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Do traditional BMI categories capture future obesity? A comparison with trajectories of BMI and incidence of cancer.
Watson, Charlotte; Geifman, Dr Nophar.
Afiliação
  • Watson C; Manchester Cancer Research Centre & NIHR Manchester Biomedical Research Centre, Manchester, UK.
  • Geifman DN; Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
AMIA Annu Symp Proc ; 2020: 1287-1294, 2020.
Article em En | MEDLINE | ID: mdl-33936505
ABSTRACT
In 2016, 13 specific obesity related cancers were identified by IARC. Here, using baseline WHO BMI categories, latent profile analysis (LPA) and latent class trajectory modelling (LCTM) we evaluated the usefulness of one-off measures when predicting cancer risk vs life-course changes. Our results in LPA broadly concurred with the three basic WHO BMI categories, with similar stepwise increase in cancer risk observed. In LCTM, we identified 5 specific trajectories in men and women. Compared to the leanest class, a stepwise increase in risk for obesity related cancer was observed for all classes. When latent class membership was compared to baseline BMI, we found that the trajectories were composed of a range of BMI (baseline) categories. All methods reveal a link between obesity and the 13 cancers identified by IARC. However, the additional information included by LCTM indicates that lifetime BMI may highlight additional group of people that are at risk.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias / Obesidade Tipo de estudo: Etiology_studies / Incidence_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias / Obesidade Tipo de estudo: Etiology_studies / Incidence_studies / Prognostic_studies / Risk_factors_studies Limite: Aged / Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article