Search tips
Search criteria 


Logo of jcoHomeThis ArticleSearchSubmitASCO JCO Homepage
J Clin Oncol. 2011 September 1; 29(25): 3358–3365.
Published online 2011 July 25. doi:  10.1200/JCO.2010.34.2048
PMCID: PMC3164241

Obesity and Survival Among Black Women and White Women 35 to 64 Years of Age at Diagnosis With Invasive Breast Cancer



To evaluate the effect of obesity on survival among black women and white women with invasive breast cancer and to determine whether obesity explains the poorer survival of black women relative to white women.

Patients and Methods

We observed 4,538 (1,604 black, 2,934 white) women who were 35 to 64 years of age when diagnosed with incident invasive breast cancer between 1994 and 1998. Multivariate Cox regression models were used to examine the effect of body mass index (BMI, in kilograms per square meter) 5 years before diagnosis on risk of death from any cause and from breast cancer.


During a median of 8.6 years of follow-up, 1,053 women died (519 black, 534 white), 828 as a result of breast cancer (412 black, 416 white). Black women were more likely to die than white women (multivariate-adjusted relative risk [RR], 1.33; 95% CI, 1.16 to 1.53). Compared with women with BMI of 20 to 24.9 kg/m2, those who were obese (BMI ≥ 30 kg/m2) had a greater risk of all-cause mortality (RR, 1.23; 95% CI, 1.04 to 1.47) and breast cancer–specific mortality (RR, 1.20; 95% CI, 0.99 to 1.46). These associations were observed among white women (all-cause RR, 1.54; 95% CI, 1.21 to 1.96; breast cancer RR, 1.46; 95% CI, 1.11 to 1.92), but not among black women (all-cause RR, 1.03; 95% CI, 0.81 to 1.29; breast cancer RR, 1.02; 95% CI, 0.79 to 1.33).


Obesity may play an important role in mortality among white but not black patients with breast cancer. It is unlikely that differences in obesity distributions between black women and white women account for the poorer survival of black women.


Although breast cancer–specific mortality rates have decreased for both black women and white women,1 rates have decreased less among black women, and sizable survival disparity remains.2,3 The 5-year US relative breast cancer survival rates for women diagnosed between 1999 and 2006 were 78% for blacks and 90% for whites.3 Epidemiologic studies have suggested that obesity or high body mass index (BMI, measured in kilograms per square meter) before breast cancer diagnosis is associated with increased mortality risk.413 It has been well documented that black women have higher prevalence of obesity and are more likely to be diagnosed at more advanced stages of breast cancer than white women.1416 However, whether obesity explains the racial disparity in survival is largely unknown.

To explore whether obesity accounts for the black–white disparity in breast cancer survival, we examined whether BMI before diagnosis affects risk of all-cause and breast cancer–specific mortality among black women and white women with invasive breast cancer who participated in a large multicenter, population-based, case-control study.


Study Design

Participants were breast cancer patients enrolled in the Women's Contraceptive and Reproductive Experiences (CARE) Study, a population-based, multicenter, case-control study designed to examine risk factors for invasive breast cancer among black women and white women.17 Women 35 to 64 years of age diagnosed with histologically confirmed incident invasive breast cancer (International Classification of Diseases for Oncology codes C50.0–C50.9) from July 1994 through April 1998 were randomly sampled from five field sites: Atlanta, Detroit, Los Angeles, Philadelphia, and Seattle. Black women were oversampled to maximize their numbers in the study, and white women were sampled to provide approximately equal numbers of women in each 5-year age category (35 to 39, 40 to 44, 45 to 49, 50 to 54, 55 to 59, and 60 to 64 years). Among 5,982 eligible patients with breast cancer, 4,575 (76.5%) participated in this study, including 1,622 black women (72.2% of eligible patients) and 2,953 white women (79.1% of eligible patients). The Women's CARE Study protocol was approved by the institutional review boards at participating institutions.

We abstracted stage of tumor at diagnosis, estrogen receptor (ER) status, and progesterone receptor (PR) status from Surveillance, Epidemiology, and End Results (SEER) registry records at the four SEER sites (Atlanta, Detroit, Los Angeles, and Seattle) and directly from medical records in Philadelphia.

Shortly after breast cancer diagnosis, trained staff administered standardized in-person interviews to collect detailed information on exposures before breast cancer diagnosis, including demographic characteristics, tallest height without shoes (in feet and inches), weight (in pounds) 5 years before breast cancer diagnosis, disease history and medical conditions, reproductive history, exogenous hormone use, mammography use, and histories of recreational physical activity, smoking, and alcohol consumption. Women were interviewed, on average, 5.1 months after diagnosis.

All interviewed patients from the Women's CARE Study were followed up annually for vital status, date of death, and cause of death. The four SEER-based field sites used standard SEER follow-up procedures. The Philadelphia field site used state death records to track vital status. Patients from the Atlanta, Detroit, and Seattle study sites were followed up through December 31, 2004; follow-up extended through December 2005 in Philadelphia and through December 2007 in Los Angeles.

We excluded 37 women who died as a result of injury, poisoning, and certain other consequences of external cause (n = 9), were immediately lost to follow-up (n = 2), or had missing information on education or BMI 5 years before diagnosis (n = 26). Thus our analytic cohort consisted of 1,604 black women and 2,934 white women.

Statistical Analysis

Our end points were death resulting from any cause and death resulting from breast cancer (International Classification of Diseases codes ICD9-174, ICD10-C50). Kaplan-Meier curves were constructed to describe the survival experience of the study population stratified by race (black v white) and BMI 5 years before diagnosis (obese [BMI ≥ 30 kg/m2] v nonobese [BMI < 30 kg/m2]). To compare survival across the four subgroups, we performed pairwise comparisons using the log-rank test, and we imposed a Bonferroni correction to the P value, restricting the overall type I error rate to 5% by considering only two-sided P values less than .008 as statistically significant for each pairwise comparison of obesity across the two race groups.18

Self-reported height and weight 5 years before diagnosis were used to calculate BMI, which was categorized into thin (< 20 kg/m2), normal weight (20 to 24.9 kg/m2), overweight (25 to 29.9 kg/m2), or obese (≥ 30 kg/m2).19

Multivariate Cox proportional hazards regression models provided estimates of the hazard rate ratio of death, a measure of relative risk (RR), and 95% CI. Age in days at diagnosis and age in days at death or end of follow-up defined the time scale for analysis. In the analyses of breast cancer–specific mortality, women who died from other causes were censored on their dates of death. All statistical multivariate models were stratified by age in years at diagnosis and adjusted for study site (Atlanta, Detroit, Los Angeles, Philadelphia, Seattle), race (black, white), education (less than high school, high school, some college, college graduate), tumor stage (localized, nonlocalized), ER status (positive, negative, unknown), and number of comorbidities before breast cancer diagnosis (zero, one, two or more). Comorbidities included hypertension, myocardial infarction, stroke, diabetes, and cancers other than nonmelanoma skin cancers. We also assessed the influence of additional potential confounders, including first-degree family history of breast cancer, alcohol consumption level, smoking history, average intensity-hours per week of physical activity, age at menarche, parity, number of full-term pregnancies, months of breastfeeding, lifetime total number of mammograms, months of oral contraceptive use, menopausal status, and months of postmenopausal hormonal use. As none of these factors substantially influenced the RR estimates, none were included in the final models.

We performed tests for trend for ordinal variables by fitting the median value for each category as a continuous variable. To test whether the association between BMI 5 years before diagnosis and mortality was modified by race, we constructed a likelihood ratio test comparing two multivariate Cox proportional hazards models (likelihood ratio test for heterogeneity of trends with 1 df).20 We further examined the effect of BMI on mortality among black women and white women stratified by ER status, tumor stage, menopausal status, and education level. Results for models based on ER and PR status, although based on smaller numbers for ER-positive/PR-positive and ER-negative/PR-negative tumors, were consistent with those presented here stratified by ER status. The assumption of proportionality of hazards was assessed for each final model; no violation of the proportional hazards assumption was observed. Two-sided P values are reported. We did not adjust P values for multiple comparisons. All statistical analyses were performed using SAS version 9.2 software (SAS Institute, Cary, NC).


The mean age at breast cancer diagnosis was 49.7 years among these women who were, by design, sampled from women diagnosed at ages 35 to 64 years. During a median follow-up of 8.6 years, 1,053 women died (519 black, 534 white), 828 as a result of breast cancer (412 black, 416 white). Overall, 786 women (17.3%) were obese (BMI ≥ 30 kg/m2) 5 years before breast cancer diagnosis (26.9% of black women; 12.1% of white women; Table 1). Obese women were more likely to be older, have low education levels, be postmenopausal, have more comorbidities, and be diagnosed with nonlocalized tumors. Black women were more likely to have low education levels, have more comorbidities, and be diagnosed with nonlocalized tumors or ER-negative tumors.

Table 1.
Distribution of Selected Characteristics at Diagnosis of Patients With Breast Cancer According to BMI 5 Years Before Diagnosis and Race

The RRs for mortality associated with the demographic and tumor characteristics are shown in Table 2. Older women and women with lower levels of education, more comorbidities, ER-negative tumors, or nonlocalized tumors had higher risks of mortality. Within each demographic and tumor characteristics stratum, black women had a higher risk of mortality than white women, except for women who had two or more comorbidities.

Table 2.
Selected Characteristics at Diagnosis of Patients With Breast Cancer, Race, and RRs of Mortality

The mortality risk for black women was nearly twice that of white women (RR = 1.90; 95% CI, 1.68 to 2.14). The RR decreased to 1.68 (95% CI, 1.47 to 1.91) when education and study site were included in the Cox model and decreased further when tumor characteristics (tumor stage, ER status) and comorbidities were added to this model (RR = 1.36; 95% CI, 1.19 to 1.57). Adjusting this latter model for BMI 5 years before diagnosis did not fundamentally change the RR from this latter model (RR = 1.33; 95% CI, 1.16 to 1.53). Considering that BMI is associated with tumor characteristics and comorbidities, we also conducted analyses that adjusted for BMI before adding tumor characteristics and comorbidities into the model. Nevertheless, the RR risk only changed from 1.68 to 1.57 (95% CI, 1.37 to 1.80) when adding BMI to a model that included only education level and study site. Similar risk patterns were observed when using breast cancer–specific mortality as the outcome of interest.

Figures 1A andand1B1B show Kaplan-Meier survival curves for black women and white women stratified by obesity status 5 years before diagnosis. A survival difference was observed between nonobese and obese white women (log-rank P < .001 for all-cause and for breast cancer–specific mortality), but not between nonobese and obese black women. In fact, curves for black women (obese and nonobese) did not differ from those of obese white women.

Fig 1.
(A) Kaplan-Meier all-cause survival of black and white women diagnosed with invasive breast cancer stratified by obesity status 5 years before breast cancer diagnosis. (B) Kaplan-Meier breast cancer–specific survival of black and white women diagnosed ...

Obese women overall had a 20% greater risk of dying as a result of any cause (P trend = .01; RR, 1.23; 95% CI, 1.04 to 1.47) or breast cancer (P trend = .03; RR, 1.20; 95% CI, 0.99 to 1.46) than women with BMI in the normal range (Table 3). Obese white women had a 54% greater risk of all-cause mortality than the reference group (P trend < .01; RR, 1.54; 95% CI, 1.21 to 1.96); however, no such association was observed for black women. The trends for black women and white women were statistically significantly different (P for homogeneity of trends = .03). Similar risk patterns were observed for breast cancer–specific mortality.

Table 3.
RR Estimates and 95% CIs for the Association Between BMI 5 Years Before Diagnosis and Risk of Mortality in the Women's CARE Study

When we examined the association between BMI 5 years before diagnosis, race, and mortality stratified by ER status, tumor stage, menopausal status, and education level, we observed risk patterns similar to those presented overall; that is, within these strata we ob served the positive association among white women and the null results among black women across all strata except that of black women with nonlocalized tumors and of white women with low education (no more than high school education; Table 4). Among black women with nonlocalized tumors, obese women had slightly increased mortality risk associated with BMI 5 years before diagnosis (all-cause P trend = .07; RR for obese women, 1.25; 95% CI, 0.93 to 1.66; breast cancer P trend = .04; RR for obese women, 1.31; 95% CI, 0.97 to 1.78). Similar to the results for black women, among white women with no more than a high school education, obesity was not associated with all cause (P trend = .66) or breast cancer mortality (P trend = .60).

Table 4.
RR Estimates and 95% CIs for the Association Between BMI 5 Years Before Diagnosis and Risk of Mortality in Black and White Women in the Women's CARE Study


In this large, population-based study of black women and white women diagnosed with invasive breast cancer between ages 35 and 64 years, black women had greater risk of mortality than white women overall. High BMI 5 years before diagnosis was associated with increased risk of all-cause and breast cancer–specific mortality among white women, but not among black women.

Because black women generally have a higher prevalence of obesity than white women at the time of breast cancer diagnosis, several authors have postulated that obesity could explain some of the observed racial differences in mortality.2124 However, our data do not support this hypothesis. Black women were more likely than white women to have lower education levels, ER-negative tumors, nonlocalized tumors, and comorbidities. All of these factors were associated with increased risk of mortality. After considering age, education, study site, tumor stage, ER status, and comorbidities, obesity did not further explain any differences in mortality risk between black women and white women. The study by Chlebowski et al25 showed a continuing racial difference in mortality after adjusting for BMI. However, the number of deaths among black women was small (n = 21), and the median follow-up was only 3.1 years. Further, this study did not address the extent to which inclusion of BMI in the model affected the risk estimates, nor were they able to look separately for black and white women at how BMI affected risk.25

Our results showing increased risk of mortality for obese white women compared with normal-weight white women are consistent with those of most previous studies,413 although results stratified by tumor characteristics are not totally consistent with previous studies. Our data and others4,5,10 show that obese women were more likely to be diagnosed with later-stage tumors. We, and one other study,4 observed similar obesity-survival risk patterns among women with different tumor stages. In contrast, another study reported a stronger association among women with early-stage tumors.6 However, the number of women with later-stage tumors was relatively small in the latter study (n = 192).6 Previous studies have demonstrated that obesity is more strongly associated with developing ER-positive tumors than ER-negative tumors.25 For survival, our study and others have suggested that no differences exist in the obesity-survival association by ER status.4,6,8 However, a recent study with a small number of deaths (n = 87) reported that obesity was not associated with overall survival among women with triple-negative breast cancer.26 These results suggest that mechanisms involved in the obesity-incidence association may differ from those involved in the obesity-survival association.

It has been hypothesized that adiposity affects breast cancer prognosis by elevating circulating levels of endogenous estrogen that result from the conversion of adrenal androgens to estrogen in peripheral adipose tissue,27 lowering circulating levels of sex hormone–binding globulin,28 increasing insulin resistance,29 and increasing insulin-like growth factor-1 levels.30 Furthermore, adipose tissue produces leptin and a group of other growth factors (eg, interleukin-6, tumor necrosis factor-α, vascular endothelial growth factor) that may stimulate angiogenesis, lead to more rapid growth of malignant cells, and promote metastasis.3133

Another possible explanation for the adverse effect of obesity on mortality is attributed to the more advanced tumor stage associated with obesity.3335 Among women with nonlocalized tumors, but not among women with localized tumors, we observed increased risk of mortality with obesity, especially breast cancer–specific mortality, for both black women and white women. Thus the obesity-mortality association may reflect the more advanced stage at cancer diagnosis.

It is not clear why obesity-associated mortality risk patterns differ between black women and white women with breast cancer. The Cancer Prevention Study II with a cohort of participants free of cancer at baseline examined the effect of BMI on the risk of fatal breast cancer.22 Of interest, the authors found that higher BMI at baseline was positively associated with fatal breast cancer among white women, but not among black women.22 Furthermore, increasing evidence suggests a stronger association between BMI and coronary heart disease, stroke, and cardiovascular disease mortality among white than among black individuals.36 In our study, normal-weight black women had 53% (95% CI, 24% to 88%) greater risk of all-cause mortality than normal-weight white women, but obese black women did not have greater risk of all-cause mortality than obese white women (RR, 1.02; 95% CI, 0.78 to 1.32); these risk patterns were consistent across all strata examined. Thus other factors such as different cultural, social environmental, psychological, and behavioral factors; health care quality and access; and biologic characteristics that are associated with both obesity and survival may be a partial explanation for black women's higher mortality.

A major strength of our study is the large, population-based sampling of black women and white women. To our knowledge, our study is the first to examine the association of mortality with BMI between black women and white women with invasive breast cancer living in the same geographical regions. The detailed information on a large number of potential risk factors for breast cancer incidence and mortality enabled us to assess many potential confounders, build appropriate multivariate models, and evaluate possible effect modifiers. Finally, our high rate and long duration of follow-up (median, 8.6 years; 25th to 75th percentiles, 7.1 to 10.1 years) enabled us to have large numbers of events.

A limitation is that our results are not generalizable to all patients with breast cancer. In the United States, 57% of women diagnosed with invasive breast cancer are between the ages of 35 and 64 years.3 Our results apply only to women in this age range. Further, self-reported measures of body size may be inaccurate, with heavier women more likely to underreport their weights.14,37 Such measurement error would be expected to be nondifferential with respect to mortality, resulting in attenuation of the true underlying associations. Importantly, the validity of self-reported data on weight among black women is similar to that of white women.38 We were unable to assess BMI at diagnosis or weight change after diagnosis, which were of prognostic value in some studies.39,40 Prior studies show no evidence to suggest that women's weight in the few years before cancer diagnosis differs much from their weight at diagnosis.41,42 Further, prediagnosis body weight may be a stronger predictor of mortality than weight gain after diagnosis.9,12

Although we lacked information on the breast cancer therapies, we have presumed that controlling for age, stage of disease, and hormone receptor status has provided some control for treatment. Nevertheless, previous studies have suggested that black women may have less optimal treatment than white women. They are more likely to delay the initiation of treatment,43 less likely to receive radiation therapy or appropriate dose-intensities of adjuvant chemotherapy,44,45 more likely to terminate treatment prematurely,46 and less likely to adhere to recommended treatment regimens44,45 than white women. However, we found no data regarding whether obese black women's treatment differs from that of normal weight black women. Further, the lack of data on human epidermal growth factor receptor 2 expression prevented informative analyses of the obesity-survival association for women with triple-negative subtype.

Because we did not adjust for multiple testing in our assessment of main effects and stratified analyses, some results (eg, that for the inverse BMI association with decreasing breast cancer mortality among black women) may be false positives and due to few deaths in some strata. Additionally, the results for thin women (BMI < 20 kg/m2) may not be as informative as those for heavier women given the small number of thin women.

In summary, we find that obesity 5 years before breast cancer diagnosis is an independent predictor of survival among white women ages 35 to 64 years, but not among black women in this age group. These findings suggest that differences in the distribution of obesity among black women and white women diagnosed with breast cancer are unlikely to account for the poorer survival of black women.


We thank James V. Lacey Jr, PhD, for his comments on the manuscript.


Support information appears at the end of this article.

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.

Presented in part at the New Investigators Workshop, American Society of Preventive Oncology Annual Meeting, March 21-23, 2010, Bethesda, MD; and at the 102nd American Association for Cancer Research Annual Meeting, April 2-6, 2011, Orlando, FL.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.


Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a “U” are those for which no compensation was received; those relationships marked with a “C” were compensated. For a detaileddescription of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of of Potential Conflicts of Interest section in Information for Contributors.

Employment or Leadership Position: None Consultant or Advisory Role: Michael F. Press, sanofi-aventis (C), GlaxoSmithKline (C), Ventana Medical System (C) Stock Ownership: None Honoraria: None Research Funding: Michael F. Press, Genentech, Ventana Medical System Expert Testimony: None Other Remuneration: None


Conception and design: Yani Lu, Kathleen E. Malone, Polly A. Marchbanks, Robert Spirtas, Dennis Deapen, Jill A. McDonald, Leslie Bernstein

Financial support: Robert Spirtas, Leslie Bernstein

Administrative support: Yani Lu, Leslie Bernstein

Provision of study materials or patients: Kathleen E. Malone, Sandra A. Norman, Brian L. Strom, Dennis Deapen, Michael F. Press, Leslie Bernstein

Collection and assembly of data: Yani Lu, Kathleen E. Malone, Sandra A. Norman, Jane Sullivan-Halley, Brian L. Strom, Polly A. Marchbanks, Dennis Deapen, Suzanne G. Folger, Michael F. Press, Jill A. McDonald, Leslie Bernstein

Data analysis and interpretation: Yani Lu, Huiyan Ma, Sandra A. Norman, Brian L. Strom, Polly A. Marchbanks, Ronald T. Burkman, Michael S. Simon, Leslie Bernstein

Manuscript writing: All authors

Final approval of manuscript: All authors


Supported by the California Breast Cancer Research Program (Grant No. 15FB-0004). The Women's Contraceptive and Reproductive Experiences Study was funded by the National Institute of Child Health and Human Development, with additional support from the National Cancer Institute, through contracts with Emory University (Grant No. N01-HD-2-3168), Fred Hutchinson Cancer Research Center (Grant No. N01-HD-2-3166), Karmanos Cancer Institute at Wayne State University (Grant No. N01-HD-3-3174), the University of Pennsylvania (Grant No. N01-HD-3-3176), and the University of Southern California (Grant No. N01-HD-3-3175), and through an intra-agency agreement with the US Centers for Disease Control and Prevention (Grant No. Y01-HD-7022). Support for use of Surveillance, Epidemiology, and End Results cancer registries for case identification was through Grants No. N01-PC-67006 (Atlanta), N01-CN-65064 (Detroit), N01-PC-67010 (Los Angeles), and N01-CN-05230 (Seattle).


1. Edwards BK, Ward E, Kohler BA, et al. Annual report to the nation on the status of cancer, 1975-2006, featuring colorectal cancer trends and impact of interventions (risk factors, screening, and treatment) to reduce future rates. Cancer. 2010;116:544–573. [PubMed]
2. Jemal A, Siegel R, Ward E, et al. Cancer statistics, 2008. CA Cancer J Clin. 2008;58:71–96. [PubMed]
3. Altekruse SF, Kosary CL, Krapcho M, et al. Bethesda, MD: National Cancer Institute; 2010. SEER Cancer Statistics Review, 1975-2007 based on November 2009 SEER data submission, posted to the SEER web site.
4. Chen X, Lu W, Zheng W, et al. Obesity and weight change in relation to breast cancer survival. Breast Cancer Res Treat. 2010;122:823–833. [PubMed]
5. Majed B, Moreau T, Senouci K, et al. Is obesity an independent prognosis factor in woman breast cancer? Breast Cancer Res Treat. 2008;111:329–342. [PubMed]
6. Dal Maso L, Zucchetto A, Talamini R, et al. Effect of obesity and other lifestyle factors on mortality in women with breast cancer. Int J Cancer. 2008;123:2188–2194. [PubMed]
7. Whiteman MK, Hillis SD, Curtis KM, et al. Body mass and mortality after breast cancer diagnosis. Cancer Epidemiol Biomarkers Prev. 2005;14:2009–2014. [PubMed]
8. Loi S, Milne RL, Friedlander ML, et al. Obesity and outcomes in premenopausal and postmenopausal breast cancer. Cancer Epidemiol Biomarkers Prev. 2005;14:1686–1691. [PubMed]
9. Kroenke CH, Chen WY, Rosner B, et al. Weight, weight gain, and survival after breast cancer diagnosis. J Clin Oncol. 2005;23:1370–1378. [PubMed]
10. Bastarrachea J, Hortobagyi GN, Smith TL, et al. Obesity as an adverse prognostic factor for patients receiving adjuvant chemotherapy for breast cancer. Ann Intern Med. 1994;120:18–25. [PubMed]
11. Barnett GC, Shah M, Redman K, et al. Risk factors for the incidence of breast cancer: Do they affect survival from the disease? J Clin Oncol. 2008;26:3310–3316. [PubMed]
12. Caan BJ, Kwan ML, Hartzell G, et al. Pre-diagnosis body mass index, post-diagnosis weight change, and prognosis among women with early stage breast cancer. Cancer Causes Control. 2008;19:1319–1328. [PMC free article] [PubMed]
13. Abrahamson PE, Gammon MD, Lund MJ, et al. General and abdominal obesity and survival among young women with breast cancer. Cancer Epidemiol Biomarkers Prev. 2006;15:1871–1877. [PubMed]
14. Ogden CL, Carroll MD, Curtin LR, et al. Prevalence of overweight and obesity in the United States, 1999-2004. JAMA. 2006;295:1549–1555. [PubMed]
15. Moorman PG, Jones BA, Millikan RC, et al. Race, anthropometric factors, and stage at diagnosis of breast cancer. Am J Epidemiol. 2001;153:284–291. [PubMed]
16. Jones BA, Kasi SV, Curnen MG, et al. Severe obesity as an explanatory factor for the black/white difference in stage at diagnosis of breast cancer. Am J Epidemiol. 1997;146:394–404. [PubMed]
17. Marchbanks PA, McDonald JA, Wilson HG, et al. The NICHD Women's Contraceptive and Reproductive Experiences Study: Methods and operational results. Ann Epidemiol. 2002;12:213–221. [PubMed]
18. Pagano M, Gauvreau K. Principles of Biostatistics. ed 2. Pacific Grove, CA: Duxbury Press; 2000.
19. Physical status: The use and interpretation of anthropometry—Report of a WHO Expert Committee. World Health Organ Tech Rep Ser. 1995;854:1–452. [PubMed]
20. Kleinbaum G, Kupper L, Morganstern H. Epidemiologic Research: Principles and Quantitative Methods. New York, NY: Van Nostrand Reinhold; 1982.
21. Coates RJ, Clark WS, Eley JW, et al. Race, nutritional status, and survival from breast cancer. J Natl Cancer Inst. 1990;82:1684–1692. [PubMed]
22. McCullough ML, Feigelson HS, Diver WR, et al. Risk factors for fatal breast cancer in African-American women and White women in a large US prospective cohort. Am J Epidemiol. 2005;162:734–742. [PubMed]
23. McKenzie F, Jeffreys M. Do lifestyle or social factors explain ethnic/racial inequalities in breast cancer survival? Epidemiol Rev. 2009;31:52–66. [PubMed]
24. Rose DP, Haffner SM, Baillargeon J. Adiposity, the metabolic syndrome, and breast cancer in African-American and white American women. Endocr Rev. 2007;28:763–777. [PubMed]
25. Chlebowski RT, Chen Z, Anderson GL, et al. Ethnicity and breast cancer: Factors influencing differences in incidence and outcome. J Natl Cancer Inst. 2005;97:439–448. [PubMed]
26. Ademuyiwa FO, Groman A, O'Connor T, et al. Impact of body mass index on clinical outcomes in triple-negative breast cancer. Cancer. [epub ahead of print on March 8, 2011] doi: 10.1002/cncr.26019. [PubMed]
27. McTiernan A, Rajan KB, Tworoger SS, et al. Adiposity and sex hormones in postmenopausal breast cancer survivors. J Clin Oncol. 2003;21:1961–1966. [PMC free article] [PubMed]
28. Kaye SA, Folsom AR, Soler JT, et al. Associations of body mass and fat distribution with sex hormone concentrations in postmenopausal women. Int J Epidemiol. 1991;20:151–156. [PubMed]
29. Rose DP, Komninou D, Stephenson GD. Obesity, adipocytokines, and insulin resistance in breast cancer. Obes Rev. 2004;5:153–165. [PubMed]
30. Yu H, Rohan T. Role of the insulin-like growth factor family in cancer development and progression. J Natl Cancer Inst. 2000;92:1472–1489. [PubMed]
31. Goodwin PJ, Ennis M, Fantus IG, et al. Is leptin a mediator of adverse prognostic effects of obesity in breast cancer? J Clin Oncol. 2005;23:6037–6042. [PubMed]
32. Rose DP, Gilhooly EM, Nixon DW. Adverse effects of obesity on breast cancer prognosis, and the biological actions of leptin (review) Int J Oncol. 2002;21:1285–1292. [PubMed]
33. Tao MH, Shu XO, Ruan ZX, et al. Association of overweight with breast cancer survival. Am J Epidemiol. 2006;163:101–107. [PubMed]
34. Berclaz G, Li S, Price KN, et al. Body mass index as a prognostic feature in operable breast cancer: The International Breast Cancer Study Group experience. Ann Oncol. 2004;15:875–884. [PubMed]
35. Obermair A, Kurz C, Hanzal E, et al. The influence of obesity on the disease-free survival in primary breast cancer. Anticancer Res. 1995;15:2265–2269. [PubMed]
36. Abell JE, Egan BM, Wilson PW, et al. Differences in cardiovascular disease mortality associated with body mass between Black and White persons. Am J Public Health. 2008;98:63–66. [PubMed]
37. Gorber SC, Tremblay M, Moher D, et al. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: A systematic review. Obes Rev. 2007;8:307–326. [PubMed]
38. Gillum RF, Sempos CT. Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: The Third National Health and Nutrition Examination Survey. Nutr J. 2005;4:27–35. [PMC free article] [PubMed]
39. Demark-Wahnefried W, Peterson BL, Winer EP, et al. Changes in weight, body composition, and factors influencing energy balance among premenopausal breast cancer patients receiving adjuvant chemotherapy. J Clin Oncol. 2001;19:2381–2389. [PubMed]
40. Chlebowski RT, Aiello E, McTiernan A. Weight loss in breast cancer patient management. J Clin Oncol. 2002;20:1128–1143. [PubMed]
41. Flegal KM, Graubard BI, Williamson DF, et al. Reverse causation and illness-related weight loss in observational studies of body weight and mortality. Am J Epidemiol. 2011;173:1–9. [PubMed]
42. Stevens J, Juhaeri, Cai J. Changes in body mass index prior to baseline among participants who are ill or who die during the early years of follow-up. Am J Epidemiol. 2001;153:946–953. [PubMed]
43. Gorin SS, Heck JE, Cheng B, et al. Delays in breast cancer diagnosis and treatment by racial/ethnic group. Arch Intern Med. 2006;166:2244–2252. [PubMed]
44. Du Xianglin L, Gor BJ. Racial disparities and trends in radiation therapy after breast-conserving surgery for early-stage breast cancer in women, 1992 to 2002. Ethn Dis. 2007;17:122–128. [PMC free article] [PubMed]
45. Griggs JJ, Sorbero ME, Stark AT, et al. Racial disparity in the dose and dose intensity of breast cancer adjuvant chemotherapy. Breast Cancer Res Treat. 2003;81:21–31. [PubMed]
46. Hershman D, McBride R, Jacobson JS, et al. Racial disparities in treatment and survival among women with early-stage breast cancer. J Clin Oncol. 2005;23:6639–6646. [PubMed]

Articles from Journal of Clinical Oncology are provided here courtesy of American Society of Clinical Oncology