Relationship of Fat Mass Index and Fat Free Mass Index With Body Mass Index and Association With Function, Cognition and Sarcopenia in Pre-Frail Older Adults.

Body mass index (BMI) is an inadequate marker of obesity, and cannot distinguish between fat mass, fat free mass and distribution of adipose tissue. The purpose of this study was twofold. First, to assess cross-sectional relationship of BMI with fat mass index (FMI), fat free mass index (FFMI) and ratio of fat mass to fat free mass (FM/FFM). Second, to study the association of FMI, FFMI and FM/FFM with physical function including sarcopenia, and cognition in pre-frail older adults. Cross-sectional study of 191 pre-frail participants ≥ 65 years, 57.1% females. Data was collected on demographics, cognition [Montreal Cognitive Assessment (MoCA)], function, frailty, calf circumference, handgrip strength (HGS), short physical performance battery (SPPB) and gait speed. Body composition was measured using InBody S10. FMI, FFMI and FM/FFM were classified into tertiles (T1, T2, T3) with T1 classified as lowest and T3 highest tertile respectively and stratified by BMI. Higher FFMI and lower FM/FFM in the high BMI group were associated with better functional outcomes. Prevalence of low muscle mass was higher in the normal BMI group. FMI and FM/FFM were significantly higher in females and FFMI in males with significant gender differences except for FFMI in ≥ 80 years old. Small calf circumference was significantly less prevalent in the highest tertile of FMI, FM/FMI and FFMI. Prevalence of sarcopenic obesity and low physical function (HGS, gait speed and SPPB scores) were significantly higher in the highest FMI and FM/FFM tertile. Highest FFMI tertile group had higher physical function, higher MoCA scores, lower prevalence of sarcopenic obesity and sarcopenia, After adjustment, highest tertile of FFMI was associated with lower odds of sarcopenia especially in the high BMI group. Highest tertile of FM/FFM was associated with higher odds of sarcopenia. Higher BMI was associated with lower odds of sarcopenia. FFMI and FM/FFM may be a better predictor of functional outcomes in pre-frail older adults than BMI. Cut-off values for healthy BMI values and role of calf circumference as a screening tool for sarcopenia need to be validated in larger population. Health promotion intervention should focus on FFMI increment.

Merchant RA ，Seetharaman S ，Au L ，Wong MWK ，Wong BLL ，Tan LF ，Chen MZ ，Ng SE ，Soong JTY ，Hui RJY ，Kwek SC ，Morley JE ... -  《Frontiers in Endocrinology》

Gender Differences in Body Composition in Pre-Frail Older Adults With Diabetes Mellitus.

Ageing is a risk factor for diabetes mellitus (DM) and frailty. It is associated with body composition changes including increase in fat mass (FM), central fat distribution, decrease in fat free mass (FFM) and skeletal muscle which are risk factors for DM. This study aims to evaluate gender differences in body composition in pre-frail diabetics and association with physical performance, cognitive function and perceived health. In addition, we aim to explore the association of obesity, sarcopenia, sarcopenic obesity, and body composition in pre-frail older adults to DM status. Cross-sectional study of 192 pre-frail community dwelling older adults (≥ 65 years). Data was collected on demographics, physical function, cognition, frailty, sarcopenia, perceived health and body composition using the InBody S10. Univariate and multivariate logistic regression were undertaken to explore the association of sarcopenic obesity, obesity, sarcopenia and body composition measures to DM status. There were insignificant within-gender differences for physical function, cognition and body composition, except for a higher prevalence of obesity defined by body mass index (BMI) and body fat percentage (BF%), increased fat mass index(FMI) and fat free mass index(FFMI) in females with DM. There were significant between-gender differences for those with DM where females overall had lower education levels, lower perceived health, higher prevalence of depression and low mental vitality, lower overall physical function (low short physical performance battery scores, low gait speed and hand grip strength), lower cognitive scores, lower muscle mass and muscle quality with higher FMI, FM/FFM and visceral fat area(VFA). BMI, VFA>100 cm2, FMI and FFMI were found to be independently associated with DM status after multivariable adjustment. Within pre-frail DM vs non-DM, there were insignificant differences in body composition, physical function, cognition and perceived health within gender except for FMI, BF% and FFMI in females. There were significant differences between gender in pre-frail DM in muscle mass, quality, functional, cognitive and mental status. Further longitudinal studies are required to understand the pathogenesis, trajectory of DM and protective role of oral hypoglycemics in pre-frail older adults.

Merchant RA ，Soong JTY ，Morley JE 《Frontiers in Endocrinology》

Fat and fat-free mass as important determinants of body composition assessment in relation to sarcopenic obesity.

Fat and fat-free/muscle mass and their ratio reflecting the possible presence of obesity or sarcopenic obesity are important in assessing body composition. The aim of the work was to assess the use of fat and fat-free mass and their ratio in the diagnosis of sarcopenic obesity, as well as correlations with selected anthropometric, somatic and biochemical parameters and indices. The object of the study was a group of 201 women (20-68 aged) randomly selected from the population without the presence of a serious disease or without the use of medication. Body composition was assessed by the MFBIA method (InBody 720). We used the ratio of fat to fat-free mass (FM/FFM) to define sarcopenic obesity. A Biolis 24i Premium biochemical analyzer was used to determine biochemical parameters. Using FM and FFM values and their mutual ratio, we identified women with a healthy body weight (28.9%), obese women (58.2%) and women with sarcopenic obesity (12.9%). Values of anthropometric parameters (body weight, BMI, WC, WHR, WHtR, BAI, FM (kg, %), FMI, VFA, FFM (kg), FFMI, SMM (kg), SMMI, ICW, ECW, TBW, CHC, HC), with the exception of FFM (%), SMM (%) and TBW (%), increased significantly with increasing FM/FFM values, so the highest values were found in subjects with sarcopenic obesity. In the case of biochemical parameters, with increasing FM/FFM values, the values of T-CH, LDL, TAG, GLU, hs-CRP, UA, systolic and diastolic blood pressure also increased, so the highest values were again found in women with sarcopenic obesity. HDL values, on the contrary, decreased. FM/FFM had the strongest positive association with the proportion of fat mass on body weight (r=0.989), then with FMI (r=0.980), FM (r=0.965), VFA (r=0.938), WHtR (r=0.937), BMI (r=0.922), WC (r=0.901. We found the strongest negative association with the proportion of FFM on body weight (r=-0.989), the proportion of total body water (r=-0.988) and the proportion of skeletal muscle mass (r=-0.987). FM/FFM correlates excellently with FM and VFA and can be implemented to diagnose obesity. In order to comprehensively evaluate the state of health and body composition, the proportionality of not only fat, but also fat-free/muscle mass should be analyzed, because it turns out that a negative impact on health and survival is associated not only with an excessive amount of adipose tissue, but also with a lower muscle mass.

Gažarová M ，Bihari M ，Šoltís J 《-》

Association of anthropometric measures with fat and fat-free mass in the elderly: The Rotterdam study.

The decrease in fat-free mass (FFM) seen in many elderly people is usually associated with an increase in fat mass (FM), a state referred to as sarcopenic obesity. It is not clear which anthropometric measures are best used to identify sarcopenic obesity. We therefore evaluated which anthropometric measures are differentially associated with FM and FFM. The anthropometric measures tested were body mass index (BMI), waist circumference (WC), and a body shape index (ABSI = WC/(BMI(2/3)*Height(1/2))). FM and FFM were estimated by dual-energy X-ray absorptiometry. An index-score was calculated for both FM (FMI) and FFM (FFMI) by dividing FM and FFM by height. Multivariable linear regression models were used to assess the associations of BMI, WC and ABSI with FMI and FFMI among 3612 participants (2092 women) from the prospective population-based Rotterdam Study. In multivariate models adjusted for confounders, BMI and WC were positively associated with both FMI and FFMI in men and women. ABSI was positively associated with FMI (β 1.01, 95% confidence interval (95%CI) 0.85, 1.17) and negatively associated with FFMI (β -0.28, 95%CI -0.38, -0.17) in men. In women, ABSI was not associated with FMI and was positively associated with FFMI (β 0.18, 95%CI 0.10, 0.26). While BMI and WC were both positively associated with FM and FFM, ABSI showed a differential association with FM and FFM in men, but not in women. Since sarcopenic obesity is associated with decreased FFM and increased FM, ABSI could be a useful tool for identifying men at higher risk of sarcopenic obesity.

Dhana K ，Koolhaas CM ，Schoufour JD ，Rivadeneira F ，Hofman A ，Kavousi M ，Franco OH ... -  《-》

Comparison of body mass index and fat mass index to classify body composition in adolescents-The EVA4YOU study.

The objectives of this study were to develop age- and sex-specific reference percentiles for fat mass index (FMI) and fat-free mass index (FFMI) in adolescents aged 14 to 19 years and to determine differences in overweight/obesity classification by FMI and body mass index (BMI). The EVA4YOU study is a single-center cross-sectional study conducted in western Austria. Cardiovascular risks including anthropometric measurements and bioelectrical impedance analysis were assessed in adolescents (mean age 17 years). FMI and FFMI were calculated as the ratio of fat mass (FM) and fat-free mass (FFM) to the square of height and compared to study population-specific BMI percentiles. One thousand four hundred twenty-two adolescents were included in the analysis. Girls had a significantly higher mean FM and FMI and a significantly lower mean FFM, FFMI (p < 0.001, each), and mean BMI (p = 0.020) than boys. Body composition classification by FMI and BMI percentiles shows a concordance for the < 75th and > 97th percentile, but a significant difference in percentile rank classifications between these two cut-off values (all p < 0.05). Based on FMI, 15.5% (221/1422) of the whole population and 29.4% (92/313) of those between the 75th and 97th percentiles are classified one category higher or lower than those assigned by BMI.  Classification of normal or pathologic body composition based on BMI and FMI shows good accordance in the clearly normal or pathologic range. In an intermediate range, FMI reclassifies categories based on BMI in more than a quarter of adolescents. Cut-off values to differentiate normal from pathologic FMI values on a biological basis are needed. The study is registered at www. gov  (Identifier: NCT04598685; Date of registration: October 22, 2020). • Chronic non-communicable diseases (NCDs) are the leading cause of morbidity and mortality globally, with major risk factors including unhealthy diets, harmful behaviors, and obesity. Obesity in children and adolescents is a key risk factor for later NCDs, which is commonly measured by Body Mass Index (BMI). • BMI can be misleading as it doesn't distinguish between fat mass (FM) and fat-free mass (FFM), leading to potential misclassification of obesity in children. Previous studies have already suggested the use of the Fat Mass Index (FMI) and Fat-Free Mass Index (FFMI) as a more accurate measures of body composition. • This study adds the first age- and sex-specific reference values for FMI and FFMI in Austrian adolescents using bioelectrical impedance analysis (BIA) as a safe and secure measurement method of a large representative cohort. • We found percentile misclassification between BMI and FMI when categorizing for obesity, especially in intermediate categories of body composition. Furthermore, when comparing the new reference values for FMI and FFMI to existing ones from the US, UK, and Germany we could show a good alignment within the European cohorts and major differences with American values, indicating and confirming the difference of FMI and FFMI for different populations of different ethnical background, living on different continents.

Messner A ，Nairz J ，Kiechl S ，Winder B ，Pechlaner R ，Geiger R ，Knoflach M ，Kiechl-Kohlendorfer U ，EVA4YOU Tyrol Study Group ... -  《-》