Dataset Information

Datasets on the GRP of Russian regions, GRP sectoral composition and growth rates in 2013-2018.

ABSTRACT: This paper presents a comparative analysis of the gross regional products (GRPs) of 85 Russian regions. Statistical methods were used to analyze datasets on regional GRP, its sectoral composition and growth rates. Many datasets have been computed for the first time, including those of gross value added per capita and per employee. The work reviews a range of evidence on the contribution of the production of goods and market and non-market services to regional GRPs. The production of goods was further analyzed by economic sectors for each region. The data used in computations were provided by the Russian Federal State Statistics Service (ROSSTAT). The authors built a typology of Russian regions based on GRP figures, GRP sectoral composition and growth rates. The data obtained make it possible to determine a set of indicators of the geographical distribution of Russia's economy and its growth rates. The findings are presented in the form of tables, maps and graphic materials (three tables, three charts and 11 cartographic maps), displaying quantitative measures of the economic performance of Russian regions .

SUBMITTER: Fedorov GM

PROVIDER: S-EPMC7718172 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Datasets on the GRP of Russian regions, GRP sectoral composition and growth rates in 2013-2018.

Fedorov Gennady M GM Kuznetsova Tatyana Yu TY

Data in brief 20201125

This paper presents a comparative analysis of the gross regional products (GRPs) of 85 Russian regions. Statistical methods were used to analyze datasets on regional GRP, its sectoral composition and growth rates. Many datasets have been computed for the first time, including those of gross value added per capita and per employee. The work reviews a range of evidence on the contribution of the production of goods and market and non-market services to regional GRPs. The production of goods was fu ...[more]

PMID: 33304954

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Project description:Background and aimsDespite increases in opioid prescribing and related morbidity and mortality, few studies have comprehensively documented harms across opioid types. We examined a population-wide indicator of extramedical pharmaceutical opioid-related harm to determine if the supply-adjusted rates of ambulance presentations, the severity of presentations or other attendance characteristics differed by opioid type.DesignRetrospective observational study of coded ambulance patient care records related to extramedical pharmaceutical opioid use, January 2013 to September 2018.SettingAustralia CASES: Primary analyses used Victorian data (n = 9823), with available data from other Australian jurisdictions (n = 4338) used to determine generalizability.MeasurementsWe calculated supply-adjusted rates of attendances using Poisson regression, and used multinomial logistic regression to compare demographic, presentation severity, mental health, substance use and other characteristics of attendances associated with seven pharmaceutical opioids.FindingsIn Victoria, the highest rates of attendance [per 100?000 oral morphine equivalent mg (OME)] were for codeine (0.273/100?000) and oxycodone (0.113/100?000). The lowest rates were for fentanyl (0.019/100?000) and tapentadol (0.005/100?000). Oxycodone-naloxone rates (0.031/100 000) were lower than for oxycodone as a single ingredient (0.113/100?000). Fentanyl-related attendances were associated with the most severe characteristics, most likely to be an accidental overdose, most likely to have naloxone administered and least likely to be transferred to hospital. In contrast, codeine-related attendances were more likely to involve suicidal thoughts/behaviours, younger females and be transported to hospital. Supply-adjusted attendance rates for individual opioids were stable over time. Victorian states were broadly consistent with non-Victorian states.ConclusionsIn Australia, rates and characteristics of opioid-related harm vary by opioid type. Supply-adjusted ambulance attendance rates appear to be both stable over time and unaffected by large changes in supply.

Project description:ImportanceRecent data on prevalence, awareness, treatment, and risk factors of diabetes in China is necessary for interventional efforts.ObjectiveTo estimate trends in prevalence, awareness, treatment, and risk factors of diabetes in China based on national data.Design, setting, and participantsCross-sectional nationally representative survey data collected in adults aged 18 years or older in mainland China from 170 287 participants in the 2013-2014 years and 173 642 participants in the 2018-2019 years.ExposuresFasting plasma glucose and hemoglobin A1c levels were measured for all participants. A 2-hour oral glucose tolerance test was conducted for all participants without diagnosed diabetes.Main outcomes and measuresPrimary outcomes were diabetes and prediabetes defined according to American Diabetes Association criteria. Secondary outcomes were awareness, treatment, and control of diabetes and prevalence of risk factors. A hemoglobin A1c level of less than 7.0% (53 mmol/mol) among treated patients with diabetes was considered adequate glycemic control.ResultsIn 2013, the median age was 55.8 years (IQR, 46.4-65.2 years) and the weighted proportion of women was 50.0%; in 2018, the median age was 51.3 years (IQR, 42.1-61.6 years), and the weighted proportion of women was 49.5%. The estimated prevalence of diabetes increased from 10.9% (95% CI, 10.4%-11.5%) in 2013 to 12.4% (95% CI, 11.8%-13.0%) in 2018 (P < .001). The estimated prevalence of prediabetes was 35.7% (95% CI, 34.2%-37.3%) in 2013 and 38.1% (95% CI, 36.4%-39.7%) in 2018 (P = .07). In 2018, among adults with diabetes, 36.7% (95% CI, 34.7%-38.6%) reported being aware of their condition, and 32.9% (95% CI, 30.9%-34.8%) reported being treated; 50.1% (95% CI, 47.5%-52.6%) of patients receiving treatment were controlled adequately. These rates did not change significantly from 2013. From 2013 to 2018, low physical activity, high intake of red meat, overweight, and obesity significantly increased in prevalence.Conclusions and relevanceIn this survey study, the estimated diabetes prevalence was high and increased from 2013 to 2018. There was no significant improvement in the estimated prevalence of adequate treatment.

Project description:This article presents a performance dataset of 93 Russian universities, collected from 2015 to 2018 and evaluated according to 24 indicators. These data were gathered from materials, published in the process of monitoring the effectiveness of higher education institutions by the Ministry of Science and Higher Education of the Russian Federation, Web of Science (citation-based research analytics tool InCites) and Scopus (citation-based research analytics tool SciVal) databases, and information from international ranking agencies QS, THE, ARWU. The dataset comprises the assessments of university performances according to the most important indicators used in socio-economic studies of comparative analysis of higher education system development levels in different countries: educational, scientific and research, international, financial and economic performance and international public recognition (university positions in leading international rankings). Evaluated universities are grouped pursuant to their missions: Federal Universities (FU), National Research Universities (NRU), Flagship Universities (FlU) and university-participants of the Russian Academic Excellence Project (Project 5-100). The indicators for the comparative analysis are aggregated by the type of activities and analyzed based on the calculation of median values and Displaced Ideal Method. The dataset can be helpful to researchers, university administration, specialists of higher education system, etc. Data processing can be executed using data mining methods, machine learning, and pattern analysis for the development of intellectual structures, applicable for university performance assessment in different educational systems. Presented data allows us to assert that the implementation of targeted support for leading Russian universities has a positive impact on the development of Russian higher education increasing its role on the international academic arena. Leading national research university-participants of the Project 5-100 had the greatest influence on increasing the competitiveness of Russian education in the world.

Dataset Information

Datasets on the GRP of Russian regions, GRP sectoral composition and growth rates in 2013-2018.

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Datasets on the GRP of Russian regions, GRP sectoral composition and growth rates in 2013-2018.

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