Prediction of segmental lean mass using anthropometric variables in young adults

Relationship between Longitudinal Upper Body Rotation and Energy Cost of Running in Junior Elite Long-Distance Runners

Running is a basic form of human locomotion and one of the most popular sports worldwide. While the leg biomechanics of running have been studied extensively, few studies have focused on upper-body movement. However, an effective arm swing and longitudinal rotation of the shoulders play an important role in running efficiency as they must compensate for the longitudinal torques generated by the legs. The aim of this study is to assess the upper-body rotation using wearable inertial sensors and to elucidate its relation to energy expenditure. Eighty-six junior elite middle- and long-distance runners (37 female, 49 male) performed an incremental treadmill test with sensors attached on both shoulders, tibiae and the sacrum. The mean and total horizontal shoulder and pelvis rotations per stride were derived while energy costs were determined using respiratory gas analysis and blood sampling. Results show that shoulder and pelvis rotations increase with running speed. While shoulder rotation is more pronounced in female than in male runners, there is no sex difference for pelvis rotation. The energy cost of running and upper trunk rotation prove to be slightly negatively correlated. In conclusion, upper body rotation appears to be an individual characteristic influenced by a sex-specific body mass distribution.

Prediction equations to estimate muscle mass using anthropometric data: a systematic review

CONTEXT

Reduced muscle mass is linked to poor outcomes in both inpatients and outpatients, highlighting the importance of muscle mass assessment in clinical practice. However, laboratory methods to assess muscle mass are not yet feasible for routine use in clinical practice because of limited availability and high costs.

OBJECTIVE

This work aims to review the literature on muscle mass prediction by anthropometric equations in adults or older people.

DATA SOURCES

The following databases were searched for observational studies published until June 2022: MEDLINE, Embase, Scopus, SPORTDiscus, and Web of Science.

DATA EXTRACTION

Of 6437 articles initially identified, 63 met the inclusion criteria for this review. Four independent reviewers, working in pairs, selected and extracted data from those articles.

DATA ANALYSIS

Two studies reported new equations for prediction of skeletal muscle mass: 10 equations for free-fat mass and lean soft tissue, 22 for appendicular lean mass, 7 for upper-body muscle mass, and 7 for lower-body muscle mass. Twenty-one studies validated previously proposed equations. This systematic review shows there are numerous equations in the literature for muscle mass prediction, and most are validated for healthy adults. However, many equations were not always accurate and validated in all groups, especially people with obesity, undernourished people, and older people. Moreover, in some studies, it was unclear if fat-free mass or lean soft tissue had been assessed because of an imprecise description of muscle mass terminology.

CONCLUSION

This systematic review identified several feasible, practical, and low-cost equations for muscle mass prediction, some of which have excellent accuracy in healthy adults, older people, women, and athletes. Malnourished individuals and people with obesity were understudied in the literature, as were older people, for whom there are only equations for appendicular lean mass.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42021257200.

Anthropometric equations to estimate appendicular muscle mass from dual-energy X-ray absorptiometry (DXA): A scoping review

BACKGROUND

Appendicular skeletal muscle mass (ASM) obtained from dual-energy x-ray absorptiometry (DXA) is recommended to quantify sarcopenia, but has limited availability in disadvantaged-income countries, moreover in an epidemiological context. Predictive equations are easier and less costly to apply, but a review of all available models is still lacking in the scientific literature. The objective of this work is to map, with a scoping review, the different proposed anthropometric equations to predict ASM measured by DXA.

METHODS

Six databases were searched without restriction on publication date, idiom, and study type. A total of 2,958 studies were found, of which 39 were included. Eligibility criteria involved ASM measured by DXA, and equations proposed to predict ASM.

RESULTS

predictive equations (n = 122) were gathered for 18 countries. The development phase involves sample size, coefficient of determination (r²), and a standard error of estimative (SEE) varying between 15 and 15,239 persons, 0.39 and 0.98, 0.07 and 3.38 kg, respectively. The validation phase involves a sample size, accuracy, and a SEE between 15 and 3,003 persons, 0.61 and 0.98, 0.09 and 3.65 kg, respectively.

CONCLUSIONS

The different proposed predictive anthropometric equations of ASM DXA were mapped, including validated pre-existing equations, offering an easy-to-use referential article for clinical and research applications. It is necessary to propose more equations for other continents (Africa and Antarctica) and specific health-related conditions (e.g., diseases), once the equations can only have sufficient validity and accuracy to predict ASM generally when applied to the same population.

The rs483145 polymorphism of MC4R gene is not associated with obesity in the Chilean population: Results of GENADIO study

INTRODUCTION

The melanocortin receptor 4 (MC4R) participates in the control of appetite at the level of the central nervous system, through the leptin-melanocortin pathway. An association between different polymorphisms of the MC4R gene and obesity has been reported. However, there are few studies of the rs483145 single nucleotide polymorphism (SNP) of this gene.

OBJECTIVE

To investigate its prevalence and association with adiposity markers in Chilean adults.

METHODS

The prevalence of SNP rs483145, of the MC4R gene, was determined in 259 participants of the GENADIO study (genes, environment, diabetes and obesity) by means of real-time polymerase chain reaction (PCR). The association between the risk allele of MC4R (A) and adiposity markers (body weight, body mass index, fat mass percentage, hip circumference, waist circumference, waist-to-hip ratio) was performed by linear regression analysis and adjusted for confusion variables (socio-demographic and physic activity) using three statistical models.

RESULTS

It was determined that the prevalence of the risk allele (A) of the SNP rs483145 of the MC4R gene is 24.5% in the Chilean adult population included in this study, without finding an association with any of the adiposity markers studied, both in adjusted and unadjusted models.

CONCLUSION

The presence of the risk allele of SNP rs483145 of the MC4R gene is not associated with adiposity markers in the Chilean adult population studied. New studies with a bigger sample size will be necessary to confirm these results.

The rs483145 polymorphism of MC4R gene is not associated with obesity in the Chilean population: Results of GENADIO study

INTRODUCTION

The melanocortin receptor 4 (MC4R) participates in the control of appetite at the level of the central nervous system, through the leptin-melanocortin pathway. An association between different polymorphisms of the MC4R gene and obesity has been reported. However, there are few studies of the rs483145 single nucleotide polymorphism (SNP) of this gene.

OBJECTIVE

To investigate its prevalence and association with adiposity markers in Chilean adults.

METHODS

The prevalence of SNP rs483145, of the MC4R gene, was determined in 259 participants of the GENADIO study (genes, environment, diabetes and obesity) by means of real-time polymerase chain reaction (PCR). The association between the risk allele of MC4R (A) and adiposity markers (body weight, body mass index, fat mass percentage, hip circumference, waist circumference, waist-to-hip ratio) was performed by linear regression analysis and adjusted for confusion variables (socio-demographic and physic activity) using three statistical models.

RESULTS

It was determined that the prevalence of the risk allele (A) of the SNP rs483145 of the MC4R gene is 24.5% in the Chilean adult population included in this study, without finding an association with any of the adiposity markers studied, both in adjusted and unadjusted models.

CONCLUSION

The presence of the risk allele of SNP rs483145 of the MC4R gene is not associated with adiposity markers in the Chilean adult population studied. New studies with a bigger sample size will be necessary to confirm these results.

Predicting muscular strength using demographics, skeletal dimensions, and body composition measures

The purpose of this study was to develop an equation to predict strength for seven common resistance training exercises using anthropometric and demographic measures. One-hundred forty-seven healthy adults (74 males, 73 females, 35 ± 12 yr, 174 ± 10 cm, 88 ± 19 kg) volunteered to participate. Body composition values (regional/total) and body dimensions were assessed using dual-energy x-ray absorptiometry (DEXA). Subjects underwent the following maximal strength assessments: Leg Press, Chest Press, Leg Curl, Lat Pulldown, Leg Extension, Triceps Pushdown, and Biceps Curl. Multiple linear regression with stepwise removal was used to determine the best model to predict maximal strength for each exercise. Independent predictor variables identified (p < 0.05) were height (cm); weight (kg); BMI; age; sex (0 = F,1 = M); regional lean masses (LM,kg); fat mass (FM,kg); fat free mass (FFM,kg); percent fat (%BF); arm, leg, and trunk lengths (AL, LL, TL; cm); and shoulder width (SW,cm). Analyses were performed with and without regional measures to accommodate scenarios where DEXA is unavailable. All models presented were significant (p < 0.05, R² = 0.68–0.83), with regional models producing the greatest accuracy. Results indicate that maximal strength for individual resistance exercises can be reasonably estimated in adults.

Are body circumferences able to predict strength, muscle mass and bone characteristics in obesity? A preliminary study in women

Measurement of body circumferences (BCs) is widely used as an anthropometric tool to assess body composition and health risk in obese individuals. In this preliminary work we evaluated the association of several BCs with Dual-energy X-ray Absorptiometry (DXA)-measured lean mass as well as leg press test scores with an aim at exploring the potential of BCs as predictor of body composition and muscle strength. A total of 34 female participants aged 47.3±7.6 y who were obese (BMI, 30.4-43.7 kg/m2) were recruited. The upper arm (relaxed), wrist, chest, waist, hip, thigh, and calf circumferences were measured. The skinfold-corrected muscle (including bone) circumferences at the arm, thigh, and calf site were also calculated. Lean mass components were measured by DXA with a Hologic QDR Explorer scanner according to the manufacturer's procedures. Lower limbs strength was assessed with the 1-Repetition Maximum leg press. Bivariate association between variables was assessed with the Spearman's correlation coefficient after the Benjamini and Hochberg False Discovery Rate procedure. Predictive equations were developed using stepwise multiple regression analysis. Several statistically significant correlations (Benjamini and Hochberg corrected P [Pc] < 0.05) were present between BCs and DXA-measured body composition variables, and leg press test scores with special regard to the chest, arm, waist, and hip circumferences. Multiple regression analysis yielded statistically significant predictive models (Pc < 0.05 for all; adjusted R2 ranging 0.123 - 0.504; standard error of the estimate ranging 4.0% - 11% of the mean measured value) for all body composition as well as leg press outcomes. The current findings show that BCs represent a simple, suitable anthropometric measurement with a potential to predict several lean mass components as well as lower limbs strength in obese females. The proposed predictors need to be validated in a larger sample of participants and in obese males.

Upper and lower limbs composition: a comparison between anthropometry and dual-energy X-ray absorptiometry in healthy people

The detection of changes in lean mass (LM) distribution can help to prevent disability. This study assessed the degree of association between anthropometric measurements and dual-energy X-ray absorptiometry (DXA) body composition (BC) parameters of the upper and lower limbs in a healthy general population and collected DXA age- and sex-specific values of BC that can be useful to build a reference standard.

PURPOSE

The primary aim of this study was to investigate the reliability of some widely available anthropometric measurements in the assessment of body composition (BC) at the limbs, especially in terms of muscle mass, in a large sample of healthy subjects of different age bands and sex, using fat mass (FM) and lean mass (LM) parameters derived by dual-energy X-ray absorptiometry (DXA) as the gold standard. The secondary aim was to collect DXA age- and sex-specific values of BC of left and right limbs (upper and lower) in a healthy Italian population to be used as reference standards.

METHODS

Two hundred fifty healthy volunteers were enrolled. Arm circumference (AC) and thigh circumference (ThC) were measured, and total and regional BC parameters were obtained by a whole-body DXA scan (Lunar iDXA, Madison, WI, USA; enCORE™ 2011 software version 13.6).

RESULTS

FM/LM showed only fair correlation with AC and ThC in females (r = 0.649 and 0.532, respectively); in males and in the total population, the correlation was low (r = 0.360 or lower, and p non-statistically significant). AC and ThC were not well representative of arms LM in both genders (females r = 0.452, males r = 0.530) independently of age. In general, men of all age groups showed higher values of LM and lean mass index (LMI) in both total and segmental upper and lower limbs. In males, the maximum LM and LMI were achieved in the fifth decade in both upper and lower limbs and then started to decrease with aging. In females, no significant modification with aging was identified in LM and LMI.

CONCLUSION

According to our results, anthropometry is not well representative of LM of arms in both genders, independently of age; therefore, a densitometric examination should be considered for a correct assessment of BC at limbs.

Predicting appendicular lean and fat mass with bioelectrical impedance analysis in older adults with physical function decline - The PROVIDE study

BACKGROUND & AIMS

No generalizable formulas exist that are derived from bioelectrical impedance analysis (BIA) for predicting appendicular lean mass (ALM) and fat mass (AFM) in sarcopenic older adults. Since precision of regional body composition (BC) data in multicentre trials is essential, this study aimed to: 1) develop and cross-validate soft tissue BIA equations with GE Lunar and Hologic DXA systems as their reference 2) to compare our new ALM equation to two previously published models and 3) to assess the agreement between BIA- and DXA-derived soft tissue ratios as indicators of limb tissue quality.

METHODS

Two-hundred and ninety-one participants with functional limitations (SPPB-score 4-9; sarcopenia class I or II, measured by BIA) were recruited from 18 study centres in six European countries. BIA equations, using DXA-derived ALM and AFM as the dependent variable, and age, gender, weight, impedance index and reactance as independent variables, were developed using a stepwise multiple linear regression approach.

RESULTS

Cross-validation gave rise to 4 equations using the whole sample: ALM_LUNAR (kg) = 1.821 + (0.168*height²/resistance) + (0.132*weight) + (0.017*reactance) - (1.931*sex) [R² = 0.86 and SEE = 1.37 kg] AFM_LUNAR (kg) = -6.553 - (0.093* height²/resistance) + (0.272*weight) + (4.295*sex) [R² = 0.70 and SEE = 1.53 kg] ALM_HOLOGIC (kg) = 4.957 + (0.196* height²/resistance) + (0.060*weight) - (2.554*sex) [R² = 0.90 and SEE = 1.28 kg] AFM_HOLOGIC (kg) = -4.716 - (0.142* height²/resistance) + (0.316*weight) + (4.453*sex) - (0.040*reactance) [R² = 0.73 and SEE = 1.54 kg] Both previously published models significantly overestimated ALM in our sample with biases of -0.36 kg to -1.05 kg. For the ratio of ALM to AFM, a strong correlation (r = 0.82, P < 0.0001) was found between the mean estimate from BIA and the DXA models without significant difference (estimated bias of 0.02 and 95% LOA -0.62, 0.65).

CONCLUSION

We propose new BIA equations allowing the estimation of appendicular lean and fat mass. Our equations allow to accurately estimate the appendicular lean/fat ratio which might provide information regarding limb tissue quality, in clinical settings. Furthermore, these BIA equations can be applied to characterize sarcopenia with Hologic and Lunar reference values for BC. Previously published BIA-based models tend to overestimate ALM in sarcopenic older adults. Users of both GE Lunar and Hologic may now benefit from these equations in field research.

Use of anthropometry for the prediction of regional body tissue distribution in adults: benefits and limitations in clinical practice

Regional body composition changes with aging. Some of the changes in composition are considered major risk factors for developing obesity related chronic diseases which in turn may lead to increased mortality in adults. The role of anthropometry is well recognized in the screening, diagnosis and follow-up of adults for risk classification, regardless of age. Regional body composition is influenced by a number of intrinsic and extrinsic factors. Therapeutic measures recommended to lower cardiovascular disease risk include lifestyle changes. The aim of this review is to systematically summarize studies that assessed the relationships between anthropometry and regional body composition. The potential benefits and limitations of anthropometry for use in clinical practice are presented and suggestions for future research given.

Assessment of regional adipose tissue depots: a DXA and CT comparison in cadavers of elderly persons

OBJECTIVE

Since dual energy X-ray absorptiometry (DXA) cannot distinguish between different adipose tissue (AT) deposits, it remains unclear how DXA-derived body composition variables relate to anatomical tissue (sub)compartments. The aim of the present study was to compare and relate regional DXA variables with absolute tissue masses obtained by computer tomography (CT) scanning of the lower limbs in elderly persons.

METHODS

Eleven well-preserved white Caucasian adults (seven male and four female cadavers) with a median age of 79.0 years (ranging from 68 to 96 years) were fully scanned with DXA and CT. Separate densities of skin tissue, AT, muscle tissue and bone were obtained by hydrostatic weighing.

RESULTS

The leg DXA-variables were significantly related (rho-values between 0.60 and 0.98, P < 0.01) to CT-derived tissue counterparts, but showed significant systematic differences except for subcutaneous AT mass (P = 0.773). After controlling for other AT depots, fat as measured by DXA (fat(DXA)) related only to intermuscular AT (rho = 0.82, P < 0.01) in males and to subcutaneous AT (rho = 0.84, P < 0.05) in females.

CONCLUSION

Although significantly interrelated, DXA and CT variables should not be used interchangeably since they have different quantitative and physiological significance. Our results suggest that fat(DXA) represents different parts of AT depots in elderly men and women. Since DXA is not appropriate for assessing tissue variability cautious clinical interpretation is warranted.