Breast density is strongly related to breast cancer. Identifying associations between environmental exposures and density may elucidate relationships with breast cancer. Metals and polycyclic aromatic hydrocarbons (PAHs) may influence breast density via oxidative stress or endocrine disruption.n = 222,581) underwent a screening mammogram in 2011 at a radiology facility in the Breast Cancer Surveillance Consortium. Zip code residential levels of airborne PAHs and metals  were assessed using the 2011 EPA National Air Toxics Assessment. Breast density was measured using the Breast Imaging–Reporting and Data System (BI-RADS) lexicon. Logistic regression was used to estimate adjusted odds ratios (ORs) and 95% confidence intervals (CI) for the individual air toxics and dense breasts (BI-RADS 3 or 4). Weighted quantile sum (WQS) regression was used to model the association between the air toxic mixture and density.Study participants  and lead . Associations were stronger for premenopausal women. The WQS index was associated with density overall ; the most heavily weighted air toxics were lead and cobalt.In this first study to evaluate the association between air toxics and breast density, women living in areas with higher concentrations of lead and cobalt were more likely to have dense breasts.The online version of this article (10.1186/s13058-019-1110-7) contains supplementary material, which is available to authorized users. Breast density, a marker of heightened breast cancer risk, may be influenced by environmental insults . Women iAlthough genetics is an important determinant of breast density , accumulBoth polycyclic aromatic hydrocarbons (PAHs) and heavy metals are environmental endocrine disruptors and can induce oxidative stress that may influence the risk of breast cancer. Sources of PAH exposure , includiThe aim of this study was to evaluate the relationship between living in areas of higher airborne metals and PAHs and breast density, with exposures assessed both individually, and using a mixture approach. We hypothesized that women residing in an environment with higher levels of air toxics would be more likely to have dense breasts.www.bcsc-research.org). Five registries provided data for the study: Carolina Mammography Registry, Vermont Breast Cancer Surveillance System, Kaiser Permanente Washington Registry (Washington State), San Francisco Mammography Registry, and New Hampshire Mammography Network. This resource was designed to assess breast cancer screening and patient outcomes from a geographically diverse sample of over 100 community radiology facilities. Women undergoing mammograms at these facilities complete a health questionnaire at each breast imaging exam, which includes items on sociodemographic characteristics, medical history, and breast cancer risk factors. Distributions of sociodemographic characteristics and race in women in BCSC counties are similar to those of the US population [This study utilized the National Cancer Institute’s Breast Cancer Surveillance Consortium (BCSC) . The BCSpulation . Each reSince 1994, the BCSC has prospectively collected data on mammograms conducted at participating radiology facilities. Breast density information was recorded in clinical practice by the interpreting radiologist using the standard clinical scoring information as determined by the interpreting radiologist using Breast Imaging–Reporting and Data System (BI-RADS) categories . Available data elements include demographic characteristics , reproductive characteristics (parity), health history , screening mammography history, use of HT, and menopausal status. Zip code level data on income, poverty, and education was derived from the US Census.n = 285,817 women). If a woman had more than one mammogram in 2011, we selected the first mammogram of that calendar year.The current analysis was limited to women with no personal history of breast cancer who underwent a routine screening mammogram in 2011 and who were not missing either breast density or residential zip code information  National Air Toxics Assessment (NATA), a database that provides information on concentrations of toxic air pollutants nationally. The 2011 NATA is the most recently released version of the data. NATA assessed levels of air toxics by using validated air pollution models that utilizes input from the National Emissions Inventory, a comprehensive compilation of information on major stationary sources , area and other sources , on-road and non-road mobile sources , events (wildfires), and biogenics . The validated air pollution model also incorporates secondary information, specifically the formation of secondary pollutants from reactions between pollutants, and background exposure levels from long-range transport from distant sources .NATA provides census-tract level estimates for polycyclic organic matter, which is predominately composed of PAH  in additr) were estimated. Unconditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CI) when BI-RADS categories were collapsed to a dichotomous variable with BI-RADS 1 or 2 classified as non-dense and BIRADS 3 or 4 as dense. Multinomial regression was used when the outcome was the four-level BI-RADS categories.The primary analysis was a cross-sectional study to estimate the association between living in a zip code with higher exposure to individual airborne toxics and breast density in 2011. Air toxic exposure levels were categorized based on quartiles, and the same cut points were used consistently throughout all analyses except for a sensitivity analysis for select air toxics in which they were characterized using deciles. Breast density was classified using the BI-RADS categories. Descriptive characteristics and Pearson correlation coefficients .We evaluated effect measure modification of the association between air toxics and breast density by menopausal status and hormone therapy use by including a cross-product term in the model and testing the statistical significance using a likelihood ratio test. We also considered whether PAH or selenium exposure modified the association between the remaining airborne metals and density. These specific exposures were selected as potential effect measure modifiers because selenium has been hypothesized to counteract the negative impacts of metals such as cadmium  and PAHsIn sensitivity analyses, we considered further covariate adjustment for rural/urban status, hormone replacement therapy, and BMI. BMI data were not collected at all study sites, and BMI was missing for many women (45%). Therefore, we examined the impact of adjusting for BMI as a confounder in analyses limited to BCSC participants with non-missing BMI. We additionally tested whether BMI was correlated with air toxic levels using Pearson correlation statistics.. The data were randomly split into a training (40%) and validation (60%) dataset. The weights were empirically determined in the training dataset via bootstrap sampling (n = 100). In WQS, weights can range between 0 and 1 but are constrained to sum to 1 across the individual components of the mixture. If all air toxics received equal weights, the weight for each would be 0.1. Weights greater than 0.1 signify a higher contribution to the weighted index than expected; higher weights indicate stronger associations with breast density. The strengths of WQS include the estimation of an overall mixture effect as well as the identification of the exposures that appear to drive the association. WQS was selected as prior simulation studies have shown it to have a good sensitivity and specificity compared to other mixtures approaches [As a secondary analysis, we used weighted quantile sum (WQS) regression to evaluate the relationship between the air toxic mixture and breast density overall. WQS has been described previously –34. In tproaches , 33.n = 100,107) had dense breasts, defined as BI-RADS 3 or 4 .Further adjustment for rural/urban status and hormone replacement therapy did not substantially alter our results (data not shown). In analyses limited to women with non-missing BMI (which necessitated dropping registries that did not collect BMI), associations between air toxic levels and breast density were similar in models with and without adjustment for BMI, suggesting that even though BMI is related to breast density, it was not influential as a confounder in these analyses . A quartile increase in the WQS index resulted in a 20% higher odds of having dense breasts. Only two air toxics contributed meaningfully to the overall effect. These were lead (weight = 0.56) and cobalt (weight = 0.44).In this large study population, we observed that living in areas of higher exposure to certain air toxics, especially lead and cobalt, was associated with higher odds of having dense breasts, particularly in premenopausal women. To the best of our knowledge, this is the first study to consider the relationship between air toxics and breast density. Breast density is a strong risk factor for breast cancer ; our fin2) and PAH exposure has been suggestively related to breast cancer [2.5, which is a measure of a mixture of many compounds including toxic metals [; these results are consistent with the findings presented here. None of these prior studies evaluated the relationship between breast density and metallic air toxics or PAH exposure. Both metals and PAHs are known to induce oxidative stress [Air pollution has been increasingly shown to be relevant for breast cancer . Traffict cancer , 36–39. t cancer , 40, 41 t cancer , 43. In t cancer . Howevert cancer –14. A pre stress , 44, 45 e stress , 23, 46.e stress  are hypoAir pollution is a complex mixture of many types of exposure, and a strength of this study is the inclusion of a mixture analytic approach to better mimic real life exposure to multiple correlated toxics. The use of the WQS method allows for the quantification of an overall effect—we observed 20% higher odds of dense breasts with each increasing quartile of the mixture exposure index. The WQS approach also permits the identification of the “bad actors” in the presence of correlated exposures. Lead and cobalt were identified to be the only weighted compounds of interest, suggesting they may drive the association, a finding that was consistent with the associations observed for those metals in the individual analysis. A limitation of WQS is that it only considers exposures that exhibit their effect in the same direction ; howeverIn epidemiologic studies, sources of PAH exposure, including outdoor , 39, 48 Most of the research on heavy metals and breast cancer risk has focused on the role of cadmium . The finInconsistent findings have been reported regarding the relation between urinary cadmium and breast density , 11 althAirborne exposures are only a single exposure source, and participants may be exposed to these compounds through other sources including their diet, water sources, and tobacco smoke. We were unable to capture these other sources of exposure in this study. The BCSC did not collect information on cigarette smoking history, an important source of both PAHs and metals , 62. SmoWe chose to use the most recently available NATA data release, rather than incorporating prior years of exposure because substantial changes have been made in the methodology over the years. The relevant etiologic window for exposures to alter breast density is unknown. This study was consequently cross-sectional by design, although it is likely that estimated 2011 air toxic levels may also represent past exposure. Previous studies have shown that density continues to change, even later in life , and thaWe adjusted for relevant covariates including race, zip code level education and income, which were important confounders in this study, and conducted sensitivity analyses for other potential confounding factors. Despite this, we cannot rule out the possibility that residual confounding may be present. Previous studies have reported that women in urban locations have elevated breast density compared to rural populations . In sensThis study was very well-powered, and the study population is diverse and generalizable. The air toxics were assessed by the EPA using a validated air pollution model. NATA estimates of lead have been previously related to body burden metal measures in children, supporting the validity of their air toxic models . The dosIn this large, geographically diverse study, we found that women who live in areas of higher exposure to certain air toxics, especially lead and cobalt, were at higher odds of having dense breasts. These results were stronger in premenopausal women. This is the first study to evaluate the relationship between air toxic metals and PAHs in relation to breast density. Understanding the determinants of breast density is important, as women who have dense breasts are at a four to fivefold higher risk of developing breast cancer . Breast Additional file 1:Figure S1. Deciles of selected air toxics and breast density, Breast Cancer Surveillance Consortium, 2011. Table S1. Pearson correlation coefficients for air toxics, Breast Cancer Surveillance Consortium, 2011. Table S2. Air toxics and BI-RADS score, Breast Cancer Surveillance Consortium, 2011. Table S3. Air toxics and breast density by hormone therapy use (HT), Breast Cancer Surveillance Consortium, 2011. Table S4. Metallic air toxics and breast density by PAHs, Breast Cancer Surveillance Consortium, 2011. Table S5. Metallic air toxics and breast density by selenium, Breast Cancer Surveillance Consortium, 2011. Table S6. Air toxics and breast density when limited to participants with non-missing body mass index, Breast Cancer Surveillance Consortium, 2011. (DOCX 83 kb)


The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman’s familial risk.We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline.P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk.The strength and direction of the BMI risk association depended on baseline menopausal status (The greater a woman’s familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer. Body mass index (BMI) is an intriguing risk factor for breast cancer because its association with the disease depends on time of life. Greater BMI has been found to be associated with an increased risk for postmenopausal women –9, whileBMI is an important risk factor because it is potentially modifiable. The fact that greater BMI appears to be protective at young ages, yet has the opposite association in later life, presents a potential problem for simple cancer control messaging; therefore, its consequences need to be quantified. A prospective study and a case-control study have found that the increased risk associated with higher BMI increases with time after menopause but is not evident until 10 years post menopause , 17.A better understanding of how the BMI-associated risk varies with age and menopausal status is needed. It is interesting that, from genome-wide association studies, genetic risk scores based on single-nucleotide polymorphisms (SNPs) that predict higher BMI in childhood or adulthood are associated with lower risk of both premenopausal and postmenopausal breast cancer , 19. UndFamily history is another important risk factor for breast cancer that could not exist without there being a very strong gradient in underlying familial risk. To explain an overall average estimate of a 2-fold increased risk associated with having an affected first-degree relative, there must be at least a 20-fold inter-quartile risk ratio across the underlying familial causes , 22. FamWith the advent of gene panel testing for high-risk mutations in known breast cancer susceptibility genes –25, famiThis issue of multiplicative and additive interaction with familial risk must be considered for each risk factor. If there is no difference in strength of associations by familial risk and the study is well-powered, advice on that risk factor’s relevance can be confidently given to women across the full spectrum of familial risk. In theory, if there are no interactions between risk factors on the multiplicative scale then there will be additive interactions , 27. KnoTo address the issues of whether breast cancer risk associated with BMI depends on the age of a woman, her menopausal status, and her underlying familial risk, we conducted a prospective study of women across broad ranges of age and familial risk at baseline.The Breast Cancer Prospective Family Study Cohort (ProF-SC) comprises baseline and follow-up data from the Breast Cancer Family Registry (BCFR) and the Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (kConFab) (for full details see ). These BRCA1 and BRCA2 mutation carriers in Utah; Ashkenazim in Ontario). For kConFab, participants were recruited continuously from 1997 onwards.Probands and their family members were recruited to the BCFR and kConFab according to site-specific protocols –30, 32. For the BCFR, systematic follow ups were conducted 10 years and 15 years after the first round of recruitment to the BCFR, while the kConFab participants have been followed up every 3 years. At follow-up, the risk factor and cancer family history questionnaires were updated and participants were asked to provide the date of death of any deceased relatives.The BCFR and kConFab used the same risk factor questionnaire . At baseWe studied women who were initially unaffected by invasive breast cancer or ductal carcinoma in situ of the breast up until 3 months following completion of their baseline questionnaires. To be eligible, women also had to be aged 18 to 79 years at baseline, have at least 2 months of follow up , and not have had a bilateral risk-reducing mastectomy at baseline. For these analyses, we excluded 331 women for whom we did not have complete data for BMI, 1220 women for whom we were unable to determine menopausal status, and 42 women for whom we did not have complete data for both BMI and menopausal status. From the original cohort of 17,628 women, this left 16,035 (91.0%) available for analysis.BRCA1 and BRCA2 mutation testing was also used to calculate risk. Mutations were protein-truncating or missense mutations classified as deleterious by the Breast Cancer Information Core [BRCA1 and BRCA2, respectively.Baseline BMI was calculated as current weight (kg) divided by squared height (m) using information captured by the baseline risk factor questionnaire. We used log-transformed BMI in analyses. Baseline menopausal status was determined from questions asking about time since last menstrual period and reason for cessation of menstruation. For each participant, the 1-year risk of invasive breast cancer and the lifetime risk (risk to age 80 years from birth) were calculated using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) version 3 using pedigree information at baseline. This algorithm uses information on breast, ovarian, and male breast cancer and age at diagnosis for first, second, and third-degree relatives, along with date of birth, vital status, age at interview or death, and country-specific age-specific incidences , 36 to cion Core . Detailsion Core . SensitiBRCA1 and 519 BRCA2 mutation carriers. We also conducted sensitivity analyses by including women with missing menopausal status and including a parameter for this group.Time in the study began 2 months after the age of completion of the baseline questionnaire and ended at whichever came first of the following: age last known to be alive, diagnosis of invasive or in situ breast cancer, bilateral risk-reducing mastectomy, age 80 years, or age at death. We conducted sensitivity analyses by including only invasive breast cancers and by excluding the 652 To investigate whether the hazard ratios (HRs) for the associations between risk of breast cancer and BMI differed by the underlying familial risk, we used Cox proportional hazard models with age as the time axis and stratified by study site and birth cohort in 10-year groups. Familial risk was defined as the log 1-year incidence of breast cancer predicted by BOADICEA adjusted for age and birth cohort. We fitted interaction terms between risk factors and familial risk.2) distributions (likelihood ratio criterion). We considered many reproductive and other factors  as potential confounders and retained only those that were nominally statistically significant. Analyses were therefore adjusted for history of benign breast disease, race/ethnicity and education. Because the cohort included families with multiple members, robust estimates of confidence intervals (CI) were calculated accounting for clustering by family. Tests of the proportional hazards assumption were based on Schoenfeld residuals. From the test for proportional hazards, we found evidence for non-proportionality only for study site. We therefore stratified all analyses by study site and there was no longer any evidence of non-proportionality. Stata version 14 [Statistical inference was made under maximum likelihood theory, including consideration of the changes in log likelihood between nested models compared with appropriate chi-squared (χrsion 14  was used2). All statistical tests were two sided, and P values < 0.05 were considered nominally statistically significant.We plotted the predicted age-specific absolute cumulative risk for women with different BMIs and different familial risks based on BOADICEA and underlying age-specific incidences from the Surveillance, Epidemiology, and End Results Program –43. We cFor the 16,035 women from 6701 families  = 2.4; median = 2; range = 1–75), the mean age at enrollment was 47.3 years  and the mean duration of follow up was 10.5 years (SD = 4.7). There were 896 reported incident breast cancers . Details of the participants from the seven study sites are given in Table BRCA1 and BRCA2 mutation carriers.Figure Figure P = 0.002) and on menopausal status  at baseline. When we modeled both together, the most important factor was baseline menopausal status because once this had been taken into account , the BMI risk association with age at baseline  was no longer significant. Comparison of log likelihoods from model IV versus model III shows that there was no evidence for an interaction between age at baseline and menopausal status (χ12 = 0.01). A subsequent analysis found that there was also no evidence for an association with age at baseline for postmenopausal women . Therefore, the best-fitting model for the BMI association included an interaction term between BMI and menopausal status only (model III).The results from multivariable Cox models are shown in Tables P < 0.001), there was evidence of an association with familial risk . The other models show that there was no evidence for an interaction of 1-year BOADICEA score with menopausal status , with BMI , or with the interaction of BMI and menopausal status . That is, there was no evidence that the multiplicative interaction between BMI and menopausal status differed by familial risk irrespective of how we modeled the BMI association We also re-analyzed the data by including women with missing menopausal status and putting them in a category of their own. This made no difference to our general findings of no evidence for gene–environment interactions on the multiplicative scale.Table Figure absolute breast cancer risk gradient with BMI increases with age after menopause, and with underlying familial risk. There are three key findings of clinical and biological significance and they are illustrated in Fig. Using a large international prospective cohort enriched for women with a family history of breast cancer  we have First, we found that greater BMI at a young adult age is associated with a decreased risk of breast cancer, as have others . We haveSecond, our modeling confirms that BMI is associated with an increase in risk once a woman becomes postmenopausal. In terms of differences in absolute risk, it is not until a woman is in her mid to late 50s that the risk manifests; the influence on absolute risk then increases with age.Third, our modeling predicts that the greater a woman’s familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. We base this on our finding that, in terms of multiplicative risk, the association of breast cancer with BMI did not differ for women at different underlying familial risk Table . Unlike As illustrated in Fig. One potential limitation is that a change in the BMI association with baseline menopausal status could be due to unmeasured confounders. For this to happen, such confounders would have to have a similar menopausal-dependent risk association. As most risk factors related to BMI  do not have clear differences in association by menopausal status, unmeasured confounding is not likely. Other limitations include limited power to address issues specific to mutation carriers and hormone receptor status of tumors. The evidence of whether the protective association of BMI in early life applies solely to estrogen receptor negative disease is less consistent, with contradictory findings from two meta-analyses , 51 and BRCA1 to function as a tumor suppressor [Although the negative breast cancer risk association with childhood and adolescent BMI is small in terms of absolute risk, understanding this in the light of the genome-wide association studies results , 19, whippressor , pre-pubppressor .An explanation of the negative association with childhood and adolescent BMI might be found in the growth of mammographically dense tissue and changes to the architecture surrounding the mammographically dense tissue, which develops and grows rapidly in adolescence . ImportaBRCA1 [Laboratory studies have given insights into the mechanisms that might explain why weight gain and metabolically rich environments increase postmenopausal breast cancer risk, with implications for prevention . These mBRCA1 .In summary, the negative association with BMI in premenopausal women has a much smaller influence on absolute risk than the positive association with BMI in postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk.absolute breast cancer risk gradient with BMI increases with age post menopause, and with underlying familial risk. We argue, therefore, that there is no discrepancy between the conclusions of the Mendelian randomization studies [Our modeling predicted that, for young and premenopausal women, the decrease in breast cancer risk associated with increasing BMI does not have a substantial influence on absolute risk in those periods of life. Our modeling also predicted that the  studies , 19 and  studies , maintai


P=0.17; MS HR: 0.99, 95% CI: 0.92-1.07, P=0.85); however, a weak, positive association was observed for GrimAgeAccel and invasive breast cancer . Stratification of invasive cancers by menopause status at diagnoses revealed the association was predominantly observed for postmenopausal breast cancer . Although the MS was unrelated to breast cancer risk, we find evidence that GrimAgeAccel may be weakly associated with invasive breast cancer, particularly for women diagnosed after menopause.Measures derived using blood DNA methylation are increasingly under investigation as indicators of disease and mortality risk. Three existing epigenetic age measures or “epigenetic clocks” appear associated with breast cancer. Two newly-developed epigenetic mortality predictors may be related to all-cancer incidence, but associations with specific cancers have not been examined in large studies. Using HumanMethylation450 BeadChips to measure blood DNA methylation in 2,773 cancer-free women enrolled in the Sister Study, we calculated two epigenetic mortality predictors: ‘GrimAgeAccel’ and the ‘mortality score’ (MS). Using Cox proportional hazard models, neither GrimAgeAccel nor the MS were associated with overall breast cancer incidence (GrimAgeAccel hazard ratio [HR]: 1.06, 95% confidence interval [CI]: 0.98-1.14,  Age related changes to blood DNA methylation (DNAm) have been extensively reported –4 and seWhile epigenetic clocks were designed to predict the biological consequences of aging, other combinations of CpGs have been identified to predict mortality , 27. GriGrimAgeAccel was previously reported to be associated with all-cancer incidence . Using DThe ‘mortality score’ (MS), a separate DNAm-based predictor, was also designed to predict all-cause mortality . Using 5Although GrimAgeAccel and the MS were designed to predict all-cause mortality, they may be useful in predicting cancer incidence. In additional to being strongly associated with all-cancer incidence, GrimAgeAccel may also predict menopause timing ; the MS P< 0.001), an age-adjusted MS was derived by regressing the MS on chronological age and predicting the residuals. The calculated residuals represent a MS that is independent of chronological age; as expected, this score and GrimAgeAccel were not correlated with chronological age  (P< 0.001)  had an average age of 56.6 years (standard deviation [SD]= 8.8 years); 70% of whom reported being postmenopausal. The women who developed breast cancer tended to be older at enrollment, drank more alcohol, were less physically active, had later ages at menopause, and were more likely to report postmenopausal hormone use . DistribP= 0.61) . However< 0.001) .in situ [DCIS] combined), in unadjusted models, neither of the epigenetic mortality predictors were associated with breast cancer incidence  (P=0.08) (P=0.41) (P=0.65) and neither the GrimAgeAccel nor age-adjusted MS metrics were associated with DCIS   . In anal(P=0.08) . However(P=0.41) . The age P=0.61) .P=0.04; age-adjusted MS HR: 0.99, 95% CI: 0.91, 1.08, P=0.82) (P=0.09) (P=0.40). No meaningful associations were observed for either epigenetic mortality predictor and invasive ER-negative tumors  . Account P=0.82) . Neither P=0.82) . A weak,(P=0.09) ; model ae tumors .P<0.001); cystatin C ; growth differentiation factor-1 ; leptin ; and tissue inhibitor metalloproteinase 1 . After adjustment for breast cancer risk factors, associations remained for the DNAm-predictors of cystatin C  and leptin . Similar patterns were observed for invasive breast cancer, although associations with DCIS tended to be weaker.As a post-hoc analysis to further interrogate the GrimAgeAccel metric, the separate DNAm-predictors that comprise DNAm GrimAge were tested with breast cancer overall and stratified by invasive cancers and DCIS. These components are DNAm-based predictors of circulating plasma protein concentrations, rather than directly measured concentrations. In unadjusted models, five DNAm GrimAge components were associated with breast cancer . SpecifiUsing a nationwide, prospective cohort designed to identify novel breast cancer risk factors, we found a weak association between GrimAgeAccel and invasive breast cancer. Further stratification of invasive breast cancers by tumor ER status and menopause status at diagnosis revealed somewhat enhanced associations between GrimAgeAccel and incidence of ER-positive and postmenopausal breast cancers. Although our findings suggest that this epigenetic mortality predictor may be a weak marker for these specific breast cancer subtypes, in post-hoc analyses, we found that some of the individual components of DNAm GrimAge appeared to have stronger associations with breast cancer. These components are DNAm-based predictions of circulating plasma proteins and are not based on direct measurements in study subjects. Despite the moderate correlation with GrimAgeAccel, the MS was not related to breast cancer incidence.Although GrimAgeAccel and the MS were both designed to predict all-cause mortality, we only observed breast cancer associations with GrimAgeAccel. Differences in the design of these two mortality predictors may explain the different associations: unlike the MS, DNAm GrimAge did not directly select mortality-associated CpGs. Instead, DNAm GrimAge is based on CpGs that are predictive of mortality-associated risk factors, specifically, smoking pack-years and various plasma proteins . InteresBoth epigenetic mortality predictors include CpGs previously reported to be associated with past smoking behaviors , 27, a sWhile we focused on unadjusted association estimates for the epigenetic mortality predictors, we found that adjustment for breast cancer risk factors attenuated associations. Although unadjusted analysis is appropriate given that we were primarily interested in assessing predictive utility of the epigenetic mortality predictors, the attenuation of the associations suggests the GrimAgeAccel metric may only be a marker of breast risk factors, rather than having independent associations with disease risk. Conversely, associations for the DNAm-predictors of cystatin C and leptin were robust to adjustment and may be useful DNAm-based markers for predicting breast cancer. Notably, in the FHS where these markers were developed, the DNAm-predictors of these proteins only had moderate correlations with directly measured concentrations  . AnotherIn summary, we find that the GrimAgeAccel mortality predictor was weakly associated with postmenopausal and ER-positive invasive breast cancers. Given the reliance on smoking-associated CpGs, it is perhaps unsurprising that the associations with breast cancer incidence were weak. Other components of DNAm GrimAge, however, appeared to be useful in predicting breast cancer. Blood DNAm may be a useful matrix to derive novel breast cancer predictors. For example, epigenetic clocks were designed to capture age effects and are associated with breast cancer incidence . Single in situ), and 1,479 additional women who developed breast cancer after blood draw (data release 6.0). Whole blood samples and informed consent were obtained at a home visit. The institutional review boards at the National Institute of Environmental Health Sciences and the Copernicus Group approved the study.The Sister Study is a prospective cohort of 50,884 cancer-free women, recruited from the United States (including Puerto Rico) and enrolled between 2003–2009 . EligiblProcessing procedures for the DNA samples have been previously reported . GenomicEnmix R software package was used for methylation data preprocessing and quality control [https://sisterstudy.niehs.nih.gov/English/coll-data.htm. GrimAgeAccel was calculated using an online calculator (https://dnamage.genetics.ucla.edu/home) and a continuous version of the MS was calculated as described by the developers [The  control . This in control . Data frvelopers .P-values. We treated chronological age as the time-scale in all models. For the primary analysis, we combined invasive and ducal carcinoma in situ to represent breast cancer overall. In secondary analyses, we considered those categories separately. We also investigated associations for invasive breast cancer by menopausal status at diagnosis and tumor estrogen receptor status. Because we were interested in assessing predictive utility of these biomarkers, we focused on unadjusted associations. However, we also examined associations accounting for established breast cancer risk factors, including: body mass index (BMI), menopause, a BMI-menopause interaction term, physical activity, alcohol intake, parity, age at first birth (among parous), age at menarche, breastfeeding duration, and hormone therapy and oral contraception duration [Although GrimAgeAccel was designed to be independent of chronological age, the MS was not. We therefore regressed the MS on chronological age and predicted the residuals to create a MS that was independent of chronological age to use in our main analyses. We assessed Pearson correlations between the epigenetic mortality predictors and chronological age. We standardized the epigenetic mortality predictors and the individual DNAm GrimAge components to have means of zero and standard deviations of one. To examine associations with breast cancer risk, we used case-cohort Cox proportional hazard models to calculate hazard ratios, 95% confidence intervals and duration , 53–57. Supplementary FiguresSupplementary Tables


Evaluate the beliefs about the risk factors for breast cancer in a population of women from the western Amazon and determine the factors associated with the higher belief scores presented by this population. >40 years residing in Rio Branco, Acre, Brazil. An American Cancer Society questionnaire was applied to assess the knowledge, attitudes, and beliefs about breast cancer. A population-based cross-sectional study included 478 women aged The main beliefs about the risk factors for breast cancer were breast trauma (95%), use of underwire bra (58.5%), and a high number of sexual partners (55.5%). Women from younger age groups presented higher belief scores  than those of women from older age groups. A strong association was noted between high knowledge scores of risk factors and signs/symptoms of the disease and high belief scores in the study group .The results indicate the existence of important beliefs related to the risk factors for breast cancer. Women from younger age groups, women who have seen a gynecologist in the past 2 years, and women who had more knowledge about the risk factors and signs and symptoms of breast cancer had higher belief scores. Breast cancer is a severe public health problem in Brazil and worldwide. Breast cancer is the most common cancer among women (second only to non-melanoma skin cancer) and has the highest mortality rates . This cancer is stigmatized because it involves a multisymbolic female organ, may be fatal, and treatment (mastectomy) typically involves a body-mutilating procedure. Therefore, breast cancer is surrounded by strong myths, fears, and connotations that are beyond the clinical understanding of the disease .Early detection of breast cancer by regular mammographic screening is one of the most effective methods to promote early treatment and increase the survival rate. However, the responsibility of women for achieving and maintaining good health conditions, the importance they attribute to healthy behaviors and preventive actions, the way they experience the disease, their expectations about the resolution of the problem, and their past experiences can significantly affect their health behaviors .Kleinman (1981) warns of the need to consider health care in different societies as socially organized responses that are part of a cultural system, which he refers to as the “health care system”. The health care system and other cultural systems include a set of beliefs about the causes of illnesses; rules governing treatment choices and evaluations; and socially legitimized statuses, roles, power relations, interaction models, and institutions.Studies conducted with populations from different cultures indicate the existence of a set of beliefs about the causes of breast cancer . In Australia, a population-based study of 3,005 women found that 54.8% believed that the use of deodorants increased the risk of breast cancer . In Pakistan, a study demonstrated that 32.7% of women aged 18 to 70 years believed that wearing black clothes increases the risk of breast cancer . Other factors still not widely recognized by the scientific community, such as stress  and breast trauma, have been considered by women of different cultures as risk factors for the disease .The concept of knowledge and beliefs used in the present study is based on those established by Hume (2000), which defines that knowledge and belief  are independent epistemologically and correspond to distinct cognitive abilities, and the ability to generate beliefs is complementary to the ability to generate knowledge. Leventhal’s theory of self-regulation, which is often referred to as the “common-sense model,” postulates that individuals’ cognitive representations of a disease guide health behaviors, including adherence to treatment and changes in health practices . Therefore, beliefs play a significant role in determining how women understand and explain breast cancer, and this understanding may have a strong impact on behaviors related to breast cancer screening. In addition, sociocultural and psychological barriers that may affect the decision to seek health care include denial of personal risk, fatalism attributed to the disease, lack of confidence in cancer treatment, and fear of becoming a burden to the family . In this sense, understanding the beliefs about breast cancer and associated factors from a cultural perspective is essential, especially in culturally mixed populations, such as the Brazilian population. The city of Rio Branco, Acre, is located in the western Brazilian Amazon. The first studies evaluating breast cancer in this population were conducted in 2011. The results indicated that this cancer had the highest incidence and mortality rates  among women, and that cancer-specific survival was high . In Brazil, no quantitative population-based studies to date analyzed the set of beliefs of women about the etiology of breast cancer. Therefore, the objective of this study is to evaluate the set of beliefs about breast cancer risk factor and the associated factors among women aged > 40 years living in Rio Branco, Acre, Brazil.This study is a subproject of a leading study titled “Brazilian Breast Health Knowledge, Attitudes, and Practices(KAP) Survey,” from the National School of Public Health of the Oswaldo Cruz Foundation. A population-based cross-sectional study included a sample population obtained by two-stage cluster sampling as detailed in previous studies . Briefly, from 250 census tracts defined by the Brazilian Institute of Geography and Statistics(IBGE) for the 2000 census , 35 census tracts that were previously used by the National Household Sample Survey were selected in 2006. Of these data, 25 households within each sector were randomly selected with the final selection of 875 households. Eventual losses and refusals were accounted for by selecting an additional 15% of households, totaling 977 households, which represent the population geographically distributed in the municipality of Rio Branco. From 1,516 residents aged > 18 years in the selected households, all women aged > 40 years (n = 478) were interviewed. Whenever a selected household was closed or the resident was absent, the interviewer would make at least three different attempts (at different days and times) to contact the resident in the household.Data were collected from July 2012 to March 2013 by trained interviewers. For quality control of data collection, weekly team meetings were conducted to clarify doubts and reinforce the training provided to interviewers. In addition, each interviewer was accompanied by a researcher at different stages of data collection. A semi-structured questionnaire developed by the American Cancer Society translated and back-translated into Portuguese was used for data collection. The instrument was organized in modules, which include data on sociodemographic and epidemiological characteristics, health care, women’s experiences and understanding of the disease, knowledge about breast cancer risk factors, signs, and symptoms; and beliefs about risk factors.Belief variable was assessed using questions related to the set of beliefs on the etiology of breast cancer. The study population was asked whether “hit in the breast”; “having many sexual partners”; “food additives”; “consumption of genetically modified foods”; “stress”; “depression, anger, bitterness, or resentment”; “great life disappointments”; “oral sex” and “using underwire bra” would increase the probability of breast cancer.Responses regarding the beliefs about the risk factors for breast cancer were scored from 0 to 2. A score of “0” was assigned to the belief that the analyzed factor did not increase the risk of developing breast cancer. A score of “1” was assigned to the belief of a moderate increase in the risk of breast cancer. A score of “2” corresponded to the belief that the analyzed factor strongly increased the risk of developing breast cancer. Women’s beliefs about breast cancer ranged from 0 to 18 points. The score was evaluated continuously and subsequently categorized. The belief variable was categorized using tertiles, such that a low belief score was defined by the first tertile (< 7 points), an intermediate belief score was defined by the second tertile(7 to 11 points), and a high belief score was defined by the third tertile(> 11 points). The sociodemographic and epidemiological variables studied were place of residence, age, schooling , marital status(without a partner/with a partner), history of pregnancy (yes/no), breastfeeding over 1 month(yes/no), menopausal status (yes/no), and hormone replacement therapy(yes/no). With regard to health care, Pap smear testing(yes/no), types of health services used , without SUS, or mixed services), and seeing a gynecologist in the past 2 years (yes/no) were evaluated. The interviewees were asked about their experiences and understanding of breast cancer by using the following questions: “Have any of your immediate or extended family members ever had breast cancer?” (yes/no), “Would you say your chance of getting breast cancer is low, moderate or high?” (low/moderate/high) “If you had breast cancer would you want to know?” (yes/no), “Do you think that a woman who has never had any family members with breast cancer can get breast cancer?” (yes/no), “How likely do you think it is that someone will die if they get breast cancer?”, “What extent do you think that early detection of breast cancer will influence a person´s chance of surviving the breast cancer?”(a lot/not much/nothing), “Do you think you can have breast cancer without having a lump or nodule?” (yes/no), “If a woman finds a lump or nodule in her breast, would you say the chances of it being breast cancer are low, moderate or high?” (low/moderate/high). Knowledge level about breast cancer was evaluated by scoring the knowledge of the risk factors and disease signs/symptoms, as previously described .In the statistical analysis of the data, the frequency distribution of the questions that composed the outcome variable (belief score) was determined. Then, correlation between independent variables and belief’s score was determined by comparing the means using Student’s t-test for independent samples. Associations between independent variables and belief’s score at a significance level of 5% were analyzed using simple linear regression to assess the effect of the independent variables on the belief score. Subsequently, multiple linear regression was used to evaluate the relationship between the belief score of risk factors for breast cancer and the following factors: sociodemographic and epidemiological characteristics; health care; breast cancer experiences and understanding; and knowledge about risk factors and disease signs/symptoms adjusted for age and schooling. Pearson chi-square test was used to analyze the categorized outcomes .All statistical analyses were conducted using the SPSS statistical package version 20.0. The Human Research Ethics Committee of the National School of Public Health (CEP-ENSP) approved the present study, and informed consent was obtained from all study participants.>40 years (mean age of 55.6±11.07 years), and the most common age group was 40 to 49 years(35.6%). Of the total sample, 93.1% women lived in urban areas, 10.3% had more than 12 years of schooling, and 96.7% had a history of pregnancy. Approximately 75% reported having postmenopausal status, of whom 77.6% did not use hormone replacement therapy. The Brazilian SUS was used by 66.5% of the participants, and 60.3% of the sample reported seeing a gynecologist in the past 2 years. The sample consisted of 478 women aged Approximately 11.0% of women reported knowing someone with breast cancer. Among the interviewees, 9.5% believed they had a high probability of developing the disease, 92.4% would want to know if they had breast cancer, and 90.5% responded that a woman who did not have relatives with breast cancer could get the disease. Approximately 25% of the respondents thought that the disease was fatal, 51% believed that a woman could have breast cancer without having a lump or nodule in the breast, and 32.1% reported that the likelihood of a breast lump being breast cancer was high.Almost all respondents (95%) thought that breast trauma increased the risk of developing breast cancer. Most women responded that psychological/emotional factors such as stress (68.9%); depression, anger, or bitterness (62.5%); and personal disappointment (55.8%) might increase the risk of breast cancer. Approximately 40% of the interviewees believed that a high number of sexual partners significantly increased the risk of the disease. Moreover, 58.5% of the study sample thought that the use of underwire bra was a risk factor for breast cancer .The mean belief score was 9.29±4.01 points (median=9 points). Age, seeing a gynecologist in the past 2 years, wanting to know if they had breast cancer, belief that it is possible to get breast cancer without having a lump or nodule in the breast, and the belief that the likelihood of a breast lump being breast cancer is high, were statistically associated with beliefs were. Women with higher belief scores presented statistically higher knowledge scores. All variables maintained significant correlation even after adjusting by age and schooling .Frequencies of interviewees with high, intermediate, and low belief scores was 32.3%, 41.7%, and 26.0%, respectively. Belief scores categorized as high, intermediate, and low based on sociodemographic and epidemiological characteristics, health care, women’s experiences and understanding of breast cancer, and knowledge of the risk factors and disease signs/symptoms are presented in Since 2008, the World Health Organization has recommended greater attention be paid to social determinants in public health research . Culture is a social determinant of health that acts at the community and population levels. Culture includes beliefs, customs, social behaviors, attitudes, and traits of a particular social group . In the present study, the influence of culture on women’s beliefs about the risk factors for breast cancer was evident. Accordingly, 95% of women in this study reported that breast trauma increased the risk of developing breast cancer, and 82.6% of women believed that breast trauma could significantly increase the risk of breast cancer. Similarly, a hospital-based study conducted in Trinidad and Tobago, a country first inhabited by Amerindians with a slave cultural heritage influenced by Spanish, Indian, Chinese, and Portuguese cultures, found that approximately two-thirds (63.7%) of the respondents believed that breast trauma was a risk factor for breast cancer . In both studies, most respondents believed that breast trauma was a risk factor for breast cancer, potentially due to the similar cultural heritage of these Latino countries, which were past colonies. However, the notion that breast injury leads women to seek specialized care, including screening tests, which often detect preexisting lesions, may contribute to the spread of the belief that breast trauma increases the risk of breast cancer . The hypothesis of the influence of culture on this specific belief is corroborated by a population-based study in 2,000 involving 996 British women, wherein only 28% believed that breast trauma or injury was a risk factor for the disease . In Britain, where the cultural background is sustained by rational thinking, a low percentage of the female respondents thought that breast trauma increased the risk of breast cancer. A study conducted in Egypt with women recently diagnosed with breast cancer found that 37.78% of the interviewees believed that breast trauma was a risk factor for cancer . Despite the strong cultural heritage and the strong influence of religion in Egypt, a low percentage of women thought that breast trauma was a risk factor for cancer. This result might be because the study included women diagnosed with breast cancer who probably acquired more information about the disease. The different results of these studies indicate that the beliefs about the risk of breast cancer are strongly correlated with social and cultural factors, including the health history and experiences of these women.Similarly, the majority of women in the present study(58.5%) believed that wearing underwire bra increased the risk of breast cancer. In Tanzania, a study found that a sample of 225 low-income women believed that putting money in her bra (82.2%) and regular use of a bra (18.2%) caused breast cancer . Similarly, a study from Ghana with 474 women aged 40 to 70 years reported that 20% thought that putting coins in their bra increased the risk of developing the disease . A possible explanation for these findings is that similar to breast trauma, irritation of the breasts by an underwire or coin increases the probability of palpation of the breast, which may increase the probability of diagnosis of the disease . > 40 years in the United States found that 82% of respondents believed that stress could increase the risk of developing breast cancer. In that same study, 55% of the evaluated women believed that having a positive mental attitude could reduce the risk of the disease . Although there is no strong evidence regarding the contribution of these factors to breast cancer development, some studies suggest that psychological factors, including bitterness and resentment, could explain how an emotional circumstance considered unfavorable triggers the onset of breast cancer . Dumalaon-Canaria (2014) conducted a systematic review and selected quantitative and qualitative studies that reported causal attributions or beliefs in breast cancer patients. Some women from the qualitative studies believed that breast cancer might occur after experiencing sad episodes, especially those involving bitterness. Among the nine quantitative studies included in this review, the prevalence of the belief that breast cancer was caused by characteristics associated with the personality of women  ranged from 2.6% to 35.0%, whereas the prevalence of the belief that stress was the leading cause of breast cancer was 68,9%. However, although some studies have attempted to associate breast cancer with psychosocial factors , there is no consensus to date on which of these factors and to what extent these factors may contribute to the development of breast cancer.Although controversy exists regarding whether psychosocial factors are associated with cancer risk, many women believe that these factors affect breast cancer risk. In the present study, stress (68.9%) was the most cited psychosocial factor followed by depression, anger, or bitterness (62.5%) and personal disappointment (55.8%). Similarly, a study involving female Chinese immigrants aged Sexual practices have also been identified as risk factors for breast cancer. Among those interviewed, 55.5% believed that a high number of sexual partners increased the risk of the disease. A possible explanation for this finding involves the dissemination by health education campaigns indicate that this practice is a risk factor for cervical cancer, potentially prompting women in this group to extrapolate this information to an increased risk of breast cancer. > 50 years undergo a mammography every 2 years as the primary strategy to decrease the incidence and mortality from breast cancer, it is of great importance to consider the beliefs about cancer in the planning of educational programs to increase the adherence of women in this age group to screening programs . The cultural beliefs and values of a population at the individual and social levels affect the health behavior of individuals .In the present study, women in the age group 50–59 years presented a higher average belief score compared with women in other age groups(p=0.005). Considering that the Brazilian Ministry of Health advocates that all women aged The results of the present study indicate the existence of central beliefs related to the risk of breast cancer, and these beliefs may be affected by the strong cultural miscegenation in this Brazilian region. The fact that women with high belief scores believe that the probability of breast cancer is high if the woman finds a breast lump  and that it is possible to develop breast cancer without having a lump or nodule in the breast  suggests a mix of cultural beliefs and the scientific knowledge disseminated by the media and health services. This hypothesis is supported by the positive and significant association between knowledge scores and belief scores . The strong association between beliefs and scientific knowledge about the risk factors and signs and symptoms of breast cancer may be explained by the beliefs and experiences of Amerindians combined with the beliefs and scientific knowledge brought by Portuguese, Turks, and Lebanese immigrants since the beginning of colonization , which molded the beliefs about breast cancer among women from Rio Branco over the years. Although the scientific knowledge has been widely disseminated and generalized, these findings suggest that the beliefs inherited from older generations over the years are rooted in popular beliefs. Although no ethnographic study evaluated the effect of this cultural syncretism on the set of health beliefs of the population of Rio Branco to date, the possible relationship between current beliefs and the influence of knowledge/beliefs inherited from different cultures is supported by studies with other populations, including African Americans . Bailey (1987) investigated the sociocultural factors that could affect the health care-seeking behavior in an African-American population using ethnographic data analyzed via the observation-participation method. The results indicated significant differences in health care behavior between the ethnic groups regarding health knowledge, attitudes toward health therapies, health-care seeking behavior, and the use of local health care services. Issues could arise from the limitations related to comparing our findings with the literature because there is a lack of studies that measure the relationship between scientific knowledge and beliefs about health and disease in the population. However, there are theoretical hypotheses that support and explain our findings. According to Herzlich (2005), the history of medicine indicates that both medical knowledge and lay knowledge have been reciprocally constructed and that no vertical relationship exists between “those who construct knowledge” and “those who receive and reinterpret knowledge.” In the epistemological debates about knowledge, it is common for contemporary epistemologists to consider beliefs as a necessary but not sufficient condition for knowledge . However, Hume (2000) considers that belief is not an essential condition for knowledge. This author considers that experience plays a direct epistemic role in constructing beliefs and an indirect role in constructing knowledge. In addition, experience serves only as a source of ideas. For other authors, there is an interrelationship between belief and knowledge with either primary or complementary function  that could justify the fact that the women from our study with greater knowledge about breast cancer also presented higher belief scores. Considering that epistemological issues on the process of formation of beliefs and knowledge are complex and that many theories from different thinkers seek to explain this relationship, a detailed investigation of these findings is necessary. Notwithstanding, changes in the health behavior of a population, including adherence to breast cancer screening, may be affected by whether health education programs disregard the set of beliefs acquired by this population.> 40 years in Rio Branco, Acre.One of the limitations of this study was the use of a scale that was not widely used in other studies, thus limiting the comparison with the findings from other populations. Notwithstanding, the scale used in this study was based on the previously validated Health Information National Trends Survey(HINTS) . The strengths of this study include the fact it is the first to use a population-based quantitative approach to evaluate women’s beliefs about breast cancer in Brazil. Most of the studies on this subject in Brazil used qualitative methods and evaluated selected populations. Moreover, this study is the first to evaluate this topic in the western Amazon region, home to the largest indigenous population in Brazil despite the strong miscegenation. Finally, its large sample size is another strength, as it provided sufficient power to reliably estimate the belief scores and the frequency of the most common beliefs in the population of women aged


Background: While a significant breast cancer burden exists for Korean American immigrant women, their cancer screening behavior is strikingly poor, and few interventions have focused on this population. To promote breast cancer screening behavior in Korean American immigrant women, a mobile phone multimedia messaging intervention (mMammogram) was developed. Objective: The current study explores the impact of mMammogram on changes to study participants’ screening behavior and proposes suggestions for how the intervention can be improved for wide dissemination and implementation in the Korean American community. Material and Methods: Data were collected through qualitative research methods. Three focus groups were conducted with 14 Korean immigrant women who completed the mMammogram. Findings: Three themes emerged: (1) better understanding of breast cancer and screening through mMammogram ; (2) health navigators as a trigger to promote mammography ; and (3) suggestions for mMammogram . Conclusions: Mobile app intervention that is culturally tailored, along with health navigation services, can be a feasible, effective, and acceptable tool to promote breast cancer screening behaviors in underserved immigrant women. A mobile app can cover a broad range of breast cancer health topics and the health navigator can further help women overcome barriers to screening. A health navigation service is critical in overcoming language, transportation, and health accessibility barriers and triggering a positive change in their health screening behavior, especially for newly arrived immigrant populations. Although the cancer mortality rate is decreasing in the United States (U.S.) among the general population, the rate remains on the rise for Asian Americans, specifically for the Korean American population . StudiesKorean American women experience a variety of barriers to breast cancer screening. Studies on the topic have identified several obstacles to screening, including low socioeconomic status, language barriers, difficulties accessing healthcare , lack of cultural awareness by healthcare providers, lack of knowledge about screening guidelines, culture-based health beliefs , cultural modesty or embarrassment in terms of physical examinations, a fatalistic view of cancer, and fear of screening results ,10,11,12A handful of interventions specifically designed to address barriers and promote breast cancer screening in the Korean American community have been implemented. These community-based efforts include peer-led workshops, education sessions, a lay health worker intervention, and distribution of print material about screening guidelines ,17,18,19An innovative and promising solution might be a mobile phone-based health intervention. It is likely to provide low-cost and effective methods of contacting hard-to-reach populations with tailored individual messages, covering broad content areas while also overcoming restrictions to place and time of delivery . Mobile To promote breast cancer screening behavior of Korean American immigrant women, the intervention program called mobile Mammogram (mMammogram) was developed. The current study aims to explore the perspectives of Korean American immigrant women regarding their use of mMammogram, and how the program (1) promotes knowledge and positive attitude toward breast cancer screening; (2) motivates them to get breast cancer screening; and (3) may be improved for wide dissemination and implementation in the Korean American community. The current study provides critical information for developing a culturally relevant and personally tailored intervention to promote mammograms among underserved immigrant women and other disadvantaged minority groups which can effectively improve breast cancer health equity. mMammogram was a 7-day mobile phone-based multimedia messaging program. mMammogram provided knowledge on breast cancer and screening methods along with guidelines, cultural barriers , and information to access the healthcare system. This content was delivered in various formats of tailored messages using culture-specific emoticons, graphs, images, pictures, and videos in the Korean language. mMammogram also offered health navigation services, such as providing necessary resources  and making an appointment for a mammogram. More detailed information about the mMammogram Randomized Clinical Trial (RCT) has been previously published .The research team utilized qualitative research methods to address the research aims. Three focus groups were conducted between June 2014 and February 2015 with a total of 14 Korean immigrant women who completed mMammogram prior to the focus groups. Six women participated in the first focus group, five in the second group, and three in the third group. Details of data collection  are described elsewhere . UniversThe first author, along with two research staff members, facilitated and took notes during each focus group. The focus group interviews were semi-structured and included open-ended questions that asked participants about general feedback on (1) content, duration, and concerns of mMammogram; (2) changes in their knowledge, attitude, and motivation for screening receipt after participating in mMammogram; and (3) their screening experience if they had a mammogram after the intervention and their recommendation for dissemination in the Korean American community. Some examples of questions used in the focus group include: What are your perspective about the mMammogram intervention? What did you think of the content of the mMammogram program? Was it helpful to improve your knowledge in breast cancer screening? and What are your suggestions for wide dissemination of the mMammogram intervention in our community? All focus groups were conducted in Korean. Each focus group lasted approximately 1–1.5 h and was digitally recorded. Written consent was obtained from all 14 participants before starting the focus groups. Each participant received $20 for her time commitment.A thematic analysis  was usedOverall, three themes were identified from the focus groups: (1) better understanding of breast cancer and screening; (2) health navigators as a trigger to promote mammography; and (3) suggestions for mMammogram. We indicated each participant’s number when describing quotes to protect the confidentiality of each participant. Study participants reported that mMammogram helped to (1) increase their awareness, positive attitude, and knowledge on breast cancer and breast cancer screening methods; (2) increase their understanding of the importance of regular mammography; and (3) reduce their anxiety about mammography, resulting in promoting their interests in screening participation.(1) Increased awareness and knowledge on breast cancer and screening methodsn = 12) stated that mMammogram was helpful to learn basic knowledge of breast cancer, as well as the three breast cancer screening methods: breast self-exam, clinical breast exam, and mammogram. Several participants reported that they were unaware of how prevalent breast cancer is in the Korean American community, which naturally led to their limited awareness about breast cancer screening. Interestingly, after participating in the program, they started to pay attention to information related to breast cancer when they watched TV, listened to the radio, or had conversations with their friends. The participants reported that mMammogram makes them take breast cancer seriously and encourages them to consider getting a mammogram. For example, participant #1 decided to get a mammogram after completing the program:“You know… I was surprised by the fact that breast cancer is common in our community. I believed that it is a rare disease in our community. When people talk about breast cancer, I did not carefully listen to [them]. However, the statistical graph related to breast cancer incidence and mortality in Korean American women caught my attention. It makes me to consider it more serious, leading me to think about mammogram. Early detection is better, right?” Overall, almost all participants  people who are older do not need screening and (2) mammogram causes radiation exposure, which also may cause cancer. Four participants knew an older woman with breast cancer and they thought it was a very rare case, indicating that older women do not need to get screened. For example, one participant admitted that she made a joke about her 89-year old mother-in-law who got a mammogram. She could not understand why her old mother-in-law got a mammogram at that time, but she was able to understand after completing mMammogram. Now she knows that old age is a risk factor for breast cancer and that women should get a mammogram regardless of their age. Three other participants expressed their concern about radiation exposure; their concern even led them to not get a mammogram. For instance, participant #3 shared her story:(2) Reminder of the importance of regular mammographyn = 5) did not understand why women should get a mammogram on a regular basis. They had received a mammogram before, but they did not adhere to routine screening for several reasons, such as having no symptoms on their breasts, having a busy life, and having health insurance issues. For example, participant #6 did not follow her physician’s recommendation. She was young and healthy, so she could not find reasons to get a mammogram again, even with her physician’s continuous suggestion:“Whenever I saw a doctor, he recommended me to get a mammogram because my last mammogram was 7 years ago. However, I ignored his suggestion. You know, I am healthy enough. No symptoms on my breasts. Why should I get a mammogram? Plus, I have conducted breast self-exam and had clinical breast exam. I thought these two methods are enough to check my breast. However, my thoughts have changed after I completed this program. I realized that I needed to get a mammogram on a regular basis, regardless of my health status. I learned that the two methods are not sufficient to find cancer. I did not know that breast cancer is very common in Korean American women, which makes me feel anxious.” Some participants  Reduced anxiety about mammographyn = 7) reported that mMammogram—particularly, two videos about mammogram procedures—helped reduce their anxiety about breast cancer screening. The participants were highly satisfied with the videos that demonstrated the procedure of a mammogram. One video showed the mammogram procedure briefly. The other video showed a technician at a breast imaging center explaining the mammogram procedure in step-by-step detail, from the check-in process at the front desk to taking images of the breasts. The participants mentioned that they felt a bit more confident in getting a mammogram after watching the videos. They reported getting a sense of the whole procedure of mammography, which resulted in relieving their anxiety about going to a hospital to get a mammogram. For example, participant #14 said:“I felt safe to get a mammogram after watching two videos about mammogram procedure. I learned that I don’t need to take off all my clothes while imaging my breasts… just exposure one side of breast and then if it is done… move to the other side of breast. You know the video. A nurse showed the rooms where we can change our clothes and where the mammogram machine is. This all information was super helpful to relieve my anxiety about mammogram. Now I know what to expect when I go to hospital to get a mammogram”Half of the participants (n = 8) showed passion for learning more about breast cancer, beyond what was covered in the program, such as breast density and its relationship with breast cancer incidence and various cases of breast cancer by stage and related treatment options. In addition, they were highly motivated to educate other women about the importance of breast cancer screening, including colleagues at work, friends, and family members. They wanted to share what they learned from the program with other women in the community who did not or were not able to participate in this study. Two participants said that, after completing mMammogram, they partly showed the program to their daughters to educate them on how to conduct a breast self-exam:“I showed a part of the mMammogram application (app) program to my daughter, in particular the breast self-exam video. She is a college student and I think she needs to start self-examination.”(Participant #3)More than half of the study participants  for participants who did not have health insurance, scheduling mammogram appointments for participants, helping participants select a primary care physician, helping fill out forms at hospitals or clinics, transporting participants to receive a mammogram, and/or following up after receiving a mammogram for those who have abnormal results. The study participants had an option to contact bilingual health navigators to support them in getting a mammogram. The most common requests were checking whether their health insurance covered mammography and if they were eligible to get a mammogram for free or at low cost. (1) Importance of Health Navigation Services n = 9) reported difficulties accessing healthcare due to their limited English proficiency. They highlighted how bilingual health navigators were helpful in supporting their accessibility, resulting in increased screening uptake. Some participants (n = 5) mentioned the complexity of health insurance. For example, participant #4 reported that her company chooses different health plans every year, which presents more challenges to getting a mammogram:“All the problem is rooted in health insurance. You know what? My health insurance plan is changed every year, which led me discourage to access health care. It used to change every two or three years. (…). The coverage is getting worse. I need to find a new family doctor again... and check my coverage which I do feel uncomfortable because of my English. I am getting tired of it. I sometimes think to visit Korea to get comprehensive health exam. That is going to be much easier and cheaper.”Some of the focus group participants ((2) Health Navigation Services and Regular Mammogram Receipt“After participating in this program, I decided to get a mammogram. It was my first mammogram in my lifetime. I was nervous and worried about receiving mammogram because I am not familiar with U.S. health care system and my English is not enough to communicate with doctor or nurse. I believed that I was able to get a mammogram because of health navigator’s support. She called my health insurance company to check my insurance coverage. And then, she scheduled a mammogram appointment for me and went to the clinic with me. Such a good service. I really appreciated all the things she did. You know, I would like to continue to get mammography every year if someone reminds me and assists me to get it.”The study participants reported how bilingual health navigators helped them overcome barriers to screening . They also indicated intentions to continue getting mammograms if they are able to access a health navigation service. For instance, participant #1 shared her story:n = 8) said that the subtitles on videos were too small to read via their phone, even though they were wearing glasses. They had to watch the videos several times to read the subtitles and understand the contents. Second, sometimes participants faced challenges to using their phone, such as issues with Wi-Fi connection. In addition, participants expressed a desire to receive messages later at night or at other times based on their schedules. In the current mMammogram system, study participants could select their preferred time to receive the messages between 8 a.m. and 8 p.m. They suggested they could control the starting time of the program, given that their schedules could change from day to day. Otherwise, they were unable to attend the program on time and missed it. Lastly, participants had different opinions regarding the program period. Some participants suggested a shorter period of 3–5 days, while others preferred a 7-day program. Although study participants were highly satisfied with mMammogram, they suggested how the intervention could be improved for wider dissemination and implementation in the Korean American community. Their suggestions include larger subtitles on videos, addressing technical issues , extended schedule of message delivery, and adjusting the program period duration. For example, a total of eight videos were provided via mMammogram that included Korean or English subtitles. Some participants (This study explored (1) how mMammogram helped Korean American immigrant women to increase their knowledge and positive attitude toward mammography; (2) how the program motivated them to complete breast cancer screening; and (3) how the program could be improved and disseminated in the Korean American community. Along with these findings, this study demonstrated that a mobile phone-based multimedia health intervention with health navigation services can be a feasible, effective, and acceptable tool to promote mammography uptake in underserved immigrant women. We identified three themes: (1) better understanding of breast cancer and screening through mMammogram intervention; (2) importance of health navigator services to promote mammography, and (3) suggestions for mMammogram improvement and dissemination strategies. As noted in Theme 1, multimedia messages  through a mobile phone-based application have the advantage of being entertaining and individual-targeted to capture study participants’ attention. For example, video content held great persuasive power in our intervention. Video messages were the most popular and well-accepted among the study participants, and they remembered the contents conveyed via videos much clearer and longer than other text messages. In particular, study participants liked two video clips that featured mammogram procedures and the importance of having a regular mammogram. Those who were unfamiliar with U.S. hospitals and who never had a mammogram previously got a sense of what would happen when they go to a clinic for mammography. This improved their confidence about mammography and promoted their interest in screening participation ,31.Another merit of a mobile phone-based health intervention is its easy dissemination, accessibility, and portability by having important health information at the user’s fingertips. Plus, the study participants can keep the program if they want and open it anytime to remind themselves or inform other people. A few study participants who had a passionate interest in our program taught their daughters how to conduct a breast self-exam by showing them the videos from the program. This was an unintended impact of our intervention, which implies ”ripple effects” in that they led to new effects beyond the intended primary target of the intervention . The parAs discussed in Theme 2, it is well-known that immigrants face various challenges in navigating the U.S. healthcare system due to lack of health insurance literacy and underutilization of healthcare services due to limited English proficiency. In particular, undocumented immigrants’ barriers range from financial issues to fear of deportation . Health As seen in Theme 3, on the other hand, several challenges were reported while attending mMammogram intervention. One of the challenges of a mobile phone-base health intervention is the various sizes and types of smartphones. Some participants had the latest phones with big screens (5.5 inches or larger), while some had older versions of mobile phones. Those who had mini smartphones had difficulty reading the subtitles on the videos. Given that the size of participants’ phones cannot be controlled, we may consider enlarging the subtitles or dubbing the video in participants’ native language. We need to further consider developing an application that could be downloaded onto the iPad, where participants may read subtitles through a large window. Additionally, some participants faced challenges in using their phones due to weak Wi-Fi connections or a complicated process of downloading an app. They still felt challenged even after our research team taught them how to access to our app program and respond to it before the intervention. With only a short time for training, it might be hard to overcome all challenges faced by study participants. We may need to provide ongoing training via health navigation services or a handout on how to deal with common technical challenges. Another solution is to develop a web-based app which does not need to be downloaded and can be easily seen by smartphones and any other mobile devices. This study provides a valuable contribution to knowledge on how mHealth can be used to change health behavior, particularly for promoting breast cancer screening; however, some limitations may affect its applicability to other contexts. First, while a small sample size is not a limitation of qualitative research, the data were collected from one-time focus group meetings. However, the examination of the study participants’ responses to open-ended questions regarding evaluation of the intervention after the completion of mMammogram facilitated further insights into the evaluation of and feedback on a mobile-phone text-messaging program. Lastly, the frequent interactions between study participants and research team members may impact participants’ knowledge and motivation to receive a breast cancer screening, as well as their positive attitudes toward the intervention. Whenever study participants had questions related to the app  or contents, they were allowed to contact us, which may positively impact intervention effectiveness and study results.In conclusion, mobile apps can cover a broad range of breast cancer health topics, and the health navigator can further help women overcome barriers to screening. Specifically, for newly arrived immigrant populations, a health navigation service is critical in overcoming language, transportation, and health accessibility barriers and triggering a positive change in their health screening behavior. This study demonstrates the effectiveness of a culturally tailored mobile app intervention in increasing knowledge, attitude, and receipt of breast cancer screening in an immigrant group. Mobile app intervention should be combined with health navigation services, particularly when working with immigrant or refugee groups, to provide another layer of assistance which boosts confidence and comfort level in changing health behaviors. In addition, it was revealed that providing educational health information through visual images and videos is more effective than text messages. Overall, culturally and linguistically tailored multimedia messaging intervention combined with health navigation services is feasible and acceptable as an intervention tool to produce health behavior changes. The intervention can be easily translated into other types of cancer screening and cancer prevention behaviors, which will significantly reduce the current cancer burden vulnerability that immigrant and refugee communities currently face.By applying the mobile phone-based multimedia messaging program, the most prominent findings include better understanding of breast cancer and screening through mMammogram intervention and the importance of health navigator to promote mammography, as well as suggestions for mMammogram improvements and dissemination strategies. Identifying these three themes provided important insights for mMammogram intervention to increase the breast cancer screening. The vital role of these three implies the mobile phone-based multimedia messaging program may be useful for reducing multiple challenges and barriers in navigating the healthcare system and increasing the level of health literacy implemented in the immigrant population. In light of the present findings, to produce health behavior changes and mitigate challenges in the healthcare system, mobile apps must cover a wide range of health topics in different languages with health navigator services. Mobile apps should also be tailored to different cultures among the immigrant populations to trigger positive changes in increasing health literacy and receipt of cancer screening. Furthermore, the tailored multimedia messaging intervention also need to combine with visual images and videos. In sum, culturally and linguistically tailored multimedia messaging intervention combined with health navigation services is useful and effective to reduce the current cancer burden vulnerability faced by immigrant populations.


Statistical data on the incidence, mortality, and burden of breast cancer and the relevant risk factors are valuable for policy-making. We aimed to estimate breast cancer incidence, deaths, and disability-adjusted life years (DALYs) by country, gender, age group, and social-demographic status between 1990 and 2017.We extracted breast cancer data from the 2017 Global Burden of Disease (GBD) study from 1990 through 2017 in 195 countries and territories. Data about the number of breast cancer incident cases, deaths, DALYs, and the age-standardized rates were collected. We also estimated the risk factors attributable to breast cancer deaths and DALYs using the comparative risk assessment framework of the GBD study.In 2017, the global incidence of breast cancer increased to 1,960,681 cases. The high social-development index (SDI) quintile included the highest number of breast cancer death cases. Between 2007 and 2017, the ASDR of breast cancer declined globally, especially in high SDI and high middle SDI countries. The related DALYs were 17,708,600 in 2017 with high middle SDI quintile as the highest contributor. Of the deaths and DALYs, alcohol use was the greatest contributor in most GBD regions and other contributors included high body mass index (BMI) and high fasting plasma glucose.The increasing global breast cancer burden is mainly observed in lower SDI countries; in higher SDI countries, the breast cancer burden tends to be relieving. Therefore, steps against attributable risk factors should be taken to reduce breast cancer burden in lower SDI countries. Breast cancer was the third highest incident cancer in 2017, with an estimated 1,960,681  incident cases and a high prevalence in females. Breast cancer is the leading cause of cancer death in females and also a non-negligible cause of cancer death in males worldwide, claiming 181,004 lives and resulting in 17.7 million disability-adjusted life years (DALYs), making it one of the most severe burdensome cancer globally [Thus far, several regional and national studies on breast cancer incidence and mortality have been performed, and the results of these multifarious studies from different parts of the world present an inclusive picture. Epidemiological studies from Arab countries , India , Latin Ahttp://ghdx.healthdata.org/gbd-results-tool), which is an ongoing global collaboration that uses all available epidemiological data to provide a comparative assessment of health loss from 328 diseases across 195 countries and territories. From GBD study 2017, we obtained data on annual incidence, death, DALY, and respective age-standardized rate (ASR) of breast cancer from 1990 to 2017. The SDI, which is based on national-level income per capita, average years of education among persons older than 15, and total fertility rate, was used to categorize the countries into five SDI quintiles .Data for the disease burden of breast cancer were obtained from an online data source tool, the Global Health Data Exchange (GHDx) query tool . For each included study, the proportions of breast cancer cases induced by the specific risk factors were calculated. The proportion data obtained from systematic literature review were applied to four independent DisMod-MR2.1 as inputs . MortaliYears lived with disability (YLDs) were calculated by multiplying the prevalence of each sequela by its disability weight and by adding the procedure-related morbidity associated with breast cancer treatment. YLLs due to breast cancer were calculated using standard global life expectancy and the number of deaths according to age . Breast The GBD study incorporated the comparative risk assessment framework previously  to quantASRs, DALYs, and the estimated annual percentage changes (EAPCs) were calculated to quantify breast cancer incidence and mortality trends. ASRs  were calculated on the basis of the following formula .\documeai, where i denotes the ith age class, and the number of persons (or weight) (wi) in the same age subgroup i of the selected reference standard population.), X represents calendar year, and ε represents error term. Based on this formula, β determines the positive or negative trends of ASR. The formula for calculating EAPC is EAPC = 100 × (exp(β) − 1) and 95% confidence intervals are obtained from the linear model [p value of less than 0.05 was considered statistically significant.Moreover, trends in ASIR reflect the alterations in human disease patterns and risk factors. The concept of EAPC is introduced to describe the trends in ASR within a specified time interval, as it is assumed that the natural logarithm of ASR is linear along with time. Thus, ar model , 17. It Globally, the incident cases of breast cancer has increased to 1,960,681 with an ASIR of 24.19/100,000 persons (95% UI = 23.34–24.86) in 2017  in 2017. However, in the decennium between 2007 and 2017, the ASDR of breast cancer has declined globally, especially in the high SDI and the high middle SDI quintiles  cases in 2017. Meanwhile, South Asia showed the largest increase of breast cancer deaths between 1990 and 2017. Only in high-income North America, Western Europe, and Australasia, ASDR decreased. The countries with the largest populations, including China, India, and the USA, had the most deaths in 2017 while the ASDR was highest in Fiji, Tonga, and the Bahamas , suggesting that breast cancer cases increased more slowly in higher incident countries than in lower incident countries . As shown in Fig. As shown in Additional file Generally, alcohol use was the greatest distributor of DALYs in most GBD regions and other distributors included high body mass index (BMI) and high fasting plasma glucose. It was noteworthy that East Asia was the only region in which high BMI contributed the most to DALY cases in 1990. However, in 2017, high BMI also contributed to DALYs of Southeast Asia and middle SDI countries. In 1990, the regions in which high fasting plasma glucose contributed the most are the middle SDI countries Fig. .Fig. 5aBreast cancer DALYs attributable to alcohol use varied by gender and SDI quintiles in 2017. Of the 17,708,600  global breast cancer DALYs, 9.43% (95% UI = 7.92–10.97%) was attributable to alcohol use, including 9.24% (95% UI = 7.76–10.76%) in females and 20.18% (95% UI = 15.37–25.05%) in males. Alcohol use-related breast cancer DALYs decreased globally between 1990 and 2017. On the contrary, alcohol attributed breast cancer DALYs increased in the low SDI, low middle SDI, and the middle SDI quintiles  of global breast cancer DALYs in 2017 with an increasing trend between 1990 and 2017. Except the gentle trend of high BMI attributed DALYs in the high SDI quintile, the other quintiles showed increased trends, especially in the high middle SDI and the middle SDI countries  with a slight increase. In the high SDI quintile, the ASR has been decreasing since 1990, when it was the highest among the five quintiles. However, the rate was of great fluctuation between 1990 and 2017 while the low SDI, low middle SDI, and the middle SDI countries exhibited distinct increase trends  were less prominent. According to the global cancer burden 2016 , the chaThe trend of global age-standardized DALY rate was considerably varied in females and males, between 1990 and 2017. There was a gentle decline of age-standardized DALY rate in females, while the rate was increasing in males in the same study period. This discrepancy partially reflected the consequence of different risk factors between the genders. The age-standardized DALY rate also differed in the SDI quintiles. In the low SDI, low middle SDI, and the middle SDI countries, the rate was increasing both in males and females, while in the high middle SDI countries, the DALY rate had the similar global pattern and in the high SDI countries, the rate was declining in both the genders. The global number of breast cancer deaths increased substantially during the study period in both genders. This increase was consistent with the increase in breast cancer incident cases. Global ASDR declined since 1990 which was mainly due to the decrease in the high SDI and the high middle SDI quintiles, while the ASDR of other three quintiles slightly increased, between 1990 and 2017. Much of these geographic and gender disparities could be explained by heterogeneity in the prevalence of risk factors, with alcohol use being the chief factor.Alcohol use is the most important of the risk factors contributing to breast cancer deaths and DALYs, though the attributable DALYs have been declining from 1990 to 2017. Consistently, the global daily prevalence of alcohol use declined significantly during the study period, which was more pronounced in the high and the high middle SDI countries .Moreover, high body mass index and high fasting plasma glucose were also identified as potential risk factors attributable to breast cancer deaths and DALYs, which showed an increasing contribution trend of the two risk factors globally, especially in the high SDI and the high middle SDI quintiles. According to Hyuna Sung’s study , the mosIt is worth mentioning that risk factors differed in the subtypes of breast cancer , for insPolicy-makers require country-specific information on the burden of different cancers to assess the impact of cancer control programs, benchmark progress in their nation, and allocate limited resources in their health care systems. Given the fact that existing data in many countries are of low quality or missing, the GBD study results can be used by stakeholders to study the trends of different diseases in their respective locations.GBD studies provide high-quality estimates of global cancer burden, yet there exist several limitations. One inevitable limitation is the uncertainty of GBD estimates in cases in which actual data on disease burden are unavailable, and the GBD estimates fill the vacancies in this occasion. Besides, differences in data collecting and coding, as well as quality of data sources, remain inevitable in this analysis pattern. Moreover, the fluctuations in incidence and mortality rates may partly reflect the detection bias related to adjustments in screening protocols instead of real changes in age-specific rates.The global burden of breast cancer has been increasing continuously between 1990 and 2017, although in some SDI quintiles, the ASDR and age-standardized DALY rate has been declining. In recent years, disease reduction was observed in higher SDI regions while lower SDI regions had carried an incremental burden of breast cancer, and there may be a widening in disparities in the years to come. Consequently, steps against attributable risk factors should be taken to reduce breast cancer burden especially in lower SDI countries, to prevent acceleration of these disparities, because underdeveloped countries are affected to a greater degree by increases in health burden.Additional file 1: Figure S1. Annual percent changes of age-standardized breast cancer incidence (A), death (B), and DALY (C) in 195 countries and territories between 2007 and 2017.Additional file 2: Figure S2. The proportion of three age groups for breast cancer incident cases in both genders, globally and by region, contrasted in 1990(A) and 2017(B). The populations were divided into three age groups: 15-49 years, 50-69 years and 70+ years.