• We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Am J Clin Nutr. Author manuscript; available in PMC Jun 3, 2008.
Published in final edited form as:
PMCID: PMC2409282
NIHMSID: NIHMS48641

Diet patterns and breast cancer risk in Hispanic and non-Hispanic white women: the Four-Corners Breast Cancer Study1,2,3,4

Abstract

Background

There is a lower incidence of breast cancer among Hispanic women than among non-Hispanic white women. Little is known about the role of diet in this difference.

Objective

We examined the associations of dietary patterns (Western, Prudent, Native Mexican, Mediterranean, and Dieter) with risk for breast cancer in Hispanic women (757 cases, 867 controls) and non-Hispanic white women (1524 cases, 1598 controls) from the Four-Corners Breast Cancer Study.

Design

Dietary intake, physical activity, and other exposures were assessed by using interviews. Dietary patterns were defined via factor analysis. Risk was assessed by using logistic regression with adjustment for age, center, education, smoking, total activity, calories, dietary fiber, dietary calcium, height, parity, recent hormone exposure, family history of breast cancer, menopausal status, and body mass index × recent hormone exposure.

Results

The Western (odds ratio for highest versus lowest quartile: 1.32; 95% CI: 1.04, 168; P for trend < 0.01) and Prudent (1.42; 1.14, 1.77; P for trend < 0.01) dietary patterns were associated with greater risk, and the Native Mexican (0.68; 0.55, 0.85; P for trend < 0.01) and Mediterranean (0.76; 0.63, 0.92; P for trend < 0.01) dietary patterns were associated with lower risk of breast cancer. Body mass index modified the associations of the Western diet and breast cancer among postmenopausal women and those of the Native Mexican diet among premenopausal women.

Conclusions

Associations of dietary patterns with breast cancer risk varied by menopausal and body mass index status, but there was little difference in associations between non-Hispanic white and Hispanic women.

INTRODUCTION

Every year, more than 200 000 women in the United States are diagnosed with invasive breast cancer (1). The rates of breast cancer (2) and obesity (3) differ among ethnic groups. The rate of breast cancer among Hispanic women is ≈2/3 of that among non-Hispanic white women (2), but the rate of obesity is higher among Hispanic women (3). We previously showed an increase in the prevalence of obesity with higher intakes of animal protein and fat composition in non-Hispanic white but not in Hispanic women control participants from the Four-Corners Breast Cancer (FCBC) study (4). We have found some similarities and some differences in factors associated with breast cancer between the FCBC study and the body of literature. For example, we noted ethnic differences in the associations of obesity with risk for breast cancer in postmenopausal Hispanic and non-Hispanic white women but no differences in these same associations in premenopausal women (5). In addition, the association of oral contraceptives with risk of breast cancer was similar in Hispanic and non-Hispanic white women in the FCBC study (6).

To date, the literature addressing the association of empirically defined dietary patterns and breast cancer risk has focused predominantly on postmenopausal breast cancer (7, 8). These studies suggest effect modification by estrogen receptor status and risk factors such as family history, smoking, and estrogen status (7, 8). To this end, we examined the association of 5 empirically defined dietary patterns (Western, Native Mexican, Prudent, Mediterranean, and Dieter) with risk for breast cancer among non-Hispanic white and Hispanic women participating in the FCBC study of diet, lifestyle, and genetic contributions to the etiology of breast cancer. We examined associations stratified by ethnicity, menopausal status, menopausal status within ethnicity, estrogen receptor status (cases only), and by body size [ie, body mass index (BMI; in kg/m2)].

SUBJECTS AND METHODS

Subjects

The FCBC study used a case-control design to assess breast cancer risk in women in the 4 states (Arizona, New Mexico, Colorado, and Utah) that form the Four Corners region. The Utah and New Mexico state registries are National Cancer Institute–funded Surveillance Epidemiology and End Results registries; the Arizona and Colorado registries are part of the Centers for Disease Control and Prevention’s National Program of Cancer Registries. An electronic rapid case ascertainment system was used in Utah to identify cases. In the other states, cases were identified through normal registry operations. Eligible cases had a histologically confirmed diagnosis for either in situ or invasive breast cancer [International Classification of Diseases for Oncology (ICDO) sites C50.0–C50.6 and C50.8–C50.9] between October 1999 and September 2004.

Controls were frequency-matched by ethnicity and 5-y age distribution of cases. In Arizona and Colorado, controls < 65 y old were randomly selected from a commercial mailing list; in New Mexico and Utah, they were randomly selected from driver’s license lists. In all states, women ≥ 65 y old were randomly selected from Center for Medicare Services lists.

All women identified were screened for eligibility before study enrollment. Cooperation rates (number of participants/number of eligible participants ever contacted) were 68% for cases and 42% for controls (9).

All participants gave informed written consent before participation. The study was approved by the Institutional Review Board for Human Subjects at each institution.

Interview and anthropometric data

Interviews were conducted in English or Spanish (the participant chose the language) by trained and certified interviewers. The referent year for the questionnaires was the year before cancer diagnosis or before selection as a control participant. The questionnaires included diet, physical activity, and medical and reproductive history. Each participant was asked at the conclusion of the interview to identify her race and ethnic background again. Women were allowed to report multiple races, and those who responded Hispanic or Latina and those who responded white, Caucasian, or non-Hispanic white were included in the present analysis. Dietary patterns may differ culturally between Hispanic and American Indian women; therefore, 32 cases and 51 controls who self-identified as American Indian were omitted from the present analysis. Those women who self-identified as both Hispanic and white or as both Hispanic and American Indian were classified as Hispanic. Women who were still having regular periods or who were pregnant or breastfeeding are referred to hereafter as premenopausal. Women who were having periods while taking hormone replacement therapy or who were going through menopause and were ≤ 57 y old in the reference year also were considered premenopausal. Postmenopausal status was assigned to women who reported that their periods stopped by themselves, because of an operation or medication, or because both ovaries were removed or who were having periods while taking hormone replacement therapy or going through menopause, but whose age during the reference year was > 57 y.

Food consumption was reported for foods by using a computerized, interviewer-administered dietary history questionnaire (10) patterned after the diet history questionnaire of the Coronary Artery Risk Development in Young Adults study (11, 12) and adapted to include the current food supply and ethnic foods commonly consumed in the southwestern United States. We solicited information by using 58 questions that elicited responses for hundreds of foods. At the end of the questionnaire, participants had the opportunity to report foods not queried.

Dietary patterns were identified by using factor analysis implemented with the SAS Factor Procedure (SAS Institute, Inc, Cary, NC) with varimax rotation. Foods were grouped into 69 groupings such as low-fat and high-fat dairy, cola and diet cola beverages, red meat, poultry, fish, whole and refined grains, citrus fruit, and potatoes. Factor scores were computed for each participant. Factor analysis was run on the combined control group and was run separately for the Hispanics and non-Hispanic whites. These approaches resulted in similar patterns. Therefore, the diet pattern scores based on the combined analysis were used.

Nutrient profiles and more detailed descriptions of the dietary patterns have been reported elsewhere (4). Briefly, the dietary pattern factor 1, labeled the Western diet, included high (> 0.35) factor loadings for high-fat dairy foods, refined grains, gravy and sauces, fast foods, red and processed meats, potatoes, margarine, polyunsaturated fats, and high-fat and high-sugar desserts. The Native Mexican dietary pattern (factor 2) was based on loadings ≥ 0.35 for Mexican foods such as Mexican cheeses, soups, meat dishes, legumes, and tomato-based sauces. Foods that loaded heavily on factor 3, labeled the Prudent dietary pattern, were characterized by factor loadings of > 0.35 for low-fat dairy, whole grains, fruit and fruit juice, legumes, vegetables, and soups. The Mediterranean dietary pattern (factor 4) included high factor loadings for liquor consumption, poultry, seafood, vegetables, salad greens, and high-fat salad dressings. The Dieter dietary pattern, factor 5, was associated with avoiding high-fat dairy products and salad dressing, cola beverages, and butter and with using low-fat dairy, margarine, and salad dressings, as well as low-fat high-sugar desserts, diet beverages, and sugar substitutes.

Anthropometric measures

Height and weight were measured by trained and certified staff persons during an in-person interview, usually in the subject’s home. Weight and height were measured twice while the participant was wearing light clothing but no shoes. Weight was measured on a flat, uncarpeted surface with the use of a TraveLite Portable Digital Scale (SECA, Hamburg, Germany) and was recorded to the nearest 0.1 kg. Height was measured by using the Road Rod Stadiometer (SECA). The horizontal headboard was lowered to the highest point on the head, and height was recorded to the nearest 0.64 cm. When 2 measurements differed by more than 1 pound or 1 inch, a third measurement was obtained. The average of 2 measurements was used for data analysis. Body mass index was calculated as weight in kilograms (kg)/height in meters (m) squared. BMI was categorized for analysis as < 25 (normal-weight), 25–< 30 (overweight), and ≥ 30 (obese).

Statistical analysis

All statistical analysis was performed with SAS software (version 9.1; SAS Institute, Cary, NC). Frequencies and percentages of various aspects of the study population were calculated with respect to race-ethnicity and menopausal status. A chi-square test was used to assess differences in categorical variables, and t tests were used to assess differences in continuous variables. Logistic regression models were used for case-control comparisons. Analyses were run by race-ethnicity and menopausal status and were adjusted for age, center, education, smoking, total activity, calories, dietary fiber, dietary calcium, height, parity, recent hormone exposure, reference year BMI, and the interaction of BMI and recent hormone exposure across quartiles of dietary patterns. A similar approach was taken in postmenopausal women to assess whether recent hormone exposure modified the associations of dietary patterns with the risk of breast cancer.

We stratified the data by BMI status, ethnicity, and menopausal status. There were no substantive differences by ethnicity. Therefore, data are presented as stratified by menopausal status and BMI only. For multiplicative interaction models, we input the 2 interaction terms as ordered categorical variables and added to our model a variable that was the cross-product of the 2 interaction terms. We compared the likelihood ratio for that model with the model without the interaction term by using a chi-square test with 1 df to assess the statistical significance. This model allowed assessment of excess risk for race or menopausal status with a given dietary exposure. Trends in odds ratios (ORs) were determined within each ethnicity and menopausal status strata by comparing the −2 log likelihood of a model with the dietary variable of interest as ordered categorical to a model without the variable of interest (chi-square test with 1 df). We designated the significance level for assessment of associations at P ≤ 0.05 and that for multiple-factor interactions at P < 0.10. We had 80% power to detect ORs of 1.67 among the non-Hispanic white women and 1. 73 among the Hispanic women (interaction of 4 diet factor quartiles and 2 menopausal status categories) with main effects odds ratios of 1.3 (Western diet and breast cancer risk). The minimum detectable OR in the diet factor × BMI interaction within menopausal status was 2.14 for premenopausal women and 1.96 for postmenopausal women when the main-effects OR of 1.3 was used.

RESULTS

The distribution of socioeconomic status, BMI, and physical activity distribution by ethnicity, menopausal status, and case status is shown in Table 1. Hispanic women had higher BMIs and fewer hours of vigorous and total physical activity.

TABLE 1
Characteristics of non-Hispanic white and Hispanic participants1

The risk of breast cancer increased with consumption of a Western diet pattern [OR (highest versus lowest quartile); 1.32; 95% CI: 1.04, 1.68; P for trend < 0.01 in all women combined] and in different strata by ethnicity and menopausal status, except among postmenopausal Hispanic women (Table 2). Irrespective of ethnicity and menopausal status, consumption of a Native Mexican diet was associated with a lower risk for breast cancer in all women (0.68; 0.55, 0.85; P for trend < 0.01). Consumption of a Prudent diet was also associated with a greater risk in all women [OR (highest versus lowest quartile): 1.42; 1.14, 1.77; P for trend < 0.01).The Mediterranean dietary pattern was associated with a decrease in risk of breast cancer in all women (0.76; 0.63, 0.92; P for trend < 0.01). This decrease in risk was most evident among postmenopausal Hispanic women in the highest quartile of the Mediterranean pattern (0.58; 0.37, 0.90; P for trend < 0.01). The Dieter pattern was associated with lower breast cancer risk among premenopausal Hispanic women only (P for trend = 0.01).

TABLE 2
Association of diet patterns with risk of breast cancer stratified by ethnicity and menopause status1

Associations between dietary patterns and breast cancer by BMI and menopausal status are presented in Table 3. Among premenopausal women, the inverse association of the Native Mexican diet was strongest among women with a normal BMI (≤ 25), whereas the association of the Dieter pattern tended to be stronger with BMI ≥ 30. Consumption of a Western diet was associated with a greater risk of breast cancer among postmenopausal women with a BMI < 25, whereas there was no association among women with a BMI ≥ 30.

TABLE 3
Association of diet patterns with risk of breast cancer stratified by menopausal status and body size1

DISCUSSION

In this study of non-Hispanic white and Hispanic women from the US Southwest, we observed a greater risk of breast cancer with Western (high in animal products and refined grains) and Prudent (lower in animal products and rich in fruits, vegetables, and whole grains) dietary patterns. Breast cancer risk decreased among those closely following a Native Mexican dietary pattern (Mexican cheeses, soups, meat dishes, legumes, and tomato-based sauces) and a Mediterranean diet. Associations were generally similar across ethnicity, but there were some differences in association according to menopausal status and BMI.

These data agree with cohort studies that a Western dietary pattern is associated with an increased risk of breast cancer (7, 13). The Western diet is a relatively high-fat, high-sugar, and low-fiber diet characterized by the consumption of eggs, high-fat dairy, refined grains, gravies and sauces, tomato sauces, fast foods, red and processed meats, potatoes, sugar and high-fat, high-sugar desserts. We saw greater risk without respect to menopausal status, although others reported that associations were stronger among subgroups such as postmenopausal women, women with a family history of breast cancer (13), or postmenopausal smokers (7). In contrast, no association of a Western diet and breast cancer risk was reported in a small Italian cohort (207 cases of breast cancer) (14) or in the Nurses’ Health Study II (15), except among ever smokers. Differences in associations could stem from inherent differences in the study designs, study populations, secular trends in food supply, or different definitions of Western diet.

Traditional diets appear to be associated with a lower risk of cancer (8, 13, 16). A traditional southern diet (cooked greens, beans, and legumes; cabbage; fried fish and chicken; and low intakes of mayonnaise or salad dressing) (8) and a traditional Uruguayan diet (boiled meat, grains, cooked vegetables, and tubers) were associated with a lower risk of breast cancer (13), despite being characterized by different foods. The health benefits of traditional dietary patterns may be partially behavioral, although there are clearly components of traditional diets (eg, legumes, cooked vegetables, and tubers) that could confer benefits. Nonetheless, maintenance of the healthful aspects of traditional diets and lifestyles should be encouraged.

These data indicate a greater risk of breast cancer with a dietary pattern characterized by consumption of low-fat dairy foods, fruit and fruit juices, vegetables, soyfoods, legumes and nuts, and whole-grain cereals (Prudent diet). This result is contrary to conventional wisdom and to the results from 3 large cohorts that reported no association of a Prudent or “healthy” diet pattern with breast cancer (7, 15, 17). Whereas the Prudent diet had lower fat and higher fiber than did the Hispanic and Mediterranean diets that were associated with lower risk, the greater source of fiber from the Prudent diet was fruit and vegetables, rather than legumes (4). The Prudent diet was also higher in carbohydrates than were the other diets studied; however, further study would be needed to identify specific foods or nutrients responsible for these differences in risk.

Body size influences breast cancer risk differently in premenopausal and postmenopausal women; higher weight is associated with a lower risk of premenopausal breast cancer (8, 14, 18), whereas risk is reported to increase with BMI in postmenopausal white women (19), although the association may be modified by the use of hormone replacement therapy(5, 20). In both premenopausal and postmenopausal women in the present study, stronger associations with the Western diet were observed among women with the lowest BMI. Moreover, among premenopausal women consuming Native Mexican diets, the reduction in risk was greatest among those with lower BMI. An Italian cohort of premenopausal and postmenopausal women reported a lower risk of breast cancer with the consumption of raw vegetables and olive oil, particularly among normal-weight (BMI < 25) women (14). However, among obese premenopausal women, a greater reduction in breast cancer was associated with consumption of the Mediterranean and Dieter patterns. These data imply that quality of diet is important with respect to risk for breast cancer. However, the influence of quality appears to differ among women, depending on the dietary pattern.

In the present study, women were asked to recall their diet for the year before diagnosis or selection as a control. Recall bias—in this case, women diagnosed with cancer who remembered a healthier or less healthy diet—is always a possibility with a case-control study. In addition, differences in the food supply over time may alter the association of diet with risk for breast cancer, or characteristics of the women in the different studies may contribute to differences. The participation rates in this study were not optimal. Therefore, we examined the characteristics of Hispanic women selected by surname and found that participation rate differed by age, so that older Hispanic women were easier to contact than were younger women, but older women were less likely to participate in the study (21). However, there was no association between community characteristics described by census variables and participation of cases and controls, which suggests that selection bias is not a serious issue for the present study. The participants in the present study reported diet and other exposures for the year before diagnosis with cancer or selection for the study (controls). The reference period may or may not represent the critical period for any given exposure in breast cancer development. The use of statistically defined dietary patterns implies arbitrary assignment of a dietary pattern label, which may not be consistent across studies. Nonetheless, rigorous quality-control standards were used to ensure the highest-quality data collection possible, and only participants who had complete and high-quality dietary data were included in these analyses.

These data suggest that the Western and Prudent diets are associated with greater risk of breast cancer, and that the Native Mexican and Mediterranean diets are associated with lower risk of breast cancer. Some of these associations of dietary factors and breast cancer risk vary by menopausal status and BMI. Some of the reported differences in dietary pattern associations with breast cancer between studies may be related to differences in study population characteristics. Nonetheless, the association of diet and the risk of breast cancer is complex and requires stratification by multiple characteristics.

Acknowledgments

We thank Sandra Edwards, Karen Curtin, Roger Edwards, Leslie Palmer, Joan Benson, Darcy Lauti, Betsy Risendal, Tara Patton, and Kelly May for their contributions to this study.

The authors’ responsibilities were as follows

MAM
data collection and analysis and manuscript preparation and revision
CS
data analysis and manuscript preparation and revision
ARG
study design, data collection, and manuscript preparation and revision
JSH
data analysis
LH
manuscript revision
TB
study design, data collection, and manuscript preparation and revision
KBB
study design, data collection, and manuscript preparation and revision
and MLS
study design, data collection and analysis, and manuscript preparation and revision

Footnotes

2The contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the official views of the National Cancer Institute.

3Supported by grants no. CA 078682, CA 078762, CA078552, and CA078802 from the National Cancer Institute and by the Utah Cancer Registry, which is funded by contract no. N01-PC-67000 from the National Cancer Institute, with support from the State of Utah Department of Health.

None of the authors had a personal or financial conflict of interest.

References

1. American Cancer Society. Cancer facts and figures 2005–2006. Atlanta, GA: American Cancer Society; 2006.
2. Carrozza SE, Lowe HL. Patterns of cancer incidence among US Hispanics/Latinos, 1995–2000. Cancer Causes Control. 2006;17:1067–75. [PubMed]
3. Ogden CL, Carroll MD, Curtin LR, McDowell MA, Tabak CJ, Flegal KM. Prevalence of overweight and obesity in the United States, 1999–2004. JAMA. 2006;295:1549–55. [PubMed]
4. Murtaugh MA, Herrick JS, Sweeney C, et al. Diet composition and risk of overweight and obesity in women living in the southwestern United States. J Am Diet Assoc. 2007;107:1311–21. [PubMed]
5. Slattery ML, Sweeney C, Edwards S, et al. Body size, weight change, fat distribution and breast cancer risk in Hispanic and non-Hispanic white women. Breast Cancer Res Treat. 2006;38:33–41. [PubMed]
6. Sweeney C, Giuliano AR, Baumgartner KB, et al. Oral, injected and implanted contraceptives and breast cancer risk among U.S. Hispanic and non-Hispanic white women. Int J Cancer. 2007;121:2517–23. [PubMed]
7. Fung TT, Hu FB, Holmes MD, et al. Dietary patterns and the risk of postmenopausal breast cancer. Int J Cancer. 2005;116:116–21. [PubMed]
8. Velie EM, Schairer C, Flood A, He JP, Khattree R, Schatzkin A. Empirically derived dietary patterns and risk of postmenopausal breast cancer in a large prospective cohort study. Am J Clin Nutr. 2005;82:1308–19. [PubMed]
9. Slattery ML, Sweeney C, Edwards S, et al. Body size, weight change, fat distribution and breast cancer risk in Hispanic and non-Hispanic white women. Breast Cancer Res Treat. 2007;102:85–101. [PubMed]
10. Slattery ML, Caan BJ, Duncan D, Berry TD, Coates A, Kerber R. A computerized diet history questionnaire for epidemiologic studies. J Am Diet Assoc. 1994;94:761–6. [PubMed]
11. McDonald A, Van Horn L, Slattery M, et al. The CARDIA dietary history: development, implementation, and evaluation. J Am Diet Assoc. 1991;91:1104–12. [PubMed]
12. Liu K, Slattery M, Jacobs D, Jr, et al. A study of the reliability and comparative validity of the CARDIA dietary history. Ethn Dis. 1994;4:15–27. [PubMed]
13. Ronco AL, De Stefani E, Boffetta P, Deneo-Pellegrini H, Acosta G, Mendilaharsu M. Food patterns and risk of breast cancer: a factor analysis study in Uruguay. Int J Cancer. 2006;119:1672–8. [PubMed]
14. Sieri S, Krogh V, Pala V, et al. Dietary patterns and risk of breast cancer in the ORDET cohort. Cancer Epidemiol Biomarkers Prev. 2004;13:567–72. [PubMed]
15. Adebamowo CA, Hu FB, Cho E, Spiegelman D, Holmes MD, Willett WC. Dietary patterns and the risk of breast cancer. Ann Epidemiol. 2005;15:789–95. [PubMed]
16. Marchioni DM, Fisberg RM, Francisco de Gois Filho J, et al. Dietary patterns and risk of oral cancer: a case-control study in Sao Paulo, Brazil Rev Saude Publica. 2007;41:19–26. [PubMed]
17. Terry P, Suzuki R, Hu FB, Wolk A. A prospective study of major dietary patterns and the risk of breast cancer. Cancer Epidemiol Biomarkers Prev. 2001;10:1281–5. [PubMed]
18. Kim EH, Willett WC, Colditz GA, et al. Dietary fat and risk of post-menopausal breast cancer in a 20-year follow-up. Am J Epidemiol. 2006;164:990–7. [PubMed]
19. van den Brandt PA, Spiegelman D, Yaun SS, et al. Pooled analysis of prospective cohort studies on height, weight, and breast cancer risk. Am J Epidemiol. 2000;152:514–27. [PubMed]
20. Lahmann PH, Lissner L, Gullberg B, Olsson H, Berglund G. A prospective study of adiposity and postmenopausal breast cancer risk: the Malmo Diet and Cancer Study. Int J Cancer. 2003;103:246–52. [PubMed]
21. Sweeney C, Edwards SL, Baumgartner KB, et al. Recruiting Hispanic women for a population-based study: validity of surname search and characteristics of nonparticipants. Am J Epidemiol. 2007;166:1210–9. Epub 2007 Sep 7. [PubMed]
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

Recent Activity

    Your browsing activity is empty.

    Activity recording is turned off.

    Turn recording back on

    See more...