817 resultados para fat percentage


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Milk yield, fat yield, and fat percentage during the first three lactations were studied using New York Holsteins that were milked twice daily over a 305-d, mature equivalent lactation. Those data were used to estimate variances from direct and maternal genetic effects, cytoplasmic effects, sire by herd interaction, and cow permanent environmental effects. Cytoplasmic line was traced to the last female ancestor using DHI records from 1950 through 1991. Records were 138,869 lactations of 68,063 cows calving from 1980 through 1991. Ten random samples were based on herd code. Samples averaged 4926 dams and 2026 cytoplasmic lines. Model also included herd-year-seasons as fixed effects and genetic covariance for direct-maternal effects. Mean estimates of the effects of maternal genetic variances and direct-maternal covariances, as fractions of phenotypic variances, were 0.008 and 0.007 for milk yield, 0.010 and 0.010 for fat yield, and 0.006 and 0.025 for fat percentage, respectively. Average fractions of variance from cytoplasmic line were 0.011, 0.008, and 0.009 for milk yield, fat yield, and fat percentage. Removal of maternal genetic effects and covariance for maternal direct effects from the model increased the fraction of direct genetic variance by 0.014, 0.021, and 0.046 for milk yield, fat yield, and fat percentage; little change in the fraction was due to cytoplasmic line. Exclusion of cytoplasmic effects from the model increased the ratio of additive direct genetic variance to phenotypic variance by less than 2%. Similarly, when sire by herd interaction was excluded, the ratio of direct genetic variance to phenotypic variance increased 1% or less.

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CONTEXT AND OBJECTIVE: Insulin resistance is a metabolic disorder commonly associated with excess body fat accumulation that may increase chronic disease risk. The present study was undertaken to evaluate the relationship between body composition and insulin resistance among obese adolescents. DESIGN AND SETTING: Cross-sectional study, at the Adolescence Center, Pediatric Department, Universidade Federal de São Paulo. METHODS: Body composition was assessed using dual-energy X-ray absorptiometry. Dietary intake was evaluated using a three-day dietary record. The biochemical evaluation comprised glucose, insulin, serum lipid, leptin and ghrelin measurements. Insulin resistance was calculated by means of the homeostasis model assessment of insulin resistance (HOMA-IR). RESULTS: Forty-nine post-pubertal obese adolescents participated in the study: 12 boys and 37 girls of mean age 16.6 (1.4) years and mean body mass index (BMI) of 35.0 (3.9) kg/m². The mean glucose, insulin and HOMA values were 90.3 (6.4) mg/dl, 16.6 (8.1) µIU/ml and 3.7 (1.9), respectively. Hyperinsulinemia and insulin resistance were observed in 40.2% and 57.1% of the subjects, respectively. Adolescents with insulin resistance had higher BMI and body trunk fat. There was a trend towards higher leptin concentration in obese individuals with insulin resistance. Insulin resistance was positively correlated with body trunk fat, BMI, body fat mass (kg), leptin and body fat percentage. Furthermore, there was a negative correlation between HOMA-IR and lean body mass. The body composition predicted 30% of the HOMA-IR levels, according to linear regression models. CONCLUSION: Body trunk fat was significantly associated with insulin resistance, demonstrating the clinical importance of abdominal obesity during adolescence.

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ABSTRACT: BACKGROUND: Although smokers tend to have a lower body-mass index than non-smokers, smoking may favour abdominal body fat accumulation. To our knowledge, no population-based studies have assessed the relationship between smoking and body fat composition. We assessed the association between cigarette smoking and waist circumference, body fat, and body-mass index. METHODS: Height, weight, and waist circumference were measured among 6,123 Caucasians (ages 35-75) from a cross-sectional population-based study in Switzerland. Abdominal obesity was defined as waist circumference>=102 cm for men and >=88 cm for women. Body fat (percent total body weight) was measured by electrical bioimpedance. Age- and sex-specific body fat cut-offs were used to define excess body fat. Cigarettes smoked per day were assessed by self-administered questionnaire. Age-adjusted means and odds ratios were calculated using linear and logistic regression. RESULTS: Current smokers (29% of men and 24% of women) had lower mean waist circumference, body fat percentage, and body-mass index compared with non-smokers. Age-adjusted mean waist circumference and body fat increased with cigarettes smoked per day among smokers. The association between cigarettes smoked per day and body-mass index was non-significant. Compared with light smokers, the adjusted odds ratio (OR) for abdominal obesity in men was 1.28 (0.78-2.10) for moderate smokers and 1.94 (1.15-3.27) for heavy smokers (P=0.03 for trend), and 1.07 (0.72-1.58) and 2.15 (1.26-3.64) in female moderate and heavy smokers, respectively (P<0.01 for trend). Compared with light smokers, the OR for excess body fat in men was 1.05 (95% CI: 0.58-1.92) for moderate smokers and 1.15 (0.60-2.20) for heavy smokers (P=0.75 for trend) and 1.34 (0.89-2.00) and 2.11 (1.25-3.57), respectively in women (P=0.07 for trend). CONCLUSION: Among smokers, cigarettes smoked per day were positively associated with central fat accumulation, particularly in women.

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BACKGROUND AND AIMS: little is known regarding the reproducibility of body fat measuring devices; hence, we assessed the between and within-device reproducibility, and the within-day variability of body fat measurements. METHODS: body fat percentage was measured twice on seventeen female students aged between 18 and 20 with a body mass index of 21.9 ± 2.5 kg/m2 (mean ± SD) using seven bipolar bioelectrical impedance devices. Each participant was also measured each hour between 7:00 and 22:00. RESULTS: the correlation between first and second measurements was very high (Spearman r between 0.985 and 1.000, p<0.001), as well as between devices (Spearman r between 0.916 and 0.991, p<0.001). Repeated measurements analysis showed no differences were between devices (p=0.59) or readings (first vs. second: p=0.74). Conversely, significant differences were found between assessment periods throughout the day, measurements made in the morning being lower than those made in the afternoon (F test for repeated values= 6.58, p<0.001). CONCLUSIONS: the between and within-device reproducibility for measuring body fat is high, enabling the use of multiple devices in a single study. Conversely, small but significant changes in body fat measurements occur during the day, urging body fat measurements to be performed at fixed times.

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Objective: to assess the between and within-device reproducibility, as well as within-day variability of body fat measurements. Methods: body fat percentage (%BF) was measured twice on seventeen female students aged between 18 and 20 with a body mass index of 21.9 22.6 kg/m2 (mean SD) using seven bipolar bioelectrical impedance devices (BF-306) according to the manufacturer's recommendations. Each student was also measured each hour between 7:00 and 22:00. Statistical analysis was conducted using a general linear model for repeated measurements. Results: the correlation between first and second measurements was very high (Pearson r between 0.985 and 1.000, p<0.001), as well as the correlation between devices (Pearson r between 0.986 and 0.999, all p<0.001). Repeated measurements analysis showed no differences were between devices (F test=0.83, p=0.59) or readings (first vs. second: F test=0.12, p=0.74). Conversely, significant differences were found between assessment periods throughout the day, measurements made in the morning being lower than those made in the afternoon. Assuming an overall daily average of 100 (based on all measurements), the values were 95.8 3.2 (mean SD) at 8:00 versus 101.3 3.0 at 20:00, corresponding to a mean change of 2.2 1.1 in %BF (F test for repeated values=6.58, p<0.001). Conclusions: the between and within-device reproducibility for measuring body fat is high, enabling the use of multiple devices in a single study. Conversely, small but significant changes in body fat measurements occur during the day, urging body fat measurements to be performed at fixed times.

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Objective: to assess the agreement between different anthropometric markers in defining obesity and the effect on the prevalence of obese subjects. Methods: population-based cross-sectional study including 3213 women and 2912 men aged 35-75 years. Body fat percentage (%BF) was assessed using electric bioimpedance. Obesity was defined using established cut-points for body mass index (BMI) and waist, and three population-defined cut-points for %BF. Between-criteria agreement was assessed by the kappa statistic. Results: in men, agreement between the %BF cut-points was significantly higher (kappa values in the range 0.78 - 0.86) than with BMI or waist (0.47 - 0.62), whereas no such differences were found in women (0.41 - 0.69). In both genders, prevalence of obesity varied considerably according to the criteria used: 17% and 24% according to BMI and waist in men, and 14% and 31%, respectively, in women. For %BF, the prevalence varied between 14% and 17% in men and between 19% and 36% in women according to the cut-point used. In the older age groups, a fourfold difference in the prevalence of obesity was found when different criteria were used. Among subjects with at least one criteria for obesity (increased BMI, waist or %BF), only one third fulfilled all three criteria and one quarter two criteria. Less than half of women and 64% of men were jointly classified as obese by the three population-defined cut-points for %BF. Conclusions: the different anthropometric criteria to define obesity show a relatively poor agreement between them, leading to considerable differences in the prevalence of obesity in the general population.

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Obesity is a key factor in the development of the metabolic syndrome (MetS), which is associated with increased cardiometabolic risk. We investigated whether obesity classification by body mass index (BMI) and body fat percentage (BF%) influences cardiometabolic profile and dietary responsiveness in 486 MetS subjects (LIPGENE dietary intervention study). Anthropometric measures, markers of inflammation and glucose metabolism, lipid profiles, adhesion molecules and haemostatic factors were determined at baseline and after 12 weeks of 4 dietary interventions (high saturated fat (SFA), high monounsaturated fat (MUFA) and 2 low fat high complex carbohydrate (LFHCC) diets, 1 supplemented with long chain n-3 polyunsaturated fatty acids (LC n-3 PUFAs)). 39% and 87% of subjects classified as normal and overweight by BMI were obese according to their BF%. Individuals classified as obese by BMI (± 30 kg/m2) and BF% (± 25% (men) and ± 35% (women)) (OO, n = 284) had larger waist and hip measurements, higher BMI and were heavier (P < 0.001) than those classified as non-obese by BMI but obese by BF% (NOO, n = 92). OO individuals displayed a more pro-inflammatory (higher C reactive protein (CRP) and leptin), pro-thrombotic (higher plasminogen activator inhibitor-1 (PAI-1)), pro-atherogenic (higher leptin/adiponectin ratio) and more insulin resistant (higher HOMA-IR) metabolic profile relative to the NOO group (P < 0.001). Interestingly, tumour necrosis factor alpha (TNF-α) concentrations were lower post-intervention in NOO individuals compared to OO subjects (P < 0.001). In conclusion, assessing BF% and BMI as part of a metabotype may help identify individuals at greater cardiometabolic risk than BMI alone.

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Objective: To assess viability of the development of percentage body fat cutoffs based on blood pressure values in Brazilian adolescents.Methods: A cross-sectional study was conducted with a sample of 358 male subjects from 8 to 18 years old. Blood pressure was measured by the oscilometric method, and body composition was measured by dual-energy X-ray absorptiometry (DXA).Results: For the identification of elevated blood pressure, these nationally developed body fat cutoffs presented relative accuracy. The cutoffs were significantly associated with elevated blood pressure [odds ratio = 5.91 (95% confidence interval: 3.54-9.86)].Conclusions: Development of national body fat cutoffs is viable, because presence of high accuracy is an indication of elevated blood pressure.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The purpose of the present study was to investigate percentage body fat (%BF) differences in three Spanish dance disciplines and to compare skinfold and bioelectrical impedance predictions of body fat percentage in the same sample. Seventy-six female dancers, divided into three groups, Classical (n=23), Spanish (n=29) and Flamenco (n=24), were measured using skinfold measurements at four sites: triceps, subscapular, biceps and iliac crest, and whole body multi-frequency bioelectrical impedance (BIA). The skin-fold measures were used to predict body fat percentage via Durnin and Womersley's and Segal, Sun and Yannakoulia equations by BIA. Differences in percent fat mass between groups (Classical, Spanish and Flamenco) were tested by using repeated measures analysis (ANOVA). Also, Pearson's product-moment correlations were performed on the body fat percentage values obtained using both methods. In addition, Bland-Altman plots were used to assess agreement, between anthropometric and BIA methods. Repeated measures analysis of variance did not found differences in %BF between modalities (p<0.05). Fat percentage correlations ranged from r= 0.57 to r=0.97 (all, p<0.001). Bland-Altman analysis revealed differences between BIA Yannakoulia as a reference method with BIA Segal (-0.35 ± 2.32%, 95%CI: -0.89to 0.18, p=0.38), with BIA Sun (-0.73 ± 2.3%, 95%CI: -1.27 to -0.20, p=0.014) and Durnin-Womersley (-2.65 ± 2,48%, 95%CI: -3.22 to -2.07, p<0.0001). It was concluded that body fat percentage estimates by BIA compared with skinfold method were systematically different in young adult female ballet dancers, having a tendency to produce underestimations as %BF increased with Segal and Durnin-Womersley equations compared to Yannakoulia, concluding that these methods are not interchangeable.

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Background: Vaspin is a newly-identified adipocytokine associated with insulin resistance (IR). Objective: The aim of this study was to investigate the correlation between plasma vaspin concentrations and IR and determine whether this association is affected by body composition, physical activity and pubertal stage in adolescents. Methods: Were studied 484 Brazilian adolescents aged 10-14 years whose anthropometric, clinical, biochemical, and lifestyle measurements were analized. We evaluated the correlation between vaspin and risk factors for IR in adolescents with normal and high body fat percentage (%BF) and did a logistic regression to calculate the odds ratio for IR according to vaspin quartiles sex specific for the sample. Results: Vaspin was positively correlated with IR in adolescents with high %BF (r = 0.23, p = 0.003). The logistic regression analysis adjusted for sex, age, BMI, and pubertal stage showed that adolescents in the 2nd (OR = 0.43, 95% CI = 0.23-0.80, p = 0.008) and 3rd (OR = 0.46, 95% CI = 0.25-0.85, p = 0.014) quartile of vaspin concentration had a lower risk for IR. When the model was adjusted for %BF and physical activity, the association remained statically significant only for adolescents in the 2nd quartile. Conclusion: Vaspin was correlated positively with risk factors associated with insulin metabolism in adolescents with high %BF. Vaspin was associated with a reduced risk of IR independently of BMI and pubertal stage and the association was influenced by body fat and physical activity in these adolescents.

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The aim was to analyse the physical growth and body composition of rhythmic gymnastics athletes relative to their level of somatic maturation. This was a cross-sectional study of 136 athletes on 23 teams from Brazil. Mass, standing height and sitting height were measured. Fat-free and fat masses, body fat percentages and ages of the predicted peak height velocity (PHV) were calculated. The z scores for mass were negative during all ages according to both WHO and Brazilian references, and that for standing height were also negative for all ages according to WHO reference but only until 12 years old according to Brazilian reference. The mean age of the predicted PHV was 12.1 years. The mean mass, standing and sitting heights, body fat percentage, fat-free mass and fat mass increased significantly until 4 to 5 years after the age of the PHV. Menarche was reached in only 26% of these athletes and mean age was 13.2 years. The mass was below the national reference standards, and the standing height was below only for the international reference, but they also had late recovery of mass and standing height during puberty. In conclusion, these athletes had a potential to gain mass and standing height several years after PHV, indicating late maturation.

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To describe the prevalence of hepatic steatosis and to assess the performance of biochemical, anthropometric and body composition indicators for hepatic steatosis in obese teenagers. Cross-sectional study including 79 adolecents aged from ten to 18 years old. Hepatic steatosis was diagnosed by abdominal ultrasound in case of moderate or intense hepatorenal contrast and/or a difference in the histogram ≥7 on the right kidney cortex. The insulin resistance was determined by the Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) index for values >3.16. Anthropometric and body composition indicators consisted of body mass index, body fat percentage, abdominal circumference and subcutaneous fat. Fasting glycemia and insulin, lipid profile and hepatic enzymes, such as aspartate aminotransferase, alanine aminotransferase, gamma-glutamyltransferase and alkaline phosphatase, were also evaluated. In order to assess the performance of these indicators in the diagnosis of hepatic steatosis in teenagers, a ROC curve analysis was applied. Hepatic steatosis was found in 20% of the patients and insulin resistance, in 29%. Gamma-glutamyltransferase and HOMA-IR were good indicators for predicting hepatic steatosis, with a cutoff of 1.06 times above the reference value for gamma-glutamyltransferase and 3.28 times for the HOMA-IR. The anthropometric indicators, the body fat percentage, the lipid profile, the glycemia and the aspartate aminotransferase did not present significant associations. Patients with high gamma-glutamyltransferase level and/or HOMA-IR should be submitted to abdominal ultrasound examination due to the increased chance of having hepatic steatosis.