A population-based approach to define body-composition phenotypes

Impact of high fat and low lean mass phenotype on bone mineral content: A cross-sectional study of Chinese adolescent population

BACKGROUND AND OBJECTIVE

Research on body composition phenotypes and bone health in adolescents is limited. Hence, this study aimed to analyze the relationship between different body composition phenotypes, bone mineral content, and bone metabolism markers in Chinese adolescents.

METHODS

In this cross-sectional study, 1852 adolescents aged 12 to 18 years were selected from six schools in Yinchuan City between 2017 and 2020 using stratified cluster random sampling. The participant's body composition and bone mineral content (BMC) were measured using bioelectrical impedance analysis (BIA). Serum bone metabolic markers (OC, CTX, and Ca) were measured. Based on their FMI and LMI, individuals were categorized into four body composition phenotypes: low fat mass-low lean mass (LFMI-LLMI), low fat mass-high lean mass (LFMI-HLMI), high fat mass-high lean mass (HFMI-HLMI), high fat mass-low lean mass (HFMI-LLMI).

RESULTS

There was a statistically significant difference between the four different body composition phenotypes with BMC, CTX and Ca in boys (all P < 0.05), similar conclusions were found in girls, except the OC and CTX. After adjusting for age, gender, smoking, drinking, and others, compared with the LFMI-HLMI reference group, the two high FMI groups (HFMI-LLMI and HFMI-HLMI) had a greater negative correlation with BMC, while the low BMC risk of the HFMI-LLMI group was the highest (OR = 33.28; 95%CI: 11.12-99.63; P < 0.001). The correlation between BMC of different body composition phenotypes in boys was greater than that in girls. HFMI-HLMI is a risk phenotype negatively associated with Ca content (β = -0.12; 95%CI: -0.19 to -0.04; P < 0.05). Regardless of body composition level, BMC was always negatively correlated with fat mass (LLMI: β = -0.27; 95%CI: -0.32-0.21; HLMI: β = -0.52, 95%CI: -0.65-0.40) and positively correlated with lean mass (LFMI: β =0.24; 95%CI: 0.20-0.28; HFMI: β =0.23, 95%CI:0.13-0.33) (all P < 0.001). The fat mass showed different correlations with OC and CTX in girls and boys based on LLMI or HLMI (all P < 0.05).

CONCLUSION

HFMI-LLMI is a risk phenotype of low BMC in Chinese adolescents, and the relationship between fat mass and bone metabolism markers is affected by lean body mass and gender.

Body Composition, Sarcopenic Obesity, and Cognitive Function in Older Adults: Findings From the National Health and Nutrition Examination Survey (NHANES) 1999-2002 and 2011-2014

OBJECTIVE

Sarcopenic-obesity (SO) is characterized by the concomitant presence of low muscle mass and high adiposity. This study explores the association of body composition and SO phenotypes with cognitive function in older adults.

METHODS

Cross-sectional data in older adults (≥60 years) from NHANES 1999-2002 and 2011-2014 were used. In the 1999-2002 cohort, phenotypes were derived from body mass index (BMI) and dual-X-ray-absorptiometry, and cognition was assessed the by Digit-Symbol-Substitution-Test (DSST). In the 2011-2014 cohort, phenotypes were derived from BMI, waist-circumference (WC), and hand-grip-strength (HGS). Cognition was assessed using four tests: DSST, Animal Fluency, the Consortium-to-Establish-a-Registry-for-Alzheimer's-Disease-Delayed-Recall, and Word Learning. Mediation analysis was conducted to evaluate the contribution of inflammation (C-reactive-protein, CRP) and insulin resistance (Homeostatic-Model-Assessment-for-Insulin-Resistance, HOMA-IR) to the association between body composition and cognitive outcomes.

RESULTS

The SO phenotype had the lowest DSST mean scores (p < 0.05) and was associated with a significant risk of cognitive impairment [Odds Ratio (OR) = 1.9; 95%CI 1.0-3.7, p = 0.027] in the 1999-2002 cohort. A higher ratio of fat mass and fat free mass (FM/FFM) also showed a greater risk of cognitive impairment (OR = 2.0; 95%CI 1.3-3.1, p = 0.004). In the 2011-2014 cohort, the high WC-Low HGS group showed significantly lower scores on all four cognitive tests (p < 0.05) and a higher risk of cognitive impairment. CRP and HOMA-IR were significant partial mediators of the association between FM/FFM and DSST in the 1999-2002 cohort.

CONCLUSIONS

The SO phenotype was associated with a higher risk of cognitive impairment in older adults. Insulin resistance and inflammation may represent key mechanisms linking SO to the development of cognitive impairment.

Body composition and aging: cross-sectional results from the INSPIRE study in people 20 to 93 years old

Aging is characterized by several major changes, including altered body composition, which is associated with numerous negative clinical consequences such as sarcopenia, osteoporosis, and frailty. The study is to evaluate body composition parameters depending on age and sex in a population ranging from the young adult to the very old, and to identify break points in the association between body composition and age. In this cross-sectional study, we included the enrolment population of the French INSPIRE-T prospective cohort, accounting for 915 subjects (62% female). Age ranged from 20 to 93 years, median age (years) was 63 (IQR 27). Body composition (lean mass, fat mass, and bone mineral content) was assessed with dual-X-ray absorptiometry (DXA). Different break points in the relationship between age and body composition variables in males and females were identified using a segmented regression analysis adjusted on physical activity, nutritional status, educational level, and comorbidities. Lean mass decreased from the age of 55 years for males (CI 95% 44-66) and 31 years for females (CI 95% 23-39). For fat mass, we observed a trend towards an increase with age for males. For females, we observed an increase with age up to age 75 (CI 95% 62-86), followed by a decreasing trend. In this study, we described the relationship between body composition and age as a function of sex, establishing a foundation for further studies on predictive biomarkers of age-related body composition alteration.

Predicted body fat percentage, fat mass and lean body mass in relation to risk of prostate cancer: Results from the NHANES 1999 to 2010

The purpose of this study is to examine the relationship between fat mass (FM), body fat percentage (BF%), lean body mass (LM), and prostate cancer (PCa), and evaluate their potential impact on the risk of PCa. Data from the National Health and Nutrition Examination Survey (NHANES) of the United States were utilized. Adult male participants from 6 survey cycles between 1999 and 2010 were selected as the study sample. Multivariable logistic regression analysis was conducted to explore the association between BF%, LM, and PCa, while controlling for potential confounding variables. Among the 8440 participants, 359 cases of PCa were diagnosed. The relationship between BF%, LM, and PCa was nonlinear. In the multivariable logistic regression analysis, there was an independent association between BF% and PCa risk (OR: 1.04, 95% CI: 1.02-1.06), suggesting that higher BF% levels are associated with an increased risk of PCa. Conversely, higher LM levels were associated with a decreased risk of PCa (OR: 0.96, 95% CI: 0.95-0.98). The findings of this study demonstrate a correlation between BF% and LM with PCa, but do not provide direct evidence of a causal relationship. Higher BF% levels are associated with an increased risk of PCa, while higher LM levels are associated with a decreased risk. These results provide valuable insights for understanding and potentially preventing PCa, although further research is needed to fully comprehend the underlying mechanisms.

Advances in body composition: a 100-year journey

Knowledge of human body composition at the dawn of the twentieth century was based largely on cadaver studies and chemical analyses of isolated organs and tissues. Matters soon changed by the nineteen twenties when the Czech anthropologist Jindřich Matiegka introduced an influential new anthropometric method of fractionating body mass into subcutaneous adipose tissue and other major body components. Today, one century later, investigators can not only quantify every major body component in vivo at the atomic, molecular, cellular, tissue-organ, and whole-body organizational levels, but go far beyond to organ and tissue-specific composition and metabolite estimates. These advances are leading to an improved understanding of adiposity structure-function relations, discovery of new obesity phenotypes, and a mechanistic basis of some weight-related pathophysiological processes and adverse clinical outcomes. What factors over the past one hundred years combined to generate these profound new body composition measurement capabilities in living humans? This perspective tracks the origins of these scientific innovations with the aim of providing insights on current methodology gaps and future research needs.

Body composition assessment by artificial intelligence can be a predictive tool for short-term postoperative complications in Hartmann's reversals

BACKGROUND

Hartmann's reversal, a complex elective surgery, reverses and closes the colostomy in individuals who previously underwent a Hartmann's procedure due to colonic pathology like cancer or diverticulitis. It demands careful planning and patient optimisation to help reduce postoperative complications. Preoperative evaluation of body composition has been useful in identifying patients at high risk of short-term postoperative outcomes following colorectal cancer surgery. We sought to explore the use of our in-house derived Artificial Intelligence (AI) algorithm to measure body composition within patients undergoing Hartmann's reversal procedure in the prediction of short-term postoperative complications.

METHODS

A retrospective study of all patients who underwent Hartmann's reversal within a single tertiary referral centre (Western) in Melbourne, Australia and who had a preoperative Computerised Tomography (CT) scan performed. Body composition was measured using our previously validated AI algorithm for body segmentation developed by the Department of Surgery, Western Precinct, University of Melbourne. Sarcopenia in our study was defined as a skeletal muscle index (SMI), calculated as Skeletal Muscle Area (SMA) /height2 < 38.5 cm2/m2 in women and < 52.4 cm2/m2 in men.

RESULTS

Between 2010 and 2020, 47 patients (mean age 63.1 ± 12.3 years; male, n = 28 (59.6%) underwent body composition analysis. Twenty-one patients (44.7%) were sarcopenic, and 12 (25.5%) had evidence of sarcopenic obesity. The most common postoperative complication was surgical site infection (SSI) (n = 8, 17%). Sarcopenia (n = 7, 87.5%, p = 0.02) and sarcopenic obesity (n = 5, 62.5%, p = 0.02) were significantly associated with SSIs. The risks of developing an SSI were 8.7 times greater when sarcopenia was present.

CONCLUSION

Sarcopenia and sarcopenic obesity were related to postoperative complications following Hartmann's reversal. Body composition measured by a validated AI algorithm may be a beneficial tool for predicting short-term surgical outcomes for these patients.

Association of physical functional activity impairment with severity of sarcopenic obesity: findings from National Health and Nutrition Examination Survey

We aim to clarify the relationship between low skeletal muscle mass and varying levels of adiposity and to identify the types of physical function impairments associated with sarcopenic obesity (SO). This study examined cross-sectional data from the National Health and Nutrition Examination Survey with whole-body dual-energy X-ray absorptiometry (DXA) scans. The data included age, gender, DXA-assessed body composition, and physical functional activity with performing daily tasks by questionnaire. We subdivided the data by body composition into a non-SO group and a SO group (ASMI 0-49.99% and FMI of 50-100%), after which the SO data were subdivided into three classes. A higher class indicated higher adiposity and lower muscle mass. The physical function impairment of the two groups was compared. Our study examined 7161 individuals, of which 4907 did not have SO and 2254 had SO, and their data were further divided into three classes (i.e., class I, 826 individuals; class II, 1300 individuals; and class III, 128 individuals). Significant differences in demographics and DXA parameters were identified between the non-SO and SO groups (P < 0.001); the individuals with SO were older, included more women, and exhibited high adiposity and less lean muscle mass. The individuals with class III SO exhibited greater differences and reported more difficulty in performing daily activities. The individuals with class III SO exhibited the most severe physical function impairment. Our study highlights the considerable difficulties encountered by individuals with SO in performing daily activities. Given this finding, customized rehabilitation strategies should be implemented to improve the quality of life of individuals with SO.

Sarcopenic Obesity in Community-Dwelling Spanish Adults Older than 65 Years

Sarcopenic obesity (SO) is diagnosed when sarcopenia and obesity coexist in patients. The objective of this study was to determine the prevalence of SO under different diagnostic criteria in community-dwelling Spanish adults aged over 65 years residing in Valencia (Spain). The research was conducted as an observational and cross-sectional study with a sample size of 202 subjects. To diagnose sarcopenia, we used the tests proposed by the European Working Group on Sarcopenia in Older People in 2019 (EWGSOP2): SARC-F, grip strength, sit-to-stand, gait speed, Appendicular Skeletal Muscle Mass (ASMM), and Short Physical Performance Battery (SPPB). For obesity diagnosis, we used body mass index (BMI), waist circumference (WC), total body fat percentage (%TBF), and tricipital skinfold (TS). The prevalence of SO was 16.5% in women and 29% in men, according to any of the diagnostic criteria used to determine obesity. A higher proportion of SO was observed as age increased in both groups, although no significant differences were found. Most values obtained in tests related to SO diagnosis were worse in the group affected by the disease; however, there were two exceptions related to the amount of ASMM. In total, 18.8% of the participants presented SO according to any diagnostic criteria related to obesity. Our results suggest significant differences in the number of SO cases depending on diagnostic criteria used to determine the participants' obesity. BMI, WC, and TBF% were shown as principal variables to be included in obesity diagnosis within the SO construct. These findings underscore the need to unify criteria to standardize the diagnosis of SO in the global population.

Sarcopenia Diagnosis and Management in Hematological Malignancies and Differences with Cachexia and Frailty

Sarcopenia is a geriatric syndrome characterized by a progressive loss of systemic muscle mass and decreased muscle strength or physical function. Several conditions have a role in its pathogenesis, significantly impacting adverse outcomes such as falls, functional decline, frailty, disability, multiple hospitalizations, and mortality. In the oncological setting, sarcopenia is associated with an increased risk of treatment toxicity, postoperative complications, and a higher mortality rate related to other causes (e.g., pneumonia). In the hematological field, even more so, sarcopenia predicts toxicity and response to treatments. In patients with hematologic malignancy, low muscle mass is associated with adverse outcomes and is a predictor of overall survival and non-relapse mortality. Therefore, it is essential to correctly recognize sarcopenia, evaluate the risk factors and their impact on the patient's trajectory, and effectively treat sarcopenia. Sarcopenia is a reversible condition. The most effective intervention for reversing it is physical exercise combined with nutrition. The objective of clinical assessment focused on sarcopenia is to be able to carry out a "tailor-made treatment".

Normal values for body composition in adults are better represented by continuous reference ranges dependent on age and BMI

BACKGROUND & AIMS

Reference values for body composition parameters like skeletal muscle mass index (SMI) depend on age and BMI. To ensure reference intervals reflect these changes, they have traditionally been separated into groups of young adults based on sex and BMI. However, this static stratification oversimplifies the dynamic and gradual changes of body composition with increasing age and BMI. The aim was therefore to provide continuous reference ranges for body composition parameters.

METHODS

Cross-sectional data of 1958 healthy men and women with an age between 18 and 97 years and a BMI between 17.1 und 45.6 kg/m² were obtained between 2011 and 2019. Multiple regression analyses stratified by sex with age, age² and BMI as independent variables were conducted to predict fat mass index (FMI), visceral adipose tissue (VAT), SMI, appendicular lean soft tissue index (ALSTI) and the ratio between extracellular to total body water (ECW/TBW).

RESULTS

The regression models explained between 61 (VAT in women and ALSTI in men) and 93% of the variance in the respective body composition parameters (FMI in women). Age had only a minor impact (2-16%) whereas BMI substantially increased the explained variance of reference models for FMI, VAT and ALSTI (total explained variance 61-93%). In SMI, age is a major determinant of the explained variance (36% in men and 38% in women) with BMI equally contributing to the explained variance (total explained variance 72% in men and 75% in women). For ECW/TBW-ratio, age nearly completely explained the variance (79% in men and 74% in women) whereas BMI added only 2-3% to the explained variance.

CONCLUSIONS

In conclusion, the derived continuous reference ranges are expected to improve body composition evaluation especially in very overweight and very old persons. Future studies applying these reference equations need to validate these assumptions. STUDY REGISTRATION, CLINICALTRIALS.GOV: NCT01368640, NCT01481285, NCT03779932, NCT04028648.

The role of obesity in sarcopenia and the optimal body composition to prevent against sarcopenia and obesity

Background

Elderly people with low lean and high fat mass, are diagnosed with sarcopenic obesity (SO), and often have poor clinical outcomes. This study aimed to explore the relationship between obesity and sarcopenia, and the optimal proportion of fat and muscle for old individuals.

Methods

Participants aged 60 years or above were instructed to perform bioelectrical impedance analysis to obtain the muscle and fat indicators, and handgrip strength was also performed. Sarcopenia was diagnosed according to predicted appendicular skeletal muscle mass and function. Body mass index (BMI) and body fat percentage (BF%) were used to define obesity. The association of muscle and fat indicators were analyzed by Pearson's correlation coefficient. Pearson Chi-Square test was utilized to estimate odds ratios (OR) and 95% confidence intervals (CI) on the risk of sarcopenia according to obesity status.

Results

1637 old subjects (74.8 ± 7.8 years) participated in this study. Not only fat mass, but also muscle indicators were positively correlated to BMI and body weight (p < 0.05). Absolute muscle and fat mass in different positions had positive associations (p < 0.05). Muscle mass and strength were negatively related to appendicular fat mass percentage (p < 0.05). When defined by BMI (OR = 0.69, 95% CI [0.56, 0.86]; p = 0.001), obesity was a protective factor for sarcopenia, whilst it was a risk factor when using BF% (OR = 1.38, 95% CI [1.13, 1.69]; p = 0.002) as the definition. The risk of sarcopenia reduced with the increase of BMI in both genders. It was increased with raised BF% in males but displayed a U-shaped curve for females. BF% 26.0-34.6% in old females and lower than 23.9% in old males are recommended for sarcopenia and obesity prevention.

Conclusion

Skeletal muscle mass had strong positive relationship with absolute fat mass but negative associations with the percentage of appendicular fat mass. Obesity was a risk factor of sarcopenia when defined by BF% instead of BMI. The management of BF% can accurately help elderly people prevent against both sarcopenia and obesity.

Gender-Specific Prevalence and Risk Factors of Sarcopenic Obesity in the Korean Elderly Population: A Nationwide Cross-Sectional Study

Sarcopenic obesity (SO) is characterized by the combination of sarcopenia and obesity. This study evaluates the gender-specific prevalence of SO and examines the identified gender-specific risk factors in a community-dwelling elderly population aged 75-84 years. A total of 813 subjects participated in the study via the Korea National Health and Nutrition Examination Survey. The SO prevalence in males and females was 15.46% (95%CI: 11.36-20.70) and 13.59% (95%CI: 10.59-17.28), respectively. The clinical sex-specific risk factors for males were low height, high weight, body mass index, waist circumference, skeletal muscle index, fasting glucose, and triglycerides. The clinical risk factors for females were low height, high weight, body mass index, waist circumference, skeletal muscle index, smoking status, fasting glucose, total cholesterol, and systolic blood pressure. These results are essential to assist healthcare professionals and primary care clinicians with early detection, diagnosis, and intervention for potential SO patients by acknowledging the sex-based prevalence and risk factors.

High-intensity interval aerobic and resistance training to counteract low relative lean soft tissue mass in middle age: A randomized controlled trial

BACKGROUND

Age-related loss of skeletal muscle mass and function begins in early middle age, yet research to date has focused on older individuals, limiting our understanding of interventions earlier in the lifespan. To date, no high-intensity interval training studies have been conducted in middle-aged adults with low relative lean soft tissue mass.

METHODS

Eighty-two middle-aged adults (40-50 years of age) with low appendicular lean soft tissue mass index confirmed with dual energy x-ray absorptiometry (DXA) were randomly allocated (1:1) to group-based, 20-week, three times a week, high-intensity aerobic and resistance training (HIART) program or 60-min education session (Control). The primary outcome was change in total lean soft tissue mass measured by DXA. Secondary outcomes included cardiorespiratory fitness, physical function (handgrip strength, gait speed, 30-seconds sit-to-stand, quadriceps strength and muscle quality). Measures were obtained at baseline (0 weeks), mid-intervention (10 weeks) and post-intervention (20 weeks).

RESULTS

Mean age in HIART was 44.8 (SD 3.2) and 45.4 (SD 2.9) in Control group. The majority of the participants were female with 88 % in HIART and 83 % in Control group. Mean BMI in HIART was 25.8 kg/m² (SD 3.5) and 26.4 kg/m² (SD 4.1) Control group. Intention to treat analysis showed that post-intervention, HIART increased significantly more total lean soft tissue mass (0.8 kg, 95%CI 0.15, 1.46), appendicular lean soft tissue mass index (0.2 kg/m², 95%CI 0.09, 0.33), peak oxygen uptake (5.18 mL/min/kg, 2.97 to 7.39 95%CI), grip strength (2.2 kg, 95%CI 0.09, 4.32), and 30-s sit-to-stand (1.3 times, 95%CI 0.43, 2.12) with significantly greater reductions in body fat percentage (-1.1 %, 95%CI -2.03, -0.10) and maximum gait speed (-0.2 m/s, 95 % CI -0.34, -0.03) compared Control.

CONCLUSION

The HIART program is an effective exercise intervention to increase total lean soft tissue mass in middle-aged adults with low relative lean soft tissue mass compared to a waitlist control group.

A diagnostic proposal for sarcopenic obesity in adults based on body composition phenotypes

BACKGROUND & AIMS

Sarcopenic obesity (SO) associates a decrease in lean body mass (LBM) with an excessive increase in fat mass (FM). A number of diagnostic methods, definitions criteria, and thresholds have been proposed for SO resulting in markedly discordant prevalence estimates in populations with obesity. In this study, we first assessed several previously described SO diagnostic criteria and their limitations, and then we propose an innovative approach for identifying SO.

METHODS

Data were from a cross-sectional study of a cohort of overweight/obese patients who underwent clinical, laboratory, and body composition assessments by dual-energy X-ray absorptiometry (DXA). We performed unsupervised machine learning through clustering analysis to discriminate lean and fat compartments, and multivariate logistic regressions which provided prognostic variables applied on sex-specific models for SO diagnosis evaluation based on a training dataset (80% of total sample, n = 1165). The predicted models were validated by random forest (RF) machine learning algorithm in the validation dataset (20% of total sample, n = 262).

RESULTS

Data from 1427 subjects were analyzed, 79.8% women, mean (±s.d.) age 45.0 (±12.9) years, grade III obesity (BMI over 40 kg/m²) in 42.7%, diabetes in 20.7%, dyslipidemia in 86.3%, and arterial hypertension in 30.3%. Patients with grade III obesity had higher amounts of LBM, FM, and bone mass than subjects with overweight (BMI between 25.0 and 29.9 kg/m²) (p-values < 0.001). When published definitions of SO were applied to this cohort, the prevalence ranged from 0.6% to 96.6%. We built a model that identified 62 (4.3%) individuals as SO, 1125 (78.9%) as non-SO, and 240 (16.8%) as borderline-SO. SO patients showed higher body weight, FM, bone mass, leptin levels, and hepatic steatosis index, but lower LBM and all muscle indexes than non-SO subjects (p-values ≤ 0.001). Patients in the SO and borderline-SO categories were more often females than males (4.5% vs. 3.8% and 16.9% vs. 16.7% respectively, p-value < 0.001) and had significantly higher prevalence of metabolic syndrome and hypertension than non-SO subjects. Males with SO also had higher cardiovascular risk score, while females had higher prevalence of respiratory disorders (p-values < 0.05 for all).

CONCLUSIONS

Current diagnostic criteria for SO result in widely discrepant prevalence values leading to diagnosis uncertainty. We developed and validated diagnostic criteria based on body composition phenotypes, specifically for overweight/obese subjects, which identified patients at risk of cardio-metabolic complications. This approach may improve the identification of sarcopenia in subjects with obesity.

Understanding sarcopenic obesity in young adults in clinical practice: a review of three unsolved questions

INTRODUCTION

Our aim was to summarize the available literature on three yet unsolved questions, namely: 1) the dilemma surrounding definition of sarcopenic obesity (SO), especially in young adults; 2) the potential impact of this phenotype on weight-loss programme outcomes; and 3) the strategies for optimum management (prevention/treatment) of SO in clinical practice.

EVIDENCE ACQUISITION

A literature review using the PubMed/Medline database was conducted, and data were summarized based on a narrative approach.

EVIDENCE SYNTHESIS

Firstly, SO can be screened by the 30-sec sit-to-stand test; ≤25 and ≤21; and confirmed by the ratio of (appendicular lean mass/Body Mass Index) ≤0.789 and 0.512 in males and females, respectively. Secondly, SO is associated with impaired physical fitness, reduced resting energy expenditure and an inactive lifestyle, that seems to negatively impact on weight-management outcomes, namely increasing early dropout and difficulty in maintaining weight loss in the long term. Finally, prevention/treatment of SO in young adults must be realized through tailored lifestyle intervention (diet+exercise) to preserve and improve strength and muscle mass, even where weight loss is necessary.

CONCLUSIONS

Our findings have clinical implications since they may help in screening, managing and improving the weight-loss outcomes of patients with SO in clinical settings.

Low skeletal muscle mass Accompanied by Abdominal Obesity Additively Increases the Risk of Incident Type 2 Diabetes

CONTEXT

Low skeletal muscle mass often accompanies abdominal obesity in the aging process.

OBJECTIVE

We aimed to investigate the effect of reduced skeletal muscle mass and its interaction with abdominal obesity on incident type 2 diabetes.

METHODS

This retrospective longitudinal study included a total of 36,304 diabetes-free Koreans who underwent two or more health check-ups annually or biennially. Appendicular skeletal muscle mass was measured by bioelectrical impedance analysis and was presented as a skeletal muscle mass index (SMI) adjusted for body weight. Pre-sarcopenia was defined as an SMI <1 standard deviation of the sex-specific mean for a healthy young reference group. Abdominal obesity was defined using waist circumference ≥ 90 cm for men and ≥ 85 cm for women. Participants were classified into four groups of normal, pre-sarcopenia alone, abdominal obesity alone, and pre-sarcopenic obesity according to initial body composition.

RESULTS

The cumulative incidence of diabetes was 9.1% during the 7-year follow-up. Compared with the highest tertile, the lowest sex-specific SMI tertile was significantly associated with a greater risk of incident type 2 diabetes (adjusted hazard ratio [HR] = 1.31, 95% confidence interval [CI] 1.18-1.45) in a fully adjusted model. Pre-sarcopenic obesity significantly increased incident diabetes risk (adjusted HR = 1.57, 95% CI 1.42-1.73) compared with normal body composition, pre-sarcopenia alone, or abdominal obesity alone.

CONCLUSIONS

Low skeletal muscle mass and its coexistence with abdominal obesity additively increased the risk of incident type 2 diabetes independent of the glycometabolic parameters.

Musculoskeletal effects of obesity and bariatric surgery – a narrative review

Obesity affects several areas of the human body, leading to increased morbidity and mortality and the likelihood of other diseases, such as type 2 diabetes mellitus, cardiovascular diseases and musculoskeletal disorders. These conditions predispose to bone fractures and sarcopenic obesity, defined by the presence of an obesity-associated decrease in muscle mass and strength. Both bone fragility and sarcopenic obesity disease are consequences of several factors, such as a low degree of chronic inflammation, insulin resistance, hormonal changes, nutritional deficiencies, ectopic fat deposits and sedentary lifestyle. The diagnosis of obesity-related musculoskeletal disorders is limited by the lack of sarcopenia criteria and lower accuracy of bone mineral density measurement by dual-energy X-ray absorptiometry in overweight people. Reducing body weight provides undeniable benefits to this population, however treating cases of severe obesity with bariatric surgery can cause even greater damage to bone and muscle health, especially in the long term. The mechanisms involved in this process are not yet fully understood, but factors related to nutrient malabsorption and mechanical discharge as well as changes in gut hormones, adipokines and bone marrow adiposity should be taken into account. Depending on the surgical technique performed, greater musculoskeletal damage may occur, especially in cases of malabsorptive surgeries such as Roux-en-Y gastric bypass, when compared to restrictive techniques such as sleeve gastrectomy. This difference is probably due to greater weight loss, nutrient malabsorption and important hormonal changes that occur as a consequence of the diversion of intestinal transit and loss of greater absorptive surface. Thus, people undergoing bariatric procedures, especially malabsorptive ones, should have their musculoskeletal health supervised to allow early diagnosis and appropriate therapeutic interventions to prevent osteoporotic fractures and preserve the functionality of the skeletal muscles.

Body-composition phenotypes and their associations with cardiometabolic risks and health behaviours in a representative general US sample

Body mass index is poor at distinguishing between adiposity and muscle. Based on dual energy X-ray absorptiometry data, a diagnostic framework to analyze body composition by categorizing fat- and muscle-mass body composition into four phenotypes has been proposed. The objective of this study was to assess the association between body-composition phenotypes with adiposity measures, health behaviours and cardiometabolic risks in a representative U.S. adult population. Data were from NHANES (1999-2006: n = 9867; 2011-2018: n = 10,454). Four phenotypes based on being above/below the 50th percentile of age- and sex- adjusted reference curves of fat-mass and muscle-mass were identified. Multiple linear and logistic regressions were used to assess phenotypes (high [H] or low [L] adiposity [A] or muscle mass [M]) against adiposity measures, health behaviours, cardiometabolic risk, and dietary intake. Low-adiposity/high-muscle (LA-HM) was the referent. Analyses incorporated the complex sampling design and survey weights, and were adjusted for age, sex, race, and education. Compared to the LA-HM reference group, the HA-LM phenotype was less physically active, had higher total and lower high-density lipoprotein cholesterol, and had lower intake of all examined nutrients (all p < 0.01). For the HA-HM phenotype, unfavourable values were detected for all adiposity and cardiometabolic measures compared to the LA-HM phenotype (all p < 0.01). The two high adiposity phenotypes were associated with poorer health behaviours and cardiovascular risk factors, regardless of muscle-mass, but associations differed across the phenotypes. Results further underscores the importance of accounting for both adiposity and muscle mass in measurement and analysis. Further longitudinal investigation is needed.

A feasibility trial of prehabilitation before oesophagogastric cancer surgery using a multi-component home-based exercise programme: the ChemoFit study

BACKGROUND

Treatment for locally advanced oesophagogastric adenocarcinoma involves neoadjuvant chemotherapy which has a negative impact on patient fitness. Using 'prehabilitation' to increase activity levels and fitness may affect physiology, postoperative outcomes and improve patient wellbeing and quality of life. The aims of the trial were to address the feasibility and acceptability of recruiting participants to a home-based prehabilitation programme and provide data to allow design of future studies.

METHODS

We recruited patients to a single-arm feasibility trial of home-based exercise prehabilitation. Eligible patients were aged ≥18years, had operable oesophageal or gastric adenocarcinoma and were receiving neoadjuvant chemotherapy at our tertiary referral hospital. All participants commenced a home-based exercise programme utilising pedometers and step counting to target daily aerobic exercise sessions alongside daily strengthening exercises. A weekly telephone consultation directed the exercise programme and facilitated weekly data collection. The primary (feasibility) outcomes for the trial were (a) recruitment rate, (b) completion rate, (c) engagement with the programme (use of pedometers, recording step counts, telephone consultations) and (d) compliance with exercise sessions, exercise intensity and strengthening exercises.

RESULTS

There were 42 patients recruited, and the recruitment rate was 72.4% (42/58). 92.3% (36/39) of patients completed the exercise programme. There was 98.7% (IQR 93.2-100.0%) compliance with wearing a pedometer and recording data, and 100.0% (IQR 93.1-100.0%) compliance with a weekly telephone consultation. Exercise sessions and strengthening exercises were completed 70.2% (IQR 53.1-88.9%) and 69.4% (IQR 52.1-84.3%) of the time, respectively. Appropriate exercise intensity was recorded 96% (IQR 85.4-99.4%) of the time. There were no adverse events. Participants were enrolled in the exercise programme for a median of 91 days (IQR 84 to 105 days).

CONCLUSIONS

The results of this trial support the feasibility and acceptability of recruiting participants to an appropriately powered randomised controlled trial of prehabilitation.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04194463 . Registered on 11th December 2019-retrospectively registered.

Body Composition and Prostate Cancer Risk: A Systematic Review of Observational Studies

Body composition parameters are not captured by measures of body mass, which may explain inconsistent associations between body weight and prostate cancer (PC) risk. The objective of this systematic review was to characterize the association between fat mass (FM) and fat-free mass (FFM) parameters and PC risk. A search of PubMed, Embase, and Web of Science identified case-control and cohort studies that measured body composition in relation to PC risk. Methodological quality was assessed using the Newcastle-Ottawa Scale (NOS). Thirteen observational studies were included, of which 8 were case-control studies (n = 1572 cases, n = 1937 controls) and 5 were prospective cohort studies (n = 7854 incident cases with PC). The NOS score was 5.9 ± 1.1 for case-control studies and 8.4 ± 1.3 for cohort studies. The most common body composition technique was bioelectrical impedance analysis (n = 9 studies), followed by DXA (n = 2), computed tomography (n = 2), air displacement plethysmography (n = 1), and MRI (n = 1). No case-control studies reported differences in %FM between PC cases and controls and no consistent differences in FM or FFM (in kilograms) were observed. Two out of 5 cohort studies reported that higher %FM was associated with lower PC risk. Conversely, 3 cohort studies reported a greater risk of being diagnosed with advanced/aggressive PC with higher FM (expressed in kilograms, %FM, or fat distribution). Two out of 4 studies (both case-control and cohort) found that higher abdominal adipose tissue was associated with increased PC risk. In conclusion, although results were inconsistent, there is some evidence that FM may be negatively associated with total PC risk but positively associated with the risk of advanced/aggressive PC; modest evidence suggests that abdominal adipose tissue may increase the risk of PC. Future work should elucidate unique patterns of FM distribution and PC risk to triage men at risk for developing PC. This study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO) database as CRD42019133388.

Diagnostic Evaluation of the Functional Muscle-Bone Unit in Children With Cerebral Palsy With and Without Low Trauma Fractures

Children and adolescents with cerebral palsy (CP) are at increased risk of low trauma fractures (LTF) due to low bone mineral content (BMC). The risk of LTFs might be overestimated by only age - and sex adjusted Z-scores for BMC because Z-score based DXA techniques do not take into account other relevant parameters like height, muscle and fat mass. This study aimed to present an update of the functional muscle-bone unit-algorithm (uFMBU-A) to evaluate bone health in children with CP in order to predict the risk of LTF taking into account the parameters sex, age, height, muscle and fat mass. We performed a monocentric retrospective analysis of 177 DXA-scans of children and adolescents with CP aged 8-19. Six of these 177 patients had sustained at least 1 LTF. Age-, sex- and size adjusted Z-scores of total body less head (TBLH)-BMC, lean body mass and fat mass were calculated. The uFMBU-A was applied to the study group and results were compared with established Z-score based DXA-measurements and algorithm based diagnostic techniques concerning the prediction of LTF risk. The uFMBU-A had the greatest diagnostic odds ratio (13.3 [95% CI 2.41; 72.9]) of the evaluated predictors with a sensitivity of 50.0% (95% CI 11.8; 88.2), specifity of 93% (95% CI 88.1; 96.3). The uFMBU-A was the most accurate method of the evaluated parameters to predict LTF in children with CP and is recommended when evaluating bone health.

Physical Activity, Exercise Capacity, and Body Composition in U.S. Veterans with Chronic Obstructive Pulmonary Disease (COPD)

RATIONALE

Differences in body composition may contribute to variability in exercise capacity (EC) and physical activity (PA) in chronic obstructive pulmonary disease (COPD). Most studies have employed bioimpedance-based surrogates of muscle (lean) mass; relatively few studies have included consideration of fat mass and limited studies have been performed using dual X-ray absorptiometry (DXA)-assessed body composition.

OBJECTIVE

To determine whether DXA-assessed muscle (lean) and fat mass exhibit differential correlations with EC and PA in COPD Methods: US Veterans with COPD (defined as FEV1/FVC<0.7 or emphysema on clinical chest computed tomography) had DXA-assessed body composition, EC (6-minute walk distance; 6MWD), objective PA (average daily step counts), and self-reported PA measured at enrollment. Associations between EC, PA, and body composition were examined using Spearman correlations and multivariable models adjusted a priori for age, sex, race, and lung function.

RESULTS

Subjects (n=98) were predominantly white (88%), obese (mean BMI 30.2±6.2), and male, (94%) with a mean age (±SD) of 69.9±7.9 years and moderate airflow obstruction (mean FEV1% 68±20). Modest inverse correlations between EC and PA with fat mass were observed (Spearman's rho range [-0.20]-[-0.34]) while measures of muscle (lean) mass were not significantly associated with EC or PA. The appendicular skeletal muscle (ASM)-to-weight ratio, which considers both muscle (lean) and fat mass, was consistently associated with EC (8.4 [95%CI=2.9-13.8] meter increase on 6MWD per 1% increase in ASM-to-weight ratio), objective PA (194.8 [95%CI=15.2-374.4] steps per day per 1% increase in ASM-to-weight ratio), and self-reported PA in multivariable-adjusted models.

CONCLUSION

DXA-assessed body composition measures which include consideration of both lean and fat mass are associated with cross-sectional EC and PA in COPD populations. Clinical trial registered at ClinicalTrials.gov (NCT02099799).

Assessment of Osteogenesis Enhancement in Rats Using Bone Densitometry: An In Vivo Study

Background: Human survival depends on the availability of water. Safe drinking water is a fundamental human right as well as a basic need for a good health. At the mineral and organic levels of water composition, exposure to electromagnetic fields can cause considerable changes in the quality of drinking water. As a result, water is more easily absorbed into the cell walls throughout the body, making it better suited for organ growth and development. When drunk on a daily basis, magnetic water causes dramatic changes in bone mineral density and content. Due to the necessity for distinct beam filtering and near-perfect spatial discography of the two attenuations, DXA (DualEnergy X-ray Absorptiometry) was included with general-purpose X-ray systems. In rats that drink magnetized water on a daily basis, the DXA can be used to calculate the weight and area of all head compartments. Objective: By employing a Bone Densitometry scan on the head regions of rats, this study aims to assess the changes in the rat's skull bone measures (area, weight, bone mineral content, and bone mineral density) after feeding the animal with magnetized water. Methods: This study involved thirty adult male rats (6 weeks old). For 30 days, 15 rats were given a magnetized water to drink and used as experimental animals. For comparison purposes, the remaining 15 rats were given regular water for 30 days. After the experimental procedure was done, each rat's head was scanned with a DXA to determine bone weight, area, bone mineral content, and bone mineral density. Before drinking water, each rat in both the experimental and control groups was examined. The head of each rate was scanned using a DXA to get the values of bone: weight, area, mineral density, and mineral content after 30 days of consuming magnetized water. The four bone measures were statistically compared in the experimental and control rats, p-values below 0.05 were considered significant. Results: Comparing to control rats, experimental rats showed a significant increase in the bone’s weight and area of the skull (p<0.05, Wilcoxon test).  Bone marrow content and bone marrow density enhanced significantly as well in experimental rats after drinking the magnetized water for 30 days. Conclusions: Drinking water that has been subjected to electromagnetic fields for 30 days can improve bone marrow content and density in rats. Drinking magnetized water also has a substantial impact on bone mass and area.

Body Composition and Serum Concentration of Thyroid Hormones in Euthyroid Men and Women from General Population

Body composition, especially an increased amount of fat mass and decreased lean body mass, is connected with metabolic complications. Thyroid hormones can influence body composition pattern. To date, scarce data defining the relationships between thyroid hormones and parameters of body composition using dual-energy X-ray absorptiometry (DXA), especially in cohort studies, are available. Therefore, the aim of the present study was to investigate the relationships among serum concentrations of (thyroid-stimulating hormone (TSH), thyroid hormones, and distribution of fat tissue assessed using the DXA method in a euthyroid cohort from the Białystok PLUS study. We examined 582 euthyroid subjects who were divided into lean (body mass index (BMI) < 25 kg/m2) and overweight/obese (BMI ≥ 25 kg/m2) (84 lean men, 182 overweight/obese men, 160 lean women, and 156 overweight/obese women). Serum concentrations of TSH, free T3 (fT3), and free T4 (fT4) were assessed, and DXA was performed. We observed lower serum levels of fT4 (p = 0.03) and higher serum levels of fT3 (p = 0.04) in overweight/obese vs. lean men, whereas serum levels of TSH did not differ between these groups (p = 0.38). In lean men, we only observed a relationship between serum levels of TSH and visceral adipose tissue (VAT) (r = −0.24, p = 0.02). In overweight/obese men, we found that serum levels of fT3 were positively connected with total fat mass (r = 0.16, p = 0.02), android fat mass (r = 0.15, p = 0.03), and gynoid fat mass (r = 0.17, p = 0.01), but not with VAT (r = 0.03, p = 0.63). We did not observe differences in serum levels of TSH, fT3, and fT4 between lean and overweight/obese women. Additionally, we did not notice relationships between serum levels of thyroid hormones and fat in different regions estimated by DXA in lean and overweight/obese women (all p > 0.05). We concluded that the serum concentration of TSH is connected with VAT in lean men, whereas, in overweight/obese men, higher fT3 is connected with an increased fat amount. These associations are absent in women.

Associations of Computed Tomography Image-Assessed Adiposity and Skeletal Muscles with Triple-Negative Breast Cancer

Obesity measured by anthropometrics is associated with increased risk of triple-negative breast cancer (TNBC). It is unclear to what extent specific adipose tissue components, aside from muscle, are associated with TNBC. This retrospective study included 350 breast cancer patients who received treatment between October 2011 and April 2020 with archived abdominal or pelvic computed tomography (CT) images. We measured the areas of adipose tissue and five-density levels of skeletal muscle on patients' third lumbar vertebra (L3) image. Logistic regression was performed to examine the associations of specific adiposity and skeletal muscles components and a four-category body composition phenotype with the TNBC subtype. Results showed that higher vs. lower areas (3rd vs. 1st tertiles) of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were associated with increased odds of TNBC vs. non-TNBC after adjusting for age, race, stage, tumor grade, tumor size, and skeletal muscle areas (adjusted odds ratio [AOR], 11.25 [95% CI = 3.46-36.52]) and (AOR, 10.34 [95% CI = 2.90-36.90]) respectively. Higher areas of low density muscle was also associated with increased odds of TNBC (AOR, 3.15 [95% CI = 1.05-10.98]). Compared to normal body composition (low adipose tissue/high muscle), high adiposity/high muscle was associated with higher odds of TNBC (AOR, 5.54 [95% CI = 2.12-14.7]). These associations were mainly in premenopausal women and among patients with the CT performed after breast cancer surgery. Specific adipose tissue and low-density muscle can be associated with the TNBC subtype in breast cancer patients. The direction of association warrants confirmation by prospective studies.

Sarcopenic obesity is associated with telomere shortening: findings from the NHANES 1999-2002

Sarcopenic obesity (SO) is characterised by the concurrent presence of sarcopenia and excess adiposity. Telomere shortening has been associated with sarcopenia and obesity alone but the association between SO and telomere length (TL) has not been investigated. This study aimed to investigate SO and TL in an adult population. Data were from 5397 individuals (mean age = 44.7 years, 51.3% male) enrolled in the National Health and Nutrition Examination Survey. Body composition (BC) was assessed by Dual Energy X-Ray Absorptiometry. Two models were used to assess SO: a BC model including four phenotypes derived from the combination of high or low adiposity and muscle mass; and, a truncal fat mass to appendicular skeletal mass ratio (TrFM/ASM). TL was assessed using quantitative polymerase chain reaction and expressed as base pairs. The mean TL, relative to the reference DNA, was calculated and expressed as the mean T/S ratio. A General Linear Model was applied to determine associations between TL for SO. In adjusted analysis, only individuals with SO, defined as the presence of high adiposity-low muscle mass (four-phenotype model), had significantly shorter telomeres (p = 0.05) than the reference group (i.e. low adiposity-high muscle mass), with a mean T/S ratio of 1.02 (95%CI: 0.98-1.05) compared to 1.05 (95%CI: 1.01-1.09), respectively. TrFM/ASM was not associated with TL. Preliminary findings suggest that sarcopenia and obesity may act synergistically to shorten telomeres.

Muscle plays a more superior role than fat in bone homeostasis: A cross-sectional study of old Asian people

OBJECTIVES

The aim of this study was to discover the role of fat and muscle in bone structures, as well as the relationship between obesity and sarcopenia on age-related osteoporosis.

METHODS

A total of 400 participants (65.0 ± 8.2 years old, 42.3% women) were recruited. Fat, muscle, bone parameters, basic demographics, medical history, physical performance and activity, and calcium intake of participants were obtained from datasets. The diagnosis of osteoporosis, sarcopenia, and obesity was based on current recommendations. Pearson correlation, non-linear regression models, and decision tree analyses were performed to study the relationship between fat, muscle, and bone. Logistic regression analyses were used to explore the risk of osteoporosis in old people with obesity or sarcopenia via Model 1 (unadjusted) and Model 2 (adjusted by age, physical activity, and calcium intake).

RESULTS

Correlation analysis showed that limb muscle mass and index, and age were best related to bone mineral density (BMD) (|r| = 0.386-0.632, p < 0.001). On the contrary, body mass index (BMI) and increased body fat percentage (BF%) were harmful for bone health. An increase of BMI and fat mass index slowed the increase of BMD in the spine, while skeletal muscle mass index accelerated the increase. People with sarcopenia had low muscle mass and strength. When separating subjects into sarcopenia and non-sarcopenia status, sarcopenia was independently related to higher risks of osteoporosis in both models (OR > 1, p < 0.05). BMI-defined obesity in Model 1 as well as BF%-defined obesity in both models did not reduce the risk of osteoporosis in both models (p > 0.05). The decision tree classification (85% accuracy) showed that greater body weight and larger lower limb muscle performance were negatively related to osteoporosis, while fat mass and percentage did not play roles in this prediction.

CONCLUSION

Low muscle mass and function were harmful to bone health. Obesity defined by both BMI and BF% had limited protective roles in osteoporosis. The benefits for bone from increased muscle mass and function play a more superior role than increased fat mass in old people. Sarcopenia prevention and treatment instead of controlling obesity should be recommended as an approach to reduce the risks of age-related osteoporosis and fragility fracture for elderly people.

Joint effect of multiple air pollutants on lipid profiles in obese and normal-weight young adults: The key role of ozone

Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM_2.5, PM₁₀, NO₂, SO₂, O₃ and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O₃ had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O₃-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O₃ in the future.

Pediatric Reference Centiles of Bone Mineral Density and Body Composition of Lower Limbs

Localized neurological diseases such as spina bifida are often accompanied by normal upper limb and spinal bone mineral density (BMD), whereas regional BMD of the lower limbs may be decreased. Therefore, regional BMD measurements may be more accurate to quantify regional bone health. Until now, no pediatric reference centiles of bone mineral density and body composition of the lower extremities are available for Hologic DXA systems. The objective was to generate age-and sex specific reference centiles of DXA scans of lower limbs for Hologic DXA systems. Data from the National Health and Nutrition Examination Survey of the period 1999-2004 (age 8 - 20 years) were used to generate age-specific and sex-specific reference centiles for the non-Hispanic Black, non-Hispanic White and Mexican-American NHANES study population. The LMS method was used to calculate the reference centiles. Data of DXA scans of 2233 non-Hispanic black children (880 females), 1869 non-Hispanic white children (803 females) and 2350 Mexican American children (925 females) were used to create age-specific and sex-specific reference curves. We presented age-and sex-specific reference centiles for regional bone mineral density, bone mineral content, lean body mass and fat mass at the lower limbs for children and adolescents which were ethnicity specific and directly applicable to Hologic QDR-4500A fan-beam densitometer.

Agreement between GLIM and PG-SGA for diagnosis of malnutrition depends on the screening tool used in GLIM

BACKGROUND & AIM

The Global Leadership Initiative on Malnutrition (GLIM) has suggested a process for the diagnosis of malnutrition. The process consists of applying an existing screening tool for malnutrition screening, followed by malnutrition diagnostics, and finally categorization of malnutrition severity (moderate or severe) according to specific GLIM criteria. However, it is not known how well the GLIM process agrees with other diagnostic tools used in the current clinical practice. The aim of this study was to validate the GLIM process against the Patient Generated-Subjective Global Assessment (PG-SGA) when different screening tools were applied in the screening step of the GLIM process.

METHODS

Colorectal cancer (CRC) patients from the ongoing CRC-NORDIET study were included. For the GLIM process, the patients were first screened for malnutrition using either 1) Nutritional risk screening, first 4 questions (NRS-2002-4Q), 2) Malnutrition Screening Tool (MST), 3) Malnutrition Universal Screening Tool (MUST) or 4) the PG-SGA short form (PG-SGA-SF). The GLIM malnutrition diagnosis was then based on combining the result from each of the screening methods with the etiological and phenotypic GLIM-criteria including weight loss, BMI and fat free mass. In parallel, the patients were diagnosed using the PG-SGA methodology categorizing the patients into either A: well nourished, B: moderately malnourished or C: severely malnourished. The four different GLIM based diagnoses were then validated against the diagnosis obtained by the PG-SGA tool. Sensitivity, specificity and positive predictive value (PPV) were calculated to evaluate validity.

RESULTS

In total, 426 patients were included (mean age: 66, ±8 years) at a mean time of 166 (±56) days after surgery. The GLIM diagnosis based on the four different screening tools identified 10-24% of the patients to be malnourished, of which 3-8% were severely malnourished. The PG-SGA method categorized 15% as moderately malnourished (PG-SGA: category B) and no patients as severely malnourished (PG-SGA: category C). The agreement between the PG-SGA and GLIM process was in general low, but differed according to the tools: PG-SGA SF (sensitivity 47%, PPV 71%), MST (sensitivity 56%, PPV 47%), NRS-2002-4Q (sensitivity 63%, PPV 53%) and MUST (sensitivity 53%, PPV 34%).

CONCLUSION

In this cross-sectional study of patients with CRC, the concordance between the GLIM-criteria and PG-SGA depended on the screening tool used in the GLIM process. Malnutrition frequency based on the GLIM process schould be reported with and without the use of a screening tool.

Using Body Composition Groups to Identify Children and Adolescents at Risk of Dyslipidemia

The impact of body composition on the early origin of chronic diseases is an increasingly appreciated phenomenon. Little is known about the characteristics of children with varying body composition. The aim of this study was to investigate serum lipid profiles and other characteristics in relation to body composition. The data of 1394 participants (aged 6 to <18 years) of the observational general population-based Austrian LEAD Study have been analyzed. Body composition groups were defined by appendicular lean mass (ALMI) and fat mass (FMI) indices assessed by DXA. Serum lipid profiles (triglycerides, LDL-c, HDL-c) and other characteristics (e.g., prematurity, smoke exposure, physical activity, nutrition) were investigated in these body composition groups. Different body composition groups, which are not distinguishable by BMI, exist. Children with high ALMI and high FMI showed higher triglycerides and LDL-c, but lower HDL-c levels. In contrast, levels did not differ between those with high FMI but low (or normal) ALMI, and other body composition groups. BMI should be interpreted cautiously, and body composition should be measured by more precise techniques. In particular, children and adolescents with high FMI who have concomitantly high ALMI should be followed closely in future studies to investigate whether they are at increased risk of cardiovascular problems.

Body Composition Characteristics of a Load-Capacity Model: Age-Dependent and Sex-Specific Percentiles in 5- to 17-Year-Old Children

INTRODUCTION

Body composition assessment is superior to the use of body mass index (BMI) to characterize the nutritional status in pediatric populations. For data interpretation, suitable reference data are needed; hence, we aimed to generate age-dependent and sex-specific body composition reference data in a larger population of children and adolescents in Germany.

METHODS

This is a cross-sectional study on a representative group of 15,392 5- to 17-year-old children and adolescents. Body composition was assessed by bioelectrical impedance analysis using a population-specific algorithm validated against air displacement plethysmography. Age- and sex-specific percentiles for BMI, fat mass index (FMI), fat-free mass index (FFMI), and a "load-capacity model" (characterized by the ratios of fat mass [FM]/ fatt-free mass [FFM] and FM/FFM2) were modeled using the LMS method.

RESULTS

BMI, FMI, FFMI, FM/FFM, and FM/FFM2 curves showed similar shapes between boys and girls with steady increases in BMI, FMI, and FFMI, while FM/FFM2-centiles decreased during early childhood and adolescence. Sex differences were observed in FMI and FM/FFM percentiles with increases in FMI up to age 9 years followed by a steady decrease in FM/FFM during and after puberty with a fast-growing FFMI up to age 17 in boys. The prevalence of low FFM relative to FM reached more than 60% in overweight children and adolescents.

CONCLUSION

These pediatric body composition reference data enable physicians and public health scientists to monitor body composition during growth and development and to interpret individual data. The data point out to an early risk of sarcopenia in overweight children and adolescents.

Effects of acute and chronic nuts consumption on energy metabolism: a systematic review of randomised clinical trials

Nuts are high-energy density foods and are associated with beneficial effects on health, including weight control. Effects on resting energy expenditure, respiratory quotient, and diet-induced thermogenesis are suggested mechanisms behind the effects of nuts consumption on weight control. Thus, we revised the randomised clinical trials that assessed acute and chronic nuts consumption effects on energy metabolism. Walnuts (22.1 g to 56 g) consumption appears to modulate energy metabolism markers differently depending on the dose and profile of the evaluated subject. In its turn, 56 g of high-oleic peanuts increased postprandial energy expenditure and thermic effect of food after three hours postprandial compared to consumption of conventional peanuts. Almonds, hazelnuts, peanuts, and a mix of nuts were the nuts studies in the chronic studies, which does not seem to influence energy metabolism markers. Further studies are needed to elucidate the effects of other types of nuts consumption on energy metabolism.

Association of body mass index with outcomes after thoracic endovascular aortic repair in the vascular quality initiative

OBJECTIVE

Although several studies have evaluated the impact of obesity on outcomes after abdominal aortic aneurysm repair, literature examining this association in thoracic endovascular aortic repair (TEVAR) is sparse. Here, we use a multi-institutional, international database to assess the role of body mass index (BMI) on adverse outcomes in patients who underwent TEVAR for descending thoracic aortic aneurysms (DTAA) and type B dissections (TBD).

METHODS

A retrospective review of all patients who underwent TEVAR for DTAA or TBD from August 2014 to August 2020 was performed. Patients who were underweight (BMI <18.5 kg/m²) or obese (BMI ≥30 kg/m²) were compared with those of normal weight (≥18.5 to <30 kg/m²). Adjustment for confounding was done with multivariable logistic regression or Cox proportional hazards regression as appropriate for studying postoperative or 1-year outcomes. Primary outcomes were 30-day and 1-year mortality. Other outcomes included any postoperative complication, stroke, and spinal cord ischemia.

RESULTS

A total of 3423 participants were included in the study, of whom 3.3% (n = 113) were underweight, 65.9% (n = 2253) had normal weight, and 30.8% (n = 1053) were obese. Compared with normal weight, there was no significant difference in 30-day mortality in underweight patients (odds ratio [OR], 1.81; 95% confidence interval [CI], 0.80-4.14; P = .156). Obese patients who underwent TEVAR for TBD had a 2.7-fold increase in the odds of 30-day mortality compared with normal weight (OR, 2.67; 95% CI, 1.52-4.68; P = .001). Obese and normal weight patients with DTAA had equivalent odds of 30-day mortality (OR, 1.32; 95% CI, 0.79-2.23; P = .292). The adjusted hazard of 1-year mortality was 2-fold higher in underweight patients compared with normal weight (hazard ratio, 2.15; 95% CI, 1.41-3.29; P < .001), driven by a higher risk of mortality among patients with thoracic aortic aneurysm (OR, 2.62; 95% CI, 1.63-4.21; P < .001). There was no significant difference in 1-year mortality risk between normal weight and obesity in both DTAA (OR, 0.77; 95% CI, 0.54-1.09; P = .146) and TBD (OR, 1.26; 95% CI, 0.85-1.86; P = .248).

CONCLUSIONS

In this study, obese patients who underwent TEVAR for DTAA had comparable 30-day and 1-year mortality risk as normal weight individuals. Obese patients who underwent TEVAR for TBD demonstrated a 2.7-fold increase in the odds of 30-day mortality, but equivalent mortality risk as normal weight patients at 1 year. TEVAR represents a safe minimally invasive option for treatment of DTAA in obese patients. Future work should be directed toward minimizing perioperative mortality among patients with TBD to optimize TEVAR outcomes.

Association of Body Composition and Sarcopenia with NASH in Obese Patients

Obese patients often suffer from sarcopenia or sarcopenic obesity (SO) that can trigger inflammatory diseases including non-alcoholic steatohepatitis (NASH). Sarcopenia and SO can be diagnosed through measuring parameters of body composition such as skeletal muscle mass (SMM), skeletal muscle index (SMI) and fat mass (FM) obtained by bioelectrical impedance analysis (BIA). The aim of this study was to assess the relationship of body composition and NASH in patients with obesity. A total of 138 patients with obesity that underwent bariatric surgery were included in this study. BIA was used to estimate body composition. A liver biopsy was taken intraoperatively and histological assessment of NASH was performed. A total of 23 patients (17%) were classified as NASH and 65 patients (47%) met the criteria for borderline NASH. Body mass index (BMI) was significantly higher in patients with NASH compared to borderline NASH and no NASH (56.3 kg/m² vs. 51.6 kg/m² vs. 48.6 kg/m², p = 0.004). Concerning body composition, FM, but also SMM and SMI were significantly higher in patients with NASH (p-values 0.011, 0.005 and 0.006, resp.). Fat mass index (FMI) and weight-adjusted skeletal muscle index (SMI_weight) failed to reach statistical significance (p-values 0.067 and 0.661). In patients with obesity, higher FM were associated with NASH. Contrary to expectations, SMM and SMI were also higher in patients with NASH. Therefore, higher body fat, rather than sarcopenia and SO, might be decisive for development of NASH in patients with obesity.

Adiposity and muscle mass phenotyping is not superior to BMI in detecting cardiometabolic risk in a cross-sectional study

OBJECTIVE

Classifying adiposity based on dual-energy x-ray absorptiometry (DXA) muscle and fat mass phenotypes has been proposed. Whether these phenotypes are more accurate in predicting cardiometabolic risk than BMI weight status is unknown.

METHODS

Data were from the National Health and Nutrition Examination Survey (NHANES; 1999-2006 cycles, n = 5,475). Weight status was defined by BMI. Phenotypes of adiposity and muscle were based on high (≥50th percentile) and low (<50th percentile) permutations of sex- and age-specific fat and muscle mass population curves. The area under the curves of receiver operating characteristic curves (ROC-AUCs), which predicted the presence of abnormal lipids, glucose, and blood pressure, were compared. All analyses were stratified by sex and incorporated the complex survey design and weighting of NHANES.

RESULTS

The ROC-AUCs from weight status models used to correctly identify cardiometabolic risk ranged from 0.57 to 0.68, indicating generally weak predictive power. However, the ROC-AUCs from DXA phenotypes were lower (ranging from 0.53-0.68), indicating weaker predictive power than weight status, and were statistically inferior for nearly all of the comparisons.

CONCLUSIONS

Despite DXA's high cost and detailed output regarding body composition, its phenotype classification was inferior to weight status in predicting cardiometabolic risk. Further studies investigating the utility of the phenotypes are needed.

Body composition reference ranges in community-dwelling adults using dual-energy X-ray absorptiometry: the Australian Body Composition (ABC) Study

BACKGROUND

Reference ranges for lean mass (LM) and fat mass (FM) are essential in identifying soft tissue disorders; however, no such reference ranges exist for the most commonly used Hologic dual-energy X-ray absorptiometry (DXA) machine in Australia.

METHODS

Cross-sectional study of community-dwelling adults (aged 18-88 years) who underwent a Hologic DXA scan at one of three commercialized densitometry centres in Australia. Age-specific and sex-specific percentile curves were generated for LM [LM, appendicular lean mass (ALM), ALM adjusted for height squared (ALM/h² ), and ALM adjusted for body mass index (ALM/BMI)] and FM [FM, FM adjusted for height squared (FM/h² ), appendicular fat mass, and android and gynoid fat] parameters using the LMS statistical method. Cutpoints equivalent to T-scores of -1, -2, and -2.5 standard deviations below the young mean reference group (20-29 years) were also generated for LM parameters.

RESULTS

A total of 15 479 community-dwelling adults (54% men) with a median age of 33 years (interquartile range: 28, 42) were included. LM, ALM, and ALM/h² remained stable until age 50, after which these parameters started to decline in both sexes. Compared with age 50, median percentiles of LM, ALM, and ALM/h² declined by -5.9 kg, -3.7 kg, and -0.86 kg/m² in men and by -2.5 kg, -1.8 kg, and -0.10 kg/m² in women at age 70, respectively. Adjusting ALM for BMI (rather than height squared) resulted in different trends, with ALM/BMI decreasing from as early as age 20. Compared with age 20, median percentiles of ALM/BMI at age 40 declined by -0.10 kg/kg/m² in men and by -0.06 kg/kg/m² in women; and at age 70, ALM/BMI declined by -0.25 kg/kg/m² in men and by -0.20 kg/kg/m² in women. Cutpoints equivalent to T-scores of -1, -2, and -2.5 standard deviations for ALM/BMI were 1.01, 0.86, and 0.77 kg/kg/m² in men and 0.70, 0.59, and 0.53 kg/kg/m² in women, respectively. All FM parameters progressively increased from age 20 and continued up until age 70.

CONCLUSIONS

We developed reference ranges for LM and FM parameters from Hologic DXA machines in a large cohort of Australian adults, which will assist researchers and clinicians in identifying soft tissue disorders such as obesity, sarcopenia, and cachexia.

Bioelectrical Impedance Analysis and Mid-Upper Arm Muscle Circumference Can Be Used to Detect Low Muscle Mass in Clinical Practice

Identification of low muscle mass becomes increasingly relevant due to its prognostic value in cancer patients. In clinical practice, mid-upper arm muscle circumference (MAMC) and bioelectrical impedance analysis (BIA) are often used to assess muscle mass. For muscle-mass assessment, computed tomography (CT) is considered as reference standard. We investigated concordance between CT, BIA, and MAMC, diagnostic accuracy of MAMC, and BIA to detect low muscle mass and their relation with the clinical outcome malnutrition provided with the Patient-Generated Subjective Global Assessment Short Form (PG-SGA SF). This cross-sectional study included adult patients with advanced esophageal and gastrointestinal cancer. BIA, MAMC, and PG-SGA-SF were performed. Routine CT-scans were used to quantify psoas muscle index (PMI) and skeletal muscle area. Good concordance was found between CT_PMI and both BIA_{FFMI (fat free mass index)} (ICC 0.73), and BIA_{ASMI (appendicular skeletal muscle index)} (ICC 0.69) but not with MAMC (ICC 0.37). BIA_FFMI (94%), BIA_ASMI (86%), and MAMC (86%) showed high specificity but low sensitivity. PG-SGA-SF modestly correlated with all muscle-mass measures (ranging from -0.17 to -0.43). Of all patients with low muscle mass, 62% were also classified with a PG-SGA-SF score of ≥4 points. Although CT remains the first choice, since both BIA and MAMC are easy to perform by dieticians, they have the potential to be used to detect low muscle mass in clinical practice.

Benchmarking the Discriminatory Performance of Body Mass Index and Body Fat for Obesity Detection in Patients Treated by Intragastric Balloon

INTRODUCTION/PURPOSE

The accuracy of body mass index (BMI) in detecting obesity in patients treated by intragastric balloon (IGB) remains still speculative. We aimed to determine the discriminatory performance of BMI as an estimate of excess body fat (%BF) in an IGB-treated population.

MATERIAL AND METHODS

Retrospective analysis of prospectively collected data of 476 patients who completed the 6-month IGB treatment period and were subjected to body composition analysis. We evaluated the relationship between BMI and %BF or lean mass and the diagnostic performance of BMI ≥ 30 kg/m² for adipose tissue detection, stratified by age (< 40 and ≥ 40 years) and gender. Moreover, we identified anthropometric and body composition parameters serving as predictors of obesity according to %BF-based criteria (> 25% in men or > 35% in women).

RESULTS

Gender emerged as an effect modifier in the quadratic polynomial relationship between BMI and %BF (R² = 0.849 for men, R² = 0.715 for women), while BMI was linearly associated with %BF in both age groups (R² = 0.435 for men, R² = 0.474 for women). BMI was strongly correlated with both %BF (r = 0.67) and lean mass (r = - 0.65). The overall area under the ROC curve for BMI ≥ 30 kg/m² to detect %BF was 0.87 (95%CI 0.85-0.90). A regression model including lean mass, total body water, age, BMI, and female gender explained 0.970 of the variance in %BF.

CONCLUSION

The discriminatory performance of BMI as an estimate of excess body fat is enhanced by the implementation of gender- and age-specific BMI thresholds for defining obesity, in IGB-treated patients.

Longitudinal changes in total and regional body composition in patients with chronic obstructive pulmonary disease

Background and objective

Low fat‐free mass (FFM) is common in patients with chronic obstructive pulmonary disease (COPD) and contributes to morbidity and mortality. Few studies have evaluated longitudinal changes in body composition in patients with COPD compared with non‐COPD controls. This study aimed to compare longitudinal changes in total and regional body composition between patients with COPD and non‐COPD controls and investigate predictors of changes in body composition in COPD.

Methods

Patients with COPD and non‐COPD controls participating in the Individualized COPD Evaluation in relation to Ageing (ICE‐Age) study, a single‐centre, longitudinal, observational study, were included. Subjects were assessed at baseline and after 2 years of follow‐up. Among other procedures, body composition was measured by dual‐energy X‐ray absorptiometry scan. The number of exacerbations/hospitalizations 1 year before inclusion and during follow‐up were assessed in patients with COPD.

Results

A total of 405 subjects were included (205 COPD, 87 smoking and 113 non‐smoking controls). Patients with COPD and smoking controls presented a significant decline in total FFM (mean [95% CI]: −1173 [−1527/−820] g and −486 [−816/−156] g, respectively) while body composition remained stable in non‐smoking controls. In patients with COPD, the decline in FFM was more pronounced in legs (−174 [−361/14] g) and trunk (−675 [−944/406] g) rather than in arms (54 [−19/126] g). The predictors of changes in total and regional FFM in patients with COPD were gender, number of previous hospitalizations, baseline values of FFM and BMI.

Conclusion

Patients with COPD present a significant decline in FFM after 2 years of follow‐up, this decline is more pronounced in their legs and trunk.

Patients with chronic obstructive pulmonary disease (COPD) present a significant decline in total, leg and trunk low fat‐free mass (FFM), while arms FFM remains stable after 2 years of follow‐up. We identified a subgroup of patients with preserved FFM at baseline and history of previous hospitalizations that present greater decline in total and leg FFM compared to other patients with COPD.

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Prevalence of Sarcopenic Obesity Using Different Definitions and the Relationship With Strength and Physical Performance in the Canadian Longitudinal Study of Aging

Sarcopenic obesity is associated with several negative health outcomes. However, the prevalence of this condition – and the relationship to physical performance parameters – varies across definitions. The aim of this cross-sectional investigation was to describe the prevalence of sarcopenic obesity using different published definitions and their relationship with handgrip strength and walking speed in older Canadian adults. Individuals aged 65+ in the Canadian Longitudinal Study on Aging (n = 11,803; 49.6% male, 50.4% female) were included. Body composition was measured using dual X-ray absorptiometry. Sarcopenic obesity was defined using 29 definitions. Low handgrip strength was identified as < 27 kg in males and < 16 kg in females and poor physical performance was defined as gait speed ≤ 0.8 m/s. The prevalence of sarcopenic obesity ranged from 0.1 to 85.3% in males, and from 0 to 80.4% in females. Sarcopenic obesity was frequently associated with low handgrip strength (p < 0.05) in both males (14/17 definitions, 82.4%) and females (21/29 definitions, 72.4%). In very few definitions, sarcopenic obesity was associated with slow gait speed (males: 1/17 definitions [6.7%]; females: 2/29 [6.9%]). In conclusion, the prevalence of sarcopenic obesity varied greatly according to definitions and sarcopenic obesity was frequently associated with low handgrip strength.

Prevalence of sarcopenic obesity and sarcopenic overweight in the general population: The lifelines cohort study

BACKGROUND & AIMS

Sarcopenic obesity (SO) is defined by a relatively low muscle mass in combination with obesity. Sarcopenic obesity was first noted as a health risk in geriatric populations but has recently been recognized as a scientific and clinical priority that may extend beyond geriatric settings. Obesity is generally preceded by overweight, so the prevalence and health risks of sarcopenia in those with overweight (SOW) is of interest for preventive purposes. The aim of this study, therefore, was to assess the prevalence and determinants of SO and SOW in a general population.

METHODS

Participants (n = 119,494), aged 18-90 years were included from the Dutch Lifelines cohort study. Muscle mass was assessed by 24-h urine creatinine excretion and stratified for gender for analysis, and obesity was defined as a Body Mass Index (BMI) ≥30 kg/m² and overweight ≥25 kg/m². Multivariate logistic regression models were applied to assess the relevant determinants of SO and SOW.

RESULTS

Respectively for men and women the prevalence of SO was 0.9% and 1.4%, and prevalence of SOW 6.5% and 6.0%. In subjects with sarcopenia, BMI was ≥25 kg/m² in 45.5% and ≥30 kg/m² in 6.1%. Overall females had a higher prevalence of SOW and SO in all age groups except for SOW in males between ages 40-59. Also, age was a significant determinant of SO and SOW, with a rise in prevalence as of age 50. Of all subjects with SO and SOW, respectively 82.5% and 80.4% were below the age of 70. Compared to those with no morbidities, the odds ratio of SO and SOW among participants with >3 comorbidities was 2.71 (95% CI: 1.62-4.54) and 1.33 (95% CI: 1.07-1.65) among males and 1.14 (95% CI: 0.79-1.65) and 1.28 (95% CI: 1.06-1.54) among females, independent of other determinants. Overall, an inverse association was found between SOW and SO and physical activity and macronutrient intake.

CONCLUSION

The results support the need for more awareness of SO beyond the field of geriatrics, in particular in subjects with comorbidities. SOW is more prevalent than SO and may provide opportunities for preventive strategies for the general population.

Association between Skeletal Mass Indices and Metabolic Syndrome in Brazilian Adults

INTRODUCTION

Skeletal muscle is the primary site of glucose uptake and its reduction would increase insulin resistance, which is a determinant factor for diseases such as type 2 diabetes mellitus, hypertension, and metabolic syndrome. However, the role of low skeletal muscle mass as a risk factor for metabolic syndrome and its association with cardiometabolic risk is still uncertain. We aimed to investigate the association between muscle mass (determined by different skeletal mass indices) and metabolic syndrome in Brazilian adults.

METHODOLOGY

We conducted a cross-sectional population-based study with 689 adults of both sexes aged between 20 and 59 years. Data were collected through questionnaires and assessment of body composition through dual-energy X-ray absorptiometry and anthropometric, clinical, and biochemical measurements.

RESULTS

Older individuals, obese and those with metabolic syndrome predominated in the highest tertile of skeletal mass index adjusted by height (SMI_height), whereas using skeletal mass index adjusted by weight (SMI_weight) and skeletal mass index adjusted by body mass index (SMI_BMI) these individuals were the majority in the lowest tertile of these indices. In men and women, the adjusted logistic regression model revealed that the highest tertile of SMI_weight (odds ratio [OR]: 0.06; 95% confidence interval [CI]: 0.02-0.21 and OR: 0.27, 95% CI: 0.10-0.74) and SMI_BMI (OR: 0.14, 95% CI: 0.05-0.37 and OR: 0.34, 95% CI: 0.12-0.94) were negatively associated with metabolic syndrome. On the other hand, the highest tertile of SMI_height was positively associated with metabolic syndrome in both sexes (OR: 4.17, 95% CI: 1.80-9.66 and OR: 6.15, 95% CI: 2.31-16.37, respectively in men and women).

CONCLUSION

In adults, the muscle mass assessed from the skeletal mass index adjusted for body weight and body mass index is inversely associated with metabolic syndrome in both sexes.

Association between appendicular skeletal muscle index and leukocyte telomere length in adults: A study from National Health and Nutrition Examination Survey (NHANES) 1999-2002

BACKGROUND

A higher body mass index (BMI) is associated with shorter telomeres. The loss of muscle mass with aging is associated with adverse outcomes. The appendicular skeletal muscle index (ASMI) is currently used to quantify muscle mass.

OBJECTIVE

We investigated the association of the ASMI with leukocyte telomere length in adult Americans.

METHODS

This cross-sectional study used the National Health and Nutrition Examination Survey (NHANES) 1999-2002 dataset. Body composition was measured by dual-energy X-ray absorptiometry. Low muscle mass was defined using sex-specific thresholds of the appendicular skeletal muscle mass index (ASMI). The telomere-to-single-copy gene ratio (T/S ratio) was converted to base pairs. Generalized linear models were performed to evaluate the association of ASMI with telomere length.

RESULTS

In multivariable adjustment regression models, higher ASMI was associated with longer telomeres in US adults (β = 70.2, P < 0.001, P trend<0.001). In participants with preserved muscle mass, the ASMI was related to longer telomere length (β = 75.1, P < 0.001), but not significantly in low muscle mass participants (β = 68.7, P = 0.30). Further subgroup analysis by a combination of age groups and muscle mass status showed positive association with young-preserved muscle mass (β = 82.6, P < 0.001), old-preserved muscle mass (β = 44.4, P = 0.12), young-low muscle mass (β = 135.4, P = 0.20), and old-low muscle mass (β = 52.7, P = 0.55). Because each additional year of chronological age was associated with telomeres that were 15.3 base pairs shorter, on average, this would equate to 5.4 fewer years of biological aging (82.6 ÷ 15.3) in the young-preserved muscle mass participants.

CONCLUSIONS

A higher ASMI is associated with longer telomeres. The prevention of skeletal muscle loss has the potential to delay telomere shortening and account for less biological aging.

High-Intensity Interval Aerobic Resistance Training to Counteract Low Relative Appendicular Lean Soft Tissue Mass in Middle Age: Study Protocol for a Randomized Controlled Trial

BACKGROUND

Sarcopenia is the age-related loss of skeletal muscle mass and function and may exist in early middle age. Previous research in this area has focused on resistance training in older individuals; however, there is a lack of intervention trials in middle-aged adults with low relative appendicular lean soft tissue mass who may be at risk for sarcopenia in older age.

OBJECTIVE

This randomized controlled trial aims to determine the effects of a high-intensity interval aerobic resistance training intervention on appendicular lean soft tissue mass in middle-aged adults with low relative appendicular lean soft tissue mass.

METHODS

We will conduct a 40-week, single-blinded randomized controlled trial in 84 middle-aged adults with low appendicular lean soft tissue mass in the wider Dunedin area, New Zealand. We will randomly allocate participants to receive either a group-based, 20-week high-intensity interval aerobic resistance training intervention program or a single, 60-minute education session on current exercise recommendations. After the first 20 weeks, both groups will be given a 20-week home program. The study will assess primary and secondary outcome measures, including body composition (regional and whole-body lean soft tissue mass, fat mass, percentage body fat, measured by dual x-ray absorptiometry), blood biomarkers (cortisol, creatinine, C-reactive protein, lipid profile, hemoglobin), physical fitness (maximum oxygen consumption, blood pressure), physical activity (accelerometry), physical function (handgrip strength, sit-to-stand, gait speed, quadriceps strength), and self-reported questionnaires (health outcomes, self-efficacy, perceived enjoyment of physical activity, and multifactorial lifestyle), at baseline, 20 weeks, and 40 weeks. Physical function and self-reported questionnaires will also be measured at 10 weeks. We will assess the primary outcome measure, total body lean soft tissue mass, at baseline, 20 weeks, and 40 weeks. Analyses will be performed using intention-to-treat principles, comparing the outcomes resulting from the intervention, using linear mixed models.

RESULTS

We obtained ethical approval for this study from The University of Otago Human Ethics Committee on December 10, 2018. Participant recruitment started on February 11, 2019 and was completed on May 14, 2019. Data collection started on February 25, 2019 and was completed on February 28, 2020. We expect to publish the results in January 2021.

CONCLUSIONS

High-intensity interval aerobic resistance training is a time-efficient form of exercise, enabling busy middle-aged adults to meet physical activity recommendations while maximizing training results. The findings can inform the development of future prevention-focused interventions aimed at counteracting the high prevalence of sarcopenia in the aging population.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ACTRN12618001778279); https://tinyurl.com/y555z6fz.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/22989.

Reference Centiles for the Evaluation of Nutritional Status in Children using Body Fat Percentage, Fat Mass and Lean Body Mass Index

BACKGROUND

Body fat percentage (BF%), fat mass index (FMI), and lean body mass index (LBMI) are often used to evaluate the nutritional status of children. Until now, no pediatric FMI reference centiles are applicable for GE Healthcare Lunar DXA systems. The aim of the study was to generate age-specific BF%, FMI, and LBMI references centiles for GE Healthcare Lunar DXA systems.

METHODOLOGY

Published values from the National Health and Nutrition Examination Survey 1999-2004 (age 8-20 years) were used to generate the reference centiles for the non-Hispanic black, non-Hispanic white, and Mexican American NHANES population. The LMS and LMSP methods were used to generate the reference centiles.

RESULTS

Data of 2433 non-Hispanic black children (972 females), 2026 non-Hispanic white children (873 females), and 2547 Mexican American children (1010 females) were eligible.

CONCLUSIONS

We presented age-specific reference centiles for BF%, FMI, and LBMI for children and adolescents which were ethnicity specific (non-Hispanic black, non-Hispanic white, and Mexican American) and directly applicable to Prodigy and iDXA GE Healthcare Lunar systems with software version 14.0. We proposed the use of BF%, FMI, and LBMI together to evaluate nutritional status in children.