Sex-Based Differences in Imaging-Derived Body Composition and Their Association with Clinical Malnutrition in Abdominal Surgery Patients

Background: Malnutrition significantly impacts surgical outcomes yet is difficult to identify preoperatively. Few studies have investigated the association between comprehensive body composition assessment and malnutrition in males and females separately. This study evaluates sex-specific associations between preoperative imaging-derived body composition features and malnutrition in abdominal surgery patients. Methods: This cross-sectional study included patients who underwent a preoperative abdominal computed tomography scan and elective abdominal surgery at a single institution (2018–2021). A deep learning algorithm quantified five muscle groups and two fat depots from CT scans. Clinical malnutrition was diagnosed by registered dietitians using standardized criteria. Sex-specific associations between imaging features and malnutrition were evaluated using logistic regression. Results: Among 1143 patients, 20.2% had clinical malnutrition, with prevalence varying by procedure type (3.5–38.2%). Malnutrition was associated with reduced muscle volume for both sexes; however, myosteatosis was only associated with malnutrition in females. In males, malnutrition was associated with decreased psoas volume (OR: 0.58, 95% CI [0.41–0.82]), decreased quadratus lumborum volume (OR: 0.52, 95% CI [0.35–0.77]), and reduced erector spinae attenuation (OR 0.58, 95% CI [0.41–0.82]). In females, decreased psoas volume (OR 0.56, 95% CI [0.41–0.77]) and attenuation (OR 0.59, 95% CI [0.44–0.79]) were associated with malnutrition. Both sexes showed increased subcutaneous fat attenuation (males: OR 1.58, 95% CI [1.22–2.04]; females: OR 1.96, 95% CI [1.54–2.50]) and visceral fat attenuation (males: OR 1.43 95% CI [1.07–1.90]; females: OR 1.68 95% CI [1.29–2.20]) associated with malnutrition. Conclusions: Males and females exhibit distinct body composition features associated with clinical malnutrition. Comprehensive analysis of muscle and fat characteristics reveals these sex-specific relationships, providing foundational knowledge for future development of predictive tools to enable earlier identification of patients at higher nutrition-related surgical risk.