Project description:Background: Dynamics of health care has changed over time along with development of the countries themselves. The aim of the study is to compare macroeconomic and health expenditure indicators of interest, such as total health expenditure (THE) as percentage of global domestic product, global domestic product per capita in US$, and private households' out-of-pocket payments of Balkan and Eastern European countries on health, as well as to assess their progress over the observed period. Methods: This research report represents a descriptive data analysis of indicators extracted from the European Health for All database. The data were analyzed using a linear trend and regression analysis to estimate the timeline changes. Results: Greece and Slovenia have the largest median values of global domestic product per capita throughout the whole period, and the largest increment trend was in Lithuania. Median value in out-of-pocket payment of THE was the highest in Albania and Ukraine, while the largest decrease in trend was noticed in Albania and Bosnia and Herzegovina. Bosnia and Herzegovina and Greece had the largest median value of THE as percentage of Gross Domestic Product (GDP) in the observed period, while regression trend analysis showed that Serbia had the largest increase. Most of the countries showed a significant correlation between observed indicators. Conclusion: Trends in the economy must be constantly monitored due to the fact that the population is aging and non-communicable diseases are multiplying, which requires innovations in medical treatment and pharmaceutical development.
Project description:BACKGROUND: The 5000 randomised controlled trials (RCTs) in the Cochrane Schizophrenia Group's database affords an opportunity to research for variables related to the differences between nations of their output of schizophrenia trials. METHODS: Ecological study--investigating the relationship between four economic/demographic variables and number of schizophrenia RCTs per country. The variable with closest correlation was used to predict the expected number of studies. RESULTS: GDP closely correlated with schizophrenia trial output, with 76% of the total variation about the Y explained by the regression line (r = 0.87, 95% CI 0.79 to 0.92, r2 = 0.76). Many countries have a strong tradition of schizophrenia trials, exceeding their predicted output. All nations with no identified trial output had GDPs that predicted zero trial activity. Several nations with relatively small GDPs are, nevertheless, highly productive of trials. Some wealthy countries seem either not to have produced the expected number of randomised trials or not to have disseminated them to the English-speaking world. CONCLUSIONS: This hypothesis-generating study could not investigate causal relationships, but suggests, that for those seeking all relevant studies, expending effort searching the scientific literature of Germany, Italy, France, Brazil and Japan may be a good investment.
Project description:Maximizing science achievement is a critical target of educational policy and has important implications for national and international economic and technological competitiveness. Previous research has identified both science interest and socioeconomic status (SES) as robust predictors of science achievement, but little research has examined their joint effects. In a data set drawn from approximately 400,000 high school students from 57 countries, we documented large Science Interest × SES and Science Interest × Per Capita Gross Domestic Product (GDP) interactions in the prediction of science achievement. Student interest in science is a substantially stronger predictor of science achievement in higher socioeconomic contexts and in higher-GDP nations. Our results are consistent with the hypothesis that in higher-opportunity contexts, motivational factors play larger roles in learning and achievement. They add to the growing body of evidence indicating that substantial cross-national differences in psychological effect sizes are not simply a logical possibility but, in many cases, an empirical reality.
Project description:BackgroundThe spread of COVID-19 depends on a lot of social and economic factors.The aimto study the influence of country's gross domestic product, population prevalence of overweight/ obesity, NCD mortality, and vaccination on COVID-19 morbidity and mortality rates.MethodsA cross-sectional study with two phases: correlation-regression interrelations in 1) all world countries; 2) all world non-island countries. The study includes the following data from 218 world countries: COVID-19 morbidity/mortality rates, GDP per capita, the prevalence of overweight/ obesity, NCD mortality among adults (both sexes), people fully vaccinated against COVID-19.ResultsAn average percentage of the prevalence of overweight among adults in world countries by 2019 was 47.31 ± 15.99%, obesity 18.34 ± 9.64%, while the prevalence by 2016 were 39% and 13%, respectively. Overweight and obesity among adults during three years grew by 21.2% and 40.8%, respectively. Data from the world countries provide significant correlations (p < 0.0001) between COVID-19 morbidity, and: GDP (r = 0.517), overweight (r = 0.54), obesity (r = 0.528), NCD mortality (r = 0.537); COVID-19 mortality, and: GDP (r = 0.344), overweight (r = 0.514), obesity (r = 0.489), NCD mortality (r = 0.611); GDP, and: overweight (r = 0.507), obesity (r = 0.523), NCD mortality (r = 0.35), fully vaccinated people (r = 0.754). An increase in fully vaccinated people, from 3% to 30% of world population, decreases new confirmed COVID-19 cases, although the dependence was not significant (p = 0.07). Data from non-island world countries provides more highly significant correlations (p < 0.0001) between COVID-19 morbidity, and: GDP (r = 0.616), overweight (r = 0.581), obesity (r = 0.583); COVID-19 mortality, and: GDP (r = 0.43), overweight (r = 0.556), obesity (r = 0.539); GDP, and: overweight (r = 0.601), obesity (r = 0.633). The differences of correlation coefficients between data of 176 world countries and data of 143 world non-island countries were not significant (Z-scores<1.29; p > 0.05).ConclusionThe study provides evidence of a significant impact of overweight/obesity prevalence on the increase in COVID-19 morbidity/mortality. Countries with higher GDP have a high overweight/obesity prevalence and possibility to get vaccinated.
Project description:BackgroundNew data on COVID-19 may influence the stringency of containment policies, but these potential effect are not understood. We aimed to understand the associations of new COVID-19 cases and deaths with policy stringency globally and regionally.MethodsWe modelled the marginal effects of new COVID-19 cases and deaths on policy stringency (scored 0-100) in 175 countries and territories, adjusting for gross domestic product (GDP) per capita and health expenditure (% of GDP), and public expenditure on health. The time periods examined were March to August 2020, September 2020 to February 2021, and March to August 2021.ResultsPolicy response to new cases and deaths was faster and more stringent early in the COVID-19 pandemic (March to August 2020) compared to subsequent periods. New deaths were more strongly associated with stringent policies than new cases. In an average week, one new death per 100 000 people was associated with a stringency increase of 2.1 units in the March to August 2020 period, 1.3 units in the September 2020 to February 2021 period, and 0.7 units in the March to August 2021 period. New deaths in Africa and the Western Pacific were associated with more stringency than in other regions. Higher health expenditure as a percentage of GDP was associated with less stringent policies. Similarly, higher public expenditure on health by governments was mostly associated with less stringency across all three periods. GDP per capita did not have consistent patterns of associations with stringency.ConclusionsThe stringency of COVID-19 policies was more strongly associated with new deaths than new cases. Our findings demonstrate the need for enhanced mortality surveillance to ensure policy alignment during health emergencies. Countries that invest less in health or have a lower public expenditure on health may be inclined to enact more stringent policies. This new empirical understanding of COVID-19 policy drivers can help public health officials anticipate and shape policy responses in future health emergencies.
Project description:An increasing amount of high-resolution global spatial data are available, and used for various assessments. However, key economic and human development indicators are still mainly provided only at national level, and downscaled by users for gridded spatial analyses. Instead, it would be beneficial to adopt data for sub-national administrative units where available, supplemented by national data where necessary. To this end, we present gap-filled multiannual datasets in gridded form for Gross Domestic Product (GDP) and Human Development Index (HDI). To provide a consistent product over time and space, the sub-national data were only used indirectly, scaling the reported national value and thus, remaining representative of the official statistics. This resulted in annual gridded datasets for GDP per capita (PPP), total GDP (PPP), and HDI, for the whole world at 5 arc-min resolution for the 25-year period of 1990-2015. Additionally, total GDP (PPP) is provided with 30 arc-sec resolution for three time steps (1990, 2000, 2015).
Project description:The purpose of this paper is to investigate the application of a generalized dynamic factor model (GDFM) based on dynamic principal components analysis to forecasting short-term economic growth in Romania. We have used a generalized principal components approach to estimate a dynamic model based on a dataset comprising 86 economic and non-economic variables that are linked to economic output. The model exploits the dynamic correlations between these variables and uses three common components that account for roughly 72% of the information contained in the original space. We show that it is possible to generate reliable forecasts of quarterly real gross domestic product (GDP) using just the common components while also assessing the contribution of the individual variables to the dynamics of real GDP. In order to assess the relative performance of the GDFM to standard models based on principal components analysis, we have also estimated two Stock-Watson (SW) models that were used to perform the same out-of-sample forecasts as the GDFM. The results indicate significantly better performance of the GDFM compared with the competing SW models, which empirically confirms our expectations that the GDFM produces more accurate forecasts when dealing with large datasets.
Project description:Growing prosperity, but also disease outbreaks, natural disasters, and consumer preferences are changing global meat consumption. We investigated the 2000-2019 trends in 35 countries monitored by the Food and Agriculture Organization and the Organisation for Economic Co-operation and Development. We also tested relationships with Gross Domestic Product (GDP). Several countries appeared to be reaching peak consumption of some meats, and three (New Zealand, Canada, and Switzerland) have reached this. Poultry consumption increased over time in most countries, and beef and mutton/lamb consumption decreased in many. Using cluster analysis, we divided countries into two clusters: one in which increases in GDP per capita matched increases in meat consumption; and a second one of nine countries, for which there was no association between per capita change in GDP and meat consumption. There was evidence of a tipping point around USD 40,000 of GDP per capita, after which increases in economic well-being do not lead to increased meat consumption.
Project description:This study aimed to explore the association between the GDP of various countries and the progress of COVID-19 vaccinations; to explore how the global pattern holds in the continents, and investigate the spatial distribution pattern of COVID-19 vaccination progress for all countries. We have used consolidated data on COVID-19 vaccination and GDP from Our World in Data, an open-access data source. Data analysis and visualization were performed in R-Studio. There was a strong linear association between per capita income and the proportion of people vaccinated in countries with populations of one million or more. GDP per capita accounts for a 50% variation in the vaccination rate across the nations. Our assessments revealed that the global pattern holds in every continent. Rich European and North-American countries are most protected against COVID-19. Less developed African countries barely initiated a vaccination program. There is a significant disparity among Asian countries. The security of wealthier nations (vaccinated their citizens) cannot be guaranteed unless adequate vaccination covers the less affluent countries. Therefore, the global community should undertake initiatives to speed up the COVID-19 vaccination program in all countries of the world, irrespective of their wealth.