Development and validation of anthropometric equations to estimate appendicular muscle mass in elderly women

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.

Altered Visceral Adipose Tissue Predictors and Women’s Health: A Unicenter Study

(1) Background: The excess visceral adipose tissue (VAT) accumulation in women may reflect an early or advanced state of a metabolic disorder and a higher risk of cardiovascular disease than other types of obesity. This study aimed to determine the predictor variables (demographic information, anthropometric data, and blood biomarkers) for changes in VAT in adult women. (2) Methods: This cross-sectional study was conducted with women aged 18–59 years attending nutritional consultation at the Centro Universitário de Brasília (CEUB)’s nutrition school clinic, Brazil. All participants’ medical records were reviewed throughout the study and data of interest were collected. Various anthropometric measurements and biochemical exams were performed and analyzed in a univariate logistic regression model to identify the possible risk factors predictors for the presence of altered VAT. (3) Results: Our logistic regression model considered body mass index (BMI) greater than 25 kg/m², lipid accumulation product (LAP), and waist–hip ratio (WHR) as predictors of altered VAT. (4) Conclusion: LAP has a robust predictive capacity for changes in visceral fat in adult women, followed by WHR and BMI, making these variables effective in assessing the risk for changes in visceral fat and their inclusion essential in the individual and collective clinical practice.

Artificial neural network model effectively estimates muscle and fat mass using simple demographic and anthropometric measures

BACKGROUND & AIMS

Lean muscle and fat mass in the human body are important indicators of the risk of cardiovascular and metabolic diseases. Techniques such as dual-energy X-ray absorptiometry (DXA) accurately measure body composition, but they are costly and not easily accessible. Multiple linear regression (MLR) models have been developed to estimate body composition using simple demographic and anthropometric measures instead of expensive techniques, but MLR models do not explore nonlinear interactions between inputs. In this study, we developed simple demographic and anthropometric measure-driven artificial neural network (ANN) models that can estimate lean muscle and fat mass more effectively than MLR models.

METHODS

We extracted the demographic, anthropometric, and body composition measures of 20,137 participants from the National Health and Nutrition Examination Survey conducted between 1999 and 2006. We included 13 demographic and anthropometric measures as inputs for the ANN models and divided the dataset into training and validation sets (70:30 ratio) to build and cross-validate the models that estimate lean muscle and fat mass, which were originally measured using DXA. This process was repeated 100 times by randomly dividing the training and validation sets to eliminate any effect of data division on model performance. We built additional models separately for each sex and ethnicity, older individuals, and people with underlying diseases. The coefficient of determination (R²) and standard error of estimate (SEE) were used to quantify the goodness of fit.

RESULTS

The ANN models yielded high R² values between 0.923 and 0.981. These values were significantly higher than those of the MLR models (p < 0.001) in all cases. The percentage difference in R² between the ANN and MLR models ranged between 0.40% ± 0.02% and 2.65% ± 0.27%. The SEE values of the ANN models, which were below 2 kg for all cases, were significantly lower than those of MLR models (p < 0.001). The percentage difference in SEE values between the ANN and MLR models ranged between -5.67% ± 0.39% and -22.32% ± 1.98%.

CONCLUSIONS

We developed and validated an inexpensive but effective method for estimating body composition using easily obtainable demographic and anthropometric data.

Associations between locomotive and non-locomotive physical activity and physical performance in older community-dwelling females with and without locomotive syndrome: a cross-sectional study

Background

Locomotive syndrome (LS) is a condition of reduced mobility due to a disorder of the locomotive system. Increasing moderate to vigorous physical activity (MVPA) has been recommended to prevent LS. However, to increase daily MVPA is difficult for older people with LS. The MVPA consists of not only locomotive activities such as walking but also non-locomotive activities such as household activities. The aim of this study was to examine the associations between locomotive/non-locomotive MVPA and physical performance in older females with and without LS.

Methods

Participants of this cross-sectional study were 143 older community-dwelling Japanese females. The participants were divided into two groups based on the results of the stand-up test: the normal group (NL) (n = 86) and the LS group (n = 57). Both the locomotive and non-locomotive PA seperately measured with its intensity. The intensity of physical activity (PA) was calculated as METs and classified as sedentary behavior (SB 1–1.5 metabolic equivalent tasks (METs)), low-intensity physical activity (LPA 1.6–2.9 METs), and MVPA (≥ 3 METs). For example, locomotive LPA is slow walking speed of 54 m/min, and locomotive MVPA is walking speed of 67 m/min. While non-locomotive LPA is office work and cooking, non-locomotive MVPA is housecleaning. Physical function was evaluated by handgrip strength, walking speed, and 2-step test.

Results

Walking speed, hand-grip strength, 2-step test, daily step counts, and all PA measurements were not significantly different between two groups. In the LS, locomotive MVPA (r = 0.293, p < 0.05) and total MVPA (r = 0.299, p < 0.05) was significantly correlated with walking speed, but not in the NL.

Conclusions

Walking speed was positively correlated with locomotive MVPA and total MVPA in the LS group, but not in NL group. This result suggests that slow walking speed in older people with LS occur in connection with lower locomotive MVPA and total MVPA.

Development of a Simple and Practical Screening Tool for Detection of Sarcopenia in Older People: The Bushehr Elderly Health Program

Background: Sarcopenia is defined by the loss of muscle mass and function with a considerable prevalence which increases morbidity and mortality. We aimed to develop and validate a simple tool for screening of sarcopenia in Iranian older population.

Methods: In this study, we included 2,211 adults aged 60 years or older that participated in the stage II of Bushehr Elderly Health (BEH) program, a population-based prospective cohort study. We defined sarcopenia as reduced skeletal muscle strength plus low muscle mass. The study sample was divided into two parts; development set which were allocated to the development of the model (n = 1,499) and validation set (n = 712) were allocated to validation of the model.

Results: There were 22.9% of men and 23.2% women classified as having sarcopenia based on EWGSOP-2.After selection of variables, the final models named SarSA-Mod (Sarcopenia Scoring Assessment Models) were developed with area to under curves (AUC) of 0.82 (0.79–0.86) and 0.87 (0.84–0.90) in men and women, respectively. The final model included “age,” “weight,” and “calf circumference” in both sexes. The sensitivity and specificity and positive and negative predictive values for sarcopenia were 84.3, 76.0, 49.8, and 94.5% for women, 85.4, 64.8, 40.2, and 94.2% for men, respectively. The model performance was tested in the validation set with accuracy 91 and 84% among women and men, respectively.

Conclusions: Sarcopenia could be detected using SarSA-Mod, as a simple screening test with high accuracy among both sexes. Also, this screening test is valid, feasible, reliable and cost-effective compared to other tools.

Development of new adjusted equations to estimate the skeletal muscle mass stratified by nutritional status for patients with rheumatoid arthritis: a methodological study

Abstract Our objective was to adjust and validate predictive equations for appendicular skeletal muscle mass (ASM) in patients with Rheumatoid Arthritis (RA). Whole-body DXA data in 90 RA patients were used for measurement of ASM (kg). The prediction equation anthropometric for muscle mass proposed by Lee et al was used to generate estimates of ASM. Appendicular skeletal muscle mass index (ASMI, kg/m2) was calculated. Frequency analysis, Paired student's t-test, Linear regression, Pearson correlation, Intraclass correlation coefficients, and Bland-Altman scatter were performed. The statistical significance considered was p<0.05. Lee’s equation was overestimated by 30% when compared with ASMI by DXA. When stratified by nutritional status, Lee’s equation overestimated the ASMI by 30% in overweight patients and by 50% in obese patients when compared with DXA (p<0.05). These adjusted equations estimated values for ASMI were closer to those obtained by DXA than those estimated by the original Lee’s equation (p<0.05). This greater concordance was confirmed by the observed interclass correlation coefficients and by Bland-Altman scatter graphs. In conclusion, the prediction of muscle mass in RA patients may be performed with equations that consider the nutritional status of patients.

Estimating appendicular muscle mass in older adults with consideration on paralysis

AIM

This study aimed to develop appendicular skeletal muscle mass (ASM) estimating formulas that also consider the presence of paralysis for older adults and people with disabilities.

METHODS

This retrospective study analyzed 315 consecutive patients, post-stroke, aged ≥65 years, in a rehabilitation hospital. Six different ASM estimating formulas were developed using a five-fold cross-validation method and compared with the measured ASM obtained from bioelectrical impedance analysis. These formulas included age, gender, height, weight, arm circumference, triceps skinfold, calf circumference and presence of paralysis. Using Pearson's correlation coefficients (r) and intraclass correlation coefficient (ICC), we examined the correlation between the formulas and the measured ASM. The accuracy of the ASM estimating formula for detecting decreased muscle mass was evaluated using the F-value and Matthew's correlation coefficient.

RESULTS

Patients' mean ± SD age was 79.0 ± 8.1 years, and 51.4% of them were men. The mean ± SD bioelectrical impedance analysis-measured ASM was 13.7 ± 4.3 kg. Furthermore, 241 (76.5%) patients had decreased measured ASM. The mean adjusted R² of the developed six formulas was 0.861-0.871. In all formulas, the r and ICC of the estimated ASM for the measured ASM were strong (r = 0.936-0.930 and ICC = 0.928-0.934). These formulas revealed excellent sensitivity (86.0-88.2%), specificity (72.5-81.1%), accuracy (0.838-0.870), F-value (0.899-0.918) and Matthew's correlation coefficient (0.509-0.612) for measured ASM depletion.

CONCLUSIONS

We successfully developed ASM estimating formulas using anthropometric measurements considering the presence of paralysis. Thus, these formulas are beneficial for diagnosing sarcopenia in older adults, without requiring any special equipment. Geriatr Gerontol Int 2020; 20: 1145-1150.

Population specificity affects prediction of appendicular lean tissues for diagnosed sarcopenia: a cross-sectional study

Introduction

Introduction: the estimation of appendicular lean soft tissue by DXA (ALSTDXA) is one of the criteria for the diagnosis of sarcopenia. However, this method is expensive and not readily avaiable in clinical practice. Anthropometric equations are low-cost and able to accurate predict ALST, but such equations have not been validated for male Brazilian older adults between the ages of 60 to 79 years. To this end, this study sought to validate the existing predictive anthropometric equations for ALST, and to verify its accuracy for the diagnosis of sarcopenia in male Brazilian older adults. Methods: this cross-sectional study recruited and enrolled 25 male older adults (69.3 ± 5.60 years). ALSTDXA and anthropometric measures were determined. ALST estimations with 13 equations were compared to ALSTDXA. The validity of the equations was established when: p > 0.05 (paired t-test); standard error of the estimate (SEE) < 3.5 kg; and coefficient of determination r² > 0.70. Results: two Indian equations met the criteria (Kulkarini 1: 22.19 ± 3.41 kg; p = 0.134; r² = 0.78; EPE = 1.3 kg. Kulkarini 3: 22.14 ± 3.52 kg; p = 0.135; r² = 0.82; SEE = 1.2 kg). However, these equations presented an average bias (Bland-Altman: 0.54 and 0.48 kg) and 'false negative' classification for the ALST index. Thus, three explanatory equations were developed. The most accurate equation demonstrated a high level of agreement (r2adj = 0.87) and validity (r²PRESS = 0.83), a low predictive error (SEEPRESS = 1.53 kg), and an adequate ALST classification. Conclusion: anthropometric models for predicting ALST are valid alternatives for the diagnosis and monitoring of sarcopenia in older adults; however, population specificity affects predictive validity, with risks of false positive/negative misclassification.

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.

Osteosarcopenic obesity, the coexistence of osteoporosis, sarcopenia and obesity and consequences in the quality of life in older adults ≥65 years-old in Greece

OBJECTIVE

We investigated the coexistence of sarcopenia and obesity in older adults≥65 years diagnosed with osteoporosis and the association with Quality of Life (QoL).

METHODS

A Cross-sectional survey has been performed on a randomized sample of 50 diagnosed osteoporotic elderly people from both sexes (Men=16; Women=34).

MEASUREMENTS

Quantitative ultrasound was conducted to identify osteoporosis and defined with a T score ≤2.5. Validated anthropometric equations were used in order to estimate body fat percentage and skeletal muscle mass so as to detect the reallocation of body fat and lean muscle. 10m gait speed and hand grip strength was measured in order to diagnose sarcopenia according to European Society for Clinical Nutrition and Metabolism (ESPEN) algorithm. The evaluation of QoL was conducted using a QoL questionnaire specific to osteoporosis. The data were analyzed with descriptive statistics and a chi-square test was performed to examine if Osteosarcopenic Obesity (OSO) is sex related and the correlation between OSO and QoL.

RESULTS

From the 50 participants, 40%(n=19) were classified as people with OSO and 60%(n=31) without OSO. From n=19 people that experienced OSO women represent 20% (n=9) and men 18% (n=9); with the latter had a greater decline in muscle mass than women, while women had lower BMD than men according to the z score. OSO is not related with sex (p>.05) and there is no significant association between OSO and QoL (p> .05 for all the domains of QoL questionnaire).

CONCLUSION

Osteoporosis in the elderly often coexists with reduced muscle mass and muscle strength as well as an increase in adiposity and was independently associated with QoL. People that experience OSO presenting lower functionality that increases the risk for falls and bone fractures originated from the decline in bone and muscle mass, and increased adiposity. Increased awareness of OSO may help develop efficient interventions and public health policies for healthier and more active elderly people.

Potential Role of Nutrient Intake and Malnutrition as Predictors of Uremic Oxidative Toxicity in Patients with End-Stage Renal Disease

Oxidative stress is an important risk factor for cardiovascular disease and death in hemodialysis (HD) patients. However, whether biochemical and nutritional markers might be useful to stratify HD patients according to the risk of oxidative damage remains unclear. We investigated whether low-cost and easily available parameters such as the profile of nutrients intake, nutritional status, and antioxidant defenses can predict lipid and protein oxidation in HD patients. Forty-nine HD patients (women = 20, men = 29), ranging from 18 to 65 years of age (73.5%) were submitted to biochemical and nutritional analysis. At least 93.9% of HD patients had malnutrition. A patient's stratification according to nutritional risk was highly coherent with anthropometric parameters and nutrients intake, which were complementarily used as markers of malnutrition. Nutritional stratification was unable to reveal differences in the oxidative status. On the other hand, carbohydrate and zinc intake, serum zinc (Zn), glutathione peroxidase (GPx) activity, total antioxidant capacity (TAC), and nonprotein antioxidants (npAC) in serum were predictive markers of lipid (R 2 = 0.588, P < 0.001) and protein (R 2 = 0.581, P < 0.001) oxidation. Interestingly, GPx activity, TAC, and npAC exhibited good (>80% < 90%) or excellent (>90%) accuracy to estimate lipid oxidation (P ≤ 0.01). Regarding the prediction of protein oxidation, GPx activity and TAC presented regular accuracy (>70% < 80%), and Zn serum levels exhibited good sensitivity (P ≤ 0.01). Herein, we provided evidence that clinical characteristics relevant to predict different levels of lipid and protein oxidation in HD patients can be easily obtained, during routine hospital visits by means of the combined analyses of biochemical and nutritional parameters.

Development & cross-validation of anthropometric predictive models to estimate the appendicular skeletal muscle mass in middle-aged women in Sri Lanka

Background & objectives:

Attempts have been made to estimate appendicular skeletal muscle mass (ASMM) using anthropometric indices and most of these are country specific. This study was designed to develop and cross-validate simple predictive models to estimate the ASMM based on anthropometry in a group of healthy middle-aged women in Sri Lanka.

Methods:

The study was conducted on a randomly selected group of community-dwelling women aged 30-60 years. ASMM (kg) quantified with dual-energy X-ray absorptiometry (DXA) (ASMM_DXA) was used as the reference standard. Anthropometric measurements such as body weight (kg), height (m), limb circumferences (cm) and skinfold thickness (mm) which showed significant correlations with ASMM_DXA, were used to develop the models. The models were developed using a group of 165 women (aged 30-60 yr) and were cross-validated using a separate sample of women (n=167) (mean age: 48.9±8.56 yr), selected randomly.

Results:

Nine anthropometry-based models were developed using weight, height, skinfold thicknesses, circumferences, body mass index, menopausal status (MS) and age as independent variables. Four models which were based on height, weight, triceps skinfold thickness (TSFT), age and MS met all the validation criteria with high correlations (ranged 0.89-0.92) and high predictive values explaining high variance (80-84%) with low standard error of estimate (1.10-1.24 kg).

Interpretation & conclusions:

The four models (ASMM 1-ASMM 4) developed based on height, weight, TSFT, age and MS showed a high accuracy in estimating the ASMM in middle-aged women.

Estimation of appendicular skeletal muscle: Development and validation of anthropometric prediction equations in Chinese patients with knee osteoarthritis

OBJECTIVE

To develop anthropometric prediction equations for estimating appendicular skeletal muscle (ASM) in Chinese knee osteoarthritis patients.

METHODS

Subjects were divided into the model development group (MD group: 104 cases, 47 men and 57 women) and cross-validation group (CV group: 69 cases, 38 men and 31 women). Stepwise multiple linear regression analyses were undertaken in the MD group to identify the best equations. Agreement between the estimated ASM and ASM measured by dual-energy X-ray absorptiometry (DXA) was tested in the CV group.

RESULTS

Two models were developed in the MD group. Validation in the CV group showed that our models (R²  = 0.83 and R²  = 0.90) had a high coefficient of determination. The mean bias of ASM estimated by the two models from the ASM measured by DXA in the CV group showed no significant difference (P > 0.05).

CONCLUSION

These models could be useful for older Chinese patients with knee osteoarthritis to estimate ASM.

Concordance between appendicular skeletal muscle mass measured with DXA and estimated with mathematical models in middle-aged women

BACKGROUND

Appendicular skeletal muscle mass (ASMM) is a measure of body muscle content, and it correlates with nutrition and physical status. Estimation of ASMM using anthropometric models is a well-established strategy to overcome issues related to the restricted availability of sophisticated techniques in measuring ASMM. This study aimed to assess the validity of four selected anthropometric models in estimating ASMM in middle-aged women in Sri Lanka.

METHODS

A group of women (n = 165) aged 30-60 years underwent a series of anthropometric measurements such as body weight, height, circumferences, and skin fold thickness at specific sites. The limb circumferences were corrected for subcutaneous adipose tissue thickness. Two models developed by Lee et al. (ASM 1, ASM2) and two models developed by Wen et al. (ASM3, ASM4) were validated using ASMM measured by dual energy x-ray absorptiometry (ASMM_DXA) as the reference standard.

RESULTS

Mean (SD) age of the study group was 49.0 (8.2) years. Mean (SD) ASMM_DXA and ASMM estimated by the four models were ASMM_DXA = 15.39 (2.75) kg, ASM1 = 18.36 (3.27) kg, ASM2 = 16.46 (3.01) kg, ASM3 = 15.44 (2.40) kg, and ASM4 = 14.44 (2.45) kg. Correlations of ASMM_DXA with ASMM estimated by the models were as follows: ASM1, r = 0.68, R² = 0.46, SEE = 2.02 kg; ASM2, r = 0.90, R² = 0.81, SEE = 1.18 kg; ASM3, r = 0.90, R² = 0.81, SEE = 1.17 kg; and ASM4, r = 0.91, R² = 0.82, SEE = 1.14 kg. ASMM estimated by ASM3 was not significantly different (P > 0.05) from ASMM_DXA with mean difference of - 0.05 (range, 0.12 to - 0.23). Bland and Altman plot revealed satisfactory measurement agreements between ASM3 and ASMM_DXA. The ASMM estimated by the other three models was significantly different from the ASMM_DXA (P < 0.05).

CONCLUSION

The ASM3 model introduced by Wen et al. met all validation criteria and can be recommended for the estimation of ASMM in middle-aged women in Sri Lanka.

High Volume Exercise Training in Older Athletes Influences Inflammatory and Redox Responses to Acute Exercise

To examine whether the volume of previous exercise training in older athletes influences inflammatory, redox, and hormonal profiles, 40 trained marathon runners were divided into higher-volume (HVG, ∼480 min/week) and lower-volume groups (LVG, ∼240 min/week). Plasma inflammatory proteins, redox biomarkers, salivary testosterone, and cortisol were assessed at restand following two maximal acute exercise bouts. At rest, the LVG exhibited higher CRP, higher protein carbonyls, and lower SOD activity compared to the HVG (p's < .05). In response to exercise, TNF-α declined similarly in both groups whereas CRP increased differentially (+60% LVG; +24% HVG; p's < .05). Protein carbonyls decreased and thiols increased similarly in both groups, but SOD declined differentially between groups (-14% LVG; -20% HVG; p's < .05). Salivary testosterone decreased similarly in both groups, whereas cortisol did not change. A higher volume of training is associated with favorable inflammatory and redox profiles at rest, perhaps mediated by small inflammatory responses to acute exercise.

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.

Discriminant model possibility of occurrence pubertal uterine bleeding in girls depending on the characteristics of the structure and size of the body

In this paper, based on the performance characteristics of the structure and size of the body, and through step discriminant analysis, we have built an accurate and highly informative model of the possibility of pubertal uterine bleeding in a general population of girls aged from 14 to 18 years, and as broken down into groups 14-15 and 16-18 years. In the total group of girls of 14-18 years and notably in girls 16-18 years, indicators of skin thickness and fat fold are consistent with such a possibility, while in girls 14-15 years old, indicators of body diameter, width of distal epiphysis of long bones of the limbs and encompassing body size, show correlation with pubertal uterine bleeding. The largest contribution to discrimination, regardless of the age groups, is, however, the value of the fat component of body weight.