RACIAL DISPARITIES IN NUTRITIONAL FACTORS AND BREAST CANCER RISK URMILA CHANDRAN. A dissertation submitted to the. School of Public Health

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1 RACIAL DISPARITIES IN NUTRITIONAL FACTORS AND BREAST CANCER RISK By URMILA CHANDRAN A dissertation submitted to the School of Public Health University of Medicine and Dentistry of New Jersey and the Graduate School New Brunswick Rutgers, The State University of New Jersey In partial fulfillment of the requirements for the degree of Doctor of Philosophy UMDNJ-School of Public Health Awarded jointly by these institutions and Written under the direction of Elisa V. Bandera MD, PhD And Approved by Piscataway/New Brunswick, New Jersey January, 2013

2 ABSTRACT OF THE DISSERTATION Racial Disparities in Nutritional Factors and Breast Cancer Risk By URMILA CHANDRAN Dissertation Director: Elisa V. Bandera MD, PhD The current evidence on nutritional factors and breast cancer risk is largely based on studies in white women while research in women of African ancestry (AA) is severely limited. We examined racial differences in the relationship between consuming foods of animal origin (never investigated) and alcohol (limited evidence) and breast cancer risk. We also assessed racial disparities in behaviors consistent with evidence-based cancer prevention recommendations and association with breast cancer risk. Investigations were conducted in AA and white women participating in the Women s Circle of Health Study, a case-control study based in NY and NJ. A total of 1692 AA and 1455 white women completed a questionnaire on important risk factors and a Food Frequency Questionnaire. Risk estimates and 95% confidence intervals were calculated using logistic regression adjusting for potential covariates. Racial differences in consumption levels of red meat, poultry, dairy, and alcohol as well as adherence to guidelines on body fatness and physical activity were observed in our study. We found increased risks for greater consumption of red meat and poultry and reduced risks for dairy foods in white but not in AA women. Further differences emerged in subgroup analyses. Lifetime alcohol consumption was inversely related to decreased breast cancer risk in AA women but no association between recent or lifetime drinking was observed in white women. While assessing racial differences in behaviors that are consistent with cancer prevention ii

3 recommendations and breast cancer risk, we observed that recommendations pertaining to foods and drinks that promote weight gain, sodium, alcohol, and red meat intakes were suggestive of reduced breast cancer risk among subgroups of AA women. Restricting red meat intake and caloric dense foods appeared to be beneficial in sub groups of white women. A positive relationship between physical activity and disease risk was observed in AA women. Overall, this study observed racial disparities in nutritional factors and highlighted relationships warranting replication, particularly in AA women given the dearth of research in this group. Put together, the findings contribute towards filling the large gap in understanding disease-environment associations that could be modified by race to facilitate effective prevention strategies. iii

4 ACKNOWLEDGMENTS This work was funded by National Cancer Institute (P01 CA151135, R01 CA100598, K22 CA138563, and P30CA072720) and the Breast Cancer Research Foundation. I would like to acknowledge all research personnel at the Cancer Institute of New Jersey, Roswell Park Cancer Institute, and New Jersey State Cancer Registry, community advocates as well as all the women who generously donated their time to participate in the study. The New Jersey State Cancer Registry is supported by the National Program of Cancer Registries of the Centers for Disease Control and Prevention under cooperative agreement 5U58DP awarded to the New Jersey Department of Health. The collection of New Jersey cancer incidence data is also supported by the Surveillance, Epidemiology, and End Results program of the National Cancer Institute under contract N01-PC and the State of New Jersey. I would also like to personally thank: My advisor Dr. Elisa Bandera, for mentoring and guiding me tirelessly to facilitate my progress in the program; Dr. Christine Ambrosone for her expertise on racial disparities and breast cancer and for agreeing in my using data from the Women s Circle of Health Study for my dissertation; Dr. Kitaw Demissie for his mentorship and training in epidemiological principles and advancing my growth as an epidemiologist throughout the program; and Dr. Yong Lin for his expertise in statistical methods and specifically, for guiding me through statistical applications adopted in my doctoral thesis. Finally, I could not have sustained the demands of a doctoral degree program if not for my parents and my husband who provided a tremendous amount of encouragement, moral and social support throughout the process. To all of you, I say a heartfelt Thank You! iv

5 TABLE OF CONTENTS ABSTRACT OF THE DISSERTATION.. ii ACKNOWLEDGMENTS.. iv OVERALL INTRODUCTION...01 OVERALL METHODS 04 REFERENCES.07 CHAPTER 1: RACIAL DISPARITIES IN ANIMAL FOOD INTAKE AND BREAST CANCER RISK - Introduction.10 - Methods Results 14 - Discussion References.. 27 CHAPTER 2: RACIAL DIFFERENCES IN ALCOHOL CONSUMPTION AND BREAST CANCER RISK - Introduction 38 - Methods Results 42 - Discussion References.. 53 CHAPTER 3: RACIAL DISPARITIES IN THE ADHERENCE TO WCRF/AICR CANCER PREVENTION GUIDELINES AND BREAST CANCER RISK - Introduction 63 - Methods Results 72 - Discussion References.. 86 OVERALL CONCLUSION AND SUMMARY 102 REFERENCES v

6 List of Tables Table I: Distribution of selected characteristics for breast cancer among women participating in WCHS 08 CHAPTER 1 Table 1.1: Comparison of mean and median intakes of total and individual animal food groups.. 31 Table 1.2: Association between intake of animal foods and breast cancer risk among all white women (n=1455) and stratified by menopausal status.. 32 Table 1.3: Association between intake of animal foods and breast cancer risk among white women stratified by hormone receptor status.33 Table 1.4: Association between intake of animal foods and breast cancer risk among all AA women (n=1692) and stratified by menopausal status. 34 Table 1.5: Association between intake of animal foods and breast cancer risk among AA women stratified by hormone receptor status Supplemental Table 1a: Association between intake of animal foods and breast cancer risk among white women (n=1321) and stratified by menopausal status [excluding ductal carcinoma in situ cases]..36 Supplemental Table 1b: Association between intake of animal foods and breast cancer risk among AA women (n=1573) and stratified by menopausal status [excluding ductal carcinoma in situ cases]...36 Supplemental Table 1c: Association between intake of animal foods and breast cancer risk among white women (n=1455) and stratified by menopausal status [excluding community controls]...37 Supplemental Table 1d: Association between intake of animal foods and breast cancer risk among AA women (n=1353) and stratified by menopausal status [excluding community controls]...37 CHAPTER 2 Table 2.1: Comparison of mean and median intakes of recent and lifetime alcohol consumption.56 Table 2.2: Association between recent alcohol consumption (in grams per week), lifetime alcohol consumption (in absolute number of drinks) and disease risk among all women stratified by race. 57 Table 2.3: Recent and lifetime alcohol consumption stratified by menopausal status in AA and white women 58 Table 2.4: Recent and lifetime alcohol consumption stratified by hormone receptor status in AA and white women.. 59 vi

7 Table 2.5: Recent and lifetime alcohol consumption and breast cancer risk stratified by folate intake in AA and white women 60 Supplemental Table 2a: Association between recent alcohol consumption (in grams per week), lifetime alcohol consumption (in absolute number of drinks) and breast cancer risk among women stratified by race [excluding ductal carcinoma in situ cases] 61 Supplemental Table 2b: Association between recent alcohol consumption (in grams per week),lifetime alcohol consumption (in absolute number of drinks) and breast cancer risk among women stratified by race [excluding community controls] CHAPTER 3 Table II: Operationalization and scoring criteria for the 2007 WCRF/AICR cancer prevention recommendations in the WCHS.89 Table III: List of foods from the FFQ included in the calculation of intake Table 3.1: Frequencies for adherence to overall score and individual recommendations among AA and white women stratified by case-control status.. 93 Table 3.2: Association between selected characteristics and adherence to cancer prevention recommendations in the WCHS. 94 Table 3.3: Association between total score, individual recommendations, and breast cancer risk among women in WCHS stratified by race Table 3.4: Association between total score, individual recommendations, and breast cancer risk among AA women in WCHS stratified by menopausal status Table 3.5: Association between total score, individual recommendations, and breast cancer risk among white women in WCHS stratified by menopausal status Table 3.6: Association between adherence to sub-recommendations and breast cancer risk among all women in WCHS stratified by race Supplemental Table 3a: Association between total score, individual recommendations, and breast cancer risk among AA women in WCHS stratified by menopausal status [excluding community controls]. 99 Supplemental Table 3b: Association between total score, individual recommendations, and breast cancer risk among white women in WCHS stratified by menopausal status [excluding community controls].100 Supplemental Table 3c: Patterns related to change in dietary consumption and physical activity since reference date in AA and white cases and controls 101 vii

8 1 OVERALL INTRODUCTION: Breast cancer remains the most commonly diagnosed non-skin cancer in both white and African American women in the US 1, 2. An estimated 226,870 incident cases and 39,510 breast cancer deaths are expected to occur in Factors that influence estrogen exposure such as obesity, age at menarche, age at menopause, exogenous hormones, age at first birth, breastfeeding, and even certain dietary constituents such as ethanol are risk factors for breast cancer 3. Although the overall incidence of breast cancer is higher in white women than in women of African ancestry (AA), AA women are more likely to be diagnosed at younger ages and present with more advanced stage disease in addition to experiencing lower survival rates at every stage 2, 4. Estrogen receptor (ER) negative tumors, which are aggressive in nature and harder to treat also occur more frequently in AA women; particularly triple negative tumors that are basal-like are diagnosed more often in premenopausal AA women 5, 6. In 2007, the World Cancer Research Fund and American Institute for Cancer Research (WCRF/AICR) published eight general cancer prevention recommendations based on systematic reviews of the evidence by scientific experts 7. However, the evidence was largely based on studies mostly involving white women, thus potentially limiting the application of these findings to AA women. AA women who develop breast cancer tend to have different tumor biology 4 and also differ in the prevalence of lifestyle factors such as obesity, diet, and physical activity 8, 9. Hence, it is possible that they may also be affected differently by these factors. For example, an experimental study found that AA women had higher levels of serum hormones such as estrone, estradiol, and

9 2 androstenedione than their white counterparts 10. Of interest was that when their diet was modified to accommodate healthier choices that were low in fat and high in fiber, the estrogen levels in AA women significantly decreased. To better understand the impact of lifestyle factors on the etiology of breast cancer risk in AA women, we searched for studies that presented specific findings on the role of nutritional factors in breast cancer risk among AA women. The findings from the preliminary literature review 11 that now serves as background research for this dissertation were published in The major finding of this review was that there were too few studies that presented risk estimates stratified by race, and even fewer that equally or solely focused on AA women. Hence, definitive conclusions even for known risk factors for breast cancer such as alcohol and anthropometry exposures as they pertain to AA women could not be drawn. There were also no studies on specific food groups such as animal foods including meat intake in AA women, limiting the generalization of the guideline on red meat and processed meat intakes, one of the eight general recommendations for cancer prevention 7. Furthermore, research on racial disparities in the overall impact of nutrition and anthropometric factors was also limited. Even among the studies that did report specific findings in AA women, many of them had sample sizes too small to provide conclusive findings and were not sufficiently powered to detect effects. Given the highlighted gaps in nutrition and breast cancer research in AA women, the main purpose of this dissertation was to evaluate racial disparities in the role of nutritional factors (including anthropometric measures) on breast cancer risk in a case-

10 3 control study, the Women s Circle of Health Study (WCHS) designed to study breast cancer risk factors in AA women. Since evaluating the role of all nutrition and dietary factors in breast carcinogenesis among AA women is beyond the scope of this thesis, we have focused our investigations on 1) animal food consumption (an area with essentially no studies in AA women), 2) alcohol consumption (a confirmed risk factor for breast cancer but with very limited evidence in AA women), and 3) modifiable behaviors consistent with the 2007 WCRF/AICR cancer prevention recommendations (to obtain an overall understanding of racial disparities in following cancer prevention guidelines based on our study population and to evaluate the association between adherence to the nutrition-related recommendations and breast cancer risk among AA and white women). The above mentioned investigations are detailed in three separate chapters in this document. The influence of lifestyle factors such as diet, body fatness, and physical activity on endogenous levels of estrogens also points to potential modification of breast cancer risk profiles according to menopausal status, hormone receptor status, and use of hormone replacement therapy (HRT). Since hormones play a critical role in stimulating tumor growth in the breast 12, a comprehensive assessment of the impact of anthropometric and nutritional factors on disease risk will also include evaluation of outcomes according to hormonal factors. Findings in both AA and white women will be evaluated and compared to better understand potential disparities by exposures of interest.

11 4 OVERALL METHODS: Study Population: The Women s Circle of Health Study (WCHS) has been described in detail elsewhere 13. In brief, WCHS is a National Cancer Institute-funded case-control study conducted in NY and NJ involving both white and AA women. Recruitment in NY was based at Mount Sinai School of Medicine, with recruitment through all major hospitals in New York City for cases with large referral patterns for AA women in four boroughs of the metropolitan NYC area (Manhattan, Brooklyn, Bronx, and Queens). Controls were identified through random digit dialing (RDD) of residential telephone and cell phone numbers and concluded in In NJ, data collection was based at The Cancer Institute of New Jersey. Newly diagnosed, histologically confirmed invasive or DCIS (ductal carcinoma in situ) cases were identified through the NJ State Cancer Registry (NJSCR) using rapid case ascertainment in seven NJ counties. Specifically, case recruitment involved identifying all AA women meeting the eligibility criteria and a random sample of eligible white women matched to AA women by county. White and AA controls were recruited through RDD supplemented by community recruitment efforts for AA women in the same counties (mainly through churches and health events) with the help of community partners and advocates. Recruitment in NJ concluded in March The eligibility criteria for cases were: self-identified AA and white women, years of age at diagnosis, no previous history of cancer except non-melanoma skin cancer, recently diagnosed with primary, histologically confirmed breast cancer, and English speaking. Controls without a history of any cancer diagnosis other than non-melanoma

12 5 skin cancer living in the same seven NJ counties as cases were frequency matched to cases by self-reported race and age. Overall Data Collection: Data collection for the WCHS took place during an in-person interview and included the main study questionnaire (administered by the interviewer) that elicited information on demographics and known and potential risk factors for breast cancer such as physical activity, hormone use, reproductive history, alcohol consumption, smoking, etc.; a Food Frequency Questionnaire (FFQ); a self-administered questionnaire that queried about changes in diet and other practices since reference date; anthropometric measurements including height, weight, body mass index (BMI), waist and hip circumferences, and measures of body composition by bioelectrical impedance analyses using the Tanita scale; and a saliva sample. The FFQ developed by the Nutrition Assessment Shared Resource (NASR) at the Fred Hutchinson Cancer Research Center (FHCRC) queried about both usual frequency and portion size for approximately 125 food items during 12 months prior to diagnosis (for cases) and a comparable recall period for controls. Although the FFQ was generally selfadministered, it was completed as part of the in-person appointment to allow the interviewer to educate all participants about how to respond to the FFQ. The interviewer was also available to answer questions while the participant completed the questionnaire. A total of 827 AA cases, 905 AA controls, 772 white cases, and 714 white controls participated in the study, and over 97% of the participants completed the FFQ resulting in

13 6 a total of 803 AA cases, 889 AA controls, 755 white cases, and 700 white controls available for analyses. The study was approved by the institutional review boards at the University of Medicine and Dentistry of New Jersey, Mount Sinai School of Medicine, and Roswell Park Cancer Institute. Methods specific to each project are detailed in the respective chapters. Statistical Analyses: The distribution of selected categorical variables (demographic, socio-economic, and known and potential breast cancer determinants) for AA and white cases and controls was summarized using frequencies and proportions while means and standard deviations were calculated for continuous terms. Chi square tests were used to compare the frequencies of the two groups while t-statistics and analysis of covariance (ANCOVA) were used to compare the mean differences of selected factors between cases and controls separately in AA and white women. Statistical analyses specific to each project are detailed in the respective chapters. All analyses were conducted using SAS version 9.2 (Cary, North Carolina). Characteristics of Study Population: The distribution of demographic and socioeconomic (SES) characteristics as well as potential risk factors for breast cancer in the entire study population is summarized in Table I. Overall, white women tended to be of higher SES (higher education and higher income) and less obese than AA women. As compared to AA and white controls, both AA and white cases were more likely to have

14 7 ever used HRT, have a history of benign breast disease, and family history of breast cancer respectively. Results specific to each project are detailed in the respective chapters. REFERENCES: 1. American Cancer Society. Cancer Facts & Figures ent/acspc pdf. Accessed March 28, American Cancer Society. Cancer Facts & Figures for African Americans Atlanta: American Cancer Society; Schottenfeld D, Fraumeni JF. Breast Cancer. In: Colditz G, Baer, HJ., Jamimi, RM., ed. Cancer epidemiology and prevention. 3rd ed. Oxford ; New York: Oxford University Press; 2006:xviii, 1392 p. 4. Amend K, Hicks D, Ambrosone CB. Breast cancer in African-American women: differences in tumor biology from European-American women. Cancer Res. Sep ;66(17): Millikan RC, Newman B, Tse CK, et al. Epidemiology of basal-like breast cancer. Breast Cancer Res Treat. May 2008;109(1): Agurs-Collins T, Dunn BK, Browne D, Johnson KA, Lubet R. Epidemiology of health disparities in relation to the biology of estrogen receptor-negative breast cancer. Semin Oncol. Aug 2010;37(4): World Cancer Research Fund/American Institute for Cancer Research. Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective. Washington DC:American Institute for Cancer Research Forshee RA, Storey ML, Ritenbaugh C. Breast cancer risk and lifestyle differences among premenopausal and postmenopausal African-American women and white women. Cancer. Jan ;97(1 Suppl): American Cancer Society. Cancer Facts & Figures for African Americans Atlanta:American Cancer Society Woods MN, Barnett JB, Spiegelman D, et al. Hormone levels during dietary changes in premenopausal African-American women. J Natl Cancer Inst. Oct ;88(19): Chandran U, Hirshfield KM, Bandera EV. The role of anthropometric and nutritional factors on breast cancer risk in African-American women. Public Health Nutr. 2012;15(4): Hankinson SE, Colditz GA, Willett WC. Towards an integrated model for breast cancer etiology: the lifelong interplay of genes, lifestyle, and hormones. Breast Cancer Res. 2004;6(5): Ambrosone CB, Ciupak GL, Bandera EV, et al. Conducting Molecular Epidemiological Research in the Age of HIPAA: A Multi-Institutional Case-Control Study of Breast Cancer in African-American and European-American Women. J Oncol. 2009;2009:

15 8 Table I: Distribution of selected characteristics for breast cancer among women participating in WCHS Cases (n=803) n(%) AA women Controls (n=889) n(%) Cases (n=755) n(%) White women Controls (n=700) n(%) Age at interview (yrs) (4.6) 71(8.0) 23(3.1) 32(4.6) (20.2) 182(20.5) 140(18.5) 156(22.3) (32.5) 320(36) 254(33.6) 256(36.6) (32.6) 272(30.6) 247(32.7) 251(35.9) (10.1) 44(4.9) 91(12.1) 5(0.7) Chi square p value < < Mean (± SD) 52.07± ± ± ±8.7 p value < < Education <High school 118(14.7) 112(12.6) 21(2.8) 10(1.4) High school graduate 241(30) 227(25.5) 127(16.8) 69(9.9) Some college 213(26.5) 259(29.1) 165(21.9) 131(18.7) College graduate 141(17.6) 180(20.2) 230(30.5) 226(32.3) Post-graduate degree 90(11.2) 111(12.5) 212(28.1) 264(37.7) Chi square p value 0.11 < Country of origin United States 552(68.7) 711(80) 639(84.6) 616(88) Caribbean countries 189(23.5) 129(14.5) 25(3.3) 2(0.3) Other 62(7.7) 49(5.5) 91(12.1) 82(11.7) Chi square p value < < Ethnicity Hispanic 45(5.6) 26(2.9) 62(8.2) 15(2.1) Non-Hispanic 758(94.4) 863(97.1) 693(91.8) 685(97.9) Chi square p value < Marital Status Married 287(35.7) 306(34.5) 468(62.1) 476(68) Living as married 13(1.6) 19(2.1) 22(2.9) 22(3.1) Widowed 74(9.2) 58(6.5) 40(5.3) 19(2.7) Separated 62(7.7) 57(6.4) 14(1.9) 16(2.3) Divorced 138(17.2) 136(15.3) 91(12.1) 73(10.4) Single, never married or never lived as married 229(28.5) 312(35.1) 119(15.8) 94(13.4) Chi square p value Age at menarche (yrs) <12 228(28.4) 250(28.2) 175(23.4) 156(22.5) (45.4) 399(44.9) 416(55.6) 368(53) >13 210(26.2) 239(26.9) 157(21) 170(24.5) Chi square p value Mean (± SD) 12.54± ± ± ±1.5 p value Menopausal status Premenopausal 408(50.8) 463(52.1) 389(51.5) 384(54.9) Postmenopausal 395(49.2) 426(47.9) 366(48.5) 316(45.1) Chi square p value Age at menopause (yrs) 45 36(9.4) 52(12.3) 29(8.1) 27(8.7) (15.6) 108(25.6) 73(20.4) 71(22.9) (64.2) 220(52.1) 204(57) 175(56.4) >55 42(10.9) 42(10.1) 52(14.5) 37(11.9) Chi square p value

16 Mean (± SD) 49.79± ± ± ±4.2 Age-adjusted Mean (± SE) 49.57± ± ± ±0.24 p value Parity (livebirths) 0 124(15.4) 148(16.7) 237(31.4) 206(29.4) (51.6) 438(49.3) 355(47) 354(50.6) (24.9) 237(26.7) 146(19.3) 117(16.7) >5 65(8.1) 66(7.4) 17(2.3) 23(3.3) Chi square p value Mean (± SD) 2.12± ± ± ±1.5 Age-adjusted Mean (± SE) 2.09± ± ± ±0.05 p value Age at first birth (yrs) Nulliparous (0 birthcount) 124(15.5) 148(16.7) 237(31.4) 206(29.4) (31.6) 294(33.1) 36(4.8) 32(4.6) (24.3) 220(24.8) 134(17.8) 110(15.7) (18.6) 120(13.5) 190(25.2) 170(24.3) >31 81(10.1) 106(11.9) 158(20.9) 182(26) Chi square p value Mean (± SD) 22.79± ± ± ±5.9 Age-adjusted Mean (± SE) 22.83± ± ± ±0.26 p value Breastfeeding Never 470(58.5) 529(59.5) 430(57) 355(50.7) Ever 333(41.5) 360(40.5) 325(43) 345(49.3) Chi square p value Mean months (± SD) 18.07± ± ± ±21.8 Age-adjusted Mean (± SD) 17.91± ± ± ±1.06 p value Family history No 687(85.6) 786(88.4) 578(76.5) 583(83.3) Yes 116(14.4) 103(11.6) 177(23.4) 117(16.7) Chi square p value Past benign breast disease No 547(68.3) 685(77.1) 431(57.6) 465(66.7) Yes 254(31.7) 203(22.9) 317(42.4) 232(33.3) Chi square p value < HRT use Never 682(85.4) 785(88.5) 559(74) 539(77.1) Ever 117(14.6) 102(11.5) 196(26) 160(22.9) Chi square p value Oral contraceptive use Never 333(41.5) 387(43.6) 261(34.7) 203(29) Ever 470(58.5) 501(56.4) 492(65.3) 497(71) Chi square p value BMI Underweight/Normal 151(18.8) 157(17.7) 342(45.3) 317(45.4) Overweight 235(29.3) 255(28.7) 206(27.3) 191(27.3) Obese 416(51.9) 477(53.7) 207(27.4) 191(27.3) Chi square p value

17 10 CHAPTER 1: RACIAL DISPARITIES IN ANIMAL FOOD INTAKE AND BREAST CANCER RISK INTRODUCTION: Meat consumption in the US has been rising (based on data tracked since 1909) and is considerably higher in the US than in other developed countries 1. The role of consumption of foods of animal origin (such as red and processed meats, poultry, seafood, eggs, and dairy) has been extensively investigated for their role in carcinogenesis. However, their impact on breast cancer prevention is inconclusive 2-8. Red and processed meats have been consistently linked to colorectal cancer risk 2, 9, 10. The association between meat consumption and colorectal cancer risk has also been investigated in African Americans 10, 11 with the authors reporting no racial differences 10 or null findings in AA 11. Consumption of red meat cooked at high temperatures has been linked to increased prostate cancer risk among AA men 12. Hence, the World Cancer Research Fund / American Institute for Cancer Research (WCRF/AICR) recommends limiting red meat intake to less than 500 g/week (18 oz) with very little if any to be processed 2. Interestingly, the plethora of evidence on dietary factors and breast cancer risk is based on studies predominantly involving white women. In a recent systematic review on nutritional and anthropometric factors and breast cancer risk in women of African ancestry (AA), we found essentially no studies on any type of animal foods and breast cancer risk in AA women 13, thus leaving a large gap remaining to be addressed in the area of racial disparities and nutritional epidemiology. There is also limited evidence

18 11 suggesting a relationship between meat intake and breast cancer risk when stratified by hormone receptor status 14. Therefore, further research has been proposed to also investigate the association between consumption of animal products and breast cancer specifically stratified by menopausal status and hormone receptor status 14, 15. There are clear racial differences in consumption patterns of different animal food groups. NHANES data show that AA women have higher mean consumption of red meat, poultry, and seafood compared to white women 16. The USDA also reported Non- Hispanic Blacks to be the highest beef consumers among all races with ground beef being the most frequently consumed type of beef product 17. In parallel, there are also well known racial disparities in breast tumor biology We evaluated the role of animal food intake and breast cancer risk in the Women s Circle of Health Study, a case-control study based in New Jersey and New York. To our knowledge, this is the first study to examine the association between intake of foods of animal origin and breast cancer risk as well as to evaluate racial differences by menopausal status and hormone receptor status in a large sample of AA women. METHODS: Details about the study population and overall data collection procedures have been outlined in the introductory section. Additional information pertinent to this specific research question is included below. Data Collection: The FFQ included sections on meat, fish, eggs as well as dairy products. Unprocessed red meat items in the FFQ included beef, pork, ham and lamb and ground meat including

19 12 hamburgers and meatloaf while processed red meat items included lunch meats and other items such as bacon, sausages, bratwursts, chorizo, salami, and hot dogs. Total red meat was computed as the sum of processed and unprocessed red meat. Poultry meat items included chicken and turkey. Dairy products included milk and products made from milk such as cheese, butter, ice cream and milkshakes, and yogurt. Seafood included tuna, shellfish, white fish, and dark fish. Weekly gram and ounce equivalents for the specified medium serving size of each food item were obtained from the USDA National Nutrient Database for Standard Reference 21. For example, 1 cup of milk is 244 g 21 ; hence a person drinking 1 cup of milk once per day would consume 1,708 grams of milk per week as a beverage. Animal foods were divided into different groups (processed meat, unprocessed red meat, poultry, seafood, eggs, and dairy products), and total animal food consumption was calculated as the sum of these individual food groups. Statistical Analyses: The distribution of consumption levels pertaining to total as well as individual animal food groups in cases and controls stratified by race were compared using the Wilcoxon rank-sum test. All animal food intakes were expressed as a density measure as grams per week for every 1,000 kcal of total energy intake for inclusion in the model that also adjusted for total energy intake as per the multivariate nutrient density method 22. The density measures for each animal food group were categorized into quartiles based on distribution among all controls with the fourth quartile representing the highest level of consumption. Unconditional logistic regression analyses were used to compute odds ratios (OR) and 95% confidence intervals (CI). Tests for linear trend were conducted by

20 13 including the median intake in each quartile as a continuous variable in regression models. Analyses also included modeling total red meat consumption in a continuous form to assess change in risk for every 500 g/week (approximately one serving a day) increase in intake as per the WCRF/AICR recommendation for red meat 2. Similarly, processed meat and poultry consumption were modeled in 200 g/week increments (~ one ounce per day). A total of 1,767 women had poultry consumption exceeding 200 g/week and 727 women consumed more than 500 g/week of red meat. All analyses were stratified by race as the primary effect modifier. Subgroup analyses included further stratification by menopausal status and polytomous logistic regression analyses to simultaneously model risk of ER+/PR+ and ER-/PR- tumors with controls as the reference. Potential confounders of interest that were included in multivariable models were age, ethnicity (Hispanic or Non-Hispanic), country of origin ( US born, Caribbean born, Other ), education ( less than 12 th grade, high school graduate or equivalent, some college, college graduate, post-graduate degree ), age at menarche, age at menopause (only for postmenopausal women), menopausal status (if not stratified by this variable), parity (continuous), age at first birth ( 0-19, 20-24, 25-30, 31 ), breastfeeding status (ever/never), family history of breast cancer, hormone replacement therapy (HRT) use, body mass index (BMI), and total energy intake. In sensitivity analyses, we repeated regression analyses after further adjustment for total fat intake (in a model that excluded total calories) and alcohol. We also further evaluated if associations differed when excluding community controls in AA women (n=339) to

21 14 examine possible differences by source of controls, excluding non-invasive cases (n=253), excluding HRT users (n=575), and after excluding participants (n=157) with total energy intake of less than 500 calories 7 or more than 4500 calories (approximately three standard deviations away from the mean). RESULTS: Mean and median intakes of the different foods between cases and controls among AA and white women are reported in Table 1.1. Mean and median consumption of unprocessed red meat was higher in AA controls than cases (p=0.05) while total animal food intake was significantly higher in white controls as compared to white cases (p=0.02). Regardless of case-control status, consumption of processed meat, poultry, and seafood tended to be higher in AA women while white women reported higher intakes of unprocessed red meat, dairy foods, and total animal foods. Egg consumption appeared to be similar among both races. Among white women (Table 1.2), there were increases in risk with red meat and poultry consumption. Every 500 g/week increase in consumption of any kind of red meat was associated with increased risk (OR=1.30; 95% CI: ), which was also observed for both processed (OR=1.47; 95% CI: , p trend=0.07) and unprocessed red meat in the highest quartile compared to the lowest quartile (OR=1.40; 95% CI: , p trend =0.28). Increased breast cancer risk was also found among women who consumed poultry in the highest quartile (OR=1.43; 95% CI: , p trend =0.04) compared to the lowest quartile as well as when risk was assessed for 200 g/week increment in poultry intake (OR=1.17; 95% CI: ). In contrast, higher intake of

22 15 animal foods overall (OR=0.71; 95% CI: , p trend=0.01) and dairy foods (OR=0.64; 95% CI: , p trend=0.001) were suggestive of decreased breast cancer risk among white women. No associations were found for consumption of seafood or eggs after adjusting for major covariates. When further stratified by menopausal status, associations appeared stronger among premenopausal women for increased risk associated with every 500 g/week increment in total red meat intake (OR=1.47; 95% CI: ), 200 g/week in poultry intake (OR=1.43; 95% CI: ), consumption in the highest quartile of unprocessed red meat (OR=1.65; 95% CI: , p trend =0.15) and poultry (OR=2.34; 95% CI: , p trend <0.001). The decreased risk observed with higher dairy food consumption also seemed to be stronger among premenopausal white women (OR=0.49; 95% CI: , p trend <0.001). On the other hand, stronger risk estimates for increased processed meat intake comparing highest versus lowest quartile were seen among postmenopausal white women (OR=1.74; 95% CI: , p trend=0.08). Results from the polytomous regression analyses among white women (Table 1.3) suggested that unprocessed red meat consumption in the fourth quartile increased risk of both ER+/PR+ (OR=1.74; 95% CI: , p trend =0.11) and ER-/PR- (OR=1.80; 95% CI: , p trend =0.19) tumors compared to intakes in the first quartile, but the confidence intervals in women with negative receptor tumors included the null value. Similar associations for ER+/PR+ (OR=1.47; 95% CI: ) and ER-/PR- (OR=1.48; 95% CI: ) were also observed for every 500 g/week increase in total red meat intake. Inverse relationship with consuming dairy foods was observed for risk of both hormone receptor positive (OR=0.66; 95% CI: , p trend=0.03) and receptor

23 16 negative tumors (OR=0.48; 95% CI: , p trend=0.04). However, increased breast cancer risk associated with processed red meat intake (OR=1.97; 95% CI: , p trend=0.04) and decreased risk related to higher consumption of all animal foods in total (OR=0.50; 95% CI: , p trend=0.05) were observed for ER-/PR- tumors in white women. Furthermore, every 200 g/week increase in poultry intake increased odds of disease by 33% (95% CI: ) for white women with ER-/PR- tumors while poultry consumption in the highest quartile corresponded to a more than two-fold increased odds of disease (OR=2.21; 95% CI: , p trend=0.04) in this group. Findings among AA women are presented in Tables 1.4 and 1.5. In contrast to results observed in white women, there was no clear evidence of an association between total or any of the individual animal food groups and breast cancer risk in AA women (Table 1.4) even when stratified by menopausal status. When stratified by ER status (Table 1.5) in AA women, findings suggested a positive relationship between risk of ER+/PR+ tumors and total red meat (OR=1.50; 95% CI: , p trend=0.09) and processed red meat (OR=1.49; 95% CI: , p trend=0.02). An association of borderline significance was also suggested for risk of hormone receptor positive tumors and high egg consumption (OR=1.42; 95% CI: , p trend=0.09) as well as risk of hormone receptor negative tumors and seafood intake (OR=1.58; 95% CI: , p trend=0.08). Further adjustment for total fat intake slightly attenuated risk estimates for unprocessed and processed red meat in white women but conclusions remained unchanged in both races [data not shown]. Adding physical activity or alcohol essentially did not change

24 17 main conclusions [data not shown]. Repeating analyses after excluding women with extreme values for total calories or HRT users did not alter findings [data not shown]. Excluding women with non-invasive breast cancers (Supplemental Tables 1a and 1b) did not change study conclusions. Odds ratios for most food groups tended to go in the same direction in sensitivity analyses that excluded AA controls recruited through community efforts (Supplemental Tables 1c and 1d). However, a stronger increased risk associated with dairy consumption in postmenopausal AA women (OR: 1.78; 95% CI: ) and processed meat (OR: 1.56; 95% CI: ) was observed. Disease risk associated with poultry consumption in all white women (OR changing from 1.43 to 1.29) was attenuated but remained strong and statistically significant among premenopausal white women (OR=2.13; 95% CI: ). DISCUSSION: In this case-control study involving a large sample of AA and white women, there were racial differences in the association between intake of certain foods of animal origin and breast cancer risk. To our knowledge, this is the first large study to investigate animal foods in AA women and in subgroups of pre- and postmenopausal women, as well as by hormone receptor status for breast cancer patients. Mean and median consumption levels of almost all types of animal foods were different between the groups, with AA women having higher intake of processed meat and poultry in this study. Increased risks associated with consuming more than 100 g of processed red meat, 170 g of unprocessed red meat, and 245 g of white meat per 1,000 kcal of intake per week (as compared to consumption in the lowest quartile) were observed among white women but not among

25 18 AA women. An elevated breast cancer risk in white women was also found per 500 g/week of red meat consumption and per 200 g/week of poultry consumption. The risks were generally more pronounced for premenopausal white women. White women who consumed animal foods or dairy foods in the highest quartile appeared to experience a reduction in disease risk. Some differences by hormone receptor status were also suggested. Although red meat consumption increased risk for ER+/PR+ and ER-/ERtumors among white women, consumption of processed red meat and poultry was strongly associated with ER-/PR- tumors in this group. Among AA women, consumption of red meat, particularly processed meat was suggestive of an increased risk of ER+/PR+ tumors; however no clear evidence of an association with any other animal food intakes was present. Overall, primary and subgroup analyses indicated racial disparities not only in intake of different types of animal foods and breast cancer risk but further differences even by menopausal status and hormone receptor status of tumors. Results from past studies that have investigated the impact of animal food intake such as red and processed meats on breast cancer risk are inconsistent. The Pooling Project 23 (data from eight large cohorts) and the EPIC cohort 5 found limited evidence of an association between meat intake and breast cancer risk while results from other recent studies such as the UK Women s Cohort Study 7 and a nested case-control study from the Diet, Cancer, and Health cohort 6 reported significantly increased breast cancer risks with increased consumption of total meat and red meat, similar to findings in white women in our study. Our study also lent support to the WCRF/AICR recommendation of limiting total red meat to less than 500 g/week among white women.

26 19 It has been postulated that similar to risk factors such as adiposity and years before first pregnancy, diet in early life may have a different impact on breast cancer risk than diet in later ages; thus indicating potential modification of risks by menopausal status 24. Evaluating associations stratified by menopausal status separately in AA and white women was also important because premenopausal and postmenopausal breast cancers seem to operate through different mechanisms, complemented by previous research showing that AA and white women have different hormonal profiles 25 and are differently impacted by some known risk factors for breast cancer 13, 20. A meta-analysis 26 of 10 studies that investigated the impact of red meat consumption focusing on premenopausal women observed a summary RR of 1.24 (95% CI: ) with stronger estimates coming from case-control studies while cohort studies showed a non-significant modest increase in breast cancer risk. Our positive findings on (unprocessed) red meat in premenopausal white women are consistent with results from the meta-analysis. Although risk estimates for processed meat were stronger in postmenopausal white women, in general, findings for both processed and unprocessed red meat consumption suggested potential detrimental effects in white women. This is consistent with findings from the UK Women s Cohort Study 7 that reported highest risk for highest meat eaters in both pre- and postmenopausal groups as well as a national study in Canada reporting an elevated breast cancer risk among postmenopausal women 27. Red meat intakes in AA women were generally lower than levels in white women in our study with the exception of processed meat, which may have contributed to the limited evidence relating meat consumption and breast cancer risk in AA women. However there was an indication of a positive relationship for total red meat, processed meat

27 20 consumption and hormone receptor positive tumors in AA women, which needs further evaluation. In the past, studies that evaluated meat intake and breast cancer risk stratified by receptor status have observed stronger associations for ER/PR positive tumors than for ER/PR negative cancer 24, 28, 29. Our results on red meat were consistent with this past research. On the other hand, it must be noted that the increased risk observed for total and unprocessed red meat in white women and for processed meat in AA women appeared to be of similar magnitude for ER+/PR+ and ER-/PR- tumors in our study. However, the confidence interval for hormone receptor negative tumors was less precise and included the null value, which could be due to smaller sample size. Recent results from the Shanghai Breast Cancer Study, also a case-control study reported elevated breast cancer risk for all types of meat regardless of hormone receptor status 30. These findings could indicate presence of both estrogenic and non-estrogenic pathways involving meat and carcinogenesis as well as potential racial differences in food preparation methods and gene-environment interactions resulting in differences in the way animal protein, estrogens, and other carcinogens are metabolized and their consequential impact on breast tissue. However, the findings in general could be due to chance and need replication especially since general linear trend statistics for some associations were not significant. There are several potential mechanisms for the role of red meat in the cancer development process. Red meat is generally regarded as a high-protein and high-fat food product. However, when red meats are processed or preserved using techniques such as smoking, curing, salting, or by adding nitrites and other preservatives, their risk profile could be altered. For example, nitrites that are used to preserve processed meats also

28 21 undergo chemical reactions endogenously to form nitrosamines, also a mutagen and probable carcinogen 2, 31. In addition, cooking red meat at high temperatures (charring, grilling, frying) lead to the production of heterocyclic amines (HCAs) and polycyclic aromatic hydrocarbons, which are mutagens and suspected carcinogens 2, 32. For instance, a 4.6-fold increased risk of breast cancer was observed among postmenopausal women who consistently ate well-done meat in the Iowa Women s Health Study 33. Results from the Nashville Breast Health Study that specifically assessed breast cancer risk with regard to not just intake levels, but also cooking methods and doneness levels showed a significant elevated risk of breast cancer with high red meat intake 34. This increased risk was stronger for high intake of well-done red meat and was observed in both pre and postmenopausal women. In our study, it was not possible to evaluate impact of cooking temperatures since the FFQ did not query about cooking methods or meat doneness levels. Furthermore, heme iron (dietary hemoglobin) present in red meat and responsible for its dark red color could have a catalytic effect on endogenous formation of nitrosamines 35. In fact, heme iron content in red meat is 10-fold higher than in white meat 35, and has been shown to promote estrogen-induced tumors 36. Exposure to meatderived mutagens has also been observed to be significantly correlated with DNA adducts in breast tissue, potentially leading to unrepaired DNA damage and carcinogenesis 37. A cross-sectional analysis conducted in postmenopausal women found mean plasma concentrations of sex hormone-binding globulin (SHBG) to be lower with higher intakes of total and fresh red meat 38. Lower SHBG levels correspond with increased bioavailability of estradiol 39, 40. There is also some evidence that the impact of well-done meat on breast cancer risk could be modified by certain polymorphisms in the NAT1,

29 22 NAT2, GSTM1, GSTT1, and SULT1A1 genes that encode enzymes involved in HCA activation or detoxification 41. Furthermore, animal studies have shown that HCAs are estrogenic and could stimulate ER and PR gene expression, thereby supporting evidence showing impact of red meat intake on ER positive tumors 42, 43, which was also shown among white and AA women in our study. Finally, there is evidence linking exogenous hormone treatment of beef cattle to increased risk of estrogen-related illnesses even with low levels of exposure in the long term 44. In our study, there was also a positive association translating to odds of 17% per 200 g/week intake of poultry and 43% when using percentile cut-offs between intake of poultry meat and breast cancer risk in white women, and over 2-fold risk among premenopausal white women and among women with ER-/PR- tumors, which are most commonly seen among premenopausal women 20. Past evidence relating poultry intake and breast cancer risk is inconclusive 2, 3, 34, 37. Biological mechanisms for the role of white meat are not clear, except for the potential influence of fat in the meat supplemented by meal preparation methods such as frying, but in our study, this association remained even after adjusting for fat. However, it is possible that poultry intake could be correlated with other factor(s) that could be associated with breast cancer risk. A recent cross-sectional study reported that intake of chicken, high-fat dairy products, and animal fat may be important determinants of oxidative stress in women with breast cancer 45. However, results from the Nashville Breast Health Study did not find any association between levels of chicken consumption and breast cancer risk such that even

30 23 when poultry consumption was high, there was no correlation between cooking poultry at high temperatures and formation of DNA adducts in breast tissue 34, 37. NHANES data show that poultry consumption from has more than doubled with consumption being the highest among AA at 54.4 g/day 1, which could be partially driven by culture, socio-economic status, and cost of food. Despite higher mean and median levels of poultry intake in our study, there was no evidence linking poultry consumption and breast cancer risk in AA women in our study, thus indicating that racial differences in factors influencing the role of white meat in breast cancer prevention merit further attention. The inverse association observed in white women in our study between increased consumption of foods of animal origin and breast cancer risk should be viewed with caution as not all animal foods share the same risk-benefit ratio for chronic diseases. It is possible that the relationship we observed with animal foods in general may be driven by similar associations observed with dairy food intake, which in fact accounted for the largest proportion of animal foods. In our study, dairy products included milk and products made from milk such as cheese, yogurt, cream, ice cream and milkshakes. No specific WCRF/AICR recommendations exist about dairy consumption although this food group is relevant to reducing energy consumption by decreased intake of dairy products in their whole form and from fats such as butter and ghee (clarified butter) 2. To evaluate the dairy food group further, we repeated analyses only including milk, cream, ice cream and milkshakes in this group. The association between animal foods and breast cancer risk was now reversed, with odds ratios being above one albeit statistically nonsignificant.