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The present study was carried out to evaluate the effect of net energy levels in diets for barrows, from 70 to 100 kg, on performance, plasma parameters and carcass characteristics. Two experiments were carried out: in the first (Experiment I), a metabolism assay was carried out to estimate the net energy (NE) of experimental diets. Twelve crossbred barrows, averaging 85.74 ± 6.80 kg initial body weight, were distributed in a randomized block design with two metabolizable energy (ME) levels (3100 and 3500 kcal kg–¹) with six replicates and one animal per experimental unit. In the second (Experiment II), 45 castrated male pigs were used, averaging 70.10 ± 1.26 kg of initial body weight distributed in a randomized block design, with five NE levels (2345, 2425, 2505, 2585, 2665 kcal kg–¹), nine replicates and one animal per experimental unit. The increase in diet NE levels provided a linear reduction (p ≤ 0.00039) in average daily feed intake (ADFI). There was a quadratic effect on NE efficiency (p ≤ 0.0027), average daily gain (ADG), (p ≤ 0.0352) and the feed:gain ratio (F:G), (p ≤ 0.0024), the optimal levels being estimated at 2485, 2493 and 2533 kcal kg–¹, respectively. Drip loss (DL) decreased (p ≤ 0.0001) as NE levels increased. There was also a linear decrease (p ≤ 0.0462) in the Minolta color parameter (+a*), due to the NE levels. Plasma parameters were not affected (p > 0.05) by NE levels. The dietary net energy levels affected the performance and meat quality of finishing pigs and the level of 2493 kcal kg–¹ provided the best ADG.

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The present study was carried out to evaluate the effect of net energy levels in diets for barrows, from 70 to 100 kg, on performance, plasma parameters and carcass characteristics. Two experiments were carried out: in the first (Experiment I), a metabolism assay was carried out to estimate the net energy (NE) of experimental diets. Twelve crossbred barrows, averaging 85.74 ± 6.80 kg initial body weight, were distributed in a randomized block design with two metabolizable energy (ME) levels (3100 and 3500 kcal kg­1) with six replicates and one animal per experimental unit. In the second (Experiment II), 45 castrated male pigs were used, averaging 70.10 ± 1.26 kg of initial body weight distributed in a randomized block design, with five NE levels (2345, 2425, 2505, 2585, 2665 kcal kg­1), nine replicates and one animal per experimental unit. The increase in diet NE levels provided a linear reduction (p ≤ 0.00039) in average daily feed intake (ADFI). There was a quadratic effect on NE efficiency (p ≤ 0.0027), average daily gain (ADG), (p ≤ 0.0352) and the feed:gain ratio (F:G), (p ≤ 0.0024), the optimal levels being estimated at 2485, 2493 and 2533 kcal kg­1, respectively. Drip loss (DL) decreased (p ≤ 0.0001) as NE levels increased. There was also a linear decrease (p ≤ 0.0462) in the Minolta color parameter (+a*), due to the NE levels. Plasma parameters were not affected (p > 0.05) by NE levels. The dietary net energy levels affected the performance and meat quality of finishing pigs and the level of 2493 kcal kg­1 provided the best ADG.(AU)

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ABSTRACT The present study was carried out to evaluate the effect of net energy levels in diets for barrows, from 70 to 100 kg, on performance, plasma parameters and carcass characteristics. Two experiments were carried out: in the first (Experiment I), a metabolism assay was carried out to estimate the net energy (NE) of experimental diets. Twelve crossbred barrows, averaging 85.74 ± 6.80 kg initial body weight, were distributed in a randomized block design with two metabolizable energy (ME) levels (3100 and 3500 kcal kg1) with six replicates and one animal per experimental unit. In the second (Experiment II), 45 castrated male pigs were used, averaging 70.10 ± 1.26 kg of initial body weight distributed in a randomized block design, with five NE levels (2345, 2425, 2505, 2585, 2665 kcal kg1), nine replicates and one animal per experimental unit. The increase in diet NE levels provided a linear reduction (p 0.00039) in average daily feed intake (ADFI). There was a quadratic effect on NE efficiency (p 0.0027), average daily gain (ADG), (p 0.0352) and the feed:gain ratio (F:G), (p 0.0024), the optimal levels being estimated at 2485, 2493 and 2533 kcal kg1, respectively. Drip loss (DL) decreased (p 0.0001) as NE levels increased. There was also a linear decrease (p 0.0462) in the Minolta color parameter (+a*), due to the NE levels. Plasma parameters were not affected (p > 0.05) by NE levels. The dietary net energy levels affected the performance and meat quality of finishing pigs and the level of 2493 kcal kg1 provided the best ADG.

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INTRODUÇÃO: O pico de fluxo expiratório (PFE) é comumente usado para monitorar a progressão de doenças respiratórias, pois fornece boas informações sobre o estado das vias aéreas. Uma boa quantidade de pesquisas está sendo feita em todo o mundo para estabelecer uma equação de previsão local. A força-tarefa conjunta da Sociedade Torácica Americana e da Sociedade Respiratória Europeia promoveu pesquisas a esse respeito. Na Índia, os dados derivados da população caucasiana ainda são usados para o PFE. OBJETIVO: Estudar a relação dos parâmetros do PFE e os dados antropométricos como idade, altura, peso, índice de massa corporal (IMC), área de superfície corporal (ASC) e estabelecer uma equação de regressão para jovens adultos indianos. MÉTODOS: PFE foi feito em 1000 sujeitos de 15-25 anos da região metropolitana de Mumbai. O coeficiente de correlação de Pearson foi usado para entender a relação dos parâmetros antropométricos e PFE. A análise de regressão multivariada foi feita para estabelecer uma equação de predição. (Alfa 5%) RESULTADOS: Idade e todos os parâmetros antropométricos foram correlacionados com PFE. O pico de fluxo expiratório médio da população masculina foi de 515 ml / seg, enquanto a feminina foi de 399 ml / seg. Para o PFE, a maior correlação foi observada com a ASC seguida de altura, peso e idade, enquanto o IMC apresentou o menor coeficiente de correlação. TPFE teve a melhor significância com a idade, ASC, altura e IMC. Teve menos significado com o peso. No sexo feminino, a TPFE teve a melhor significância com altura, peso, IMC e idade. CONCLUSÃO: Existem diferenças de gênero na TPFE. Portanto, equações específicas de gênero são necessárias para a estimativa da TPFE

INTRODUCTION: Peak expiratory flow rate (PEFR) is commonly used to monitor the progression of respiratory diseases as it gives good information about the status of airways. A good amount of research is going across the world to establish a local prediction equation. The joint task force of the American thoracic society and European Respiratory Society has promoted research in this regard. In India, data derived from the Caucasian population are still used for PEFR. OBJECTIVE: To verify the relationship between PEF levels and the variables age, sex, anthropometric and body surface area, and establish the regression equation for young Indian adults. METHODS: A cross-sectional observational study was conducted in 15-25 years aged 1000 subjects from the Metropolitan region of Mumbai. Pearson's correlation coefficient was used to understand the relation of anthropometric parameters and PEFR. Multivariate regression analysis was done for establishing a prediction equation (Alpha 5%). RESULTS: Age and all anthropometric parameters were correlated with PEFR. The mean PEFR of the male population was 515 ml/sec, whereas, for females, it was 399 ml/sec, for PEFR highest correlation was observed with BSA (.696) followed by weight (.667), height (.630), age (.504) whereas BMI shown lowest correlation coefficient (.445). PEFR had the best significance with age, BSA, Height, and BMI. It had less significance with weight. In females, PEFR had the best significance with Height, weight, BMI, and Age. CONCLUSION: Gender-wise differences exist in PEFR. Hence gender-specific equations are needed for the estimation of PEFR.

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This work aimed to compare pre- and post-slaughter methodologies to estimate body fat reserves in dairy goats. Twenty-six lactating Saanen goats ranging from 43.6 to 69.4 kg of body weight (BW) and from 1.84 to 2.96 of body condition score (BCS; 0-5 range) were used. Fifteen pre-slaughter and four post-slaughter measurement values were used to estimate the weight of fat in the omental (OM), mesenteric (MES), perirenal (PR), organ (ORG), carcass (CARC), and non-carcass components (NC) and total (TOT, calculated as the sum of CARC and NC) depots in goats. The pre-slaughter measurements were withers height; rump height; rump length; pelvis width; chest depth; shoulder width; heart girth; body length; sternum height; BW; BCS assessed in the lumbar (BCSl) and sternal (BCSs) regions; and fat thickness measured by ultrasound in the lumbar (FTUSl), sternal (FTUSs), and perirenal (FTUSpr) regions. The post-slaughter measurements were hot carcass weight (HCW), empty body weight (EBW), and fat thickness measured by digital caliper in the lumbar (FTDCl) and sternal (FTDCs) regions. Linear and multiple regressions were fit to data collected. BW, BCS (from lumbar and sternal regions), all somatic measurements, and fat thickness measured by ultrasound in the lumbar and sternal regions were not adequate to estimate the weight of total fat in lactating Saanen goats (R2 ≤ 0.55). The best pre-slaughter and post-slaughter estimators of OM, MES, PR, ORG, NC, and TOT fat were FTUSpr and EBW, respectively. Among pre- and post-slaughter measurements, BCSl (R2 = 0.63) and HCW (R2 = 0.82) provided the most accurate predictions of CARC fat, respectively. Multiple regression using the pre-slaughter variables FTUSpr, BW, and BCSl yielded estimates of TOT fat with an R2 = 0.92 (RSD = 1.14 kg). On the other hand, TOT fat predicted using the post-slaughter variables HCW and FTDCs had an R2 = 0.83 (RSD = 1.41 kg). These results confirm that fat reserves can be predicted in lactating Saanen goats with high precision using multiple regression equations combining in vivo measurements.

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ABSTRACT This study assessed whether the net energy (NE) system is beneficial for determining the efficiency of feed utilization in Chinese Yellow Chickens. A total of 5,600 male Chinese Yellow Chickens were assigned to eight dietary treatments (ten replicate pens per treatment and 70 chickens per pen) of differing apparent metabolizable energy (AME) and NE values. A highly significant linear correlation between dietary energy and feed conversion ratios (FCR) was observed (p 0.01). The linear regression equation between metabolizable energy (ME) and FCR was: AME=1435.5×F/G+6278.2, where R²=0.8272. The linear regression equation between NE and FCR was NE=1350.1×F/G+5340.9, and R²=0.9551. The R² of FCR (0.9551) for diets formulated using NE values was higher than the R² of FCR (0.8272) for diets prepared on the basis of the ME system. We conclude that the NE system is more accurate than the AME system for determining the energy requirements of Chinese Yellow Chickens.

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PURPOSE: To evaluate the concordance between the value of the actual maximum voluntary ventilation (MVV) and the estimated value by multiplying the forced expiratory volume in the first second (FEV1) and a different value established in the literature. METHODS: A retrospective study was conducted with healthy subjects and patients with stable chronic obstructive pulmonary disease (COPD). Five prediction formulas MVV were used for the comparison with the MVV values. Agreement between MVV measured and MVV obtained from five prediction equations were studied. FEV1 values were used to estimate MVV. Correlation and agreement analysis of the values was performed in two groups using the Pearson test and the Bland-Altman method; these groups were one group with 207 healthy subjects and the second group with 83 patients diagnosed with COPD, respectively. RESULTS: We recruited 207 healthy subjects (105 women, age 47 ± 17 years) and 83 COPD patients (age 66 ± 6 years; 29 GOLD II, 30 GOLD III, and 24 GOLD IV) for the study. All prediction equations presented a significant correlation with the MVV value (from 0.38 to 0.86, p < 0.05) except for the GOLD II subgroup, which had a poor agreement with measured MVV. In healthy subjects, the mean difference of the value of bias (and limits of agreement) varied between -3.9% (-32.8 to 24.9%), and 27% (-1.4 to 55.3%). In COPD patients, the mean difference of value of bias (and limits of agreement) varied between -4.4% (-49.4 to 40.6%), and 26.3% (-18.3 to 70.9%). The results were similar in the subgroup analysis. CONCLUSION: The equations to estimate the value of MVV present a good degree of correlation with the real value of MVV, but they also show a poor concordance. For this reason, we should not use the estimated results as a replacement for the real value of MVV.

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Background: Oxygen uptake (VO2) evaluations by cardiopulmonary exercise test is expensive and time-consuming. Estimating VO2 based on a field test would be an alternative. Objective: To develop and validate an equation to predict VO2peak based on the modified shuttle test (MST). Methods: Cross sectional study, with 97 children and adolescents with asthma. Participants were divided in two groups: the equation group (EG), to construct the equation model of VO2peak, and the cross-validation group (VG). Each subject performed the MST twice using a portable gas analyzer. The peak VO2peak during MST was used in the equation model. The patients' height, weight, gender, and distance walked (DW) during MST were tested as independent variables. Results: The final model [-0.457 + (gender × 0.139) + (weight × 0.025) + (DW × 0.002)] explained 87% of VO2peak variation. The VO2peak predicted was similar to VO2peak measured by gas analyzer (1.9 ± 0.5 L/min and 2.0 ± 0.5 L/min, respectively) (p = 0.67), and presented significant ICC 0.91 (IC95% 0.77 to 0.96); p < 0.001. The Bland-Altman analysis showed low bias (-0.15 L/min) and limits of agreement (-0.65 to 0.35 L/min). There was no difference in DW between EG (760 ± 209 m) and VG (731 ± 180 m), p = 0.51. Conclusion: The developed equation adequately predicts VO2peak in pediatric patients with asthma.

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OBJECTIVE: To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. STUDY DESIGN: Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. RESULTS: Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m) - (0.732 × body mass indexkg/m2) (R2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R2p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). CONCLUSIONS: This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings.

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Data from 292 hot fat trimmed carcasses derived from Costa Rican cattle were used to predict yield of fabricated boneless, closely-trimmed, high-valued cuts (BVS, by weight and percentage); yield of total saleable product (TSP, by weight and percentage); and percentage yields of bone and trim fat. Backfat thickness was not significantly associated with weight of BVS or TSP. Carcass weight explained 93.7% and 95.9% of the total variation in weight of BVS and TSP, respectively. Equations for predicting percentage yields of BVS and TSP showed little predictive efficacy. Conversely, the greater precision of the equations selected to predict the quantity (kg) of BVS or TSP, offers a practical alternative of using them in hot fat trimmed carcasses.

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BACKGROUND: Little information is available on the validity of anthropometry or impedance-based equations for prediction of total body water (TBW) in African children. This study was designed to validate and develop equations to predict total body water in Cameroonian children. METHODS: TBW was measured by deuterium dilution in 102 children between 24 and 60 months of age and compared with the ones predicted by 5 anthropometric and 7 BIA equations. Multiple linear regression analysis was used to develop prediction equations for TBW from anthropometric parameters. RESULTS: Unacceptable discrepancies in the estimates of TBW at individual level were noted with all the equations tested. The following new anthropometry and BIA equations for the estimation of TBW were respectively developed: TBW = 6.488 + 0.434 × sex−0.039 × age + 0.670 × weight−0.081 × MUAC (cm)−0.372 × BMI (adjustedR2= 0.71,RMSE = 3.6), and TBW =−6.206 + 0.0037 × height2/Z−0.041 × age + 0.265 × weight + 0.1214 × height (adjustedR2=0.68, RMSE = 1.4). The cross-validation procedures revealed that the predicted values of TBW compared with measured values are accurate at a group level. CONCLUSION: The current published anthropometric and BIA equations are invalid for the estimation of TBW in Cameroonian preschool children. The newly developed anthropometry or BIA prediction equations are valid for use in Cameroonian children aged 24­60 months

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Rectal temperature (RT) is the foremost physiological variable indicating if an animal is suffering hyperthermia. However, this variable is traditionally measured by invasive methods, which may compromise animal welfare. Models to predict RT have been developed for growing pigs and lactating dairy cows, but not for pregnant heat-stressed ewes. Our aim was to develop a prediction equation for RT using non-invasive physiological variables in pregnant ewes under heat stress. A total of 192 records of respiratory frequency (RF) and hair coat temperature in various body regions (i.e., head, rump, flank, shoulder, and belly) obtained from 24 Katahdin × Pelibuey pregnant multiparous ewes were collected during the last third of gestation (i.e., d 100 to lambing) with a 15 d sampling interval. Hair coat temperatures were taken using infrared thermal imaging technology. Initially, a Pearson correlation analysis examined the relationship among variables, and then multiple linear regression analysis was used to develop the prediction equations. All predictor variables were positively correlated (P<0.01; r=0.59-0.67) with RT. The adjusted equation which best predicted RT (P<0.01; Radj(2)=56.15%; CV=0.65%) included as predictors RF and head and belly temperatures. Comparison of predicted and observed values for RT indicates a suitable agreement (P<0.01) between them with moderate accuracy (Radj(2)=56.15%) when RT was calculated with the adjusted equation. In general, the final equation does not violate any assumption of multiple regression analysis. The RT in heat-stressed pregnant ewes can be predicted with an adequate accuracy using non-invasive physiologic variables, and the final equation was: RT=35.57+0.004 (RF)+0.067 (heat temperature)+0.028 (belly temperature).

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A set of prediction equations to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of individual ingredients and diets used in the poultry feed industry was evaluated. The AMEn values of three energy ingredients (maize, sorghum and defatted maize germ meal), four protein ingredients (soybean meal, maize gluten meal 60% crude protein, integral micronized soy and roasted whole soybean) and four diets (three containing four feedstuffs, complex diets, and one containing only corn-soybean meal, basal diet) were determined using a metabolism assay with male broilers from 1 to 7, 8 to 21, 22 to 35, and 36 to 42 days old. These values were compared to the AMEn values presented in the tables of energy composition or estimated by equation predictions based on chemical composition data of feedstuffs. In general, the equation predictions more precisely estimated the AMEn of feedstuffs when compared to the tables of energy composition. The equation AMEn (dry matter [DM] basis) = 4,164.187+51.006 ether extract (% in DM basis)-197.663 ash-35.689 crude fiber (% in DM basis)-20.593 neutral detergent fiber (% in DM basis) (R(2) = 0.75) was the most applicable for the prediction of the energy values of feedstuffs and diets used in the poultry feed industry.

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OBJECTIVE: In the United States of America, 6.2 million individuals are using elliptical motion trainers in fitness centres. However, graded exercise test protocols to estimate peak oxygen consumption (VO2peak) using elliptical motion trainers have not been developed for the general population. METHODS: Fifty-nine subjects (mean age: 23.5 ± 4.1 years) were randomly divided into a validation (VAL: n = 39) or cross-validation (XVAL: n = 20) group. Peak oxygen consumption (ml×kg-1×min-1) was measured via indirect calorimetry on an elliptical motion trainer for both groups. Subjects exercised at 150 strides×min-1 against a resistance of four and a crossramp of 8%. The resistance was increased every two minutes by two units until exhaustion. For the VAL group, a stepwise regression analysis was used to predict VO2peak from resistance, maximal heart rate (HRmax), body mass index (BMI), height and gender (female = 0, male = 1). RESULTS: The prediction equation derived from this study was VO2peak (ml·kg-1·min-1) = 187.39403 + 12.97271 (gender) - 1.45311 (height) - 1.21604 (BMI) - 0.19613 (HRmax) + 1.57093 (resistance) (R² = 0.76, SEE = 4.47, p < 0.05). Using this equation, the predicted VO2peak of the XVAL group was 45.18 ± 6.42 ml·kg-1×min-1, while the measured VO2peak was 43.55 ± 6.23 ml·kg-1×min-1 CONCLUSION: No significant difference was found between the measured and predicted VO2peak in the XVAL group. Therefore, it appears this protocol and equation will allow individuals to accurately estimate their VO2peak without using direct calorimetry. However, future studies should investigate the validity of this protocol with diverse populations.

OBJETIVO: En los Estados Unidos de América, 6.2 millones de personas están utilizando actualmente entrenadores de movimiento elíptico en los gimnasios. Sin embargo, no se han desarrollado protocolos de pruebas de ejercicios graduados para la población general, con el fin de calcular el consumo máximo de oxígeno (VO2máx) usando entrenadores elípticos. MÉTODOS: Cincuenta y nueve sujetos (edad media: 23.5 ± 4.1 años) fueron divididos aleatoriamente en un grupo de validación (VAL: n = 39) y un grupo de validación cruzada (XVAL: n = 20) respectivamente. El consumo de oxígeno máximo (ml×kg-1×min-1) se midió mediante calorimetría indirecta en un entrenador de movimiento elíptico para ambos grupos. Los sujetos ejercitaron 150 pasos por minuto frente a una resistencia de cuatro y una rampa cruz de 8%. La resistencia fue aumentada cada dos minutos en dos unidades hasta la extenuación. Para el grupo VAL, se utilizó un análisis de regresión paso a paso para predecir el VO2máx de la resistencia, la frecuencia cardíaca máxima (FCmáx), el índice de masa corporal (IMC), la altura y el género (mujer = 0, hombre = 1). RESULTADOS: La ecuación de predicción derivada de este estudio fue VO2máx (ml·kg-1 min-1) = 187.39403 + 12.97271 (sexo) - 1.45311 (altura) - 1.21604 (IMC) - 0.19613 (FCmáx) + 1.57093 (resistencia) [R2 = 0.76, SEE = 4.47, p < 0.05]. Usando esta ecuación, la predicción en VO2máx para el grupo XVAL fue 45.18 ± 6.42 ml·kg-1 min-1, mientras que la medición de VO2máx fue 43.55 ± 6.23 ml·kg-1×min-1. CONCLUSIÓN: No se hallaron diferencias significativas entre los valores de la medición y la predicción de VO2máx en el grupo XVAL. Por lo tanto, se evidencia que este protocolo y esta ecuación permitirán a las personas calcular con precisión su VO2máx sin utilizar calorimetría directa. Sin embargo, los estudios futuros deben investigar la validez de este protocolo con distintas poblaciones.

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O presente estudo tem como objetivos: a) verificar a concordância entre os métodos da impedância bioelétrica (BIA) e da absortometria radiológica de dupla energia (DEXA), para a estimativa da massa muscular esquelética (MME); b) analisar o poder preditivo das variáveis antropométricas e de BIA para predição da MME em idosos. Foram avaliados 60 homens idosos (61 a 80 anos), residentes na região Sul do Brasil. Mensuraram-se as variáveis antropométricas (massa corporal e estatura), as variáveis de resistência e hidratação dos tecidos livres de gordura foram medidas pela técnica da BIA tetrapolar (Biodinamics - BF-310), realizou-se também um scan de corpo inteiro através da DEXA (LUNAR PRODIGY DF + 14319 Radiation e software 7.52.002 DPX-L). A diferença entre os métodos foi verificada pelo teste “t”, análise dos resíduos e o coeficiente de correlação. O valor preditivo das variáveis antropométricas e de BIA foi verificado pela regressão Linear Múltipla. Observou-se que a BIA superestimou em média 0,6 kg (dp= 1,59) a MME, quando comparada com a DEXA, contudo não houve diferença estatística (p<0,05). Foi observada uma forte relação entre os métodos (r=0,90; p<0,01). A análise de regressão demonstrou que a variável EST²/R explica 86 por cento da variação da MME, quando ajustada para massa corporal e idade e esta relação é independente das variáveis de gordura corporal, hidratação dos tecidos livres de gordura e IMC. Assim, nota-se que o método da BIA, aqui testado, é válido para a estimativa da MME em homens idosos e seus valores podem ser melhor preditos pelo modelo de regressão proposto a partir da medida de EST²/R ajustada para a massa corporal e idade.

The aim of the present study was twofold: a) to determine the agreement between bioelectrical impedance analysis (BIA) and dual energy X-ray absorptiometry (DEXA) for the estimation of skeletal muscle mass (SMM), and b) to analyze the predictive power of anthropometric variables and BIA for the prediction of SMM in the elderly. Sixty elderly men (61 to 80 years) from the southern region of Brazil were studied. Anthropometric variables (body weight and height) were measured, the resistance and hydration of fat-free tissues variables were determined by tetrapolar BIA (BF-310, Biodynamics). A whole body DEXA scan was also performed (Lunar Prodigy DF + 14319 Radiation and 7.52.002 DPX-L software). Differences between methods were analyzed using the t-test, analysis of residues and correlation coefficient. The predictive value of the anthropometric variables and BIA was evaluated by multiple linear regression. BIA overestimated SMM on average by 0.60 kg (sd=1.59) when compared to DEXA, however, no statistical difference was observed (p>0.05). There was a strong correlation between methods (r=0.90; p<0.01). Regression analysis demonstrated that the Ht²/R variable explained 86 percent of the variation in SMM when adjusted for body weight and age, and this relationship did not depend on body fat, hydration of fat-free tissues or BMI. Thus, BIA as tested here is a valid method for the estimation of SMM in elderly men and its values can be best predicted using the regression model proposed, which included Ht²/R adjusted for body weight and age.

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RESUMEN

O objetivo do presente estudo foi desenvolver uma equação para predição da carga de uma repetição máxima (1RM) em homens e mulheres, usando exclusivamente as características antropométricas. Participaram deste estudo 44 jovens de baixo risco, com experiência em treinamento de força, sendo 22 do sexo masculino (23 ± 4 anos, 76,6 ± 12,7kg, 173,9 ± 5,5cm, 11 ± 4,5 por cento de gordura) e 22 do feminino (22 ± 4 anos, 54 ± 6,0kg, 161 ± 5,8cm, 18 ± 2,2 por cento de gordura). Inicialmente, eles passaram por uma avaliação antropométrica seguida de um teste de 1RM de familiarização no exercício de desenvolvimento, que foi repetido após 48h. A repetibilidade do teste de 1RM foi testada pelo Wilcoxon matched paired test. Finalmente, a carga de 1RM foi modelada em função das variáveis antropométricas por regressão linear múltipla (forward stepwise) usando como critério de corte das variáveis independentes deltar² < 0,01. A confiabilidade dos modelos foi expressa pela análise de Bland e Altman. Adotou-se em todos os testes alfa = 0,05. Não se registraram diferenças entre teste e reteste, resultando em 44,6 ± 13,2kg e 12,2 ± 3,2kg nos indivíduos do sexo masculino (SM) e feminino (SF), respectivamente. Além das variáveis antropométricas, incluiu-se aos modelos o tempo de experiência em treinamento de força. No SM, o modelo resultou em 84 por cento da variância explicada, com erro padrão equivalente a 12 por cento. Por outro lado, no SF, a capacidade preditiva do modelo obtido foi mais fraca, resultando em 56 por cento da variância explicada e erro padrão equivalente a 20 por cento. Em conclusão, os modelos obtidos mostraram adequada confiabilidade, de forma que podem ser utilizados como ferramentas para predição da carga de 1RM.

The goal of the present study was to develop an equation for predicting the workload of one maximal repetition (1RM) in women and men, based exclusively on anthropometrical characteristics. Forty-four low-risk and experienced in strength training young subjects, being 22 male (23 ± 4 years, 76.6 ± 12.7 kg, 173.9 ± 5.5 cm, 11 ± 4.5 percent of body fat) and 22 female (22 ± 4 years, 54 ± 6.0 kg, 161 ± 5.8 cm, 18 ± 2.2 percent of body fat) volunteered for this study. All subjects were submitted to an anthropometrical evaluation followed by a 1RM familiarization test (shoulder press), which was repeated after 48h. The repeatability was tested using Wilcoxon Matched paired test. Finally, the 1RM workload was modeled in relation to the anthropometrical variables through multiple linear regression (forward stepwise) using as cutoff criteria for the independent variables deltar² < 0.01. The models reliability was expressed by the Bland and Altman analysis. All tests assumed alpha = 0.05. No significant differences were recorded between the two tests, resulting 44.6 ± 13.2 kg and 12.2 ± 3.2kg, for male (MS) and female (FS) subjects respectively. The time of practice in strength training was also included in the models. The model resulted in 84 percent of explained variance and a standard error of 12 percent for the MS. On the other hand, for the FS the predictive capacity was weaker than for = the MS, resulting in 56 percent of the explained variance and a standard error of 20 percent. In conclusion, the obtained models showed acceptable reliability so that they can be currently used as a tool for predicting the 1RM workload.

El objetivo del presente estudio ha sido desarrollar una ecuación para predecir la carga de una repetición máxima (1RM) en hombres y mujeres, usando exclusivamente las características antropométricas. Participaron de este estudio 44 jóvenes de bajo riesgo, con experiencia en entrenamiento de fuerza, 22 del sexo masculino (23 ± 4 años, 76,6 ± 12,7 kg, 173,9 ± 5,5 cm, 11 ± 4,5 por ciento de grasa) y 22 del sexo femenino (22 ± 4 años, 54 ± 6,0 kg, 161 ± 5,8 cm, 18 ± 2,2 por ciento de grasa). Al inicio, estos pasaron por una evaluación antropométrica seguida de un test de 1RM de familiarización en el ejercicio en desarrollo, que fue repetido después de 48 h. La repetibilidad del test de 1RM fue probada por Wilcoxon matched paired test. Finalmente la carga de 1RM fue modelada en función de las variables antropométricas por regresión lineal múltiple (forward stepwise) usando como criterio de aglomeración de las variables independientes deltar² < 0,01. La confiabilidad de los modelos se expresó por el análisis de Bland y Altman. En todos los tests se adoptó alfa = 0,05. No se registraron diferencias entre el test y el retest, resultando en 44,6 ± 13,2 kg y 12,2 ± 3,2kg en los individuos del sexo masculino (SM) y femenino (SF), respectivamente. Fuera de las variables antropométricas, se incluyó a los modelos el tiempo de experiencia en la actividad de fuerza. En el SM, el modelo resultó en 84 por ciento de la varianza explicada, con un error padrón equivalente a 12 por ciento. Por otro lado, en el SF, la capacidad predictiva del modelo obtenido no fue tan eficaz, resultando en 56 por ciento de la varianza explicada y un error padrón equivalente a 20 por ciento. En conclusión, los modelos obtenidos mostraron adecuada confiabilidad, de forma que pueden ser utilizados como herramientas para predecir la carga de 1RM.

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