Skip to main content

The association between the multiple birth and breast cancer incidence: an update of a systematic review and meta-analysis from 1983 to 2022

Abstract

Background

It has been assumed that perinatal factors such as multiple pregnancies may affect subsequent breast cancer risk in the mother. Considering the inconsistencies in the results of case-control and cohort studies published in the world, this meta-analysis was conducted in order to determine the exact association between multiple pregnancies (twins or more) and the breast cancer incidence.

Methods

This study was performed as a meta-analysis based on PRISMA guidelines by searching the international databases of PubMed (Medline), Scopus, and Web of Science as well as by screening selected articles based on their subject, abstract and full text. The search time was from January 1983 to November 2022. Then the NOS checklist was used to evaluate the quality of the final selected articles. The indicators considered for the meta-analysis included the odds ratio (OR) and the risk ratio (RR) along with the confidence interval reported in the selected primary studies. The desired analyzes were performed with STATA software version 17 to be reported.

Results

In this meta-analysis, 19 studies were finally selected for analysis, which fully met the inclusion criteria. Of these, 11 were case-control studies and 8 were cohort ones. Their sample size was 263,956 women (48,696 with breast cancer and 215,260 healthy) and 1,658,378 (63,328 twin or multiple pregnancies and 1,595,050 singleton pregnancies), respectively. After combining the results of cohort and case-control studies, the effect of multiple pregnancies on the breast cancer incidence was equal to 1.01 (95% CI: 0.89–1.14; I2: 44.88%, P: 0.06) and 0.89 (95% CI: 0.83–0.95; I2: 41.73%, P: 0.07), respectively.

Conclusion

The present meta-analysis results showed, in general, multiple pregnancies were one of the preventive factors of breast cancer.

Peer Review reports

Introduction

The growing breast cancer prevalence in women is one of the most important problems of humanity in today’s society. In 2020, 2.3 million women were diagnosed with breast cancer and 685,000 died because of its worldwide [1,2,3]. By the end of 2020, in the last 5 years, 7.8 million women were diagnosed with breast cancer the most common cancer in the world. About 1 in 8 American women (about 13%) develops invasive breast cancer in her lifetime [3]. In 2021, 281,550 new cases of invasive breast cancer and 49,290 new cases of noninvasive breast cancer were estimated in women in the United States [4, 5]. Breast cancer most often begins with cells in the milk-producing ducts (invasive ductal carcinoma). Also, it may begin in the glandular tissue called lobules (invasive lobular carcinoma) or in other cells or tissue within the breast. Results of previous studies showed change of hormonal status, lifestyle and environmental factors that may increase your risk of breast cancer. But it’s not clear why some people who have no risk factors develop cancer, yet other people with risk factors never do. It’s likely that breast cancer is caused by a complex interaction of your genetic makeup and your environment [6, 7]. Many factors are effective in causing breast cancer malignancies, the most important of which are changes in pregnancy patterns and the obesity prevalence [8,9,10]. In general, these factors include diet, alcohol consumption, body mass index, estrogen consumption, smoking, physical activity, maternal age at the first delivery, menopause, breastfeeding rate, genetic characteristics and family history, race and age at onset of menstruation [11,12,13]. Epidemiological studies [14] show pregnancy can have different and dual effects on developing tumors as well as increasing the breast cancer risk. On the one hand, after giving birth and in the short term due to cell growth stimulation in the stages of transformation and malignancy, the infection chance increases, and on the other hand, in the long term, we see a decrease in the breast cancer prevalence in mothers because the differentiation of stem cells prone to tumor formation in the breast is intensified following hormonal changes, and as a result, the possibility of malignancy decreases [15, 16]. Furthermore, long-term breastfeeding is associated with a decrease in the breast cancer risk due to the delay in regular ovulation [17]. The results of previous studies have shown there is no clear association between breast cancer and the number of births, age at the time of the last pregnancy, use of birth control pills and hormone replacement therapy in postmenopausal women [18]. In a case-control study, Morabia et al. [19] investigated the breast cancer prevalence and reproductive factors related to it in seven countries (Australia, China, Colombia, Germany, Israel, Philippines and Thailand). The results showed the cancer prevalence was related to early menstruation, late menopause, long duration of pregnancy and more delay in the time of the first delivery. The results of past studies have been completely contradictory. Kim et al. (2012) conducted a meta-analysis to investigate the association between twin births and breast cancer [20]. Although they observed a reduction in the breast cancer risk in the analysis of cohort studies, in general, this association was not statistically significant. This study had some basic limitations. For example, the qualitative evaluation of the selected articles (as the main part of meta-analysis studies) was not properly performed, and subgroup analyzes and meta-regression were not conducted to identify the main heterogeneity sources by identifying confounding variables and controlling their effect. On the other hand, many studies have been published since 2007, which can help in obtaining more accurate information. Therefore, the present meta-analysis aimed to determine the association between multiple births and breast cancer occurrence with the hope that the study results can be effective in health and care programs or interventions for pregnant women and pregnancy outcomes.

Methods

The present study was a systematic review and meta-analysis based on the structure of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) [21]. The search in the present meta-analysis was performed using the main keywords and their synonyms found by searching in Mesh, Thesauruses, and EMTREE. The desired databases in this study included PubMed (Medline), Scopus, and Web of Science. The present meta-analysis was carried out in order to update the study of Kim, Hye Sook et al., published in 2012 [20]. So, the search time was from January 1983 to November 2022. In order to search, keywords related to twin birth were combined with keywords related to breast cancer and searched in the desired databases. Researchers performed a search of these databases, with hand searching through the reference lists and grey literature. The search protocol, developed based on three main roots of “twin birth”, “multiple birth”, and “breast cancer”. All related components of twin or multiple birth including [(Pregnancies AND Twin), “Twin Pregnancies”, “Twin Pregnancy”, (Pregnancy AND Multiple), “Multiple Pregnancy”, “Multiple Pregnancies”, and (Pregnancies AND Multiple)] and related components of breast cancer including [“Breast Neoplasms”, “Breast Carcinoma”, “Cancer of Breast”, “Breast Malignant Tumor”, “Malignant Tumor of Breast”, “Breast Neoplasm”, “Breast Tumors”, “Breast Cancer”, and “Mammary Cancer”] added to searched queries based on scientific Mesh terms, EMTREE or the key words. The results limited to human subjects and refined for women with breast cancer. Reference Manager bibliographic software was used to manage searched citations. Duplicate entries were searched by considering the title of the published papers, authors, the year of publication, and specifications of the source’s types. In questionable records, the texts were compared. Authors reviewed the primary search results, and after reviewing each article by title and available abstract, some of the articles were eliminated. The evaluation of the papers under consideration was based on the inclusion and exclusion criteria by the researchers, separately (PV, MCH, and YM).

Inclusion and exclusion criteria

The inclusion criteria were defined based on the PECOT structure [22]. This structure is proper when the objective studies were case-control and cohort. In other word, when the objective of meta-analysis was determined association without any interventions, this structure was used for doing all sections of meta-analysis. The PECOT structure is a helpful approach for summarizing research questions that explore the effect of exposure and is consisted of Population, Exposure (without any intervention), Comparison, Outcomes and Type of studies (22). All case-control and cohort studies which determined the association between the birth of multiple and twin babies and the occurrence of breast cancer met the necessary conditions to enter this study. Other studies with other characteristics and outcomes were excluded from the study. The steps of selecting and screening articles in this meta-analysis were independently performed by two authors (PV and MCH).

Data extraction

After the screening stage based on the inclusion and exclusion criteria, an information extraction checklist containing information related to studies (including the names of authors, publication year, type of studies, country and number of samples), information related to the desired exposure (singleton, twin or multiple pregnancy), information related to the target population (mothers’ age and body mass index, and the type of population examined in the studies) and information related to the outcome (the desired effect size in the studies along with the 95% confidence interval) was designed, based on which information was extracted from the final articles.

Quality evaluation of articles

Two of the authors (YM and PV) conducted a qualitative evaluation of the studies on the basis of the Newcastle-Ottawa Quality Assessment Scale (NOS) checklist [23]. This checklist was designed to evaluate the quality of analytical observational studies like case-control and cohort studies. This tool examines each research with eight items in three groups, including how to select study samples, how to compare and analyze study groups, and how to measure and analyze the desired outcome. Each of these items is given a score of one if it is observed in the studies, and the maximum score for each study is 9 points. In case of discrepancies in the score assigned to the published articles, the discussion method and the third researcher were applied to reach an agreement.

Statistical analysis

In this meta-analysis, two types of case-control and cohort studies were analyzed. The indicators considered for the analysis included the odds ratio (OR) and the risk ratio (RR) along with the confidence interval reported in the selected primary studies. Since these indicators are right-skewed, they should be converted to normal distribution for analysis, and for this reason, the logarithm of these indicators was included in the analysis. The desired model for analysis was random effects or fixed effects (inverse variance). The degree and percentage of heterogeneity in this study were expressed using I square and Cochrane’s Q index [24]. According to the criteria reported by Cochrane [24], 0 to 25% indicates no heterogeneity, 25 to 50% low heterogeneity, 50 to 75% high but acceptable heterogeneity, and 75 to 100% high and unacceptable heterogeneity. In order to evaluate the publication bias, Egger’s test [25] and funnel plot were used. Subgroup analyzes were performed based on type of birth (twin or multiple pregnancies) and different continents.

Results

After completing the search, 558 studies were retrieved in PubMed, 893 in Scopus and 330 in Web of Science. A total of 1781 studies were included in the review, of which 681 were duplicated and in the first step, 1100 studies were entered into the screening stage based on the title. After removing irrelevant studies in this stage, 190 articles were entered into the screening stage based on the abstract. In this step, 99 studies were excluded and in the next step, i.e., screening based on the full text, 91 studies were evaluated (Fig. 1). In this meta-analysis, 19 studies which fully met the inclusion criteria, were finally selected for analysis. Of these, 11 were case-control studies and 8 were cohort ones. Their sample size was 263,956 women (48,696 with breast cancer and 215,260 healthy) and 1,658,378 (63,328 twin or multiple pregnancies and 1,595,050 singleton pregnancies), respectively (Table 1).

Fig. 1
figure 1

Flow diagram for related article numbers which included in meta-analysis

Table 1 The characteristics of studies (case-control and cohort) on multiple births and maternal breast cancer risk

In the first step of meta-analysis, the results of cohort studies were evaluated and reviewed. From the 8 examined cohort studies, 10 effect sizes including the risk ratio were extracted. The highest and lowest reported associations belonged to the study of Wyshak et al. and Ji et al., respectively. After combining the extracted results, the pooled risk ratio was equal to 1.01 (RR: 1.01; 95% CI: 0.89–1.14; I2: 44.88%, P: 0.06) (Fig. 2).

Fig. 2
figure 2

Meta-analysis of the association between multiple pregnancy and maternal risk of breast cancer by combining cohort studies from 1983 to 2022

Subgroup analyzes were performed to determine the association between multiple pregnancies and breast cancer incidence based on the different continents and the type of multiple pregnancies (twins or more) and the results have been reported in Table 2. The results of subgroup analyze after combining cohort studies showed in the American continent, women with multiple pregnancies were 1.27 times more likely to develop breast cancer (RR: 1.27; 95% CI: 0.86–1.88; I2: 62.41%, P: 0.10) while this risk was 1.11 in European women with multiple pregnancies (RR: 1.11; % 95 CI: 1.01–1.34; I2: 77.74%, P: 0.18) (Table 2). Subgroup analysis was also performed based on the type of multiple pregnancies including twins or multiples. The meaning of multiple births was the category of studies which did not specify the exact exposure mode. For example, they did not specify whether the pregnancies were twins or more than twins, like triplets or more. Therefore, they were placed in the multiple birth category. The meta-analysis results showed the association between twin pregnancy and breast cancer incidence was equal to 1.39 (RR: 1.39; 95% CI: 1.14–1.69; I2: 0.00%, P: 0.38) while for multiple pregnancies, this risk was equal to was 0.92 (RR: 0.92; 95% CI: 0.84–1.01; I2: 12.88%, P: 0.16) (Table 2).

Table 2 Subgroup analysis of the association between multiple pregnancy and maternal risk of breast cancer by combining cohort/ case-control studies from 1983 to 2022 based on type of birth and continents

In the second step of meta-analysis, the results of case-control studies were evaluated. Of the 11 selected studies, the highest and lowest odds ratios were related to the studies of Muphy et al. and Innes et al., respectively. After combining these studies, the pooled OR was equal to 0.89 (OR: 0.89; 95% CI: 0.83–0.95; I2: 41.73%, P: 0.07) (Figs. 3, 4). Subgroup analyzes were performed to determine the association between multiple pregnancies and breast cancer occurrence based on the different continents and the type of multiple pregnancies (twins or more) and the results have been reported in Table 2. The results of subgroup analyze after combining case-control studies showed in the Americas, women with multiple pregnancies were 1.03 times more likely to develop breast cancer (OR: 1.03; 95% CI: 0.89–1.18; I2: 0.00). %, P: 0.79) while in European countries, this risk was lower and equal to 0.89 (OR: 0.89; % 95 CI: 0.79–0.92; I2: 59.51%, P: 0.04) (Table 2). Subgroup analysis based on the type of multiple pregnancies including twins or multiples showed the association between twin pregnancy and the chance of breast cancer was equal to 0.90 (RR: 0.90; 95% CI: 0.82–0.99; I2: 52.22%, P: 0.03) while for multiple pregnancies, this risk was equal to 0.87 (RR: 0.87; % 95 CI: 0.79–0.97; I2: 0.00%, P: 0.66) (Table 2).

Fig. 3
figure 3

The funnel and Galbraith plots of the association between multiple pregnancy and maternal risk of breast cancer by combining cohort and case-control studies from 1983 to 2022

Fig. 4
figure 4

Meta-analysis of the association between multiple pregnancy and maternal risk of breast cancer by combining case-control studies from 1983 to 2022

Discussion

The main goal of this meta-analysis was to determine the association between multiple births and the incidence of breast cancer in women. In this meta-analysis, two types of case-control and cohort studies were examined and analyzed. Due to the fact that these two types of studies were different in terms of the nature and method and reporting the effect sizes, we decided to separately report the combination of the results of these two types of studies to determine the association. On the other hand, because breast cancer was not rare in women with multiple births according to the results of previous studies, combining the results of these two types of studies was not correct in terms of methodology and increased the possibility of reporting an unrealistic effect size [26,27,28]. The effect size is reported in case-control studies as the odds ratio (OR) and in cohort ones as the risk ratio (RR).

The combination of these two indicators is possible only if the desired outcome frequency in the studied population is less than 0.05 or the desired outcome is rare [29, 30]. However, in the present meta-analysis and in the studies which examined the association between multiple births and breast cancer, the prevalence of breast cancer in women with multiple births was higher than 0.05 [31,32,33]. In the combination of cohort studies, the results showed there was no significant association between multiple births and the occurrence of breast cancer, but the combination of the results of case-control studies showed multiple births (twins or more) significantly reduced the chance of developing breast cancer. This issue can be caused by differences and changes related to pregnancy, which occur in the final pregnancy stages. Although high levels of estrogen, IGF-1 and other cell division stimulators in pregnancy can lead to the stimulation of breast cell proliferation and are a precursor to the initiation and progression towards breast cancer, high levels of HCG and alpha-phytoprotein in pregnancy can have a protective role against breast cancer by increasing apoptosis, inhibiting cell division and enhancing differentiation, and this protective role is often greater in the first pregnancy [34,35,36,37].

In addition, according to the results of the study of Janssens, Jaak Ph et al., the HCG hormone has an anti-proliferative role in the laboratory environment on cancer cells [38] and its levels in twin pregnancies are about two times more than that of singleton pregnancies. This can be a justification for the present meta-analysis results [39,40,41,42]. In order to confirm these explanations, according to the results of some studies, the levels of AFP produced in the liver and a peptide which inhibits mitogen-activated protein kinase (MAPK or MAP kinase), are higher in multiple pregnancies than in singleton pregnancies. This substance has anti-hormonal effects and can inhibit estrogen-sensitive cells by inactivating the mentioned kinase, neutralizing the effect of estrogen on them and preventing the proliferation of breast cells [41, 43,44,45].

An increase in the levels of estradiol, testosterone, progesterone, human chorionic gonadotropin and alpha-fetoprotein hormones has been observed and proven in pregnancy, and it seems the increase in human chorionic gonadotropin and fetoprotein progesterone can have a protective effect against breast cancer due to its anti-estrogenic properties effective on the breast tissue, but the association between the higher incidence of breast cancer and the birth of twins or multiples was first established in the 1980s [46]. The physiology of twin and singleton pregnancy differs because higher levels of estradiol and testosterone are observed during twin pregnancy and higher concentrations of follicle-stimulating hormone and sex hormone-binding globulin are seen after twin pregnancy [47]. These changes may affect the incidence of hormone-responsive cancers such as breast, endometrial, and ovarian cancers [48, 49]. Another important point in the current meta-analysis was the existence of a small association between multiple births and breast cancer, which was not statistically significant. In addition, preliminary studies have also shown a significant association in this regard [31, 46, 50], the reason for which can be the higher serum levels of estrogen in multiple pregnancies than in singleton pregnancies. Estrogen stimulates the division of mammary cells and increases hormonal activities such as cytochrome p450 which itself activates metabolic pathways and in this way, it can increase gene mutations and aneuploidy [51,52,53].

In a similar meta-analysis published by Kim, Hye Sook et al., analyzing 17 articles published from 1983 to 2007, different results were obtained [20]. After combining the results, Kim, Hye Sook et al. showed twin birth was not associated with a reduced incidence of breast cancer. However, subgroup analyzes for cohort studies in this research showed the breast cancer risk tended to decrease in women with a history of multiple births. In the mentioned meta-analysis, the association between multiple births, twin births and breast cancer was not separately stated, but in our meta-analysis, in addition to the association between multiple births and breast cancer, the association between twin births and breast cancer was separately investigated in subgroup analyses. Also, another advantage of the current study was to perform subgroup analyzes to separately determine the association between multiple births, twin births and breast cancer in different continents. Also, different guidelines in the field of breast cancer need to update the information, and the present meta-analysis results can be suitable for updating the information of these guidelines.

One of the current meta-analysis limitations was the lack of subgroup analyzes based on important variables such as receiving treatment, the type of treatment, time and method of cancer diagnosis, body mass index and age which were not examined due to non-reporting or incomplete reporting in the initial studies.

Conclusion

The present meta-analysis results showed, in general, multiple pregnancies were one of the preventive factors of breast cancer, but information on twin pregnancies was conflicting. Therefore, it is necessary to conduct more cohort and case-control studies with appropriate sample sizes, taking into account important and effective factors such as genetics, age, body mass index, receiving treatment and type of treatment.

Data Availability

and other materials.

Data and materials are available within the supplementary materials, and further information can be made available by request to the corresponding author.

Abbreviations

CI:

Confidence Interval

OR:

Odds Ratio

RR:

Risk Ratio/Relative Risk

I2 :

I Square

NOS:

Newcastle Ottawa Scale

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

References

  1. Koroltchouk V, Stanley K, Stjernswärd J. The control of breast cancer a World Health Organization perspective. Cancer. 1990;65(12):2803–10.

    Article  CAS  PubMed  Google Scholar 

  2. Wilkinson L, Gathani T. Understanding breast cancer as a global health concern. Br J Radiol. 2022;95(1130):20211033.

    Article  PubMed  Google Scholar 

  3. Ferlay J, Colombet M, Soerjomataram I, Parkin DM, Piñeros M, Znaor A, et al. Cancer statistics for the year 2020: an overview. Int J Cancer. 2021;149(4):778–89.

    Article  CAS  Google Scholar 

  4. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2018;68(6):394–424.

    Article  Google Scholar 

  5. Ferlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Piñeros M, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941–53.

    Article  CAS  PubMed  Google Scholar 

  6. Samadder NJ, Giridhar KV, Baffy N, Riegert-Johnson D, Couch FJ, editors. Hereditary cancer syndromes—A primer on diagnosis and management: Part 1: Breast-ovarian cancer syndromes. Mayo Clinic proceedings; 2019: Elsevier.

  7. Gilman EA, Pruthi S, Hofstatter EW, Mussallem DM, editors. Preventing breast cancer through identification and pharmacologic management of high-risk patients. Mayo Clinic proceedings; 2021: Elsevier.

  8. Gadi VK. Fetal microchimerism and cancer. Cancer Lett. 2009;276(1):8–13.

    Article  CAS  PubMed  Google Scholar 

  9. Gadi VK. Fetal microchimerism in breast from women with and without breast cancer. Breast Cancer Res Treat. 2010;121(1):241–4.

    Article  PubMed  Google Scholar 

  10. Gilmore GL, Haq B, Shadduck RK, Jasthy SL, Lister J. Fetal-maternal microchimerism in normal parous females and parous female cancer patients. Exp Hematol. 2008;36(9):1073–7.

    Article  CAS  PubMed  Google Scholar 

  11. Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast cancer—epidemiology, risk factors, classification, prognostic markers, and current treatment strategies—an updated review. Cancers. 2021;13(17):4287.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Kashyap D, Pal D, Sharma R, Garg VK, Goel N, Koundal D et al. Global increase in breast cancer incidence: risk factors and preventive measures. BioMed research international. 2022;2022.

  13. Momenimovahed Z, Salehiniya H. Epidemiological characteristics of and risk factors for breast cancer in the world. Breast Cancer: Targets and Therapy. 2019:151 – 64.

  14. Ruiz R, Herrero C, Strasser-Weippl K, Touya D, Louis JS, Bukowski A, et al. Epidemiology and pathophysiology of pregnancy-associated breast cancer: a review. The Breast. 2017;35:136–41.

    Article  PubMed  Google Scholar 

  15. Britt K, Ashworth A, Smalley M. Pregnancy and the risk of breast cancer. Endocrine-related Cancer. 2007;14(4):907–33.

    Article  CAS  PubMed  Google Scholar 

  16. Fatima N, Zaman M, Fatima T. Increased risk of breast cancer in multiparous and lactating women attending a breast care clinic in pakistan: a paradigm shift. Asian Pac J Cancer Prev. 2010;11(5):1219–23.

    PubMed  Google Scholar 

  17. DeVita VT, Lawrence TS, Rosenberg SA, DeVita. Hellman, and Rosenberg’s cancer: principles & practice of oncology. Lippincott Williams & Wilkins; 2008.

  18. Viladiu P, Izquierdo A, De Sanjosé S, Bosch F. A breast cancer case-control study in Girona, Spain. Endocrine, familial and lifestyle factors. Eur J Cancer Prev. 1996:329–35.

  19. Morabia A, Costanza M. Reproductive factors and incidence of breast cancer: an international ecological study. Sozial-und Präventivmedizin. 2000;45(6):247–57.

    Article  CAS  PubMed  Google Scholar 

  20. Kim HS, Woo OH, Park KH, Woo SU, Yang DS, Kim A-R, et al. The relationship between twin births and maternal risk of breast cancer: a meta-analysis. Breast Cancer Res Treat. 2012;131(2):671–7.

    Article  PubMed  Google Scholar 

  21. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Syst reviews. 2021;10(1):1–11.

    Article  Google Scholar 

  22. Guyatt GH, Rennie D. Users’ guides to the medical literature. JAMA. 1993;270(17):2096–7.

    Article  CAS  PubMed  Google Scholar 

  23. Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. Oxford; 2000.

  24. Tarsilla M. Cochrane handbook for systematic reviews of interventions. J Multidisciplinary Evaluation. 2010;6(14):142–8.

    Article  Google Scholar 

  25. Harbord RM, Egger M, Sterne JA. A modified test for small-study effects in meta‐analyses of controlled trials with binary endpoints. Stat Med. 2006;25(20):3443–57.

    Article  PubMed  Google Scholar 

  26. Mann C. Observational research methods. Research design II: cohort, cross sectional, and case-control studies. Emerg Med J. 2003;20(1):54–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Mann C. Observational research methods—cohort studies, cross sectional studies, and case–control studies. Afr J Emerg Med. 2012;2(1):38–46.

    Article  Google Scholar 

  28. Vansteelandt S. Estimating direct effects in cohort and case–control studies. Epidemiology. 2009:851–60.

  29. Mansori K, Moradi Y, Naderpour S, Rashti R, Moghaddam AB, Saed L, et al. Helicobacter pylori infection as a risk factor for diabetes: a meta-analysis of case-control studies. BMC Gastroenterol. 2020;20(1):1–14.

    Article  Google Scholar 

  30. Saed L, Varse F, Baradaran HR, Moradi Y, Khateri S, Friberg E, et al. The effect of diabetes on the risk of endometrial Cancer: an updated a systematic review and meta-analysis. BMC Cancer. 2019;19(1):1–10.

    Article  Google Scholar 

  31. Albrktsen G, Heuch I, Kvåle G. Multiple births, sex of children and subsequent breast-cancer risk for the mothers: a prospective study in Norway. Int J Cancer. 1995;60(3):341–4.

    Article  Google Scholar 

  32. Hsieh CC, Goldman M, Pavia M, Trichopoulos D, Ekbom A, Adami HO, et al. Breast cancer risk in mothers of multiple births. Int J Cancer. 1993;54(1):81–4.

    Article  CAS  PubMed  Google Scholar 

  33. Lambe M, Hsieh C-c, Tsaih S-w, Ekbom A, Adami H-O, Trichopoulos D. Maternal risk of breast cancer following multiple births: a nationwide study in Sweden. Cancer Causes Control. 1996;7(5):533–8.

    Article  CAS  PubMed  Google Scholar 

  34. Colditz GA, Rosner BA, Chen WY, Holmes MD, Hankinson SE. Risk factors for breast cancer according to estrogen and progesterone receptor status. J Natl Cancer Inst. 2004;96(3):218–28.

    Article  CAS  PubMed  Google Scholar 

  35. Innes KE, Byers TE. First pregnancy characteristics and subsequent breast cancer risk among young women. Int J Cancer. 2004;112(2):306–11.

    Article  CAS  PubMed  Google Scholar 

  36. Lagiou A, Lagiou P, Vassilarou DS, Stoikidou M, Trichopoulos D. Comparison of age at first full-term pregnancy between women with breast cancer and women with benign breast diseases. Int J Cancer. 2003;107(5):817–21.

    Article  CAS  PubMed  Google Scholar 

  37. Sellers TA, Potter JD, Severson RK, Bostick RM, Nelson CL, Kushi LH, et al. Difficulty becoming pregnant and family history as interactive risk factors for postmenopausal breast cancer: the Iowa Women’s Health Study. Cancer Causes Control. 1993;4(1):21–8.

    Article  CAS  PubMed  Google Scholar 

  38. Janssens JP, Russo J, Russo I, Michiels L, Donders G, Verjans M, et al. Human chorionic gonadotropin (hCG) and prevention of breast cancer. Mol Cell Endocrinol. 2007;269(1–2):93–8.

    Article  CAS  PubMed  Google Scholar 

  39. Cuckle H, Iles R, Chard T. Urinary β-core human chorionic gonadotrophin: a new approach to Down’s syndrome screening. Prenat Diagn. 1994;14(10):953–8.

    Article  CAS  PubMed  Google Scholar 

  40. Macintosh M, Iles R, Teisner B, Sharma K, Chard T, Grudzinskas J, et al. Maternal serum human chorionic gonadotrophin and pregnancy-associated plasma protein A, markers for fetal Down syndrome at 8–14 weeks. Prenat Diagn. 1994;14(3):203–8.

    Article  CAS  PubMed  Google Scholar 

  41. Van Lith J, Diagnosis DWPoP. First-trimester maternal serum human chorionic gonadotrophin as a marker for fetal chromosomal disorders. Prenat Diagn. 1992;12(6):495–504.

    Article  PubMed  Google Scholar 

  42. Wald N, Densem J. Maternal serum free α-human chorionic gonadotrophin levels in twin pregnancies: implications for screening for Down’s syndrome. Prenat Diagn. 1994;14(8):717–9.

    Article  CAS  PubMed  Google Scholar 

  43. Kato S, Endoh H, Masuhiro Y, Kitamoto T, Uchiyama S, Sasaki H, et al. Activation of the estrogen receptor through phosphorylation by mitogen-activated protein kinase. Science. 1995;270(5241):1491–4.

    Article  CAS  PubMed  Google Scholar 

  44. Mizejewski G, Vonnegut M, Jacobson H. Estradiol-activated alpha-fetoprotein suppresses the uterotropic response to estrogens. Proceedings of the National Academy of Sciences. 1983;80(9):2733-7.

  45. Zheng M-m, Hu Y-l, Zhang C-y, Ru T, Liu Q-l, Xu B-y, et al. Comparison of second-trimester maternal serum free-β-human chorionic gonadotropin and α-fetoprotein between normal singleton and twin pregnancies: a population-based study. Chin Med J. 2010;123(05):555–8.

    CAS  PubMed  Google Scholar 

  46. Wyshak G, Honeyman MS, Flannery JT, Beck AS. Cancer in mothers of dizygotic twins. J Natl Cancer Inst. 1983;70(4):593–9.

    CAS  PubMed  Google Scholar 

  47. Thomas H, Murphy M, Key T, Fentiman I, Allen D, Kinlen L. Pregnancy and menstrual hormone levels in mothers of twins compared to mothers of singletons. Ann Hum Biol. 1998;25(1):69–75.

    Article  CAS  PubMed  Google Scholar 

  48. Neale RE, Mineau G, Whiteman DC, Brownbill PA, Murphy MF. Childhood and adult cancer in twins: evidence from the Utah genealogy. Cancer Epidemiol Biomarkers Prev. 2005;14(5):1236–40.

    Article  PubMed  Google Scholar 

  49. Neale RE, Purdie DM, Murphy MF, Mineau GP, Bishop T, Whiteman DC. Twinning and the incidence of breast and gynecological cancers (United States). Cancer Causes Control. 2004;15(8):829–35.

    Article  PubMed  Google Scholar 

  50. Wohlfahrt J, Melbye M. Maternal risk of breast cancer and birth characteristics of offspring by time since birth. Epidemiology. 1999:441–4.

  51. Russo J, Lareef MH, Balogh G, Guo S, Russo IH. Estrogen and its metabolites are carcinogenic agents in human breast epithelial cells. J Steroid Biochem Mol Biol. 2003;87(1):1–25.

    Article  CAS  PubMed  Google Scholar 

  52. Russo J, Tahin Q, Lareef MH, Hu YF, Russo IH. Neoplastic transformation of human breast epithelial cells by estrogens and chemical carcinogens. Environ Mol Mutagen. 2002;39(2–3):254–63.

    Article  CAS  PubMed  Google Scholar 

  53. Santen R, Cavalieri E, Rogan E, Russo J, Guttenplan J, Ingle J, et al. Estrogen mediation of breast tumor formation involves estrogen receptor-dependent, as well as independent, genotoxic effects. Ann N Y Acad Sci. 2009;1155(1):132–40.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This article resulted from a master’s thesis approved and supported by the Kurdistan University of Medical Sciences, Sanandaj, Iran.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization, YM, MCH; methodology, YM.; software, YM., validation, YM, and MN; investigation, YM, and PV; resources YM; writing—original draft YM, MCH, MN, PV and SHSH; writing—review and editing, YM; visualization, YM, and SHSH; supervision, YM; project administration, YM. All authors have read and agreed to the published version of the manuscript. Yousef Moradi and Mojtaba Cheraghi are coreesponding authors, and Maziar Nikouei and Pedram Veisi are first authors.

Corresponding authors

Correspondence to Mojtaba Cheraghi or Yousef Moradi.

Ethics declarations

Ethics approval and consent to participate

Ethical issues (Including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, etc.) have been completely observed by the authors. This article extracted from medical student thesis with Ethical Code “IR.MUK.REC.1401.019”.

Competing interests

No conflict of interest for the present review.

Consent for publication

Not applicable.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Veisi, P., Nikouei, M., Cheraghi, M. et al. The association between the multiple birth and breast cancer incidence: an update of a systematic review and meta-analysis from 1983 to 2022. Arch Public Health 81, 76 (2023). https://doi.org/10.1186/s13690-023-01089-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13690-023-01089-0

Keywords