Association of Serum Albumin with Markers of Nutritional Status among HIV-Infected and Uninfected Rwandan Women

The objectives of this study are to address if and how albumin can be used as an indication of malnutrition in HIV infected and uninfected Africans.In 2005, 710 HIV-infected and 226 HIV-uninfected women enrolled in a cohort study. Clinical/demographic parameters, CD4 count, albumin, liver transaminases; anthropometric measurements and Bioelectrical Impedance Analysis (BIA) were performed. Malnutrition outcomes were defined as body mass index (BMI), Fat-free mass index (FFMI) and Fat mass index (FMI). Separate linear predictive models including albumin were fit to these outcomes in HIV negative and HIV positive women by CD4 strata (CD4>350,200-350 and <200 cells/µl).In unadjusted models for each outcome in HIV-negative and HIV positive women with CD4>350 cells/µl, serum albumin was not significantly associated with BMI, FFMI or FMI. Albumin was significantly associated with all three outcomes (p<0.05) in HIV+ women with CD4 200-350 cells/µl, and highly significant in HIV+ women with CD4<200 cells/µl (P<0.001). In multivariable linear regression, albumin remained associated with FFMI in women with CD4 count<200 cells/µl (p<0.01) but not in HIV+ women with CD4>200.While serum albumin is widely used to indicate nutritional status it did not consistently predict malnutrition outcomes in HIV- women or HIV+ women with higher CD4. This result suggests that albumin may measure end stage disease as well as malnutrition and should not be used as a proxy for nutritional status without further study of its association with validated measures

Body composition in male elite athletes, comparison of bioelectrical impedance spectroscopy with dual energy X-ray absorptiometry

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to compare body composition results from bioelectrical spectroscopy (BIS) with results from dual energy X-ray absorptiometry (DXA) in a population of male elite athletes. Body composition was assessed using DXA (Lunar Prodigy, GE Lunar Corp., Madison, USA) and BIS (Hydra 4200, Xitron Technologies Inc, San Diego, California, USA) at the same occasion. Agreement between methods was assessed using paired t-tests and agreement-plots.</p> <p>Results</p> <p>Thirty-three male elite athletes (soccer and ice hockey) were included in the study. The results showed that BIS underestimates the proportion of fat mass by 4.6% points in the ice hockey players. In soccer players the BIS resulted in a lower mean fat mass by 1.1% points. Agreement between the methods at the individual level was highly variable.</p> <p>Conclusion</p> <p>Body composition results assessed by BIS in elite athletes should be interpreted with caution, especially in individual subjects. BIS may present values of fat mass that is either higher or lower than fat mass assessed by DXA, independent of true fat content of the individual.</p

Body Fat Free Mass Is Associated with the Serum Metabolite Profile in a Population-Based Study

To characterise the influence of the fat free mass on the metabolite profile in serum samples from participants of the population-based KORA (Cooperative Health Research in the Region of Augsburg) S4 study. Analyses were based on metabolite profile from 965 participants of the S4 and 890 weight-stable subjects of its seven-year follow-up study (KORA F4). 190 different serum metabolites were quantified in a targeted approach including amino acids, acylcarnitines, phosphatidylcholines (PCs), sphingomyelins and hexose. Associations between metabolite concentrations and the fat free mass index (FFMI) were analysed using adjusted linear regression models. To draw conclusions on enzymatic reactions, intra-metabolite class ratios were explored. Pairwise relationships among metabolites were investigated and illustrated by means of Gaussian graphical models (GGMs). We found 339 significant associations between FFMI and various metabolites in KORA S4. Among the most prominent associations (p-values 4.75 × 10(-16)-8.95 × 10(-06)) with higher FFMI were increasing concentrations of the branched chained amino acids (BCAAs), ratios of BCAAs to glucogenic amino acids, and carnitine concentrations. For various PCs, a decrease in chain length or in saturation of the fatty acid moieties could be observed with increasing FFMI, as well as an overall shift from acyl-alkyl PCs to diacyl PCs. These findings were reproduced in KORA F4. The established GGMs supported the regression results and provided a comprehensive picture of the relationships between metabolites. In a sub-analysis, most of the discovered associations did not exist in obese subjects in contrast to non-obese subjects, possibly indicating derangements in skeletal muscle metabolism. A set of serum metabolites strongly associated with FFMI was identified and a network explaining the relationships among metabolites was established. These results offer a novel and more complete picture of the FFMI effects on serum metabolites in a data-driven network

Is bioelectrical impedance accurate for use in large epidemiological studies?

Percentage of body fat is strongly associated with the risk of several chronic diseases but its accurate measurement is difficult. Bioelectrical impedance analysis (BIA) is a relatively simple, quick and non-invasive technique, to measure body composition. It measures body fat accurately in controlled clinical conditions but its performance in the field is inconsistent. In large epidemiologic studies simpler surrogate techniques such as body mass index (BMI), waist circumference, and waist-hip ratio are frequently used instead of BIA to measure body fatness. We reviewed the rationale, theory, and technique of recently developed systems such as foot (or hand)-to-foot BIA measurement, and the elements that could influence its results in large epidemiologic studies. BIA results are influenced by factors such as the environment, ethnicity, phase of menstrual cycle, and underlying medical conditions. We concluded that BIA measurements validated for specific ethnic groups, populations and conditions can accurately measure body fat in those populations, but not others and suggest that for large epdiemiological studies with diverse populations BIA may not be the appropriate choice for body composition measurement unless specific calibration equations are developed for different groups participating in the study

Body composition in older acute stroke patients after treatment with individualized, nutritional supplementation while in hospital

<p>Abstract</p> <p>Background</p> <p>Individualized, nutritional support reduced undernutrition among older stroke patients and improved quality of life in our recent randomized, controlled trial. Weight control thus seems to be important after stroke, and methods for monitoring nutritional status need to be simple and non-invasive. Here we aimed to assess if the nutritional intervention altered body composition in men and women in this study cohort, and also to examine the correlation between the methods for assessing body-, fat- and fat-free mass.</p> <p>Methods</p> <p>Acute stroke patients > 65 years at nutritional risk were randomized to either individualized, nutritional treatment with energy- and protein rich supplementation (intervention, n = 58) or routine, nutritional care (control, n = 66) while in hospital. Body composition was assessed with anthropometry and bioelectrical impedance. The follow-up period was three months.</p> <p>Results</p> <p>During the first week while in hospital, weight loss was smaller in the intervention group compared with the controls (P = 0.013). After three months weight- and fat loss were significant in both men and women. Whereas no significant differences were found in changes in body composition between the male study groups, in the women both weight loss (P = 0.022) and fat loss (P = 0.005) was smaller in the intervention group compared with the controls. A high correlation (r = 0.87) between mid upper arm circumference (MUAC) and body mass index (BMI) was found.</p> <p>Conclusions</p> <p>Individualized nutritional support to older stroke patients in hospital was beneficial for maintaining an adequate body mass and body composition the first week and seemed to have a preventive effect on fat loss among women, but not among men after three months. Measurement of MUAC may be used in the assessment of nutritional status when BMI cannot be obtained.</p> <p>Trial registration</p> <p>This trial is registered with ClinicalTrials.gov, number NCT00163007.</p

Improving nutritional care quality in the orthopedic ward of a Septic Surgery Center by implementing a preventive nutritional policy using the Nutritional Risk Score: a pilot study.

Septic Surgery Center (SSC) patients are at a particularly high risk of protein-energy malnutrition (PEM), with a prevalence of 35-85% found in various studies. Previous collaboration between our hospital's SSC and its Clinical Nutrition Team (CNT) only focussed on patients with severe PEM. This study aimed to determine whether it was possible to improve the quality of nutritional care in septic surgery patients with help of a nutritional policy using the Nutritional Risk Score (NRS). Nutritional practices in the SSC were observed over three separate periods: in the 3 months leading up to the implementation baseline, 6 months after implementation of preventive nutritional practices, and at 3 years. The nutritional care quality indicator was the percentage of patients whose nutritional care, as prescribed by the SSC, was adapted to their specific requirements. We determined the septic surgery team's NRS completion rate and calculated the nutritional policy's impact on SSC length of stay. Data before (T &lt;sub&gt;0&lt;/sub&gt; ) and after (T &lt;sub&gt;1&lt;/sub&gt; + T &lt;sub&gt;2&lt;/sub&gt; ) implementation of the nutritional policy were compared. Ninety-eight patients were included. The nutritional care-quality indicator improved from 26 to 81% between T &lt;sub&gt;0&lt;/sub&gt; and T &lt;sub&gt;2&lt;/sub&gt; . During the T &lt;sub&gt;1&lt;/sub&gt; and T &lt;sub&gt;2&lt;/sub&gt; audits, septic surgery nurses calculated NRS for 100% and 97% of patients, respectively. Excluding patients with severe PEM, SSC length of stay was significantly reduced by 23 days (p = 0.005). These findings showed that implementing a nutritional policy in an SSC is possible with the help of an algorithm including an easy-to-use tool like the NRS

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian, Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

Background Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat. Methods Cross-sectional study of children aged 8–10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height2/Z); C: FFM = linear combination(height2/Z+weight)}. Results Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set. Conclusions Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences