Metabolically defined body size and body shape phenotypes and risk of postmenopausal breast cancer in the European Prospective Investigation into Cancer and Nutrition

Author:

Mahamat‐Saleh Y.1ORCID,Rinaldi S.1ORCID,Kaaks R.2,Biessy C.1,Gonzalez‐Gil E. M.1,Murphy N.1,Le Cornet C.2,Huerta J. M.34ORCID,Sieri S.5,Tjønneland A.67,Mellemkjær L.6ORCID,Guevara M.8910,Overvad K.11,Perez‐Cornago A.12ORCID,Tin Tin S.12ORCID,Padroni L.13,Simeon V.14,Masala G.15,May A.16,Monninkhof E.16,Christakoudi S.1718ORCID,Heath A. K.17ORCID,Tsilidis K.17ORCID,Agudo A.1920,Schulze M. B.2122,Rothwell J.23,Cadeau C.23,Severi S.23ORCID,Weiderpass E.1ORCID,Gunter M. J.1,Dossus L.1

Affiliation:

1. International Agency for Research on Cancer Lyon France

2. Division of Cancer Epidemiology German Cancer Research Center (DFKZ) Heidelberg Germany

3. Department of Epidemiology Murcia Regional Health Council Murcia Spain

4. CIBER Epidemiología y Salud Pública (CIBERESP) Madrid Spain

5. Epidemiology and Prevention Unit Fondazione IRCCS Istituto Nazionale dei Tumori 20133 Milan Italy

6. Danish Cancer Society Research Center Copenhagen Denmark

7. Department of Public Health University of Copenhagen Copenhagen Denmark

8. Navarra Public Health Institute 31003 Pamplona Spain

9. Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP) 28029 Madrid Spain

10. Navarra Institute for Health Research (IdiSNA) 31008 Pamplona Spain

11. Department of Public Health, Section for Epidemiology Aarhus University Aarhus Denmark

12. Cancer Epidemiology Unit Nuffield Department of Population Health University of Oxford Oxford UK

13. Department of Clinical and Biological Sciences University of Turin Turin Italy

14. Dipartimento di Salute Mentale e Fisica e Medicina Preventiva Università degli Studi della Campania 'Luigi Vanvitelli' 80121 Naples Italy

15. Institute for Cancer Research, Prevention and Clinical Network (ISPRO) Florence Italy

16. Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht University Utrecht The Netherlands

17. Department of Epidemiology and Biostatistics School of Public Health, Imperial College London London UK

18. Department of Inflammation Biology School of Immunology and Microbial Sciences King's College London London UK

19. Unit of Nutrition and Cancer Catalan Institute of Oncology – ICO L'Hospitalet de Llobregat Spain

20. Nutrition and Cancer Group; Epidemiology, Public Health, Cancer Prevention and Palliative Care Program Bellvitge Biomedical Research Institute – IDIBELL L'Hospitalet de Llobregat Spain

21. Department of Molecular Epidemiology German Institute of Human Nutrition Potsdam‐Rehbruecke Nuthetal Germany

22. Institute of Nutritional Science University of Potsdam Nuthetal Germany

23. Paris‐Saclay University UVSQ, Inserm, Gustave Roussy, “Exposome and Heredity” team, CESP Villejuif France

Abstract

AbstractBackgroundExcess body fatness and hyperinsulinemia are both associated with an increased risk of postmenopausal breast cancer. However, whether women with high body fatness but normal insulin levels or those with normal body fatness and high levels of insulin are at elevated risk of breast cancer is not known. We investigated the associations of metabolically defined body size and shape phenotypes with the risk of postmenopausal breast cancer in a nested case–control study within the European Prospective Investigation into Cancer and Nutrition.MethodsConcentrations of C‐peptide—a marker for insulin secretion—were measured at inclusion prior to cancer diagnosis in serum from 610 incident postmenopausal breast cancer cases and 1130 matched controls. C‐peptide concentrations among the control participants were used to define metabolically healthy (MH; in first tertile) and metabolically unhealthy (MU; >1st tertile) status. We created four metabolic health/body size phenotype categories by combining the metabolic health definitions with normal weight (NW; BMI < 25 kg/m2, or WC < 80 cm, or WHR < 0.8) and overweight or obese (OW/OB; BMI ≥ 25 kg/m2, or WC ≥ 80 cm, or WHR ≥ 0.8) status for each of the three anthropometric measures separately: (1) MHNW, (2) MHOW/OB, (3) MUNW, and (4) MUOW/OB. Conditional logistic regression was used to compute odds ratios (ORs) and 95% confidence intervals (CIs).ResultsWomen classified as MUOW/OB were at higher risk of postmenopausal breast cancer compared to MHNW women considering BMI (OR = 1.58, 95% CI = 1.14–2.19) and WC (OR = 1.51, 95% CI = 1.09–2.08) cut points and there was also a suggestive increased risk for the WHR (OR = 1.29, 95% CI = 0.94–1.77) definition. Conversely, women with the MHOW/OB and MUNW were not at statistically significant elevated risk of postmenopausal breast cancer risk compared to MHNW women.ConclusionThese findings suggest that being overweight or obese and metabolically unhealthy raises risk of postmenopausal breast cancer while overweight or obese women with normal insulin levels are not at higher risk. Additional research should consider the combined utility of anthropometric measures with metabolic parameters in predicting breast cancer risk.

Funder

Cancer Research UK Manchester Centre

Centre International de Recherche sur le Cancer

Danish Cancer Society Research Center

Bundesministerium für Bildung und Forschung

Fondation ARC pour la Recherche sur le Cancer

Imperial College London

Institut National de la Santé et de la Recherche Médicale

Medical Research Council

Publisher

Wiley

Subject

Cancer Research,Radiology, Nuclear Medicine and imaging,Oncology

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