Abstract
Despite mounting evidence that dietary polyphenols might have a protective role against the risk of breast cancer (BC), few studies have assessed the relationship between intake of polyphenol classes and subclasses with BC. Thus, we examined the relationship between dietary polyphenol classes and individual polyphenol subclasses and the risk of BC. Overall, 134 newly diagnosed BC patients and 267 healthy hospitalized controls were studied. Dietary intake was assessed using a validated 168-item food frequency questionnaire (FFQ). To estimate dietary intake of polyphenols, polyphenol content (flavonoids, lignans, stilbenes and phenolic acids) of 80 food items were derived from an updated version of the phenol explorer database containing information on the effects of food processing on polyphenol content. The dietary polyphenol intake was calculated by matching the subjects' food consumption data with our polyphenol content database. Multivariate logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Controls had higher intake of total polyphenol (marginally significant; p = 0.07), hydroxycinnamic acid (marginally significant; p = 0.05) and lignan (p = 0.01). After adjusting for potential confounders, high consumption of lignans (highest vs. lowest tertile: OR, 0.51; 95% CI, 0.26–0.97; p for trend = 0.04) associated with decreased risk of BC. There was no significant relationship between intake of other polyphenols and risk of BC. Our findings suggest that high lignan intake is associated with a reduced risk of BC.
Keywords: Breast cancer, Polyphenols, Flavonoids, Lignans
INTRODUCTION
Cancer, as the most deadly disease, has become a major threat to human life around the world [1]. Cancer is a hereditary disorder that develops through multistep carcinogenesis with the involvement of different physiological systems in the human body, including cell signaling and apoptosis, therefore making it highly difficult to treat [2]. The evidence has shown that the different types of cancers are caused by a change in the structure and function of deoxyribonucleic acid (DNA), vascular endothelial growth factor (VEGF), topoisomerase I & II, mitotic spindle microtubules, histone deacetylases, receptor tyrosine kinases, topoisomerases, CYP26A1 enzyme, etc. [3,4]. Breast cancer (BC) is the most common cancer in women and the second most diagnosed cancer after lung cancer in many societies [5,6]. The prevalence of BC in developed countries is higher than in developing countries, which can be related to many factors such as aging, lifestyle changes, migration to urban communities, etc. [7]. The World Health Organization reports that annually 1.7 million cases are diagnosed and 515,000 die from BC worldwide [6]. Although Iran is a country with a low incidence of BC in the world (25 per 100,000) [8], the incidence of this malignancy has increased over the past decade in this country and affects Iranian women about 10 years earlier than Western countries [9]. Epidemiological studies have suggested that dietary factors play a crucial role in BC [10,11], and diets high in fruits and vegetables are associated with a decreased risk of BC [12,13]. Polyphenols are bioactive and antioxidant compounds existing in plant-based food such as fruits, vegetables, whole grains, and beverages such as tea and coffee [14]. Based on their chemical structure, dietary polyphenols can be categorized into 4 major classes, namely, flavonoids, stilbenes, phenolic acids, and lignans [14]. In recent decades, experimental studies have shown potential anti-carcinogenic action of polyphenols including anti-proliferative, inhibition of angiogenesis, and stimulation of apoptosis against BC [15,16]. On the other hand, some studies have shown that polyphenol-rich foods may play a protective role against BC [17]. Nevertheless, results from previous studies are rather inconsistent and controversial. In addition, the majority of studies have investigated the association of some classes of polyphenols, such as flavonoids, and the risk of BC, while other classes of polyphenols including phenolic acids have been less studied and most of them conducted in Western and developed societies [18,19,20]. There is a lack of published data on the topic of the relationship between dietary polyphenol classes and individual polyphenol subclasses in the Middle-East region, especially Iran as a developing country. Therefore, to further explore the role of polyphenols in BC, we examined the association of dietary polyphenol classes and individual polyphenol subclasses and the risk of BC among Iranian women.
MATERIALS AND METHODS
Participants
This hospital-based case-control study was conducted at the 2 referral hospitals, Tehran (capital of Iran), between September 2015 and February 2016. We recruited 136 women aged ≥ 30 years and newly diagnosed (< 6 months) with histologically confirmed BC. The control group consisted of 272 women of similar age who were admitted to the same hospital for a wide spectrum of non-neoplastic diseases that were unrelated to smoking, alcohol abuse, and long-term diet modification. Controls were matched to cases on age (within 5 years). Data on cases and controls were collected at the same time and interviewed in the same setting using standardized procedures. Less than 8% of subjects approached for the interview refused to participate. Seven participants were excluded from the analysis because their reported energy intakes were outside of the ± 3 standard deviation (SD) from the mean energy intakes of the population (n = 5 controls, 2 cases). Finally, 134 cases and 267 controls remained in the final analysis. All protocols and procedures of the current study were approved by the Shahid Beheshti Ethics Committee (IR.SBMU.RETECH.REC.1398.640). Written informed consent was obtained from all patients.
Assessment of dietary intake
Participants' dietary intake during the year prior to diagnosis for cases or interview for controls was assessed in a personal interview using a valid and reliable semi-quantitative 168 food item food frequency questionnaire (FFQ) [21]. Participants were asked to specify their consumption frequency for each food item on a daily, weekly, monthly, or yearly basis. Intakes were then converted to daily frequencies and a manual for household measures was used to convert intake frequencies to daily grams of food intake [22]. The energy and nutrient content of foods was calculated by the U.S. Department of Agriculture (USDA) food composition table. For some traditional Iranian food items that are not included in the USDA database (e.g., traditional bread), the Iranian food composition table was used. Due to Iranian cultural beliefs, alcohol consumption was not asked and, therefore, was unavailable for the analysis.
Polyphenol assessment
To estimate dietary intake of polyphenols, polyphenol content (flavonoids, lignans, stilbenes and phenolic acids) of 80 food items (including fruits, vegetables, bread and grains, legume and soybean, nuts and seeds, oils, tea and coffee) were derived from an updated version of the phenol explorer database (www.phenol-explorer.eu) containing information on the effects of food processing on polyphenol content [23]. This database contains more than 35,000 content values, for 500 different polyphenols, in over 400 foods. The intake of polyphenols was calculated by multiplying the polyphenol content by the daily consumption of each food. The polyphenol subclasses consisted of five group for flavonoids (anthocyanin, flavones, flavonols, flavanols, flavanones) and two group for phenolic acids (hydroxybenzoic acids and hydroxycinnamic acid).
Assessment of other data
For all participants, the required information about socio-demographic, lifestyle, and clinical information including age (years), menopausal status (pre-menopause, post-menopause), education (illiterate, less than a high school diploma, high school diploma, and more), cancer family history (yes, no), breast cancer family history (yes, no), bra-wearing (day [yes, no], night [yes, no]), marital status (single, married, divorced, widowed), smoking (yes, no), supplement intake (including calcium, iron, zinc, selenium, B complex, vitamin C, folic acid, vitamin A, β carotene, vitamin E, vitamin D, multivitamins-minerals, omega-3 fatty acids, and probiotics; yes, no; If yes, the complementary information about dose and frequency), and anti-inflammatory drug use (yes, no) were collected by general questionnaires. Weight was measured to the nearest 0.5 kg using a digital scale (Seca, Hamburg, Germany) with the participant wearing lightweight clothing and no shoes. Height was measured to the nearest 0.5 cm using by tape meter fixed to a wall. Body mass index (BMI) was then calculated by dividing weight (kg) by the square of height (meter). Furthermore, waist circumference (at the level midway between the lowest rib margin and the iliac) and hip circumference (at the widest point over the buttocks) were measured both to the nearest 0.5 cm using a non-stretchable tape-measure. Subsequently, the waist-hip ratio was calculated. Also, physical activity assessed with a valid and reliable questionnaire [24].
Statistical analysis
The Kolmogorov-Smirnoff test was used to evaluate whether or not the distribution of the variables was normal. The mean values of two groups were compared using the Student's t-test and the means of more than two groups were assessed using analysis of variance for normal distribution variables. Also, non-parametric statistics, including the Mann-Whitney U test or Kruskal-Wallis test were used for variables without normal distribution. Moreover, the χ2 test was used for comparing categorical variables. Total polyphenols and polyphenols subclasses were categorized into tertiles based on the distribution of the dietary intake of controls. Binary logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) adjusted for multiple covariates including age, menopausal status, cancer family history, day bra wearing, physical activity (MET-h/day), vitamin D supplement, total energy intake (kcal/day), BMI and total fiber intake (g/day) in different models. Statistical tests were performed using SPSS software (v.21.0; IBM Corp., Armonk, NY, USA). The p values < 0.05 were considered statistically significant.
RESULTS
The distribution of general characteristics of 134 cases and 267 controls are shown in Table 1. Compared with controls, cases were older, post-menopause, and were more likely to have cancer family history and bra use across days. Controls were more likely to take vitamin D supplements than cases. Consumption of polyphenols between cases and controls are presented in Table 2. According to this table, the median intake of total polyphenol (marginally significant; p = 0.07), hydroxycinnamic acid (marginally significant; p = 0.05), and lignan (p = 0.01) was higher among controls. The ORs and 95% CIs for BC risk and intakes of total polyphenol and subclasses are presented in Table 3. After adjusting for potential confounders, only consumption of lignans (highest vs. lowest tertile: OR, 0.51; 95% CI, 0.26–0.97; p for trend = 0.04) was associated with decreased risk of BC. The ORs and 95% CIs between subgroups of flavonoids and phenolic acids and the risk of BC are presented in Table 4. As shown, there was no significant relationship between intakes of flavonoids and phenolic acids subgroup and risk of BC.
Table 1. General characteristics of participants.
Variables | Cases (n = 134) | Controls (n = 267) | p value*,‡ | |
---|---|---|---|---|
BMI (kg/m2) | 29.5 (7.3) | 28.5 (7.7) | NS | |
Waist circumference (cm)† | 99.5 ± 14.5 | 96.4 ± 13.3 | NS | |
Age (yr) | 49.5 ± 10.7 | 47.13 ± 10.1 | 0.03‡ | |
Physical activity (MET-h/day) | 32.1 (6.2) | 31.47 (6.1) | NS | |
Daily energy intake(kcal/day) | 2,467.8 (890.2) | 2,549.6 (1,068.7) | NS | |
Breast cancer family history (yes) | 11 (8.2%) | 12 (4.5%) | NS | |
Night bra wearing (yes) | 106 (79.1%) | 190 (71.4%) | NS | |
Day bra-wearing (yes) | 122 (91.0%) | 217 (81.6%) | 0.01 | |
Inflammatory disease history (yes) | 15 (10.4%) | 35 (13.2%) | NS | |
Menopausal status | 0.04 | |||
Pre-menopause | 62 (46.3%) | 153 (57.3%) | ||
Post-menopause | 72 (53.7%) | 114 (42.7%) | ||
Marital status | NS | |||
Single | 9 (6.8%) | 16 (6.0%) | ||
Married | 105 (78.9%) | 206 (77.4%) | ||
Divorced | 5 (3.8%) | 13 (4.9%) | ||
Widowed | 14 (10.5%) | 31 (11.7%) | ||
Educational level | NS | |||
Illiterate | 13 (10.0%) | 24 (9.0%) | ||
Less than a high school diploma | 55 (42.3%) | 134 (50.4%) | ||
High school diploma and more | 62 (47.7%) | 108 (40.6%) | ||
Smoking (present smoker) | 4 (3.0%) | 9 (3.4%) | NS | |
Vitamin D supplement (yes) | 20 (14.9%) | 65 (24.4%) | 0.03 | |
Total fiber intake (g/day) | 33.5 (18.7) | 35.3 (21.9) | 0.21 |
Continuous values are shown as mean ± standard deviation or median (interquartile range). Categorical values are shown as number (%).
NS, non-significant; MET, metabolic equivalent; BMI, body mass index.
*Independent t-test or Mann-Whitney was used for continuous variables; χ2 test was used for categorical variables. †Normal distribution. ‡Bold p-values are statistically significant.
Table 2. Intake of total polyphenol and subclasses between cases and controls.
Polyphenols | Cases (n = 134) | Controls (n = 267) | p value*,† |
---|---|---|---|
Total polyphenol (mg/day) | 2,079.31 (976.19) | 2,193.83 (1,069.87) | 0.07 |
Total flavonoids (mg/day) | 725.22 (561.25) | 733.23 (471.13) | 0.15 |
Flavonol (mg/day) | 591.57 (544.62) | 595.13 (399.05) | 0.13 |
Flavan-3-ol (mg/day) | 80.10 (50.10) | 83.29 (49.72) | 0.17 |
Flavone (mg/day) | 3.29 (3.44) | 3.72 (3.35) | 0.28 |
Flavanones (mg/day) | 63.34 (28.84) | 63.09 (41.93) | 0.22 |
Total phenolic acid (mg/day) | 232.22 (155.48) | 236.72 (141.56) | 0.21 |
Hydroxybenzoic acid (mg/day) | 134.06 (101.94) | 133.36 (90.68) | 0.41 |
Hydroxycinnamic acid (mg/day) | 86.14 (55.44) | 91.70 (61.48) | 0.05 |
Lignan (mg/day) | 8.93 (3.98) | 9.33 (6.31) | 0.01† |
Stilbenes (mg/day) | 0.16 (0.10) | 0.11 (0.12) | 0.28 |
Values are shown as median (interquartile range).
NS, non-significant.
*Mann-Whitney test was used. †Bold p-values are statistically significant.
Table 3. Association between dietary intake of polyphenols and the risk of breast cancer.
Polyphenols | T1 | T2 | T3 | p for trend† | |
---|---|---|---|---|---|
Total polyphenols (mg/day) | < 1,814.91 | 1,814.91–2,474.72 | > 2,474.72 | ||
Cases/controls | 48/88 | 44/89 | 42/90 | ||
Age-adjusted model | Ref. (1.00) | 0.86 (0.51–1.44) | 0.79 (0.47–1.32) | 0.37 | |
Multi-adjusted model* | Ref. (1.00) | 0.86 (0.51–1.47) | 0.68 (0.39–1.19) | 0.18 | |
Flavonoids (mg/day) | < 579.18 | 579.18–954.94 | > 954.94 | ||
Cases/controls | 57/101 | 35/87 | 42/79 | ||
Age-adjusted model | Ref. (1.00) | 0.73 (0.43–1.22) | 0.92 (0.55–1.52) | 0.68 | |
Multi-adjusted model | Ref. (1.00) | 0.82 (0.47–1.41) | 1.11 (0.64–1.92) | 0.61 | |
Phenolic acids (mg/day) | < 187.76 | 187.76–284.83 | > 284.83 | ||
Cases/controls | 53/101 | 44/85 | 37/81 | ||
Age-adjusted model | Ref. (1.00) | 0.97 (0.59–1.59) | 0.85 (0.50–1.43) | 0.56 | |
Multi-adjusted model | Ref. (1.00) | 1.32 (0.76–2.28) | 1.11 (0.61–2.02) | 0.72 | |
Lignans (mg/day) | < 7.61 | 7.61–10.76 | > 10.76 | ||
Cases/controls | 56/88 | 50/89 | 28/90 | ||
Age-adjusted model | Ref. (1.00) | 0.82 (0.50–1.34) | 0.48 (0.28–0.84) | 0.01 | |
Multi-adjusted model | Ref. (1.00) | 0.81 (0.48–1.36) | 0.51 (0.26–0.97) | 0.04† | |
Stilbenes (mg/day) | < 0.12 | 0.12–0.23 | > 0.23 | ||
Cases/controls | 36/98 | 54/80 | 45/89 | ||
Age-adjusted model | Ref. (1.00) | 1.16 (0.66–2.04) | 0.43 (0.27–0.83) | 0.01 | |
Multi-adjusted model | Ref. (1.00) | 0.83 (0.37–1.93) | 0.62 (0.26–1.53) | 0.31 |
Logistic regression models were used to obtain the odds ratio of breast cancer risk, with 95% confidence intervals in tertile of dietary total and subclasses of polyphenols intake.
*Additionally adjusted menopausal status, cancer family history, day bra-wearing, physical activity (MET-h/day), vitamin D supplement, total energy intake (kcal/day), body mass index and total fiber intake (g/day). †Bold p-values are statistically significant.
Table 4. The OR (95%CI) of dietary intake of flavonoid and phenolic acid subclasses for breast cancer.
Flavonoid and phenolic acid subclasses | T1 | T2 | T3 | p for trend | |
---|---|---|---|---|---|
Flavones (mg/day) | < 2.78 | 2.78–4.84 | > 4.84 | ||
Cases/controls | 50/88 | 42/88 | 42/91 | ||
Age-adjusted model | Ref. (1.00) | 0.87 (0.52–1.46) | 0.85 (0.51–1.42) | 0.54 | |
Multi-adjusted model* | Ref. (1.00) | 0.91 (0.53–1.57) | 0.84 (0.48–1.48) | 0.56 | |
Flavonols (mg/day) | < 414.25 | 414.25–763.43 | > 763.43 | ||
Cases/controls | 51/88 | 39/91 | 44/88 | ||
Age-adjusted model | Ref. (1.00) | 0.71 (0.42–1.20) | 0.82 (0.49–1.36) | 0.43 | |
Multi-adjusted model | Ref. (1.00) | 0.65 (0.38–1.13) | 0.88 (0.51–1.52) | 0.67 | |
Flavanols (mg/day) | < 65.13 | 65.13–98.67 | > 98.67 | ||
Cases/controls | 54/88 | 34/89 | 46/90 | ||
Age-adjusted model | Ref. (1.00) | 0.60 (0.35–1.02) | 0.77 (0.46–1.27) | 0.29 | |
Multi-adjusted model | Ref. (1.00) | 0.70 (0.40–1.21) | 1.01 (0.56–1.76) | 0.99 | |
Flavanones (mg/day) | < 53.45 | 53.45–73.29 | > 73.29 | ||
Cases/controls | 43/87 | 60/90 | 31/90 | ||
Age-adjusted model | Ref. (1.00) | 1.25 (0.76–2.05) | 0.67 (0.38–1.17) | 0.19 | |
Multi-adjusted model | Ref. (1.00) | 1.33 (0.78–2.27) | 0.90 (0.49–1.63) | 0.73 | |
Anthocyanins (mg/day) | < 23.61 | 23.61–42.91 | > 42.91 | ||
Cases/controls | 37/96 | 50/85 | 47/86 | ||
Age-adjusted model | Ref. (1.00) | 0.84 (0.47–1.49) | 0.47 (0.26–0.85) | 0.01 | |
Multi-adjusted model | Ref. (1.00) | 0.45 (0.23–1.21) | 0.54 (0.21–1.32) | 0.14 | |
Hydroxybenzoic acid (mg/day) | < 98.05 | 98.05–172.51 | > 172.51 | ||
Cases/controls | 56/90 | 35/89 | 43/88 | ||
Age-adjusted model | Ref. (1.00) | 0.61 (0.36–1.03) | 0.77 (0.46–1.27) | 0.28 | |
Multi-adjusted model | Ref. (1.00) | 0.76 (0.44–1.31) | 0.91 (0.52–1.57) | 0.73 | |
Hydroxycinnamic acid (mg/day) | < 72.61 | 72.61–110.58 | > 110.58 | ||
Cases/controls | 48/90 | 52/88 | 34/89 | ||
Age-adjusted model | Ref. (1.00) | 1.09 (0.66–1.79) | 0.71 (0.42–1.22) | 0.24 | |
Multi-adjusted model | Ref. (1.00) | 1.33 (0.77–2.31) | 1.02 (0.52–1.97) | 0.95 |
Logistic regression models were used to obtain the OR of breast cancer risk, with 95% CIs in tertile of flavonoids and phenolic acids subclasses.
OR, odds ratio; CI, confidence interval.
*Additionally adjusted for menopausal status, cancer family history, day bra wearing, physical activity (MET-h/day), vitamin D supplement, total energy intake (kcal/day), body mass index and total fiber intake (g/d).
DISCUSSION
In the present study, higher lignan intake was associated with a reduced risk of BC. There was no significant association between flavonoids and phenolic acids subclasses including flavones, flavanols, flavonols, flavanones, anthocyanins, hydroxybenzoic acids and hydroxycinnamic acids with the risk of BC. In consistent with our results, an inverse association of lignans with BC risk has previously been reported [25,26,27]. However, no inverse relationship has been reported in some other studies [28,29,30]. The results of a meta-analysis showed that there was no association between plant lignan intake and overall risk of BC. When analysis was stratified by menopausal status, a significant reduction was observed in post-menopausal women [31]. The protective effect of lignan against BC in post-menopausal women suggests that dietary lignan has a protective role only at low estradiol levels [31]. Previous studies, mainly from the Asian population, have shown that high consumption of flavonoids, especially isoflavones, is inversely related to the risk of BC [32,33]. Our findings failed to confirm the result of these studies. It may be due to low consumption of isoflavonoids rich foods in Iran. Except for soya, other sources of isoflavones are rarely consumed in Iran. It should be noted that the mean intake of isoflavones in our study is < 1 mg/day (data not shown). However, some studies have not found an association between isoflavones and breast cancer risk [17,34]. It is possible that the association between isoflavones and BC risk is not established through dietary studies, but only through urine excretion measurements [35]. Most previous studies have focused on some specific classes of polyphenols and flavonoids, while the evaluation of other polyphenol subclasses has been less studied [36,37,38]. Previous studies have reported different levels of polyphenol and polyphenol subclasses consumption [39,40]. The heterogeneity of individual food composition and different dietary patterns in populations makes it relatively difficult to compare polyphenol consumption in different individuals [41]. The findings of European Prospective Investigation into Cancer and Nutrition (EPIC) Study indicate no associations between flavonoid and lignan intake and BC risk. Results after analysis based on menopausal status also remained insignificant [42]. The results of a meta-analysis showed an inverse association between flavonols and flavones and the risk of BC. However, no significant association was found for other flavonoid subclasses or total flavonoids [43]. These discrepancies in the reported results may be explained by various reasons. One of the main reasons could be the variety of polyphenols measurement methods and possible measurement errors [14]. Differences in polyphenol content during processing such as canning, storing, freezing, and cooking can be another reason [44]. On the other hand, the amount, type and source of polyphenols might be different in diverse countries. For example, dietary intake of polyphenols may be higher in Asia and countries that adherence the Mediterranean diet [45,46]. Most intrinsic polyphenols are thought to damage BC metastasis through inhibiting of matrix metalloproteinase expression, intervention with the VEGF signaling pathway, modulation of epithelial-mesenchymal transition regulator, inhibition of nuclear factor kappa B, and mammalian target of rapamycin expression, and other associated mechanisms. Consumption of natural polyphenols has been shown to affect endogenous metabolites and complex biological metabolic pathways in the body [16]. On the other hand, women tend to start menopausal hormone therapy (MHT) during menopause, which can continue for several years [47]. MHT involves the use of estrogen alone or in combination with progesterone, which is more commonly used in western countries [48]. Estrogen is recognized as a factor that induces the progression of BC [49]. Studies have also shown that the risk of BC for estrogen and progesterone together was higher than for estrogen alone, especially if progesterone use was daily rather than intermittent [47]. Epidemiological studies have demonstrated that there is a link between soy consumption as an isoflavones-rich food and the menopausal symptoms such as hot flashes [50]. Indeed, isoflavones can mimic the effects of estrogen by binding to estrogen receptors and relieve menopausal symptoms. [51]. Despite the beneficial effects of isoflavones, there is still no consensus on their use instead of MHT [52]. A meta-analysis of 51 randomized controlled trials showed that both MHT and soy isoflavones interventions are effective for the reduction of menopausal hot flushes. However, using indirect comparison, a significant difference between the effects of MHT and soy isoflavones on hot flashes was observed [53]. Due to Iranian cultural beliefs, alcohol consumption was not asked and, therefore, was unavailable for the analysis. But a study found BC risk was reduced in women who did not drink alcohol but consumed polyphenols. Whereas, BC risk was increased in heavy alcohol drinkers [54]. Polyphenols have been shown to inhibit the proliferation and transformation of cancer cells by scavenging free radicals, regulating nitric oxide production, and affecting signal transduction pathways (such as mitogen-activated protein kinase) [55].
Our study has some advantages. We estimated dietary intakes using a FFQ developed for assessing Iranian dietary intake. Validity and reliability of the FFQ was qualified in a previous study [21]. Also, use of new patient cases, using hospital controls and administering FFQs by trained interviewers were other strengths of our study. In contrast, several limitations are also intrinsic in the present study. The diversity of polyphenols compounds is complex and the use of FFQs may lead to measurement errors. Recall bias is a limitation in any dietary research using a questionnaire to quantify dietary intake, because it depends on the individual's memory and there is a possibility of over or under reporting by individuals. Additionally, the selection bias is difficult to avoid in case-control studies. However, these problems were ameliorated by using new patient cases through hospital controls and implementation FFQs by trained interviewers in a hospital setting. Moreover, the present study is a case-control study with a small sample size that unable to investigate the long-term effects of risk factors on the occurrence of BC. A cohort or longitudinal study will be required to evaluate the association between the risk factors such as diet and the risk of chronic diseases.
CONCLUSION
The present study showed that the high intake of lignans was related to the decreased risk of BC. As shown in previous studies, our findings confirm that a polyphenol-rich diet may reduce the risk of breast cancer but to understand the interactions between diet and health, an assessment of the diet with all its complexity of foods would be required. This complexity illustrates the exposure to food bio-actives and their impacts on human health.
ACKNOWLEDGEMENTS
This study is related to project NO. 19714 from Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran. We also appreciate the “Student Research Committee” and “Research & Technology Chancellor” in Shahid Beheshti University of Medical Sciences for their support of this study.
Footnotes
Conflict of Interest: The authors declare that they have no competing interests.
References
- 1.Saleem K, Wani WA, Haque A, Lone MN, Hsieh MF, Jairajpuri MA, Ali I. Synthesis, DNA binding, hemolysis assays and anticancer studies of copper(II), nickel(II) and iron(III) complexes of a pyrazoline-based ligand. Future Med Chem. 2013;5:135–146. doi: 10.4155/fmc.12.201. [DOI] [PubMed] [Google Scholar]
- 2.Reichert JM, Wenger JB. Development trends for new cancer therapeutics and vaccines. Drug Discov Today. 2008;13:30–37. doi: 10.1016/j.drudis.2007.09.003. [DOI] [PubMed] [Google Scholar]
- 3.Ali I, Lone MN, Aboul-Enein HY. Imidazoles as potential anticancer agents. MedChemComm. 2017;8:1742–1773. doi: 10.1039/c7md00067g. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Ketron AC, Denny WA, Graves DE, Osheroff N. Amsacrine as a topoisomerase II poison: importance of drug-DNA interactions. Biochemistry. 2012;51:1730–1739. doi: 10.1021/bi201159b. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.DeSantis CE, Bray F, Ferlay J, Lortet-Tieulent J, Anderson BO, Jemal A. International variation in female breast cancer incidence and mortality rates. Cancer Epidemiol Biomarkers Prev. 2015;24:1495–1506. doi: 10.1158/1055-9965.EPI-15-0535. [DOI] [PubMed] [Google Scholar]
- 6.Khalili R, Bagheri-Nesami M, Janbabai G, Nikkhah A. Lifestyle in Iranian patients with breast cancer. J Clin Diagn Res. 2015;9:XC06–XC09. doi: 10.7860/JCDR/2015/13954.6233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Lu S, Qian Y, Huang X, Yu H, Yang J, Han R, Su J, Du W, Zhou J, Dong M, Yu X, Duijnhoven FJ, Kampman E, Wu M. The association of dietary pattern and breast cancer in Jiangsu, China: a population-based case-control study. PLoS One. 2017;12:e0184453. doi: 10.1371/journal.pone.0184453. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Asadzadeh Vostakolaei F, Broeders MJ, Mousavi SM, Kiemeney LA, Verbeek AL. The effect of demographic and lifestyle changes on the burden of breast cancer in Iranian women: a projection to 2030. Breast. 2013;22:277–281. doi: 10.1016/j.breast.2012.07.002. [DOI] [PubMed] [Google Scholar]
- 9.Hosseinzadeh M, Eivazi Ziaei J, Mahdavi N, Aghajari P, Vahidi M, Fateh A, Asghari E. Risk factors for breast cancer in Iranian women: a hospital-based case-control study in Tabriz, Iran. J Breast Cancer. 2014;17:236–243. doi: 10.4048/jbc.2014.17.3.236. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Shapira N. The potential contribution of dietary factors to breast cancer prevention. Eur J Cancer Prev. 2017;26:385–395. doi: 10.1097/CEJ.0000000000000406. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Kim JH, Lee J, Jung SY, Kim J. Dietary factors and female breast cancer risk: a prospective cohort study. Nutrients. 2017;9:1331. doi: 10.3390/nu9121331. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Kooshki A, Moghaddam MY, Akbarzadeh R. Study of fruit and vegetable intake in breast cancer patients in the city of Sabzevar. Electron Physician. 2016;8:3011–3014. doi: 10.19082/3011. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Bao PP, Shu XO, Zheng Y, Cai H, Ruan ZX, Gu K, Su Y, Gao YT, Zheng W, Lu W. Fruit, vegetable, and animal food intake and breast cancer risk by hormone receptor status. Nutr Cancer. 2012;64:806–819. doi: 10.1080/01635581.2012.707277. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Zamora-Ros R, Touillaud M, Rothwell JA, Romieu I, Scalbert A. Measuring exposure to the polyphenol metabolome in observational epidemiologic studies: current tools and applications and their limits. Am J Clin Nutr. 2014;100:11–26. doi: 10.3945/ajcn.113.077743. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Mocanu MM, Nagy P, Szöllősi J. Chemoprevention of breast cancer by dietary polyphenols. Molecules. 2015;20:22578–22620. doi: 10.3390/molecules201219864. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ci Y, Qiao J, Han M. Molecular mechanisms and metabolomics of natural polyphenols interfering with breast cancer metastasis. Molecules. 2016;21:1634. doi: 10.3390/molecules21121634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Peterson J, Lagiou P, Samoli E, Lagiou A, Katsouyanni K, La Vecchia C, Dwyer J, Trichopoulos D. Flavonoid intake and breast cancer risk: a case--control study in Greece. Br J Cancer. 2003;89:1255–1259. doi: 10.1038/sj.bjc.6601271. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Takemura H, Sakakibara H, Yamazaki S, Shimoi K. Breast cancer and flavonoids - a role in prevention. Curr Pharm Des. 2013;19:6125–6132. doi: 10.2174/1381612811319340006. [DOI] [PubMed] [Google Scholar]
- 19.Wang Y, Gapstur SM, Gaudet MM, Peterson JJ, Dwyer JT, McCullough ML. Evidence for an association of dietary flavonoid intake with breast cancer risk by estrogen receptor status is limited. J Nutr. 2014;144:1603–1611. doi: 10.3945/jn.114.196964. [DOI] [PubMed] [Google Scholar]
- 20.Pantavos A, Ruiter R, Feskens EF, de Keyser CE, Hofman A, Stricker BH, Franco OH, Kiefte-de Jong JC. Total dietary antioxidant capacity, individual antioxidant intake and breast cancer risk: the Rotterdam study. Int J Cancer. 2015;136:2178–2186. doi: 10.1002/ijc.29249. [DOI] [PubMed] [Google Scholar]
- 21.Asghari G, Rezazadeh A, Hosseini-Esfahani F, Mehrabi Y, Mirmiran P, Azizi F. Reliability, comparative validity and stability of dietary patterns derived from an FFQ in the Tehran Lipid and Glucose Study. Br J Nutr. 2012;108:1109–1117. doi: 10.1017/S0007114511006313. [DOI] [PubMed] [Google Scholar]
- 22.Ghaffarpour M, Houshiar-Rad A, Kianfar H. The manual for household measures, cooking yields factors and edible portion of food. Tehran: Nashre Olume Keshavarzy; 1999. [Google Scholar]
- 23.Rothwell JA, Perez-Jimenez J, Neveu V, Medina-Remón A, M’hiri N, García-Lobato P, Manach C, Knox C, Eisner R, Wishart DS, Scalbert A. Phenol-Explorer 3.0: a major update of the Phenol-Explorer database to incorporate data on the effects of food processing on polyphenol content. Database (Oxford) 2013;2013:bat070. doi: 10.1093/database/bat070. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Aadahl M, Jørgensen T. Validation of a new self-report instrument for measuring physical activity. Med Sci Sports Exerc. 2003;35:1196–1202. doi: 10.1249/01.MSS.0000074446.02192.14. [DOI] [PubMed] [Google Scholar]
- 25.Suzuki R, Rylander-Rudqvist T, Saji S, Bergkvist L, Adlercreutz H, Wolk A. Dietary lignans and postmenopausal breast cancer risk by oestrogen receptor status: a prospective cohort study of Swedish women. Br J Cancer. 2008;98:636–640. doi: 10.1038/sj.bjc.6604175. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Touillaud MS, Thiébaut AC, Fournier A, Niravong M, Boutron-Ruault MC, Clavel-Chapelon F. Dietary lignan intake and postmenopausal breast cancer risk by estrogen and progesterone receptor status. J Natl Cancer Inst. 2007;99:475–486. doi: 10.1093/jnci/djk096. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Fink BN, Steck SE, Wolff MS, Britton JA, Kabat GC, Schroeder JC, Teitelbaum SL, Neugut AI, Gammon MD. Dietary flavonoid intake and breast cancer risk among women on Long Island. Am J Epidemiol. 2007;165:514–523. doi: 10.1093/aje/kwk033. [DOI] [PubMed] [Google Scholar]
- 28.den Tonkelaar I, Keinan-Boker L, Veer PV, Arts CJ, Adlercreutz H, Thijssen JH, Peeters PH. Urinary phytoestrogens and postmenopausal breast cancer risk. Cancer Epidemiol Biomarkers Prev. 2001;10:223–228. [PubMed] [Google Scholar]
- 29.Peeters PH, Keinan-Boker L, van der Schouw YT, Grobbee DE. Phytoestrogens and breast cancer risk. Review of the epidemiological evidence. Breast Cancer Res Treat. 2003;77:171–183. doi: 10.1023/a:1021381101632. [DOI] [PubMed] [Google Scholar]
- 30.McCann SE, Moysich KB, Freudenheim JL, Ambrosone CB, Shields PG. The risk of breast cancer associated with dietary lignans differs by CYP17 genotype in women. J Nutr. 2002;132:3036–3041. doi: 10.1093/jn/131.10.3036. [DOI] [PubMed] [Google Scholar]
- 31.Velentzis LS, Cantwell MM, Cardwell C, Keshtgar MR, Leathem AJ, Woodside JV. Lignans and breast cancer risk in pre- and post-menopausal women: meta-analyses of observational studies. Br J Cancer. 2009;100:1492–1498. doi: 10.1038/sj.bjc.6605003. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Yamamoto S, Sobue T, Kobayashi M, Sasaki S, Tsugane S, Japan Public Health Center-Based Prospective Study on Cancer Cardiovascular Diseases Group Soy, isoflavones, and breast cancer risk in Japan. J Natl Cancer Inst. 2003;95:906–913. doi: 10.1093/jnci/95.12.906. [DOI] [PubMed] [Google Scholar]
- 33.Dai Q, Franke AA, Jin F, Shu XO, Hebert JR, Custer LJ, Cheng J, Gao YT, Zheng W. Urinary excretion of phytoestrogens and risk of breast cancer among Chinese women in Shanghai. Cancer Epidemiol Biomarkers Prev. 2002;11:815–821. [PubMed] [Google Scholar]
- 34.Bosetti C, Spertini L, Parpinel M, Gnagnarella P, Lagiou P, Negri E, Franceschi S, Montella M, Peterson J, Dwyer J, Giacosa A, La Vecchia C. Flavonoids and breast cancer risk in Italy. Cancer Epidemiol Biomarkers Prev. 2005;14:805–808. doi: 10.1158/1055-9965.EPI-04-0838. [DOI] [PubMed] [Google Scholar]
- 35.Grace PB, Taylor JI, Low YL, Luben RN, Mulligan AA, Botting NP, Dowsett M, Welch AA, Khaw KT, Wareham NJ, Day NE, Bingham SA. Phytoestrogen concentrations in serum and spot urine as biomarkers for dietary phytoestrogen intake and their relation to breast cancer risk in European prospective investigation of cancer and nutrition-norfolk. Cancer Epidemiol Biomarkers Prev. 2004;13:698–708. [PubMed] [Google Scholar]
- 36.Mink PJ, Scrafford CG, Barraj LM, Harnack L, Hong CP, Nettleton JA, Jacobs DR., Jr Flavonoid intake and cardiovascular disease mortality: a prospective study in postmenopausal women. Am J Clin Nutr. 2007;85:895–909. doi: 10.1093/ajcn/85.3.895. [DOI] [PubMed] [Google Scholar]
- 37.Zamora-Ros R, Andres-Lacueva C, Lamuela-Raventós RM, Berenguer T, Jakszyn P, Barricarte A, Ardanaz E, Amiano P, Dorronsoro M, Larrañaga N, Martínez C, Sánchez MJ, Navarro C, Chirlaque MD, Tormo MJ, Quirós JR, González CA. Estimation of dietary sources and flavonoid intake in a Spanish adult population (EPIC-Spain) J Am Diet Assoc. 2010;110:390–398. doi: 10.1016/j.jada.2009.11.024. [DOI] [PubMed] [Google Scholar]
- 38.Bahrami A, Jafari S, Rafiei P, Beigrezaei S, Sadeghi A, Hekmatdoost A, Rashidkhani B, Hejazi E. Dietary intake of polyphenols and risk of colorectal cancer and adenoma-a case-control study from Iran. Complement Ther Med. 2019;45:269–274. doi: 10.1016/j.ctim.2019.04.011. [DOI] [PubMed] [Google Scholar]
- 39.Hollman PC, Cassidy A, Comte B, Heinonen M, Richelle M, Richling E, Serafini M, Scalbert A, Sies H, Vidry S. The biological relevance of direct antioxidant effects of polyphenols for cardiovascular health in humans is not established. J Nutr. 2011;141:989S–1009S. doi: 10.3945/jn.110.131490. [DOI] [PubMed] [Google Scholar]
- 40.Erdman JW, Jr, Balentine D, Arab L, Beecher G, Dwyer JT, Folts J, Harnly J, Hollman P, Keen CL, Mazza G, Messina M, Scalbert A, Vita J, Williamson G, Burrowes J. Flavonoids and heart health: proceedings of the ILSI North America flavonoids workshop, May 31–June 1, 2005, Washington, DC. J Nutr. 2007;137:718S–737S. doi: 10.1093/jn/137.3.718S. [DOI] [PubMed] [Google Scholar]
- 41.Pérez-Jiménez J, Fezeu L, Touvier M, Arnault N, Manach C, Hercberg S, Galan P, Scalbert A. Dietary intake of 337 polyphenols in French adults. Am J Clin Nutr. 2011;93:1220–1228. doi: 10.3945/ajcn.110.007096. [DOI] [PubMed] [Google Scholar]
- 42.Zamora-Ros R, Ferrari P, González CA, Tjønneland A, Olsen A, Bredsdorff L, Overvad K, Touillaud M, Perquier F, Fagherazzi G, Lukanova A, Tikk K, Aleksandrova K, Boeing H, Trichopoulou A, Trichopoulos D, Dilis V, Masala G, Sieri S, Mattiello A, Tumino R, Ricceri F, Bueno-de-Mesquita HB, Peeters PH, Weiderpass E, Skeie G, Engeset D, Menéndez V, Travier N, Molina-Montes E, Amiano P, Chirlaque MD, Barricarte A, Wallström P, Sonestedt E, Sund M, Landberg R, Khaw KT, Wareham NJ, Travis RC, Scalbert A, Ward HA, Riboli E, Romieu I. Dietary flavonoid and lignan intake and breast cancer risk according to menopause and hormone receptor status in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study. Breast Cancer Res Treat. 2013;139:163–176. doi: 10.1007/s10549-013-2483-4. [DOI] [PubMed] [Google Scholar]
- 43.Hui C, Qi X, Qianyong Z, Xiaoli P, Jundong Z, Mantian M. Flavonoids, flavonoid subclasses and breast cancer risk: a meta-analysis of epidemiologic studies. PLoS One. 2013;8:e54318. doi: 10.1371/journal.pone.0054318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Rickman JC, Barrett DM, Bruhn CM. Nutritional comparison of fresh, frozen and canned fruits and vegetables. Part 1. Vitamins C and B and phenolic compounds. J Sci Food Agric. 2007;87:930–944. [Google Scholar]
- 45.Ozasa K, Nakao M, Watanabe Y, Hayashi K, Miki T, Mikami K, Mori M, Sakauchi F, Washio M, Ito Y, Suzuki K, Wakai K, Tamakoshi A JACC Study Group. Serum phytoestrogens and prostate cancer risk in a nested case-control study among Japanese men. Cancer Sci. 2004;95:65–71. doi: 10.1111/j.1349-7006.2004.tb03172.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Kurahashi N, Iwasaki M, Inoue M, Sasazuki S, Tsugane S. Plasma isoflavones and subsequent risk of prostate cancer in a nested case-control study: the Japan Public Health Center. J Clin Oncol. 2008;26:5923–5929. doi: 10.1200/JCO.2008.16.8807. [DOI] [PubMed] [Google Scholar]
- 47.Collaborative Group on Hormonal Factors in Breast Cancer. Type and timing of menopausal hormone therapy and breast cancer risk: individual participant meta-analysis of the worldwide epidemiological evidence. Lancet. 2019;394:1159–1168. doi: 10.1016/S0140-6736(19)31709-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Beral V, Gaitskell K, Hermon C, Moser K, Reeves G, Peto R Collaborative Group On Epidemiological Studies Of Ovarian Cancer. Menopausal hormone use and ovarian cancer risk: individual participant meta-analysis of 52 epidemiological studies. Lancet. 2015;385:1835–1842. doi: 10.1016/S0140-6736(14)61687-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Ziaei S, Halaby R. Dietary isoflavones and breast cancer risk. Medicines (Basel) 2017;4:18. doi: 10.3390/medicines4020018. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Welty FK, Lee KS, Lew NS, Nasca M, Zhou JR. The association between soy nut consumption and decreased menopausal symptoms. J Womens Health (Larchmt) 2007;16:361–369. doi: 10.1089/jwh.2006.0207. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Ewies AA. Phytoestrogens in the management of the menopause: up-to-date. Obstet Gynecol Surv. 2002;57:306–313. doi: 10.1097/00006254-200205000-00023. [DOI] [PubMed] [Google Scholar]
- 52.Chen LR, Ko NY, Chen KH. Isoflavone supplements for menopausal women: a systematic review. Nutrients. 2019;11:2649. doi: 10.3390/nu11112649. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.Bolaños-Díaz R, Zavala-Gonzales JC, Mezones-Holguín E, Francia-Romero J. Soy extracts versus hormone therapy for reduction of menopausal hot flushes: indirect comparison. Menopause. 2011;18:825–829. doi: 10.1097/gme.0b013e31820750bc. [DOI] [PubMed] [Google Scholar]
- 54.Touvier M, Druesne-Pecollo N, Kesse-Guyot E, Andreeva VA, Fezeu L, Galan P, Hercberg S, Latino-Martel P. Dual association between polyphenol intake and breast cancer risk according to alcohol consumption level: a prospective cohort study. Breast Cancer Res Treat. 2013;137:225–236. doi: 10.1007/s10549-012-2323-y. [DOI] [PubMed] [Google Scholar]
- 55.Yang CS, Wang X, Lu G, Picinich SC. Cancer prevention by tea: animal studies, molecular mechanisms and human relevance. Nat Rev Cancer. 2009;9:429–439. doi: 10.1038/nrc2641. [DOI] [PMC free article] [PubMed] [Google Scholar]