast cancer in women <50 years old (IRR = 0.83; 95 % CI 0.76–0.90), particularly among women with high BMI [7].

Studies that have examined individual cardiometabolic factors or components of metabolic syndrome have suggested that certain factors or components increase the risk of breast cancer, particularly among postmenopausal women [46, 1122]. While the strongest associations have been observed for abdominal obesity [12, 22, 4854] and type 2 diabetes [8, 13, 5558], some studies suggest null associations [25, 5962]. Only a few studies provide evidence for a positive association of breast cancer with either hypertension [17, 18, 63] or high cholesterol [19, 21, 64].

The WHI [5] and the Me-Can [7] studies had clinical measurements of the components of metabolic syndrome, whereas we used self-reported data of waist circumference and history of hypertension, diabetes, and high cholesterol. Misclassification in our study would tend to attenuate associations. A majority of the studies evaluating metabolic syndrome and breast cancer risk [49], including the WHI [5] and Me-Can [7] studies, were largely of white women, whereas the BWHS considered U.S. black women only. The number of breast cancer cases in the BWHS (N = 1,228) and the Me-Can study (N = 4,862) was appreciably larger than that in the WHI (N = 168).

With regard to individual components of the metabolic syndrome, a positive association between prevalence of high cholesterol and breast cancer has been reported [6]. Low HDL cholesterol level measured at baseline was not associated with breast cancer in the WHI [5] or in women ≥50 years old in the Me-Can study [7], but the Atherosclerosis Risk in Communities (ARIC) cohort [24] and a Norwegian cohort [19] observed that low HDL cholesterol levels were significantly associated with a 30 and 67 % increased risk of breast cancer, respectively. The Me-Can study also reported that low HDL cholesterol was inversely associated with breast cancer in women under 50 years old [7]. A positive association between breast cancer and time-dependent high triglycerides was observed in the WHI [5, 7], but the presence of high triglycerides appeared to decrease breast cancer risk in the Me-Can cohort study [7]. High cholesterol reported in the BWHS did not distinguish between high triglycerides, high total cholesterol, and low HDL cholesterol. We did not observe a significant association of self-reported high cholesterol with breast cancer incidence.

The ratio of the waist-to-hip ratio has been the most frequently used measurement to assess body fat distribution with upper body, or “central,” obesity being represented by a high ratio. However, waist circumference is considered a better indicator of the visceral adipose tissue and a better predictor of breast cancer risk [12] than waist-to-hip ratio [65]. Several large prospective studies, including the Nurses’ Health Study [12] and the European Prospective Investigation of Cancer and Nutrition (EPIC) study [50], observed that larger waist circumference was associated with an increased breast cancer risk. Several other studies that assessed metabolic syndrome in relation to breast cancer risk also found an association with central obesity [810]. In contrast to those findings, waist circumference of ≥88 cm was not associated with breast cancer in our study or in the WHI [5]. No association was observed between waist circumference and breast cancer in a previous analysis in the BWHS [25]. In studies evaluating the association of waist circumference or high BMI with breast cancer risk, the increased risk of breast cancer in white women was attenuated by use of hormone therapy [22, 66, 67]. However, when we restricted our analysis to the subset of postmenopausal women who never used hormone therapy, the results for the association of all four cardiometabolic factors and ≥3 factors with breast cancer risk did not change. These findings are consistent with a previous analysis of the BWHS cohort that observed high BMI at age 18 was inversely associated with breast cancer risk among postmenopausal women, and the inverse association persisted among non-users of hormone therapy [25].

The Nurses’ Health Study [13], a retrospective cohort study of Canadian administrative health care data [55], and several case–control studies [8, 5658] have reported that a history of type 2 diabetes was significantly associated with a 10–20 % increased risk of breast cancer, particularly among postmenopausal women. In the Nurses’ Health Study, the positive association was based on 6,220 women with a history of type 2 diabetes and 5,189 breast cancer cases among the postmenopausal women [13]. However, other studies did not observe an association between type 2 diabetes and breast cancer risk [5962, 68]. The ARIC study observed that diabetic glucose levels (≥125 mg/dL), compared with normal levels (<100 mg/dL), were associated with a non-significant increase in breast cancer risk (IRR = 1.39; 95 % CI 0.86–2.23) [43]. We did not observe a positive association between type 2 diabetes and breast cancer, and results were similar for women who treated their diabetes with oral medication and those who used insulin. Previous studies have suggested that certain type 2 diabetic medications may be associated with breast cancer risk [20, 69, 70]. For example, metformin—an oral antidiabetic medication—may protect against breast cancer [20, 69, 71], while long-acting insulin, such as glargine, may increase risk of breast cancer [70]. Our study lacked data for evaluating glucose levels, and we were unable to assess specific types of antidiabetic medications.

Limited evidence suggests a weak association between hypertension and breast cancer [5, 9, 17, 18]. Two case– control studies reported an association of hypertension with increased risk of breast cancer among postmenopausal women [17, 18], particularly in women who were overweight or obese [17]. Porto et al. [9], reported that high blood pressure (≥135/85 mmHg) increased breast cancer risk (odds ratio = 3.64; 95 % CI 1.89–6.98) in a Brazilian case–control study of 81 breast cancer cases and 81 matched controls. In addition, the WHI reported that high diastolic blood pressure (≥85 mmHg), compared with low blood pressure (<74 mmHg) increased breast cancer risk (IRR = 1.55; 95 % CI 1.02–2.36) [5]. On the other hand, a few studies have found that antihypertensive medications increase breast cancer risk [17, 72]. We did not observe an association between hypertension and breast cancer. We did not have blood pressure measurements to evaluate systolic and diastolic blood pressure separately [5].

This present study is the first to assess the association between cardiometabolic factors and breast cancer in U.S. black women. The prevalence of the cardiometabolic factors was higher in the BWHS for abdominal obesity, drugtreated hypertension and high cholesterol, but lower for type 2 diabetes, than the components of metabolic syndrome reported in previous studies evaluating metabolic syndrome and breast cancer risk [410]. Baseline BMI was also higher among BWHS participants than in previous studies [410]. Despite these differences in the distribution of cardiometabolic factors, we observed a positive association between all four factors and ≥3 factors in relation to breast cancer risk among postmenopausal women. The incidence of breast cancer is higher among black women than white women before the age of 45, and metabolic syndrome is more prevalent in black women at all ages [73], yet we did not observe an association among premenopausal women. However, the number of premenopausal breast cancer cases with three or more cardiometabolic risk factors was relatively small, thereby making it unlikely that differences in risk would have been detectable, even if the association was present.

Strengths of the present study include high rates of participation over 12 years of follow-up, prospective data collection, detailed information on potential confounders, updated exposure status over time, accurate reporting of breast cancer, and the large number of cases. We used definitions for type 2 diabetes [28] and hypertension [29] that were previously validated for our study population, but these were surrogates for the clinical measurements that make up the definition of metabolic syndrome. The correlation between self-reported baseline waist circumference and clinical measurements was good, even though the self-reported measurements were compared with measurements obtained several years later [29]. Previous analyses based on BWHS data have yielded associations, in the expected direction, for physical activity [74] and BMI [25] with breast cancer risk. Although no validation data are available for high cholesterol, we would expect misclassification to be non-differential, thus biasing our results towards the null. The BWHS population may have differed in some respects from black women in the general population, but we were able to control for various potentially known confounding variables in the analysis. Unmeasured confounding may have influenced our findings, but controlling for important breast cancer risk factors [30] did not substantially alter our results. The use of medical care in the BWHS is high. At baseline, 98 % of participants had had a health care visit in the previous 2 years, and 91 % of women aged 40 and older had a mammogram in the previous 2 years. Obesity has been associated with mammographic screening in some studies, but it was not associated with obesity in the BWHS cohort [75]. Finally, the exclusion of women who did not report their waist circumference at baseline may have biased our results toward the null because these women were more likely to have a high BMI and be less physically active and therefore have a higher risk of breast cancer.

In summary, the present study provides some support for an association between the combination of all four cardiometabolic factors (abdominal obesity, type 2 diabetes, hypertension, and high cholesterol) and breast cancer incidence among postmenopausal U.S. black women. The findings of this study do not support an association between individual cardiometabolic factors and breast cancer in black women.

Acknowledgments

The authors gratefully acknowledge the contributions of the participants and the staff of the BWHS. This study was supported by the National Institutes of Health, and the National Cancer Institute grant R01 CA058420. The content is solely the responsibility of the authors and does not necessarily represent the official view of the National Cancer Institute or the National Institutes of Health. Although data on breast cancer pathology were obtained from several state cancer registries (AZ, CA, CO, CT, DE, DC, FL, GA, IL, IN, KY, LA, MD, MA, MI, NJ, NY, NC, OK, PA, SC, TN, TX, and VA), the results reported do not necessarily represent their views.

Abbreviations

ARIC
Atherosclerosis Risk in Communities
BMI
Body mass index
BWHS
Black Women’s Health Study
CI
Confidence interval
EPIC
European Prospective Investigation of Cancer and Nutrition
HDL
High-density lipoprotein
IRR
Incidence rate ratio
Me-Can
MEtabolic syndrome and CANcer Study
mIRR
Multivariable incidence rate ratio
SHBG
Sex-hormone binding globulin
WHI
Women’s Health Initiative;

Footnotes

Conflict of interest The authors declare that they have no conflict of interest.

Contributor Information

Jaclyn L. F. Bosco, Dana-Farber Cancer Institute, 450 Brookline Avenue LW519, Boston, MA 02215, USA, jaclyn_bosco/at/dfci.harvard.edu. Section of Geriatrics, Department of Medicine, Boston University School of Medicine, 88 East Newton Street, Robinson 2, Boston, MA 02118, USA.

Julie R. Palmer, Slone Epidemiology Center at Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, USA.

Deborah A. Boggs, Slone Epidemiology Center at Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, USA.

Elizabeth E. Hatch, Department of Epidemiology, Boston University School of Public Health, 715 Albany Street, T3E, Boston, MA 02118, USA.

Lynn Rosenberg, Slone Epidemiology Center at Boston University, 1010 Commonwealth Avenue, Boston, MA 02215, USA.

References

1. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, Jr., et al. Diagnosis and management of the metabolic syndrome: an American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Circulation. 2005;112:2735–2752. [PubMed]
2. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. J Am Med Assoc. 2002;287:356–359. [PubMed]
3. Park Y-W, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988–1994. Arch Intern Med. 2003;163:427–436. [PMC free article] [PubMed]
4. Agnoli C, Berrino F, Abagnato CA, Muti P, Panico S, Crosignani P, Krogh V. Metabolic syndrome and postmenopausal breast cancer in the ORDET cohort: a nested case-control study. Nutr Metab Cardiovasc Dis. 2010;20:41–48. [PMC free article] [PubMed]
5. Kabat GC, Kim M, Chlebowski RT, Khandekar J, Ko MG, McTiernan A, Neuhouser ML, Parker DR, Shikany JM, Stefanick ML, et al. A longitudinal study of the metabolic syndrome and risk of postmenopausal breast cancer. Cancer Epidemiol Biomark Prev. 2009;18:2046–2053. [PubMed]
6. Sinagra D, Amato C, Scarpilta AM, Brigandì M, Amato M, Saura G, Latteri MA, Caimi G. Metabolic syndrome and breast cancer risk. Euro Rev Med Pharmacol Sci. 2002;6:55–59. [PubMed]
7. Bjørge T, Lukanova A, Jonsson H, Tretli S, Ulmer H, Manjer J, Stocks T, Selmer R, Nagel G, Almquist M, et al. Metabolic syndrome and breast cancer in the Me-Can (MEtabolic syndrome and CANcer) project. Cancer Epidemiol Biomark Prev. 2010;19:1737–1745. [PubMed]
8. Rosato V, Bosetti C, Talamini R, Levi F, Montella M, Giacosa A, Negri E, La Vecchia C. Metabolic syndrome and the risk of breast cancer in postmenopausal women. Ann Oncol. 2011;22:2687–2692. [PubMed]
9. Porto L, Lora K, Soares J, Costa L. Metabolic syndrome is an independent risk factor for breast cancer. Arch Gynecol Obstet. 2011;284:1271–1276. [PubMed]
10. Osaki Y, Taniguchi S-i, Tahara A, Okamoto M, Kishimoto T. Metabolic syndrome and incidence of liver and breast cancers in Japan. Cancer Epidemiol. 2012;36:141–147. [PubMed]
11. Rose DP, Haffner SM, Baillargeon J. Adiposity, the metabolic syndrome, and breast cancer in African-American and white American women. Endocrine Rev. 2007;28:763–777. [PubMed]
12. Huang Z, Willett WC, Colditz GA, Hunter DJ, Manson JE, Rosner B, Speizer FE, Hankinson SE. Waist circumference, waist: hip ratio, and risk of breast cancer in the Nurses’ Health Study. Am J Epidemiol. 1999;150:1316–1324. [PubMed]
13. Michels KB, Solomon CG, Hu FB, Rosner BA, Hankinson SE, Colditz GA, Manson JE. Type 2 diabetes and subsequent incidence of breast cancer in the Nurses’™ Health Study. Diabetes Care. 2003;26:1752–1758. [PubMed]
14. Xue F, Michels KB. Diabetes, metabolic syndrome, and breast cancer: a review of the current evidence. Am J Clin Nutr. 2007;86:823S–835S. [PubMed]
15. Wolf I, Sadetzki S, Catane R, Karasik A, Kaufman B. Diabetes mellitus and breast cancer. Lancet Oncol. 2005;6:103–111. [PubMed]
16. Vona-Davis L, Howard-McNatt M, Rose DP. Adiposity, type 2 diabetes and the metabolic syndrome in breast cancer. Obes Rev. 2007;8:395–408. [PubMed]
17. Largent JA, McEligot AJ, Ziogas A, Reid C, Hess J, Leighton N, Peel D, Anton-Culver H. Hypertension, diuretics and breast cancer risk. J Hum Hypertens. 2006;20:727–732. [PubMed]
18. Soler M, Chatenoud L, Negri E, Parazzini F, Franceschi S, La Vecchia C. Hypertension and hormone-related neoplasms in women. Hypertension. 1999;34:320–325. [PubMed]
19. Furberg A-S, Veierod MB, Wilsgaard T, Bernstein L, Thune I. Serum high-density lipoprotein cholesterol, metabolic profile, and breast cancer risk. J Natl Cancer Inst. 2004;96:1152–1160. [PubMed]
20. Libby G, Donnelly LA, Donnan PT, Alessi DR, Morris AD, Evans JMM. New users of metformin are at low risk of incident cancer. Diabetes Care. 2009;32:1620–1625. [PMC free article] [PubMed]
21. Moorman PG, Hulka BS, Hiatt RA, Krieger N, Newman B, Vogelman JH, Orentreich N. Association between high-density lipoprotein cholesterol and breast cancer varies by menopausal status. Cancer Epidemiol Biomark Prev. 1998;7:483–488. [PubMed]
22. Morimoto LM, White E, Chen Z, Chlebowski RT, Hays J, Kuller L, Lopez AM, Manson JE, Margolis KL, Muti P, et al. Obesity, body size, and risk of postmenopausal breast cancer: the Women’s Health Initiative (United States) Cancer Causes Control. 2002;13:741–751. [PubMed]
23. Eliassen AH, Colditz GA, Rosner B, Willett WC, Hankinson SE. Serum lipids, lipid-lowering drugs, and the risk of breast cancer. Arch Intern Med. 2005;165:2264–2271. [PubMed]
24. Kucharska-Newton AM, Rosamond WD, Mink PJ, Alberg AJ, Shahar E, Folsom AR. HDL-cholesterol and incidence of breast cancer in the ARICCohort Study. Ann Epidemiol. 2008;18:671–677. [PMC free article] [PubMed]
25. Palmer JR, Adams-Campbell LL, Boggs DA, Wise LA, Rosenberg L. A prospective study of body size and breast cancer in black women. Cancer Epidemiol Biomark Prev. 2007;16:1795–1802. [PubMed]
26. Palmer JR, Rao SR, Adams-Campbell LL, Rosenberg L. Height and breast cancer risk: results from the Black Women’s Health Study (United States) Cancer Causes Control. 2001;12:343–348. [PubMed]
27. Wise LA, Palmer JR, Spiegelman D, Harlow BL, Stewart EA, Adams-Campbell LL, Rosenberg L. Influence of body size and body fat distribution on risk of uterine leiomyomata in U.S. black women. Epidemiology. 2005;16:346–354. [PMC free article] [PubMed]
28. Krishan S, Rosenberg L, Djousse L, Cupple LA, Palmer JR. Overall and central obesity and risk of type 2 diabetes. Obesity. 2007;15:1860–1866. [PubMed]
29. Cozier Y, Palmer JR, Horton NJ, Fredman L, Wise LA, Rosenberg L. Racial discrimination and the incidence of hypertension in US black women. Ann Epidemiol. 2006;16:681–687. [PubMed]
30. Stephenson GD, Rose DP. Breast cancer and obesity: an update. Nutr Cancer. 2003;45:1–6. [PubMed]
31. Monninkhof EM, Elias SG, Vlems FA, van der Tweel I, Schuit AJ, Voskuil DW, van Leeuwen FE. on behalf of TFPAC. Physical activity and breast cancer: a systematic review. Epidemiology. 2007;18:137–157. [PubMed]
32. Band PR, Le ND, Fang R, Deschamps M. Carcinogenic and endocrine disrupting effects of cigarette smoke and risk of breast cancer. Lancet. 2002;360:1044–1049. [PubMed]
33. Boffetta P, Hashibe M. Alcohol and cancer. Lancet Oncol. 2006;7:149–156. [PubMed]
34. Kelsey JL. Breast cancer epidemiology: summary and future directions. Epidemiol Rev. 1993;15:256–263. [PubMed]
35. Kelsey JL, Gammon MD, John EM. Reproductive factors and breast cancer. Epidemiol Rev. 1993;15:36–47. [PubMed]
36. Kelsey JL, Horn-Ross PL. Breast cancer: magnitude of the problem and descriptive epidemiology. Epidemiol Rev. 1993;15:7–16. [PubMed]
37. Carter-Nolan PL, Adams-Campbell LL, Makambi K, Lewis S, Palmer JR, Rosenberg L. Validation of physical activity instruments: Black Women’s Health Study. Ethn Dis. 2006;16:943–947. [PubMed]
38. Cox DR. Regression models and life-tables. J R Stat Soc B (Methodol) 1972;34:187–220.
39. Therneau TM, Grambsch PM. Modeling survival data: extending the Cox model. New York: Springer; 2000.
40. Rose DP, Komninou D, Stephenson G. Obesity, adipocytokines, and insulin resistance in breast cancer. Obes Rev. 2004;5:153–165. [PubMed]
41. Kabat GC, Kim M, Caan BJ, Chlebowski RT, Gunter MJ, Ho GY, Rodriguez BL, Shikany JM, Strickler HD, Vitolins MZ, et al. Repeated measures of serum glucose and insulin in relation to postmenopausal breast cancer. Int J Cancer. 2009;125:2704–2710. [PubMed]
42. Lorincz AM, Sukumar S. Molecular links between obesity and breast cancer. Endocr Relat Cancer. 2006;13:279–292. [PubMed]
43. Mink PJ, Shahar E, Rosamond WD, Alberg AJ, Folsom AR. Serum insulin and glucose levels and breast cancer incidence. Am J Epidemiol. 2002;156:349–352. [PubMed]
44. Pollak M. Insulin and insulin-like growth factor signalling in neoplasia. Nat Rev Cancer. 2008;8:915–928. [PubMed]
45. Bruning PF. Endogenous estrogens and breast cancer a possible relationship between body fat distribution and estrogen availability. J Steroid Biochem Mol Biol. 1987;27:487–492. [PubMed]
46. Tworoger SS, Eliassen AH, Kelesidis T, Colditz GA, Willett WC, Mantzoros CS, Hankinson SE. Plasma adiponectin concentrations and risk of incident breast cancer. J Clin Endocrinol Metab. 2007;92:1510–1516. [PubMed]
47. Fast Stats: an interactive tool for access to SEER cancer statistics. [Last accessed 21 Nov 2010]; http://seer.cancer.gov/faststats.
48. Kaaks R, Van Noord PAH, Den Tonkelaar I, Peeters PHM, Riboli E, Grobbee DE. Breast-cancer incidence in relation to height, weight and body-fat distribution in the Dutch “DOM” cohort. Int J Cancer. 1998;76:647–651. [PubMed]
49. Hall IJ, Newman B, Millikan RC, Moorman PG. Body size and breast cancer risk in black women and white women: the Carolina Breast Cancer Study. Am J Epidemiol. 2000;151:754–764. [PubMed]
50. Lahmann PH, Hoffmann K, Allen N, van Gils CH, Khaw K-T, Tehard B, Berrino F, Tjønneland A, Bigaard J, Olsen A, et al. Body size and breast cancer risk: findings from the European prospective investigation into cancer and nutrition (EPIC) Int J Cancer. 2004;111:762–771. [PubMed]
51. Adebamowo C, Ogundiran T, Adenipekun A, Oyesegun R, Campbell O, Akang E, Rotimi C, Olopade O. Waist-hip ratio and breast cancer risk in urbanized Nigerian women. Breast Cancer Res. 2003;5:R18–R24. [PMC free article] [PubMed]
52. Ballard-Barbash R, Schatzkin A, Carter CL, Kannel WB, Kreger BE, D’Agostino RB, Splansky GL, Anderson KM, Helsel WE. Body fat distribution and breast cancer in the Framingham Study. J Natl Cancer Inst. 1990;82:286–290. [PubMed]
53. Folsom AR, Kaye SA, Prineas RJ, Potter JD, Gapstur SM, Wallace RB. Increased incidence of carcinoma of the breast associated with abdominal adiposity in postmenopausal women. Am J Epidemiol. 1990;131:794–803. [PubMed]
54. Sonnenschein E, Toniolo P, Terry MB, Bruning PF, Kato I, Koenig KL, Shore RE. Body fat distribution and obesity in pre- and postmenopausal breast cancer. Int J Epidemiol. 1999;28:1026–1031. [PubMed]
55. Lipscombe LL, Goodwin PJ, Zinman B, mclaughlin JR, Hux JE. Diabetes mellitus and breast cancer: a retrospective population-based cohort study. Breast Cancer Res Treat. 2006;98:349–356. [PubMed]
56. Weiderpass E, Gridley G, Persson I, Nyre´n O, Ekbom A, Adami H-O. Risk of endometrial and breast cancer in patients with diabetes mellitus. Int J Cancer. 1997;71:360–363. [PubMed]
57. Baron J, Weiderpass E, Newcomb P, Stampfer M, Titus-Ernstoff L, Egan K, Greenberg ER. Metabolic disorders and breast cancer risk (United States) Cancer Causes Control. 2001;12:875–880. [PubMed]
58. Talamini R, Franceschi S, Favero A, Negri E, Parazzini F, La Vecchia C. Selected medical conditions and risk of breast cancer. Br J Cancer. 1997;75:1699–1703. [PMC free article] [PubMed]
59. Franceschi S, La Vecchia C, Negri E, Parazzini F, Boyle P. Breast cancer risk and history of selected medical conditions linked with female hormones. Eur J Cancer. 1990;26:781–785. [PubMed]
60. Sellers T, Sprafka J, Gapstur S, Rich S, Potter J, Ross J, McGovern P, Nelson C, Folsom A. Does body fat distribution promote familial aggregation of adult onset diabetes mellitus and postmenopausal breast cancer? Epidemiology. 1994;5:102–108. [PubMed]
61. Swerdlow AJ, Laing SP, Qiao Z, Slater SD, Burden AC, Botha JL, Waugh NR, Morris AD, Gatling W, Gale EA, et al. Cancer incidence and mortality in patients with insulin-treated diabetes: a UK cohort study. Br J Cancer. 2005;92:2070–2075. [PMC free article] [PubMed]
62. Inoue M, Iwasaki M, Otani T, Sasazuki S, Noda M, Tsugane S. for the Japan Public Health Center-Based Prospective Study Group. Diabetes mellitus and the risk of cancer: results from a large-scale population-based cohort study in Japan. Arch Intern Med. 2006;166:1871–1877. [PubMed]
63. Lindgren A, Pukkala E, Tuomilehto J, Nissinen A. Incidence of breast cancer among postmenopausal, hypertensive women. Int J Cancer. 2007;121:641–644. [PubMed]
64. Furberg A-S, Jasienska G, Bjurstam N, Torjesen PA, Emaus A, Lipson SF, Ellison PT, Thune I. Metabolic and hormonal profiles: HDL cholesterol as a plausible biomarker of breast cancer risk. The Norwegian EBBA Study. Cancer Epidemiol Biomark Prev. 2005;14:33–40. [PubMed]
65. Rimm EB, Stampfer MJ, Colditz GA, Chute CG, Litin LB, Willett WC. Validity of self-reported waist and hip circumferences in men and women. Epidemiology. 1990;1:466–473. [PubMed]
66. Rose DP, Vona-Davis L. Interaction between menopausal status and obesity in affecting breast cancer risk. Maturitas. 2010;66:33–38. [PubMed]
67. White KK, Park S-Y, Kolonel LN, Henderson BE, Wilkens LR. Body size and breast cancer risk: the Multiethnic Cohort. Int J Cancer. 2012 [PubMed]
68. Rollison DE, Giuliano AR, Sellers TA, Laronga C, Sweeney C, Risendal B, Baumgartner KB, Byers T, Slattery ML. Population-based case-control study of diabetes and breast cancer risk in Hispanic and non-Hispanic white women living in US Southwestern States. Am J Epidemiol. 2008;167:447–456. [PMC free article] [PubMed]
69. Bodmer M, Meier C, Krähenbühl S, Jick SS, Meier CR. Long-term metformin use is associated with decreased risk of breast cancer. Diabetes Care. 2010;33:1304–1308. [PMC free article] [PubMed]
70. Jonasson JM, Ljung R, Talbäck M, Haglund B, Gudbjörnsdòttir S, Steineck G. Insulin glargine use and short-term incidence of malignancies—a population-based follow-up study in Sweden. Diabetologia. 2009;52:1745–1754. [PubMed]
71. Bosco JLF, Antonsen S, Sørensen HT, Pedersen L, Lash TL. Metformin and incident breast cancer among diabetic women: a population-based case-control study in Denmark. Cancer Epidemiol Biomark Prev. 2011;20:101–111. [PubMed]
72. Moysich KB, Beehler GP, Zirpoli G, Choi J-Y, Baker JA. Use of common medications and breast cancer risk. Cancer Epidemiol Biomark Prev. 2008;17:1564–1595. [PubMed]
73. Rose DP, Royak-Schaler R. Tumor biology and prognosis in black breast cancer patients: a review. Cancer Detect Prev. 2001;25:16–31. [PubMed]
74. Adams-Campbell LL, Rosenberg L, Rao RS, Palmer JR. Strenuous physical activity and breast cancer risk in African-American women. J Natl Med Assoc. 2001;93:267–275. [PMC free article] [PubMed]
75. Cozier Y, Palmer JR, Rosenberg L, Adams-Campbell LL. Recent mammography use among African-American women. Ethn Dis. 2001;11:188–191. [PubMed]