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Martin L, Saha S, Linton L, Taylor M, Zhu J, Chavez S, Stanisz G, Minkin S, Boyd N. Dietary Fiber, Insulin and Breast Tissue Composition at Age 15-18: A Cross-Sectional Study. Nutr Cancer 2022; 74:2946-2954. [PMID: 35243935 DOI: 10.1080/01635581.2022.2047738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Risk of breast cancer in adult life is influenced by body size and height in childhood, but the mechanisms responsible for these associations are currently unknown. We carried out research to determine if, at age 15-18, measures of dietary intake were associated with body size, hormones, and with variations in breast tissue composition that in adult life are associated with risk of breast cancer. METHODS In a cross-sectional study of 766 healthy Caucasian women aged 15-18, we measured percent breast water (PBW), total breast water and fat by magnetic resonance (MR), and assessed dietary intake using a validated food frequency questionnaire. We also measured height, weight, skin-fold thicknesses and waist-to-hip ratio, and in fasting blood assayed glucose and insulin. RESULTS After adjustment for age, measures of body size, and energy intake, dietary fiber (insoluble and total fiber) and insulin were associated positively and significantly with PBW. CONCLUSIONS Dietary fiber and fasting insulin were associated with breast tissue measures. These data suggest a potential approach to breast cancer prevention.
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Affiliation(s)
- Lisa Martin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sudipta Saha
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Linda Linton
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Monica Taylor
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Jie Zhu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Sofia Chavez
- Imaging Research, Sunnybrook Hospital, Toronto, ON, Canada
| | - Greg Stanisz
- Imaging Research, Sunnybrook Hospital, Toronto, ON, Canada
| | - Salomon Minkin
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Norman Boyd
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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Oskar S, Kehm R, Terry MB. Breast Tissue Composition-Why It Matters and How Can We Measure It More Accurately in Epidemiology Studies. Cancer Epidemiol Biomarkers Prev 2021; 30:590-592. [PMID: 33811170 DOI: 10.1158/1055-9965.epi-20-1807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 01/08/2021] [Accepted: 01/19/2021] [Indexed: 11/16/2022] Open
Abstract
Early-life body size has been consistently associated with breast cancer risk. The direction of the association changes over time, with high birth weight, smaller adolescent body size, and adult weight gain all increasing breast cancer risk. There is also a clear positive association between larger body size and increased breast adipose tissue measured by mammograms, but less is known about how body size changes across life stages affect stromal and epithelial breast tissue. Using breast tissue slides from women with benign breast disease, Oh and colleagues applied machine learning methods to evaluate body size across the life course and adipose, epithelial, and stromal tissue concentrations in adulthood. They found consistent patterns for higher adipose and lower stromal tissue concentrations with larger childhood and adult body size at age 18 years. They reported lower levels of epithelial tissue with larger body size at 18 years, but not at other time periods. Additional studies examining how body size at different life stages may affect breast tissue composition will be important. Noninvasive methods that can provide measures of breast tissue composition may offer potential ways forward to ensure generalizability, and repeated measurements by life stage.See related article by Oh et al., p. 608.
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Affiliation(s)
- Sabine Oskar
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Rebecca Kehm
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Mary Beth Terry
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York. .,Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
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His M, Biessy C, Torres-Mejía G, Ángeles-Llerenas A, Alvarado-Cabrero I, Sánchez GI, Borrero M, Porras C, Rodriguez AC, Garmendia ML, Olivier M, Porter PL, Lin M, Gunter MJ, Romieu I, Rinaldi S. Anthropometry, body shape in early-life and risk of premenopausal breast cancer among Latin American women: results from the PRECAMA study. Sci Rep 2020; 10:2294. [PMID: 32042008 PMCID: PMC7010745 DOI: 10.1038/s41598-020-59056-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Accepted: 12/17/2019] [Indexed: 12/24/2022] Open
Abstract
Cumulating evidence in Caucasian women suggests a positive association between height and premenopausal breast cancer risk and a negative association with overall adiposity; however data from Latin America are scarce. We investigated the associations between excess adiposity, body shape evolution across life, and risk of premenopausal breast cancer among 406 cases (women aged 20-45) and 406 matched population-based controls from Chile, Colombia, Costa Rica, and Mexico. Negative associations between adult adiposity and breast cancer risk were observed in adjusted models (body mass index (BMI): Odds ratio (OR) per 1 kg/m2 = 0.93; 95% confidence interval = 0.89-0.96; waist circumference (WC): OR per 10 cm = 0.81 (0.69-0.96); hip circumference (HC): OR per 10 cm = 0.80 (0.67-0.95)). Height and leg length were not associated with risk. In normal weight women (18.5 ≤ BMI < 25), women with central obesity (WC > 88 cm) had an increased risk compared to women with normal WC (OR = 3.60(1.47-8.79)). Residuals of WC over BMI showed positive associations when adjusted for BMI (OR per 10 cm = 1.38 (0.98-1.94)). Body shape at younger ages and body shape evolution were not associated with risk. No heterogeneity was observed by receptor status. In this population of Latin American premenopausal women, different fat distributions in adulthood were differentially associated with risk of breast cancer.
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Affiliation(s)
- Mathilde His
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Carine Biessy
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Gabriela Torres-Mejía
- Centre for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
| | | | - Isabel Alvarado-Cabrero
- Servicio de Patología del Hospital de Oncología, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico city, Mexico
| | - Gloria Inés Sánchez
- Group Infection and Cancer, School of Medicine, University of Antioquia, Medellín, Colombia
| | - Mauricio Borrero
- Group Infection and Cancer, School of Medicine, University of Antioquia, Medellín, Colombia
- Department of Gynecology and Obstetrics, School of Medicine, University or Antioquia, Medellín, Colombia
- Cinica Vida Fundacion, Medellín, Colombia
| | - Carolina Porras
- Agencia Costarricense de Investigaciones Biomédicas (ACIB)-Fundación INCIENSA, San José, Costa Rica
| | - Ana Cecilia Rodriguez
- Agencia Costarricense de Investigaciones Biomédicas (ACIB)-Fundación INCIENSA, San José, Costa Rica
| | - Maria Luisa Garmendia
- Instituto de Nutrición y de Tecnología de los Alimentos, Universidad de Chile, Santiago, Chile
| | - Magali Olivier
- Molecular Mechanisms and Biomarkers Group, Section of Mechanisms of Carcinogenesis, International Agency for Research on Cancer, Lyon, France
| | - Peggy L Porter
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - MingGang Lin
- Division of Human Biology, Fred Hutchinson Cancer Research Center, Seattle, United States of America
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France
| | - Isabelle Romieu
- Centre for Population Health Research, National Institute of Public Health, Cuernavaca, Mexico
- Hubert Department of Global Health, Emory University, Atlanta, Georgia, United States of America
| | - Sabina Rinaldi
- Section of Nutrition and Metabolism, International Agency for Research on Cancer, Lyon, France.
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Environmental Influences on Mammographic Breast Density in California: A Strategy to Reduce Breast Cancer Risk. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16234731. [PMID: 31783496 PMCID: PMC6926682 DOI: 10.3390/ijerph16234731] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 11/21/2019] [Accepted: 11/22/2019] [Indexed: 12/17/2022]
Abstract
State legislation in many U.S. states, including California, mandates informing women if they have dense breasts on screening mammography, meaning over half of their breast tissue is comprised of non-adipose tissue. Breast density is important to interpret screening sensitivity and is an established breast cancer risk factor. Environmental chemical exposures may play an important role in this, especially during key windows of susceptibility for breast development: in utero, during puberty, pregnancy, lactation, and the peri-menopause. There is a paucity of research, however, examining whether environmental chemical exposures are associated with mammographic breast density, and even less is known about environmental exposures during windows of susceptibility. Now, with clinical breast density scoring being reported routinely for mammograms, it is possible to find out, especially in California, where there are large study populations that can link environmental exposures during windows of susceptibility to breast density. Density scores are now available throughout the state through electronic medical records. We can link these with environmental chemical exposures via state-wide monitoring. Studying the effects of environmental exposure on breast density may provide valuable monitoring and etiologic data to inform strategies to reduce breast cancer risk.
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Terry MB, Cohn BA, Goldberg M, Flom JD, Wei Y, Houghton LC, Tehranifar P, McDonald JA, Protacio A, Cirillo P, Michels KB. Do Birth Weight and Weight Gain During Infancy and Early Childhood Explain Variation in Mammographic Density in Women in Midlife? Results From Cohort and Sibling Analyses. Am J Epidemiol 2019; 188:294-304. [PMID: 30383202 DOI: 10.1093/aje/kwy229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 10/01/2018] [Indexed: 02/06/2023] Open
Abstract
High birth weight is associated with increased breast cancer risk and, less consistently, with higher mammographic density. In contrast, adolescent body size has been consistently, negatively associated with both MD and breast cancer risk. It is unclear when the direction of these associations changes and whether weight gain in infancy is associated with MD. We evaluated the associations of birth weight and postnatal weight (measured at 4 months, 1 year, and 4 years) by absolute and velocity measures (relative within-cohort percentile changes) with adult mammographic density, assessed using a computer-assisted thresholding program (Cumulus), using linear regression models with generalized estimating equations to account for correlation between siblings in the Early Determinants of Mammographic Density study (1959-2008; n = 700 women with 116 sibling sets; mean age = 44.1 years). Birth weight was positively associated with dense area (per 1-kg increase, β = 3.36, 95% confidence interval (CI): 0.06, 6.66). Weight gains from 0 months to 4 months and 1 year to 4 years were negatively associated with dense area (for 10-unit increase in weight percentile, β = -0.65, 95% CI: -1.23, -0.07, and β = -1.07, 95% CI: -1.98, -0.16, respectively). Findings were similar in the sibling subset. These results support the hypothesis that high birth weight is positively associated with increased breast density and suggest that growth spurts starting in early infancy reduce mammographic dense area in adulthood.
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Affiliation(s)
- Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
- Imprints Center for Genetic and Environmental Lifecourse Studies, Mailman School of Public Health, Columbia University, New York, New York
| | - Barbara A Cohn
- The Child Health and Development Studies, Public Health Institute, Berkeley, California
| | - Mandy Goldberg
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Julie D Flom
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Ying Wei
- Department of Biostatistics, Mailman School of Public Health, Columbia University, New York, New York
| | - Lauren C Houghton
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Parisa Tehranifar
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York
| | - Jasmine A McDonald
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Angeline Protacio
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Piera Cirillo
- The Child Health and Development Studies, Public Health Institute, Berkeley, California
| | - Karin B Michels
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California
- Institute for Prevention and Cancer Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
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Hopper JL, Dite GS, MacInnis RJ, Liao Y, Zeinomar N, Knight JA, Southey MC, Milne RL, Chung WK, Giles GG, Genkinger JM, McLachlan SA, Friedlander ML, Antoniou AC, Weideman PC, Glendon G, Nesci S, Andrulis IL, Buys SS, Daly MB, John EM, Phillips KA, Terry MB. Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC). Breast Cancer Res 2018; 20:132. [PMID: 30390716 PMCID: PMC6215632 DOI: 10.1186/s13058-018-1056-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 10/02/2018] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman's familial risk. METHODS We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. RESULTS The strength and direction of the BMI risk association depended on baseline menopausal status (P < 0.001); after adjusting for menopausal status, the association did not depend on age at baseline (P = 0.6). In terms of absolute risk, the negative association with BMI for premenopausal women has a much smaller influence than the positive association with BMI for postmenopausal women. Women at higher familial risk have a much larger difference in absolute risk depending on their BMI than women at lower familial risk. CONCLUSIONS The greater a woman's familial risk, the greater the influence of BMI on her absolute postmenopausal breast cancer risk. Given that age-adjusted BMI is correlated across adulthood, maintaining a healthy weight throughout adult life is particularly important for women with a family history of breast cancer.
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Affiliation(s)
- John L. Hopper
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
| | - Gillian S. Dite
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
| | - Robert J. MacInnis
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC Australia
| | - Yuyan Liao
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY USA
| | - Nur Zeinomar
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY USA
| | - Julia A. Knight
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON Canada
| | - Melissa C. Southey
- Department of Pathology, Genetic Epidemiology Laboratory, The University of Melbourne, Parkville, VIC Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, CA VIC 3168 USA
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC Australia
| | - Wendy K. Chung
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY USA
- Departments of Pediatrics and Medicine, Columbia University, New York, NY USA
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC Australia
| | - Jeanine M. Genkinger
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY USA
| | - Sue-Anne McLachlan
- Department of Medicine, St Vincent’s Hospital, The University of Melbourne, Parkville, VIC Australia
- Department of Medical Oncology, St Vincent’s Hospital, Fitzroy, VIC Australia
| | - Michael L. Friedlander
- Prince of Wales Clinical School, University of New South Wales, Sydney, NSW Australia
- Department of Medical Oncology, Prince of Wales Hospital, Randwick, NSW Australia
| | - Antonis C. Antoniou
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Prue C. Weideman
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
| | - Gord Glendon
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON Canada
| | - Stephanie Nesci
- Division of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC Australia
| | - kConFab Investigators
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC Australia
- The Research Department, The Peter MacCallum Cancer Centre, Melbourne, VIC Australia
| | - Irene L. Andrulis
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON Canada
- Departments of Molecular Genetics and Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON Canada
| | - Saundra S. Buys
- Department of Medicine and Huntsman Cancer Institute, University of Utah Health Sciences Center, Salt Lake City, UT USA
| | - Mary B. Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA USA
| | - Esther M. John
- Department of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA USA
| | - Kelly Anne Phillips
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, VIC Australia
- Division of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, VIC Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, VIC Australia
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, 722 W 168th St, 7th Floor, New York, NY USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY USA
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Childhood body size and midlife mammographic breast density in foreign-born and U.S.-born women in New York City. Ann Epidemiol 2018; 28:710-716. [PMID: 30172558 DOI: 10.1016/j.annepidem.2018.08.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 07/26/2018] [Accepted: 08/02/2018] [Indexed: 11/20/2022]
Abstract
PURPOSE We investigated whether childhood body size is associated with midlife mammographic density, a strong risk factor for breast cancer. METHODS We collected interview data, including body size at age 10 years using a pictogram, and measured height and weight from 518 women, recruited at the time of screening mammography in New York City (ages 40-64 years, 71% Hispanic, 68% foreign-born). We used linear regression models to examine childhood body size in relation to percent density and areas of dense and nondense tissue, measured using a computer-assisted method from digital mammograms. RESULTS In models that adjusted for race/ethnicity, and age and body mass index at mammogram, the heaviest relative to leanest childhood body size was associated with 5.94% lower percent density (95% confidence interval [CI]: -9.20, -2.29), 7.69 cm2 smaller dense area (95% CI: -13.94, -0.63), and 26.17 cm2 larger nondense area (95% CI: 9.42, 43.58). In stratified analysis by menopausal status and nativity, the observed associations were stronger for postmenopausal and U.S.-born women although these differences did not reach statistical significance. CONCLUSIONS Heavy childhood body size is associated with lower mammographic density, consistent with its associations with breast cancer risk. Suggestive findings by nativity require confirmation in larger samples.
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