Adiposity Change Patterns and Prostate Cancer Risk: Age- and Smoking-Specific Associations in 1,332,372 Korean Males.
TL;DR
The impact of longitudinal adiposity patterns varied by smoking status and age, supporting personalized, lifestage-specific prevention emphasizing weight management and lifestyle modification.
Abstract
Purpose
Evidence linking body mass index (BMI) change to prostate cancer risk remains inconsistent despite known associations between adiposity and prostate carcinogenesis.
Materials And Methods
We conducted a population-based cohort study of 1,332,372 Korean males who completed health examinations in 2009 and 2013 and were followed through 2017. BMI was classified using Asia-Pacific criteria, and changes between 2009 and 2013 defined 25 groups. Prostate cancers were ascertained by ICD-10 (International Classification of Diseases, 10th Revision) codes. Cox proportional hazards models estimated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) controlling for demographics, lifestyle factors, and comorbidities.
Results
Over 12.7 million person-years, 9,147 prostate cancers were identified. BMI trajectories displayed distinct risk patterns. Remaining underweight (aHR, 0.76; 95% CI, 0.61 to 0.96) or moving from underweight to normal (aHR, 0.65; 95% CI, 0.47 to 0.91) was associated with lower risk, whereas persistent overweight (aHR, 1.18; 95% CI, 1.10 to 1.27), persistent obesity I (aHR, 1.19; 95% CI, 1.12 to 1.27), and transition from overweight to obesity I (aHR, 1.14; 95% CI, 1.03 to 1.27) were associated with higher risk compared with persistent normal BMI. Among males with obesity I, weight loss to normal BMI was associated with reduced risk compared to persistent obesity I (aHR, 0.63; 95% CI, 0.46 to 0.87). Smoking amplified the adverse associations of persistent overweight and obesity. However, persistent obesity II (≥30 kg/m²) was associated with lower risk among males <60 years (aHR, 0.62; 95% CI, 0.44 to 0.89), though this finding should be interpreted with caution as it may reflect detection bias.
Conclusions
The impact of longitudinal adiposity patterns varied by smoking status and age, supporting personalized, lifestage-specific prevention emphasizing weight management and lifestyle modification.