Waist circumference-years and cancer risk: a prospective study of the association and comparison of predictive performance with waist circumference and body mass index.


Journal

British journal of cancer
ISSN: 1532-1827
Titre abrégé: Br J Cancer
Pays: England
ID NLM: 0370635

Informations de publication

Date de publication:
04 Oct 2024
Historique:
received: 26 03 2024
accepted: 18 09 2024
revised: 09 09 2024
medline: 5 10 2024
pubmed: 5 10 2024
entrez: 4 10 2024
Statut: aheadofprint

Résumé

Associations of waist circumferences (WC) and body mass index (BMI) measured once or over time, with cancer incidence were studied. WC is associated with some cancers independent of BMI. Analyses of cumulative central adiposity and cancer are lacking. We investigated associations between waist circumference-years, incorporating exposure time to WC ≥ 102 cm in men or ≥88 cm in women, and cancer, and compared this with single WC or BMI. Serial WC measurements taken over 9 years in the prospective Atherosclerosis Risk in Communities Study (ARIC) predicted yearly WC. Cox proportional hazards regression estimated hazard ratios (HRs) of cancer incidence for waist circumference-years, WC or BMI, measured in Visit 4. Harrell's C-statistic quantified metric predictive performances. 10,172 participants were followed up from Visit 4 for cancer over a median 13.7 for men and 15.8 years for women. For obesity-related cancers, HRs per standard deviation waist circumference-years were 1.14 (95%CI:1.04,1.25) and 1.19 (95%CI:1.12,1.27), respectively. Differences in metric predictive performances were marginal. This is the first study to identify positive associations between waist circumference-years and cancer. Waist circumference-years did not provide additional information on cancer risk beyond that of WC and BMI. BMI is routinely measured in clinic so it may be preferred over WC.

Sections du résumé

BACKGROUND BACKGROUND
Associations of waist circumferences (WC) and body mass index (BMI) measured once or over time, with cancer incidence were studied. WC is associated with some cancers independent of BMI. Analyses of cumulative central adiposity and cancer are lacking. We investigated associations between waist circumference-years, incorporating exposure time to WC ≥ 102 cm in men or ≥88 cm in women, and cancer, and compared this with single WC or BMI.
METHODS METHODS
Serial WC measurements taken over 9 years in the prospective Atherosclerosis Risk in Communities Study (ARIC) predicted yearly WC. Cox proportional hazards regression estimated hazard ratios (HRs) of cancer incidence for waist circumference-years, WC or BMI, measured in Visit 4. Harrell's C-statistic quantified metric predictive performances.
RESULTS RESULTS
10,172 participants were followed up from Visit 4 for cancer over a median 13.7 for men and 15.8 years for women. For obesity-related cancers, HRs per standard deviation waist circumference-years were 1.14 (95%CI:1.04,1.25) and 1.19 (95%CI:1.12,1.27), respectively. Differences in metric predictive performances were marginal.
DISCUSSION CONCLUSIONS
This is the first study to identify positive associations between waist circumference-years and cancer. Waist circumference-years did not provide additional information on cancer risk beyond that of WC and BMI. BMI is routinely measured in clinic so it may be preferred over WC.

Identifiants

pubmed: 39367274
doi: 10.1038/s41416-024-02860-y
pii: 10.1038/s41416-024-02860-y
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Cancer Research UK (CRUK)
ID : [C19941/A28707]
Organisme : DH | National Institute for Health Research (NIHR)
ID : IS-BRC-1215-20007

Informations de copyright

© 2024. The Author(s).

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Auteurs

Nadin Hawwash (N)

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK. nadin.hawwash@manchester.ac.uk.
Cancer Research UK Manchester Cancer Research Centre, Manchester, UK. nadin.hawwash@manchester.ac.uk.

Matthew Sperrin (M)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

Glen P Martin (GP)

Centre for Health Informatics, Division of Informatics, Imaging and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.

Corinne E Joshu (CE)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA.

Roberta Florido (R)

Johns Hopkins University School of Medicine, Department of Medicine, Division of Cardiology, Baltimore, MD, USA.
Department of Medicine, Division of Cardiology, University of Utah, Salt Lake City, UT, USA.

Elizabeth A Platz (EA)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA.

Andrew G Renehan (AG)

Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
National Institute for Health Research (NIHR) Manchester Biomedical Research Centre, Manchester, UK.

Classifications MeSH