The an analysis of 15 micronutrients and breast cancer risk revealed that none of the micronutrients were associated with breast cancer risk after adjusting for covariates. In obese women, the risk of breast cancer was significantly reduced in the group that consumed vitamin C more than the recommended level  and vitamin B6 levels above the recommended level . In obese women, exceeding the recommended daily intake levels of vitamin C and vitamin B6 was associated with a lower risk of breast cancer. However, other micronutrients were not associated with breast cancer risk in these women.This study investigated the association between micronutrient intake and breast cancer risk in South Korean adult women. This association was stratified according to body mass index (BMI) categories. Data from the Korean Genome and Epidemiology Study (KoGES) and the Health Examinee Study were analyzed. Altogether, 63,337 individuals (aged ≥40 years) completed the baseline and first follow-up surveys; 40,432 women without a history of cancer at baseline were included in this study. The association between micronutrient intake and breast cancer was determined by estimating the hazard ratio (HR) and 95% confidence interval (CI) using the Cox proportional hazard regression model. A stratified analysis by BMI (<25 kg/m According to GLOBOCAN 2020, breast cancer is the most common cancer in women worldwide and ranks first in terms of cancer incidence and mortality in most countries  . The facThe incidence of breast cancer in women is rapidly increasing in Asian countries, including in South Korea . The rapIn South Korea, most studies on diet and cancer have focused on single nutrients or macronutrients, and most of the results were retrieved from small case-control studies, showing large variations in study results . In addiThe KoGES is a cohort study administered by the Korea Agency for Disease Control and Prevention for the purpose of identifying the genetic and environmental etiology of common chronic diseases in the Korean population to establish a scientific basis for personalized prevention. The KoGES consists of six subcohorts: three population-based cohorts and three gene-environment model studies . Of the n = 5843) were excluded  were included in the study. Women with missing information on the date of the baseline or follow-up survey and women with a daily energy intake of <500 kcal or >3500 kcal (n = 1161) were excluded, leaving 40,432 participants to be included in the analysis. This study was approved by the institutional review board of the Hanyang University College of Medicine, Republic of Korea .The baseline study population of the HEXA study included men and women aged ≥40 years who underwent a national health examination at 38 health examination centers from 2004 to 2013 . Of the excluded . A total, vitamin B2, niacin, vitamin C, zinc, vitamin B6, folate, vitamin E, and cholesterol) and four main nutrients  according to age group. Participants were divided into two groups: women who consumed more than the recommended daily nutritional intake and those who consumed up to the recommended daily nutritional intake. Cut-off values differ by age group  and by nutrients. For example, women aged 30–49 years consuming >700 mg of calcium fall into the recommended excess group (>recommended intake). Details on the recommended nutrient intake standards are presented in Dietary evaluation in the KoGES was based on the results of a standardized semi-quantitative food frequency questionnaire (FFQ). A total of 103 items were included in the FFQ, and micronutrient intake was estimated based on the FFQ. The detailed process for the development and validation of the FFQ is described elsewhere . The estThe incidence of breast cancer was defined as that among those who reported cancer-free at baseline survey and those who answered that they had been diagnosed with breast cancer by a doctor after the baseline survey at the follow-up survey. A total of 232 women reported that they had been diagnosed with breast cancer by a physician after the baseline survey.2, ≥25 kg/m2, or missing), history of benign breast tumors , age at menarche , menopausal status and age , breastfeeding , smoking , drinking , physical activity , and family history of breast cancer . BMI was calculated by dividing weight by the square of height in meters and was classified as ≥25 kg/m2 or <25 kg/m2.Participants’ information was retrieved from the data surveyed by well-trained staff using standardized questionnaires. Basic survey data included sociodemographic factors, medical history, family medical history, smoking, drinking, level of physical activity, and female reproductive history . The cov2) and non-obese women (BMI <25 kg/m2). All statistical analyses were performed using the SAS statistical software .The distribution of risk factors for breast cancer and micronutrient intake at baseline was compared between women who developed breast cancer and those who did not develop. Nutritional intake was presented as the mean and proportion of women who consumed more or less than the daily recommended intake. We investigated the association between micronutrient intake (more than the recommended level vs. less than the recommended level) and breast cancer risk by estimating hazard ratio (HR) and 95% confidence interval (CI) using the Cox proportional hazards regression model adjusted for the above-mentioned covariates. The follow-up period was calculated as the number of years between the baseline survey and the year of cancer diagnosis or the year of the follow-up survey. In addition, the association between micronutrient intake and breast cancer risk was estimated in obese (BMI ≥25 kg/mp = 0.012). The proportion of premenopausal women, women without breastfeeding experience, and women with physical activity for ≥150 min/week were higher in women who developed breast cancer than those in women without breast cancer (p < 0.05).Of the 40,432 cancer-free women who completed both the baseline and follow-up surveys, 232 were diagnosed with breast cancer. The mean follow-up period was 4.9 years (median: 4.0 years). p = 0.017). However, the average intake between the two groups was not significantly different.Among the micronutrients, iron intake above the recommended daily intake was associated with a reduced risk of breast cancer in the univariate analysis , iron intake more than the daily recommended level was associated with a reduced risk of breast cancer with a cHR of 0.69 (95% CI: 0.50–0.96) in a univariate analysis with a normal weight. In addition, the intake of vitamin C and vitamin B6 above the daily recommended value was associated with a reduced risk in obese women with aHR of 0.53 (95% CI: 0.30–0.92) and 0.45 (95% CI: 0.24–0.86), but a significant association was not observed in women with normal weight (In a separate analysis by obesity status (BMI ≥25 kg/ml weight . None ofThis study evaluated micronutrients in a large prospective cohort study in Korea and identified that the intake of vitamin C and vitamin B6 above the daily recommendation level was associated with a reduced risk of breast cancer in obese women. To the best of our knowledge, this is the first prospective study to investigate the association between micronutrients and breast cancer in Korea.Vitamin C has antioxidant activity and is found in vegetables and fruits. Its ability to reduce free radicals and oxidative damage to DNA are suggested mechanisms for reducing cancer risk ,25. DespFirst, the association between vitamin C and breast cancer was affected by the study design. A meta-analysis of case-control studies showed a protective effect of high-dose vitamin C on breast cancer risk; cohort studies did not show significant associations. In addition, the heterogeneity of the included studies was high ,32. SimiSecond, dietary vitamin C was associated with a decreased risk of breast cancer, but supplementation did not show this association ,32. HoweVitamin B6 is a B vitamin found in various sources, such as meat, fish, dairy, and root vegetables. Vitamin B6 is a one-carbon metabolism-related vitamin that affects carcinogenesis and development through its effect on DNA replication, repair, gene expression, DNA synthesis, and methylation, upholding DNA integrity, and regulating gene expression ,42. VitaPrevious studies on diet and cancer risk in Korea were mostly case-control studies . To the In this study, only two micronutrients showed a reduced association with breast cancer risk. Recent studies have identified that only a few nutrients or food items are associated with breast cancer ,53. Acco


However, the mechanism is still unclear. This study aimed to find an association between exposure to six criteria ambient air pollutants  exposure was associated with an increased risk of breast density with an OR equal to 1.04 (95CI: 1.01 to 1.07). Furthermore, CO level was associated with a decreasing breast density . None of the other pollutants were associated with breast density.The final analysis in 791 eligible women showed that low and high breast density was detected in 34.8 and 62.2 of participants, respectively. Logistic regression analysis after considering all possible confounding factors represented that an increase in each unit of NO2, as a marker of traffic-related air pollution. Furthermore, CO concentration was associated with a lower MBD, while other criteria air pollutants were not related to MBD. Further studies are needed to evaluate the association between ambient air pollutants with MBD.Higher MBD was associated with an increased level of NOhttps://doi.org/10.1265/ehpm.22-00027.The online version contains supplementary material available at  Air pollution is one of the major public health challenges in many parts of the world and in large cities. Ambient air pollution is a mixture of different pollutants originating from natural and anthropogenic sources and the International Agency for Research on Cancer (IARC) classified it as Group 1 carcinogenic to humans –5.Breast cancer is one of the worldwide leading causes of mortality and morbidity, and according to a report of GLOBOCAN in 2018 accounts for more than 11.6 of all female cancers; while the disease burden of breast cancer shows an increasing trend in some populations [Ecologic studies suggest that breast cancer risk is elevated in urban areas with high levels of air pollution compared to rural areas , 8. Air 2 had a “moderate level of evidence” and that PM2.5 and PM10 have an “inadequate level of evidence” for supporting their association with breast cancer risk. Also, the biological mechanism of the effects of air pollutants on breast cancer still remains unknown [A systematic review and meta-analysis in 2021 investigated whether high levels of air pollution exposure were related to increased breast cancer risk . This st unknown .Mammographic breast density (MBD) is one of the strongest predictors and biomarkers for breast cancer . Limited2), Sulfur dioxide (SO2), Carbon monoxide (CO), Ozone (O3), and Particulate matter (PM) 2.5, 10) and MBD in women living in Tehran, Iran.Tehran the capital of Iran is a megacity with about 10 million residents and air pollution is a major environmental challenge in this city. Tehran with an altitude of 1000–1800 meters above the mean sea level is located in a valley and is surrounded on the north, northwest, east, and southeast by medium-high to high Alborz mountain ranges. The climate is semi-arid with a lack of wind and low annual precipitation. Tehran’s geographical and climate situation causes trapping air pollution within the city, especially during winter. The people of Tehran are exposed to high levels of ambient air pollution, to the point where government and non-government offices are sometimes closed due to the severity of air pollution , 17. TheThis study was designed as a cross-sectional study; participants were selected from women attending two university hospitals affiliated to Tehran University of Medical Sciences, Tehran, Iran, for screening mammography from 2019 to 2021. The study was approved by the ethics committee of Tehran University of Medical Sciences (IR.TUMS.VCR.REC.1398.897), and all participants have signed informed consent. All methods have been performed in accordance with the relevant principles of the Declaration of Helsinki.Criteria for inclusion in the study were at least 3 years of residency in the capital city of Iran (Tehran) and having the ability to fill questionnaires. Exclusion criteria included suspicion for malignancy in the current mammography and an imprecise address.Participants were asked to fill out a questionnaire that captured demographic information, self-reported age, weight, height, reproductive history, menopause status, smoking history (active and passive), history of oral contraceptive (OCP) use, current use of hormone replacement therapy, and familial history of breast and ovarian cancer. All women who either had a current or previous history of active and passive (secondhand) smoking were defined as having a positive exposure to smoke. Menopause was defined as cessation of the menstrual period at least one year sooner; women were stratified into premenopausal and postmenopausal status. Furthermore, we gathered information about current aspirin and metformin use and consumption duration in each woman. Routine use of supplements including vitamin D, calcium, Vitamin E, Omega 3, and Evening Primrose oil were also recorded.One expert radiologist reported the breast density in each center. In order to evaluate the agreement between the radiologists’ reports, the third independent radiologist was rated the mammographic breast density of the same cases. Radiologists rated MBD according to the American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) classification into four categories: almost entirely fatty (BI-RADS a), scattered areas of fibro glandular density (BI-RADS b), heterogeneously dense (BI-RADS c), and extremely dense (BI-RADS d) . We cateThe exact address of residence of the participants in the recent 3 years and the telephone number of that place were recorded. Also, in the employed women, the address of their place of work and the hours of their attendance to work were recorded.www.cdc.gov/epiinfo).For sample size calculation, since the association between MBD and air ambient pollutants, has been investigated in limited studies which had inconsistent results, we expected 40% exposure to high ambient air pollutants in low breast density with assumed odds ratio (OR) equal to 1.5. Therefore, we calculated that about 800 samples would be required to find any possible association between pollutants and MBD with a power of 80% and α = 0.05 by using the Epi Info website  approach.2.5, PM10, NO2, O3, SO2, and CO). At the time of this study in 2020, there were 22 monitoring stations in Tehran that belonged to the AQCC. Considering that the data of the AQCC stations are available on an hourly basis and are publicly available online and that these monitoring stations are spatially located in all districts of Tehran city, therefore we used the data obtained from air quality monitoring stations belonged to AQCC in this study. Air quality monitoring stations in Tehran city are measured ambient PM2.5 and PM10, NO2, O3, CO, and SO2 by using the beta-attenuation , chemiluminescence , UV-spectrophotometry , non-dispersive infrared absorption , and ultraviolet fluorescence  methods, respectively [Real-time hourly ambient air quality in Tehran city is monitored by fixed monitoring stations. In Tehran city, Air Quality Control Company (AQCC) affiliated with the Tehran Municipality is responsible for monitoring criteria air pollutants (PMectively .http://airnow.tehran.ir/home/DataArchive.aspx).Finally, hourly data of six outdoor criteria air pollutants for the 3-year residency of participants were obtained from the website of AQCC , Environmental Protection Agency (EPA), and the European Union –22. Due In the present study, first, the data of all monitoring stations were obtained and then hourly data coverage of each pollutant in each station during the three years was determined. Included monitoring stations were only stations with ≥75 completeness of the total hours during the study period , 22. TheCalculating the Z score for each hourly data at each station using the following equation:To determine the long-term exposure of each participant to ambient air pollutants, the exact address according to the area, place, street, and alley in each year was obtained. In working women, if the place of work and living were different, the area and time spent in that area were also considered. Then, according to the location of monitoring stations and the location of the study subject, three of the nearest included air quality monitoring stations were identified for each participant, and using the average annual data and IDW method, the 3-year annual mean of exposure was estimated as long-term exposure for each study subject.Cohen’s kappa (κ) was run to determine if there was an agreement between two radiologists on breast density in the reports of the same case. Data were presented with mean ± standard deviation (SD) for continuous and frequency (percentage) for categorical variables. The ANOVA, t-test, and chi-square test were used to compare variables between study groups in the univariable analysis step. A multiple logistic regression analysis was done between all pollutants criteria as independent variables with breast density as a dichotomous dependent variable (low = 0 and high = 1). Because the pollutants criteria had a high inter-correlation with each other and the multivariable regression could be affected by the collinearity problem, the number of independent variables was reduced in order to solve this problem. So, we ran two multivariable logistic regressions, non-stepwise and stepwise algorithms and the result of the stepwise algorithm was chosen as the final results. After that, another logistic regression analysis was done to evaluate whether the effects of pollutants on breast density were independent or affected by potential confounding variables. This analysis was done as three models. For the first one, only significant pollutants were considered in the model. In the second model, in addition to pollutants, medical  and demographic  variables were considered. In the last model, the history of medicine and supplement use  was added to the previous variables. In the logistic regression analysis, an OR with a 95% confidence interval (CI) was reported in addition to the p-value. All calculations were performed in IBM SPSS  and the charts were drawn with MS Excel . P-value < 0.05 was considered significant.The response rate of women to participate in this study was 98%. Based on inclusion criteria 813 women were screened in this study. We excluded participants who were suspicious for malignancy in the current mammography (n = 14), and who had written an incomplete address (n = 8); finally, 791 eligible women were recruited. The mean age was 50.14 ± 7.61 (38–80) years old. About half of the women (50.1) were premenopausal, and half of them were in menopause (49.9) at time of the recruitment in the study.There was almost perfect agreement between the radiologists’ report, κ = 0.979 . In the mammographies, low breast density was reported in 34.8 (n = 299) and high breast density in 62.2 (n = 492). Table In the first step, in a univariate analysis using a t-test, all six pollutants criteria were compared between low and high breast density. In this comparison, except for ambient air CO, which was on the borderline statistically significant , other variables were not significantly different between the two groups Fig. . Due to 2  and CO  had a significant relationship with breast density. Logistic regression analysis with stepwise algorithm and breast density as a dependent variable showed that an increase in each unit of NO2 (ppb) exposure was associated with an increased risk of breast density with an OR equal to 1.04 (95 CI: 1.01 to 1.07); and an OR equal to 1.47 (95CI: 1.10 to 1.97) for each 10 unit increase in NO2. Furthermore, CO level was associated with a decreasing risk of breast density in each 1 ppm . None of the other pollutants were associated with breast density  had independent effects on breast density.In order to evaluate whether the effects of pollutants on MBD are independent or disappear under the influences of confounding variables, two other multiple analyses were performed. In the first model, basic and reproductive factors , Smoking, history of OCP usage, parity, menopause, and history of breast disease) were entered into the model. In the second model, metformin and aspirin intake, vitamin D, and calcium consumption were also entered into the model. Table 2  and CO  with MBD was observed only in menopausal women in the same direction as stated. In premenopausal women, breast density was not associated with ambient air pollutants  and other women didn’t show any significant difference (data not shown in table).The present study has evaluated the precise impact of long-term exposure to six criteria ambient air pollutants on MBD in Iranian women for the first time. Actually, many known and unknown factors are involved in breast tissue changes and eventually in breast cancer and it’s not possible to control all confounding factors in a single context. By the way, based on the available evidence, we tried to evaluate the effects of six criteria ambient air pollutants on breast density considering the factors that seem to have an impact on MBD . To the best of our knowledge, there is no study with this broad level of assessment.2 and CO exposure had statistically significant impacts on MBD. We found that an increased level of NO2, as a marker of traffic-related air pollution [2 and PMx (PM2.5 & PM10) concentration were consistent with a recent systematic study and meta-analysis that found an increased risk of breast cancer with an increase in each 10 unit in NO2 exposure (Hazard ratio (HR) = 1.02, 95 CI = 1.01–1.04), while PM2.5 and PM10 revealed no statistically significant associations with breast cancer risk [Our results represented that outdoor air NOollution , is assocer risk . The res2.5, PM air2.5-10, PM10) influenced breast density [2, NOx) and MBD in a prospective cohort of women aged 50 and older. They found a reverse association between air NO2 level and MBD  with no interaction with menopause, smoking, or obesity [2.5 and O3 levels for the year preceding the mammogram date were included. They found that women with extreme breast density had higher mean PM2.5 and lower O3 exposure levels [Limited studies have evaluated the association between criteria ambient air pollutants and MBD with inconsistent results , 14, 16. density . Two othNumerous studies in line with our study have investigated the relationship between endocrine-disrupting chemicals (EDCs) and heavy metals with MBD , 26, 27.2 and CO with MBD was observed only in menopausal women in the same direction as stated and in premenopausal women, breast density was not associated with ambient air pollutants. These findings should confirm in a large population study, because the impact of environmental pollutants on breast cancer may be greater during several windows of susceptibility (WOS) in women’s life such as pregnancy, puberty, and the menopausal transition [In the present study, the relationship between ambient air NOansition . Therefo2 or NOX level and breast cancer [Consistent with the present study, a review study by White and colleagues that summarized eight case-control studies and nine cohort studies suggested little evidence to support an association between particulate matter and breast cancer risk. More consistent findings have reported a relation between NOt cancer .This study has provided an interesting finding on the reverse association between MBD and CO. Since we couldn’t find any studies that examine the association between MBD and CO and there is a positive correlation between MBD and breast cancer, we have mentioned studies that evaluated the effects of CO on breast cancer. Two recent studies evaluated the effect of CO on breast cancer had equivocal results. A Korean study reported that CO concentration was positively and significantly associated with breast cancer   and anotOur results show that some of the risk factors of breast cancer such as age, BMI, and smoking had the reverse association with breast density. These findings are debatable because the evidence showed breast density is a strong risk factor for breast cancer, independent of age and other risk factors, is highly heritable, and has the properties of a quantitative trait . TherefoBecause the probability of developing breast cancer increases with age, declining the prevalence of MBD that occurs with increasing age could seem a paradox. However, Pike and Colleagues’ model explained the rate of breast-tissue aging, rather than chronological age, is the relevant measure for describing the age-specific incidence of breast cancer . FinallyThe advantage of this study is, we considered all the possibly effective factors and known determinants of MBD, all of which are estrogen-related. As it was demonstrated in Table According to the findings of the mentioned studies and the high percentage of women who had taken metformin (11.5), aspirin (13.4), vitamin D (49.7), and calcium (44.4) in our study, it seems that without considering the use of these drugs, the results may not be expressed correctly. However, our findings showed that even by considering these factors, the results did not change.Our study had some limitations. The primary limitation is due to sampling type that the temporal link between the outcome and the exposure cannot be determined. Another point is that despite the high sample size, the generalizability of the study may be questionable. Due to the ultrasound device in our center was not able to assess the percent density of the breast, we couldn’t report the exact percentage of breast density as well as the cut-off point level. It is important to note that most of the sampling in this study coincided with the worldwide onset of the COVID-19 pandemic. Therefore, it is possible that the participants during this period were women at higher risk of breast cancer, who had been referred for screening despite the COVID-19 pandemic. In this study, since our sampling area was two public hospitals and women were homogenous from the view of socioeconomic status and the majority of them belong to low to middle SES, we didn’t collect information on socioeconomic status. Therefore, we assume that this factor was not a significant confounder in our study.Considering our results and other evidence, in highly air polluted areas, perhaps MBD monitoring as an available tool in each population, can help the prediction of future breast cancer occurrence. Further studies are necessary to find the prevalence of breast cancer in highly polluted geographic areas.2, as a marker of traffic-related air pollution. Moreover, air CO concentration was associated with a lower MBD, while other criteria air pollutants were not related to MBD. Further studies are needed to evaluate the association between ambient air pollutants especially CO level as well as other pollutants with MBD.In conclusion, higher MBD was associated with an increased level of NO


High-fat diets have been identified as a major cause of obesity and a potential risk factor for breast cancer. Fat tissue, also known as adipose tissue, produces an excess of estrogen, which has been linked to an increased risk of breast cancer. Determining the impact of HFDs in the development and progression of breast cancer is essential, as it will enable us to identify the role of dietary modification in preventing and managing the disease.The impact of a high-fat diet (HFD) on the development of breast cancer in humans has yet to be fully explained, as very few human studies are available to effectively analyze the effect fatty food has on breast cancer development. This meta-analysis, therefore, seeks to determine the strength of association, if any, between HFD and an increased risk of breast cancer development. This research will help inform good eating habits, potentially reducing the disease's incidence and outcome.2 = 93.38%, p0.05). Changes in dietary fat consumption may thus help mitigate some of the unfavorable consequences of breast cancer and survival. Even if further research is needed to support this assertion, the findings are compelling enough to advocate for low-fat, healthy diets to avoid breast cancer.This meta-analysis examined eight (8) papers from various nations examining the effect of a high-fat diet as a risk factor for breast cancer development between 2010 and 2020. The study employed the multivariable-adjusted hazard ratio (H.R.), odds ratio (OR), or relative risk (R.R.) from the studies. Breast cancer cases were histologically and radiologically confirmed in the studies evaluated, and validated food frequency questionnaires were used to assess their dietary patterns. This metanalysis study found a substantial link between a high-fat diet and an increased risk of breast cancer, with statistically significant results (I Breast cancer is the second most common cancer in women worldwide, next to skin cancers, with over 2 million cases observed in 2018 .Several factors have been identified to increase the risk of breast cancer development, including genetics, family and personal histories, age, sex, race, lifestyle, and dietary factors. Most breast cancers are found in women aged 50 and above -6. Of thHigh dietary fat, which is a major cause of obesity, has been proposed as a risk factor for breast cancer -8. ObesiMethodologyA PubMed search for the terms "risk factors for breast cancer" and "high-fat diet" produced 49 results. "High-fat diet," "diet," "risk factors," and "breast neoplasm" or "breast cancer" were the MeSH search phrases. After filters were applied, the study's most relevant articles were included based on our eligibility criteria.Eligibility criteria Randomized clinical controlled trials, cohort studies, and case-control studies between 2010 and 2020, which focused on high-fat diet and breast cancer risk were reviewed. Systematic review articles and meta-analyses were excluded. Articles, abstracts, and titles irrelevant to this paper's aim were excluded. Of the 49 articles identified, eight were included in this meta-analysis based on the exclusion and inclusion criteria as listed in Table Figure Data analysis methodThe multivariable-adjusted hazard ratio (H.R.), odds ratio (O.R.), or relative risk (R.R.) provided in various studies was used in the data analysis. The specific software used to create the forest plot was STATA 16 . Forest plots were created for all studies reviewed. Sub-group analysis was also performed comparing the cohort and case-control studies.ResultEight (8) studies from different countries published between 2010 and 2020 were reviewed for this meta-analysis  and multivariate-adjusted OR derived from the individual papers. The square sizes were proportional to each study’s sample size, as shown in Figure 2=93.38%, p<0.05), as shown in Figure In the studies analyzed, there was a statistically significant association between a high-fat diet and breast cancer incidence , as seen in Figure Although all the studies showed a significant association, a stronger association was found in the cohort studies , monoglycerides, diglycerides, sterols, and phospholipids. The fatty acid component based on the type of carbon bonding (saturated vs. unsaturated), number of double bonds (monounsaturated versus polyunsaturated), location of the double bond (trans versus cis), and chain length  -8,16-21.The statistically significant findings in this meta-analysis linking a high-fat diet to breast cancer can be compared to numerous other archival findings that echo a similar result. Even though these studies are not without confounders, they provided useful insight into this burning topic. First, some pre-clinical studies documented the positive association between a high-fat diet and breast cancer carcinogenesis -27. For Human studies have demonstrated an association between a high-fat diet and breast cancer incidence. Nonetheless, the outcomes of human trials were not as substantial as those of preclinical investigations ,24,28-31Limitations of this studyAccording to the National Cancer Institute, a limited number of these studies show the strength of the association , and manObesity is a risk factor for breast cancer. Several theories have been given to explain this relationship, including the role of adipose tissues in producing estrogen, which plays a role in tumorigenesis. High-fat diets can result in obesity. However, the relationship between a high-fat diet as a risk factor for breast cancer is still complex. Not all existing studies demonstrate a strong association. This meta-analysis sought to determine the strength of the association between a high-fat diet and breast cancer risk while reviewing existing observational studies. The type of fat consumed has been found to determine to what extent the risk of breast cancer is increased. Hence, this paper also looked at various kinds of lipids and fats consumed in diets, including oils and polyunsaturated, saturated, trans, and monounsaturated fats, and their association with breast cancer risk. Though the studies were observational, with possible confounders, we sequenced data for the meta-analysis and determined some statistically significant positive correlations between a "high-fat" diet and the incidence of breast cancer. A healthy diet indeed includes eating foods that are rich in fats. However, the effect of consuming "excess fat" as a probable cause of breast cancer continues to accrue statistical strength. While other stronger risk factors for breast cancer exist, including age, sex, and genetics, dietary counseling must not be neglected, as making nutritional modifications that favor a healthy lifestyle can significantly reduce breast cancer risk and, thus, mortality and morbidity from the disease. Historically, scientific arguments and empirical data have suggested that high consumption of "bad fats," such as saturated and trans fats, may have a direct association with the development of breast cancer; however, quantitative data are still lacking in the discussion. Because of the scarcity of data from well-designed randomized controlled interventional trials to support or refute the findings of these observational studies, there is room for more research in this area of interest.


Background: Breast cancer is the leading cause of cancer incidence worldwide and in Taiwan. The relationship between breast cancer and occupational types remains unclear. This study aimed to investigate lifetime breast cancer incidence by different occupational industries among female workers in Taiwan. Methods: A population-based retrospective case–control study was conducted using three nationwide population-based databases. Matched case and control groups were identified with 1-to-4 exact matching among 103,047 female workers with breast cancer diagnosed in 2008–2017 and those without breast cancer. Their lifetime labor enrollment records were tracked using the National Labor Insurance Database, 1950–2017. Conditional logistic regression was used to analyze the association between types of occupational industries and risk of incident breast cancer. Results: Our study found slightly significant breast cancer risk among the following major occupational classifications: manufacturing ; wholesale and retail trade ; information and communication ; financial and insurance activities ; real estate activities ; professional, scientific, and technical activities ; public administration, defense, and social security , education ; and human health and social work activities . Conclusions: Greater percentages of industrial occupations  were associated with slightly increased breast cancer risk. Further studies should investigate the possible risk factors among female workers in those industries with slightly higher incidence of breast cancer. The GLOBOCAN 2020 estimate of 2.3 million new female breast cancer cases exceeds lung cancer as the top cause of cancer incidence worldwide . Breast The International Agency for Research on Cancer (IARC) noted several factors with sufficient or limited evidence for human breast cancer risk, including X- and gamma-radiation, night-shift work, dieldrin, ethylene oxide, and polychlorinated biphenyls. The relationship between night-shift work, defined as work at the usual sleeping time and including trans-meridian air travel, and breast cancer incidence had been investigated in past studies among nurses ,4. In adFrequently discussed occupations with higher breast cancer risk include flight attendants, medical professionals, and workers in some production positions. A meta-analysis found a combined standard incidence ratio of breast cancer among female flight attendants of 1.40 (95% CI: 1.30–1.50) , and a sRegarding breast cancer risk among other occupations, a Canadian case–control study found that automotive plastics manufacturing, food canning, and metalworking were associated with higher breast cancer risk . A CECILMost previous studies were conducted in Western countries, with fewer population-based studies focused on Asia. For instance, a population-based study among 74,942 female workers in Shanghai found higher breast cancer risk among white-collar and several types of production workers . A JapanThis study conducted a retrospective case–control study design among women with an incident breast cancer diagnosis between 2008 and 2017, matched with those with no breast cancer diagnosis. Using three nationwide population-based labor insurance databases in Taiwan, we then tracked the study cohorts’ labor enrollment records for almost 70 years from 1950 to 2017 to explore potential breast cancer risks in different occupational industries over a lifetime period. The first was the National Labor Insurance Database (NLID) from the Ministry of Labor, containing representative data on labor enrollment profiles from 1950 to 2017. According to the official Labor Insurance Act in Taiwan, all industrial workers and companies are required to enroll in National Labor Insurance to protect workers’ livelihoods and promote social security. The NLID provided detailed information regarding labor enrollment profiles, company profiles, and industrial classifications. The industrial classifications were based on the tenth version of the standard industrial classification of Taiwan’s National Statistics. The second database was the National Taiwan Cancer Registry, containing records of all cancer diagnoses, tracked from 1979 to 2017. The third was a National Death Registry tracked from 1971 to 2017, containing accurate death dates and causes. These databases are complete and representative of all Taiwanese workers, and were linked using encrypted identifiers. All data analyses were completed in Taiwan’s Health and Welfare Data Science Center, Ministry of Health and Welfare, in 2020–2021. This study was approved by the Institutional Review Board.n = 124,007), linked with the National Death Registry and the NLID. We then excluded those aged younger than 20 years at incident breast cancer diagnosis, those with any cancer diagnosis or death records prior to the date of newly diagnosed breast cancer, those with no labor insurance enrollment records prior to the date of newly diagnosed breast cancer, those with missing specific working company records in the NLID, and those with total cumulative job tenure less than 3 months in working industries. The index date for the case group was defined as the date of incident breast cancer diagnosis, and the index date was assigned to the comparison group matched based on age and major working locations. For the comparison group, we identified female workers with no breast cancer diagnosis and enrolled in the NILD with at least 3 months of cumulative job tenure in working industries between 1950 and 2017. We further excluded comparison subjects with any cancer diagnoses or death records prior to the study end date (31 December 2017). Finally, 103,051 female workers with incident breast cancer (case group) and 8,111,155 female workers without breast cancer (comparison group) were included in the analysis. We first identified female workers newly diagnosed with breast cancer as a case group using the National Taiwan Registry Database between 2008 and 2017  among case and comparison female workers based on the National Labor Insurance Database enrollment records. Specifically, we tracked back to investigate potential breast cancer incident risks in different occupational industries over a lifetime period using the national labor enrollment records from 1950 to 2017 in Taiwan. The industrial classifications were based on the tenth version of the standard industrial classification of Taiwan’s National Statistics, at four levels: section, division, group, and class. We focused on analyzing the association between occupational industries at the section (from section A to S) and division (from division 1 to 96) levels, and the incident breast cancer diagnosis.p values among multiple specific occupational industry comparisons to handle multiple testing concerns [® software, Version 9.4 of the SAS System for Windows . A p value < 0.05 was considered statistically significant.A chi-square test was used to evaluate categorical variables between the case and control groups. The association between types of occupational industries and the risk of incident breast cancer was analyzed by using conditional logistic regression, while controlling for total cumulative job tenure years. Odds ratios (ORs) and 95% confidence intervals (CIs) showed the risk of incident breast cancer. The Bonferroni and false discovery rate approaches were used to calculate adjusted concerns . The datp < 0.0002); wholesale and retail trade ; information and communications ; financial and insurance activity ; real estate activity ; professional, scientific, and technical activities ; public administration and defense, and social security ; education ; and human health and social work activities . This study also provides detailed results at the division level in We conducted a population-based retrospective case–control study and tracked back the national labor enrollment records for approximately 70 years from 1950 to 2017 to investigate potential breast cancer incident risks in different occupational industries over a lifetime period among female workers. Our study found significant breast cancer risk among the major occupational classifications including manufacturing; wholesale and retail trade; information and communication; financial and insurance activities; real estate activities; professional, scientific and technical activities; public administration; defense; social security; education; and human health and social work activities.Some of our findings were consistent with those from previous population-based international research investigating the relationship between breast cancer and kinds of occupations ,17. For Our findings suggest higher breast cancer risk for female workers in most subgroups of manufacturing with possible exposure to several kinds of organic solvents. Past studies found similar results. For example, Oddone et al. 2013) reported a case–control study in Italy that found that breast cancer incidence was associated with employment in textile, rubber, paper, and electrical manufacturing industries . Kaneko 13 reportResults in the existing literature are mixed with respect to the association between agricultural work and breast cancer risk. Agricultural workers may be exposed to chemicals, pesticides, solvents, and biological agents . An agriWe found higher breast cancer risk among telecommunications workers, which may be partly associated with exposure to electromagnetic fields (EMF). Several occupations may be with higher workplace EMF exposure, including telecommunications, broadcasting, and security and identification. Kliukiene et al. (2003) reported a cohort study that found elevated breast cancer risk among female Norwegian radio and telegraph workers, and EMF exposure was associated with different subtypes of breast cancer among women in different age groups . McElroyWe found elevated breast cancer risk among female water transportation and air transportation workers, and marginal risk among land transportation workers. A possible exposure may be exhaust from engines powered by diesel and other fuels, composed of several gases including carbon monoxide, nitrogen oxides, and polycyclic aromatic hydrocarbons . HoweverAnother possible exposure may be night shift work, which is important in some public service occupations, such as transportation, electricity, and health care . The IntSales, retail, and accommodation service workers had higher breast cancer risk in our study. Higher breast cancer incidence has been observed in past studies . Our stuWe observed higher breast cancer risk in some white-collar occupations, such as legal and accounting activities, education, and medicine, possibly partly associated with reproductive risk factors including older age at first child’s birth and lower parity due to longer training time in highly professional field ,38. One The strength of the current case–control study is that we designed a longitudinal cohort combining three nationwide population-based databases, creating a large sample size with the labor insurance registry from 1950 to 2017 and exact matching 1-to-4. Each section and division of occupational industries and job tenure was collected from the National Labor Insurance enrollment databases, possibly reducing recall bias. However, our study had some limitations. First, several unobservable risk factors could be confounders because of secondary data analysis, including hormone-related risk factors, family history, alcohol consumption, and possible occupational exposures such as night shift work, organic chemicals, physical activities, working hours and even different exposure and its duration in each section and division level of the industry. We also lack the records on labors’ attendance including information on sick leaves for maternity or pregnancies in each industry. Second, some subgroup occupations with higher breast cancer risk may be overestimated due to smaller sample sizes. Third, the total cumulative job tenures were confounding factors for conditional logistic regression in our study. However, we did not particularly investigate the association between breast cancer incidence and job employment duration of each industry for individual women. Further study may investigate the relationship between breast cancer incidence and each job employment duration in each industry. Fourth, mammography screening utilization and screening adherence might also be a potential confounder while investigating breast cancer risks among these occupational industries. However, the current study did not examine mammography rate among occupational industries. Future study may further investigate whether mammography rate varies with occupations. Finally, our findings may not generalize to other countries because the occupational exposures may be at different levels in each country.Our study found slightly significant breast cancer risk among the major classification of occupations including manufacturing, wholesale and retail trade, information and communication activities, financial and insurance activities, real estate activities, professions, scientific and technical activities, public administration, defense, social security, education, and human health and social work activities from the section and division levels according to the standard industrial classification of Taiwan’s National Statistics. Further studies should investigate the possible risk factors among female workers in those industries with slightly higher incident breast cancer.


Whether pioglitazone may affect breast cancer risk in female diabetes patients is not conclusive and has not been investigated in the Asian populations.P-value < 0.05) between ever users and never users; and 3) after adjustment for all covariates.The reimbursement database of Taiwan’s National Health Insurance was used to enroll an unmatched cohort and a propensity score-matched cohort of ever users and never users of pioglitazone in female patients with newly diagnosed type 2 diabetes during 1999–2008. The patients were alive on January 1, 2009 and were followed up for breast cancer incidence until December 31, 2011. Cox regression was used to estimate hazard ratios for ever users and tertiles of cumulative duration of pioglitazone therapy versus never users, and for cumulative duration of pioglitazone therapy treated as a continuous variable. Three models were created for the unmatched cohort and the matched cohort, respectively: 1) without adjustment for covariates; 2) after adjustment for covariates that differed with statistical significance  in the unmatched cohort and was 0.824  in the matched cohort. None of the hazard ratios for the tertiles of cumulative duration of pioglitazone therapy and for the cumulative duration being treated as a continuous variable were statistically significant.This study suggests a null association between pioglitazone and breast cancer risk in female patients with type 2 diabetes mellitus. However, because of the small breast cancer cases and the limited follow-up time, further studies are warranted to confirm our findings. The safety monitoring data of several previous clinical trials that compared the risk of cardiovascular disease between pioglitazone and placebo , 2 or beThere are several pharmacoepidemiological studies, all conducted in Caucasians, investigating breast cancer risk associated with use of pioglitazone and/or rosiglitazone. Analyses of the US Kaiser Permanente Northern California  Diabetes Registry  and the In Taiwan, previous pharmacoepidemiological studies suggested that metformin  and rosiThis is a retrospective cohort analysis of Taiwan’s NHI reimbursement database. The NHI, a compulsory and universal healthcare system in Taiwan, has been implemented since March 1995. More than 99% of the population are covered by the NHI, and all in-hospitals and 93% of all medical settings have contracts with the NHI. The NHI database contains detailed records of every visit of each patient and includes principal and secondary diagnostic codes, prescription orders and procedures performed. The present study was approved after ethics review by the National Health Research Institutes with number 99274. Informed consent was not required according to local regulations because the database has been de-identified for the protection of privacy.International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM).During the study period diabetes was coded 250.XX and breast cancer 174, based on the n = 535,025). To ensure a newly diagnosed diabetes after 1999, patients having a diagnosis of diabetes between 1996 and 1998 were not included. The following patients were then excluded: 1) type 1 diabetes mellitus (n = 3078), 2) missing data (n = 950), 3) men , 4) use of rosiglitazone  and 6) patients who died or had been diagnosed of breast cancer before January 1, 2009 (n = 4916). As a result, 6926 ever users and 174,233 never users of pioglitazone were identified as the unmatched cohort. A cohort of 6926 ever users and 6926 never users of pioglitazone (the matched cohort) was created by matching the propensity score based on the Greedy 8➔1 digit match algorithm [More detailed description of the database can be seen in previously published papers , 10. Fig in vivo  and humalgorithm . LogistiCumulative duration of pioglitazone therapy in months was calculated from the database and its tertiles were used to evaluate a possible dose-response relationship. Potential confounders included in the analyses were classified into the following categories. Demographic data included age, diabetes duration, occupation and living region . Occupation was classified as class I , class II , class III (farmers or fishermen) and class IV . Major comorbidities included hypertension (ICD-9-CM: 401–405), dyslipidemia (272.0–272.4) and obesity (278). Diabetes-related complications included nephropathy (580–589), eye diseases , stroke (430–438), ischemic heart disease (410–414) and peripheral arterial disease . Antidiabetic drugs included insulin, sulfonylureas, metformin, meglitinide and acarbose. Factors that may affect cancer risk or lifespan included chronic obstructive pulmonary disease , tobacco abuse , alcohol-related diagnoses , hypoglycemia , head injury (959.01), Parkinson’s disease (332), benign breast conditions  and cancers other than breast cancer prior to baseline . Some examinations that might potentially lead to the diagnosis of breast cancer were considered as an indicator of “potential detection bias”. These included 1) mammogram and/or breast ultrasound; 2) chest computed tomography and/or magnetic resonance imaging; and 3) tumor markers, including carcinoembryonic antigen and/or carbohydrate antigen 153. Commonly used medications in diabetes patients that may affect cancer risk included angiotensin converting enzyme inhibitor/angiotensin receptor blocker, calcium channel blocker, statin, fibrate, aspirin and estrogen.Analyses were conducted in the unmatched cohort and the matched cohort, respectively. Student’s t test compared the difference of age and diabetes duration between never and ever users of pioglitazone and Chi-square test was used for other variables. Standardized difference was calculated for each variable and a value > 10% is considered as an indicator of potential confounding from the variable .Incidence density of breast cancer was calculated with regards to the use of pioglitazone in the following subgroups: never users, ever users and the tertiles of cumulative duration. The case number of newly diagnosed breast cancer identified during follow-up was the numerator. The denominator was the follow-up duration in person-years, which started on January 1, 2009 and ended on December 31, 2011, at the time of a new diagnosis of breast cancer, or on the date of death or the last reimbursement record, whichever occurred first.P-values < 0.05 and after adjustment for all covariates, respectively.Hazard ratios and their 95% confidence intervals for ever users and for each tertile of cumulative duration in referent to never users were estimated by Cox proportional hazards model. Additionally, cumulative duration of pioglitazone therapy was treated as a continuous variable for estimating the hazard ratio. To examine the consistency of the findings, models were created in both the unmatched cohort and the matched cohort, respectively; and without adjustment for covariates, after adjustment for covariates with More antidiabetic drugs have been introduced into clinical practice and the guidelines for the use of antidiabetic drugs have evolved over the long enrollment period from 1999 to 2008. To examine whether the risk of breast cancer associated with pioglitazone use might change during different period of time, the overall hazard ratios were additionally estimated for two periods of time: 1999–2003 and 2004–2008, respectively.P < 0.05 was considered statistically significant.Analyses were conducted using SAS statistical software, version 9.4 . Table Table Table This is the first observational study conducted in an Asian population that suggested a null association between pioglitazone use and breast cancer risk. The findings were consistent in the unmatched and the matched cohorts and in all models with different sets of adjusted covariates Table . The finInsulin resistance is an early pathophysiological change related to type 2 diabetes mellitus  and patiin vitro and in vivo studies may provide evidence to support these discrepant clinical observations. In a breast cancer cell line, rosiglitazone stimulates the expression of tumor suppressor gene PTEN  but pioglitazone does not exert a similar effect [Findings from some r effect . Anotherr effect . In an ar effect . On the r effect , it doesr effect . Studiesr effect . Taken tAfter the withdrawal of rosiglitazone from the market because of a potential risk of macrovascular disease , pioglitIn the present study, we aimed at clarifying the effect of pioglitazone on breast cancer and therefore the balance of other potential confounders including the use of other antidiabetic drugs is important for an unbiased estimate. Although ever users and never users of pioglitazone differed significantly in the distribution of potential confounders in the unmatched cohort, they were well balanced in the matched cohort Table . BecauseWe did not simultaneously investigate the effects of other antidiabetic drugs because no other antidiabetic drugs (except rosiglitazone that has been withdrawn from the market in many countries) had ever experienced such a great public health concern. The restrictions imposed by regulatory authorities after the publication of the interim analysis of the KPNC in 2011  on the uThe patients were enrolled from 1999 to 2005 and followed up until 2011. This database seemed to be too old. However, the study period was deliberately selected to reduce potential biases based on the following considerations. First, this time frame would avoid unidentifiable biases resulting from the impacts of the publication of the interim analysis of the KPNC study in 2011  and the It was also deemed inappropriate to investigate too many drugs and too many different cancers in a single study especially when pioglitazone was the target drug to be investigated because of the following reasons. First, as previously mentioned, the time frame for studying pioglitazone should be carefully restricted so that the findings would not be biased. The restriction on the use of pioglitazone would also affect the prescription and the adherence of other antidiabetic drugs and these behavior changes might have caused unexpected biases. Second, different antidiabetic drugs have different indications, contraindications and side effects and different cancers have different risk factors. It would be complicated to balance different sets of confounders. Third, cancer screening programs are evolving and different for different cancers. It may not be possible to simultaneously consider the impacts of these different screening programs when too many cancers are investigated in one single study.Breast cancer screening programs have been conducted in either the USA  or in FrIn Taiwan, breast cancer screening programs have evolved from hospital-based project 1995–1998), to community-based projects (1999–2001 and 2002–2004) and finally to nationwide programs  . The pha995–1998,Although the median follow-up duration of 2.8 years in our present study was relatively short, this was comparable to the median duration of pioglitazone exposure of 2.8 years in the final report of the US KPNC study (study period 1997–2012)  and was Based on the following additional considerations, we did not follow the patients forward from the time of drug exposure. First, pioglitazone is not a first-line antidiabetic drug and it has not been approved for clinical use in Taiwan until after 2002. If the patients were to be followed since enrollment at the time of diabetes diagnosis  would potentially lead to a conclusion of null association because of lack of statistical power. Therefore, additional studies are warranted to confirm our findings.The study limitations included a lack of actual measurement data for potential confounders such as obesity, smoking, alcohol drinking, family history, lifestyle, dietary pattern, and genetic parameters. In addition, we did not have biochemical data such as hormonal profiles, blood glucose levels, hemoglobin A1C concentrations, insulin, C-peptide levels, or calculation of homeostasis model assessment for insulin resistance for evaluating their impacts. Another limitation is the lack of information on the pathology, grading and staging of breast cancer. Finally, we should point out that the short median follow-up time of 2.8 years and the relatively low number of breast cancer cases (Table In summary, this study supports a null association between pioglitazone use and breast cancer risk in Taiwanese female patients with type 2 diabetes mellitus. The findings of the present study together with those of our previous studies , 45, 46