DISTRIBUCION DE GRASA CORPORAL ANDROIDE Y GINECOIDE PDF

Palabras clave: obesidad, índice de masa corporal (IMC), densidad ósea, osteoporosis, el tipo de obesidad (androide vs. ginecoide) y osteoporosis . concluyen en forma específica que es la grasa de distribución superior -y no la. La obesidad se define como un exceso de grasa corporal. Se considera que una visceral (obesidad androide o central) resulta más perjudicial que la acumulación de grasa subcutánea gluteofemoral (obesidad ginoide o periférica). Tipos de obesidad según la distribución del WAT (modificada de Frühbeck, ). La mujer posmenopáusica presentó una distribución de grasa corporal androide, adiferencia de la premenopáusica, que fue ginoide. Su tejido adiposo.

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The graph below shows the difference of this change the increase in BFM is represented above the y -axis and the decrease, below. Baseline clinical, biochemical, anthropometric and body-composition parameters studied from the aggregate sample of 46 patients, stratified by method of renal replacement therapy.

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Biochemical, anthropometric and body composition parameters studied in 18 haemodialysis patients, stratified by baseline and annual samples. Demographic, biochemical, anthropometric and body composition parameters studied in 18 haemodialysis patients, stratified by sex and monitored for one year. Estimate using a generalised estimating equation of the effect of association between body composition parameters measured by bioimpedance and dual-energy X-ray absorptiometry and adipocytokines studied in 18 haemodialysis patients.

Matrix of correlation between the variation of body composition parameters at one year, measured in the 18 haemodialysis patients using bioimpedance and dual-energy X-ray absorptiometry, and the increase in adipocytokines studied.

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Evaluation of the degree of concordance measured using Pearson’s bivariate correlations between the body fat mass measurement, estimated using single-frequency bioimpedance and other body composition techniques multifrequency bioimpedance and dual-energy X-ray absorptiometryin 29 HD patients.

Abdominal fat and its increment over time in particular has become a cardiovascular risk factor in uraemic patients. To analyse changes in abdominal fat in haemodialysis patients over one year and study androids possible correlation with the variation in adipocytokine serum levels. As a secondary objective, we tried to validate the data obtained by bioelectrical impedance analysis BIA with data obtained by dual X-ray absorptiometry DXA.

A prospective one-year study was performed in 18 patients on haemodialysis HD. Several adipocytokine and biochemical parameters were determined. A significant increase in phase angle [4. These findings might explain the increased cardiovascular risk in these patients. Cardiovascular CV disease is the leading cause of morbidity and mortality in patients with kidney disease.

Leptin cofporal a modulator of the immune-response that causes stimulation of proinflammatory cytokines the production and produces a significant increase in sympathetic activity.

Fibroblast growth factor 21 FGF stimulates the uptake of glucose by the adipocyte independently of insulin, suppresses the production of hepatic glucose and is involved in regulating body fat. Abdominal fat and, above all, the gain of abdominal fat over time, has been established as a significant CV risk factor, especially in uraemic patients. Dual-energy X-ray absorptiometry DXA 14 is a reference technique able to assess body composition as in 3 compartments: Whole-body scans allow for regional determinations of BFM.

The limited information available coproral body composition in uraemic patients and its effects on CV mortality encouraged us to carry out this pilot study. Our main objective has been not only to verify whether there is an abdominal fat gain in haemodialysis HD patients, but also to study a possible relationships with the changes in plasma levels of adipocytokines, which could be related to the metabolic disorders induced by adipocyte activity in uraemia.

As a secondary objective, we tried to validate the data obtained by bioelectrical impedance analysis Andgoide with those obtained by DXA gold standard for determining body composition and poorly accessible technique in daily clinical practice.

A prospective, one-year study was conducted in which 18 patients undergoing HD were included. The inclusion criteria were as follows: The exclusion criteria were: Advanced age was not an exclusion criterion. Demographic data and data on renal replacement therapy, as well as comorbidities or intercurrent processes, were recorded. The recruitment period for patients lasted from May to March An informed consent template was designed and it was signed by each participant.

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The measurements of anthropometric and body composition, and the collection of blood samples, were obtained under fasting conditions at baseline between and and 12 months later. Ginecokde both samples the following parameters were measured: All the laboratory tests were done under fasting conditions: Subsequently, we performed a second part of the study; a control group of 17 patients on PD, from the Nephrology Department, who fulfilled the same criteria as the HD patients were compared with the 29 patients on HD cross-sectional baseline.

Thus, this study compares data on the body composition of both groups of patients to perform concordance studies among methods for analysing body composition.

The anthropometric measurements of the patients were obtained in accordance with the standard technique and the current international recommendations WHO, These measurements were obtained in subjects barefoot and in their underwear.

The measurements were always taken pre-dialysis in HD patients, and with the abdomen empty in PD patients. Height was measured by a millimetre precision rod range: Triceps skin fold TSF was obtained by means of a Holtain skinfold calliper with a range of 20 cm and a sensitivity of 0.

Waist circumference WC was measured in cm, using a millimetre precision tape measure with the waist in a horizontal position narrower torso level, midline between the iliac crest and the last rib. This was measured at the end of a normal exhalation. To determine body composition by BIA, a four-pole vector device 50 kHzwith an intensity of 0.

The measurement was performed according to the criteria established by the National Institutes of Health Technology Assessment Conference Statement. The assay sensitivity was 1. IL-6 sensitivity was 1. Leptin sensitivity was 7. Free fatty acids were measured based on an in vitro enzymatic colorimetric method A25, Biosystems, Barcelona, Spain.

The expected values were 2. Insulin was measured by direct chemiluminescence-based giencoide Liaison, Ginecpide, Saluggia, Italy.

Insulin sensitivity was 0. Considering the baseline analysis of the data, qualitative variables among 2 or more groups were compared by using a chi-squared test or Fisher’s exact test, depending on the data distribution. Quantitative variables between 2 groups were compared by using the Mann—Whitney U test or a Student’s t -test, depending on the data distribution. Levene’s test was used to compare response variability by group.

Spearman’s rank correlation coefficient was used to analyse the baseline linear association of 2 continuous variables. To evaluate the degree of agreement between 2 variables that evaluated the same concept, Pearson’s bivariate correlations were used.

For the longitudinal analysis of the laboratory parameters studied based on 2 time points baseline and yearlya stratified analysis by modality and incidence of the response variable was performed first. The effect of the method, the incidence or prevalence and the interaction between them was estimated, and the adjustment of the model was considered by using generalised estimating equations GEE for longitudinal data.

In order to analyse any association among the different laboratory parameters studied and the independent variables analysed anthropometric and body-composition parameters estimated by BIA and DXAthe effect was estimated by using the Score Statistics For Type 3 GEE Analysis. Spearman’s correlations were used to analyse the association of stratified variables, for which the sample size was small.

The same study was performed for the analysis of the increase delta or the difference between the final and baseline values, although in this case the model was adjusted with a general linear model. All statistical tests were considered two-sided, while significant values were considered those where p was less than 0. The data were analysed using SAS 9. The main clinical, laboratory and anthropometric characteristics of both groups are presented in Table 1.

In terms of lab parameters, there were no differences between the groups, except for higher albumin and lower cholesterol in HD patients, despite the fact that these patients had been on dialysis for more time than PD patients. The data are shown as mean SD for normal distribution variables and as median p25; p75 for non-parametric variables. Homeostasis Model Assessment; IL HD patients had a lower phase angle and higher resistance than PD patients. HD patients showed a lower percent of body-water: No significant differences were found in the laboratory parameters, except for cholesterol.

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Given that gender affects body composition, Table 3 shows the same data, but separated by gender. In women, no significant differences were found in the anthropometric, laboratory or body-composition parameters measured by BIA. Although there was a trend towards an increase in fat in all the parameters studied Fig. Baseline anthropometric or laboratory parameters in men and women were not significantly different, except for albumin and adiponectin values Table 3.

Significant differences were found in almost all the body-composition parameters measured by BIA and in most measured by DXA. Contrary to what it was expected, men had a higher percentage of BFM as compared with women at baseline; this difference was no longer present after one year of follow up because of a trend towards a gain in BFM especially in womenFig. Men and women showed no significant differences in baseline leptin and adiponectin values, nor at one year of follow up.

This is despite the trend towards an increase in leptin in women and in adiponectin in men. A statistically significant relationship was found between leptin and adiponectin concentrations, with both the percentage of fat mass measured by BIA and abdominal fat estimated by DXA Table 4.

In both cases the relationships were statistically significant. In addition, increment in these adipocytokines correlated with the percentage change in BFM Table 5. This later correlation was also observed after a year of follow-up. However such a correlation was not observed with leptin.

There were no significant differences in the longitudinal study in serum FGF concentrations in the overall population or in the subgroups by gender. The variables are expressed as correlation coefficients for non-parametric data Spearman’s rho.

Regarding the second objective of our study, a significant correlation was found between the fat-mass parameters quantified by BIA and DXA Table 6thus indicating a good concordance between both methods of body-composition measurement.

The variables are expressed as Pearson’s correlation coefficients, comparing the different variables against body fat mass estimated using bioimpedance vector analysis.

The results of the present study show that fat gain occurs in patients on HD over time, even during limited follow-up periods, such as one year.

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This gain is clearly of abdominal distribution, which increases CV risk associated with the time on dialysis. We were also able to verify that the d in body-composition parameters BFM gains or losses during the follow-up were correlated with the changes in the adipocytokine concentrations analysed in these patients. Unlike our study, they did not find differences by gender, and they described a negative correlation with baseline albumin and with basal BFM.

According to the studies by Vague 20 on the distribution patterns of BFM and their association with metabolic disorders, the android, or predominantly abdominal, distribution of body fat has a greater clinical significance, given its association with an increase in CV risk.

Excess abdominal fat android is associated with several CV risk factors. This relationship may play a role in assessing CV risk in overweight patients. The uraemic medium contributes to the retention of adipocytokines, systemic inflammation, oxidative stress and insulin resistance. Our results andriode a statistically significant increase in plasma levels of leptin and a decrease in plasma levels of adiponectin, even after adjusting their levels for BMI in HD patients.

It should be noticed that the elevated adiponectin levels, which according to some studies, are related to an increase in mortality. A secondary objective of our study was to validate the data obtained by BIA a technique commonly used in clinical practice with those obtained by DXA gold standard for the study of body composition.

Our data indicate the existence of a strong distibucion between the body-composition parameters percentage of fat mass obtained from both techniques.