Abstract
Limiting energy-dense foods, fast foods, and sugary drinks that promote weight gain is a cancer prevention recommendation, but no studies have evaluated intake in relation to breast cancer risk in African American (AA) women. In a case-control study with 1692 AA women (803 cases and 889 controls) and 1456 European American (EA) women (755 cases and 701 controls), odds ratios (OR) and 95% confidence intervals (CI) for risk were computed, stratifying for menopausal and estrogen receptor (ER) status. Among postmenopausal EA women, breast cancer risk was associated with frequent consumption of energy-dense foods (OR=2.95; 95% CI: 1.66-5.22), fast foods (OR=2.35; 95% CI: 1.38-4.00), and sugary drinks (OR=2.05; 95% CI: 1.13-3.70). Elevated risk of ER+ tumors in EA women was associated with energy-dense (OR=1.75; 95% CI: 1.14-2.69) and fast foods (OR=1.84; 95% CI: 1.22-2.77). Among AA women, frequent fast food consumption was related to premenopausal breast cancer risk (OR=1.97; 95% CI: 1.13-3.43), and with ER+ tumors. Energy adjustment attenuated risk estimates in AA women, while strengthening them among EA women. Frequent consumption of energy-dense and fast foods that have poor nutritive value appeared to increase breast cancer risk in AA and EA women, with differences by menopausal status and ER status.
Keywords: race, breast cancer, energy-dense, African American
Introduction
Weight gain is a critical issue in the US with obesity rates increasing in women regardless of education and income (1). The obesity problem is even graver among African American (AA) women in whom the prevalence of obesity has significantly increased from 1999-2010 (2). Weight gain and obesity have been linked to several chronic diseases including cancer. In particular, body fatness and adult weight gain have been judged as “convincing” and “probable” causes of postmenopausal breast cancer, respectively (3). Consumption of energy-dense foods and sugary drinks could promote weight gain by contributing to increased caloric intake. Energy-dense foods and fast foods mainly include processed food items that contain large amounts of fat or sugar and are commonly consumed, such as baked goods (e.g. cakes, pastries, cookies, and other desserts and confectionery), burgers, and deep fried foods (e.g. French fries, chips, chicken pieces)(3). Sugary drinks mainly include fruit juices with added sugar, sodas and other soft drinks that lead to overconsumption of energy and resulting weight gain.
According to past NHANES data, energy-dense and nutrient-poor foods contribute about 27% of total daily energy intake, with desserts and sweeteners making up almost 20% among all energy-dense and nutrient-poor food groups (4). Higher frequency of fast food consumption has been associated with diets that are loaded with calories and limited in essential nutrients, which could promote weight gain and obesity (5, 6). Increase in dietary energy density has been associated with obesity (7) and overweight across all ethnic groups (8) among US adults. Similarly sugar-sweetened drinks such as soft drinks have also been linked to weight gain and obesity in both observational and experimental studies (9). Increases in energy intake are closely related to circulating levels of insulin-like growth factor (IGF)-1, sex hormone-binding globulin, and estrogen, all important hormonal factors that can play a critical role in cancer cell proliferation or inhibition (10).
Limiting consumption of foods that are high in energy (including fast foods) and sugary drinks is one of the eight evidence-based recommendations proposed by the World Cancer Research Fund (WCRF) and American Institute for Cancer Research (AICR) published in 2007 (3) and included as part of the 2010 Dietary Guidelines for Americans (11). However, to our knowledge, no studies have operationalized this guideline and investigated the association between energy-dense foods or sugary drinks and breast cancer in AA women despite disproportionate rates of overweight and obesity (80% in AA women vs. 60.2% in European American (EA) women) (12). Even in EA women, to our knowledge, no studies have conducted a comprehensive evaluation (such as stratification by menopausal status or hormone receptor status) of foods and drinks promoting weight gain as defined by the WCRF/AICR report (3) and breast cancer risk. Hence, there is a clear gap to be addressed in the nutritional and cancer epidemiology literature. Research on dietary factors that contribute to increased energy intake and weight gain is critical for health education relating to cancer prevention.
We evaluated the relationship between frequency of consuming foods and drinks that promote weight gain, including energy-dense foods, fast foods, and sugary drinks, by operationalizing the definition of the specified guideline provided by WCRF/AICR (3), as well as assessed racial differences in the associations among participants in the Women's Circle of Health Study (WCHS), a case-control study of EA and AA women in New York (NY) and New Jersey (NJ).
Materials and Methods
Study population
The WCHS (13, 14) was a multi-site case-control study conducted in NY and NJ. AA and EA women who were newly diagnosed with histologically confirmed breast cancer, 20-75 years of age, with no prior history of cancer except non-melanoma skin cancer, and able to complete study materials in English were eligible to be cases. Controls did not have breast cancer at the time of recruitment, but met all other eligibility criteria as cases. Case recruitment in NY began in January 2002 and involved major hospitals with the largest referral patterns for AA, and controls were identified through random digit dialing (RDD) matched to cases by area code. Study recruitment in NY ended in 2008. In NJ, the NJ State Cancer Registry implemented rapid case ascertainment in seven NJ counties while controls were recruited using a combination of RDD supplemented by community recruitment for AA women (13). Study recruitment in NJ began in March 2006 and ended in 2012.
Data collection
Home interviews were conducted by trained interviewers to administer questionnaires and collect body measurements. Participants first completed an informed consent following which they completed a main study questionnaire that queried about demographics, and major factors suspected or known to affect breast cancer risk, such as family history, reproductive factors, hormone use, physical activity, and other medical and lifestyle factors. A Food Frequency Questionnaire (FFQ) developed by the Fred Hutchinson Cancer Research Center collected information on frequency and serving size of approximately 125 food items in the 12 month period prior to reference date. Reference date was date of diagnosis for cases and for controls, it was 97 days before date of interview to ensure comparability in recall period by compensating for the time lag between case diagnosis and reporting to registry. This FFQ was based on questionnaires used in two large NIH-funded studies, the Selenium and Vitamin E Cancer Prevention Trial and the VITamins and Lifestyle study. In the past, studies that have specifically assessed the validity and reliability of FFQs in minority populations observed a need to train participants on using self-administered FFQs especially when participants are poorly educated (15). In the WCHS, although the FFQ was generally self-administered, the study interviewers educated all participants on how to respond to the FFQ as part of the in-person appointment. Anthropometric measurements included standing height and weight, were collected as part of the interview, which were then used to compute body mass index (BMI).
Overall, among those who were contacted and eligible, participation rates were 78.7% in AA cases, 48.2% in AA controls, 79% in EA cases, and 49% in EA controls. Hence, a total of 1732 AA women (827 cases and 905 controls) and 1487 EA women (772 cases and 715 controls) participated in the study. Of these, over 97% of women completed the FFQ. Thus, the study sample for this analysis involved 803 AA cases, 889 AA controls, 755 EA cases, and 701 EA controls who completed both the main study questionnaire and the FFQ. The study was approved by the Institutional Review Boards at the University of Medicine and Dentistry of New Jersey (now Rutgers University), Mount Sinai School of Medicine (now Icahn School of Medicine at Mount Sinai), and Roswell Park Cancer Institute.
Operationalization of foods and drinks that promote weight gain
As per WCRF/AICR guidelines(3), foods and drinks that promote weight gain were classified into energy-dense foods, fast foods, and sugary drinks. Food items from the FFQ that were included for each of these food groups are listed in Appendix 1. Using the USDA National Nutrient Database for Standard Reference (16), food items in the FFQ that delivered more than 225 kcal per 100 grams of food were identified as energy-dense foods. Although fast foods are generally energy dense, they were listed under their own category to enable us to evaluate that food group independently. All other foods that met the criteria (3) for being energy dense were included in the energy-dense foods category.
As the recommendation was to consume these foods (and drinks) sparingly, we calculated total frequency of consumption per week for the medium serving of foods included in each of these three groups. As there are no established recommended thresholds, we computed quartiles for frequency of consumption of energy-dense and fast foods based on distribution among controls. Due to the limited consumption of sugary drinks in general, we categorized frequency of consumption as none, low (below median), and high (above median). Frequency of consuming fast foods and sugary drinks was lower in EA women than in AA women, resulting in skewed distributions and very small cell counts especially in the extreme categories when using similar cut points in both races. Hence, to be consistent across all three food groups, race-specific quartiles were used to categorize frequency of energy dense foods, fast foods and sugary drink intake. Since the distribution relating to frequency of energy-dense food consumption was very similar in both races, the race-specific cut points for frequency of energy-dense foods are the same in both EA and AA women. To facilitate interpretation of cut points relating to frequency of intake per week, the thresholds were rounded to the nearest whole number, due to which distribution of frequencies may not be exactly equal in the four groups. Except for one AA woman missing value for sugary drinks, there were no other missing values for energy-dense foods, fast foods, and sugary drinks.
Statistical analyses
Chi square statistics were used to compare distribution of demographics and other characteristics between cases and controls in each race. Summary statistics (mean, median, standard deviation) were computed to compare distributions relating to total caloric intake as well as frequency of consumption of energy-dense and fast foods, and sugary drinks between cases and controls separately in AA and EA women. The non-parametric Wilcoxon Rank Sum Test provided p values for the difference in distributions. Unconditional logistic regression was used to obtain odds ratios (OR) and 95% confidence intervals (CI). Tests of linear trend were computed by assigning the median value to each category. Statistical significance was defined as a p value≤0.05.
Multivariable models were adjusted for age, ethnicity (Hispanic or Non-Hispanic), country of origin (“US born”, “Caribbean born”, “Other”), education (“less than 12th grade”, “high school graduate or equivalent”, some college”, “college graduate”, “post-graduate degree”), age at menarche (continuous), age at menopause (continuous; only for postmenopausal women), menopausal status (if not stratified by this variable), parity (continuous), age at first birth (“nulliparous”, “0-19”, “20-24”, “25-30”, “≥31”), breastfeeding status (ever/never), history of benign breast disease (yes/no), family history of breast cancer (yes/no), hormone replacement therapy (HRT) use (ever/never), oral contraceptive (OC) use (ever/never), body mass index (BMI - continuous), and study site (NY/NJ). As the purpose of this study was to investigate the independent association between frequency of consumption of foods and drinks that promote weight gain and breast cancer risk (as per AICR/WCRF recommendations (3)), results are presented for models with and without adjustment for total caloric intake. Estimates were also assessed with adjustment for total fat intake in place of total calories. Observations that had missing data for any of the covariates were dropped from regression models (n=29 for AA and n=32 for EA women).
All analyses were stratified by race and further stratified by menopausal status and hormone receptor status. As over 70% of cases had information for ER status of their tumor, polytomous logistic regression was used to compute risk estimates for estrogen receptor positive (ER+) and estrogen receptor negative (ER-) tumors with controls as reference. Statistical interactions were evaluated by including a cross product term involving the potential effect modifier in logistic models.
In sensitivity analyses, models were repeated after excluding women with extreme caloric intake (n=157) i.e. less than 500 kcal (n=81 in AA and 21 in EA) or greater than 4500 kcal in a day (n=50 in AA and 5 in EA). All analyses were completed using SAS version 9.2 (SAS Institute, Cary NC).
Results
Study population characteristics are presented in Table 1. Higher proportions of EA women had higher education and were non-obese compared to AA women. In both races, cases were more likely to be HRT users, to have a family history of breast cancer and personal history of benign breast disease. More AA cases had hormone receptor negative tumors than EA cases. The differences in frequency of consuming energy-dense or fast foods were not significantly different between cases and controls in either race (Table 2), but AA women (cases and controls) reported higher total caloric intake compared to EA women. The distribution of reporting frequency of consuming sugary drinks in a week was marginally higher in EA cases than controls (p=0.06), although the opposite was true for total caloric intake (p=0.06).
Table 1. Distribution of selected characteristics for breast cancer among women participating in WCHS, n=3148.
| AA women | EA women | |||
|---|---|---|---|---|
| Cases (n=803) N (%) |
Controls (n=889) N (%) |
Cases (n=755) N (%) |
Controls (n=701) N (%) |
|
| Age at reference date (yrs) | ||||
| 20-34 | 44 (5.5) | 74 (8.3) | 27 (3.6) | 35 (5.0) |
| 35-44 | 173 (21.5) | 190 (21.4) | 153 (20.3) | 162 (23.1) |
| 45-54 | 261 (32.5) | 325 (36.6) | 252 (33.4) | 258 (36.8) |
| 55-64 | 254 (31.6) | 259 (29.1) | 245 (32.5) | 245 (35.0) |
| 65-76 | 71 (8.8) | 41 (4.6) | 78 (10.3) | 1 (0.1) |
| Chi square p value | 0.001 | <0.001 | ||
| 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 (9.8) |
| Some college | 213 (26.5) | 259 (29.1) | 165 (21.9) | 132 (18.8) |
| College graduate | 141 (17.6) | 180 (20.2) | 230 (30.5) | 226 (32.2) |
| Post-graduate degree | 90 (11.2) | 111 (12.5) | 212 (28.1) | 264 (37.7) |
| Chi square p value | 0.11 | <0.001 | ||
| Country of origin | ||||
| United States | 552 (68.7) | 711 (80) | 639 (84.6) | 617 (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 | <0.001 | <0.001 | ||
| 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) | 686 (97.9) |
| Chi square p value | 0.01 | <0.001 | ||
| Marital Status | ||||
| Married | 287 (35.7) | 306 (34.5) | 468 (62.1) | 477 (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 | 0.03 | 0.06 | ||
| Age at menarche (yrs) | ||||
| <12 | 228 (28.4) | 250 (28.2) | 175 (23.4) | 157 (22.6) |
| 12-13 | 365 (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 | 0.94 | 0.28 | ||
| Menopausal status | ||||
| Premenopausal | 408 (50.8) | 463 (52.1) | 389 (51.5) | 385 (54.9) |
| Postmenopausal | 395 (49.2) | 426 (47.9) | 366 (48.5) | 316 (45.1) |
| Chi square p value | 0.60 | 0.20 | ||
| Age at menopause (yrs) | ||||
| ≤45 | 36 (9.4) | 52 (12.3) | 29 (8.1) | 27 (8.7) |
| 46-49 | 60 (15.6) | 108 (25.6) | 73 (20.4) | 71 (22.9) |
| 50-54 | 247 (64.2) | 220 (52.1) | 204 (57) | 175 (56.4) |
| >55 | 42 (10.9) | 42 (10) | 52 (14.5) | 37 (11.9) |
| Chi square p value | 0.001 | 0.70 | ||
| Parity (livebirths) | ||||
| 0 | 124 (15.4) | 148 (16.7) | 237 (31.4) | 206 (29.4) |
| 1-2 | 414 (51.6) | 438 (49.3) | 355 (47) | 355 (50.6) |
| 3-4 | 200 (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 | 0.67 | 0.24 | ||
| Age at first birth (yrs) | ||||
| Nulliparous (0 birthcount) | 124 (15.5) | 148 (16.7) | 237 (31.4) | 206 (29.4) |
| ≤19 | 253 (31.6) | 294 (33.1) | 36 (4.8) | 32 (4.6) |
| 20-24 | 195 (24.3) | 220 (24.8) | 134 (17.8) | 110 (15.7) |
| 25-30 | 149 (18.6) | 120 (13.5) | 190 (25.2) | 170 (24.3) |
| >31 | 81 (10.1) | 106 (11.9) | 158 (20.9) | 183 (26.1) |
| Chi square p value | 0.07 | 0.24 | ||
| Breastfeeding | ||||
| Never | 470 (58.5) | 529 (59.5) | 430 (57) | 355 (50.6) |
| Ever | 333 (41.5) | 360 (40.5) | 325 (43) | 346 (49.4) |
| Chi square p value | 0.68 | 0.02 | ||
| Family history of breast cancer | ||||
| No | 687 (85.6) | 786 (88.4) | 578 (76.5) | 584 (83.3) |
| Yes | 116 (14.4) | 103 (11.6) | 177 (23.4) | 117 (16.7) |
| Chi square p value | 0.08 | 0.001 | ||
| Past benign breast disease | ||||
| No | 547 (68.3) | 685 (77.1) | 431 (57.6) | 466 (66.7) |
| Yes | 254 (31.7) | 203 (22.9) | 317 (42.4) | 232 (33.3) |
| Chi square p value | <0.001 | <0.001 | ||
| HRT use | ||||
| Never | 682 (85.4) | 785 (88.5) | 559 (74) | 540 (77.1) |
| Ever | 117 (14.6) | 102 (11.5) | 196 (26) | 160 (22.9) |
| Chi square p value | 0.06 | 0.17 | ||
| 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) | 498 (71) |
| Chi square p value | 0.38 | 0.02 | ||
| BMI | ||||
| Underweight/Normal | 151 (18.8) | 157 (17.7) | 342 (45.3) | 317 (45.3) |
| Overweight | 235 (29.3) | 255 (28.7) | 206 (27.3) | 191 (27.3) |
| Obese | 416 (51.9) | 477 (53.7) | 207 (27.4) | 192 (27.4) |
| Chi square p value | 0.73 | 0.99 | ||
| Estrogen receptor status | ||||
| ER positive | 409 (69) | - | 413 (82.1) | - |
| ER negative | 184 (31) | - | 90 (17.9) | - |
Table 2. Distribution of the frequency of consuming energy-dense foods, fast foods, and sugary drinks per week among women participating in WCHS, n=3148.
| AA | EA | |||
|---|---|---|---|---|
| Cases | Controls | Cases | Controls | |
| Total caloric intake (kcal) | ||||
| Mean ± SD | 1807.79±1227.46 | 1765.84±1132.48 | 1683.32±721.79 | 1742.19±721.18 |
| Median | 1510.08 | 1553.52 | 1570.47 | 1657.20 |
| P value* | 0.97 | 0.06 | ||
| Frequency of ED foods intake/week | ||||
| Mean ± SD | 8.24±8.57 | 8.46±8.70 | 8.16±6.90 | 7.64±6.64 |
| Median | 6.08 | 5.69 | 6.46 | 6.08 |
| P value* | 0.85 | 0.10 | ||
| Frequency of fast foods intake/week | ||||
| Mean ± SD | 4.09±4.51 | 4.07±4.10 | 4.07±4.10 | 2.53±2.41 |
| Median | 2.77 | 2.85 | 2.15 | 2 |
| P value* | 0.53 | 0.07 | ||
| Frequency of sugary drink intake/week | ||||
| Mean ± SD | 5.00±10.14 | 5.18±9.82 | 1.31±3.98 | 1.19±4.33 |
| Median | 1 | 1 | 0 | 0 |
| P value* | 0.67 | 0.06 | ||
P values are from non-parametric tests
Among AA women (Table 3), after adjustment for total energy intake, consuming fast foods more than five times a week as compared to once or less a week was associated with increased premenopausal breast cancer risk (OR=1.97; 95% CI: 1.13-3.43, p-trend=0.04). Although a significant positive trend between frequency of consuming energy-dense foods and breast cancer was also observed in premenopausal AA women (OR=1.73; 95% CI: 1.13-2.65, p-trend<0.01), this association was not independent of caloric intake. No clear associations were found for postmenopausal women. None of the statistical interaction terms across menopausal status were significant regardless of calorie adjustment [data not shown].
Table 3. Consumption of foods and drinks that promote weight gain and breast cancer risk among AA women by menopausal status.
| (frequency of intake/week) | All women | Premenopausal (n=871) | Postmenopausal (n=821) | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Ca (n) | Co (n) | OR1 | 95% CI | OR2 | 95% CI | Ca (n) | Co (n) | OR1 | 95% CI | OR2 | 95% CI | Ca (n) | Co (n) | OR1 | 95% CI | OR2 | 95% CI | |
| Energy dense foods | ||||||||||||||||||
| Q1 (≤3) | 226 | 256 | Ref | Ref | 99 | 120 | Ref | Ref | 127 | 136 | Ref | Ref | ||||||
| Q2 (3.1-6) | 173 | 214 | 1.07 | 0.80-1.42 | 1.04 | 0.78-1.39 | 91 | 121 | 1.15 | 0.76-1.75 | 1.13 | 0.74-1.72 | 82 | 93 | 1.01 | 0.66-1.53 | 0.99 | 0.65-1.51 |
| Q3 (6.1-11) | 210 | 196 | 1.52 | 1.14-2.02 | 1.43 | 1.06-1.92 | 114 | 108 | 1.54 | 1.01-2.33 | 1.43 | 0.93-2.19 | 96 | 88 | 1.47 | 0.97-2.23 | 1.42 | 0.92-2.18 |
| Q4 (>11) | 194 | 223 | 1.31 | 0.98-1.75 | 1.15 | 0.82-1.61 | 104 | 114 | 1.73 | 1.13-2.65 | 1.45 | 0.89-2.37 | 90 | 109 | 1.04 | 0.69-1.58 | 0.97 | 0.59-1.57 |
| P for linear trend | 0.05 | 0.41 | 0.008 | 0.14 | 0.77 | 0.93 | ||||||||||||
| Fast foods | ||||||||||||||||||
| Q1 (≤1) | 155 | 166 | Ref | Ref | 59 | 71 | Ref | Ref | 96 | 95 | Ref | Ref | ||||||
| Q2 (1.1-3) | 271 | 298 | 1.24 | 0.92-1.66 | 1.22 | 0.91-1.64 | 125 | 144 | 1.52 | 0.95-2.44 | 1.49 | 0.93-2.39 | 146 | 154 | 1.09 | 0.74-1.63 | 1.08 | 0.73-1.61 |
| Q3 (3.1-5) | 158 | 177 | 1.25 | 0.90-1.75 | 1.20 | 0.86-1.68 | 85 | 95 | 1.71 | 1.02-2.86 | 1.61 | 0.95-2.71 | 73 | 82 | 1.01 | 0.64-1.60 | 0.98 | 0.61-1.57 |
| Q4 (>5) | 219 | 248 | 1.53 | 1.10-2.13 | 1.36 | 0.94-1.96 | 139 | 153 | 2.30 | 1.38-3.82 | 1.97 | 1.13-3.43 | 80 | 95 | 1.11 | 0.70-1.77 | 1.02 | 0.60-1.74 |
| P for linear trend | 0.02 | 0.18 | 0.002 | 0.04 | 0.77 | 0.93 | ||||||||||||
| Sugary drinks | ||||||||||||||||||
| None | 285 | 315 | Ref | Ref | 119 | 146 | Ref | Ref | 166 | 169 | Ref | Ref | ||||||
| Low (≤3) | 281 | 282 | 1.16 | 0.91-1.48 | 1.15 | 0.90-1.48 | 147 | 147 | 1.41 | 0.98-2.03 | 1.42 | 0.99-2.05 | 134 | 135 | 0.92 | 0.65-1.31 | 0.91 | 0.64-1.29 |
| High (>3) | 237 | 291 | 1.07 | 0.83-1.39 | 0.97 | 0.74-1.27 | 142 | 169 | 1.35 | 0.92-1.96 | 1.17 | 0.79-1.74 | 95 | 122 | 0.81 | 0.56-1.18 | 0.76 | 0.51-1.12 |
| P for linear trend | 0.94 | 0.45 | 0.41 | 0.98 | 0.30 | 0.18 | ||||||||||||
Ca – case; Co- control
OR1: Adjusted for age, ethnicity, country of origin, education, age at menarche, menopausal status, parity, age at first birth, breastfeeding status, family history of breast cancer, HRT use, OC use, history of benign breast disease, study site, BMI, total MET hours per week
OR2: Further adjusted for total energy intake
In analyses that stratified by hormone receptor status (Table 4), there was a suggestion of an increased risk of ER+ tumors among AA women who reported frequency of consuming energy-dense foods (OR=1.65; 95% CI: 1.15-2.37, p-trend=0.02) or fast foods (OR=1.73; 95% CI: 1.16-2.59; p-trend=0.02) in the highest quartile compared to lowest. However, the estimates were attenuated when total energy intake was added to the model, and confidence interval included the null value. Findings related to risk of ER- tumors were mostly null for all food groups.
Table 4. Consumption of foods and drinks that promote weight gain and breast cancer risk among AA women by hormone receptor status.
| (frequency of intake/week) | ER+Ca (n) | ER-Ca (n) | Co (n) | ER+ vs. Co | ER- vs. Co | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| OR1 | 95% CI | OR2 | 95% CI | OR1 | 95% CI | OR2 | 95% CI | ||||
| Energy dense foods | |||||||||||
| Q1 (≤3) | 99 | 63 | 256 | Ref | Ref | Ref | Ref | ||||
| Q2 (3.1-6) | 100 | 30 | 214 | 1.47 | 1.03-2.09 | 1.43 | 1.00-2.04 | 0.63 | 0.39-1.03 | 0.61 | 0.37-1.01 |
| Q3 (6.1-11) | 108 | 50 | 196 | 1.80 | 1.26-2.58 | 1.68 | 1.17-2.43 | 1.15 | 0.73-1.78 | 1.07 | 0.67-1.69 |
| Q4 (>11) | 102 | 41 | 223 | 1.65 | 1.15-2.37 | 1.40 | 0.92-2.13 | 0.81 | 0.51-1.30 | 0.69 | 0.40-1.19 |
| P for linear trend | 0.02 | 0.25 | 0.72 | 0.34 | |||||||
| Fast foods | |||||||||||
| Q1 (≤1) | 77 | 41 | 166 | Ref | Ref | Ref | Ref | ||||
| Q2 (1.1-3) | 144 | 55 | 298 | 1.33 | 0.93-1.91 | 1.31 | 0.91-1.88 | 0.89 | 0.55-1.44 | 0.87 | 0.54-1.41 |
| Q3 (3.1-5) | 68 | 44 | 177 | 1.08 | 0.71-1.65 | 1.03 | 0.67-1.57 | 1.25 | 0.75-2.09 | 1.19 | 0.70-2.01 |
| Q4 (>5) | 120 | 44 | 248 | 1.73 | 1.16-2.59 | 1.49 | 0.95-2.33 | 0.91 | 0.53-1.56 | 0.79 | 0.43-1.44 |
| P for linear trend | 0.02 | 0.19 | 0.96 | 0.59 | |||||||
| Sugary drinks | |||||||||||
| None | 143 | 63 | 315 | Ref | Ref | Ref | Ref | ||||
| Low (≤3) | 145 | 64 | 282 | 1.23 | 0.91-1.66 | 1.23 | 0.91-1.65 | 1.11 | 0.74-1.66 | 1.11 | 0.74-1.66 |
| High (>3) | 121 | 57 | 291 | 1.14 | 0.83-1.57 | 1.01 | 0.73-1.41 | 0.97 | 0.63-1.49 | 0.91 | 0.58-1.41 |
| P for linear trend | 0.74 | 0.65 | 0.69 | 0.48 | |||||||
Ca – case; Co- control
OR1: Adjusted for age, ethnicity, country of origin, education, age at menarche, menopausal status, parity, age at first birth, breastfeeding status, family history of breast cancer, HRT use, OC use, history of benign breast disease, study site, BMI, total MET hours per week
OR2: Further adjusted for total energy intake
Results from analyses in EA women stratified by menopausal status are presented in Table 5. A statistically significant increased breast cancer risk associated with more frequent consumption of energy-dense foods (OR=1.57; 95% CI: 1.10-2.24, p-trend=0.02) and fast foods (OR=1.75; 95% CI: 1.24-2.46, p-trend<0.01) was observed after adjusting for caloric intake. These associations appeared to be stronger in postmenopausal EA women. In addition, a positive trend between consuming more than one sugary drink a week compared to no consumption and postmenopausal breast cancer risk was also observed in EA women (OR=2.05; 95% CI: 1.13-3.70, p-trend-0.02). There was no significant statistical interaction by menopausal status.
Table 5. Consumption of foods and drinks that promote weight gain and breast cancer risk among EA women by menopausal status.
| (frequency of intake/week) | All women | Premenopausal (n=774) | Postmenopausal (n=682) | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Ca (n) | Co (n) | OR1 | 95% CI | OR2 | 95% CI | Ca (n) | Co (n) | OR1 | 95% CI | OR2 | 95% CI | Ca (n) | Co (n) | OR1 | 95% CI | OR2 | 95% CI | |
| Energy dense foods | ||||||||||||||||||
| Q1 (≤3) | 181 | 198 | Ref | Ref | 93 | 90 | Ref | Ref | 88 | 108 | Ref | Ref | ||||||
| Q2 (3.1-6) | 175 | 151 | 1.28 | 0.93-1.75 | 1.32 | 0.96-1.81 | 76 | 86 | 0.81 | 0.51-1.29 | 0.80 | 0.50-1.27 | 99 | 65 | 1.73 | 1.09-2.74 | 1.91 | 1.19-3.06 |
| Q3 (6.1-11) | 202 | 184 | 1.27 | 0.94-1.73 | 1.36 | 0.99-1.86 | 112 | 105 | 0.97 | 0.63-1.50 | 0.93 | 0.59-1.45 | 90 | 79 | 1.64 | 1.03-2.60 | 2.05 | 1.26-3.32 |
| Q4 (>11) | 197 | 168 | 1.37 | 1.01-1.87 | 1.57 | 1.10-2.24 | 108 | 104 | 1.14 | 0.74-1.75 | 1.04 | 0.64-1.70 | 89 | 64 | 1.82 | 1.12-2.95 | 2.95 | 1.66-5.22 |
| P for linear trend | 0.08 | 0.02 | 0.31 | 0.59 | 0.03 | 0.001 | ||||||||||||
| Fast foods | ||||||||||||||||||
| Q1 (≤1) | 164 | 187 | Ref | Ref | 69 | 73 | Ref | Ref | 95 | 114 | Ref | Ref | ||||||
| Q2 (1.1-2) | 196 | 180 | 1.49 | 1.09-2.03 | 1.51 | 1.11-2.07 | 87 | 98 | 1.16 | 0.72-1.88 | 1.15 | 0.71-1.86 | 109 | 82 | 1.97 | 1.26-3.07 | 2.05 | 1.30-3.21 |
| Q3 (2.1-3) | 156 | 132 | 1.67 | 1.19-2.35 | 1.74 | 1.23-2.45 | 86 | 76 | 1.53 | 0.92-2.52 | 1.49 | 0.89-2.48 | 70 | 56 | 1.83 | 1.11-3.03 | 1.99 | 1.19-3.30 |
| Q4 (>3) | 239 | 202 | 1.60 | 1.16-2.19 | 1.75 | 1.24-2.46 | 147 | 138 | 1.46 | 0.92-2.31 | 1.39 | 0.85-2.27 | 92 | 64 | 1.81 | 1.12-2.95 | 2.35 | 1.38-4.00 |
| P for linear trend | 0.02 | 0.005 | 0.11 | 0.21 | 0.04 | 0.004 | ||||||||||||
| Sugary drinks | ||||||||||||||||||
| None | 524 | 512 | Ref | Ref | 248 | 263 | Ref | Ref | 276 | 249 | Ref | Ref | ||||||
| Low (≤1) | 125 | 120 | 1.08 | 0.80-1.45 | 1.09 | 0.80-1.46 | 86 | 76 | 1.13 | 0.77-1.65 | 1.10 | 0.75-1.62 | 39 | 44 | 0.86 | 0.52-1.44 | 0.88 | 0.53-1.47 |
| High (>1) | 106 | 69 | 1.28 | 0.90-1.84 | 1.31 | 0.91-1.89 | 55 | 46 | 1.01 | 0.62-1.64 | 0.95 | 0.58-1.56 | 51 | 23 | 1.92 | 1.07-3.44 | 2.05 | 1.13-3.70 |
| P for linear trend | 0.18 | 0.15 | 0.97 | 0.80 | 0.03 | 0.02 | ||||||||||||
Ca – case; Co- control
OR1: Adjusted for age, ethnicity, country of origin, education, age at menarche, menopausal status, parity, age at first birth, breastfeeding status, family history of breast cancer, HRT use, OC use, history of benign breast disease, study site, BMI, total MET hours per week; OR2: Further adjusted for total energy intake
When evaluating associations stratified by hormone receptor status in EA women (Table 6), increased reported frequency of consuming energy-dense foods (OR=1.75; 95% CI: 1.14-2.69, p-trend=0.01) and fast foods (OR=1.84; 95% CI: 1.22-2.77, p-trend<0.01) was strongly associated with elevated risk of ER+ tumors. There was a suggestion of elevated risk of ER- tumors with higher frequency of sugary drink intake, but the association was not statistically significant (OR=1.82; 95% CI: 0.93-3.57, p-trend=0.08), possibly due to limited power as there were only 17 EA ER- cases consuming more than one sugary drink per week.
Table 6. Consumption of foods and drinks that promote weight gain and breast cancer risk among EA women by hormone receptor status.
| (frequency of intake/week) | ER+Ca (n) | ER-Ca (n) | Co (n) | ER+ vs. Co | ER- vs. Co | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| OR1 | 95% CI | OR2 | 95% CI | OR1 | 95% CI | OR2 | 95% CI | ||||
| Energy dense foods | |||||||||||
| Q1 (≤3) | 103 | 18 | 198 | Ref | Ref | Ref | Ref | ||||
| Q2 (3.1-6) | 89 | 22 | 151 | 1.10 | 0.75-1.61 | 1.17 | 0.79-1.72 | 1.48 | 0.75-2.93 | 1.47 | 0.74-2.92 |
| Q3 (6.1-11) | 109 | 28 | 184 | 1.22 | 0.85-1.76 | 1.36 | 0.93-1.99 | 1.54 | 0.80-2.99 | 1.52 | 0.76-3.01 |
| Q4 (>11) | 112 | 22 | 168 | 1.38 | 0.95-2.00 | 1.75 | 1.14-2.69 | 1.47 | 0.74-2.94 | 1.43 | 0.65-3.13 |
| P for linear trend | 0.08 | 0.01 | 0.37 | 0.50 | |||||||
| Fast foods | |||||||||||
| Q1 (≤1) | 89 | 21 | 187 | Ref | Ref | Ref | Ref | ||||
| Q2 (1.1-2) | 96 | 21 | 180 | 1.37 | 0.94-2.02 | 1.42 | 0.96-2.08 | 1.07 | 0.55-2.10 | 1.06 | 0.54-2.09 |
| Q3 (2.1-3) | 95 | 17 | 132 | 1.86 | 1.24-2.79 | 1.98 | 1.31-3.00 | 1.25 | 0.60-2.59 | 1.24 | 0.59-2.59 |
| Q4 (>3) | 133 | 31 | 202 | 1.60 | 1.09-2.34 | 1.84 | 1.22-2.77 | 1.46 | 0.76-2.79 | 1.42 | 0.70-2.87 |
| P for linear trend | 0.03 | 0.006 | 0.22 | 0.29 | |||||||
| Sugary drinks | |||||||||||
| None | 292 | 58 | 512 | Ref | Ref | Ref | Ref | ||||
| Low (≤1) | 67 | 15 | 120 | 1.00 | 0.70-1.43 | 1.01 | 0.71-1.45 | 1.08 | 0.57-2.05 | 1.08 | 0.57-2.05 |
| High (>1) | 54 | 17 | 69 | 1.35 | 0.88-2.07 | 1.40 | 0.91-2.16 | 1.86 | 0.96-3.61 | 1.82 | 0.93-3.57 |
| P for linear trend | 0.17 | 0.13 | 0.07 | 0.08 | |||||||
Ca – case; Co- control
OR1: Adjusted for age, ethnicity, country of origin, education, age at menarche, menopausal status, parity, age at first birth, breastfeeding status, family history of breast cancer, HRT use, OC use, history of benign breast disease, study site, BMI, total MET hours per week
OR2: Further adjusted for total energy intake
In sensitivity analyses, overall, there was no change in direction of odds ratios or in main study conclusions when women reporting extremely low or high energy intake were excluded [data not shown]. Adjusting for fat instead of energy intake produced very similar estimates.
Discussion
In the first study to evaluate associations between frequency of consuming foods and drinks that promote weight gain (operationalized as per the AICR/WCRF guideline) and breast cancer risk in a large sample of AA and EA women, higher consumption of energy-dense foods and fast foods was associated with increased breast cancer risk in both AA and EA women, with some differences by menopausal and ER status of the tumor. The positive associations with frequency of fast food intake were stronger among premenopausal AA women and postmenopausal EA women, in whom a positive trend was also observed with frequent intake of energy-dense foods and sugary drinks. Higher frequency of consuming fast foods was associated with increased risk of ER+ tumors in AA women while among EA women, significant risk increase with frequent consumption of energy-dense and fast foods were also mostly observed for ER+ tumors. Adjustment for total energy intake attenuated odds ratios in AA women, but strengthened risk estimates in EA women.
In the EPIC study (17), greater adherence to following the guideline on restricting foods and drinks that promote weight gain was not associated with total cancer incidence in women, and the population was mostly Caucasian. An investigation from the VITamins and Lifestyle Study cohort (18) that focused on adherence to the cancer prevention recommendations and breast cancer risk in postmenopausal women also found no association with meeting the guideline on limiting foods and drinks that promote weight gain and disease risk, but operationalization of this guideline was different from our study. Although there is a plethora of evidence on other AICR/WCRF dietary guidelines in relation to red meat, fruits, vegetables, and alcohol intakes and breast cancer risk, the majority of the literature have focused on EAs (19), with very scarce research on evaluating specific foods and drinks that promote weight gain. Evaluating frequency of commonly consumed energy-dense foods and drinks instead of assessing total energy or dietary fat intake not only serves to directly operationalize the cancer prevention guideline (3), but also presents both a measure and actual food groups that can be more easily comprehended by health promoters and the public. No studies have operationalized and examined racial differences in meeting the guideline on energy-dense foods, fast foods, and sugary drinks in relation to breast cancer risk. Hence, there are no direct comparisons available for most of our study findings.
In the only study that presented breast cancer risk estimates associated with dietary fat in AA and EA women, no significant relationships were observed in AA women while percentage of energy from total fat increased risk in EA women (20). In our study, findings were very similar when adjusting for fat or adjusting for calories. We report results before and after energy adjustment to account for diet composition as well as the total volume of food. Although energy-dense foods increased breast cancer risk in both races, adjustment for energy attenuated associations in AA women and strengthened odds ratios in EA women. To understand potential reasons for these differences, we obtained estimates pertaining to proportion of variation in energy intake accounted for by frequency of consuming energy-dense foods, fast foods, and sugary drinks. Each of these food groups seemed to explain a much higher proportion of total energy intake in AA than in EA women, which suggests that these foods are a bigger part of the diet composition in AA women. In contrast, EA women reported lower intakes of these food groups, and the total energy intake in these women is probably explained by a wider variety of foods. Past NHANES data that investigated dietary diversity in US adults also observed lower diet diversity scores in AA than in EAs (21). Hence, it is possible that among EA women, relatively higher proportions of energy coming from foods that are dense in calories results in stronger associations with risk, while in AA women, the diet composition is not varied enough to detect differences in risk. However, we were unable to evaluate the contrasting findings on energy adjustment after accounting for potential racial differences in metabolism rate, as data on energy expenditure was not collected in our study.
In addition to differences following energy adjustment, EA women appeared to experience increased risks associated with frequent fast food and sugary drink intake at lower thresholds than AA women. These racial differences once again support the notion of more distinct diet composition in EA compared to AA women, due to which small differences in intake levels could result in significant associations. In addition, the differences could also potentially indicate varied levels of susceptibility to physiological changes impacted by dietary intake in addition to BMI. In fact, the relationship between BMI and breast cancer risk has not been consistent in EA and AA women in the literature. Although BMI is an established risk factor for breast cancer in postmenopausal EA women, the associations in AA women are inconclusive(19), including a null association that was observed between BMI and breast cancer risk using anthropometric data collected in the WCHS(22). Furthermore, the body composition publication from WCHS also observed increased premenopausal breast cancer risk with higher waist and hip circumferences in AA women(22), while among premenopausal EA women, the literature has shown reduced breast cancer risk with increased body fatness(3). Put together, this evidence suggests plausible racial differences in nutritional factors and breast cancer risk and possibly suggests that the increased risk may not just be mediated by increases in body weight.
Reasons for the observed racial differences by menopausal status are unclear. In our study, the positive associations observed with increased frequency of consuming energy-dense foods were more dominant in premenopausal AA and postmenopausal EA women. Energy imbalance was related to increased breast cancer risk particularly in premenopausal women in the National Breast Screening Study (23), and total energy intake increased breast cancer risk in premenopausal women in a study involving sisters in a recent study (24), but race-specific estimates were not provided. Aside from consideration of chance findings, potential racial differences in the way menopausal status modifies the relationship between consuming energy-dense foods and breast cancer risk should be investigated further.
The elevated risks associated with energy-dense and fast food intakes were more pronounced for ER+ tumors in both AA and EA women, however the risk estimates were attenuated with energy adjustment in AA women. Our findings are consistent with a recent study based on data from the Breast Cancer Family Registry that reported elevated risk of both hormone receptor positive and negative tumors corresponding to energy intake, but significant increased risk was found only for hormone receptor positive tumors (24). In addition to being more common than ER- tumors, ER+ tumors are more closely related to hormonal factors and therefore may be more responsive to hormonal levels impacted by diet. However, findings for ER- tumors warrant further investigation on potential non-estrogenic pathways that could mediate the role of consuming energy-dense foods and drinks. The small sample sizes in some cells could also have caused significant differences in risk, and hence the strong odds ratios should be viewed with caution.
Certain limitations of the study should be noted. Bias in recalling intake of ‘seemingly’ unhealthy foods cannot be ignored. Data on change in behaviors since diagnosis showed that more AA and EA cases (49% and 35%) had decreased total energy intake since diagnosis compared to AA and EA controls (35% and 30%), respectively. A similar pattern was observed for fast food consumption. However, if cases had under-reported intake of energy-dense foods by incorrectly reporting dietary behavior since diagnosis, then such an under-reporting would probably underestimate the observed associations. Racial differences in recall should also be considered, especially in studies that use self-reported data. For instance, more EA respondents (both cases and controls) reported ‘no change’ in their intake of calories and fast foods than AA participants, while the majority of AA cases and controls reported ‘decreasing’ total caloric and fast food intake (data not shown), despite having higher caloric intake (Table 2) and more frequent intake compared to EA women, as demonstrated by the higher cut points for fast foods and sugary drinks. Nutrition studies that have evaluated racial differences have also used self-reported dietary data in the past (25, 26), and results should be viewed with caution until investigations are repeated in other EA and AA populations.
The main strength of this study was the ability to conduct a comprehensive evaluation of the AICR/WCRF guideline on restricting foods and drinks that promote weight gain and using a large sample of AA and EA women. As WCHS was specifically designed to evaluate breast cancer risk factors in AA women, the study sample enabled analyses further stratified by menopausal and ER status while evaluating racial differences in the associations. Moreover, as this study involved population-based recruitment and is an association study rather than a prevalence study, findings can be generalized to AA and EA women in the US.
In summary, frequent consumption of energy-dense and fast foods that are poor in nutritive value appeared to increase breast cancer risk in AA and EA women, with some differences by menopausal status and hormone receptor status. Hence, public health education programs should continue to promote the cancer prevention guidelines, with specific attention to diet interventions that could have multifaceted benefits by reducing weight gain while improving dietary quality.
Acknowledgments
We thank the colleagues, physicians and clinical staff in New York and New Jersey who facilitated identification and enrollment of cases into the study: Kandace Amend (i3 Drug Safety), Helena Furberg (Memorial Sloan-Kettering Cancer Center), Thomas Rohan and Joseph Sparano (Albert Einstein College of Medicine), Paul Tartter and Alison Estabrook (St. Luke's Roosevelt Hospital), James Reilly (Kings County Hospital Center), Benjamin Pace, George Raptis, and Christina Weltz (Mount Sinai School of Medicine), Maria Castaldi (Jacob Medical Center), Sheldon Feldman (New York-Presbyterian), and Margaret Kemeny (Queens Hospital Center). We also thank our research personnel at the Rutgers Cancer Institute of New Jersey, Roswell Park Cancer Institute, Mount Sinai School of Medicine, Rutgers School of Public Health, and the New Jersey State Cancer Registry, as well as our African American breast cancer advocates and community partners, and all the women who generously donated their time to participate in the study.
Sources of support: This work was funded by National Cancer Institute (P01 CA151135, R01 CA100598, K22 CA138563, and P30CA072720), US Army Medical Research and Material Command (DAMD-17-01-1-0334), the Breast Cancer Research Foundation, and a gift from the Philip L. Hubbell family. 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 1US58DP003931-01 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 N01PC-2010-00027 and the State of New Jersey. The funding agents played no role in design, in the collection, analysis, and interpretation of data, in the writing of the manuscript, or in the decision to submit the manuscript for publication.
Abbreviations
- AA
African American
- EA
European American
- OR
odds ratio
- CI
confidence interval
- WCRF
World Cancer Research Fund
- AICR
American Institute for Cancer Research
- WCHS
Women's Circle of Health Study
- NY
New York
- NJ
New Jersey
- RDD
random digit dialing
- FFQ
food frequency questionnaire
- HRT
hormone replacement therapy
- OC
oral contraceptive
- BMI
body mass index
- ER
estrogen receptor
Appendix
Appendix 1.
List of food items from the FFQ that were included in the energy-dense foods, fast foods, and sugary drinks groups as per Second Expert Report(3).
| Category of foods/drinks that promote weight gain | Food Items from the FFQ |
|---|---|
| Energy-dense foods | “Ice cream and milkshakes”, “doughnuts, pies and pastries”, “cookies and cakes”, “chocolate, candy bars and toffee”, “other candy”, “buttered or regular microwave popcorn”, “regular crackers”, “regular potato chips, tortilla chips, corn chips, and puffs”, “pancakes, French toast, waffles”, “muffins, scones, croissants and biscuits”, “cornbread and corn muffins” |
| Fast foods | “hot dogs and sausage”, “ground meat including hamburgers and meatloaf”, “fried chicken, including nuggets and tenders”, “fried fish, fish sandwich, fried shellfish”, “pizza”, “burritos, tacos, quesadillas”, “French fries, fried potatoes and hash browns”, “enchiladas” |
| Sugary drinks | “Fruit drinks fortified with Vitamin C such as Hi-C, Fruitopia, and Kool-Aid”, “regular soft drinks” |
Footnotes
Conflicts of Interest: None of the authors have any conflicts of interest to declare.
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