Breast cancer is known as one of the deadliest forms of cancer, and it is increasing globally. There are a variety of proven and controversial risk factors for this malignancy. Herein, we aimed to undertake a systematic review and meta-analysis focus on the epidemiology of breast cancer risk factors in Iran.
We performed a systematic search via PubMed, Scopus, Web of Science, and Persian databases for identifying studies published on breast cancer risk factors up to March 2019. Meta-analyses were done for risk factors reported in more than one study. We calculated odds ratios (ORs) with corresponding 95% confidence intervals (CIs) using a fixed/random-effects models.
Thirty-nine studies entered into the meta-analysis. Pooling of ORs showed a significant harmful effect for risk factors including family history (OR: 1.80, 95%CI 1.47–2.12), hormonal replacement therapy (HRT) (OR: 5.48, 95%CI 0.84–1.74), passive smokers (OR: 1.68, 95%CI 1.34–2.03), full-term pregnancy at age 30 (OR: 3.41, 95%CI 1.19–5.63), abortion (OR: 1.84, 95%CI 1.35–2.33), sweets consumption (OR: 1.71, 95%CI 1.32–2.11) and genotype Arg/Arg (crude OR: 1.59, 95%CI 1.07–2.10), whereas a significant protective effect for late menarche (OR: 0.58, 95%CI 0.32–0.83), nulliparity (OR: 0.68, 95%CI 0.39–0.96), 13–24 months of breastfeeding (OR: 0.68, 95%CI 0.46–0.90), daily exercise (OR: 0.59, 95%CI 0.44–0.73) and vegetable consumption (crude OR: 0.28, 95%CI 0.10–0.46).
This study suggests that factors such as family history, HRT, passive smokers, late full-term pregnancy, abortion, sweets consumption and genotype Arg/Arg might increase risk of breast cancer development, whereas late menarche, nulliparity, 13–24 months breastfeeding, daily exercise and vegetable consumption had an inverse association with breast cancer development.
Breast cancer is one of the most common health concerns throughout the world , , , , which includes 30% of female cancers , . It is also known as the second cause of death in developed countries and the third leading cause of death in less developed countries , , . Surprisingly, approximately 502,000 women die due to breast cancer annually . According to the World Health Organization (WHO) prediction, up to 2.3 million women will be diagnosed for breast cancer by 2050 , .
In Iran, breast cancer has been identified as the most common cancer and also the fifth main cause of death among Iranian women , . The standardized incidence rate (ASR) is about 28 per 100,000 people, which has increased in recent years . There are a variety of proven and controversial risk factors for breast cancer. The American Cancer Society has reported that only about a quarter of breast cancers are due to identified risk factors. These factors include aging, urban life, social class (upper-middle class), marital status (single), white race, history of ovarian cancer, early menarche age, late menopause age, history of breast cancer, history of fibrocystic breast disease, family history of breast, uterine and ovarian cancers, and history of radiation exposure. However, it seems that numerous factors have not yet been identified .
According to the Iran, aging, history of breast cancer, genetic modification, chest radiation therapy, diethylstilbestrol (DES) intervention, using hormonal replacement therapy (HRT), low levels of vitamin D, exposure to chemicals in cosmetics, diet, obesity , smoking , alcohol, fertility and hormonal factors, contraceptives, early menarche, late menopause, high age at first birth, absence of labor history, other malignancies such as ovarian and endometrial carcinoma, are all the most commonly reported risk factors for breast cancer , .
Considering the incidence and prevalence of breast cancer, the high cost of treatment, risk of involvement in women who are productive in social and socioeconomic settings (>35-year-old) and lack of national screening or early diagnosis, breast cancer is an important subject, the importance of which is reported widely , , , .
Despite the importance of the associated risk factors with this malignancy, there is no nationwide study in this regard according to our knowledge. Hence, we aimed to undertake a systematic review and meta-analysis focus on the epidemiology of breast cancer risk factors in Iran. We hope our findings could provide a comprehensive report to be useful for future studies.
We followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for study design, search protocol, screening, and reporting. A systematic search was performed via international databases of PubMed, Scopus, and Web of Science until 05 March 2019. Moreover, for finding Persian papers, we used Google Scholar database and national databases of Scientific Information Database (SID), Iranmedex, and Magiran. The search strategy included MeSH terms and free keywords as follows: ((Breast OR Mammary) AND (Cancer* OR Neoplasm* OR Tumor* OR Malignancy* OR Carcinoma*) AND (“Risk factor” OR “Risk factors” OR “Population at Risk” OR “Populations at Risk”) AND AND Iran). Persian equivalent words were used for searching in national databases. There was no limitation about the date of publications in our search.
Criteria study selection
Two group members (A.SH and K.HD) selected the papers independently and discussed to solve the disagreements. Studies met the following criteria included in the meta-analysis: (1) comparative studies with a control group such as case-control and cross-sectional; and (2) studies reported the risk factors of female breast cancer patients in Iran. Studies were excluded if they were: (1) conference abstracts, comments, letters, animal studies, reviews, case reports, and in vitro studies; (2) duplicate publications; and (3) included insufficient data for calculating desired parameters.
Data extraction & quality assessment
Two researchers (Z.SH and K.HD) have independently evaluated the quality of studies and extracted data from included papers. The supervisor (R.AN) resolved any disagreements in this part. Data extraction checklist included the name of the first author, publication year, a region of study, number of patients, mean age, quantitative information of risk factors, clinicopathological features, and available correlations.
The Newcastle-Ottawa Scale (NOS) checklist was used to value the selected papers in relation to various aspects of the methodology and study process.
Statistical analysis was performed using STATA v.11 software. To assess the heterogeneities, we used the I-square (I2) test. According to the studies heterogeneity, we pooled results using a fixed-effects or random-effects model as appropriate for heterogeneity more or less than 50%, respectively.
Study selection process
Our initial search through databases resulted in 562 papers. After excluding duplicated papers, remained papers screened using title and abstract. Finally, after eligibility assessment of 84 full texts, 41 studies entered into qualitative synthesis, and finally, 39 studies entered into the meta-analysis. PRISMA flow diagram for the study selection process is presented in Figure 1.
Out of 39 included studies, 35 studies were case-control, and four of them were cross-sectional studies. The studies’ sample size ranged from 93 to 25,592, including 54,347 participants. Nine studies were conducted in Tehran province, six in Fars, four in Mazandaran, four in Isfahan, three in East Azerbaijan, two in Guilan, two in Kermanshah, one in West Azerbaijan, one in Golestan, one in Yazd, one in Hormozgan, one in Khuzestan, and one in Razavi Khorasan. Moreover, one study was a joint study between Mazandaran and Guilan, and one study between Tehran and East Azerbaijan. Characteristics of studies entered into meta-analysis presented in Table 1.
|Author, year||Design||Region C/P||No. of participants||Case||Control||Risk factors||Adjusted by|
|(Case/Control)||Mean age, SD||Mean age, SD|
|Ebrahimi et al. (2002) ||CC||Tehran C||535(286/249)||47.5(12.8)||44.2(13.2)||Age (+), parity (+), FH (+), OCP (−), MeS (+), MaS (+), ES (+), nulliparity (+), AFFTP (+)|
|Pesaran et al. (2003) ||CC||Isfahan C||352(176/176)||49(11.3)||47(11.4)||FH (+)|
|Montazeri et al. (2004) ||CC||Tehran C||729(243/486)||46.6(11.2)||45.5(10.1)||Age (=), FH (+), OCP (+), MeS (−), MeAS (−), MaS (*), ES (+), depression (+), Hopelessness (+), quality of life (−), AFFTP (+), anxiety (+), psychiatric medications (+)||MeAS, FH, depression and hopelessness|
|Yavari et al. (2005) ||CC||Tehran C||606(303/303)||48.8(9.8)||50.2(11.1)||FH (+), PBBD (+), OCP (+), MeS (+), MeAS (+), MaS (+), XE (+), ES (+), parity (+), abortion (−), BF (*)||FH, PBBD, OCP, MeS, MeAS, MaS, XE, ES, abortion, BF|
|Mahouri et al. (2007) ||CC||Bandar-Abbas C||672(168/504)||48.6(13.7)||48.4(13.6)||FH (+), PBBD (+), OCP (−), MeS (−), MaS (+), MeAS (+), smoking (+), HRT (+), Nulliparity (+), abortion (+), BF (−), AFFTP (+)|
|Naieni et al. (2007) ||CC||Mazandaran P||750(250/500)||48.7(11.3)||48(11.4)||FH (+), PBBD (+), OCP (+), MeS (+), MeAS (+), smoking (+), ES (+), BMI (+), income (=), SS (=), BF (−), parity (−), IM (+)||Unclear adjustment|
|Lotfi et al. (2008) ||CC||Yazd C||160(80/80)||48.9(9.7)||49.1(9.8)||FH (+), OCP (−), MeS (+), MeAS (+), MaS (+), occupation (+), XE (+), PhA (+),|
ES (+), BMI (+), BF (+), GS (+)
|Kazemi et al. (2009) ||CC||Rasht & Tonekabon C||102(42/60)||TP53 codon 72 polymorphism (+)|
|Ghiasvand et al. (2010) ||CC||Shiraz C||1042(521/521)||41.24||41.06||FH (+), OCP (+), MeAS (−), MaS (+), occupation (+), ES (+), BMI (*), AFFTP (*), parity (−), MA (+)||Age, HP, height, weight, BMI, OCP, BF. MeS, MeAS, ES, MaS|
|Hajian-tilaki and Kaveh-ahangar (2011) ||CC||Babol C||300(100/200)||51.2(9.6)||51.1(9.3)||MeS (−), MeAS (*), AFFTP (+), Parity (−), abortion (+), BF (−)||Parity|
|Hajian-tilaki (2011) ||CC||Babol C||300(100/200)||51.2(9.6)||51.1(9.3)||ES (−)||Re, MeAS, parity, abortion, MeS, BF, OCP, FH, XE, smoking, exercise, BMI|
|Motie et al. (2011) ||CC||Golestan P||267(134/133)||47.15(10.36)||42.96(11.93)||FH (+), XE (*), MaS (+), MeAS (−), PBBD (+), infertility (*)||Unclear adjustment|
|Ghiasvand et al. (2012) ||CC||Shiraz C||986(493/493)||58.2(7.2)||58(7.4)||FH (+), OCP (+), MeAS (+), Occupation (+), ES (+), BMI (*)||Age, Re|
|Sigaroodi et al. (2012) ||CC||Sari C||130(79/51)||47.77(12.55)||34.2(9.7)||Age (−), human papillomavirus (+)|
|Ahmadinejad et al. (2013) ||CS||Tehran C||728(184/544)||48.6(8.3)||Age (*), MeS (−), MaS (−), smoking (−), Parity (−), AFFTP (+), BMI (−), occupation (+)||MeAS, parity, AFD|
|Kaviani et al. (2013) ||CS||Tehran C||646||Unclear adjustment|
|Pourzand et al. (2013) ||CC||Tabriz C||400(200/200)||50.05(11.47)||49.91(11.83)||GS (+), SS (+)|
|Zare et al. (2013) ||CC||Tabriz & Tehran||25592(111/25481)||49.18(8.86)||46.65(9.4)||Age (+), FH (+), occupation (+), OCP (−), MeS (+), MaS (*), HRT (+), ES (*), BMI (*), MA (+)||Age, occupation, ES, BMI, MeS, HRT, OCP|
|Bidgoli and Azarshab (2014) ||CC||Sabzevar C||176(60/116)||36.45(7.02)||34.2(5.7)||SLE (−), SI (*), diet (*)|
|Hosseinzadeh et al. (2014) ||CC||Tabriz C||420(140/280)||47.6(10.7)||46.8(10.4)||FH (+), PBBD (+), OCP (+), MeAS (*), MeS (+), MaS (+), smoking (+), PS (+), HRT (+), ES (+), BMI (+), Migration (+), diet (*), nulliparity (+), Abortion (+), BF (−), infertility (+)||MeS, BF, PBBD, MeAS, parity, AFD, abortion, OCP|
|Mobarakeh et al. (2014) ||CC||Tehran C||93(53/40)||40.02(10.01)||39.78(11.21)||BMI (+), diet (*)||Age, BMI, ES|
|Sepandi (2014) ||CC||Shiraz C||11850(197/11653)||49.4(8.7)||40.9(10.5)||FH (+), OCP (+), MeS (+), MeAS (−), MaS (*), occupation (+), ES (−), BMI (+), Nulliparity (*), parity (*), AFFTP (+)||Age, MeAS, AFP, occupation, parity, FH, BF, OCP|
|Tazhibi et al. (2014) ||CC||Isfahan P||257(216/41)||OCP (−), MeS (+), MaS (+), HRT (+)||Occupation, age, MaS, MeS, OCP, HRT|
|Salarabadi et al. (2015) ||CC||Kermanshah C||152(47/105)||Diet (*), SI (+)|
|Tajaddini (2015) ||CC||Tabriz C||615(306/309)||46.4(10.2)||41.4(9.6)||Diet (*)||Age, MeS, parity, BMI|
|Veisy et al. (2015) ||CC||West Azerbaijan P||194(111/830)||47.6||46.5||OCP (+), MeAS (*), AFFTP (*)|
|Ahmadnia et al. (2016) ||CC||Guilan P||450(225/225)||Diet (*)|
|Jafari-Mehdiabad et al. (2016) ||CC||Isfahan P||296(98/198)||MaS (+), ES (−), BF (+), income (−)|
|Jafarinia et al. (2016) ||CC||Dezful C||340(170/170)||45.4(11)||45||FH (+), OCP (*), HRT (+), PhA (*), AFFTP (+), BF (−)||ES, BF, parity, MaS|
|Montazeri et al. (2016) ||CC||Tehran C/Tabriz C||975(432/543)||48.6(4.7)||40.6(10.7)||BF (+), MeAS (−), AFFTP (+)||MeS, AFP, age, BF|
|Dehghan et al. (2017) ||CC||Isfahan P||182(86/96)||52.88(11.92)||40.31(16.82)||Age (+), FH (+)||FH, occupation, MaS, age, MeAS, MeS, HRT, abortion, BMI|
|Dianatinasab et al. (2017) ||CC||Shiraz C||1052(526/526)||47.8(10.58)||46.75(11.08)||FH (+), OCP (+), MeS (+), MaS (+), Smoking (+), PS (+), occupation (+), XE (+), PhA (−), ES (*), hair coloring (+), BMI (+), SQ (*), parity (*), AFFTP (+), BF (*)||MaS, AFD, parity, birth spacing, BF, MeAS|
|Dianatinasab-2 et al. (2017) ||CS||Shiraz C||497||Age (−), FH (+), smoking (−), XE (+), PhA (−), income (−), CD (+)|
|Mirfarhadi et al. (2017) ||CS||Rasht C||232||FH (+), MaS (+), ES (−), RR (+), IC (+), income (+)|
|Vahid et al. (2017) ||CC||Tehran C||293(145/148)||49.8(11.8)||48.5(11.9)||SI (−)||Age, BMI, ES, smoking, MeAS, occupation, MeS|
|Fararouei et al. (2018) ||CC||Shiraz C||1010(505/505)||41.78(10.56)||42.24(10.62)||FH (+), OCP (+), smoking (+), PS (+), occupation (+), PhA (−), ES (+), MA (−), diet (−)||Diet, PhA, ES, occupation, PBBD, OCP, smoking|
|Pouladi et al. (2018) ||CC||Tabriz C||303(143/160)||TP53 codon 72 polymorphism (+)|
|Vahid et al. (2018) ||CC||Tehran C||293(145/148)||49.83(11.86)||48.54(12)||Age, ES, exercise, BMI, smoking, FH, MeAS, parity, MaS, MeS, OCP, HRT|
|Marzbani et al. (2019) ||CC||Kermanshah C||620(212/408)||41.5(6.2)||39.5(7.1)||Age (+), MaS (−), S (+), BMI (*), Diet (+), RR (+), IC (+), occupation (*)||Age, sex, ES, BMI|
(+), risk-increasing; (−), risk-reducing; (=), null; (*), consists of various effects; C, City; P, Province; CC, Case-control; CS, Cross-sectional; FH, Familial history; OCP, Oral contraceptive pill; MeS, Menopause status; MaS, Marital status; ES, Educational status; AFFTP, Age at first full-term pregnancy; HRT, Hormone replacement therapy; SLE, Sunlight exposure; SI, Supplement intake; XE, X-ray exposure; PhA, Physical activity; CD, Chronic diseases; PS, Passive smoker; SQ, Sleep quality; MeAS, Menarche age status; BF, Breastfeeding; IM, Irregular menstruation; PBBD, Previous benign breast disease; RR, Rural residency; Re, Residence area; IC, Insurance coverage; SS, Socioeconomic status; GS, Genital surgery; OC, Ovary cancer; HP, History of pregnancy; AFD, age at the first delivery; MA, Marriage age.
According to quality assessment using the NOS checklist, 39 studies earned the minimum eligibility score and entered into the meta-analysis. It is remarkable that the NOS modified checklist was used for cross-sectional studies . Only one paper was excluded due to a low score. Summary of risk of bias presented in Figure 2. for details, see Supplementary material 2.
Risk factors for breast cancer
According to included studies, over 20 risk factors were reported for breast cancer. The factors reported in only one study, which seems to be rare are as follows: High-fat foods and dairy (e. g. milk, yogurt, and cheese) , Fast foods , Genital surgery (surgeries related to uterus and ovary such as hysterectomy or oophorectomy) , , Hopelessness , Hair coloring , Human papillomavirus infection , Epstein–Barr virus infection , Ovarian cancer , Supplements of selenium, calcium, Vit B12 and Vit D .
The factors reported in more than one study are as follows: Age, Family history, Menarche age, Body mass index (BMI), Relationship status, Education Level, Smoking status, Daily exercise, Menopausal status, HRT, Oral contraceptive, birth-giving status, Abortion status, Benign Breast Conditions, X-ray exposure, Breastfeeding duration, Dietary status (including sweets, egg, fish, and vegetables), Genotype status and Residency status.
Only clear well-known risk factors reported in two or more studies entered into the meta-analysis.
Individual-related risk factors (Table 2)
|Risk factor||Number of studies||I-squared; crude, %||p-Value; crude||OR (95%CI); crude||Number of studies||I-squared;|
|p-Value; adjusted||OR (95%CI); adjusted|
|Age||5||94.2||0.000||0.97 (0.92, 1.02)||2||80.6||0.023||1.04 (0.97, 1.11)|
|Family history||18||24.6||0.165||2.31 (1.95, 2.86)||12||24.3||0.205||1.80 (1.47, 2.12)|
|Menarche age status|
|Unknown categorization||2||89.6||0.002||2.25 (−0.80, 5.30)|
|Less than 12 years||5||81.4||0.000||1.31 (0.23, 2.40)|
|Between 12 and 15 years||2||54.8||0.137||0.52 (0.26, 0.78)||2||77.3||0.036||0.55 (0.07, 1.03)|
|Less than 13 years||5||0.0||0.710||1.19 (0.94, 1.44)|
|Less than 14 years||5||38.6||0.164||0.91 (0.68, 1.15)|
|More than 15 years||5||75.5||0.003||0.81 (0.39, 1.23)||4||35.3||0.201||0.58 (0.32, 0.83)|
|Body mass index status|
|Unknown categorization||3||65.3||0.056||1.02 (1.00, 1.05)||2||77.9||0.034||1.04 (0.99, 1.09)|
|Between 25 and 29.9||6||0.0||0.699||1.09 (0.91, 1.28)||3||0.0||0.766||1.07 (0.82, 1.32)|
|More than 30||5||0.0||0.433||1.15 (0.91, 1.39)||3||0.0||0.994||1.21 (0.90, 1.52)|
|Single||11||13.6||0.315||0.98 (0.74, 1.23)|
|Married||2||0.0||0.678||0.64 (−0.25, 1.54)|
|Divorced||7||0.0||0.619||1.15 (0.87, 1.43)|
|Basic education||14||75.5||0.000||1.23 (0.94, 1.51)||9||87.5||0.000||1.18 (0.70, 1.66)|
|Academic education||12||71.4||0.000||1.21 (0.80, 1.62)||8||69.8||0.002||0.67 (0.24, 1.10)|
|Active smoker||5||63.5||0.027||1.49 (0.89, 2.08)||3||66.3||0.051||1.70 (0.66, 2.74)|
|Passive smoker||2||0.0||0.657||1.84 (1.43, 2.25)||3||0.0||0.442||1.68 (1.34, 2.03)|
|Daily exercise||4||73.5||0.010||0.40 (0.05, 0.75)||3||0.0||0.678||0.59 (0.44, 0.73)|
|Menopausal status||12||88.9||0.000||1.53 (1.06, 1.99)||9||73.9||0.000||1.29 (0.84, 1.74)|
|Hormone replacement therapy||4||61.9||0.049||1.80 (0.36, 3.23)||3||0.0||0.509||5.48 (2.71, 8.25)|
|Oral contraceptive||14||80.0||0.000||1.18 (0.93, 1.44)||10||86.9||0.000||1.17 (0.77, 1.57)|
|Age at first full-term pregnancy|
|20–24 years||3||68.0||0.044||1.48 (0.79, 2.17)||2||0.0||0.484||1.92 (1.14, 2.71)|
|25–29 years||5||0.0||0.560||1.40 (1.00, 1.80)||4||5.3||0.367||1.55 (0.82, 2.29)|
|30 years||5||0.0||0.758||2.23 (1.45, 3.01)||3||0.0||0.970||3.41 (1.19, 5.63)|
|Birth giving status|
|Nulliparity||6||40.4||0.136||0.77 (0.55, 0.98)||3||28.0||0.249||0.68 (0.39, 0.96)|
|Abortion||5||86.9||0.000||1.25 (0.57, 1.93)||3||0.0||0.393||1.84 (1.35, 2.33)|
|Previous benign breast||5||0.0||0.672||1.24 (0.82, 1.67)|
|X-ray exposure||5||0.0||0.676||1.42 (1.18, 1.66)||3||83.6||0.002||1.02 (0.19, 1.86)|
|Breastfeeding||3||0.0||0.526||0.58 (0.30, 0.85)||2||88.1||0.004||0.73 (0.14, 1.31)|
|1–12 months||3||40.0||0.189||0.95 (0.41, 1.49)|
|13–24 months||4||0.0||0.602||0.57 (0.42, 0.72)||2||0.0||0.624||0.68 (0.46, 0.90)|
|25–48 months||2||92.1||0.000||1.12 (−0.68, 2.92)||2||0.0||0.402||0.24 (−0.46, 0.94)|
|More than 49 months||2||0.0||0.410||0.10 (−0.25, 0.44)|
|Egg||2||82.7||0.016||0.92 (−0.64, 2.47)|
|Fish||2||0.0||0.462||1.47 (0.68, 2.25)|
|Sweets||2||73.2||0.053||2.83 (1.38, 4.29)||2||0.0||0.391||2.21 (1.56, 2.87)|
|Vegetables||3||56.1||0.102||0.28 (0.10, 0.46)|
|Arg/Arg||2||0.0||0.835||1.59 (1.07, 2.10)|
|Arg/Pro||2||0.0||0.824||0.69 (0.37, 1.00)|
|Genital surgery||2||0.0||0.325||2.23 (0.91, 3.55)|
|Rural||2||0.0||0.875||1.37 (0.87, 1.86)|
Age was considered as a risk factor in four papers. The meta-analysis showed no significant difference between groups for breast cancer occurrence regarding age (OR: 1.04, 95%CI 0.97–1.11). A significant heterogeneity was observed (I2=80.6%, p=0.023) (Supplementary material 1).
Eighteen studies reported on a family history of breast cancer. The meta-analysis between two groups showed that the odds of breast cancer development was 1.80 times higher in subject with a family history of breast cancer (OR: 1.80, 95%CI 1.47–2.12). A modest heterogeneity was observed (I2=24.3%, p=0.205) (Supplementary material 1).
This factor was studied in Nine articles. The meta-analysis showed a significant protective effect for menarche age more than 15 (OR: 0.58, 95%CI 0.32–0.83). Moderate heterogeneity was observed in this regard (I2=35.3%, p=0.201) (Supplementary material 1).
Body mass index
BMI was investigated in nine studies. The meta-analysis indicated no significant differences between groups for BMI status (OR: 1.04, 95%CI 0.99–1.09), BMI 25–29.9 (OR: 1.07, 95%CI 0.82–1.32) and BMI more than 30 (OR: 1.21, 95%CI 0.90–1.52) (Supplementary material 1).
Thirteen papers were studied relationship status. The meta-analysis found that there were no significant differences between groups regarding single status (crude OR: 0.98, 95%CI 0.74–1.23), married status (crude OR: 0.64, 95%CI −0.25 to 1.54) and divorced status (crude OR: 1.15, 95%CI 0.87–1.43) (Supplementary material 1).
This factor was studied in 15 papers. According to meta-analysis, no significant differences were found for both basic education level (OR: 1.18, 95%CI 0.70–1.66) and academic education level (OR: 0.67, 95%CI 0.24–1.10) (Supplementary material 1).
Six papers studied this factor. The meta-analysis showed that the odds of breast cancer occurrence was 1.68 times higher in the passive smokers (OR: 1.68, 95%CI 1.34–2.03). However, no significant relationships were observed for active smokers (OR: 1.70, 95%CI 0.66–2.74) (Supplementary material 1).
Three studies were included with this factor. The daily exercise showed a protective effect on the occurrence of breast cancer (OR: 0.59, 95%CI 0.44–0.73). No heterogeneity was observed (I2=0.0%, p=0.678) (Supplementary material 1).
Thirteen studies have investigated this factor. No significant relationships were observed between groups in this regard (OR: 1.29, 95%CI 0.84–1.74). High heterogeneity was observed (I2=73.9%, p<0.0001) (Supplementary material 1).
Hormone replacement therapy
HRT was studied in five papers. The meta-analysis indicated that the odds of breast cancer occurrence was 5.48 time higher in the group with HRT history (OR: 5.48, 95%CI 0.84–1.74). No significant heterogeneity was observed (I2=0.0%, p=0.509) (Supplementary material 1).
A history of OCP intake was discussed in 15 papers. The meta-analysis showed no significant differences between groups in this regard (OR: 1.17, 95%CI 0.77–1.57). High heterogeneity was observed (I2=86.9%, p<0.0001) (Supplementary material 1).
Birth giving status
Age at first full-term pregnancy was considered in six studies. Meta-analysis showed a significant difference for age 20 to 24 (OR: 1.92, 95%CI 1.14–2.71) and age 30 (OR: 3.41, 95%CI 1.19–5.63) in this regard, but no substantial relationships were found for age 25 to 29 (OR: 1.55, 95%CI 0.82–2.29) (Supplementary material 1).
Six studies investigated the relation of nulliparity and chance of breast cancer development. The meta-analysis results indicated that this condition has an inverse relation with the occurrence of breast cancer (OR: 0.68, 95%CI 0.39–0.96) (Supplementary material 1).
Moreover, five papers studied the history of abortion. A significant difference in odds was observed in the meta-analysis of two groups. Subjects with a history of abortion have a higher chance of breast cancer development (OR: 1.84, 95%CI 1.35–2.33). No significant heterogeneity was observed (I2=0.0%, p=0.393) (Supplementary material 1).
Benign breast conditions
Data from five studies were combined for the meta-analysis of benign breast history as a risk factor to develop breast cancer. No significant difference was observed in this regard (crude OR: 1.24, 95%CI 0.82–1.67) (Supplementary material 1).
This factor was studied in four papers. No significant differences were observed regarding the history of X-rays exposure between cases and controls (OR: 1.02, 95%CI 0.19–1.86). A significant heterogeneity was observed (I2=83.6%, p=0.002) (Supplementary material 1).
This factor was investigated in seven studies. The meta-analysis revealed that 13–24 months of breastfeeding has an inverse association with breast cancer occurrence (OR: 0.68, 95%CI 0.46–0.90). No significant heterogeneity was observed (I2=0.0%, p=0.624) (Supplementary material 1).
This factor was studied for egg, fish, sweets, and vegetables. The meta-analysis revealed that egg (crude OR: 0.92, 95%CI −0.64 to 2.47) and fish (crude OR: 1.47, 95%CI 0.68–2.25) do not affect the chance of breast cancer occurrence significantly (Supplementary material 1). However, findings showed that the odds of developing breast cancer were higher in individuals with high sweets consumption (OR: 1.71, 95%CI 1.32–2.11) (Supplementary material 1) and lower in subjects with regular vegetable consumption (crude OR: 0.28, 95%CI 0.10–0.46) (Supplementary material 1).
Two studies were investigated p53 codon 72 polymorphisms as a breast cancer risk factor. Although genotype Arg/Pro (crude OR: 0.69, 95%CI 0.37–1.00) was not related to the odds of breast cancer development, a significantly higher chance found for genotype Arg/Arg (crude OR: 1.59, 95%CI 1.07–2.10) in this regard (Supplementary material 1).
Genital surgery was considered in two studies. No significant differences were found regarding the history of genital surgery for breast cancer development (crude OR: 1.37, 95%CI 0.87–1.86) (Supplementary material 1).
The place of living was investigated in two studies. The meta-analysis delivered no significant difference between two groups with rural and urban residency status for breast cancer occurrence (crude OR: 1.37, 95%CI 0.87–1.86) (Supplementary material 1).
We undertook this systematic review and meta-analysis to identify the risk factors contributing to the occurrence of female breast cancer in Iran. Out of 39 included papers, more than 60 factors were studied as breast cancer risk factors, of which only 27 factors entered the meta-analysis. Out of all risk factors, factors including family history, HRT, passive smokers, late full-term pregnancy, abortion, sweets consumption, and genotype Arg/Arg indicated to be significantly associated with a higher chance of breast cancer development. In contrast, factors of late menarche, nulliparity, 13–24 months of breastfeeding, daily exercise, and vegetable consumption, were demonstrated to be protective. The other remaining risk factors were not associated with the development of breast cancer.
A family history of breast cancer was one of the associated risk factors for breast cancer development in our study. In one of the first meta-analysis on “Family history and the risk of breast cancer”, Pharoah et al.  pooled estimate of relative risk (RR) indicated that the probability of breast cancer occurrence is higher in those individuals with a family history of this malignancy (RR: 1.9, 95%CI, 1.7–2.0). They also found that this probability is higher in first-degree relatives, especially mother and sister (RR: 3.6, 95%CI 2.5–5.0). There are many other studies that reported the association of family history with the risk of breast cancer , , .
High levels of estrogen can increase the chance of breast cancer development through genotoxic stress induction and breast tissue mutations , . Therefore, receiving external estrogen through HRT may increase the risk of breast cancer development. In this regard, HRT users showed the highest chance of developing breast cancer in our meta-analysis (OR: 5.48, 95%CI 0.84–1.74), inconsistent with several studies , , . In contrast, the study of Bae et al. reported no significant association in this regard among Korean Women .
In our meta-analysis, although passive smokers were at higher risk of breast cancer development, no significant association was found for active smokers in this case. Our findings were in the same line with the systematic review of Chen et al.  among Chinese females, which implied that passive smokers were at higher risk of breast cancer development (OR: 1.62, 95%CI 1.39–1.85), but not active smokers (OR: 1.04, 95%CI 0.89–1.20). Moreover, some other studies reported a significant association between passive smoking and the risk of breast cancer , , .
Regarding the age at first full-term pregnancy, our results were in the same line with previous studies, which indicated the increased risk of breast cancer in individuals with late first full-term pregnancy (at age 30 or older) , . For nulliparity conditions, our study showed an inverse association with breast cancer development, which was in contrast with several previous reports , .
Numerous investigators have studied the association of induced abortion and the risk of breast cancer throughout the world. One of the oldest studies titled “Induced abortion as a cancer risk factor” discussed the induced abortion as a breast cancer risk factor . Similarly, some meta-analysis also reported the same conclusions , . In this regard, our meta-analysis found that induced abortion was significantly associated with the risk of breast cancer in Iranian women. Besides, the study of Deng et al. demonstrated that induced abortion might be related to the risk of breast cancer in parous women (OR: 1.11, 95%CI 1.02–1.20, p = 0.01), but not in nulliparous women (OR :1.02, 95%CI 0.86–1.21, p = 0.85). In contrast, several studies arrived at contradictory conclusions , .
The meta-analysis findings showed a significant association between sweet foods consumption and the risk of breast cancer. Although we did not find a specific systematic review in this regard, several epidemiological studies in different regions reported the association of sweet foods consumption and risk of breast cancer , , , . For example, Tavani et al. performed a comprehensive case-control study in Italy and found a direct relationship between sweet foods consumption and risk of breast cancer development . In fact, excessive sweets intake with a high glycemic index may cause insulin resistance as well as insulin-related growth factors as promoters of breast carcinogenesis. Moreover, ovarian steroid secretion, including estrogens and androgens, might be stimulated by insulin. Altogether, these processes end up at an increased risk of breast cancer , .
Previous studies have investigated the relationships of p53 codon 72 polymorphisms and the risk of breast cancer development in different regions . In this investigation, we found that the genotype Arg/Arg is associated with the development of breast cancer, which was inconsistent with the study of Al-Qasem et al. among Saudi women, and in contrast with meta-analysis carried out by Ma et al. and Hou et al. studies , .
Menarche age does not precisely match with the breast cancer onset. However, they are significantly correlated . This meta-analysis demonstrated an inverse association between late menarche age and risk of breast cancer (OR: 0.58, 95%CI 0.32–0.83). Our findings were in the same direction with two other meta-analyses carried out by Li et al.  and Collaborative Group on Hormonal Factors in Breast Cancer .
We found that longer breastfeeding duration (13–24 months) plays a protective rule against breast cancer development, inconsistent with numerous meta-analysis in various populations , , , . In this regard, according to one of the most comprehensive studies on “Breast cancer and breastfeeding” including 47 epidemiological studies in 30 countries, breast cancer development would be reduced by 42%, especially in developing countries because women in these countries usually have a long duration of breastfeeding throughout their lives . In contrast, short breastfeeding duration, which is usual among women in developed countries with small family size, would contribute to a higher risk of breast cancer development in such countries .
The updated report “Food, Nutrition, Physical Activity, and the Prevention of Cancer: A Global Perspective” in 2007, recommended physical activity as a protective factor against cancers, especially post-menopausal breast cancer . It was also recommended by the “American Cancer Society Guidelines on nutrition and physical activity for cancer prevention” . Our findings also support this hypothesis as a preventive factor for breast cancer development. In fact, physical activities affect the risk of cancer development through mechanisms such as metabolic, reproductive effects, hormonal, and immunity enhancement, etc. . The comprehensive study of Moore et al.  titled “Association of Leisure-Time Physical Activity with Risk of 26 Types of Cancer in 1.44 Million Adults” reported the significant association for high and low physical activity and lower risk of breast cancer (hazard ratio (HR): 0.9, 95%CI 0.87–0.93).
The association between vegetable intake and risk of breast cancer was always controversial. Our results suggest a protective effect of vegetable consumption on the risk of breast cancer. In the same direction, meta-analyses carried out by Liu et al., Woo et al., and Aune et al. indicated a significant association between various types of vegetables and dietary fiber consumption and risk of breast cancer development , , . In contrast, several systematic reviews and meta-analysis showed no significant relationships in this regard , , and some others were controversial regarding the types of vegetables and their combination intake with fruits as well as breast cancer types , .
According to the retrospective nature of the included studies, it is recommended to design some longitudinal cohort investigations in order to examine the fundamental role of these risk factors in breast cancer development.
Based on this systematic review and meta-analysis, factors including a family history of breast cancer, HRT, passive smokers, abortion, sweets consumption, and genotype Arg/Arg, play a significant role in the development of breast cancer. In contrast, late menarche, nulliparity, long breastfeeding duration, regular physical activity, and consumption of vegetables showed a significant inverse association with breast cancer occurrence.
Research funding: None.
Author contributions: ASH, RAN, ZSH, and KH designed the study protocol and wrote the manuscript. RAN performed the statistical analysis. ARA, DSH, ORT, ZA, LS, HM, NM, BZ, KK, BZ, and AHO contributed to the study screen, quality assessment, and made critical comments on the manuscript. All authors have read and approved the final manuscript.
Competing interests: The authors declare that they have no competing interests.
Informed consent: Not applicable.
Ethical approval: Not applicable. The protocol of this systematic review and meta-analysis was registered in the International Prospective Register of Systematic Reviews (PROSPERO) with the code CRD42019127382.
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