Dataset Information

Development of Novel Methods to Define Deficits in Appendicular Lean Mass Relative to Fat Mass.

ABSTRACT:

Background

Recent studies suggest that adjustment of measures of lean mass for adiposity improves associations with physical function. Our objective was to develop and test a method to adjust appendicular lean mass for adiposity.

Methods

Whole-body DXA data in 14,850 adults in the National Health and Nutrition Examination Survey were used to generate sex-, and race-specific standard deviation scores (Z-Scores relative to age and T-scores relative to 25 year-olds) for appendicular lean mass index (ALMI, kg/m2) and fat mass index (FMI, kg/m2). Correlations between ALMI and FMI Z- and T-Scores were assessed within demographic categories. Fat-adjusted ALMI (ALMIFMI) scores were determined using residual methods. Sarcopenia was defined as a T-Score <-2.0 and low lean for age as a Z-Score <-1.0. Correlations with physical function were assessed in an at-risk population.

Results

Positive associations between ALMI and FMI Z- and T-Scores were significant (R >0.50; p<0.001) within all demographic categories. The impact of a unit greater FMI Z-score on ALMI Z-score was less in the elderly, men, white subjects, and among individuals with lower FMI (all tests for interaction p<0.001). There was fair agreement between ALMI and ALMIFMI estimates of sarcopenia and low lean for age [Kappa: 0.46, 0.52, respectively (p<0.0001)]. Elderly subjects were likely to be re-classified as sarcopenic while young subjects were likely to be re-classified as normal using ALMIFMI. ALMIFMI T-scores resulted in approximately twice the number of subjects defined as sarcopenic, compared with ALMI T-Scores. (1299 v. 534). Among rheumatoid arthritis patients, ALMIFMI Z-scores correlated with physical function (Health Assessment Questionnaire: rho = -0.22, p = 0.04; Short Physical Performance Battery: rho = 0.27, p = 0.01); however, the ALMI Z-Score did not.

Conclusions

Adjustment of ALMI for the confounding association with FMI impacts the definition of lean mass deficits. These methods provide a practical tool for investigators and clinicians based on population-based reference data.

SUBMITTER: Weber D

PROVIDER: S-EPMC5056731 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Development of Novel Methods to Define Deficits in Appendicular Lean Mass Relative to Fat Mass.

Weber David D Long Jin J Leonard Mary B MB Zemel Babette B Baker Joshua F JF

PloS one 20161010 10

<h4>Background</h4>Recent studies suggest that adjustment of measures of lean mass for adiposity improves associations with physical function. Our objective was to develop and test a method to adjust appendicular lean mass for adiposity.<h4>Methods</h4>Whole-body DXA data in 14,850 adults in the National Health and Nutrition Examination Survey were used to generate sex-, and race-specific standard deviation scores (Z-Scores relative to age and T-scores relative to 25 year-olds) for appendicular ...[more]

PMID: 27723820

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Project description:BackgroundLittle is known about the association of changes in two body components, muscle and fat mass, with the risk of cardiovascular disease (CVD) among young adults. We investigated the association of changes in predicted lean body mass index (LBMI), appendicular skeletal muscle mass index (ASMI), and body fat mass index (BFMI) with the development of CVD among young adults.MethodsThis nationwide, population-based cohort study included 3 727 738 young adults [2 406 046 (64.5%) men and 1 321 692 (35.5%) women] aged 20-39 years without a previous history of CVD who underwent two health screening examinations during 2009-2010 and 2011-2012. Using validated and robust prediction equations, we calculated the changes in predicted LBMI, ASMI, and BFMI from the first to the second examinations.ResultsThe mean (SD) age was 32.2 (4.9) years, and 2 406 046 (64.5%) of the participants were men. A total of 23 344 CVD events were detected during 22 257 632 person-years of follow-up. Each 1 kg/m2 increase in predicted LBMI and ASMI change was associated with a reduced risk of CVD among men [adjusted hazard ratio (aHR): 0.86, 95% confidence interval (CI) 0.82-0.91; aHR: 0.76, 95% CI 0.69-0.82, respectively] and women (aHR: 0.77, 95% CI 0.63-0.95; aHR: 0.75, 95% CI 0.59-0.96). Each 1 kg/m2 increase in predicted BFMI change was associated with an increased risk of CVD among men (aHR: 1.16, 95% CI 1.10-1.22) and women (aHR: 1.32, 95% CI 1.06-1.65). In both sexes, decreases in predicted LBMI and ASMI were associated with greater CVD risk, and decreased predicted BFMI was associated with a reduced CVD risk. Those who maintained their BMI between -1 and +1 kg/m2 also had a decreased risk of CVD per 1 kg/m2 increase in predicted LBMI and ASMI change among men (aHR: 0.86, 95% CI 0.80-0.92; aHR: 0.85, 95% CI 0.76-0.95) and women (aHR: 0.62, 95% CI 0.47-0.83; aHR: 0.59, 95% CI 0.44-0.80) and had a greater risk of CVD per 1 kg/m2 increase in predicted BFMI change among men (aHR: 1.17, 95% CI 1.10-1.25) and women (aHR: 1.64, 95% CI 1.20-2.23). Regardless of changes in weight, such as from normal to obese or vice versa, these results were consistent.ConclusionsAmong young adults, increased predicted muscle mass or decreased predicted fat mass were associated with a reduced risk of development of CVD. Decreased predicted muscle mass or increased predicted fat mass were associated with an elevated risk of development of CVD.

Project description:BackgroundUltrasound is a non-invasive and readily available tool that can be prospectively applied at the bedside to assess muscle mass in clinical settings. The four-site protocol, which images two anatomical sites on each quadriceps, may be a viable bedside method, but its ability to predict musculature has not been compared against whole-body reference methods. Our primary objectives were to (i) compare the four-site protocol's ability to predict appendicular lean tissue mass from dual-energy X-ray absorptiometry; (ii) optimize the predictability of the four-site protocol with additional anatomical muscle thicknesses and easily obtained covariates; and (iii) assess the ability of the optimized protocol to identify individuals with low lean tissue mass.MethodsThis observational cross-sectional study recruited 96 university and community dwelling adults. Participants underwent ultrasound scans for assessment of muscle thickness and whole-body dual-energy X-ray absorptiometry scans for assessment of appendicular lean tissue. Ultrasound protocols included (i) the nine-site protocol, which images nine anterior and posterior muscle groups in supine and prone positions, and (ii) the four-site protocol, which images two anterior sites on each quadriceps muscle group in a supine position.ResultsThe four-site protocol was strongly associated (R2 = 0.72) with appendicular lean tissue mass, but Bland-Altman analysis displayed wide limits of agreement (-5.67, 5.67 kg). Incorporating the anterior upper arm muscle thickness, and covariates age and sex, alongside the four-site protocol, improved the association (R2 = 0.91) with appendicular lean tissue and displayed narrower limits of agreement (-3.18, 3.18 kg). The optimized protocol demonstrated a strong ability to identify low lean tissue mass (area under the curve = 0.89).ConclusionsThe four-site protocol can be improved with the addition of the anterior upper arm muscle thickness, sex, and age when predicting appendicular lean tissue mass. This optimized protocol can accurately identify low lean tissue mass, while still being easily applied at the bedside.

Dataset Information

Development of Novel Methods to Define Deficits in Appendicular Lean Mass Relative to Fat Mass.

Background

Methods

Results

Conclusions

Publications

Development of Novel Methods to Define Deficits in Appendicular Lean Mass Relative to Fat Mass.

Similar Datasets

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