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Abstract
Menopause nomenclature varies in the scholarly literature making synthesis and interpretation of research findings difficult. Therefore, the present study aimed to review and discuss critical developments in menopause nomenclature; determine the level of heterogeneity amongst menopause definitions and compare them with the Stages of Reproductive Aging Workshop criteria. Definitions/criteria used to characterise premenopausal and postmenopausal status were extracted from 210 studies and 128 of these studies were included in the final analyses. The main findings were that 39.84% of included studies were consistent with STRAW classification of premenopause, whereas 70.31% were consistent with STRAW classification of postmenopause. Surprisingly, major inconsistencies relating to premenopause definition were due to a total lack of reporting of any definitions/criteria for premenopause (39.84% of studies). In contrast, only 20.31% did not report definitions/criteria for postmenopause. The present findings indicate that there is a significant amount of heterogeneity associated with the definition of premenopause, compared with postmenopause. We propose three key suggestions/recommendations, which can be distilled from these findings. Firstly, premenopause should be transparently operationalised and reported. Secondly, as a minimum requirement, regular menstruation should be defined as the number of menstrual cycles in a period of at least 3 months. Finally, the utility of introducing normative age-ranges as supplementary criterion for defining stages of reproductive ageing should be considered. The use of consistent terminology in research will enhance our capacity to compare results from different studies and more effectively investigate issues related to women's health and ageing.
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Affiliation(s)
- Ananthan Ambikairajah
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, 2601, Australia.
- Discipline of Psychology, Faculty of Health, University of Canberra, Building 12, 11 Kirinari Street, Canberra, ACT, 2617, Australia.
| | - Erin Walsh
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, 2601, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Canberra, ACT, 2601, Australia
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Association between skeletal muscle mass and mammographic breast density. Sci Rep 2021; 11:16785. [PMID: 34408263 PMCID: PMC8373895 DOI: 10.1038/s41598-021-96390-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 08/09/2021] [Indexed: 11/09/2022] Open
Abstract
Mammographic density (MD) of the breast and body mass index (BMI) are inversely associated with each other, but have inconsistent associations with respect to the risk of breast cancer. Skeletal muscle mass index (SMI) has been considered to reflect a relatively accurate fat and muscle percentage in the body. So, we evaluated the relation between SMI and MD. A cross-sectional study was performed in 143,456 women who underwent comprehensive examinations from 2012 to 2016. BMI was adjusted to analyze whether SMI is an independent factor predicting dense breast. After adjustment for confounding factors including BMI, the odds ratios for MD for the dense breasts was between the highest and lowest quartiles of SMI at 2.65 for premenopausal women and at 2.39 for postmenopausal women. SMI was a significant predictor for MD, which could be due to the similar growth mechanism of the skeletal muscle and breast parenchymal tissue. Further studies are needed to understand the causal link between muscularity, MD and breast cancer risk.
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The Relationship between Body Mass Index and Mammographic Density during a Premenopausal Weight Loss Intervention Study. Cancers (Basel) 2021; 13:cancers13133245. [PMID: 34209579 PMCID: PMC8269424 DOI: 10.3390/cancers13133245] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 06/17/2021] [Accepted: 06/18/2021] [Indexed: 11/17/2022] Open
Abstract
We evaluated the association between short-term change in body mass index (BMI) and breast density during a 1 year weight-loss intervention (Manchester, UK). We included 65 premenopausal women (35-45 years, ≥7 kg adult weight gain, family history of breast cancer). BMI and breast density (semi-automated area-based, automated volume-based) were measured at baseline, 1 year, and 2 years after study entry (1 year post intervention). Cross-sectional (between-women) and short-term change (within-women) associations between BMI and breast density were measured using repeated-measures correlation coefficients and multivariable linear mixed models. BMI was positively correlated with dense volume between-women (r = 0.41, 95%CI: 0.17, 0.61), but less so within-women (r = 0.08, 95%CI: -0.16, 0.28). There was little association with dense area (between-women r = -0.12, 95%CI: -0.38, 0.16; within-women r = 0.01, 95%CI: -0.24, 0.25). BMI and breast fat were positively correlated (volume: between r = 0.77, 95%CI: 0.69, 0.84, within r = 0.58, 95%CI: 0.36, 0.75; area: between r = 0.74, 95%CI: 0.63, 0.82, within r = 0.45, 95%CI: 0.23, 0.63). Multivariable models reported similar associations. Exploratory analysis suggested associations between BMI gain from 20 years and density measures (standard deviation change per +5 kg/m2 BMI: dense area: +0.61 (95%CI: 0.12, 1.09); fat volume: -0.31 (95%CI: -0.62, 0.00)). Short-term BMI change is likely to be positively associated with breast fat, but we found little association with dense tissue, although power was limited by small sample size.
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Ma Z, Li X, Chen Y, Tang X, Gao Y, Wang H, Liu R. Comprehensive evaluation of the combined extracts of Epimedii Folium and Ligustri Lucidi Fructus for PMOP in ovariectomized rats based on MLP-ANN methods. JOURNAL OF ETHNOPHARMACOLOGY 2021; 268:113563. [PMID: 33176184 DOI: 10.1016/j.jep.2020.113563] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 10/25/2020] [Accepted: 11/02/2020] [Indexed: 06/11/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Kidney deficiency is the main pathogenesis of osteoporosis based on the theory of "kidney governing bones" in traditional Chinese medicine (TCM). Osteoporosis is a systemic disease; kidney deficiency influences the growth, aging and reproduction of human body, reflecting in endocrine, nerve, immunity, metabolism and other functions. Multi-target drugs composed of natural non-toxic products from kidney-reinforcing herbs, are being investigated for the treatment of osteoporosis. Therefore, it is necessary and imperative to develop an objective and comprehensive method to evaluate and compare the effects of herbs with listed drugs. AIM OF THE STUDY This study was designed to evaluate and compare the therapeutic effects and the underlying molecular mechanism of the combined extracts of Epimedii Folium and Ligustri Lucidi Fructus (EL) with Raloxifene hydrochloride (RH) in ovariectomy (OVX)-induced postmenopausal osteoporosis (PMOP) rats based on the multi-layer perception (MLP)-artificial neural network (ANN) model. MATERIALS AND METHODS Female SD rats were subjected to either sham surgery (n = 8) or bilateral OVX (n = 48). One week after recovering from surgery, the OVX-induced rats were randomly divided into three groups: OVX model group (n = 32, every 8 rats were killed at the end of the 5th, 9th, 11th or 13th week after OVX), EL group (treated with EL 0.35 g/kg, n = 8), and RH group (treated with RH 6.25 mg/kg, n = 8). The rats in the treatment groups were administrated once a day for 12 weeks, then sacrificed. We observed bone mass and quality, bone remodeling, the function of estrogen and TGF-β1/Smads pathway in all rats. RESULTS Both EL and RH could increase bone mineral density, enhance bone strength, relieve bone micro-structure degeneration, re-balance bone remodeling, regulate estrogen dysfunction, and up-regulate TGF-β1 expression. The evaluation of the MLP-ANN model showed that EL and RH had markedly anti-PMOP effects, and there was no significant difference in the comprehensive evaluation of anti-osteoporosis between the two drugs. However, RH had better effects on bone mass and quality and TGF-β1/Smads pathway than EL; EL had better effects on estrogen function than RH. CONCLUSION Combined extracts of Epimedii Folium and Ligustri Lucidi Fructus (EL) exhibited bone-protective effects on PMOP. The MLP-ANN method evaluated the efficacy of drugs more comprehensively, which provided a new direction for the evaluation and comparison of drugs.
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Affiliation(s)
- Zitong Ma
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China
| | - Xiaoxi Li
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China
| | - Yuheng Chen
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China
| | - Xiufeng Tang
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China
| | - Yingying Gao
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China
| | - Han Wang
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China
| | - Renhui Liu
- School of Traditional Chinese Medicine, Capital Medical University and Beijing Key Lab of TCM Collateral Disease Theory Research, No.10 Xitoutiao, Youanmenwai, Fengtai District, Beijing, 100069, China.
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Kwan JYY, Famiyeh P, Su J, Xu W, Kwan BYM, Jones JM, Chang E, Yip KW, Liu FF. Development and Validation of a Risk Model for Breast Cancer-Related Lymphedema. JAMA Netw Open 2020; 3:e2024373. [PMID: 33175175 PMCID: PMC7658732 DOI: 10.1001/jamanetworkopen.2020.24373] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
IMPORTANCE Approximately 1 in 5 patients with breast cancer who undergo axillary lymph node dissection will develop lymphedema. To appropriately triage and monitor these patients for timely diagnosis and treatment, robust risk models are required. OBJECTIVE To evaluate the prognostic value of mammographic breast density in estimating lymphedema severity. DESIGN, SETTING, AND PARTICIPANTS This prognostic study collected data from July 16, 2018, to March 3, 2020, from the electronic health records of patients of the Cancer Rehabilitation and Survivorship Program at the Princess Margaret Cancer Centre in Toronto, Ontario, Canada. Participants included women who had completed curative treatment for a first diagnosis of breast cancer and who were referred to the program. Also included were a sample of patients in the general breast oncology population who were receiving follow-up care at the center during the same period but who were not referred to the program. All patients attended follow-up appointments at the Princess Margaret Cancer Centre from January 1, 2016, to May 1, 2018. The cohort was randomly split 2:1 to group patients into a training cohort and a validation cohort. EXPOSURES Participant demographic and clinical characteristics included age, sex, body mass index (BMI), medical history, cancer characteristics, and cancer treatment. MAIN OUTCOMES AND MEASURES Spearman correlation coefficient between measured and predicted volume of lymphedema was calculated. Area under the curve (AUC) values were generated for predicting the occurrence of at least mild lymphedema (volume, >200 mL) and severe lymphedema (volume, >500 mL) at the time of initial lymphedema diagnosis. RESULTS A total of 373 female patients (median [interquartile range] age, 52.3 [45.9-60.1] years) were eligible for this analysis. Multivariate linear regression identified 3 patient factors (age, BMI, and mammographic breast density), 1 cancer factor (number of pathological lymph nodes), and 1 treatment factor (axillary lymph node dissection) as independent prognostic variables. In validation testing, Spearman correlation revealed a statistically significant moderate correlation (coefficient, 0.42; 95% CI, 0.26-0.56; P < .001) between measured volume and predicted volume of lymphedema. The AUC values were 0.72 (95% CI, 0.60-0.83) for predicting the occurrence of mild lymphedema and 0.83 (95% CI, 0.74-0.93) for severe lymphedema. CONCLUSIONS AND RELEVANCE This prognostic study found that patients with low breast density appeared to be at a higher risk of developing severe lymphedema. The finding suggests that by combining breast density with established risk factors a multivariate linear regression model could be used to predict the development of lymphedema and provide volumetric estimates of lymphedema severity in patients with breast cancer.
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Affiliation(s)
- Jennifer Yin Yee Kwan
- Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Research Institute, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Petra Famiyeh
- Research Institute, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Jie Su
- Biostatistics Division, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Wei Xu
- Biostatistics Division, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Benjamin Yin Ming Kwan
- Department of Diagnostic Radiology, School of Medicine, Queen’s University, Kingston, Ontario, Canada
| | - Jennifer M. Jones
- Cancer Rehabilitation and Survivorship Program, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Eugene Chang
- Cancer Rehabilitation and Survivorship Program, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Kenneth W. Yip
- Research Institute, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Fei-Fei Liu
- Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Research Institute, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Radiation Medicine Program, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
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Lope V, Del Pozo MDP, Criado-Navarro I, Pérez-Gómez B, Pastor-Barriuso R, Ruiz E, Castelló A, Lucas P, Sierra Á, Salas-Trejo D, Llobet R, Martínez I, Romieu I, Chajès V, Priego-Capote F, Pollán M. Serum Phospholipid Fatty Acids and Mammographic Density in Premenopausal Women. J Nutr 2020; 150:2419-2428. [PMID: 32584993 DOI: 10.1093/jn/nxaa168] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/26/2020] [Accepted: 05/19/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The role of fatty acids (FAs) on mammographic density (MD) is unclear, and available studies are based on self-reported dietary intake. OBJECTIVES This study assessed the association between specific serum phospholipid fatty acids (PLFAs) and MD in premenopausal women. METHODS The cross-sectional study DDM-Madrid recruited 1392 Spanish premenopausal women, aged 39-50 y, who attended a screening in a breast radiodiagnosis unit of Madrid City Council. Women completed lifestyle questionnaires and FFQs. Percentage MD was estimated using a validated computer tool (DM-Scan), and serum PLFA percentages were measured by GC-MS. Multivariable linear regression models were used to quantify the association of FA tertiles with MD. Models were adjusted for age, education, BMI, waist circumference, parity, oral contraceptive use, previous breast biopsies, and energy intake, and they were corrected for multiple testing. RESULTS Women in the third tertile of SFAs showed significantly higher MD compared with those in the first tertile (βT3vsT1 = 7.53; 95% CI: 5.44, 9.61). Elevated relative concentrations of palmitoleic (βT3vsT1 = 3.12; 95% CI: 0.99, 5.25) and gondoic (βT3vsT1 = 2.67; 95% CI: 0.57, 4.77) MUFAs, as well as high relative concentrations of palmitelaidic (βT3vsT1 = 5.22; 95% CI: 3.15, 7.29) and elaidic (βT3vsT1 = 2.69; 95% CI: 0.59, 4.79) trans FAs, were also associated with higher MD. On the contrary, women with elevated relative concentrations of n-6 (ω-6) linoleic (βT3vsT1 = -5.49; 95% CI; -7.62, -3.35) and arachidonic (βT3vsT1 = -4.68; 95% CI: -6.79, -2.58) PUFAs showed lower MD. Regarding desaturation indices, an elevated palmitoleic to palmitic ratio and a low ratio of oleic to steric and arachidonic to dihomo-γ-linolenic acids were associated with higher MD. CONCLUSIONS Spanish premenopausal women with high relative concentrations of most SFAs and some MUFAs and trans FAs showed an increased MD, whereas those with high relative concentrations of some n-6 PUFAs presented lower density. These results, which should be confirmed in further studies, underscore the importance of analyzing serum FAs individually.
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Affiliation(s)
- Virginia Lope
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - María Del Pilar Del Pozo
- Department of Preventive Medicine, Public Health, and Microbiology, Autonomous University of Madrid, Madrid, Spain
| | - Inmaculada Criado-Navarro
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Cordoba, Cordoba, Spain
- Maimónides Institute of Biomedical Research, Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Roberto Pastor-Barriuso
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Emma Ruiz
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Adela Castelló
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
- Faculty of Medicine, University of Alcalá, Alcalá de Henares, Madrid, Spain
| | - Pilar Lucas
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Ángeles Sierra
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Dolores Salas-Trejo
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
- Valencian Breast Cancer Screening Program, General Directorate of Public Health, Valencia, Spain
- Center for Public Health Research CSISP, FISABIO, Valencia, Spain
| | - Rafael Llobet
- Institute of Computer Technology, Polytechnic University of Valencia, Valencia, Spain
| | - Inmaculada Martínez
- Valencian Breast Cancer Screening Program, General Directorate of Public Health, Valencia, Spain
- Center for Public Health Research CSISP, FISABIO, Valencia, Spain
| | - Isabelle Romieu
- Center for Research on Population Health, National Institute of Public Health, Cuernavaca, Mexico
- Huber Department of Global Health, Emory University, Atlanta, GA, USA
| | - Véronique Chajès
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Feliciano Priego-Capote
- Department of Analytical Chemistry, Annex Marie Curie Building, Campus of Rabanales, University of Cordoba, Cordoba, Spain
- Maimónides Institute of Biomedical Research, Reina Sofia University Hospital, University of Cordoba, Cordoba, Spain
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, Department of Epidemiology of Chronic Diseases, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
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Han Y, Berkey CS, Herman CR, Appleton CM, Alimujiang A, Colditz GA, Toriola AT. Adiposity Change Over the Life Course and Mammographic Breast Density in Postmenopausal Women. Cancer Prev Res (Phila) 2020; 13:475-482. [PMID: 32102947 PMCID: PMC8210631 DOI: 10.1158/1940-6207.capr-19-0549] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Revised: 01/21/2020] [Accepted: 02/19/2020] [Indexed: 11/16/2022]
Abstract
Mammographic breast density is a strong risk factor for breast cancer. We comprehensively investigated the associations of body mass index (BMI) change from ages 10, 18, and 30 to age at mammogram with mammographic breast density in postmenopausal women. We used multivariable linear regression models, adjusted for confounders, to investigate the associations of BMI change with volumetric percent density, dense volume, and nondense volume, assessed using Volpara in 367 women. At the time of mammogram, the mean age was 57.9 years. Compared with women who had a BMI gain of 0.1-5 kg/m2 from age 10, women who had a BMI gain of 5.1-10 kg/m2 had a 24.4% decrease [95% confidence interval (CI), 6.0%-39.2%] in volumetric percent density; women who had a BMI gain of 10.1-15 kg/m2 had a 46.1% decrease (95% CI, 33.0%-56.7%) in volumetric percent density; and women who had a BMI gain of >15 kg/m2 had a 56.5% decrease (95% CI, 46.0%-65.0%) in volumetric percent density. Similar, but slightly attenuated associations were observed for BMI gain from ages 18 and 30 to age at mammogram and volumetric percent density. BMI gain over the life course was positively associated with nondense volume, but not dense volume. We observed strong associations between BMI change over the life course and mammographic breast density. The inverse associations between early-life adiposity change and volumetric percent density suggest that childhood adiposity may confer long-term protection against postmenopausal breast cancer via its effect of mammographic breast density.
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Affiliation(s)
- Yunan Han
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri
- Department of Breast Surgery, First Hospital of China Medical University, Shenyang, Liaoning Province, China
| | - Catherine S Berkey
- Channing Division of Network Medicine, Department of Medicine, Brigham & Women's Hospital and Harvard Medical School, Boston, Massachusetts
| | - Cheryl R Herman
- Alvin J. Siteman Cancer Center, Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri
| | | | - Aliya Alimujiang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Graham A Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri
- Alvin J. Siteman Cancer Center, Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri
| | - Adetunji T Toriola
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, Missouri.
- Alvin J. Siteman Cancer Center, Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri
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Ambikairajah A, Walsh E, Tabatabaei-Jafari H, Cherbuin N. Fat mass changes during menopause: a metaanalysis. Am J Obstet Gynecol 2019; 221:393-409.e50. [PMID: 31034807 DOI: 10.1016/j.ajog.2019.04.023] [Citation(s) in RCA: 106] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/15/2019] [Accepted: 04/19/2019] [Indexed: 02/08/2023]
Abstract
OBJECTIVE Data: Fat mass has been shown to increase in aging women; however, the extent to which menopausal status mediates these changes remains unclear. The purpose of this review was to determine (1) how fat mass differs in quantity and distribution between premenopausal and postmenopausal women, (2) whether and how age and/or menopausal status moderates any observed differences, and (3) which type of fat mass measure is best suited to the detection of differences in fat mass between groups. STUDY This review with metaanalyses is reported according to Metaanalysis of Observational Studies in Epidemiology guidelines. STUDY APPRAISAL AND SYNTHESIS METHODS Studies (published up to May 2018) were identified via PubMed to provide fat mass measures in premenopausal and postmenopausal women. We included 201 cross-sectional studies in the metaanalysis, which provided a combined sample size of 1,049,919 individuals and consisted of 478,734 premenopausal women and 571,185 postmenopausal women. Eleven longitudinal studies were included in the metaanalyses, which provided a combined sample size of 2472 women who were premenopausal at baseline and postmenopausal at follow up. RESULTS The main findings of this review were that fat mass significantly increased between premenopausal and postmenopausal women across most measures, which included body mass index (1.14 kg/m2; 95% confidence interval, 0.95-1.32 kg/m2), bodyweight (1 kg; 95% confidence interval, 0.44-1.57 kg), body fat percentage (2.88%; 95% confidence interval, 2.13-3.63%), waist circumference (4.63 cm; 95% confidence interval, 3.90-5.35 cm), hip circumference (2.01 cm; 95% confidence interval, 1.36-2.65 cm), waist-hip ratio (0.04; 95% confidence interval, 0.03-0.05), visceral fat (26.90 cm2; 95% confidence interval, 13.12-40.68), and trunk fat percentage (5.49%; 95% confidence interval, 3.91-7.06 cm2). The exception was total leg fat percentage, which significantly decreased (-3.19%; 95% confidence interval, -5.98 to -0.41%). No interactive effects were observed between menopausal status and age across all fat mass measures. CONCLUSION The change in fat mass quantity between premenopausal and postmenopausal women was attributable predominantly to increasing age; menopause had no significant additional influence. However, the decrease in total leg fat percentage and increase in measures of central fat are indicative of a possible change in fat mass distribution after menopause. These changes are likely to, at least in part, be due to hormonal shifts that occur during midlife when women have a higher androgen (ie, testosterone) to estradiol ratio after menopause, which has been linked to enhanced central adiposity deposition. Evidently, these findings suggest attention should be paid to the accumulation of central fat after menopause, whereas increases in total fat mass should be monitored consistently across the lifespan.
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Mammographic density: intersection of advocacy, science, and clinical practice. CURRENT BREAST CANCER REPORTS 2019; 11:100-110. [PMID: 33312342 DOI: 10.1007/s12609-019-00316-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Purpose Here we aim to review the association between mammographic density, collagen structure and breast cancer risk. Findings While mammographic density is a strong predictor of breast cancer risk in populations, studies by Boyd show that mammographic density does not predict breast cancer risk in individuals. Mammographic density is affected by age, parity, menopausal status, race/ethnicity, and body mass index (BMI).New studies normalize mammographic density to BMI may provide a more accurate way to compare mammographic density in women of diverse race and ethnicity. Preclinical and tissue-based studies have investigated the role collagen composition and structure in predicting breast cancer risk. There is emerging evidence that collagen structure may activate signaling pathways associated with aggressive breast cancer biology. Summary Measurement of film mammographic density does not adequately capture the complex signaling that occurs in women with at-risk collagen. New ways to measure at-risk collagen potentially can provide a more accurate view of risk.
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Toribio MJ, Lope V, Castelló A, Salas D, Vidal C, Ascunce N, Santamariña C, Moreo P, Pedraz-Pingarrón C, Sánchez-Contador C, Aragonés N, Pérez-Gómez B, Pollán M. Prevalence of healthy lifestyles against cancer in Spanish women. Sci Rep 2019; 9:10638. [PMID: 31337864 PMCID: PMC6650391 DOI: 10.1038/s41598-019-47180-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 07/11/2019] [Indexed: 01/30/2023] Open
Abstract
Modifying behavior towards healthier lifestyles could prevent a significant number of malignant tumors. We evaluated the prevalence of healthy habits against cancer in Spanish women free of this disease, taking as a reference the recommendations for cancer prevention included in the European Code Against Cancer (ECAC), and we explored the characteristics associated with it. Our population comprised 3,584 women recruited in a population-based cross-sectional study carried out in 7 breast cancer screening programs. Information was directly surveyed and used to calculate a score based on ECAC recommendations referred to bodyweight, physical activity, diet, breastfeeding, tobacco, alcohol and hormone replacement therapy use. The degree of adherence was estimated with a score that evaluated null (0 points), partial (0.5 points) and full adherence (1 point) of each specific recommendation. Associations were explored using binary and ordinal logistic regression models. The median score was 5.7 out of 9 points. Recommendations with lower adherence were those related to intake of red/processed meat and foods high in salt (23% of total adherence), physical activity (24%) and body weight (29%), and recommendations with greater adherence where those related to hormone replacement therapy use (91%), vegetable intake (84%), alcohol (83%) and tobacco (61%). Overall adherence was better among older women, parous women, and in those living in rural areas, and worse among women with higher caloric intake. These recommendations should be evaluated periodically. Screening programs can be an appropriate place to disseminate this information.
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Affiliation(s)
- María José Toribio
- Servicio de Medicina Preventiva y Gestión de Calidad, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Virginia Lope
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain. .,Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain.
| | - Adela Castelló
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Dolores Salas
- General Directorate Public Health, and FISABIO, Valencia, Spain
| | - Carmen Vidal
- Cancer Prevention and Control Unit, Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Nieves Ascunce
- Navarra Breast cancer Screening Program, Public Health Institute, Pamplona, Spain
| | - Carmen Santamariña
- Galicia Breast Cancer Screening Program, Regional Authority of Health, Galicia Regional Government, Corunna, Spain
| | - Pilar Moreo
- Aragon Breast Cancer Screening Program, Health Service of Aragon, Zaragoza, Spain
| | - Carmen Pedraz-Pingarrón
- Castile-Leon Breast Cancer Screening Program, General Directorate Public Health SACYL, Burgos, Spain
| | - Carmen Sánchez-Contador
- Balearic Islands Breast Cancer Screening Program, Health Promotion for Women and Childhood, General Directorate Public Health and Participation, Regional Authority of Health and Consumer Affairs, Balearic Islands, Palma, Spain
| | - Nuria Aragonés
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain.,Epidemiology Section, Public Health Division, Department of Health of Madrid, Madrid, Spain
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Madrid, Spain
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11
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Ligibel JA, Basen-Engquist K, Bea JW. Weight Management and Physical Activity for Breast Cancer Prevention and Control. Am Soc Clin Oncol Educ Book 2019; 39:e22-e33. [PMID: 31099634 DOI: 10.1200/edbk_237423] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Observational evidence has consistently linked excess adiposity and inactivity to increased breast cancer risk and to poor outcomes in individuals diagnosed with early-stage, potentially curable breast cancer. There is less information from clinical trials testing the effect of weight management or physical activity interventions on breast cancer risk or outcomes, but a number of ongoing trials will test the impact of weight loss and other lifestyle changes after cancer diagnosis on the risk of breast cancer recurrence. Lifestyle changes have additional benefits beyond their potential to decrease primary or secondary breast cancer risk, including improvements in metabolic parameters, reduction in the risk of comorbidities such as diabetes and heart disease, improvement of physical functioning, and mitigation of side effects of cancer therapy. Despite these myriad benefits, implementation of lifestyle interventions in at-risk and survivor populations has been limited to date. This article reviews the evidence linking lifestyle factors to breast cancer risk and outcomes, discusses completed and ongoing randomized trials testing the impact of lifestyle change in primary and secondary breast cancer prevention, and reviews efforts to implement and disseminate lifestyle interventions in at-risk and breast cancer survivor populations.
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12
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Del Pozo MDP, Castelló A, Vidal C, Salas-Trejo D, Sánchez-Contador C, Pedraz-Pingarrón C, Moreo P, Santamariña C, Ederra M, Llobet R, Vioque J, Pérez-Gómez B, Pollán M, Lope V. Overeating, caloric restriction and mammographic density in Spanish women. DDM-Spain study. Maturitas 2018; 117:57-63. [PMID: 30314562 DOI: 10.1016/j.maturitas.2018.09.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 09/07/2018] [Accepted: 09/28/2018] [Indexed: 12/26/2022]
Abstract
OBJECTIVES Mammographic density (MD) is a strong risk factor for breast cancer. The present study evaluates the association between relative caloric intake and MD in Spanish women. STUDY DESIGN We conducted a cross-sectional study in which 3517 women were recruited from seven breast cancer screening centers. MD was measured by an experienced radiologist using craniocaudal mammography and Boyd's semi-quantitative scale. Information was collected through an epidemiological survey. Predicted calories were calculated using linear regression models, including the basal metabolic rate and physical activity as explanatory variables. Overeating and caloric restriction were defined taking into account the 99% confidence interval of the predicted value. Odds ratios (OR) and 95% confidence intervals (95%CI) were estimated using center-specific mixed ordinal logistic regression models, adjusted for age, menopausal status, body mass index, parity, tobacco use, family history of breast cancer, previous biopsies, age at menarche and adherence to a Western diet. MAIN OUTCOME MEASURE Mammographic density. RESULTS Those women with an excessive caloric intake (>40% above predicted) presented higher MD (OR = 1.41, 95%CI = 0.97-2.03; p = 0.070). For every 20% increase in relative caloric consumption the probability of having higher MD increased by 5% (OR = 1.05, 95%CI = 0.98-1.14; p = 0.178), not observing differences between the categories of explanatory variables. Caloric restriction was not associated with MD in our study. CONCLUSIONS This is the first study exploring the association between MD and the effect of caloric deficit or excessive caloric consumption according to the energy requirements of each woman. Although caloric restriction does not seem to affect breast density, a caloric intake above predicted levels seems to increase this phenotype.
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Affiliation(s)
- María Del Pilar Del Pozo
- Department of Preventive Medicine, Public Health and Microbiology, Universidad Autónoma de Madrid (UAM), C/ Arzobispo Morcillo 4, 28029, Madrid, Spain
| | - Adela Castelló
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Faculty of Medicine, University of Alcalá, Campus Científico-Tecnológico, Crta. de Madrid-Barcelona, Km. 33,600, 28871, Alcalá de Henares, Madrid, Spain
| | - Carmen Vidal
- Cancer Prevention and Control Program, Catalan Institute of Oncology-IDIBELL, Av. Gran Vía s/n km 2,7, 08907, L'Hospitalet de Llobregat, Barcelona, Spain
| | - Dolores Salas-Trejo
- General Directorate Public Health, and FISABIO, Av. de Catalunya 21, 46020, Valencia, Spain
| | - Carmen Sánchez-Contador
- Balearic Islands Breast Cancer Screening Program, Health Promotion for Women and Childhood, General Directorate Public Health and Participation, Regional Authority of Health and Consumer Affairs, C/Jesús, 40 Pabellón II, 07010, Palma, Balearic Islands, Spain
| | - Carmen Pedraz-Pingarrón
- Castile-Leon Breast Cancer Screening Program, General Directorate Public Health SACYL, Av. Sierra de Atapuerca s/n, 09002, Burgos, Spain
| | - Pilar Moreo
- Aragon Breast Cancer Screening Program, Health Service of Aragon, Av. Cesar Augusto 11, 50004, Zaragoza, Spain
| | - Carmen Santamariña
- Galicia Breast Cancer Screening Program, Regional Authority of Health, Galicia Regional Government, C/ Duran Loriga 3, 15003, Corunna, Spain
| | - María Ederra
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Early Detection Section, Public and Labor Health Institute of Navarra, C/ Leyre, 15, 31003, Pamplona, Spain; Healthcare Research Institute of Navarre (IdiSNA), C/ de Irunlarrea 3, 31008, Pamplona, Spain
| | - Rafael Llobet
- Institute of Computer Technology, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain
| | - Jesús Vioque
- Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Nutritional Epidemiology Unit, University Miguel Hernandez, ISABIAL-FISABIO, Ctra. Nacional 332 s/n, 03550, Sant Joan D'alacant, Alicante, Spain
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Av. Monforte de Lemos 5, 28029, Madrid, Spain
| | - Virginia Lope
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Av. Monforte de Lemos 5, 28029, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health, CIBERESP, Av. Monforte de Lemos 5, 28029, Madrid, Spain.
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Abstract
OBJECTIVE The use of some forms of hormone therapy (HT) is associated with an increase in mammographic density-a major risk factor for breast cancer. The role of isoflavones, however, is unclear. Here, we quantify the prevalence of HT and isoflavone use among postmenopausal Spanish women, determine associated risk factors, and explore the relationship between these therapies and mammographic density. METHODS This cross-sectional study included 2,754 postmenopausal women who underwent breast cancer screening in seven geographical areas. Mammographic density was evaluated using Boyd's semiquantitative scale. Multinomial logistic regression models were adjusted to assess risk factors associated with both therapies. Ordinal regression models were fitted to study the association between HT and isoflavone consumption with mammographic density. RESULTS The prevalence of ever-use of HT was 12%, whereas that of the current use was 2.3%. Isoflavone lifetime prevalence was 3.7%, and current use was 1.7%. The most common HT types were tibolone and estrogens. Surgical menopause, oral contraceptive use, educational level, population density, and years since menopause were positively associated with HT, whereas body mass index and parity were inversely associated. Mammographic density was not associated with current or past HT use. However, women who reported having consumed isoflavones in the past and those who started their use after menopause had a higher mammographic density when compared with never-users (odds ratio 1.98, 95% CI 1.21-3.25, P = 0.007; and odds ratio 1.60, 95% CI 1.01-2.53, P = 0.045 respectively). CONCLUSIONS Our results show a low prevalence of HT and isoflavone use in postmenopausal Spanish women. In this population, HT use was not associated with mammographic density, whereas some categories of isoflavone users had higher density.
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14
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Soguel L, Durocher F, Tchernof A, Diorio C. Adiposity, breast density, and breast cancer risk: epidemiological and biological considerations. Eur J Cancer Prev 2017; 26:511-520. [PMID: 27571214 PMCID: PMC5627530 DOI: 10.1097/cej.0000000000000310] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2016] [Revised: 01/29/2016] [Indexed: 12/16/2022]
Abstract
Excess total body fat and abdominal adipose tissue are recognized risk factors for metabolic diseases but also for some types of cancers, including breast cancer. Several biological mechanisms in connection with local and systemic effects of adiposity are believed to be implicated in breast cancer development, and may involve breast fat. Breast adipose tissue can be studied through mammography by looking at breast density features such as the nondense area mainly composed of fat, or the percent breast density, which is the proportion of fibroglandular tissue in relation to fat. The relation between adiposity, breast density features, and breast cancer is complex. Studies suggest a paradoxical association as adiposity and absolute nondense area correlate positively with each other, but in contrast to adiposity, absolute nondense area seems to be associated negatively with breast cancer risk. As breast density is one of the strongest risk factors for breast cancer, it is therefore critical to understand how these factors interrelate. In this review, we discuss these relations by first presenting how adiposity measurements and breast density features are linked to breast cancer risk. Then, we used a systematic approach to capture the literature to review the relation between adiposity and breast density features. Finally, the role of adipose tissue in carcinogenesis is discussed briefly from a biological perspective.
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Affiliation(s)
- Ludivine Soguel
- Departments of Social and Preventive Medicine
- CHU de Québec Research Center
- Department of Nutrition and Dietetics, University of Applied Sciences Western Switzerland (HES-SO) Geneva, 25 rue des Caroubiers, Carouge, Switzerland
| | - Francine Durocher
- Molecular Medicine, Cancer Research Center, Laval University, 2325 rue de l’Université
- CHU de Québec Research Center, CHUL, 2724 Laurier Boulevard
| | - André Tchernof
- CHU de Québec Research Center, CHUL, 2724 Laurier Boulevard
- Department of Nutrition, Laval University, 2425 rue de l’Agriculture, Quebec City, Quebec, Canada
| | - Caroline Diorio
- Departments of Social and Preventive Medicine
- CHU de Québec Research Center
- Deschênes-Fabia Center for Breast Diseases, Saint-Sacrement Hospital, 1050 Chemin Ste-Foy
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15
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García-Pérez J, Pollán M, Pérez-Gómez B, González-Sánchez M, Cortés Barragán RA, Maqueda Blasco J, González-Galarzo MC, Alba MÁ, van der Haar R, Casas S, Vicente C, Medina P, Ederra M, Santamariña C, Moreno MP, Casanova F, Pedraz-Pingarrón C, Moreo P, Ascunce N, García M, Salas-Trejo D, Sánchez-Contador C, Llobet R, Lope V. Occupation and mammographic density: A population-based study (DDM-Occup). ENVIRONMENTAL RESEARCH 2017; 159:355-361. [PMID: 28843166 DOI: 10.1016/j.envres.2017.08.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 07/21/2017] [Accepted: 08/14/2017] [Indexed: 06/07/2023]
Abstract
INTRODUCTION High mammographic density is one of the main risk factors for breast cancer. Although several occupations have been associated with breast cancer, there are no previous occupational studies exploring the association with mammographic density. Our objective was to identify occupations associated with high mammographic density in Spanish female workers. METHODS We conducted a population-based cross-sectional study of occupational determinants of high mammographic density in Spain, based on 1476 women, aged 45-68 years, recruited from seven screening centers within the Spanish Breast Cancer Screening Program network. Reproductive, family, personal, and occupational history data were collected. The latest occupation of each woman was collected and coded according to the 1994 National Classification of Occupations. Mammographic density was assessed from the cranio-caudal mammogram of the left breast using a semi-automated computer-assisted tool. Association between mammographic density and occupation was evaluated by using mixed linear regression models, using log-transformed percentage of mammographic density as dependent variable. Models were adjusted for age, body mass index, menopausal status, parity, smoking, alcohol intake, educational level, type of mammography, first-degree relative with breast cancer, and hormonal replacement therapy use. Screening center and professional reader were included as random effects terms. RESULTS Mammographic density was higher, although non-statistically significant, among secondary school teachers (eβ = 1.41; 95%CI = 0.98-2.03) and nurses (eβ = 1.23; 95%CI = 0.96-1.59), whereas workers engaged in the care of people (eβ = 0.81; 95%CI = 0.66-1.00) and housewives (eβ = 0.87; 95%CI = 0.79-0.95) showed an inverse association with mammographic density. A positive trend for every 5 years working as secondary school teachers was also detected (p-value = 0.035). CONCLUSIONS Nurses and secondary school teachers were the occupations with the highest mammographic density in our study, showing the latter a positive trend with duration of employment. Future studies are necessary to confirm if these results are due to chance or are the result of a true association whose causal hypothesis is, for the moment, unknown.
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Affiliation(s)
- Javier García-Pérez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | - Mario González-Sánchez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
| | | | - Jerónimo Maqueda Blasco
- Instituto Nacional de Seguridad e Higiene en el Trabajo, Ministerio de Empleo y Seguridad Social, Madrid, Spain.
| | | | - Miguel Ángel Alba
- Área de Higiene Industrial, PREMAP Seguridad y Salud S.L.U., Barcelona, Spain.
| | | | - Silvia Casas
- Programa de Detección Precoz de Cáncer de Mama, Dirección General de Salud Pública y Participación, Palma, Spain.
| | - Cándida Vicente
- Programa de Prevención de Cáncer de Mama, Dirección General de Salud Pública, Valencia, Spain.
| | - Pilar Medina
- Programa de Prevención y Control del Cáncer, Unidad de Biomarcadores y Susceptibilidad, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain.
| | - María Ederra
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain; Navarra Breast Cancer Screening Program, Public Health Institute, Pamplona, Spain.
| | - Carmen Santamariña
- Galicia Breast Cancer Screening Program, Regional Authority of Health, Galicia Regional Government, Corunna, Spain.
| | - María Pilar Moreno
- Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain.
| | - Francisco Casanova
- Sección de Promoción de la Salud del Servicio Territorial de Sanidad de Burgos, Dirección General de Salud Pública de la Consejería de Sanidad de Castilla y León, Burgos, Spain.
| | - Carmen Pedraz-Pingarrón
- Sección de Promoción de la Salud del Servicio Territorial de Sanidad de Burgos, Dirección General de Salud Pública de la Consejería de Sanidad de Castilla y León, Burgos, Spain.
| | - Pilar Moreo
- Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain.
| | - Nieves Ascunce
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain; Navarra Breast Cancer Screening Program, Public Health Institute, Pamplona, Spain.
| | - Montse García
- Programa de Prevención y Control del Cáncer, Unidad de Biomarcadores y Susceptibilidad, Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Institut Català d'Oncologia, L'Hospitalet de Llobregat, Spain.
| | - Dolores Salas-Trejo
- Programa de Prevención de Cáncer de Mama, Dirección General de Salud Pública, Valencia, Spain.
| | - Carmen Sánchez-Contador
- Programa de Detección Precoz de Cáncer de Mama, Dirección General de Salud Pública y Participación, Palma, Spain.
| | - Rafael Llobet
- Institute of Computer Technology, Universitat Politècnica de València, Valencia, Spain.
| | - Virginia Lope
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Spain.
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16
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Lope V, García-Pérez J, Pérez-Gómez B, Pedraza-Flechas AM, Alguacil J, González-Galarzo MC, Alba MA, van der Haar R, Cortés-Barragán RA, Pedraz-Pingarrón C, Moreo P, Santamariña C, Ederra M, Vidal C, Salas-Trejo D, Sánchez-Contador C, Llobet R, Pollán M. Occupational exposures and mammographic density in Spanish women. Occup Environ Med 2017; 75:124-131. [PMID: 29074552 DOI: 10.1136/oemed-2017-104580] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Revised: 09/20/2017] [Accepted: 09/28/2017] [Indexed: 12/29/2022]
Abstract
OBJECTIVES The association between occupational exposures and mammographic density (MD), a marker of breast cancer risk, has not been previously explored. Our objective was to investigate the influence of occupational exposure to chemical, physical and microbiological agents on MD in adult women. METHODS This is a population-based cross-sectional study based on 1476 female workers aged 45-65 years from seven Spanish breast cancer screening programmes. Occupational history was surveyed by trained staff. Exposure to occupational agents was assessed using the Spanish job-exposure matrix MatEmESp. Percentage of MD was measured by two radiologists using a semiautomatic computer tool. The association was estimated using mixed log-linear regression models adjusting for age, education, body mass index, menopausal status, parity, smoking, alcohol intake, type of mammography, family history of breast cancer and hormonal therapy use, and including screening centre and professional reader as random effects terms. RESULTS Although no association was found with most of the agents, women occupationally exposed to perchloroethylene (eβ=1.51; 95% CI 1.04 to 2.19), ionising radiation (eβ=1.23; 95% CI 0.99 to 1.52) and mould spores (eβ=1.44; 95% CI 1.01 to 2.04) tended to have higher MD. The percentage of density increased 12% for every 5 years exposure to perchloroethylene or mould spores, 11% for every 5 years exposure to aliphatic/alicyclic hydrocarbon solvents and 3% for each 5 years exposure to ionising radiation. CONCLUSIONS Exposure to perchloroethylene, ionising radiation, mould spores or aliphatic/alicyclic hydrocarbon solvents in occupational settings could be associated with higher MD. Further studies are needed to clarify the accuracy and the reasons for these findings.
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Affiliation(s)
- Virginia Lope
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain
| | - Javier García-Pérez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain
| | - Ana María Pedraza-Flechas
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Juan Alguacil
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain.,Centro de Investigación en Salud y Medio Ambiente (CYSMA), Universidad de Huelva, Huelva, Spain
| | | | - Miguel Angel Alba
- Área de Higiene Industrial, PREMAP Seguridad y Salud S.L.U, Barcelona, Spain
| | | | | | | | - Pilar Moreo
- Aragon Breast Cancer Screening Program, Aragon Health Service, Zaragoza, Spain
| | - Carmen Santamariña
- Servicio de Alertas Epidemiolóxicas, Programa Galego Diagnostico Precoz Cancro de Mama, Unidade Central A Coruña, Conselleria de Sanidade, A Coruña, Spain
| | - María Ederra
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain.,Public Health Institute, Navarra Breast Cancer Screening Programme, Pamplona, Spain
| | - Carmen Vidal
- Prevention and Control Program, Catalan Institute of Oncology, Barcelona, Spain
| | - Dolores Salas-Trejo
- Valencia Breast Cancer Screening Program, General Directorate Public Health, Valencia, Spain
| | | | - Rafael Llobet
- Institute of Computer Technology, Universitat Politècnica de València, Valencia, Spain
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain.,Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública - CIBERESP), Madrid, Spain
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17
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Alimujiang A, Appleton C, Colditz GA, Toriola AT. Adiposity during early adulthood, changes in adiposity during adulthood, attained adiposity, and mammographic density among premenopausal women. Breast Cancer Res Treat 2017; 166:197-206. [PMID: 28702890 DOI: 10.1007/s10549-017-4384-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Accepted: 07/07/2017] [Indexed: 01/09/2023]
Abstract
PURPOSE We investigated the associations of adolescent adiposity, changes in adiposity during adulthood, and attained adiposity with volumetric mammographic density measures. METHODS We recruited 383 premenopausal women who had a routine screening mammogram at the Breast Health Center, Washington University in St. Louis, MO from December 2015 to October 2016. Trained research personnel assessed current adiposity measures. Weight at ages 18 and 30 were self-reported. We evaluated mammographic density measures: volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV) using Volpara. Multivariable linear regression models were used to evaluate the associations of adiposity measures with volumetric mammographic density measures. RESULTS All attained adiposity measures, BMI at age 18, age 30, and weight change were significantly inversely associated with VPD, and positively associated with DV and NDV. One unit increase in body fat % was associated with a 4.9% decrease in VPD and a 6.5% increase in NDV (p-values <0.001). For each kilogram increase in weight change from age 18 to attained, VPD decreased by 16.3%, 47.1%, and 58.8% for women who gained 5.1-15, 15.1-25 and >25 kg, respectively, compared to women who gained less than 5 kg during this time period (p-values <0.001). Irrespective of BMI at age 18, VPD significantly decreased and NDV increased among women who were currently obese. CONCLUSIONS There is a need for mechanistic studies focusing on early adulthood to provide a better understanding of how adiposity in early life relates to mammographic density, and possibly breast cancer development in premenopausal women.
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Affiliation(s)
- Aliya Alimujiang
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Siteman Cancer Center, Campus Box 8100, 660 South Euclid Ave, St Louis, MO, 63110, USA
| | - Catherine Appleton
- Division of Diagnostic Radiology, and Siteman Cancer Center, Department of Radiology, Washington University School of Medicine, St Louis, MO, 63144, USA
| | - Graham A Colditz
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Siteman Cancer Center, Campus Box 8100, 660 South Euclid Ave, St Louis, MO, 63110, USA
| | - Adetunji T Toriola
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine and Siteman Cancer Center, Campus Box 8100, 660 South Euclid Ave, St Louis, MO, 63110, USA.
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18
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Pedraza-Flechas AM, Lope V, Sánchez-Contador C, Santamariña C, Pedraz-Pingarrón C, Moreo P, Ederra M, Miranda-García J, Vidal C, Llobet R, Aragonés N, Salas-Trejo D, Pollán M, Pérez-Gómez B. High Mammographic Density in Long-Term Night-Shift Workers: DDM-Spain/Var-DDM. Cancer Epidemiol Biomarkers Prev 2017; 26:905-913. [DOI: 10.1158/1055-9965.epi-16-0507] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2016] [Revised: 07/08/2016] [Accepted: 01/13/2017] [Indexed: 11/16/2022] Open
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19
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Arimura T, Ogino T, Yoshiura T, Matsuyama M, Kondo N, Miyazaki H, Sakuragi A, Ohara T, Ogo E, Hishikawa Y. A feasibility study of a hybrid breast-immobilization system for early breast cancer in proton beam therapy. Med Phys 2017; 44:1268-1274. [PMID: 28211058 DOI: 10.1002/mp.12166] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 01/07/2017] [Accepted: 02/10/2017] [Indexed: 11/11/2022] Open
Abstract
PURPOSE We aimed to develop a new breast-immobilizing system for proton beam therapy (PBT) of early breast cancer (EBC) that would provide the optimum breast shape during the treatment as well as increased fixation reliability by reducing the influence of respiratory movement. METHODS The breast-immobilizing system (HyBIS; hybrid breast-immobilizing system) consists of a whole body immobilization system (WBIS), position-converting device (to change patient position), photo-scanning system, breast cup (made using a three-dimensional printer), breast cup-fitting apparatus, breast cup-holding device (to ensure the breast remains lifted in the supine position), and dedicated stretcher fixed to the WBIS (to carry the patient). We conducted a phantom experiment to evaluate the effect of the HyBIS on breast immobilization during the respiratory cycle. Thirteen markers were embedded in the right breast of a female phantom that simulated respiratory thoracic movement at an amplitude of 15 mm, and their displacements on four-dimensional computed tomography were compared between conditions with and without immobilization by HyBIS. RESULTS When immobilization was applied with the HyBIS, breast protrusion was maintained in the phantom in the supine treatment position. The mean values of the anteroposterior, superoinferior, lateral, and three-dimensional (3D) displacement of the markers were 2.7 ± 1.7, 0.3 ± 0.5, 0.9 ± 0.8, and 3.1 ± 1.6 mm with HyBIS, and 5.5 ± 2.9, 0.6 ± 0.8, 0.5 ± 0.4, and 5.6 ± 2.9 mm without HyBIS, respectively; thus, the anteroposterior (P = 0.014) and 3D (P = 0.007) displacements significantly improved with HyBIS. CONCLUSIONS We demonstrated that the HyBIS can help retain the protruded breast shape in the supine position during treatment and can reduce the influence of respiratory movement. Thus, the HyBIS can help to reliably and precisely perform PBT for EBC.
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Affiliation(s)
- Takeshi Arimura
- Medipolis Proton Therapy and Research Center, Ibusuki, Japan.,Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Takashi Ogino
- Medipolis Proton Therapy and Research Center, Ibusuki, Japan
| | - Takashi Yoshiura
- Department of Radiology, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | | | - Naoaki Kondo
- Medipolis Proton Therapy and Research Center, Ibusuki, Japan
| | | | | | | | - Etsuyo Ogo
- Department of Radiology, Kurume University School of Medicine, Kurume, Japan
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20
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Reproducibility of data-driven dietary patterns in two groups of adult Spanish women from different studies. Br J Nutr 2016; 116:734-42. [PMID: 27374250 DOI: 10.1017/s000711451600252x] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
The objective of the present study was to assess the reproducibility of data-driven dietary patterns in different samples extracted from similar populations. Dietary patterns were extracted by applying principal component analyses to the dietary information collected from a sample of 3550 women recruited from seven screening centres belonging to the Spanish breast cancer (BC) screening network (Determinants of Mammographic Density in Spain (DDM-Spain) study). The resulting patterns were compared with three dietary patterns obtained from a previous Spanish case-control study on female BC (Epidemiological study of the Spanish group for breast cancer research (GEICAM: grupo Español de investigación en cáncer de mama)) using the dietary intake data of 973 healthy participants. The level of agreement between patterns was determined using both the congruence coefficient (CC) between the pattern loadings (considering patterns with a CC≥0·85 as fairly similar) and the linear correlation between patterns scores (considering as fairly similar those patterns with a statistically significant correlation). The conclusions reached with both methods were compared. This is the first study exploring the reproducibility of data-driven patterns from two studies and the first using the CC to determine pattern similarity. We were able to reproduce the EpiGEICAM Western pattern in the DDM-Spain sample (CC=0·90). However, the reproducibility of the Prudent (CC=0·76) and Mediterranean (CC=0·77) patterns was not as good. The linear correlation between pattern scores was statistically significant in all cases, highlighting its arbitrariness for determining pattern similarity. We conclude that the reproducibility of widely prevalent dietary patterns is better than the reproducibility of more population-specific patterns. More methodological studies are needed to establish an objective measurement and threshold to determine pattern similarity.
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21
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McCormack VA, Burton A, dos-Santos-Silva I, Hipwell JH, Dickens C, Salem D, Kamal R, Hartman M, Lee CPL, Chia KS, Ozmen V, Aribal ME, Flugelman AA, Lajous M, Lopez-Riduara R, Rice M, Romieu I, Ursin G, Qureshi S, Ma H, Lee E, van Gils CH, Wanders JOP, Vinayak S, Ndumia R, Allen S, Vinnicombe S, Moss S, Won Lee J, Kim J, Pereira A, Garmendia ML, Sirous R, Sirous M, Peplonska B, Bukowska A, Tamimi RM, Bertrand K, Nagata C, Kwong A, Vachon C, Scott C, Perez-Gomez B, Pollan M, Maskarinec G, Giles G, Hopper J, Stone J, Rajaram N, Teo SH, Mariapun S, Yaffe MJ, Schüz J, Chiarelli AM, Linton L, Boyd NF. International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries. Cancer Epidemiol 2016; 40:141-51. [PMID: 26724463 PMCID: PMC4738079 DOI: 10.1016/j.canep.2015.11.015] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Revised: 11/12/2015] [Accepted: 11/30/2015] [Indexed: 12/31/2022]
Abstract
Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.
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Affiliation(s)
- Valerie A McCormack
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France.
| | - Anya Burton
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Isabel dos-Santos-Silva
- Dept of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - John H Hipwell
- Centre for Medical Image Computing, University College London, UK
| | | | | | - Rasha Kamal
- Woman Imaging Unit, Radiodiagnosis Department, Kasr El Aini, Cairo University Hospitals, Cairo, Egypt
| | - Mikael Hartman
- Department of Surgery, Yong Loo Lin School of Medicine and Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Charmaine Pei Ling Lee
- Department of Surgery, Yong Loo Lin School of Medicine and Saw Swee Hock School of Public Health, National University of Singapore, Singapore; NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | - Kee-Seng Chia
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore
| | | | | | | | - Martín Lajous
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, USA; Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico, Mexico City, Mexico
| | - Ruy Lopez-Riduara
- Center for Research on Population Health, Instituto Nacional de Salud Pública, Mexico, Mexico City, Mexico
| | - Megan Rice
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Isabelle Romieu
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Giske Ursin
- Cancer Registry of Norway, Oslo, Norway; Department of Nutrition, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway; Department of Preventive Medicine, University of Southern California, Los Angeles, California, USA
| | - Samera Qureshi
- Norwegian Center for Minority Health Research (NAKMI), Oslo, Norway
| | - Huiyan Ma
- Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, USA
| | - Eunjung Lee
- Department of Preventive Medicine, University of Southern California, Los Angeles, California, USA
| | - Carla H van Gils
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | - Johanna O P Wanders
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, The Netherlands
| | | | - Rose Ndumia
- Aga Khan University Hospital, Nairobi, Kenya
| | - Steve Allen
- Department of Imaging, Royal Marsden NHS Foundation Trust, London, UK
| | - Sarah Vinnicombe
- Division of Cancer Research, Ninewells Hospital & Medical School, Dundee, UK
| | - Sue Moss
- Wolfson Institute of Preventive Medicine, Queen Mary University of London, UK
| | | | - Jisun Kim
- Asan Medical Center, Seoul, Republic of Korea
| | - Ana Pereira
- Institute of Nutrition and Food Technology, University of Chile, Chile
| | | | - Reza Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Sirous
- Isfahan University of Medical Sciences, Isfahan, Iran
| | | | | | - Rulla M Tamimi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | | | | | - Ava Kwong
- Division of Breast Surgery, The University of Hong Kong Faculty of Medicine, and Department of Surgery, Hong Kong Sanatorium and Hospital, Hong Kong, People's Republic of China
| | - Celine Vachon
- Dept Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Christopher Scott
- Dept Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Beatriz Perez-Gomez
- Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain
| | - Marina Pollan
- Cancer Epidemiology Unit, Instituto de Salud Carlos III and CIBERESP, Madrid, Spain
| | | | - Graham Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia; School of Population and Global Health, The University of Melbourne, Australia
| | - John Hopper
- School of Population and Global Health, The University of Melbourne, Australia
| | - Jennifer Stone
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Australia
| | - Nadia Rajaram
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | - Soo-Hwang Teo
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia; Cancer Research Malaysia, Subang Jaya, Malaysia
| | - Shivaani Mariapun
- Breast Cancer Research Group, University Malaya Medical Centre, University Malaya, Kuala Lumpur, Malaysia
| | | | - Joachim Schüz
- Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France
| | - Anna M Chiarelli
- Ontario Breast Screening Program, Cancer Care Ontario, Toronto, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, Toronto, Canada
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22
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Soguel L, Diorio C. Anthropometric factors, adult weight gain, and mammographic features. Cancer Causes Control 2015; 27:333-40. [PMID: 26667319 DOI: 10.1007/s10552-015-0706-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2015] [Accepted: 12/06/2015] [Indexed: 12/16/2022]
Abstract
PURPOSE To evaluate the association between anthropometric factors, weight gain during adulthood, and mammographic features among 1,435 women recruited at screening mammography. METHODS Spearman's partial coefficients were used to evaluate the correlation of anthropometric factors with mammographic features (percent density, absolute dense area, and non-dense area). Multivariate generalized linear models were used to evaluate the associations between weight change categories and mammographic features. RESULTS Body mass index was inversely correlated with percent density (r = -0.49, p < 0.0001) or absolute dense area (r = -0.21, p < 0.0001) and positively correlated with absolute non-dense area (r = 0.69, p < 0.0001). However, body mass index was positively correlated with absolute dense area when adjusting for absolute non-dense area (r = 0.16, p < 0.0001). Similar results were observed for weight, waist circumference, and waist-to-hip ratio with mammographic features. Within increasing categories of weight change, percent density (p trend < 0.0001) and absolute dense area (p trend = 0.025) increased, while absolute non-dense area decreased (p trend < 0.0001). After stratification by the median of non-dense area, the positive association between weight gain and absolute dense area remained only among women with higher non-dense area. CONCLUSIONS Adiposity seems positively associated with both dense and non-dense areas following adjustment for each other. Our findings suggest a higher breast dense area among women who gained weight and that a minimum of breast fat may be needed to promote the proliferation of this fibroglandular tissue.
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Affiliation(s)
- Ludivine Soguel
- Department of Social and Preventive Medicine, Cancer Research Center, Laval University, 2325, rue de l'Université, Quebec City, QC, G1V 0A6, Canada.,Oncology Unit, CHU de Québec Research Center, Saint-Sacrement Hospital, 1050, chemin Ste-Foy, Quebec City, QC, G1S 4L8, Canada.,Nutrition and Dietetics Department, University of Applied Sciences Western Switzerland (HES-SO) Geneva, rue des Caroubiers 25, 1227, Carouge, Switzerland
| | - Caroline Diorio
- Department of Social and Preventive Medicine, Cancer Research Center, Laval University, 2325, rue de l'Université, Quebec City, QC, G1V 0A6, Canada. .,Oncology Unit, CHU de Québec Research Center, Saint-Sacrement Hospital, 1050, chemin Ste-Foy, Quebec City, QC, G1S 4L8, Canada. .,Deschênes-Fabia Center for Breast Diseases, Saint-Sacrement Hospital, 1050, chemin Ste-Foy, Quebec City, QC, G1S 4L8, Canada.
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23
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Lope V, García-Esquinas E, Pérez-Gómez B, Altzibar JM, Gracia-Lavedan E, Ederra M, Molina de la Torre AJ, LLorca FJ, Tardón A, Moreno V, Bayo J, Salas-Trejo D, Marcos-Gragera R, Pumarega J, Dierssen-Sotos T, Lera JPB, de Miguel Medina MAC, Tusquets I, Amiano P, Boldo E, Kogevinas M, Aragonés N, Castaño-Vinyals G, Pollán M. Perinatal and childhood factors and risk of breast cancer subtypes in adulthood. Cancer Epidemiol 2015; 40:22-30. [PMID: 26613540 DOI: 10.1016/j.canep.2015.11.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 11/04/2015] [Accepted: 11/06/2015] [Indexed: 11/16/2022]
Abstract
BACKGROUND Accumulated exposure to hormones and growth factors during early life may influence the future risk of breast cancer (BC). This study examines the influence of childhood-related, socio-demographic and anthropometric variables on BC risk, overall and by specific pathologic subtypes. METHODS This is a case-control study where 1539 histologically-confirmed BC cases (23-85 years) and 1621 population controls, frequency matched by age, were recruited in 10 Spanish provinces. Perinatal and childhood-related characteristics were directly surveyed by trained staff. The association with BC risk, globally and according to menopausal status and pathologic subtypes, was evaluated using logistic and multinomial regression models, adjusting for tumor specific risk factors. RESULTS Birth characteristics were not related with BC risk. However, women with high socioeconomic level at birth presented a decreased BC risk (OR=0.45; 95% CI=0.29-0.70), while those whose mothers were aged over 39 years at their birth showed an almost significant excess risk of hormone receptor positive tumors (HR+) (OR=1.35; 95% CI=0.99-1.84). Women who were taller than their girl mates before puberty showed increased postmenopausal BC risk (OR=1.26; 95% CI=1.03-1.54) and increased HR+ BC risk (OR=1.26; 95% CI=1.04-1.52). Regarding prepubertal weight, while those women who were thinner than average showed higher postmenopausal BC risk (OR=1.46; 95% CI=1.20-1.78), associated with HR+ tumors (OR=1.34; 95% CI=1.12-1.61) and with triple negative tumors (OR=1.56; 95% CI=1.03-2.35), those who were heavier than average presented lower premenopausal BC risk (OR=0.64; 95% CI=0.46-0.90) and lower risk of epidermal growth factor receptor positive tumors (OR=0.61; 95% CI=0.40-0.93). CONCLUSION These data reflect the importance of hormones and growth factors in the early stages of life, when the mammary gland is in development and therefore more vulnerable to proliferative stimuli.
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Affiliation(s)
- Virginia Lope
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Manuel de Falla 1, 28222 Madrid, Spain.
| | - Esther García-Esquinas
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid/IdiPaz, Arzobispo Morcillo 4, 28029 Madrid, Spain
| | - Beatriz Pérez-Gómez
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Manuel de Falla 1, 28222 Madrid, Spain
| | - Jone M Altzibar
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Public Health Division of Gipuzkoa, Avenida de Navarra 4, 20013 Donostia, San Sebastián, Spain; Biodonostia Research Institute, Doctor Begiristain s/n, 20014 Donostia, San Sebastián, Spain
| | - Esther Gracia-Lavedan
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Centre for Research in Environmental Epidemiology (CREAL). Doctor Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Doctor Aiguader 88, 08003 Barcelona, Spain
| | - María Ederra
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Early Detection Section, Public Health Institute of Navarra, Leyre 15, 31003 Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Irunlarrea 3, 31008 Pamplona, Spain
| | | | - Francisco Javier LLorca
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Universidad de Cantabria-IDIVAL. Avenida Cardenal Herrera Oria s/n, 39011, Santander, Spain
| | - Adonina Tardón
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Instituto Universitario de Oncología, Universidad de Oviedo, Facultad de Medicina, Planta 7, Campus de El Cristo B, 33006 Oviedo, Asturias, Spain
| | - Víctor Moreno
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; IDIBELL-Catalan Institute of Oncology, Gran Via km 2.7, 08907L'Hospitalet de Llobregat, Spain; Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Campus de Bellvitge, Pavelló de Govern, Feixa Llarga s/n 08907, L'Hospitalet del Llobregat, Barcelona, Spain
| | - Juan Bayo
- Servicio de Oncología Médica, Hospital Juan Ramón Jiménez, Avenida de la Orden s/n, 21005 Huelva, Spain; Centro de Investigación en Salud y Medio Ambiente (CYSMA), Universidad de Huelva, Campus Universitario de El Carmen, 21071 Huelva, Spain
| | - Dolores Salas-Trejo
- General Directorate Public Health, and FISABIO, Avenida de Catalunya, 21, 46020 Valencia, Spain
| | - Rafael Marcos-Gragera
- Epidemiology Unit and Girona Cancer Registry, Oncology Coordination Plan, Department of Health, Autonomous Government of Catalonia, Catalan Institute of Oncology, Girona Biomedical Research Institute (IdiBGi), Carrer del Sol 15, 17004 Girona, Spain
| | - José Pumarega
- Grup de Recerca en Epidemiologia Clínica i Molecular del Càncer (GRECMC), Hospital del Mar Medical Research Institute (IMIM), Doctor Aiguader 88, 08003 Barcelona, Spain
| | - Trinidad Dierssen-Sotos
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Universidad de Cantabria-IDIVAL. Avenida Cardenal Herrera Oria s/n, 39011, Santander, Spain
| | - Juan Pablo Barrio Lera
- Grupo de Investigación en Interacciones Gen-Ambiente y Salud, Universidad de León, 24071 León, Spain
| | - M A Concepción de Miguel Medina
- Navarra Institute for Health Research (IdiSNA), Irunlarrea 3, 31008 Pamplona, Spain; Pathology Department, Navarra Hospital Complex, Irunlarrea 3, 31008 Pamplona, Spain
| | - Ignasi Tusquets
- Servei d'Oncologia Mèdica, Hospital del Mar, Passeig Marítim 25-29, 08003 Barcelona, Spain; Cancer Research Program IMIM (Hospital del Mar Medical Research Institute). Doctor Aiguader 88, 08003 Barcelona, Spain; Universitat Autònoma de Barcelona, Plaza Cívica s/n, 08193 Bellaterra, Barcelona, Spain
| | - Pilar Amiano
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Public Health Division of Gipuzkoa, Avenida de Navarra 4, 20013 Donostia, San Sebastián, Spain; Biodonostia Research Institute, Doctor Begiristain s/n, 20014 Donostia, San Sebastián, Spain
| | - Elena Boldo
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Manuel de Falla 1, 28222 Madrid, Spain
| | - Manolis Kogevinas
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Centre for Research in Environmental Epidemiology (CREAL). Doctor Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Doctor Aiguader 88, 08003 Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Doctor Aiguader 88, 08003 Barcelona, Spain
| | - Nuria Aragonés
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Manuel de Falla 1, 28222 Madrid, Spain
| | - Gemma Castaño-Vinyals
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Centre for Research in Environmental Epidemiology (CREAL). Doctor Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Doctor Aiguader 88, 08003 Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Doctor Aiguader 88, 08003 Barcelona, Spain
| | - Marina Pollán
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Avenida Monforte de Lemos 5, 28029 Madrid, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER Epidemiología y Salud Pública, CIBERESP), Spain; Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Manuel de Falla 1, 28222 Madrid, Spain
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24
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Abstract
Introduction Mammographic density (MD) is considered a strong predictor of Breast Cancer (BC). The objective of the present study is to explore the association between MD and the compliance with the World Cancer Research Fund and the American Institute for Cancer Research (WCRF/AICR) recommendations for cancer prevention. Methods Data of 3584 women attending screening from a population-based multicenter cross-sectional study (DDM-Spain) collected from October 7, 2007 through July 14, 2008, was used to calculate a score that measures the level of compliance with the WCRF/AICR recommendations: R1)Maintain adequate body weight; R2)Be physically active; 3R)Limit the intake of high density foods; R4)Eat mostly plant foods; R5)Limit the intake of animal foods; R6)Limit alcohol intake; R7)Limit salt and salt preserved food intake; R8)Meet nutritional needs through diet. The association between the score and MD (assessed by a single radiologist using a semi-quantitative scale) was evaluated using ordinal logistic models with random center-specific intercepts adjusted for the main determinants of MD. Stratified analyses by menopausal status and smoking status were also carried out. Results A higher compliance with the WCRF/AICR recommendations was associated with lower MD (OR1-unit increase = 0.93 95%CI:0.86;0.99). The association was stronger in postmenopausal women (OR = 0.91 95%CI:0.84;0.99) and nonsmokers (OR = 0.87;95%CI:0.80;0.96 for nonsmokers, OR = 1.01 95%CI:0.91;1.12 for smokers, P-interaction = 0.042). Among nonsmokers, maintaining adequate body weight (OR = 0.81 95%CI:0.65;1.01), practicing physical activity (OR = 0.68 95%CI:0.48;0.96) and moderating the intake of high-density foods (OR = 0.58 95%CI:0.40;0.86) and alcoholic beverages (OR = 0.76 95%CI:0.55;1.05) were the recommendations showing the strongest associations with MD. Conclusions postmenopausal women and non-smokers with greater compliance with the WCRF/AICR guidelines have lower MD. These results may provide guidance to design specific recommendations for screening attendants with high MD and therefore at higher risk of developing BC.
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Peiró-Pérez R, Salas D, Vallés G, Abad-Fernandez MS, Vidal C, Sanchez-Contador Escudero C, Ascunce-Elizaga N, Zubizarreta R, Pedraz C, Pérez-Gómez B, Navarrete-Muñoz EM, Vioque J, Pollán M. Walking, biking or sport: how Spanish women attending breast cancer screening meet physical activity recommendations? Eur J Public Health 2015; 25:857-63. [PMID: 25767095 DOI: 10.1093/eurpub/cku248] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND The aim is to analyse physical activity (PA), the fulfillment recommendation of at least 150 min of moderate PA, through walking/biking (W&B), sport, both types of PA and the factors associated with inactivity by Spanish women who attended breast cancer screening programmes. METHODS The DDM-Spain is a multicentre cross-sectional study involving 3584 women, aged 45-68, attending screening in seven Spanish cities. Data were collected using a questionnaire, including age, socio-demographic and lifestyle characteristics, family burden and PA. PA was converted into metabolic equivalent of task (METs), categorized as low ≤ 600 METs min per week (m/w), moderate 600-3000 METs m/w and high ≥ 3000 METs m/w. A multivariate logistic regression was performed to identify variables associated with inactivity for each type of PA. RESULTS No women achieved a high level of PA through sport. 79.2% achieved a high or moderate level of PA by W&B. Lack of sport was associated with being overweight (odds ratio OR = 1.31; 95% confidence interval CI: 1.06 to 1.62), body mass index (BMI) ≥ 30 (OR = 1.85; 95% CI: 1.44 to 2.38), smoking (OR = 1.56; 95% CI: 1.22 to 2.00) and living with a disabled person (OR = 1.64; 95% CI: 1.0 to 2.81), whereas enough sport practice was associated with higher educational or socio-economic level (SEL). Regarding W&B, inactivity was associated with BMI ≥ 30 (OR = 1.91; 95% CI: 1.49 to 2.45) and living with someone >74 (OR = 1.96; 95% CI: 1.48 to 2.58). Inactivity for both types of exercise was associated with a BMI ≥ 30 (OR = 2.13; 95% CI: 1.63 to 2.8), smoking (OR = 1.41; 95% CI: 1.09 to 1.81) and living with someone >74 (OR = 1.69; 95% CI: 1.24 to 2.28). CONCLUSIONS Family burden and BMI ≥ 30 are inversely associated with both types of PA. W&B is the most common type of PA regardless of educational and SEL.
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Affiliation(s)
- Rosana Peiró-Pérez
- 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain 2 CIBER Epidemiología y Salud Pública (CIBERESP), ISCIII, Madrid, Spain 3 Breast Cancer Screening Programme, Valencian Public Health Directorate, Valencia, Spain
| | - Dolores Salas
- 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain 3 Breast Cancer Screening Programme, Valencian Public Health Directorate, Valencia, Spain
| | - Guillermo Vallés
- 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain
| | | | - Carmen Vidal
- 5 Cancer Prevention and Control Unit, Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Carmen Sanchez-Contador Escudero
- 6 Balearic Islands Breast Cancer Screening Programme, General Directorate Public Health and Consumer Affairs, Balearic Islands, Spain
| | - Nieves Ascunce-Elizaga
- 2 CIBER Epidemiología y Salud Pública (CIBERESP), ISCIII, Madrid, Spain 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain
| | - Raquel Zubizarreta
- 8 Galicia Breast Cancer Screening Programme, Regional Authority of Health, Galicia Regional Government, A Coruna, Spain
| | - Carmen Pedraz
- 9 Castilla-Leon Breast Cancer Screening Programme, General Directorate Public Health, Burgos, Spain
| | - Beatriz Pérez-Gómez
- 2 CIBER Epidemiología y Salud Pública (CIBERESP), ISCIII, Madrid, Spain 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain 11 Cancer and Environmental Epidemiology Unit, National Centre for Epidemiology, Carlos III Institute of Health, Madrid, Spain
| | - Eva María Navarrete-Muñoz
- 2 CIBER Epidemiología y Salud Pública (CIBERESP), ISCIII, Madrid, Spain 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain
| | - Jesús Vioque
- 2 CIBER Epidemiología y Salud Pública (CIBERESP), ISCIII, Madrid, Spain 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain
| | - Marina Pollán
- 2 CIBER Epidemiología y Salud Pública (CIBERESP), ISCIII, Madrid, Spain 1 Cancer and Public Health Area. Fundación Para el Fomento de la Investigación Sanitaria y Biomédica (FISABIO), Valencia, Spain 11 Cancer and Environmental Epidemiology Unit, National Centre for Epidemiology, Carlos III Institute of Health, Madrid, Spain
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Mammographic density and breast cancer risk by family history in women of white and Asian ancestry. Cancer Causes Control 2015; 26:621-6. [PMID: 25761408 DOI: 10.1007/s10552-015-0551-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 03/04/2015] [Indexed: 10/23/2022]
Abstract
PURPOSE Mammographic density, i.e., the radiographic appearance of the breast, is a strong predictor of breast cancer risk. To determine whether the association of breast density with breast cancer is modified by a first-degree family history of breast cancer (FHBC) in women of white and Asian ancestry, we analyzed data from four case-control studies conducted in the USA and Japan. METHODS The study population included 1,699 breast cancer cases and 2,422 controls, of whom 45% reported white (N = 1,849) and 40% Asian (N = 1,633) ancestry. To standardize mammographic density assessment, a single observer re-read all mammograms using one type of interactive thresholding software. Logistic regression was applied to estimate odds ratios (OR) while adjusting for confounders. RESULTS Overall, 496 (12%) of participants reported a FHBC, which was significantly associated with breast cancer risk in the adjusted model (OR 1.51; 95% CI 1.23-1.84). There was a statistically significant interaction on a multiplicative scale between FHBC and continuous percent density (per 10 % density: p = 0.03). The OR per 10% increase in percent density was higher among women with a FHBC (OR 1.30; 95% CI 1.13-1.49) than among those without a FHBC (OR 1.14; 1.09-1.20). This pattern was apparent in whites and Asians. The respective ORs were 1.45 (95% CI 1.17-1.80) versus 1.22 (95% CI 1.14-1.32) in whites, whereas the values in Asians were only 1.24 (95% CI 0.97-1.58) versus 1.09 (95% CI 1.00-1.19). CONCLUSIONS These findings support the hypothesis that women with a FHBC appear to have a higher risk of breast cancer associated with percent mammographic density than women without a FHBC.
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Fernandez-Navarro P, González-Neira A, Pita G, Díaz-Uriarte R, Tais Moreno L, Ederra M, Pedraz-Pingarrón C, Sánchez-Contador C, Vázquez-Carrete JA, Moreo P, Vidal C, Salas-Trejo D, Stone J, Southey MC, Hopper JL, Pérez-Gómez B, Benitez J, Pollan M. Genome wide association study identifies a novel putative mammographic density locus at 1q12-q21. Int J Cancer 2014; 136:2427-36. [PMID: 25353672 DOI: 10.1002/ijc.29299] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Accepted: 10/16/2014] [Indexed: 01/26/2023]
Abstract
Mammographic density (MD) is an intermediate phenotype for breast cancer. Previous studies have identified genetic variants associated with MD; however, much of the genetic contribution to MD is unexplained. We conducted a two-stage genome-wide association analysis among the participants in the "Determinants of Density in Mammographies in Spain" study, together with a replication analysis in women from the Australian MD Twins and Sisters Study. Our discovery set covered a total of 3,351 Caucasian women aged 45 to 68 years, recruited from Spanish breast cancer screening centres. MD was blindly assessed by a single reader using Boyd's scale. A two-stage approach was employed, including a feature selection phase exploring 575,374 SNPs in 239 pairs of women with extreme phenotypes and a verification stage for the 183 selected SNPs in the remaining sample (2,873 women). Replication was conducted in 1,786 women aged 40 to 70 years old recruited via the Australian Twin Registry, where MD were measured using Cumulus-3.0, assessing 14 SNPs with a p value <0.10 in stage 2. Finally, two genetic variants in high linkage disequilibrium with our best hit were studied using the whole Spanish sample. Evidence of association with MD was found for variant rs11205277 (OR = 0.74; 95% CI = 0.67-0.81; p = 1.33 × 10(-10) ). In replication analysis, only a marginal association between this SNP and absolute dense area was found. There were also evidence of association between MD and SNPs in high linkage disequilibrium with rs11205277, rs11205303 in gene MTMR11 (OR = 0.73; 95% CI = 0.66-0.80; p = 2.64 × 10(-11) ) and rs67807996 in gene OTUD7B (OR = 0.72; 95% CI = 0.66-0.80; p = 2.03 × 10(-11)). Our findings provide additional evidence on common genetic variations that may contribute to MD.
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Affiliation(s)
- Pablo Fernandez-Navarro
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health, Madrid, Spain; Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Spain
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García-Arenzana N, Navarrete-Muñoz EM, Lope V, Moreo P, Vidal C, Laso-Pablos S, Ascunce N, Casanova-Gómez F, Sánchez-Contador C, Santamariña C, Aragonés N, Pérez Gómez B, Vioque J, Pollán M. Calorie intake, olive oil consumption and mammographic density among Spanish women. Int J Cancer 2013; 134:1916-25. [PMID: 24254818 PMCID: PMC4166692 DOI: 10.1002/ijc.28513] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2013] [Revised: 09/16/2013] [Accepted: 09/19/2013] [Indexed: 01/08/2023]
Abstract
High mammographic density (MD) is one of the main risk factors for development of breast cancer. To date, however, relatively few studies have evaluated the association between MD and diet. In this cross-sectional study, we assessed the association between MD (measured using Boyd's semiquantitative scale with five categories: <10%, 10–25%, 25–50%, 50–75% and >75%) and diet (measured using a food frequency questionnaire validated in a Spanish population) among 3,548 peri- and postmenopausal women drawn from seven breast cancer screening programs in Spain. Multivariate ordinal logistic regression models, adjusted for age, body mass index (BMI), energy intake and protein consumption as well as other confounders, showed an association between greater calorie intake and greater MD [odds ratio (OR) = 1.23; 95% confidence interval (CI) = 1.10-1.38, for every increase of 500 cal/day], yet high consumption of olive oil was nevertheless found to reduce the prevalence of high MD (OR = 0.86;95% CI = 0.76-0.96, for every increase of 22 g/day in olive oil consumption); and, while greater intake of whole milk was likewise associated with higher MD (OR = 1.10; 95%CI 1.00-1.20, for every increase of 200 g/day), higher consumption of protein (OR = 0.89; 95% CI 0.80-1.00, for every increase of 30 g/day) and white meat (p for trend 0.041) was found to be inversely associated with MD. Our study, the largest to date to assess the association between diet and MD, suggests that MD is associated with modifiable dietary factors, such as calorie intake and olive oil consumption. These foods could thus modulate the prevalence of high MD, and important risk marker for breast cancer.
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Affiliation(s)
- Nicolás García-Arenzana
- National Center for Epidemiology, Instituto de Salud Carlos III, Madrid, Spain; Preventive Medicine Unit. Hospital Infanta Leonor, Madrid, Spain
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Pollán M, Llobet R, Miranda-García J, Antón J, Casals M, Martínez I, Palop C, Ruiz-Perales F, Sánchez-Contador C, Vidal C, Pérez-Gómez B, Salas-Trejo D. Validation of DM-Scan, a computer-assisted tool to assess mammographic density in full-field digital mammograms. SPRINGERPLUS 2013; 2:242. [PMID: 23865000 PMCID: PMC3693435 DOI: 10.1186/2193-1801-2-242] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2013] [Accepted: 05/03/2013] [Indexed: 11/17/2022]
Abstract
We developed a semi-automated tool to assess mammographic density (MD), a phenotype risk marker for breast cancer (BC), in full-field digital images and evaluated its performance testing its reproducibility, comparing our MD estimates with those obtained by visual inspection and using Cumulus, verifying their association with factors that influence MD, and studying the association between MD measures and subsequent BC risk. Three radiologists assessed MD using DM-Scan, the new tool, on 655 processed images (craniocaudal view) obtained in two screening centers. Reproducibility was explored computing pair-wise concordance correlation coefficients (CCC). The agreement between DM-Scan estimates and visual assessment (semi-quantitative scale, 6 categories) was quantified computing weighted kappa statistics (quadratic weights). DM-Scan and Cumulus readings were compared using CCC. Variation of DM-Scan measures by age, body mass index (BMI) and other MD modifiers was tested in regression mixed models with mammographic device as a random-effect term. The association between DM-Scan measures and subsequent BC was estimated in a case–control study. All BC cases in screening attendants (2007–2010) at a center with full-field digital mammography were matched by age and screening year with healthy controls (127 pairs). DM-Scan was used to blindly assess MD in available mammograms (112 cases/119 controls). Unconditional logistic models were fitted, including age, menopausal status and BMI as confounders. DM-Scan estimates were very reliable (pairwise CCC: 0.921, 0.928 and 0.916). They showed a reasonable agreement with visual MD assessment (weighted kappa ranging 0.79-0.81). DM-Scan and Cumulus measures were highly concordant (CCC ranging 0.80-0.84), but ours tended to be higher (4%-5% on average). As expected, DM-Scan estimates varied with age, BMI, parity and family history of BC. Finally, DM-Scan measures were significantly associated with BC (p-trend=0.005). Taking MD<7% as reference, OR per categories of MD were: OR7%-17%=1.32 (95% CI=0.59-2.99), OR17%-28%=2.28 (95% CI=1.03-5.04) and OR>=29%=3.10 (95% CI=1.35-7.14). Our results confirm that DM-Scan is a reliable tool to assess MD in full-field digital mammograms.
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Affiliation(s)
- Marina Pollán
- National Center for Epidemiology, Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029 Spain ; Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública - CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029 Spain ; Centro Nacional de Epidemiología, Instituto de Salud Carlos III, Monforte de Lemos 5, Madrid, 28029 Spain
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Pollán M, Ascunce N, Ederra M, Murillo A, Erdozáin N, Alés-Martínez JE, Pastor-Barriuso R. Mammographic density and risk of breast cancer according to tumor characteristics and mode of detection: a Spanish population-based case-control study. Breast Cancer Res 2013; 15:R9. [PMID: 23360535 PMCID: PMC3672793 DOI: 10.1186/bcr3380] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2012] [Revised: 12/03/2012] [Accepted: 01/24/2013] [Indexed: 12/18/2022] Open
Abstract
INTRODUCTION It is not clear whether high mammographic density (MD) is equally associated with all subtypes of breast cancer (BC). We investigated the association between MD and subsequent BC, considering invasiveness, means of detection, pathologic subtype, and the time elapsed since mammographic exploration and BC diagnosis. METHODS BC cases occurring in the population of women who attended screening from 1997 through 2004 in Navarre, a Spanish region with a fully consolidated screening program, were identified via record linkage with the Navarre Cancer Registry (n = 1,172). Information was extracted from the records of their first attendance at screening in that period. For each case, we randomly selected four controls, matched by screening round, year of birth, and place of residence. Cases were classified according to invasiveness (ductal carcinoma in situ (DCIS) versus invasive tumors), pathologic subtype (considering hormonal receptors and HER2), and type of diagnosis (screen-detected versus interval cases). MD was evaluated by a single, experienced radiologist by using a semiquantitative scale. Data on BC risk factors were obtained by the screening program in the corresponding round. The association between MD and tumor subtype was assessed by using conditional logistic regression. RESULTS MD was clearly associated with subsequent BC. The odds ratio (OR) for the highest MD category (MD >75%) compared with the reference category (MD <10%) was similar for DCIS (OR = 3.47; 95% CI = 1.46 to 8.27) and invasive tumors (OR = 2.95; 95% CI = 2.01 to 4.35). The excess risk was particularly high for interval cases (OR = 7.72; 95% CI = 4.02 to 14.81) in comparison with screened detected tumors (OR = 2.17; 95% CI = 1.40 to 3.36). Sensitivity analyses excluding interval cases diagnosed in the first year after MD assessment or immediately after an early recall to screening yielded similar results. No differences were seen regarding pathologic subtypes. The excess risk associated with MD persisted for at least 7 to 8 years after mammographic exploration. CONCLUSIONS Our results confirm that MD is an important risk factor for all types of breast cancer. High breast density strongly increases the risk of developing an interval tumor, and this excess risk is not completely explained by a possible masking effect.
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Affiliation(s)
- Marina Pollán
- National Center for Epidemiology, Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029 Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029, Spain
| | - Nieves Ascunce
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029, Spain
- Navarre Breast cancer Screening Program, Navarre Institute of Public Health, Leyre 15, Pamplona, 31003, Spain
| | - María Ederra
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029, Spain
- Navarre Breast cancer Screening Program, Navarre Institute of Public Health, Leyre 15, Pamplona, 31003, Spain
| | - Alberto Murillo
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029, Spain
- Navarre Breast cancer Screening Program, Navarre Institute of Public Health, Leyre 15, Pamplona, 31003, Spain
| | - Nieves Erdozáin
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029, Spain
- Navarre Breast cancer Screening Program, Navarre Institute of Public Health, Leyre 15, Pamplona, 31003, Spain
| | - Jose Enrique Alés-Martínez
- Medical Oncology Unit, Nuestra Señora de Sonsoles Hospital, Avenida Juan Carlos I s/n, Avila, 05004, Spain
| | - Roberto Pastor-Barriuso
- National Center for Epidemiology, Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029 Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBER en Epidemiología y Salud Pública-CIBERESP), Carlos III Institute of Health, Monforte de Lemos 5, Madrid, 28029, Spain
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