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      Examining the mediating role of muscle quantity in adolescents: associations with adiposity, cardiorespiratory fitness, muscular fitness, and cardiometabolic risk factors

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          Abstract

          The aim of this study was to evaluate the mediation role of muscle quantity in the relationship between physical fitness and cardiometabolic risk factors (CMRF) in adolescents. This cross-sectional study conducted with 120 adolescents of both sexes, aged between 10 and 17 years. Body mass, height, fat mass (FM), lean mass, blood pressure, high-density lipoprotein, low-density lipoprotein, triglycerides, glucose, insulin, cardiorespiratory fitness (CRF) and 1 repetition maximum strength (1-RM) with evaluation of the leg press 45° (RM-leg), bench press (RM-bench) and arm curl (RM-arm). Body mass index z-score, appendicular skeletal muscle mass, appendicular skeletal muscle mass index, lean mass index (LMI), muscle-to-fat ratio (MFR), age at peak height velocity, and CMRF z-score were calculated. The direct relation between FM and CMRF was mediated by the LMI (26%) and inverse relation between CRF and CMRF was mediated by the LMI (26%). For girls, the direct relation between FM and CMRF was mediated by the LMI (32%); the inverse relation between CRF, RM-leg, RM-arm and CMRF was mediated by the LMI (32%, 33%, and 32%, respective). For boys, the indirect effect was not significant, indicating that LMI is not a mediator in the relation between FM, CRF, 1-RM with CMRF. The direct relation between RM-leg and CMRF was mediated by the MRF (16%). This finding evidenced the importance of promoting a healthy lifestyle to improve physical fitness levels and the quantity of muscle mass in adolescents.

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          Sarcopenia: European consensus on definition and diagnosis

          The European Working Group on Sarcopenia in Older People (EWGSOP) developed a practical clinical definition and consensus diagnostic criteria for age-related sarcopenia. EWGSOP included representatives from four participant organisations, i.e. the European Geriatric Medicine Society, the European Society for Clinical Nutrition and Metabolism, the International Association of Gerontology and Geriatrics—European Region and the International Association of Nutrition and Aging. These organisations endorsed the findings in the final document. The group met and addressed the following questions, using the medical literature to build evidence-based answers: (i) What is sarcopenia? (ii) What parameters define sarcopenia? (iii) What variables reflect these parameters, and what measurement tools and cut-off points can be used? (iv) How does sarcopenia relate to cachexia, frailty and sarcopenic obesity? For the diagnosis of sarcopenia, EWGSOP recommends using the presence of both low muscle mass + low muscle function (strength or performance). EWGSOP variously applies these characteristics to further define conceptual stages as ‘presarcopenia’, ‘sarcopenia’ and ‘severe sarcopenia’. EWGSOP reviewed a wide range of tools that can be used to measure the specific variables of muscle mass, muscle strength and physical performance. Our paper summarises currently available data defining sarcopenia cut-off points by age and gender; suggests an algorithm for sarcopenia case finding in older individuals based on measurements of gait speed, grip strength and muscle mass; and presents a list of suggested primary and secondary outcome domains for research. Once an operational definition of sarcopenia is adopted and included in the mainstream of comprehensive geriatric assessment, the next steps are to define the natural course of sarcopenia and to develop and define effective treatment.
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            Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man.

            The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
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              Development of a WHO growth reference for school-aged children and adolescents

              OBJECTIVE: To construct growth curves for school-aged children and adolescents that accord with the WHO Child Growth Standards for preschool children and the body mass index (BMI) cut-offs for adults. METHODS: Data from the 1977 National Center for Health Statistics (NCHS)/WHO growth reference (1-24 years) were merged with data from the under-fives growth standards' cross-sectional sample (18-71 months) to smooth the transition between the two samples. State-of-the-art statistical methods used to construct the WHO Child Growth Standards (0-5 years), i.e. the Box-Cox power exponential (BCPE) method with appropriate diagnostic tools for the selection of best models, were applied to this combined sample. FINDINGS: The merged data sets resulted in a smooth transition at 5 years for height-for-age, weight-for-age and BMI-for-age. For BMI-for-age across all centiles the magnitude of the difference between the two curves at age 5 years is mostly 0.0 kg/m² to 0.1 kg/m². At 19 years, the new BMI values at +1 standard deviation (SD) are 25.4 kg/m² for boys and 25.0 kg/m² for girls. These values are equivalent to the overweight cut-off for adults (> 25.0 kg/m²). Similarly, the +2 SD value (29.7 kg/m² for both sexes) compares closely with the cut-off for obesity (> 30.0 kg/m²). CONCLUSION: The new curves are closely aligned with the WHO Child Growth Standards at 5 years, and the recommended adult cut-offs for overweight and obesity at 19 years. They fill the gap in growth curves and provide an appropriate reference for the 5 to 19 years age group.
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                Author and article information

                Contributors
                mctadiotto@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                26 May 2024
                26 May 2024
                2024
                : 14
                : 12030
                Affiliations
                [1 ]Department of Physical Education, Federal University of Paraná, ( https://ror.org/05syd6y78) Street Col. Francisco H. Dos Santos, 100, Jardim das Americas, Curitiba, Paraná 81531-980 Brazil
                [2 ]State University of Western Paraná, ( https://ror.org/05ne20t07) Cascavel, Brazil
                [3 ]State University of Maringá, ( https://ror.org/04bqqa360) Maringá, Brazil
                [4 ]Technological Federal University of Paraná, ( https://ror.org/002v2kq79) Curitiba, Brazil
                [5 ]University of Coimbra, FCDEF, ( https://ror.org/04z8k9a98) Coimbra, Portugal
                [6 ]University of Coimbra, CIDAF (Uid/04213/2020), ( https://ror.org/04z8k9a98) Coimbra, Portugal
                Author information
                http://orcid.org/0000-0002-4752-6697
                http://orcid.org/0000-0002-6953-0793
                http://orcid.org/0000-0002-9001-6123
                http://orcid.org/0000-0003-4389-1213
                http://orcid.org/0000-0001-7910-2445
                http://orcid.org/0000-0003-3111-5364
                http://orcid.org/0000-0001-7895-6799
                http://orcid.org/0000-0002-5422-9623
                http://orcid.org/0000-0003-4035-106X
                http://orcid.org/0000-0003-4512-7331
                Article
                61805
                10.1038/s41598-024-61805-w
                11128436
                38797741
                3fc91d46-e579-44d5-9f69-6c4d3bd2d1fc
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 October 2023
                : 9 May 2024
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                © Springer Nature Limited 2024

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                dxa,physical fitness,low muscle mass,lean mass index,muscle-to-fat ratio,biomarkers,endocrinology,health care,risk factors

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