{Reference Type}: Journal Article
{Title}: Forecasting and validating fat mass ratio models through anthropometric measurements and health-related factors among people with HIV: a cross-sectional investigation.
{Author}: Dos Santos AP;da Silva LSL;Navarro AM;Cordeiro JFC;Marchiori GF;Abdalla PP;Tasinafo Júnior MF;Venturini ACR;Gomide EBG;Brilhadori J;Correia IM;Benedetti C;Mota J;Bohn L;Machado DRL;
{Journal}: Ann Transl Med
{Volume}: 12
{Issue}: 3
{Year}: 2024 Jun 10
{Factor}: 3.616
{DOI}: 10.21037/atm-23-1946
{Abstract}: <B>UNASSIGNED: </B>There is a limited research on predictive models of fat mass ratio (FMR) in people living with human immunodeficiency virus (HIV) (PWH). This study aimed to develop models considering anthropometric and health-related factors to predict and validate FMR in PWH regardless of sex.<BR><B>UNASSIGNED: </B>One hundred and six Brazilian PWH (46.4±9.8 years) were evaluated for body composition using dual-energy X-ray absorptiometry (DXA), body circumference (BC), and skinfold thicknesses (SKs). FMR predictive models were developed using stepwise linear regression, and their agreement with DXA was assessed using Bland-Altman plots. Cross-validation was performed using the predicted residual error sum of squares (PRESS) method.<BR><B>UNASSIGNED: </B>Six FMR estimation models were developed for PWH, with adjusted R2 ranging from 0.43 to 0.72, standard error of the estimate (SEE) from 0.16% to 0.22%, and 95% confidence interval (CI) from 1.03 to 1.15. Model 6, including thigh SK, waist BC, therapy duration, subscapular SK, education years, and abdominal SK, exhibited the highest determination power (R2 adjusted 0.72, SEE 0.16%, and 95% CI: 1.06-1.15). The agreement between DXA-based FMR and predictive models showed minimal bias (-0.03 to +0.04) and narrower limits of agreement, particularly for the top-performing model (-0.33 to +0.30). Model 6 exhibited a high adjusted Q2PRESS (0.70) and low SPRESS (0.17).<BR><B>UNASSIGNED: </B>Our predictive models advance the study of body composition in PWH by consolidating the use of anthropometry for diagnosing and monitoring lipodystrophy regardless of sex.