sources

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Countries with no application for accreditation with the Paris Principles, D status  (1 = YES; 0 = NO) \n \n Variable code: SG_NHR_NOAPPLN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-0a-01.pdf \n \n Detailed sources: Source: The Office of the United Nations High Commissioner for Human Rights (OHCHR) in collaboration with Global Alliance of National Human Rights Institutions (GANHRI).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Statistics Division"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Countries with National Human Rights Institutions not fully compliant with the Paris Principles, B status (1 = YES; 0 = NO) \n \n Variable code: SG_NHR_INTEXSTN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-0a-01.pdf \n \n Detailed sources: Source: The Office of the United Nations High Commissioner for Human Rights (OHCHR) in collaboration with Global Alliance of National Human Rights Institutions (GANHRI).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Statistics Division"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Countries with National Human Rights Institutions and no status with the Paris Principles, C status (1 = YES; 0 = NO) \n \n Variable code: SG_NHR_NOSTUSN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-0a-01.pdf \n \n Detailed sources: Source: The Office of the United Nations High Commissioner for Human Rights (OHCHR) in collaboration with Global Alliance of National Human Rights Institutions (GANHRI).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Statistics Division"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of countries that applied for accreditation as independent National Human Rights Institutions in compliance with the Paris Principles (%) \n \n Variable code: SG_NHR_INTEXST \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-0a-01.pdf \n \n Detailed sources: Source: The Office of the United Nations High Commissioner for Human Rights (OHCHR) in collaboration with Global Alliance of National Human Rights Institutions (GANHRI).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Statistics Division"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Countries with National Human Rights Institutions in compliance with the Paris Principles, A status (1 = YES; 0 = NO) \n \n Variable code: SG_NHR_IMPLN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-0a-01.pdf \n \n Detailed sources: Source: The Office of the United Nations High Commissioner for Human Rights (OHCHR) in collaboration with Global Alliance of National Human Rights Institutions (GANHRI).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Statistics Division"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of countries with independent National Human Rights Institutions in compliance with the Paris Principles (%) \n \n Variable code: SG_NHR_IMPL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-0a-01.pdf \n \n Detailed sources: Source: The Office of the United Nations High Commissioner for Human Rights (OHCHR) in collaboration with Global Alliance of National Human Rights Institutions (GANHRI).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Statistics Division"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of children under 5 years of age whose births have been registered with a civil authority (% of children under 5 years of age) \n \n Variable code: SG_REG_BRTH \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-09-01.pdf \n \n Detailed sources: DHS, MICS, other national surveys, censuses and vital registration systems DHS 2015 DHS 2017-18 MICS 2018-19 UNSD Population and Vital Statistics Report, January 2021, latest update on 4 Jan 2022 DHS 2015-16 DHS 2006 MICS 2019-20 Information and e-Government Authority MICS 2019 MICS 2012 MICS 2010 EDSA 2016 MICS 2006 Demographic Survey 2017 Estat\u00edsticas do Registro Civil MICS 2015 Vital registration, Immigration and National Registration Department DHS 2016-17 Vital registration data DHS 2014 DHS 2018 Censo 2010 DHS 2006-07 Estad\u00edsticas Vitales 2011 DHS 2012 MICS 2014-15 MICS 2017-18 Vital statistics 2017 INEC 2013 Ministry of Public Administration Statistics Denmark Registro Civil 2020 General Directorate for Statistics and Census DHS 2011 DHS 2016 MICS 2021 Preliminary report WMS 2017 DHS 2019-20 Federal Statistical Office ENSMI 2014-15 NFHS 2015-16 Susenas 2021 as part of Welfare Statistics 2021 MIDHS 2010 MICS 2018 MICS 2016 MICS 2009 MICS 2017 MICS 2015-16 Statistics Lithuania 2020 MICS 2013-14 INEGI. Population and Housing Census 2020 MICS 2013 National Civil Authority, Registry Department, 2017 ENPSF 2018 AIS 2015 Ministry of Health and Civil Registration Intercensal Survey 2016 Vital statistics 2013 DHS 2013 ENDESA 2011/12 ICHNS 2017 INEC, Encuesta de Prop\u00f3sitos M\u00faltiples DHS 2016-18 DGEEC 2015-18 ENAPRES 2020 DHS 2017 Polish Ministry of Interior and Administration Portuguese Civil Registry Office Vital statistics, Ministry of Public Health Live births statistical bulletins, National Institute of Statistics, 2020 Household health survey 2018 Continuous DHS 2019 DHS 2019 Local birth registration, Immigration and Checkpoints Authority, 2020 Vital statistics, Statistical Office of Slovak Republic 2020 MICS 2014 SDHS 2020 Recorded live births 2017 SHHS-2 2010 MICS 2011 Ministry of Health and Prevention 2018 DHS 2010 Vital registration system 2017",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportions of positions in the judiciary compared to national distributions, Constitutional Court (ratio) \n \n Variable code: SG_DMK_JDC_CNS \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: STATISTIK AUSTRIA Supreme Judicial Council Administrative data from: High Judicial and Prosecutorial Council of Bosnia and Herzegovina, Court of BiH, Court of FBiH and Court of RS. Personnel records of Ministry of Justice and Public Administration of the Republic of Croatia Administrative records of the Judicial service of the Republic. Czech Statistical\u00a0 Office Denmark \u2013 Register based Labour Force Survey Ministry of Justice of the Republic of Estonia Statistics Finland Palestinian central bureau of statistic Federal Office of Justice Supreme Court of Judicature\nCourt of Appeal Judges and Registrars Division Data provided by the Department for Ensuring the Activities of Courts under the Supreme Court of the Republic of Kazakhstan. Judiciary; 2 19 KPH Census https://www.gerichte.li/  for Supreme Court (OGH), Court of Justice, Court of Appeal\nhttp://www.staatskalender.li/gerichte-des-oeffentlichen-rechts  for Constitutional Court, Administrative Court Register of Judges for data on judges, Register of the Civil servants for data on registrars. The Judiciary National level: Censo Nacional de Impartici\u00f3n de Justicia Federal 2 2 \nhttps://www.inegi.org.mx/programas/cnijf/2 2 /\nSub-national level: Censo Nacional de Impartici\u00f3n de Justicia Estatal 2 2 \nhttps://www.inegi.org.mx/programas/cnije/2 2 / Court Administration Agency, Ministry of Justice Direcci\u00f3n Administrativa de Estad\u00edsticas Judiciales \u00d3rgano Judicial HR and Financial System: ZSRK (based on SAP) Statistical Office of the Slovak Republic; Trexima RVE",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportions of positions in the judiciary compared to national distributions, Lower Courts (ratio) \n \n Variable code: SG_DMK_JDC_LWR \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: STATISTIK AUSTRIA Supreme Judicial Council Administrative data from: High Judicial and Prosecutorial Council of Bosnia and Herzegovina, Court of BiH, Court of FBiH and Court of RS. Personnel records of Ministry of Justice and Public Administration of the Republic of Croatia Administrative records of the Judicial service of the Republic. Czech Statistical\u00a0 Office Denmark \u2013 Register based Labour Force Survey Judiciary Council Staff Information Ministry of Justice of the Republic of Estonia Statistics Finland Palestinian central bureau of statistic Federal Office of Justice Administrative data from Ministry of Justice Supreme Court of Judicature\nCourt of Appeal Judges and Registrars Division Data provided by the Department for Ensuring the Activities of Courts under the Supreme Court of the Republic of Kazakhstan. Judiciary; 2 19 KPH Census Central Statistical Bureau of Latvia Register of Judges for data on judges, Register of the Civil servants for data on registrars. National Statistical Office of Malta National level: Censo Nacional de Impartici\u00f3n de Justicia Federal 2 2 \nhttps://www.inegi.org.mx/programas/cnijf/2 2 /\nSub-national level: Censo Nacional de Impartici\u00f3n de Justicia Estatal 2 2 \nhttps://www.inegi.org.mx/programas/cnije/2 2 / Court Administration Agency, Ministry of Justice Direcci\u00f3n Administrativa de Estad\u00edsticas Judiciales \u00d3rgano Judicial HR and Financial System: ZSRK (based on SAP) Statistical Office of the Slovak Republic; Trexima RVE",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportions of positions in the judiciary compared to national distributions, Higher Courts (ratio) \n \n Variable code: SG_DMK_JDC_HGR \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: STATISTIK AUSTRIA Supreme Judicial Council Administrative data from: High Judicial and Prosecutorial Council of Bosnia and Herzegovina, Court of BiH, Court of FBiH and Court of RS. Personnel records of Ministry of Justice and Public Administration of the Republic of Croatia Czech Statistical\u00a0 Office Denmark \u2013 Register based Labour Force Survey Judiciary Council Staff Information Ministry of Justice of the Republic of Estonia Statistics Finland Palestinian central bureau of statistic Federal Office of Justice Administrative data from Ministry of Justice Supreme Court of Judicature\nCourt of Appeal Judges and Registrars Division Data provided by the Department for Ensuring the Activities of Courts under the Supreme Court of the Republic of Kazakhstan. Judiciary; 2 19 KPH Census Central Statistical Bureau of Latvia https://www.gerichte.li/  for Supreme Court (OGH), Court of Justice, Court of Appeal\nhttp://www.staatskalender.li/gerichte-des-oeffentlichen-rechts  for Constitutional Court, Administrative Court Register of Judges for data on judges, Register of the Civil servants for data on registrars. National Statistical Office of Malta National level: Censo Nacional de Impartici\u00f3n de Justicia Federal 2 2 \nhttps://www.inegi.org.mx/programas/cnijf/2 2 /\nSub-national level: Censo Nacional de Impartici\u00f3n de Justicia Estatal 2 2 \nhttps://www.inegi.org.mx/programas/cnije/2 2 / Court Administration Agency, Ministry of Justice Direcci\u00f3n Administrativa de Estad\u00edsticas Judiciales \u00d3rgano Judicial HR and Financial System: ZSRK (based on SAP) Statistical Office of the Slovak Republic; Trexima RVE",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportions of positions in the judiciary compared to national distributions (ratio) \n \n Variable code: SG_DMK_JDC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: STATISTIK AUSTRIA Supreme Judicial Council Administrative data from: High Judicial and Prosecutorial Council of Bosnia and Herzegovina, Court of BiH, Court of FBiH and Court of RS. The Supreme Court of the Union Personnel records of Ministry of Justice and Public Administration of the Republic of Croatia Administrative records of the Judicial service of the Republic. Czech Statistical\u00a0 Office Ministry of Justice of the Czech Republic Register-based labour force statistics. Denmark \u2013 Register based Labour Force Survey Judiciary Council Staff Information Ministry of Justice of the Republic of Estonia Statistics Finland Palestinian central bureau of statistic Federal Office of Justice Administrative data from Ministry of Justice Division des Ressources Humaines du Minist\u00e8re de la justice / Chambre Nationale des Huissiers de Justice / Barreau de l'Ordre des Avocats / Chambre Nationale des Notaires de Guin\u00e9e Supreme Court of Judicature\nCourt of Appeal The Judiciary of the Hong Kong Special Administrative Region Judges and Registrars Division Ministry of Internal Affairs and Communications Data provided by the Department for Ensuring the Activities of Courts under the Supreme Court of the Republic of Kazakhstan. Judiciary; 2 19 KPH Census Central Statistical Bureau of Latvia https://www.gerichte.li/  for Supreme Court (OGH), Court of Justice, Court of Appeal\nhttp://www.staatskalender.li/gerichte-des-oeffentlichen-rechts  for Constitutional Court, Administrative Court Register of Judges for data on judges, Register of the Civil servants for data on registrars. MALDIVES BUREAU OF STATISTICS National Statistical Office of Malta The Judiciary National level: Censo Nacional de Impartici\u00f3n de Justicia Federal 2 2 \nhttps://www.inegi.org.mx/programas/cnijf/2 2 /\nSub-national level: Censo Nacional de Impartici\u00f3n de Justicia Estatal 2 2 \nhttps://www.inegi.org.mx/programas/cnije/2 2 / Court Administration Agency, Ministry of Justice National Bureau of Statistics We have used register-based data in order to report the number of judiciary personnel. We were not able to disaggregate by type of court. You will therefore only get the total numbers of personnel in the judiciary but they are disaggregated by type of position and for each socio-demographic characteristics, except for Disability status. \n\nHere you can read more about our register-based data: https://www.ssb.no/en/arbeid-og-lonn/sysselsetting/statistikk/sysselsetting-registerbasert, \nand here for immigrants: https://www.ssb.no/en/arbeid-og-lonn/sysselsetting/statistikk/sysselsetting-blant-innvandrere-registerbasert\n\nThe numbers we report are based on a data collection containing personnel in the industry '84.23 : Justice and judicial activities' with the occupations '2611: Lawyers', '2612: Judges' or '2619: Legal professionals not elsewhere classified'. Read more about the classifications we use on industry (SIC 2  7: https://www.ssb.no/klass/klassifikasjoner/6) and occupations (ISCO- 8: https://www.ssb.no/klass/klassifikasjoner/7) in order to see what is included or not. We have used register-based data in order to report the number of judiciary personnel. We were not able to disaggregate by type of court. You will therefore only get the total numbers of personnel in the judiciary but they are disaggregated by type of position and for each socio-demographic characteristics, except for Disability status. \n\nHere you can read more about our register-based data: https://www.ssb.no/en/arbeid-og-lonn/sysselsetting/statistikk/sysselsetting-registerbasert, \nand here for immigrants: https://www.ssb.no/en/arbeid-og-lonn/sysselsetting/statistikk/sysselsetting-blant-innvandrere-registerbasert\n\nThe numbers we report are based on a data collection containing personnel in the industry '84.230: Justice and judicial activities' with the occupations '2611: Lawyers', '2612: Judges' or '2619: Legal professionals not elsewhere classified'. Read more about the classifications we use on industry (SIC 2007: https://www.ssb.no/klass/klassifikasjoner/6) and occupations (ISCO-08: https://www.ssb.no/klass/klassifikasjoner/7) in order to see what is included or not. Labour Force Survey 2 17/2 18 Micro Data Direcci\u00f3n Administrativa de Estad\u00edsticas Judiciales \u00d3rgano Judicial HR and Financial System: ZSRK (based on SAP) Statistical Office of the Slovak Republic; Trexima Instituto Nacional de Estad\u00edstica Statistics Sweden Structural Survey https://www.gov.uk/government/statistics/diversity-of-the-judiciary-2 21-statistics\n\nDiversity of the judiciary 2 21 statistics: Data tables (see table 3.1) RVE",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportions of positions in the public service compared to national distributions (ratio) \n \n Variable code: SG_DMK_PSRVC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: General Directorate of Taxation, social insurance contributors; INSTAT's calculation 2 16 Census Agency for Statistics of Bosnia and Herzegovina HRMIS Bulgaria National Statistics Institute Union Civil Service Board, Central Statistical Organization Administrative records (payroll of all public service employees kept by the Treasury of the Republic) Statistics Denmark \u2013 Register based Labour Force Survey Distributive breakdown of institutions that form the 111 sector (Central Administration) and 112 (Universities) Ministry of Finance, public staff and payroll database, annual data collection \u00a0Institut National de la Statistique et des \u00c9tudes \u00c9conomiques Institut National de la Statistique et des \u00c9tudes \u00c9conomiques General Personnel Council database Federal Statistical Office of Germany (Destatis) Estimations from Labour Force Survey, 2 2   Minist\u00e8re du Plan et du D\u00e9veloppement Economique, Institut National de la Statistique (INS), Bureau Central du Recensement(BCR) R\u00e9publique de Guin\u00e9 Census and Statistics Department, HKSAR, China badan kepegawain nasional Israel Central Bureau of Statistics LFS LFS Survey on Remuneration of Local Public Employees, Statistical Tables of Employment Status of National Public Employees in General Services https://www.gov.kz/memleket/entities/qyzmet?lang=ru. State Chancellery State social insurance Fund board (SODRA) Ministry of the Civil Service  MALDIVES BUREAU OF STATISTICS, MINISTRY OF NATIONAL PLANNING, HOUSING AND INFRASTRUCTURE Survey of employment , Ministry of Gender Equality & Family welfare Censo Nacional de Seguridad P\u00fablica Federal (CNSPF 2 19), Censo Nacional de Gobierno Federal (CNGF 2 2 ), Censo Nacional de Procuraci\u00f3n de Justicia Federal (CNPJF 2 2 ) Censo Nacional de Seguridad P\u00fablica Federal (CNSPF 2019), Censo Nacional de Gobierno Federal (CNGF 2020), Censo Nacional de Procuraci\u00f3n de Justicia Federal (CNPJF 2020) Employment, register-based Pakistan Bureau of Statistics Data on education personnel comes from 'Structure of Earnings Survey', carried out by Statistics Poland.; Data on front-desk administrative personnel comes from 'Structure of Earnings Survey', carried out by Statistics Poland.; Data on health personnel comes from 'Structure of Earnings Survey', carried out by Statistics Poland.; Data on health, education and front-desk administrative personnel comes from 'Structure of Earnings Survey', carried out by Statistics Poland. Data on police comes from the Report on the Size of police Employment, provided by the National Police Headquarters.; The National Police Headquarters: the Report on the Size of Police Employment Directorate general for administration and public employment Statistical Office of the Slovak Republic NACE Rev. 2:  P85 Education; NACE Rev. 2: O84.24 Public order and safety activities; NACE Rev. 2: Q86 Human health activities; NACE Rev.2: O84.1 Administration of the State and the economic and social policy of the community; SKIS 1311 Central government (excluding social security funds)  Excluded NACE Rev 2.:  O84.22  Defence activities NACE Rev. 2:  P85 Education; NACE Rev. 2: O84.24 Public order and safety activities; NACE Rev. 2: Q86 Human health activities; NACE Rev.2: O84.1 Administration of the State and the economic and social policy of the community; SKIS 1311 Central government (excluding social security funds)  Excluded NACE Rev 2.:  O84.220 Defence activities The Swedish Occupational Register swiss labour force suvey (together with central and sub-central) Annual Population Survey/Labour Force Survey ONSC Samoa Bureau of Statistics Central Statistical Organizations",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of youth in parliament (age 45 or below), Upper Chamber (Number) \n \n Variable code: SG_DMK_PARLYN_UC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of youth in parliament (age 45 or below), Upper Chamber (%) \n \n Variable code: SG_DMK_PARLYP_UC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Ratio of young members in parliament (Ratio of the proportion of young members in parliament (age 45 or below) in the proportion of the national population (age 45 or below)\u00a0with the age of eligibility as a lower bound boundary), Upper Chamber \n \n Variable code: SG_DMK_PARLYR_UC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of youth in parliament (age 45 or below), Lower Chamber or Unicameral (Number) \n \n Variable code: SG_DMK_PARLYN_LC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of youth in parliament (age 45 or below), Lower Chamber or Unicameral (%) \n \n Variable code: SG_DMK_PARLYP_LC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Ratio of young members in parliament (Ratio of the proportion of young members in parliament (age 45 or below) in the proportion of the national population (age 45 or below)\u00a0with the age of eligibility as a lower bound boundary), Lower Chamber or Unicameral \n \n Variable code: SG_DMK_PARLYR_LC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of chairs of permanent committees, by age sex and focus of the committee, Upper Chamber \n \n Variable code: SG_DMK_PARLCC_UC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of speakers in parliament, by age and sex, Upper Chamber \n \n Variable code: SG_DMK_PARLSP_UC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Ratio for female members of parliaments (Ratio of the proportion of women in parliament in the proportion of women in the national population\u00a0with the age of eligibility as a lower bound boundary), Upper Chamber \n \n Variable code: SG_DMK_PARLMP_UC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of chairs of permanent committees, by age sex and focus of the committee, Lower Chamber or Unicameral \n \n Variable code: SG_DMK_PARLCC_LC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of speakers in parliament, by age and sex , Lower Chamber or Unicameral \n \n Variable code: SG_DMK_PARLSP_LC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Ratio for female members of parliaments (Ratio of the proportion of women in parliament in the proportion of women in the national population\u00a0with the age of eligibility as a lower bound boundary), Lower Chamber or Unicameral \n \n Variable code: SG_DMK_PARLMP_LC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of chairs of permanent committees, by age sex and focus of the committee, Joint Committees \n \n Variable code: SG_DMK_PARLCC_JC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-16-07-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Primary government expenditures as a proportion of original approved budget (%) \n \n Variable code: GF_XPD_GBPC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-06-01.pdf \n \n Detailed sources: Public Expenditure and Financial Accountability\u00a0(PEFA). Ministry of Finance (MoF).",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Public Expenditure and Financial Accountability program via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Prevalence rate of bribery, by sex (%) \n \n Variable code: IU_COR_BRIB \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-05-01.pdf \n \n Detailed sources: UNODC and Islamic Republic of Afghanistan High Office of Oversight and Anti-Corruption (2013) Corruption in Afghanistan: Recent patterns and trends UNODC and INSTAT (2011) Corruption in Albania: Bribery as experienced by the population INDEC, Encuesta Nacional de Victimizaci\u00f3n 2017  en Argentina UNODC and Prism Research (2011) Corruption in Bosnia and Herzegovina: Bribery as experienced by the population  Institut National de Statistique: Base de donn\u00e9es de l'Enqu\u00eate sur les conditions de vie des m\u00e9nages de 2013/2014: Module Gouvernance, paix et s\u00e9curit\u00e9 UN-CTS Ministry of Interior - Service Statistique Minist\u00e9riel de la S\u00e9curit\u00e9 Int\u00e9rieure (SSMSI) Palestinian Central Bureau of Statistics,Perceptions Survey of Individuals on the Prevalence of Corruption in Palestine, 2013; PCBS_Database of Rule of Law and Access to Justice Survey 2018 UNODC and Central Statistical Office, Kurdistan Region Statistical Office and Commission of Integrity (2012) Corruption and integrity challenges in the public sector of Iraq UNODC and Prism Research (2011) Corruption in Kosovo: Bribery as experienced by the population Special Investigation Service of the Republic of Lithuania. The survey \"Lithuanian Map of Corruption\" Independent Commission Against Corruption of Mauritius. 2014 National Survey on Corruption UNODC and Prism Research (2011) Corruption in Montenegro: Bribery as experienced by the population Instance Centrale de Pr\u00e9vention de la Corruption. 2014 Enqu\u00eate Nationale sur la Corruption.  UNODC and National Bureau of Statistics (2017) Corruption in Nigeria. Bribery: public experience and response National Integrated System of Criminal Statistics. 2017 Panama's National Crime Victim Survey Philippine Office of the Ombudsman. 2013 National Household Survey on Experience with Corruption in the Philippines; 2016-2017: Philippine Statistics Authority and Office of the Ombudsman. Annual Poverty Indicators Survey (Module on Access to Government Services) Anti-Corruption Commission of Timor-Leste. 2011 Corruption Perception Survey  UNODC and Statistical Office of Republic of Serbia (2011) Corruption in Serbia: Bribery as experienced by the population National Governance Peace and Security Survey 2017 (not yet diseminated) UNODC and State Statistical Office (2011) Corruption in the former Yugoslav Republic of Macedonia: Bribery as experienced by the population The Prevention and Combating of Corruption Bureau of Tanzania. 2009 National Governance and Corruption Survey National Commission for Police Reform. 2007 Study on Victimization from Crime and Perception of the Police.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Bribery incidence (% of firms experiencing at least one bribe payment request) \n \n Variable code: IC_FRM_BRIB \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-05-02.pdf \n \n Detailed sources: WDI",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "World Bank"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of seized, found or surrendered arms whose illicit origin or context has been traced or established by a competent authority in line with international instruments \n \n Variable code: VC_ARM_SZTRACE \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-04-02.pdf \n \n Detailed sources: UNODC - IAFQ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Police reporting rate for robbery, by sex (%) \n \n Variable code: VC_PRR_ROBB \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-03-01.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Police reporting rate for sexual assault, by sex (%) \n \n Variable code: VC_PRR_SEXV \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-03-01.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Police reporting rate for physical assault, by sex (%) \n \n Variable code: VC_PRR_PHYV \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-03-01.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Unsentenced detainees as a proportion of overall prison population (%) \n \n Variable code: VC_PRS_UNSNT \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-03-02.pdf \n \n Detailed sources: UNODC World Prison Brief - Institute for Crime and Justice Policy Research (WPB-ICPR) United Nations Surveys on Crime Trends and the Operations of Criminal Justice Systems (UN-CTS) United Nations Survey on Crime Trends and Operations of Criminal Justice Systems and World Prison Brief-Institute for Crime and Justice Policy Research (WPB-ICPR) United Nations Surveys on Crime Trends and the Operations of Criminal Justice Systems (UN-CTS) and National Statistical Organization (NSO) United Nations Surveys on Crime Trends and the Operations of Criminal Justice Systems (UN-CTS) and Pre-Pub revision of Sustainable Development Goal indicators (SDG)",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Detected victims of human trafficking, by age and sex (number) \n \n Variable code: VC_HTF_DETV \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-02.pdf \n \n Detailed sources: GLOTIP Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Detected victims of human trafficking for sexual exploitaton, by age and sex (number) \n \n Variable code: VC_HTF_DETVSX \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-02.pdf \n \n Detailed sources: GLOTIP Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Detected victims of human trafficking for removal of organ, by age and sex (number) \n \n Variable code: VC_HTF_DETVOG \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-02.pdf \n \n Detailed sources: GLOTIP Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Detected victims of human trafficking for other purposes, by age and sex (number) \n \n Variable code: VC_HTF_DETVOP \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-02.pdf \n \n Detailed sources: GLOTIP Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Detected victims of human trafficking for forced labour, servitude and slavery, by age and sex (number) \n \n Variable code: VC_HTF_DETVFL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-02.pdf \n \n Detailed sources: GLOTIP Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of children aged 1-14 years who experienced physical punishment and/or psychological aggression by caregivers in last month (% of children aged 1-14 years) \n \n Variable code: VC_VAW_PHYPYV \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-01.pdf \n \n Detailed sources: DHS, MICS and other national surveys MICS 2010-11 DHS 2017-18 MICS 2018-19 DHS 2006 MICS 2019-20 MICS 2019 DHS 2015-16 MICS 2012 MICS 2011-12 MICS 2015 DHS 2015 DHS 2016-17 MICS 2014 MICS 2014-15 MICS 2017-18 MICS 2018 MICS 2021 Factsheets MICS 2006 MICS 2016 MICS 2011 MICS 2017 Baseline Survey 2015-16 (MICS) DHS 2019-20 MICS 2013-14 National Health and Morbidity Survey 2016 Ensanut 2018-19 DHS 2013 DHS 2012 MICS 2013 DHS 2017 DHS 2016 DHS 2014",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of population aged 18-29 years who experienced sexual violence by age\u00a018, by sex (% of population aged 18-29) \n \n Variable code: VC_VAW_SXVLN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-02-03.pdf \n \n Detailed sources: DHS, MICS and other national surveys DHS 2015 DHS 2015-16 DHS 2006 Violence against Women Survey 2015 DHS 2016-17 DHS 2014 DHS 2018, table produced at HQ DHS 2014-15 DHS 2012 DHS 2013-14 DHS 2017-18 DHS 2013 DHS 2016 DHS 2019-20 Violence Survey of the Palestinian Society, 2019 DHS 2008 MICS 2018-19, table produced at HQ Women's Health and Life Experiences Survey 2018 MICS 2019 Women's Health Survey 2016 DHS 2018 DHS 2005 AIS 2015 ENASSER 2014-15 DHS 2016-18 DHS 2017 DHS 2008-09 Continuous DHS 2019, table produced at HQ DHS 2019, table produced at HQ A National Prevalence Study on Exposure to Violence among Women and Men and its Association to Healt MICS 2019, table produced at HQ National Women's and Health Survey for Trinidad and Tobago 2017 MICS 2019-20 DHS 2007 Crime Survey for England and Wales 2016",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of cases of enforced disappearance of human rights defenders, journalists and trade unionists (Number) \n \n Variable code: VC_VOC_ENFDIS \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-10-01.pdf \n \n Detailed sources: The figures included here concern only verified cases of enforced disappearance of human rights defenders, journalists and trade unionists. OHCHR does not yet collect data on the number of cases of kidnapping, arbitrary detention or torture of human right",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Office of the High Commissioner for Human Rights"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Countries that adopt and implement constitutional, statutory and/or policy guarantees for public access to information \n \n Variable code: SG_INF_ACCSS \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-10-02.pdf \n \n Detailed sources: UNESCO Report on Public Access to Information; Global Right to Information Rating (Access Info & Center for Law and Democracy) https://www.rti-rating.org/country-data/",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UNESCO"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of cases of killings of human rights defenders, journalists and trade unionists \n \n Variable code: VC_VAW_MTUHRA \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-10-01.pdf \n \n Detailed sources: The figures included here concern only verified cases of killings of human rights defenders, journalists and trade unionists. OHCHR does not yet collect data on the number of cases of kidnapping, arbitrary detention or torture of human rights defenders, j",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Office of the High Commissioner for Human Rights"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Conflict-related death rate (civilians), by sex, age and cause of death (%) \n \n Variable code: VC_DTH_TOCVR \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-02.pdf \n \n Detailed sources: The figures include only direct conflict-related deaths of civilians recorded by the United Nations.  Office of the High Commissioner for Human Rights (OHCHR) ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Office of the High Commissioner for Human Rights"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of conflict-related deaths (civilians), by sex, age and cause of death (Number) \n \n Variable code: VC_DTH_TOCVN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-02.pdf \n \n Detailed sources: The figures include only direct conflict-related deaths of civilians recorded by the United Nations.  Office of the High Commissioner for Human Rights (OHCHR) ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Office of the High Commissioner for Human Rights"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of conflict-related deaths (civilians) per 100,000 population (Per 100,000 population) \n \n Variable code: VC_DTH_TOCV \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-02.pdf \n \n Detailed sources: The figures include only direct conflict-related deaths of civilians recorded by the United Nations. Office of the High Commissioner for Human Rights (OHCHR)",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Office of the High Commissioner for Human Rights"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of population that feel safe walking alone around the area they live (%) \n \n Variable code: VC_SNS_WALN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-04.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of population subjected to sexual violence in the previous 12 months, by sex (%) \n \n Variable code: VC_VOV_SEXL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-03.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of population subjected to robbery in the previous 12 months, by sex (%) \n \n Variable code: VC_VOV_ROBB \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-03.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of population subjected to physical violence in the previous 12 months, by sex (%) \n \n Variable code: VC_VOV_PHYL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-03.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office on Drugs and Crime"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of victims of intentional homicide, by sex (number) \n \n Variable code: VC_IHR_PSRCN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-01.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime (UNODC) National Statistical Organization World Health Organization Mortality Database National Criminal Justice Data as Collected through the United Nations Surveys on Crime Trends and the Operations of Criminal Justice Systems (UN-CTS) Pan American Health Organization (PAHO) Organization of American States (OAS) Gloal Study on Homicide 2019 - Revision United Nations Economic Commission for Europe (UNECE) World Health Organization (WHO) Anuario Brasileiro de Seguranca Publica Sustainable Development Goals / SDG Pre-Pub Ministry of Health Adhoc Collection of National Criminal Justice Data as collected by UNODC, referred to as UNODC Special Data Collection National Police Department of Peacekeeping Operations (UN-DPKO) Ministry of Interior Regional System of Standardized Indicators in Peaceful Coexistence and Citizen Security (IDB) Federal Bureau of Investigation (FBI)",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of victims of intentional homicide per 100,000 population, by sex (victims per 100,000 population) \n \n Variable code: VC_IHR_PSRC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-16-01-01.pdf \n \n Detailed sources: United Nations Office on Drugs and Crime (UNODC) National Statistical Organization World Health Organization Mortality Database National Criminal Justice Data as Collected through the United Nations Surveys on Crime Trends and the Operations of Criminal Justice Systems (UN-CTS) Pan American Health Organization (PAHO) Organization of American States (OAS) Gloal Study on Homicide 2019 - Revision United Nations Economic Commission for Europe (UNECE) World Health Organization (WHO) Anuario Brasileiro de Seguranca Publica Sustainable Development Goals / SDG Pre-Pub Ministry of Health Adhoc Collection of National Criminal Justice Data as collected by UNODC, referred to as UNODC Special Data Collection National Police Department of Peacekeeping Operations (UN-DPKO) Ministry of Interior Regional System of Standardized Indicators in Peaceful Coexistence and Citizen Security (IDB) Federal Bureau of Investigation (FBI)",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of countries with systems to track and make public allocations for gender equality and women's empowerment (%) \n \n Variable code: SG_GEN_EQPWN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-0c-01.pdf \n \n Detailed sources: Data are derived from country reporting on 13 binary questions on questionnaire, collected through the Global Partneship for Effective Development Cooperation",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of individuals who own a mobile telephone, by sex (%) \n \n Variable code: IT_MOB_OWN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-0b-01.pdf \n \n Detailed sources: NSIA Ministry of Post, Telecommunications, Technologies and Digital Instituto Nacional de Estat\u00edstica State Statistical Committee of the Republic of Azerbaijan State Statistical Committee Information and E-Government Authority Telecommunications Regulatory Authority (TRA) The Statistical Committee of the Republic of Armenia  Brazilian Internet Steering Committee Cetic.br Brazilian Institute of Geography and Statistics NIC.br Telecommunications Regulatory Commission Authority for Info-communications Technology Industry of Brunei Darussalam Central Statistical Organization ISTEEBU(Institut de Statistiques et d'Etudes Economiques du Burundi) Institut de Statistiques et d'tudes Economiques National Statistical Committee of the Republic of Belarus (Belstat) \u041d\u0430\u0446\u0438\u043e\u043d\u0430\u043b\u044c\u043d\u044b\u0439 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u043a\u043e\u043c\u0438\u0442\u0435\u0442 \u0420\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0438 \u0411\u0435\u043b\u0430\u0440\u0443\u0441\u044c National Institute of Statistics Institut National de la Statistique INSTITUTO NACIONAL DE ESTATISTICA Subsecretar\u00eda de Telecomunicaciones National Communications Commission Departamento Administrativo Nacional de Estadistica (DANE) Instituto Nacional de Estadisticas y Censos  Oficina Nacional de Estadisticas e Informacion  Statistical Service of Cyprus Czech Statistical Office Statistics Denmark Oficina Nacional de Estadistica Instituto Nacional de Estadistica y Censos Instituto Nacional de Estad\u00edsticas y Censos - INEC Direccion General de Estadistica y Censos Ministry of Communications and Information Technology Statistics Finland Institut National de la Statistique et des Etudes Economiques Direction de la Statistique et des Etudes D\u00e9mographiques National Statistics Office of Georgia National Statistics Office of Georgia - Geostat Palestinian Central Bureau of Statistics Central Statistical Office Instituto Nacional de Estadistica Institut Haitien de Statistique et d'nformatique Census and Statistics Department BPS-Statistics Indonesia Statistical Centre of Iran (SCI) Central Statistics Office Central Bureau of Statistics Italian National Institute of Statistics ARTCI Statistical Institute of Jamaica Ministry of Internal Affairs and Communications Committee on Statistics, Ministry of National Economy of the Republic of Kazakhstan Agency for Strategic planning and reforms of the Republic of Kazakhstan Bureau of National statistics KENYA NATIONAL BUREAU OF STATISTICS Kenya National Bureau of Statistics Ministry of Science, ICT and Future Planning Ministry of Science and ICT Ministriy of Sceience and ICT(MSIT) Communication and Information Technology Regulatory Authority LCA Bureau of Statistics Statistics Lithuania ITU Statistics and Census Service Department of Statistics Department of Statistics, Malaysia Statistics Mauritius Instituto Nacional de Estad\u00edstica y Geograf\u00eda (INEGI) National Statistical Office of Mongolia National Bureau of Statistics of the Republic of Moldova Agence Nationale de R\u00e9glementation des T\u00e9l\u00e9communications Direction de la Statistique INSTITTO NACIONAL DE ESTATISTICA, INE Information Technology Authority  Information Technology Authority (ITA)  Ministry of Transport, Communications and Information Technology  Statistics Netherlands Minist\u00e8re des Postes, des T\u00e9l\u00e9communications et de l'Economie Num\u00e9rique National Bureau of Statistics (NBS) Statistics Norway Pakistan Bureau of Statistics Instituto Nacional de Estadistica e Informatica Instituto Nacional de Estad\u00edstica e Inform\u00e1tica - INEI Office of the National Statistician, Philippine Statistics Authority Ministry of Transport and Communications Federal State Statistics Service of the Russian Federation Federal State Statistics Service Statistical Office Communications & IT Commission Communications andI nformation Technology Commision Statistical Office of the Republic of Serbia Statistical office of the Republic of Serbia Infocomm Media Development Authority  Statistical Office Of the Slovak Republic Ministry of Information and Communications Statistical Office of the Republic of Slovenia Statistical Office of the Republic of Slovenia  Statistics South Africa Zimbabwe National Statistics Agency (ZIMSTAT) National Statistical Office National Statistical Office of Thailand Institut national de la statistique et des \u00e9tudes \u00e9conomiques et d\u00e9mographiques  Telecommunications Regulatory Authority  Federal Competitiveness and Statistics Authorithy Telecommunications & Digital Gevernment Regulatory Authority State Statistics Service of Ukraine I.N.E Instituto Nacional de Estadistica  State Committee of the Republic of Uzbekistan on Statistics  The State Committee of the Republic of Uzbekistan on Statistics",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Degree to which the legal framework (including customary law) guarantees women\u2019s equal rights to land ownership and/or control (1=No evidence to 6=Highest levels of guarantees) \n \n Variable code: SG_LGL_LNDFEMOD \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-0a-02.pdf \n \n Detailed sources: State Committee for Family, Women and Children Affairs Instituto Nacional de Reforma Agraria (INRA) - UDAPE - Agency for Statistics of BiH (BHAS) - Environmnet, Energy, Regional Statistics Department Ministry of Agriculture, Livestock and Irrigation (MoALI)\t- Department of Agricultural Land Management and Statistics and Department of Planning -; Ministry of Natural Resources and Environmental Conservation - Forest Department-; Union Attorney General\u2019s Office - Legislative Vetting and Advising Department-; Ministry of Planning, Finance and Industry - Agriculture, Livestock and Fishery Section/ Central Statistical Organization- State Committee on Property of the Republic of Belarus Ministry of Women Affairs Minist\u00e8re de l\u2019Economie, de la Planification de D\u00e9veloppement et de la Coop\u00e9ration Internationale  Ministerio de la Mujer y la Equidad de G\u00e9nero Ministerio de Agricultura y Desarrollo Rural (MADR)\nMinisterio de Vivienda, Ciudad y Territorio (MVCT)\nUnidad de Planificaci\u00f3n Rural Agropecuaria (UPRA)\nDepartamento Administrativo Nacional de Estad\u00edstica (DANE) Instituto Nacional de las Mujeres Minist\u00e8re des Affaires Sociales et de la Microfinance Minstry of Women Affairs  Office of Attorney General and Ministry of Justice (OAGMoJ) Secretar\u00eda de Planificaci\u00f3n y Programaci\u00f3n de la Presidencia -SEGEPLAN- Ministry of Agriculture  Department for Statistical Production Ministry of Finance / The Department of Land and Survey  Ministry of Public Service and Gender -Gender Mainstreaming Department- Ministry of Gender, Children and Social Protection -Department of Policy and Planning Minist\u00e8re de l\u2019Economie et des Finances;  Minist\u00e8re de l\u2019Am\u00e9nagement du Territoire et des Travaux Publics; Minist\u00e8re de la Population, de la Protection Sociale et de la Promotion de la Femme; Minist\u00e8re de la Justice Ministry of Lands, Ministry of Lands Minist\u00e8re de l'Agriculture (CPS/SDR) Secretariado Ejecutivo del Consejo Nacional de la Agenda 2030 Ministry of Justice and Home Affairs (MOJHA); Ministry of Food, Agriculture and Light Industry (MOFALI); Ministry of Labor and Social Protection (MLSP) Ministry of Sustainable Development and Tourism and Minijust National Planning Commission and Ministry of Land Management, Cooperatives and Poverty Alleviation Procuraduria General de la Republica (PGR)- Intendencia de la Propiedad (IP)\u00a0 Minist\u00e8re de la Promotion de la Femme et de l'Enfant Ministry of Human Rights Ministerio de la Mujer Ministerio de la Mujer y Poblaciones Vulnerables Ministerio da Agricultura, Florestas e Desenvovimento Rural (MAFDR) Ministry of Administrative Development, Labour and Social Affairs\nMinistry of Justice  Ministry of Gender and Family Promotion Department of Agriculture, Fisheries, Natural Resources and Co-operatives Republic Geodetic Authority Ministry of Lands, Housing and Country Planning The Statistical Office of the Slovak Republic and the Ministry of Labour, Social Affairs and Family of the Slovak republic General Statistics Office of Viet Nam (GSO), Agriculture, Forestry and Fishery Statistics Department  Ministry of Lands, Agriculture, Water and Rural Resettlement -Legal Department- Sub-Directorate of Land Management\nDivision of Legal Affairs Ministry of Enterprise and Innovation  Federal Office for Agriculture Department of Women and Family Development and National Statistical Office Institut National de la Statistique et \ndes Etudes Economiques et D\u00e9mographiques (INSEED) Ministry of Family and Social Services Ministry of Labor and Social Policy in coordination with other institutions  Ministry of Constitutional and Legal Affairs  Minist\u00e8re en charge de l\u2019Agriculture Instituto Nacional de Colonizaci\u00f3n State Committee for Land Resources, Geodesy, Cartography and State Cadastre Ministry of Agriculture and Irrigation and Fisheries",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Share of women among owners or rights-bearers of agricultural land, by type of tenure (%) \n \n Variable code: SP_GNP_WNOWNS \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-0a-01.pdf \n \n Detailed sources: Demographic and Health Survey Household Socio-Economic Survey Enqu\u00eate Harmonis\u00e9e sur les conditions de vie des m\u00e9nages (WAEMU) Ethiopian Rural Socio-economic Survey India Human Development Survey Enqu\u00eate Multisectorielle Continue  Integrated Household Panel Survey Fourth Integrated Household Survey Fifth Integrated Household Survey National Survey on Household and Living Conditions  General Household Survey Panel-Wave 2 General Household Survey Panel-Wave 3 General Household Survey Panel- Wave 4 Encuesta Nacional Agropecuaria Annual Agricultural Survey National Panel Survey ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of people with ownership or secure rights over agricultural land (out of total agricultural population), by sex (%) \n \n Variable code: SP_LGL_LNDAGSEC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-0a-01.pdf \n \n Detailed sources: Demographic and Health Survey Household Socio-Economic Survey Enqu\u00eate Harmonis\u00e9e sur les conditions de vie des m\u00e9nages (WAEMU) Ethiopian Rural Socio-economic Survey India Human Development Survey Integrated Household Panel Survey Fourth Integrated Household Survey Fifth Integrated Household Survey National Survey on Household and Living Conditions  General Household Survey Panel  General Household Survey Panel-Wave 2 General Household Survey Panel-Wave 3 General Household Survey Panel- Wave 4 Encuesta Nacional Agropecuaria Annual Agricultural Survey National Panel Survey  Enqu\u00eate Multisectorielle Continue ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.4) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Section 4: HIV and HPV (%) \n \n Variable code: SH_LGR_ACSRHES4 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.3) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Section 3: Sexuality Education (%) \n \n Variable code: SH_LGR_ACSRHES3 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.2) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Section 2: Contraceptive and Family Planning (%) \n \n Variable code: SH_LGR_ACSRHES2 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.1) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Section 1: Maternity Care (%) \n \n Variable code: SH_LGR_ACSRHES1 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.3.C.9) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 9: Sexuality Education Curriculum Topics (%) \n \n Variable code: SH_LGR_ACSRHEC9 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.3.C.8) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 8: Sexuality Education Curriculum Laws (%) \n \n Variable code: SH_LGR_ACSRHEC8 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.2.C.7) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 7: Emergency Contraception (%) \n \n Variable code: SH_LGR_ACSRHEC7 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.2.C.6) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 6: Contraceptive Consent (%) \n \n Variable code: SH_LGR_ACSRHEC6 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.2.C.5) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 5: Contraceptive Services (%) \n \n Variable code: SH_LGR_ACSRHEC5 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.1.C.4) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 4: Post-Abortion Care (%) \n \n Variable code: SH_LGR_ACSRHEC4 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.1.C.3) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 3: Abortion \n \n Variable code: SH_LGR_ACSRHEC3 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.1.C.2) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 2: Life Saving Commodities (%) \n \n Variable code: SH_LGR_ACSRHEC2 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.4.C.13) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 13: HPV Vaccine (%) \n \n Variable code: SH_LGR_ACSRHEC13 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.4.C.12) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 12: HIV Confidentiality (%) \n \n Variable code: SH_LGR_ACSRHEC12 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.4.C.11) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 11: HIV Treatment and Care Services (%) \n \n Variable code: SH_LGR_ACSRHEC11 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.4.C.10) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 10: HIV Counselling and Test Services \n \n Variable code: SH_LGR_ACSRHEC10 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: (S.1.C.1) Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education: Component 1: Maternity Care (%) \n \n Variable code: SH_LGR_ACSRHEC1 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Extent to which countries have laws and regulations that guarantee full and equal access to women and men aged 15 years and older to sexual and reproductive health care, information and education (%) \n \n Variable code: SH_LGR_ACSRHE \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-02.pdf \n \n Detailed sources: United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th and 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 12th Inquiry among Governments on Population and Development.  United Nations Population Fund, global databases, 2022. Based on official responses to the United Nations 13th Inquiry among Governments on Population and Development. ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women who make their own informed decisions regarding reproductive health care (% of women aged 15-49 years) \n \n Variable code: SH_FPL_INFMRH \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-01.pdf \n \n Detailed sources: UNFPA Global Database, 2022. DHS 2008-2009. UNFPA Global Database, 2022. DHS 2017-2018. UNFPA Global Database, 2022. DHS 2015-2016. UNFPA Global Database, 2022. DHS 2010. UNFPA Global Database, 2022. DHS 2016-2017. UNFPA Global Database, 2022. DHS 2014. UNFPA Global Database, 2022. DHS 2011. UNFPA Global Database, 2022. DHS 2018. UNFPA Global Database, 2022. DHS 2014-2015. UNFPA Global Database, 2022. DHS 2012. UNFPA Global Database, 2022. DHS 2011-2012. UNFPA Global Database, 2022. DHS 2007. UNFPA Global Database, 2022. DHS 2013-2014. UNFPA Global Database, 2022. DHS 2006. UNFPA Global Database, 2022. ENSANUT 2018. UNFPA Global Database, 2022. DHS 2016. UNFPA Global Database, 2022. MICS 2018. UNFPA Global Database, 2022. DHS 2013. UNFPA Global Database, 2022. DHS 2019-2020. UNFPA Global Database, 2022. DHS 2008. UNFPA Global Database, 2022. DHS 2009. UNFPA Global Database, 2022. DHS 2012-2013. UNFPA Global Database, 2022. Mongolia Social Indicator Sample Survey (MICS) 2018. UNFPA Global Database, 2022. Generations and Gender Survey 2020. UNFPA Global Database, 2022. DHS 2006-2007. UNFPA Global Database, 2022. ENASSER 2014. UNFPA Global Database, 2022. DHS 2016-2018. UNFPA Global Database, 2022. DHS 2017. UNFPA Global Database, 2022. DHS Continuous 2015. UNFPA Global Database, 2022. DHS Continuous 2016. UNFPA Global Database, 2022. DHS Continuous 2017. UNFPA Global Database, 2022. MICS 2019. UNFPA Global Database, 2022. DHS 2019. UNFPA Global Database, 2022. DHS 2005-2006. UNFPA Global Database, 2022. DHS 2010-2011. UNFPA Global Database, 2022. DHS 2015. UNFPA Global Database, 2022. MICS 2018-2019. UNFPA Global Database, 2022.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women who make their own informed decisions regarding contraceptive use (% of women aged 15-49 years) \n \n Variable code: SH_FPL_INFMCU \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-01.pdf \n \n Detailed sources: UNFPA Global Database, 2022. DHS 2008-2009. UNFPA Global Database, 2022. DHS 2017-2018. UNFPA Global Database, 2022. DHS 2015-2016. UNFPA Global Database, 2022. DHS 2010. UNFPA Global Database, 2022. DHS 2016-2017. UNFPA Global Database, 2022. DHS 2014. UNFPA Global Database, 2022. DHS 2011. UNFPA Global Database, 2022. DHS 2018. UNFPA Global Database, 2022. DHS 2014-2015. UNFPA Global Database, 2022. DHS 2012. UNFPA Global Database, 2022. DHS 2011-2012. UNFPA Global Database, 2022. DHS 2007. UNFPA Global Database, 2022. DHS 2013-2014. UNFPA Global Database, 2022. DHS 2006. UNFPA Global Database, 2022. ENSANUT 2018. UNFPA Global Database, 2022. DHS 2016. UNFPA Global Database, 2022. MICS 2018. UNFPA Global Database, 2022. DHS 2013. UNFPA Global Database, 2022. DHS 2019-2020. UNFPA Global Database, 2022. DHS 2008. UNFPA Global Database, 2022. DHS 2009. UNFPA Global Database, 2022. DHS 2012-2013. UNFPA Global Database, 2022. Mongolia Social Indicator Sample Survey (MICS) 2018. UNFPA Global Database, 2022. Generations and Gender Survey 2020. UNFPA Global Database, 2022. DHS 2006-2007. UNFPA Global Database, 2022. ENASSER 2014. UNFPA Global Database, 2022. DHS 2016-2018. UNFPA Global Database, 2022. DHS 2017. UNFPA Global Database, 2022. DHS Continuous 2015. UNFPA Global Database, 2022. DHS Continuous 2016. UNFPA Global Database, 2022. DHS Continuous 2017. UNFPA Global Database, 2022. MICS 2019. UNFPA Global Database, 2022. DHS 2019. UNFPA Global Database, 2022. DHS 2005-2006. UNFPA Global Database, 2022. DHS 2010-2011. UNFPA Global Database, 2022. DHS 2015. UNFPA Global Database, 2022. MICS 2018-2019. UNFPA Global Database, 2022.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women who make their own informed decisions regarding sexual relations (% of women aged 15-49 years) \n \n Variable code: SH_FPL_INFMSR \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-01.pdf \n \n Detailed sources: UNFPA Global Database, 2022. DHS 2008-2009. UNFPA Global Database, 2022. DHS 2017-2018. UNFPA Global Database, 2022. DHS 2015-2016. UNFPA Global Database, 2022. DHS 2010. UNFPA Global Database, 2022. DHS 2016-2017. UNFPA Global Database, 2022. DHS 2014. UNFPA Global Database, 2022. DHS 2011. UNFPA Global Database, 2022. DHS 2018. UNFPA Global Database, 2022. DHS 2014-2015. UNFPA Global Database, 2022. DHS 2012. UNFPA Global Database, 2022. DHS 2011-2012. UNFPA Global Database, 2022. DHS 2007. UNFPA Global Database, 2022. DHS 2013-2014. UNFPA Global Database, 2022. DHS 2006. UNFPA Global Database, 2022. ENSANUT 2018. UNFPA Global Database, 2022. DHS 2016. UNFPA Global Database, 2022. MICS 2018. UNFPA Global Database, 2022. DHS 2013. UNFPA Global Database, 2022. DHS 2019-2020. UNFPA Global Database, 2022. DHS 2008. UNFPA Global Database, 2022. DHS 2009. UNFPA Global Database, 2022. DHS 2012-2013. UNFPA Global Database, 2022. Mongolia Social Indicator Sample Survey (MICS) 2018. UNFPA Global Database, 2022. Generations and Gender Survey 2020. UNFPA Global Database, 2022. DHS 2006-2007. UNFPA Global Database, 2022. ENASSER 2014. UNFPA Global Database, 2022. DHS 2016-2018. UNFPA Global Database, 2022. DHS 2017. UNFPA Global Database, 2022. DHS Continuous 2015. UNFPA Global Database, 2022. DHS Continuous 2016. UNFPA Global Database, 2022. DHS Continuous 2017. UNFPA Global Database, 2022. MICS 2019. UNFPA Global Database, 2022. DHS 2019. UNFPA Global Database, 2022. DHS 2005-2006. UNFPA Global Database, 2022. DHS 2010-2011. UNFPA Global Database, 2022. DHS 2015. UNFPA Global Database, 2022. MICS 2018-2019. UNFPA Global Database, 2022.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women who make their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women aged 15-49 years) \n \n Variable code: SH_FPL_INFM \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-06-01.pdf \n \n Detailed sources: UNFPA Global Database, 2022. DHS 2008-2009. UNFPA Global Database, 2022. DHS 2017-2018. UNFPA Global Database, 2022. DHS 2015-2016. UNFPA Global Database, 2022. DHS 2010. UNFPA Global Database, 2022. DHS 2016-2017. UNFPA Global Database, 2022. DHS 2014. UNFPA Global Database, 2022. DHS 2011. UNFPA Global Database, 2022. DHS 2018. UNFPA Global Database, 2022. DHS 2014-2015. UNFPA Global Database, 2022. DHS 2012. UNFPA Global Database, 2022. DHS 2011-2012. UNFPA Global Database, 2022. DHS 2007. UNFPA Global Database, 2022. DHS 2013-2014. UNFPA Global Database, 2022. DHS 2006. UNFPA Global Database, 2022. ENSANUT 2018. UNFPA Global Database, 2022. DHS 2016. UNFPA Global Database, 2022. MICS 2018. UNFPA Global Database, 2022. DHS 2013. UNFPA Global Database, 2022. DHS 2019-2020. UNFPA Global Database, 2022. DHS 2008. UNFPA Global Database, 2022. DHS 2009. UNFPA Global Database, 2022. DHS 2012-2013. UNFPA Global Database, 2022. Mongolia Social Indicator Sample Survey (MICS) 2018. UNFPA Global Database, 2022. Generations and Gender Survey 2020. UNFPA Global Database, 2022. DHS 2006-2007. UNFPA Global Database, 2022. ENASSER 2014. UNFPA Global Database, 2022. DHS 2016-2018. UNFPA Global Database, 2022. DHS 2017. UNFPA Global Database, 2022. DHS Continuous 2015. UNFPA Global Database, 2022. DHS Continuous 2016. UNFPA Global Database, 2022. DHS Continuous 2017. UNFPA Global Database, 2022. MICS 2019. UNFPA Global Database, 2022. DHS 2019. UNFPA Global Database, 2022. DHS 2005-2006. UNFPA Global Database, 2022. DHS 2010-2011. UNFPA Global Database, 2022. DHS 2015. UNFPA Global Database, 2022. MICS 2018-2019. UNFPA Global Database, 2022.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of elected seats held by women in deliberative bodies of local government (%) \n \n Variable code: SG_GEN_LOCGELS \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01b.pdf \n \n Detailed sources: UN Women Compiled by UN Women Compiled by UNECE Statistical Division and UN Women Compiled by UNECA African Centre for Statistics and UN Women Compiled by ECLAC Division for Gender Affairs and UN Women Compiled by UN Women in collaboration with ESCAP Statistics Division Compiled by ESCWA Statistics Division and UN Women Compiled by UN Women ",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of seats held by women in national parliaments (% of total number of seats) \n \n Variable code: SG_GEN_PARL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), the database on Women in National Parliament, accessed February 1 of given year for annual data. Inter-Parliamentary Union (IPU), the database on Women in National Parliament, accessed January 1 of given year for annual data. Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Current number of seats in national parliaments (number) \n \n Variable code: SG_GEN_PARLNT \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Inter-Parliamentary Union via United Nations Global SDG Database"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of seats held by women in national parliaments (number) \n \n Variable code: SG_GEN_PARLN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01a.pdf and https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-01b.pdf \n \n Detailed sources: Inter-Parliamentary Union (IPU), the database on Women in National Parliament, accessed February 1 of given year for annual data. Inter-Parliamentary Union (IPU), the database on Women in National Parliament, accessed Jan 1 of given year for annual data. Inter-Parliamentary Union (IPU), Parline Database",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women in senior and middle management positions (%) \n \n Variable code: IC_GEN_MGTN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-02.pdf \n \n Detailed sources: HIES - Living Conditions Survey LFS - Labour Force Survey HIES - Core Welfare Indicators Questionnaire PC - Population Census LFS - Permanent Household Survey (Urban) LFS - EU Labour Force Survey HS - Survey of Improvement of Living Conditions HIES - Household Survey LFS - Continuous Employment Survey HS - Botswana Core Welfare Indicators (Poverty) Survey HS - Multi-Topic Household Survey HS - National Household Sample Survey HS - Continuous National Household Sample Survey HIES - Household Income and Expenditure Survey HIES - Household Socio-Economic Survey HS - National Survey on Socio-Economic Conditions LFS - Survey 1-2-3, Employment, informal sector and household's living conditions HS - Household Survey of Multiple Purposes LFS - National Labour Force Survey LFS - Continuous National Labour Force Survey LFS - National Survey on Employment, Unemployment and Underemployment HS - Multi-purpose Household Survey LFS - National Labor Force Survey LFS - Employment, Unemployment Survey HS - Integrated Household Survey HIES - Living Standards Survey LFS - Monthly Employment and Income Survey HIES - Living Conditions National Survey HS - Continous Multi-Purpose Household Survey HS - National Sample Survey LFS - Periodic Labour Force Survey LFS - National Survey on the Employment Situation LFS - Regional Integrated Survey on Employment and the Informal Sector LFS - Employment and Unemployment Survey HIES - Household Budget Survey LFS - National Survey on Employment and the Informal Sector LFS - Continuous Multi-Purpose Household Survey LFS - National Occupation and Employment Survey PC - National Population and Housing Census HIES - National Household Survey on Measuring Living Conditions LFS - Continous Household Survey HS - General Household Survey HIES - Socio Economic Survey LFS - Labour Market Survey LFS - Permanent Employment Survey (Urban) LFS - National Employment Survey LFS - Quarterly Labour Force Survey HIES - Survey on Living Conditions HIES - Living Standard Survey LFS - National Population and Employment Survey LFS - Household Labour Force Survey LFS - Labour Force Sample Survey LFS - Current Population Survey",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women in managerial positions (%) \n \n Variable code: IC_GEN_MGTL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-05-02.pdf \n \n Detailed sources: ILO modelled estimates, November 2020, available in ILOSTAT (https://ilostat.ilo.org/). For the specific sources by country and the estimation methodology refer to ILOSTAT directly. HIES - Living Conditions Survey LFS - Labour Force Survey LFS - Household Employment Survey HIES - Core Welfare Indicators Questionnaire LFS - Employment Survey PC - Population Census LFS - Permanent Household Survey (Urban) LFS - EU Labour Force Survey LFS - Labour Force & Household Survey OE - Estimates of Central informatics organization LFS - Household Labour Force Survey HIES - Households' Integrated Living Conditions Survey PC - Census of Population & Housing LFS - Labour Force Survey Report LFS - Continuous Employment Survey HIES - Household Survey HIES - Living Standards Measurement Survey HS - Botswana Core Welfare Indicators (Poverty) Survey HS - Multi-Topic Household Survey HS - National Household Sample Survey HS - Continuous National Household Sample Survey HIES - Household Income and Expenditure Survey HIES - Living Standards Survey HIES - Household Socio-Economic Survey HS - Household Survey LFS - Continuous Multi-Objective Survey Employment and Labor Market Statistics HS - National Survey on Socio-Economic Conditions PC - Census of Population and Housing LFS - National Employment Survey OE - Official Estimates HS - Integrated Household Survey LFS - National Survey on Employment and the Informal Sector LFS - Survey 1-2-3, Employment, informal sector and household's living conditions HS - National Household Survey HS - Household Survey of Multiple Purposes HIES - Monitoring Survey of the Modular and Integrated Survey of Household Living Conditions LFS - National Labour Force Survey LFS - Continuous National Labour Force Survey LFS - National Survey on Employment, Unemployment and Underemployment HS - Multi-purpose Household Survey LFS - National Labor Force Survey LFS - Employment, Unemployment Survey HS - Djiboutian Household Survey LFS - Monthly Employment and Income Survey HIES - Living Conditions National Survey HS - Continous Multi-Purpose Household Survey LFS - General Household Survey HS - National Sample Survey LFS - Periodic Labour Force Survey LFS - National Survey on the Employment Situation LFS - Regional Integrated Survey on Employment and the Informal Sector LFS - Sample Survey of Employment LFS - Employment and Unemployment Survey HIES - Household Budget Survey LFS - Economically Active Population Survey LFS - Labour Force Sample Survey LFS - Integrated Labour Force Survey HS - Periodic Household Survey PC - Population and Housing Census LFS - Continous Household Employment Survey LFS - Continuous Multi-Purpose Household Survey LFS - National Occupation and Employment Survey PC - National Population and Housing Census HIES - National Household Survey on Measuring Living Conditions LFS - Continous Household Survey HS - General Household Survey HIES - Socio Economic Survey LFS - Labour Market Survey HS - Continous Household Survey HS - Continuous Permanent Household Survey LFS - Permanent Employment Survey (Urban) LFS - Household Survey LFS - Labor Force Sample Survey PC - Qatar Population and Housing Census HIES - Integrated Household Survey on Living Conditions OE - Estimates of the Office of economic planning, data processing and statistics LFS - Quarterly Labour Force Survey LFS - Continuous Household Sample Survey HIES - Survey on Living Conditions HIES - Living Standard Survey HIES - Questionnaire on Indicators of Well-being LFS - Continuous Sample Survey of the Population LFS - National Population and Employment Survey HIES - National Household Survey PC - Jersey Census LFS - Current Population Survey LFS - Household Sample Survey",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of time spent on unpaid domestic chores and care work, by sex, age and location (%) \n \n Variable code: SL_DOM_TSPD \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-04-01.pdf \n \n Detailed sources: Calculated by UNSD based on available country data from the Albanian time use survey (ATUS) 2010-2011 to apply ICATUS. Calculated by UNSD based on available country data from the National Survey on time use of Algerians \u2013 ENET 2012 to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey of the population in the Republic of Azerbaijan to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Annual Household Survey 2005 to apply ICATUS. Calculated by UNSD based on available country data from the Time-use and Volunteer Activities Survey to apply ICATUS. Data provided by the Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations from time-use survey. Australian Bureau of Statistics based on 2006 Time Use Survey Statistics Austria based on Time Use Survey 2008/09 National Statistical Service Republic of Armenia based on Armenian Time Use Pilot Survey National Statistical Service Republic of Armenia based on Time Use Sample Survey in the Republic of Armenia Calculated by UNSD based on available country data from the The Belgian Time Use Survey 1999 to apply ICATUS. Calculated by UNSD based on available country data from the Survey 2005 on the use of time in Belgium to apply ICATUS. Calculated by UNSD based on available country data from the Harmonised European Belgian Time Use Survey to apply ICATUS. Federal Planning Bureau Belgium based on BTUS2013 based on Harmonised European Belgian Time Use Survey Calculated by UNSD based on available country data from the Pilot Time use survey to apply ICATUS. Calculated by UNSD based on available country data from the 2015 Gross National Happiness Survey to apply ICATUS. Calculated by UNSD based on available country data from the Pilot Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the 2009-2010 Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Belarus to apply ICATUS. Calculated by UNSD based on available country data from the Module in Cambodia Socio-Economic Survey 2003-04 (CSES 2003-04) to apply ICATUS. INS, Cameroun based on Fourth Cameroon Household Survey ECAM 4 Statistics Canada based on General Social Survey 2005 - Cycle 19- Time Use Survey Statistics Canada based on General Social Survey 2010 - Cycle 24- Time Use Statistics Canada based on General Social Survey 2015-2016 - Cycle 29 - Time Use Instituto Nacional de Estad\u00edsticas Chile based on Time Use Survey 2007 Instituto Nacional de Estad\u00edsticas Chile based on Time Use Survey 2015 Calculated by UNSD based on available country data from the Time Use Survey in China to apply ICATUS. Calculated by UNSD based on available country data from the 2018 National Time Use Survey to apply ICATUS. DANE based on National Time Use Survey INEC based on National time use survey 2017 Calculated by UNSD based on available country data from the Survey on the time use and use of free time (5 municipalities) to apply ICATUS. Calculated by UNSD based on available country data from the The Time Budget Survey (TBO) to apply ICATUS. Calculated by UNSD based on available country data from the Danish Time-Use and Consumption Survey to apply ICATUS. Calculated by UNSD based on available country data from the Ethiopian Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use at different stages of life to apply ICATUS. Fiji Bureau of Statistics based on Employment and Unemployment Survey 2015-16 Statistics Finland\u00a0 based on Time Use Survey Institut National de la Statistique et des Etudes Economiques (INSEE) based on Survey on the use of time 2009-2010 / EDT Palestinian Central Bureau of Statistics (PCBS) based on Time Use Survey 1999-2000 Palestinian Central Bureau of Statistics (PCBS) based on Time Use Survey 2012/2013 Federal Statistical Office\u00a0 based on Time Use Survey in Germany Calculated by UNSD based on available country data from the Ghana Time Use Survey to apply ICATUS. Hellenic Statistical Authority (ELSTAT) based on Time use survey Calculated by UNSD based on available country data from the Thematic Household Survey (Time use) to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey to apply ICATUS. Hungarian Central Statistical Office based on Time use survey Calculated by UNSD based on available country data from the Time Use Survey in Urban Areas to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Iraq as Module of Iraq Household Socio-Economic Survey - HSES to apply ICATUS. Calculated by UNSD based on available country data from the The Irish National Time-Use Survey 2005 to apply ICATUS. Italian National Institute of Statistics (Istat) based on National Time Use Survey Ministry of Internal Affairs and Communications (MIC) based on Survey on Time Use and Leisure Activities Ministry of Internal Affairs and Communications (MIC) based on 2011 Survey on Time Use and Leisure Activities Ministry of Internal Affairs and Communications (MIC) based on 2016 Survey on Time Use and Leisure Activities Calculated by UNSD based on available country data from the Time use survey in Kazakhstan to apply ICATUS. Calculated by UNSD based on available country data from the The time use budget of population to apply ICATUS. The Agency of the Republic of Kazakhstan on Statistics based on The time use budget of population Statistics Korea based on Time Use Survey Calculated by UNSD based on available country data from the Time Budget Survey to apply ICATUS. Calculated by UNSD based on available country data from the Lao Expenditure and consumption survey to apply ICATUS. Calculated by UNSD based on available country data from the Lao expenditure and consumption survey 2012/13 to apply ICATUS. Lao Statistics Bureau based on Labor force survey in Lao PDR- 2017 Calculated by UNSD based on available country data from the Household Budget Survey (HBS) to apply ICATUS. Calculated by UNSD based on available country data from the HETUS to apply ICATUS. Liberia Institute of Statistics and Geo-Information Services (LISGIS) based on Labour Force Survey 2010  Statistics Lithuania based on Time Use Survey Calculated by UNSD based on available country data from the Time use of Luxembourg residents to apply ICATUS. Calculated by UNSD based on available country data from the Module on the use of time to apply ICATUS. Calculated by UNSD based on available country data from the 2nd Malawi Integrated household survey (IHS2) to apply ICATUS. Calculated by UNSD based on available country data from the Unpaid work survey to apply ICATUS. Calculated by UNSD based on available country data from the Malian Survey on Time Use to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2002 (pilot) to apply ICATUS. Calculated by UNSD based on available country data from the The Continuous Multi-Purpose Household Survey (CMPHS) to apply ICATUS. INEGI based on National time use survey 2002  (Module in ENIGH) INEGI based on National time use survey 2009  INEGI based on National time use survey 2014  INEGI based on National time use survey 2019  National Statistical Office based on Time Use Survey (pilot) National Statistical Office based on Time Use Survey 2007 National Statistical Office based on Time use survey 2011 National Statistical Office based on Time use survey 2015 National Statistical Office based on Time use survey 2019 National Bureau of Statistics, Republic of Moldova based on Time use survey Calculated by UNSD based on available country data from the National Survey on time use in Morocco to apply ICATUS. National Center for Statistics and Information (NCSI) based on Overall Monitoring of Annual National Indicators Survey National Center for Statistics and Information (NCSI) based on Time Use Survey Calculated by UNSD based on available country data from the Dutch Time Use Survey (TBO) to apply ICATUS. Calculated by UNSD based on available country data from the Dutch Time Use Survey  to apply ICATUS. Calculated by UNSD based on available country data from the Dutch Time Use Survey (TBO) 2011 to apply ICATUS. Statistics Norway based on Time Use Survey Pakistan Bureau of Statistics based on Time Use Survey Direccion General de Estadistica, Encuestas y Censos (DGEEC) based on Time use survey 2016 Instituto Nacional de Estad\u00edstica e Inform\u00e1tica based on National Survey of Time Use 2010 Statistics Poland based on Time Use Survey  Statistics Portugal based on National Survey on Time Use by Men and Women INSSE based on National Time Use Study INSSE based on Time Use of the Romanians - 2012 Calculated by UNSD based on available country data from the 2014 Time-use survey to apply ICATUS. Statistical Office of the Republic of Serbia based on Time Use Survey in Serbia Statistical Office of the Republic of Slovenia based on Time Use Survey Calculated by UNSD based on available country data from the Time Use Survey 2000 to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey 2010 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2002-2003 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2009-2010 to apply ICATUS. Statistics Sweden based on The Swedish Time-Use Survey 2000 Statistics Sweden based on The Swedish Time Use Survey 2010/11 Federal\u00a0Statistical Office\u00a0FSO based on Swiss Labour Force Survey - Unpaid Work Module Calculated by UNSD based on available country data from the Time Budget of Women and Men in Tunisia to apply ICATUS. Turkish Statistical Institute (TurkStat) based on Turkey - Time Use Survey 2006 Turkish Statistical Institute (TurkStat) based on Turkey - Time Use Survey 2014-15 Uganda Bureau of Statistics based on time use survey Calculated by UNSD based on available country data from the Time use survey, 2014/2015 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Egypt  to apply ICATUS. Office for National Statistics based on United Kingdom Time Use Survey, 2000 Office for National Statistics based on United Kingdom Time Use Survey, 2014-2015 Calculated by UNSD based on available country data from the Integrated Labour Force Survey - Time Use Survey Module to apply ICATUS. US Bureau of Labor Statistics based on American Time Use Survey 2003 US Bureau of Labor Statistics based on American Time Use Survey 2004 US Bureau of Labor Statistics based on American Time Use Survey 2005 US Bureau of Labor Statistics based on American Time Use Survey 2006 US Bureau of Labor Statistics based on American Time Use Survey 2007 US Bureau of Labor Statistics based on American Time Use Survey 2008 US Bureau of Labor Statistics based on American Time Use Survey 2009 US Bureau of Labor Statistics based on American Time Use Survey 2010 US Bureau of Labor Statistics based on American Time Use Survey 2011 US Bureau of Labor Statistics based on American Time Use Survey 2012 US Bureau of Labor Statistics based on American Time Use Survey 2013 US Bureau of Labor Statistics based on American Time Use Survey 2014 US Bureau of Labor Statistics based on American Time Use Survey 2015 US Bureau of Labor Statistics based on American Time Use Survey 2016 US Bureau of Labor Statistics based on American Time Use Survey 2017 US Bureau of Labor Statistics based on American Time Use Survey 2018 Calculated by UNSD based on available country data from the Survey on the use of time and unpaid work 2007 to apply ICATUS.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of time spent on unpaid domestic chores, by sex, age and location (%) \n \n Variable code: SL_DOM_TSPDDC \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-04-01.pdf \n \n Detailed sources: Calculated by UNSD based on available country data from the Albanian time use survey (ATUS) 2010-2011 to apply ICATUS. Calculated by UNSD based on available country data from the National Survey on time use of Algerians \u2013 ENET 2012 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Annual Household Survey 2005 to apply ICATUS. Calculated by UNSD based on available country data from the Time-use and Volunteer Activities Survey to apply ICATUS. Data provided by the Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations from time-use survey. Australian Bureau of Statistics based on 2006 Time Use Survey Statistics Austria based on Time Use Survey 2008/09 National Statistical Service Republic of Armenia based on Armenian Time Use Pilot Survey National Statistical Service Republic of Armenia based on Time Use Sample Survey in the Republic of Armenia Calculated by UNSD based on available country data from the The Belgian Time Use Survey 1999 to apply ICATUS. Calculated by UNSD based on available country data from the Survey 2005 on the use of time in Belgium to apply ICATUS. Calculated by UNSD based on available country data from the Harmonised European Belgian Time Use Survey to apply ICATUS. Federal Planning Bureau Belgium based on BTUS2013 based on Harmonised European Belgian Time Use Survey Calculated by UNSD based on available country data from the Pilot Time use survey to apply ICATUS. Calculated by UNSD based on available country data from the 2015 Gross National Happiness Survey to apply ICATUS. Calculated by UNSD based on available country data from the Pilot Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the 2009-2010 Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Belarus to apply ICATUS. INS, Cameroun based on Fourth Cameroon Household Survey ECAM 4 Statistics Canada based on General Social Survey 2005 - Cycle 19- Time Use Survey Statistics Canada based on General Social Survey 2010 - Cycle 24- Time Use Statistics Canada based on General Social Survey 2015-2016 - Cycle 29 - Time Use Instituto Nacional de Estad\u00edsticas Chile based on Time Use Survey 2007 Instituto Nacional de Estad\u00edsticas Chile based on Time Use Survey 2015 Calculated by UNSD based on available country data from the Time Use Survey in China to apply ICATUS. Calculated by UNSD based on available country data from the 2018 National Time Use Survey to apply ICATUS. DANE based on National Time Use Survey INEC based on National time use survey 2017 Calculated by UNSD based on available country data from the Danish Time-Use and Consumption Survey to apply ICATUS. Calculated by UNSD based on available country data from the Ethiopian Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use at different stages of life to apply ICATUS. Fiji Bureau of Statistics based on Employment and Unemployment Survey 2015-16 Statistics Finland\u00a0 based on Time Use Survey Institut National de la Statistique et des Etudes Economiques (INSEE) based on Survey on the use of time 2009-2010 / EDT Palestinian Central Bureau of Statistics (PCBS) based on Time Use Survey 1999-2000 Palestinian Central Bureau of Statistics (PCBS) based on Time Use Survey 2012/2013 Federal Statistical Office\u00a0 based on Time Use Survey in Germany Calculated by UNSD based on available country data from the Ghana Time Use Survey to apply ICATUS. Hellenic Statistical Authority (ELSTAT) based on Time use survey Calculated by UNSD based on available country data from the Thematic Household Survey (Time use) to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey to apply ICATUS. Hungarian Central Statistical Office based on Time use survey Calculated by UNSD based on available country data from the Time Use Survey in Urban Areas to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Iraq as Module of Iraq Household Socio-Economic Survey - HSES to apply ICATUS. Calculated by UNSD based on available country data from the The Irish National Time-Use Survey 2005 to apply ICATUS. Italian National Institute of Statistics (Istat) based on National Time Use Survey Ministry of Internal Affairs and Communications (MIC) based on Survey on Time Use and Leisure Activities Ministry of Internal Affairs and Communications (MIC) based on 2011 Survey on Time Use and Leisure Activities Ministry of Internal Affairs and Communications (MIC) based on 2016 Survey on Time Use and Leisure Activities Calculated by UNSD based on available country data from the Time use survey in Kazakhstan to apply ICATUS. Calculated by UNSD based on available country data from the The time use budget of population to apply ICATUS. The Agency of the Republic of Kazakhstan on Statistics based on The time use budget of population Statistics Korea based on Time Use Survey Calculated by UNSD based on available country data from the Time Budget Survey to apply ICATUS. Calculated by UNSD based on available country data from the Lao Expenditure and consumption survey to apply ICATUS. Calculated by UNSD based on available country data from the Lao expenditure and consumption survey 2012/13 to apply ICATUS. Lao Statistics Bureau based on Labor force survey in Lao PDR- 2017 Calculated by UNSD based on available country data from the HETUS to apply ICATUS. Liberia Institute of Statistics and Geo-Information Services (LISGIS) based on Labour Force Survey 2010  Statistics Lithuania based on Time Use Survey Calculated by UNSD based on available country data from the Time use of Luxembourg residents to apply ICATUS. Calculated by UNSD based on available country data from the Unpaid work survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2002 (pilot) to apply ICATUS. Calculated by UNSD based on available country data from the The Continuous Multi-Purpose Household Survey (CMPHS) to apply ICATUS. INEGI based on National time use survey 2002  (Module in ENIGH) INEGI based on National time use survey 2009  INEGI based on National time use survey 2014  INEGI based on National time use survey 2019  National Statistical Office based on Time Use Survey (pilot) National Statistical Office based on Time Use Survey 2007 National Statistical Office based on Time use survey 2011 National Statistical Office based on Time use survey 2015 National Statistical Office based on Time use survey 2019 National Bureau of Statistics, Republic of Moldova based on Time use survey National Center for Statistics and Information (NCSI) based on Overall Monitoring of Annual National Indicators Survey National Center for Statistics and Information (NCSI) based on Time Use Survey Calculated by UNSD based on available country data from the Dutch Time Use Survey (TBO) to apply ICATUS. Calculated by UNSD based on available country data from the Dutch Time Use Survey  to apply ICATUS. Calculated by UNSD based on available country data from the Dutch Time Use Survey (TBO) 2011 to apply ICATUS. Statistics Norway based on Time Use Survey Pakistan Bureau of Statistics based on Time Use Survey Direccion General de Estadistica, Encuestas y Censos (DGEEC) based on Time use survey 2016 Instituto Nacional de Estad\u00edstica e Inform\u00e1tica based on National Survey of Time Use 2010 Statistics Poland based on Time Use Survey  Statistics Portugal based on National Survey on Time Use by Men and Women INSSE based on National Time Use Study INSSE based on Time Use of the Romanians - 2012 Calculated by UNSD based on available country data from the 2014 Time-use survey to apply ICATUS. Statistical Office of the Republic of Serbia based on Time Use Survey in Serbia Statistical Office of the Republic of Slovenia based on Time Use Survey Calculated by UNSD based on available country data from the Time Use Survey 2000 to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey 2010 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2002-2003 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2009-2010 to apply ICATUS. Statistics Sweden based on The Swedish Time-Use Survey 2000 Statistics Sweden based on The Swedish Time Use Survey 2010/11 Federal\u00a0Statistical Office\u00a0FSO based on Swiss Labour Force Survey - Unpaid Work Module Calculated by UNSD based on available country data from the Time Budget of Women and Men in Tunisia to apply ICATUS. Turkish Statistical Institute (TurkStat) based on Turkey - Time Use Survey 2006 Turkish Statistical Institute (TurkStat) based on Turkey - Time Use Survey 2014-15 Uganda Bureau of Statistics based on time use survey Calculated by UNSD based on available country data from the Time use survey, 2014/2015 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Egypt  to apply ICATUS. Office for National Statistics based on United Kingdom Time Use Survey, 2000 Office for National Statistics based on United Kingdom Time Use Survey, 2014-2015 Calculated by UNSD based on available country data from the Integrated Labour Force Survey - Time Use Survey Module to apply ICATUS. US Bureau of Labor Statistics based on American Time Use Survey 2003 US Bureau of Labor Statistics based on American Time Use Survey 2004 US Bureau of Labor Statistics based on American Time Use Survey 2005 US Bureau of Labor Statistics based on American Time Use Survey 2006 US Bureau of Labor Statistics based on American Time Use Survey 2007 US Bureau of Labor Statistics based on American Time Use Survey 2008 US Bureau of Labor Statistics based on American Time Use Survey 2009 US Bureau of Labor Statistics based on American Time Use Survey 2010 US Bureau of Labor Statistics based on American Time Use Survey 2011 US Bureau of Labor Statistics based on American Time Use Survey 2012 US Bureau of Labor Statistics based on American Time Use Survey 2013 US Bureau of Labor Statistics based on American Time Use Survey 2014 US Bureau of Labor Statistics based on American Time Use Survey 2015 US Bureau of Labor Statistics based on American Time Use Survey 2016 US Bureau of Labor Statistics based on American Time Use Survey 2017 US Bureau of Labor Statistics based on American Time Use Survey 2018 Calculated by UNSD based on available country data from the Survey on the use of time and unpaid work 2007 to apply ICATUS.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of time spent on unpaid care work, by sex, age and location (%) \n \n Variable code: SL_DOM_TSPDCW \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-04-01.pdf \n \n Detailed sources: Calculated by UNSD based on available country data from the Albanian time use survey (ATUS) 2010-2011 to apply ICATUS. Calculated by UNSD based on available country data from the National Survey on time use of Algerians \u2013 ENET 2012 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Annual Household Survey 2005 to apply ICATUS. Calculated by UNSD based on available country data from the Time-use and Volunteer Activities Survey to apply ICATUS. Data provided by the Economic Commission for Latin America and the Caribbean (ECLAC), on the basis of special tabulations from time-use survey. Australian Bureau of Statistics based on 2006 Time Use Survey Statistics Austria based on Time Use Survey 2008/09 National Statistical Service Republic of Armenia based on Armenian Time Use Pilot Survey National Statistical Service Republic of Armenia based on Time Use Sample Survey in the Republic of Armenia Calculated by UNSD based on available country data from the The Belgian Time Use Survey 1999 to apply ICATUS. Calculated by UNSD based on available country data from the Survey 2005 on the use of time in Belgium to apply ICATUS. Federal Planning Bureau Belgium based on BTUS2013 based on Harmonised European Belgian Time Use Survey Calculated by UNSD based on available country data from the Harmonised European Belgian Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Pilot Time use survey to apply ICATUS. Calculated by UNSD based on available country data from the 2015 Gross National Happiness Survey to apply ICATUS. Calculated by UNSD based on available country data from the Pilot Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the 2009-2010 Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Belarus to apply ICATUS. INS, Cameroun based on Fourth Cameroon Household Survey ECAM 4 Statistics Canada based on General Social Survey 2005 - Cycle 19- Time Use Survey Statistics Canada based on General Social Survey 2010 - Cycle 24- Time Use Statistics Canada based on General Social Survey 2015-2016 - Cycle 29 - Time Use Instituto Nacional de Estad\u00edsticas Chile based on Time Use Survey 2007 Instituto Nacional de Estad\u00edsticas Chile based on Time Use Survey 2015 Calculated by UNSD based on available country data from the Time Use Survey in China to apply ICATUS. Calculated by UNSD based on available country data from the 2018 National Time Use Survey to apply ICATUS. DANE based on National Time Use Survey INEC based on National time use survey 2017 Calculated by UNSD based on available country data from the Danish Time-Use and Consumption Survey to apply ICATUS. Calculated by UNSD based on available country data from the Ethiopian Time Use Survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use at different stages of life to apply ICATUS. Fiji Bureau of Statistics based on Employment and Unemployment Survey 2015-16 Statistics Finland\u00a0 based on Time Use Survey Institut National de la Statistique et des Etudes Economiques (INSEE) based on Survey on the use of time 2009-2010 / EDT Palestinian Central Bureau of Statistics (PCBS) based on Time Use Survey 1999-2000 Palestinian Central Bureau of Statistics (PCBS) based on Time Use Survey 2012/2013 Federal Statistical Office\u00a0 based on Time Use Survey in Germany Calculated by UNSD based on available country data from the Ghana Time Use Survey to apply ICATUS. Hellenic Statistical Authority (ELSTAT) based on Time use survey Calculated by UNSD based on available country data from the Thematic Household Survey (Time use) to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey to apply ICATUS. Hungarian Central Statistical Office based on Time use survey Calculated by UNSD based on available country data from the Time Use Survey in Urban Areas to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Iraq as Module of Iraq Household Socio-Economic Survey - HSES to apply ICATUS. Calculated by UNSD based on available country data from the The Irish National Time-Use Survey 2005 to apply ICATUS. Italian National Institute of Statistics (Istat) based on National Time Use Survey Ministry of Internal Affairs and Communications (MIC) based on Survey on Time Use and Leisure Activities Ministry of Internal Affairs and Communications (MIC) based on 2011 Survey on Time Use and Leisure Activities Ministry of Internal Affairs and Communications (MIC) based on 2016 Survey on Time Use and Leisure Activities Calculated by UNSD based on available country data from the Time use survey in Kazakhstan to apply ICATUS. Calculated by UNSD based on available country data from the The time use budget of population to apply ICATUS. The Agency of the Republic of Kazakhstan on Statistics based on The time use budget of population Statistics Korea based on Time Use Survey Calculated by UNSD based on available country data from the Time Budget Survey to apply ICATUS. Calculated by UNSD based on available country data from the Lao Expenditure and consumption survey to apply ICATUS. Calculated by UNSD based on available country data from the Lao expenditure and consumption survey 2012/13 to apply ICATUS. Lao Statistics Bureau based on Labor force survey in Lao PDR- 2017 Calculated by UNSD based on available country data from the HETUS to apply ICATUS. Liberia Institute of Statistics and Geo-Information Services (LISGIS) based on Labour Force Survey 2010  Statistics Lithuania based on Time Use Survey Calculated by UNSD based on available country data from the Time use of Luxembourg residents to apply ICATUS. Calculated by UNSD based on available country data from the Unpaid work survey to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2002 (pilot) to apply ICATUS. Calculated by UNSD based on available country data from the The Continuous Multi-Purpose Household Survey (CMPHS) to apply ICATUS. INEGI based on National time use survey 2002  (Module in ENIGH) INEGI based on National time use survey 2009  INEGI based on National time use survey 2014  INEGI based on National time use survey 2019  National Statistical Office based on Time Use Survey (pilot) National Statistical Office based on Time Use Survey 2007 National Statistical Office based on Time use survey 2011 National Statistical Office based on Time use survey 2015 National Statistical Office based on Time use survey 2019 National Bureau of Statistics, Republic of Moldova based on Time use survey National Center for Statistics and Information (NCSI) based on Overall Monitoring of Annual National Indicators Survey National Center for Statistics and Information (NCSI) based on Time Use Survey Calculated by UNSD based on available country data from the Dutch Time Use Survey (TBO) to apply ICATUS. Calculated by UNSD based on available country data from the Dutch Time Use Survey  to apply ICATUS. Calculated by UNSD based on available country data from the Dutch Time Use Survey (TBO) 2011 to apply ICATUS. Statistics Norway based on Time Use Survey Pakistan Bureau of Statistics based on Time Use Survey Direccion General de Estadistica, Encuestas y Censos (DGEEC) based on Time use survey 2016 Instituto Nacional de Estad\u00edstica e Inform\u00e1tica based on National Survey of Time Use 2010 Statistics Poland based on Time Use Survey  Statistics Portugal based on National Survey on Time Use by Men and Women INSSE based on National Time Use Study INSSE based on Time Use of the Romanians - 2012 Calculated by UNSD based on available country data from the 2014 Time-use survey to apply ICATUS. Statistical Office of the Republic of Serbia based on Time Use Survey in Serbia Statistical Office of the Republic of Slovenia based on Time Use Survey Calculated by UNSD based on available country data from the Time Use Survey 2000 to apply ICATUS. Calculated by UNSD based on available country data from the Time Use Survey 2010 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2002-2003 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey 2009-2010 to apply ICATUS. Statistics Sweden based on The Swedish Time-Use Survey 2000 Statistics Sweden based on The Swedish Time Use Survey 2010/11 Federal\u00a0Statistical Office\u00a0FSO based on Swiss Labour Force Survey - Unpaid Work Module Calculated by UNSD based on available country data from the Time Budget of Women and Men in Tunisia to apply ICATUS. Turkish Statistical Institute (TurkStat) based on Turkey - Time Use Survey 2006 Turkish Statistical Institute (TurkStat) based on Turkey - Time Use Survey 2014-15 Uganda Bureau of Statistics based on time use survey Calculated by UNSD based on available country data from the Time use survey, 2014/2015 to apply ICATUS. Calculated by UNSD based on available country data from the Time use survey in Egypt  to apply ICATUS. Office for National Statistics based on United Kingdom Time Use Survey, 2000 Office for National Statistics based on United Kingdom Time Use Survey, 2014-2015 Calculated by UNSD based on available country data from the Integrated Labour Force Survey - Time Use Survey Module to apply ICATUS. US Bureau of Labor Statistics based on American Time Use Survey 2003 US Bureau of Labor Statistics based on American Time Use Survey 2004 US Bureau of Labor Statistics based on American Time Use Survey 2005 US Bureau of Labor Statistics based on American Time Use Survey 2006 US Bureau of Labor Statistics based on American Time Use Survey 2007 US Bureau of Labor Statistics based on American Time Use Survey 2008 US Bureau of Labor Statistics based on American Time Use Survey 2009 US Bureau of Labor Statistics based on American Time Use Survey 2010 US Bureau of Labor Statistics based on American Time Use Survey 2011 US Bureau of Labor Statistics based on American Time Use Survey 2012 US Bureau of Labor Statistics based on American Time Use Survey 2013 US Bureau of Labor Statistics based on American Time Use Survey 2014 US Bureau of Labor Statistics based on American Time Use Survey 2015 US Bureau of Labor Statistics based on American Time Use Survey 2016 US Bureau of Labor Statistics based on American Time Use Survey 2017 US Bureau of Labor Statistics based on American Time Use Survey 2018 Calculated by UNSD based on available country data from the Survey on the use of time and unpaid work 2007 to apply ICATUS.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women aged 20-24 years who were married or in a union before age 15 (%) \n \n Variable code: SP_DYN_MRBF15 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-03-01.pdf \n \n Detailed sources: DHS, MICS and other national surveys LCS 2016-17 DHS 2017-18 MICS 2018-19 DHS 2015-16 DHS 2011 MICS 2019-20 MICS 2019 MICS 2012 Statistics Belgium derived from the Population register, 2020 MICS 2010 DHS (ENDESA) 2016 MICS 2011-12 PNDS 2006 MICS 2015-16 DHS 2015 DHS 2016-17 DHS 2014 DHS 2018 DHS 2016 DHS 2012 MICS 2014-15 MICS 2017-18 MICS 2018 ENSANUT 2018 Encuesta Nacional de Salud (ENS/MICS) 2014 EPHS 2010 MICS 2021 Preliminary results PAPFAM 2012 DHS 2019-20 NFHS 2015-16 DHS 2017 MIDHS 2010 MICS 2016 MICS 2011 MICS 2015 MICS 2017 Statistics Lithuania 2021 ENADID 2018 ENSPF 2018 AIS 2015 MICS 2014 DHS 2013 DHS 2007 ENDESA 2011-12 MICS 2013 DHS 2016-18 ENDES 2020 RPN 2017, Sample Survey of the Reproductive Plans of the Population Continuous DHS 2019 DHS 2019 Singapore Department of Statistics SHDS 2020 SHHS-2 2010 MICS 2006 DHS 2010",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of girls and women aged 15-49 years who have undergone female genital mutilation/cutting, by age (%) \n \n Variable code: SH_STA_FGMS \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-03-02.pdf \n \n Detailed sources: DHS, MICS and other national surveys DHS 2004 MICS 2018-19 MICS 2019 MICS 2014 DHS 2016 Population and Health Survey 2010 PAPFAM 2012 DHS 2019-20 MICS 2017-18 DHS 2018 MICS 2018 MICS 2016 DHS 2014 DHS 2016-17 MICS 2015 DHS/MICS 2012 Continuous DHS 2019 DHS 2019 SHDS 2020 MICS 2017 Health Issues Survey (DHS) 2015 DHS 2015-16 DHS/MICS 2010 DHS 2013",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of women aged 20-24 years who were married or in a union before age 18 (%) \n \n Variable code: SP_DYN_MRBF18 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-03-01.pdf \n \n Detailed sources: DHS, MICS and other national surveys LCS 2016-17 DHS 2017-18 MICS 2018-19 DHS 2015-16 DHS 2011 MICS 2019-20 MICS 2019 MICS 2012 Statistics Belgium derived from the Population register, 2020 MICS 2010 DHS (ENDESA) 2016 MICS 2011-12 PNDS 2006 MICS 2015-16 DHS 2015 DHS 2016-17 DHS 2014 DHS 2018 DHS 2016 DHS 2012 MICS 2014-15 MICS 2017-18 MICS 2018 Statistics Denmark 2021 ENSANUT 2018 Encuesta Nacional de Salud (ENS/MICS) 2014 EPHS 2010 MICS 2021 Preliminary results Statistics Finland 2020 PAPFAM 2012 DHS 2019-20 NFHS 2015-16 DHS 2017 MIDHS 2010 MICS 2016 MICS 2011 MICS 2015 MICS 2017 Statistics Lithuania 2021 ENADID 2018 ENSPF 2018 AIS 2015 MICS 2014 DHS 2013 DHS 2007 ENDESA 2011-12 Statistics Norway 2021 MICS 2013 DHS 2016-18 ENDES 2020 RPN 2017, Sample Survey of the Reproductive Plans of the Population Continuous DHS 2019 DHS 2019 Singapore Department of Statistics SHDS 2020 SHHS-2 2010 MICS 2006 Office for National Statistics DHS 2010",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Proportion of ever-partnered women and girls subjected to physical and/or sexual violence by a current or former intimate partner in the previous 12 months, by age (%) \n \n Variable code: VC_VAW_MARR \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-02-01.pdf \n \n Detailed sources: All Surveys and studies that are population-based, representative at the national or sub-national level, conducted between 2000 and 2018 and measured IPV using act-specific questions.",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "Data from multiple sources compiled by the UN"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Legal frameworks that promote, enforce and monitor gender equality (percentage of achievement, 0 - 100) -- Area 4: marriage and family \n \n Variable code: SG_LGL_GENEQMAR \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-01-01.pdf \n \n Detailed sources: UN Women",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Women"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Legal frameworks that promote, enforce and monitor gender equality (percentage of achievement, 0 - 100) -- Area 3: employment and economic benefits \n \n Variable code: SG_LGL_GENEQEMP \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-01-01.pdf \n \n Detailed sources: UN Women",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Women"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Legal frameworks that promote, enforce and monitor gender equality (percentage of achievement, 0 - 100) --  Area 2: violence against women \n \n Variable code: SG_LGL_GENEQVAW \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-01-01.pdf \n \n Detailed sources: UN Women",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Women"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Legal frameworks that promote, enforce and monitor gender equality (percentage of achievement, 0 - 100) -- Area 1: overarching legal frameworks and public life \n \n Variable code: SG_LGL_GENEQLFP \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-05-01-01.pdf \n \n Detailed sources: UN Women",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Women"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Countries that have national urban policies or regional development plans that respond to population dynamics; ensure balanced territorial development; and increase local fiscal space (1 = YES; 0 = NO) \n \n Variable code: SD_CPA_UPRDP \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-11-0a-01.pdf \n \n Detailed sources: NUP 2020 Status",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "United Nations Human Settlement Programme"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Municipal Solid Waste collection coverage, by cities (%) \n \n Variable code: EN_REF_WASCOL \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-11-06-01.pdf \n \n Detailed sources: United Nations Human Settlements Programme (UN-Habitat)",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Human Settlements Programme"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Annual mean levels of fine particulate matter (population-weighted), by location (micrograms per cubic meter) \n \n Variable code: EN_ATM_PM25 \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-11-06-02.pdf \n \n Detailed sources: WHO",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "World Health Organization"
}

{
    "link": "https://unstats.un.org/sdgs/indicators/database/",
    "retrievedDate": "2022-05-03",
    "additionalInfo": "Variable description: Number of disruptions to other basic services attributed to disasters (number) \n \n Variable code: VC_DSR_OBDN \n \n Metadata available at: https://unstats.un.org/sdgs/metadata/files/Metadata-11-05-03.pdf \n \n Detailed sources: United Nations Office for Disaster Risk Reduction (2022)",
    "dataPublishedBy": "United Nations Statistics Division",
    "dataPublisherSource": "UN Office for Disaster Risk Reduction"
}