Data from Dual-energy X-ray Absorptiometry–Derived Adiposity and Colorectal Cancer Incidence and Mortality in Postmenopausal Women

<div>AbstractBackground:<p>Determine if dual-energy X-ray absorptiometry (DXA)–derived adiposity was associated with colorectal cancer incidence and mortality in postmenopausal women from the Women’s Health Initiative DXA cohort.</p>Methods:<p>Whole-body DXA scans estimated adiposity. Women with a history of cancer (except nonmelanoma skin cancer) or missing baseline DXA were excluded. For 27 years of follow-up, outcomes and deaths were adjudicated. Descriptive statistics by colorectal cancer status were calculated. Fine and Gray’s competing risks regression was used to estimate sub-HRs and 95% confidence intervals. Observation time was from enrollment to the first colorectal cancer event or competing risk (other cancer, other cause of death); women without cancer at the last follow-up were censored. Covariates included sociodemographic, clinical, and study characteristics.</p>Results:<p>After exclusions, 9,950 women were included, with 191 first-incident colorectal cancer cases and 88 colorectal cancer–related deaths identified. At baseline, the mean (±SD) age was 63.3 (±7.4) years, and the body mass index (BMI) was 28.2 (±5.7) kg/m<sup>2</sup>. In adjusted models, baseline continuous abdominal visceral adipose tissue (VAT; per 100 cm<sup>2</sup>) and android fat (per kg) were significantly associated with a higher risk of first-incident colorectal cancer: sub-HRs (95% confidence interval) were 1.23 (1.04–1.45) and 1.15 (1.01–1.31), respectively. There were no significant associations between adiposity and colorectal cancer mortality.</p>Conclusions:<p>Higher amounts of abdominal VAT and android fat were associated with a higher risk of colorectal cancer incidence in postmenopausal women.</p>Impact:<p>Associations between VAT and colorectal cancer, independent of BMI, support the clinical assessment of body composition across weight categories. A head-to-head comparison of VAT and BMI for colorectal cancer prediction is recommended in future research.</p></div>