964 resultados para body weight at slaughtering


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We estimated genetic changes in body and carcass weight traits in a giant freshwater prawn (GFP) (Macrobrachium rosenbergii) population selected for increased body weight at harvest in Vietnam. The data set consisted of 18,387 individual body and 1730 carcass weight records, as well as full pedigree information collected over four generations. Average selection response (per generation) in body weight at harvest (transformed to square root) estimated as the difference between the Selection line and the Control group was 7.4% calculated from least squares mean (LSMs), 7.0% from estimated breeding values (EBVs) and 4.4% calculated from EBVs between two consecutive generations. Favorable correlated selection responses (estimated from LSMs) were found for other body traits including: total length, cephalothorax length, abdominal length, cephalothorax width, and abdominal width (12.1%, 14.5%, 10.4%, 15.5% and 13.3% over three selection generations, respectively). Data in the second generation of selection showed positive correlated responses for carcass weight traits including: abdominal weight, exoskeleton-off weight, and telson-off weight of 8.8%, 8.6% and 8.8%, respectively. We conclude that body weight at harvest responded well to the application of combined (between and within) family selection and correlated responses in carcass weight traits were favorable.

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BACKGROUND/OBJECTIVE: To investigate the extent of baseline psychosocial characterisation of subjects in published dietary randomised controlled trials (RCTs) for weight loss. SUBJECTS/METHODS: Systematic review of adequately sized (nX10) RCTs comprising X1 diet-alone arm for weight loss were included for this systematic review. More specifically, trials included overweight (body mass index 425 kg/m2) adults, were of duration X8 weeks and had body weight as the primary outcome. Exclusion criteria included specific psychological intervention (for example, Cognitive Behaviour Therapy (CBT)), use of web-based tools, use of supplements, liquid diets, replacement meals and very-low calorie diets. Physical activity intervention was restricted to general exercise only (not supervised or prescribed, for example, VO2 maximum level). RESULTS: Of 176 weight-loss RCTs published during 2008–2010, 15 met selection criteria and were assessed for reported psychological characterisation of subjects. All studies reported standard characterisation of clinical and biochemical characteristics of subjects. Eleven studies reported no psychological attributes of subjects (three of these did exclude those taking psychoactive medication). Three studies collected data on particular aspects of psychology related to specific research objectives (figure scale rating, satiety and quality-of-life). Only one study provided a comprehensive background on psychological attributes of subjects. CONCLUSION: Better characterisation in behaviour-change interventions will reduce potential confounding and enhance generalisability of such studies.

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Background & aims Depression has a complex association with cardiometabolic risk, both directly as an independent factor and indirectly through mediating effects on other risk factors such as BMI, diet, physical activity, and smoking. Since changes to many cardiometabolic risk factors involve behaviour change, the rise in depression prevalence as a major global health issue may present further challenges to long-term behaviour change to reduce such risk. This study investigated associations between depression scores and participation in a community-based weight management intervention trial. Methods A group of 64 overweight (BMI > 27), otherwise healthy adults, were recruited and randomised to follow either their usual diet, or an isocaloric diet in which saturated fat was replaced with monounsaturated fat (MUFA), to a target of 50% total fat, by adding macadamia nuts to the diet. Subjects were assessed for depressive symptoms at baseline and at ten weeks using the Beck Depression Inventory (BDI-II). Both control and intervention groups received advice on National Guidelines for Physical Activity and adhered to the same protocol for food diary completion and trial consultations. Anthropometric and clinical measurements (cholesterol, inflammatory mediators) also were taken at baseline and 10 weeks. Results During the recruitment phase, pre-existing diagnosed major depression was one of a range of reasons for initial exclusion of volunteers from the trial. Amongst enrolled participants, there was a significant correlation (R = −0.38, p < 0.05) between BDI-II scores at baseline and duration of participation in the trial. Subjects with a baseline BDI ≥10 (moderate to severe depression symptoms) were more likely to dropout of the trial before week 10 (p < 0.001). BDI-II scores in the intervention (MUFA) diet group decreased, but increased in the control group over the 10-week period. Univariate analysis of variance confirmed these observations (adjusted R2 = 0.257, p = 0.01). Body weight remained static over the 10-week period in the intervention group, corresponding to a relative increase in the control group (adjusted R2 = 0.097, p = 0.064). Conclusions Depression symptoms have the potential to affect enrolment in and adherence to dietbased risk reduction interventions, and may consequently influence the generalisability of such trials. Depression scores may therefore be useful for characterising, screening and allocating subjects to appropriate treatment pathways.

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It is often reported that females lose less body weight than males do in response to exercise. These differences are suggested to be a result of females exhibiting a stronger defense of body fat and a greater compensatory appetite response to exercise than males do. Purpose This study aimed to compare the effect of a 12-wk supervised exercise program on body weight, body composition, appetite, and energy intake in males and females. Methods A total of 107 overweight and obese adults (males = 35, premenopausal females = 72, BMI = 31.4 ± 4.2 kg·m−2, age = 40.9 ± 9.2 yr) completed a supervised 12-wk exercise program expending approximately 10.5 MJ·wk−1 at 70% HRmax. Body composition, energy intake, appetite ratings, RMR, and cardiovascular fitness were measured at weeks 0 and 12. Results The 12-wk exercise program led to significant reductions in body mass (males [M] = −3.03 ± 3.4 kg and females [F] = −2.28 ± 3.1 kg), fat mass (M = −3.14 ± 3.7 kg and F = −3.01 ± 3.0 kg), and percent body fat (M = −2.45% ± 3.3% and F = −2.45% ± 2.2%; all P < 0.0001), but there were no sex-based differences (P > 0.05). There were no significant changes in daily energy intake in males or females after the exercise intervention compared with baseline (M = 199.2 ± 2418.1 kJ and F = −131.6 ± 1912.0 kJ, P > 0.05). Fasting hunger levels significantly increased after the intervention compared with baseline values (M = 11.0 ± 21.1 min and F = 14.0 ± 22.9 mm, P < 0.0001), but there were no differences between males and females (P > 0.05). The exercise also improved satiety responses to an individualized fixed-energy breakfast (P < 0.0001). This was comparable in males and females. Conclusions Males and premenopausal females did not differ in their response to a 12-wk exercise intervention and achieved similar reductions in body fat. When exercise interventions are supervised and energy expenditure is controlled, there are no sex-based differences in the measured compensatory response to exercise.

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Body composition of 292 males aged between 18 and 65 years was measured using the deuterium oxide dilution technique. Participants were divided into development (n=146) and cross-validation (n=146) groups. Stature, body weight, skinfold thickness at eight sites, girth at five sites, and bone breadth at four sites were measured and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-stature ratio (WSR) calculated. Equations were developed using multiple regression analyses with skinfolds, breadth and girth measures, BMI, and other indices as independent variables and percentage body fat (%BF) determined from deuterium dilution technique as the reference. All equations were then tested in the cross-validation group. Results from the reference method were also compared with existing prediction equations by Durnin and Womersley (1974), Davidson et al (2011), and Gurrici et al (1998). The proposed prediction equations were valid in our cross-validation samples with r=0.77- 0.86, bias 0.2-0.5%, and pure error 2.8-3.6%. The strongest was generated from skinfolds with r=0.83, SEE 3.7%, and AIC 377.2. The Durnin and Womersley (1974) and Davidson et al (2011) equations significantly (p<0.001) underestimated %BF by 1.0 and 6.9% respectively, whereas the Gurrici et al (1998) equation significantly (p<0.001) overestimated %BF by 3.3% in our cross-validation samples compared to the reference. Results suggest that the proposed prediction equations are useful in the estimation of %BF in Indonesian men.

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Background: While weight gain following breast cancer is considered common, results supporting these findings are dated. This work describes changes in body weight following breast cancer over 72 months, compares weight with normative data and explores whether weight changes over time are associated with personal, diagnostic, treatment or behavioral characteristics. Methods: A population-based sample of 287 Australian women diagnosed with early-stage invasive breast cancer was assessed prospectively at six, 12, 18 and 72 months post-surgery. Weight was clinically measured and linear mixed models were used to explore associations between weight and participant characteristics (collected via self-administered questionnaire). Those with BMI changes of one or more units were considered to have experienced clinically significant changes in weight. Results: More than half (57%) of participants were overweight or obese at 6 months post-surgery, and by 72 months post-surgery 68% of women were overweight or obese. Among those who gained more weight than age-matched norms, clinically significant weight gain between 6 and 18 months and 6 and 72 months post-surgery was observed in 24% and 39% of participants, respectively (median [range] weight gain: 3.9kg [2.0-11.3kg] and 5.2kg [0.6-28.7], respectively). Clinically-significant weight losses were observed in up to 24% of the sample (median [range] weight loss between 6 and 72 months post-surgery: -6.4kg [-1.9--24.6kg]). More extensive lymph node removal, being treated on the non-dominant side, receiving radiation therapy and lower physical activity levels at 6 months was associated with higher body weights post-breast cancer (group differences >3kg; all p<0.05). Conclusions: While average weight gain among breast cancer survivors in the long-term is small, subgroups of women experience greater gains linked with adverse health and above that experienced by age-matched counterparts. Weight change post-breast cancer is a contemporary public health issue and the integration of healthy weight education and support into standard breast cancer care has potential to significantly improve the length and quality of cancer survivorship.

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OBJECTIVE: To evaluate the effectiveness of a telephone-delivered behavioral weight loss and physical activity intervention targeting Australian primary care patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: Pragmatic randomized controlled trial of telephone counseling (n = 151) versus usual care (n = 151). Reported here are 18-month (end-of-intervention) and 24-month (maintenance) primary outcomes of weight, moderate-to-vigorous-intensity physical activity (MVPA; via accelerometer), and HbA1c level. Secondary outcomes include dietary energy intake and diet quality, waist circumference, lipid levels, and blood pressure. Data were analyzed via adjusted linear mixed models with multiple imputation of missing data. RESULTS: Relative to usual-care participants, telephone counseling participants achieved modest, but significant, improvements in weight loss (relative rate [RR] -1.42% of baseline body weight [95% CI -2.54 to -0.30% of baseline body weight]), MVPA (RR 1.42 [95% CI 1.06-1.90]), diet quality (2.72 [95% CI 0.55-4.89]), and waist circumference (-1.84 cm [95% CI -3.16 to -0.51 cm]), but not in HbA1c level (RR 0.99 [95% CI 0.96-1.02]), or other cardio-metabolic markers. None of the outcomes showed a significant change/deterioration over the maintenance period. However, only the intervention effect for MVPA remained statistically significant at 24 months. CONCLUSIONS: The modest improvements in weight loss and behavior change, but the lack of changes in cardio-metabolic markers, may limit the utility, scalability, and sustainability of such an approach.

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A single-generation dataset consisting of 1,730 records from a selection program for high growth rate in giant freshwater prawn (GFP, Macrobrachium rosenbergii) was used to derive prediction equations for meat weight and meat yield. Models were based on body traits [body weight, total length and abdominal width (AW)] and carcass measurements (tail weight and exoskeleton-off weight). Lengths and width were adjusted for the systematic effects of selection line, male morphotypes and female reproductive status, and for the covariables of age at slaughter within sex and body weight. Body and meat weights adjusted for the same effects (except body weight) were used to calculate meat yield (expressed as percentage of tail weight/body weight and exoskeleton-off weight/body weight). The edible meat weight and yield in this GFP population ranged from 12 to 15 g and 37 to 45 %, respectively. The simple (Pearson) correlation coefficients between body traits (body weight, total length and AW) and meat weight were moderate to very high and positive (0.75–0.94), but the correlations between body traits and meat yield were negative (−0.47 to −0.74). There were strong linear positive relationships between measurements of body traits and meat weight, whereas relationships of body traits with meat yield were moderate and negative. Step-wise multiple regression analysis showed that the best model to predict meat weight included all body traits, with a coefficient of determination (R 2) of 0.99 and a correlation between observed and predicted values of meat weight of 0.99. The corresponding figures for meat yield were 0.91 and 0.95, respectively. Body weight or length was the best predictor of meat weight, explaining 91–94 % of observed variance when it was fitted alone in the model. By contrast, tail width explained a lower proportion (69–82 %) of total variance in the single trait models. It is concluded that in practical breeding programs, improvement of meat weight can be easily made through indirect selection for body trait combinations. The improvement of meat yield, albeit being more difficult, is possible by genetic means, with 91 % of the variation in the trait explained by the body and carcass traits examined in this study.

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Malnutrition is common in end-stage liver disease, but a correction after transplantation is expected. Body cell mass (BCM) assessment using total body potassium (TBK) measurements is considered the gold standard for assessing nutritional status. The aim of this study was to examine the BCM and, therefore, nutritional status of long-term survivors after childhood liver transplantation. © 2014 American Association for the Study of Liver Diseases.

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Objective: To develop bioelectrical impedance analysis (BIA) equations to predict total body water (TBW) and fat-free mass (FFM) of Sri Lankan children. Subjects/Methods: Data were collected from 5- to 15-year-old healthy children. They were randomly assigned to validation (M/F: 105/83) and cross-validation (M/F: 53/41) groups. Height, weight and BIA were measured. TBW was assessed using isotope dilution method (D2 O). Multiple regression analysis was used to develop preliminary equations and cross-validated on an independent group. Final prediction equation was constructed combining the two groups and validated by PRESS (prediction of sum of squares) statistics. Impedance index (height2/impedance; cm2/Ω), weight and sex code (male = 1; female = 0) were used as variables. Results: Independent variables of the final prediction equation for TBW were able to predict 86.3% of variance with root means-squared error (RMSE) of 2.1l. PRESS statistics was 2.1l with press residuals of 1.2l. Independent variables were able to predict 86.9% of variance of FFM with RMSE of 2.7 kg. PRESS statistics was 2.8 kg with press residuals of 1.4 kg. Bland Altman technique showed that the majority of the residuals were within mean bias±1.96 s.d. Conclusions: Results of this study provide BIA equation for the prediction of TBW and FFM in Sri Lankan children. To the best of our knowledge there are no published BIA prediction equations validated on South Asian populations. Results of this study need to be affirmed by more studies on other closely related populations by using multi-component body composition assessment.

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Background: Better understanding of body composition and energy metabolism in pediatric liver disease may provide a scientific basis for improved medical therapy aimed at achieving optimal nutrition, slowing progression to end-stage liver disease (ESLD), and improving the outcome of liver transplantation. Methods: Twenty-one children less than 2 years of age with ESLD awaiting liver transplantation and 15 healthy, aged-matched controls had body compartment analysis using a four compartment model (body cell mass, fat mass, extracellular water, and extracellular solids). Subjects also had measurements of resting energy expenditure (REE) and respiratory quotient (RQ) by indirect calorimetry. Nine patients and 15 control subjects also had measurements of total energy expenditure (TEE) using doubly labelled water. Results: Mean weights and heights were similar in the two groups. Compared with control subjects, children with ESLD had higher relative mean body cell mass (33 ± 2% vs 29 ± 1% of body weight, P < 0.05), but had similar fat mass, extracellular water, and extracellular solid compartments (18% vs 20%, 41% vs 38%, and 7% vs 13% of body weight respectively). Compared with control subjects, children with ESLD had 27% higher mean REE/body weight (0.285 ± 0.013 vs 0.218. ± 0.013 mJ/kg/24h, P < 0.001), 16% higher REE/unit cell mass (P < 0.05); and lower mean RQ (P < 0.05). Mean TEE of patients was 4.70 ± 0.49 mJ/24h vs 3.19 ± 0.76 in controls, (P < 0.01). Conclusions: In children, ESLD is a hypermetabolic state adversely affecting the relationship between metabolic and non-metabolic body compartments. There is increased metabolic activity within the body cell mass with excess lipid oxidation during fasting and at rest. These findings have implications for the design of appropriate nutritional therapy.

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Patients with anorexia nervosa (AN) have low body weight, depleted fat stores, and reduced muscle mass. Both total body potassium (TBK) and bioelectrical impedance analysis (BIA) have been used to measure the body composition of these patients.1–4 Whereas TBK accurately measures body cell mass, the metabolically active compartment of the body, whole body potassium counters are expensive and not readily available. The purpose of this study was to investigate the potential of multiple frequency BIA (MFBIA) to monitor changes in body compartments in patients with AN.

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Malnutrition is a common problem in children with end-stage liver disease (ESLD), and accurate assessment of nutritional status is essential in managing these children. In a retrospective study, we compared nutritional assessment by anthropometry with that by body composition. We analyzed all consecutive measurements of total body potassium (TBK, n = 186) of children less than 3 years old with ESLD awaiting transplantation found in our database. The TBK values obtained by whole body counting of 40K were compared with reference TRK values of healthy children. The prevalence of malnutrition, as assessed by weight (weight Z score < -2) was 28%, which was significantly lower (chi-square test, p < 0.0001) than the prevalence of malnutrition (76%) assessed by TBK (< 90% of expected TRK for age). These results demonstrated that body weight underestimated the nutritional deficit and stressed the importance of measuring body composition as part of assessing nutritional status of children with ESLD.

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Objective: To investigate measures aimed at defining the nutritional status of cystic fibrosis (CF) populations, this study compared standard anthropometric measurements and total body potassium (TBK) as indicators of malnutrition. Methods: Height, weight, and TBK measurements of 226 children with CF from Royal Children's Hospital, Brisbane, Australia, were analyzed. Z scores for height for age, weight for age, and weight for height were analyzed by means of the National Centre for Health Statistics reference. TBK was measured by means of whole body counting and compared with predicted TBK for age. Two criteria were evaluated with respect to malnutrition: (1) a z score < -2.0 and (2) a TBK for age <80% of predicted. Results: Males and females with CF had lower mean height-for-age and weight-for-age z scores than the National Centre for Health Statistics reference (P < .01), but mean weight-for-height z score was not significantly different. There were no significant gender differences. According to anthropometry, only 7.5% of this population were underweight and 7.6% were stunted. However, with TBK as an indicator of nutritional status, 29.9% of males and 22.0% of females were malnourished. Conclusion: There are large differences in the percentage of patients with CF identified as malnourished depending on whether anthropometry or body composition data are used as the nutritional indicator. At an individual level, weight-based indicators are not sensitive indicators of suboptimal nutritional status in CF, significantly underestimating the extent of malnutrition. Current recommendations in which anthropometry is used as the indicator of malnutrition in CF should be revised.

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Early deficits in nutritional status that might require specific treatment and early response to nutritional therapy were studied longitudinally in 25 infants with cystic fibrosis (CF) diagnosed by neonatal screening, using anthropometric and research body composition methodology, and evaluation of pancreatic function. At the time of confirmed diagnosis (mean 5.4 weeks), body mass, length, total body fat (TBF), and total body potassium (TBK) were all significantly reduced. Following diagnosis and commencement of therapy there was a normalization of weight, length, and TBK by 6-12 months of age, indicating catch-up growth. But in some individuals the response was incomplete, and as a group, mean total body fat remained significantly lower than normal at 1 year of age. Seven of 25 (28%) were pancreatic sufficient at diagnosis, and all but one had evidence of declining pancreatic function requiring the institution of pancreatic enzyme therapy during the next 1-9 months. The median age of commencement of enzyme therapy was 10 weeks (range 5 weeks to 11 months). These longitudinal assessments emphasize the dynamic changes occurring in absorptive function, body composition, and nutritional status following neonatal diagnosis of cystic fibrosis and may reflect previously described abnormalities of energy metabolism in this age group. Abnormal body composition is evident in most CF infants following diagnosis by neonatal screening but pancreatic damage may still be evolving. We suggest that early active nutritional therapy and surveillance for changes in pancreatic function are warranted in CF infants diagnosed by neonatal screening.