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American Association for Cancer Research, Cancer Epidemiology, Biomarkers & Prevention, 2(30), p. 373-379, 2021

DOI: 10.1158/1055-9965.epi-20-0690

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Latent Class Trajectory Modeling of Adult Body Mass Index and Risk of Obesity-Related Cancer: Findings from the Melbourne Collaborative Cohort Study

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Background: Obesity increases the risk of 13 cancer types. Given the long process of carcinogenesis, it is important to determine the impact of patterns of body mass over time. Methods: Using data from 30,377 participants in the Melbourne Collaborative Cohort Study, we identified body mass index (BMI) trajectories across adulthood and examined their association with the risk of obesity-related cancer. Participants completed interviews and questionnaires at baseline (1990–1994, age 40–69 years), follow-up 1 (1995–1998), and follow-up 2 (2003–2005). Body mass was recalled for age 18 to 21 years, measured at baseline, self-reported at follow-up 1, and measured at follow-up 2. Height was measured at baseline. Cancer diagnoses were ascertained from the Victorian Cancer Registry and the Australian Cancer Database. A latent class trajectory model was used to identify BMI trajectories that were not defined a priori. Cox regression was used to estimate HRs and 95% confidence intervals (CI) of obesity-related cancer risks by BMI trajectory. Results: Six distinct BMI trajectories were identified. Compared with people who maintained lower normal BMI, higher risks of developing obesity-related cancer were observed for participants who transitioned from normal to overweight (HR, 1.29; 95% CI, 1.13–1.47), normal to class I obesity (HR, 1.50; 95% CI, 1.28–1.75), or from overweight to class II obesity (HR, 1.66; 95% CI, 1.32–2.08). Conclusions: Our findings suggest that maintaining a healthy BMI across the adult lifespan is important for cancer prevention. Impact: Categorization of BMI by trajectory allowed us to identify specific risk groups to target with public health interventions.