This study was drawn from a prospective cohort of 32,383 women and men who provided blood specimens at baseline: c-peptide and HbA1c were assessed in 3,000 randomly selected participants who were cancer-free-at-baseline and an additional 2,281 participants who were cancer-free-at-baseline and subsequently diagnosed with incident colorectal, liver, pancreatic, female breast, endometrial, ovarian, bladder, or kidney cancers. Weighted Cox regression models estimated HRs and 95% confidence intervals (CI), adjusted for covariates. c-peptide was associated with higher risk of liver cancer . HbA1c was associated with higher risk of pancreatic cancer  and with some suggestion of higher risks for all-cancers-of-interest  and colorectal , ovarian  and bladder  cancers. Compared with no self-reported T2DM and HbA1c < 6.5% (reference group), self-reported T2DM and HbA1c < 6.5%  was not associated with risk of colorectal cancer, whereas it was associated with higher risks of all-cancers-of-interest combined , especially for breast and endometrial cancers. Additional large, prospective studies are needed to further explore the roles of hyperglycemia, hyperinsulinemia, and related metabolic traits with T2DM-associated cancers to better understand the mechanisms underlying the self-reported T2DM-cancer association and to identify persons at higher cancer risk.Self-reported type 2 diabetes mellitus (T2DM) is a risk factor for many cancers, suggesting its pathology relates to carcinogenesis. We conducted a case-cohort study to examine associations of hemoglobin A1c and c-peptide, markers of hyperglycemia and hyperinsulinemia respectively, are associated with certain cancers, though people with diabetes may be at increased risk of these cancers, perhaps other than colorectal, even when their glucose is well controlled.The results from this study suggest that HbA There is ample evidence that self-reported type 2 diabetes mellitus (T2DM) is associated with increased risks of liver , pancrea1c, HbA1c) or hyperinsulinemia . Self-reported T2DM alone is also prone to misclassification. Approximately 7.3 million of the estimated 34 million adults with diabetes in the United States are undiagnosed and would be misclassified by self-report alone; furthermore, an estimated 88 million adults in the United States have prediabetes  versus 1c (an indicator of average blood glucose levels in the past 2 to 3 months) and c-peptide (an indicator of average insulin secretion in recent days/weeks) with the above-mentioned diabetes-associated cancers in a case-cohort study of 5,050 U.S. adults. For the first time in the literature, we also explored the potential influence of well-controlled diabetes, undiagnosed diabetes, and less-well-controlled diabetes on cancer risk, via variables jointly defined from self-reported T2DM and measured HbA1c levels.Relatively few large, prospective cohort studies have evaluated associations of biomarkers for hyperglycemia and hyperinsulinemia with risks of diabetes-associated cancers . To addrThe Cancer Prevention Study-II (CPS‐II) Nutrition Cohort was enrolled in 1992 and 1993, in 21 states when 184,000 participants completed a mailed, self-administered questionnaire on lifestyle, behavioral, pharmacologic, medical, and sociodemographic factors. Follow‐up surveys were sent to participants beginning in 1997, and biennially thereafter, to update information and to learn of newly diagnosed cancers. Self-reported cancer diagnoses were verified by medical record abstraction or by linkage to state cancer registries. From 1998 to 2001, CPS-II Nutrition Cohort participants were invited to enroll in the CPS‐II LifeLink subcohort by providing a blood sample at a local medical facility. All LifeLink participants completed a brief questionnaire on parameters relevant to blood collection, including timing of last meal, recent medication use, diabetes status, and acute illness. Participants were not required to fast prior to blood collection. Blood samples were collected into two Ethylenediamine tetraacetic acid (EDTA) tubes and a serum separator tube. Blood samples were shipped chilled overnight to a central repository where they were fractionated and placed in liquid nitrogen freezers for long‐term storage. Further details on CPS-II Nutrition and the LifeLink subcohort are presented elsewhere .n = 479; liver, n = 35; pancreas, n = 176; invasive female breast, n = 889; endometrium, n = 155; ovary, n = 93; bladder, n = 344; and kidney, n = 110) and through June 30, 2013 (the most recent data available when the study was initiated). All CPS-II LifeLink participants gave written, informed consent. CPS-II and all related substudies are approved by the Institutional Review Board at Emory University  and all aspects of the study were conducted in accordance with the Declaration of Helsinki.For this study, we used a case-cohort study design whereby a random subcohort of 3,000 participants was selected from the 32,383 participants who provided a blood sample and did not have a prior cancer diagnosis at the time of blood draw. Next, we identified all participants who were diagnosed with one of the cancers-of-interest  after bl1c) or serum (for c-peptide) samples from the subcohort of 3,000 participants and from the 2,281 prospectively identified cancer cases of interest . Both biomarkers have been reliable and clinically useful when measured from nonfasting samples  for HbA1c was 8.9%, with an intraclass correlation coefficient (ICC) of 74.7% for the anonymized study samples that were included on each plate. An enzymatically amplified one-step sandwich-type immunoassay measured c-peptide (Ansh labs). The CV for c-peptide was 7.7%, with an ICC of 97.5%, for the anonymized CPS-II study samples. Additional assay details are shown in 1c reliability and validity from CPS-II long-term frozen samples, and (ii) HbA1c values from frozen RBCs compared with whole blood samples from the same participants. CVs and ICCs from this latter QC experiment were 7.6% and 0.95, respectively. The mean from the frozen, fractionated RBC specimen was 4.8% whereas it was 5.2% from whole blood.The HbAWeighted Cox proportional hazards regression models examined the associations of each biomarker with risk of all-cancers-of-interest combined, and with risk of the specific cancer types, with control for potential confounding variables.1c was modeled continuously (per SD) and categorically , prediabetes (HbA1c: 5.7%–6.4%), and T2DM  and updated biennially beginning in 1997. Participants were asked whether they had ever been diagnosed with T2DM by a physician; beginning with the 1997 questionnaire, and for all subsequent surveys, the question also added wording to exclude persons with gestational diabetes only and the year that diabetes was diagnosed. As reported previously, self-reported T2DM was in strong agreement (90% concordant) with clinical records abstracted to confirm cancer diagnoses .a priori and based on their potential to confound or modify the association between the biomarkers of interest and cancer risk. All covariates were collected from the questionnaires and modeled using values defined as closest time prior to or at blood draw. The covariates included in the multivariable-adjusted models were: physical activity , alcohol use , smoking , hours since last meal , and hormone treatment for women . In addition, multivariable weighted Cox models were run with and without  to show its potential confounding influence on these associations. We were unable to more finely consider the potential influence of diabetes treatments because of limited data.Covariates for multivariable models in this study were selected 2, separately, with risks of the cancers-of-interest to provide broader context on the generalizability of the case-cohort participants randomly selected for this study.Sensitivity analyses included stratifying by smoking status and, for women, by those who were current versus non-current hormone users at the time of blood draw. Additional sensitivity analyses excluded case participants diagnosed with a cancer-of-interest within 2 years after blood draw and all participants with self-reported T2DM . We also stratified bladder cancer by stage  because of previous findings for bladder cancer risk in CPS-II , and we 1C < 6.5% (reference group); self-reported T2DM with good glucose control ; undiagnosed diabetes ; and, less-well-controlled diabetes .To explore the potential influence of well-controlled diabetes, undiagnosed diabetes, and less-well controlled diabetes on cancer risk, we used weighted Cox proportional hazards regression models to examine cancer risk with jointly defined exposures: no self-reported T2DM and HbAThe data underlying this article are available upon request from the corresponding author.1c and 2,993 participants with measured c-peptide (seven assays failed) are shown in 1c and c-peptide values were higher in men than in women and for persons with versus without self-reported T2DM. HbA1c and c-peptide increased directly with age and BMI. HbA1c and c-peptide decreased with increasing physical activity and with moderate alcohol consumption. For both biomarkers, the lowest values were observed among current smokers compared with either former or never smokers. For the cancer outcomes identified in this study, the mean follow-up time from blood draw to diagnosis was 6.0 years . For participants not diagnosed with cancer, the mean follow-up time from blood draw to end-of-study was 10.8 years . Self-reported T2DM, compared with no self-reported T2DM, was associated with all-cancers-of-interest in multivariable models that included BMI  and was also associated with higher risks of breast, endometrial, and ovarian cancers (2) was associated with higher risks of all-cancers-of-interest and colorectal, liver, pancreatic, breast, endometrial, and kidney cancers ; when BMI was added, the HR was attenuated . For all-cancers-of-interest, prediabetes (HbA1c: 5.7%–6.4%) was associated with some suggestion of higher risk  in the model that did not include BMI. In addition, HbA1c ≥ 6.5%, compared with <5.7%, was statistically significantly associated with higher risk of colorectal cancer only; however, HRs for all other types of cancer, except female breast, were in the range of 1.2 to 2. Continuous HbA1c (per SD) was associated with higher pancreatic cancer risk .Associations between HbA1c ≥ 6.5%, compared with <5.7%, was associated with higher risk of pancreatic cancer in women in multivariable models that excluded BMI; these results were attenuated when BMI was included. In men, HbA1c ≥ 6.5% was associated with risk of all-cancers-of-interest and colorectal cancer. Results from the continuous models were largely consistent with these findings.In analyses stratified by sex , HbA1c ≥1c values. Self-reported diabetes in good metabolic control , compared with the no self-reported diabetes and low HbA1c (<6.5%) reference group, was associated with higher risks of all-cancers-of-interest ; this association was most clearly observed for breast  and endometrial cancers . In contrast, self-reported diabetes with good glucose control, compared with no self-reported diabetes and HbA1c < 6.5%, was not associated with risk of colorectal cancer  whereas both groups with high HbA1c, whether with undiagnosed T2DM  or diagnosed T2DM with less-well-controlled diabetes , had suggestive, albeit not statistically significant, increases in colorectal cancer risk. For liver and bladder cancers, undiagnosed T2DM was associated with statistically significantly higher risks, whereas undiagnosed T2DM was suggestively, but not statistically significantly, associated with all-cancers-of-interest and colorectal, pancreatic, and kidney cancers.1c was associated with risk of invasive disease  and not associated with risk of noninvasive disease .The sensitivity and subgroup analyses were largely consistent with the main findings although we acknowledge we were underpowered for many of the stratified analyses with the rarer cancers. One exception was for bladder cancer where high HbA1c and c-peptide with cancer risk.Diabetes is a well-established major cause of macrovascular and microvascular diseases, such as heart disease, stroke, kidney failure, and blindness . StudiesThis study identified a 4-fold increased risk of liver cancer comparing the highest with the lowest tertiles of c-peptide. This finding is consistent with results from two other prospective studies that identified 3-fold increased risks of liver cancer comparing highest with lowest categories . These r1c with risks of all-cancers-of-interest and with colorectal cancer, although HRs for both were attenuated with the addition of BMI to the model, consistent with recent studies , future investigation of this biomarker-disease association is warranted.We did not observe statistically significant associations between HbAncidence  and selfncidence . Our res1c. These findings, if corroborated in future studies, may add colorectal cancer prevention to the list of clinical benefits from achieving glycemic targets among people with T2DM.A strong translational aspect of this study was the ability to assess the influence of well-controlled diabetes, less-well-controlled diabetes, and undiagnosed diabetes with cancer risks. The motivation for this joint analysis came from an earlier CPS-II publication where we noted that self-reported T2DM was associated with colorectal cancer risk in men but not in women , consistpost hoc analyses, the prevalence of mammography screening within 2 years of blood draw was similar across all four categories of this joint exposure  and women in all four exposure groups were mostly diagnosed with local staged breast or endometrial tumors. Thus, the higher risks of these cancers cannot be readily explained by a screening effect (for breast cancer) or by early detection bias  in women with T2DM and low HbA1c. These results underscore the increased importance for women with T2DM of being aware of signs and symptoms for endometrial and breast cancers and to undergo age-appropriate breast cancer screening.In contrast to the null association between good glucose control among people who self-reported T2DM and colorectal cancer risk, this study reported increased risks of all-cancers-of-interest, and especially for female breast and endometrial cancers, with this same exposure definition, an unexpected finding. In related 1c) and hyperinsulinemia (via c-peptide). Our QC experiments, conducted prior to launching the full study, further confirmed the validity and reliability of these assays from frozen RBCs compared with whole blood and the pilot study showed good face validity for HbA1c values from RBCs stored frozen for approximately 15 years, including correlations of HbA1c with BMI and T2DM in the expected directions, as well as strong CVs and ICCs from paired, frozen samples; however, we acknowledge from our QC experiments that RBC values from frozen samples were modestly lower than measures from whole blood  and therefore may have led to some misclassification in the overall study. Future studies should consider using fresh whole blood samples were appropriate. The hybrid variable created from self-reported T2DM and HbA1c used in this study also allowed for initial exploration of the potential role of glucose control in determining cancer risk among people with T2DM, as well as the cancer risks associated with undiagnosed T2DM—both are topics for future research with other large studies or consortia projects. In addition, future pooled studies should consider a broader array of biomarkers related to metabolic health, including sex hormones and inflammatory adipocytokines.Strengths of the current study include its relatively large sample size, prospectively collected blood specimens and cancer outcomes, repeat measures of important study variables via questionnaire (including the ability to update T2DM data), and objectively measured biomarkers. By presenting results for the eight cancer sites often reported associated with self-reported T2DM, we were able to more broadly evaluate objective biomarkers for two of the main hypotheses suspected to link T2DM to cancer risk, hyperglycemia . In post hoc analyses, excluding these participants from the referent group had no material effect on the study findings and the “no-self-reported T2DM and prediabetes” group had similar cancer rates to the referent group. Similarly, we defined HbA1c values <6.5% among people with T2DM as indicative of “good diabetes control” whereas we acknowledge the most recent guidelines from the American Diabetes Association recommend a more relaxed target of 7% (1c of 6.5% to 7%, we opted not to attempt another sensitivity analysis and to current findings according to our original study protocol using the cut-off point of 6.5%. This study was largely limited to older, non-Hispanic White women and men with moderate or higher education levels and these results may not be generalizable to other populations.We acknowledge the subjectivity in defining the joint T2DM-HbAet of 7% . Given tPerhaps, the most significant limitation of this study was the availability of samples from only one nonfasted blood draw. Although serial blood draws from prospective studies in sufficient numbers are rare, and with adequately long follow-up periods to identify cancer occurrences, we acknowledge that serial fasted blood draws for most biomarkers would be superior. Cases and noncases in this study had similar distributions for timing since last meal and blood draw, with 55.0% and 55.7% of noncases and cases, respectively, reporting eating anything within 2 hours of blood draw and only 4.1% and 3.8% of cases and noncases, respectively reporting not eating or drinking within 8 hours of blood draw. An additional limitation in this study was the relatively low sample sizes for the rarer cancers, including liver and ovarian cancers.1c, a marker of average circulating glucose over the last 2–3 months, was associated with all-cancers-of-interest and with colorectal and pancreatic cancers, specifically, in support of hyperglycemia as a mechanism linking T2DM to these cancers. Our finding that well-controlled T2DM was not associated with risk of colorectal cancer supports an earlier hypothesis (In conclusion, this study found little support for a link between c-peptide, a marker of endogenous insulin release, and most cancers-of-interest with the notable exception of a strong positive association with liver cancer risk. HbApothesis  that gooSupplementary Tables S1-S4Supplemental Table 1 - Association of self-reported T2DM at blood draw with risk of all-cancers combined and separately in CPS-II LifeLink participants; Supplemental Table 2 - Association BMI per 5 kg/m2 at blood draw with risk of all-cancers combined and separately in CPS-II LifeLink participants. Excludes those with BMI <18.5 kg/m2; Supplementary Table 3 - Associations of c-peptide with risk of all cancers combined and for the specific cancers of interest by sex in the CPS-II LifeLink cohort; Supplementary Table 4 - Associations of HbA1c with risk of all cancers combined and for the specific cancers of interest by sex in the CPS-II LifeLink cohort.Click here for additional data file.Appendix 1lab methods and qcClick here for additional data file.


Several studies have demonstrated that cardiovascular risk factors play a role in the etiology of breast cancer. However, the combined effect of cardiovascular risk factors on the risk of breast cancer is still uncertain.Data from the Atherosclerosis Risk in Communities (ARIC) study, a prospective cohort of middle-aged women, were used to investigate the association of individual and combined cardiovascular risk factors with breast cancer. Cox proportional hazards models were applied to calculate the hazard ratio (HR) and 95% confidence intervals (CI).A total of 7501 women were included. During a mean follow-up of 19.7 years, 576 women were diagnosed with breast cancer. White women and premenopausal status were independently associated with increased risk of breast cancer. Of the individual cardiovascular risk factors, only obesity was independently associated with an increased risk of breast cancer . Compared with women without cardiovascular risk factors, women having three or greater, but not those with fewer than three cardiovascular risk factors, had a significantly higher risk of developing breast cancer . Subgroup analyses indicated that women with three or greater cardiovascular risk factors had higher risk of breast cancer among postmenopausal Black women, but not among premenopausal Black and White women.Combinations of cardiovascular risk factors are associated with increased risk of breast cancer in middle-aged women, especially in postmenopausal Black women. Joint interventions to modify cardiovascular risk factors could be used to prevent breast cancer in these higher-risk individuals. Breast cancer is the most common female malignant tumor worldwide and comprises 30% of new diagnoses among women in the United States, with an estimated incidence of 268,600 in 2019 . There iConsidering the interaction in cardiovascular risk factors, it is possible that a combination of cardiovascular risk factors could convey more information than a single factor alone. The clinical effects of clustering of cardiovascular risk factors on breast cancer incidence still remain unknown. In addition, studies have found that women who experience a late menopause have an increased risk of developing breast cancer . TogetheTo address this gap in knowledge, we used data from the Atherosclerosis Risk in Communities (ARIC) study and performed a secondary analysis to explore the relationship between independent and combining effects of cardiovascular risk factors and breast cancer in women from the United States (US) to evaluate the associations of risk factors across race/ethnicity and menopausal status.The ARIC Study is a prospective cohort study designed to investigate atherosclerosis risk factors among four communities in the United States . The study objectives, design, sampling scheme, and cohort examination procedures have been described in detail . In brieInformation regarding age, sex, race/ethnicity, education level, income, alcohol drinking habits, and menopausal status was obtained through interviews at Visit 1. Education level was classified into 3 categories: below high school, high school and graduate school, and education beyond graduate school. Income (US$ / Year) was classified into five groups: < 16,000, ≥16,000 to < 25,000, ≥25,000 to < 35,000, ≥35,000 to < 50,000, and ≥ 50,000. For the sub-analysis relative to alcohol drinking habits, participants were grouped into current, former, and never alcohol consumers. Menopausal status was defined as: primary amenorrhea, premenopause, perimenopause, natural postmenopause, and surgical post-menopause. We classified subjects who were premenopausal or perimenopausal at baseline into one category which we labeled “premenopause” and those with primary amenorrhea or natural and surgical menopause at baseline into a category labeled “postmenopause”.2 was calculated based on measured weight wearing a scrub suit and standing height. The BMI was categorized into four groups: underweight (< 18.5), normal (≥18.5 to < 25.0), overweight (≥25.0 to < 30.0), and obese (≥30.0) . Although menopausal status at diagnosis is more relevant to the incidence of breast cancer, one point that should be mentioned is that, in general, we consider late age at menopause associated with prolonged estrogen exposure, which may be related to the timing of onset of cardiovascular risk factors.In the present study, among the cardiovascular risk factors evaluated, obesity was the only factor independently associated with an increased breast cancer risk, however, the association between individual cardiovascular risk factors and incident breast cancer is still contradictory. Herein, we demonstrated that there was an obvious strong association between obesity and increased breast cancer incidence. Recent studies have demonstrated that premenopausal women with a high BMI exhibit an inverse association with breast cancer risk, while postmenopausal women with a high BMI show a positive correlation with higher breast cancer risk. The latter study is consistent with our findings, which provide further evidence demonstrating that the impact of obesity on breast cancer risk varies based on menopausal status. A meta-analysis showed that an inverse association between physical activity and breast cancer risk can be subdivided into menopausal status, whereby a stronger association between physical activity and breast cancer risk was found for premenopausal women but such association was not been observed in the present study . SimilarWe were surprised to observe there was a significant trend for higher breast cancer incidence in patients exhibiting a large number of cardiovascular risk factors. The combined effects of cardiovascular risk factors on breast cancer incidence stratified by race/ethnicity and menopausal status, to our knowledge, have not been previously considered in the literature.P for trend = 0.11) [Indeed, the finding that combined effects may influence the incidence of breast cancer was consistent with a meta-analysis published in 2019, which suggested that the metabolic syndrome  was associated with a significantly increased risk of breast cancer, particularly among postmenopausal women, although the studies examined mainly concerned Caucasian and Asian women . Further = 0.11) . HoweverThe current study provides evidence of the association between race/ethnicity and menopausal status in American women. The findings of the present study contradict those of our previous study and warrants further discussion. We found that White women, and women with premenopausal status in midlife are more likely to develop breast cancer, however, in the stratified analysis we demonstrated having at least three cardiovascular risk factors was associated with increased breast cancer risk in postmenopausal Black women instead of in White women. Several studies have reported that the prevalence of comorbidities  is higher, particularly among Black women , 36. OurP < 0.01 for all) [We may hypothesize that the potential mechanism for these differences involves the presence of circulating estrogen and adipokine levels, which may act as potential mediators linking cardiovascular risk factors and breast cancer. Indeed, ovarian synthesis of endogenous hormones is confirmed to play a role in breast cancer, especially in premenopausal breast cancer, although endogenous hormones decelerate the progression of cardiovascular risk in premenopausal women . Nonethefor all) . Thus, lBased on the findings of our study, we recommend that individuals presenting numerous cardiovascular risk factors should receive more attention, appropriate screening, and careful follow-up, particularly among the Black women, as a preventative strategy for the occurrence of breast cancer and other diseases. In addition, caution should also be exercised in other countries, as the current results derived from a population sample from the United States.The strengths of our study included the analysis of a population-based prospective cohort consisting of a long follow-up duration. We were able to obtain information about cardiovascular risk factors in the study designed to investigate atherosclerosis risk factors in four communities in the United States. However, this study has several limitations. Although the sample size was adequately powered, it was relatively small for the present study. We did not further explore the association between cardiovascular risk factors and breast cancer subtypes due to absence of histologic information. Second, baseline characteristic and cardiovascular risk factors were obtained through interviews at Visit 1, without considering behavior changes occurring during the follow-up period. Third, our results might be susceptible to residual confounding due to missing information for some covariates. Although the interaction only existed between cardiovascular risk factors and race/ethnicity, we still stratified menopausal status to explore the association of combined cardiovascular risk factors with breast cancer because estrogen exposure plays important role in breast cancer and cardiovascular risk factors.The novel findings in this study demonstrate that combinations of cardiovascular risk factors are associated with an increased risk of breast cancer in participants of the ARIC Study cohort, while the effect of individual cardiovascular risk factors is limited to obesity alone. Having ≥3 cardiovascular risk factors increased the rate of breast cancer by 27%, and was particularly significant among postmenopausal Black women in the United States. In a public health perspective, joint interventions aimed at modifying cardiovascular risk factors could be used to prevent breast cancer in these higher-risk individuals.


Dietary intake was assessed using a validated quantified FFQ. Food items were categorised using the NOVA system ((1) unprocessed/minimally processed foods, (2) culinary ingredients, (3) processed foods and (4) ultra-processed foods). Conditional logistic regression models were used to estimate OR and 95 % CI of dietary contributions from each NOVA food group ) and adjusting for potential confounders. Considering contributions to total EI per day, ultra-processed food consumption contributed to 44·8 % in cases and 47·9 % in controls, while unprocessed/minimally processed foods contributed to 38·8 % in cases and 35·2 % in controls. Unprocessed/minimally processed food consumption showed an inverse association with breast cancer risk overall , as well as in pre- and postmenopausal women separately  and in women with progesterone positive breast cancer . There was no heterogeneity in association with breast cancer when analyses were stratified according to BMI. No significant associations were observed for the consumption of other NOVA food groups. Intake of unprocessed/minimally processed foods may reduce the risk of developing breast cancer in black women from Soweto, South Africa.This study aimed to investigate the association between consumption of ultra-processed foods, whole foods and breast cancer risk in black women from Soweto, South Africa. A population-based case ( Modifiable risk factors such as an unhealthy diet, obesity and physical inactivity have already been identified and play a crucial role in primary breast cancer prevention.Breast cancer is currently the cancer with the highest incidence rate among South African women. However, as a result of the nutrition transition, the South African food environment is becoming more obesogenic where whole foods are frequently being replaced by ultra-processed foods,6. According to the NOVA food processing classification system (not an acronym but a name and hereafter referred to as the NOVA system), ultra-processed foods are defined as ‘formulations of ingredients, mostly of exclusive industry use, that result from a series of industrial processes’. Ultra-processed foods are becoming more accessible, available and affordable in both rural and urban areas of South Africa,9. This is worrisome since ultra-processed food consumption has been associated with an increased risk of gaining weight or becoming obese and developing non-communicable diseases, including breast cancer–14.South Africa has several policies in line with the comprehensive NOURISHING  policy framework of the World Cancer Research Fund and American Institute for Cancer Research, promoting healthy diets and lifestyle behaviour that may reduce the risk of developing breast cancer. However, diets characterised by more frequent consumption of ultra-processed foods are more energy dense and contain less micro-nutrients and fibre than diets characterised with frequent consumption of unprocessed/minimally processed foods–16.Not all aspects of food processing such as grinding, milling, freezing and drying of fresh foods are nutritionally harmful and some are mainly used to manufacture various nutritious staple foods –21. But, the NOVA system established by Monteiro and associates is used the most in research and policy development,21,22. The NOVA system assigns foods to one of four food classification groups according to the extent and purpose of processing. These groups include (1) unprocessed or minimally processed foods ; (2) culinary ingredients ; (3) processed foods  and (4) ultra-processed foods .Various classification systems have been proposed for categorising foods according to their degree of processing such as the International Food Information Council and University of North Carolina UNC systems, Foodex and LanguaLa posteriori dietary patterns and breast cancer risk in black urban South African women from Soweto. In this study, several patterns have been identified: a traditional pattern , cereal-dairy breakfast-pattern  and a processed food dietary pattern . While the traditional- and cereal-dairy breakfast dietary patterns were significantly inversely associated with breast cancer risk, no association was observed between a processed food dietary pattern and breast cancer risk. However, this approach did not consider the degree of industrial food processing according to the NOVA system specifically. In addition, individual consumption data have never been assessed according to the degree of food processing in any South African study. Therefore, the aim of the present study was to (1) describe dietary intake of ultra-processed food according to the degree of food processing, using the NOVA system, in an urban population of Black South African women from Soweto, South Africa who participated in a population-based case–control study and (2) to investigate the association of UPF with breast cancer risk.A previous study conducted by Jacobs and colleagues investigated the association between –26. The SABC study was conducted at the Chris Hani Baragwanath Academic Hospital in Soweto from 2014 to 2017 and included a total of 399 cases and 399 matched controls. Due to missing dietary intake information, three cases and three controls were excluded. The final population of the study included 396 cases and 396 matched controls. Breast cancer cases  included black urban adult women (over 18 years of age) who were newly diagnosed with breast cancer and who did not previously receive any cancer treatment. Breast cancer cases were invited to participate at referral for diagnostic biopsy, and failing that, as soon as possible after cancer diagnosis. Stage at breast cancer was clinically assessed at diagnoses and coded according to the tumour-node-metastasis classification. Breast cancer subtypes were defined using the Allred score. Controls  were black adult women from Soweto (over 18 years of age) and unrelated to breast cancer cases with no history of cancer diagnoses. Controls were recruited using a multistep sampling procedure from the areas of residency of the cases and matched by area of residence and age (±5 years),26. Other matching criteria of interest  were captured and used in statistical models to allow us to study these criteria in relation to breast cancer risk. The sample size (396 cases and 396 matched controls) was sufficient to obtain a power > 80 % (type-II error rate β = 10 %) for ORs ≥ 1·5 when type-I error is set to 5 %. For subcategory analysis, a size of ≥132 participants were sufficient to obtain a power > 80 % (type-II error rate β = 10 %) for ORs ≥ 1·7 when type-I error is set to 5 %.Data from the South African Breast Cancer (SABC) study, a population-based, case–control study among black urban women, were used for this studyThe International Agency for Research on Cancer and the University of the Witwatersrand Committee for Research on Human Subjects granted ethical approval for the SABC study (M140980). The Gauteng Province Medical Advisory Committee gave permission to conduct research at the Chris Hani Baragwanath Academic Hospital. The North-West University gave ethical approval for the use of the quantified FFQ (QFFQ). All participants gave written informed consent prior to participation to the study.2. Questionnaires used to obtain the above-mentioned information were validated–30.Trained investigators and fieldworkers conducted face-to-face interviews at inclusion in the study and for cases as soon as possible after breast cancer diagnoses. Information regarding socio-economic and demographics  was self-reported. Detailed information was further collected with a questionnaire regarding history of health, ethnicity, reproductive risk factors, breast health, family history of cancer, physical activity and smoking habits. Anthropometric measurements such as height, sitting height, weight and waist circumference were performed according to a standardised protocol. BMI was calculated as kg/m–33. The QFFQ entailed of 145 food items reported by recently published literature as regularly consumed staple foods and foods less regularly consumed. The dietary intake frequency included the amount of times foods were consumed per day/week/month or never. Life size colour photographs of thirty-seven foods (in three portion sizes) were displayed in the food portion picture booklet. A detailed description of the method used to determine the daily intakes is described elsewhere. The nutrient and energy intakes (EI) were calculated by multiplying the daily intake of each food item by the nutrient and energy content (per 100 g), derived from the South African Food Composition Tables, and then adding the contribution from all food items together.Participants were asked about their habitual dietary intake over the past month  and dietary intake data were collected immediately after breast cancer diagnoses (at recruitment) before any cancer treatment. A validated and reproducible culture-specific QFFQ was used together with food models, food portion pictures and household utensils alongside the South African Food Composition Tables to determine habitual dietary intake. Foods were categorised into their most usual form of consumption with the most conservative classification option (less processed level) chosen in a case of doubt. Homemade dishes and culinary ingredients used in preparation methods (onions fried in oil or pumpkin candied with added sugar) were disaggregated according to the standardised recipes of the South African Food Composition Tables. Disaggregated food items were then categorised based on the NOVA system. For instance, onions fried in oil were categorised as follows: onions as unprocessed/minimally processed food and oil as culinary ingredients.To classify foods based on the level of food processing, all foods and drinks, collected through the QFFQ, were categorised into one of the four NOVA food groups. The NOVA system was used in our study since it is the most used food classification system in research studies and will enhance comparability of our study results. These foods included staple foods mostly consumed in South Africa .Unprocessed or minimally processed foods are defined as foods that are naturally ready to consume or foods altered by minimal processing such as removal of inedible parts, drying, grinding, crushing, filtering, roasting, freezing, chilling, pasteurising, fermenting and boiling. These processing methods do not add any salt, sugar, oils or fats to the original products. Industrial processes, such as pressing, refining, centrifuging, mining or extracting, are mainly used in food preparation, seasoning and cooking of unprocessed/minimally processed foods.Culinary ingredients (NOVA 2) are substances extracted from unprocessed/minimally processed foods or from nature, such as salt, sugar, fat and oil. The aim of food processing in this group is to increase the durability of foods within the unprocessed/minimally processed food group and to make them more enjoyable by enhancing their sensory qualities. Foods is this category include: cheese, preserved fruits, vegetables and beans in brine, salted nuts or nut spreads, sweetened dairy products (contains only added sugar with no additives), beer, wine and non-ultra-processed bakery products.Processed foods (NOVA 3) are defined as industrial products made with added salt, sugar or other culinary ingredients to unprocessed/minimally processed foods, using preservation methods. For instance, bottling or canning and using non-alcoholic fermentation in the case of cheeses and breadsUltra-processed foods (NOVA 4) included carbonated drinks, industrial pre-packaged fortified* bread and buns, cookies, pastries, cakes, cake mixes, breakfast cereals, energy bars, margarines and spreads, instants sauces, soup powders, pre-prepared pies, pasta and pizza dishes, reconstituted meat products, sweet and savoury packaged snacks, ice-cream, fruit yogurts, instant desserts and noodles and distilled alcohol products such as whiskey, gin, rum and vodka. All breads were considered to be industrial pre-packed breads and were classified under ultra-processed foods since the QFFQ used to determine dietary intake did not specify between processed or ultra-processed bread. *Fortification of wheat flour, used to make bread, is compulsory in South Africa since bread is considered a staple food .t test  and Wilcoxon signed rank test (skewed data) for continuous variables and paired χ2 test for categorical variables (presented as percentages).Descriptive analyses were presented by mean values and standard deviations  and median; 25th−75th percentile (for data with skewed distributions). Differences between breast cancer cases and controls were assessed using paired sample v. post) and BMI status (BMI < 30 kg/m2v. BMI ≥ 30 kg/m2).For each participant, the relative energy contribution  of each NOVA food group in the diet was calculated and then categorised into tertiles. Conditional logistic regression was applied to compute OR and associated 95 % CI to determine the associations with each NOVA food group  and breast cancer risk and when stratified by oestrogen positive and progesterone positive (PR+) receptors. Due to the limited number of participants in each breast cancer subcategory, which may have insufficient statistical power, we decided to explore associations by oestrogen positive and PR+ receptors only, and not in combination. Unconditional logistic regression was used to determine the association with breast cancer risk when analysis was stratified by menopausal status , age at menarche (continuous), full-term pregnancy (yes/no), age at first pregnancy , age of menopause , parity , ever breast-feeding (yes/no), duration of exclusive breast-feeding (months), use of exogenous hormones , family history of breast cancer (yes/no), alcohol consumption, HIV positivity (yes/no) and reporting of energy (under-reporting v. over-reporting).A two-stage model was used to obtain OR and the associated 95 % CI. Confounding factors were considered as factors influencing the crude OR output by more than 10 %. The crude output was reported in model 1, taken into account the matched factors of breast cancer cases and controls . The following confounders were examined in the analysis before insertion in model 2: age (continuous), ethnicity , ‘individual income/month in South African Rand  and income ≥ R3001+ (> ± $ 195), categorised based on data from this study)’, level of education , smoking (smokers and non-smokers), height (continuous), waist circumference (continuous), total physical activity/d , physical activity and menopausal status  influenced the crude output by more than 10 % and were therefore included in model 2.A generalised linear model was used to estimate the differences in least square means (measured in kJ per day) of (1) unprocessed/minimally processed foods, (2) processed foods and (3) ultra-processed foods between breast cancer cases and control participants. The effect of potential confounders  was tested for by including additional variables into the generalised linear regression model.sd 13·8) cm) compared with controls (95·8 cm (sd 13·7) cm) and had a lower percentage of HIV-positive women (16·5 % v. 22·6 %). Considering dietary factors, the percentage of non-alcohol consumers was higher in cases (80·8 %) than in control participants (69·4 %). Additionally, in breast cancer case participants, oestrogen positive (75·2 %) and PR+ (75·2 %) were the dominant hormonal breast cancer tumour receptors, while triple negative breast cancer receptors accounted for 16·1 % of all tumour types.P < 0·05) , ultra-processed food consumption contributed to 44·8 % in breast cancer cases and 47·9 % in control participants (·05) see . UnproceP-trend < 0·001), for postmenopausal women , for PR+ breast cancers  and for obese women . Trend analysis further showed that higher consumption of culinary ingredients, processed foods and ultra-processed foods was inversely associated with breast cancer risk overall .P-trend = 0·001), for postmenopausal women  for PR+ breast cancers , for women with a BMI < 30 kg/m2  and for women with a BMI ≥ 30 kg/m2 . An inverse association with breast cancer risk and higher consumption of unprocessed/minimally processed foods was additionally noted for premenopausal women .After adjusting for possible confounders, the associations between breast cancer risk and higher consumption of unprocessed/minimally processed foods remained significant for breast cancer risk overall  (instead of under ultra-processed foods) in the analysis, since the QFFQ used to determine dietary intake did not specify whether breads consumed were processed or ultra-processed. However, sensitivity analysis did not significantly change the results. Sensitivity analysis was conducted, using the proportion of each NOVA food group as a weighted ratio (percentage g/d) of the total food intakes to take into account non-nutritional factors that do not provide any energy  in ultra-processed foods. Results did not differ from the analysis with food groups measured as percentage kJ/d.sd 13·1) g). The unprocessed/minimally processed food group had the highest content of dietary fibre (mean = 28·1 g (sd 14·9) g) while having the lowest content of saturated fats  and added sugar . Both the unprocessed/minimally processed and ultra-processed food groups had similar high contents of micronutrients.S1 presents the top ten single foods consumed between breast cancer cases and controls within the unprocessed/minimally processed, processed and ultra-processed food groups. The culinary ingredients group was excluded from this table. Maize meal, white rice, apples, eggs and beetroot were among the most consumed single foods within the unprocessed/minimally processed food group in both breast cancer cases and controls.Online Supplementary Table Regarding processed foods, peanut butter, atchar , vetkoek (deep fried doughnut like dough) scones and canned pilchards  were among the top ten single foods consumed in both breast cancer cases and controls.The most consumed single foods within the ultra-processed food group in both breast cancer cases and control participants were brown bread, white bread, soup powder, beef sausages , margarine and carbonated soft drinks.2 and for women with a BMI ≥ 30 kg/m2. No significant association with breast cancer risk was observed for higher consumption of culinary ingredients, processed and ultra-processed foods.In this study of black women from Soweto, South Africa, consumption of unprocessed/minimally processed foods contributed to more than a third of the total EI per day in both case and control participants, while ultra-processed foods contributed to more than 44 % and processed food to about 12 % of the total EI per day. Higher consumption of unprocessed/minimally processed foods was inversely associated with breast cancer risk overall, for pre- and postmenopausal women, for PR+ breast cancers, for women with a BMI < 30 kg/m,36,37.Unprocessed/minimally processed food consumption accounted for 38·8 % of total EI in breast cancer cases and 35·2 % in controls in this study. Studies investigating the association between breast cancer risk and unprocessed/minimally processed foods (NOVA 1), as a group, are lacking. However, similar intakes of unprocessed/minimally processed foods were observed in studies  conducted in Canada (39·2 %), Australia (35 %) and Chile (33·8 %),39. In general, plant-based unprocessed/minimally processed foods have a healthier nutrient profile with a lower energy density and high content of various phytochemicals , vitamins and minerals, which may be linked to several anti-cancerous cell effects in the human body,37. The unprocessed/minimally processed food group in our study had a similar ‘healthy’ nutrient profile as these plant-based unprocessed/minimally processed foods, which may explain the significant inverse association thereof with breast cancer risk in our study. Unprocessed or minimally processed foods are also linked to a lower risk of gaining weight or being obese, which may reduce the risk of developing postmenopausal breast cancer. Disease prevention dietary guidelines such as the World Cancer Research fund/American Institute for Cancer Research’s Cancer Prevention Recommendations and the South African Food Based Dietary Guidelines therefore advise to consume unprocessed whole foods  while limiting highly processed foods with added sugar, saturated fat and salt,40. Results of this study support the use of the above-mentioned dietary guidelines as educational tools to promote healthy diets in Soweto, South Africa that could assist in preventing breast cancer development.Results of our study are in line with other studies (conducted in different populations), which have found an inverse association between plant-based unprocessed/minimally processed food groups or dietary patterns with non-communicable diseases,37,41–43. Higher consumption of culinary ingredients and processed foods  did not show any significant association with breast cancer risk in our study. More research regarding culinary ingredients and processed food consumption is required in South Africa and in particular this population.The contribution of culinary ingredients and processed foods to total EI/d was similarly distributed in both breast cancer cases  and controls . Similar percentage energy contributions of culinary and processed foods to total EI/d were noted in other studies –43. Our study showed similar percentage intakes of ultra-processed foods as in studies conducted in Canada (48 %) and Australia (42 %), while lower percentages of ultra-processed food consumption were noted in Belgium (29·6 %), France (18·7 %) and other middle-income countries such as Brazil (21·5 %), Mexico (29·8 %) and Chile (28·6 %),36,37,44. This indicates that this urban female population of Soweto, South Africa, an upper middle-income country, has higher percentages of ultra-processed food contributions in their diets than other middle-income countries and similar percentage intakes than high-income countries. However, cultural influences and preferences of different countries may also influence the amount of ultra-processed food consumed.Dietary contributions of ultra-processed foods to total EI per day in this study (> 44 %) were lower than studies conducted in the USA (between 55·0 and 57·5 %) and the UK (between 48·6 and 56·8 %),45. In the South African context, cost and affordability can also be a major driver of food choices, irrespective of their nutritional value and quality. For example, mass-produced fortified white-and-brown bread, an affordable staple food in South Africa, was the most consumed ultra-processed food item in both breast cancer cases and controls. Compared with affordable unprocessed/minimally processed starchy staples such as rice and maize meal in South Africa, mass-produced white-and-brown breads are cheaper and require less preparation time and may therefore be more frequently bought.The high percentage ultra-processed food contributions to total EI in this study reflect the changes in dietary patterns due to the growing obesogenic food environment in South Africa,40,41,46. The high percentage of ultra-processed food consumption in this study is therefore concerning and emphasises the need for healthy, affordable and sustainable food environments that prioritise nutrition policies supporting the NOURISHING framework,48. However, creating healthier and affordable food environments remains a difficult task and will require commitment from various stakeholders across multiple  sectors in South Africa.Compared with the other NOVA food groups, the ultra-processed food group in our study had the highest content of saturated fat and added sugar while having the lowest content of dietary fibre. A diet consisting mainly of foods with a less healthy nutrient profile  reduces the overall quality of the diet and increases the risk of developing obesity and other diet-related non-communicable diseases. Another matched case–control study conducted in Brazil found that regular consumption of ultra-processed foods (> 5 portions per week) was associated with having a 2·35 times higher odds of developing breast cancer. Although the ultra-processed food group in our study had a high content of energy, saturated fat and added sugar, together with a low content of dietary fibre, a high content of micronutrients was observed. The high content of micronutrients, which may increase the quality of the overall diet, may explain why no significant association between ultra-processed food consumption and breast cancer risk was observed in our study. It is therefore possible that the type and nutritional value of ultra-processed foods consumed in South Africa differ from the French and Brazilian studies. However, ultra-processed foods are not considered healthy since evidence has linked higher consumption thereof to various non-communicable diseases and therefore requires more research.Interestingly, no significant associations were observed between higher ultra-processed food consumption and breast cancer risk in this study. In contrast to our findings, the French NutriNet-Santé cohort study (104 980 participants) showed that higher consumption of ultra-processed foods, using the NOVA system, was positively associated with breast cancer riskGiven that cancer develops over an extended period, diet in the past several years may also influence cancer risk. Therefore, results of our study should be interpreted with caution since data collection of the SABC study focused on the participant’s current diet (past month at the time of diagnosis) and not past dietary intake of several years back. However, this is a general problem for any study that collect current dietary data only once. Additionally, it is possible that the period of data collection in our study overlapped with breast cancer symptoms, which could have led to changes in habitual dietary intake of breast cancer cases. Thus, a possibility of biased dietary data for cases due to changes in dietary intake, but dietary intake may also depend on the stage of cancer at diagnoses and therefore, require more research.Our study has some strengths and limitations. Strengths include that cases were recruited prior to any breast cancer treatment and questionnaires used to obtain data were proven to be validated. Trained personnel were used to administer all questionnaires (not self-reported). Data used in the analysis were standardised and the categorisation of the food items according to the NOVA system was discussed with experts involved in the development of the NOVA system. Limitations include the relatively small sample size of this study, especially for subgroup analyses, and the fact that dietary intake was measured over the past month (at recruitment of the study) when habitual dietary intake of case participants could have changed due to illness . The nature of the study design could potentially result in non-differential misclassification and underestimation of the associations. In addition, although dietary intakes were captured throughout the year (in different participants) seasonal variability of foods (not adjusted for) may have influenced usual reporting of dietary intakes. The QFFQ used to evaluate the NOVA food groups was not specifically designed to capture foods based on their degree of processing. This made the recognition of each NOVA food group difficult. In addition, foods were categorised into their most usual form of consumption with the most conservative classification option (less processed level) chosen in a case of doubt. Information bias may therefore exist, while residual confounding can also not be ruled out.In conclusion, unprocessed/minimally processed foods may reduce the risk of developing breast cancer in this population. Foods associated with unprocessed/minimally processed foods may play an important role in primary breast cancer prevention guidelines. However, more research on this topic is required and our results first need to be replicated in other South African regions and populations before any dietary guidelines can be formulated. Our results suggest that food environments and dietary intake behaviour should be prioritised to make unprocessed/minimally processed foods more affordable, accessible and available in South Africa. The high amount of EI from ultra-processed foods is worrisome as these foods may displace possibly protective foods from the unprocessed/minimally processed food group, which may reduce the risk of breast cancer in this population.


The aim of this study was to investigate the influence of previous mammography screening on the performance of breast cancer detection. The screened women were divided into first-visit and follow-up groups for breast cancer screening. The positive predictive value (PPV), cancer detection rate (CDR), and recall rate were used to evaluate and analyze the overall screening performance among the two groups. Among them, 10,040 screenings (67.2%) were first visits and 4895 screenings (32.8%) were follow-up visits. The proportion of positive screening results for first-visit participants was higher than that for their follow-up counterparts (9.3% vs. 4.0%). A total of 98 participants (74 first-visit and 24 follow-up visit) were confirmed to have breast cancer. The PPV for positive mammography for women who underwent biopsy confirmation was 28.7% overall, reaching 35.8% for the follow-up visit group and 27.0% for the first-visit group. The CDR was 6.6 per 1000 overall, reaching 7.4 per 1000 for first-visit group and 4.9 per 1000 for the follow-up group. The overall recall rate was 7.9%, reaching 9.7% for the first-visit group and 4.2% for the follow-up group. The PPV is improved and the recall rate is decreased if prior mammography images are available for comparison when conducting mammography screening for breast cancer. By this study, we concluded that prior mammography plays an important role for breast cancer screening, while follow-up mammography may increase the diagnostic rate when compared to the prior mammography. We suggest that the public health authority can encourage subjects to undergo screenings in the same health institute where they regularly visit. Breast cancer accounts for 30% of all new cancer diagnoses for women and is a heterogeneous disease presenting various clinical behaviors, morphological appearances, and treatment responses . The higEarly detection in the clinical setting plays an important role in cancer treatment. The goal of screening is to find cancers when they are still curable  to decrease cancer-related mortality. Regular mammography screening allows the early detection of benign and malignant tumors, thus facilitating immediate treatment and significantly reducing the mortality rate and treatment-related morbidity ,6. EarlyAlthough mammography screening is widely considered effective, the distress associated with false positive results cannot be overlooked. For women who started receiving screening mammography annually at age 40, the 10-year cumulative probability of a false positive recall is 61% in Taiwan . In JapaPrevious studies focused on the fact that regular screening can reduce mortality. Our study focuses on the theory that regular screening within the same institution can increase the true positive rate, reduce patient anxiety, facilitate medical management, and avoid unnecessary medical expenses. The aim of this study was to compare the performance of screening mammography based on first visits and follow-up visits and to determine the effect of prior mammograms on screening performance, recall rates, and positive predictive values (PPVs).In Taiwan, the peak age for breast cancer diagnosis is between 45 and 69 years old. Therefore, the Health Promotion Administration offers a free mammography exam biennially for women aged 45 to 69 and for those aged 40 to 44 years with a family history of breast cancer .The research sample of this study consisted of women who received a free mammography exam offered by the Health Promotion Administration in Taiwan from 1 January 2015 to 31 December 2018. The study design was approved by the Institutional Review Board in our hospital (KMUHIRB-E(I)-20220019).Women with existing clinical symptoms  were excluded. Women who had been diagnosed with breast cancer more than 10 years prior to this study and were previously declared disease-free by their physicians were enrolled. The examinees’ clinical data  were recorded by the technician who conducted the mammography. The examinees filled out a written informed consent form to allow their data to be transferred to the screening database.A total of 12,301 women participated in this study, and 15,661 mammography screenings were performed. Of them, 626 screenings were visits due to clinical symptoms and were excluded. Of the remaining 14,935 screenings , 10,040 As the Health Promotion Administration offers a free mammography exam biennially, this study included 4 years’ worth of data. Thus, if a woman was regularly screened at this hospital, the same woman would have 2 screening data records.The mammography images were taken with a Giotto Image 3D full-field digital mammography unit . A movable grid was used with voltage ranging from 22 to 35 kVp to obtain the mammograms. The mAs value is an important parameter indicating the radiation dose to patients, and it ranges from 4 to 500 mAs, with an interval of no more than 15%. In our study, it was set to around 30 to 100 mAs. The mammography method involved the standard bilateral craniocaudal view and mediolateral oblique view. Each woman received a total of 4 mammograms. The physician’s screen for image interpretation was a display with a resolution of 5M pixels. All mammograms were interpreted by the radiologists. The CDR was obtained by dividing the number of participants diagnosed with breast cancer by the total number of participants screened (CDR per 1000 screenings).The screened women were divided according to whether it was their first visit or a follow-up visit for breast cancer screening. First visit means that the participant came to this hospital for examination for the first time. This could mean that the participant met the qualifications of the Health Promotion Administration for the first time and came to this hospital for screening (first screening), or that the participant, who had been screened at a different location before, visited this hospital for the first time for screening (previous images were unavailable). Follow-up visit means that the participant had been screened in this hospital before, possessed previous imaging data, and was also screened in this hospital this time (with previous images). The mammography report was described using the 5th edition of the Breast Imaging Reporting and Database System score (BI-RADS) of the American College of Radiology (ACR).Categories 1 to 3 were classified as negative; Categories 4, 5, and 0 were classified as positive. Participants with Category 0 were requested to return for a follow-up to undergo other examinations and reassessment. If examinees were classified as Category 1, 2, or 3, regular examination for them was recommended. If the follow-up results were Category 4 or 5, surgical tests, namely fine-needle aspiration biopsy, pathological tissue biopsy, core biopsy, hook wire needle localization, stereotactic localization, and surgical biopsy, were recommended. The pathological results were obtained from the screening database of the Ministry of Health and Welfare and were divided into benign and malignant tumors. Benign breast diseases were defined as non-breast cancer, whereas ductal carcinoma in situ (DCIS) and invasive carcinoma were defined as breast cancer.Descriptive statistics were adopted to classify the data and acquire the percentages (%). The specificity, PPV, cancer detection rate (CDR), and recall rate were used to evaluate and analyze the overall screening performance. SPSS 12.0 version was used for all statistical analyses.This study consisted of 11,892 participants, of whom 3043 (25.6%) participated in two screenings in this study and 8849 (74.4%) participated in one screening. The mean age of the women undergoing screening was 54 years. The percentages of the age groups at screening were as follows: 5.3% were screened at the age of 40 to 44 years, 26.7% were screened at the age of 45 to 49 years, 23.4% were screened at the age of 50 to 54 years, 20.9% were screened at the age of 55 to 59 years, 15.3% were screened at the age of 60 to 64 years, and 8.5% were screened at the age of 65 to 69 years. In terms of education level, most participants graduated from high school/vocational high school (48.5%), followed by those who attended junior college/university (30.1%), junior high school (10.0%), elementary school (7.4%), or graduate school or higher (3.2%) and those with no formal education (0.9%). Most women had no history of breast cancer (73.4%), followed by those with benign breast tumor (25.2%), those with other cancers (1.1%), and those who previously had breast cancer (0.2%). Participants with and without a history of breast cancer within their second-degree relatives accounted for 73.4% and 6.3%, respectively. Furthermore, 88.4% had a childbearing history, 60.1% were menopausal, and 91.0% had no history of breast surgery. In terms of the classification of the participants’ mammary glands, most were classified as heterogeneous (68.1%), followed by extremely dense (18.5%), scattered fibroglandular (13.0%), and fatty (0.4%).p < 0.0001). In comparison, the proportion of positive screening results for first-visit participants (9.3%) was higher than that for their follow-up counterparts .The initial mammography interpretation results are listed in p = 0.1491).A total of 98 participants (74 first-visit participants and 24 follow-up participants) were confirmed to have breast cancer in this study. The pathology report concluded a slight difference between the percentage of DCIS among first-visit (46.0%) and follow-up visit participants (41.7%). In comparison, a higher percentage of follow-up visit participants (58.3%) were diagnosed with invasive carcinoma compared to first-visit participants (50.0%).Most breast cancer cases detected by screening had no lymphatic metastasis. Moreover, little difference was observed between the two groups of participants in terms of whether cancer metastasis was observed . The maximum size of the breast cancer masses detected among follow-up visit participants was <20.0 mm (mean size: 10.1 mm). However, 24.3% of first-visit participants had masses >20.0 mm (mean size: 16.8 mm).The effect of comparing first-visit and follow-up visit participants on the performance and effectiveness of mammography is described as follows and in p < 0.0001).p = 0.0761).The overall CDR was 6.6 per 1000. As presented in p < 0.0001).PPV was divided into PPV1, PPV2, and PPV3, among which PPV1 was the number of participants with positive mammography results  who were actually diagnosed with breast cancer. The overall PPV1  was 8.3%, and the PPV1 value of follow-up visit participants (11.8%) was significantly higher than that of first-visit participants .PPV2 (biopsy recommended) was the number of participants with positive mammography results (BI-RADS Categories 4 and 5) who were actually diagnosed with breast cancer. The overall PPV2 was 25.7%, and the PPV2 value of follow-up visit participants (32.0%) was significantly higher than that of first-visit participants .PPV3 (biopsy conducted) was the number of participants with positive mammography results (BI-RADS Categories 4 and 5) who underwent biopsy tests  and were actually diagnosed with cancer. The overall PPV3 was 28.7%, and the PPV3 value of follow-up visit participants (35.8%) was significantly higher than that of first-visit patients  than in the first-visit (7.4 per 1000) counterparts. Although the CDR in the follow-up visit group failed to be higher than that of the first-visit group in the current study, the overall CDR was still superior to the data in other studies. Previous reports showed that the detection rate of screening mammography was 2 to 8 cancers per 1000 mammograms ,24,25.In the current study, the overall PPV3 for examinees was 28.7%. The performance was similar to that in the literature review . MoreoveAs to the size of an early breast cancer detected by the screening, when physicians had access to previous imaging data for reference (follow-up visits), the mass size of the breast cancer detected did not exceed 2 cm. However, when the physicians did not have access to previous imaging data (first visits), a proportion of the patients diagnosed with breast cancer did have masses exceeding 2 cm. Moreover, the data indicated that when physicians had access to previous images (follow-up visits), breast cancer could be detected immediately when the mean mass size was only 1 cm. If no image was available for comparison (first visits), breast cancer could only be detected when the mass grew to a mean of 2 cm.p = 0.0316) [The sensitivity of mammography is lower in women with dense breasts ,27,28,29This study has provided clinical evidence of the effects of screening mammography, especially at follow-up visit. However, it still has the following limitations. Among the positive cases in this study, not every screened participant returned for follow-up or biopsy examinations, and these data would affect the research results. In addition, mammogram interpretation was conducted by two radiologists, and the inter-observer bias of interpretation needs to be further evaluated.Accordingly, when performing large-scale screening mammography, we encourage the public to undergo mammography screening at the same health institute, which is helpful to the overall performance of mammography and can reduce the possibility of false positive results. The government and health units are recommended to provide relevant information to the public as a reference. According to prior data, about 15% of breast cancer diagnoses may not be detected by mammography, depending on technical limitations and/or operator skill. If patients undergo mammography screening at the same health institute, it may prevent false positive results. A follow-up mammography may increase the PPV of disease diagnosis as compared with prior mammography. On the other hand, patients are encouraged to have a digital copy of each mammography as their own record, so they can bring them for the next mammography. The authors hope that the settings for viewing images on the cloud system will be more comprehensive in the future to provide references for physicians and facilitate the public’s convenience.Mammography can detect the transformation of breast microcalcifications and abnormal shadows of early lesions along with early detection of malignant tumors. If prior mammography images are available to be compared, the PPV can be increased and the recall rate can be reduced. In this study, the average lump size, if confirmed to be malignant, was within 1 cm. The public health authority should encourage subjects to undergo screenings at the same health institute where they regularly visit. In our study, when the previous mammography images could be compared, the PPV increased and the recall rate was reduced. This may establish a system for early detection and prevention.


Nipple fluid aspiration (NFA) is a technique to acquire nipple aspirate fluid (NAF), which is considered a rich source of breast-specific biomarkers. Originating directly from the mammary ducts, this liquid biopsy can offer insight into the process of carcinogenesis at its earliest stage and therefore could be of added value to the current imaging-based breast cancer screening tools. With that in mind, it is necessary to know how well NFA is tolerated.To evaluate the participants’ tolerability of NFA compared to breast imaging screening methods and blood draws.n = 190), women diagnosed with breast cancer (n = 137) and women at high risk of developing breast cancer (n = 48). A 0–10 discomfort score of NFA, mammography, breast MRI and blood draws, was filled in at the study visits, which took place once or annually.Three cohorts of women underwent NFA: healthy women (p < 0.001), but significantly higher than median discomfort for blood draws . The great majority of women would undergo the procedure again (98%) and recommend it to others (97%).The median discomfort rate of NFA was 1, which was significantly lower than the median discomfort of mammography and breast MRI (5 and 3, respectively, This study shows that NFA was well tolerated by healthy women, women diagnosed with breast cancer and high-risk women. This makes NFA a feasible method to pursue as a potential future breast cancer early detection tool, based on resident biomarkers.NL41845.041.12, NL57343.041.16 and NL11690.041.06 in trialregister.nl.The online version contains supplementary material available at 10.1186/s12885-022-09795-8. Breast cancer is the most common cancer amongst women  and deteA specific liquid biopsy of the breast is nipple aspirate fluid (NAF), a biofluid that accumulates at small amounts in the breast ducts of non-lactating women . As suchWe previously published the feasibility results of (repeated) NFA in separate cohorts of healthy women  and highThree cohorts of women were included in the present analysis: healthy women, women with breast cancer and women at high-risk of developing breast cancer. These cohorts are all part of the Dutch Nipple Aspirate Fluid project –26, 28. Inclusion of the healthy cohort  was starIn the second cohort, breast cancer patients  were incn = 48) of high-risk women was selected based on overlapping study participation period with the healthy and breast cancer cohorts and comprises consecutive inclusions of high-risk women, except for two women with a history of invasive breast cancer, who were excluded from the analyses. Participants were informed about the study at the outpatient clinics of the genetics department and familial cancer clinic in the UMC Utrecht. Inclusion criteria comprised having a cumulative lifetime risk (LTR) higher than 20% estimated at the genetics department at the time of inclusion [Women at high risk of developing breast cancer and undergoing routine surveillance were included in the high-risk cohort  between nclusion  as descrExclusion criteria for all cohorts comprised active breast infection, pregnancy and lactation. See File S1 for specified inclusion and exclusion criteria per cohort. Written informed consent was obtained from all participants and the ethical review boards within the participating hospitals approved the studies .Study visits were carried out by trained research nurses, and included NFA, phlebotomy and questionnaires. Performing NFA requires a short practical training and can be easily learned. Participants were asked to apply an anesthetic cream onto the nipple covered with an occlusive plaster prior to the study visits (for at least one hour), to minimize discomfort due to the NFA. At the study visit, participants were seated in an upright position. The trained research nurse cleansed the breast, smeared a scrub gel to remove any occluding keratin plugs and disinfected the nipple with alcohol. This was followed by inhalation of one spray of oxytocin nasal spray in both nostrils, in a dose of 4 IU per spray, to stimulate NAF flow towards the nipple. Subsequently, a suction cup  was plan = 10) and plasma (n = 6) were immediately biobanked at -80ºC. Blood collection was initially not part of the high-risk cohort study protocol, and hence, not included in the discomfort assessment of our previous studies [Blood was collected by phlebotomy in the median cubital vein. After collection, serum (in BD Vacutainer SST II Advance tubes) and plasma (in BD Vacutainer K2E (EDTA) tubes) were processed within 1 h by centrifugation at 1500 × g for 20 min. Aliquots of serum  and GraphPad Prism for Windows version 8.0 . A two-tailed p-value < 0.05 was considered statistically significant. Data are presented as median with interquartile range (IQR) or mean with standard deviation (SD) when appropriate for continuous data, and counts with percentages for categorical data. Normality of data distribution was evaluated by Kolmogorov–Smirnov test.The chi-square test was used to compare the binary variables breastfeeding, mammography, breast MRI, blood collection, breast MRI, breast physical exam (yes vs. no) between cohorts. The Mann Whitney test was used to compare age between cohorts. The Mann–Whitney test was used to compare median discomfort of NFA with the median discomforts of breastfeeding, breast physical exam, mammography, breast MRI and blood collection. Violin plots were made in GraphPad to display experienced discomfort distribution and medians. In the high-risk cohort, discomfort scores of the first study visit were included in the analyses. The Hodges-Lehmann Estimate (HLE)  was usedThe Spearman’s test was used to investigate correlation between discomfort scores with age, parity, breastfeeding, duration of breastfeeding, history of spontaneous nipple fluid discharge, breast size, use of contraception, age at menarche, menopausal status, NAF sample volume, duration of the NFA and successful NFA (at least one droplet). A significance value below < 0.05 was deemed necessary to indicate a correlation and a minimum of 0.7 was considered a lower bound value to indicate a strong correlation between variables. For logistic regression analyses, the enter method was used and NFA discomfort was dichotomized into ‘no discomfort’ (scores 0–3) and ‘discomfort’ (scores 4–10). A significance value below < 0.05 was deemed necessary for a variable to indicate a relevant effect on NFA discomfort.A total of 375 women of three cohorts were included in the study Table . Median p < 0.001; Table Women in the healthy volunteer and breast cancer cohorts were significantly older than women in the high-risk cohort   with a median time of one year in between visits .p = 0.001), breast MRI  and mammography ; NFA scores were nevertheless significantly higher compared to discomfort of blood collection . These results were confirmed with a Hodges-Lehmann Estimate analysis   and the breast cancer cohort (median = 1), compared to the median NFA score of 3 in the high-risk cohort  Table S. As the ) Table S. A stratp < 0.0001 in the three cohorts) and breast MRI . NFA discomfort was consistently higher than blood collection (p < 0.002) within cohorts. Discomfort regarding breastfeeding and breast physical exam was not significantly different compared to the discomfort rates of NFA within the breast cancer cohort and the high-risk cohort  and would recommend NFA to others . Additionally, we asked whether women would endorse NFA in the context of screening, and most responses were positive , if proven effective  than the discomfort experienced from the conventional screening/diagnostic tools mammography and breast MRI. The discomfort scores presented here are comparable to our previous reports in other cohorts of healthy women  and high.  reportedAs a means of comparison between liquid biopsies, discomfort of blood collection, the most regular applied source of liquid biopsy, was taken along in our analyses. Blood collection is a fast, widely performed and accepted procedure that only requires exposure of the arm. As such, its discomfort scored unsurprisingly the lowest. Still, the advantages of NAF as a valuable information source for biomarkers about alterations in intraductal health, together with information about breast side and intra-patient control, have the potential to surpass the advantages of blood-based biomarkers. Such studies are under way –26.The high (intended) willingness of the women in our cohorts to participate again is consistent with our previous studies , 23, 27.The presented results might be influenced by self-selection bias. That is, by participating in the study, women are already willing to collect NAF and blood. Similarly, women who previously experienced a high discomfort during mammography and/or breast MRI, could be more motivated to participate in our study. Still, our discomfort scores for mammography are in line with the reported means for pain in other studies, which vary between 4 and 7  –39. WhilIn summary, NFA and blood collection are simple, minimally invasive, repeatable methods that are very well accepted and endured by women. The great majority of participating women would undergo NFA again in the context of research and screening. These data indicate that a liquid biopsy biomarker-based (repeated) surveillance testing tool could be well received by women.Additional file 1. Figure S1a. Picture of syringe attached to the plastic tube on one end and to the plastic cup on the other end.Additional file 2. Figure S1b. Picture of a glass capillary used to collect nipple fluid droplets. Additional file 3. File S1. Eligibility criteria per cohort.Additional file 4. Supplementary File 2. Discomfort questionnaire Additional file 5. Supplementary Tables 1-12. (S1) Inclusion reason in the high-risk cohort, (S2) Cohort characteristics in breast cancer, healthy volunteers and high-risk cohorts, (S3) Discomfort of nipple fluid aspiration (NFA) compared to breast physical exam, breastfeeding, mammography, breast MRI and blood collection in the breast cancer cohort, healthy volunteers cohort and high-risk cohort, (S4) Hodges-Lehmann Estimate (HLE) of discomfort scores for nipple fluid aspiration (NFA), mammography, breast MRI, breast physical exam, breastfeeding and blood collection, (S5) Percentage of women of all cohorts who reported a discomfort score of 5 or above for NFA, mammography, breast MRI, breast physical exam, breastfeeding and blood collection, (S6) Correlation tests comparing NFA discomfort with other variables and significance values from the linear regression analyses, (S7) Logistic regression showing that, when corrected for age, NFA discomfort scores are not significantly different between cohorts, (S8a) Nipple fluid aspiration discomfort scores by age in all cohorts, (S8b) Median duration of nipple fluid aspiration by menopausal status in all cohorts, (S9) Association between discomfort NFA and repeated NFA in the high-risk cohort, (S10) Response of women in all cohorts and specifically in the breast cancer, healthy volunteers and high-risk cohorts,(S11) Drop-out reasons in high-risk cohort, (S12) Adverse events in all cohorts and specifically in the breast cancer, healthy volunteers and high-risk cohorts.


Metabolic syndrome (MetS), a group of risk factors that define metabolic dysfunction in adults, is strongly associated with obesity and is an emerging risk factor for cancer. However, the association of MetS and degree of metabolic dysfunction with obesity‐related cancer is unknown.Using National Health and Nutrition Examination Survey data from 1999 to 2018, we identified 528 obesity‐related cancer cases and 18,972 cancer‐free participants. MetS was defined as the presence of or treatment for ≥3 of hyperglycemia, hypertension, hypertriglyceridemia, low HDL–cholesterol, and abdominal obesity. A metabolic syndrome score (MSS) was computed as the total number of abnormal MetS parameters to determine the severity of metabolic dysfunction. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression models, adjusting for sociodemographic and lifestyle factors.About 45.7% of obesity‐related cancer cases were classified as having MetS compared with only 33.0% of cancer‐free participants. Overall, MetS and MSS were not associated with obesity‐related cancer. However, MSS was associated with higher obesity‐related cancer risk among participants under 50 years of age (OR [95% CI] = 1.28 [1.08–1.52]). When evaluating MSS categorically, compared with healthy participants with no abnormal MetS parameters (MSS = 0), participants with one or two abnormal parameters had a statistically significant higher risk of obesity‐related cancer (OR [95% CI] = 1.73 [1.06–2.83]).Metabolic dysfunction is associated with a higher risk of obesity‐related cancer, particularly in young adults under 50 years of age, and among participants with one or two abnormal metabolic parameters. A more accurate indicator of metabolic dysfunction, beyond metabolic syndrome, is needed to better assist in stratifying individuals for obesity‐related cancer risk. Participants with mild metabolic dysfunction i.e., 1‐2 abnormal metabolic syndrome (MetS) parameters, especially participants younger than 50 years, have a higher risk of obesity‐related cancer (ORC) compared to participants with zero abnormal MetS parameters. Traditionally, these individuals would not have been clinically diagnosed with MetS or perceived to be at higher risk for ORC, suggesting that measures beyond the clinical MetS diagnosis need to be considered to stratify individuals with respect to their ORC risk. We also excluded participants with a cancer diagnosis other than obesity‐related cancer , fasting hypoglycemia , and pregnant or lactating women . Additionally, despite being obesity related, we had to exclude all esophageal, gastric, blood, and brain cancers as NHANES lacks the histological and molecular classification needed to determine which ones are obesity related (N = 107 [0.11%]). After all exclusions, the analytical data set included data on 19,500 study participants.All participants in the NHANES database 18 years of age or older that provided a fasting blood sample were eligible to be included in the current analysis. As the MetS definition is based on the presence of three or more abnormal parameters, we excluded participants with three or more missing values for the MetS criteria  criteriaPrevalent MetS was identified using questionnaire information, anthropometric data, and laboratory values. Hyperglycemia was determined by FBG concentration, drug treatment of hyperglycemia, or self‐report of a prior history of diabetes. The presence of hypertension was calculated by an average of at least two SBP or DBP readings, drug treatment for hypertension, or self‐report of a prior history of hypertension. In concordance with previous studies, participants with only one available blood pressure reading were not labeled as having hypertension due to the potential for inaccuracy.The metabolic syndrome score (MSS), calculated as the total number of abnormal MetS components, was computed to determine if the number of abnormal MetS criteria present was associated with obesity‐related cancer risk, beyond the presence of MetS itself. This provides a score rather than a binary measure of metabolic dysfunction, allowing us to evaluate incremental associations of metabolic dysfunction with obesity‐related cancer. The MSS ranged from a minimum possible value of 0  to a maximum of 5 .2.4Participants were classified as having obesity‐related cancer using the NHANES medical condition questionnaires. Obesity‐related cancer sites were determined as defined by the National Cancer Institute (NCI)2.5r2 = 0.90, p < 0.0001), we did not adjust for BMI in the current analysis.Analyses were adjusted for age , sex, race/ethnicity , education level , annual household income , smoking status , alcohol use (yes/no), sedentary behavior , weekly physical activity level , daily calorie intake, and survey year. As WC was statistically significantly correlated with BMI  were changed to missing. Missing covariate values were analyzed as a separate category. In sensitivity analyses, we evaluated the risk of obesity‐related cancer with MetS in a complete case analysis, excluding all participants with missing MetS parameter data. All statistical analyses were carried out using SAS Studio, and significance was determined at α = 0.05.Descriptive statistics and correlations between all MetS components were computed. Odds ratios (ORs) and 95% confidence intervals (95% CIs) for obesity‐related cancer risk and association with the various parameters of metabolic health , the presence of MetS, and severity of MetS were estimated using multivariable logistic regression models adjusting for (1) age and sex and (2) age, sex, race/ethnicity, education level, annual household income, smoking status, alcohol use, daily hours sedentary, weekly physical activity, daily calorie intake, and survey year. To determine the degree to which the associations between MetS, MSS, and obesity‐related cancer were modified by age, sex, race/ethnicity, and BMI, subgroup analyses were conducted using multivariable‐adjusted logistic regression models. Because of the complex survey design of NHANES, all estimates were weighted according to the NHANES analytic guidelines to be representative of the U.S. civilian noninstitutionalized‐resident population.3In the current analyses, we evaluated associations of MetS and other metabolic dysfunction parameters with obesity‐related cancer among NHANES participants from 1999 to 2018. Baseline characteristics with weighted proportions are summarized in Table Table r = 0.84).Mutual correlations between the various metabolic dysfunction parameters are outlined in Table Neither the presence of MetS nor the severity of MetS as indicated by increasing MSS was associated with obesity‐related cancer overall  Table . In subgAdditional subgroup analyses were conducted to evaluate differences by age, sex, race/ethnicity, and BMI Figure . There w2) were older; 59.1% of cancer‐free overweight participants were under 50 years of age compared with 69.2% of normal weight cancer‐free participants. As expected, all metabolic parameter levels were worse for overweight cancer‐free participants compared with normal weight cancer‐free participants. Obesity‐related cancer participants were more likely to be older and female compared with overweight cancer‐free participants, owing to the association of age with cancer development and most obesity‐related cancers being cancers of the female reproductive system. Notably, metabolic parameters were very similar between obesity‐related cancer cases and overweight cancer‐free participants. Metabolic parameters were mostly worse for obesity‐related cancer cases, except, however, for HOMA‐IR and abdominal obesity, adding to the hypothesis that metabolic dysfunction may be an important component of cancer risk.We performed an additional analysis comparing normal weight and overweight cancer‐free participants to participants with obesity‐related cancer Table . In geneBecause many obesity‐related cancers are reproductive cancers, sensitivity analyses were performed by restricting our data set to females and additionally adjusting for menopausal status and HRT use. We also performed a sensitivity analysis for overall obesity‐related cancer risk and breast cancer risk with MetS and MSS, restricting to postmenopausal breast cancer cases only . No significant differences were observed in these analyses compared with the entire population Tables  and S6. 4We examined the association between metabolic dysfunction and obesity‐related cancer in a nationally representative cohort comprised of 528 obesity‐related cancer cases and 18,972 cancer‐free participants. We observed a greater degree of metabolic dysfunction among those that reported obesity‐related cancer compared with cancer‐free participants. For example, almost half of obesity‐related cancer cases had MetS versus just over a third of cancer‐free individuals. Moreover, 93% of obesity‐related cancer cases had at least one abnormal MetS parameter compared with 79% of cancer‐free participants. Our results suggest that metabolic dysfunction even in a single MetS parameter, in contrast to the binary definition of MetS, was positively associated with the presence of obesity‐related cancer.Proposed mechanisms to explain the relationship between MetS and obesity‐related cancer include alterations in hormone signaling, oxidative stress, and chronic low‐grade inflammation.Each of the MetS parameters is associated with cancer development.Radišauskas et al. reported that although there are multiple studies linking total cholesterol levels to increased cancer risk,Dyslipidemia is also an independent risk factor for obesity‐related cancer. Although the MetS parameters may have independent associations with obesity‐related cancer, it remains unclear whether these effects are additive and whether increasing severity of metabolic dysfunction increases cancer risk in a dose–response manner. Our study did not observe that the number of abnormal MetS parameters, calculated as MSS, was monotonically associated with obesity‐related cancer. However, compared with healthy participants , having one or two abnormal MetS criteria was statistically significantly associated with obesity‐related cancer. Traditionally, these individuals (~46%) would not have been clinically diagnosed with MetS. This suggests that mild metabolic dysfunction may increase cancer risk, and measures beyond the clinical MetS diagnosis need to be considered to stratify individuals with respect to their obesity‐related cancer risk.Having MetS was not associated with obesity‐related cancer in this study. However, with evidence that MetS increases cancer‐related mortality,We observed that metabolic dysfunction was associated with obesity‐related cancer among younger adults (<50 years). Recent reports show an increasing incidence of obesity‐related cancer in adolescents and young adults, specifically for colorectal, breast, kidney, uterine, pancreatic, and thyroid cancers.Our study has some limitations. Cancers were self‐reported and, therefore, there is a possibility of misclassification and recall bias. There may also be misclassification of the exposure resulting from imperfect biomarker measurement. However, we anticipate any such misclassification to be non‐differential and, therefore, will only bias the ORs towards the null. Another major limitation is the cross‐sectional nature of the data, thus precluding us from making inferences on temporality. Because of this, we are unable to preclude the temporality of obesity and cancer diagnoses in NHANES participants. Moreover, NHANES does not include data on cancer treatment. It is possible that cancer patients in this population experienced weight reduction after a cancer diagnosis, which could result in the absence of MetS and reverse causality in this study. Multiple mechanisms may be involved in such a weight loss, including reduced food intake, response to cancer treatment, and hypercatabolism resulting from inflammation, tumor metabolism, or insulin resistance.In conclusion, metabolic dysfunction is associated with higher obesity‐related cancer risk, particularly in young adults under 50 years of age and in participants with one or two abnormal metabolic parameters. Previous studies that have only considered those with MetS  as metabolically unhealthy may, in fact, be excluding many metabolically unhealthy individuals at a higher risk for obesity‐related cancer. Further research on metabolic dysfunction could provide insight into potential mechanisms between metabolic parameters and obesity‐related cancer and allow for better risk stratification and cancer prevention strategies in higher‐risk subgroups.Conceptualization: M.W., M.P., and S.H.; methodology: M.W., M.P., and S.H; formal analysis: M.W., M.P., S.H., and B.H.; writing—original draft preparation: M.W. and S.H.; writing—review and editing: M.W., P.K., J.D., S.S., B.H., M.L., M.G., M.P., and S.H; visualization: M.W., M.P., and S.H.; supervision: M.P. and S.H.S.A. Summers is a co‐founder and consultant with Centaurus Therapeutics. All other co‐authors do not declare any conflict of interest.NHANES is a publicly available data set approved by the National Center for Health Statistics institutional review board, and all participants provided written informed consent.Figure S1Click here for additional data file.Table S1‐S7Click here for additional data file.