177 resultados para Percent body fat
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Body mass index (BMI) is related with cardiorespiratory fitness (CRF), but less is known regarding the combined relationships between BMI and body fat (BF) on CRF. Cross-sectional study included 2361 girls and 2328 boys aged 10–18 years living in the area of Lisbon, Portugal. BMI was calculated by measuring height and weight, and obesity was assessed by international criteria. BF was assessed by bioimpedance. CRF was assessed by the 20-m shuttle run and the participants were classified as normal-to-high or low-CRF level according to Fitness gram criterion-referenced standards. The prevalence of low CRF was 47 and 39% in girls and boys, respectively. The corresponding values for the prevalence of obesity were 4.8 and 5.6% (not significant) and of excess BF of 12.1 and 25.1% (P <0.001), respectively. In both sexes, BMI and BF were inversely related with CRF: r = – 0.53 and – 0.45 for BMI and % BF, respectively, in boys and the corresponding values in girls were – 0.50 and – 0.33 (all P <0.01). When compared with a participant with normal BMI and BF, the odds ratios (95% confidence interval) for low CRF were 1.94 (1.46–2.58) for a participant with normal BMI and high BF, and 6.19 (5.02–7.63) for a participant with high BMI and high BF. The prevalence of low-CRF levels is high in Portuguese youths. BF negatively influences CRF levels among children/adolescents with normal BMI.
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Introduction Discrepancies appear in studies comparing fat oxidation between men and women during exercise (1). Therefore, this study aimed to quantitatively describe and compare whole body fat oxidation kinetics between genders during exercise using a sinusoidal model (SIN) (2). Methods Twelve men and 11 women matched for age, body mass index (23.4±0.6 kg.m-2 and 21.5±0.8 kg.m-2, respectively) and aerobic fitness [maximal oxygen uptake ( ) (58.5±1.6 mL.kg FFM-1.min-1 and 55.3±2.0 mL.kg FFM-1.min-1, respectively) and power output ( ) per kilogram of fat-free mass (FFM)] performed submaximal incremental tests (Incr) with 5-min stages and 7.5% increment on a cycle ergometer. Respiratory and HR values were averaged over the last 2 minutes of each stage. All female study participants were eumenorrheic, reported regular menstrual cycles (28.6 ± 0.8 days) and were not taking oral contraceptives (OC) or other forms of exogenous ovarian hormones. Women were studied in the early follicular phase (FP) of their menstrual cycle (between days 3 and 8, where day 1 is the first day of menses). Fat oxidation rates were determined using indirect calorimetry and plotted as a function of exercise intensity. The SIN model (2), which includes three independent variables (dilatation, symmetry, translation), was used to mathematically describe fat oxidation kinetics and to determine the intensity (Fatmax) eliciting the maximal fat oxidation (MFO). Results During Incr, women exhibited greater fat oxidation rates from 35 to 85% , MFO (6.6 ± 0.9 vs. 4.5 ± 0.3 mgkg FFM-1min-1) and Fatmax (58.1 ± 1.9 vs. 50.0 ± 2.7% ) (P<0.05) than men. While men and women showed similar global shapes of fat oxidation kinetics in terms of dilatation and symmetry (P>0.05), the fat oxidation curve tended to be shifted towards higher exercise intensities in women (rightward translation, P=0.08). Conclusion These results showed that women, eumenorrheic, not taking OC and tested in FP, have a greater reliance on fat oxidation than men during submaximal exercise, but they also indicate that this greater fat oxidation is shifted towards higher exercise intensities in women compared with men. References 1. Blaak E. Gender differences in fat metabolism. Curr Opin Clin Nutr Metab Care 4: 499-502, 2001. 2. Cheneviere X, Malatesta D, Peters EM, and Borrani F. A mathematical model to describe fat oxidation kinetics during graded exercise. Med Sci Sports Exerc 41: 1615-1625, 2009.
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The aim of this study was to determine the prevalence of low fat-free mass index (FFMI) and high and very high body fat mass index (BFMI) after lung transplantation (LTR). A total of 37 LTR patients were assessed prior to and at 1 month, 1 year and 2 years for FFM and compared to 37 matched volunteers (VOL). FFM was calculated by the Geneva equation and normalized for height (kg/m(2)). Subjects were classified as FFMI "low", <or=17.4 in men and <or=15.0 in women; BFMI "high", 5.2-8.1 in men and 8.3-11.7 in women; or "very high" >8.2 kg/m(2) in men and >11.8 kg/m(2) in women. In 23 M/14 F, body mass index (BMI) was 22.3+/-4.4 and 20.1+/-4.9 kg/m(2), respectively. The prevalence of low FFMI was 80% at 1 month and 33% at 2 years after LTR. Prevalence of very high BFMI increased and was higher in patients than VOL after LTR. The prevalence of low FFMI was high prior to and remained important 2 years after LTR, whereas BFMI was lower prior to and higher 2 years after LTR.
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BACKGROUND: Intraabdominal adipose tissue (IAAT) is the body fat depot most strongly related to disease risk. Weight reduction is advocated for overweight people to reduce total body fat and IAAT, although little is known about the effect of weight loss on abdominal fat distribution in different races. OBJECTIVE: We compared the effects of diet-induced weight loss on changes in abdominal fat distribution in white and black women. DESIGN: We studied 23 white and 23 black women, similar in age and body composition, in the overweight state [mean body mass index (BMI; in kg/m(2)): 28.8] and the normal-weight state (mean BMI: 24.0) and 38 never-overweight control women (mean BMI: 23.4). We measured total body fat by using a 4-compartment model, trunk fat by using dual-energy X-ray absorptiometry, and cross-sectional areas of IAAT (at the fourth and fifth lumbar vertebrae) and subcutaneous abdominal adipose tissue (SAAT) by using computed tomography. RESULTS: Weight loss was similar in white and black women (13.1 and 12.6 kg, respectively), as were losses of total fat, trunk fat, and waist circumference. However, white women lost more IAAT (P < 0.001) and less SAAT (P < 0.03) than did black women. Fat patterns regressed toward those of their respective control groups. Changes in waist circumference correlated with changes in IAAT in white women (r = 0.54, P < 0.05) but not in black women (r = 0.19, NS). CONCLUSIONS: Despite comparable decreases in total and trunk fat, white women lost more IAAT and less SAAT than did black women. Waist circumference was not a suitable surrogate marker for tracking changes in the visceral fat compartment in black women.
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BACKGROUND AND AIMS: There is little information regarding the effect of different definitions of obesity on nutritional epidemiology. The aim was thus to assess: (a) the values of percentage of body fat (%BF) by gender and age; (b) the prevalence of obesity according to different %BF cut-offs; and (c) the sensitivity and specificity of BMI according to different %BF cut-offs used to define obesity. METHODS: Cross-sectional study on 2494 boys and 2519 girls aged 1018 years from the Lisbon area. %BF was measured using a hand-held device. In a sub sample of 211 boys and 724 girls %BF was assessed using skin folds. RESULTS: %BF levels were higher in girls and decreased with age in both genders. Prevalence of obesity varied considerably according to the %BF cut-off used: in boys, it ranged from 4.7% (age-specific 95th percentile) to 26.5% (fixed 25% cut-off), whereas by BMI it was 5.3%. In girls, prevalence of obesity ranged from 0.4% (age-specific BMI-derived %BF values) to 25.4% (fixed 30% cut-off), whereas by BMI it was 4.7%. The specificity of BMI criteria was over 95% irrespective of the %BF cut-off used; conversely, most sensitivities were below 40%. Sensitivities over 50% were obtained for the age-specific BMI-derived %BF values in boys and the age-specific 95th %BF percentile in both genders. Using %BF derived from the skin fold measurements leads to similar results. CONCLUSIONS: Prevalence of obesity varies considerably according to the %BF cut-off used. BMI cut-offs have a low sensitivity but a high specificity. Age- and gender-specific cut-offs for %BF should be used to define pediatric obesity.
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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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OBJECTIVE: Body mass index does not discriminate body fat from fat-free mass or determine changes in these parameters with physical activity and aging. Body fat mass index (BFMI) and fat-free mass index (FFMI) permit comparisons of subjects with different heights. This study evaluated differences in body mass index, BFMI, and FFMI in physically active and sedentary subjects younger and older than 60 y and determined the association between physical activity, age, and body composition parameters in a healthy white population between ages 18 and 98 y. METHODS: Body fat and fat-free mass were determined in healthy white men (n = 3549) and women (n = 3184), between ages 18 and 98 y, by bioelectrical impedance analysis. BFMI and FFMI (kg/m2) were calculated. Physical activity was defined as at least 3 h/wk of endurance-type activity for at least 2 mo. RESULTS: Physically active as opposed to sedentary subjects were more likely to have a low BFMI (men: odds ratio [OR], 1.4; confidence interval [CI], 0.7-2.5; women: OR 1.9, CI 1.6-2.2) and less likely to have very high BFMI (men: OR, 0.2; CI, 0.1-0.2; women: OR, 0.1; CI, 0.02-0.2), low FFMI (men: OR, 0.5; CI, 0.3-0.9; women: OR, 0.7; CI, 0.6-0.9), or very high FFMI (men: OR, 0.6; CI, 0.4-0.8; women: OR, 0.7; CI, 0.5-1.0). Compared with subjects younger than 60 y, those older than 60 y were more like to have very high BFMI (men: OR, 6.5; CI, 4.5-9.3; women: OR, 14.0; CI, 9.6-20.5), and women 60 y and older were less likely to have a low BFMI (OR, 0.4; CI, 0.2-0.5). CONCLUSIONS: A clear association was found between low physical activity or age and height-normalized body composition parameters (BFMI and FFMI) derived from bioelectrical impedance analysis. Physically active subjects were more likely to have high or very high or low FFMI. Older subjects had higher body weights and BFMI.
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This study aimed to compare the effects of 2 different prior endurance exercises on subsequent whole-body fat oxidation kinetics. Fifteen men performed 2 identical submaximal incremental tests (Incr2) on a cycle ergometer after (i) a ∼40-min submaximal incremental test (Incr1) followed by a 90-min continuous exercise performed at 50% of maximal aerobic power-output and a 1-h rest period (Heavy); and (ii) Incr1 followed by a 2.5-h rest period (Light). Fat oxidation was measured using indirect calorimetry and plotted as a function of exercise intensity during Incr1 and Incr2. A sinusoidal equation, including 3 independent variables (dilatation, symmetry and translation), was used to characterize the fat oxidation kinetics and to determine the intensity (Fat(max)) that elicited the maximal fat oxidation (MFO) during Incr. After the Heavy and Light trials, Fat(max), MFO, and fat oxidation rates were significantly greater during Incr2 than Incr1 (p < 0.001). However, Δ (i.e., Incr2-Incr1) Fat(max), MFO, and fat oxidation rates were greater in the Heavy compared with the Light trial (p < 0.05). The fat oxidation kinetics during Incr2(Heavy) showed a greater dilatation and rightward asymmetry than Incr1(Heavy), whereas only a greater dilatation was observed in Incr2(Light) (p < 0.05). This study showed that although to a lesser extent in the Light trial, both prior exercise sessions led to an increase in Fat(max), MFO, and absolute fat oxidation rates during Incr2, inducing significant changes in the shape of the fat oxidation kinetics.
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BACKGROUND AND AIMS: Normal weight obesity (NWO) has been defined as an excessive body fat (BF) associated with a normal body mass index (BMI). Still, little is known regarding the effect of differing cut-offs for %BF on the prevalence of NWO. We thus conducted a study to assess the effect of modifying the cut-offs for excessive %BF on the prevalence of NWO. METHODS: We examined a convenience sample of 1523 Portuguese adults. BF was measured by validated hand-held bioimpedance. NWO was defined as a BMI < 25 kg/m2 and a %BF >30% or according to sex- and age-specific %BF cut-offs. RESULTS: Prevalence of NWO was 10.1% in women and 3.2% in men. In women, prevalence of NWO increased considerably with age, and virtually all women aged over 55 with a BMI < 25 kg/m2 were actually considered as NWO. Using sex-specific cut-offs for BF (men: 29.1%; women: 37.2%) led to moderately lower prevalence of NWO in women. Using sex and age-specific cut-offs for %BF considerably decreased the prevalence of NWO in women, i.e. 0.5e2.5% (depending on the criterion) but not in men, i.e. 1.9e3.4%. CONCLUSIONS: In women, the prevalence of NWO varies considerably according to the cut-off used to define excess BF, whereas a much smaller variation is found in men. While further studies are needed to describe the risk associated with NWO using various %BF cut-offs, this study suggests that sex- and age-specific cut-offs may be preferred.
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AIMS: More than two billion people worldwide are deficient in key micronutrients. Single micronutrients have been used at high doses to prevent and treat dietary insufficiencies. Yet the impact of combinations of micronutrients in small doses aiming to improve lipid disorders and the corresponding metabolic pathways remains incompletely understood. Thus, we investigated whether a combination of micronutrients would reduce fat accumulation and atherosclerosis in mice. METHODS AND RESULTS: Lipoprotein receptor-null mice fed with an original combination of micronutrients incorporated into the daily chow showed reduced weight gain, body fat, plasma triglycerides, and increased oxygen consumption. These effects were achieved through enhanced lipid utilization and reduced lipid accumulation in metabolic organs and were mediated, in part, by the nuclear receptor PPARα. Moreover, the micronutrients partially prevented atherogenesis when administered early in life to apolipoprotein E-null mice. When the micronutrient treatment was started before conception, the anti-atherosclerotic effect was stronger in the progeny. This finding correlated with decreased post-prandial triglyceridaemia and vascular inflammation, two major atherogenic factors. CONCLUSION: Our data indicate beneficial effects of a combination of micronutritients on body weight gain, hypertriglyceridaemia, liver steatosis, and atherosclerosis in mice, and thus our findings suggest a novel cost-effective combinatorial micronutrient-based strategy worthy of being tested in humans.
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Objective: to assess the diagnostic accuracy of different anthropometric markers in defining low aerobic fitness among adolescents. Methods: cross-sectional study on 2,331 boys and 2,366 girls aged 10 - 18 years. Body mass index (BMI) was measured using standardized methods; body fat (BF) was assessed by bioelectrical impedance. Low aerobic fitness was assessed by the 20-meter shuttle run using the FITNESSGRAMR criteria. Waist was measured in a subsample of 1,933 boys and 1,897 girls. Overweight, obesity and excess fat were defined according to the International Obesity Task Force (IOTF) or FITNESSGRAMR criteria. Results: 38.5% of boys and 46.5% of girls were considered as unfit according to the FITNESSGRAMR criteria. In boys, the area under the ROC curve (AUC) and 95% confidence interval were 66.7 (64.1 - 69.3), 67.1 (64.5 - 69.6) and 64.6 (61.9 - 67.2) for BMI, BF and waist, respectively (P<0.02). In girls, the values were 68.3 (65.9 - 70.8), 63.8 (61.3 - 66.3) and 65.9 (63.4 - 68.4), respectively (P<0.001). In boys, the sensitivity and specificity to diagnose low fitness were 13% and 99% for obesity (IOTF); 38% and 86% for overweight + obesity (IOTF); 28% and 94% for obesity (FITNESSGRAMR) and 42% and 81% for excess fat (FITNESSGRAMR). For girls, the values were 9% and 99% for obesity (IOTF); 33% and 82% for overweight + obesity (IOTF); 22% and 94% for obesity (FITNESSGRAMR) and 26% and 90% for excess fat (FITNESSGRAMR). Conclusions: BMI, not body fat or waist, should be used to define low aerobic fitness. The IOTF BMI cut-points to define obesity have a very low screening capacity and should not be used.
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Previous studies have demonstrated the difference between the basal metabolic rate (BMR) and the sleeping metabolic rate (SMR): however, the difference in the Japanese population has not yet been explored. This study examined the relationship between the BMR and SMR in ninety-four healthy Japanese subjects (37 males and 57 females, 39 +/- 12 y of age and 22.0 +/- 7.4% body fat) in a respiratory chamber. The SMR was significantly lower than the BMR (1416 +/- 245 vs. 1492 +/- 256 kcal/d): however, there was a highly significant correlation between the two (r = 0.867; p < 0.001). The ratio of SMR/BMR largely varied among individuals (0.95 +/-0.08, 8.4% of the coefficient of variation). The ratio was significantly lower in males than in females (0.93 +/- 0.10 vs. 0.97 +/- 0.06, p < 0.05). None of the anthropometric measures (age, weight, body mass index, body surface area or percent body fat) correlated with the ratio. These results showed that SMR was 95%, of BMR on average in a healthy Japanese group. However, when applied over a longer time period (24 h or more), the difference tends to become negligible for most analyses in a group. Although the difference between SMR and BMR will induce a 5% gap of physical activity level defined as the total energy expenditure divided by the BMR or SMR, this factor seems to have little practical importance in epidemiological research.
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PURPOSE: Self-administered questionnaires continue to be the most widely used type of physical activity assessment in epidemiological studies. However, test-retest reliability and validity of physical activity questionnaires have to be determined. In this study, three short physical activity questionnaires already used in Switzerland and the International Physical Activity Questionnaire (IPAQ) were validated. METHODS: Test-retest reliability was assessed by repeated administration of all questionnaires within 3 wk in 178 volunteers (77 women, 46.1+/-14.8 yr; 101 men 46.8+/-13.2 yr). Validity of categorical and continuous data was studied in a subsample of 35 persons in relation to 7-d accelerometer readings, percent body fat, and cardiorespiratory fitness. RESULTS: Reliability was fair to good with a Spearman correlation coefficient range of 0.43-0.68 for measures of continuous data and moderate to fair with Kappa values between 0.32 and 0.46 for dichotomous measures active/inactive. Total physical activity reported in the IPAQ and the Office in Motion Questionnaire (OIMQ) correlated with accelerometry readings (r=0.39 and 0.44, respectively). In contrast, correlations of self-reported physical data with percent body fat and cardiorespiratory fitness were low (r=-0.26-0.29). Participants categorized as active by the Swiss HEPA Survey 1999 instrument (HEPA99) accumulated significantly more days of the recommended physical activities than their inactive counterparts (4.4 and 2.7 d.wk, respectively, P<0.05). However, compared with accelerometer data, vigorous physical activities were overreported in investigated questionnaires. CONCLUSION: Collecting valid data on physical activity remains a challenging issue for questionnaire surveys. The IPAQ and the three other questionnaires are characterized to inform decisions about their appropriate use.
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To estimate the prevalence of metabolically healthy obesity (MHO) according to different definitions. Population-based sample of 2803 women and 2557 men participated in the study. Metabolic abnormalities were defined using six sets of criteria, which included different combinations of the following: waist; blood pressure; total, high-density lipoprotein or low-density lipoprotein-cholesterol; triglycerides; fasting glucose; homeostasis model assessment; high-sensitivity C-reactive protein; personal history of cardiovascular, respiratory or metabolic diseases. For each set, prevalence of MHO was assessed for body mass index (BMI); waist or percent body fat. Among obese (BMI 30 kg/m(2)) participants, prevalence of MHO ranged between 3.3 and 32.1% in men and between 11.4 and 43.3% in women according to the criteria used. Using abdominal obesity, prevalence of MHO ranged between 5.7 and 36.7% (men) and 12.2 and 57.5% (women). Using percent body fat led to a prevalence of MHO ranging between 6.4 and 43.1% (men) and 12.0 and 55.5% (women). MHO participants had a lower odd of presenting a family history of type 2 diabetes. After multivariate adjustment, the odds of presenting with MHO decreased with increasing age, whereas no relationship was found with gender, alcohol consumption or tobacco smoking using most sets of criteria. Physical activity was positively related, whereas increased waist was negatively related with BMI-defined MHO. MHO prevalence varies considerably according to the criteria used, underscoring the need for a standard definition of this metabolic entity. Physical activity increases the likelihood of presenting with MHO, and MHO is associated with a lower prevalence of family history of type 2 diabetes.