scholarly journals Biological Maturation, Body Morphology and Physical Performance in 8-16 Year-Old Obese Girls from Montes Claros – Mg

2014 ◽  
Vol 43 (1) ◽  
pp. 169-176 ◽  
Author(s):  
Alex S. Freitas ◽  
António J.B. Figueiredo ◽  
Andréia L. R. de Freitas ◽  
Vinícius D. Rodrigues ◽  
Alexandre A. C. da Cunha ◽  
...  
Keyword(s):  
Body Composition ◽  
Physical Performance ◽  
Handgrip Strength ◽  
Age Groups ◽  
Bone Age ◽  
Chronological Age ◽  
Age At Menarche ◽  
Anthropometric Measures ◽  
Body Morphology ◽  
Biological Maturation

Abstract Measurements of maturity depend on the biological system considered since differences are often found in performance and body size in subjects of the same chronological age. The objective of this study was to identify associations between biological maturation, body morphology and physical performance in girls aged from 8.0 to 15.9 year-old and to verify the bone age in obese girls and compare it with chronological age. For that purpose 2040 (11.9 ± 2.3 years) school girls from Montes Claros, participated in this study. Regular anthropometric measures as height and body mass were taken. Triceps, biceps, subscapular, abdominal, suprailiac and calf skinfolds were also registered. Physical performance was assessed trough the test of a standing long jump, handgrip strength and 20 m multistage shuttle run. Maturational status, the average age at menarche and identification of PHV (maturity off set) were determined by means of the retrospective method. Girls with the BMI above the 95th percentile got their bone age evaluated through X-ray of the left hand/wrist, in accordance with the FELS method. It was possible to find an average age at menarche of 11.30 ± 0.70, while the average age at PHV was 12.17 ± 0.71 years of age. It was observed that both body composition and physical performance showed a tendency to increase with advancing age. However, when controlling the effect of maturation, despite having higher values in body composition the post-menarche girls group did not show higher levels of physical performance. In all age groups, obese girls showed mean rates of bone age higher than chronologic age (12.25 ± 2.09 and 14.09 ± 2.35, respectively, p=0.000). Chronological age should be used with caution when evaluating obese teenagers as it may underestimate biological age.

scholarly journals Body Physique, Body Composition, Physical Performance, Technical and Tactical Skills, Psychological Development, and Club Characteristics of Young Male Portuguese Soccer Players: The INEX Study

2021 ◽  
Vol 18 (7) ◽  
pp. 3560
Author(s):  
Maryam Abarghoueinejad ◽  
Daniel Barreira ◽  
Cláudia Dias ◽  
Eduardo Guimarães ◽  
Adam D. G. Baxter-Jones ◽  
...  
Keyword(s):  
Body Composition ◽  
Physical Performance ◽  
Age Groups ◽  
Young Male ◽  
Physical Growth ◽  
Soccer Players ◽  
Youth Soccer ◽  
Age Cohorts ◽  
Biological Maturation ◽  
Age Related

Youth soccer performance is multifaceted, includes physical growth, biological maturation, and physical fitness, and is linked to the sporting environment to which the players are exposed. We aim to describe age-related associations in body physique, body composition, physical performance technical and tactical skills, psychological and club characteristics of male soccer players aged 12 to 14 years. A total of 157 male soccer players clustered into three age-cohorts (12, 13 and 14 years) were recruited from six soccer clubs. Anthropometric, body composition and body physique, biological maturation, physical performance, skill/game proficiency data, psychological characteristics, and clubs’ characteristics were collected. Group means were compared using analysis of variance and covariance. Fourteen years old players were significantly taller, heavier, leaner, faster, stronger, and technically more skilled than their younger peers (p < 0.05). Differences in physical performance and technical skills (p < 0.05) were found between age groups when adjusting for confounders of soccer training and biological maturation. No significant differences (p > 0.05) between age groups were found in psychological domains. Our findings suggest that age, biological maturation, and training volume are key factors influencing young soccer players’ performance and development. Further, clubs’ conditions provide players with ample resources for their success in training and competition.

scholarly journals Body Size Measurements and Physical Performance of Youth Female Judo Athletes with Differing Menarcheal Status

2021 ◽  
Vol 18 (23) ◽  
pp. 12829
Author(s):  
Marina Saldanha da Silva Athayde ◽  
Rafael Lima Kons ◽  
David Hideyoshi Fukuda ◽  
Daniele Detanico
Keyword(s):  
Body Size ◽  
Physical Performance ◽  
Handgrip Strength ◽  
Linear Regression Analysis ◽  
Somatic Growth ◽  
Young Female ◽  
Chronological Age ◽  
Age At Menarche ◽  
Training Experience ◽  
Judo Athletes

Purpose: To compare body size measurements and physical performance among female youth judo athletes with differing menarcheal status and to identify indicators of physical performance in post-menarcheal girls. Methods: Nineteen young female judo athletes (age 13.9 ± 2.3 years) were divided into a pre-menarche (n = 7) and a post-menarche (n = 12) group. The athletes were evaluated through neuromuscular tests, including standing long jump (SLJ), medicine ball throw (MBT), and handgrip strength (HGS), and judo-specific assessments, including the Special Judo Fitness Test (SJFT) and the Judogi Grip Strength Test (JGSTISO). Furthermore, years of experience in judo and the age at menarche were determined. Results: The main results showed higher performance for the post-menarche group for most variables (p < 0.05) compared to the pre-menarche group. A multiple linear regression analysis demonstrated that age at menarche, chronological age, and body mass explained close to 70% of JGSTISO, while training experience, chronological age, and age at menarche explained close to 59% of SLJ. Additionally, chronological age and age at menarche explained 40% of MBT, and chronological age and height explained 52% of HGS. Conclusions: Age at menarche and somatic growth variables explained moderate proportions of the variance of physical performance, thereby providing evidence that these parameters are the primary indicators of physical performance in young female judo athletes.

scholarly journals Chronological Age, Somatic Maturation and Anthropometric Measures: Association with Physical Performance of Young Male Judo Athletes

2021 ◽  
Vol 18 (12) ◽  
pp. 6410
Author(s):  
Bruno B. Giudicelli ◽  
Leonardo G. O. Luz ◽  
Mustafa Sogut ◽  
Hugo Sarmento ◽  
Alain G. Massart ◽  
...  
Keyword(s):  
Physical Performance ◽  
Handgrip Strength ◽  
Young Male ◽  
Upper Body ◽  
Chronological Age ◽  
Anthropometric Measures ◽  
Physical Test ◽  
Bivariate Correlation ◽  
Judo Athletes ◽  
Adult Stature

Sport for children and adolescents must consider growth and maturation to ensure suitable training and competition, and anthropometric variables could be used as bio-banding strategies in youth sport. This investigation aimed to analyze the association between chronological age, biologic maturation, and anthropometric characteristics to explain physical performance of young judo athletes. Sixty-seven judokas (11.0–14.7 years) were assessed for anthropometric and physical performance. Predicted adult stature was used as a somatic maturation indicator. A Pearson’s bivariate correlation was performed to define which anthropometric variables were associated with each physical test. A multiple linear hierarchical regression was conducted to verify the effects of age, maturity, and anthropometry on physical performance. The regression models were built with age, predicted adult stature, and the three most significantly correlated anthropometric variables for each physical test. Older judokas performed better in most of the physical tests. However, maturation attenuated the age effect in most variables and significantly affected upper body and handgrip strength. Anthropometric variables attenuated age and maturity and those associated with body composition significantly affected the performance in most tests, suggesting a potential as bio-banding strategies. Future studies should investigate the role of anthropometric variables on the maturity effect in young judokas.

scholarly journals Effects of Sweet-Liking on Body Composition Depend on Age and Lifestyle: A Challenge to the Simple Sweet-Liking—Obesity Hypothesis

Nutrients ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2702
Author(s):  
Vasiliki Iatridi ◽  
Rhiannon M. Armitage ◽  
Martin R. Yeomans ◽  
John E. Hayes
Keyword(s):  
Body Composition ◽  
Body Fat ◽  
Weight Maintenance ◽  
Age Groups ◽  
Hierarchical Cluster ◽  
Food Choices ◽  
Fat Free Mass ◽  
Obesogenic Environment ◽  
Anthropometric Measures ◽  
The Uk

Taste hedonics drive food choices, and food choices affect weight maintenance. Despite this, the idea that hyper-palatability of sweet foods is linked to obesity development has been controversial for decades. Here, we investigate whether interpersonal differences in sweet-liking are related to body composition. Healthy adults aged 18–34 years from the UK (n = 148) and the US (n = 126) completed laboratory-based sensory tests (sucrose taste tests) and anthropometric measures (body mass index; BMI, body fat; fat-free mass; FFM, waist/hips circumferences). Habitual beverage intake and lifestyle and behavioural characteristics were also assessed. Using hierarchical cluster analysis, we classified participants into three phenotypes: sweet liker (SL), sweet disliker (SD), and inverted-U (liking for moderate sweetness). Being a SD was linked to higher body fat among those younger than 21 years old, while in the older group, SLs had the highest BMI and FFM; age groups reflected different levels of exposure to the obesogenic environment. FFM emerged as a better predictor of sweet-liking than BMI and body fat. In the older group, sweetened beverage intake partially explained the phenotype–anthropometry associations. Collectively, our findings implicate underlying energy needs as an explanation for the variation in sweet-liking; the moderating roles of age and obesogenic environment require additional consideration.

scholarly journals PHYSICAL FUNCTION AND BODY COMPOSITION AS NUTRITIONAL OUTCOMES: ASSESSMENT APPROACHES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S392-S392
Author(s):  
Connie W Bales ◽  
Kathryn N Porter Starr ◽  
Marshall Miller
Keyword(s):  
Older Adults ◽  
Body Composition ◽  
Physical Function ◽  
Physical Performance ◽  
Performance Test ◽  
Handgrip Strength ◽  
Muscle Quality ◽  
Physical Performance Test ◽  
Nutritional Interventions ◽  
Obesity Interventions

Abstract Nutritional status is a strong determinant of both body composition and physical function (PF), parameters that are closely interrelated but rarely evaluated in the clinical setting due to cost, access, and lack of agreement on best approaches in older adults. Recent evidence that changes in muscle mass do not closely correspond to changes in muscle function will be reviewed in the context of our studies of higher protein obesity interventions. PF assessments, including indices for older adults (Short Physical Performance Battery and Physical Performance Test), as well as specific tests like gait speed and handgrip strength, will be explained as nutrition outcomes and in relation to body composition from air displacement (BodPod) and dual energy x-ray absorptiometry (DXA). These results, along with new studies of muscle quality, will bring a better understanding of the complexity of responses to nutritional interventions designed to optimize body mass and composition in older adults.

Differences in anthropometric and physical performance characteristics between U17, U19, and Senior Irish female international football players

2020 ◽  
pp. 174795412096819
Author(s):  
Brian Doyle ◽  
Declan Browne ◽  
Dan Horan
Keyword(s):  
Physical Performance ◽  
Body Mass ◽  
Age Groups ◽  
Performance Characteristics ◽  
Football Players ◽  
Anthropometric Measures ◽  
Physical Tests ◽  
Level 1 ◽  
Test Level ◽  
Anthropometric Profile

This study aimed to compare the anthropometric physical performance characteristics of Irish female international footballers at U17, U19, and Senior age groups. Fifty-five (U17, n =24, U19, n =21, Senior, n = 10) female international football players participated in this study. The subjects underwent anthropometric measurements (height and body mass) and physical performance tests countermovement jump (CMJ), reactive strength index (RSI), 10-m, 20-m, 30-m linear sprint, and yo-yo intermittent recovery test level 1 (YYIR1). No significant differences were identified between any age groups for the anthropometric measures of height and body mass. Concerning the physical tests, senior players displayed greater CMJ scores in comparison with the U17 (P = 0.040). Senior players also possessed higher levels of reactive strength with large effect sizes present (ES = 0.83 - 0.92) in comparison to all age groups. No significant differences were identified between any of the age groups across the 10-m, 20-m, 30-m, and rolling 20-m linear speed assessments. Senior players covered the greatest distance in the YYIR1 (P = 0.0001) versus the U19 and U17. These results indicate there was no difference in the anthropometric profile of the age groups assessed. However, differences in physical performance characteristics were present between age groups, thus suggesting improvements in lower limb power and aerobic endurance are achievable in adulthood as players physically mature.

scholarly journals Osteosarcopenic Obesity Syndrome: What Is It and How Can It Be Identified and Diagnosed?

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Jasminka Z. Ilich ◽  
Owen J. Kelly ◽  
Julia E. Inglis
Keyword(s):  
Body Composition ◽  
Diagnostic Criteria ◽  
Physical Performance ◽  
Handgrip Strength ◽  
Functional Decline ◽  
Assessment Process ◽  
Mineral Density ◽  
Osteosarcopenic Obesity ◽  
Long Term Impact ◽  
Composition Measurements

Conditions related to body composition and aging, such as osteopenic obesity, sarcopenia/sarcopenic obesity, and the newly termed osteosarcopenic obesity (triad of bone muscle and adipose tissue impairment), are beginning to gain recognition. However there is still alack of definitive diagnostic criteriafor these conditions. Little is known about the long-term impact of these combined conditions of osteoporosis, sarcopenia, and obesity in older adults. Many may go undiagnosed and progress untreated. Therefore, the objective of this research is to creatediagnostic criteriafor osteosarcopenic obesity in older women. The proposeddiagnostic criteriaare based ontwo types of assessments: physical,via body composition measurements, andfunctional,via physical performance measures. Body composition measurements such asT-scores for bone mineral density, appendicular lean mass for sarcopenia, and percent body fat could all be obtained via dual energy X-ray absorptiometry. Physical performance tests: handgrip strength, one-leg stance, walking speed, and sit-to-stand could be assessed with minimal equipment. A score could then be obtained to measure functional decline in the older adult. Fordiagnosing osteosarcopenic obesityand other conditions related to bone loss and muscle loss combined with obesity, a combination of measures may more adequately improve the assessment process.

scholarly journals Chronological Age Assessment in Young Individuals Using Bone Age Assessment Staging and Nonradiological Aspects: Machine Learning Multifactorial Approach (Preprint)

2020 ◽  
Author(s):  
Ana Luiza Dallora ◽  
Ola Kvist ◽  
Johan Sanmartin Berglund ◽  
Sandra Diaz Ruiz ◽  
Martin Boldt ◽  
...  
Keyword(s):  
Machine Learning ◽  
Age Groups ◽  
Bone Age ◽  
Chronological Age ◽  
Learning Methods ◽  
Age Assessment ◽  
Male And Female ◽  
Machine Learning Methods ◽  
Bone Age Assessment ◽  
Female Subjects

BACKGROUND Bone age assessment (BAA) is used in numerous pediatric clinical settings as well as in legal settings when entities need an estimate of chronological age (CA) when valid documents are lacking. The latter case presents itself as critical as the law is harsher for adults and granted rights along with imputability changes drastically if the individual is a minor. Traditional BAA methods have drawbacks such as exposure of minors to radiation, they do not consider factors that might affect the bone age, and they mostly focus on a single region. Given the critical scenarios in which BAA can affect the lives of young individuals, it is important to focus on the drawbacks of the traditional methods and investigate the potential of estimating CA through BAA. OBJECTIVE This study aims to investigate CA estimation through BAA in young individuals aged 14-21 years with machine learning methods, addressing the drawbacks of research using magnetic resonance imaging (MRI), assessment of multiple regions of interest, and other factors that may affect the bone age. METHODS MRI examinations of the radius, distal tibia, proximal tibia, distal femur, and calcaneus were performed on 465 men and 473 women (aged 14-21 years). Measures of weight and height were taken from the subjects, and a questionnaire was given for additional information (self-assessed Tanner Scale, physical activity level, parents' origin, and type of residence during upbringing). Two pediatric radiologists independently assessed the MRI images to evaluate their stage of bone development (blinded to age, gender, and each other). All the gathered information was used in training machine learning models for CA estimation and minor versus adult classification (threshold of 18 years). Different machine learning methods were investigated. RESULTS The minor versus adult classification produced accuracies of 0.90 and 0.84 for male and female subjects, respectively, with high recalls for the classification of minors. The CA estimation for the 8 age groups (aged 14-21 years) achieved mean absolute errors of 0.95 years and 1.24 years for male and female subjects, respectively. However, for the latter, a lower error occurred only for the ages of 14 and 15 years. CONCLUSIONS This study investigates CA estimation through BAA using machine learning methods in 2 ways: minor versus adult classification and CA estimation in 8 age groups (aged 14-21 years), while addressing the drawbacks in the research on BAA. The first achieved good results; however, for the second case, the BAA was not precise enough for the classification.

scholarly journals Chronological Age Assessment in Young Individuals Using Bone Age Assessment Staging and Nonradiological Aspects: Machine Learning Multifactorial Approach

10.2196/18846 ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. e18846
Author(s):  
Ana Luiza Dallora ◽  
Ola Kvist ◽  
Johan Sanmartin Berglund ◽  
Sandra Diaz Ruiz ◽  
Martin Boldt ◽  
...  
Keyword(s):  
Machine Learning ◽  
Age Groups ◽  
Bone Age ◽  
Chronological Age ◽  
Learning Methods ◽  
Age Assessment ◽  
Male And Female ◽  
Machine Learning Methods ◽  
Bone Age Assessment ◽  
Female Subjects

Background Bone age assessment (BAA) is used in numerous pediatric clinical settings as well as in legal settings when entities need an estimate of chronological age (CA) when valid documents are lacking. The latter case presents itself as critical as the law is harsher for adults and granted rights along with imputability changes drastically if the individual is a minor. Traditional BAA methods have drawbacks such as exposure of minors to radiation, they do not consider factors that might affect the bone age, and they mostly focus on a single region. Given the critical scenarios in which BAA can affect the lives of young individuals, it is important to focus on the drawbacks of the traditional methods and investigate the potential of estimating CA through BAA. Objective This study aims to investigate CA estimation through BAA in young individuals aged 14-21 years with machine learning methods, addressing the drawbacks of research using magnetic resonance imaging (MRI), assessment of multiple regions of interest, and other factors that may affect the bone age. Methods MRI examinations of the radius, distal tibia, proximal tibia, distal femur, and calcaneus were performed on 465 men and 473 women (aged 14-21 years). Measures of weight and height were taken from the subjects, and a questionnaire was given for additional information (self-assessed Tanner Scale, physical activity level, parents' origin, and type of residence during upbringing). Two pediatric radiologists independently assessed the MRI images to evaluate their stage of bone development (blinded to age, gender, and each other). All the gathered information was used in training machine learning models for CA estimation and minor versus adult classification (threshold of 18 years). Different machine learning methods were investigated. Results The minor versus adult classification produced accuracies of 0.90 and 0.84 for male and female subjects, respectively, with high recalls for the classification of minors. The CA estimation for the 8 age groups (aged 14-21 years) achieved mean absolute errors of 0.95 years and 1.24 years for male and female subjects, respectively. However, for the latter, a lower error occurred only for the ages of 14 and 15 years. Conclusions This study investigates CA estimation through BAA using machine learning methods in 2 ways: minor versus adult classification and CA estimation in 8 age groups (aged 14-21 years), while addressing the drawbacks in the research on BAA. The first achieved good results; however, for the second case, the BAA was not precise enough for the classification.

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