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Department of Epidemiology and Surveillance Research, American Cancer Society, Atlanta, Georgia 30329-4251
| Abstract |
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| Introduction |
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The composition of dietary carbohydrate is a major determinant of postprandial blood glucose concentrations, and resultant fluctuations in circulating insulin. The glycemic response induced by carbohydrate intake and subsequent demand for insulin secretion can be classified by the glycemic index of foods (17
, 18)
. Consumption of high glycemic index foods for short time periods (<6 weeks) has been associated with higher postprandial plasma insulin concentrations in healthy adults (19
, 20)
, as well as increased fasting insulin concentrations in obese, insulin-resistant adults (21)
. Prolonged intake of high glycemic index diet patterns were positively associated with the onset of type II diabetes in normal weight and obese adults in population-based studies (22
, 23)
. Two recent case-control studies have reported
30% higher breast cancer risk among women with the highest intake of sweet food items or high dietary glycemic load compared with those with lowest intake of high glycemic index foods (24
, 25) . We prospectively evaluated the association between breast cancer risk and diets containing a high glycemic load and index in postmenopausal women in the CPS II Nutrition Cohort.
| Materials and Methods |
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1.2 million men and women in all 50 states (26)
. Members of the CPS II cohort who resided in 21 states with population-based state cancer registries were invited to participate in the Nutrition Cohort, as described in detail elsewhere (26)
.
The participants were 5074 years of age in 1992, when they completed a 10-page self-administered questionnaire that included information on demographic, medical, behavioral, environmental, occupational, and dietary factors. A follow-up questionnaire was sent to cohort members in September 1997 through August 1998 to update information and to ascertain newly diagnosed cancers. For living cohort members, the response rate was
91%. We excluded from the analysis women who were lost to follow-up from 1992 to 19971998 (n = 7,581), who at baseline reported prevalent breast or other cancer (n = 11,602) or history of diabetes (n = 4,148), or who were not postmenopausal (n = 4,851). Also excluded were women who did not meet the a priori criteria of daily energy intake in the range of 5503,500 kcal/day or who left ≥10 of the 68 questions (15% of items) on the diet questionnaire blank (n = 6,298). After all of the exclusions, the final analytic cohort consisted of 63,307 women. As assessed at baseline in 1992, the majority of participants were white (97.9%), elderly (mean age 62.5 ± 6.1 years), and educated at high school level or higher (95.1%). Those excluded were not different from those who remained with regard to age, weight gain, BMI, reproductive history, and education.
Dietary Assessment.
Usual dietary intake over the past year was assessed at baseline using a semiquantitative 68-item FFQ, which is a modification of the brief "Health Habits and History Questionnaire" developed by Block et al. (27)
. Daily nutrient intake was estimated from the FFQ using the "Health Habits and History Questionnaire" diet analysis software DIETSYS, Version 3.8a (27)
. As assessed previously in this cohort, median validity and reproducibility for nutrients and food groups on the FFQ correlations were 0.58 and 0.69, respectively (28)
.
Total daily dietary glycemic load and glycemic index values were derived from food intake reported on the FFQ. The glycemic index value of a specific food represents a ratio measure for the incremental increase in blood glucose after its consumption relative to that induced by a standard food, white bread (18) . Glycemic index (GI) values for individual food items were added to the nutrient database using published data of glycemic responses measured using standardized analytic methods (18 , 29) . In the case of multiple line items on the Block FFQ, we estimated GI for each food and assigned the line item the weighted average of GI values based on prevalence of estimated population consumption of those items (18 , 30) . The glycemic load of the total diet was calculated by summing across all food items the products of: (a) glycemic index for that food; (b) grams of carbohydrate per serving of that food; and (c) number of daily servings. To derive a score for total dietary glycemic index, the dietary glycemic load of the total diet was divided by total daily carbohydrate intake in grams (22) . Dietary glycemic load and index were evaluated to examine a quantitative measure of the glucose response induced by total daily carbohydrate intake and a score reflecting the relative proportion of high glycemic index foods composing the diet, respectively. To control for energy intake, measures of dietary glycemic index and load were adjusted for total energy using the residuals method (31) .
Case Ascertainment.
This analysis included a total of 1,442 incident breast cancer cases diagnosed after return of the baseline questionnaire through August 31, 1997. The majority of incident cases were initially identified by self-report on the 19971998 follow-up questionnaire and then verified by obtaining medical records or through linkage with state registries when complete medical records could not be obtained (n = 1,164). Verified incident breast cancer cases also included those identified during confirmation of any cancer diagnosis but not self-reported (n = 38). Pilot work linking the Nutrition Cohort members to four state cancer registries indicated that the ability of our respondents to accurately report a past diagnosis of cancer is very high (sensitivity = 0.93, specificity >0.99; Ref. 32
). Therefore, we included in this analysis self-reported breast cancers for which confirmed diagnosis information had not yet been obtained (n = 213). A few incident cases (n = 27) were also identified through automated linkage of the cohort with the National Death Index (33)
. For these cases, the death certificate listed breast cancer as a primary or contributory cause of death (International Classification of Diseases, Ninth Revision, codes 174.0174.9) during the interval from the date of enrollment in 1992 or 1993 and August 31, 1997.
For analysis by stage of disease, the 1,158 breast cancer cases for whom we had information on stage from medical records or state registry linkage were classified by general summary stage into one of three groups. Cases were grouped as in situ (stage I, n = 174), localized (stage II, n = 762), or regional by direct extension, regional to lymph node, regional by direct extension and lymph node, and distant/systemic disease (stage III, n = 222).
Statistical Analysis.
We used Cox proportional hazards modeling to examine the association of dietary glycemic index and dietary glycemic load with breast cancer incidence while adjusting for other potential risk factors. All of the Cox models were stratified on single year of age at enrollment. Multivariate models included other risk factors and confounders, including age at menarche (<12, 13, or ≥14 years), age at menopause (<45, 45-<50, 50-<54, or ≥54 years), number of live births (nulliparous, 12 births, or ≥3 births), age at first live birth (nulliparous, <20, 2024, 2529, or ≥30 years), hormone replacement therapy (never, current, or former), oral contraceptive use (ever or never), family history of breast cancer in a mother or sister (yes or no), personal history of breast cysts (yes or no), education (less than high school, high school graduate, some college, or college graduate), BMI [weight (kg)/height (m)2 ] (<22, 22-<25, 25-<27, 27-<30, or ≥30), adult weight gain from age 18 (≤10, 1025, 2642, or >42 pounds), location of body weight gain by self-report (chest/waist, chest/waist/other, or other than chest/waist), height (<63, 63-<64, 64-<66, or ≥66 inches), physical activity as assessed by metabolic equivalent energy expenditure units (METs) for exercise (34
; MET-hours per week <7, 7-<15, 15-<25.5, or ≥25.5), total energy (quintiles), diethylstilbestrol use (ever or never), alcohol use (none, <1, 1, or >1 drink/day), race (white, black, or other), and smoking status (never, current, or former). Total energy (quintiles) was included, consistent with the residual method of energy adjustment (31)
. Other nondietary and dietary factors (i.e., fat, fiber intake) were considered but were not confounders in the multivariate models.
To test for effect modification by the potential confounders described above, interaction terms between dietary glycemic index (or load) tertiles and each other risk factor were included in multivariate models. Also, we evaluated whether the association between dietary glycemic index or load and breast cancer risk varied by follow-up time. The likelihood ratio test was used to test for significance (35) .
| Results |
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| Discussion |
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Our findings are in contrast to two previous case-control studies evaluating dietary intake patterns characteristic of high glycemic responses (24 , 25) . A positive association of high dietary glycemic load (OR, 1.5) and index (OR, 1.4) with postmenopausal breast cancer risk was described in a large hospital-based case-control study (25) . Another case-control study evaluated early stage disease in premenopausal women only; high intake of refined carbohydrate food items modestly increased risk (OR, 1.3; Ref. 24 ). The lack of association of dietary patterns proposed to increase insulin and potentially IGF-I levels (13, 14, 15, 16) in our cohort of postmenopausal women is not incongruent with studies demonstrating insulin and IGF-I associations only with premenopausal, and modest or no associations only with postmenopausal breast cancer (8, 9, 10 , 37) . Furthermore, it is possible that an association will not be found among disease-free older women (e.g., we excluded women with diabetes at baseline) who are potentially less susceptible to these dietary influences.
Strengths of this study include its prospective design, large size, and ability to examine breast cancer by stage. This study extends findings from available case-control studies by evaluating high glycemic diet patterns and breast cancer risk prospectively with adequate power, while controlling for various potential confounding factors. Furthermore, we found that the relationship between glycemic load or index and breast cancer risk did not differ by breast cancer stage. This does not appear to support the hypotheses that these dietary factors may have a stronger role in advanced cases by influencing the growth-promoting effects of insulin and IGF-I on breast tumor cells (5) .
A potential limitation of our study is the ability of the brief 68-item FFQ to capture the true range of total dietary glycemic load or index, which may be restricted by the limited variety of low and high glycemic index food items. Associations between glycemic load and index, and breast cancer would be expected to be attenuated by random measurement error. In addition, other dietary and behavioral factors, which are known to modify the glycemic response to foods consumed, are not easily assessed by our FFQ. These include food processing or preparation, specific mixtures of food items consumed, and the frequency, timing, and size of meals in relation to daily physical activity. However, reported intake on the FFQ produced estimates for glycemic load and index that were similar in range and variation to values reported in other large cohorts, which were positively predictive of other chronic disease states in those cohorts (22 , 23 , 38) . Although there is some evidence in our data that glycemic load and index are differentially associated with other risk factors, including BMI, weight gain, and physical activity, and, thus, may be measuring different dietary qualities, neither were related to breast cancer risk. Our relatively short follow-up period of 5 years may not have allowed an effect of diet to emerge.
Clinical and observational studies show that prolonged consumption of high glycemic index foods contribute to increased fasting and postprandial insulin levels (19, 20, 21) , and promote the onset of type II diabetes mellitus in healthy adults (22 , 23) . Several prospective and case-control studies have demonstrated independent and positive associations of fasting and nonfasting plasma insulin, and IGF-I concentrations and breast cancer risk (7, 8, 9, 10, 11, 12) . The limited epidemiological data available provide little support for a link between carbohydrate intake and IGF-I levels in women (39) . Future evaluations of dietary glycemic effects would be strengthened by measurement of plasma insulin and IGF-I levels and their relation to postmenopausal breast cancer in this cohort.
In summary, dietary patterns proposed to promote hyperinsulinemia and potentially IGF activity did not appear to increase risk of postmenopausal breast cancer, at least during this 5-year follow-up. A central role of hormonal mechanisms in the etiology of breast cancer is well established. However, the influence of environmental or dietary factors on metabolic or endocrine profiles that ultimately affect breast cancer risk is not well understood. Additional studies are needed to more clearly describe the link between these blood hormone levels and breast cancer risk, and to characterize the lifestyle and physiological factors that determine plasma insulin and IGF-I levels.
| Acknowledgments |
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| Footnotes |
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1 To whom requests for reprints should be addressed, at Epidemiology and Surveillance Research, American Cancer Society, National Home Office, 1599 Clifton Road NE, Atlanta, GA, 30329-4251. Phone: (404) 377-9139; Fax: (404) 327-6450; E-mail: jonasclyn{at}aol.com ![]()
2 The abbreviations used are: IGF, insulin-like growth factor; CPS II, Cancer Prevention Study II; BMI, body mass index; FFQ, food frequency questionnaire; RR, risk ratio; CI, confidence interval; OR, odds ratio. ![]()
Received 12/ 7/01; revised 2/25/03; accepted 3/ 4/03.
| References |
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