Volume 137, Issue 7 pp. 1699-1708
Epidemiology

Comparison of anthropometric measures as predictors of cancer incidence: A pooled collaborative analysis of 11 Australian cohorts

Jessica L. Harding

Corresponding Author

Jessica L. Harding

Department of Clinical Diabetes and Epidemiology, Baker IDI Heart and Diabetes Institute, Melbourne, Australia

Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia

Correspondence to: Jessica L. Harding Level 4, 99 Commercial Road Melbourne, VIC, Australia 3004, Tel.: +61 (3) 8532 1582, Fax: +61 (3) 8532 1100, E-mail: [email protected]Search for more papers by this author
Jonathan E. Shaw

Jonathan E. Shaw

Department of Clinical Diabetes and Epidemiology, Baker IDI Heart and Diabetes Institute, Melbourne, Australia

Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia

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Kaarin J. Anstey

Kaarin J. Anstey

Research School of Population Health, The Australian National University, Canberra, Australia

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Robert Adams

Robert Adams

The Health Observatory Discipline of Medicine, The University of Adelaide, Adelaide, Australia

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Beverley Balkau

Beverley Balkau

Centre for Research in Epidemiology and Population Health, INSERM, U018 France

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Sharon L. Brennan-Olsen

Sharon L. Brennan-Olsen

IMPACT Strategic Research Centre School of Medicine, Deakin University, Geelong, Australia

Department of Medicine, NorthWest Academic Centre, The University of Melbourne, St Albans, Australia

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Tom Briffa

Tom Briffa

School of Population Health, The University of Western Australia, Crawley, Australia

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Timothy M.E. Davis

Timothy M.E. Davis

School of Medicine and Pharmacology, The University of Western Australia, Crawley, Australia

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Wendy A. Davis

Wendy A. Davis

School of Medicine and Pharmacology, The University of Western Australia, Crawley, Australia

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Annette Dobson

Annette Dobson

School of Population Health, The University of Queensland, Brisbane, Australia

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Leon Flicker

Leon Flicker

Centre for Medical Research, The University of Western Australia, Crawley, Australia

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Graham Giles

Graham Giles

Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia

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Janet Grant

Janet Grant

Population Research & Outcome Studies, The University of Adelaide, Adelaide, Australia

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Rachel Huxley

Rachel Huxley

School of Population Health, The University of Queensland, Brisbane, Australia

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Matthew Knuiman

Matthew Knuiman

School of Population Health, The University of Western Australia, Crawley, Australia

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Mary Luszcz

Mary Luszcz

Flinders Centre for Ageing Studies, Flinders University, Adelaide, Australia

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Robert J. MacInnis

Robert J. MacInnis

School of Population and Global Health, The University of Melbourne, Melbourne, Australia

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Paul Mitchell

Paul Mitchell

Westmead Millennium Institute, The University of Sydney, Sydney, Australia

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Julie A. Pasco

Julie A. Pasco

IMPACT Strategic Research Centre School of Medicine, Deakin University, Geelong, Australia

Department of Medicine, NorthWest Academic Centre, The University of Melbourne, St Albans, Australia

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Christopher Reid

Christopher Reid

School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia

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David Simmons

David Simmons

Institute of Metabolic Science, Cambridge University Hospitals NHS Foundation Trust, Cambridge, England

Department of Rural Health, The University of Melbourne, Shepparton, Australia

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Leon Simons

Leon Simons

UNSW Australia Lipid Research Dept, St Vincent's Hospital, Sydney, Australia

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Andrew Tonkin

Andrew Tonkin

School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia

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Mark Woodward

Mark Woodward

The George Institute for Global Health, The University of Sydney, Sydney, Australia

The George Institute for Global Health, Nuffield Department of Population Health, University of Oxford, United Kingdom

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Anna Peeters

Anna Peeters

Department of Clinical Diabetes and Epidemiology, Baker IDI Heart and Diabetes Institute, Melbourne, Australia

Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia

A.P. and D.J.M. Joint senior authorship

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Dianna J. Magliano

Dianna J. Magliano

Department of Clinical Diabetes and Epidemiology, Baker IDI Heart and Diabetes Institute, Melbourne, Australia

Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia

A.P. and D.J.M. Joint senior authorship

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First published: 24 March 2015
Citations: 47

Abstract

Obesity is a risk factor for cancer. However, it is not known if general adiposity, as measured by body mass index (BMI) or central adiposity [e.g., waist circumference (WC)] have stronger associations with cancer, or which anthropometric measure best predicts cancer risk. We included 79,458 men and women from the Australian and New Zealand Diabetes and Cancer Collaboration with complete data on anthropometry [BMI, WC, Hip Circumference (HC), WHR, waist to height ratio (WtHR), A Body Shape Index (ABSI)], linked to the Australian Cancer Database. Cox proportional hazards models assessed the association between each anthropometric marker, per standard deviation and the risk of overall, colorectal, post-menopausal (PM) breast, prostate and obesity-related cancers. We assessed the discriminative ability of models using Harrell's c-statistic. All anthropometric markers were associated with overall, colorectal and obesity-related cancers. BMI, WC and HC were associated with PM breast cancer and no significant associations were seen for prostate cancer. Strongest associations were observed for WC across all outcomes, excluding PM breast cancer for which HC was strongest. WC had greater discrimination compared to BMI for overall and colorectal cancer in men and women with c-statistics ranging from 0.70 to 0.71. We show all anthropometric measures are associated with the overall, colorectal, PM breast and obesity-related cancer in men and women, but not prostate cancer. WC discriminated marginally better than BMI. However, all anthropometric measures were similarly moderately predictive of cancer risk. We do not recommend one anthropometric marker over another for assessing an individuals' risk of cancer.

Abstract

What's New?

The accumulation of excess fat around the abdomen is a well-known risk factor for cardiovascular and metabolic diseases and is associated with a variety of cancers. While measures that reflect central adiposity, namely waist circumference (WC) and waist-to-hip ratio (WHR), are strongly associated with cardiometabolic disease risk, their ability to predict cancer risk is unclear. In this study, overall cancer risk and risk of colorectal and obesity-related cancers were associated with multiple anthropometric measures—not only WC or WHR. An exception was prostate cancer, which was not significantly associated with any anthropometric marker.

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