Age and Training-Related Changes on Body Composition and Fitness in Male Amateur Cyclists

Master athletes are considered as a model of healthy aging because they can limit the age-related decline of physiological abilities compared to sedentary individuals. The main objective of this study is to analyze age-related changes and annual training on body composition (BC) and cardiorespiratory fitness (CRF) parameters. The participants in this retrospective cross-sectional study were 176 male cyclists, aged 40–60 years. BC was evaluated through anthropometric measurements and CRF was determined by an incremental cycle ergometer test to exhaustion. A comparative study between age groups was carried out through a one-way ANOVA test and the associations between the variables were assessed by Spearman’s correlation coefficients and multiple regression analysis to estimate the performance. Training was generally associated with a decrease in both body weight and body fat (p < 0.05). A decrease in resting heart rate was observed as a vagal effect of kilometers cycled per year (p < 0.05). Kilometers cycled per year were associated with an increase in peak power output, which was larger in the master 40 group (p < 0.05) with a non-significant upward in VO2max (p > 0.05). In the performance prediction model, the included variables explained 52% of the variance. In summary, the changes induced by age were minimal in BC and negligible in CRF, whereas HR decreased with age. Training load was generally associated with a decrease in body weight, BMI and body fat percentage that was particularly notable in the abdominal skin folds. A decrease in HRrest was observed as a vagal effect due to kilometers cycled per year, and age did not seem to have a significant effect. The annual cycling kilometers were associated with to high PPO that is greater in the M40 group and a non-significant upward trend in VO2max.

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Body Composition of Children in the Pre-pubertal and Early-pubertal Period: Are There Some Age-related and Intersexual Differences?

GYMNASIUM ◽

10.29081/gsjesh.2018.19.2.06 ◽

2019 ◽

Vol XIX (2) ◽

pp. 64

Author(s):

Pavol Čech ◽

Pavel Ružbarský ◽

Ľubomír Paučír ◽

Dalibor Dzugas

Keyword(s):

Body Composition ◽

Body Fat ◽

Bioelectrical Impedance ◽

Impedance Analysis ◽

Body Fat Percentage ◽

Fat Percentage ◽

Age Related ◽

Health Related ◽

Wallis Anova ◽

Vega 1

The aim of the presented study was to assess changes in body composition and intersexual differences among children at pre-pubertal and early-pubertal age. The research was designed as a non-randomized cross-section study. The screened sample consisted of 136 girls and 212 boys assigned into three groups according to their age. Body composition was measured using a direct segmental multi-frequency bioelectrical impedance analysis (DSM-BIA). To examine the association between obesity and selected health-related parameters, Kruskal-Wallis ANOVA and Eta2 were used. For evaluation of intersexual differences, Mann-Whitney U-test was used. The presented article is the part of VEGA 1/0840/17 project. From the perspective of age, neither in the group of girls nor boys we recorded any differences in indicators of body composition, namely in body fat mass index, body fat percentage and, in addition, in the group of girls in the waist to hip ratio parameter.

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Fitness and body composition profiling of elite junior South African rugby players

South African Journal of Sports Medicine ◽

10.17159/2413-3108/2006/v18i2a242 ◽

2009 ◽

Vol 18 (2) ◽

pp. 38 ◽

Cited By ~ 8

Author(s):

J Durandt ◽

S Du Toit ◽

J Borresen ◽

T Hew-Butler ◽

H Masimla ◽

...

Keyword(s):

Body Composition ◽

South African ◽

Body Fat ◽

Age Groups ◽

Rugby Union ◽

The Body ◽

Upper Body ◽

Cross Sectional ◽

Sprinting Speed ◽

Rugby Players

Objective. The aim of this study was to describe the body composition, strength and speed characteristics of elite junior South African rugby players. Design. Cross-sectional. Setting. Field study. Subjects. Rugby players (16 and 18 years old, N = 174) selected for the South African Rugby Union National Green Squad. Outcome measures. Body composition, 10 m and 40 m speed, agility, 1RM bench press, underhand pull-ups, push-ups, multistage shuttle run. Results. The under-16 players were on average shorter (175.6 ± 5.7 v. 179.2 ± 6.7 cm), weighed less (76.5 ± 8.2 v. 84.8 ± 8.3 kg) had less upper body absolute strength (77.1 ± 11.8 kg v. 95.3 ± 16.7 kg) and muscular endurance (41 ± 12 v. 52 ± 15 push-ups) and aerobic fitness (87.1 ± 19.4 v. 93.5 ± 15.3 shuttles) than the under-18 players. There were no differences in body fat, sprinting speed (10 m and 40 m) or agility between the two age groups. There were differences between playing positions, with the props having the most body fat, strongest upper bodies, slowest sprinting speed, least agility and lowest aerobic capacity compared with players in the other positions. Conclusion. This study provides data for elite junior rugby players and can be used to monitor the progression of players after intervention while also assisting with talent identification for the different playing positions. South African Journal of Sports Medicine Vol. 18 (2) 2006: pp. 38-45

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Associations between folate intake, body composition, and liver status in healthy adults

Proceedings of The Nutrition Society ◽

10.1017/s0029665120004383 ◽

2020 ◽

Vol 79 (OCE2) ◽

Author(s):

Monika Młodzik-Czyżewska ◽

Anna Malinowska ◽

Agata Chmurzynska

Keyword(s):

Body Composition ◽

Body Weight ◽

Fatty Liver ◽

Body Mass ◽

Body Fat ◽

Liver Steatosis ◽

Folate Intake ◽

Whole Body ◽

Body Fat Percentage ◽

Fat Percentage

AbstractA link has recently been underlined between one-carbon metabolism and body weight and body composition, suggesting that folate may account for body mass determination and lipid metabolism. The aim of this study was thus to analyze whether folate intake is associated with body weight, body mass index (BMI), body fat percentage, and liver status.409 subjects aged 20–40 were enrolled in Poznań, Poland from 2016 to 2018. Food intake was assessed using three-day food records. Folate intake was calculated based on food composition tables using the Diet 5.0 program (National Food and Nutrition Institute, Poland). Weight to 0.1 kg and height to 0.01 m were measured using an electronic scale and a stadiometer, respectively. BMI was calculated as body weight in kilograms divided by height in meters squared. Fat mass and lean body mass were determined using whole-body air-displacement plethysmography (BodPod, Cosmed, Italy). Genotyping of rs1801133 (MTHFR) was performed with TaqMan probes. The following biomarkers of liver steatosis were calculated: NAFLD liver fat score (NAFLD-LFS), fatty liver index (FLI), and hepatic steatosis index (HSI). To analyze the associations between folate intake and the measured parameters, we used multiple regression with adjustments for age, sex, and energy intake.The mean body weight was 78.57 ± 18.14 kg, BMI 25.96 ± 5.28 kg/m2, and fat percentage 29.20% ± 10.78%. The median folate intake was 299.3 μg/day. Dietary folate intake was negatively associated with body weight, BMI, and body fat percentage (p < 0.05 for all associations). Folate intake was also associated with fatty liver indices—namely HSI (p < 0.05) and FLI (p < 0.05). There was no association between folate intake and NAFLD-LFS. MTHFR rs1801133 polymorphism was not associated with any of the measured parameters.Our findings suggest that folate intake may affect body weight and composition, as well as liver status. Higher folate intake could have a protective effect against obesity, but further studies are necessary to investigate the mechanism.The authors declare that they have no conflict of interests.This work was supported by the Polish National Science Centre(grants 2014/15/B/NZ9/02134 and 2016/21/N/NZ9/01195).

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Effects of Fed- Versus Fasted-State Aerobic Training During Ramadan on Body Composition and Some Metabolic Parameters in Physically Active Men

International Journal of Sport Nutrition and Exercise Metabolism ◽

10.1123/ijsnem.22.1.11 ◽

2012 ◽

Vol 22 (1) ◽

pp. 11-18 ◽

Cited By ~ 16

Author(s):

Khaled Trabelsi ◽

Kais el Abed ◽

Stephen R. Stannard ◽

Kamel Jammoussi ◽

Khaled M. Zeghal ◽

...

Keyword(s):

Body Composition ◽

Body Weight ◽

Body Fat ◽

Aerobic Training ◽

Metabolic Parameters ◽

Body Fat Percentage ◽

Fat Percentage ◽

Physically Active ◽

Fed State ◽

Fasted State

The aim of this study was to evaluate the effects of aerobic training in a fasted versus a fed state during Ramadan on body composition and metabolic parameters in physically active men. Nineteen men were allocated to 2 groups: 10 practicing aerobic training in a fasted state (FAST) and 9 training in an acutely fed state (FED) during Ramadan. All subjects visited the laboratory for a total of 4 sessions on the following occasions: 3 days before Ramadan (Bef-R), the 15th day of Ramadan; the 29th day of Ramadan (End-R), and 21 days after Ramadan. During each session, subjects underwent anthropometric measurement, completed a dietary questionnaire, and provided fasting blood and urine samples. Body weight decreased in FAST and FED by 1.9% (p < .001) and 2.6% (p = .046), respectively. Body fat percentage decreased only in FAST by 6.2% (p = .016). FAST experienced an increase in the following parameters from Bef-R to End-R: urine specific gravity (0.64%, p = .012), urea (8.7%, p < .001), creatinine (7.5%, p < .001), uric acid (12.7%, p < .001), sodium (1.9%, p = .003), chloride (2.6%, p < .001), and high-density lipoprotein cholesterol (27.3%, p < .001). Of these parameters, only creatinine increased (5.8%, p = .004) in FED. Creatinine clearance values of FAST decreased by 8.9% (p < .001) and by 7.6% in FED (p = .01) from Bef-R to End-R. The authors conclude that aerobic training in a fasted state lowers body weight and body fat percentage. In contrast, fed aerobic training decreases only body weight. In addition, Ramadan fasting induced change in some metabolic parameters in FAST, but these changes were absent in FED.

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Age-Associated Differences of Modules and Hubs in Brain Functional Networks

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2020.607445 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yinghui Zhang ◽

Yin Wang ◽

Nan Chen ◽

Man Guo ◽

Xiuzhen Wang ◽

...

Keyword(s):

Healthy Aging ◽

Middle Age ◽

Age Groups ◽

Young Group ◽

Brain Dysfunction ◽

Modular Organization ◽

Functional Networks ◽

Inverse Association ◽

Cross Sectional ◽

Age Related

Healthy aging is usually accompanied by changes in the functional modular organization of the human brain, which may result in the decline of cognition and underlying brain dysfunction. However, the relationship between age-related brain functional modular structure differences and cognition remain debatable. In this study, we investigated the age-associated differences of modules and hubs from young, middle and old age groups, using resting-state fMRI data from a large cross-sectional adulthood sample. We first divided the subjects into three age groups and constructed an individual-level network for each subject. Subsequently, a module-guided group-level network construction method was applied to form a weighted network for each group from which functional modules were detected. The intra- and inter-modular connectivities were observed negatively correlated with age. According to the detected modules, we found the number of connector hubs in the young group was more than middle-age and old group, while the quantity of provincial hubs in middle-age group was discovered more than other two groups. Further ROI-wise analysis shows that different hubs have distinct age-associated trajectories of intra- and inter-modular connections, which suggests the different types of topological role transitions in functional networks across age groups. Our results indicated an inverse association between functional segregation/integration with age, which demonstrated age-associated differences in communication effeciency. This study provides a new perspective and useful information to better understand the normal aging of brain networks.

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Associations between choline intake, body composition, lipid profile, and liver status in healthy adults

Proceedings of The Nutrition Society ◽

10.1017/s0029665120003195 ◽

2020 ◽

Vol 79 (OCE2) ◽

Author(s):

Monika Młodzik-Czyżewska ◽

Anna Malinowska ◽

Agata Chmurzyńska

Keyword(s):

Body Composition ◽

Body Weight ◽

Body Fat ◽

Ldl Cholesterol ◽

Liver Steatosis ◽

Hdl Cholesterol ◽

Body Fat Percentage ◽

Fat Percentage ◽

The Mean ◽

Choline Intake

AbstractCholine is an essential nutrient involved in several processes, including the export of lipids from the liver. Recent studies have underlined that low choline intake may be linked to greater body weight and liver dysfunction. The aim of this study was thus to determine whether choline intake is associated with body weight, body mass index (BMI), body composition, lipid profile, or liver steatosis indices.407 healthy subjects aged 20–40 were enrolled in Poznań, Poland from 2016 to 2018. Food intake was assessed using three-day food records. Choline intake was analyzed using the USDA Database for the Choline Content of Common Foods, which summarizes the levels of choline found in a range of food items. Weight to 0.1 kg and height to 0.01 m were measured using an electronic scale and a stadiometer, respectively. BMI was calculated as body weight in kilograms divided by height in meters squared. Fat mass and lean body mass were determined using whole-body air-displacement plethysmography. Waist and hip circumferences were measured to 0.5 cm using nonelastic tape. Total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels in serum were determined using a biochemical analyzer. The following biomarkers of liver steatosis were calculated: NAFLD liver fat score (NAFLD-LFS), fatty liver index (FLI), and hepatic steatosis index (HSI). To analyze associations between choline intake and these parameters, we used multiple regression with adjustments for age, sex, and energy intake.The mean BMI was 25.9 ± 5.28 kg/m2, the mean body weight was 78.39 ± 18.03 kg, the mean body fat percentage was 29.1 ± 10.79%, and the mean choline intake was 447.93 ± 235 mg/day. Choline intake was negatively associated with body weight, body fat percentage, waist circumference, and FLI index (p < 0.05 for all associations) and positively associated with HDL cholesterol (p < 0.05). There were no associations between choline intake and BMI, hip circumference, total cholesterol, LDL cholesterol, and the following fatty liver indexes: HSI and NAFLD-LFS.Our study suggests that higher choline intake is associated with favorable body composition and may have a protective role on liver status. However, additional studies are needed to understand the effect of choline on these parameters.The authors declare that they have no conflict of interests.This work was supported by the Polish National Science Centre (grants 2014/15/B/NZ9/02134 and 2016/21/N/NZ9/01195).

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Association Between KCNJ11 Gene E23K Polymorphism and Body Composition Together with Its Response to Endurance Training

The Open Biomedical Engineering Journal ◽

10.2174/1874120701509010121 ◽

2015 ◽

Vol 9 (1) ◽

pp. 121-125

Author(s):

Zhou Duoqi ◽

He Qing ◽

Hu Yang ◽

Li Yanchun ◽

Xi Yi ◽

...

Keyword(s):

Body Composition ◽

Body Weight ◽

Endurance Training ◽

Body Fat ◽

The Body ◽

Lean Body Weight ◽

Fat Percentage ◽

Kcnj11 Gene ◽

Significant Difference ◽

E23k Polymorphism

To explore the association between KCNJ11 gene E23K polymorphism of Chinese and body composition together with its response to endurance training. 102 biologically unrelated Han nationality male new recruits from northern China volunteered to execute a 5000-m running program, and the intensity is 95–105% individual lactate threshold. The protocol was lasted for 18 weeks, three times per week. The body composition index, including body weight (WT), lean body weight (LBW), body mass index (BMI) and body fat percentage (Fat%), was measured before and after training. PCR-RFLP was used to detect the KCNJ11 gene E23K polymorphism. Hardy-Weinberg equilibrium was observed for the frequency of genotypes in these subjects. Before training, WT, BMI and Fat% in KK group were significantly higher than those in EE and KK group (P<0.05 or P<0.01). There was no significant difference in LBW among groups (P>0.05). After training, the changes of all body composition index in KK group were bigger significantly greater than those in EE and EK groups (P<0.01). KCNJ11 gene E23K polymorphism might contribute to individual body composition together with its response to endurance training. The body fat content at baseline in KK was more than those in EE and EK groups, and it may hinder that individual to eliminate their body fat during endurance training.

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Body composition associations with muscle strength in older adults living in Auckland, New Zealand

PLoS ONE ◽

10.1371/journal.pone.0250439 ◽

2021 ◽

Vol 16 (5) ◽

pp. e0250439

Author(s):

Anne N. Hiol ◽

Pamela R. von Hurst ◽

Cathryn A. Conlon ◽

Owen Mugridge ◽

Kathryn L. Beck

Keyword(s):

Older Adults ◽

Body Composition ◽

Muscle Strength ◽

Grip Strength ◽

Muscle Mass ◽

Body Fat ◽

Muscle Quality ◽

Body Fat Percentage ◽

Fat Percentage ◽

Cross Sectional

Background Aging is associated with decreases in muscle strength and simultaneous changes in body composition, including decreases in muscle mass, muscle quality and increases in adiposity. Methods Adults (n = 369; 236 females) aged 65–74 years living independently were recruited from the cross-sectional Researching Eating Activity and Cognitive Health (REACH) study. Body fat percentage and appendicular skeletal muscle mass (ASM) (sum of lean mass in the arms and legs) were assessed using Dual-energy X-ray Absorptiometry (Hologic, QDR Discovery A). The ASM index was calculated by ASM (kilograms) divided by height (meters) squared. Isometric grip strength was measured using a hand grip strength dynamometer (JAMAR HAND). Results Linear regression analyses revealed that muscle strength was positively associated with the ASM index (R2 = 0.431, p < 0.001). When exploring associations between muscle strength and muscle mass according to obesity classifications (obesity ≥30% males; ≥40% females), muscle mass was a significant predictor of muscle strength in non-obese participants. However, in participants with obesity, muscle mass was no longer a significant predictor of muscle strength. Conclusions Body fat percentage should be considered when measuring associations between muscle mass and muscle strength in older adults.

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Body composition assessment among adults in Thika, Kiambu county, Kenya

International Journal of Research in Medical Sciences ◽

10.18203/2320-6012.ijrms20192879 ◽

2019 ◽

Vol 7 (7) ◽

pp. 2568

Author(s):

Mututho L. N. ◽

Kiboi W. K. ◽

Waihenya R. N.

Keyword(s):

Body Composition ◽

Body Fat ◽

Visceral Fat ◽

Bioelectrical Impedance ◽

The Body ◽

Hydration Status ◽

P Value ◽

Fat Percentage ◽

Body Composition Assessment ◽

Cross Sectional

Background: Research has shown that body composition is directly related to health. Altered body composition, can greatly increase the risks of conditions such as cardiovascular disease and diabetes. Bioelectrical Impedance Analysis fosters early detection of an improper balance in the body composition, which allows for earlier intervention and prevention.Methods: This was a cross sectional analysis of body composition for adults who volunteered to be screened during a Nutrition week in Kiambu County, Kenya. A total of 301 adults were included in the assessment. Body Mass Index (BMI) and Body composition (body fat %, bone mass, muscle mass, visceral fat and water %) were measured using bioelectrical impedance analysis.Results: The age of the participants ranged from 18-99 years (mean 42.19±16.57 years). Most of the participants were males (53.5%). More than half (53.2%) of the participants had a poor BMI, 37.2% had high total body fat percentage, 12.6% had excess levels of visceral fat and 26.6% had poor water hydration status. Age (OR=0.095; p value <0.001; CI 0.033-0272) and visceral fat (r=0.74; p value <0.001) were significantly associated with the BMI. Females had a significantly higher BMI (P <0.001). Visceral fat was also positively correlated with age: r=0.74; P value <0.001.Conclusions: Sex, age and BMI were important determinants of body composition. Increased physical activity, appropriate dietary practices are crucial in maintaining a healthy BMI and body composition. For timely intervention regular nutrition screening should be promoted among different populations.

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Circulating Metabolites Associated with Body Fat and Lean Mass in Adults with Overweight/Obesity

Metabolites ◽

10.3390/metabo11050317 ◽

2021 ◽

Vol 11 (5) ◽

pp. 317

Author(s):

Christopher Papandreou ◽

Jesús García-Gavilán ◽

Lucía Camacho-Barcia ◽

Thea T. Hansen ◽

Anders Sjödin ◽

...

Keyword(s):

Body Composition ◽

Body Fat ◽

Lean Mass ◽

Pearson Correlation ◽

Correlation Coefficients ◽

The Body ◽

Acid Oxidation ◽

Cross Sectional ◽

Body Compartments ◽

Fold Cross Validation

The interplay between fat mass and lean mass within human metabolism is not completely understood. We aimed to identify specific circulating metabolomic profiles associated with these body composition compartments. Cross-sectional analyses were conducted over 236 adults with overweight/obesity from the Satiety Innovation (SATIN) study. Body composition was assessed by dual-energy X-ray absorptiometry. A targeted multiplatform metabolite profiling approach was applied. Associations between 168 circulating metabolites and the body composition measures were assessed using elastic net regression analyses. The accuracy of the multimetabolite weighted models was evaluated using a 10-fold cross-validation approach and the Pearson’s correlation coefficients between metabolomic profiles and body compartments were estimated. Two different profiles including 86 and 65 metabolites were selected for % body fat and lean mass. These metabolites mainly consisted of lipids (sphingomyelins, phosphatidylcholines, lysophosphatidylcholines), acylcarnitines, and amino acids. Several metabolites overlapped between these body composition measures but none of them towards the same direction. The Pearson correlation coefficients between the metabolomic profiles and % body fat or lean mass were 0.80 and 0.79, respectively. Our findings suggest alterations in lipid metabolism, fatty acid oxidation, and protein degradation with increased adiposity and decreased lean body mass. These findings could help us to better understand the interplay between body composition compartments with human metabolic processes.

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