Influence of hormonal status and oral intake on phase angle in HIV-infected men

Objective Phase angle α can be easily obtained from bioelectrical impedance analysis. In the literature, this angle is the single best predictor of survival in patients with the human immunodeficiency virus (HIV). The aim of our study was to detect nutritional and biochemical parameters that influence the phase angle. Methods One hundred men with HIV were studied. In all patients, anthropometric and biochemical nutritional evaluations were performed. Basal concentrations of testosterone and somatomedin C (insulin-like growth factor-1) were measured. Tetrapolar bioelectrical impedance analysis was used to determine body composition. All patients received instruction on keeping 24-h written food records. Albumin, prealbumin, transferrin, CD4 count, and total lymphocytes were measured. Results Patientsʹ mean age was 39.1 ± 9.9 y, mean body weight was 66.8 ± 11.2 kg, and mean body mass index was 22.5 ± 3.5 kg/m2. Patientsʹ average fat-free mass was 58.05 ± 8.7 kg and average fat mass was 9.17 ± 4.9 kg. Average phase angle α was 8.21 ± 0.88 degrees. Patients were assigned to one of two groups according to phase angle: those with a phase angle α smaller than 8.2 degrees (group 1) and those with a phase angle α of at least 8.2 degrees (group 2). Weight, body mass index, transferrin, and somatomedin C were significantly higher in group 2 (P < 0.05 for all). There were significant positive correlations between phase angle α and somatomedin C (r = 0.3, P < 0.05) and protein intake (r = 0.2, P < 0.05). In the multivariate analysis (adjusted for number of antiretroviral drugs prescribed, age, disease stage, and energy and protein intakes), only somatomedin C remained in the model (F = 4.5, P < 0.05), with an increase in phase angle α of 0.56 degrees (95% confidence interval, 0.04 to 1.08) with each 1-nM/L increase in somatomedin C. Conclusion Somatomedin C and protein intake influenced phase angle α, but only somatomedin C remained as an independent factor in the multivariate analysis.