Examples of 'anthropometric variables' in a sentence
Meaning of "anthropometric variables"
Anthropometric variables are measurements or characteristics of the human body that are used to assess various aspects of health and physical fitness. These variables can include height, weight, body mass index (BMI), waist circumference, and body fat percentage. Anthropometric measurements are commonly used in research, sports science, and clinical settings to evaluate growth, development, and health status of individuals
How to use "anthropometric variables" in a sentence
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anthropometric variables
Analysis of anthropometric variables showed no statistically significant difference.
In the first experimental session the anthropometric variables were determined.
Anthropometric variables were also recorded.
Several clinical and anthropometric variables were also collected.
Significant differences were observed between genders in all anthropometric variables.
Correlation with anthropometric variables.
All anthropometric variables studied were submitted to univariate and multivariate analyses.
Both groups were similar in relation to the age and anthropometric variables.
Discriminative performance of anthropometric variables in the identification of frailty in the elderly.
A second meeting was then scheduled for the assessment of anthropometric variables.
Anthropometric variables for assessment of the nutritional state of the critical patient.
There was no statistically significant difference in the comparisons of the anthropometric variables studied.
Rm vs anthropometric variables.
Descriptive statistics were used for characterization purposes regarding the main clinical and anthropometric variables.
Anthropometric variables and body composition indicators were all measured using standardized procedures.
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Statistical analysis repeated measures analysis of anthropometric variables was performed using the friedman test.
Standard anthropometric variables and their respective calculated body composition parameters were recorded.
The present study found no association between anthropometric variables and the practice of physical activity.
The anthropometric variables were obtained according to procedures proposed by Lohman et al.
Table 1 shows demographic and anthropometric variables.
The demographic and anthropometric variables in this group were obtained by interview and clinical examination.
Relationship between maximal and submaximal strength tests and / or anthropometric variables.
CPP was related to anthropometric variables using standard and allometric models.
Pearson 's correlation coefficient was used to analyze relationships between biochemical and anthropometric variables.
There was no correlation between anthropometric variables or the social aspects investigated and PH.
Table 2 shows the correlations of segmental body fat percentage with the other anthropometric variables.
The descriptive values of the anthropometric variables are shown in table 1.
The proposed methodology ensured a homogeneous sample for both sexes, especially in terms of anthropometric variables.
The ad measurement of anthropometric variables was not seen on a frequent basis n 1.
The comparison between the two groups athletes and non-athletes showed no difference in anthropometric variables.
Table 2 displays the correlations of anthropometric variables according to sex.
Prediction of whole-body fat percentage and visceral adipose tissue mass from five anthropometric variables.
However, differences were observed regarding anthropometric variables and blood pressure levels.
The anthropometric variables can be found in Table 3.
Table 2 shows the minimum and maximum values of the anthropometric variables as a function of time.
Objective, analyze the anthropometric variables along the menstrual cycle of eumenorrheic and eutrophic college students.
The groups were similar regarding age and anthropometric variables Table 1.
Mean values of anthropometric variables are shown in Table 1.
Table 1 shows results of descriptive statistics and t-test results for anthropometric variables and MR indicators.
Socioeconomic and demographic status, anthropometric variables and dietary profile were assessed for all individuals.
Anthropometric variables were compared between groups by one-way ANOVA and post hoc Tukey 's test.
Also, correlate the findings with anthropometric variables and performance of the middle distance runners.
Anthropometric variables are shown in Table 1.
The predictive power for 1RM from anthropometric variables is weak.
Although other anthropometric variables were also associated, only BMI remained in the final regression model.
On the other hand, more associations between HDL-C and anthropometric variables in females were found.
HGS, flexibility, and anthropometric variables are shown as mean and standard deviation SD.
Anthropometric variables and BP were significantly correlated with PWV Table 4.
Moreover, cardiorespiratory fitness was also associated with anthropometric variables waist-to-height ratio, obesity, and BMI.
Moreover, the anthropometric variables presented the highest correlations with the 1RM workload in the SM.
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Examples of using Anthropometric
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Anthropometric and disease characteristics were balanced at baseline
The clinical and anthropometric data were collected
Anthropometric assessment and body composition measures
Examples of using Variables
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Variables are introduced in order to track such bequests
The plan of the variables is the following
Variables to be probed as part of the study include
