QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Nielsen, T. G. Articles by Tjønneland, A. Search for Related Content PubMed PubMed Citation Articles by Nielsen, T. G. Articles by Tjønneland, A.

---

Nutrition and Cancer

Dietary Carbohydrate Intake Is Not Associated with the Breast Cancer Incidence Rate Ratio in Postmenopausal Danish Women¹

Institute of Cancer Epidemiology, The Danish Cancer Society, Copenhagen, Denmark and ^* Department of Clinical Epidemiology, Aalborg Hospital, Aarhus University Hospital, Aalborg, Denmark

²To whom correspondence should be addressed. E-mail: anja{at}cancer.dk.

	ABSTRACT

TOP ABSTRACT SUBJECTS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Although many case-control studies have suggested positive associations between carbohydrate intake and breast cancer incidence rates in both pre- and postmenopausal women, there is limited information available from cohort studies. We examined the effect of the intake of different carbohydrates, the glycemic index, and the glycemic load on breast cancer incidence in postmenopausal women taking into consideration tumor estrogen receptor status. Postmenopausal women (n = 23,870; aged 50–65 y) participated in the "Diet, Cancer, and Health" study, and provided information about diet and established risk factors for breast cancer. During follow-up, we identified 634 incidents of breast cancer. Associations between carbohydrate intake and breast cancer incidence were analyzed using Cox’s regression models. There was no association for intake of glucose, fructose, sucrose, maltose, lactose, or starch and breast cancer incidence rate, and no association for glycemic index or glycemic load after adjusting for confounding factors. Intake of different carbohydrates was not associated with breast cancer incidence rates for either estrogen receptor positive (ER⁺) or (ER^–) breast cancer. Similarly, glycemic index and glycemic load were not associated with ER⁺ breast cancer after adjusting for confounding factors. A borderline significant positive association between glycemic index and (ER^–) breast cancer was observed (P = 0.05). In conclusion, we found no clear associations between intake of different carbohydrates, total carbohydrate intake, glycemic index, or glycemic load and breast cancer incidence in postmenopausal women. Furthermore, when ER⁺ and ER^– breast cancer cases were analyzed separately, no clear associations were observed.

KEY WORDS: • breast cancer • carbohydrates • cohort study • estrogen receptor

Breast cancer is the most frequent type of cancer among women in the Western world (1). In 2002, 31% of women diagnosed with cancer in the United States were diagnosed with breast cancer (2). In Denmark, breast cancer accounted for 25% of all newly diagnosed cancer cases, which made breast cancer the most prevalent type of cancer among Danish women in 1999 (3). Although nutrition, and its potential role in breast cancer etiology, has received considerable scientific attention for many years (4), most research conducted in this field has focused on different types of fat, total energy intake, and alcohol [reviewed by Key et al. (5)], whereas less attention was given to the influence of carbohydrates.

The epidemiologic literature examining breast cancer and carbohydrates consists mainly of case-control studies [reviewed by Burley (6)], although a few prospective cohort studies that examined the effect of glycemic index/glycemic load and breast cancer were published recently. None of these prospective cohort studies were able to show any association (7–10). Some case-control studies observed a positive association between carbohydrate intake and breast cancer incidence (11,12), whereas others have not (13,14). No studies found a lower risk of breast cancer with a higher intake of carbohydrates.

A high intake of carbohydrates was suggested to elevate insulin-like growth factor-I (IGF-I)³ levels, and thereby increase the risk of breast cancer (15), although it was also suggested that the dietary factor most consistently directly related to a higher IGF-I level is protein (16–18). Currently it is not clear whether protein or carbohydrate intake has the greatest influence on IGF-I levels. In vitro, IGF-I is a mitogen for human breast cancer cells (19–21). It was hypothesized that IGF-I and estrogens may act synergistically by stimulating the estrogen receptors (ER) on the breast cancer cell to stimulate cell growth and proliferation (22,23). A recently published study by Colditz and colleagues (24) recommended separate evaluations of breast cancer receptor types, based on their findings that different receptor status types of breast cancer could be influenced by different confounding factors. Therefore, potential effects of carbohydrates on breast cancer incidence are relevant to study with regard to ER status of the breast cancer.

Using data from the "Diet, Cancer and Health" cohort, we evaluated the associations between dietary carbohydrate intake and breast cancer incidence in postmenopausal women. We examined the total daily dietary intake of carbohydrates, glucose, fructose, sucrose, lactose, maltose, starch, glycemic index, and glycemic load. Glycemic index is a measure of postprandial blood glucose response per gram of carbohydrate, whereas the glycemic load value also takes into account the amount of carbohydrate in the given food item.

ER status was available for most of the breast cancer cases, which allowed us to evaluate breast cancer incidence specifically for estrogen receptor positive (ER⁺) and estrogen receptor negative (ER^–) breast cancer. To our knowledge, an investigation of the potential association between carbohydrate intake and the incidence of ER⁺ and ER^– breast cancer has not been published previously.

	SUBJECTS AND METHODS

TOP ABSTRACT SUBJECTS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
    Study population. Danish women (n = 79,729) between 50 and 64 y of age were invited to participate in the "Diet, Cancer and Health" study. Potential participants were identified in The Central Population Registry by a unique 10-digit personal number, which is given to all Danish citizens. Those eligible to participate in the study were women who were born in Denmark, lived in either the greater Copenhagen or Aarhus area, and had never been diagnosed with any type of cancer. A total of 29,875 accepted the invitation, corresponding to 37.5% of the women invited. All participants were interviewed between December 1993 and May 1997.

The "Diet, Cancer, and Health" study along with the present substudy were approved by the regional ethical committees on human studies in Copenhagen and Aarhus and by the Danish Data Protection Agency.

    Data collection. Before examination at 1 of the 2 established study clinics, participants completed a 192-item FFQ, which they received by mail. The development and description of the FFQ were published elsewhere (25). Participants were asked to report their average intake of specific foods and beverages over the past 12 mo, within 12 possible categories ranging from never to 8 times/d. In our analysis, we examined the association between breast cancer incidence and the following carbohydrate fractions: glucose, fructose, sucrose, maltose, lactose, and starch, along with the total daily intake of carbohydrates. Total carbohydrate intake was obtained by summing the known carbohydrate types. Dietary fibers were not included in the analysis because this carbohydrate fraction does not contribute to energy. Daily intake of the different carbohydrate fractions for each participant was calculated by the software program Food Calc (26), using specially developed standardized recipes and portion sizes. A pilot study validated the nutrients recorded in the FFQ against multiple diet records. The nutrients were found to be reasonably well correlated with the diet records [mean energy-adjusted correlation for total carbohydrate intake was r = 0.47 (27)]. In addition to the specific carbohydrate intake, glycemic index and glycemic load were calculated (28).

On entry to the study clinic, participants were further asked to complete a lifestyle questionnaire, which included questions regarding lifestyle habits, social factors, family history of cancer, reproductive factors, and health status. From this questionnaire, we obtained information about parity (parous/nulliparous, number of births, and age at 1st birth), length of school education (short: 7 y, medium: 8–10 y, long: >10 y), use of hormone replacement therapy (HRT; never, past, current), duration of HRT, and alcohol intake. Additional anthropometric measurements were obtained by professional staff, and BMI was calculated as weight (kg) per height (m) squared.

During the visit to the study clinic, the 2 self-administered questionnaires were processed by optical scanning and checked for missing or unclear information. This allowed correct information to be obtained from the participant while still at the study clinic. A few missing questions were accepted in the lifestyle questionnaire but not in the FFQ.

    Exclusions. A total of 333 women were later reported to the Danish Cancer Registry with a diagnosis of cancer before entry into the study, and were excluded. In addition, 8 women were excluded from the study because they did not respond to the lifestyle questionnaire. Because the present analysis aimed at women who were postmenopausal at study entry, we further excluded 4843 women, including 4797 who were considered premenopausal because they had reported at least one menstruation <12 mo before entry and no use of HRT, 9 women who gave a lifetime history of no menstruation, and 37 women who did not answer the questions about current or previous use of HRT. Finally, 821 women were excluded as a consequence of missing information on at least 1 of the questions regarding parity (parous/nulliparous, number of births, and age at 1st birth), length of school education, use of HRT, duration of HRT, and intake of alcohol. A total of 23,870 women met the requirements of the study, including 5247 women who reported a history of either hysterectomy or oophorectomy or both.

    Identification of breast cancer cases. All 23,870 participants were linked to the Central Population Registry for information on vital status and migration. Information regarding cancer occurrence was obtained by linking the personal identification number to the Danish Cancer Registry (29), a registry that includes information regarding individuals diagnosed with cancer. Follow-up for breast cancer was done from the date of entering the study, (i.e., date of first visit to the study clinic), until censoring [the date of diagnosis of any cancer (except for nonmelanoma skin cancer), date of death, date of emigration or December 31, 2002, whichever came first]. Information regarding tumor ER status was obtained from the Danish Breast Cooperative Group, where information regarding > 90% of all breast cancer cases can be retrieved (30).

    Statistical analyses. The analyses of the relation between the breast cancer incidence rate and the exposure variables were based on Cox’s proportional hazard model stratified according to age at entry (1-y intervals) to ensure that the estimation procedure was based on comparisons of individuals of similar age. Additionally, this ensured that the individuals were compared with individuals for whom the exposure variables were registered at the same baseline age. Time under study was used as the time axis. In analysis considering ER status, the 2 types of receptors were regarded as competing causes of failure. The ER⁺ and ER^– cases were analyzed separately where the opposite receptor type was censored at the age of cancer diagnosis. Cases with unknown receptor status were also censored at the age of diagnosis in both analyses.

All statistical analyses were adjusted for known risk factors such as parity (entered as 2 variables, i.e., the categorical variable, parous/nulliparous and the quantitative variable, number of births), age at 1st birth, length of school education (low, medium, high), use of HRT (never, former, current), duration of HRT, BMI, and alcohol intake.

All quantitative variables were entered linearly in the Cox model because this is biologically more reasonable than the step functions corresponding to categorization; furthermore, it increases the power of the analysis (31). The linearity of the associations was evaluated graphically by linear splines with 3 boundaries placed at the quartiles among cases (32). None of the associations showed signs of deflection or threshold values. Glycemic index, glycemic load, and intake of carbohydrates were evaluated linearly for varying units of increment in intake. The units were based on realistic increases of the evaluated type of carbohydrate, glycemic index, or glycemic load. Two-sided 95% CI for the incidence rate ratio (IRR) were calculated on the basis of Wald’s test of the Cox regression parameter, that is, on the log rate ratio scale. The procedure PHREG in SAS (release 8.2; SAS Institute) on a TextPad platform was used for statistical analysis.

	RESULTS

TOP ABSTRACT SUBJECTS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Median age at entry of the women in the study cohort was 57 y (range 50–65 y). Over a mean follow-up of 6.6 (1.1–8.8) y (1st–99th percentile), 634 primary breast cancer cases were identified. Information about tumor ER status was available for 578 (91%) of the 634 breast cancer cases; 456 were ER⁺, and 122 ER^–. For 56 cases, information on receptor status was not available. Of these, it was impossible to determine ER status on 9 in situ tumors, and the remaining 47 could not be located in the registry. The median age of cases at the time of diagnosis of breast cancer was 61 (52–71) y (1st–99th percentile).

Baseline characteristics of the study population and breast cancer cases are presented in Table 1, along with reported mean daily intake of total carbohydrate, glucose, fructose, sucrose, maltose, lactose, and starch. All of the previously suggested risk factors for breast cancer were associated in the expected direction, i.e., breast cancer cases were more highly educated, more often nulliparous, more likely to use or have used HRT, and drank more alcohol than the cohort in general. The reported intake of total carbohydrates was not associated with the incidence rate of breast cancer [IRR: 1.04 (95% CI, 0.95–1.14) per 50 g higher daily intake] (Table 2). Additionally, no association was observed with intake of different carbohydrates (glucose, fructose, sucrose, maltose, lactose, and starch) (Table 2). Adjusting for established risk factors and the intake of different carbohydrate fractions did not appreciably change the results. All adjusted analyses for carbohydrate intake did result in an IRR value > 1 (in the range 1.01–1.06); none were significant. For the glycemic index and the breast cancer incidence rate ratio, a significant negative association was observed before adjusting for potential confounding factors, but this association was not sustained after adjustments were made. Analysis showed that alcohol was the primary factor that changed the estimate (results not shown). We further found no evidence of associations between glycemic load and breast cancer incidence rates (Table 2).

	DISCUSSION

TOP ABSTRACT SUBJECTS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
In this prospective study of the association between intake of dietary carbohydrates, glycemic index, and glycemic load and breast cancer incidence among postmenopausal Danish women, no clear overall associations were found. A borderline significant positive association between glycemic index and ER^– breast cancer incidence (P = 0.05) was observed when differentiating between ER⁺ and ER^– breast cancer cases and adjusting for known risk factors. Results for the other carbohydrate variables did not differ by ER status.

The present study has several strengths. First, the prospective nature of the study eliminated potential recall-bias and the possibility of bias in control selection seen in case-control studies. Second, we were able to control for a variety of potential confounding variables. Third, information about tumor ER status was available for 90% of our breast cancer cases, which allowed us to analyze ER⁺ and ER^– cases separately. Limitations of this study are the relatively short duration of follow-up, as well as the small number of cases, which is primarily a weakness in the analysis restricted to ER^– breast cancer cases. Another limitation is that our results may be biased by unmeasured confounders or by poorly estimated dietary or lifestyle variables. In addition, dietary habits of the study population were considered only at baseline, reflecting the intake during the previous year. This makes it impossible to estimate whether a potential change in dietary habits during the follow-up period would influence breast cancer risk.

Although the number of studies examining intake of dietary carbohydrate and breast cancer incidence was limited and results were conflicting, our results support the findings of the most recently published prospective cohort studies (7,9,10). In 1998, Burley reviewed the available literature on breast cancer and sugar consumption (6). Most studies included in the review were case-control studies. Burley concluded that there might be a weak positive association between a higher intake of carbohydrates and increased breast cancer risk. The same conclusion was reached in a case-control study conducted by Augustin et al. in 2001 (11). They found that breast cancer cases on average consumed a diet with a higher glycemic index compared with controls. However, several recent prospective cohort studies were not able to support these findings. Jonas et al. (7), Higginbotham et al. (9), and Holmes et al. (10) found that dietary glycemic index and overall glycemic load were not associated with the breast cancer rate among postmenopausal women.

The biological background for studying the etiology of carbohydrates in breast cancer is that a positive relation between the levels of the peptide hormone IGF-I and glucose levels was reported in both animal (33) and human (34,35) studies. The physiologically available IGF-I is influenced by IGF binding protein, which was shown to be inversely correlated with serum insulin levels (34). Consequently, elevated blood glucose levels lead to an increase in blood insulin and a decreased production of IGF binding protein, which in turn results in more bioavailable IGF-I (15). Because IGF-I is a mitogen for human breast cancer cells (19–21), an indirect elevation in IGF-I by dietary carbohydrate intake could play a role in breast cancer development. It was also hypothesized that IGF-I and estrogen may be able to stimulate the ER on the breast cancer cell in a synergistic way, and fuel cell growth and proliferation (22,23).

It has not yet been fully established whether ER^– breast cancer is a progressed form of ER⁺ breast cancer or whether the ER⁺ and ER^– breast cancers are 2 biologically different diseases with different risk factors (36). However, a study by Colditz et al. (24) recommended that breast cancer cases should be stratified and analyzed according to their ER status. This recommendation is based on the findings that risk factors may differ between breast cancer cases according to their tumor ER status. The observed increase in breast cancer incidence in the Western world was shown predominantly to be ER⁺ breast cancer cases (37). To our knowledge, this study is the first to examine breast cancer incidence and carbohydrate intake, glycemic index, or glycemic load while differentiating between the 2 types of ER status. Even though the stratification of breast cancer cases weakened the power of our analysis because only 122 women were diagnosed with ER^– breast cancer, our results should be considered as serving to generate hypotheses.

Our findings of the inverse effect of glycemic index on ER⁺ breast cancer and the direct effect on ER^– breast cancer were not expected. These results could be chance findings, and must be examined in other studies.

In conclusion, our results from the prospective cohort study "Diet, Cancer, and Health" indicate that there is no clear association between the intake of different carbohydrates, total carbohydrate intake, overall glycemic index, or dietary glycemic load and breast cancer in postmenopausal Danish women. Furthermore, no associations were found when breast cancer cases were analyzed according to the ER status of their tumor. These results are in accordance with previous prospective cohort studies, but in disagreement with case-control studies. Because relatively few prospective studies on carbohydrate and breast cancer have been published and no previous studies evaluated the effect of ER status of the tumor, further prospective studies are warranted and should include a larger sample size due to the low proportion of ER^– breast cancer tumors.

	ACKNOWLEDGMENTS

 
The authors acknowledge the contribution of Katja Boll, Programmer, and Jytte Fogh Larsen, Secretary, in the collection of the data.

	FOOTNOTES

 
¹ Supported by grants from The Danish Cancer Society and "Europe against cancer:" European Prospective Investigation into Cancer and Nutrition (EPIC).

³ Abbreviations used: ER, estrogen receptor; ER⁺, estrogen receptor positive; ER^–, estrogen receptor negative; HRT, hormone replacement therapy; IGF-I, insulin-like growth factor-I; IRR, incidence rate ratio.

Manuscript received 29 July 2004. Initial review completed 29 August 2004. Revision accepted 24 September 2004.

	LITERATURE CITED

TOP ABSTRACT SUBJECTS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 

1. Parkin, D. M., Pisani, P. & Ferlay, J. (1999) Global cancer statistics. CA Cancer J. Clin. 49:33-64.[Abstract/Free Full Text]

2. Jemal, A., Thomas, A., Murray, T. & Thun, M. (2002) Cancer statistics, 2002. CA Cancer J. Clin. 52:23-47.[Abstract/Free Full Text]

3. [Cancer Incidence in Denmark 1999], in Danish 2003 Danish National Board of Health Copenhagen, Denmark.

4. Wynder, E. L. & Gori, G. B. (1977) Contribution of the environment to cancer incidence: an epidemiologic exercise. J. Natl. Cancer Inst. 58:825-832.

5. Key, T. J., Allen, N. E., Spencer, E. A. & Travis, R. C. (2003) Nutrition and breast cancer. Breast 12:412-416.[Medline]

6. Burley, V. J. (1998) Sugar consumption and human cancer in sites other than the digestive tract. Eur. J. Cancer Prev. 7:253-277.[Medline]

7. Jonas, C. R., McCullough, M. L., Teras, L. R., Walker-Thurmond, K. A., Thun, M. J. & Calle, E. E. (2003) Dietary glycemic index, glycemic load, and risk of incident breast cancer in postmenopausal women. Cancer Epidemiol. Biomark. Prev. 12:573-577.[Abstract/Free Full Text]

8. Cho, E., Spiegelman, D., Hunter, D. J., Chen, W. Y., Colditz, G. A. & Willett, W. C. (2003) Premenopausal dietary carbohydrate, glycemic index, glycemic load, and fiber in relation to risk of breast cancer. Cancer Epidemiol. Biomark. Prev. 12:1153-1158.[Abstract/Free Full Text]

9. Higginbotham, S., Zhang, Z. F., Lee, I. M., Cook, N. R., Buring, J. E. & Liu, S. (2004) Dietary glycemic load and breast cancer risk in the Women’s Health Study. Cancer Epidemiol. Biomark. Prev. 13:65-70.[Abstract/Free Full Text]

10. Holmes, M. D., Liu, S., Hankinson, S. E., Colditz, G. A., Hunter, D. J. & Willett, W. C. (2004) Dietary carbohydrates, fiber, and breast cancer risk. Am. J. Epidemiol. 159:732-739.[Abstract/Free Full Text]

11. Augustin, L. S., Dal Maso, L., La Vecchia, C., Parpinel, M., Negri, E., Vaccarella, S., Kendall, C. W., Jenkins, D. J. & Francesch, S. (2001) Dietary glycemic index and glycemic load, and breast cancer risk: a case-control study. Ann. Oncol. 12:1533-1538.[Abstract/Free Full Text]

12. Potischman, N., Coates, R. J., Swanson, C. A., Carroll, R. J., Daling, J. R., Brogan, D. R., Gammon, M. D., Midthune, D., Curtin, J. & Brinton, L. A. (2002) Increased risk of early-stage breast cancer related to consumption of sweet foods among women less than age 45 in the United States. Cancer Causes Control 13:937-946.[Medline]

13. Katsouyanni, K., Trichopoulou, A., Stuver, S., Garas, Y., Kritselis, A., Kyriakou, G., Stoikidou, M., Boyle, P. & Trichopoulos, D. (1994) The association of fat and other macronutrients with breast cancer: a case-control study from Greece. Br. J. Cancer 70:537-541.[Medline]

14. Dos Santos Silva, I., Mangtani, P., McCormack, V., Bhakta, D., Sevak, L. & McMichael, A. J. (2002) Lifelong vegetarianism and risk of breast cancer: a population-based case-control study among South Asian migrant women living in England. Int. J. Cancer 99:238-244.[Medline]

15. Kaaks, R. (1996) Nutrition, hormones, and breast cancer: is insulin the missing link?. Cancer Causes Control 7:605-625.[Medline]

16. Giovannucci, E., Pollak, M., Liu, Y., Platz, E. A., Majeed, N., Rimm, E. B. & Willett, W. C. (2003) Nutritional predictors of insulin-like growth factor I and their relationships to cancer in men. Cancer Epidemiol. Biomark. Prev. 12:84-89.[Abstract/Free Full Text]

17. Allen, N. E., Appleby, P. N., Davey, G. K., Kaaks, R., Rinaldi, S. & Key, T. J. (2002) The associations of diet with serum insulin-like growth factor I and its main binding proteins in 292 women meat-eaters, vegetarians, and vegans. Cancer Epidemiol. Biomark. Prev. 11:1441-1448.[Abstract/Free Full Text]

18. Holmes, M. D., Pollak, M. N., Willett, W. C. & Hankinson, S. E. (2002) Dietary correlates of plasma insulin-like growth factor I and insulin-like growth factor binding protein 3 concentrations. Cancer Epidemiol. Biomark. Prev. 11:852-861.[Abstract/Free Full Text]

19. Papa, V., Pezzino, V., Costantino, A., Belfiore, A., Giuffrida, D., Frittitta, L., Vannelli, G. B., Brand, R., Goldfine, I. D. & Vigneri, R. (1990) Elevated insulin receptor content in human breast cancer. J. Clin. Investig. 86:1503-1510.

20. Helle, S. I. & Lonning, P. E. (1996) Insulin-like growth factors in breast cancer. Acta Oncol. 35(suppl. 5):19-22.

21. Yu, H., Shu, X. O., Li, B. D., Dai, Q., Gao, Y. T., Jin, F. & Zheng, W. (2003) Joint effect of insulin-like growth factors and sex steroids on breast cancer risk. Cancer Epidemiol. Biomark. Prev. 12:1067-1073.[Abstract/Free Full Text]

22. Lykkesfeldt, A. (1997) Growth Regulation of Human Breast Cancer Cells by Estrogens and Antiestrogens 1997 Doctoral thesis, Department of Tumor Endocrinology, Institute of Cancer Biology, Danish Cancer Society Copenhagen, Denmark.

23. Yee, D. & Lee, A. V. (2000) Crosstalk between the insulin-like growth factors and estrogens in breast cancer. J. Mammary Gland Biol. Neoplasia 5:107-115.[Medline]

24. Colditz, G. A., Rosner, B. A., Chen, W. Y., Holmes, M. D. & Hankinson, S. E. (2004) Risk factors for breast cancer according to estrogen and progesterone receptor status. J. Natl. Cancer Inst. 96:218-228.[Abstract/Free Full Text]

25. Overvad, K., Tjonneland, A., Haraldsdottir, J., Ewertz, M. & Jensen, O. M. (1991) Development of a semiquantitative food frequency questionnaire to assess food, energy and nutrient intake in Denmark. Int. J. Epidemiol. 20:900-905.[Abstract/Free Full Text]

26. Lauritsen, J. () Foodcalc 1.3 http://foodcalc.dk [accessed 1 August 2004].

27. Tjonneland, A., Overvad, K., Haraldsdottir, J., Bang, S., Ewertz, M. & Jensen, O. M. (1991) Validation of a semiquantitative food frequency questionnaire developed in Denmark. Int. J. Epidemiol. 20:906-912.[Abstract/Free Full Text]

28. Foster-Powell, K., Holt, S. H. & Brand-Miller, J. C. (2002) International table of glycemic index and glycemic load values: 2002. Am. J. Clin. Nutr. 76:5-56.[Abstract/Free Full Text]

29. Storm, H. H., Michelsen, E. V., Clemmensen, I. H. & Pihl, J. (1997) The Danish Cancer Registry—history, content, quality and use. Dan. Med. Bull. 44:535-539.[Medline]

30. Fischerman, K. & Mouridsen, H. T. (1988) Danish Breast Cancer Cooperative Group (DBCG). Structure and results of the organization. Acta Oncol. 27:593-596.[Medline]

31. Greenland, S. (1995) Previous research on power loss associated with categorization in dose-response and trend analysis. Epidemiology 6:641-642.[Medline]

32. Greenland, S. (1995) Dose-response and trend analysis in epidemiology: alternatives to categorical analysis. Epidemiology 6:356-365.[Medline]

33. Bar, R. S., Boes, M., Clemmons, D. R., Busby, W. H., Sandra, A., Dake, B. L. & Booth, B. A. (1990) Insulin differentially alters transcapillary movement of intravascular IGFBP-1, IGFBP-2 and endothelial cell IGF-binding proteins in the rat heart. Endocrinology 127:497-499.[Abstract]

34. Conover, C. A. & Lee, P. D. (1990) Insulin regulation of insulin-like growth factor-binding protein production in cultured HepG2 cells. J. Clin. Endocrinol. Metab. 70:1062-1067.[Abstract]

35. Conover, C. A., Lee, P. D., Kanaley, J. A., Clarkson, J. T. & Jensen, M. D. (1992) Insulin regulation of insulin-like growth factor binding protein-1 in obese and nonobese humans. J. Clin. Endocrinol. Metab. 74:1355-1360.[Abstract]

36. Zhu, K., Bernard, L. J., Levine, R. S. & Williams, S. M. (1997) Estrogen receptor status of breast cancer: a marker of different stages of tumor or different entities of the disease?. Med. Hypotheses 49:69-75.[Medline]

37. Lawson, J. S., Field, A. S., Champion, S., Tran, D., Ishikura, H. & Trichopoulos, D. (1999) Low oestrogen receptor alpha expression in normal breast tissue underlies low breast cancer incidence in Japan. Lancet 354:1787-1788.[Medline]

This article has been cited by other articles:

				P. Gnagnarella, S. Gandini, C. La Vecchia, and P. Maisonneuve Glycemic index, glycemic load, and cancer risk: a meta-analysis Am. J. Clinical Nutrition, June 1, 2008; 87(6): 1793 - 1801. [Abstract] [Full Text] [PDF]

				M. Lajous, M.-C. Boutron-Ruault, A. Fabre, F. Clavel-Chapelon, and I. Romieu Carbohydrate intake, glycemic index, glycemic load, and risk of postmenopausal breast cancer in a prospective study of French women Am. J. Clinical Nutrition, May 1, 2008; 87(5): 1384 - 1391. [Abstract] [Full Text] [PDF]

				M. M Heinen, B. A. Verhage, L. Lumey, H. A. Brants, R A. Goldbohm, and P. A van den Brandt Glycemic load, glycemic index, and pancreatic cancer risk in the Netherlands Cohort Study Am. J. Clinical Nutrition, April 1, 2008; 87(4): 970 - 977. [Abstract] [Full Text] [PDF]

				A. W Barclay, P. Petocz, J. McMillan-Price, V. M Flood, T. Prvan, P. Mitchell, and J. C Brand-Miller Glycemic index, glycemic load, and chronic disease risk--a meta-analysis of observational studies Am. J. Clinical Nutrition, March 1, 2008; 87(3): 627 - 637. [Abstract] [Full Text] [PDF]

				S. Sieri, V. Pala, F. Brighenti, N. Pellegrini, P. Muti, A. Micheli, A. Evangelista, S. Grioni, P. Contiero, F. Berrino, et al. Dietary glycemic index, glycemic load, and the risk of breast cancer in an Italian prospective cohort study Am. J. Clinical Nutrition, October 1, 2007; 86(4): 1160 - 1166. [Abstract] [Full Text] [PDF]

				S. E McCann, W. E McCann, C.-C. Hong, J. R Marshall, S. B Edge, M. Trevisan, P. Muti, and J. L Freudenheim Dietary patterns related to glycemic index and load and risk of premenopausal and postmenopausal breast cancer in the Western New York Exposure and Breast Cancer Study Am. J. Clinical Nutrition, August 1, 2007; 86(2): 465 - 471. [Abstract] [Full Text] [PDF]

				E. B Levitan, C. W Westgren, S. Liu, and A. Wolk Reproducibility and validity of dietary glycemic index, dietary glycemic load, and total carbohydrate intake in 141 Swedish men Am. J. Clinical Nutrition, February 1, 2007; 85(2): 548 - 553. [Abstract] [Full Text] [PDF]

This Article Abstract Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Nielsen, T. G. Articles by Tjønneland, A. Search for Related Content PubMed PubMed Citation Articles by Nielsen, T. G. Articles by Tjønneland, A.