Norm references of fat-free mass index and fat mass index and subtypes of obesity based on the combined FFMI–%BF indices in the Korean adults aged 18–89yr

Study of Body Composition by Biphotonic X-ray Absorptiometry in a Moroccan Female Population, an Indicator of Obesity?

INTRODUCTION

Our purpose was to study the body composition in a healthy female Moroccan adult group, and to help physicians to evaluate nutritional status.

MATERIALS AND METHODS

Five hundred and nineteen healthy women aged from 20 to 80 years were included in the study. Bone mineral density at the hip and lumbar spine and the body composition parameters were measured by dual-energy X-ray absorptiometry: fat mass (FM), fat-free mass (FFM), and percentage (%) of body fat. The FFM index (FFMI) and the FM index (FMI) were calculated. We analyzed the population by age and body mass index (BMI) defined groups.

RESULTS

The mean age of the population was 53.14 ± 13.69 years with an average BMI of 29.30 ± 5.04 kg/m2. Means of FM and FFM were 33.93 ± 9.18 kg and 36.91 ± 5 kg, respectively, with FM and FFMI of 13.65 ± 3.66 kg/m2 and 14.85 ± 1.91 kg/m2, respectively. The % FM, FFM, and their corresponding indices increased with age; a statistically significant difference was observed between the 20 and 39 age categories and the two other categories. The BMI category analysis showed that FFMI and FMI increased in obese women with a statistically significant difference between the four groups. Age and BMI were correlated significantly with the different parameters.

CONCLUSION

This is the first Moroccan study to present body composition indexes in healthy Moroccan female adults. These reference values may be useful for the clinical evaluation of body composition and nutritional status.

Loss of Muscle Mass in Delayed Diagnosis of Renal Cysts and Diabetes Syndrome: A Case Report

Renal cysts and diabetes syndrome (RCAD) is a rare disease caused by abnormalities in the HNF1B gene, which often leads to dysfunction in the renal, genital tracts, and pancreas. In this report, we present a rare case of a 27-year-old female with muscle mass loss who experienced a delayed diagnosis of RCAD. The patient had been misdiagnosed as "type 1 diabetes" for a long period. Her main clinical manifestations included muscle loss, renal magnesium loss, and an incomplete longitudinal uterus. Ultimately, the diagnosis of RCAD syndrome was confirmed through genetic testing. Reduction of muscle mass, although rarely reported, can progress to sarcopenia. Therefore, early intervention should be strongly emphasized. Furthermore, in future research, it is crucial to explore the mechanisms and relationships underlying these patients and their unusual manifestations.

Exploring Handgrip Strength as a Cross-cultural Correlate of Body Composition and Upper Body Strength in Older Adults from Costa Rica and Kansas

Sarcopenia and disability in older adults are often characterized by body composition measurements; however, the gold standard of body composition measurement, dual-energy X-ray absorptiometry (DEXA), is expensive to acquire and maintain, making its use in low and middle income countries (LMIC) it out-of-reach in developing nations. Because these LMIC will bear a disproportionate amount of chronic disease burden due to global aging trends, it is important that reliable, low-cost surrogates need to be developed. Handgrip strength (HGS) is a reliable measure of disability in older adults but has not been used widely in diverse populations. This study compared HGS to multiple measurements of body composition in older adults from the US (Kansas) and a middle-income country (Costa Rica) to test if HGS is a cross-culturally appropriate predictive measure that yields reliable estimates across developed and developing nations. Percent body fat (%BF), lean tissue mass index (LTMI), appendicular lean soft tissue index (ALSTI), body fat mass index (BFMI), bone mineral density (BMD), and HGS were measured in older Costa Ricans (n = 78) and Kansans (n = 100). HGS predicted lean arm mass with equal accuracy for both samples (p ≤ 0.05 for all groups), indicating that it is a reliable, low-cost and widely available estimate of upper body lean muscle mass. Older adults from Costa Rica showed different body composition overall and HGS than controls from Kansas. Handgrip operates equivalently in the US and Mesoamerica and is a valid estimate of lean arm muscle mass as derived by the more expensive DEXA.

Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning

Background

Metabolic syndrome (Mets) is considered a global epidemic of the 21st century, predisposing to cardiometabolic diseases. This study aims to describe and compare the body composition profiles between metabolic healthy (MH) and metabolic unhealthy (MU) phenotype in normal and obesity population in China, and to explore the predictive ability of body composition indices to distinguish MU by generating machine learning algorithms.

Methods

A cross-sectional study was conducted and the subjects who came to the hospital to receive a health examination were enrolled. Body composition was assessed using bioelectrical impedance analyser. A model generator with a gradient-boosting tree algorithm (LightGBM) combined with the SHapley Additive exPlanations method was adapted to train and interpret the model. Receiver-operating characteristic curves were used to analyze the predictive value.

Results

We found the significant difference in body composition parameters between the metabolic healthy normal weight (MHNW), metabolic healthy obesity (MHO), metabolic unhealthy normal weight (MUNW) and metabolic unhealthy obesity (MUO) individuals, especially among the MHNW, MUNW and MUO phenotype. MHNW phenotype had significantly lower whole fat mass (FM), trunk FM and trunk free fat mass (FFM), and had significantly lower visceral fat areas compared to MUNW and MUO phenotype, respectively. The bioimpedance phase angle, waist-hip ratio (WHR) and free fat mass index (FFMI) were found to be remarkably lower in MHNW than in MUNW and MUO groups, and lower in MHO than in MUO group. For predictive analysis, the LightGBM-based model identified 32 status-predicting features for MUNW with MHNW group as the reference, MUO with MHO as the reference and MUO with MHNW as the reference, achieved high discriminative power, with area under the curve (AUC) values of 0.842 [0.658, 1.000] for MUNW vs. MHNW, 0.746 [0.599, 0.893] for MUO vs. MHO and 0.968 [0.968, 1.000] for MUO and MHNW, respectively. A 2-variable model was developed for more practical clinical applications. WHR > 0.92 and FFMI > 18.5 kg/m2 predict the increased risk of MU.

Conclusion

Body composition measurement and validation of this model could be a valuable approach for the early management and prevention of MU, whether in obese or normal population.

Body composition assessment using bioelectrical impedance analysis (BIA) in a wide cohort of patients affected with mild to severe obesity

BACKGROUND & AIMS

Obesity is characterized by fat mass excess (FM), extra cellular water increase (ECW) and, with ageing, decrease in fat free mass (FFM). The validity of body impedance analysis (BIA) in patients with mild to severe obesity is still debated. The purpose of this study is to describe the Resistance (Rz) and Reactance (Xc) values obtained by Body Impedance Analysis (BIA) in a wide cohort of Italian patients with mild to severe obesity. The secondary endpoint is to describe the resulting body composition values (as percentage and indexes) in this population.

METHODS

The study enrolled adult in-patients with mild to severe obesity (classified with class I, II and III obesity) undergoing clinical care rehabilitation program for obesity complications and weight loss. BIA values were grouped by sex, BMI and age classes.

RESULTS

A total of 8303 patients with obesity, aged 18 to 90 y, were studied. The Resistance (Rz) and Reactance (Xc) were reported by sex, age and BMI classes. In women and men both, the phase angle (PhA) decreases with increasing BMI (kg/m²) and the resulting BIA vector was significantly shifted. The FM index (FMI) was higher (p < 0.0001) in women while FFM index (FFMI) was higher in men (p < 0.0001) and significantly associated with BMI. FFMI decreased with age in both sex (p < 0.0001). Skeletal mass (SM) presents a progressive reduction in relation to age and gender both.

CONCLUSIONS

The present BIA-based body composition analysis in a wide cohort of mild to severe obese patients revealed a significantly decreased Rz and Xc values with a consequent significant decrease of PhA in a BMI-dependent manner. The body compartments estimation with available equations was BMI, sex and age dependent. These observational results could be the basis for the development of new equations adapted for patients suffering from obesity.

Reference values of skeletal muscle mass, fat mass and fat-to-muscle ratio for rural middle age and older adults in western China

BACKGROUND

Skeletal muscle mass (SMM), fat mass (FM) and fat-to-muscle ratio (FMR) are significant indicators in epidemiology studies and clinical settings. The aim of this study was to establish age-related and sex-specific reference values for skeletal muscle mass index (SMMI), fat mass index (FMI) and FMR by bioelectrical impedance analysis (BIA) for healthy rural adults in western China.

METHODS

This study is a cross-sectional study from Ningxia cohort study, included 13,790 individuals aged 35 to 74 years. Bioelectrical impedance analysis (BIA) was performed to measure body composition. Lambda-mu-sigma method was used to establish age-related and sex-specific percentile curves for SMMI, FMI and FMR.

RESULTS

Overall, men had higher SMMI, but lower FMI and FMR than women for all ages. The SMMI decreased rapidly with age for men and women after 55 years and 45 years, respectively. FMI in men remain stable until 70 years; women's FMI showed a rapidly increasing after 50 years. The FMR increased consistently after 35 years for both men and women. These age-related and sex-specific reference values were established with the mean ± SD as the normal reference range.

CONCLUSIONS

These reference values could be used as simple tools to identify age-specific low SMMI or high FMI and facilitate earlier identification sarcopenia or sarcopenic obesity in rural Chinese adults.

The myostatin rs1805086 variant is associated with obesity in Mexican adults, independently of metabolic risk factors

AIM

To determine whether rs1805086 is associated with obesity and metabolic disturbances in a Mexican adult population.

SUBJECTS AND METHODS

We genotyped rs1805086 in 1024 men and women aged 18-58 years. Anthropometric and body fat data were used to estimate obesity. Biochemical parameters were measured and DNA was used to determine the rs1805086 genotype.

RESULTS

rs1805086 heterozygous AG frequency was 5.4%, and the homozygous for the risk allele GG was absent. Heterozygous had higher levels of body mass index (BMI) and waist/height ratio (WHtR). Heterozygous subjects showed a greater total and central obesity compared to the homozygous for ancestral allele AA (OR BMI > 30 kg/m² ₌ 2.35, 95% CI 1.29-4.29; OR WHtR > 0.5 = 2.03, 95% CI 1.19-3.45; OR elevated fat mass (EFM) %= 1.72, 95% CI 1.01-2.92; OR fat mass index (FMI)>p85 = 1.96, 95% CI 1.05-3.68). rs1805086 was not associated with metabolic alterations.

CONCLUSION

Heterozygosity for rs1805086 showed a predisposition to having elevated overall and central obesity parameters. This association with adiposity seems to be independent of metabolic risk.

Normative fat-free mass index values for a diverse sample of collegiate female athletes

The purpose of this study was to establish normative fat-free mass index (FFMI) ranges in collegiate female athletes. A sample of 266 female athletes (Mean±SD; Age: 19.7 ± 1.5 yrs, Height: 166.0 ± 6.4 cm, Weight: 63.2 ± 8.8 kg) were included in analyses. Dual-energy X-ray absorptiometry measured bone mineral content (BMC; kg) and lean mass (LM; kg). Fat-free mass index was calculated as follows: FFMI = (BMC + LM)/Height². Participants were classified by sport: cross-country (XC), field hockey, football, gymnastics, lacrosse, resistance-trained, swimming track. Mean, range and percentile ranks of FFMI were calculated for the full sample for each cohort. For all females, mean FFMI was 16.9 ± 1.7 kg/m², FFMI values ranged from 13.3 to 25.5 kg/m². The XC athletes had the lowest FFMI (15.3 ± 0.96 kg/m²; p < 0.001). Mean FFMI measures were similar between all other female athletes. Percentile ranks varied across sport; median FFMI was highest for football (18.0 kg/m²), lowest for XC (15.1 kg/m²) and ranged between 16.4 and 17.3 kg/m² for all other athletes. Establishing sport-specific FFMI values for female athletes may be beneficial for athletes and coaches by leading to more appropriate body composition goals based on FFM.

Characteristics and reference values of fat mass index and fat free mass index by bioelectrical impedance analysis in an adult population

BACKGROUND & AIMS

We aim to examine the influence of sex, age, region and ethnicity on fat mass index (FMI) and fat free mass index (FFMI), and to establish FMI and FFMI reference values in Chinese adults.

METHODS

A stratified cluster sampling method was adopted to enroll Chinese participants in this cross-sectional study. Questionnaire surveys and medical examinations were performed to collect data, and body composition parameters were measured by bioelectrical impedance analysis. FMI and FFMI were calculated as the ratio of fat mass and fat free mass to the square of height. Differences in mean values for parameters were tested by Student's t-test or one-way analysis of variance. Reference values of FMI and FFMI were obtained using the percentiles method.

RESULTS

A total of 8959 multiethnic healthy Chinese adults were included in the analysis. Males had higher mean FFMI (males, 18.6 ± 1.6 kg/m²; females, 15.7 ± 1.1 kg/m², P < 0.001) but lower mean FMI (males, 5.1 ± 2.1 kg/m²; females, 7.8 ± 2.8 kg/m², P < 0.001) than did female participants regardless of age and ethnicity. For both sexes, FMI (Male: Bouyei, 4.2 ± 1.8 kg/m²; Uygur, 5.8 ± 2.2 kg/m², P < 0.001; Female: Bouyei, 6.7 ± 2.3 kg/m²; Uygur, 9.0 ± 3.2 kg/m², P < 0.001) and FFMI (Male: Bouyei, 17.8 ± 1.4 kg/m²; Uygur, 19.4 ± 1.6 kg/m², P < 0.001; Female: Bouyei, 15.1 ± 1.0 kg/m²; Uygur, 16.3 ± 1.1 kg/m², P < 0.001) were lowest in Bouyeis and highest in Uygurs. FMI and FFMI values increased with age until they peaked in the 30-39 year age group in males and after the age of 40 years in females for all ethnic groups. Reference values (5th-95th percentile) of FMI and FFMI were presented according to gender, age, region and ethnicity.

CONCLUSION

The body composition of Chinese population differs in different age, sex, ethnicity and region subgroups. Practitioners and future studies may need to consider different reference values for FMI and FFMI in Chinese adults among Han, Bouyei and Uygur populations; these values can serve as indices for evaluating nutrition status and identifying abnormalities in body composition.

Reference Values and Age Differences in Body Composition of Community-Dwelling Older Japanese Men and Women: A Pooled Analysis of Four Cohort Studies

Objectives

To determine age- and sex-specific body composition reference values and investigate age differences in these parameters for community-dwelling older Japanese men and women, using direct segmental multi-frequency bioelectrical impedance analysis.

Methods

We conducted a pooled analysis of data collected in four cohort studies between 2008 and 2012: Kusatsu Longitudinal Study, Hatoyama Cohort Study, Itabashi Cohort Study, and Kashiwa Cohort Study. The pooled analysis included cross-sectional data from 4478 nondisabled, community-dwelling adults aged 65-94 years (2145 men, 2333 women; mean age: 72.9 years in men and 72.6 years in women). Body weight, fat mass (FM), percentage FM, fat-free mass (FFM), and appendicular lean soft tissue mass were measured using the InBody 720 and 430 (Biospace Co. Ltd, Seoul, Korea). The values were then normalized by height in meters squared to determine body mass index (BMI), FM index (FMI), FFM index (FFMI), and skeletal muscle mass index (SMI).

Results

Simple means (standard deviation) of BMI, percentage FM, FMI, FFMI, and SMI were 23.4 (2.9) kg/m², 24.9 (6.3)%, 5.96 (2.09) kg/m², 17.4 (1.5) kg/m², and 7.29 (0.76) kg/m², respectively, in men and 22.7 (3.3) kg/m², 31.7 (7.1)%, 7.40 (2.61) kg/m², 15.3 (1.2) kg/m², and 5.86 (0.67) kg/m², respectively, in women. We then calculated quartiles and quintiles for these indices after stratifying for sex and 5-year age group. FFMI and SMI decreased significantly with age in both sexes (P < 0.001 for trends), but FFMI remained constant among the women with only a 1% decrease up to age 84 years. Percentage FM increased significantly, with age (P < 0.001 in men and P = 0.045 in women for trends), but FMI was unchanged in both sexes (P = 0.147 in men and P = 0.176 in women for trends).

Conclusion

The present data should be useful in the clinical evaluation of body composition of older Japanese and for international comparisons. The small age-related decrease in FFMI may be a noteworthy characteristic of body composition change in older Japanese women.

Influence of age and gender on fat mass, fat-free mass and skeletal muscle mass among Australian adults: the Australian diabetes, obesity and lifestyle study (AusDiab)

BACKGROUND

Bioelectrical impedance (BIA) represents a simple, inexpensive and non-invasive method that is often used to assess fat-mass (FM) and fat-free mass (FFM) in large population-based cohorts.

OBJECTIVE

The aim of this study was to describe the reference ranges and examine the influence of age and gender on FM, FFM and skeletal muscle mass (SMM) as well as height-adjusted estimates of FM [fat mass index (FMI)], FFM [fat-free mass index (FFMI)] and SMM [SMM index (SMI)] in a national, population-based cohort of Australian adults.

DESIGN AND PARTICIPANTS

The analytical sample included a total of 8,582 adults aged 25-91 years of Europid origin with complete data involved in the cross-sectional 1999-2000 Australian, Diabetes, Obesity and Lifestyle (AusDiab) Study.

MEASUREMENTS

Bioelectrical impedance analysis was used to examine components of body composition. Demographic information was derived from a household interview.

RESULTS

For both genders, FFM, SMM and SMI decreased linearly from the age of 25 years, with the exception that in men SMI was not related to age and FFM peaked at age 38 years before declining thereafter. The relative loss from peak values to ≥75 years in FFM (6-8%) and SMM (11-15%) was similar between men and women. For FM and FMI, there was a curvilinear relationship with age in both genders, but peak values were detected 6-7 years later in women with a similar relative loss thereafter. For FFMI there was no change with age in men and a modest increase in women.

CONCLUSION

In Australian adults there is heterogeneity in the age of onset, pattern and magnitude of changes in the different measures of muscle and fat mass derived from BIA, but overall the age-related losses were similar between men and women.