Background:

predicting weight loss outcomes from information collected from subjects before they start a weight management program is an objective strongly pursued by scientists who study energy balance.

Objective:

to develop and validate two prognostic models for the estimation of final body weight after a six-month intervention period.

Material and methods:

the present work was developed following the TRIPOD standard to report prognostic multivariable prediction models. A multivariable linear regression analysis was applied to 70 % of participants to identify the most relevant variables and develop the best prognostic model for body weight estimation. Then, 30 % of the remaining sample was used to validate the model. The study involved a 6-month intervention based on 25-30 % caloric restriction and exercise. A total of 239 volunteers who had participated in the PRONAF study, aged 18 to 50 years, with overweight or obesity (body mass index: 25-34.9 kg/m2), were enrolled. Body composition was estimated by dual-energy X-ray absorptiometry (DXA) and by hand-to-foot bioelectrical impedance (BIA) analysis.

Results:

prognostic models were developed and validated with a high correlation (0.954 and 0.951 for DXA and BIA, respectively), with the paired t-tests showing no significant differences between estimated and measured body weights. The mean difference, standard error, and 95 % confidence interval of the DXA model were 0.067 ± 0.547 (-1.036-1.170), and those of the BIA model were -0.105 ± 0.511 (-1.134-0.924).

Conclusions:

the models developed in this work make it possible to calculate the final BW of any participant engaged in an intervention like the one employed in this study based only on baseline body composition variables.

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