Inflammation-related mechanisms may contribute to the link between diet and cancer. We sought to investigate the inflammatory impact of diet on cancer risk using the Dietary inflammatory index (DII) and an adapted Mediterranean diet score (MDS).This population-based, prospective cohort study used self-reported dietary data from the Västerbotten Intervention Programme, including 100,881 participants, of whom 35,393 had repeated measures. Associations between dietary patterns and cancer risk were evaluated using Cox proportional hazards regression. We also used restricted cubic splines to test for potential non-linear associations.A total of 9,250 incident cancer cases were diagnosed during a median follow-up of 15 years. The two dietary patterns were moderately correlated to each other and had similar associations with cancer risk, predominantly lung cancer in men (DII per tertile decrease: Hazard ratio (HR) 0.81 (0.66–0.99), MDS per tertile increase: HR 0.86 (0.72–1.03)), and gastric cancer in men (DII: 0.73 (0.53–0.99), MDS: 0.73 (0.56–0.96)). Associations were, in general, found to be linear. We found no longitudinal association between 10-year change in diet and cancer risk.We confirm small, but consistent and statistically significant associations between a more anti-inflammatory or healthier diet and reduced risk of cancer, including a lower risk of lung and gastric cancer in men. The dietary indexes produced similar associations with respect to the risk of cancer. A third of all cancer-related deaths may be linked to diet  and inflExcess body fat is an established risk factor for many types of cancers . An enerThe aim of this study was to investigate the inflammatory impact of diet in determining cancer risk using two widely used indices, the inflammation-specific DII and an adapted MDS. These dietary indices were examined in 9,250 prospective cancer cases in a population-based cohort of 100,881 participants, including 35,393 individuals with repeated measures ≥10 years apart.st or above the 99th percentile for each version of the food frequency questionnaire (FFQ) and for each sex), implausible energy intakes , implausible anthropometric data  <15 or >70 kg/m2), and cancer cases diagnosed within 1 year of their last measurement (n = 605).Study participants were selected from the Västerbotten Intervention Programme (VIP) cohort, an ongoing population-based, prospective cohort in northern Sweden, established in 1986 . During We also estimated associations between 10-year changes in dietary pattern scores and cancer risk. Participants with health examinations deviating by more than ±2 years from the VIP age groups or more than ±2 years from the 10-year time span between health examinations, were excluded. For participants with three measurements , the two earliest measurements were used. After exclusions , a total of 35,393 participants were included in the longitudinal analyses.Dietary data were harmonized and refined by the Northern Sweden Diet Database (NSDD) management. Validated FFQs—a longer version with 84 items and a shortened version of the same FFQ with 64–66 items—were used to calculate dietary pattern scores –14. FoodDetailed descriptions of development and scoring algorithm of the DII , as wellThe Mediterranean diet is characterized by high intake of vegetables, legumes, fruits, nuts, seeds, cereals, and olive oil, moderately high intake of fish, low to moderate intake of dairy products, moderate intake of alcohol, and low intake of saturated fat, meat and meat products . We used2) was calculated using measurements taken by a health care professional. Physical activity refers to recreational physical activity, harmonized between questionnaire versions and classified in three levels: low , medium (up to 2 times a week), and high (≥3 times a week). Educational status was defined at three levels; elementary school , upper secondary school or post-secondary education. Total energy intake was calculated from FFQ-derived dietary data and expressed as kcal/day.Smoking status was classified as daily smoker, ex-smoker (former daily smoker), or never smoker . Diabetes was defined as self-reported or diagnosed at the health examination according to fasting blood glucose (≥7.0mmol/L) or 2-hour post-load plasma glucose (≥12.2mmol/L in capillary blood). BMI , as well as first incident breast (C50), prostate (C61), lung (C34), gastric (C16), pancreas (C25), colorectal C18-C20.9), and gastrointestinal (GI) including: esophagus (C15), gastric (C16), liver/intrahepatic bile ducts (C22), pancreas (C25) and small intestine C17) cancer. We also investigated smoking-related and obesity-related cancers. Smoking-related cancers were defined according to the International Agency for Research on Cancer (IARC) [.9, and g cancer. This study was approved by the Regional ethical review board of northern Sweden (Dnr 2013/332–31). All study subjects provided written informed consent at recruitment for all collection for research purposes, and the study was conducted in accordance with the Declaration of Helsinki.Baseline characteristics of men and women were calculated for sex- and FFQ-specific categories approximating tertiles of the dietary pattern scores. DII tertiles (T) were constructed according to the distribution of participants. MDS tertiles were distributed to avoid ties: T1) Score 0–3, T2) Score 4, and T3) Score 5–8. Comparisons were made using Pearson Chi-square tests for categorical variables and ANOVA for continuous variables. Correlations between dietary patterns were estimated with Spearman’s correlation coefficient.Associations between baseline dietary patterns and cancer risk were evaluated using Cox proportional hazards regression with age as the time scale. The proportional hazards assumption was checked by evaluating Schoenfeld residuals. In the all-cancer risk analysis, sex showed signs of non-proportionality characterized as a higher risk of cancer in women compared to men before age 67 years and the opposite after age 67. Therefore, risk estimates are presented for all participants, stratified by sex within the Cox model, but also for men and women separately. In the analysis of breast and lung cancer, both BMI and smoking showed signs of non-proportionality. Because stratification for BMI categories or smoking status did not affect risk estimates, estimates from non-stratified models are presented.2, BMI <30kg/m2). HRs were also estimated by excluding participants with diabetes. Heterogeneity in HR estimates between subgroups were tested with a Wald’s test.To facilitate comparisons between risk estimates, linear associations are presented as hazard ratios (HR) per tertile decrease in DII or tertile increase in MDS, obtained by modelling continuous scaled variables, i.e. by dividing each dietary pattern score by its respective sex- and FFQ-specific intertertile range. The mean intertertile ranges were 1.7 for DII and 2 for MDS. Estimates were adjusted for covariates with a potential association to both dietary pattern and cancer risk: energy intake, BMI, physical activity, smoking, and educational status. In sensitivity analyses, HRs were estimated separately by age groups , smoking status , and BMI . Tests for associations were made with a likelihood ratio test comparing the dietary pattern spline model with a model without the dietary pattern. Non-linearity was tested with a likelihood ratio test comparing the spline model to a linear model.To test for non-linear associations, continuous dietary pattern variables were modelled using restricted cubic splines . We also evaluated longitudinal associations between continuous change in dietary pattern score (Δ = repeat–baseline) and cancer risk. HRs per tertile decrease in ΔDII or tertile increase in ΔMDS were obtained by modelling continuous scaled difference variables  in Cox models. Estimates were adjusted for baseline and Δenergy intake, baseline and ΔBMI, smoking , physical activity , and baseline educational status.All computations were conducted in R v.3.4.2 . All tests were 2-sided, and P-values <0.05 were considered statistically significant.P <0.001) and from 44.3 to 48.7 for women (P <0.001). Mean age was more similar across DII tertiles, though P <0.001. Obesity was more common among men with a more pro-inflammatory diet as estimated by the DII (P <0.001), and among both men and women with low adherence to MDS (P <0.001). Participants with higher DII and lower MDS scores , were less likely to be married or co-habitating, to have post-secondary education or to be physically active, but more likely to be current smokers . Additionally, they were less likely to have been diagnosed with diabetes .Characteristics of the 100,881 study participants at first visit are presented in P<0.001) and correlations were similar for the repeat measures , 9,250 prospective cancer diagnoses were detected, 4,830 in men and 4,420 in women. Linear HRs for cancer by baseline dietary pattern scores, adjusted for potential confounders, are presented in The overall accuracy for predicting cancer for models including age, energy intake, BMI, physical activity, smoking, educational status, and dietary patterns, was similar for the two dietary patterns .Associations between dietary patterns and overall cancer risk in subgroups defined by baseline age, smoking status, and BMI, are presented in Pheterogeneity = 0.12 and 0.03 for ever smokers and non-smokers, respectively (Pheterogeneity = 0.13). There were no clear differences in the relation between the risk of obesity- or non-obesity-related cancer and dietary patterns.For smoking-related cancers, lower DII or higher MDS were mainly associated with a decreased risk in ever smokers, with weak evidence of heterogeneity in associations between smoking-related and other cancers , presented separately in Passociation = 0.09). The suggested nonlinear association between MDS and gastric cancer risk in women was U-shaped, with increased risk at low or high MDS compared to the median (Passociation = 0.06).HRs for cancer types by DII and MDS in all participants, men, and women, modelled by restricted cubic splines, are presented in Moderate correlations were observed between the baseline and repeat measurement for each dietary pattern (r = 0.40 to 0.53) . Most paParticipants, primarily men, with an unchanged, more pro-inflammatory diet at follow-up, as well as participants who went from “healthy” to a more pro-inflammatory diet over the 10-year period were at a slightly increased risk for cancer; however, the association was attenuated and not significant after adjusting for change in BMI and smoking status . A similTen-year change in DII was not associated with the risk of cancer (HR per tertile decrease in ΔDII: 0.99 (0.95–1.04) . ParticiIn this prospective, population-based study, the DII and the MDS were moderately correlated to each other and produced similar associations with the risk of cancer. An anti-inflammatory or healthier diet was weakly associated with a reduced overall cancer risk, most evident for lung and gastric cancer. Ten-year change in dietary pattern score was not related to cancer risk.Helicobacter pylori infection in relation to diet are warranted [These results are consistent with previously observed positive associations between the inflammatory potential of diet and risk of gastric cancer , 22, andarranted . Our nularranted , 26, 27.arranted , which mWe observed a general association between a more anti-inflammatory/healthier diet and lower risk of lung cancer, consistent with previous findings , 23, 29.The null findings for prostate and breast cancer contrast with results from meta-analyses of DII , 23. HowThe study population did not alter its dietary habits substantially according to our supplementary analysis of longitudinal changes in DII and MDS, which probably explains the fairly consistent results for the longitudinal analyses compared to baseline. Interestingly, a change toward better adherence to the MDS, was associated with an increased cancer risk, primarily in women. This might be due to residual confounding by socioeconomic status, not sufficiently captured by the education variable. Higher socioeconomic status is a risk factor for breast cancer, probably acting as a summary marker for factors related to reproduction . DiabeteThe fifteen DII food parameters lacking in this study are all considered anti-inflammatory, which might limit the ability of the score to capture an anti-inflammatory diet. However, the range of DII scores in our population is similar to a validation study in an American population based on 44 of the 45 components, which showed a direct association with CRP levels [Nutrients and food components with evidence for a relation to cancer risk are largely covered by both DII and MDS, which undoubtedly contributed to the similar estimates for cancer risk. Whereas the DII was designed specifically to estimate the inflammatory potential of diet , the MDSA weakness in this study is the self-reported dietary intake, which is subject to recall bias and underreporting. Underreporting of socially undesirable foods has been documented, especially in women  and obesAlthough confounders may differ between cancer types, we applied the same set of covariates in all analyses, in order to simplify interpretation of results. Information about some potential confounders was lacking, such as use of nonsteroidal anti-inflammatory drugs (NSAID), of particular relevance for CRC, and menopausal hormone therapy, of relevance for breast cancer. Many types of cancer demonstrate substantial intertumoral heterogeneity. More specific anatomic location for cancers of the upper and lower gastrointestinal tract, as well as tumor characteristics, such as histological subtype for lung and gastric cancer, hormone receptor status for breast cancer, and microsatellite instability and other molecular traits in CRC could, therefore, add valuable information.A major strength of this study is its prospective design, with over 100,000 participants and up to 26 years of follow-up. Because exposure data were collected before cancer diagnosis, reverse causality and disease-specific recall bias were unlikely to have influenced the results. Furthermore, repeated measures  were available for over 35,000 participants, allowing investigation of longitudinal dietary changes in relation to cancer risk. Although these analyses were sufficiently powered to examine overall cancer risk, a larger sample size would be necessary for site-specific cancer. Additionally, with restricted cubic spline models we could show that most associations were linear. Another important strength is the population-based nature of the cohort used, as demonstrated by the very similar cancer incidence in the VIP and the background population , as wellIn conclusion, in this prospective cohort study, we confirm small, consistent, and statistically significant associations between a more anti-inflammatory or healthier diet and reduced risk of cancer, for lung and gastric cancer in specific, and particularly in men. Although several mechanisms may be involved, the consistency of the findings for the DII, designed specifically to capture the inflammatory impact of diet, and the MDS, suggests that inflammation may be a common denominator.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S1 FigHazard ratios (HRs) and 95% CI for all cancer per tertile decrease in DII and tertile increase per MDS at baseline.(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S4 FigRestricted cubic splines with hazard ratio (HR) and 95% confidence interval of cancer in a) all participants b) men, and c) women by baseline dietary pattern score.(DOCX)Click here for additional data file.S5 Fig(DOCX)Click here for additional data file.


Even though in situ breast cancer (BCIS) accounts for a large proportion of the breast cancers diagnosed, few studies have investigated potential risk factors for BCIS. Their results suggest that some established risk factors for invasive breast cancer have a similar impact on BCIS risk, but large population-based studies on lifestyle factors and BCIS risk are lacking. Thus, we investigated the association between lifestyle and BCIS risk within the European Prospective Investigation into Cancer and Nutrition cohort.Lifestyle was operationalized by a score reflecting the adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations. The recommendations utilized in these analyses were the ones pertinent to healthy body weight, physical activity, consumption of plant-based foods, energy-dense foods, red and processed meat, and sugary drinks and alcohol, as well as the recommendation on breastfeeding. Cox proportional hazards regression was used to assess the association between lifestyle score and BCIS risk. The results were presented as hazard ratios (HR) and corresponding 95% confidence intervals (CI).After an overall median follow-up time of 14.9 years, 1277 BCIS cases were diagnosed. Greater adherence to the WCRF/AICR cancer prevention recommendations was not associated with BCIS risk . An inverse association between the lifestyle score and BCIS risk was observed in study centers, where participants were recruited mainly via mammographic screening and attended additional screening throughout follow-up , but not in the remaining ones .While we did not observe an overall association between lifestyle and BCIS risk, our results indicate that lifestyle is associated with BCIS risk among women recruited via screening programs and with regular screening participation. This suggests that a true inverse association between lifestyle habits and BCIS risk in the overall cohort may have been masked by a lack of information on screening attendance. The potential inverse association between lifestyle and BCIS risk in our analyses is consistent with the inverse associations between lifestyle scores and breast cancer risk reported from previous studies. In situ breast cancer (BCIS) is an intraepithelial lesion with malignant potential. Generally, it is considered a non-obligatory precursor or a potential risk factor for invasive breast cancer. Women with BCIS rarely report symptoms, and the majority of in situ tumors are detected through organized or opportunistic mammographic screening attendance .Even though BCIS accounts for up to 20% of the breast cancer cases diagnosed , censoreConsidering the abovementioned studies suggesting an inverse association of a more health-conscious lifestyle with a decreased risk of BCIS, and the lack of large epidemiological studies, we investigated the association between lifestyle, operationalized by a score reflecting the adherence to cancer prevention recommendations, and BCIS risk within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.EPIC is a multicenter prospective cohort study designed to investigate the associations between diet, lifestyle, genetic and environmental factors, and the incidence of cancers and other chronic diseases. Over 520,000 participants, aged 25–70 years, were recruited between 1992 and 2000 in 10 European countries . The French cohort included members of a health insurance plan for school and university employees. Participants at the Spanish and Italian centers (except Florence) included blood donors, members of several health insurance programs, employees of several enterprises, civil servants, and people from the general population. In Utrecht and Florence, women mainly participating in mammographic screening programs were recruited for the study. In Oxford, most of the cohort consisted of “health-conscious” persons from England, Wales, Scotland, and Northern Ireland, many of whom were vegetarians. Participants were recruited from the general population in the other centers. The cohorts of France, Norway, Utrecht, and Naples included only women. All study participants provided written informed consent. Ethical approval for this study was obtained from the International Agency for Research on Cancer review board and local participating centers.Detailed information on the study design, methods, and rationale of the EPIC cohort has been previously reported , 14. Upon = 20,477), women who were lost to follow-up (n = 2557), pregnant women at study enrollment (n = 556), and women with missing data on diet, weight or height, physical activity, or breastfeeding were excluded from the analyses . The latter exclusions due to missing covariates comprised all participants from Umeå, Sweden, and Norway, where physical activity was not collected in sufficient detail as well as participants from Bilthoven, the Netherlands, where information on breastfeeding was not collected. Additionally, in order to exclude implausible dietary intakes, participants within the lowest and highest 1% of the cohort distribution of the ratio of total energy intake to estimated energy requirements were excluded (n = 5033). Therefore, 260,151 women were finally included in the analytical sample.For the present study, women with prevalent cancers (except non-melanoma skin cancer) at study enrollment (A score reflecting the adherence to the World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations was constructed, as in previous studies , 17, 18.Detailed information on the construction of the WCRF/AICR lifestyle score for the EPIC cohort has previously been reported . In shorThe main difference between our WCRF/AICR lifestyle score and the scores used previously in EPIC and other studies , 17, 18 Of note, we decided to assign 1 point for adherence to the WCRF/AICR recommendation on alcohol consumption to individuals, who had reported moderate alcohol consumption (≤ 10 g of ethanol intake per day), in addition to non-consumers , 17. ThiWomen who developed first primary incident and histologically confirmed BCIS between recruitment and the latest date of complete information were considered as cases. BCIS cases were identified through population cancer registries in Denmark, Italy, the Netherlands, Spain, Sweden, and the UK. In France, Germany, and Greece, a combination of methods was used including health insurance records, cancer pathology registries, and active follow-up of study participants and their next of kin. The latest dates of complete information for BCIS incidence varied among centers, ranging between 2008 and 2013. Cancer cases were coded according to the 10th Revision of the International Statistical Classification of Diseases, Injuries, and Causes of Death and the Second Revision of the International Classification of Diseases for Oncology.In situ tumors were further classified based on their morphology as ductal carcinoma in situ  or lobular carcinoma in situ .Categorical variables were presented by percentages and continuous variables by arithmetic means and standard deviations (SD) for descriptive purposes. Missing covariate values were sporadic  and occurred in all participating study centers. We used multiple imputation with a fully conditional specification as provided by PROC MI in SAS , and misCox proportional hazards regression was used to assess the association between the WCRF/AICR lifestyle score as well as its individual components and the risk of BCIS development. Entry time was defined as the date of a participant’s recruitment in the study and exit time as the date of diagnosis of BCIS. Participants who were not diagnosed with BCIS were censored on the date of diagnosis of other cancers, except non-melanoma skin cancer, or on the date of loss to follow-up, end of follow-up, or death, whichever came first. All analyses were stratified by age at recruitment  and center.Two sets of covariates were evaluated for statistical adjustment. In model 1, we adjusted for the highest level of attained education , smoking status , and total dietary energy consumption . Model 2 was additionally adjusted for a priori determined confounders including the presence of chronic diseases at recruitment , age at menarche , age at first full-term pregnancy , menopausal status , ever use of oral contraceptive pills , and ever use of menopausal hormone therapy . The WCRF/AICR lifestyle score was assessed both as a continuous and as a categorical variable. BCIS was evaluated as a composite outcome  and by morphological subtypes (DCIS vs. LCIS). The results are presented as hazard ratios (HR) and corresponding 95% confidence intervals (CI).n = 1794). Analyses were conducted using SAS version 9.4 . All statistical tests were two-sided, and p values < 0.05 were considered statistically significant.Given that BCIS is mainly diagnosed by mammographic screening, we conducted subgroup analyses evaluating the association in centers where most women were recruited via screening programs and in which screening participation during follow-up was high  cases were diagnosed in the EPIC cohort. Proportions of BCIS to overall breast cancer cases varied between 4.3 and 15.8% across the study centers  in the full EPIC cohort. A significant inverse BCIS risk association for WCRF/AICR lifestyle score was observed in the screening-recruited cohorts , but not in the other centers . While prespecified subgroup analyses of smoking status and menopausal status showed similar associations as the overall analyses, the inverse association between lifestyle score and BCIS risk was more pronounced among women with lower education level in the screening-recruited cohorts  breast cancer risk. The majority of these studies have reported inverse associations between the WCRF/AICR lifestyle score and invasive [both in postmenopausal and in mixed  populations] , 24, 25 The lack of a statistically significant association between the individual components of the WCRF/AICR lifestyle score and BCIS risk that we observed in the present study is overall consistent with the findings from studies on invasive breast cancer risk using similar scores , 25–27, Our findings from the subgroup analyses in the screening-recruited EPIC cohorts could suggest that a combined healthy lifestyle  is important for the carcinogenetic process in the breast. However, the lack of association for individual components of the WCRF/AICR lifestyle score in our analyses could also be due to the relatively small proportion of the study population in the screening-recruited EPIC cohorts . Future large-scale studies with more detailed information on mammographic screening attendance during follow-up and BCIS status at recruitment are needed in order to investigate the individual lifestyle factors in relation to BCIS risk in more detail.Given the agreement between our subgroup finding of an inverse association between lifestyle score and BCIS risk and those reported in other studies for invasive or total breast cancer  , 18, 25,The strengths of this study included the prospective design and the substantial number of histologically confirmed incident BCIS cases, but it also had some limitations. Information on lifestyle habits was only available from baseline and thus may not reflect the long-term lifestyle habits of the study participants. Furthermore, information on mammographic screening attendance was not available for large parts of our study population. The fact that proportions of BCIS to total breast cancer cases ranged between 4.3 and 15.8% across the centers of the EPIC cohort suggests that screening participation but potentially also BCIS registration were different across study sites. In this context, it should be noted that we could not disentangle the underlying reasons with our data. Temporal and regional differences in BCIS reporting are not expected to be differential among EPIC participants with different lifestyle behaviors or characteristics , differential detection bias, i.e., a differential individual likelihood to participate in screening related to individual health consciousness and socio-economic status cannot be ruled out. Nevertheless, we were able to perform analyses restricted to women mainly recruited via organized mammographic screening programs at the EPIC centers in Florence and Utrecht and reported the results from these analyses separately. While our main objective was to evaluate the adherence to lifestyle recommendations in relation to BCIS risk, we acknowledge that more etiology-oriented analyses on BCIS risk from EPIC and other cohorts are needed, also taking into account morphological tumor subtypes based on larger case numbers. Finally, as in any observational study, we cannot exclude the possibility of residual confounding.In summary, women with a higher lifestyle score including healthy body weight, regular physical activity, consumption of a high-quality diet, breastfeeding, and drinking a moderate amount of alcohol, if any, did not have a statistically significant lower risk of BCIS compared to participants who did not adhere to these habits in the EPIC cohort. However, there was a statistically significant inverse association among participants recruited via screening programs and with high screening participation during follow-up, suggesting that a true inverse association between lifestyle habits and BCIS risk in the overall cohort may have been masked by the lack of information on screening attendance. The potential inverse association between lifestyle and BCIS risk in our subgroup analyses restricted to screening-recruited EPIC cohorts is consistent with the inverse associations between lifestyle scores and mammographic density as well as breast cancer risk reported in previous studies. These findings may indicate that BCIS and invasive breast cancer have a similar risk factor profile. Additional studies, with more detailed information on screening participation, are required in order to validate our findings.Additional file 1: This file contains Table S1. The World Cancer Research Fund/American Institute for Cancer Research (WCRF/AICR) cancer prevention recommendations and the operationalization of the WCRF/AICR lifestyle score in the European Prospective Investigation into Cancer and Nutrition cohort; Table S2. The proportion of primary in situ breast cancer cases over the total primary breast cancer cases diagnosed in the European Prospective Investigation into Cancer and Nutrition cohort; Table S3. The association between the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and the risk for the most common morphological subtypes of BCIS  in the European Prospective Investigation into Cancer and Nutrition cohort; Table S4. The associations between the individual components of the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and in situ breast cancer risk by menopausal status and menopausal hormone use assessed in the total study population.


Fibrocystic breast change (FBC) is extremely common and occurrs in 90% of women during their lives. The association between body composition and risk of breast cancer is well established. We hypothesized that the effect might exist during the development of FBC. Our aim was to examine the relationships of total lean mass (TLM) and percent body fat (PBF) with FBC in a general female population. In total, 8477 female subjects aged 20 years or older were enrolled in the study at the Tri-Service General Hospital in Taiwan from 2011 to 2016. Comprehensive examinations including biochemical data, measurements of body composition and breast ultrasound were performed. PBF was positively associated with the presence of FBC , and TLM showed the opposite result . Condition of metabolic syndrome (MetS), diabetes (DM) and fatty liver modified the association between PBF and FBC . Female subjects diagnosed with MetS, DM, and fatty liver had higher risk of developing FBC than control subjects . Those with higher PBF  or lower TLM  had increased risk of developing FBC. In conclusion, increased PBF and reduced TLM were likely to predict the risk of the presence of FBC in a general female population. FBC is most common among premenopausal women aged 20–50 years old2. Such changes comprise all types of benign conditions such as cysts, papilloma, apocrine metaplasia, epithelial hyperplasia, and adenosis3. Several studies indicated that the lifetime prevalence of FBC in women might be as high as 70% to 90%5.Fibrocystic breast change (FBC), also termed 7. In a study composed of women diagnosed with benign breast disease, females with atypical epithelial proliferation had higher risk than women over 55 years with the same diagnosis8.These fibrocystic changes might be discovered incidentally by radiologists in women who began screening. Generally, FBC is not related to breast cancer. However, accumulating evidence has proposed that the breast cancer risk is involved with FBC. Women with nonproliferative lesions did not have a risk for breast cancer, whereas those with proliferative lesions without atypia had an approximately 2-fold increase in risk and those with atypical ductal or lobular hyperplasia had an approximately 5-fold increase in risk10. Adipose tissue might increase the risk of breast cancer by influencing sex hormone balance, endocrine function and adipokine expression11. Recently, lean body mass was found to represent a powerful endocrine, immune and hormonal influence within the body12. However, few studies have addressed the effect of obesity on FBC and the association was largely unknown.The associations between body composition and breast cancer have been examined and well established for decadesDue to the potential risk of FBC in the development of breast cancer, we were inspired to examine whether the alteration in body composition would increase the risk of FBC. The aim of our study was to investigate the associations between FBC with percent body fat (PBF) and total lean mass (TLM) with FBC in a large-scale general female population who had undergone health examinations in a medical center in Taiwan.The demographic characteristics including age, body composition indices and laboratory biochemical data of participants with or without FBC are represented in Table As shown in Table The associations between PBF and diagnoses of FBC with or without underlying diseases such as metabolic syndrome (MetS), diabetes mellitus (DM) and fatty liver performed by multivariable logistic regression are listed in Table As shown in Table In our study, we highlighted the important role of body composition in the process of FBC. Subjects with higher TLM had a lower risk of developing FBC. In contrast, higher PBF was significantly associated with an increased risk of the presence of FBC. It appeared that TLM played a protective role; however, increased PBF was detrimental to the general female population. To the best of our knowledge, the present study was the first to examine the relationship between different anthropometric parameters and FBC in a cross-sectional study composed of a large female general population.13. Sex hormonal alterations with estrogen dominance over progesterone were considered to contribute to the development of hyperproliferation of breast tissue13. Adipose tissue has been suggested as an endocrine organ that secretes numerous hormones such as sex hormones14. Excessive body fat could raise levels of estrogen and increase the risk of hormone-receptor-positive breast cancer15. Numerous studies have reported that postmenopausal women placed on hormone replacement therapy had symptoms of FBC, indicating that hormones might play a role16. Aside from estrogen and progesterone, prolactin also led to FBC by expression outside of the breast and acting on the breast in important ways17. Prolactin was responsible for the growth and development of mammary glands18. There were specific prolactin receptors in breast tissue that increased during pregnancy and throughout estrogen therapy19. In a previous study, obesity and increased body fat were reported to be related to high levels of prolactin20. Kok et al. demonstrated that release of prolactin was enhanced in obese premenopausal women and was particularly associated with the amount of visceral fat21. The above evidence supported our findings that increased PBF was associated with a high risk of FBC in a general female population.The most significant contributing factor to FBC was the normal hormonal variation of women during the menstrual cycle22. The term “sarcopenic obesity”, known as TLM loss with fat tissue accumulation was common in breast cancer survivors23. TLM loss appears to be associated with metabolic abnormalities and is a positive predictor of adverse outcomes, such as chronic heart failure, chronic kidney disease and cancer cachexia26. Villasenor et al. reported that sarcopenia was associated with an increased risk of breast-cancer-specific mortality. It is important to improve prognosis by maintaining and increasing skeletal muscle mass27. The direct mechanism underlying the effect of lean body mass on breast diseases and cancer remains unknown. Concurrent lean mass loss caused by fat tissue accumulation might be a plausible explanation for the induction of elevated levels of estrogen in the development of FBC.In a case-control study, a higher fat-muscle ratio was associated with increased risk of breast cancer, whereas muscle fraction was negatively associatedThere were still potential limitations in the study. First, a cross-sectional design could not be assessible for casual inference between anthropometric indices and the presence of FBC. A longitudinal survey was suggested to be examined in further studies. Second, only Taiwanese females had enrolled in the study from health examinations at a single medical center. Limited ethnic diversity might not reflect the association in different ethnicities. Last, the measurement of body composition in the health check-up was performed by BIA, but not DEXA, a standard measurement for body composition with higher accuracy.Our findings highlighted the associations of TLM and PBF with the presence of FBC in a general female population. Decreased fat mass and increased lean mass might reduce the risk of FBC and even retard the progress of cancer. A better understanding of the pathophysiological underlying shared associations of TLM and PBF may provide biological insights into the etiology of FBC.A total of 69226 participants aged 20 years and older were enrolled in health examinations at Tri-Service General Hospital from 2011 to 2016, and all characteristics of the study sample were analyzed in the retrospective cross-sectional study. Study approval was conduct by the Institutional Review Board (IRB) of Tri-Service General Hospital (TSGH), Taiwan. The TSGH IRB waived the need to obtain individual informed consent because these data were analyzed anonymously. Based on our inclusion criteria, males were excluded in the first step. Female participants with missing biochemical data and those lacking comprehensive examinations were excluded. In all, 8477 eligible subjects were included in the final analysis.28. The breast tissue was dense and tightly packed with lobules, ducts and connective tissue in young females29. Due to the above supportive evidence, breast ultrasound was better than mammography for evaluating breast condition. Ultrasound imaging used sound waves to produce pictures of the internal structures of the breast. The radiographic features of breast ultrasound for FBC showed prominent fibroglandular tissue in palpable nodules without discernible mass or small cysts in the mammary zone30.The study sample in our study was composed of a Taiwanese general female population. Several studies had reported that the morphological view of breast tissue in Asian women is denser than that in Caucasian women2). Biochemistry laboratory data were collected by drawing blood samples from subjects after fasting for at least 8 hours and analyzed by different standard procedures. TC and AST were measured by an enzymatic colorimetric method. The latex-enhanced nephelometry was used to detect hsCRP. UA was measured by the Hitachi 737 automated multichannel chemistry analyzer . Cr was measured by the uncompensated Jaffe method with the alkaline picrate kinetic test. TSH was accessed by an immune-enzymatic assay.The baseline data in the present study included age, body composition , laboratory data , and personal history . A self-reported questionnaire was used to collect age, gender and personal history. TLM and PBF were the indicators used in the study and were measured by BIA , an effective and validated method that was widely used for assessing body composition. BMI was measured by trained investigators using a general formula that the weight divided by the square of the height  for associations between TLM and PBF with the presence of FBC were performed. A univariate logistic model was applied in the first step (Model 1: unadjusted.) After adjusting pertinent confounders, multivariate models were investigated . Second, multivariable logistic regression was used for PBF predicting the risk of developing FBC with or without the presence of MetS, DM and fatty liver. The effect of modification by FBC and different health outcomes was tested by including interaction terms in the models for the PBF, and the results were shown in the following table. There were significant interactions between FBC with MetS (p < 0.001), DM (p = 0.032) and fatty liver (p = 0.007). According to the significant findings of the interaction testing, further stratified analyses were performed. Finally, ORs for associations between TLM and PBF with the presence of FBC in quartile analysis were conducted. Multivariable models were adjusted as follows. Statistical estimations used in the study were performed by the Statistical Package for the Social Sciences, version18.0  for Windows. The differences between males and females in terms of demographic information and biochemistry data were examined by Student’s t test and Pearson’s chi-square test. A two-sided


To examine whether breast cancer is associated with body composition and level of physical activity, considering the menstrual status. This was a case-control study with 116 women recently diagnosed with breast cancer and 226 controls. Body composition was assessed by dual-energy X-ray absorptiometry, and cardiometabolic risk was assessed by conicity index and waist-to-height ratio. The short version of the International Physical Activity Questionnaire was used to estimate the level of physical activity. All analyses were adjusted for age and BMI. The total body fat percentage, android body fat, android-gynoid ratio, and waist circumference were positively associated (p < 0.05), whereas the percentage of lean body mass (p <0.05) and the level of physical activity (p < 0.01) were inversely associated with breast cancer in premenopausal women. Among postmenopausal women, physical activity decreased the chance of developing breast cancer by 49% . A low percentage of lean body mass and high abdominal adiposity in the premenopausal period increase the chances of developing breast cancer. Regular physical activity is inversely associated with breast cancer in pre- and postmenopausal women. Breast cancer is the most common cancer among women in developed and developing countries , 2. ThisIn recent years, several studies have associated physical activity with a reduced risk of breast cancer, especially in women after menopause and those who have not been exposed to hormone replacement therapy –7. HowevMost epidemiological studies use body mass index (BMI) as an indirect measure of adiposity , 8. DespIt remains uncertain whether there is an association between breast cancer and body composition when analyses are adjusted by BMI and when considering the menstrual status , 11, 12.This was a case-control study conducted in a referral public hospital in the diagnosis and treatment of breast cancer. Data were collected from August 2014 to June 2016. Ethical approval was obtained from the Ethics Committee of the Federal University of Goiás (protocol number 751.387/2014). All participants were informed about the study orally and by writing and gave their written informed consent to participate.α = 5%), and a probable loss of 30%, a minimum sample of 75 cases and 150 controls was obtained, totaling 225 women.For the sample size calculation, a standard deviation of ± 8.8 (%) for the total body fat variable  and a coThe study included women aged between 30 and 80 years. In the case group, those with newly diagnosed breast cancer, prior to the start of chemotherapy, excluding carriers of metastatic disease or with a history of other cancers, were considered eligible. The control group included women who recently underwent mammography and/or physical examination of the breasts without changes and who had no history of breast cancer or other cancers. The presence of any cognitive impairment or psychiatric disorder, which would preclude the understanding of the work and the collection of the necessary information, and the presence of medical conditions that could compromise the nutritional status and/or harm physical activities were defined as exclusion criteria for both groups. Groups were matched for age, BMI, and menopause status.Initially, we conducted a pilot study for the adequacy, accuracy, and precision of the anthropometric and body composition measurements using a reference anthropometry standardization technique recommended by Habicht (1974) . Sociode2); the waist-height ratio (WHtR), obtained by dividing the waist circumference (cm) by height (cm) [A digital scale with an accuracy of 0.1 kg and capacity of 150 kg was used for body weight (kg) evaluation. Height was measured with a stadiometer, with an accuracy of 0.1 cm, using a standard technique . The waight (cm) ; and conght (cm) .Body composition was determined using dual-energy X-ray absorptiometry with a GE Lunar densitometer  with the enCORE 2011 software . All metal objects were removed from the women before the scan. The tests included a complete body scan of the patients, in supine position, and all the measures and calibrations were performed by the same operator . At the The database was entered in duplicate in the Epi-Info™ software (version 7.1.5), and data analysis was conducted using Stata software for Windows (version 12.0), considering the outcome diagnosis of breast cancer. We used the Shapiro Wilk test to verify the distribution of continuous variables. The chi-square test was used to identify possible differences in demographic, clinical, and behavioral characteristics between groups. Associations between body composition and physical activity were examined using Pearson's or Spearman's correlation coefficient for parametric and nonparametric samples, respectively. We applied the Mann–Whitney U test (nonparametric distribution) to compare continuous variables between groups. Subsequently, age- and BMI-adjusted logistic regression analysis were determined in order to get the odds ratio (OR) and 95% confidence interval (95% CI). Variables with a significance level of less than 0.05 were considered to be associated with breast cancer.A total of 342 women were included in the study: 116 cases and 226 controls. There was a predominance of non-Caucasian (70.00%) and postmenopausal women (61.11%). Sixty-seven percent of the women were overweight according to their BMI (n = 232), and this prevalence was higher when assessed by DXA . The mean age ± standard deviation was 41.88 ± 6.61 and 42.40 ± 6.40 years among the premenopausal women and 58.80 ± 8.07 and 59.17 ± 7.74 years among the postmenopausal women for cases and control, respectively. Age, ethnicity, menopause status, BMI, percentage of smokers, and alcohol consumption did not differ among groups; however, the level of physical activity was higher in control when compared to cases . BMI  and lower levels of physical activity (p < 0.001) when compared to the control group . The % LOur study showed that physical inactivity, excessive total and abdominal body fat, and lower % LBM are associated with breast cancer in premenopausal women, whereas in postmenopausal women only physical inactivity is associated with the outcome. Some studies have linked breast cancer to these factors. However, in subgroup analysis according to the menstrual status, the results remain controversial. Among the factors that could explain the different results for the association between physical activity, body composition, and risk of breast cancer are the different levels of physical activity , 5 and mAccording to Howell et al. (2014) , there aOne of the possible factors that could associate obesity to a probable protection against breast cancer in the premenopausal stage would be the anovulatory effect which reduces the cumulative exposure of the breast to estrogen. However, this physiological change usually occurs with BMIs consistent with severe obesity , 26, andA cohort study conducted in the United States, with a mean follow-up of 12.9 years, observed that postmenopausal women with a higher percentage of body fat and fat accumulation in the trunk, both measured by DXA, had a higher risk for developing breast cancer  . The difThe relevance of LBM as a protective factor for breast cancer has been questioned . The higA case-control study with 343 Uruguayan women newly diagnosed with breast cancer and 1,125 healthy controls homogenized by age was conducted in a public hospital. The authors observed a positive association between the lowest % LBM and a higher percentage of body fat with breast cancer. The heterogeneity between premenopausal and postmenopausal women was analyzed by means of the likelihood ratio test, but there was no effect modification from menopausal status. The authors suggest that muscles can improve insulin sensitivity by regulating the immune system and myokine production, reducing inflammatory status .No association was found between BMI and breast cancer in women of African ancestry . On the The practice of physical exercises has been highlighted as an important protective factor against breast cancer, since it reduces serum levels of estrogen, insulin, leptin, and proinflammatory cytokines and increases adiponectin. Besides contributing to a lower body adiposity , 6, exerFriedenreich et al. 2015) verified a reduction of approximately 25% in the risk of breast cancer in active versus inactive women in different population groups and all types of activities  . These f5 verifieSome potential limitations of our study were the case-control study design, the use of a questionnaire to assess the level of physical activity, and the absence of food consumption analysis.In conclusion, we found that a low % LBM and a high abdominal adiposity in premenopausal women were associated with breast cancer. In addition, high level of physical activity remained inversely associated with breast cancer in pre- and postmenopausal women.


BRCA mutation and at average population risk for breast cancer based on family history. Most women were either white (50%) or African American (38%) and were 50 years or older (74%). One-third of women (32%) were willing to decrease mammogram frequency (as consistent with the USPSTF guideline), 42% reported being unwilling and 26% were unsure. Multivariate logistic regression showed that feeling worried about breast cancer , greater genetic risk knowledge , and more frequent past mammogram screening  were associated with being less willing to decrease screening frequency. Findings suggest that emerging genomics-informed medical guidelines may not be accepted by many patients when the recommendations go against what is considered standard practice. Further study of the interplay between emotion- and cognition-based processing of the HBOC screen result will be important for strategizing communication interventions aimed at realizing the potential of precision public health.This study aimed to assess women’s willingness to alter mammogram frequency based on their low risk for HBOC, and to examine if cognitive and emotional factors are associated with women’s inclination to decrease mammogram frequency. We conducted an online survey with women (N = 124) who were unlikely to have a  The rationale is that such risk information enables a veritable “win-win” that enables prevention and early detection strategies to be tailored to improve health outcomes while reducing patient burden and health care costs. Concurrently, the US Preventative Services Task Force (USPSTF) has updated screening mammography recommendations holding that asymptomatic individuals who are at low risk for familial breast cancer syndromes (such as hereditary breast and ovarian cancer syndrome [HBOC]) begin mammogram screening at age 50 and that women have biannual mammograms3. Similarly, the American Cancer Society (ACS) announced in 2015 that, it had modified its recommendations to align more closely with the USPSTF4. ACS’s stated rationale was that the modification better balanced the potential benefit of early detection against the now-clearer evidence about the risks of false alarms and overtreatment5.Evidence-based guidelines now endorse using genetics-informed assessments to stratify populations on cancer risk1 and provide guidance regarding who should get a mammogram and when. Implementation of these risk assessment tools at the population level as supported by the CDC Tier 1 evidence6 will identify the majority of women to be at low genetic risk. To date, no one has considered whether HBOC screening could be a “teachable moment” for encouraging the adoption of risk-stratified screening guidelines, particularly for women at low hereditary risk. Understanding how the majority of women who participate in HBOC screening perceive the implications of their results as they relate to breast cancer screening could have significant public health impact.Brief family history screening tools have been scientifically validated for use to stratify risk7. Half of all women getting annual mammograms beginning at age 40, over a 10-year period will be called back for what is determined to be a false positive finding8. Additionally, societal health care costs attributed to annual mammography were estimated at 7.8 billion dollars in 20109. Screening frequency is one of the major drivers of these costs; adoption of USTPSTF guidelines would reduce these costs by half to 3.5 billion9. Thus, increasing breast cancer screening intervals for those not deemed to be at high inherited risk could reduce adverse consequences and lower health care costs14.Despite the established utility of mammography screening for early detection of breast cancer, mammograms can yield false positive results that produce unwarranted fear and psychological stress, and expose women to unnecessary treatment, pain, side effects, and health care costs17. Women did not view these guideline changes favorably, and reacted to reductions in mammography frequency with feelings of distrust as they felt the guideline change was driven by cost saving efforts on the part of insurance companies as opposed to improving their health19. This may be particularly true for women from minority groups who have experienced health care discrimination, commonly report lower trust in health care systems20 and are more skeptical of genomics21. Although many women had stories of anxiety and discomfort related to mammograms, the majority of women stated that they intended to continue with annual screenings, with some wanting screenings more than once a year from an earlier age18. While screening practices that are contrary to guideline recommendations are common, the determinants of patient receptivity to shifting mammography screening frequency have yet to be explored.Convincing women at low risk for HBOC that they could start screening at a later age or decrease the frequency of their mammograms will likely be very challenging, despite the sizeable risk-benefit tradeoff related to the frequency of screening. As evidence, mammography rates did not decrease following the release of the 2009 USPSTF guideline supporting less frequent mammograms starting at age 5023. Important cognitive factors include risk-related knowledge, perceived salience and reliability of information. This level of processing is influenced in turn, by emotional factors such as worry and fear that can motivate self-protective reasoning and influence how risk information is interpreted22. Thus, consideration of these factors will be critical to any efforts to engage women to thoughtfully consider decreasing mammography screening.Conceptual models of information processing can provide a framework for considering factors that might influence willingness to reduce mammography frequency. These models suggest both cognitive and emotional factors that together influence how individuals respond to risk informationTo this end, we conducted an exploratory study aimed to assess women’s willingness to alter mammogram frequency based on their low likelihood to be at risk for HBOC, and to examine if individual cognitive and emotional factors suggested by information processing frameworks are associated with women’s inclination to decrease mammogram frequency.TM 3.0, www.brcagenescreen.org) was used24. B-RSTTM has been endorsed by the USPSTF as one of several validated screening tools that are clinically useful for estimating the probability of BRCA1/2 mutations and identifying women who should be referred for cancer genetic counseling1. This tool uses a validated algorithm which includes breast cancer , bilateral breast cancer, ovarian cancer, male breast cancer and Ashkenazi Jewish ancestry in 1st and 2nd degree relatives26. It should be noted that the B-RSTTM does not incorporate other breast cancer risk factors  for breast cancer risk assessment. The B-RSTTM provides two categories of risk results for BRCA1/2 mutation based on family history: “positive” and “negative”. Individuals who screen “positive” are at heightened risk for carrying a BRCA1/2 mutation and directed to receive genetic counseling. The “negative” category is further sub-divided into “negative-average risk” and “negative-moderate risk”, reflective of the expected familial risk for breast cancer aside from carrying a mutation in BRCA1/2. Women who screened as negative-average risk were told that they were unlikely to carry a BRCA1/2 mutation and were at average population risk for breast cancer based on family history. Those who screened as negative-moderate risk were told they were at low risk (less than 5%) of carrying a BRCA1/2 mutation, and at greater than average population risk for breast cancer.This pilot study was a substudy of a larger project aimed at increasing identification and referral of women at highest risk for HBOC to genetic services. Women were approached in the waiting rooms of three Emory clinic breast imaging centers to complete an HBOC screening tool between April 2016 and June 2017. The Breast Cancer Genetics Referral Screening Tool version 3.0  completed the screening. Among 1,768 women who screened negative (1461 negative-average risk and 307 negative-moderate risk), about 500 were contacted for the online survey. 124 women with a negative-average risk result completed the online survey. All research activities were reviewed and approved by Institutional Review Boards at the Emory University.A total of 3,883 women were approached to complete the B-RSTTM result?” Possible responses were: very unwilling, unwilling, not sure, willing, very willing. Participants’ responses were categorized into willing, unwilling, and unsure.Willingness to decrease mammogram frequency was assessed with the item “How willing would you be to have mammography screening less often if you were found to be at lower genetic risk of breast cancer based on the B-RSTPerceived need for biannual mammogram: Participants were provided with the stem question, “Based on what you know about mammography screening recommendations for your age” and asked to endorse the recommended mammography frequency: biannual, annual, depends on doctor recommendation, and I don’t know. Women’s perceived need for biannual mammogram was calculated as the agreement between their understanding of mammogram frequency and the USPSTF guideline . Provider perceived need for biannual mammogram was assessed from the patient perspective using one 5-point Likert item, “My health care provider thinks that I should have a mammogram every two years.”TM risk estimation: “negative-average risk” (as likely as the average woman).Risk perception: Relative risk perception was assessed by the item “compared to the average woman your age, would you say that you are less likely/as likely/more likely to develop breast cancer.” Risk perception alignment was the 100% agreement of women’s perceived risk with their B-RST27 and Erblich28. It includes seven items with response options of “true”, “false” and “don’t know” to questions such as: “Ovarian cancer and breast cancer in the same family can be a sign of an inherited BRCA1 or BRCA2 mutation.” Recall of B-RSTTM result was scored as correct or incorrect and calculated as the concordance of participants’ self-reported screen result and their actual result. Understanding of results (correct/incorrect) was assessed by two items regarding the likelihood of carrying a BRCA1/2 mutation and the likelihood of breast cancer based on family history. B-RSTTM result acceptance was assessed by a 9-item 5-point Likert scale29, where participants were asked to respond to statements including “The information I received from the B-RST™ result about my risk for hereditary breast and ovarian cancer seems accurate” and “The information I received from the B-RST™ result was missing some important information about me or my family” (reverse-scored). Sum scores range from 0–45, with a higher score indicating a higher level of acceptance (Cronbach’s Alpha = 0.79).Knowledge: Breast cancer genetic knowledge was assessed using a validated scale developed by Lerman30. Participants were asked to respond to statements including “My health care provider will do whatever it takes to give me the medical care that I need” (Cronbach’s Alpha = 0.96). Trust in breast cancer screening guidelines was measured on a 5-point Likert 5-item scale. Participants were asked to “think about national recommendations for breast cancer screening” and indicate whether they agreed or disagreed with statements such as: “The recommendations for breast cancer screening I have heard are trustworthy” (Cronbach’s Alpha = 0.92).Trust: Trust in health care provider was measured on a 5-point Likert scale using five items from the multidimensional trust in health care systems scale33.Cancer worry: Women were asked how often they worried about getting breast cancer with response options from “rarely or never” to “all the time” on a 4-point Likert scale34 was used to measure emotions that might be generated by breast cancer risk information. Women were provided with the stem question, “When I think about breast cancer” and then asked to endorse the extent to which they felt: anxious, calm (reverse coded), upset, confident (reverse coded), and uneasy (Cronbach’s Alpha = 0.89). Total score ranges from 0 to 5; a higher score indicates more negative affect of breast cancer.Negative affect: A shortened 5-item Positive and Negative Affect Schedule (PANAS) scaleTM screen. Possible responses were: personal choice for routine screening and doctor recommendation for routine screening.Reason for current mammogram: Participants were asked to indicate the reason for their mammogram at the time of the B-RSTPast mammogram frequency: Women were asked to report how frequently they had a mammogram in the past two years with answers grouped to “biannually or less” (consistent with USPSTF guideline) or “annually or more.”35. We used a dichotomized age variable  to reflect the USPSTF mammogram screening guideline2. Health literacy was assessed by a single item, “How confident are you filling out medical forms by yourself?” This has been shown to be accurate in detecting inadequate health literacy skills37.Participants age, race, level of education, and annual household income were measured using items developed from the U.S. Census guidelinesTM result recall and understanding, trust in health care), and mammogram history . To increase power, we combined the “unwilling” and “unsure” groups to be one group, “not willing,” in subsequent logistic regression analyses with “not willing” as the reference category. The dichotomized outcome, willing vs. not willing to decrease screening frequency, was regressed on each of the patient factors separately. In all analyses, 2-tailed tests and p-values < 0.05 were used to draw conclusions regarding statistical significance.Survey responses were collated into Microsoft Excel from REDCap, and all data analyses were performed using STATA Version 15.0 . Descriptive statistics analyzed the demographic and outcome variables to describe the study participants. There was no significant difference between the “unwilling” and “unsure” group in the following patient factors: patient socio-demographic characteristics , emotional factors (cancer worry and negative affect), cognitive factors  were either white (50%) or African American (38%) and were 50 years or older (74%) Table . About oThe reason for women’s current mammogram was for routine screening, either due to personal choice (n = 42) or doctor recommendation (n = 75). Few women reported having had a mammogram biannually or less frequently in the past two years , believed that they should have biannual mammogram based on age , or agreed their doctor would support biannual mammogram .One third (n = 40) of women reported being willing to decrease screening (as consistent with the USPSTF guideline), 42% (n = 52) reporting being “unwilling” and 26% (n = 32) were “unsure” about decreasing mammogram frequency.Over half (54%) of women reported feeling worried at least sometimes about getting breast cancer. Breast cancer-related negative affect was moderate . In particular, more than one-third women agreed or strongly agreed that they felt uneasy (48%), or anxious (44%) when they thought about breast cancer.TM result) while 44% indicated they were at lower risk and 6% indicated they were at higher risk.Half of the women perceived themselves to be as likely to develop breast cancer as other women their age , “there are many different genes that when altered can increase cancer risk” (80%), and “a woman who does not have a BRCA1/2 gene mutation can still get breast or ovarian cancer” (79%). However, most women (87%) incorrectly agreed “that about half of all breast cancers are caused by mutations in BRCA1 and BRCA2”.Women demonstrated a moderate level of knowledge related to factors that influence breast cancer risk . The majority of women responded correctly that: TM result as “negative-average risk”. Over half of the women  correctly interpreted that their negative-screen result indicated it was unlikely that they carried a BRCA1/2 mutation, but fewer women  correctly understood that they remained at average risk for breast cancer. B-RSTTM result acceptance  was high .Less than half of women  accurately reported their B-RSTWomen reported relatively high trust in health care providers , but their trust in national professional mammogram screening guidelines was relatively lower .As shown in Table Although our power was limited, we conducted selected multivariate logistic regression analyses. Significant patient factors identified from the bivariate logistic regressions were included in the final multivariate logistic regression model: cancer worry, genetic risk knowledge, and past mammogram frequency. Results indicated that feeling worried about breast cancer , greater genetic risk knowledge scores , and more frequent past mammogram screening  were associated with being less willing to decrease screening frequency (pseudo r-square = 0.17).BRCA1/2 mutation carriers might respond to recommendations for decreased frequency of mammogram screening. These women make up the majority of women who participate in HBOC screening. Women who receive a “negative-average” HBOC screen result are unlikely to have a BRCA mutation and are at average population risk for breast cancer based on family history24. National guidelines support initiating mammography at age 50 with biannual screening thereafter2. We found that a large proportion of women (86%) in the study had adopted routine annual mammogram screening regimen, which is in excess of guideline recommendation. After learning that they were at lower genetic risk of breast cancer, over half (67%) reported that they were either unwilling or unsure about reducing mammography screening. These preliminary results suggest that proactive efforts would be needed to sway the large proportion of low risk women to consider reducing mammography screening frequency.To our knowledge, this is the first study to explore how women screened at low risk of being 23. This approach was particularly novel, as past studies of “deimplementation” of medical overuse have focused on provider and contextual factors39 and not on patients’ processes of “unlearning” ineffective health behaviors. Results from this study support some of the proposed relationships, most notably those between breast cancer worry, genetic risk knowledge, past mammogram frequency, and women’s willingness to decrease mammogram screening.We further explained how individual emotional and cognitive factors influence how willing women may be to adjust their screening based on their genetic risk, guided by information processing models40 or lead to screening avoidance41. Unfortunately, we did not assess worry related to the likelihood of false positive results. Others have shown with a sample of women ages of 40 and 59 that awareness of over-diagnoses (27%) or overtreatment (40%) due to mammography was low42. Prior work has also shown that women experience anxiety about guideline changes and prefer not to change the frequency of their use of mammography18. Due to the widely reinforced mammogram recommendation as the way to prevent breast cancer, negative emotions associated with breast cancer likely would need to be addressed in helping women consider less frequent mammograms. Future larger studies should include a broader array of emotion-related measures based on information processing frameworks.Cancer worry was significantly associated with women being less willing to adopt less frequent mammography screening. The effect of breast cancer worry on screening behavior has been inconsistent; worry may enhance screeningnot being willing to decrease mammogram frequency. We evaluated whether heightened knowledge might be due to cancer worry prompting more information seeking or lessened trust. However, we did not find significant associations between knowledge and worry or trust in this population. Unfortunately, the small sample size precluded us from testing moderating and mediating associations. Given these factors, intervention efforts that solely focus on improving the public’s cancer genetic knowledge may not serve the goal of promoting adoption of evidence-based screening guidelines. Understanding how different types of knowledge impact women’s willingness to de-implement, when appropriate, annual mammogram screening based on their genetic risk, and how relevant knowledge interacts with women’s emotional factors, will be critical to facilitate effective decision making for patients.Greater genetic risk knowledge related to breast cancer was associated with 44. The interplay between emotion- and cognition-based processing of the HBOC screen result may be particularly important to the mammogram decision against the backdrop of discrepancies in public messages about mammography45, the complexity of risk factors of breast cancer, and the uncertainty of potential harms 46. Women faced with this discrepant information will likely default to previous screening behaviors rather than to act on uncertain information. It is evident that most women in the study believed that they should have annual mammogram based on age (90%) and did not believe their doctor would support biennial mammogram (85%). In the context of the widely reinforced one-size-fits-all annual mammogram recommendation being deeply ingrained into patients’ and providers’ perceptions of appropriate medical care, and with public health organizations and advocacy groups pushing screening through advertisements and media campaigns47, effectively implementing risk stratified mammogram screening recommendations may be challenging.We also found that women who had annual or more frequent screening in the past were less likely to forgo future mammograms based on learning more about their breast cancer risk. This finding is consistent with previous researchTM was developed and validated as a tool to identify individuals at increased risk for BRCA1/2 mutations and it does not incorporate other breast cancer risk factors . As such, its predictions for breast cancer risk in the average and moderate range are limited to family history-based information. It should be noted however, that the screen result information sheet did describe non-familial risk factors for breast cancer. Women’s perceptions of the need for annual mammograms may have been influenced by these risk factors.We acknowledge that our study findings are limited due to small sample and require replication. While it was difficult to assess the actual participation, survey completion of 124 from 500 contacted, while not unusual, may have resulted in a highly selective sample. Accordingly, the sample was relatively homogeneous with respect to education, income, and other demographics. Women who were recruited at mammography clinics in one medical system and responded to the survey may not be generalizable to women outside of this context. The small sample size also limited power to explore associations among patient factors and women’s willingness to decrease mammogram frequency. In addition, it should be noted that the B-RST14. To increase the likelihood of adopting genomics-informed medical recommendations, further study of the interplay between emotion- and cognition-based processing of the HBOC screen result will be important, particularly for strategizing communication interventions aimed at realizing the potential of precision public health.Despite these limitations, our findings show that, while some women at low genetic risk for breast cancer were willing to decrease mammogram frequency consistent with the USPSTF guideline, more were unwilling or unsure about reducing the frequency of mammography. Our sample likely represents the most adherent mammography screening population given that the majority of women adopted routine annual screening schedule. The resistance of guideline change among these well-educated adherent screeners may be suggestive of broader resistance to de-implementing annual mammograms among an average risk population of screeners. The use of screening mammography in excess of guidelines by low risk women could divert health care resources from those who benefit most from screening. Moreover, resulting false positive screening results in unnecessary diagnostic work-up, and biopsies could also divert limited health services


Unhealthy dietary patterns are the most important changeable risk factors for breast cancer. The aim of this study was to assess the relationship between dietary patterns and the risk of breast cancer among under-50 year women in the west of Iran.All women under 50 years old with pathologically confirmed breast cancer between 2013 and 2015 who were referred to oncology clinics in the west of Iran, and 408 under-50 women referred to other outpatient clinics who were without breast or other cancers at the time of the study and 2 years later were selected as the control group. The data were collected using the middle-aged periodical care form of the Iranian Ministry of Health and analyzed using univariate and multivariate logistic regression in Stata.The most powerful risk factor for breast cancer was fried foods; the odds ratio of consuming fried foods more than once a month for breast cancer was 4.5 . A dose-response model indicated that increasing vegetable and fruit consumption up to 90 servings per month decreased the odds of breast cancer, but consuming more than 90 servings per month increased the risk.Inadequate consumption of vegetables and consumption of soft drinks, industrially produced juices, fried foods, and sweets were identified as risk factors for breast cancer. In response to these findings, it is necessary to raise awareness and to provide education about healthy diets and the need to change unhealthy dietary patterns.  Cancer is one of the most important causes of death throughout the world . The WorThe epidemiological model of breast cancer in Iran is similar to that of other east Mediterranean and developing countries . On the The American Cancer Society has identified several risk factors for breast cancer, including age, gender, family history, early menstruation, hysterectomy, fibrocystic history, family history of uterine and ovarian cancers, and history of radiation into the chest; the majority of these risk factors are unchangeable . HoweverFew studies have assessed the changeable risk factors of breast cancer in Iran, especially the role of dietary patterns ,13. RegiThis case-control study was performed among 620 women (212 cases and 408 controls) in Kermanshah Province, in the west of Iran. In the first phase, all women under 50 years old with pathologically confirmed breast cancer (235 cases) between 2013 and 2015 who were referred to the radiation therapy, oncology, and chemotherapy clinics of the cancer diagnosis referral center in the west of Iran  were selected as the cases. As In the second phase, the case and control patients were matched by age, with a 4-year range. Due to the possibility of breast cancer incidence in the control group, all persons in the control group were followed for 2 years. During this time period, 28 persons were excluded from the control group: 6 (21.4%) because of having other cancers, 9 (32.2%) persons because of suspicion of breast cancer based on symptoms, 11 (39.2%) persons due to lack of a response, and 2 (7.1%) persons because of pathologically confirmed breast cancer. These 2 persons were added to the case group .Data were collected through verbal interviews, a review of medical records, and telephone follow-ups. To collect data on additional demographic and anthropometric variables, the middle-aged integrated health care form of the Iranian Ministry of Health was used to assess dietary patterns . This quAs indicated in Before collecting the data, informed consent was obtained from the participants. All ethical considerations, including obtaining verbal consent, were approved by the Ethical Committee of Kermanshah University of Medical Sciences.The relationships between the variables were assessed using univariate and multivariate logistic regression. Variables with a p-value <0.3 in the univariate analysis were entered into the multivariate model. Then, using forward or backward methods, variables with a p-value more than 0.05 were removed from the model.Fractional polynomials were used to quantify the effects of patterns of food consumption on the odds of breast cancer. Fractional polynomials are an alternative to regular polynomials that provide flexible parameterization for continuous variables. In this method, the effects of demographic variables and body mass index (BMI) on breast cancer risk were first controlled. Then, the impact of food consumption models was assessed. Fewer than 1% of the data points were missing, and missing data points were deleted from the study. All analyses were performed using Stata version 14.1  with 95% confidence intervals (CIs).In total, 620 women under 50 years old (212 cases and 408 controls) were studied. Their mean age was 41.5±6.2 years and 39.5± 7.1 years for the case and control groups, respectively. No statistically significant relationship was found between breast cancer and place of residence, marital status, employment status, insurance coverage, or BMI in the univariate and multivariate analyses. The odds ratio (OR) of breast cancer increased with higher levels of education, so that the OR of breast cancer in women with primary and secondary schooling was 2.2 in comparison to illiterate women  and the OR for women with university education was 2.8 in comparison to illiterate women .In the univariate analysis, breast cancer risk decreased with increasing fruit consumption, and in the univariate and multivariate analyses, breast cancer risk decreased with increasing vegetable consumption. Therefore, the OR of breast cancer associated with consumption of 2-3 servings of vegetables per month was 2.8 in comparison to daily consumption .The OR of breast cancer in women who consumed soft drinks , industrially produced juices  and solid oils  more than once a month was significantly elevated relative to their counterparts who did not consume those substances or did so no more than once a month.The most powerful risk factor for breast cancer in the univariate and multivariate analyses was fried foods, even though the magnitude of this relationship decreased after controlling for other variables. The OR of breast cancer in women consuming fried foods more than once a month was 4.5 in comparison to women who consumed fried foods never or once a month .A significant relationship was found between sweets consumption and the odds of breast cancer. The OR of breast cancer in women who consumed sweets more than a month was 2.6 in comparison with women whose sweets consumption was in the favorable range  .After controlling for demographic variables, including age, education level, and BMI, a non-linear relationship was found between the odds of breast cancer and consumption of food materials. In particular, the consumption of fast foods and soft drinks increased the odds of breast cancer .The relationship of fruit and vegetable consumption with breast cancer was analyzed using the same model. The odds of breast cancer decreased as fruit and vegetable consumption increased to 90 units per month, but increased at higher levels of consumption .The risk of breast cancer was found to be higher in women who consumed soft drinks more than once a month than in those who did not consume soft drinks or did so once a month. It has been previously reported that the consumption of soft drinks significantly increases the odds of breast cancer. Soft drinks, since they are calorically dense, lead to increases in BMI, obesity, and insulin resistance, which are mediators of cancer risk ,15. The In a meta-analysis of 55 articles, Boyle et al.  assessedDong et al. , in a meOn the basis of the dose-response graph, although the odds of breast cancer increased with the frequency of fast food consumption, the relationship was not significant. The odds of breast cancer associated with consuming fast foods more than 15 times a month showed high variation and a wide confidence interval, which may have been because of the low sample size. Therefore, it did not show statistical significance. Michels et al. , in a stThe most important result of the current study is the highly significant relationship found between consumption of fried foods and the odds of breast cancer, as the odds of breast cancer in women who frequently consumed fried foods were 4.5 times higher than among their counterparts. A study by Agurs-Collins et al.  regardinThe results indicated that the odds of breast cancer in women who consumed unfavorable fats more than once a month  was higher than women who consumed such fats never or once a month. Holmes & Willett  reportedThe dose-response pattern indicated that more frequent sweets consumption increased the odds of breast cancer, with a steep slope. Of note, in a study conducted in Australia, Harray et al.  found thA significant direct relationship was found between the odds of breast cancer and education level. Other studies confirm this result ,28. HoweThe consumption of vegetables is recommend because of their antioxidant properties. An inverse relationship was found between vegetable consumption and the odds of breast cancer. In other words, the odds of breast cancer increased as vegetable consumption decreased. For example, the odds of breast cancer increased when vegetable consumption decreased from daily consumption to weekly or monthly consumption. Boffetta et al.  obtainedNo significant relationship was found between the odds of breast cancer and place of residence. In this regard, previous studies have indicated that differences in the risk of breast cancer according to place of residence are more likely to stem from differences in diet patterns and personal habits than from environmental factors. Additionally, as the lifestyle of people living in rural and urban regions has become more similar, it is expected that differences in the rate of breast cancer between rural and urban regions will decrease in the future .No significant relationship was found between the odds of breast cancer and marital status. However, international studies have indicated that single women have a higher risk of breast cancer than married women. Overall, on one hand, it might seem that married, divorced, and widowed women have no inherent differences in their risk of breast cancer compared with single women, and that the apparent protective effect of marriage may be because of the age of their first pregnancy and childbirth. Additionally, older age at marriage leads to delays in the first pregnancy and childbirth, which are a risk factor for breast cancer. On the other hand, single women less frequently visit doctors, which may lead to late diagnosis and treatment ,33.BMI is known to affect the risk of breast cancer, but no significant relationship was found in the current study. This is in accordance with the study of Alim & Kiziltan , but GalAge is known to be the most important and challenging risk factor for breast cancer, as the risk of breast cancer dramatically increases with age . The curAlthough this study has some limitations, such as not assessing other risk factors such as hormonal medications, the sensitivity and specificity of the logistic model are indicative of the adequacy of the model and the studied variables. Another limitation is the method of measuring nutrition status; although the validity and reliability of the questionnaire have been confirmed, it is known that responses to nutrition questions include both over-reporting and under-reporting. Trained interviewers who were thoroughly familiar with the nutrition questionnaire were used to decrease this type of error. We sought to minimize the inherent risk of bias associated with case-control studies by assessing the treatment history and 2-year follow-up of the control group.In summary, increasing age, higher education levels, inadequate consumption of vegetables, and consumption of soft drinks, industrially produced juices, fried foods, and sweets were identified as risk factors for breast cancer among women under 50. Therefore, it is essential to raise awareness and to disseminate education about a healthy diet and how to change unhealthy dietary patterns. Certain risk factors, such as BMI, place of residence, lack of daily consumption of dairy products and fruits, and consumption of salt and fast foods were not found to be related with the risk of breast cancer in this study, but have been in other studies, suggesting that it is necessary to assess these factors in greater depth.The main measures to strengthen cultural support for consuming a healthy diet that would reduce the risk of breast cancer include acceptance of responsibility by political leaders from the capital to the most remote villages and funding initiatives that promote healthy dietary patterns. More local measures include carrying out national and subnational campaigns such as public walking initiatives; educational sessions; designing brochures, posters and banners and distributing them in cities and villages; and showing appreciation for the healthcare workers who are active in this regard.


Breast density is a risk factor for breast cancer. As density changes across a woman's life span, we studied for how long a single density measurement taken in (post-)menopausal women remains informative.We used data from Singaporean women who underwent a single mammography screen at age 50–64 years. For each case with breast cancer diagnosed at screening or in the subsequent 10 years, whether screen detected or diagnosed following symptoms, two age-matched controls were selected. We studied the excess risk of breast cancer, calculated as an odds ratio (OR) with conditional logistic regression and adjusted for body mass index, associated with 26–50% and with 51–100% density compared with ≤25% density by time since screening.In total, 490 women had breast cancer, of which 361 were diagnosed because of symptoms after screening. Women with 51–100% breast density had an excess risk of breast cancer that did not seem to attenuate with time. In 1–3 years after screening, the OR was 2.22 ; in 4–6 years after screening, the OR was 4.09 (95% CI: 2.21–7.58), and in 7–10 years after screening, the OR was 5.35 (95% CI: 2.57–11.15). Excess risk with a stable OR of about 2 was also observed for women with 26–50% breast density. These patterns were robust when the analyses were limited to post-menopausal women, non-users of hormonal replacement therapy and after stratification by age at density measurement.A single breast density measurement identifies women with an excess risk of breast cancer during at least the subsequent 10 years. •Dense mammographic areas confer an excess breast cancer risk for at least 10 years.•This risk does not wane with time.•The risk is not limited to women who took hormonal replacement therapy. Each screened woman with a breast cancer diagnosis (N = 491) was matched on age and ethnicity with two women (N = 982) with a mammogram who had not developed breast cancer; the same selection of cases and controls was studied previously by Wong et al. 2.2Density was estimated retrospectively using screening mammograms from both the cases and their matched controls. Although this work was undertaken after the case-control status had become known, the final disease status was not revealed during the density scoring process. Percent breast density was estimated in the contralateral breast using the quantitative Cumulus interactive threshold method 2.32 statistic.The differences in the distributions of dichotomised sociodemographic risk factors  between cases and their matched controls were assessed with conditional logistic regression. For the continuous measures of body mass index (BMI) and percent density, the differences  were assessed using the t test. A Shapiro-Wilk test for non-normality was not significant: P = 0.42 for BMI and P = 0.77 for percent density. The differences between cases and controls in the categorical distributions of breast density  were evaluated using the χThe risk of breast cancer associated with breast density was calculated with conditional logistic regression. When the risk was calculated by year since screening, percent density was categorised as ≤25%, 26–50% and ≥51% to avoid cells with small numbers. To keep the models simple, they were adjusted for BMI only, while age and ethnicity were controlled for in the matching. In an earlier analysis of the same data set All analyses were undertaken with R Studio, version 1.1.419.3Of the 491 cancers, 129 (26%) were detected at screening within the trial, and 362 (74%) were diagnosed outside of the trial, most likely as a result of seeking medical advice for symptoms. Among the 491 cases, three (1%) were younger than 50 years at screening, 157 (32%) were aged 50–54, 196 (40%) were aged 55–59, 115 (23%) were aged 60–64 and 20 (4%) were aged ≥65 years. Cases were statistically significantly less likely to have at most primary education than controls; they were also more likely to have a higher BMI, be younger at menarche, to have ever used HRT and were slightly more likely to be nulliparous and premenopausal . These rCases had significantly denser breasts than controls, with 22% of cases and 41% of controls having 0–25% density and 34% of cases and 19% of controls having 51–100% density . Cases hAs expected, the risk of cancer detected at screening or in the subsequent 10 years increased with percentage of breast density, with about a five-fold increase in the risk in women with ≥51% density compared with women with ≤10% density (Only 19 (5%) of the 361 symptomatic cancers in our study were diagnosed within the first year after screening, and the effect of breast density was not statistically significant . Four toThe same patterns were observed when the analysis was restricted to 270 (75%) out of 362 symptomatic cancer case-control trios in which all three women were post-menopausal; when restricted to 227 (63%) of trios in which none of the women previously took HRT; when the analysis included only 310 (86%) trios that comprised of women of Chinese origin and when stratified by age group .4A single mammographic measurement showing high breast density around or after menopause has long-term informational value for a woman's excess risk of developing breast cancer. In our predominantly post-menopausal sample of women undergoing a single mammography screen at age 50–64 years, the overall relative risk was about four in those with dense tissue covering at least half of their mammogram area compared with those with dense tissue in less than a quarter of their mammogram. This relationship was robust when analyses were stratified by age, post-menopausal status and use of HRT. This risk remained significantly elevated for at least 10 years and did not show a tendency to decline towards the end of the observation period.To detect cancers in women with dense breasts missed by mammography, some countries are now offering complementary ultrasound screening Our study was undertaken in a population of Asian descent with a somewhat higher average percent breast density than in many Western populations, although the proportion of women with ≥50% density was not exceptionally high The observation that the ORs were substantially higher for screen-detected cancers than for symptomatic cancers may be somewhat surprising. These ORs are driven not by very high rates of cancer detection in dense breasts but very low rates in non-dense breasts . They arOur results are broadly consistent with those from earlier European and Northern American studies. Byrne et al. The fact that a single density measure in post-menopausal women retains its informational value in the long term may be related to a gradual stabilisation of the decline in breast density after menopause. McCormack et al. Another reason for density measurements retaining their association with breast cancer in the long term may be the relative inelasticity of breast cancer risk to a declining breast density. Women with initially high density do not experience a substantially decreased risk even in the event that their breast density decreases at a later age For a woman's excess risk of breast cancer to diminish to a meaningful degree, the decrease in density may need to be substantially larger than the spontaneous changes brought about by ageing and menopause, estimated at about 1% per year 5A single high breast density measurement identifies  women who continue to have an excess risk of breast cancer for at least 10 years.The authors declare no potential conflict of interest related to this work.Cancer Research UK (grant number: C8162/A16892).M.R. was supported by Department of Health Policy Research Programme (106/0001). It is a collaboration between researchers from seven institutions .O.B. and SWD. contributed to this study as part of the programme of the Policy Research Unit in Cancer Awareness, Screening and Early Diagnosis, which receives funding for a research programme from the Singapore National Medical Research Council.The trial was supported by The funders had no role in study design; in the collection, analysis and interpretation of data; in the writing of the report and in the decision to submit the article for publication.