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United States of America

  • President:Donald J. Trump
  • Vice President:Mike Pence
  • Capital city:Washington, D.C.
  • Languages:English 79.2%, Spanish 12.9%, other Indo-European 3.8%, Asian and Pacific island 3.3%, other 0.9% (2011 est.) note: data represents the language spoken at home; the US has no official national language, but English has acquired official status in 31 of the 50 states; Hawaiian is an official language in the state of Hawaii
  • Government
  • National statistics office
  • Population, persons:32,71,67,434 (2018)
  • Area, sq km:91,47,420
  • GDP per capita, US$:62,641 (2018)
  • GDP, billion current US$:20,494.1 (2018)
  • GINI index:No data
  • Ease of Doing Business rank:8

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All datasets:  2 A B C D E F G H I L M N O P R S T U V W
  • 2
  • A
    • जून 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 11 जून, 2019
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      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.
    • जनवरी 2018
      Source: HealthIT.gov
      Uploaded by: Knoema
      Accessed On: 30 जनवरी, 2018
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    • नवम्बर 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 जनवरी, 2019
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      Hay fever, respiratory allergies, food allergies, and skin allergies in the past 12 months for children under age 18 years, by selected characteristics: United States
    • जुलाई 2019
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      National Hospital Ambulatory Medical Care Survey: 2016 Emergency Department Summary Tables
    • दिसम्बर 2017
      Source: National Association of Insurance Commissioners
      Uploaded by: Knoema
      Accessed On: 03 जनवरी, 2018
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    • नवम्बर 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 20 नवम्बर, 2015
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      The data are from the National Health Interview Survey (NHIS), a continuous national survey of the civilian noninstitutionalized population of the United States. Data are collected through in-person computer assisted household interviews
    • सितम्बर 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 20 अक्तूबर, 2015
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      The data are from the National Health Interview Survey (NHIS), a continuous national survey of the civilian noninstitutionalized population of the United States. Data are collected through in-person computer assisted household interviews
    • नवम्बर 2005
      Source: Disabled World
      Uploaded by: Prashanth BK Kumar
      Accessed On: 27 जनवरी, 2016
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  • B
    • नवम्बर 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 25 जनवरी, 2019
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      TOTAL FERTILITY RATE is the sum of the age-specific birth rates (5-year age groups between 10 and 49) for female residents of a specified geographic area (nation, state, county, etc.) during a specified time period (usually a calendar year) multiplied by 5. (NOTE: This rate estimates the number of children a hypothetical cohort of 1,000 females in the specified population would bear if they all went through their childbearing years experiencing the same age-specific birth rates for a specified time period.)
  • C
    • मई 2019
      Source: American Cancer Society
      Uploaded by: Knoema
      Accessed On: 31 मई, 2019
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      This data set provides the Estimated numbers of new cancer cases and deaths in 2019 (In 2019, there will be an estimated 1,762,450 new cancer cases diagnosed and 606,880 cancer deaths in the United States.
    • दिसम्बर 2018
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Sandeep Reddy
      Accessed On: 02 जनवरी, 2019
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      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."
    • अक्तूबर 2019
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 25 अक्तूबर, 2019
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      Notes Highlighted monthly caseloads are incomplete and will change Source: CHIP PPS Data HHSC Forecasting
    • मार्च 2017
      Source: ScienceDirect
      Uploaded by: Knoema
      Accessed On: 25 जुलाई, 2017
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    • नवम्बर 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 07 नवम्बर, 2019
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      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.
    • अप्रैल 2018
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 21 मई, 2018
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      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
    • जुलाई 2016
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 29 जुलाई, 2016
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      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
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 अगस्त, 2019
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      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
    • नवम्बर 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 जनवरी, 2019
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      Currently uninsured persons under age 65, by selected reasons for no health insurance coverage and by selected characteristics: United States
  • D
    • मई 2018
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 21 नवम्बर, 2018
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      .. - 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.
    • अप्रैल 2019
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 14 जून, 2019
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      This 10th edition of the Institute for Health Metrics and Evaluation’s annual Financing Global Health report provides the most up-to-date estimates of development assistance for health, domestic spending on health, health spending on two key infectious diseases – malaria and HIV/AIDS – and future scenarios of health spending. Several transitions in global health financing inform this report: the influence of economic development on the composition of health spending; the emergence of other sources of development assistance funds and initiatives; and the increased availability of disease-specific funding data for the global health community. For funders and policymakers with sights on achieving 2030 global health goals, these estimates are of critical importance. They can be used for identifying funding gaps, evaluating the allocation of scarce resources, and comparing funding across time and countries.
    • दिसम्बर 2008
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Peter Speyer
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      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.
  • E
    • फरवरी 2016
      Source: California Life Sciences Association
      Uploaded by: Knoema
      Accessed On: 28 अप्रैल, 2016
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      AdvaMed advocates for a legal, regulatory and economic environment that advances global health care by assuring worldwide patient access to the benefits of medical technology. It promotes policies that foster the highest ethical standards, rapid product approvals, appropriate reimbursement, and access to international markets. Medical technology innovators are committed to providing physicians the best tools to diagnose and treat patients. This commitment drives over 6,000 companies in the U.S. to create medical miracles everyday—leading to an 80 percent increase in patents for breakthrough medical technologies in the last decade
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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    • जुलाई 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2015
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      Note:All Data Presents in this datset is "Tooth Loss = Yes". The data are from the National Health Interview Survey (NHIS), a continuous national survey of the civilian noninstitutionalized population of the United States. Data are collected through in-person computer assisted household interviews.
    • दिसम्बर 2013
      Source: Centers for Medicare and Medicaid Services
      Uploaded by: Knoema
      Accessed On: 04 मार्च, 2016
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      The Environmental Scanning and Program Characteristics (ESPC) Database, is intended to facilitate cross-State analyses. Information from the ESPC database can be linked to the Medicaid Analytic eXtract (MAX) files and other Medicaid data to support program and comparative effectiveness research (CER), policy studies, and program evaluations. The ESPC database and companion User Guide can serve as a stand-alone tool to facilitate intra–and inter–state analysis stemming from the implementation of health reform.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 24 मई, 2015
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      Eurostat Dataset Id:hlth_sha3p Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
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      Eurostat Dataset Id:hlth_sha3m Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
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      Eurostat Dataset Id:hlth_sha3h Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
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      Eurostat Dataset Id:hlth_sha2p Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
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      Eurostat Dataset Id:hlth_sha2m Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
      Select Dataset
      Eurostat Dataset Id:hlth_sha2h Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
      Select Dataset
      Eurostat Dataset Id:hlth_sha1p Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 मई, 2015
      Select Dataset
      Eurostat Dataset Id:hlth_sha1m Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
      Select Dataset
      Eurostat Dataset Id:hlth_sha1h Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003. 3.3. Coverage - sector Public Health
  • F
    • सितम्बर 2017
      Source: National Institute for Health and Welfare
      Uploaded by: Knoema
      Accessed On: 16 फरवरी, 2018
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      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
    • सितम्बर 2017
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 08 नवम्बर, 2017
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      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
    • सितम्बर 2017
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 27 अक्तूबर, 2017
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      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.
    • मार्च 2019
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 29 अगस्त, 2019
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      Data cited at: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2017 (GBD 2017) Health-related Sustainable Development Goals (SDG) Indicators 1990-2030. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2018.   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.
    • नवम्बर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 2019
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      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/
    • मई 2019
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 18 सितम्बर, 2019
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      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."
    • मई 2019
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 27 अगस्त, 2019
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      Research by the Global Burden of Disease Health Financing Collaborator Network produced projected health spending estimates for 2017-2050 for 195 countries and territories. The estimates cover total health spending, and health spending disaggregated by source into three domestic financing source categories (government, out-of-pocket, and prepaid private) and development assistance for health (DAH). Retrospective health spending estimates for 1995-2016 and key covariates (including GDP per capita, total government spending, total fertility rate, and fraction of the population older than 65 years) were used to forecast GDP and health spending through 2050. Estimates are reported in constant 2018 US dollars, constant 2018 purchasing-power parity-adjusted (PPP) dollars, and as a percent of gross domestic product.
    • मार्च 2019
      Source: World Health Organization
      Uploaded by: Knoema
      Accessed On: 18 मार्च, 2019
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      Citation: Global Health Observatory (GHO) Data: https://www.who.int/gho/en/: World Health Organization; 2019. Licence: CC BY-NC-SA 3.0 IGO   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.
    • मई 2018
      Source: World Health Organization
      Uploaded by: Sandeep Reddy
      Accessed On: 12 दिसम्बर, 2018
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      Global Trends in Prevalence of Tobacco Smoking 2000-2025
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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  • H
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 अगस्त, 2019
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    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 अगस्त, 2019
      Select Dataset
    • अगस्त 2019
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2019
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    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
      Select Dataset
      Eurostat Dataset Id:hlth_sha_hf Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • मई 2015
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 27 जुलाई, 2015
      Select Dataset
      Eurostat Dataset Id:hlth_sha_ltc Data description Health care expenditure data provide information on expenditure in the functionally defined area of health distinct by provider category (e.g. hospitals, general practitioners), function category (e.g. services of curative care, rehabilitative care, clinical laboratory, patient transport, prescribed medicines) and financing agent (e.g. social security, private insurance company, household). The definitions and classifications of the System of Health Accounts (SHA) (see the annex at the bottom of the page) are followed, e.g. International Classification for Health Accounts - Providers of health care (ICHA-HP). Health care data on expenditure are largely based on surveys and administrative (register) data sources in the countries. Therefore, they reflect the country-specific way of organising health care and may not always be completely comparable. The database is based on a co-operation between EUROSTAT, the OECD (Organisation for Economic Co-Operation and Development) and the WHO (World Health Organisation), executing a Joint Questionnaire on Health expenditure since 2005. The area covered consists of EU-27 (excluding EL, IE, IT, MT, and UK), Norway, Iceland, Switzerland, Japan, USA, Australia and Korea. 3.2. Classification system For all data on expenditure two sources for classifications are available: the System of Health Accounts (Manual v.1.0) as presented by the OECD in 2000 and the Guide to producing national health accounts with special application for low and middle income countries produced by WHO/Worldbank/USAID in 2003 These two manuals are complemented by the Guidelines produced for EUROSTAT by the Office for National Statistics (UK) in 2003.
    • अगस्त 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 21 मार्च, 2019
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      The Health, United States series presents an annual overview of national trends in health statistics. The report contains a Chartbook that assesses the nation's health by presenting trends and current information on selected measures of morbidity, mortality, health care utilization and access, health risk factors, prevention, health insurance, and personal health care expenditures. This year's Chartbook includes a Special Feature on the health of adults aged 55–64. The report also contains 123 Trend Tables organized around four major subject areas: health status and determinants, health care utilization, health care resources, and health care expenditures. A companion report—Health, United States: In Brief—featuresinformation extracted from the full report. The complete report, In Brief, and related data products are available on the Health, United States website.
    • नवम्बर 2017
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 13 नवम्बर, 2017
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      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.
    • अगस्त 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 20 मार्च, 2019
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      Health, United States  is the report on the health status of the country, submitted by the Secretary of the U.S. Department of Health and Human Services to the President and the Congress of the United States. Every year, the report presents an overview of national health trends organized around four subject areas: health status and determinants, utilization of health resources, health care resources, and health care expenditures and payers.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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      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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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      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
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 09 जुलाई, 2019
      Select Dataset
      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.
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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      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.
    • जून 2010
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
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      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.
    • अप्रैल 2019
      Source: U.S. Census Bureau
      Uploaded by: Knoema
      Accessed On: 04 जुलाई, 2019
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      Health Indicators on US States, 2018
    • सितम्बर 2019
      Source: U.S. Census Bureau
      Uploaded by: Knoema
      Accessed On: 15 अक्तूबर, 2019
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      Health Insurance Coverage Status and Type of Coverage by State, United States, 2019
    • सितम्बर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 25 सितम्बर, 2019
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      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.
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
      Select Dataset
      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.
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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    • दिसम्बर 2018
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 26 दिसम्बर, 2018
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      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
    • अक्तूबर 2019
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 25 अक्तूबर, 2019
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      Notes Highlighted caseloads are incomplete and will change. Healthy Texas Women began July 2016; Texas Women's Health Program began Jan. 2013; Medicaid Women's Health Program began Jan. 2007. Source: PPS HHSC Forecasting
    • अक्तूबर 2019
      Source: Eurostat
      Uploaded by: Knoema
      Accessed On: 01 नवम्बर, 2019
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      Harmonised Indices of Consumer Prices (HICP) are designed for international comparisons of consumer price inflation. HICPs are used for the assessment of the inflation convergence criterion as required under Article 121 of the Treaty of Amsterdam and by the ECB for assessing price stability for monetary policy purposes. The ECB defines price stability on the basis of the annual rate of change of the euro area HICP. HICPs are compiled on the basis of harmonised standards, binding for all Member States. Conceptually, the HICP are Laspeyres-type price indices and are computed as annual chain-indices allowing for weights changing each year. The common classification for Harmonized Indices of Consumer Prices is the COICOP (Classification Of Individual COnsumption by Purpose). A version of this classification (COICOP/HICP) has been specially adapted for the HICP. Sub-indices published by Eurostat are based on this classification. HICP are produced and published using a common index reference period (2015 = 100). Growth rates are calculated from published index levels. Indexes, as well as both growth rates with respect to the previous month (M/M-1) and with respect to the corresponding month of the previous year (M/M-12) are neither calendar nor seasonally adjusted.
    • जुलाई 2013
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
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      The data are from the National Hospital Discharge Survey (NHDS). The NHDS collects data from a sample of inpatient records acquired from a national sample of short stay, non-federal hospitals in the United States. Because persons with multiple discharges during a year may be sampled more than once, estimates are for discharges, not persons.
    • जुलाई 2013
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
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      The data are from the National Hospital Discharge Survey (NHDS). The NHDS collects data from a sample of inpatient records acquired from a national sample of short stay, non-federal hospitals in the United States. Because persons with multiple discharges during a year may be sampled more than once, estimates are for discharges, not persons
    • जुलाई 2013
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
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      The data are from the National Hospital Discharge Survey (NHDS). The NHDS collects data from a sample of inpatient records acquired from a national sample of short stay, non-federal hospitals in the United States.
    • अगस्त 2018
      Source: United Nations Development Programme
      Uploaded by: Knoema
      Accessed On: 20 दिसम्बर, 2018
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      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
    • दिसम्बर 2010
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
      Accessed On: 31 जुलाई, 2013
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      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.
    • सितम्बर 2011
      Source: Institute for Health Metrics and Evaluation
      Uploaded by: Knoema
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      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.
    • जनवरी 2019
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 02 सितम्बर, 2019
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      The data are from the linked infant birth and death files. To create linked data files, death certificates are linked with corresponding birth certificates for infants who die in the U.S. before their first birthday. The linked file is used for calculating infant mortality rates by race and ethnicity because these variables are more accurately collected on the birth certificate than the death certificate. For this table, the period linked file is used (the numerator of the mortality rates includes the deaths occurring in a given calendar year whether the birth occurred in that year or the preceding year).
    • मई 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 03 जून, 2019
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      .. - 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.
    • सितम्बर 2017
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 21 जून, 2018
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      Influenza vaccination coverage estimates for persons 6 months and older by State, HHS Region, and the United States, National Immunization Survey-Flu (NIS-Flu) and Behavioral Risk Factor Surveillance System (BRFSS), 2010-11 through 2016-17 influenza seasons.
    • जुलाई 2013
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
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      This table displays statistics calculated from data from the National Hospital Ambulatory Medical Care Survey (NHAMCS). The data are from a national sample of visits to the emergency departments of general and short-stay hospitals, exclusive of Federal, military, and Veterans Administration hospitals in the United States
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 02 जुलाई, 2019
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    • अप्रैल 2017
      Source: International Comparisons
      Uploaded by: International Comparisons
      Accessed On: 29 अगस्त, 2019
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      Compared to the other 11 countries, United States has averaged more pregnancies, births, and abortions per 1,000 girls while having the lowest ratio of births to abortions.
  • L
    • जून 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 11 जून, 2019
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      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.
    • नवम्बर 2018
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 21 नवम्बर, 2018
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      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.
    • अप्रैल 2018
      Source: National Association of Insurance Commissioners
      Uploaded by: Knoema
      Accessed On: 10 मई, 2018
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    • अप्रैल 2018
      Source: National Association of Insurance Commissioners
      Uploaded by: Knoema
      Accessed On: 10 मई, 2018
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      Annual Statement Information for Life/Health Insurance Companies in 2016
    • नवम्बर 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 जनवरी, 2019
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      NOTES: Estimates are based on household interviews of a sample of the civilian noninstitutionalized population. This table is based on responses about all persons in the family. Data came from the Person file and were weighted using the Person weight. Unknowns for the columns were not included in the denominators when calculating percentages. Percentages may not add to totals due to rounding. "Total" includes other races not shown separately and persons with unknown education, family income, poverty status, and health insurance characteristics. Unless otherwise specified, estimates are age-adjusted using the projected 2000 U.S. population as the standard population and using six age groups: 0-11, 12-17, 18-44, 45-64, 65-74, and 75 and over. Estimates for age groups are not age-adjusted. For more information on the data source, methods, and definitions used for this table, refer to Technical Notes for Summary Health .
    • जनवरी 2019
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 21 अगस्त, 2019
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      In the United States, state laws require birth certificates to be completed for all births, and Federal law mandates national collection and publication of births and other vital statistics data. The National Vital Statistics System, the Federal compilation of these data, is the result of the cooperation between the National Center for Health Statistics (NCHS) and the states to provide access to national statistical information from birth certificates. For more information, see Birth Data .
  • M
    • अगस्त 2018
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2018
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      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.
    • सितम्बर 2019
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 04 नवम्बर, 2019
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      Medicaid enrollment includes Breast and Cervical Cancer Program recipients, February 2019 figures above are estimated based on incomplete data and will change, Source: PPS Data, HHSC Forecasting
    • फरवरी 2019
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 02 मई, 2019
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      NOTES: Medicaid Fee-For-Service (FFS) paid and partially paid inpatient hospital delivery claims were selected using the following DRG codes. Deliveries that occurred in other settings, such as birthing centers or homes, were excluded. MS-DRG codes 765-768 and 774-775 were used to identify FFS deliveries with discharge dates in FY2009 - FY2012. APR-DRG codes 5401-5404, 5411-5414, 5421-5424, and 5601-5604 were used to identify deliveries for FY2013-FY2015. Managed Care deliveries were selected from the Delivery Supplemental Payment (DSP) database. MCO cost was calculated by multiplying the DSP contract rate by the number of deliveries for each MCO plan. The DSP program does not include deliveries to MCO clients enrolled in STAR Health, STAR+PLUS, or MMP. The MCO Program excludes clients enrolled in Type Program 30. Deliveries are reported as the total number of unduplicated delivery dates per patient. Patients with multiple delivery claims on the same date are counted as having one delivery on that date. Some patients had more than one delivery date per fiscal year. Teenage mothers were defined as delivery patients who were under age 20 on the delivery date. Non-teenage mothers were defined as mothers who were age 20 or older on the delivery date.
    • सितम्बर 2018
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 04 अप्रैल, 2019
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      NOTES: Medicaid Fee-For-Service (FFS) paid and partially paid inpatient hospital delivery claims were selected using the following DRG codes. FFS deliveries that occurred in other settings, such as birthing centers or homes, were excluded. CMS-DRG codes 370-375 were used to identify FFS deliveries with discharge dates in FY2008. MS-DRG codes 765-768 and 774-775 were used to identify FFS deliveries with discharge dates in FY2009 - FY2012. APR-DRG codes 5401-5404, 5411-5414, 5421-5424, and 5601-5604 were used to identify deliveries in FY2013-FY2015. Managed Care deliveries were selected from the Delivery Supplemental Payment (DSP) database. The DSP Program does not include deliveries to MCO clients enrolled in STAR Health, STAR+PLUS, or MMP. The MCO Program excludes clients enrolled in Type Program 30. Number of clients during the measurement year were reported as the total number of unduplicated mothers with deliveries during that year. For patients with more that one delivery during the measurement year, only the first delivery date during that year was used for the analysis. Age was reported as the mother's age on her first delivery date during the measurement year. Teenage mothers were defined as delivery patients who were under age 20 on the delivery date. Non-teenage mothers were defined as mothers who were age 20 or older on the delivery date. Total deliveries during the five-year prior period were defined as the total number of unduplicated deliveries that occurred during the 5-year period (1,826 days) prior to the first delivery date in the measurement year. Clients with prior deliveries were defined as the unduplicated number of clients who had one or more deliveries during the prior five-year period. Percent with prior deliveries was computed as the total number of clients with one or more prior deliveries during the prior five-year period, divided by the total number of clients in the measurement year.
    • अप्रैल 2019
      Source: Medicaid
      Uploaded by: Knoema
      Accessed On: 02 अप्रैल, 2019
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      Note: For 2019 data is as of April 1 2019. This dataset provides eligibility levels in each state for key coverage groups that use Modified Adjusted Gross Income (MAGI), as of April 1, 2019. The data represent the principal, but not all, MAGI coverage groups in Medicaid, the Children’s Health Insurance Program (CHIP), and the Basic Health Program (BHP). All income standards are expressed as a percentage of the federal poverty level (FPL). The MAGI-based rules generally include adjusting an individual’s income by an amount equivalent to a 5% FPL disregard. Other eligibility criteria also apply, such as citizenship, immigration status, and state residency.
    • जुलाई 2019
      Source: U.S. Department of Health and Human Services
      Uploaded by: Knoema
      Accessed On: 30 अगस्त, 2019
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      Medical Expenditure Panel Survey MEPSnet Insurance Component (MEPSnet/IC), 2018   MEPS employer-based health insurance data are produced in the year following data collection. Private-sector data are posted in July and government data are posted in November. MEPSnet/IC is based on aggregate statistics, thus not all possible queries can be addressed. If the query is not possible, MEPSnet/IC will not allow you to choose certain parameters.
    • अगस्त 2018
      Source: Centers for Medicare and Medicaid Services
      Uploaded by: Knoema
      Accessed On: 22 मई, 2019
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    • फरवरी 2019
      Source: Centers for Medicare and Medicaid Services
      Uploaded by: Knoema
      Accessed On: 15 मई, 2019
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      The Part D Prescriber PUF is based on information from CMS’s Prescription Drug Event Standard Analytic File, which has final-action claims that are submitted by Medicare Advantage Prescription Drug (MAPD) plans and by stand-alone Prescription Drug Plans (PDP).
    • जून 2019
      Source: Mental Health America
      Uploaded by: Knoema
      Accessed On: 21 जून, 2019
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      The Access Ranking indicates how much access to mental health care exists within a state. The access measures include access to insurance, access to treatment, quality and cost of insurance, access to special education, and workforce availability. A high Access Ranking indicates that a state provides relatively more access to insurance and mental health treatment.
    • फरवरी 2015
      Source: U.S. Census Bureau
      Uploaded by: Knoema
      Accessed On: 20 सितम्बर, 2015
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      Midyear population for selected Countries
    • मार्च 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 20 मार्च, 2019
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      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.
    • मार्च 2019
      Source: U.S. Census Bureau
      Uploaded by: Knoema
      Accessed On: 12 जून, 2019
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      Model-based Small Area Health Insurance Estimates (SAHIE), 2017
    • अगस्त 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 19 अक्तूबर, 2015
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      In the United States, state laws require death certificates to be completed for all deaths, and Federal law mandates national collection and publication of deaths and other vital statistics data. The National Vital Statistics System, the Federal compilation of these data, is the result of the cooperation between the National Center for Health Statistics (NCHS) and the states to provide access to national statistical information from death certificates
    • अगस्त 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 03 नवम्बर, 2015
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      In the United States, State laws require death certificates to be completed for all deaths, and Federal law mandates national collection and publication of data on deaths. The National Vital Statistics System, the Federal compilation of these data, is the result of the cooperation between the National Center for Health Statistics (NCHS) and the States to provide access to statistical information from death certificates
  • N
    • फरवरी 2019
      Source: World Health Organization
      Uploaded by: Knoema
      Accessed On: 08 फरवरी, 2019
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      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
    • जून 2019
      Source: Substance Abuse and Mental Health Services Administration, U.S. Department of Health & Human Services
      Uploaded by: Knoema
      Accessed On: 18 सितम्बर, 2019
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  • O
    • अगस्त 2018
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2018
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      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.
    • नवम्बर 2017
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 28 फरवरी, 2019
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      BRFSS: Table of Overweight and Obesity (BMI) Based on Behavioral Risk Factor Surveillance System (BRFSS) Prevalence Data (2011 to present) 2011 to present. BRFSS combined land line and cell phone prevalence data. BRFSS is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death
  • P
    • सितम्बर 2014
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2018
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      Description not available
    • अगस्त 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 06 अगस्त, 2019
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    • मई 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 03 जून, 2019
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      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.
    • मई 2015
      Source: Earth Policy Institute
      Uploaded by: Knoema
      Accessed On: 26 जून, 2015
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      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).
    • जून 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 20 अगस्त, 2019
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      In the United States, state laws require birth certificates to be completed for all births, and Federal law mandates national collection and publication of births and other vital statistics data. The National Vital Statistics System, the Federal compilation of these data, is the result of the cooperation between the National Center for Health Statistics (NCHS) and the states to provide access to national statistical information from birth certificates. For more information, see Birth Data
    • जुलाई 2019
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 01 अगस्त, 2019
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      Description not available
    • जुलाई 2019
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 01 अगस्त, 2019
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      Description not available
    • सितम्बर 2014
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2018
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      Description not available
  • R
    • सितम्बर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 24 सितम्बर, 2019
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      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).
    • जुलाई 2019
      Source: Organisation for Economic Co-operation and Development
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      Accessed On: 02 जुलाई, 2019
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      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.
    • नवम्बर 2019
      Source: ClinicalTrials.gov
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      Accessed On: 14 नवम्बर, 2019
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      Registered studies by ClinicalTrials.gov, As of November 6, 2019
    • नवम्बर 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 जनवरी, 2019
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      Respondent-assessed health status for children under age 18 years by selected characteristics: United States TRespondent-assessed health status among adults aged 18 and over, by selected characteristics: United States
    • अक्तूबर 2019
      Source: Organisation for Economic Co-operation and Development
      Uploaded by: Knoema
      Accessed On: 08 अक्तूबर, 2019
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      Classification(s) used: ICHA-FS: Classification of revenues of health care financing schemes ICHA-HF: Classification of health care financing schemes
  • S
    • मई 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 03 जून, 2019
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      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.
    • सितम्बर 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2015
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      The data are from the National Health Interview Survey (NHIS), a continuous national survey of the civilian noninstitutionalized population of the United States. Data are collected through in-person computer assisted household interviews
    • सितम्बर 2019
      Source: Social Progress Imperative
      Uploaded by: Knoema
      Accessed On: 14 अक्तूबर, 2019
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        Data cited at: Social Progress Index https://www.socialprogress.org/download 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 2019 Social Progress Index. Therefore, using the 2019 Social Progress Index framework and methodology, we provide comparable historical data for additional five years of the Social Progress Index, from 2014 to 2018.
    • अगस्त 2018
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2018
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      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.
    • मार्च 2019
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 19 मार्च, 2019
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      Source Table: 112, 113 and 114 Note: Health, United States, 2014 is the 38th report on the health status of the nation and is submitted by the Secretary of the Department of Health and Human Services to the President and the Congress of the United States in compliance with Section 308 of the Public Health Service Act. This report was compiled by the Centers for Disease Control and Prevention's (CDC) National Center for Health Statistics (NCHS). The Health, United States series presents an annual overview of national trends in health statistics. The report contains a Chartbook that assesses the nation's health by presenting trends and current information on selected measures of morbidity, mortality, health care utilization and access, health risk factors, prevention, health insurance, and personal health care expenditures. This year's Chartbook includes a Special Feature on the health of adults aged 55–64. The report also contains 123 Trend Tables organized around four major subject areas: health status and determinants, health care utilization, health care resources, and health care expenditures. A companion report—Health, United States: In Brief—features information extracted from the full report. The complete report, In Brief, and related data products are available on the Health, United States website.
    • फरवरी 2015
      Source: World Life Expectancy
      Uploaded by: Knoema
      Accessed On: 07 मई, 2015
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    • जून 2019
      Source: Sustainable Development Solutions Network
      Uploaded by: Knoema
      Accessed On: 09 जुलाई, 2019
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      Data Cited at - Sachs, J., Schmidt-Traub, G., Kroll, C., Lafortune, G., Fuller, G. (2019): Sustainable Development Report 2019. New York: Bertelsmann Stiftung and Sustainable Development Solutions Network (SDSN). The 2019 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.
  • T
    • मई 2019
      Source: U.S. Department of Health and Human Services
      Uploaded by: Knoema
      Accessed On: 21 जून, 2019
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      Teen birth rates differ substantially by age, racial and ethnic group, and region of the country. Most adolescents who give birth are 18 or older; in 2016, 74 percent of all teen births occurred to 18- to 19-year-olds. Birth rates are also higher among Hispanic and black adolescents than among their white counterparts. In 2016, Hispanic adolescent females ages 15-19 had a higher birth rate (31.9 births per 1,000 adolescent females) than black adolescent females (29.3) and white adolescent females (14.3). To help put these differences in perspective, estimates from 2013 show that eight percent of white adolescent females will give birth by their 20th birthday, as will 16 percent of black adolescent females and 17 percent of Hispanic adolescent females. Although Hispanics still have a higher teen birth rate than their black and white peers, the rate has declined substantially in recent years. Since 2007, the teen birth rate among Hispanics has declined by 58 percent, compared with declines of 53 percent for blacks and 47 percent for whites.
    • दिसम्बर 2017
      Source: Texas Department of State Health Services
      Uploaded by: Knoema
      Accessed On: 13 दिसम्बर, 2018
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      Texas Primary Care Physicians & Psychiatrists by Health Region. Table 28: Infant, Neonatal, Fetal, Perinatal, and Maternal Deaths by Public Health Region, County and City of Residence Texas  (Rates, Ratios Per 1,000 Live Births).
    • सितम्बर 2018
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 26 दिसम्बर, 2018
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      Notes: The statewide numbers reflect the unduplicated number of children served in comprehensive and follow along services. Therefore, the sum of the counts for children served across counties does not equal the statewide counts. The projected population data are based on the number of children age 0 to 1, 1 to 2, and 2 to 3 in 2015 and the number of births in 2016, which is the children age 0 to 1 in 2016. A child who received comprehensive services and follow along services is counted only once in the total for the county. This provides a total count for each county that is an unduplicated count of children. A child who received services in a program in a county and then transferred to another program in the same county is counted only once; a child who transferred to another program in a different county is counted once in each county.
    • दिसम्बर 2015
      Source: Texas Health and Human Services
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      Accessed On: 11 सितम्बर, 2018
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      NOTES: Drug claims and acute care claims are based on the date of service. Behavioral Health expenditures for the acute care claims and encounters are based on a primary diagnosis code of 290-314.99. Psychotropic drug claims were identified as filled prescriptions with an AHFS codes beginning with 2812, 2816, 2820, 2824, 2828, or 2892. CHIP Perinate clients are included within all CHIP Behavioral Health Expenditures and are defined as follows: Risk Group 305: Risk Group 306: Long term supports and services claims (claims with Hdr_Care_Type='L') were excluded from the analysis. Prepared by Data Quality & Dissemination, Strategic Decision Support, HHSC. November 2016 (vp) Source: TX Medicaid Vendor Drug database, HHSC; 8 Month Eligibility database, HHSC; CHIP database, HHSC; CHIP DSP database, HHSC; AHQP Claims Universe, TMHP; Enc_Best Picture Universe, TMHP. Filename: TX Medicaid Behavioral Health Expenditures SFY15_primdiag_final.xlsx
    • नवम्बर 2019
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 05 नवम्बर, 2019
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    • फरवरी 2018
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 15 मई, 2019
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      NOTES: Undocumented aliens were identified as clients enrolled in Medicaid Type Program code 30 and Program code 100 (FFS Program). Fee-For-Service (FFS) paid and partially paid inpatient hospital delivery claims for Undocumented Aliens were selected using the following DRG codes. Total claims may include multiple claims per delivery date and multiple delivery dates per patient. Deliveries that occurred in other settings, such as birthing centers or homes, were excluded.   CMS-DRG codes 370-375 were used to identify deliveries with discharge dates before 10/1/2007.   MS-DRG codes 765-768 and 774-775 were used to identify deliveries with discharge dates on or after       10/1/2007.  APR-DRG codes 5401-5404, 5411-5414, 5421-5424, and 5601-5604 were used to identify deliveries with   admission dates on or after 9/1/2012. Deliveries are reported as the total number of unique delivery dates per patient. Patients with multiple delivery claims on the same date are counted as having one delivery on that date. Patients with multiple delivery dates are counted as having more than one delivery.
    • दिसम्बर 2016
      Source: Texas Health and Human Services
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      Accessed On: 11 सितम्बर, 2018
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      Note: Data include Fee-For-Service (FFS) and managed care (MCO) porgrams. Managed care health plans are paid on a capitation basis. Texas Medicaid does not reimburse individual providers under contract with the health plans.   Submitted procedure codes in FFS claims are not used for identifying relevant claims, effectively excluding most of SHARS providers from the analysis. About 0.26% of all claims/encounters in the analytic dataset are for SHARS providers, accounting for 0.04% of the amount paid reported.   Expenditures reflect client services only and do not include administrative, capitations, supplemental payments, DSH or UPL dollars.
    • दिसम्बर 2016
      Source: Texas Health and Human Services
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      Accessed On: 10 सितम्बर, 2018
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      Notes:  1) MCO medical cost was reported as the total monthly capitated cost for clients enrolled in Type Programs 40 and 42. Cost data were not available for delivery clients enrolled in other Type Programs. The MCO Program excludes clients enrolled in Type Program 30.   2) MCO delivery cost was calculated using the Delivery Supplemental Payment (DSP) program contract rates. The DSP program does not include deliveries to MCO clients enrolled in STAR Health, STAR+PLUS, or MMP. The MCO Program excludes clients enrolled in Type Program 30.   3) MCO prescription drug cost was reported as the total monthly capitated prescription drug cost for clients enrolled in Type Programs 40 and 42. Prescription drug cost data were not available for clients enrolled in other Type Programs. The MCO Program excludes clients enrolled in Type Program 30. The MCO prescription drug program began in FY2012, so MCO cost data were $0 for FY2008 - FY2011.   4) Total MCO deliveries were calculated as the total number of unduplicated delivery dates for clients with deliveries during the fiscal year. The MCO Program excludes clients enrolled in Type Program 30.     5) Estimated infant care cost for 1 year was calculated by multiplying the average monthly newborn cost by the number of deliveries times 12 months. The estimate wasn't adjusted for multiple births, fetal deaths, or attrition. The following monthly cost averages were used to calculate infant care cost for each fiscal year:   6) FFS and MCO cost data for SFY2012 and subsequent years may be different from program cost data in prior years. The MCO program expanded on March 1, 2012 to incorporate all PCCM clients. The expansion caused a reduction in FFS/PCCM deliveries and related services and an increase in MCO deliveries and related services in SFY2012 compared to prior years.  
    • दिसम्बर 2017
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 11 सितम्बर, 2018
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    • दिसम्बर 2015
      Source: Texas Health and Human Services
      Uploaded by: Knoema
      Accessed On: 11 सितम्बर, 2018
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      Long-acting reversible contraceptive (LARC) claims were defined as contraceptive implants and intrauterine devices using procedure codes 11981, 58300, J7300, J7301, J7302, and J7307. All other procedure codes were categorized as "Other Contraceptive Services". Medicaid prescription drugs used for contraception were defined using HIC3, AHFS, General Therapeutic Class, and Standard Therapeutic Class codes (see detailed list in the "Notes" tab). All payment status codes were included in the analysis. Paid claims (e.g., status code = 'PD') were used to compute unduplicated client counts and claim counts. All claims (e.g., status code = 'PD', 'RV', 'PR') were used to compute total cost. Long-acting reversible contraceptive (LARC) prescriptions were defined as contraceptive implants and intrauterine devices, using HIC3 code X1C. Women's Health Program (WHP) clients were identified as women enrolled in Medicaid Type Program code 68 between 9/1/2011 and 8/31/2012. Texas Women's Health Program (TWHP) clients were identified as women enrolled in Medicaid Type Program code 68 between 9/1/2012 and 8/31/2014. Clients were enrolled in only one Medicaid program per calendar month, but they could be enrolled in both WHP/TWHP and other Medicaid programs during the same fiscal year. Contraceptive claims and prescriptions for WHP/TWHP clients were identified by matching WHP/TWHP enrollment files with all contraceptive claims and prescription drug claims by client id and calendar month. All contraceptive claims that were not provided to WHP/TWHP clients were identified as Medicaid claims. LIMITATIONS: Diagnosis code was not used in the analysis to differentiate contraceptive-related services from general medical services. In addition, the analysis was not restricted to females, so the results for some contraceptive-related procedure codes that can also be used for non-contraceptive purposes may have inadvertently included males. The following procedure codes may include general medical services in addition to contraceptive-related services, which may overstate the results for contraceptive services: 96372 - Injection, Therapeutic, Prophalactic, or Diagnostic J3490 - Injection, Drugs Unclassified 00840 - Anesthetic, Surgery to Lower Abdomen  
    • जनवरी 2018
      Source: RAND Corporation
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      Accessed On: 24 जनवरी, 2018
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      Given the potential adverse effects of insufficient sleep on health, well-being and productivity, the consequences of sleep-deprivation have far-reaching economic consequences. Hence, in order to raise awareness of the scale of insufficient sleep as a public-health issue, comparative quantitative figures need to be provided for policy- and decision-makers, as well as recommendations and potential solutions that can help tackling the problem.
    • फरवरी 2016
      Source: Advanced Medical Technology Association
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      Accessed On: 28 अप्रैल, 2016
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    • दिसम्बर 2015
      Source: United Nations Statistics Division
      Uploaded by: Sandeep Reddy
      Accessed On: 19 अगस्त, 2017
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      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
    • फरवरी 2019
      Source: Bloomberg
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      Accessed On: 15 अक्तूबर, 2019
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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.
    • अप्रैल 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 22 अप्रैल, 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).
    • जुलाई 2019
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 01 अगस्त, 2019
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      Description not available
    • सितम्बर 2014
      Source: International Labour Organization
      Uploaded by: Knoema
      Accessed On: 31 अगस्त, 2018
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      Description not available
    • जून 2019
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 11 जून, 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.
    • सितम्बर 2018
      Source: American Hospital Association
      Uploaded by: Knoema
      Accessed On: 28 सितम्बर, 2018
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  • U
    • नवम्बर 2015
      Source: Agency for Healthcare Research and Quality, U.S. Department of Health & Human Services
      Uploaded by: Knoema
      Accessed On: 28 फरवरी, 2016
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    • नवम्बर 2015
      Source: Agency for Healthcare Research and Quality, U.S. Department of Health & Human Services
      Uploaded by: Knoema
      Accessed On: 28 फरवरी, 2016
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    • नवम्बर 2015
      Source: Agency for Healthcare Research and Quality, U.S. Department of Health & Human Services
      Uploaded by: Knoema
      Accessed On: 28 फरवरी, 2016
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    • दिसम्बर 2015
      Source: World Health Organization
      Uploaded by: Knoema
      Accessed On: 15 सितम्बर, 2017
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    • अक्तूबर 2014
      Source: United Nations Economic Commission for Europe
      Uploaded by: Knoema
      Accessed On: 16 जून, 2016
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    • अक्तूबर 2015
      Source: Joint United Nations Programme on HIV/AIDS
      Uploaded by: Sandeep Reddy
      Accessed On: 26 फरवरी, 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.
    • नवम्बर 2018
      Source: DevInfo
      Uploaded by: Knoema
      Accessed On: 05 दिसम्बर, 2018
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      This database contains country-reported GAM data. For HIV epidemiological estimates, as well as ART and PMTCT indicators
    • जुलाई 2019
      Source: Joint United Nations Programme on HIV/AIDS
      Uploaded by: Knoema
      Accessed On: 13 अगस्त, 2019
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      This Dataset contains Regional and National level Data.
    • जून 2019
      Source: Knoema
      Uploaded by: Knoema
      Accessed On: 05 अगस्त, 2019
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      State-level Data on Demographics, Economy, Labor, Income and Welfare, Crime, Health, Education and Agriculture.   Two indicators: "Enrollment in public elementary and secondary school" and "Public high school graduates" have forecast data points. References: http://nces.ed.gov/ http://quickstats.nass.usda.gov/ http://usda.mannlib.cornell.edu/ http://wonder.cdc.gov/mortSQL.html http://www.acf.hhs.gov/ http://www.bea.gov/iTable http://www.bls.gov/mls/ http://www.census.gov/ http://www.dhs.gov/ http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s http://www.infoplease.com/ http://www.usgovernmentspending.com/  
    • नवम्बर 2017
      Source: Centers for Medicare and Medicaid Services
      Uploaded by: Knoema
      Accessed On: 24 अक्तूबर, 2018
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      Per Capita Health Care and Health Insurance Spendings in United States
    • मई 2019
      Source: The Leapfrog Hospital Safety Grade
      Uploaded by: Knoema
      Accessed On: 09 अगस्त, 2019
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      Hospitals across the country show a lot of variation when it comes to patient safety. Here, states are ranked based on the number of “A” hospitals they have compared to the total number of graded hospitals on the Spring 2019 Leapfrog Hospital Safety Grade. State rankings from the previous grading cycle, Fall 2018, are also displayed.
    • नवम्बर 2018
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 जनवरी, 2019
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      Source: Usual place of health care, and type of place, for children under age 18 years, by selected characteristics: United States Having a usual place of health care, and of type of place, among adults aged 18 and over, by selected characteristics: United States
  • V
    • सितम्बर 2015
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Knoema
      Accessed On: 30 अक्तूबर, 2015
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      The data are from the National Health Interview Survey (NHIS), a continuous national survey of the civilian noninstitutionalized population of the United States. Data are collected through in-person computer assisted household interviews
  • W
    • मई 2012
      Source: World Health Organization
      Uploaded by: Knoema
      Accessed On: 01 जून, 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.
    • मार्च 2016
      Source: U.S. Centers for Disease Control and Prevention
      Uploaded by: Sandeep Reddy
      Accessed On: 27 जून, 2017
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      United States : Women’s Health Statistics
    • अक्तूबर 2019
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 06 नवम्बर, 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
    • मई 2014
      Source: World Health Organization
      Uploaded by: Knoema
      Accessed On: 18 जून, 2014
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      Includes datasets on communicable diseases, human resources for health, noncommunicable diseases and world health statistics.
    • अक्तूबर 2013
      Source: World Bank
      Uploaded by: Knoema
      Accessed On: 24 नवम्बर, 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
    • अगस्त 2018
      Source: Wikipedia
      Uploaded by: Knoema
      Accessed On: 14 अगस्त, 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

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