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Israel

  • Präsident:Reuven Rivlin
  • Premierminister:Benjamin Netanyahu
  • Hauptstadt:Jerusalem
  • Sprachen:Hebrew (official), Arabic (used officially for Arab minority), English (most commonly used foreign language)
  • Regierung
  • Nationales Amt für Statistik
  • Bevölkerung, Personen:8.712.400 (2017)
  • Fläche, km2:21.640 (2017)
  • BIP pro Kopf, US$:40.270 (2017)
  • BIP, Milliarden aktuelle US $:350,9 (2017)
  • Gini-Koeffizient:41,4 (2012)
  • Ease-of-Doing-Business-Rang:54 (2017)
Alle Datensätze:  A C D E F G H I L M N O P R S T U W
  • A
    • April 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2019
      Datensatz auswählen
      Source: UNECE Statistical Database, compiled from national and international (Eurostat, UN Statistics Division Demographic Yearbook, WHO European health for all database and UNICEF TransMONEE) official sources. Definition: Adolescent fertility covers live births to women aged 15-19. A live birth is the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, which after such separation breathes or shows any other evidence of life such as beating of the heart, pulsation of the umbilical cord or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. The adolescent fertility rate is the number of live births to women aged 15-19 per 1000 women aged 15-19. General note: Data on live births come from registers, unless otherwise specified. The adolescent fertility rate is computed by UNECE secretariat. .. - data not available Country: Albania Data refer to age group 0-19. Country: Armenia Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Azerbaijan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Belarus Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Bosnia and Herzegovina 1995 : data refer to 1996. Country: Canada Data include Canadian residents temporarily in the United States, but exclude United States residents temporarily in Canada. Country: Cyprus Data cover only the area controlled by the Republic of Cyprus. Country: Estonia Data refer to age group 0-19. Country: Finland Data include nationals temporarily outside the country. Country: Georgia Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. From 1995 : data do not cover Abkhazia and South Ossetia (Tshinvali). 1980-2003 : data refer to age group 15-20. Country: Germany 1980-1990 : data cover only West Germany (Federal Republic of Germany). From 1995 : data refer to reunified Germany, i.e. include the ex-German Democratic Republic (East Germany). Country: Ireland Data are tabulated by date of registration (rather than occurrence) and refer to births registered within one year of occurrence. 2005-2006 : provisional data. Country: Israel Data cover East Jerusalem and Israeli residents in certain other territories under occupation by Israeli military forces since June 1967. 1980 : data refer to age group 0-19. Country: Kazakhstan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Kyrgyzstan 1980-2003 : data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Country: Latvia Data refer to age group 0-19. Country: Malta Data refer to age group 0-19. Country: Netherlands Data refer to age group 0-19. Country: Norway Age classification is based on year of birth of mother rather than the exact age of mother at birth of child. Country: Poland 1980 : data refer to age group 0-19. Country: Portugal Data refer to resident mothers. Country: Russian Federation Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Serbia Data do not cover Kosovo and Metohija. Data are tabulated by date of registration (rather than occurrence). Country: Turkey 1980-2000: data source is population censuses. From 2001: data are from administrative source. Country: Turkmenistan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data refer to age group 0-19. Country: Ukraine Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. 2000 : data refer to 1998. 1990 : data refer to age group 0-19. Country: United Kingdom Data are tabulated by date of occurrence for England and Wales and by date of registration for Northern Ireland and Scotland. Country: United States 2000 : data refer to 1999. Country: Uzbekistan Data refer to age group 18-19.
  • C
    • Dezember 2018
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 02 Januar, 2019
      Datensatz auswählen
      Data cited: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2016 (GBD 2016) Cancer Incidence, Mortality, Years of Life Lost, Years Lived with Disability, and Disability-Adjusted Life Years 1990-2016. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2018.   The Global Burden of Disease Study 2016 (GBD 2016), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors for 195 countries and territories and at the subnational level for a subset of countries. Estimates for deaths, disability-adjusted life years (DALYs), years lived with disability (YLDs), years of life lost (YLLs), prevalence, and incidence for 29 cancer groups by age and sex for 1990-2016 are available from the GBD Results Tool. Files available in this record are the web tables published in JAMA Oncology in June 2018 in "Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-years for 29 Cancer Groups, 1990 to 2016."
    • Mai 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 21 Mai, 2019
      Datensatz auswählen
      Source: UNECE Statistical Database, compiled from national and international official sources. Area data exclude overseas departments and territories. For population footnotes click here. For life expectancy footnotes click here. For fertility rate footnotes click here. For population by marital status footnotes click here. For female members of parliament footnotes click here. For female government ministers footnotes click here. For female central bank board members footnotes click here. For female tertiary students footnotes click here. For economic activity rate footnotes click here. For gender pay gap footnotes click here. For employment growth rate footnotes click here. For unemployment rate footnotes click here. For youth unemployment rate footnotes click here. For employment by economic sector footnotes click here. For economic indicator footnotes click here. For road accident footnotes click here. For total length of motorways footnotes click here. For total length of railway lines footnotes click here. Key indicators in maps .. - data not availableIndicatorGDP in agriculture (ISIC4 A): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in industry (incl. construction) (ISIC4 B-F): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP in services (ISIC4 G-U): output approach, index, 2010=100If the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in agriculture etc. (ISIC4 A), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in industry etc. (ISIC4 B-E), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in construction (ISIC4 F), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in trade, hospitality, transport and communication (ISIC4 G-J), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in finance and business services (ISIC4 K-N), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in public administration, education and health (ISIC4 O-Q), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.GDP: in other service activities (ISIC4 R-U), output approach, per cent share of GVAIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in agriculture, hunting, forestry and fishing (ISIC Rev. 4 A), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in industry and energy (ISIC Rev. 4 B-E), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in construction (ISIC Rev. 4 F), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in trade, hotels, restaurants, transport and communications (ISIC Rev. 4 G-J), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in finance, real estate and business services (ISIC Rev. 4 K-N), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in public administration, education and health (ISIC Rev. 4 O-Q), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.Employment in other service activities (ISIC Rev. 4 R-U), share of total employmentIf the country has not yet provided data according to ISIC 4, you may find the data according to ISIC 3.1 in more detailed tables under the Economy section of the database.
    • April 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 21 Mai, 2018
      Datensatz auswählen
      Note: CPA data for 2018 and 2019 are projections from the 2016 Survey on Forward Spending Plans. Country Programmable Aid (CPA), outlined in our Development Brief  and also known as “core” aid, is the portion of aid donors programme for individual countries, and over which partner countries could have a significant say. CPA is much closer than ODA to capturing the flows of aid that goes to the partner country, and has been proven in several studies to be a good proxy of aid recorded at country level. CPA was developed in 2007 in close collaboration with DAC members. It is derived on the basis of DAC statistics and was retroactively calculated from 2000 onwards
    • April 2019
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 30 April, 2019
      Datensatz auswählen
      The country statistical profiles provide a broad selection of indicators, illustrating the demographic, economic, environmental and social developments, for all OECD members. The dataset also covers the five key partner economies with which the OECD has developed an enhanced engagement program with (Brazil, China, India, Indonesia and South Africa) ,accession countries (Colombia, Costa Rica and Lithuania) , Peru and the Russian Federation. The user can easily compare indicators across all countries. Total fertility rates - Unit of measure used: Number of children born to women aged 15 to 49
  • D
    • Mai 2018
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 21 November, 2018
      Datensatz auswählen
      .. - data not available Source: UNECE Statistical Division Database, compiled from national and international (WHO European health for all database) official sources. Definitions: The (age-) standardized death rate (SDR) is a weighted average of age-specific mortality rates per 100 000 population. The weighting factor is the age distribution of a standard reference population. The standard reference population used is the European standard population as defined by the World Health Organisation (WHO). As method for standardisation, the direct method is applied. As most causes of death vary significantly with age and sex, the use of standardised death rates improves comparability over time and between countries. Death refers to the permanent disappearance of all evidence of life at any time after a live birth has taken place (post-natal cessation of vital functions without capability of resuscitation). This definition therefore excludes foetal deaths. Causes of death (CoD) are all diseases, morbid conditions or injuries that either resulted in or contributed to death, and the circumstances of the accident or violence that produced any such injuries. Symptoms or modes of dying, such as heart failure or asthenia, are not considered to be causes of death for vital statistics purposes. General note:: Diseases and external causes of death are coded differently in different versions of the International Classification of Diseases (ICD). For many diseases it is not possible to identify codes in different classification systems that would correspond precisely to the same disease or groups of diseases. Often the change in the trend of a certain cause-specific mortality rate may be the result of a changing ICD version or national death certification and coding practices, rather than an actual change in the mortality. It should be noted that mortality rates for some countries may be biased due to the under-registration of death cases. The basic principle of selection of the 17 CoD for presentation in the UNECE Gender Database is to include one main SDR for each of the ICD chapters and also to focus on some of the leading CoD across the European Region and some specific causes with high gender differences. ICD versionCountries9.3 - ICD-9 3-digit codes Albania, The former Yugoslav Republic of Macedonia 9.4 - ICD-9 4-digit or mixture of 3- and 4-digit codesGreece9.5 - ICD-9 BTL codes (in most countries actually original ICD-9 codes were used but the data later were converted by WHO into BTL codes) Bosnia and Herzegovina10.1 - ICD-10 mortality tabulation condensed list No1 (103 causes) Armenia, Azerbaijan, Belarus, Kazakhstan, Russian Federation, Ukraine10.3 - ICD-10 3-digit codes Belgium, Bulgaria, Estonia, Georgia, Latvia, Montenegro, Serbia, Slovakia, Slovenia, Uzbekistan10.4 - ICD-10 4-digit or mixture of 3- and 4-digit codes Austria, Canada, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Hungary, Iceland, Ireland, Israel, Italy, Kyrgyzstan, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Republic of Moldova, Romania, Spain, Sweden, Switzerland, United Kingdom, United States 1.75 - Special tabulation list of 175 causes used in some ex-USSR countries Tajikistan, Turkmenistan Link to International Classification of Diseases 10th Revision Country: Canada Data on accidents include sequelae of transport and other accidents. Data on transport accidents include sequelae of transport accidents. Data on suicide and intentional self-harm include sequelae of intentional self-harm. Country: United States Data on accidents include sequelae of transport and other accidents. Data on transport accidents include sequelae of transport accidents.
    • April 2018
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 03 Mai, 2018
      Datensatz auswählen
      Financing Global Health 2016 is the eighth edition of IHME’s annual series on global health spending and health financing. In addition to describing the trends in development assistance for health (DAH), this year’s report features an expanded discussion of domestic spending across low-, middle-, and high-income countries to describe the context in which DAH operates, identify health financing gaps, and support the pursuit of universal health coverage. Also new in Financing Global Health this year are detailed data for the funding of specific program areas within DAH for malaria and more thorough analysis of DAH for health system strengthening. This adds to the existing detailed tracking of DAH by program area for HIV/AIDS, maternal, newborn, and child health, and non-communicable diseases (NCDs). The coverage of domestic health spending builds on data and analyses presented in two papers published this year: “Global Burden of Disease Financing Global Health Collaborator Network. Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries,” and “Global Burden of Disease Financing Global Health Collaborator Network. Future and potential spending on health 2015–2040 by government, prepaid private, out-of-pocket, and donor financing for 184 countries.” Both analyses were published in The Lancet in April 2017. More information about these data and methods are found in the online methods annex.
    • Dezember 2008
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Peter Speyer
      Datensatz auswählen
      IHME research, published in the Lancet in 2008. The study, Tracking progress towards universal childhood immunizations and the impact of global initiatives, provides estimates with confidence intervals of the coverage of three-dose diphtheria, tetanus, and pertussis (DTP3) vaccination. The estimates take into account all publicly available data, including data from routine reporting systems and nationally representative surveys.
    • Dezember 2013
      Quelle: Durex
      Hochgeladen von: Knoema
      Zugriff am: 16 Dezember, 2013
      Datensatz auswählen
      Durex Sex Survey
  • E
  • F
    • September 2017
      Quelle: National Institute for Health and Welfare
      Hochgeladen von: Knoema
      Zugriff am: 16 Februar, 2018
      Datensatz auswählen
      In 2008, National Institute for Health and Welfare brought into use a new national system of accounting health expenditure and financing that is based on the OECD System of Health Accounts (SHA). The SHA system gathers data by function, provider and source of finance.
  • G
    • September 2017
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 08 November, 2017
      Datensatz auswählen
      The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. As part of this study, estimates for daily smoking prevalence and smoking-attributable mortality and disease burden, as measured by disability-adjusted life years (DALYs), were produced by sex, age group, and year for 195 countries and territories. Estimates for deaths and DALYs (1990-2015) are available from the GBD Results Tool. Files available in this record include daily smoking prevalence (1980-2015) and annualized rate of change estimates. Study results were published in The Lancet in April 2017 in "Smoking prevalence and attributable disease burden in 195 countries and territories, 1990–2015: a systematic analysis from the Global Burden of Disease Study 2015." Date ranges have been considered as follows: 1990-2015 as 1990 1990-2005 as 2005 2005-2015 as 2015
    • September 2017
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 27 Oktober, 2017
      Datensatz auswählen
      The Global Burden of Disease Study 2015 (GBD 2015), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors at the global, regional, national, territorial, and, for a subset of countries, subnational level. This dataset measures progress towards the Millennium Development Goal 5 (MDG 5) target of a 75% reduction in the maternal mortality ratio between 1990 and 2015. Maternal mortality ratio estimates for 21 regions, 195 countries and territories and 4 United Kingdom subnational units for 1990-2015 (quinquennial) are available by age and cause from the GBD Results Tool. Files available in this record include tables published in The Lancet in October 2016 in "Global, regional, and national levels of maternal mortality, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015.
    • April 2019
      Quelle: World Bank
      Hochgeladen von: Knoema
      Zugriff am: 01 Mai, 2019
      Datensatz auswählen
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Gender Statistics Publication: https://datacatalog.worldbank.org/dataset/gender-statistics License: http://creativecommons.org/licenses/by/4.0/
    • November 2018
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 30 November, 2018
      Datensatz auswählen
      Research by the Global Burden of Disease Health Financing Collaborator Network produced retrospective national health spending estimates for 1995-2016 for 184 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. National health spending by source, including development assistance for health, was estimated based on a diverse set of data, including program reports, budget data, national estimates, and 964 National Health Accounts. The resulting estimates were used to help produce forecasted health spending estimates for 2015-2040. Results of the study were published in The Lancet in April 2017 in "Evolution and patterns of global health financing 1995–2016: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries."
    • November 2018
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 23 November, 2018
      Datensatz auswählen
      Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2016-2040 for 188 countries. The estimates cover total health spending, and health spending disaggregated by source into government spending, out-of-pocket, prepaid private, and development assistance for health. GDP and all-sector government spending were extracted for 1980–2015 and used with retrospective health spending estimates for 1995-2015 to forecast GDP, all-sector government spending, and health spending through 2040. Results of the study were published in The Lancet in April 2018 in "Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–2040."
    • März 2019
      Quelle: World Health Organization
      Hochgeladen von: Knoema
      Zugriff am: 18 März, 2019
      Datensatz auswählen
      The GHO data provides access to indicators on priority health topics including mortality and burden of diseases, the Millennium Development Goals (child nutrition, child health, maternal and reproductive health, immunization, HIV/AIDS, tuberculosis, malaria, neglected diseases, water and sanitation), non communicable diseases and risk factors, epidemic-prone diseases, health systems, environmental health, violence and injuries, equity among others.
    • Mai 2018
      Quelle: World Health Organization
      Hochgeladen von: Knoema
      Zugriff am: 12 Dezember, 2018
      Datensatz auswählen
      Global Trends in Prevalence of Tobacco Smoking 2000-2025
    • Dezember 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 03 Dezember, 2018
      Datensatz auswählen
  • H
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 September, 2018
      Datensatz auswählen
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 20 September, 2018
      Datensatz auswählen
    • November 2017
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 13 November, 2017
      Datensatz auswählen
      Cancer follow up has been given for the range of 5 years. The highest range has been considered as for this period, for example 1995-2000 is considered as 2000.
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 14 August, 2018
      Datensatz auswählen
      OECD Health Data 2016 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 16 Juli, 2018
      Datensatz auswählen
      OECD Health Data 2017 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.B1:B4
    • Mai 2019
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 13 Mai, 2019
      Datensatz auswählen
      OECD Health Data 2017 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 Juli, 2018
      Datensatz auswählen
      OECD Health Data 2015 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse healthcare systems.
    • Juni 2010
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Datensatz auswählen
      OECD Health Data 2010 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • April 2019
      Quelle: World Bank
      Hochgeladen von: Knoema
      Zugriff am: 01 Mai, 2019
      Datensatz auswählen
      Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 August, 2018
      Datensatz auswählen
      OECD Health Data 2016 offers the most comprehensive source of comparable statistics on health and health systems across OECD countries. It is an essential tool for health researchers and policy advisors in governments, the private sector and the academic community, to carry out comparative analyses and draw lessons from international comparisons of diverse health care systems.
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 23 Juli, 2018
      Datensatz auswählen
    • Dezember 2018
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 26 Dezember, 2018
      Datensatz auswählen
      Global Burden of Disease Study 2016 (GBD 2016) Healthcare Access and Quality Index Based on Amenable Mortality 1990–2016. Global Burden of Disease Study 2016 (GBD 2016) estimates were used in an analysis of personal healthcare access and quality for 195 countries and territories, as well as selected subnational locations, over time. This dataset includes the following global, regional, national, and selected subnational estimates for 1990-2016: age-standardized risk-standardized death rates from 24 non-cancer causes considered amenable to healthcare; age-standardized mortality-to-incidence ratios for 8 cancers considered amenable to healthcare; and the Healthcare Access and Quality (HAQ) Index and individual scores for each of the 32 causes on a scale of 0 to 100. Code used to produce the estimates is also included. Results were published in The Lancet in May 2018 in "Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016
    • August 2018
      Quelle: United Nations Development Programme
      Hochgeladen von: Knoema
      Zugriff am: 20 Dezember, 2018
      Datensatz auswählen
      The Human Development Index (HDI) is a summary measure of achievements in three key dimensions of human development: a long and healthy life, access to knowledge and a decent standard of living. The HDI is the geometric mean of normalized indices for each of the the three dimensions.
  • I
    • Dezember 2010
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 31 Juli, 2013
      Datensatz auswählen
      IHME research, published online in The Lancet in April 2010, with data from a global assessment of levels and trends in maternal mortality for the years 1980-2008. The study, Maternal mortality for 181 countries, 1980-2008: a systematic analysis of progress towards Millennium Development Goal 5, provides global, regional, and national level estimates of the maternal mortality ratio (MMR - the number of maternal deaths per 100,000 live births) as well as the number of maternal deaths.
    • September 2011
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Datensatz auswählen
      IHME results data from global analysis of maternal mortality for years 1990-2011 published online in The Lancet in September 2011. The study, Progress towards Millennium Development Goals 4 and 5 on maternal and child mortality: an updated systematic analysis, provides global and country level estimates of the maternal mortality ratio (MMR - the number of maternal deaths per 100,000 live births) and the number of maternal deaths.
    • April 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2019
      Datensatz auswählen
      .. - data not available Source: UNECE Statistical Database, compiled from national and international (WHO European health for all database, Eurostat and UNICEF TransMONEE) official sources. Definition: The infant mortality rate is the number of deaths of infants under one year of age per 1000 live births in a given year. Country: Azerbaijan Break in methodlogy (2000): Change in calculation methodology. Country: Cyprus Data cover only government controlled area. Country: Germany From 3 October 1990: data refer to the Federal Republic within its frontiers. Country: Italy Change in definition (1980 - 2011): Data refer to resident or non resident population. Country: Malta From 2001: data include foreign residents. Country: Serbia Break in methodlogy (2005): Change in data processing methodology. Country: Serbia Territorial change (2000 - 2012): Data do not cover Kosovo and Metohija. Country: Tajikistan Additional information (1980 - 2012): Data are from births and deaths register. Country: Ukraine From 2014 data cover the territories under the government control.
  • L
    • April 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2019
      Datensatz auswählen
      Source: UNECE Statistical Database, compiled from national and international (Eurostat, UN Statistics Division Demographic Yearbook, WHO European health for all database and UNICEF TransMONEE) official sources. Definition: Legal abortions refer to legally induced early foetal deaths and do not cover spontaneous abortions (i.e. miscarriages). The abortion rate is defined as the number of abortions per 1000 live births during a given year. General note: Data come from registers, unless otherwise specified. .. - data not available Country: Austria Additional information (1990 - 2012): Data refer to abortions carried out in hospitals. Country: Azerbaijan Data include illegal abortions. Country: Canada 2002-2005 : data do not cover abortions performed on non-Canadian residents. Country: France Data do not cover overseas territories. Country: Georgia From 1995 : data do not cover Abkhazia and South Ossetia (Tshinvali). Country: Israel Data include East Jerusalem and Israeli residents in certain other territories under occupation by Israeli military forces since June 1967. Data refer to applications for abortions and not to actual abortions performed. Country: Italy Incomplete data for the mentioned years and Regions: 1990 (Piemonte), 1995 (Piemonte), 2002 (Campania), 2003 (Campania), 2004 (Sicilia), 2005 (Friuli-Venezia Giulia, Molise, Campania, Sicilia), 2006 (Friuli-Venezia Giulia, Campania, Sicilia), 2007 (Campania). Country: Kyrgyzstan Data include spontaneous abortions (i.e. miscarriages). Country: Netherlands Data refer to abortions performed on women living in the Netherlands. Country: Russian Federation Additional information (1995 - 2012): Data include interruption of pregnancy for the total of 21 weeks. Country: Serbia Data do not cover Kosovo and Metohija. Country: Switzerland Break in methodlogy (2004): A new data collection system took place following the legal changes regarding abortion in 2002. Country: Tajikistan Data include menstrual cycle regulation procedures (also known as mini-abortions) carried out within the first 5 to 6 weeks of a possible pregnancy. Country: United Kingdom Change in definition (1980 - 2012): Data include residents and non-residents. Country: United Kingdom Territorial change (1980 - onwards): Data do not cover Northern Ireland.
    • November 2018
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 21 November, 2018
      Datensatz auswählen
      This indicator is a proxy for rights to social security and health. It represents the percentage of the population without legal health coverage. Coverage includes affiliated members of health insurance or estimation of the population having free access to health care services provided by the State. A higher figure indicates higher percentage of the population without legal health coverage.This is one of five indicators measuring key dimensions of deficits in health care access and coverage. For analytical purposes the full set of indicators should be considered together.
  • M
    • August 2018
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2018
      Datensatz auswählen
      This indicator is a proxy for health system outcomes. It represents the number of maternal deaths per 10 000 live births. A higher figure indicates worse outcomes. This is one of five indicators measuring key dimensions (drivers) of deficits in health care access and coverage. For analytical purposes the full set of indicators should be considered together.
    • März 2019
      Quelle: World Bank
      Hochgeladen von: Knoema
      Zugriff am: 20 März, 2019
      Datensatz auswählen
      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: Millennium Development Goals Publication: https://datacatalog.worldbank.org/dataset/millennium-development-goals License: http://creativecommons.org/licenses/by/4.0/   Relevant indicators drawn from the World Development Indicators, reorganized according to the goals and targets of the Millennium Development Goals (MDGs). The MDGs focus the efforts of the world community on achieving significant, measurable improvements in people's lives by the year 2015: they establish targets and yardsticks for measuring development results. Gender Parity Index (GPI)= Value of indicator for Girls/ Value of indicator for Boys. For e.g GPI=School enrolment for Girls/School enrolment for Boys. A value of less than one indicates differences in favor of boys, whereas a value near one (1) indicates that parity has been more or less achieved. The greater the deviation from 1 greater the disparity is.
  • N
    • Februar 2019
      Quelle: World Health Organization
      Hochgeladen von: Knoema
      Zugriff am: 08 Februar, 2019
      Datensatz auswählen
      National Health Accounts (NHA) provides evidence to monitor trends in health spending for all sectors- public and private, different health care activities, providers, diseases, population groups and regions in a country. It helps in developing nationals
  • O
    • August 2018
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2018
      Datensatz auswählen
      This indicator is a proxy for financial protection in case of ill health. It represents the amount of money paid directly to health care providers in exchange for health goods and services as a percentage of total health expenditure. A higher figure indicates higher percentage of out-of-pocket payments. This is one of five indicators measuring key dimensions of deficits in health care access and coverage. For analytical purposes the full set of indicators should be considered together.
  • P
    • Juni 2018
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 25 Juli, 2018
      Datensatz auswählen
    • März 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 02 April, 2019
      Datensatz auswählen
      Source: UNECE Statistical Database, compiled from national official sources. Definition: Body Mass Index (BMI) is the international standard for measuring underweight, overweight, and obesity and is defined as the weight of a person (in kg) divided by the square of the person’s height (in metres): kg/sqm. Standard BMI categories are: BMI less than 18.5 kg/sqm = underweight. BMI between 25 and 30 kg/sqm = overweight. BMI 30kg/sqm and more = obesity. General note: Percentage .. - data not available Country: Armenia 2005: Data refer to population aged 15-49 and age groups: 20-44 refers to 20-29, 45-64 refers to 30-39 and 65+ refers to 40-49. Country: Austria Break in methodlogy (2006): Data for 2006 come from the Autrian Health Interview Survey, before 2006 from the Labour force Survey ad hoc module on smoking habits. Country: Austria Change in definition (1990): Data refer to population aged 20+. Country: Austria Change in definition (2000): Data refer to population aged 20+ Country: Austria Reference period (1990): Data refer to 1991. Country: Austria Reference period (2000): Data refer to 1999. Country: Belarus Data refer to population aged 16+. Country: Belgium 15-19 age group refers to 18-19 years old Country: Bulgaria Break in methodlogy (2008): 2008 data come from the European Health Interview Survey and 2001 from the Demographic and Health survey. Country: Canada Data exclude institutional residents and full-time members of the Canadian Forces. Country: Canada Data exclude residents of Indian Reserves, Crown Lands and certain remote regions. Country: Croatia Change in definition (2003): Data refer to population aged 18+. Country: Cyprus Data cover only government controlled area. Country: Czechia 1990, 1995 and 2000: data refer to 1993, 1996 and 1999. Country: Denmark Data refer to population aged 16+ and age group 15-19 refers to 16-19. Country: Denmark Data collection mode changed from face-to-face interview to self-administered questionnaires in 2010. Country: Denmark Reference period (1990): Data refer to 1987. Country: Denmark Reference period (1995): Data refer to 1994. Country: Estonia Data refer to population aged 16-64. Country: Estonia Reference period (1995): Data refer to 1996 Country: Finland Data refer to population aged 15-64. Age group 65+ refers to 65-84 year olds. Country: France BMI is calculated on the basis of the declared weight of respondents. Country: France Reference area: 2003, 2014 - Metropolitan France; 2008 - Metropolitan France and overseas departments. Country: Germany Data refer to population aged 18+. 2000: data refer to 1999. Country: Hungary Data refer to population aged 18+. Country: Iceland Data refer to population aged 20-80 except in 2007 and 2012 where data refer to population aged 18-79. Data are not published for the age group 18-24 (15-24) as figures are too small. Country: Ireland Data refer to population aged 18+. Age group 15-19 refers to 18-19. - 2000: data refer to 1998. From 2015, data refer to population aged 15 and over and are measured data. Individuals interviewed in the Health Ireland survey 2015 survey were asked to undertake a physical measurement module. Country: Israel Break in methodlogy (2010): For 2010 data come from the Social Survey while for 2003 data come from the Knowledge, attitude and practice (KAP) Survey. Country: Israel Change in definition (2003): Data refer to population aged 21+. Country: Israel Change in definition (2010): Data refer to population aged 20+. Country: Italy Change in definition (1990 - 2012): Data refer to population aged 18+. Country: Italy Reference period (1995): Data refer to 1994. Country: Italy Reference period (2000): Data refer to 1999/2000. Country: Latvia Data for 2003 - from the Health Interview Survey. Data cover population 15-75 years old.Data for 2004, 2006, 2010 and 2012 - from Health Behaviour Survey among Latvian Adult population. Data cover population 15-64 years old.Data for 2008 and 2014 - from the European Health iInterview Survey (EHIS). Data cover population 15+, age groups: 15-19 refers to 15-24; 20-44 refers to 25-44. Country: Malta Data refer to population aged 18+ residing in private households. 2003: data for age group 15 - 24 are not available due to under-representation. Country: Netherlands Data refer to population aged 20 and over. Overweight: BMI 25 kg/sqm or more. In 2014, interviewing and weighting method was changed, causing a break in the time series. Country: Netherlands Reference period (1980): Data refer to 1981. Country: Norway Change in definition (1995 onward): Data refer to population 16 years +. Data on height and weight are self-reported. Country: Norway Reference period (2000): Data refer to 1998. Country: Poland Reference period (1995): Data refer to 1996. Country: Portugal Data for age group 15-19 refers to 18-19. 2000: data cover mainland territory (without Autonomous Regions of Acores and Madeira) and refers to 1998-1999. 2005: data refers to 2005-2006 (all territory). 2014: data with a coefficient of variation of 20% or more are not disseminated. Body Mass Index is reported for persons 18+ years. Country: Russian Federation Data refer to age groups 14-18 and 19-44 instead of 15-19 and 20-44 Country: Slovakia Until 2009, data refer to population aged up to 64. In 2009 and 2014 some values are not shown due to low sample sizes. Country: Slovakia Reference period (1990): Data refer to 1993. Country: Slovakia Reference period (1995): Data refer to 1998. Country: Slovakia Territorial change (1990): Data cover 2 districts (Banska Bystrica and Brezno) Country: Slovakia Territorial change (1995): Data cover 3 districts (Banska Bystrica, Brezno and Trebisov) Country: Slovakia Territorial change (2003): Data cover 9 districts (Banska Bystrica, Brezno, Trebisov, Dunajska Streda, Dolny Kubin, Nove Zamky, Bratislava II, Kosice II and Roznava). Country: Slovenia Break in methodlogy (2007): Data for 2007 comes from the European Health Interview Survey, for other years from the Countrywide Integrated Noncommunicable Disease Intervention survey Country: Slovenia Change in definition (2001 - 2004): Data for population aged 25-64. Country: Slovenia Change in definition (2008 - 2012): Data for population aged 25-74. Country: Spain Break in methodlogy (2003): Proxy were allowed Country: Spain Change in definition (2001): Data refer to Spanish nationals only aged 16+. Country: Spain Change in definition (2006): Age group 15-19 refers to 18-44. Country: Spain Change in definition (2009 onward): Age group 15-24 refers to 16-24. For population aged 16-17 overweight and obesity cut offs are defined according to Cole et al. BMJ 2000;320:1240-3, and underweight cut offs according to Cole et al. BMJ 2007;335:194-7. Country: Sweden Change in definition (1980 - 2001): Obesity: BMI>30 kg/sqm. Data refer to population aged 16-84; data for age group 65+ refers to 65-84. Country: Sweden Change in definition (2002 - 2010): Obesity: BMI>30 kg/sqm. Data refer to population aged 16+, data for age group 15-19 refers to 16-19. Country: Sweden Change in definition (2011 - onwards): Data refer to population aged 16+, data for age group 15-19 refers to 16-19. Country: Sweden Reference period (1990): Data refer to 1989 Country: Sweden Reference period (1995): Data refer to 1996 Country: Switzerland Reference period (1990): Data refer to 1992. Country: Switzerland Reference period (1995): Data refer to 1997. Country: Ukraine From 2014 data cover the territories under the government control. Country: Ukraine Change in definition (2006 onwards): Age group 15-19 refers to 18-19. Age group 65+ refers to 70+. Country: Ukraine Territorial change (2006 onwards): The territorial sample exclude localities in the territory which was radioactively contaminated by the Chernobyl disaster . Country: United Kingdom Change in definition (1995 - onwards): Data collected from 16 years of age rather than 15. Country: United Kingdom Territorial change (1995 - onwards): Data cover England only. Country: United States For 1980 and 1990 data refer to 1976-1980 and 1988-1994 respectively. Since 2000, data for the reference year refer to the range of this year and the previous one.
    • Mai 2015
      Quelle: Earth Policy Institute
      Hochgeladen von: Knoema
      Zugriff am: 26 Juni, 2015
      Datensatz auswählen
      This is part of a supporting dataset for Lester R. Brown, Full Planet, Empty Plates: The New Geopolitics of Food Scarcity (New York: W.W. Norton & Company, 2012).
    • September 2014
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2018
      Datensatz auswählen
      Description not available
  • R
    • März 2019
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 13 März, 2019
      Datensatz auswählen
      The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).
    • Juni 2016
      Quelle: Organisation for Economic Co-operation and Development
      Hochgeladen von: Knoema
      Zugriff am: 28 Oktober, 2016
      Datensatz auswählen
      The Regional well-being dataset presents eleven dimensions central for well-being at local level and for 395 OECD regions, covering material conditions (income, jobs and housing), quality of life (education, health, environment, safety and access to services) and subjective well-being (social network support and life satisfaction). The set of indicators selected to measure these dimensions is a combination of people's individual attributes and their local conditions, and in most cases, are available over two different years (2000 and 2014). Regions can be easily visualised and compared to other regions through the interactive website [www.oecdregionalwellbeing.org]. The dataset, the website and the publications "Regions at a Glance" and "How’s life in your region?" are outputs designed from the framework for regional and local well-being. The Regional income distribution dataset presents comparable data on sub-national differences in income inequality and poverty for OECD countries. The data by region provide information on income distribution within regions (Gini coefficients and income quintiles), and relative income poverty (with poverty thresholds set in respect of the national population) for 2013. These new data complement international assessments of differences across regions in living conditions by documenting how household income is distributed within regions and how many people are poor relatively to the typical citizen of their country. For analytical purposes, the OECD classifies regions as the first administrative tier of sub-national government, so called Territorial Level 2 or TL2 in the OECD classification. This classification is used by National Statistical Offices to collect information and it represents in many countries the framework for implementing regional policies. Well-being indicators are shown for the 395 TL2 OECD regions, equivalent of the NUTS2 for European countries, with the exception for Estonian where well-being data are presented at a smaller (TL3) level and for the Regional Income dataset, where Greece, Hungary and Poland data are presented at a more aggregated (NUTS1) level.
    • Mai 2019
      Quelle: ClinicalTrials.gov
      Hochgeladen von: Knoema
      Zugriff am: 24 Mai, 2019
      Datensatz auswählen
      Registered studies by ClinicalTrials.gov, As of May 23, 2019
    • Februar 2019
      Quelle: Eurostat
      Hochgeladen von: Knoema
      Zugriff am: 19 Februar, 2019
      Datensatz auswählen
      The focus of this domain is on the European Neighbourhood Policy (ENP) countries on the southern and eastern shores of the Mediterranean (ENP-South), namely: Algeria (DZ),Egypt (EG),Israel (IL),Jordan (JO),Lebanon (LB),Libya (LY),Morocco (MA),Palestine (PS),Syria (SY) andTunisia (TN). An extensive range of indicators is presented in this domain, including indicators from almost every theme covered by European statistics. Only annual data are published in this domain. The data and their denomination in no way constitute the expression of an opinion by the European Commission on the legal status of a country or territory or on the delimitation of its borders.
  • S
    • April 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2019
      Datensatz auswählen
      Source: UNECE Statistical Database, compiled from national official sources. Definition: Smoking is defined as the daily smoking of at least one cigarette. General note: Percentage .. - data not available Country: Armenia 1995: data refer to 1997. 2010: data refer to age group 15-49. Country: Austria Break in methodlogy (2006): Data for 2006 come from the Autrian Health Interview Survey, for 1995 from the Labour force Survey ad hoc module on smoking habits. Country: Austria Reference period (1995): Data refer to 1997. Country: Belarus Data refer to population aged 16+. Country: Bulgaria Break in methodlogy (2008): 2008 data come from the European Health Interview Survey and 2001 from the Demographic and Health survey. Country: Canada Data exclude institutional residents and full-time members of the Canadian Forces. Country: Canada Data exclude residents of Indian Reserves, Crown Lands and certain remote regions. Country: Croatia Change in definition (1995): data refer to age group 18-65. Country: Croatia Change in definition (2003): data refer to population aged 18+. Country: Croatia Reference period (2012): data refer to 2011. Country: Cyprus Reference period (1990): Data refer to 1989. Country: Cyprus Data cover only government controlled area. Country: Czechia 2004: data refer to population aged 18-64; age group 15-24 refers to 18-24. 1990, 1995 and 2000: data refer to 1993, 1996 and 1999. Country: Denmark Change in definition (1990 - 2013): Data refer to population aged 16+; age group 15-24 refers to 16-24. Country: Estonia Data refer to population aged 16-64; age group 15-24 refers to 16-24. Country: Estonia Reference period (1995): Data refer to 1996 Country: France Change in definition (1995 - 2000): Data refer to population aged 18-74; age group 15-24 refers to 18-24. Country: France Change in definition (2002 - 2014): Data refer to population aged 15-75 Country: France Territorial change (2002 - 2014): Data cover only Metropolitan France. Country: Germany 2000: data refer to 1999. Country: Iceland Change in definition (1990 - 2013): Data for smokers 15+ refers to persons aged 15-89. As of 2014, data refer to persons aged 18-89. Data for smokers aged 15-24 refers to persons aged 18-24 as of 2014. Country: Ireland Age group 15-24 refers to 15-23. 2000: data refer to 1998. 2000-2002: data include occasional smokers. 2003: data refer to people smoking one or more cigarettes a week. From 2015, data related to the population aged 15 and over who report that they are daily smokers. Country: Israel Additional information (1995 - 2013): Data are based on different surveys and methodologies across years. Country: Israel Change in definition (1995 - 2010): Data refer to population aged 20+. Country: Israel Change in definition (2003): Data refer to population aged 20+. Data refer to population aged 21+ and based on health survey. Country: Israel Change in definition (2013): Data refer to population aged 21+. Country: Israel Reference period (1995): Data refer to 1996-1997. Country: Israel Reference period (2000): Data refer to 1999-2000. Country: Israel Reference period (2003): Data refer to 2003-2004. Country: Italy Break in methodlogy (2001): From 2001 data come from survey "Aspects of daily life" , before 2001 data come from survey "Health condition and use of health services". Country: Italy Reference period (1995): Data refer to 1994. Country: Kazakhstan Age group 15+ refers to 15-49. Country: Latvia Data for 2003 - from the Health Interview Survey. Data cover population 15-75 years old.Data for 2004, 2006, 2010 and 2012 - from Health Behaviour Survey among Latvian Adult population. Data cover population 15-64 years old.Data for 2008 and 2014 - from the European Health iInterview Survey (EHIS). Data cover population 15+. Country: Malta Data refer to population aged 18+ residing in private households. Data for age group 15 - 24 are not available due to under-representation. Country: Moldova, Republic of Additional information (2010 - 2012): Data exclude the territory of the Transnistria and municipality of Bender Country: Moldova, Republic of Change in definition (2010 - 2012): Smoking is defined as daily smoking or smoking sometimes Country: Moldova, Republic of Reference period (2010): The survey was conducted in August-October 2010 Country: Moldova, Republic of Reference period (2012): The survey was conducted in July-September 2012 Country: Netherlands Change in definition (1990 - 1995): Data refer to population age 16+. Country: Netherlands Data include all types of smokers. In 2014, interviewing and weighting method was changed, causing a break in the time series. Country: Norway Change in definition (1980 - 2009): Date refer to three-year average. Country: Norway Data refer to population aged 16-74; age group 15-24 refers to 16-24. Country: Poland Reference period (1995): Data refer to 1996. Country: Portugal Before 2005: data cover only mainland territory (without Autonomous Regions of Acores and Madeira). 1995, 2000, 2005: data refer to 1995/1996, 1998/1999 and 2005/2006. Country: Romania Break in methodology (2009): From 2009 change in data source Country: Russian Federation Change in definition: Data refer to daily smokers of age 15+. Country: Slovenia Change in definition (1990): Data for population aged 15+ refer to age 18+. Country: Slovenia Change in definition (1995 - 2000): Data for population aged 15+ refer to age 18+. Age group 15-24 refers to 15-16. Country: Slovenia Change in definition (2001 - 2004): Data for population aged 25-64. Country: Slovenia Change in definition (2008 - 2012): Data for population aged 25-74. Country: Slovenia Reference period (1990): Data refer to 1988. Country: Slovenia Reference period (1995): Data refer to 1994. Country: Slovenia Reference period (2000): Data refer to 1999. Country: Spain Break in methodlogy (2003): Proxy were allowed Country: Spain Break in methodlogy (2009): Questionnaire self-administered Country: Spain Change in definition (1980 - 2003): Data refer to population aged 16+. Age group 15-24 refers to 16-24. Data refer to Spanish nationals only. Country: Spain Change in definition (2006 - 2009): Data refer to population aged 16+. Age group 15-24 refers to 16-24. Country: Spain Reference period (1990): Data refer to 1993. Country: Spain Reference period (2000): Data refer to 1997. Country: Sweden Change in definition (1980 - 2001): Age group 15+ refers to 16+, age group 15-24 refers to 16-24. Data refer to population aged 16-84. Country: Sweden Change in definition (2002 - onwards): Age group 15+ refers to 16+, age group 15-24 refers to 16-24. Country: Sweden Data do not include snuff users and smokers Country: Switzerland Reference period (1990): Data refer to 1992. Country: Switzerland Reference period (1995): Data refer to 1997. Country: Turkey Break in methodlogy (2006): Data come from the Life Satisfaction Survey. For other years data come from a different source. Country: Turkey Break in methodlogy (2008, 2012): Data for 2008 and 2012 come from the Global Adult Tobacco Survey. For other years data come from a different source. Country: Turkey Break in methodlogy (2010, 2014): Data come from the Health Interview Survey. For other years data come from a different source. Country: Ukraine From 2014 data cover the territories under the government control. Country: Ukraine Territorial change (2000 - 2013): The territorial sample exclude localities in the territory which was radioactively contaminated by the Chernobyl disaster . Country: United Kingdom Change in definition (1980 - onwards): Data refer to population aged 16+. Smokers are defined as anyone who has ever smoked and describes themselves as a current smoker. Age group 15-24 refers to 16-24. Country: United Kingdom Reference period (1995): Data refer to 1994. Country: United Kingdom Reference period (2005): Estimates prior to 2005 are based on a fiscal year rather than a calendar year. Country: United Kingdom Territorial change (1980 - onwards): Estimates are for Great Britain excluding Northern Ireland. Country: United States Data for 1980 include persons aged 17+, for all other years data refer to the population aged 18+. 1980, 1990: data refer to both daily and nondaily smokers.
    • August 2018
      Quelle: Social Progress Imperative
      Hochgeladen von: Knoema
      Zugriff am: 21 November, 2018
      Datensatz auswählen
      The Social Progress Index is a new way to define the success of our societies. It is a comprehensive measure of real quality of life, independent of economic indicators. The Social Progress Index is designed to complement, rather than replace, economic measures such as GDP. Each year, Social Progress Imperative conducts a comprehensive review of all indicators included in the Social Progress Index framework to check data updates (which frequently include retroactive revisions) and whether new indicators have been published that are well-suited to describing social progress concepts. Such a review necessitates a recalculation of previously published versions of the Social Progress Index, as any removal or additions of indicators to the framework or changes due to retroactive revisions in data from the original data sources prevent comparability between previously published versions of the Social Progress Index and the 2018 Social Progress Index. Therefore, using the 2018 Social Progress Index framework and methodology, we provide comparable historical data for four additional years of the Social Progress Index, from 2014 to 2017. To read more about our methodology, please see the 2018 Methodology here https://www.socialprogress.org/index/methodology
    • August 2018
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2018
      Datensatz auswählen
      This indicator is a proxy for the availability of health care. It represents the percentage of the population without access to health care due to the absence of the health workforce. The threshold for having a sufficient health workforce is 41.1 health workers per 10 000 population. A higher figure indicates worse availability. Note that this indicator reflects the supply side of availability, in this case the availability of human resources is at a level that guarantees at least basic, but universal, access. To estimate access to the services of skilled medical professionals (physicians, nursing and midwifery personnel), it uses as a proxy the relative difference between the density of these health workers in a given country (number per 10 000 population) and its median value in countries with a low level of vulnerability (defined according to the structure of employment and levels of poverty).To establish whether a country is spending 'enough' or has 'enough' key health workers, it is necessary first to define what constitutes 'enough', i.e. set a threshold against which a country's performance can be compared. Opinions differ on what constitutes 'enough' in these contexts, not least because it is likely to be a moving target, influenced by prevailing health issues, demography etc. The ILO's approach for measuring financial deficit is to: (i) calculate the median expenditure on health (excluding OOP) in low-vulnerability countries, then (ii) for each country, compare spending against this median. In 2014, the median in low-vulnerability countries was US$239. For example, a country spending 50% less than the median in low-vulnerability countries has a financial deficit of 50%. The same principle applies to the staff access deficit indicator, for which the 2014 median in low-vulnerability countries was 41.1. This is one of five indicators measuring key dimensions of deficits in health care access and coverage. For analytical purposes the full set of indicators should be considered together.
    • Februar 2015
      Quelle: World Life Expectancy
      Hochgeladen von: Knoema
      Zugriff am: 07 Mai, 2015
      Datensatz auswählen
    • Juli 2018
      Quelle: Sustainable Development Solutions Network
      Hochgeladen von: Knoema
      Zugriff am: 10 August, 2018
      Datensatz auswählen
      The 2018 SDG Index and Dashboards report presents a revised and updated assessment of countries’ distance to achieving the Sustainable Development Goals (SDGs). It includes detailed SDG Dashboards to help identify implementation priorities for the SDGs. The report also provides a ranking of countries by the aggregate SDG Index of overall performance.
    • November 2018
      Quelle: Institute for Health Metrics and Evaluation
      Hochgeladen von: Knoema
      Zugriff am: 30 November, 2018
      Datensatz auswählen
      The Global Burden of Disease Study 2017 (GBD 2017), coordinated by the Institute for Health Metrics and Evaluation (IHME), estimated the burden of diseases, injuries, and risk factors from 1990 to 2017. The United Nations established, in September 2015, the Sustainable Development Goals (SDGs), which specify 17 universal goals, 169 targets, and 232 indicators leading up to 2030. Drawing from GBD 2017, this dataset provides estimates on progress for 41 health-related SDG indicators for 195 countries and territories from 1990 to 2017, and projections, based on past trends, for 2018 to 2030. Estimates are also included for the health-related SDG index, a summary measure of overall performance across the health-related SDGs.
  • T
    • Dezember 2015
      Quelle: United Nations Statistics Division
      Hochgeladen von: Knoema
      Zugriff am: 19 August, 2017
      Datensatz auswählen
      Data cited at: United Nations Statistics Division https://unstats.un.org/home/ Publication: https://unstats.un.org/unsd/gender/worldswomen.html License: https://creativecommons.org/licenses/by-nc/4.0/   The World’s Women 2015 comprises eight chapters covering critical areas of policy concern: population and families, health, education, work, power and decision-making, violence against women, environment, and poverty. In each area, a life-cycle approach is introduced to reveal the experiences of women and men during different periods of life—from childhood and the formative years, through the working and reproductive stages, to older ages. The statistics and analyses presented in the following pages are based on a comprehensive and careful assessment of a large set of available data from international and national statistical agencies. Each chapter provides an assessment of gaps in gender statistics, highlighting progress in the availability of statistics, new and emerging methodological developments, and areas demanding further attention from the international community
    • März 2017
      Quelle: Bloomberg
      Hochgeladen von: Knoema
      Zugriff am: 27 November, 2017
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      To identify the healthiest countries in the world, Bloomberg Rankings created health scores and health-risk scores for countries with populations of at least 1 million. The risk score was subtracted from the health score to determine the country''s rank. Five-year averages, when available, were used to mitigate some of the short-term year-over-year swings.
    • April 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2019
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      .. - data not available Source: UNECE Statistical Database, compiled from national and international (Eurostat, UN Statistics Division Demographic Yearbook, WHO European health for all database and UNICEF TransMONEE) official sources. Definition: The total fertility rate is defined as the average number of children that would be born alive to a woman during her lifetime if she were to pass through her childbearing years conforming to the age-specific fertility rates of a given year. General note: Data come from registers, unless otherwise specified. Country: Cyprus Data cover only government controlled area. Country: Georgia From 1995 : data do not cover Abkhazia and South Ossetia (Tshinvali). Country: Germany From 3 October 1990: data refer to the Federal Republic within its frontiers. Country: Israel Data include East Jerusalem and Israeli residents in certain other territories under occupation by Israeli military forces since June 1967. Country: Russian Federation 1980 : data refer to 1980-1981. Country: Serbia Data do not cover Kosovo and Metohija. Country: Turkey Data come from the national population projections, which are based on Population Census (2000) and Turkey Demographic and Health Survey (2003).
    • Mai 2019
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 21 Mai, 2019
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      Description not available
    • September 2014
      Quelle: International Labour Organization
      Hochgeladen von: Knoema
      Zugriff am: 31 August, 2018
      Datensatz auswählen
      Description not available
    • April 2019
      Quelle: United Nations Economic Commission for Europe
      Hochgeladen von: Knoema
      Zugriff am: 22 April, 2019
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      .. - data not available Source: UNECE Statistical Database, compiled from national and international (Eurostat, UN Statistics Division Demographic Yearbook, WHO European health for all database and UNICEF TransMONEE) official sources. Definition:A live birth is the complete expulsion or extraction from its mother of a product of conception, irrespective of the duration of pregnancy, which after such separation breathes or shows any other evidence of life such as beating of the heart, pulsation of the umbilical cord or definite movement of voluntary muscles, whether or not the umbilical cord has been cut or the placenta is attached. General note: Data come from registers, unless otherwise specified. In years 2003 and before, the number of live births for girl child and boy child may not add up to the number for both sexes (Total) due to the rounding up of numbers. Country: Armenia 1980-2006 : Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Country: Azerbaijan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Data are tabulated by date of registration (rather than occurrence). Country: Belarus Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Country: Canada 1980,1995: Including Canadian residents temporarily in the United States, but excluding United States residents temporarily in Canada. Country: Cyprus Data cover only government controlled area. Country: Georgia Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. From 1995 : data do not cover Abkhazia and South Ossetia (Tshinvali). Country: Germany From 3 October 1990: data refer to the Federal Republic within its frontiers. Country: Israel Data include East Jerusalem and Israeli residents in certain other territories under occupation by Israeli military forces since June 1967. Country: Kazakhstan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Country: Malta From 2001: data include foreign residents. Country: Russian Federation Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth. Country: Serbia Data do not cover Kosovo and Metohija. Data are tabulated by date of registration (rather than occurrence). Country: Turkey 1980-2000: data source is population censuses. From 2001: data are from administrative source. Country: Turkmenistan Data do not cover infants born alive with less than 28 weeks gestation, less than 1000 grams in weight and 35 centimeters in length, who die within seven days of birth.
  • U
    • Dezember 2015
      Quelle: World Health Organization
      Hochgeladen von: Knoema
      Zugriff am: 15 September, 2017
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    • Oktober 2015
      Quelle: Joint United Nations Programme on HIV/AIDS
      Hochgeladen von: Knoema
      Zugriff am: 26 Februar, 2016
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      UNAIDS was mandated by the UN General Assembly to monitor progress on global AIDS response in the 2001 General Assembly Special Session on HIV and AIDS, and reaffirmed in the 2011 High Level Meeting. The Global AIDS Response Progress Reporting data consists of 30 indicators, divided by 10 global targets, which are reported by participating countries on their national response to HIV/AIDS. Data used to be reported every second year from 2004 until 2012, However, starting 2013, data are collected every year to enable effective monitoring towards Millennium Development Goals of 2015. Collected data are published as part of the Global Report on AIDS. In 2014, 180 out of 193 UN member states (171 in 2013) submitted their reports.
    • November 2018
      Quelle: DevInfo
      Hochgeladen von: Knoema
      Zugriff am: 05 Dezember, 2018
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      This database contains country-reported GAM data. For HIV epidemiological estimates, as well as ART and PMTCT indicators
    • Juli 2018
      Quelle: Joint United Nations Programme on HIV/AIDS
      Hochgeladen von: Knoema
      Zugriff am: 07 August, 2018
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      This Dataset contains Regional and National level Data.
  • W
    • Mai 2012
      Quelle: World Health Organization
      Hochgeladen von: Knoema
      Zugriff am: 01 Juni, 2012
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      Body mass index (BMI) is a simple index of weight-for-height that is commonly used to classify overweight and obesity in adults. It is defined as a person's weight in kilograms divided by the square of his height in meters (kg/m2). The WHO definition is: a BMI greater than or equal to 25 is overweight a BMI greater than or equal to 30 is obesity. BMI provides the most useful population-level measure of overweight and obesity as it is the same for both sexes and for all ages of adults. However, it should be considered a rough guide because it may not correspond to the same degree of fatness in different individuals.
    • April 2019
      Quelle: World Bank
      Hochgeladen von: Knoema
      Zugriff am: 01 Mai, 2019
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      The primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates
    • Mai 2014
      Quelle: World Health Organization
      Hochgeladen von: Knoema
      Zugriff am: 18 Juni, 2014
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      Includes datasets on communicable diseases, human resources for health, noncommunicable diseases and world health statistics.
    • Oktober 2013
      Quelle: World Bank
      Hochgeladen von: Knoema
      Zugriff am: 24 November, 2014
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      Data cited at: The World Bank https://datacatalog.worldbank.org/ Topic: World Report On Disability Publication: https://datacatalog.worldbank.org/dataset/world-report-disability License: http://creativecommons.org/licenses/by/4.0/   This dataset provides the World report on disability, Technical appendix A: Estimates of disability prevalence (%) and of years of health lost due to disability (YLD), by country
    • August 2018
      Quelle: Wikipedia
      Hochgeladen von: Knoema
      Zugriff am: 14 August, 2018
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      Data cited at: Wikipedia https://en.wikipedia.org Topic: 2015–16 Zika virus epidemic Publication URL: https://en.wikipedia.org/wiki/2015%E2%80%9316_Zika_virus_epidemic#cite_note-deaths-22 License : https://en.wikipedia.org/wiki/Wikipedia:Text_of_Creative_Commons_Attribution-ShareAlike_3.0_Unported_License