Gregor Starc

Background/Objectives: This study focused on the sub-national regional heterogeneity in childhood obesity prevalence across five countries in south-east Europe and the correlation between this heterogeneity and socioeconomic differences. Previous studies have mainly observed national or cross-national data but this study used a sub-national regional approach that may be beneficial in the further investigation of childhood obesity. Methods: Nationally representative samples of children from Croatia, Montenegro, North Macedonia, Serbia and Slovenia were selected using the COSI methodology and used to estimate regional childhood obesity prevalence values. The Sub-national Human Development Database provided data on the Sub-national Human Development Index (SHDI). The spatial autocorrelation analysis of childhood obesity prevalence in sub-national regions was performed and its association with sub-national human development was tested with an ordinary least squares regression model. Results: This study found statistically significant differences in childhood obesity prevalence across sub-national regions in Croatia, Slovenia and Serbia, while no such differences were observed in North Macedonia and Montenegro. There was moderate clustering in childhood obesity rates (Moran’s I = 0.337). The results indicated a significant negative association between SHDI and childhood obesity prevalence across the 48 regions (β = −66.63, p < 0.001). Conclusions: Future public health efforts should take into consideration regional differences in childhood obesity prevalence, and more targeted research is essential for understanding the mechanisms of resilience and vulnerability on a sub-national level.

In the era of ever-greater data production and collection, public health research is often limited by the scarcity of data. To improve this, we propose data sharing in the form of Data Spaces, which provide technical, business, and legal conditions for an easier and trustworthy data exchange for all the participants. The data must be described in a commonly understandable way, which can be assured by machine-readable ontologies. We compared the semantic interoperability technologies used in the European Data Spaces initiatives and adopted them in our use case of physical development in children and youth. We propose an ontology describing data from the Analysis of Children’s Development in Slovenia (ACDSi) study in the Resource Description Framework (RDF) format and a corresponding Next Generation Systems Interface-Linked Data (NGSI-LD) data model. For this purpose, we have developed a tool to generate an NGSI-LD data model using information from an ontology in RDF format. The tool builds on the declaration from the standard that the NGSI-LD information model follows the graph structure of RDF, so that such translation is feasible. The source RDF ontology is analyzed using the standardized SPARQL Protocol and RDF Query Language (SPARQL), specifically using Property Path queries. The NGSI-LD data model is generated from the definitions collected in the analysis. The translation has been verified on Smart Applications REFerence (SAREF) ontology SAREF4BLDG and its corresponding Smart Data Models (52 models at the time). The generated artifacts have been tested on a Context Broker reference implementation. The tool supports basic ontology structures, and for it to translate more complex structures, further development is needed.

In the era of ever-greater data produced and collected, public health research is often limited by the scarcity of data. To improve this, we propose a data sharing in the form of Data Spaces, which provide technical, business, and legal conditions for an easier and trustworthy data exchange for all the participants. The data must be described in a commonly understandable way, which can be assured by machine-readable ontologies. We compared the semantic interoperability technologies used in the European Data Spaces initiatives and adopted them in our use case of physical development in children and youth. We propose an ontology describing data from the Analysis of Children’s Development in Slovenia (ACDSi) study in the Resource Description Framework (RDF) format and a corresponding Next Generation Systems Interface-Linked Data (NGSI-LD) data model. For this purpose, we developed a tool to generate a NGSI-LD data model using information from an ontology in RDF format. The tool builds on the declaration from the standard that the NGSI-LD information model follows the graph structure of RDF, so that such translation is feasible. The source RDF ontology is analyzed using standardized SPARQL Protocol and RDF Query Language (SPARQL), specifically using Property Path queries. The NGSI-LD data model is generated from the definitions collected in the analysis. Multiple ancestries of classes are also supported, even over multiple or common ontologies. These features may equip the tool to be used more broadly in similar contexts.

Introduction: Physical fitness is an important indicator of health in children. Accurately monitoring child and adolescent physical fitness is critical when designing effective public health interventions and strategies. This article aims to provide an overview of the FitBack platform and the health-related criteria that support the reporting system. Methods: Four methodological phases were used to create the FitBack platform. First, a review of existing European fitness databases was conducted to identify common fitness tests and methodologies within a European framework. Second, investigators collated data to create European-level fitness norms, health-related criteria, and health-oriented educational resources dedicated to improving child fitness levels. Third, guidance on how to create one’s own fitness monitoring and surveillance system was created based on good practice examples. The FitBack platform was then piloted and launched based on data received from stakeholders who responded to ≥2 rounds of consultation dialogues. Results: The final version of online platform, with special focus on newly developed Fitback health-related fitness criteria, are communicated herein. Discussion: The FitBack web platform is a first-step towards creating a standardised, person-centred, multi-national fitness surveillance system for children, bridging existing gaps between European political recommendations, individual member states, and harmonious cooperation between sectors. This article also provided the detailed age- and sex-specific health-related fitness cut-points that are used by the FitBack platform, and that could be useful for researchers, practitioners as well as fitness monitoring systems.

Background: Providing individual‐ and population‐level data on children's physical fitness (PF) is a crucial public health and education priority. However, few national fitness monitoring or surveillance systems are currently in practice internationally. We aim to summarize the current European PF monitoring and surveillance systems for school‐aged children and to provide experience‐based guidelines on how to design such systems.Methods: The FitBack network consists of experts from diverse backgrounds with the common interest to improve the accessibility of PF monitoring for young people globally. Through FitBack network, we identified and compared the national or regional PF monitoring and surveillance systems currently in operation across Europe. We formulated a 10‐step approach for designing and establishing one's own system, based on analysis of experienced strengths, weaknesses, opportunities, and threats to monitoring childhood fitness.Results: We identified a total of eight PF monitoring systems in Finland, France, Galicia of Spain, Hungary, Lithuania, Portugal, Serbia, and Slovenia. The FitBack network recommends the following steps for designing and establishing one's own system: (1) set up mission statements and aims, (2) involve stakeholders, (3) utilize scientific background, (4) governance structure, (5) ensure sufficient funding, (6) data management planning, (7) provide meaningful feedback, (8) conduct pilot testing, (9) plan implementation process, and (10) invest in communication with stakeholders.Conclusions: This study provides an updated overview of the best practices for school‐aged children's fitness monitoring and surveillance in Europe. Additionally, it offers a 10‐step approach to assist in the creation of similar systems in Europe or globally.

Background Obesity in childhood has deleterious consequences for health while improving physical fitness can significantly reduce health risks related to high body mass index. This study leverages near-census data collected by the national fitness surveillance system in Slovenia to investigate the evolution of weight-based disparities in the physical fitness of 7–15-year-olds between 1989 and 2019. Methods We used annual data collected within the SLOfit monitoring system in the period between 1989–2019, totalling 4,256,930 participants (about 137 000 per year). We examined cardiorespiratory fitness (600-m run test), muscular fitness (60-s sit-ups, bent arm hang, and standing broad jump test) and skill-related fitness (backwards obstacle course, 60-m dash, arm plate tapping). We grouped children according to the IOTF cut-offs for BMI to those living with normal weight or excess weight and estimated changes in physical fitness over time by fitting quantile regression models separately by sex and age group, and then using segmented regression to identify the structure of trends over time. Results Weight-based disparities in physical fitness were large in 1989 and have further increased from 1989 to 2019 for all fitness components and across all age and sex groups. The increase in disparities was generally larger in boys than in girls, and 10–15-year-olds compared to younger children. Most of the increase in disparities in health-related fitness accumulated during the 2010s, when the fitness of children generally improved, but much less so in children living with excess weight. Conclusions Despite recent improvements in population fitness levels, children with excess weight seem to be left behind, which adds to existing health inequalities. Our results should encourage policymakers to redesign policies aimed at promoting physical activity and enhancing physical fitness to make them more equitable and ultimately lead to reducing inequalities in fitness.

High-quality recreation contributes significantly to life satisfaction. In recent decades, this field has experienced intense changes. Recreational activities and their popularity are changing, even if the core of the most common activities (walking, hiking, cycling, swimming...) remains fairly stable. Many of the most widespread recreational activities are linked to specific recreational infrastructure, so the existence of an adequate and accessible recreational infrastructure is also important in terms of quality of life. In addition, recreational activities, especially outdoor recreation activities, also play a significant role in the context of tourism. In tourism areas, tourists are an important segment of recreational infrastructure users, and an attractive recreational infrastructure is often one of the factors influencing the choice of a particular destination. Accordingly, Slovenian tourism policy also pays a lot of attention to the tourism potential of outdoor recreation. Nevertheless, knowledge about the state of recreational infrastructure in Slovenia is very patchy, and data on recreational infrastructure is usually not systematically collected or does not exist at all. In order to enable the analysis of this important content area, we have created a typology of recreational infrastructure and compiled its inventory through extensive data collection. Various categories of recreational infrastructure are presented in the form of specific spatial layers with different attributes. Our research focused on the question of what are the main characteristics of recreational infrastructure in Slovenia, what is its spatial distribution and what are its specific characteristics in tourist areas. The characteristics of recreational infrastructure are influenced by demand, the specific environmental/geographical requirements of individual recreational activities as well as by various policies. The growing heterogeneity of recreational infrastructure and the emergence of new types of infrastructure are evident.

For decades, projects have been carried out in various countries to assess the developmental status of children and adolescents using anthropometry and specific kinesiological measurements. There is a need for the ability to evaluate this developmental status using a sufficiently simple method or a calculation to be applicable in practice. The most commonly used feature for this purpose is currently body mass index (BMI). From recent experience, this feature may cause problems if used indiscriminately in the developmental phase of life. Therefore, we aimed to find a more suitable feature set. We used data from Artos, the national program monitoring school children and adolescents in Slovenia. The data was analyzed using machine learning (ML) tools to find the most important features to predict a motor efficiency index (MEI), which has been shown to correlate strongly with a person’s health prospects. After data preparation and training a baseline model, a feature selection process was performed, which promoted some features as candidates to predict the motor efficiency index sufficiently. By implementing a hyperparameter optimization, we tuned the ML model to improve its generalization and present the feature interaction more elaborately. We show that besides the single feature’s importance, the features’ interaction should be considered. In the case of MEI, we find that the skin fold thicknesses can complement BMI and contribute to a better development status assessment of children and adolescents.

Physical fitness is an important health indicator and component of physical literacy. Therefore, monitoring youth fitness performance is crucial for identifying potential health risks and tracking physical literacy development. Over the years, many fitness test batteries have been developed while different protocols for footwear have been used in fitness testing. The comparison of fitness results performed in different footwear could therefore be questioned. Thus, the purpose of this study was to examine the differences between barefoot and shod performance of selected motor tests in adolescents. Eighty-six adolescents aged between 14 and 16 years performed standing long jump, 20-m shuttle run, and polygon backwards in both footwear conditions. A strong correlation (r=0.83-0.95) was noted between both performances. No significant differences between barefoot and shod performance in the standing long jump and the backward obstacle course test were found, while significant differences were noted in the 20-m shuttle run. In this test, both, boys and girls performed better in shod conditions. Interestingly, there were no significant differences in performance of all tests among those who are habitually barefoot and others. From practical perspective, this study demonstrated that researchers could compare scores of samples in barefoot and shod performance of standing long jump and backward obstacle course tests. However, when physical teachers compare individual scores over the years, this should be made under the same footwear conditions, as differences in test conditions can provide a distorted picture of motor development.

It is vital from the public health and educational perspective to be familiar with changes in the fitness levels of individuals and populations since fitness is associated with several health outcomes and cognition. Skill‐related physical fitness refers to performance in sports or occupation and is associated with motor skill performance. The aim of the present study was to examine secular trends in skill‐related physical fitness of 16 678 participants in four youth generations of Slovenian children and adolescents in years 1983 (n = 3128), 1993/94 (n = 3413), 2003/04 (n = 5497), and 2013/14 (n = 4640). Using repeated cross‐sectional design, we observed fitness level of all participants divided into three age groups: 6–10, 11–14, and 15–19 years. Skill‐related physical performance was measured with seven fitness tests for speed, coordination, balance, and flexibility. Analysis of covariance was used to compare differences in fitness performance between decades in each age and sex group, adjusted for body height, body weight, and body mass index. Overall, large but inconsistent changes in coordination, a small improvement in speed, and a decline in flexibility were seen. The trends over the whole examined period were not linear throughout decades. Generally, positive trends were noticed in periods 1983–1993 (range 1.4%–17.9%; except flexibility) and 2003/04–2013/14 (range 0.2%–36.4%; except age group 15–19 years) while in the period 1993/94–2003/04 there are some particularities in secular trends according to individual components as well as age groups. In general, the secular trend showed a positive direction for both genders (p < 0.05), except for gross motor coordination, which demonstrated positive trends in 1993 and 2013 compared with a decade earlier (p < 0.05) and from 1983 to 2013/14, except for the youngest boys in 2003 and the youngest girls from 1993 to 2003 (p < 0.05). Our findings call for exercise programs aimed at improving speed and gross motor coordination in both sexes and all age groups, especially in the group of 15–19 years old.