Anthropometric and strength relationship male female differences

anthropometric and strength relationship male female differences

Gender, age, HGS, flexibility, arm muscle circumference (AMC), corrected arm evaluated the correlation of anthropometric variables with handgrip strength and This fact results in certain limitations, considering the differences between the. Anthropol Anz. Mar;56(1) Anthropometry and strength relationship: male-female differences. Fuster V(1), Jerez A, Ortega A. Author information. Previous studies have shown strength differences between men and women . The relationships among strength and anthropometric variables for the men are.

Nevertheless, given the clear methodological divergences observed in these studies, such conclusions should be reflected upon carefully.

Very little information is available on young female players, which renders comparisons quite challenging. When the maturity status is statistically controlled, results show how the group with the maximum level of performance national presents fewer differences with regard to the regional level group, which reinforces the importance of maturity as a key factor in executing talent selection 2132122with both males and females.

Once the effect of player maturity is neutralized, it is observed how anthropometric parameters sum of skinfolds, body mass, leg girth, height, thigh girth, trochanter height and arm span and physical performance parameters vertical jump SJ, CMJ, Avalakov jump, standing broad jump, flamingo balance, plate tapping, sit and reach, sit-ups, 10x5m shuttle run, 20m shuttle run and VO2 max are responsible for the difference in performance levels.

This behavior is not shown when female players are analyzed; therefore, maturity is a fundamental factor that strongly determines performance level. The only anthropometrical variables that are not affected by maturity are weight and body fat; the latter variable is inversely correlated to performance 23 This behavior would need to be taken into consideration in future research.

Regarding physical performance parameters, the data analysis suggests that explosive strength, sprinting for short distances and aerobic capacity can discriminate across levels for female players. The results of the study carried out by Vaeyens, Malina, Janssens. The results shown by Matthys, Vaeyens, Vandendriessche, Vandorpe, Pion, Coutts, Lenoir and Philippaerts 13which are directly linked to physical performance parameters, revealed that maturation is not the only variable responsible for the differences between handball players of different performance levels in parameters such as explosive strength, speed and agility; these parameters are also conditioned by the category that is analyzed, which also seems to be the case for females when the parameters of explosive strength, speed and aerobic resistance are considered.

The analysis carried out within each age under and under and the gender group revealed that the maturity parameter does not determine performance level within each age category; the selection process carried out by the group of experts could have influenced this.

A more detailed study of each age group under and under showed how the behavior of anthropometric and physical performance variables for the under category is not conditioned by gender. In fact, the parameters that best identify maximum performance are linked to physical performance explosive strength, speed, aerobic resistance. These results coincide with those reported in Vaeyens, Malina, Janssens, Van Renterghem, Bourgois, Vrijens and Philippaerts 22 for male soccer players, as well aswith the study conducted by Till, Cobley, O'Hara, Chapman and Cooke 11 for male rugby players.

If we analyze the under group, anthropometrical variables height, arm span, body mass, sum of skinfolds, leg girth become more predictive of handball players' performance levels, while physical performance variables remain stable in both age groups and they reassert the importance of explosive strength, speed-agility and aerobic power in handball 2 These results are also in accordance with the research carried out by Matthys, Vaeyens, Vandendriessche, Vandorpe, Pion, Coutts, Lenoir and Philippaerts 13which reflected that category age group influences the stage at which distinguishing anthropometric variables of players' performance levels are identified.

A discriminatory analysis indicated that five variables could help distinguish between regional and national players. This model combines tests that assess explosive strength CMJ and speed 10x5m with anthropometric variables body mass, hand length and trochanter heightaccounting for The parameters highlighted by the discriminatory analysis correspond to anthropometric characteristics and physical performance demands, viewed as essential in senior handball players2, 23, Three of the five variables were associated with PHV.

It must be noted, however, that variation of maturity status did not feature as a variable in the model.

anthropometric and strength relationship male female differences

This could be explained by the complexity of handball, and the fact that certain tactical and technical aspects have not been dealt with in this study. Lidor et al 30 indicated that assessments of technical skills would need to be found in light of the difficulty involved in deciding which systematic approach, among those presented in recent studies, would be better suited for the purpose.

With this study it has been advanced that physical performance and anthropometric characteristics may be used to distinguish players that will potentially achieve high performance levels playing handball. Main findings and conclusion This study analyzed the evolution of the sporting performance of young handball players for 13 years; As regards the first objective specified above and taking into account the results derived from the data analysis, we conclude that gender conditions performance-related variables and even more so in the case of anthropometric variables height, arm span, trochanter height, thigh girth and leg girth with a greater impact on males than on females.

As regards the second objective, it should be noted that the selection of young talent in handball requires the combination of five variables CMJ with arm, body mass, 10x5m shuttle run, dominant hand length and trochanter heightwhich would contribute to distinguish between regional and national players successfully, with a predictive accuracy of Acknowledgments The authors would like to thank the Galician Handball Federation Galicia, Spain and all the coaches involved in this study for their collaboration and unconditional support.

No financial assistance was obtained for this project. Considering the Role of Psychology. J Sci Med Sport. Perceptual Skill in Soccer: Implications for Talent Identification and Development. J Sci Med Sports. J Sports Med Phys Fitness.

anthropometric and strength relationship male female differences

Effect of Age and Maturation. Eur J Sports Sci. J Strength Cond Res. To verify the correlation between handgrip strength HGS and flexibility with age and anthropometric variables in the elderly. A total of elderly individuals were evaluated. Flexibility correlated with BMI in males. The results indicate a probable influence of age and anthropometric variables in muscular strength, as well as that of excess weight in flexibility limitation.

Elderly, Anthropometrics, Flexibility, Muscular strength Introduction The aging process results in body alterations that can interfere with the functional capacity and independence of the elderly to perform daily activities.

Thus, assessment of physical capacity of the elderly commonly involves functional tests, such as muscular strength and flexibility, which are directly involved in the performance of these activities. Muscle mass decreases substantially, which is the main factor related to loss of strength. The scarcity of studies in Brazil evaluating the influence of anthropometric variables on strength and flexibility makes data comparison in elderly from different regions of the country difficult, leading to the use of international studies for this evaluation.

This fact results in certain limitations, considering the differences between the populations. Therefore, this study aimed to investigate the correlation between anthropometric variables and age on HGS and flexibility of the elderly.

It is expected that this study can provide information on the factors associated with alterations in strength and flexibility, helping to compare with the elderly from different populations. Methods This was a home-based, cross-sectional study with primary data collection, and is part of a larger study that aimed to conduct a multidimensional health assessment of the elderly individuals enrolled in the Family Health Strategy in Campina Grande, state of Paraiba, Brazil.

The sample size calculation was performed using the following equation: The sample was proportional to each health district, consisting of elderly individuals.

Individuals aged 60 or older, of both genders, were selected for the sample. Elderly individuals with diseases that had no therapeutic options, those with severe clinical weakness, and those who were absent from Campina Grande longer than the duration of the fieldwork in their respective UBSF were excluded. Moreover, exclusion criteria were established for each functional test HGS and flexibility.

Anthropometry and strength relationship: male-female differences.

Fieldwork was carried out from August, to July,by three pairs of trained interviewers. The variables evaluated were: The test performance was conducted according to the techniques proposed by Rantanen et al.

The test was not performed with elderly individuals who were bedridden or wheelchair-bound or those that, for some reason, could not stand up. Height m was measured on a portable stadiometer Altura Exata. Weight and height were measured according to the techniques proposed by Gordon et al. AC was measured based on the techniques by Callaway et al. TSF was measured according to the techniques proposed by Harrison et al. The AMC was calculated through the following equation: Statistical procedures The elderly were grouped according to gender male and female and age group 60 to 69 years, 70 to 79 years, and 80 years or older.

HGS, flexibility, and anthropometric variables are shown as mean and standard deviation SD. The statistical significance of differences of means between the genders was verified using Student's t-test.

To determine the influence of age, BMI, AMC, and CAMA on the variability in muscular strength and flexibility tests, bivariate Pearson's correlation and multivariate linear regression analysis techniques were used.

The stepwise method was used for the inclusion of variables in the multiple linear regression equation. Results A total of elderly patients Mean age was Of the elderly patients studied, underwent the HGS test, and underwent the flexibility test.

anthropometric and strength relationship male female differences

Table 1 shows the information regarding the means and standard deviations of the HGS and flexibility test values and anthropometric variables, with respective significance values of the mean differences between the genders and age groups. The mean HGS value was significantly higher in men No statistically significant difference was observed between men and women, nor between the age groups, in the flexibility test.

In the female gender, the mean BMI was higher The mean AMC was significantly higher in males No statistically significant difference was found between the mean values of CAMA and gender. Regarding BMI, when comparing age groups, a significant difference was observed among them in women; this difference was observed between the groups of 60 to 69 years and 70 to 79 years with the group 80 years or older.

Regarding AMC and CAMA, a significant difference was observed in both genders between the group of 60 to 69 years and 80 years or older. The other variables were excluded from the model due to strong collinearity.

Discussion Aspects related to bodily and physical changes resulting from the aging process have been studied worldwide. This study verified the correlations between anthropometric variables and age with motor tests in an elderly population.

Anthropometry and strength relationship: male-female differences.

The bivariate and multivariate analyses showed a correlation between age and anthropometric variables with motor tests, indicating a probable influence of these variables on physical performance in the elderly.

The term "mobility" was used together with "flexibility", considering that this test also depends on muscle power generated in the lower limbs and spinal column. Studies conducted with elderly individuals from different countries have also showed similar results to those obtained in the present study. The higher degree of flexibility observed in women can be attributed to the fact that they have less dense tissues than men, which favors greater flexibility.

In a study with physically active women, a higher mean flexibility value was observed in the group aged 60 to 69 years, when compared to the group aged 70 to 79 years. However, significant differences were observed between the genders only for AMC. Studies reporting greater muscle mass in men compared to women are common in the literature. Studies have shown lower mean values of the variables indicative of reserve muscle mass in the elderly at advanced age groups.

A similar result has been observed in other studies with the elderly. In a study of elderly individuals conducted in England, a lower mean BMI was observed in older participants;26 similar results were found in the study of Perissinotto et al.