Background: This report provided the effect of 15 preventable factors on the risk of breast cancer incidence. Study design: A systematic review and meta-analysis. Methods: A detailed research was conducted on PubMed, Web of Science, and Scopus databases in January 2020. Reference lists were also screened. Prospective cohort studies addressing the associations between breast cancer and 15 factors were analyzed. Between-study heterogeneity was investigated using the χ2 , τ2 , and I2 statistics. The probability of publication bias was explored using the Begg and Egger tests and trim-and-fill analysis. Effect sizes were expressed as risk ratios (RRs) with 95% confidence intervals (CIs) using a random-effects model. Results: Based on the results, out of 147,083 identified studies, 197 were eligible, including 19,413,702 participants. The RRs (95% CI) of factors associated with breast cancer were as follows: cigarette smoking 1.07 (1.05, 1.09); alcohol drinking 1.10 (1.07, 1.12); sufficient physical activity 0.90 (0.86, 0.95); overweight/obesity in premenopausal 0.92 (0.82, 1.03) and postmenopausal 1.18 (1.13, 1.24); nulliparity 1.16 (1.03, 1.31); late pregnancy 1.37 (1.25, 1.50); breastfeeding 0.87 (0.81, 0.93); ever using oral contraceptive 1.00 (0.96, 1.05); ever using estrogen 1.13 (1.04, 1.23); ever using progesterone 1.02 (0.84, 1.24); ever using estrogen/progesterone 1.60 (1.42, 1.80); ever taking hormone replacement therapy 1.26 (1.20, 1.32); red meat consumption 1.05 (1.00, 1.11); fruit/vegetable consumption 0.87 (0.83, 0.90); and history of radiation therapy, based on single study 1.31 (0.87, 1.98). Conclusions: This meta-analysis provided a clear picture of several factors associated with the development of breast cancer. Moreover, the useful information in this study may be utilized for ranking and prioritizing preventable risk factors to implement effective prevention programs.

Due to the increasing use of virtual networks and, on the other hand, ambiguities towards the positive or negative effects of these networks on the level of social interaction and social capital of users. Objectives: This study aims to determine the relationship between the motivation to use virtual mobile networks and social capital among students of Hamadan University of Medical Sciences. Materials and Methods: This was a cross-sectional study carried out on 350 students of Hamadan University of Medical Sciences in 2017. The participants were selected by a stratified sampling method with the proportional assignment. Data gathering tools included the demographic form and questionnaires of motivation to use virtual networks and social capital. The subjects completed the tools through the self-reporting. The obtained data were analyzed by the Pearson correlation test and linear regression in SPSS V. 24. Results: Most students (42.6%) used virtual networks 3-5 hours per day. Entertainment and pastime were the most reported reasons and motivations for using the virtual networks among students with 59% and 58.8% of the maximum achievable score, respectively. There was a positive and significant correlation between bonding and bridging social capital and the rate of virtual network usage. Among the related factors studied, gender, nativeness, self-disclosure, immersion in the media, pastime, information search, individual status, maintaining relationships, entertainment, and linking social capital have significant roles in explaining the variance of the motivation to use the virtual network among the students (P<0.05). Conclusion: Further research is needed in this area because students increasingly use virtual networks and they are unfamiliar with other aspects of these networks affecting their health and life. University counseling centers should provide the required training based on the facts for the students about the positive and negative consequences of using virtual networks.