Vaccination associated with gross domestic product and fewer deaths in countries and regions: A verification study.
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ABSTRACT:
SUBMITTER: Wang LY
PROVIDER: S-EPMC8797536 | biostudies-literature |
REPOSITORIES: biostudies-literature
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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.
| S-EPMC7522281 | biostudies-literature
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.
| S-EPMC4224990 | biostudies-literature
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.
| S-EPMC305357 | biostudies-literature
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.
| S-EPMC8759097 | biostudies-literature
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).
| S-EPMC5800392 | biostudies-literature
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.
| S-EPMC5524352 | biostudies-literature
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.
| S-EPMC8697883 | biostudies-literature
Project description:"Labelled drug-related public expenditure" is the direct expenditure explicitly labelled as related to illicit drugs by the general government of the state. As part of the reporting exercise corresponding to 2005, the European Monitoring Centre for Drugs and Drug Addiction's network of national focal points set up in the 27 European Union (EU) Member States, Norway, and the candidates countries to the EU, were requested to identify labelled drug-related public expenditure, at the country level. This was reported by 10 countries categorised according to the functions of government, amounting to a total of EUR 2.17 billion. Overall, the highest proportion of this total came within the government functions of Health (66%), and Public Order and Safety (POS) (20%). By country, the average share of GDP was 0.023% for Health, and 0.013% for POS. However, these shares varied considerably across countries, ranging from 0.00033% in Slovakia, up to 0.053% of GDP in Ireland in the case of Health, and from 0.003% in Portugal, to 0.02% in the UK, in the case of POS; almost a 161-fold difference between the highest and the lowest countries for Health, and a 6-fold difference for POS. Why do Ireland and the UK spend so much in Health and POS, or Slovakia and Portugal so little, in GDP terms? To respond to this question and to make a comprehensive assessment of drug-related public expenditure across countries, this study compared Health and POS spending and GDP in the 10 reporting countries. Results found suggest GDP to be a major determinant of the Health and POS drug-related public expenditures of a country. Labelled drug-related public expenditure showed a positive association with the GDP across the countries considered: r = 0.81 in the case of Health, and r = 0.91 for POS. The percentage change in Health and POS expenditures due to a one percent increase in GDP (the income elasticity of demand) was estimated to be 1.78% and 1.23% respectively. Being highly income elastic, Health and POS expenditures can be considered luxury goods; as a nation becomes wealthier it openly spends proportionately more on drug-related health and public order and safety interventions.
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Project description:PurposeThe impacts of high blood eosinophil count (HBEC) at admission for COPD exacerbation on posthospitalization outcomes are still unclear. Previous studies have focused on its associations with first readmission rates; yet, its impacts on longitudinal outcomes such as subsequent readmissions still have to be explored. The main objective of this study is to investigate outcomes associated with HBEC following a first hospitalization for COPD exacerbation.Patients and methodsThis is an observational cohort study design. We retrospectively analyzed data of patients with a first hospitalization within 5 years for COPD exacerbation between April 2006 and March 2013. Patients were stratified into the HBEC group if the blood eosinophil count at admission was ?200 cells/µL and/or ?2% of the total white blood cells. With information on exact dates of subsequent hospitalizations and death, we modeled readmissions and death as states in a multi-state Markov model and estimated transition probabilities to the next states. Sensitivity analyses were performed by varying thresholds for the definition of HBEC (?300 cells/µL and/or ?3%).ResultsA total of 479 patients were included, of which 173 had HBEC. The transition probabilities for a first readmission was 74% (95% CI, 66%-83%) for patients with HBEC vs 70% (95% CI, 63%-77%) for patients with normal blood eosinophil count (NBEC). The transition probabilities for a second readmission were 91% (95% CI, 84%-100%) for HBEC patients in contrast with 83% (95% CI, 74%-92%) for NBEC patients. Meanwhile, transition probability for death was lower in patients with HBEC. The differences enlarged in sensitivity analyses with higher cutoff.ConclusionGreater blood eosinophil cell counts during a first hospitalization for COPD predict increased susceptibility to up to two readmissions. These patients may however have a lower risk of death.
| S-EPMC6363487 | biostudies-literature
Project description:The surveillance of infectious diseases is of great importance for disease control and prevention, and more attention should be paid to the Class B notifiable diseases in China. Meanwhile, according to the International Monetary Fund (IMF), the annual growth of Chinese gross domestic product (GDP) would decelerate below 7% after many years of soaring. Under such circumstances, this study aimed to answer what will happen to the incidence rates of infectious diseases in China if Chinese GDP growth remained below 7% in the next five years. Firstly, time plots and cross-correlation matrices were presented to illustrate the characteristics of data. Then, the multivariate time series (MTS) models were proposed to explore the dynamic relationship between incidence rates and GDP. Three kinds of MTS models, i.e., vector auto-regressive (VAR) model for original series, VAR model for differenced series and error-correction model (ECM), were considered in this study. The rank of error-correction term was taken as an indicator for model selection. Finally, our results suggested that four kinds of infectious diseases (epidemic hemorrhagic fever, pertussis, scarlet fever and syphilis) might need attention in China because their incidence rates have increased since the year 2010.
| S-EPMC5515987 | biostudies-literature