Nomenclature Of Territorial Units For Statistics Research Articles

HANZE v2.1: an improved database of flood impacts in Europe from 1870 to 2020

Abstract. Assessing long-term trends in flood losses and attributing them to climatic and socioeconomic changes requires comprehensive and systematic collection of historical information. Here, we present flood impact data for Europe that are part of the HANZE (Historical Analysis of Natural HaZards) database. The dataset covers riverine, pluvial, coastal, and compound floods that have occurred in 42 European countries between 1870 and 2020. The data were obtained by extensive data collection from more than 800 sources ranging from news reports through government databases to scientific papers. The dataset includes 2521 events characterized by at least one impact statistic: area inundated, fatalities, persons affected. or economic loss. Economic losses are presented both in the original currencies and price levels and with the inflation and exchange rate adjusted to the 2020 value of the euro. The spatial footprint of affected areas is consistently recorded using more than 1400 subnational units corresponding, with minor exceptions, to the European Union's Nomenclature of Territorial Units for Statistics (NUTS) level 3. Daily start and end dates, information on causes of the events, notes on data quality issues or associated non-flood impacts, and full bibliography of each record supplement the dataset. Apart from the possibility of downloading the data (https://doi.org/10.5281/zenodo.8410025; Paprotny, 2023a), the database can be viewed, filtered, and visualized online at https://naturalhazards.eu (last access: 4 November 2024). The dataset is designed to be complementary to HANZE-Exposure, a high-resolution model of historical exposure changes (such as population and asset values) and be easily usable in statistical and spatial analyses, including multi-hazard studies.

Harmonized European Union subnational crop statistics can reveal climate impacts and crop cultivation shifts

Abstract. The availability of coherent time series of crop statistics is essential for better analyzing the past, understanding the present, and predicting future trends in yield, area, and production. Importantly, such data also underpin assessments and subsequent policy actions that can shape future food systems that are more resilient in the face of climate change and that are sustainable in terms of resource use efficiency. In the European Union (EU), there currently is no legal obligation for EU countries to provide subnational crop statistics. However, such data could improve in-season crop forecasts, climate change impacts and adaption need assessments, and evaluation of agri-environmental schemes. The dataset described in this paper includes a harmonized collection of subnational crop statistics on area, production, and yield, collected for the EU from National Statistical Institutes (NSIs) and the EUROSTAT REGIO database – subnational crop statistics voluntarily contributed by EU countries. The crops considered are wheat (including soft and durum wheat), barley (including winter and spring barley), grain maize, sunflower, and sugar beet. All data are harmonized towards the hierarchical structure of the EUROSTAT legend and the regional classification of NUTS (Nomenclature of Territorial Units for Statistics) version 2016, to provide coherent time series. A total of 344 282 records is presented here (115 974 for wheat, 122 705 for barley, 35 274 for grain maize, 34 916 for sugar beet, and 35 413 for sunflower) for a total of 961 regions in 27 EU countries. Statistics are reported from 1975 to 2020, with a median time-span range of 21 years. A flagging system details, for each data record, information on data sources, processing steps, and quality-checking results. This includes consistency checks between reported values for area, yield and production, identification of null values, missing and calculated data, information on crop legend matching, and NUTS versioning. We illustrate the value of this dataset by analyzing impacts on crops and production zone shifts in Europe due to climatic and economic factors. Recommendations and future developments of collecting subnational statistics at the EU level are briefly discussed. The dataset is accessible with European Commission Authentication Service (ECAS) login at https://doi.org/10.2905/685949ff-56de-4646-a8df-844b5bb5f835 (Ronchetti et al., 2023b).

Domestic or export: What is basic at the NUTS 2 regional level? A spatial endogenous regional growth model applied in the EU

AbstractA common statement found in regional policy reports is that regional growth is an “export or die” issue. However, the succession of disruptions in the international supply chain has highlighted the crucial roles of domestic activities, local markets and short supply chains, turning the environmental and resilience challenge present in growth policy into a “domestic or die” issue. Recent regional growth theories have seriously questioned export activity as the only way in which to drive regional growth and have highlighted the crucial role of the domestic sector. However, no empirical study has assessed the roles of the domestic and export sectors in growth during this troubled economic period, despite the usefulness of this information for nonbiased policy decisions. Using a spatial endogenous regional growth model as a framework, we investigate the role of the domestic sector during the 1999–2014 period for 263 European Union (EU) Nomenclature of Territorial Units for Statistics (NUTS) regions. The results stress the importance of domestic productivity for regional growth during this period, which is characterized by three economic shocks, thereby elucidating the importance of domestic productivity for competitiveness and resilience issues.

A Geospatial Decision Support System for Supporting the Assessment of Land Degradation in Europe

Nowadays, Land Degradation Neutrality (LDN) is on the political agenda as one of the main objectives in order to respond to the increasing degradation processes affecting soils and territories. Nevertheless, proper implementation of environmental policies is very difficult due to a lack of the operational, reliable and easily usable tools necessary to support political decisions when identifying problems, defining the causes of degradation and helping to find possible solutions. It is within this framework that this paper attempts to demonstrate a new valuable web-based operational LDN tool as a component of an already running Spatial Decision Support System (S-DSS) developed on a Geospatial Cyberinfrastructure (GCI). The tool could be offered to EU administrative units (e.g., municipalities) so that they may better evaluate the state and the impact of land degradation in their territories. The S-DSS supports the acquisition, management and processing of both static and dynamic data, together with data visualization and on-the-fly computing, in order to perform modelling, all of which is potentially accessible via the Web. The land degradation data utilized to develop the LDN tool refer to the SDG 15.3.1 indicator and were obtained from a platform named Trends.Earth, designed to monitor land change by using earth observations, and post-processed to correct some of the major artefacts relating to urban areas. The tool is designed to support land planning and management by producing data, statistics, reports and maps for any EU area of interest. The tool will be demonstrated through a short selection of practical case studies, where data, tables and stats are provided to challenge land degradation at different spatial extents. Currently, there are WEBGIS systems to visualize land degradation maps but—to our knowledge—this is the first S-DSS tool enabling customized LDN reporting at any NUTS (nomenclature of territorial units for statistics) level for the entire EU territory.

Temporal and spatial mapping of theoretical biomass potential across the European Union

Abstract. With the increasing challenge to shift our economic system from carbon to renewable energy carriers, the demand for biogenic resources is growing. Biogenic municipal waste, agricultural by-products and industrial residues are under-utilised but are increasingly gaining in value. To date, there is no continuous database for these resources in the EU-27 countries. Existing datasets that estimate resource potentials for a single point in time often lack validation. A reliable and continuous database is thus needed to support the growing bioeconomy. Spatial and temporal high-resolution data of biogenic residues serve as an invaluable resource for identifying areas with significant theoretical biomass potential and allows an in-depth understanding of dynamic patterns over time. This study elucidates the theoretical biomass potentials of 13 distinct biomasses from municipal waste, agricultural by-products and industrial residues quantified annually from 2010–2020. The spatial scope of the research covers the EU-27 Member States incorporating all entities represented at various levels within the Nomenclature of Territorial Units for Statistics (NUTS) as delineated by Eurostat, where possible. The regionalised data are subsequently validated against regional statistics from different countries. The findings demonstrate the feasibility of creating a time series of theoretical biomass potentials for the 13 selected waste types, by-products, and residues, and underscore the critical role of data validation when regionalising national or sub-national data to smaller NUTS entities. It could be shown that the values of small regions (NUTS 3) correlated well on average. When looking at individual regions in detail, regional characteristics such as the location of cultivation, waste management or reporting methods could lead to over- or underestimates of up to 100 %. Therefore, data at the regional level provide only limited reliability. In the case of industrial residues, regionalisation gave good results localising preference regions of high theoretical biomass potential, but more data on industrial production are needed to also estimate residual quantities at sub-national and local levels. The biomass potentials modelled in this study have been published in an open-access database, which is designed as an extensible tool, enabling the understanding of national and regional trends of theoretical biomass potentials in the European Union and of the reliability of the regionalised data. The estimated theoretical potential dataset can be downloaded free of charge from: https://doi.org/10.48480/g53t-ks72 (Günther et al., 2023).

Mapping and modelling the main determinants of Migration Flows at the NUTS2 Level in European Union using Spatial Data Analysis Techniques

Abstract Spatial data analysis approaches have grown in popularity in recent years as there has been an increased interest in studying migration at the regional level. We employed in our analysis the Nomenclature of Territorial Units for Statistics (NUTS) level, which offers a more thorough view of migratory patterns inside a nation as well as among EU countries.Using spatial data analytic tools, this research aims to investigate the key determinants of international migration at the NUTS2 level. Using data from the Eurostat database, we undertake an extensive analysis of migration movements in a sample of European Union countries. We apply spatial econometric models to examine the relationship between crude rate migration and other relevant variables as independent variables. Although the available data at the NUTS2 level of regional ranking are limited, we believe that we included the most comprehensive set of relevant variables in our analysis.Our study contributes to the existing literature on migration determinants by highlighting the importance of spatial analysis techniques in understanding migration factors at the NUTS2 level.

The relationship between PM10 and SO2 exposure and Covid-19 infection rates in Turkey using nomenclature of territorial units for statistics level 1 regions

The Covid-19 pandemic, which has been affecting the world since December 2019, has become one of the biggest problems of the 21st century. There are studies stating that the contagiousness of the Covid-19 pandemic, which is transmitted from person to person, increases more with environmental factors such as air pollution, and accordingly, there is an increase in the number of cases. In this study, a panel regression model to investigate the effect of air pollution concentrations such as PM10 and SO2 as environmental factors and population density on the monthly mean number of Covid-19 cases for 12 regions at the nomenclature of territorial units for statistics (NUTS) level 1 in Turkey between June 2020 and November 2020, and a linear regression model to investigate the effect at the regional level. we used. Based on the model results, we concluded that a small increase in air pollution indicators led to an increase in the number of Covid-19 cases in Turkey and its regions. It is very important to identify preventable environmental factors in order to prevent and minimize the effects of respiratory tract diseases and rapidly spreading pandemic diseases such as Covid-19. Accordingly, we can conclude that countries should take some measures, especially on air pollution, in order to develop public health and pandemic/disease management strategies and to reduce the risk of respiratory diseases.

Prevalence of asymptomatic Leishmania infection and knowledge, perceptions, and practices in blood donors in mainland Portugal

BackgroundAsymptomatic infection is the most common outcome of exposure to Leishmania parasites. In the Mediterranean region, where Leishmania infantum is endemic, studies on the prevalence of asymptomatic infection have often relied on serological testing in blood donors. In Spain, regional studies have shown seroprevalence in blood donors between 1 and 8%; in Portugal, values of 0 and 2% were suggested by two localized studies, in different populations. The purpose of this study was (i) to estimate the prevalence of asymptomatic Leishmania infection in blood donors in mainland Portugal, and (ii) to study the association between the detection of antibodies to Leishmania and sociodemographic factors, and also the knowledge, perceptions and practices (KPP) of the blood donors regarding leishmaniasis.MethodsA cross-sectional study targeted the population of people who donated blood in mainland Portugal. Participants, distributed proportionally by municipality and aged between 18 and 65 years, were selected randomly in 347 blood collection points between February and June 2022, and completed a sociodemographic and a KPP questionnaire. Detection of anti-Leishmania antibodies in serum was performed using an ELISA commercial kit. Individual KPP scores were calculated by adding grades defined for each question.ResultsGlobally, 201/3763 samples were positive. The estimated national true seroprevalence was 4.8% (95% CI 4.1–5.5%). The proportion of positive results was significantly different between NUTS (Nomenclature of Territorial Units for Statistics) regions. Models suggested that seropositivity was significantly higher in male sex, people older than 25 years, or residing in the Centro NUTS2 region, but not in dog owners nor people with lower KPP scores. Overall, 72.3% of participants had previously heard of leishmaniasis and, in multivariate analysis, a higher Knowledge score was associated with age 25–40 years, female sex, ownership of dogs, and higher education.ConclusionsGlobal estimated true seroprevalence (4.8%) was similar to previous regional studies in blood donors in neighboring Spain. Higher seroprevalence values in the NUTS2 Centro region were consistent with incidence data from humans and seroprevalence studies in dogs. On the other hand, the low values in the Alentejo and the high values in the northern subregions may be the result of geographical shifts in parasite circulation due to climate change and should prompt localized and integrated, vector, canine, and human research, following a One Health approach.Graphical

Multiscale mobility patterns and the restriction of human movement.

From the perspective of human mobility, the COVID-19 pandemic constituted a natural experiment of enormous reach in space and time. Here, we analyse the inherent multiple scales of human mobility using Facebook Movement maps collected before and during the first UK lockdown. Firstly, we obtain the pre-lockdown UK mobility graph and employ multiscale community detection to extract, in an unsupervised manner, a set of robust partitions into flow communities at different levels of coarseness. The partitions so obtained capture intrinsic mobility scales with better coverage than nomenclature of territorial units for statistics (NUTS) regions, which suffer from mismatches between human mobility and administrative divisions. Furthermore, the flow communities in the fine-scale partition not only match well the UK travel to work areas but also capture mobility patterns beyond commuting to work. We also examine the evolution of mobility under lockdown and show that mobility first reverted towards fine-scale flow communities already found in the pre-lockdown data, and then expanded back towards coarser flow communities as restrictions were lifted. The improved coverage induced by lockdown is well captured by a linear decay shock model, which allows us to quantify regional differences in both the strength of the effect and the recovery time from the lockdown shock.

Mesleki Eğilimin ve Ebeveynlerin İşe Alımdaki Rolü

The aim of this study is to search to the topic “The role of professional inclination and parents on recruitment”. The data analyzed in this study have been obtained from the TURKSTAT Study held on 2016 on the Structure of Family. The sample of this study is a group providing estimation at Turkey Nomenclature of Territorial Units for Statistics (NUTS) 1 Level (12 Region) to represent universe. Their professions and the professions of their parents were asked to the 42.044 persons who participated in that study and these were recorded and classified according to their International Standard Classification of Occupation (ISCO)-08 codes. During the analysis of data, the professions of mother, father and children were coded as white, blue, gray and pink-collars. Then, whether a relationship or not between mother, father and children profession and the collar color was investigated. At the end of the study, a high correlation level was established between the mother’s collar color and the child’s collar color. Another result is the correlation observed between the father’s collar color and the child’s collar color. In addition, it was determined that the collar color of the child is correlated with the mother’s collar color at a higher level than with the father’s collar color. This result indicates that the profession of parents should also be taken in consideration as a criterion by the managers for recruitment of employees.

Understanding peripherality in a multidimensional geographical, socioeconomic, and institutional context: Evidence from Greece

AbstractThis paper develops a multidimensional methodological framework for examining the geographical handicaps and associated socioeconomic drawbacks of nomenclature of territorial units for statistics (NUTS) III regions in Greece to conceive diverse dimensions of peripherality and target the de‐peripheralization of peripheral regions. Building on the network paradigm, empirical analysis, and policy assessment, the analysis sheds light on the unique characteristics and challenges experienced by inland, island, coastal, and borderline regions across the multiple dimensions and conceives a tailored mix of policy measures to address the specific needs and catalyze development in each region. The proposed methodological framework provides a roadmap for understanding the complex interplay between geographical and socioeconomic dynamics and policy interventions, offering methodological and empirical insights for regional policymakers, practitioners, and stakeholders toward a more prosperous and equitable regional development landscape.

The impact of the creative industries and digitalization on regional resilience and productive entrepreneurship

This study investigates the impact of the creative industries on regional resilience and productive entrepreneurship. We control for the localized effects of digitalization in this relationship. We do so by linking the regional resilience theory with the literature on the creative industries, digitalization and productive entrepreneurship. The unit of our analysis is the European Union’s regions (from the 2008 Great Recession crisis to the 2015 recovery period). We empirically tested our framework in the context of the European Union with datasets from Eurostat Regional Statistics and the European Social Survey (ESS). Our analysis is focused on the Nomenclature of Territorial Units for Statistics (NUTS) 3 regions, which includes 1397 industry performance observations from 314 NUTS-3 regions and 11 European countries (Bulgaria, the Czech Republic, Denmark, Finland, France, Hungary, Italy, the Netherlands, Portugal, Romania, and Slovakia) for the period 2008–2015. Our findings demonstrate that regions with a higher share of employment in the creative industries are more likely to withstand a short-term economic shock than regions with a lower share of employment in the creative industries. Our results also indicate the importance of digitalization in the period of recovery from crises, and demonstrate that the creative industries play an important part in this process. This study offers a number of policy implications.

Regionalization in the Republic of Moldova: the essence and form of the manifestation

With the emergence and beginning of the consolidation of the contemporary Moldovan state, serious premises for spontaneous regionalization are created, by virtue of political actions initiated by the intelligentsia and part of the bureaucracy of the administrative system in the southern and eastern districts of the MSSR/Republic of Moldova. The process of spontaneous or „bottom-up” regionalization, which at that time was characterized by an open conflict between the „Political Center” and the „hotbeds” of the political movements in the respective areas, directed by the regional leaders in the bed of the autarchic movements, basically represented a strong „devolution” of the state of the Republic of Moldova, the consequences of which are felt until now. Apart from the manifestations of regionalization „from below”, starting from the second half of the 2010s, the process of regionalization from „above” is starting in the Republic of Moldova - through conscious political actions and the adoption of normative acts that also reflect the course of European integration. As a result of these actions undertaken by the Republic of Moldova and supported by representatives of civil society and the expert community, the territory of the Republic of Moldova was delimited into six „development regions”, which correspond to the European criteria set out in the Common Nomenclature of Territorial Units for Statistics (NUTS). The first results of regionalization policies in the Republic of Moldova are measurable and promising. Government of the Republic of Moldova and supported by representatives of civil society and the expert community, the territory of the Republic of Moldova was delimited into six „development regions”, which correspond to the European criteria set out in the Common Nomenclature of Territorial Units for Statistics (NUTS). The first results of regionalization policies in the Republic of Moldova are measurable and promising.

Changes in Multimorbidity Prevalence in Turkey (2008-2019)

Purpose: To examine the 11 year change in the prevalence of multimorbidity according to age, gender, educational status and NUTS (Nomenclature of Territorial Units for Statistics) regions from 2008 to 2019 in Turkey.
 
 Materials and Methods: For this study, the data from the Turkiye Health Survey conducted by the TUIK in every 2 or 3 years from 2008 to 2019 were used. Descriptive statistics for multimorbidity were calculated according to gender, age groups, educational status and IBBS regions by using the weights provided by TUIK. Linear regression analysis was used to estimate expected prevalence of multimorbidity. Absolute and relative changes in the prevalence of multimorbidity for 11 year period were examined in the EXCEL program.
 
 Results: In the period between 2008 and 2019, the prevalence of multimorbidity increased by 77.0% in relative terms. The increase in the prevalence of multimorbidity is more evident in the female gender, in the group with a low education level, in those living in the Eastern Anatolia Region, and in the group aged 55-64 years and above.
 
 Conclusion: Multimorbidity shows an increasing trend and it is a priority issue for our country.

Evaluation of the Turkish Population's Perspective on COVID-19 Vaccine Hesitancy and Routine Childhood Vaccine Applications: National Survey Study.

It is important to evaluate the attitude of society towards vaccines to understand the rates of acceptance and hesitance towards vaccination, which are essential components of public health and epidemiology. This study aimed to evaluate the perspective of the Turkish population on COVID-19 status, rate of vaccination, and also to evaluate the reasons for refusal to vaccinate, vaccine hesitancy, and related factors. A total of 4539 participants were included in this population-based descriptive and cross-sectional study. The Nomenclature of Territorial Units for Statistics (NUTS-II) was used to obtain a representative sample and for this purpose Turkey was divided into 26 regions. Participants were randomly selected based on the demographic features and population ratios of the selected regions. The following parameters were evaluated: sociodemographic characteristics and perspectives on COVID-19 vaccines, Vaccine Hesitancy Scale Adapted to Pandemics (VHS-P), and Anti-Vaccine Scale-Long Form (AVS-LF) questions. A total of 4539 participants, 2303 (50.7%) male and 2236 (49.3%) female, aged between 18 and 73 years, were included in this study. It was observed that 58.4% of the participants had hesitations towards COVID-19 vaccination, and 19.6% were hesitant about all childhood vaccinations. Those who did not have the COVID-19 vaccine, who did not think that the COVID-19 vaccine was protective, and who had hesitation to vaccinate against COVID-19 had significantly higher median scores on the VHS-P and AVS-LF scales, respectively (all p < 0.01). Those who did not have their children vaccinated in childhood and who were hesitant about childhood vaccinations, had significantly higher median scores on the VHS-P and AVS-LF scales, respectively (all p < 0.01). Although the rate of vaccination for COVID-19 was 93.4% in the study, hesitation to vaccinate was 58.4%. The median score of the scales of those who were hesitant about childhood vaccinations was higher than individuals who did not have any hesitation. In general, the source of concerns about vaccines should be clearly seen, and precautions should be taken.

The regional economic impact of wildfires: Evidence from Southern Europe

We estimate the impact of wildfires on the growth rate of gross domestic product (GDP) and employment of regional economies in Southern Europe from 2011 to 2018. To this end we match Eurostat economic data with geospatial burned area perimeters based on satellite imagery for 233 Nomenclature of Territorial Units for Statistics (NUTS) 3 level regions in Portugal, Spain, Italy, and Greece. Our panel fixed effects instrumental variable estimation results suggest an average contemporary decrease in a region’s annual GDP growth rate of 0.11–0.18% conditional on having experienced at least one wildfire. For an average wildfire season this leads to a yearly production loss of 13–21 billion euros for Southern Europe. The impact on the employment growth rate is heterogeneous across economic activity types in that there is a decrease in the average annual employment growth rate for activities related to retail and tourism (e.g., transport, accommodation, food service activities) of 0.09–0.15%, offset by employment growth in insurance, real estate, administrative, and support service related activities of 0.13–0.22%.

Multidrug resistance in pathogens of community-acquired urinary tract infections in Turkey: a multicentre prospective observational study

To have country-wide information about multidrug resistance (MDR) in isolates from community-acquired urinary tract infections (CAUTI) of Turkey, in terms of resistance rates and useful options. We used a geocode standard, nomenclature of territorial units for statistics (NUTS), and a total of 1588 community-acquired isolates of 20 centres from 12 different NUTS regions between March 2019 and March 2020 were analysed. Of the 1588 culture growths, 1269 (79. 9%) were Escherichia coli and 152 (9.6%) were Klebsiella spp. Male sex, advancedage, and having two or more risk factors showed a statistically significant relation with MDR existence (p < 0.001, p: 0.014, p < 0.001, respectively) that increasing number of risk factors or degree of advancing in age directly affects the number of antibiotic groups detected to have resistance by pathogens. In total, MDR isolates corresponded to 36.1% of our CAUTI samples; MDR existence was 35.7% in E. coli isolates and 57.2% in Klebsiella spp. isolates. Our results did not show an association between resistance or MDR occurrence rates and NUTS regions. The necessity of urine culture in outpatient clinics should be taken into consideration, at least after evaluating risk factorsfor antibacterial resistance individually. Community-acquired UTIs should be followed up time- and region-dependently. Antibiotic stewardship programmes should be more widely and effectively administrated.

Eudistance: Distance calculator for the different levels of European NUTS regions

<h2>Abstract</h2> The presented R function called eudistance calculates the centroid distance matrix for the different levels of the European Union (EU) Nomenclature of Territorial Units for Statistics (NUTS) regions in meters and complements it by their code, name, level, and country identifier, as well as their geometric data and centroids. Optionally, this R function displays centroids on a map of Europe to ease the verification of their positions. The eudistance R package (containing the aforementioned function) with the distance dataset it generates is available in this article and publicly on GitHub (Kurbucz and Katona, 2022) and Mendeley Data (Kurbucz and Katona, 2022).

Assessing the probability of risk factor control in patients with coronary heart disease: results from the ESC-EORP EUROASPIRE V survey.

In patients with coronary heart disease (CHD), we investigated whether it is possible to accurately assess the probability of short-term control of risk factors (blood pressure, cholesterol, smoking) based on individual and large-area residential characteristics. We merged individual data of participants from EUROASPIRE V who were hospitalized for CHD (2014-2017) and interviewed and examined for risk factor control (2016-2017), with large-area residential data provided by Eurostat for Nomenclature of Territorial Units for Statistics (NUTS) regions using postal codes. Data from 2562 CHD patients in 16 countries were linked to data from 60 NUTS 2 and 121 NUTS 3 regions. The median time between hospitalization and interview was 14 months. We developed prediction models to assess the probability of risk factor control at interview using data from the time of hospitalization: (i) baseline models including 35 variables on patients' demographic, clinical, and socio-economic characteristics and (ii) extended models additionally considering nine variables on large-area residential characteristics. We calculated and internally validated c-indices to assess the discriminative ability of prediction models. Baseline models showed good discrimination with c-indices of 0.69, 0.70, and 0.76 for blood pressure control, cholesterol control, and smoking cessation, respectively. Extended models for blood pressure, cholesterol, and smoking yielded improved c-indices of 0.72, 0.71, and 0.78, respectively. Our results indicate that the probability of risk factor control in CHD patients can be accurately assessed using individual and large-area residential characteristics, allowing for an identification of patients who are less likely to achieve risk factor targets.

The nexus between tourism and regional real growth: dynamic panel threshold testing

This study analyzes the nexus between tourism and regional real growth for European regions at the Nomenclature of territorial units for statistics (NUTS), level 2, for the period 1995-2019. The study uses the dynamic panel threshold model to analyze complex relations between variables. As the dependent variable, we chose real growth rate of regional gross value added at basic prices by NUTS 2 regions. The independent variable is regional arrivals at tourist accommodation, while the control variables are health, household income, and employment at NUTS 2 regional level. The study found the threshold variable for 95% confidence interval. The marginal effects in the low inflation regime are higher compared to marginal effects in the high inflation regime. The study results support tourism-led growth hypothesis, indicating tourism as a one of the main drivers of regional growth. This research contributes to rare literature in application of dynamic panel threshold model in tourism. As an implication, this study can be used as a methodological approach to analyze the impact of different variables (not only tourism, but also innovations, technology, well-being, etc.) on regional growth, especially in countries with high regional differences, such as the Commonwealth of Independent States (CIS), Latin America, etc.