Article ; Online: Do traditional BMI categories capture future obesity? A comparison with trajectories of BMI and incidence of cancer.
AMIA ... Annual Symposium proceedings. AMIA Symposium
2021 Volume 2020, Page(s) 1287–1294
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 ... ...
| 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. |
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| MeSH term(s) | Aged ; Body Mass Index ; Female ; Humans ; Incidence ; Latent Class Analysis ; Male ; Middle Aged ; Neoplasms/complications ; Neoplasms/epidemiology ; Obesity/complications ; Obesity/epidemiology ; Risk Factors |
| Language | English |
| Publishing date | 2021-01-25 |
| Publishing country | United States |
| Document type | Comparative Study ; Journal Article ; Research Support, Non-U.S. Gov't |
| ISSN | 1942-597X |
| ISSN (online) | 1942-597X |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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