Waist–hip ratio and breast cancer risk in urbanized Nigerian women
https://doi.org/10.1186/bcr567
© Adebamowo et al., licensee BioMed Central Ltd. 2003
Received: 12 August 2002
Accepted: 5 December 2002
Published: 19 December 2002
Abstract
Background
The aim of this study was to examine the relationship between waist–hip ratio and the risk of breast cancer in an urban Nigerian population.
Methods
Between March 1998 and August 2000, we conducted a case–control study of hospital-based breast cancer patients (n = 234) and population-based controls (n = 273) using nurse interviewers in urban Southwestern Nigeria.
Results
Multivariable logistic regression showed a significant association between the highest tertile of waist–hip ratio and the risk of breast cancer (odds ratio= 2.67, 95% confidence interval = 1.05–6.80) among postmenopausal women. No association was found in premenopausal women.
Conclusion
The present study, the first in an indigenous African population, supports other studies that have shown a positive association between obesity and breast cancer risk among postmenopausal women.
Keywords
Introduction
Breast cancer is the leading female malignancy in the world and is now the most common cancer in Nigeria [1–3]. Despite this, there is a sixfold variation in incidence when Western countries are compared with the developing countries of Africa and Asia, and immigrants from low incidence countries tend to acquire the rate of their new environments [2, 4]. Some of this variation may be due to demographic factors such as longer life expectancy, better reporting of disease and improved access to clinical care. There is increasing interest, however, in the relative importance of environmental and genetic factors as explanations for this difference.
In general, African breast cancer patients tend to present at a young age, with large tumors and multiple nodal involvements, and have poorer clinical and pathological prognostic factors compared with Caucasian patients. These characteristics are somewhat similar to that of African-Americans but are in contrast with those of non-Hispanic Whites in the USA, thus heightening the interest in the role of genetic factors in the etiology of breast cancer in general, and in people of African origin in particular [3, 5].
One of the often cited reasons for the difference in breast cancer incidence in Africa compared with Western countries is the difference in environmental risk factors such as diet and physical activity (both contributing to obesity), use of hormones/other medications, and obstetric/gynecological practices [6]. In the current paper, we present the results of the first study of the association between waist–hip ratio (WHR) and breast cancer in an indigenous African population.
The WHR has emerged as an important metameter of the association between central adiposity and many obesity-related diseases. Positive correlations have been seen with coronary heart disease, adult-onset diabetes mellitus and stroke [7]. However, the result with breast cancer has been inconsistent [8]. Abdominal obesity may be related to breast cancer through aberrant insulin signaling leading to increased endogenous androgen and estrogen levels [9].
Methods
Case ascertainment
All consecutive cases of breast cancer, regardless of previous history, seen at presentation and later confirmed histologically in the Departments of Surgery and Radiotherapy of the University College Hospital, Ibadan, Nigeria, from March 1998 to August 2000 were recruited at their first clinic presentation, after obtaining informed consent. Nurse interviewers asked them which risk factors did apply at the time when they were last well. The interviewer then measured the height, weight, and hip circumference at its widest diameter. Waist circumference was measured according to the guidelines in the World Health Organization MONICA Project manual [10].
There were 312 cases, of which 73 indicated that they had lived predominantly in a rural area and were excluded. There were five refusals and no further information was available from these, leaving 234 cases.
Control ascertainment
During the period of case recruitment, a community adjoining the hospital was randomly selected by ballot based on comparability with the hypothetical catchment area of the hospital. Community consent was sought from the Chief-in-Council and approval for the study was communicated to members of the community through heads of households. The census register of the people living in the community was obtained and community consent sought for the study. Names were then randomly selected from the community register and the people were invited to visit a clinic set up in the community for the study.
Inclusion criteria for the controls were females aged older than 18 years, absence of any type of cancer at recruitment, predominant urban residence for most of their lives and the ability to give informed consent. No matching of controls to cases was performed. After explaining the project to the potential participant, a complete physical examination was carried out. A trained nurse then interviewed the participants, measured their height, their weight, their hip circumference at its widest diameter and their waist circumference 1 inch below the navel, and completed the questionnaires. A total of 278 subjects were interviewed, of which 273 were recruited; there were three refusals, and two people were not recruited on account of a diagnosis of cancer (head of the pancreas cancer in one and colorectal cancer in the other).
Data collection and analysis
The information obtained from the cases and controls include age, self-reported social status based on family income and other baseline demographic information. Obstetric and gynecological history such as age of onset of menarche, menstrual cycle history, whether periods had usually been regular, age at onset of menopause (natural or otherwise) and history of previous breast disease, as well as smoking, drug and alcohol use history, were obtained from the subjects. Other information obtained included first-degree family history of breast cancer, history of ever using estrogen-containing contraceptives and where they had lived most of their lives (whether in a rural or urban setting). No information about postmenopausal hormonal use was obtained as this is an uncommon practice in Nigeria.
The body mass index (BMI) (weight [kg]/height [m2]; obesity = BMI ≥ 30) and WHR were computed (waist circumference [cm]/hip circumference [cm]), and four subjects with WHR > 1.2 and WHR < 0.6 were excluded. The rest were divided into tertiles and treated as categories. Statistical analysis of the data was carried out with SAS version8.0 (SAS Institute, Inc., Cary, NC, USA) separately for premenopausal and postmenopausal women. Univariate analysis was used to identify variables to be included in multivariable analysis using P ≤ 0.10. Purposeful stepwise multivariable logistic regression models were built to identify statistically significant variables at P = 0.05, and a 10% or greater change in the β-coefficient was used to identify confounders. In addition, automated stepwise multivariate logistic regression models were run as an adjunct to the aforementioned method.
Continuous variables were examined for assumption of linearity; age and age at onset of regular menstrual periods were found to be nonlinear. Age was subsequently divided into 5-year categories while age at onset of regular menstrual periods was left as it was because the range of values was narrow, but it was subsequently modeled as a categorical variable.
Results
The WHR in this study was measured at presentation in cases and, since most patients presented in an advanced stage of disease, there may have been significant weight loss among the cases prior to recruitment. However, there was no significant difference in the frequency of the stage of disease (based on size of tumor at presentation) by obesity (BMI > 30) among premenopausal (P [chi-squared test] = 0.18) and postmenopausal women (P = 0.20) on the one hand, and in WHR among premenopausal women (P = 0.26) and postmenopausal women (P = 0.63) on the other.
Premenopausal women
Continuous predictors of breast cancer among premenopausal women in Nigeria, 1998–2000
Predictor | Cases | Controls | Odds ratio | 95% confidence interval | P value |
|---|---|---|---|---|---|
Age (years) | 38.34 (6.55) | 34.23 (8.80) | 1.07 | 1.04–1.10 | <0.01 |
Total number of pregnancies | 4.41 (2.29) | 3.82 (2.69) | 0.90 | 0.79–1.03 | 0.13 |
Age at menarche (years) | 15.01 (1.88) | 15.51 (2.30) | 0.86 | 0.77–0.97 | 0.01 |
Age at first full-term pregnancy (years) | 23.80 (4.30) | 22.54 (3.70) | 1.09 | 1.02–1.16 | 0.01 |
Height (cm) | 160.50 (8.62) | 159.38 (7.17) | 1.03 | 1.00–1.07 | 0.07 |
Weight (kg) | 64.25 (14.51) | 65.52 (15.28) | 1.01 | 0.99–1.03 | 0.19 |
Body mass index (weight/height2) | 24.76 (5.55) | 23.65 (4.85) | 1.02 | 0.97–1.07 | 0.54 |
Waist circumference (cm) | 80.60 (11.84) | 77.56 (10.73) | 1.01 | 0.99–1.04 | 0.28 |
Hip circumference (cm) | 99.03 (14.89) | 97.07 (11.07) | 1.01 | 0.99–1.02 | 0.61 |
Categorical predictors of breast cancer among premenopausal women in Nigeria, 1998–2000
Predictor | Cases | Controls | Odds ratio | 95% confidence interval | P value |
|---|---|---|---|---|---|
Waist–hip ratio | |||||
≤ 0.77 | 37 (30.8) | 64 (35.6) | 1.00 | ||
>0.77 to ≤ 0.85 | 45 (37.5) | 78 (43.3) | 0.88 | 0.50–1.55 | 0.65 |
>0.85 | 38 (31.67) | 38 (21.2) | 1.41 | 0.80–2.78 | 0.22 |
Family history of breast cancer | |||||
Yes | 11 (9.17) | 14 (7.78) | 1.37 | 0.58–3.22 | 0.48 |
No | 109 (90.83) | 166 (92.22) | |||
Obesity (body mass index ≥ 30) | |||||
Yes | 29 (24.17) | 25 (13.89) | 1.52 | 0.82–2.82 | 0.18 |
No | 91 (75.83) | 155 (86.11) | |||
Having ever breastfed | |||||
Yes | 102 (85.71) | 133 (73.89) | 1.04 | 0.50–2.18 | 0.91 |
No | 17 (14.29) | 47 (26.11) | |||
Use of contraceptive pill | |||||
Yes | 53 (45.30) | 62 (34.44) | 0.84 | 0.51–1.39 | 0.50 |
No | 64 (54.70) | 118 (65.56) | |||
Social status | |||||
Low | 54 (46.15) | 98 (54. 75) | 1.00 | 0.15 | |
Middle | 60 (51.28) | 80 (44.69) | 1.36 | 0.85–2.18 | |
High | 3 (2.56) | 1 (0.56) | 5.44 | 0.55–53.62 |
Multivariable odds ratio, 95% confidence interval andP value, adjusted for age in categories, age at first pregnancy, height and age at menarche in premenopausal women in Nigeria, 1998–2000
Predictor | Adjusted odds ratio | 95% confidence interval | P value |
|---|---|---|---|
Waist–hip ratio | |||
≤ 0.77 | 1.00 | ||
>0.77 to ≤ 0.85 | 0.80 | 0.40–1.60 | 0.53 |
>0.85 | 1.80 | 0.85–3.81 | 0.13 |
Postmenopausal women
Continuous predictors of breast cancer among postmenopausal women in Nigeria, 1998–2000
Predictor | Cases | Controls | Odds ratio | 95% confidence interval | P value |
|---|---|---|---|---|---|
Age (years) | 53.62 (9.55) | 58.42 (7.92) | 0.939 | 0.09–0.97 | 0.01 |
Total number of pregnancies | 5.99 (2.21) | 6.75 (2.24) | 0.89 | 0.71–1.02 | 0.10 |
Age at menarche (years) | 15.58 (2.11) | 16.35 (2.72) | 0.89 | 0.78–1.02 | 0.08 |
Age at first full-term pregnancy (years) | 23.34 (4.23) | 22.99 (4.20) | 0.98 | 0.92–1.06 | 0.65 |
Age at onset of natural menopause (years) | 47.37 (6.49) | 50.02 (5.59) | 0.97 | 0.91–1.03 | 0.35 |
Height (cm) | 159.37 (6.66) | 155.99 (9.33) | 1.07 | 1.02–1.13 | 0.01 |
Weight (kg) | 65.52 (15.28) | 62.32 (13.66) | 1.02 | 1.00–1.04 | 0.07 |
Body mass index (weight/height2) | 25.71 (5.86) | 25.39 (5.63) | 1.02 | 0.97–1.08 | 0.48 |
Waist (cm) | 86.11 (14.18) | 83.28 (10.36) | 1.01 | 1.00–1.05 | 0.03 |
Hip (cm) | 102.31 (17.05) | 102.88 (16.93) | 1.00 | 0.98–1.02 | 0.93 |
Comparison of categorical predictors of breast cancer among postmenopausal women in Nigeria, 1998–2000
Predictor | Cases | Controls | Odds ratio | 95% confidence interval | P value |
|---|---|---|---|---|---|
Waist–hip ratio | |||||
≤ 0.77 | 16 (15.4) | 21 (23.6) | 1.00 | ||
>0.77 to ≤ 0.85 | 40 (38.5) | 40 (44.9) | 1.52 | 0.67–3.42 | 0.31 |
>0.85 | 48 (46.15) | 28 (31.5) | 2.79 | 1.21–6.45 | 0.02 |
Family history of breast cancer | |||||
Yes | 7 (6.73) | 8 (8.99) | 0.70 | 0.23–2.09 | 0.52 |
No | 97 (93.27) | 81 (91.01) | |||
Obesity | |||||
Yes | 31 (29.81) | 16 (17.98) | 2.01 | 0.99–4.09 | 0.05 |
No | 73 (70.19) | 73 (82.02) | |||
Having ever breastfed | |||||
Yes | 101 (97.12) | 89 (100) | a | a | a |
No | 3 (2.88) | 0 (0) | |||
Use of contraceptive pill | |||||
Yes | 34 (34) | 25 (28.09) | 0.96 | 0.50–1.84 | 0.90 |
No | 66 (66) | 64 (71.91) | |||
Social status | |||||
Low | 49 (47.12) | 57 (64.77) | 1.00 | 0.97–3.19 | 0.06 |
Middle | 47 (45.19) | 31 (35.23) | 1.79 | ||
High | 8 (7.69) | 0 | a | a |
Multivariable odds ratio, 95% confidence interval and P value, adjusted for age in categories and height in postmenopausal women in Nigeria, 1998–2000
Predictor | Adjusted odds ratio | 95% confidence interval | P value |
|---|---|---|---|
Waist–hip ratio | |||
≤ 0.77 | 1.00 | ||
>0.77 to ≤ 0.85 | 1.68 | 0.68–4.19 | 0.26 |
>0.85 | 2.67 | 1.05–6.80 | 0.04 |
Discussion
The earliest reports of the positive association between energy balance and breast cancer date back to 1942 [11]. Numerous case–control and cohort studies have subsequently supported this association. However, the strength of the association and the category of patients in whom the association was seen varied from study to study. In addition, there are methodological concerns about the most appropriate measure of obesity, and which component or type of obesity is etiologically significant.
The WHR, a measure of central adiposity, is gaining increased use as a measure of etiologically significant obesity and is thought to be more closely related to pathology, especially coronary heart disease, diabetes mellitus and stroke [7]. The metabolic changes that accompany obesity include peripheral hyperinsulinemia, hyperglycemia and glucose intolerance, hypertriglyceridemia, decreased serum low-density lipoprotein, increased serum very low-density lipoprotein, increased serum leptin, dyslipidemia, increased serum cortisol clearance, increased serum C-peptide level, downregulation of insulin receptors and an exaggerated insulin response to an oral glucose load [12–15]. These changes, especially when they occur in early adulthood, may be of fundamental importance in the development of breast cancer [9, 16].
Obesity is also associated with significant hormonal changes such as decreased serum estradiol and sex hormone binding globulin (SHBG) levels, increased peripheral fat conversion of estrogens to progesterone and increased serum testosterone levels that may be associated with an increased risk of breast cancer [17]. Estrogens are necessary for normal breast development, and they induce and promote mammary tumor growth in animal studies [18]. In addition, the close association between increased risk of breast cancer and certain reproductive factors such as early menarche and late menopause [19], as well as the fall off in the rate of increase in the incidence of disease at menopause [20] and the lowered risk of breast cancer in oophorectomized women and those taking antiestrogens [21, 22], all support the role of estrogen in breast carcinogenesis.
The results from cohort studies about the association between WHR and the risk of breast cancer are inconsistent. In the Nurses' Health Study, the adjusted risk for the highest quintile compared with the lowest quintile of WHR among postmenopausal women who had never used hormone replacement therapy was 1.85 (95% confidence interval = 1.25–2.74) [23]. Kaaks et al. reported a risk ratio of 2.63 (95% confidence interval = 1.09–6.35) comparing the highest quintile with the lowest quintile of WHR [24]. These are similar to the results obtained in the present study. In contrast, the Iowa Women's Health Study showed no association with WHR, and an earlier report of interaction with family history appeared to have attenuated with time [25, 26]. In the New York University Women's Health Study, the multivariable analysis showed an association between the lowest quintile and the highest quintile of WHR and breast cancer of 1.72 (95% confidence interval = 1.0–3.1) among premenopausal women, but there was no association among postmenopausal women [27].
Most case–control studies have found an association between WHR and the risk of postmenopausal breast cancer [28–37], and most report either null or weakly positive association with premenopausal breast cancer. In the present study, there was no statistically significant association between breast cancer and WHR for premenopausal women.
Studies of WHR and the risk of breast cancer are limited by systematic bias in the measurement of WHR across studies [36], which may have been controlled somewhat in this study by using nurse interviewers and adhering to the World Health Organization MONICA guidelines [10]. In case–control studies like the present one, selection and recall bias can be problematic. While we restricted our analysis to urban dwellers, finer adjustment based on the community of residence or the restriction of cases to only those from the community from which controls were selected would have increased the validity of the result. The finding of two cases of cancer among the controls may be due to chance.
The prevalence of obesity in the cases and controls also appears higher than expected but this may be consistent with the increasing rate of obesity in developing countries, especially in the urban areas [38]. Preclinical weight loss is not usually a problem in breast cancer [39], and sub-analysis of our data confirmed this. Inclusion of obesity in the multivariate analysis did not change the result, and obesity was not a significant predictor of outcome in multivariate regression analysis. Other limitations of this study include the absence of information about breastfeeding and the features of a 'Western lifestyle' such as physical activity, diet and use of postmenopausal hormones and other medications.
In conclusion, the present study is consistent with findings in other environments that central adiposity is a risk factor for breast cancer in postmenopausal women.
Abbreviations
- BMI:
-
body mass index
- LRT:
-
likelihood ratio test
- SHBG:
-
sex hormone binding globulin
- WHR:
-
waist–hip ratio.
Declarations
Acknowledgements
The authors thank Ms Funmi Oyetunji and Ms Fisayo Adejuyigbe for conducting the interviews. Supported in part through a generous grant from the Falk Medical Research Trust (to OIO). OIO is a Doris Duke Distinguished Clinical Scholar.
Authors’ Affiliations
References
- McPherson K, Steel CM, Dixon JM: ABC of breast diseases. Breast cancer-epidemiology, risk factors, and genetics. BMJ. 2000, 321: 624-628. 10.1136/bmj.321.7261.624.PubMed CentralView ArticlePubMedGoogle Scholar
- Fisher B, Osborne KC, Bloomer WD, Margolese RG: Neoplasms of the breast. In Cancer Medicine Plus [CD-ROM]. Edited by: Holland JF, Frei III E, Bast RC, Morton DL, Kufe DW, Weichselbaum RR. 1998, Baltimore, MD: Williams and WilkinsGoogle Scholar
- Adebamowo CA, Ajayi OO: Breast cancer in Nigeria. West Afr J Med. 2000, 19: 179-191.PubMedGoogle Scholar
- Ziegler RG, Hoover RN, Pike MC, Hildesheim A, Nomura AM, West DW, Wu-Williams AH, Kolonel LN, Horn-Ross PL, Rosen-thal JF: Migration patterns and breast cancer risk in Asian-American women. J Natl Cancer Inst. 1993, 85: 1819-1827.View ArticlePubMedGoogle Scholar
- Rose DP, Royak-Schaler R: Tumor biology and prognosis in black breast cancer patients: a review. Cancer Detect Prev. 2001, 25: 16-31.PubMedGoogle Scholar
- Friedenreich CM: Review of anthropometric factors and breast cancer risk. Eur J Cancer Prev. 2001, 10: 15-32. 10.1097/00008469-200102000-00003.View ArticlePubMedGoogle Scholar
- Lev-Ran A: Human obesity: an evolutionary approach to understanding our bulging waistline. Diabetes Metab Res Rev. 2001, 17: 347-362. 10.1002/dmrr.230.View ArticlePubMedGoogle Scholar
- Swerdlow AJ, De Stavola BL, Floderus B, Holm NV, Kaprio J, Verkasalo PK, Mack T: Risk factors for breast cancer at young ages in twins: an international population-based study. J Natl Cancer Inst. 2002, 94: 1238-1246. 10.1093/jnci/94.16.1238.View ArticlePubMedGoogle Scholar
- Stoll BA: Upper abdominal obesity, insulin resistance and breast cancer risk. Int J Obes Relat Metab Disord. 2002, 26: 747-753. 10.1038/sj.ijo.0801998.View ArticlePubMedGoogle Scholar
- WHO: WHO MONICA Project Manual. Geneva: World Health Organization MONICA Project;. 1990Google Scholar
- Tannenbaum A: Genesis and growth of tumors. II. Effects of caloric restriction per se. Cancer Res. 1942, 2: 460-467.Google Scholar
- Kolterman OG, Insel J, Saekow M, Olefsky JM: Mechanisms of insulin resistance in human obesity. J Clin Invest. 1980, 65: 1272-1284.PubMed CentralView ArticlePubMedGoogle Scholar
- Del Giudice ME, Fantus IG, Ezzat S, McKeown-Eyssen G, Page D, Goodwin PJ: Insulin and related factors in premenopausal breast cancer risk. Breast Cancer Res Treat. 1998, 47: 111-120. 10.1023/A:1005831013718.View ArticlePubMedGoogle Scholar
- Folsom AR, Vitelli LL, Lewis CE, Schreiner PJ, Watson RL, Wagenknecht LE: Is fasting insulin concentration inversely associated with rate of weight gain? Contrasting findings from CARDIA and ARIC study cohorts. Int J Obes Relat Metab Disord. 1998, 22: 48-54. 10.1038/sj.ijo.0800542.View ArticlePubMedGoogle Scholar
- Kaaks R: Nutrition, hormones, and breast cancer: is insulin the missing link?. Cancer Causes Control. 1996, 7: 605-625.View ArticlePubMedGoogle Scholar
- Toniolo PG: Endogenous estrogens and breast cancer risk: the case for prospective cohort studies. Environ Health Perspect. 1997, 105: 587-592.PubMed CentralView ArticlePubMedGoogle Scholar
- Pollack M: Insulin-like growth factor physiology and cancer risk. Eur J Cancer. 2000, 36: 1224-1228. 10.1016/S0959-8049(00)00102-7.View ArticleGoogle Scholar
- Mackenzie I: The production of mammary cancer in rats using oestrogens. Br J Cancer. 1955, 9: 284-299.PubMed CentralView ArticlePubMedGoogle Scholar
- Kelsey JL, Bernstein L: Epidemiology and prevention of breast cancer. Annu Rev Public Health. 1996, 17: 47-67. 10.1146/annurev.pu.17.050196.000403.View ArticlePubMedGoogle Scholar
- Key TJ, Pike MC: The role of oestrogens and progestagens in the epidemiology and prevention of breast cancer. Eur J Cancer Clin Oncol. 1988, 24: 29-43.View ArticlePubMedGoogle Scholar
- Lilienfeld AM: The relationship of cancer of the female breast to artificial menopause and marital status. Cancer. 1956, 9: 927-934.View ArticlePubMedGoogle Scholar
- Bush TL, Helzlsouer KJ: Tamoxifen for the primary prevention of breast cancer: a review and critique of the concept and trial. Epidemiol Rev. 1993, 15: 233-244.PubMedGoogle Scholar
- Huang Z, Willett WC, Colditz GA, Hunter DJ, Manson JE, Rosner B, Speizer FE, Hankinson SE: Waist circumference, waist:hip ratio, and risk of breast cancer in the Nurses' Health Study. Am J Epidemiol. 1999, 150: 1316-1324.View ArticlePubMedGoogle Scholar
- Kaaks R, Van Noord PA, Den Tonkelaar I, Peeters PJ, Riboli E, Grobbee DE: Breast-cancer incidence in relation to height, weight and body-fat distribution in the Dutch 'DOM' cohort. Int J Cancer. 1998, 76: 647-651. 10.1002/(SICI)1097-0215(19980529)76:5<647::AID-IJC6>3.0.CO;2-Q.View ArticlePubMedGoogle Scholar
- Sellers TA, Sprafka JM, Gapstur SM, Rich SS, Potter JD, Ross JA, McGovern PG, Nelson CL, Folsom AR: Does body fat distribution promote familial aggregation of adult onset diabetes mellitus and postmenopausal breast cancer?. Epidemiology. 1994, 5: 102-108.View ArticlePubMedGoogle Scholar
- Sellers TA, Davis J, Cerhan JR, Vierkant RA, Olson JE, Pankratz VS, Potter JD, Folsom AR: Interaction of waist/hip ratio and family history on the risk of hormone receptor-defined breast cancer in a prospective study of postmenopausal women. Am J Epidemiol. 2002, 155: 225-233. 10.1093/aje/155.3.225.View ArticlePubMedGoogle Scholar
- Sonnenschein E, Toniolo P, Terry MB, Bruning PF, Kato I, Koenig KL, Shore RE: Body fat distribution and obesity in pre- and postmenopausal breast cancer. Int J Epidemiol. 1999, 28: 1026-1031. 10.1093/ije/28.6.1026.View ArticlePubMedGoogle Scholar
- Ballard-Barbash R, Schatzkin A, Carter CL, Kannel WB, Kreger BE, D'Agostino RB, Splansky GL, Anderson KM, Helsel WE: Body fat distribution and breast cancer in the Framingham Study. J Natl Cancer Inst. 1990, 82: 286-290.View ArticlePubMedGoogle Scholar
- Schapira DV, Kumar NB, Lyman GH, Cox CE: Abdominal obesity and breast cancer risk. Ann Intern Med. 1990, 112: 182-186.View ArticlePubMedGoogle Scholar
- den Tonkelaar I, Seidell JC, Collette HJ, de Waard F: Obesity and subcutaneous fat patterning in relation to breast cancer in postmenopausal women participating in the Diagnostic Investigation of Mammary Cancer Project. Cancer. 1992, 69: 2663-2667.View ArticlePubMedGoogle Scholar
- Swanson CA, Coates RJ, Schoenberg JB, Malone KE, Gammon MD, Stanford JL, Shorr IJ, Potischman NA, Brinton LA: Body size and breast cancer risk among women under age 45 years. Am J Epidemiol. 1996, 143: 698-706.View ArticlePubMedGoogle Scholar
- Bruning PF, Bonfrer JM, Hart AA, van Noord PA, van der Hoeven H, Collette HJ, Battermann JJ, de Jong-Bakker M, Nooijen WJ, de Waard F: Body measurements, estrogen availability and the risk of human breast cancer – a case–control study. Int J Cancer. 1992, 51: 14-19.View ArticlePubMedGoogle Scholar
- Folsom AR, Kaye SA, Prineas RJ, Potter JD, Gapstur SM, Wallace RB: Increased incidence of carcinoma of the breast assoicated with abdominal adiposity in postmenopausal women. Am J Epidemiol. 1990, 131: 794-803.PubMedGoogle Scholar
- Mannisto S, Pietinen P, Pyy M: Body size indicators and risk of breast cancer according to menopause and estrogen receptor status. Cancer. 1996, 68: 8-13. 10.1002/(SICI)1097-0215(19960927)68:1<8::AID-IJC2>3.0.CO;2-V.Google Scholar
- Petrek JA, Peters M, Cirrincione C, Rhodes D, Bajorunas D: Is body fat topography a risk factor for breast cancer?. Ann Intern Med. 1993, 118: 356-362.View ArticlePubMedGoogle Scholar
- Hall IJ, Newman B, Millikan RC, Moorman PG: Body size and breast cancer risk in black women and white women: the Carolina Breast Cancer Study. Am J Epidemiol. 2000, 151: 754-764.View ArticlePubMedGoogle Scholar
- Shu XO, Jin F, Dai Q, Shi JR, Potter JD, Brinton LA, Hebert JR, Ruan Z, Gao YT, Zheng W: Association of body size and fat distribution with risk of breast cancer among Chinese women. Int J Cancer. 2001, 94: 449-455. 10.1002/ijc.1487.View ArticlePubMedGoogle Scholar
- World Health Organization: Diet, Nutrition and the Prevention of Chronic Diseases. Geneva: World Health Organization;. 2002, 1-55.Google Scholar
- London SJ, Colditz GA, Stampfer MJ, Willett WC, Rosner B, Speizer FE: Prospective study of relative weight, height, and risk of breast cancer. JAMA. 1989, 262: 2853-2858. 10.1001/jama.262.20.2853.View ArticlePubMedGoogle Scholar
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