5 resultados para prediction equations
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
There is no consensus regarding the accuracy of bioimpedance for the determination of body composition in older persons. This study aimed to compare the assessment of lean body mass of healthy older volunteers obtained by the deuterium dilution method (reference) with those obtained by two frequently used bioelectrical impedance formulas and one formula specifically developed for a Latin-American population. A cross-sectional study. Twenty one volunteers were studied, 12 women, with mean age 72 +/- 6.7 years. Urban community, Ribeiro Preto, Brazil. Fat free mass was determined, simultaneously, by the deuterium dilution method and bioelectrical impedance; results were compared. In bioelectrical impedance, body composition was calculated by the formulas of Deuremberg, Lukaski and Bolonchuck and Valencia et al. Lean body mass of the studied volunteers, as determined by bioelectrical impedance was 37.8 +/- 9.2 kg by the application of the Lukaski e Bolonchuk formula, 37.4 +/- 9.3 kg (Deuremberg) and 43.2 +/- 8.9 kg (Valencia et. al.). The results were significantly correlated to those obtained by the deuterium dilution method (41.6 +/- 9.3 Kg), with r=0.963, 0.932 and 0.971, respectively. Lean body mass obtained by the Valencia formula was the most accurate. In this study, lean body mass of older persons obtained by the bioelectrical impedance method showed good correlation with the values obtained by the deuterium dilution method. The formula of Valencia et al., developed for a Latin-American population, showed the best accuracy.
Resumo:
Background: Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations. Results: The independent variables determined by BIO, BIA and US that best correlated (p < 0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows'Cp statistics, p value and r(2), 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats. Conclusions: The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed.
Resumo:
The objective of this study was to develop equations to predict retail product and fat trim (weights and percentages) for Nellore (Bos indicus) cattle. Live ultrasound measurements of the longissimus muscle area, backfat thickness at the 12th rib and rump fat depth and shrunk body weight were obtained from 218 Nellore steers to predict weights and percentages of carcass retail product, pistola retail product and fat trimmings. After slaughter, carcasses were deboned and weighed and percentages of retail cuts were obtained directly. Measurements taken directly in the carcasses explained 97% and 36% of variation in carcass retail product weight and percentage, and 94% and 36% of variation in pistola retail weight and percentage, respectively. Live measurements explained 93% of carcass retail product weight and 39% of carcass retail product percentage. Lower accuracies were observed for pistola retail product weight (R-2=0.87) and percentage (R-2=0.33). Accuracies for fat trimmings weight and percentage were 79% and 55%, respectively. Ultrasound rump fat thickness showed greater correlations with retail product and fat trimmings (weights and percentages) when compared with ultrasound backfat thickness. The weight and percentage of retail products and of trimmable fat can be estimated in Nellore steers from live animal measurements, with similar accuracy to equations developed based on carcass measurements obtained at slaughter.
Resumo:
Introduction: Computerizd tomography (CT) is the gold standard for the evaluation of intra- (IAF) and total (TAF) abdominal fat; however, the high cost of the procedure and exposure to radiation limit its routine use. Objective: To develop equations that utilize anthropometric measures for the estimate of IAF and TAF in obese women with polycystic ovary syndrome (PCOS). Methods: The weight, height, BMI, and abdominal (AC), waist (WC), chest (CC), and neck (NC) circumferences of thirty obese women with PCOS were measured, and their IAF and TAF were analyzed by CT. Results: The anthropometric variables AC, CC, and NC were chosen for the TAF linear regression model because they were better correlated with the fat deposited in this region. The model proposed for TAF (predicted) was: 4.63725 + 0.01483 x AC - 0.00117 x NC - 0.00177 x CC (R-2 = 0.78); and the model proposed for IAF was: IAF (predicted) = 1.88541 + 0.01878 x WC + 0.05687 x NC - 0.01529 x CC (R-2 = 0.51). AC was the only independent predictor of TAF (p < 0.01). Conclusion: The equations proposed showed good correlation with the real value measured by CT, and can be used in clinical practice. (Nutr Hosp. 2012;27:1662-1666) DOI:10.3305/nh.2012.27.5.5933
Resumo:
Background: The double burden of obesity and underweight is increasing in developing countries and simple methods for the assessment of fat mass in children are needed. Aim: To develop and validate a new anthropometric predication equation for assessment of fat mass in children. Subjects and methods: Body composition was assessed in 145 children aged 9.8 +/- 1.3 (SD) years from Sao Paulo, Brazil using dual energy X-ray absorptiometry (DEXA) and skinfold measurements. The study sample was divided into development and validation sub-sets to develop a new prediction equation for FM (PE). Results: Using multiple linear regression analyses, the best equation for predicting FM (R-2 - 0.77) included body weight, triceps skinfold, height, gender and age as independent variables. When cross-validated, the new PE was valid in this sample (R-2 = 0.80), while previously published equations were not. Conclusion: The PE was more valid for Brazilian children that existing equations, but further studies are needed to assess the validity of this PE in other populations.