Is red meat intake a risk factor for breast cancer among premenopausal women?
Breast cancer is the second leading cause of cancer deaths in women today and is the most common cancer among women. Although a number of risk factors such as genetics, family history, parity, age at first birth, and age at menarche and menopause have been established, most are difficult to modify. Diet, however, is a potentially modifiable approach for prevention and a variety of dietary patterns have been examined with respect to their role in breast cancer. One such dietary factor is red meat consumption. Red meat intake has been hypothesized to increase breast cancer risk but while both case–control and ecologic studies have supported a positive association, prospective cohort studies have been inconsistent. One explanation for this inconsistency may be related to menopausal status. We performed a meta-analysis on the association between breast cancer risk and red meat consumption in premenopausal women. A total of ten studies were identified. The summary relative risk was 1.24 (95% CI 1.08–1.42). Case–control studies (N = 7) had a risk of 1.57 (95% CI 1.23–1.99), while cohort studies (N = 3) had a summary relative risk of 1.11 (95% CI 0.94–1.31).
KeywordsBreast cancer Diet
Breast cancer is the second leading cause of cancer deaths in women today and is the most common cancer among women, excluding nonmelanoma skin cancers [1, 2]. The annual incidence rate of breast cancer (number of new breast cancers per 100,000 women) increased by ~4% during the 1980s but leveled off to 100.6 cases per 100,000 women in the 1990s. The death rates from breast cancer also declined significantly between 1992 and 1996, with the largest decreases among younger women. Medical experts attribute the decline in breast cancer deaths to earlier detection and more effective treatments . While breast cancer is less common in women less than 30 years of age, they tend to have more aggressive breast cancers, which may explain why survival rates are lower among younger women . Although a number of risk factors such as genetics, family history, parity, age at first birth, and age at menarche and menopause have been established, most are difficult to modify [1, 5]. Diet, however, is a potentially modifiable approach for prevention and a variety of dietary patterns have been examined with respect to their role in breast cancer. One such dietary factor is red meat consumption.
The link between red meat and breast cancer
A number of biological mechanisms have been putatively linked to the association between red meat and breast cancer. Red meat, depending upon processing methods, may be a source of heterocyclic amines (HCA), N-nitroso compounds, and polyaromatic hydrocarbons, all of which have been shown to be mammary carcinogens in rodents and in human breast cell cultures [6, 7, 8, 9, 10]. Exogenous hormone treatment of beef cattle has also been hypothesized as a causative mechanism. There has also been increasing concern regarding the treatment of cattle with naturally occurring or synthetic sex hormones as a means of enhancing muscle growth. It has been suggested that a population exposed to chronic low levels of estrogen may manifest an increase in estrogen-related illnesses such as breast cancer . Red meat is also a source of heme-iron, a highly bioavailable form of iron, which has been shown to enhance estrogen-induced tumor formation [12, 13].
This biological plausibility has not consistently translated to a clear putative model. While there is good evidence from cell-culture and animal studies supporting the role of dietary components in mammary cell tumorigenesis [14, 15, 16] results from studies in women have been variable. Red meat intake has been hypothesized to increase breast cancer risk, but while case–control and ecologic studies have supported a positive association, prospective cohort studies have been inconsistent. Two meta-analyses on the topic resulted in different conclusions. In a meta-analysis by Boyd et al. , meat intake was considered to be a modest risk factor for breast cancer, with a summary relative risk of 1.54 (CI 1.31–1.82), but this conclusion was reached despite the fact the results were significant in only 1 of 5 cohort studies and 1 of 12 case–control studies reviewed. A second meta-analysis, involving a pooled analysis of 9 cohort studies, did not find any association .
One possible reason for this equivocal finding may be related to menopausal status. The majority of reported studies evaluated postmenopausal breast cancer risk [19, 20, 21, 22], but some investigations suggest a high risk of developing breast cancer in premenopausal women [23, 24]. The aim of this review is to examine the influence of red meat on breast cancer risk among premenopausal women.
A MEDLINE search, citing articles from 1966 onward, supplemented by a review of bibliographies was conducted to identify relevant studies. Breast cancer, diet, and red meat were used as keywords. Criteria used to select studies included: (1) English language, (2) published studies with original data in peer-reviewed journals, and (3) studies that confirmed red meat intake and menopausal status, providing data on premenopausal risk.
Description of studies examining breast cancer risk associated with red meat intake in premenopausal women
No. of cases/controls
Type of controls
Lee et al. 
Age range: 24–57 (cases), 24–58 controls. Hospital admissions for breast cancer between 1986 and 1988
OR: 2.57 (1.36–4.87)10,11 (p = 0.003)
De Stefani et al. 
Hospital admissions in Uruguay, 1994–1997
OR: 3.01(0.77–11.7)11,16,3,6,8,12,13,14,15, p (trend) = 0.09
Ambrosone et al. 
Aged 40–85. Diagnosed with breast cancer
OR: 1.2 (0.8–1.9)11,17,6,10,4,3,14,18, p (trend) = 0.3
Hermann et al. 
<51 years of age hospitalized between 1992 and 1995. Mean age 42.6 years (SD = 5.48 for cases, 5.77 for controls)
OR: 1.99 (1.25–3.18)11,9,3,8,4,13,2,6,10
Witte et al. 
United states, Canada
Women <50 cases identified between 1957 and 1989. Mean age at diagnosis was 41 90% Caucasian
OR: 0.6 (0.3–1.3)11,6,8,18,2,4,13, p (trend) = 0.13
Dai et al. 
Chinese women in Shanghai, age range: 25–64. Diagnosed between 1996 and 1998
OR: 1.8911,6,8,18,2,4,13 (p < 0.01)
Toniolo et al. 
Nested case–control New York University women’s Health study (1985–1991)
Cohort: 14,291, Premenopausal cases: 79
Women in New York attending a breast screening clinic
85% of cases and controls were Caucasians. In the remaining 15%, African Americans, Latinas, and Asians were equally represented
OR: 1.89 (0.79–4.53)6,10,3,8,12,13
Holmes et al. 
Cohort Nurses Health study 1980–1994
Cohort: 53,952, cases: 854
Nurses in the US
Started in 1976. Nurses aged 30–55
RR: 0.94 (0.72–1.22)11,1,8,10,4,6,3,12,19,2,13, p = 0.9
Cho et al. 
Cohort nurses health study II (1991–2003)
Cohort: 90,659, cases: 1021
Premenopausal nurses in the US
Age range at baseline 36 ± 4.6, age at time of diagnosis 43.0 ± 4.5
RR: 1.27 (0.961.67)11,1,8,10,4,6,3,12,19,2,13,p for trend 0.28
Taylor et al. 
UK Women’s cohort
Cohort: 33,725, cases: 70/3334
Women aged 35–69
Women aged 35–69
RR: 1.20 (0.68–1.68)1,4,5,8,11,13,1417,19,20
All case–control studies that met inclusion criteria for this review were similar in that they studied a population of premenopausal women with breast cancer who were identified via hospital records and contacted within weeks of diagnosis. All participants were required to provide information via dietary interview and/or food frequency questionnaire (FFQ) about their dietary habits prior to the breast cancer diagnosis. These responses were compared to those of an identified control population.
The first case–control study examining breast cancer risk associated with red meat consumption in premenopausal women was carried out by Lee et al. in Singapore in 1991 . This study examined a cohort of 125 premenopausal women who were identified and interviewed within 3 weeks of their breast cancer diagnosis. They were interviewed with regard to their food intake 1 year prior to diagnosis. This study found a statistically significant increased risk of breast cancer for premenopausal women (RR 2.57, 95% CI 1.36–4.87, p < 0.003); however, there were no significant changes seen in the postmenopausal group. Controls were selected from patients admitted to surgical wards over the same time period. A similar study was completed in Uruguay in 1997 . Unlike the Lee study, the FFQ used in this study did not specify portion sizes; these were determined later by a nutritionist according to local practices. Again, an association between red meat and breast cancer was observed; the RR for premenopausal women was 3.01 (95% CI 0.77–11.7) and for postmenopausal women was 2.79 (95% CI 1.35–5.75). This was surprising given the homogeneity of the diet in Uruguay , as the finding of an effect of individual dietary factors on cancer risk is more likely in populations with a high variation in intake and less likely when variance is low. This study appears to support an association between breast cancer and red meat, but broad confidence intervals and the small sample size of only 32 cases and 22 controls weaken this conclusion. A limitation of both studies is that controls were chosen from hospitalized patients, as the effect of disease in hospitalized patients could modify dietary recall.
A study by Witte et al.  also examined the risk of breast cancer in premenopausal women and was one of the two case–control studies conducted in North America. This study examined women with bilateral breast cancer, who are known to have an increased risk of carrying a genetic mutation than women with unilateral breast cancer . This study was unique in that, for each case, an unaffected sister served as the matched control. It was felt that the sibling controls had a similar motivation to cases in answering questions, reducing recall bias. Using siblings of patients as controls decreases potential bias related to odds ratio estimates, assuming that the exposure-specific risk of breast cancer is relatively constant over time . All case–control studies examined in this review have inherent in them a recall bias, as respondents were asked to recollect dietary patterns in one or 2 years leading up to the diagnosis. This potential bias was amplified in this study as some subjects were asked about exposure information in the remote past, which for some respondents required recollection of dietary intake patterns more than 15 years previous. To investigate this potential bias, the authors stratified their results by year of diagnosis, a technique that did not change their ORs. Given the rarity of bilateral breast cancer both incident and prevalent cases were included in analysis and this could lead to biased results if some dietary risk factors affected survival among prevalent cases. The authors of this study concluded that there was no association between red meat intake and breast cancer but given the rare illness being investigated it is difficult to generalize this conclusion.
A case–control study by Ambrosone et al.  also examined premenopausal breast cancer patients in the United States. This study identified cases from two different hospitals in New York and took controls from the general population. Patients were contacted within 2 months postdiagnosis and asked about diet 2 years prior to diagnosis. This study had the lowest participation rate, with only 66% of eligible controls (n = 301) and 62% of eligible cases (n = 316) electing to take part. This leads to a risk of selection bias, as most case nonparticipation was due to physicians’ refusals to allow contact with patients (72%). Thus, the most ill patients may have been excluded, limiting generalizability. One interesting difference in this study was the fact that they included fruit and vegetable consumption in the list of confounding variables adjusted for. The rational for doing this was that this dietary factor may be associated with reduced risk and could therefore skew the results of the study . A slightly increased risk was found for premenopausal women (RR 1.2 CI 0.8–1.9) as opposed to postmenopausal women (RR 1.0 CI 0.7–1.4).
A study by Hermannn et al.  looked at breast cancer risk in a population of 278 premenopausal German women. Unlike the other case–control studies, in this study, patients were contacted twice, once to obtain demographic and risk factor information and then later to do a FFQ. FFQs have been validated to assess consumption patterns over extended periods but as the time frame for recall lengthens, so does the risk of error caused by attrition and selection bias. Recall bias may have been a problem as the time span between questioned food intake and FFQ completion was up to 2 years. In some cases, the diagnosis of breast cancer may have caused changes in dietary habits, which would affect the precision and validity of the recalled dietary habits. This study found that red meat consumption was associated with a significantly increased risk of breast cancer (RR 1.99 CI 1.23–3.18). A study by Dai et al.  also looked at red meat intake in a population of Chinese women in Shanghai, an area traditionally known to have a low risk of breast cancer. For premenopausal women, the OR was 1.89 while for postmenopausal women the OR was 2.04. This was the only study to stratify by activity level, attempting to control for this possible confounder in the end results. We are not provided with any description of how activity was accessed, however, so the merit of this is unknown.
Use of food frequency questionnaires
One bias inherent in all the studies described earlier involves the use of a FFQ. Regarding measurement error, clearly the use of a FFQ or any self report measure to assess consumption can lead to misclassification of intake. For many cancers, illness may have caused changes in dietary habits, possibly influencing memory of past eating habits. Thus, recall bias may affect observed associations between dietary intake and cancer risk. The problems with the use of FFQs have been investigated by Giovannucci et al. . He conducted a study in which dietary questionnaires obtained before and after breast cancer diagnosis were completed for cancer cases and controls. They concluded that selection and recall bias, i.e., the tendency of breast cancer cases to report past food consumption differently than controls, would by itself explain the results of case–control studies even in the absence of true association . This conclusion has been challenged by investigators who did not find evidence of recall bias in a study of similar design .
One strategy to minimize error in dietary assessments is to obtain data on both food frequency and estimate of portion size, as this has been demonstrated to enhance the fidelity of diet estimates . To adjust for subjects’ tendency to consistently overreport or underreport, it is also important to adjust for total energy intake  and to reduce potential error due to multiple comparisons, analyses should be conducted on a priori study hypothesis. It is also important to remember that in general, FFQs only provide information on the immediate past and are not able to estimate intake patterns during periods of exposure dating back several years. It may be that more remote events are actually periods of exposure that are critical. A selection bias is also built in to all the case–control studies reviewed in this paper. Among controls, if women who chose to participate are healthier, the results may be biased away from the null. Among patients, death or disease severity affected participation. If a dietary factor is related to this, then reports of associations may be somewhat distorted. Despite inherent problems, it is likely that FFQs do enable investigators to rank order subjects and identify relationships.
One means of reducing bias conferred by the effect of disease status on recall is to obtain dietary information prior to diagnosis. Interviewing patients prior to diagnosis eliminates both the psychological effects of diagnosis and treatment, as well as the influence of health-related information on the perception of lifestyle behaviors. A nested case–control within the cohort of the New York University’s Women’s Health Study attempted to do this . This group showed an increased risk of breast cancer (1.87 CI 1.09–3.21 p for trend .01) in all women studied (n = 180), and this risk did not change appreciably when premenopausal women were considered separately (1.89, 95% CI 0.79–4.53). This study appears to support an association between breast cancer and red meat, but again, broad confidence intervals weaken this conclusion. This study was also designed and analyzed as a nested case–control rather than a full cohort and this approach may have caused some further loss in statistical efficiency, although this loss should have been small (<20%) since there was an average of 4.6 controls per case, with true relative risks probably in the range between 1 and 2.
A cohort design with repeated measures would address weaknesses related to recall bias and this is an obvious strength of the three cohort studies looking at premenopausal breast cancer and red meat intake identified by this review. The first of these studies, the Nurses Health Study (NHS) I, looked at breast cancer risk in a cohort of 53,952 nurses in the United States from 1980 to 1994 . A FFQ was administered on five separate associations between 1980 and 1995 with respondents followed until 1998. This study found no association between breast cancer risk and red meat for either premenopausal (RR = 0.94, 95% CI 0.72–1.22) or postmenopausal (RR 0.99, 95% CI 0.86–1.13) women. The results of this study were not supported by the most recent study to look at the association between premenopausal breast cancer and red meat . This study used the NHS II cohort of 116,671 nurses, administered FFQs at two time points and followed participants from 1991 to 1999. The investigators here documented an association between meat consumption and breast cancer with a RR of 1.27(0.72–1.22) . A recent study examining the link between red meat and breast cancer involved the UK Women’s Cohort, a cohort of over 35,000 women . This study found that a high consumption of red meat was associated with premenopausal breast cancer. (RR 1.20, 95% CI 0.86–1.68) It is worth noting that the cohort in the NHS I was older than that followed in NHS II (30–55 vs. 25–43) and therefore closer to menopause. This may explain the difference in the impact of red meat in the two populations.
All these studies have a number of strengths. They were prospective, included a large number of cases, had little loss to follow up, and were not prone to the biases of case–control studies. They also assessed dietary intake at multiple points over an extended follow-up period.
Estrogen receptors are nuclear receptors that bind estrogen, resulting in DNA and protein synthesis, cell division, and breast cancer proliferation [44, 45, 46]. Progesterone receptors bind progesterone in a similar manner . Breast tumors that express ERs and PRs behave differently, both clinically and biologically, than tumors that do not express to hormonal receptors and have better overall outcomes. It has been hypothesized that risk factors most closely associated with ER+/PR+ breast tumors may involve mechanisms related to estrogen and progesterone exposure, whereas the etiology of ER−/PR− breast cancer may be independent of hormonal exposure. Epidemiologic studies [48, 49] have found that several hormone-related lifestyle such as nulliparity, earlier age at menarche, higher body mass index, and use of oral contraceptive pills or hormone therapy are more strongly related to elevated risk of hormone receptor positive breast cancers but not hormone receptor negative cancers.
The incidence rates for hormone receptor–negative tumors have remained relatively constant in the United States while the incidence of hormone receptor positive tumors has been increasing, with an increase from 65.2 (per 100,000 person-years) in 1992 to 75.1 (per 100,000 person-years) in 1998 among women in the 40–49 year age group [50, 51]. This increasing trend of hormone receptor-positive breast cancers suggests a possible role of environmental or lifestyle factors in the development of this type of cancer. Given that a number of putative pathways put forward linking red meat consumption and breast cancer involve hormonal mechanisms, the effect of red meat on the development of hormone receptor–positive cancer may explain the possible association between this dietary factor and premenopausal breast cancer.
A mandate of the Canadian Cancer Statistics 2007 document is for research to identify modifiable risk factors for breast cancer. The American cancer society publishes nutrition guidelines to advise health care professionals and the general public about dietary practices that reduce cancer risk and these guidelines are based on existing scientific evidence. According to these guidelines, the evidence linking red meat consumption to breast cancer is rated at level B: no clear harm or benefit. As is shown by this review, emerging evidence indicates that this dietary variable may carry a different risk profile in premenopausal woman as opposed to their postmenopausal counterparts and this risk needs to be reflected in cancer guidelines. It is also important that further research looking at red meat and other dietary variables can be carried out in different populations, to identify groups that are at increased risk. Beginning to address this, it would be important to utilize a quantitative measurement of HCAs or estrogen levels, as these have been cited as possible causative mechanisms linking red meat to breast cancer. Most studies examining HCA exposure have used recent data on HCA concentrations in various meats prepared in the United States in the 1990s . No biomarker has currently been established to serve as an independent measure of HCA intake, but recent studies have indicated that the concentration of a fried food mutagen 2-amino-1-methyl-6-phenylimidazo [4,5-b] pyridine (PhIP) levels in human hair can be used as a biological indicator of dietary HCAs [53, 54]. The use of radioimmunoassay to measure reproductive sex steroid hormones as a marker of endogenous estrogen levels would also provide information. These measurements used concurrently with FFQs would help quantify exposure and aid in establishing clearer biological causality.
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