Aleš Gába

Mr. Aleš Gába

Palacký University Olomouc
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 January 2018 in Journal of Physical Activity and Health
Verified
Journal Article
Open access
SASalomé Aubert
Salomé Aubert
JBJoel D. Barnes
Joel D. Barnes
CAChalchisa Abdeta
Chalchisa Abdeta
PNPatrick Abi Nader
Patrick Abi Nader
AAAde F. Adeniyi
Ade F. Adeniyi
MTMark Tremblay
Mark Tremblay
Background: Accumulating sufficient moderate to vigorous physical activity is recognized as a key determinant of physical, physiological, developmental, mental, cognitive, and social health among children and youth (aged 5–17 y). The Global Matrix 3.0 of Report Card grades on physical activity was developed to achieve a better understanding of the global variation in child and youth physical activity and associated supports. Methods: Work groups from 49 countries followed harmonized procedures to develop their Report Cards by grading 10 common indicators using the best available data. The participating countries were divided into 3 categories using the United Nations’ human development index (HDI) classification (low or medium, high, and very high HDI). Results: A total of 490 grades, including 369 letter grades and 121 incomplete grades, were assigned by the 49 work groups. Overall, an average grade of “C-,” “D+,” and “C-” was obtained for the low and medium HDI countries, high HDI countries, and very high HDI countries, respectively. Conclusions: The present study provides rich new evidence showing that the situation regarding the physical activity of children and youth is a concern worldwide. Strategic public investments to implement effective interventions to increase physical activity opportunities are needed.

4 January 2022 in Archives of Public Health
Verified
Journal Article
Open access
PDF file
LRLukáš Rubín
Lukáš Rubín
Aleš GábaAleš Gába
Aleš Gába
JPJana Pelclová
Jana Pelclová
NŠNikola Štefelová
Nikola Štefelová
LJLukáš Jakubec
Lukáš Jakubec
KHKarel Hron
Karel Hron
Background: To date, no longitudinal study using a compositional approach has examined sedentary behavior (SB) patterns in relation to adiposity in the pediatric population. Therefore, our aims were to (1) investigate the changes in SB patterns and adiposity from childhood to adolescence, (2) analyze the prospective compositional associations between changes in SB patterns and adiposity, and (3) estimate the changes in adiposity associated with substituting SB with physical activity (PA) of different intensities. Methods: The study presents a longitudinal design with a 5-year follow-up. A total of 88 participants (61% girls) were included in the analysis. PA and SB were monitored for seven consecutive days using a hip-worn accelerometer. Adiposity markers (fat mass percentage [FM%], fat mass index [FMI], and visceral adiposity tissue [VAT]) were assessed using the multi-frequency bioimpedance analysis. The prospective associations were examined using compositional data analysis. Results: Over the follow-up period, the proportion of time spent in total SB increased by 154.8 min/day (p < 0.001). The increase in total SB was caused mainly by an increase in middle and long sedentary bouts, as these SB periods increased by 79.8 min/day and 62.0 min/day (p < 0.001 for both), respectively. FM%, FMI, and VAT increased by 2.4% points, 1.0 kg/m2, and 31.5 cm2 (p < 0.001 for all), respectively. Relative to the remaining movement behaviors, the increase in time spent in middle sedentary bouts was significantly associated with higher FM% (βilr1 = 0.27, 95% confidence interval [CI]: 0.02 to 0.53) at follow-up. Lower VAT by 3.3% (95% CI: 0.8 to 5.7), 3.8% (95% CI: 0.03 to 7.4), 3.9% (95% CI: 0.8 to 6.9), and 3.8% (95% CI: 0.7 to 6.9) was associated with substituting 15 min/week spent in total SB and in short, middle, and long sedentary bouts, respectively, with an equivalent amount of time spent in vigorous PA. Conclusions: This study showed unfavorable changes in SB patterns and adiposity status in the transition from childhood to adolescence. Incorporating high-intensity PA at the expense of SB appears to be an appropriate approach to reduce the risk of excess adiposity in the pediatric population.


Viktoryia KarchynskayaViktoryia Karchynskaya
Viktoryia Karchynskaya
JKJaroslava Kopcakova
Jaroslava Kopcakova
DKDaniel Klein
Daniel Klein
Aleš GábaAleš Gába
Aleš Gába
Andrea Madarasova GeckovaAndrea Madarasova Geckova
Andrea Madarasova Geckova
SRSijmen Reijneveld
Sijmen Reijneveld
Background: Overweight and obesity are mostly monitored via the Body Mass Index (BMI), based on self-reported or measured height and weight. Previous studies have shown that BMI as a measure of obesity can introduce important misclassification problems. The aim of this study was to assess the validity of overweight and obesity classification based on self-reported and on measured height and weight versus the proportion of body fat as the criterion. Methods: We used data on 782 adolescents (mean age = 13.5, 55.8% boys) from the Health Behaviour in School-Aged Children (HBSC) study conducted in 2018 in Slovakia. We obtained self-reported (height and weight) and objective measures (height, weight) and the proportion of fat (as the criterion measure) measured via bioimpedance body composition analysis (BIA) with an InBody 230 from the adolescents. Results: Both measured and self-reported BMI indicated overweight and obesity with relatively low sensitivity (66–82%), but high specificity (90–92%). The superior accuracy of measured BMI in comparison to self-reported BMI was confirmed by the area under the curve (AUC) based on the receiver operating characteristics (ROC) curves (AUC measured/self-reported: 0.94/0.89; p < 0.001). The misclassification of overweight and obesity was significantly higher when using self-reported BMI than when using measured BMI. Conclusion: Both self-reported and measured BMI as indicators of overweight and obesity underestimate the prevalence of adolescents with overweight and obesity.

2 January 2018 in Journal of Physical Activity and Health
Verified
Journal Article
Open access
SASalomé Aubert
Salomé Aubert
JBJoel D. Barnes
Joel D. Barnes
NANicolas Aguilar-Farias
Nicolas Aguilar-Farias
GCGreet Cardon
Greet Cardon
CCChen-Kang Chang
Chen-Kang Chang
MTMark Tremblay
Mark Tremblay
Background: To better understand the childhood physical inactivity crisis, Report Cards on physical activity of children and youth were prepared concurrently in 30 very high Human Development Index countries. The aim of this article was to present, describe, and compare the findings from these Report Cards. Methods: The Report Cards were developed using a harmonized process for data gathering, assessing, and assigning grades to 10 common physical activity indicators. Descriptive statistics were calculated after converting letter grades to interval variables, and correlational analyses between the 10 common indicators were performed using Spearman’s rank correlation coefficients. Results: A matrix of 300 grades was obtained with substantial variations within and between countries. Low grades were observed for behavioral indicators, and higher grades were observed for sources of influence indicators, indicating a disconnect between supports and desired behaviors. Conclusion: This analysis summarizes the level and context of the physical activity of children and youth among very high Human Development Index countries, and provides additional evidence that the situation regarding physical activity in children and youth is very concerning. Unless a major shift to a more active lifestyle happens soon, a high rate of noncommunicable diseases can be anticipated when this generation of children reaches adulthood.

11 April 2013 in European Journal of Nutrition
Verified
Journal Article
Open access
PDF file
Aleš GábaAleš Gába
Aleš Gába
MPMiroslava Pridalova
Miroslava Pridalova
The Czech Republic lacks body composition data for women. Therefore, the purpose of the study was to analyze body composition [body fat mass (BFM), fat-free mass (FFM), body fat percentage (%BFM) and visceral adipose tissue (VAT)] and to evaluate the changes that occur with aging in women aged 18–89 years. We also analyzed anthropometric characteristics of study participants and developed age-specific percentile curves for body composition parameters.