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Limitations of body mass index to assess body composition due to sarcopenic obesity during leukemia therapy.

ABSTRACT: Obesity as defined by body mass index percentile (BMI%) is strongly associated with relapse and poorer survival in childhood ALL. Whether BMI% accurately reflects body fat percentage (BF%) in this population is unknown. We conducted a prospective study assessing body composition during frontline ALL therapy. Dual-energy X-ray absorptiometry measured BF% and lean muscle mass (LMM) at diagnosis, end of Induction, and end of Delayed Intensification. Sarcopenic obesity (gain in BF% with loss of LMM) was surprisingly common during ALL treatment, resulting in poor correlation between changes in BMI% (expressed as Z-score) and BF% overall (r?=?-0.05) and within patients (r?=?-0.09). BMI Z-score and BF% changed in opposite directions in?>50% of interval assessments. While BMI% at diagnosis is a suitable predictor of obesity/BF% for epidemiological studies, change in BMI% (as expressed as Z-score) does not reflect body composition. Studies evaluating obesity in leukemia should consider using direct measures of body composition.

SUBMITTER: Orgel E

PROVIDER: S-EPMC5362342 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Limitations of body mass index to assess body composition due to sarcopenic obesity during leukemia therapy.

Orgel Etan E Mueske Nicole M NM Sposto Richard R Gilsanz Vicente V Freyer David R DR Mittelman Steven D SD

Leukemia & lymphoma 20160127 1

Obesity as defined by body mass index percentile (BMI%) is strongly associated with relapse and poorer survival in childhood ALL. Whether BMI% accurately reflects body fat percentage (BF%) in this population is unknown. We conducted a prospective study assessing body composition during frontline ALL therapy. Dual-energy X-ray absorptiometry measured BF% and lean muscle mass (LMM) at diagnosis, end of Induction, and end of Delayed Intensification. Sarcopenic obesity (gain in BF% with loss of LMM) ...[more]

PMID: 26818609

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Project description:Highlights • Women with patellofemoral pain have higher body mass index and body fat and lower skeletal muscle mass compared to pain-free women.• Men with patellofemoral pain and both sexes combined have no difference in body mass index, body fat, or skeletal muscle mass compared to their respective pain-free control groups.• Body mass index and levels of body fat and skeletal muscle mass should be considered when assessing women with patellofemoral pain.• Future studies should not assess body composition measures in a mixed-sex population without discriminating between men and women. Background We compared body mass index (BMI), body fat, and skeletal muscle mass between (1) a mixed-sex nonathletic cohort of people with patellofemoral pain (PFP) and pain-free people, and (2) a nonathletic cohort of people with PFP and pain-free people subgrouped by sex (i.e., men and women with PFP vs. pain-free men and women). Methods This cross-sectional study included 114 people with PFP (71 women, 43 men) and 54 pain-free controls (32 women, 22 men). All participants attended a single testing session to assess body composition measures, which included BMI, percentage of body fat (%BFBioimpedance), and skeletal muscle mass (both assessed by bioelectrical impedance analysis), and percentage of body fat (%BFSkinfold) (assessed by skinfold caliper analysis). A one-way univariate analysis of covariance (age and physical activity levels as covariates) was used to compare body composition measures between groups (i.e., PFP vs. pain-free group; women with PFP vs. pain-free women; men with PFP vs. pain-free men). Results Women with PFP presented significantly higher BMI, %BFBioimpedance, and %BFSkinfold, and lower skeletal muscle mass compared to pain-free women (p ≤ 0.04; effect size : ‒0.47 to 0.85). Men with PFP and men and women combined had no differences in BMI, %BFBioimpedance, %BFSkinfold, and skeletal muscle mass compared to their respective pain-free groups (p > 0.05). Conclusion Our findings indicate that BMI and body composition measures should be considered as part of the evaluation and management of people with PFP, especially in women, who have demonstrated higher BMI and body fat and lower skeletal muscle mass compared to pain-free controls. Future studies should not assess body composition measures in a mixed-sex population without distinguishing men participants from women participants. Graphical abstract Image, graphical abstract

Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.

Project description:BackgroundSarcopenic obesity is a condition characterised by the coexistence of low muscle mass and function (sarcopenia) and excessive fat mass (obesity). The aim of this study was to determine the prevalence of this condition in patients undergoing orthopaedic surgery by gender and type of orthopaedic surgery. In addition, this study investigated the suitability of a waist circumference-based anthropometric measure, body shape index (ABSI), for predicting sarcopenic obesity and the predictive power of ABSI for fat-free mass index (FFMI), a surrogate marker of lean body mass.Methods and findingsA cross-sectional study of overweight and obese orthopaedic patients undergoing knee or hip and spine surgery was conducted between October 2019 and March 2020 in Orthopaedic Hospital Valdoltra, Slovenia. General anthropometric parameters body mass index (BMI) and ABSI = (WC/(BMI2/3x height½) as well as body composition data (fat mass FM, fat-free mass FFM, FFMI, and the ratio FM/FFM as an index of sarcopenic obesity) were determined in 120 women (aged 66.5 ± 9.6 years) and 89 men (aged 65.5 ± 7.8 years) with overweight (25 kg/m2 ≤ BMI < 30 kg/m2) and obesity (BMI ≥ 30 kg/m2) by bioelectrical impedance analysis (BIA). Sarcopenic obesity phenotypes based on FM/FFM ratio > 0.80 was present in 15.3% of patients, mainly in female patients undergoing knee surgery. ABSI was significantly associated with age in all women and obese men and with waist circumference (WC) in all patients. ABSI did not correlate with BMI in women and men; however, multiple linear regression analysis showed that BMI independently predicted FFMI (R = 0.83 and 0.70, respectively, p < 0.001) in women and men (β-coefficients: 0.801 and 0.686, respectively) and ABSI in women only (β-coefficient: -0.104). Women with a lower ABSI had a significantly higher FFMI than the group with a higher ABSI.ConclusionsSarcopenic obesity was most prevalent in obese women scheduled for knee surgery. In addition, ABSI, independently predicted FFMI in women and represents a significant predictor of sarcopenic obesity.

Project description:BackgroundBody mass index (BMI) and A Body Shape Index (ABSI) are current independent risk factors for non-alcoholic fatty liver disease (NAFLD). The aim of this study was to explore the value of combining these two most common obesity indexes in identifying NAFLD.MethodsThe subjects in this study were 14,251 individuals from the NAfld in the Gifu Area, Longitudinal Analysis (NAGALA) cohort who underwent routine health examination. We integrated BMI with WC and with ABSI to construct 6 combined obesity indicators-obesity phenotypes, the combined anthropometric risk index (ARI) for BMI and ABSI, optimal proportional combination OBMI+WC and OBMI+ABSI, and multiplicative combination BMI*WC and BMI*ABSI. Several multivariable logistic regression models were established to evaluate the relationship between BMI, WC, ABSI, and the above six combined indicators and NAFLD; receiver operating characteristic (ROC) curves were drawn to compare the ability of each obesity indicator to identify NAFLD.ResultsA total of 2,507 (17.59%) subjects were diagnosed with NAFLD. BMI, WC, ABSI, and all other combined obesity indicators were significantly and positively associated with NAFLD in the current study, with BMI*WC having the strongest correlation with NAFLD in female subjects (OR per SD increase: 3.13) and BMI*ABSI having the strongest correlation in male subjects (OR per SD increase: 2.97). ROC analysis showed that ARI and OBMI+ABSI had the best diagnostic performance in both sexes, followed by BMI*WC (area under the curve: female 0.8912; male 0.8270). After further age stratification, it was found that ARI and multiplicative indicators (BMI*WC, BMI*ABSI) and optimal proportional combination indicators (OBMI+WC, OBMI+ABSI) significantly improved the NAFLD risk identification ability of the basic anthropometric parameters in middle-aged females and young and middle-aged males.ConclusionIn the general population, BMI combined with ABSI best identified obesity-related NAFLD risk and was significantly better than BMI or WC, or ABSI. We find that ARI and the multiplicative combined indicators BMI*WC and BMI*ABSI further improved risk prediction and may be proposed for possible use in clinical practice.

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Limitations of body mass index to assess body composition due to sarcopenic obesity during leukemia therapy.

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Limitations of body mass index to assess body composition due to sarcopenic obesity during leukemia therapy.

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